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Quartet decomposition server: a platform for analyzing phylogenetic trees
Background The frequent exchange of genetic material among prokaryotes means that extracting a majority or plurality phylogenetic signal from many gene families, and the identification of gene families that are in significant conflict with the plurality signal is a frequent task in comparative genomics, and especially in phylogenomic analyses. Decomposition of gene trees into embedded quartets (unrooted trees each with four taxa) is a convenient and statistically powerful technique to address this challenging problem. This approach was shown to be useful in several studies of completely sequenced microbial genomes. Results We present here a web server that takes a collection of gene phylogenies, decomposes them into quartets, generates a Quartet Spectrum, and draws a split network. Users are also provided with various data download options for further analyses. Each gene phylogeny is to be represented by an assessment of phylogenetic information content, such as sets of trees reconstructed from bootstrap replicates or sampled from a posterior distribution. The Quartet Decomposition server is accessible at http://quartets.uga.edu. Conclusions The Quartet Decomposition server presented here provides a convenient means to perform Quartet Decomposition analyses and will empower users to find statistically supported phylogenetic conflicts.
Background
Sequence data revealed that genetic material in prokaryotes (bacteria and archaea) can be transferred between divergent organisms [1] to an extent that makes it difficult to reconstruct their evolutionary history [2][3][4]. Many microorganisms can take DNA directly from the environment; phages infect prokaryotic cells and may bring new DNA fragments into the host genomes; the conjugation machinery allows for DNA exchange directly between cells; and phage derived gene transfer agents [5] were suggested to transfer genetic material between related and possibly unrelated organisms [6]. Gene transfer results in genes found in the same genome to have different phylogenies. The currently popular strategies for inference of organismal relationships include (i) construction of an organismal tree based on conserved genes presumed to be not transferred such as 16S ribosomal RNA and ribosomal proteins, or (ii) the assumption that the plurality phylogenetic signal contained in all genes reflects the organismal history. The plurality signal is either extracted through joint analysis of several genes, usually after removing genes that show signs of having been horizontally transferred [7], or individual gene trees are combined using a variety of supertree approaches [8,9].
Phylogeny is typically represented as a tree, often with tens or hundreds of leaves. The large size and unequal number of taxa makes comparisons between trees difficult. A common approach is to compare all significantly supported bipartitions. Lento plots allow visualizing the bipartitions supported by many gene families, and also depict, for each bipartition, all those bipartitions that are in conflict [10][11][12]. As well as requiring all phylogenies to be the same size i.e., all gene families represented in all genomes analyzed, bipartition-based approaches suffer from a loss of resolution as more sequences and therefore tips and edges are included. Quartet Decomposition avoids both of these problems [13,14].
Quartets are unrooted trees consisting of four taxa ( Figure 1). A quartet is the minimal informative unit in a tree, and it has three possible topologies. An unrooted three-taxon tree unit only has one topology and thus is not informative, while a five-taxon tree unit has fifteen topologies, thus is too complicated; the four-taxon tree unit has a good balance between the amount of information it can carry and the complexity involved in analyzing it [15]. Quartet Decomposition is the analysis of quartets embedded in larger phylogenies. Support for bipartitions that include all taxa present in a phylogenetic tree can decrease, if one sequence in a larger phylogeny has low phylogenetic signal causing its position among bootstrap replicates to vary. In addition, as more taxa are added to an analysis, the shorter the internal branches, and the lower their support values become. This situation is unsatisfactory, because increased taxon sampling is expected to increase the reliability of the phylogenetic reconstruction; however, the increase in reliability is not reflected in increased bipartition support values. To illustrate this paradox we performed simulations summarized in Figure 2. Figure 2A shows how the simulation is performed: starting from a tree with four tips, we grow the tree by adding more tips at the internal branch; and then generate replicates, carry out bipartition and quartet-based analysis. Figure 2B shows that even for sequences 1000 amino acids long, with 10 additional tips, the maximum support for a bipartition separating AB from CD is less than 80% on average, and with 20 additional tips it is close to 60%, too low to provide insight into any biological processes. In contrast, Figure 2C shows the ((A,B),(C,D)) embedded quartet is present in almost all replicates, demonstrating the near independence of sample size and embedded quartet resolution.
The use of quartets has been explored in various phylogenetic applications. In 1996 K. Strimmer and A. von Haeseler developed the quartet puzzling algorithm for tree reconstruction [20]. Since then a quartet-based software TREE-PUZZLE [21] has been developed and widely used for tree reconstruction from DNA and protein sequences. Later, two software packages, Clann [22] and QuartetSuite [23], were developed allowing construction of supertrees from multiple trees using quartets. Zhaxybayeva and Gogarten [24] introduced the use of embedded quartets to solve the taxon-sampling problem usually associated with quartet based analyses [25], and used the analysis of embedded Quartet Decomposition to examine gene histories in cyanobacteria, and to identify horizontally transferred genes [13,14]. Boc et al. recently developed a Horizontal Gene Transfer (HGT) detection algorithm that uses a quartet-based distance as one of the criteria when reconciling gene and organismal phylogenies [26]. Quartet analysis is also a good choice for multi-locus sequence data analysis [27], and has been used to infer taxonomic relationships [28,29] as well as tree-like and net-like evolutionary processes [30].
To facilitate a wider application of Quartet Decomposition, we present a web-based platform for decomposing a given set of trees into quartets. The web server also provides several quartet-based analysis tools such as quartet spectrum generation, agreement score calculation, and split network generation. Considering that a user may want to carry out additional analyses of the quartets, we also provide several options to download the computed quartets.
Given a gene tree, our algorithm enumerates all possible combinations M of any four out of x total taxa under consideration, Let's use A, B, C and D to represent the four taxa in a specific embedded quartet of the full phylogenetic tree. In order to determine what specific topology the embedded quartet has, we calculate pairwise distances d AB , d AC , d AD , d BC , d BD and d CD , where the distance d XY is defined as the sum of all branch lengths in the given tree from leaf X to leaf Y. If (d AC + d BD )-(d AB + d CD ) > 0, the quartet has topology TOP1 ( Figure 1 Each branch of the embedded quartet may correspond to several internal edges of the full phylogeny and has a length calculated as exemplified for topology TOP1 (Figure 1): the length of the internal branch is The lengths of other external branches are calculated similarly.
Implementation
The server is implemented on a computer running Linux RedHat Enterprise 5.0 operating system. Apache 2.2.9 is used as the web server, and PHP 5.2.6 is used to develop dynamic webpages. Scripts implementing the server functions are written in Perl. The BioPerl 1.60 [31] TreeIO module is used to help compute the Simulations for each topology were performed with Seq-Gen [16] using the indicated trees, the WAG substitution matrix [17] and a Γ distribution with a shape parameter of 1 approximated by four discrete rate categories for the rate distribution. SEQBOOT from the PHYLIP package [18] was used to generate 100 bootstrap sequences and trees were reconstructed from each bootstrap sample using FastTree 2.1 [19] using the same model for sequence evolution and parameters "-spr 4", "-mlacc 2", and "-slownni" for increased reconstruction accuracy. decomposition of an input tree, and the Perl graphic library GD is used to draw the quartet spectrum. Split-Tree4 [32] is used to generate the split network. A Linux computer cluster with 8 nodes which can support 32 simultaneous jobs is used as the backend for tree decomposition calculation. The Sun Grid Engine 6.2 is used for job management. The overall structure of the server is illustrated in Figure 3. A user needs to prepare two input files: one containing the names of the genomes or taxa under consideration, the other is a compressed file of all gene trees (currently the server will accept .tar.gz, .rar and .zip files). Each gene tree is represented by multiple trees that assess phylogenetic information content, such as sets of trees reconstructed from bootstrap replicates or sampled from a posterior distribution. We also provide an interface for users to generate bootstrap replicates from multiple sequence alignment. The replicates are generated by a BioPerl utility function, and the trees are generated by FastTree 2.1 [19]. Since we are comparing quartets across gene families to obtain a plurality signal, taxa labels corresponding to genes in the same organism are expected to have the same name. To facilitate the replacement of gene identifiers with the names of the genomes, we provide Perl scripts (see FAQ section in the server) for conversion and consistency checks. These scripts require BioPerl 1.60 or newer version on the user's computer. If the user does not have BioPerl installed in their local computer, we also provide a web interface for the user to do the name conversion in the server.
After the name conversion, the user can upload the files to the server, specify the parameter values (or just use the default parameter values given by the server), and start the decomposition calculation. The computation may take several hours depending on the number of taxa, the number of gene families and the number of trees per gene family. For example, when we provided trees from 100 bootstrap samples for each gene family, it took 2 hours and 10 minutes for a job with 1128 gene families from 10 genomes, and 15 hours and 21 minutes for a job with 1734 gene families from 19 genomes. The run time is heavily dependent on the number of genomes since the number of quartets is a fourth degree polynomial of this number. Due to the limitations of computer hardware housing the server at the time of writing (May 2012), we suggest the user not to submit a job with more than 20 genomes. However, the server will accept a job with up to 100 genomes, issuing a warning for a job with more than 40 genomes. The user can refresh the job status page while the job is running: the server will display the currently analyzed gene family. The server will send an email to the user with a link to the status page once the job is submitted; and it will send another email after the job is completed. After the decomposition is done, a quartet spectrum [14] (see next section for its description) will be generated, and the user can run various analyses using tools provided by server, such as filtering quartets, calculating an agreement score, downloading a specified subset of the decomposed quartets, and generating a splits network.
Results and discussion
The server provides a platform for performing the following quartet-based analyses.
Quartet spectrum generation
Quartet Decomposition of a gene tree is the process of finding all possible embedded quartet topologies for a given tree. For a given list of genomes and multiple gene families collected from these genomes, the quartet topologies in a specific gene family are identified, and for the set of taxa summarized in a quartet spectrum. The calculation consists of the following steps (the user needs to perform steps a-c, the server performs steps d-g): a. For a set of genomes of interest, assemble and align gene families, and obtain trees either from bootstrap replicates or from a posterior distribution. b. Prepare trees in Newick format for each gene family. Put all trees for the same gene family to one file. Compress all tree files to a single file. c. Upload genome list and the compressed tree file to the server. Specify the parameters for filters (see below). Start the job. d. Decompose each tree into embedded quartets. e. For each gene family, calculate the support value for the three topologies of each quartet by counting the fraction of the bootstrap trees that contain this quartet topology. In case of 100 replicate trees, each embedded quartet in a family has a dominant topology with a maximum score of 100. Comparable scores for the alternative quartet topologies, such as 34, 33, 33, are indicative of no or little phylogenetic signal for that embedded quartet in a particular gene phylogeny. f. For each quartet, determine the plurality topology across all gene families as follows: given a threshold for a support value cut-off to determine whether the dominant topology is supported (85%, 90% and 95% are currently supported by the server), count the number of gene families supporting each of the three topologies. The topology with the highest number of supporting gene families is considered the plurality topology of the quartet among all the analyzed gene families. g. Sort the quartets by the number of gene families supporting the plurality topologies, and plot as a histogram with these sorted numbers along with the labels of the associated quartets. Analogous to the Lento plot [10], another histogram on the negative side of the Y-axis is also added to show the sum of the two non-plurality topologies (conflicting topologies) for each quartet. The resulting diagram is called the quartet spectrum ( Figure 4).
The quartet spectrum provided by the server is interactive: when a user clicks on the bar representing a specific quartet, a new page pops-up with the detailed information for that quartet, including its support value in each gene family.
Sometimes a user may prefer to compare the individual gene phylogenies against another tree obtained from other sources, such as phylogenies calculated from ribosomal components [33], the Tree of Life Project (http:// tolweb.org/tree/), or the NCBI taxonomy database [34] (http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax. cgi). The server can compare the quartets in the gene families against the quartet topologies embedded in the reference tree and generate a quartet spectrum counting the quartet topologies in the reference tree as positive. Large values in the negative part of the spectrum would indicate specific conflicts between gene phylogenies and the reference tree. The presence of at least one embedded quartet with a bootstrap support value greater than 80 in conflict with a reference phylogeny reveals a significant phylogenetic conflict suggestive of an HGT event. Depending on the data analyzed, alternative explanations for phylogenetic conflict may need to be considered. Lineage sorting occurs in taxa with large populations and a rapid succession of speciation events; unrecognized paralogy always is an alternative explanation to HGT [35] and needs to be considered when independent and parallel gene loss cannot be excluded because only few lineages are analyzed. While the rate of false positives is reasonably assessed through the bootstrap support values [14,36], the rate of false negatives likely is large, especially for transfers between close relatives [37].
Processing of paralogs
If there are paralogs in a gene family (and hence multiple homologs per gene family have the same label), the distribution of quartet topologies will be calculated as follows. Given a tree and four genomes A, B, C and D, the number of paralogs are a, b, c and d for each genome respectively. The total number of quartet topologies with the four genomes will be t = a × b × c × d. Since each topology will represent one of TOP1, TOP2 or TOP3 (see Figure 1), we can count the total number of quartet topologies with TOP1, TOP2 and TOP3 as t 1 , t 2 and t 3 . The sum of t 1 , t 2 and t 3 is equal to t. For the given tree, we calculate the ratio of TOP1, TOP2 and TOP3 as t 1 /t, t 2 /t and t 3 /t, respectively. The sum of the three ratios will be equal to 1, which is the same for a tree without paralogs. In addition, quartets with two tips from same genome (i.e., paralogs) will be ignored. If gene families with paralogs are included in a quartet decomposition analysis, conflicting quartets may reflect the gene duplication events, and can no longer be identified with gene transfer events. However, families with paralogs are useful to extract the plurality phylogenetic signal contained in a set of genomes.
Agreement score calculation
For each gene family we also calculate an agreement score [13], which measures how well the gene family agrees with the plurality or the reference tree: where N is the number of trees for this gene family; M is the number of possible quartets; and n i is the number of topologies that agree with the plurality (or reference) for the i th quartet. The score S is equal to 1 if all the trees have the same topology which is also identical to the reference, and it is less than 1 otherwise. The more conflicts between the gene trees and the reference are observed, the closer the score is to 0.
Filters
The inaccuracies in phylogenetic reconstruction may introduce noise and misleading information to quartet analysis. To minimize their impact, we designed three filters to remove such quartets, categorized as follows.
Long external branch(es)
Each quartet has four external branches and one internal branch ( Figure 1). Long external branches may lead to the so called long branch attraction artifact [38], which may erroneously lead to the conclusion that two rapidly evolving lineages are closely related. A filter is implemented to remove quartets with long external branches according to the following criterion: if the ratio between the longest external branch and the internal branch is larger than a pre-set threshold (default value is 10), it will be removed.
Short internal branch
If a quartet has a very short internal branch, there may not be enough phylogenetic information to resolve the topology correctly. The server provides an option to remove a quartet if its internal branch is shorter than a pre-set threshold (default value is 0.02 substitutions per site). If the branch length in the tree is not measured by substitutions per site, 0.02 may not be an appropriate value, and the user has to decide a proper value by himself.
Less supported quartets
Quartets that due to a lack of phylogenetic signal are poorly resolved in most gene families could result in erroneous but significant conflicts with the plurality (false positives) [14]. To remove quartets that are not resolved by most gene families, we implemented the following filter, defined by two thresholds, T 1 (ranges between 0% and 100%) and T 2 (a positive integer). For a specific quartet, if the proportion of the gene families supporting it with a support value of at least T 1 is less than T 2 , this quartet will be removed from a quartet spectrum. This filter is applied after the decomposition process is done, and the effect of different filter settings on the quartet spectrum can be explored. In contrast, the other two filters have to be specified before the decomposition process starts.
Splits network generation
A splits network is a network representation of the relationship of a set of taxa [39], in which multiple alternative splits (and not just the most supported one) are depicted. In situations with frequent exchanges of genetic material, a split network is a better representation for the taxa relationship than a tree. Our server can convert any quartet subset (see next section for a description of quartet sets) to a matrix [40,41], and then generate a split network by using the SplitTree4 program [32].
Quartet download
Although we have provided a number of quartet analysis tools through the server, a user may want to perform his/her own analyses on the computed quartets. We offer two options to download the decomposed quartets. The first option is to download a subset of the quartets that are supported with a support value of at least T 1 in at least T 2 gene families (see section on filters for descriptions of T 1 and T 2 ). The second option is based on the quartet spectrum. The quartet topologies in agreement with the plurality are considered as plurality quartet topologies, and as conflicting quartet topologies otherwise. The user can obtain the subsets of plurality or conflicting quartet topologies using thresholds T 1 and T 2 as described above.
Examples
We provide two quartet decomposition examples, which can be accessed from the Frequently Asked Questions Figure 4 An example of a quartet spectrum. The x-axis represents the quartets, one per column, arranged in descending order of the number of gene families supporting the plurality/ reference topology of each quartet. For each column, the y-axis represents the number of gene families in which that quartet supports (positive y values, one topology) or conflicts (negative y values, the other two possible topologies) with the plurality or reference topology. For the conflicts, the y value represents a sum of gene families supporting the two other topologies. The spectrum is color-coded according to different bootstrap support thresholds used.
section on the quartet server web page. Both the data sets and the quartet spectrum are available on the server. The user can run the job by using the data sets, or go directly to the quartet spectrum and explore other analyses on the server.
One data set consists of 1,128 gene families present in at least 9 of 11 selected cyanobacterial genomes [14]. Quartet Decomposition of these families revealed that cyanobacterial evolution is incompatible with strictly bifurcating tree and helped to pinpoint specific cases of horizontal gene transfer.
The other data set consists of 1,812 gene families present in at least 4 of 18 specific cyanobacterial genomes of Prochlorococcus marinus and marine Synechococcus spp. [13]. Quartet Decomposition identified 495 gene families that did not separate genera Prochlorococcus and Synechococcus as expected. This observation can be explained by the existence of a "highway of gene sharing" between marine Synechococcus spp. and low-light adapted Prochlorococcus spp. (see [13] for additional discussion).
In both studies the Quartet Decomposition has proven to be an invaluable tool for identification of phylogenetic signal shared by genes in analyzed genomes and for discovery of horizontally transferred genes.
Conclusion
The Quartet Decomposition server presented here provides an interactive interface to dissect complex evolutionary histories of microbial genomes. We believe that this online service will be a valuable tool for the comparative genomics community.
Availability and requirements
Project name: Quartet Decomposition server. Project home page: http://quartets.uga.edu. Operating system(s): Platform independent Other requirements: The server has been tested using Firefox (Windows, Linux and Mac OS X), Internet Explorer (Windows), Safari (MacOS X Lion), and Google Chrome (Windows and Linux) browsers. | 5,384.4 | 2012-06-07T00:00:00.000 | [
"Biology",
"Computer Science"
] |
Limb regeneration revisited
The investigation of vertebrate limb regeneration, a favorite topic of early developmental biologists, is enjoying a renaissance thanks to recently developed molecular and genetic tools, as indicated in recent papers in BMC Biology and BMC Developmental Biology. Classical experiments provide a rich context for interpreting modern functional studies.
W Wo ou un nd d h he ea al li in ng g m ma ak ke es s a al ll l t th he e d di if ff fe er re en nc ce e Following amputation, a salamander's limb bleeds only briefly and the important operation of healing the wound in a way conducive to regeneration begins. Within 24 hours, the cut surface is ensheathed by epithelial cells that migrate from the surface of the stump (Figure 1). These 'wound epidermis' cells proliferate, forming the 'apical epidermal cap' (AEC), a structure postulated to provide key molecular signals needed to stimulate and/or maintain the early stages of regeneration. Without this specialized wound healing, regeneration fails; for instance, if the limb is amputated and the dorsal and ventral skin is pulled together and sutured, no true AEC forms and the limb remains a stump.
B Bu ui il ld di in ng g a a b bl la as st te em ma a The next critical step is to create a blastema -a pool of cells from which the new limb will arise. Forming at the distal tip of the old stump but beneath the AEC, the blastema morphologically appears as a transparent outgrowth that acquires the shape of a cone as regeneration proceeds ( Figure 1). Blastema cells are thought to be relatively undifferentiated mesenchymal cells, but their origins remain A Ab bs st tr ra ac ct t The investigation of vertebrate limb regeneration, a favorite topic of early developmental biologists, is enjoying a renaissance thanks to recently developed molecular and genetic tools, as indicated in recent papers in BMC Biology and BMC Developmental Biology. Classical experiments provide a rich context for interpreting modern functional studies.
highly controversial (reviewed in [5]). Early work suggested that at least some blastema cells arise by the dedifferentiation of muscle fibers, as the fibers immediately adjacent to the amputation plane showed microscopic signs of cellularization, and these presumably newly created mononucleate cells incorporated tritiated thymidine [6]. Studies using modern labeling techniques, such as fluorescent dye tracking and fluorescently labeled antibodies, support a similar model, yet controversy remains because others claim that a stem-cell population, the muscle satellite cells, also participate in blastema formation. Furthermore, the possibility of transdifferentiation of cells in the stump to different cell types in the regenerate, a process hinted at in earlier studies, needs to be definitively addressed, both in terms of the potential of blastema cells for transdifferentiation and the extent to which this phenomenon is significant for normal regeneration. These questions await more sophisticated cell-lineage analysis. Such analysis may be facilitated by the identification of cell-type-specific promoters in conjunction with the recently developed transgenic approaches.
Once the blastema cells are collected under the AEC, they must proliferate to provide enough cells to drive the regeneration process forward ( Figure 1). The proliferation of blastema cells has been shown to be critically reliant on the presence of the nerve in the limb [7]. For example, a limb that has been denervated and then amputated will close the wound in an outwardly normal manner, and a blastema will form, but the blastema cells do not proliferate enough and regeneration fails. Interestingly, if a limb is manipulated to develop originally without the nerve, this limb can be amputated and a fairly normally regenerated limb grows. These data suggest the limb somehow becomes 'addicted' to factors produced by the nerve and then needs them for regeneration.
Recent work has shown that regeneration of a denervated limb can be mostly rescued by providing cDNA encoding a single protein, nAG [8]. nAG is a secreted ligand for Prod1, a hitherto mysterious cell-surface molecule whose expression is graded along the proximal-distal axis in a salamander limb. A yeast two-hybrid strategy was used to uncover nAG, and the relatively modern technique of electroporation of plasmid DNA into limb blastemas was used to demonstrate its sufficiency for replacing the nerve.
While the outlines of blastema formation are fairly well understood, relatively few molecules have been implicated in specific events that form and shape the blastema. Much work remains to discover the cellular origins of blastema cells, how these cells are cued to form a blastema, and how the blastema cells are stimulated to proliferate. Some clues may be found using genomic approaches, as shown by the recent study by Monaghan et al. [2], where many transcripts were identified as differentially expressed in blastemas undergoing normal regeneration compared with those whose limb had been denervated. F Fi in ni is sh hi in ng g t th he e j jo ob b Eventually, blastema cells begin the process of reorganizing and of specifying distinct cellular identities for the new limb. Morphologically, the blastema becomes flattened and acquires the shape characteristic of a 'palette-staged' limb bud with the vague outline of future digits discernable ( Figure 1). Most of the events governing the regeneration process from this point onward are presumed to be similar or identical to the molecular events that transform a limb bud into a limb. It is, however, important to note that many of these assumptions remain to be tested, and that the two scenarios cannot be completely equivalent. For instance, the scale at which a limb regenerates is often many timesperhaps even thousands of times -larger than that at which it developed when the animal was a tiny larva. In addition, new features such as blood vessels and fine nerves need to be seamlessly integrated into the existing structures on the stump if the limb is to thrive and function properly. Nonetheless, some mechanisms have already been shown to be common; for example, the ectopic production of Sonic hedgehog signaling activity in the anterior margin of a regenerating limb produces the same effect -duplication of posterior digits -in a regenerating blastema as in a newly developing limb bud [9].
D De ec co od di in ng g t th he e s se ec cr re et ts s o of f p pe er rf fe ec ct t r re eg ge en ne er ra at ti io on n If all steps proceed normally, the salamander or tadpole regrows a perfect replica of its original limb. This precise replication is one of the most remarkable aspects of regeneration. An animal that loses a foot will grow back only a foot and no more; one that loses the leg from the thigh will grow back everything that was once distal to the thigh's amputation plane. Somehow, the salamander's body can measure where the amputation occurred along the proximaldistal axis and replace only the missing part, but how?
While the process is still poorly understood, some clues have come from blastema-grafting experiments (reviewed in [10]). When grafted to a proximal 'thigh' blastema, a distal blastema 'fated' to make a foot translocates distally with the host's regenerating limb and gives rise to a regenerated limb that essentially has two feet. Alternatively, a proximal blastema grafted to a proximal blastema host will create a salamander with essentially two complete legs. Therefore, the proximo-distal information is encoded within the blastema. Remarkably, if a proximal limb blastema is grafted to a receptive field such as the eye (parts of which can also regenerate in many salamanders), a limb will grow from the eye socket, demonstrating that the blastema is indeed an autonomous unit and, once created, may only rely on the underlying tissue for survival factors but not for contextual information. On a molecular level, there is evidence that the cell surface protein Prod1, mentioned above, plays a critical role in mediating proximo-distal positional information. However, the question of how positional information is established in the blastema and how it influences cell behavior to achieve precise replacement of amputated structures remains largely untouched but will benefit from the application of the modern genomic and genetic techniques discussed earlier.
Understanding the molecular and cellular mechanisms that allow salamanders to create and develop a blastema may help develop therapies for improving regeneration in animals that do not. A good starting point for comparison is a salamander, which can regenerate throughout its life, and a frog, which can only regenerate limbs while it is a tadpole and gradually loses the ability to regenerate as it approaches the final step of metamorphosis. An even simpler comparison can be made between a tadpole at a stage that regenerates versus a laterstaged tadpole that cannot. The recent work from Caroline Beck's lab (Pearl et al. [3]) profiled gene expression in blastemas from normally regenerating tadpoles compared with those in which regeneration was blocked by the misexpression of Noggin, an inhibitor of the secreted signal molecule bone morphogenetic protein (BMP). Genes defined as essential regulators of regeneration in this case included those that specifically influence the transition from an early blastema to a larger, cone-shaped blastema (the step that is blocked in the absence of BMP activity).
Similar approaches may prove fruitful for discovering transcripts expressed at other discrete stages, for instance, during the critical wound healing that initiates limb regeneration in the salamander. Further evidence for the importance of this step comes from human medicine: in young children with distal amputations of digits, regeneration of a perfect fingertip can occur, but only if the stump skin is not sutured together. If early healing stages were better understood in both regenerating and non-regenerating scenarios, we would have a better chance of figuring out how to heal a wound in a way that leads to formation of a blastema.
Regeneration research is now undergoing a resurgence, with initial efforts fueled by modern approaches to understanding gene expression. Upcoming work will take advantage of the power of transgenesis to explicitly address the functions of specific genes at particular stages of regeneration and in particular cell types. Additional tools are still needed, however. Limb regeneration is most impressive among salamanders, and no salamander genomes have been sequenced to date (mostly due to their enormous size). Moreover, a reliable method for eliminating or reducing gene function in salamanders has not yet been established.
As such new genetic and genomic tools are developed, we will be able to fully realize the power of salamanders as model systems for understanding limb regeneration.
A Ac ck kn no ow wl le ed dg ge em me en nt ts s Regeneration research in the Tabin lab is funded by the NIH, grants R01 HD045499, 1F32 HD054082-01. | 2,511.6 | 2009-01-13T00:00:00.000 | [
"Biology"
] |
Disentangling the effects of structure and lone-pair electrons in the lattice dynamics of halide perovskites
Halide perovskites show great optoelectronic performance, but their favorable properties are paired with unusually strong anharmonicity. It was proposed that this combination derives from the ns2 electron configuration of octahedral cations and associated pseudo-Jahn–Teller effect. We show that such cations are not a prerequisite for the strong anharmonicity and low-energy lattice dynamics encountered in these materials. We combine X-ray diffraction, infrared and Raman spectroscopies, and molecular dynamics to contrast the lattice dynamics of CsSrBr3 with those of CsPbBr3, two compounds that are structurally similar but with the former lacking ns2 cations with the propensity to form electron lone pairs. We exploit low-frequency diffusive Raman scattering, nominally symmetry-forbidden in the cubic phase, as a fingerprint of anharmonicity and reveal that low-frequency tilting occurs irrespective of octahedral cation electron configuration. This highlights the role of structure in perovskite lattice dynamics, providing design rules for the emerging class of soft perovskite semiconductors.
2][3] These compounds are highly unusual among the established semiconductors because they feature an intriguing combination of properties.Strong anharmonic fluctuations [4][5][6] in these soft materials appear together with optoelectronic characteristics that are favorable for technological applications. 7,8This confluence raised puzzling questions regarding the microscopic characteristics of the materials and the compositional tuning of their properties alike.On the one hand, the soft anharmonic nature of the HaP structure may be beneficial in self-healing mechanisms of the material, [9][10][11] allowing for low-energy synthesis routes in their fabrication.On the other hand, pairing of anharmonic fluctuations and optoelectronic processes for key quantities of HaPs, e.g., band gaps, [12][13][14][15] optical absorption profiles, [16][17][18] and chargecarrier mobilities, 8,[19][20][21][22][23][24][25] exposed incomplete microscopic rationales for the fundamental physical processes involved in solar-energy conversion.Established materials design rules are now being challenged by these observations, opening a gap in our protocols for making improved com-pounds.Significant efforts are now underway to discern the chemical effects giving rise to these remarkable properties of HaPs.Because lattice dynamical and optoelectronic properties appear both to be special and coupled in unusual ways, a common origin in chemical bonding could underlie these phenomena.In this context, an interesting chemical feature is that the octahedral cations in these compounds often bear an ns 2 electron configuration (e.g., Pb 2+ with configuration [Xe]6s 2 ), which is not present in many other semiconductors. 26This particular aspect of HaPs leads to a "strong" or "weak" pseudo-Jahn-Teller (PJT) effect, [27][28][29] depending on the particulars of cation and anion composition and chemical pressure.6][37] The weak PJT effect associated with 6s 2 Pb 2+ coordinated by heavy halides plays a role in optoelectronic properties of these materials: its influence on the dielectric function can modify the Coulomb screening that is relevant for small exciton binding energies, reduced recombination rates and other key properties of HaPs. 38,39onfluences of the propensity for lone-pair formation with structural and lattice-dynamical properties were investigated in previous work exploring the chemical space of HaPs.Gao et al. 32 found an inverse relationship between the Goldschmidt tolerance factor, t, 40 and anharmonic octahedral tilting motions.Similarly, Huang et al. varied the A-site cation to explore interrelations of chemical, structural, and dynamical effects in HaPs, 34 reporting t-induced modulations of octahedral tiltings and lone-pair stereoactivity.A recent study by several of the present authors found that Cs 2 AgBiBr 6 lacks some expressions of lattice anharmonicity found in other HaP variants. 41ecause every other octahedral cation (Ag + , 4d 10 ) cannot form a lone pair in this compound, this raised the possibility that changing the electron configuration of the cations may also suppress certain aspects of the lattice dynamics in HaPs.Taken together, previous work assigned a central role of the ns 2 electron configuration and associated PJT effect in the anharmonic lattice dynamics of HaPs in addition to their established effect on the electronic structure and dielectric screening.However, exploring the chemical space of HaPs in this way simultaneously changes their structures.Therefore, isolating the convoluted occurrences of cation lone-pair formation propensity and purely structurally-determined changes in the lattice dynamics of HaPs remained challenging, making an assessment of the precise impact of chemical bonding on anharmonicity in these soft semiconductors largely inaccessible.Here, we address this issue and show that an ns 2 cation compatible with lone-pair formation is not required for the strong anharmonicity in the low-energy lattice dynamics of soft HaP semiconductors.We disentangle structural and chemical effects in the lattice dynamics of HaPs by comparing the well-known CsPbBr 3 with the far less studied CsSrBr 3 .Both exhibit almost identical geometrical and structural parameters, but CsSrBr 3 exhibits a negligible PJT effect on the octahedral Sr 2+ site, owing to weaker vibronic coupling to degenerate excited states of appropriate symmetry which lie higher in energy than in the Pb 2+ case, allowing separation of the effects of the ns 2 electron configuration and the geometry on the lattice dynamics in a direct manner.[42][43][44] While the electronic structure and dielectric properties of CsPbBr 3 and CsSrBr 3 are very different, their vibrational anharmonicities are found to be remarkably similar.In particular, the crucial dynamic octahedral tiltings giving rise to the Raman central peak are still present even in the absence of ns 2 octahedral cations in CsSrBr 3 .Our results provide microscopic understanding of precisely how the propen-sity for lone-pair formation influences the anharmonic octahedral tiltings that dynamically break the average cubic symmetry in both compounds, and rule out the weak PJT associated with the ns 2 main-group cations as the sole reason for the appearance of such anharmonicity in soft HaPs.These findings are important for chemical tuning of HaPs needed for new materials design.
Electronic structure and bonding
We first investigate the electronic structure and bonding of CsPbBr 3 and CsSrBr 3 using density-functional theory (DFT).Figure 1 shows their band structure, total and projected density of states (DOS), as well as the total and projected crystal-orbital Hamilton population (COHP) of the high-temperature cubic phases of CsPbBr 3 and CsSrBr 3 .The electronic band structure and bonding of CsPbBr 3 were extensively investigated before: 45 conduction band minimum (CBM) is formed by antibonding interactions (positive COHP in Figure 1c) between Pb-6p and Br-4p/Br-4s orbitals, while the valence band maximum (VBM) is formed by anti-bonding interactions between Br-4p and Pb-6s orbitals.The electronic structure of CsSrBr 3 exhibits entirely different characteristics, 26,46 especially a much larger band gap and weaker covalent interactions.Notably, the magnitude of the COHP is significantly reduced with respect to that of CsPbBr 3 , indicating much greater ionicity, and the COHP is almost entirely recovered by interactions between Cs and Br.Importantly, all bands derived from antibonding interactions between Sr-5s and Br-4p/Br-4s are empty due to the electron configuration of Sr 2+ ([Kr]), and there is no potential for lone pair formation on Sr 2+ .A manifestation of the lack of ns 2 cations in CsSrBr 3 is that there is no cross-gap hybridization of the halide valence orbitals.By contrast, Br-4p orbitals hybridize with Pb-6p across the gap of CsPbBr 3 (see the pCOHP in Figure 1c).This leads to large Born effective charges, i.e., large changes in the macroscopic polarization upon ionic displacements [47][48][49][50] reported in Table I, which for CsPbBr 3 are more than double the formal charge of Pb (+2) and Br (-1) and much larger than the corresponding values for CsSrBr 3 .Similarly, there is also a larger electronic contribution to the dielectric response in CsPbBr 3 and it features a larger value of the dielectric function at the high-frequency limit (ε ∞ ) compared to CsSrBr 3 .
Structural properties and phase transitions
In spite of the markedly different electronic structure and bonding characteristics, CsSrBr 3 and CsPbBr 3 exhibit the same high-temperature cubic crystal structure (P m 3m) and very similar lattice parameters (see Supplementary Information).One can rationalize this through the nearly identical ionic radii of Pb 2+ and Sr 2+ (119 and 118 pm) and the resulting Goldschmidt factors for the compounds (0.862 and 0.865).Furthermore, both materials exhibit the same sequence of structural phase transitions from the high-temperature cubic to the lowtemperature orthorhombic phase (with an intermediate tetragonal phase), as shown by temperature-dependent lattice parameters in Figure 2 that were determined via XRD.The cubic-to-tetragonal phase transition tempera- ture of CsSrBr 3 (∼520 K) is noticeably higher than that of CsPbBr 3 (∼400 K) 51,52 and slightly higher (∼10 K) than that reported for Eu-doped CsSrBr 3 :Eu 5%. 53he volumetric thermal expansion coefficient (α V ) of CsSrBr 3 (∼1.32× 10 −4 K −1 at 300 K) is large and similar to that of CsPbBr 3 (∼1.29 × 10 −4 K −1 , see the Supplementary Information for details), in good agreement with the one reported for CsSrBr 3 :Eu. 53Just as for other inorganic HaPs, α V of CsSrBr 3 slightly decreases with temperature. 54,55The similarity of geometric factors and structural phase transitions suggests that the octahedral tilting dynamics in CsSrBr 3 might be similar to those in CsPbBr 3 , which contrasts with their markedly different electronic structure, and prompts a deeper investigation of the impact of the ns 2 cations on structural dynamics.
Lower-temperature lattice dynamics
We conduct IR and Raman spectroscopy at different temperatures as well as DFT-based harmonic-phonon calculations.The measured IR spectra show that the dominant CsSrBr 3 features are blue-shifted compared to those of CsPbBr 3 (see Figure 3a).Indeed, our DFT calculations of IR activities find a significant softening of the infrared-active TO modes in CsPbBr 3 compared to those in CsSrBr 3 (see Figure 3b): the most prominent IR-active TO mode in CsPbBr 3 and CsSrBr 3 appears at ∼68 and 146 cm −1 , respectively, corresponding to the same irreducible representation (B3u) with similar eigenvectors (see Supplementary Information) in each system.This is in line with the theory of weak PJT effects in general 29 and expectations for lone pairs in particular, with significant softening of ungerade modes in CsPbBr 3 that would correspond to lone-pair formation in the strong PJT case relative to those in CsSrBr 3 .Notably, this softening is primarily driven by differences in bonding rather than the difference in the atomic masses (see Supplementary Information).Moreover, the LO/TO splitting is enhanced in CsPbBr 3 compared to in CsSrBr 3 and the LO phonon modes are hardened.Related to this, the CsPbBr 3 IR spectrum exhibits a broad feature which is known as the Reststrahlen band as has been reported before for MA-based HaPs. 56This particular effect results in near-zero transmission through the material in a frequency range between the TO and LO modes, represented by high IR intensity values, and occurs in polar materials with larger Born-effective charges.Because the TO modes are softened and the LO modes hardened in CsPbBr 3 compared to CsSrBr 3 , and because the latter is less polar (cf.Table I), the absence of the ns 2 cations leads to a much less pronounced, blue-shifted Reststrahlen band appearing in a smaller frequency window in CsSrBr 3 (see Figure 3a, and Supplementary Information).
Figure 3c shows the 80 K Raman spectra of CsPbBr 3 and CsSrBr 3 , which are in good agreement with the Raman activities calculated for harmonic phonons (Figure 3d).Specifically, the experimental spectrum of CsPbBr 3 in Figure 3b finds three broader features at frequencies below and one weaker-intensity feature at frequencies above 100 cm −1 .Conversely, CsSrBr 3 exhibits a structured feature around 50 cm −1 , a pronounced signal close to 100 cm −1 , and then a series of weaker intensities between 100-150 cm −1 .
While the DFT-computed Raman activities calculated in the harmonic approximation are in broad agreement with these findings (see Figure 3d), we note a slightly larger deviation of approximately 20 cm −1 for the higher-frequency peak in CsPbBr 3 .These findings lead us to conclude that unlike in IR, the Raman spectrum of CsSrBr 3 exhibits no substantial energy shifts with respect to CsPbBr 3 .Computing the phonon DOS for the orthorhombic phase of both compounds with DFT (see Supplementary Information), we find that they exhibit similar phonon DOS below 100 cm −1 , i.e., in the region of most of the Raman-active modes.The similar phonon DOS and the contributions of the M-site at low frequencies explain the limited shift of the CsSrBr 3 Raman spectrum, which might be surprising at first sight given the different atomic masses of Sr and Pb.Above this range, CsPbBr 3 exhibits few vibrational states while CsSrBr 3 shows its most pronounced phonon DOS peaks, which correspond well with the strongest IR mode calculated from the harmonic approximation.
High-temperature lattice dynamics
[42][43][44] We use this feature that is nominally symmetry-forbidden in the cubic phase as a fingerprint to directly investigate how the propensity for cation lone-pair formation or lack thereof determines anharmonicity in these materials, using Raman spectroscopy and DFT-based MD simulations.Interestingly, a central peak also appears in the high-temperature Raman spectrum of CsSrBr 3 (see Figure 4 and Supplementary Information for full temperature range).We note that differences in Raman intensity imply that the scattering cross-section of CsSrBr 3 is notably weaker than that of CsPbBr 3 , which is due to its significantly higher bandgap and weaker dielectric response at the Raman excitation wavelength (785 nm) and because a powder sample of CsSrBr 3 has been used for which scattering of light in the back-scattering direction is considerably lower.The presence of a central peak in CsSrBr 3 shows that local fluctuations associated with a cation lone-pair are not required for the low-frequency diffusive Raman scattering and anharmonicity to occur.This result, together with the identical phase-transition sequences of both materials (see Figure 2), led us to investigate the role of tilting instabilities in CsSrBr 3 and CsPbBr 3 .We first calculate the Raman spectrum for both compounds using MD calculations (see Figure 4 and Methods section).Remarkably, a central peak appears also in the MD-computed high-temperature Raman spectrum of CsPbBr 3 and CsSrBr 3 .We find good agreement between experiment and theory, both showing a feature between 50-100 cm −1 in the Raman spectra of the two materials in addition to the central peak.Next, we compute harmonic phonon dispersions of both compounds (see Figure 5) and find these to be remarkably similar for cubic CsSrBr 3 and CsPbBr 3 in the low frequency region, in line with the aforementioned similarities in the phonon DOS of the orthorhombic phase.Specifically, both compounds exhibit the same dynamic tilting instabilities at the edge of the Brillouin zone (BZ), governed by in-phase (M point) and three degenerate out-of-phase (R point) rotations.][59][60] Finally, using the MD trajectories of CsPbBr 3 and CsSrBr 3 in the cubic phase, we calculate the frequencyresolved dynamic changes of octahedral rotation angles, Φ α (ω) (see Figure 6 and Equation 1 in the Methods Section).Figure 6b shows Φ α (ω) for CsPbBr 3 and CsSrBr 3 and indicates strong low-frequency tilting components in both CsPbBr 3 and CsSrBr 3 .2][63] Our results confirm that substantial octahedral dynamics correspond to low-frequency features dynamically breaking the cubic symmetry in CsPbBr 3 and CsSrBr 3 . 4,14,43,64,65nterestingly, this low-frequency component appears irrespective of the presence of ns 2 cations and induces the formation of relatively long-lived (tens of ps) structural distortions (see Supplementary Information), which strongly deviate from the average cubic symmetry.This suggests that the dynamic deviations from the long-range, FIG. 4. Lattice dynamics at higher temperature.Raman spectra of CsPbBr3 (panel a) and CsSrBr3 (panel b) in the high-temperature cubic phase measured experimentally and calculated using DFT-MD.The central peak appears for both compounds in the experiments and computations despite significant differences in bonding: [PbBr6] 4− is proximate to lone-pair formation (i.e., exhibits a "weak" PJT effect), 29 while PJT effects associated with [SrBr6] 4− are negligible.crystallographic structure enable the low-frequency Raman response without violating the selection rules.We investigate the impact of the M-site chemistry on octahedral tilting tendencies 32 by computing the Fourier-transform of cross-correlations between rotation angles and M-site displacements, C αβ (ω) (see Equation 2in the Methods section).Larger values of C αβ generally indicate stronger coupling between octahedral rotations and Pb displacements.Absence of the propensity for lone-pair formation becomes evident in the low intensity of C αβ (ω) for CsSrBr 3 (Figure 6c), which is less than half of that of CsPbBr 3 , especially at low-frequencies relevant for the slow, anharmonic, symmetry-breaking rotational features.This suggests that the presence of the ns 2 cations in CsPbBr 3 enhances the low-frequency octahedral tilting, in line with the literature. 32M-site displacements and octahedral rotations are correlated because the latter is accompanied by changes of the Br-Pb-Br resonant network 17 affecting the charge density in the vicinity of the M-site.While this effect is very weak in CsSrBr 3 (see Supplementary Information), the non-zero C αβ for this case shows that the presence of ns 2 cations is not necessary to couple octahedral rotations and M-site displacements because the ions are still interacting through other types of interactions, e.g., electrostatically or due to Pauli repulsion.In CsPbF 3 , the interaction of tilting and M-site displacements is strong enough to drive the adoption of an unusual tilt pattern. 36We speculate that the lone-pair-enhanced tilting could contribute to the fact that CsPbBr 3 has a lower tetragonal-to-cubic phase transition temperature compared to that of CsSrBr 3 .
Discussion
We directly disentangled structural and chemical effects in HaPs by comparing CsPbBr 3 and CsSrBr 3 , two compounds with similar ionic radii and structural properties but entirely different orbital interactions that imbue CsPbBr 3 with the weak PJT effect common to technologically-relevant Pb perovskites and CsSrBr 3 with negligible PJT effects.While the ns 2 configuration of the octahedral cations is paramount for the optoelectronic and dielectric properties of these materials, using the Raman central peak at higher temperatures as a fingerprint to detect anharmonicity we found it to appear also for CsSrBr 3 with 5s 0 cations and to correlate with slow, anharmonic rotations of the octahedra.Altogether, these findings demonstrate that the perovskite structure allows for anharmonic vibrational dynamics to occur, irrespective of the presence of ns 2 cations with the propensity to form lone pairs, which establishes this somewhat unusual behavior as a generic effect in this material class.We note that recent work by some of the present authors has investigated the commonalities and differences between oxide perovskites and HaPs in this context. 44ince octahedral dynamics impact the optoelectronic characteristics of these systems, our results have implications for synthesis of new HaPs with improved properties for technological applications.For instance, Pb-Sr alloying has been proposed as a method to tune the band gap of HaPs for light emission and absorption applications. 46Our work implies that such Sr alloying for tuning electronic and dielectric properties preserves the strongly anharmonic lattice dynamics.Furthermore, investigating related compounds with distinct electronic configurations on the octahedral cation, such as CsEuBr 3 , may provide further insight about chemical trends in tuning of the HaP properties.The relevance of these findings for material design strategies of HaP compounds is additionally affirmed when putting our results in the context of previous work discussing anharmonic effects in this class of materials.
34]66 By contrast, the high symmetry phase of Cs 2 AgBiBr 6 is anharmonically stabilized and exhibits well-defined normal modes and a soft-mode transition on cooling. 41Cs 2 SnBr 6 , on the other hand, lacks any phase transitions and similarly exhibits well-defined normal modes. 67Where previously the strength of the PJT effect associated with ns 2 cations or the density of such cations appeared to be a plausible predictor of broad, nominally symmetry-forbidden Raman scattering resulting in a central peak, our work suggests that instead the differing symmetry in both the structure and the chemical bonding of metal halide perovskites and double-perovskites may be a controlling factor.Notably, CsGeBr 3 , which exhibits no octahedral tilting transitions 68 and a broad Raman central peak in the cubic phase with a mode reflecting persistent pyramidal [GeBr 3 ] − anions, 32 corresponds to the "strong" PJT 29 case: Stereochemically expressed cation lone pairs are evident in the low temperature average structure 68 and in the local fluctuations of the cubic phase. 32Dynamic symmetry-breaking giving rise to a broad Raman central peak is thus observed for three distinct bonding regimes with regard to pseudo-Jahn-Teller effects: strong PJT (CsGeBr 3 ), 32 weak PJT (CsPbBr 3 and others), 33 and negligible PJT (CsSrBr 3 ).In conclusion, the ns 2 electron configuration in HaPs that can result in formation of lone-pairs is crucial to several favorable electronic features 26,38,45 and gives rise to the elevated ionic dielectric response via enhancement of Born effective charges. 38,47However, we found that presence of a strong or weak PJT effect associated with ns 2 cations is not necessary to produce dynamic symmetry-breaking of the sort that gives rise to broad, intense Raman scattering in the high temperature phases of HaPs and that has been associated with the unique optoelectronic properties in these compounds such as long charge-carrier lifetimes and photoinstabilities.Instead, such dynamic symmetry breaking is common to all cubic bromide and iodide (single-)perovskites thus far studied to the best of our knowledge.These results highlight the key role of structural chemistry in the anharmonic dynamics of halide perovskites, providing a new criterion for the design of soft optoelectronic semiconductors.
Electronic Structure Calculations
DFT calculations were performed with Vienna ab-initio simulation package (VASP) code 69 using the projectoraugmented wave (PAW) method. 70We employed the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional 71 and the Tkatchenko-Scheffler (TS) scheme 72 -using an iterative Hirshfeld partitioning of the charge density 73,74 -to account for dispersive interactions.This setup has been shown to accurately describe the structure of HaPs. 75,76All static calculations used an energy convergence threshold of 10 −6 eV, a plane-wave cutoff of 500 eV, and a Γ-centered k-grid of 6 × 6 × 6 (6 × 4 × 6) for the P m 3m (P nma) structures.Lattice parameters were optimized by a fitting procedure using the Birch-Murnaghan equation of state 77,78 The final structures used in all subsequent calculations were obtained by relaxing the ionic degrees of freedom until the maximum residual force was below 10 −4 eV/Å.The total and projected electronic DOS and COHP, were calculated by partitioning the DFT-calculated band structure into bonding and antibonding contributions using the LOBSTER code. 79,80For this task, the DFT-computed electronic wave functions were projected onto Slater-type orbitals (basis set name: "pbeVaspFit2015") 79 including Cs 6s, 5p and 5s, Pb 6s and 6p, and Br 4p and 4s states.The maximum charge spilling in this procedure was 1.3%.Spin-orbit coupling was not included in our calculations, since it is currently not supported by the LOBSTER code.We emphasize that our focus is on the orbital contributions to the (anti) bonding interactions, rather than on a quantitative descriptions of the energy.
Phonon Calculations
Phonon dispersions and DOSs were obtained via the finite displacements method implemented in the phonopy package. 81For these calculations, we used 2 × 2 × 2 supercells with 40 (160) atoms of the P m 3m (P nma) CsMBr 3 structures reducing k-space sampling accordingly.IR and Raman spectra were computed with the phonopyspectroscopy package, 82 using zone-center phonon modes, Born-effective charges and polarizabilities, calculated with density functional perturbation theory (DFPT). 83rst-principles Molecular Dynamics DFT-based MD calculations were performed for 2 × 2 × 2 supercells of the P m 3m structures using a Nosé-Hoover thermostat within the canonical ensemble (NVT), as implemented in VASP. 84The simulation temperature was set to T =525 and 570 K for CsPbBr 3 and CsSrBr 3 , respectively.An 8 fs timestep, reduced k-grid of 3 × 3 × 3, and energy convergence threshold of 10 −5 eV were used for the 10 ps equilibration and 115 ps production runs.
Raman Spectra From Molecular Dynamics
DFT-based MD calculations were used to compute the high-temperature Raman spectra of CsPbBr 3 and CsSrBr 3 .We calculated Raman intensities from the autocorrelation function of the polarisability, as detailed elsewhere. 85The polarizabilities were calculated with DFPT 83 on 400 evenly-spaced snapshots every 0.11 ps for a total of 44.8 ps.The k-grid employed for the DFPT calculations was set to 4 × 4 × 4 after testing convergence of the polarisability tensor for several snapshots.
Octahedral Rotation Dynamics and Cross-correlations
We quantified the octahedral dynamics using the rotation angles, ϕ α , around a given Cartesian axis α (see Figure 6a).The frequency-resolved rotational dynamics were calculated as the Fourier transform of ϕ α : where N steps is the number of snapshots.To compute the angles we selected 1000 equally spaced snapshots.We calculated the frequency-resolved cross-correlation between octahedral rotation angles (around a Cartesian direction α) and the displacements (along a Cartesian direction β) of the corresponding M-site, d M β (t), as:
Infrared Reflectivity Measurements
IR-reflection spectra in the THz range were measured as a combination of time-domain THz spectroscopy (TDS) for the low-frequency end and bolometer detection for the higher frequencies.Bolometer spectra were measured using a Bruker 80v Fourier-transform IR spectrometer with a globar source and a bolometer detector cooled to liquid He temperatures.The crystals were mounted for reflection measurements and the instrument was sealed in vacuum.A gold mirror was used as reflection reference.TDS was performed using a Spectra Physics Mai Tai-Empower-Spitfire Pro Ti:Sapphire regenerative amplifier.The amplifier generates 35 fs pulses centered at 800 nm at a repetition rate of 5 kHz.THz pulses were generated by a spintronic emitter, which was composed of 1.8 nm of Co 40 Fe 40 B 20 sandwiched between 2 nm of Tungsten and 2 nm of Platinum, all supported by a quartz substrate.The THz pulses were detected using electro-optic sampling in a (100)-ZnTe crystal.A gold mirror was used as reflection reference.The sample crystals, THz emitter and THz detector were held under vacuum during the measurements.TDS offers better signal at low frequency, while bolometer measurements have an advantage over TDS at higher frequencies.Therefore, the spectra were combined and merged at 100 cm −1 .Owing to scattering losses, the absolute intensity of reflected light can not be taken quantitatively.Therefore, the spectra were scaled to the signal level at 100 cm −1 before merging the data.The final reflectivity spectra are given in arbitrary units.The phonon frequencies and overall spectral shape allows for fitting to the dielectric function.
Raman Spectroscopy
All the measurements were taken in a home-built back scattering Raman system.For all measurements, the laser was focused with a 50x objective (Zeiss, USA), and the Rayleigh scattering was then filtered with a notch filter (Ondax Inc., USA).The beam was focused into a spectrometer 1 m long (FHR 1000, Horiba) and then on a CCD detector.To get the unpolarized Raman spectrum for the single crystals (CsSrBr 3 low temperatures and CsPbBr 3 ), two orthogonal angles were measured in parallel and cross configurations (four measurements overall).The unpolarized spectrum is a summation of all four spectra.The samples were cooled below room temperature by a Janis cryostat ST-500 controlled by Lakeshore model 335 and were heated above room temperature by a closed heating system (Linkam Scientific).Due to the extreme sensitivity of CsSrBr 3 to ambient moisture, CsSrBr 3 powder was flame-sealed in a small quartz capillary for the high-temperature measurements, and a single crystal was loaded into a closed cell under an Ar environment for the low temperatures measurements.CsSrBr 3 low temperature measurements were taken with a 2.5 eV CW diode laser (Toptica Inc.).CsSrBr 3 high-temperature measurement and all the CsPbBr 3 measurements were taken with a 1.57 eV CW diode laser (Toptica Inc.).We note that while Raman spectra on quartz show a contribution towards zero frequency, 88
theFIG. 1 .
FIG. 1. Electronic structure.DFT-computed electronic band structure of cubic CsPbBr3 (panel a) and corresponding total and projected density of states (DOS, panel b) and crystal-orbital Hamilton population (COHP, panel c).Panels d-f show the same data for CsSrBr3.
FIG. 2 .
FIG. 2. Structural properties.Temperature-dependent lattice parameters of CsPbBr3 (panel a) and CsSrBr3 (panel b) determined by XRD throughout the orthorhombictetragonal-cubic phases.We show reduced lattice parameters ã, b and c for better visualization, with the orthorhombic phase expressed in the P bnm setting.Dashed vertical lines indicate phase-transition temperatures.Error bars from Pawley fitting are smaller than the markers and are omitted.
FIG. 3 .
FIG. 3. Lattice dynamics at lower temperatures.a) IR-reflectivity spectra (dashed curves) and fitted imaginary part of the dielectric function (solid curves, see Supplementary Information for details) of CsPbBr3 and CsSrBr3 measured at room temperature.b) DFT-calculated IR-absorption spectra within the harmonic approximation for the orthorhombic phases.c) Raman spectra of orthorhombic CsPbBr3 and CsSrBr3 measured at 80 K. d) DFT-calculated Raman spectra of both compounds within the harmonic approximation for the orthorhombic phases.
FIG. 5 .
FIG. 5. Dynamic instabilities in the lattice dynamics.Harmonic phonon dispersion of cubic CsPbBr3 and CsSrBr3 showing the dynamic instabilities in the hightemperature, cubic phase of both compounds.The imaginary modes at the M and R points are the in-phase and out-of-phase tilting depicted on the right panels.The tilting modes are almost identical for CsSrBr3 and CsPbBr3.
FIG. 6 .
FIG. 6. Impact of cation electron configuration on octahedral dynamics at higher temperature.a) Schematic representation of the MBr6 octahedron aligned along the z Cartesian axis.The octahedral rotation angle around z, ϕz, is defined as the average of the angles formed by the x/y Cartesian axis and the vector connecting two in-plane Br atoms at opposing edges of the octahedron (ϕ (x) z in red and ϕ (y) z in blue).Note that a clockwise rotation is defined as positive and counter-clockwise as negative.b) Fourier transform of the octahedral rotation angle, Φα(ω), and c) cross-correlation between rotation angle and M-site displacement, C αβ (ω), calculated using DFT-MD trajectories of cubic CsPbBr3 (upper panels, 525 K) and CsSrBr3 (lower panels, 570 K).
TABLE I .
Dielectric properties of cubic CsMBr3.Dielectric constant in the high-frequency limit with respect to the optical phonon mode frequencies, ε∞, and Born effective charges, Z * i , of cubic CsPbBr3 and CsSrBr3 as calculated by DFT.We report Z * Br for the Br bonded with Pb/Sr along the z axis.
86(2) Cs 2 CO 3 , PbO, and concentrated aqueous HBr were purchased and used as received.Guided by the reported pseudo-binary phase diagram,86polycrystalline CsSrBr 3 for X-ray powder diffraction and Raman spectroscopy was prepared by a solid-state reaction at 600 • C. CsBr (5 mmol, 1064 mg) and SrBr 2 (5 mmol, 1237 mg) were ground and pressed into a 5 mm diameter pellet, placed in an alumina crucible, and flame-sealed under ∼1/3 atmosphere of argon in a fused silica ampoule.The reaction yields a porous, colorless pellet which is easily separated from the crucible and ground in inert atmosphere.Polycrystalline CsPbBr 3 for X-ray powder diffraction was prepared in ambient atmosphere by precipitation from aqueous hydrobromic acid.PbO (2 mmol, 446.4 mg) was dissolved in 2 mL hot concentrated HBr under stirring.Cs 2 CO 3 (1 mmol, 325.8 mg) was added slowly resulting in an immediate bright orange precipitate.13mL additional HBr was added and the mixture left to stir.After an hour, stirring was stopped and the mixture allowed to cool to room temperature.Exess solution was decanted, and the remaining mixture was evaporated to dryness on a hotplate and ground.Phase purity of all prepared compounds was established by powder XRD.Single crystals of CsSrBr 3 were grown by the Bridgman method from a stoichiometric mixture of the binary metal bromides in a 10 mm diameter quartz ampoule.CsSrBr 3 was pulled at 0.5 mm/h through an 800 • C hot zone, yielding a multi-crystalline rod from which several-mm single crystal regions could be cleaved.CsSrBr 3 is extremely hygroscopic and all preparation and handling was performed in an inert atmosphere.The vertical Bridgman method was used to grow large, high-quality single crystals of CsPbBr 3 . Afer synthesis and purification (see Supplementary Information for details), the ampoule was reset to the hot zone for the Bridgman Growth.The zone 1 temperature was set to 650 • C with a 150 • C/h ramp rate, and held for 12 h to ensure a full melt before sample motion occurred.The zone 2 and 3 temperatures were set to 375 • C.These temperatures were held for 350 h while the ampoule was moved through the furnace at a rate of 0.9 mm/h under 0.3 rpm rotation.After the motion had ceased, the zone 1 temperature ramped to 375 • C to make the temperature profile in the furnace uniform.The cooling program was set to slow during the phase transitions occurring near 120 and 90 • C, with a 10 • C/h cooling rate from 375 • C to 175 • C, a 2.5 • C/h slow cooling rate from 175 • C to 75 • C, and a 10 • C/h rate to 30 • C. The resulting CsPbBr 3 ingot was orange-red and had large (≥5 mm) transparent single-crystalline domains, though the edges of some portions exhibited twinning.
it is narrower in frequency than what we observe.Results from control experiments (see Supplementary Information) show that the main signals from quartz do not contribute to the measured Raman spectra of CsSrBr 3 . | 7,662.2 | 2023-10-05T00:00:00.000 | [
"Materials Science",
"Physics"
] |
Copula-Based Uncertainty Quantification (Copula-UQ) for Multi-Sensor Data in Structural Health Monitoring
The problem of uncertainty quantification (UQ) for multi-sensor data is one of the main concerns in structural health monitoring (SHM). One important task is multivariate joint probability density function (PDF) modelling. Copula-based statistical inference has attracted significant attention due to the fact that it decouples inferences on the univariate marginal PDF of each random variable and the statistical dependence structure (called copula) among the random variables. This paper proposes the Copula-UQ, composing multivariate joint PDF modelling, inference on model class selection and parameter identification, and probabilistic prediction using incomplete information, for multi-sensor data measured from a SHM system. Multivariate joint PDF is modeled based on the univariate marginal PDFs and the copula. Inference is made by combing the idea of the inference functions for margins and the maximum likelihood estimate. Prediction on the PDF of the target variable, using the complete (from normal sensors) or incomplete information (due to missing data caused by sensor fault issue) of the predictor variable, are made based on the multivariate joint PDF. One example using simulated data and one example using temperature data of a multi-sensor of a monitored bridge are presented to illustrate the capability of the Copula-UQ in joint PDF modelling and target variable prediction.
Introduction
The problem of uncertainty quantification (UQ) for multi-sensor data has been one of the main concerns in nondestructive testing and structural health monitoring (SHM) over the years [1][2][3][4][5][6][7][8][9]. One important task is multivariate joint probability density function (PDF) modelling. Due to irregularities of multi-sensor data, the joint PDF can be too complicated to be modelled by traditional approaches. For example, traditional multivariate PDFs (such as a multivariate normal distribution) cannot model the PDF with multiple peaks. The multivariate mixture PDFs (such as multivariate normal mixture model), utilized in SHM and damage detection [10][11][12][13], rely on the proper choice of the number and the type of the mixture distributions and an initial value of parameter vector in optimization [14]. The Nataf distribution, utilized in SHM and structural reliability [15,16], relies on the assumption that the transformed random variables, obtained from the marginal transformations of the original random variables, are multivariate normal distribution [17].
In recent years, copula-based statistical inference has attracted significant attention due to the fact that it decouples the inference on the univariate marginal PDF of each random variable and the statistics dependence structure (called copula) among the random variables. In the areas of the SHM and structural assessment, Zhang and Kim [18] investigated a way of detecting bridge damage for the long-term health monitoring by using the copula theory. Fan and Liu [19] predicted the dynamic reliability of a bridge system based on SHM data. Pan et al. [20] developed a copula-based approach to model the structural health of an operational metro tunnel in a dependent system. Liu et al. [21] considered the correlation between the fatigue equivalent stress and the stress cycle using the copula function in the fatigue reliability assessment. Srinivas et al. [22] proposed the multivariate simulation of dependent axle weights of different vehicle classes. Zhang et al. [23] investigated the specification of long-term design loads for offshore structures considering multiple environmental factors.
Although the copula-based statistical inference has been widely applied, there are two limitations in previous works related to the SHM and structural assessment. The first limitation is insufficient types of probabilistic model candidates for univariate marginal PDF modelling. From the parametrization point of view, there are parametric models and nonparametric models for PDF modelling. The former type, assuming that sample data come from a distribution that has a fixed set of parameters, is suitable for data with regular statistical pattern; the latter type, being not specified a priori but being instead adaptively determined from data, is suitable for data with an irregular statistical pattern. In the SHM, it is well known that the statistical regularities of data from multiple sensors can be significantly different from each other. Thus, due to the complexity of real SHM data, only considering one type of probabilistic model in PDF modelling bounds the solution space for UQ, leading to incapability of capturing a statistical pattern of data. However, this important issue was not realized in previous works, so parametric models and nonparametric models were not considered simultaneously. For example, References [18][19][20][21]23] solely adopted parametric models, while Reference [22] solely adopted nonparametric models for univariate marginal PDF modelling. Thus, this paper attempts to break through this limitation by including sufficient types of probabilistic models as candidates. The second limitation is negligence of probabilistic prediction using available information, especially in the case of using the incomplete information of the predictor variable due to missing data caused by a sensor fault issue. For the works of the research area of SHM using the copula [18][19][20][21][22][23], it had not been realized that the joint PDF can be utilized for probabilistic prediction on the target variable using the available information of the predictor variable. Even for the very recent work of another research area using the copula [24], probabilistic prediction on the target variable is limited to the case using the complete information of the predictor variable only. However, the case of incomplete information of the predictor variable, due to missing data caused by a sensor fault issue, is critical and common in the SHM. Thus, this paper attempts to break through this limitation by conducting computation of marginalization and conditioning based on the copula-based joint PDF, for prediction on the PDF of the target variable using the complete (from normal sensors) or incomplete information (due to missing data caused by sensor fault issue) of the predictor variable.
This paper proposes the copula-based UQ (Copula-UQ), composing multivariate joint PDF modelling, inference on model class selection and parameter identification, and probabilistic prediction using incomplete information, for multi-sensor data measured from a SHM system. The proposed Copula-UQ contains two stages. The first stage is the copula-based multivariate joint PDF modelling. It is based on the univariate marginal PDFs and the copula. The second stage is copula-based inference and prediction. Inference, including determination of optimal parameters and selection of optimal model classes, is made by combining the idea of the inference functions for margins (IFM) and the maximum likelihood estimate (MLE). Prediction on the PDF of the target variable, using the complete or incomplete information of the predictor variable, are made based on the copula-based multivariate joint PDF.
The structure of this paper is outlined as follows. Section 2 presents copula-based multivariate joint PDF modelling, including model class candidates for univariate marginal PDFs and copula. Section 3 presents copula-based inference and prediction, including inference on univariate marginal PDFs and copula, and prediction on the target variable. Section 4 presents illustrative examples. One example using simulated data and one example using temperature data of multi-sensor of a monitored bridge are presented to illustrate the capability of the proposed Copula-UQ in joint PDF modelling and target variable prediction.
Copula-Based Multivariate Joint PDF Modelling
Let p(x 1 , x 2 , · · · , x D ) denote the joint PDF of D random variables (X 1 , X 2 , . . . X D ), and X ∈ R D×N denote the measured data matrix with its component X d,i being the d-th dimension of the i-th data point, with d = 1, . . . , D and i = 1, . . . , N. The copula-based multivariate joint PDF is to model p(x 1 , x 2 , · · · , x D ) based on the univariate marginal PDFs p(x d ), d = 1, 2, . . . , D of each random variable and the statistics dependence structure (called copula) among the random variables, given the measured data matrix X.
Univariate Marginal PDFs
For the d-th univariate random variable X d , consider a set of N M model class candidates, namely, M Consider the joint CDF of (X 1 , X 2 , . . . X D ): Sklar's theorem states that there exists a D-dimensional copula, such that [27]: where ψ is the parameter vector of the copula. If P x d θ are continuous, the copula is unique; otherwise, it is uniquely determined on the Cartesian product of the ranges of the marginal CDFs. Sklar's theorem clearly indicates that the joint CDF of random variables can be characterized by a copula in terms of the marginal CDFs.
Thus, the joint PDF, p(x 1 , x 2 , · · · , x D ), can be derived from its joint CDF, P(x 1 , x 2 · · · , x D ), of Equation (10): where c u m 1 1 , u m 2 2 , · · · , u m D D ψ is the copula density function: and In this paper, the multivariate Gaussian copula and the associated copula density function are introduced as follows [28]: where Φ −1 (·) is the inverse CDF of the univariate standard normal distribution function, Φ ρ(ζ) (·) is the joint CDF of a D-dimensional normal distribution with mean vector zero and covariance matrix equal to the correlation coefficient matrix ρ(ζ) of ζ defined in Equation (15), the parameter vector ψ is the collection of the off-diagonal elements of the upper triangular part of ρ(ζ) and I is a D-dimensional identity matrix.
Inference on Univariate Marginal PDFs and Copula
This stage is to make inference on Θ = θ m 1 1 , . . . (model class candidates of the marginal PDFs) and ψ (parameters of the multivariate Gaussian-copula), based on the measured data matrix X ∈ R D×N and the probability matrix U ∈ R D×N , with its component U d,i = P X d,i Θ, M . Under the idea of the inference functions for margins (IFM) [29], Θ (along with M) and ψ can be determined separately.
For the univariate marginals, the optimal parameter values can be obtained by the MLE: where log{·} is the logarithmic function. For most of the parametric models, analytical forms for the optimal parameters can be derived (for example, see Reference [30]). For nonparametric models, the optimal value,θ m d d (bandwidth), can be obtained by considering the asymptotic mean integrated squared error solution [31]:θ where Q d (0.75) and Q d (0.25) are the 75% and 25% quantiles of X d .
The optimal marginal PDFs (M = M 1 , . . . ,M D ) are selected by comparing the optimal likelihood values of different m d : After selectingM, the optimal parameters associated withM are denoted asΘ = θ 1 , . . .θ D .
Based onM andΘ, the component of the optimal probability matrixÛ d,i = P X d,i Θ ,M can be obtained.
The optimal values of the parameters of the multivariate Gaussian-copulaψ can be determined by considering the optimization on Lc Û ψ : where c Û 1,i ,Û 2,i , · · · ,Û D,i ψ is obtained by substitutingÛ 1,i ,Û 2,i , · · · ,Û D,i into Equation (14). For the multivariate Gaussian copula, the optimal parameterψ is the collection of the off-diagonal elements of the upper triangular part of ρ(ζ), with each component being Pearson's correlation coefficient.
Prediction on the Target Variable Given Complete or Incomplete Information (Due to Missing Data Caused by a Sensor Fault Issue)
Let p x 1 , x 2 , · · · , x D ψ ,Θ,M denote the multivariate joint PDF obtained by substitutingψ,Θ,M into Equation (11). Let the target variable be the set containing the selected components of X 1 , X 2 , . . . X D for prediction, and the predictor variable be the complement of the target variable. As the joint PDF contains all the statistical information about the random variables (X 1 , X 2 , . . . X D ), prediction on the PDF of the target variable can be obtained using the complete or incomplete information of the predictor variable. Let x ta , x o and x uo denote the target variable, observed predictor variable and unobserved predictor variable, respectively. It is worth noting that the existence of unobserved predictor variable x uo is very common in the SHM as it represents missing data of the corresponding channels of fault sensors. However, the very recent work of copula-based prediction [24] was still incapable of tackling the existence of x uo in its prediction phase. Here, by conducting computation of marginalization and conditioning on the copula-based multivariate joint PDF, the prediction on the PDF of x ta based on the observation x o = x o only (that is, available information only) can be obtained by: where p x 1 , x 2 , · · · , x D ψ ,Θ,M is the copula-based multivariate joint PDF with substituting Accordingly, the predicted value (mean) and the associated uncertainty (standard deviation) of x ta can be obtained.
Illustrative Examples
One example of simulation data and one example of real SHM data are demonstrated. For the simulation data example, the design of it is to validate the following three critical issues: (1) the necessary introduction of both parametric and nonparametric models for breaking through the first limitation (i.e., insufficient types of probabilistic model candidates), (2) the capability of the multivariate joint PDF modelling of the proposed Copula-UQ (as the true joint PDF is known) and (3) the performance of the proposed Equation (23) for prediction on the target variable given complete or incomplete information (due to missing data caused by a sensor fault issue). For the real SHM data example, the performance of the proposed Copula-UQ for prediction on the target variable under complete (normal sensors) or incomplete (fault sensors) information is further validated by considering the following two cases: (1) the test dataset is identical to the training dataset, and (2) the test dataset is different from the training dataset.
Simulation Data
This example applies the proposed Copula-UQ for multivariate joint PDF modelling and prediction of five-dimensional random variables, X = [X 1 , . . . , X 5 ] T . First, five uncorrelated random variables, Z = [Z 1 , . . . , Z 5 ] T , with different marginal PDFs are constructed (see Table 1). Then, the random variables X = [X 1 , . . . , X 5 ] T are obtained by applying an affine transformation X = AZ with A given as: Thus, the analytical form of the joint PDF of X is: where p Z z = A −1 x is the joint PDF of Z with z = A −1 x. Figure 1 shows the scatter plot of the simulated data for X 1 to X 5 (N = 500). The correlation coefficient matrix for X is: High correlation (for example, between x 1 and x 4 ), medium correlation (for example, between x 2 and x 5 ) and low correlation (for example, between x 1 and x 3 ) can be found in this case. Table 2 shows the maximum log-likelihood value of different univariate marginal PDFs of X 1 to X 5 . Using Equation (20), the optimal univariate marginal PDF of each dimension can be determined, and they are indicated by "_" (underline) in Table 2. The optimal PDFs of X 1 to X 5 are Normal kernel, Triangle kernel, Lognormal distribution, Lognormal distribution and Triangle kernel, respectively. In order to compare the fitting capacities of different PDFs shown in Table 2, Figure 2 shows the univariate marginal PDFs of X 1 to X 5 . Each subplot shows the data histogram, the top ranking PDF (that is, the optimal marginal PDF in Table 2; line style as "dash-dot line"), an intermediate ranking PDF (that is, an intermediate ranking PDF in Table 2; line style as "dashed line") and a low ranking PDF (that is, a low ranking PDF in Table 2; line style as "dotted line"). From each subplot, it can be reconfirmed that the optimal marginal PDF of each dimension in Table 2 is the best model for uncertainty quantification of the corresponding component of X. It is worth noting that, from Table 2, even though X is a linear mapping of Z only composing very regular types of distributions described in Table 1, the optimal univariate marginal PDFs of X are not only from parametric but also from nonparametric models. This result shows that the introduction of both parametric and nonparametric models is necessary for breaking through the first limitation (i.e., insufficient types of probabilistic model candidates) described in Section 1 because it provides a large solution space for uncertainty quantification. Table 1. Probability density functions (PDFs) of Z 1 to Z 5 (Simulation data).
Random Variable
Distribution Type PDF The multivariate joint PDF of X is determined by Equation (11) with substituting the optimal marginal PDFsM along with the associated optimal parametersΘ and the optimal parameterψ of the multivariate Gaussian copula. Figure 3 shows the projections of the multivariate joint PDF of X 1 to X 5 . Each subplot represents the projection of the multivariate joint PDF between two specific components of X. The black contour is the true PDF of Equation (25) while the green contour is the joint PDF by the proposed Copula-UQ. It can be shown that, even though the shape of the true PDF is irregular, the proposed Copula-UQ is capable of describing the statistical dependency structure. Figure 4 shows the comparisons of observed values and predicted values of X 2 to X 5 . The 45-degree reference line represents that the observed values and predicted values are identical. Each subplot shows the predicted value of the target variable, determined based on Equation (23), using the incomplete information (yellow dots) and complete information (blue dots) of the predictor variable. For example, for the yellow dots of the subplot in the upper left (for x 2 ), the target variable, observed predictor variable and unobserved predictor variable are respectively. For the blue dots of the subplot in the upper left (for x uo is an empty set. By comparing the scatter plots of yellow and blue dots, one can observe the evolution of the predicated value changes with respect to the amount of information given by the predictor variable. It can be anticipated that the predicted values can be improved (that is, the dots distributing closer to the 45-degree reference line) when given more information from the predictor variable. This conclusion can be confirmed from the subplots in the upper left (for x 2 ), lower left (for x 4 ) and lower right (for x 5 ) of Figure 4. Note that there is insignificant improvement of the predicted values of the subplots located in the upper right (for x 3 ), this is because of low correlations between x 3 and other components, shown in Equation (26). This result shows that the proposed formulation of Equation (23), breaking through the second limitation (i.e., negligence of probabilistic prediction using available information) by conducting computation of marginalization and conditioning, is capable of making predictions even though the information of the predictor variable is incomplete.
Temperature Data of Multi-Sensor of a Monitored Bridge
Temperature is a critical loading factor for structures [32]. Variation of temperatures in structures significantly influences the material properties (for example, Young's modulus [32]), static characteristics (for example, deflection and deformation [32]), dynamic characteristics (for example, structural frequencies [33][34][35], damping ratios and mode shapes [36]) and boundary conditions [37]. Temperatures, including ambient air temperature and structural component temperature, of a multi-sensor of a structure are uncertain due to the fact that they are affected by not only the ambient factors, including air temperature variation, solar radiation intensity, humidity and wind speed, but also the complex processes of heat transfer [38]. Practically, UQ in temperatures are conducted based on temperature data measured from multiple sensors installed in different locations of a monitored structure [38][39][40][41][42]. As these works utilized traditional PDF modelling approaches, and modelling of temperature-related random variables was limited to two-dimensional. Here, due to the capacity of the multivariate joint PDF modelling of the proposed Copula-UQ, the dimension can be extended to D-dimensional, where D is the number of temperature sensors selected in the analysis.
This study utilized the proposed Copula-UQ to analyze temperature data of the multi-sensor of the Dowling Hall Footbridge [36]. The bridge, located on the Medford campus of Tufts University, has a two-span continuous steel frame (each spam is 22 m) and a reinforced concrete deck. Temperatures of different locations are monitored using the type T thermocouples manufactured by Omega Engineering (measurement ranging from -250 to +350 • C). Multi-sensor layout for temperature monitoring can be referred to in Figure 7 of Reference [43]. There are in total ten temperature sensors and they can be divided into two sensor clusters according to their locations: the west span cluster and the east span cluster. The west span cluster includes sensors for pier temperature (C 1 ), bridge deck temperature (C 2 ), steel temperature at the south side (S 1 ), steel temperature at the north side (S 3 ) and air temperature (A 1 ). The east span cluster includes sensors for pier temperature (C 4 ), bridge deck temperature (C 3 ), steel temperature at the south side (S 2 ), steel temperature at the north side (S 4 ) and air temperature (A 2 ).
The temperature data can be accessed from Reference [44]. Figure 5 shows time histories of ten temperature sensors beginning on January 5 2010 and ending on May 2 2010. In each subplot, two sensors monitor the same type of temperature, but these two sensors belong to the west span cluster and the east span cluster, respectively. For example, in the first subplot, both C 1 and C 4 monitored pier temperature, but C 1 and C 4 belong to the west span cluster and the east span cluster, respectively. It can be observed that there is insignificant difference in measurement between two sensors monitoring the same type of temperature even though they belong to two different clusters. It is worth noting that there is difference between the steel temperature at the south and north sides of the bridge. The reason is due to the fact that the effects of sunlight to the south and north side are different. During the daytime hours, the sensor on the south side (S 1 and S 2 ) was significantly warmer than the sensor on the north side (S 3 and S 4 ) [36]. Therefore, temperature data of five sensors from the west span cluster (C 1 , C 2 , S 1 , S 3 , A 1 ) are utilized for UQ. The corresponding correlation coefficient matrix is: Table 3 shows the maximum log-likelihood value of the univariate marginal PDFs of C 1 , C 2 , S 1 , S 3 and A 1 . It can be observed that the optimal PDFs of C 1 , C 2 , S 1 , S 3 and A 1 are distributed as the nonparametric model with the Normal kernel. Figure 6 shows the univariate marginal PDFs of C 1 , C 2 , S 1 , S 3 and A 1 . It is obvious that in each subplot, the top-ranking model fits the frequency histogram better than the intermediate-and low-ranking models, reconfirming the model class selection results in Table 3. Figure 7 shows the projections of the multivariate joint PDF of C 1 , C 2 , S 1 , S 3 and A 1 .
It can be shown that the contours by the Copula-UQ are capable of quantifying the uncertainty of the multivariate temperature data. Figure 4, shows the comparisons of observed values and predicted values of C 1 , C 2 , S 1 and S 3 (training dataset: full monitoring dataset, test dataset: full monitoring dataset). Again, for each subplot, it can be observed that the predicted values can be improved when given more information of the predictor variable. Note that the yellow dots correspond to incomplete information of the predictor variable due to a sensor fault. For example, for the yellow dots of the subplot in the upper left (for C 1 ), the target variable, observed predictor variable and unobserved predictor variable are x ta = C 1 , x o = A 1 , x uo = {C 2 , S 1 , S 3 }, respectively. That is, the yellow dots show the predicted value of the target variable C 1 using the information from the observed variable of normal sensor A 1 , but without using the information from the unobserved variable of fault sensors C 2 , S 1 , S 3 because of the fault status of these three sensors. For the blue dots of the subplot in the upper left (for C 1 ), x ta = C 1 , x o = {A 1 , C 2 , S 1 , S 3 }, x uo is an empty set. From the four subplots of Figure 8, although the sensor fault issue enlarges the fluctuation of the yellow dots, the proposed Copula-UQ gives satisfactory results as the available information of sensor A 1 is properly utilized for making predictions on the target variable. For further validating the prediction capacity of the proposed Copula-UQ under data missing by sensor fault issue, a new computation is conducted as follows: (1) the monitored dataset was divided into the training dataset (data covering first 90% of days out of total monitoring period) and the test dataset (complement of the training dataset), (2) the marginal PDF along with the copula model was inferred based on the training dataset and (3) the prediction capacity of the trained copula model was validated based on the test dataset with or without data missing by sensor fault issue. Figure 9, in the same fashion as Figure 8, shows comparisons of observed values and predicted values of C 1 , C 2 , S 1 and S 3 (training dataset: dataset of first 90% of total number of the monitoring days, test dataset: complement of training dataset). It can be observed that the fluctuations of both the blue dots (corresponding to complete information from normal sensors) and the yellow dots (corresponding to incomplete information due to data missing by sensor fault issue) are acceptable. Therefore, it can be concluded that even though the training dataset is different from the test dataset, the proposed Copula-UQ still gives satisfactory results in multivariate PDF modelling and target variable prediction. Figure 9. Comparisons of observed values and predicted values of C 1 , C 2 , S 1 , S 3 (training dataset: data covering first 90% days out of total monitoring period, test dataset: complement of training dataset). 2 Note that the yellow dots correspond to incomplete information of the predictor variable due to missing data caused by a sensor fault issue Figure 10 shows the predicted joint PDFs between S 1 and S 3 under incomplete information with different given values of A 1 only, and without observing information of fault sensors C 1 and C 2 . That is, the joint PDF p S 1 , S 3 A 1 = A 1 shows how the steel temperatures of the south and north sides evolve with changing the air temperature. As A 1 increases, the optimal values of p S 1 , S 3 A 1 = A 1 increased accordingly. It can be observed that the differences between the steel temperature (S 1 or S 3 ) and the air temperature ( A 1 ) become more significant as A 1 increases. The reason is as follows: higher A 1 associates with higher solar radiation intensity. Given that the specific heat capacity of steel is higher than that of air, the increase of temperature of steel is more significant than that of air. It can also be observed that the temperature of S 3 is lower than that of S 1 . This result coincides with the on-site situation of sunlight of the Dowling Hall Footbridge, in that the sunlight intensity to the north side (S 3 ) is lower than that to the south side (S 1 ) [36]. The predicted joint PDFs among the temperature of different locations of the structure are important pieces of information for uncertain thermal loading and can be utilized for thermal-induced structural response assessment.
Conclusions
This paper proposed the Copula-UQ for multivariate joint PDF modelling, inference on model class selection and parameter identification, and probabilistic prediction using incomplete information, and presented one example using simulated data and one example using temperature data of a multi-sensor of a monitored bridge. For inference on univariate marginal PDFs, the results show that, in general cases, the optimal univariate marginal PDFs of different dimensions are different, so the introduction of both parametric and nonparametric models is necessary because it provides a large solution space for uncertainty quantification. For prediction on the target variable using the complete (from normal sensors) or incomplete information (due to missing data caused by a sensor fault issue) of the predictor variable, the proposed Copula-UQ is capable of obtaining the PDF of the target variable. The proposed methodology can be extended to tackle different multivariate joint PDF modelling problems in SHM with emphasizing the prediction purpose under incomplete information with a sensor fault issue. This important piece of information of the PDF of the target variable can be utilized for uncertainty propagation in further analysis. | 6,934.2 | 2020-10-01T00:00:00.000 | [
"Computer Science"
] |
The Effect of α-Al(MnCr)Si Dispersoids on Activation Energy and Workability of Al-Mg-Si-Cu Alloys during Hot Deformation
.e hot deformation behaviors of homogenized direct-chill (DC) casting 6061 aluminum alloys andMn/Cr-containing aluminum alloys denoted as WQ1 were studied systematically by uniaxial compression tests at various deformation temperatures and strain rates. Hot deformation behavior of WQ1 alloy was remarkably changed compared to that of 6061 alloy with the presence of α-Al(MnCr)Si dispersoids. .e hyperbolic-sine constitutive equation was employed to determine the materials constants and activation energies of both studied alloys. .e evolution of the activation energies of two alloys was investigated on a revised Sellars’ constitutive equation. .e processing maps and activation energy maps of both alloys were also constructed to reveal deformation stable domains and optimize deformation parameters, respectively. Under the influence of α dispersoids, WQ1 alloy presented a higher activation energy, around 40 kJ/mol greater than 6061 alloy’s at the same deformation conditions. Dynamic recrystallization (DRX) is main dynamic softening mechanism in safe processing domain of 6061 alloy, while dynamic recovery (DRV) was main dynamic softening mechanism in WQ1 alloy due to pinning effect of α-Al(MnCr)Si dispersoids. α dispersoids can not only resist DRX but also increase power required for deformation of WQ1 alloy..emicrostructure analysis revealed that the flow instability was attributed to the void formation and intermetallic cracking during hot deformation of both alloys.
Introduction
Al-Mg-Si-Cu alloys (6xxx series alloys) have been widely applied in auto industry for their high specific strength, excellent formability, and corrosion resistance [1,2]. Adding of transition elements, such as Mn and/or Cr, will significantly enhance mechanical properties of 6xxx alloys at both ambient and elevated temperatures due to formation of α-Al(FeMnCr)Si dispersoids via homogenization heat treatments [3][4][5]. e α-Al(FeMnCr)Si dispersoids can also effectively pin migration of dislocation and substructures and therefore restrain recovery and recrystallization. In these hot processings, the workability of alloys directly relates to their deformation conditions (i.e., temperature and strain as well as strain rate) [6] and their chemical composition [7] and microstructure evolution. e processing maps based on dynamic material modeling (DMM) have been proved to be an effective approach to distinguish optimum processing domains with high power dissipation efficiency from instability domains associated with microstructural defects for hot deformed alloys [8,9]. Wang et al. [10] predicted the optimum processing parameters for 7050 Al alloy as 653-693 K and 0.001-0.18 s −1 for temperatures and strain rates, respectively. Kai et al. [11] proposed that the optimum processing window for 6X82 was 465-535°C and 0.09-1.2 s −1 . Owing to alloying elements addition and dispersion strengthening, the plastic characteristics of 6xxx alloys with α-Al(FeMnCr)Si dispersoids are quite different from those of traditional 6xxx alloys and the related study is rare. Given current status, it is necessary to clearly understand effect of α-Al(MnCr)Si dispersoids on hot deformation behaviors and workability of 6xxx alloys.
Arrhenius type constitutive equations established by Jonas et al. [12] are also widely used to characterize flow behaviors and interpret activation energy (Q) of alloys deformed over a wide range of deformation temperatures and stain rates. Q can be expressed as necessary free energy for dislocation to slip on slip planes and hence indicate deformation resistance of alloys [13]. Q was used to be treated as a constant under different hot deformation conditions, which is contrary to recent researches. e results [13] revealed that the activation energy value of AA7150 Al alloy during hot deformation was not constant but decreased with increasing of deformation temperature and strain rate. Wang et al. [10] proved that Q of 7050 Al alloy during hot deformation were greatly affected by activation of dynamic recovery mechanism. Qin et al. [14] demonstrated that the activation energy map of the composites containing Sc and Zr was divided into two regions associated with dynamic precipitation. Qian et al. [3] showed that activation energy increased with increasing Mn contents in 6082 Al alloy. However, the influences of α-Al(MnCr)Si dispersoids on activation energy evolution of corresponding alloys during hot deformation process remain rarely reported. e hot deformation behaviors of alloys are directly affected by the dynamic balance between work hardening and softening mechanisms [15][16][17]. erefore, the microstructural evolution and flow characteristics are the key to understand plastic behaviors of Al alloys during deformation process. It is commonly accepted that DRV and DRX are the main softening mechanisms for alloys deformed at high temperature. But how α-Al(MnCr)Si dispersoids affect microstructural evolution and softening mechanics of hot deformed 6xxx is still not well clarified.
In the present study, a new type of 6xxx alloy with addition of Mn and Cr (donated as WQ1) was designed aiming to form fine α-Al(MnCr)Si dispersoids. e hot deformation behaviors of 6061 and WQ1 Al alloys were compared as a function of deformation temperatures and strain rates. e materials constants and activation energies of the two studied alloys were derived by application of hyperbolic-sine constitutive equation. e activation energies of the two alloys as a function of deformation conditions were constructed and compared to illustrate the impacts of deformation parameters and α-Al(MnCr)Si dispersoids in detail. e processing maps that present processing safe domains and flow instability domains of both alloys were also established. Effects of α dispersoids on dynamic softening mechanisms and working windows of studied alloys were also analyzed. e workability of both alloys was discussed in combination with processing maps and activation energy maps. Microstructure evolution of both alloys was also observed to reveal the mechanism by which dispersoids affect softening mechanisms and verify workability of the alloys during hot deformation.
Experimental Procedure
e samples used in the present work were from ingots with 150 mm in diameter of 6061 and Mn/Cr-containing aluminum alloys denoted as WQ1 which were fabricated by DC casting. e ingots of 6061 and WQ1 were homogenized at 555°C for 6 h with a heating rate of 111°C/h and 530°C for 6 h with a heating rate of 133°C/h, respectively, followed by air cooling to ambient temperature. Chemical compositions of these two alloys were examined by SPECTROLAB optical emission spectroscopy and corresponding results are listed in Table 1. e cylindrical hot compression samples with 10 mm in diameter and 15 mm in height were extracted from at half radius to center position of homogenized ingots as shown in Figure 1. To characterize the distribution of α-Al(MnCr)Si dispersoids in studied alloys on as-homo condition, the samples were etched in 0.5 wt.% HF solution for 15 s at ambient temperature. To determine average grain size of two alloys, the homogenized samples were anodecoated at 18 V in a solution of 38 wt.% H 2 SO 4 + 43 wt.% HNO 3 + 19 wt.% deionized water for 1.5 min.
Isothermal compression deformation tests were performed on a Gleeble-3500 thermomechanical simulator with deformation temperature ranging from 300 to 500°C and strain rate range of 0.01-10 s −1 to strain of 1.2. To assure a uniform deformation process, graphite foils were placed at both sides of the sample and the anvil. ermocouples were welded on cylindrical surface of each sample to record and control deformation temperature. e samples are heated to the targeted temperature with a heating rate of 5°C/s and soaked for 2 min to ensure thermal uniformity.
All deformed samples were immediately quenched into water at room temperature after hot deformation to preserve compressed microstructures. e specimens for microstructural observation were selected from the central part of the deformed samples along compression direction and metallographically prepared. Prior to electron-back scattering diffraction (EBSD) analysis, the prepared samples were electropolished in a solution (10 wt.% perchloric acid and 90 wt.% ethanol) at the voltage of 20 V for 40 s to produce strain-free surface. All EBSD data was processed by commercial software HKL Channel 5. In EBSD inverse pole figures (IPF), high-angle boundaries (HABs) expressed as black lines were defined as a misorientation larger than 15°, while low-angle boundaries (LABs) shown as white lines are set as a misorientation between 1°and 15°. Boundaries with misorientation less than 1°were taken as noises. Microstructure evolution was studied by JEOL JEM-2100F field emission transmission electron microscope (TEM) operated at 200 kV. e TEM samples were prepared by twin-jet electropolishing method at −20°C in a solution containing 75 vol.% of methanol and 25 vol.% HNO 3 . Convergent beam electron diffraction (CBED) patterns were used to measure the thickness of the observed TEM foils. e volume fraction of dispersoids of 6061 and WQ1 alloys were determined, using equation proposed by Li and Arnberg [18]. Figure 2 shows the optical microscope images of 6061 and WQ1 alloys on homogenization condition after anodecoating. e microstructures of both alloys are composed of equiaxed grains with average of 95.75 ± 6.34 μm and 216.76 ± 13 μm for 6061 and WQ1, respectively. According to previous study [19], grain size variation plays an insignificant role in affecting flow stress during high temperature deformation. However, grain size in the range among commercial alloys has limit effect on flow stress.
Microstructure after Homogenization Annealing.
It can be seen from dark field optical microscope images in Figure 3 that few and unevenly size of dispersoids precipitate in 6061 (Figure 3(a)) due to lack of Mn and Cr elements. Meanwhile fine and dense dispersoids generated in WQ1 (Figure 3(b)) during homogenization heat treatment.
e distribution of dispersoids in 6061 and WQ1 alloys is inhomogeneous, especially in former, and large area of dispersoid free zone (DFZ) is observed. e nonuniform distribution of dispersoids is caused by initial segregation of Mn/Cr at interdendritic regions during solidification [2] and low diffusion coefficients of Mn/Cr elements.
TEM images of as-homo 6061 and WQ1 are shown in Figure 4. It is obvious that the number density of dispersoids in WQ1 is significantly higher than that of 6061. Based on quantitative analysis of TEM image of dispersoids in both alloys, the average equivalent diameters are determined as 124 ± 6 nm and 129 ± 23 nm for 6061 and WQ1, respectively. According to the method proposed by Li and Arnberg [18], the volume fraction of dispersoids in 6061 and WQ1 was calculated as 0.1% and 1.1%, respectively. e chemical composition of the dispersoids was also examined by energy disperse spectroscopy (EDS) as shown in Figure 4(c). Based on the morphology [5] and composition, the dispersoids were identified as α-Al(MnCr)Si dispersoids [20].
Flow Stress Behavior.
e true strain-true stress curves of the isothermal compression deformation of studied alloys are drawn in Figure 5. It is obvious that both deformation temperature and strain rate are of great importance to the flow behaviors of the alloys. Flow stresses of both alloys increase with decreasing deformation temperatures as well as increasing strain rates. Overall, the true stress ascends rapidly at initial stage of deformation and subsequently reaches a plateau or slightly increases throughout compression process, indicating a dynamic equilibrium between work hardening and dynamic softening. All results show the flow stresses of WQ1 ( Figure 5(b)) are obviously higher than those of 6061 ( Figure 5(a)) under the same deformation conditions.
At initial stage, compression deformation triggers generation of massive microscopic defects (vacancies and dislocations). e complex interaction within these overwhelming microdefects causes dislocation multiplication and tangling as well as vacancy-dislocation kinking and jogging throughout the material, leading to conspicuous work hardening effect. With increasing of strain, two mutually counteracting phenomena impact the microstructure simultaneously. On one side, newly formed movable defects trapped into the preexisting dislocations and vacancies causing further strengthen work hardening. On the other side, a critical dislocation density value was reached; the dislocation cross-slip was activated along favorable slip system, resulting in dislocation annihilation and recombination as well as reduction in dislocation density. erefore, the dynamic balance between work hardening and dynamic softening eventually developed into a steady state of flow stress during further compression. As the steady state of flow stress always presents at the strain where it reaches its peak stress, hence, peak stress is applied for the following constitutive analysis. Figure 6 illustrates the peak flow stresses evolution of 6061 and WQ1 as function of deformation temperatures and strain rates. ere is a strong connection between peak flow stresses and deformation conditions (deformation temperature and strain rates). e peak flow stresses are set as the maximum stress value of each flow curve, which increase associated with increasing strain rates and decreasing deformation temperatures. Under the same deformation condition, the peak stresses of 6061 ( Figure 6(a)) are lower than those of WQ1 ( Figure 6(b)), which means α-Al(MnCr) Si dispersoids considerably increase deformation resistance of WQ1. e mobility of dislocations and grain boundaries is thermally activated. Restrained by deformation temperature, lower temperature will limit DRV and DRX, therefore causing a higher flow stress. Lower strain rates can provide sufficient time for activation energy of dynamic softening mechanism leading to lower flow stress.
Constitutive Analysis.
Constitutive equations are often applied to reveal the intrinsic relationships between flow stress of alloys and deformation conditions (deformation temperatures and strain rates) and predict flow stress behaviors of alloys during hot deformation. Among numerous equations, Arrhenius constitutive equation proposed by Sellars and Tegart is mostly utilized set [21]:
Based on previous study, a power relationship equation (2) is applied to low flow stress situation. On the contrary, an exponential relationship equation (3) is applied to high flow stress situation. e hyperbolic sine law equation (4) is suitable for wide range of flow stress situation. Applying natural logarithms to both sides of equations (2)-(4), the equations for constants of the materials can be obtained: Subsequently, the values of n 1 and β can be determined by the slope of the plots for ln _ ε − ln σ and ln _ ε − σ, respectively. According to α � β/n 1 , the value of α can be obtained by substituting the average values of n 1 and β.
After undergoing partial differentiation on equation (7), Q for hot deformation of the studied alloys can be calculated as By substituting experimental data of 6061 and WQ1 into equation (8), the corresponding material constants (A, β, α, and n) and Q can be obtained and calculated values are presented in Table 2. e average Q value of 6061 alloy is 148.73 kJ/mol; meanwhile Q value of WQ1 reaches 189.12 kJ/mol. Apparently, Q of WQ1 is higher than that of 6061, which is caused by synthetic effect of higher solute level of Mn and α-Al(MnCr)Si dispersoids in WQ1. Solute atoms can work as obstacles to restrict dislocation motions during hot deformation, causing ascending activation energy of alloys [19,22]. α-Al(MnCr)Si dispersoids are able to effectively pin dislocation migration as well as subgrain boundaries migration. erefore, extra energy was required for dislocations or subgrain boundaries for unpinning from α-Al(MnCr)Si dispersoids, therefore resulting in a greater Q for WQ1 and higher hot deformation resistance.
Recent works [10,14,23] demonstrate that activation energy for hot deformation of a given material varies with deformation parameters rather than remaining a constant. Shi et al. [13] proposed a revised Sellars' constitutive equation (equation (9)) to present the relation between activation energy and deformation parameters (T and _ ε) (equation (12)): M (T) represents the slope of ln(_ ε) versus ln[sinh(ασ p )] plotted at different deformation temperatures and N _ ε is the slope of ln[sinh(ασ p )] versus 1/T plotted at different strain rates. e value of Q at various deformation conditions can be obtained according to M and N; hence, the corresponding Q maps for 6061 and WQ1 can be illustrated (Figure 7).
For 6061 alloys (Figure 7(a)), Q is 170.82 kJ/mol at 300°C with strain rate of 0.01/s, while it degrades to 132.33 kJ/mol at 550°C with strain rate of 10/s. For WQ1 alloys (Figure 7(b)), Q is about 208.12 kJ/mol at 300°C with strain rate of 0.01/s, while it decreases to 152.03 kJ/mol at 550°C with strain rate of 0.01/s. Q of WQ1 is significantly increased compared to that of 6061 under the same deformation conditions. It is reported that Q is directly connected with density and movement of dislocations [10]. e presence of α-Al(MnCr)Si dispersoids in WQ1 alloy effectively retards movement of dislocations and (sub)grain boundaries, resulting in higher Q value than 6061's.
As shown in Figure 7, it is obvious that Q is not constant but is influenced by thermomechanical conditions, that is, deformation temperatures as well as strain rates. Q of 6061 and WQ1 alloy decreases with increasing deformation temperatures and increasing strain rates. On one hand, dynamic restoration process is expedited when the alloy is deformed at higher strain rates [24], leading to promoted dislocation movement. On the other hand, increasing strain rates leads to increasing resolved shear stress along the dislocation slipping direction [25], resulting in advanced initiation of dislocation movement. With increasing deformation temperature, DRV and DRX are greatly boosted, including formation, growth, and polygonization of welldefined subgrains as well as formation of recrystallized grains, respectively. erefore, the activation energy decreases with increasing deformation temperature. e activation energy can reflect workability of alloys under various deformation conditions. Higher Q domains in activation map are often related to inferior workability [26], while lower Q domains indicate less processing difficulty.
ere is a correlation between Q and hot deformation mechanism as well as microstructural evolution, which will be discussed in the following section.
Processing Maps.
Based on the dynamic material model, the processing map is established by superposition of a flow instability map over a power dissipation efficiency map. e efficiency of power dissipation (η) is employed to assess the power dissipation capacity of the material, which is represented as [27,28] where m is strain rate sensitivity. Basically, higher efficiency of power dissipation indicates that more power is consumed by microstructural evolution, meaning better hot workability. e flow instability of the material, including microcracks, flow localization, and adiabatic shear bands, can be expressed by a parameter (ξ) [8,29,30]: e instability map is composed of two parts according to the value of ξ. One is the processing zone, which is considered as safe domain when ξ ＞ 0, while the remaining part (ξ ＜ 0) is taken as flow instability domain. Figure 8 shows the processing maps at the true strain of 1.2 for 6061 and WQ1 alloys as a function of deformation temperatures and strain rates. As shown in Figure 8, the contour numbers represent the value of power dissipation efficiency and the shadow area stands for instability regions. A safe processing domain is always with a high-power dissipation efficiency and absence from instability region. e selected safe domains are marked in red boxes in Figure 8 and the corresponding processing window values of deformation temperatures and strain rates are listed in Table 3.
As shown in Figure 8(a) and Table 3, there are three safe domains for 6061 alloys; domain I locates at temperatures ranging from 485 to 550°C with strain rates of 0.01-0.08 s −1 where power dissipation efficiency is 0.34-0.40 and domain II locates at temperatures of 440-480°C and strain rates of 0.05-0.6 s −1 with power dissipation efficiency of 0.34, while optimal domain III covers the region with higher temperatures and higher strain rates (530-550°C, 6-10 s −1 ). For WQ1 alloys (Figure 8(b)), there is mainly one safe domain, which locates at temperature ranging from 485 to 550°C with strain rates of 0.01-0.1 s −1 whose power dissipation efficiency is 0.26-0.29. Comparing processing maps of 6061 and WQ1 alloys, the safe domain of both alloys locates at high deformation temperatures with low strain rates but 6061 alloy is accompanied with higher power dissipation efficiency. It has been reported [31,32] that the deformation mechanism is DRV if power dissipation efficiency value during hot deformation is less than 0.3; otherwise, higher value is associated with DRX, which indicates that the dynamic softening mechanism of WQ1 is inhibited by α-Al(MnCr)Si dispersoids. is point will be verified in the examination of microstructure evolution part. Overall, safe processing domain and low activation energy should be key determinants for the optimum workability and elimination of deformation defects. . Figures 9(a) and 9(b) show the microstructures of deformed 6061 and WQ1 alloys at safe domains with low Q (550°C and 10 s −1 ). e microstructures of both alloys mainly consisted of elongated grains and a certain area fraction of recrystallized grains, indicating a typical DRV process. Moreover, different degrees of recrystallization occur for 6061 and WQ1 alloys. It can be seen from Figure 9(a) that recrystallization happens extensively along deformed grain boundaries (marked by black box) and the area fraction of recrystallized grains is as much as 50.12% for 6061 alloy. Figure 9(b) shows that partial recrystallization mainly initiates around triple junction grain boundaries (noted by black box) and the area fraction of recrystallized grains is only 9.78% for WQ1 alloy. Particlestimulated nucleation (PSN) of recrystallization has been identified as an active nucleation mechanism of DRX for hot deformed alloys, which is strongly dependent on the size of second phase particles. Normally, particles can induce PSN effect and enhance the DRX when they are larger than 1 μm, while they can, on the other hand, suppress the DRX for the strong pining effect when particles are smaller than 1 μm [33,34]. Hence, recrystallization in WQ1 alloy is severely restrained by the presence of large amount of nanoscale (∼120 nm) α-Al(MnCr)Si dispersoids. Misorientation distributions based on Figures 9(a) and 9(b) are presented in Figures 9(c) and 9(d), respectively. It is obvious that WQ1 alloys hold more percentage of LABs and lower average misorientation angle (θ ave ) compared to 6061 alloys, which is consistent with results of Figures 9(a) and 9(b). e substructure of 6061 (Figure 9(e)) is composed of abundant equiaxed subgrains with LABs and recrystallized grains with size of 10 μm. It can be concluded that the main mechanism for DRX is continuous dynamic recrystallization [35]. e recrystallized grains formed by transformation of LABs to HABs (pointed out by black box). For WQ1 alloys (Figure 9(f )), the microstructure is composed of subgrains and recrystallized grains with size around 5 μm. It should be noticed that some subgrains in WQ1 alloys are elongated rather than equiaxed (marked by black arrows), indicating that subgrain rotation is strongly suppressed. Owing to pinning effect of α-Al(MnCr)Si dispersoids, subgrain rotation and (sub)grain boundaries migration are inhibited. Hence, DRV was main dynamic softening mechanism for WQ1 alloy at its safe processing domain. Figure 10(a) demonstrated the interaction of α-Al(MnCr)Si dispersoids with dislocation and dislocation walls when WQ1 was deformed at 450°C and 0.1 s −1 . It can be seen that dislocation walls movement is retarded and dislocations bow when encountered with dispersoids, showing a strong pinning effect of α-Al(MnCr)Si dispersoids on dislocation migration. Moreover, dispersoids also inhibit grain boundaries (Figure 10(b)), even though WQ1 was compressed at 550°C. Hence, DRV in WQ1 is significantly restrained due to pinning effects of α-Al(MnCr)Si dispersoids on dislocation motions and grain rotations [19,24].
Interpretation of Instable Domains.
e flow instability is often related to generation of microstructural defects, including flow localization, adiabatic shear bands, micro/macro cracks, and intermetallic/particle cracking and debonding. Micro/macro damages are closely related to shear bands and flow localization. Based on research of Ramanathan et al. [36], flow localization refers to discontinuous and inhomogeneous deformation around adjacent areas resulting from composition differences, interphase boundaries, and loading conditions [37]. e optical micrographs of 6061 deformed at 300°C with 0.1 s −1 to a strain of 1.2 were shown in Figure 11. Micro cracks and voids (marked by arrows) are observed around intermetallic particles indicating the formation of micro defects related to intermetallic particles.
In flow instable domain of 6061 alloys, cracking of primary Mg 2 Si phases (pointed in Figure 12(a)) along compression direction and interfacial debonding between Mg 2 Si and Al matrix was observed. ose sites are preferential places for micro crack formation and propagation. Flow localization happens around brittle Fe-bearing particles ( Figure 12(b)) and cracked Fe bearing intermetallic causes matrix cracks initiation and propagate perpendicular to compression direction. As the compression proceeds, both primary Mg 2 Si and Fe-containing particles are prone to cracking and debonding rather than deforming in WQ1 alloys ( Figure 13). us inhomogeneous deformation leads to severe stress concentration and enables cracking at the interface between the second phase particles and Al matrix under the action of external loading. Visible voids and cracks formed due to flow localization (Figures 13(a) and 13(b)) and then the pores grew and finally formed a fracture. Multiple voids and micro cracks tend to expand by linking adjacent voids.
Conclusions
(1) A great amount of α dispersoids formed in WQ1 alloy, which is with addition of Mn and Cr, while limited α dispersoids were observed in 6061 alloy. Flow stresses of both alloys increased with decreasing temperatures and increasing strain rates. Furthermore, flow stresses of WQ1 alloy were higher than those of 6061 alloy under all deformation conditions owing to dispersion strengthening caused by α-Al(MnCr)Si dispersoids. (2) e materials constants in constitutive equation and activation energies of WQ1 and 6061 alloys during hot deformation were calculated by applying constitutive analysis. Due to presence of α-Al(MnCr)Si dispersoids in WQ1, activation energy of it for hot deformation was 40.4 kJ/mol higher than that of 6061. (3) e activation energy maps and processing maps of the two alloys during hot deformation were constructed. e activation energy of both alloys is variant and is greatly influenced by deformation temperatures and strain rates. Optimized hot deformation parameters for WQ1 and 6061 were determined with high dissipation efficiency and low activation energy within safe processing domains. (4) e microstructure analysis revealed that main dynamic softening mechanism for 6061 under optimized hot deformation parameters was DRV and extensive DRX, while DRV was predominant softening mechanism for WQ1 due to strong pinning effect of α-Al(MnCr)Si dispersoids on subgrain rotation and subgrain boundaries migration. (5) For both alloys, flow instability was associated with cracking and debonding of intermetallic particles as well as void formation during hot deformation.
Data Availability
All experimental data are available.
Disclosure
Part of the manuscript was presented in Sub-Session: Materials Forming and Modeling, but the manuscript was not submitted in the session. Furthermore, the content of the manuscript was revised.
Conflicts of Interest
e authors declare no conflicts of interest. | 6,094.2 | 2020-05-20T00:00:00.000 | [
"Materials Science"
] |
Proposal of Automatic Methods for the Reuse of Software Components in a Library
The increasing complexity of applications is constraining developers to use reusable components in component markets and mainly free software components. However, the selected components may partially satisfy the requirements of users. In this article, we propose an approach of optimization the selection of software components based on their quality. It consists of: (1) Selecting components that satisfy the customer's non-functional needs; (2) Calculate the quality score of each of these candidate components to select; (3) Select the best component meeting the customer's non-functional needs with linear programming by constraints. Our aim is to maximize this selection for considering financial cost of component and adaptation effort. Yet in the literature review, researchers are unanimous that software components reuse reduces the cost of development, maintenance time and also increases the quality of the software. However, the models already developed to evaluate the quality of the component do not simultaneously take into account financial cost and adaptation effort factors. So, in our research, we established a connection between the financial cost and the adaptation time of the selected component by a linear programming model with constraints. For our work's validation, we propose an algorithm to support the developed theory. User will then be able to choose the relevant software component for his system from the available components. Keywords—Method development; reuse; software component; quality of component; functional size; functional processes; financial cost; adaptation effort
I. INTRODUCTION
The increasing size of applications and the accretion of their complexity pose enormous challenges for developers.To solve these problems, they must have to recourse to reusable components in their applications.However, selected components may not totally meet the requirements of users.Moreover, there may be functionality defects of these software components or quality services partially rendered by the ones.then, their selection and reuse require the development of appropriate models and methods.In addition, several works relating to the selection of reusable software components have been conducted.And researchers are unanimous on the fact that the reuse of these software components reduces the financial cost, the development time and the effort of adaptation [5], [6], [7].In [7], the researchers proposed a software component selection model based on integer linear programming.This method makes it possible to measure and evaluate the quality of the software system according to various quality attributes defined in ISO 9126 / IEC and the cost of the components.In [13], the authors worked on the selection of software components based on the attributes or quality criteria most important to practitioners.This survey allowed practitioners to select the most important attributes from a list of factors.The method showed that cost was the most important factor when selecting these components.In [24], based on an exploratory study, researchers have shown that in addition to the cost considered as the most important factor in the selection, other factors such as longevity, compatibility and in charge of the component exist.Their goal is to study the most important factors in a list when selecting components for practitioners.Then to hierarchize them.This study helps companies improve their component selection process.They concluded that small businesses focus on properties associated with ease of use, component development and maintenance, while larger firms and more mature products are more interested in cost-related properties.However, we find that the dependence between financial cost and maintenance time that are the main factors for the selection process, is not considering in the different models of evaluation for denoting the quality of software components.In this research, we will propose automatic methods for: Facilitating and accelerating the selection process; Evaluate the quality of selected software components according to the criteria and quality indicators desired by the user; Selecting the best component satisfying the client's non-functional needs; Improving the quality of these softwares to adapt them to the targeted problem.
This work is organized as follows.The first part deals with Section 1.It concerns the state of the art relating to the selection of reusable components, the limits of previous work and research hypotheses.The second part concerns Section 2. It is about different models that we have developed.The third part concerns the validation of the results in Section 3. The last part concerns the conclusion and the perspectives.
II. STATE OF THE ART
Several research works relating to the selection of reusable software components have been made.In [1] and [2], the authors have shown that traditional approaches for developing software from scratch are not optimal for building complex software systems.They argue that the use of reusable software components is more efficient and better suited for building complex applications.In [3], the authors proposed the socalled "Storyboard" approach.This method improves and www.ijacsa.thesai.orgfacilitates the choice of customer for appropriate commercial products as their requirements are better understood.His interest is to help the user better understand his requirements.Other selection studies based on surveys and experiments have been conducted.Thus, in [4] an empirical study led on the selection of commercial components.Thus, researchers in [4] led an empirical study on the selection of commercial components.They conducted structured interviews on 16 software projects.This method allowed to customize the development process based of COTS software components.The goal is to know if it is more interesting to build the software components or buy the Cost components for the Norwegian industries.In [8], the research has proposed a method for selecting standard and commercial components.It raises the problem of inadequacy between the software system to be built and the components selected during and after selection.They proposed a decision-support approach aimed at remedying the imbalances noted on the components by estimating the anticipated aptitudes and by suggesting alternative plans for the resolution of the observed disparities.The authors in [9] offer a comparative study of available software before any selection.The goal is to evaluate and select open source software for the management of electronic and digital medical records.This study is carried out with different decision-making techniques multi-criteria.These software systems are selected on the basis of a set of metric results using the AHP technique integrated with different multicriteria decision-making techniques.
In [21], the authors use a software selection approach based on the characteristics of the ISO-9126 standard.The AHP method is used to weight these characteristics of components.Then, the researchers choose the appropriate software component according to the weight evaluation.
In [10], a mechanism allowing the automation of the selection of a software component among a set of candidates according to their functional and non-functional properties was studied.This mechanism permits to facilitate the extraction and the comparison of components.This is after the selection of components, to measure their satisfaction index to find the most relevant.To optimize the quality of selected components, several models and selection methods have been developed and are available.Among these models, some are focused on optimization algorithms.Thus in [11], the researchers proposed a software component selection approach based on the genetic algorithm for optimizing the performance of the software system.Their goal is to maximize the functional performance of the system.This permits to maximize cohesion and to minimize the coupling of software modules for the optimal selection of software components.In [23], the research focused on optimizing the system to build.Researchers have conducted work on selecting optimized software components when user requirements are unclear.it is a question of optimizing the selection in the generic applications unknown to the developers.The authors in [5] have proposed a model for the selection of components with constraint optimization.The goal is to model the component selection problem as a constraint satisfaction optimization problem.In addition to the quality criteria determining the choice of attributes of quality of the component, other important factors are identified in the literature.These factors can also affluence the quality of the components when selecting.Therefore, authors sustain that the use of reusable software components reduces the time, cost of development and cost of maintenance [5], [6], [7], [20], [22], [25].
In [25], the authors propose in this work, how to select the best component in a repository meeting all functional requirements and user requirements.The best components are recovered in two levels.The first step gives all the components that correspond to the functional requirements, and the second step recommends the components the weighting is the highest to software developer.
In [12], the work focused on the problem of optimizing non-functional attributes when selecting software components.The method consists in choosing software components that provide all the necessary functionalities while optimizing certain non-functional attributes such as the financial cost.In [7], the researchers proposed a software component selection model based on integer linear programming.This so-called flexibility method makes it possible to measure and then evaluate the quality of the software system according to different attributes of quality and the cost of the components.In [13], the authors conducted work on the selection of software components based on the attributes or quality criteria most important to practitioners.This survey allowed practitioners to select the most important attributes from a list of factors.The method showed that cost was the most important factor when selecting these components.
In [14], authors argue that "the quality and cost of a software strongly depend on the quality and cost of the components assembled to produce the product".They proposed a W-shaped model for component selection.This model is a decision support tool for software developers.It permits to obtain data on the stages of component selection and the development process.The article [15] gives different mathematical models of optimization in linear programming.One of these models is a compromise between the minimum monetary cost and the response time in cloud computing.It is formulated below:
A. Hypotheses
The work that we present treats with the problematic of the evaluation of the quality of the pre-made components.It concerns the maximization of their calculated quality values while optimizing the financial cost and the adaptation time.Our goal is therefore to determine a score based on linear programming with constraints that will maximize the quality of the selected software component.Then we will balance the financial cost and the adaptation time of this component.Finally, we establish a model based on a score to evaluate the quality of the selected software component on the one hand, www.ijacsa.thesai.organd moreover, to predict the adaptation effort of this component.
This leads us to formulate the following hypothesis: H1: The simultaneous consideration of the financial cost and the adaptation effort makes it possible to better evaluate the quality of the software component, H2: The selection of reusable and user-friendly software components makes it possible to build quality software.
B. Limit of Methods
Several works relating to the selection of reusable software components have been conducted.Researchers are unanimous that the reuse of these software components can reduce the financial cost, the development time and the effort of adaptation [5], [6], [7], [23].However, we find that the dependence between the financial cost and maintenance time that are key factors for the selection process, is not taking into account in the different models of quality evaluation of software components.Indeed, the selected components can meet the expectations of the users partially.Faced with failures and user requirements, improvements can be made to correct weaknesses and increase the quality of these components.Indeed, the selected components can partially meet the expectations of users.Faced with failures of certain functionalities and user requirements, improvements can be made to correct weaknesses and increase the quality of these components.This can generate a maintenance effort and a financial cost that can be estimated and predicted.Finally, we can give a model for optimizing parameters.
C. Tool to Predict the Adaptation Time of the Component
To estimate maintenance time and adaptation effort, we will use methods and tools to measure the size of the software component.We used the Cosmic v4.0.1 method and its methods in our work.Below you will find some tools for estimating the development time and their normalization histories in Table 1.
From 1970s, the COCOMO method (Constructive Cost Model) has made it possible to determine the code lines of the programs and to measure the development effort.At present, methods and tools exist to estimate the size of a software and predict the development effort.In [16], the authors gave a summary of these tools with the different standards (see Table 1).The COSMIC method is used to calculate the measurement of the functional size of a software.According to [17], [18] and [19], functional size measurement is a means of determining the size of software, regardless of the technology used to implement it.This size is in units of Cosmic Function Points, noted as PFC.This method also gives the estimate of the adaptation effort.In [16], researchers present measurement aggregation rules.These rules make it possible to calculate. The functional size of each process i The size of a software by aggregating the sizes of its functional processes under certain conditions, Development effort or adaptation effort
A. Defining the Software Component Quality Model
We are interested in evaluating the selection and integration of software components in a software system.Our main objective is to select the "best software component" according to the defined characteristics.But given the multiplicity of quality indicators and quality sub-indicators according to ISO / IEC 9126, we studied the following characteristics in our work.These characteristics include: functional capability, reliability, ease of use, security and maintainability.This allows us to define the following model1 : This model is based on the ISO 9126 quality model and quality representations of literature reviews.It allows to specify the most important characteristics according to the needs of the user.Using the Analytic Hierarchy Process (AHP) method, we define the objective of our project and then construct the hierarchical quality model according to the characteristics and sub-characteristics of the software components (see Fig. 1).
Finally, using the multi-criteria analysis method, we constructed a binary comparison table of characteristics and sub-characteristics.This makes it possible to determine the weights of the various defined quality criteria of the software component.Also, this method makes it possible to evaluate the coherence of our work.
B. The Proposed or Software Component Selection Process
We gave a description of the selection process of the selected components and then we evaluated them.This process is modeled in UML by activity diagram as follows according to Fig. 2: Step 1: The user expresses its functional requirements and quality requirements of the component.
Step 2: A first search consists in considering the functional properties expressing the needs of the user.These needs must be related to the type of software to build.We obtain a set of software components selected functional properties meeting the requirements expressed by the customer.In other words, it is the different services rendered by the software components.
Step 3: This step consists to make selection based on nonfunctional properties.This is to consider the quality of the software component that is, how the features render the services.This step consists in evaluating the quality of characteristics of the component from defined metrics.This metric will be associated with an ordinal variable of modalities belonging to the set of values: Modalities defined in (3) will be associated to following numerical values respectively: 1; 2; 3; 4 and 5.
Step 4: At this step, we observe that the selected components do not fully meet the quality and service requirements.For each component selected i, some features make the services perfectly, others do it partially.if we consider that each component contains p functionalities.Assuming that the user is satisfied with k functionalities (k <p), then we must maintain (p-k) functionalities of the component.To predict the adaptation effort of (p-k) functionalities, we used the Cosmic method.It first determines the size of the functional processes of the component.Then we calculate the functional size of the component with defective functionalities.In [16], the authors defined the size of the functional process i as follows according to (2).So, for any component i of the set of selected components SC having P functional processes, we deduce: Then we apply the estimate of the adaptation effort developed according to [19] (5) This phase makes it possible to determine the adaptation time interval of the component to be predicted.This method then evaluates a financial cost and an adaptation time.Finally, with the predicted time, we apply the score that assesses the quality of the component using our objective function.
Step5: In case the cost and time parameters are optimized, then the selected component is retained.
Step 6: If the parameters are not, then the search continues and the process resumes.
C. Our Proposal Model to Maximize the Quality of Software Component
Our model is based on constrained linear programming.It considers the time and the financial cost parameters.Our goal is to define a metric with two parameters: the financial cost and the time.This score serves to optimize the parameters on the one hand and on the other hand to balance the financial cost coupling and the adaptation time.www.ijacsa.thesai.orgWe define our function as follows: ) ) ⟦ ⟧ 1) and the metric developed in [7], we are able to define a new score to evaluate the quality of the software component.So, our model for any software component i selected will be: Model (9) represents the objective function.This function is used to calculate and evaluate the quality of the characteristics of the selected software components.For optimizing the parameters Time and maintenance cost, we maximize the objective function.
For any software component i of the library, we obtain the following system: We will then be able to compare and order the different values designating the quality values of each selected software component.
V. VALIDATION PHASE
In the field of research, any theory must go through an experimentation or simulation phase before its validation.To do so, we propose an algorithm to support and validate the developed theory.It evaluates the quality of software component.It is also optimizing the two parameters including the adaptation time and the financial cost.Indeed, we propose the algorithm "SelectCompo" to solve the problem.
A. Presentation of our Algorithm
The algorithm SelectCompo aims to select in a set of available components (Cd), the optimized and selected component (Cos).See algorithm Fig. 3. 12)
Fig. 1 .
Fig. 1.Hierarchical Structure Indicating the Quality of the Software Component.
Fig. 2 .
Fig. 2. Software Component Selection Process.) ∑ ) of software quality characteristics; SC: set of available components (candidate components); q h i : the standard level of the quality attribute h A for component i; Wh: weight attributed to the quality attribute h∊A; xi = 1 if component i is selected, 0 otherwise; Ci : standardized cost of component i; C i_rel : relative cost generated by component i; t i : Standardized component maintenance time; t i_rel : Relative time, generated by component i; a: Adaptation coefficient to be specified
TABLE I
: Standardized cost of maintenance of the component i C i_rel : relative cost generated by component i; C max : maximum cost achieved by one of the selected components; t i : Standardized adaptation and maintenance time of the component i t i_rel : Relative time, generated by component i; T max is the maximum time achieved by one of the selected components; i a: Coefficient of adaptation By taking inspiration from the model ( | 4,421.2 | 2019-01-01T00:00:00.000 | [
"Computer Science",
"Business"
] |
The Range of the Spectral Projection Associated with the Dunkl Laplacian
For s ∈R, denote by Pk f the “projection” of a function f inDðRdÞ into the eigenspaces of the Dunkl Laplacian Δk corresponding to the eigenvalue −s2: The parameter k comes from Dunkl’s theory of differential-difference operators. We shall characterize the range of Pk on the space of functions f ∈DðRdÞ supported inside the closed ball BðO, RÞ: As an application, we provide a spectral version of the Paley-Wiener theorem for the Dunkl transform.
Introduction
Analysis of the Dunkl Laplacian operator Δ k on ℝ d commenced in the early 90's, inspired by numerous results in the Euclidean setting, as well as some extensions of this to flat symmetric spaces. Here, the parameter k comes from Dunkl's theory of differential-difference operators [1]. In recent years, there have been increasing interests in the study of problems involving the Dunkl Laplacian and have received a lot of attention, see for instance [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. The purpose of this paper is to study a family of eigenfunctions for the Dunkl Laplacian derived through the use of the inversion formula for the Dunkl transform. Our main result may be interpreted as a contribution to the spectral theory of the Dunkl Laplacian.
To state our main result, we need to introduce some notation. Writing the inversion formula for the Dunkl transform in polar coordinates, we obtain where f s k are "projections" of f into the eigenspaces of Δ k corresponding to the eigenvalue −s 2 (see (35)). We may also write the projection operators f ↦ f s k as Dunkl-convolution with a normalized Bessel function of the first kind (see (43)). In this paper, we discuss on Dðℝ d Þ how properties of f are related to properties of the eigenfunctions f s k : Essentially, we prove a theorem characterizing f s k for f ∈ Dðℝ d Þ with supp ð f Þ ⊂ BðO, RÞ, involving analytic continuation to s ∈ ℂ and growth estimates of type, for all N ∈ ℕ and for all multi-index m ∈ ℕ d , where C k,m,N is a positive continuous increasing function on ℝ + (see Theorem 9). Several contributions have been dedicated to this subject, see for instance [16][17][18][19][20][21][22].
As an application of the main result, we prove a spectral version of the complex Paley-Wiener theorem for the Dunkl transform F k given in [23]. More precisely, we characterize the set of functions φðs, ηÞ defined on ℝ × S d−1 for which there exists a compactly supported smooth function f with support in BðO, RÞ so that φðs, ηÞ = F k ð f ÞðsηÞ (see Theorem 10).
Background
For x, y ∈ ℝ d , we let hx, yi denote the usual Euclidean inner product of ℝ d and ∥x∥≔ ffiffiffiffiffiffiffiffiffiffi ffi hx, xi p the Euclidean norm. Let S d−1 be the unit sphere in ℝ d : We denote by dσ as the Lebesgue surface measure on S d−1 : For a nonzero vector α ∈ ℝ d define the reflection r α by A root system is a finite set R of nonzero vectors in ℝ d such that α, β ∈ R implies r α ðβÞ ∈ R: If, in addition, α, β ∈ R and α = cβ for some scalar c implies c = ±1, then R is called reduced. Henceforth, we will assume that R is a reduced root system. Fix a set of positive roots R + , so that The finite reflection group G generated by the root system R is the subgroup of the orthogonal group OðdÞ generated by the reflections fr α : α ∈ R + g: For a given root system R, a multiplicity function Given a reduced root system R on ℝ d and a multiplicity function k = ðk α Þ α∈R , we define the weight function ϑ k by Then, ϑ k is a positively homogeneous G-invariant function of degree 2hki, where The main ingredient of the Dunkl theory is a family of commuting first-order differential-difference operators, T ξ ðkÞ (called the Dunkl operators [1]), defined by where ∂ ξ is the ordinary partial derivative with respect to ξ: The Dunkl operators are akin to the partial derivatives and they can be used to define the Dunkl Laplacian Δ k , which plays the role similar to that of the ordinary Laplacian Δ, where fξ 1 , ⋯, ξ d g is an orthonormal basis of ðℝ d , h·, · iÞ: The above explicit expression of Δ k has been proved in [24].
For arbitrary finite reflection group G, and for any nonnegative multiplicity function k, there is a unique linear operator V k on the space of algebraic polynomials on ℝ d that intertwines between the Dunkl operators and the partial derivatives, It has been proved in [25] that V k has a Laplace type representation which allows to extend V k to larger function spaces: with a unique probability measure μ k x ∈ M 1 ðℝ d Þ: In fact, V k induces a homeomorphism of Cðℝ d Þ and also that of C ∞ ðℝ d Þ ; see [23,26].
(1) For all z, w ∈ ℂ d and λ ∈ ℂ, we have E k ðz, wÞ = E k ðw, zÞ and E k ðλz, wÞ = E k ðz, λwÞ: where where c k is the constant The Dunkl transform was introduced in [28] where the L 2 -isometry (or the Plancherel theorem) was proved, while the main results of the L 1 -theory were established in [11]. In particular, it has been proved that if f and F k f are in L 1
2
Journal of Function Spaces It is worth mentioning that the Dunkl transform is a homeomorphism of the Schwartz space Sðℝ d Þ: Further, according to ( [29], Proposition 5. where and H α is the Hankel transform of index α on L 1 ðℝ + , r 2α+1 drÞ, given by Here, j α is the normalized Bessel function of the first kind defined by Let y ∈ ℝ d be given. For f ∈ Sðℝ d Þ, the generalized translation operator is defined by Fact 2 (see [26]). The translation operator has the following properties: (1) For all x, y ∈ ℝ d ,τ y f ðxÞ = τ x f ðyÞ: (2) For fixed y ∈ ℝ d ,τ y extends to a continuous linear The generalized translation operator is used to define a convolution structure: For f , g ∈ Sðℝ d Þ, where gðxÞ ≔ gð−xÞ: We can also write the convolution * k as We refer the reader to [15] for more details on the convolution product * k : It is worth mentioning, for the distributional version of the Dunkl transform, the translation operator and the Dunkl convolution of distributions and properties, we refer the reader to [30].
For n ∈ ℕ, let H n k be the space of k-harmonic polynomials of degree n on ℝ d , where Δ k is the Dunkl Laplacian and P n ðℝ d Þ denotes the space of homogeneous polynomials of degree n on ℝ d : The restriction of elements in H n k on the unit sphere S d−1 in ℝ d are the so-called k-spherical harmonics. We shall not distinguish between Y n k ∈ H n k and its restriction to S d−1 : The space H n k has a reproducing kernel Q n k ð·, · Þ in the sense that Here, d k is the constant where c k and λ k are as defined in (13) and (16), respectively. According to [31], for x, y ≠ 0, the kernel Q n k can be written as where V k is the Dunkl intertwining operator (8), and C α n is the Gegenbauer polynomial of degree n, for α > 0, with 2 F 1 is the Gauss hypergeometric function.
The following analogue of the Funk-Hecke formula for k -spherical harmonics will be used later on; for the proof, the reader is referred to [32]. Let h be a continuous function on ½−1, 1: Then, for any Y n k ∈ H n k , 3 Journal of Function Spaces where Λ n ðhÞ is a constant defined by We summarize some basic properties of Gegenbauer polynomials in a way that we shall use later. . For λ ∈ ℂ such that Re λ > 0, the following two integral formulas hold: Let D R ðℝÞ e denote the space of even compactly supported smooth functions with support in ½−R, R, where R > 0: The Paley-Wiener theorem for the Hankel transform H α (see (17)) states that H α maps D R ðℝÞ e bijectively onto the space H R ðℂÞ e of even entire functions g satisfying, for all N ∈ ℕ, for some positive constant C N ; see for instance [34]. This result has been generalized by de Jeu [23] to the Dunkl transform. To state the (complex) Paley-Wiener theorem for F k , we introduce the following notation. For R > 0, let H R ðℂ d Þ be the space of entire functions F on ℂ d with the property that for all N ∈ ℕ there exists a constant C N > 0 such that We let D R ðℝ d Þ denote the space of smooth compactly supported functions with support contained in the closed ball BðO, RÞ ⊂ ℝ d with radius R > 0 and the origin as center.
Fact 4 (see [23]). The Dunkl transform F k is a linear isomorphism between D R ðℝ d Þ and H R ðℂ d Þ, for all R > 0: An immediate consequence of the above Paley-Wiener theorems can be stated as follows: for all N ∈ ℕ: Proof. The statement follows from the fact that F k f ðξÞ = H λ k f 0 ð∥ξ∥Þ whenever f is a radial function with f ðxÞ = f 0 ð∥ x∥Þ (see (15)), together with the Paley-Wiener theorems stated above for the Hankel and the Dunkl transforms.
The Range of the Spectral Projection Associated with Δ k
Recall from (12) that the Dunkl transform of f ∈ Dðℝ d Þ is defined by Using polar coordinates, the Dunkl inversion formula (14) becomes where Notice that Δ x k P s k f ðxÞ = −s 2 P s k f ðxÞ: From (36), we may derive a second formula for P s k f : Indeed, substituting (34) into (36), we obtain According to [[35], page 2424], the inner integral is equal to 4 Journal of Function Spaces where d k is the constant (25), Q n k ð·, · Þ is the reproducing kernel (26), and j α is the normalized Bessel function (18). We now use the well-known addition formula for Bessel functions (see [[36] , p. 215]): for a,b,θ ∈ ℝ, which converges uniformly with respect to θ ∈ ℝ: Using (38) and (26) together with the Laplace representation (9) for V k , we deduce that Define j s,λ k ðyÞ ≔ j λ k ðs∥y∥Þ, then, by [ [35] , p. 2429], we have Consequently, the eigenfunction P s k f can be rewritten as Above, we have used some of the properties of the generalized translation operator listed in Fact 2. The following statement lists the necessary conditions for Theorem 9.
Proposition 6. Assume that f ∈ D R ðℝ d Þ and let P s k f ðxÞ defined either by (36) or (42), with s ∈ ℝ and x ∈ ℝ d : Then the following hold: (5) For any k-spherical harmonic Y ℓ k of degree ℓ and for every r > 0, the map is entire on ℂ: Proof.
(1) In view of properties of the translation operator τ x and the normalized Bessel function j α , the first statement follows from the representation (42) of P s k f ðxÞ: (2) The second property is immediate from (36) We now apply the Funk-Hecke formula (28) to deduce that ð where, by Fact 3, we have Using the above identities, it follows that ð where φ ℓ+λ k ðzÞ ≔ 1/ð2 λ k +ℓ Γðλ k + ℓ + 1ÞÞz ℓ j ℓ+λ k ðzÞ and Above, we have used the fact that d k = c k /f2 λ k Γðλ k + 1Þg ; see (25). In conclusion, The desired result now follows from the fact that s −ℓ φ ℓ+λ k ðszÞ is an entire function of s ∈ ℂ: The following lemma is needed for later use.
(1) In the polar coordinates x = rω, the Dunkl Laplacian operator is expressed as where Δ k,S d−1 is the analogue of the Laplace-Beltrami operator on the sphere S d−1 , which, in particular, has k-spherical harmonics as eigenfunctions, We refer the reader to [37] for more details on Δ k,S d−1 : (2) Obvious Next we will list the sufficient conditions for Theorem 9.
Proposition 8. For s ∈ ℝ and x ∈ ℝ d , let f s ðxÞ be a function satisfying the following conditions: (1) f s ðxÞ is smooth on ℝ × ℝ d (2) f s ðxÞ is an eigenfunction of the Dunkl Laplacian with eigenvalue −s 2 The mapping s ↦ f s ðxÞ extends to an even entire function on ℂ | 3,168.2 | 2020-07-24T00:00:00.000 | [
"Mathematics"
] |
Anti-inflammatory and immunomodulatory properties of Mentha piperita green-formulated gold nanoparticles and its effect on ovalbumin-induced asthma and lung pathological changes in rats
Abstract Regarding applicative, facile, green chemical research, a bio-inspired approach is being reported for the synthesis of Au nanoparticles by Mentha piperita as a natural reducing and stabilising agent in alkaline medium without using any toxic reducing agent. The biosynthesized Au NPs@Mentha piperita were characterised by advanced physicochemical techniques like ultraviolet-visible (UV-Vis), Fourier Transformed Infrared spectroscopy (FT-IR), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Energy Dispersive X-ray spectroscopy (EDX), and X-ray Diffraction (XRD) study. It has been established that Au NPs@Mentha piperita have a spherical shape with a mean diameter from ∼10 nm. To survey the cytotoxicity effects of Au NPs@Mentha piperita, MTT assay was used on HUVEC cell line. To survey the antioxidant properties of Au NPs@Mentha piperita, the DPPH test was used in the presence of butylated hydroxytoluene as the positive control. The Au NPs@Mentha piperita inhibited half of the DPPH molecules in the concentration of 113 µg/mL. In the in vivo, wistar rats were divided to four groups; non-sensitised, sensitised to ovalbumin, sensitised and treated with dexamethasone (1.25 μg/mL), and Au NPs@Mentha piperita (5 μg/mL) in drinking water for 21 days. The levels of total protein (TP), phospholipase A2 (PLA2), immunoglobulin E (IgE), IFN-γ/IL-4 ratio, interferon gamma (IFN-γ), and interleukin 4 (IL-4) in BALF, and lung pathological changes were examined. A significant increase in PLA2, IgE, IL-4, and TP levels, all lung pathological indices as well as significant decrease in IFN-γ/IL-4 ratio was seen in the asthmatic compared to the control rats. Treatment with Au NPs@Mentha piperita (5 μg/mL) resulted in decreased PLA2, IgE, IL-4, and TP levels, but increased IFN-γ/IL-4 ratio compared to untreated sensitised rats. The Au NPs@Mentha piperita significantly improved the pathological changes of sensitised rats. The improvement effects of higher concentrations of the Au NPs@Mentha piperita extract were significantly more than those of dexamethasone. The improvement effects of Au NPs@Mentha piperita on pathological changes, immunological and inflammatory markers in sensitised rats comparable or even more potent than dexamethasone suggests the therapeutic potential of the nanoparticle in asthma. After confirming these results in clinical trial studies, Au NPs@Mentha piperita can be used as a new drug for the treatment of asthma in humans.
Introduction
Mentha piperita L. is a plant with a warm and dry nature that has many medicinal properties. It can be consumed in various forms such as fresh, dried, essential oil, brewed, powder, etc. Mentha piperita leaves contain the highest amount of antioxidants compared to other plants [1][2][3]. Mentha piperita oil contains phenolic acids, phytosterols, saponins, triterpenes, flavonoids, carotenoids, anthocyanins, etc. Phosphorus, iron and calcium with vitamins C and A Mentha piperita are very important for skin cell repair and growth. These vitamins and minerals also form parts of the cell wall in the circulatory system that are vital to life [4][5][6][7]. Mentha piperita oil is widely used for various purposes. This oil is widely used today in the preparation of foods, perfumes and to treat various types of problems. Mentha piperita is soothing and has cleansing and detoxifying properties. Mentha piperita prevents inflammation in the stomach, cleanses the palate and strengthens the digestive process. This is due to the activation of the salivary glands in the consumption of Mentha piperita, which enables digestive enzymes to produce sufficient amounts [2][3][4][5][6]. Mentha piperita, the release of digestive enzymes enables the body to consume more fat to produce energy. Mentha piperita is a very useful plant to increase liver strength due to its essential nutrients and properties such as its sedative and soothing properties [5][6][7][8]. People who are regular consumers of Mentha piperita are extremely alert and intelligent. Mentha piperita is known to be an effective stimulant, which increases long-term memory retention and clear alertness. Mentha piperita is a very fragrant natural stimulant that increases energy in the body. It can be used as an oil or inhaler or as a steamer to reduce depression and fatigue. It stimulates the mind, strengthens it and increases the overall state and function of the body. Due to the anti-inflammatory nature of Mentha piperita leaves, it is likely that the red and swollen areas within the respiratory tract will be relieved in a short time by eating a fresh Mentha piperita [3][4][5][6]. The oils contained in Mentha piperita are widely known to resist the release of certain chemicals in the body, which can also lead to seasonal allergies and hay fever. Mentha piperita is best consumed raw or in the form of tea, to protect against allergies [2][3][4][5][6]. These benefits also make Mentha piperita leaves great for coughs and other problems that are exacerbated by sudden and sudden contractions of muscles in the surrounding area. Mentha piperita is used in the form of tea or chewing gum to relieve congestion of the throat, nose, bronchitis and lungs [1][2][3][4]. It helps soothe the nose, throat and airways and prevent a long-term disorder that usually starts with asthma or colds. Mentha piperita has soothing properties and is very useful for patients with asthma, because it causes blockage in the nasal tube. However, the amount and frequency of Mentha piperita consumption should be controlled as overuse may lead to nasal and gastric irritation [4][5][6][7][8].
Asthma is a chronic inflammatory disease characterised by reversible obstruction of the small airways. Symptoms include attacks of shortness of breath, cough, and wheezing (classic triad). It may wake the person up due to the severity of the symptoms or lead to hypoxia, cyanosis, and suffocation [9-12]. Causes (triggers) mentioned for asthma include: Infections (especially viral types); Pollutants, some medications, some occupations, exercise and psychological causes. In both conventional and traditional Iranian medicine, there are treatments for asthma that fall into two categories: For immediate control and for long-term control [10-12]. Traditional medicine uses methods for immediate control of asthma to divert phlegm to places other than the airways and lungs, and for long-term control of phlegm excretion from the body in general [9][10][11]. To link herbal medicines in the world's pharmacopoeias to the advice of scholars in traditional medicine texts in the treatment of asthma, extensive searches were made in a number of reputable herbal medicine books available in pharmacopoeias of some developed countries [10][11][12]. In total, about 130 plants and their products with anti-shortness of breath and asthma properties were found, of which about 30 are specific and specific cases for the treatment of asthma. To date, the use of nanotechnology continues to provide numerous benefits in the treatment of various chronic diseases and leads to significant improvements in treatment outcomes [9-12]. The use of nano-based delivery systems such as liposomes, micelles and nanoparticles in pulmonary drug delivery has shown a promising strategy in achieving drug deposition and maintaining controlled drug release in the lungs. They have been widely used to minimise the risks of drug toxicity in the body [9-11].
Nanotechnology is defined in different ways in several countries, which affects the nanodrugs clinical validation. However, what these different definitions have in common is the use of nanoscale structures. There are several distinct benefits to using nanotechnology in the diseases treatment [13][14][15]. Nanoparticles, especially metal nanoparticles and metal oxides, have been widely used by medical consumers and manufacturers. The mechanism of nanoparticle-induced toxicity against cancer cells is the production of reactive oxygen species (ROS). Excessive production of reactive oxygen species can lead to oxidative stress, disruption of normal physiological maintenance, and oxidation regulation [12][13][14][15]. These effects in turn lead to DNA damage, unregulated cell signalling pathways, changes in cell evolution, cytotoxicity, apoptotic death, and the onset of cell death. Critical-deterministic factors can affect the production of reactive oxygen species. These critical-deterministic factors include shape, size, nanoparticle surface area, particle surface baroelectricity, surface-forming groups, Particle solubility, metal ion emission from nanomaterials and nanoparticles, optical activation, model of cell reactions, inflammatory effects and ambient pH [11][12][13][14][15]. Metal nanoparticles and oxides of metal nanoparticles due to their optical properties due to the large active area and high atomic number, amplify the photoelectric and Compton effects of both X-ray and gamma-ray interactions with the adsorbent in the diagnostic and therapeutic range [9][10][11][12][13][14]. Finally, they can lead to the development of methods for the destruction of tumour cells and reduce their survival with minimal side effects in radiation therapy [12][13][14][15].
In this study, the anti-inflammatory and immunomodulatory properties of Mentha piperita green-formulated gold nanoparticles and its effect on ovalbumin-induced asthma and lung pathological changes were investigated in rats.
Materials
The Mentha piperita plant, which is applied in this study as a factor for reducing metal ions and stabilising nanoparticles, has been prepared from the mountainous areas. HAuCl 4 , ethanol and methanol were purchased from Merck.
Preparation and extraction of aqueous extract
First, it was necessary for the experiments to provide a pure solution of the extracts of the leaves of Mentha piperita plant. To do this, 1.5 g of leaf powder was added to 60 mL of deionised water. Then, the resulting solution is placed on a hot plate at 60 C for 2.5 h to dissolve plant agents and metabolites well in the solvent. The resulting solution was poured into the Falcon tubes, and centrifuged at 5000 rpm for 10 min to separate the plant residue from the extract. Then, the resulting extract was moved into test tubes, and placed in the refrigerator to keep it fresh and healthy.
Green synthesis and chemical characterisation of gold nanoparticles
The biosynthesis of AuNPs, a 10 mL of aqueous extract solution (20 mg/mL) was added to 30 mL of HAuCl 4 .6H 2 O in the concentration of 0.02. The mixture was stirred for 90 min at 50 C. The colour-changing from yellow to black indicated the formation of gold nanoparticles. The precipitate was triplet washed with water and centrifuged at 12000 rpm for 15 min subsequently. The obtained black powder was kept in a vial for the chemical characterisation and evaluation of its biological activity.
Different spectroscopic and imaging techniques were used to evaluate and identify the AuNPs. At the first step, UV-vis spectrum (Cary UV-Vis 4000, Agilent) was used to identify gold nanoparticles. Typically, gold nanoparticles have two absorption spectra in the range of 400-700 nm. The FT-IR spectrum (PERKIN-ELMER, RXI) was used to identify nanoparticles and plant metabolites in plant extracts. TEM (H9500, HITACHI) was also used to examine the shape and size of nanoparticles.
In vivo design
Young male rats (60) of Wistar strain weighing 220-250 g were procured. The experimental animals were housed in a temperature controlled room (24 ± 1 C) with 12:12 h L:D illumination cycle. Rats were sensitised as previously described [16]. Rats were divided to four groups; non-sensitised, sensitised to ovalbumin, sensitised and treated with dexamethasone (1.25 lg/mL), and Au NPs@Mentha piperita (5 lg/mL) in drinking water for 21 days. The levels of total protein (TP), phospholipase A 2 (PLA 2 ), immunoglobulin E (IgE), IFN-c/IL-4 ratio, interferon gamma (IFN-c), and interleukin 4 (IL-4) in BALF, and lung pathological changes were examined. Briefly, 1 mg/kg ovalbumin (OA) plus 100 mg Al(OH) 3 was administered intraperitoneal (i.p.) and rats were exposed to 2% OA aerosol with air flow of 8 lit/min for 20 min/day in a 0.8 m 3 chamber, with animal normal-breathing. Saline was used instead of the ovalbumin solution in the control rats. One day after the end of sensitisation, animals were sacrificed by i.p. administration of 50 mg/kg ketamine and 5 mg/kg xylazine. The left lung was washed with one mL saline five times (5 mL totally). BALF was centrifuged at 2500 g at 4 C for 10 min and supernatant was stored at À 70 C [16] until analysis. Cytokine and inflammatory levels including interleukin 4, interferon gamma, immunoglobulin E, phospholipase A2 and total protein in the BALF were measured by enzyme-linked immunosorbent assay (ELISA) sandwich method with appropriate protocol recommended by company. The ratio of IFN-c/IL4 as an index of Th1/Th2 was also calculated [16].
The results were evaluated as Mean ± SE using SPSS software version 12 and statistical tests of variance of completely randomised block design. Drawing graphs in Excel software was performed and the significance level of the differences was considered p < 0.05.
Results and discussion
UV-Vis is based on the irradiation of ultraviolet and visible photons on the sample and measures the rate of passage or absorption of matter at different wavelengths in the range of 200 to 1100 nm. It is possible to measure the spectrum for samples in solution, solid as well as thin layers. The size of solid samples should be larger than 20 mm. This test is not possible for powder samples. One of the important applications of UV device is to determine the concentration of the unknown solution. By having the original sample and its solvent and making several solutions with different percentages and drawing a calibration diagram based on the calculation of the maximum land, the concentration of the unknown solutions can be calculated [10].
The successful biosynthesis of AuNPs using Mentha piperita leaf aqueous extract was observed visually. Figure 1 displays the UVs absorption spectrum of the AuNPs. The spectrum of AuNPs exhibited a peak at 537 nm due to intrinsic bandgap absorption, which is confirmation of AuNPs. During the biosynthesis of AuNPs, the colour of the reaction solution changed to dark red after mixing plant extract with HAuCl 4 .
FT-IR (Fourier Transform Infrared) has been a suitable technique for analyzing materials in the laboratory. An infrared spectrum represents the fingerprint of the sample under test with absorption peaks, which depends on our vibrational frequencies between the atomic bonds of that material. Since each substance has its own atomic bonds, no two compounds with the same infrared spectrum are alike. Hence, infrared spectroscopy can be effective in better identification (qualitative analysis) of different types of materials. In addition, the peak sizes are in the range indicating the amount of material present. Advanced software algorithms make this spectroscopy a great tool for quantitative analysis [10].
According to Figure 2 (FT-IR spectrum), the extract revealed peaks corresponding to hydroxide and carboxyl functional groups of phytochemical substances. Stretching of the Au-O peak was observed at 513 cm À1 . C-H stretching at 2379 cm À1 , COO asymmetric and symmetric stretching at 1856 cm À1 and 1608 cm À1 , respectively, and OH stretching at 3422 cm À1 were observed. These peaks are also observed in the spectra of the AuNPs, which also displayed a redshift from the COO symmetric and asymmetric stretching from the extract. This indicates that the carboxyl group is bound to the surface of the AuNPs and acts as a stabilising agent. The effective formation of AuNPs may be attributed to the phytochemical compounds present in the Mentha piperita aqueous extract, which can act as reducing as well as stabilising agents for the reduction and formation of AuNPs.
TEM (transmission electron microscope) is used for determining the structure and morphology of materials. TEM transmission electron microscope products enable microstructural studies with high resolution and high magnification such as studies of crystal structures, symmetry, orientation and crystal defects. TEM and SEM microscopes differ in how the beam passes and the information obtained from the sample. Scanning microscopes take pictures of the sample surface, while passing microscopes take pictures of the inside of the sample. The resolution and magnification of electron microscopes are higher than those of scanning electron microscopes. The electron beams in the scanning electron microscope scan the surface of the sample point-by-point, but the TEM microscope beams hit and pass through the entire sample. In addition, sample preparation for the SEM microscope is easier than for the TEM microscope [10]. Figure 3 shows the shape and size of the AuNPs using TEM techniques. The fast reduction of the gold ions by the Mentha piperita aqueous extract allowed homogeneous nucleation of gold metals, which cause to form AuNPs with small size. The AuNPs are confined within a Mentha piperita matrix, likely comprised of biomolecules that are acting as a stabiliser or capping agent during synthesis. The obtained AuNPs found spherical and the size of 13-58 nm. In rare cases, particles with larger sizes were also seen in the sample, but their numbers were rather low.
BALF level of IFN-c in ovalbumin group was significantly different compared to normal group. There were significant decrease in BALF level of IFN-c in Dexamethasone group compared to normal group. Treatment of sensitised rats with two low concentrations of the Au NPs@Mentha piperita and dexamethasone led to significant decrease in IFN-c as compared to ovalbumin group. A significant difference in BALF level of IFN-c between Au NPs@Mentha piperita and Dexamethasone groups was also seen (Figure 4). BALF level of IL-4 in ovalbumin group was significantly higher than normal group. BALF level of IL-4 in Dexamethasone and Au NPs@Mentha piperita groups were significantly lower than ovalbumin group. There reduction of IL-4 level in Au NPs@Mentha piperita group was not significantly more than Dexamethasone group (Figure 4). The ratio of IFN-c/IL-4 was decreased in all untreated and treated sensitised groups compare to normal group. The ratio of IFN-c/IL-4 in Au NPs@Mentha piperita group was also significantly higher compared to Dexamethasone group (Figure 4). BALF IgE level was significantly higher in ovalbumin, Dexamethasone, and Au NPs@Mentha piperita group compared to that of normal group. The BALF IgE level in Dexamethasone and Au NPs@Mentha piperita groups were significantly decreased compared to ovalbumin group. BALF IgE level in treated group with high concentration of the Au NPs@Mentha piperita was also lower than Dexamethasone group ( Figure 5).
BALF level of PLA2 in ovalbumin group were significantly higher than normal group. The level of PLA2 was decreased in all treated groups. BALF level of TP in ovalbumin group was significantly higher than normal group ( Figure 6). The level of TP was decreased in Dexamethasone and Au NPs@Mentha piperita groups compare to ovalbumin group. The mean value of TP in Au NPs@Mentha piperita group was not significantly lower compared to Dexamethasone group. There was significant difference between Au NPs@Mentha piperita and normal groups, (Figure 7).
Conclusion
The aim of this study was to synthesise green AuNPs using Mentha piperita extract and to investigate the therapeutic properties of gold nanoparticles on asthma. Many factors are involved in the synthesis of green AuNPs. These factors include temperature, time of reaction, concentration of gold salt solution and volume ratio of extract solution to gold solution. TEM analysis showed that nanoparticles have a spherical morphology.
Anti-inflammatory and immunomodulatory effects of Au NPs@Mentha piperita on asthma were shown by increasing the IFN-c/IL-4 ratio (Th1/Th2 balance) and decreasing BALF levels of IgE, PLA2 and TP as well as improvement of pathological changes in sensitised rats by the nanoparticles. These findings suggest the preventive therapeutic potential for the Au NPs@Mentha piperita on animal model of asthma.
Disclosure statement
The authors report no conflict of interest.
Notes on contributor
Data availability statement Data available within the article. | 4,424 | 2022-04-04T00:00:00.000 | [
"Medicine",
"Environmental Science",
"Chemistry",
"Materials Science"
] |
An improved method for estimating soil moisture over cropland using SAR and optical data
The paper aims to construct simple soil moisture(SM) retrieval model using Sentinel-1 synthetic aperture radar (SAR) data. The water cloud model (WCM) removed the contribution of vegetation to the radar backscattering coefficient, and the backscattering coefficient of soil was estimated. Based on the established SM retrieval model without soil roughness parameters, the SM in farmland and forest land was retrieved using radar VV-VH dual-polarization data. We considered the interference of uneven surfaces on the radar signal, added the radar local incidence angle parameter to improve the model, and constructed a semi-empirical SM retrieval model. The accuracy of the results showed Root Mean Square Error (RMSE) of 0.04 and the Pearson correlation coefficient (r) of 0.80. The SM retrieval model for removing soil roughness parameters can estimate soil moisture with reasonable accuracy. The influence of topographic factors (elevation, slope and aspect) on the retrieval results of the model was analyzed. It was found that the area with the steep slope and blocked radar signal is not conducive to estimate SM. The SM retrieval method constructed in this paper provides many advantages for some research and practical applications, and its application in other SAR data remains to be further studied.
Introduction
Soil moisture (SM) is closely related to many basic agricultural activities and hydrological processes, and it is of great significance in agricultural applications such as crop growth monitoring, crop yield estimation, and irrigation (Koster et al. 2004;Leenhardt et al. 2004;Saux-Picart et al. 2009;Balenzano et al. 2011). The temporal variability of SM provides good information on crop water demand, which is helpful to formulate agricultural water management policies (Champagne et al. 2012;Trudel et al. 2012;Sekertekin et al. 2020). Due to its significant spatial heterogeneity and the high cost of SM observation equipment, it is not easy to establish a high-resolution observation network in the region (Korres et al. 2013;Hajj et al. 2016).
The rapid development of microwave (MW) remote sensing (RS), especially the spaceborne synthetic aperture radar (SAR), breaks through the limitation of traditional pointbased measurement to obtain SM, making it possible to monitor SM in a large area in real-time (Mattia et al. 2009;Wei et al. 2014;Shi et al. 2021). The SAR can provide high temporal and spatial resolution monitoring data under any weather conditions (Gherboudj et al. 2011;Bauer-Marschallinger et al. 2018). The surface backscattering coefficient provided by SAR directly relates to the dielectric constant, which can effectively extract the surface SM information (Zribi et al. 2019).
The method of soil moisture retrieval using SAR data can be divided into theoretical, empirical, and semi-empirical models. The theoretical model involves a wide range of parameters, which makes the model difficult to realize (Gorrab et al. 2015). The empirical model is established under specific conditions. For different regions, the applicability of empirical model is uncertain when the surface and radar parameters are different (Chen et al. 2003;Baghdadi et al. 2012 the backscattering coefficient, surface parameters, and radar parameters, which has the advantage of a wide application range (Shakya et al. 2021;Stuurop et al. 2021). Due to the complexity of the interaction between electromagnetic wave and surface, the radar backscattering coefficient is affected by the surface dielectric constant and soil roughness and radar parameters (incidence angle, frequency, and polarization), and vegetation cover (Balenzano et al. 2013). The water cloud model (WCM) uses simulated or measured surface roughness and vegetation coverage datasets to simplify the theoretical backscattering models (El Hajj et al. 2017;Wang et al. 2020). In the vegetated area, the WCM can effectively remove the contribution of vegetation to backscattering coefficient . Soil roughness is one of the crucial factors affecting retrieval accuracy and one of the most challenging factors to monitor large-scale areas (Aubert et al. 2011;Balenzano et al. 2011;Zheng et al. 2021). It is difficult to measure accurate soil roughness in large areas, primarily on cultivated land, which will change over time (Balenzano et al. 2013;Zheng et al. 2021). Eliminating the soil roughness parameters can simplify the SM retrieval model. Using multi-polarization, multi-angle, and multi-band radar data can eliminate the influence of soil roughness and simplify the relationship model between soil moisture and radar data (Dey et al. 2020). When the ground fluctuation is obvious, the influence of the local terrain on the radar beam should be considered (Rahman et al. 2008;Ouellette et al. 2017;Zhu et al. 2019). The radar local incidence angle fully considers the influence of local terrain on radar signal.
A semi-empirical retrieval model was constructed using Sentinel-1 SAR VV-VH dual-polarization and measured SM data based on the established SM retrieval model for removing soil roughness parameters. The influence of topographic factors (elevation, slope, and aspect) on the retrieval results was analyzed. Remove data from areas that were not conducive to estimating SM. Add The radar local incidence angle parameter to improve the model and improve the accuracy of SM estimation. The semi-empirical model can effectively remove the effects of soil roughness and topography on radar backscattering coefficient. The model is not limited by surface conditions and can estimate soil moisture well.
Study area
The study area is in southern Henan Province, China. Figure 1 shows the geographical location of the study area and SM observation stations. The study area is in the transition zone between the subtropical and temperate zones. The interannual precipitation variation is considerable, with the uneven temporal and spatial distribution. Generally, there is less precipitation in winter and spring, more precipitation in summer and autumn, and mainly concentrated in July and August.
The southwest of the study area is Nanyang Basin, the middle is Tongbai hill, and the northeast is Huaihe River alluvial plain. As an area focusing on agricultural development, the basin and plain are cultivated land, with many crops growing on the surface, mainly wheat and corn. Dense broad-leaved forests grow in hilly areas. The demand for crops for water is different in different periods. Timely monitoring of soil drought is of positive significance to agricultural production.
In situ measurements
The in situ measurements data used in this work are those collected by the China National Meteorological Science Data Center (available at https:// data. cma. cn/). The meteorology stations are equipped with different types of sensors to measure the parameters such as: soil relative moisture and soil temperature at different depths, precipitation, wind speed and temperature. The meteorological bureau uses the GStar-I (DZN2) automatic SM observation instrument to collect hourly soil relative moisture data. The soil relative moisture with an underground depth of 10cm-100cm is measured, and the sampling interval is 1 hour. The hourly SM curve of each station can test the integrity of the data of these station. Abnormal values can be eliminated through the data change trend to ensure the accuracy of the measured SM. The In situ measurements data with a depth of 10cm was used to build the model and verify the accuracy of the estimated SM.
Sentinel-1
Sentinel-1 is recognized as an earth observation satellite, comprising two polar orbiting satellites A and B. Sentinel-1 equipped with a C-band SAR sensor with an operating frequency of 5.4 GHz has a multi-polarization imaging capability. The revisit cycle of one satellite is 12 days, while the use of two satellites declines to 6 days. Under the data acquisition mode of satellite, images with 5-40m resolution can be captured under all-weather conditions. The imaging mode of The SAR image used in this study is single look complex (SLC) data from the interferometric wide swath (IW) mode which provided VV and VH polarization data. The Sentinel-1 data were obtained on 7 July and 16 November 2019.
Landsat-8
The Landsat 8 data is provided at no cost for global users through the data distribution website (https:// glovis.usgs.gov/) of the United States Geological Survey (USGS). Landsat-8 carries operational land imager (OLI) and thermal infrared sensor (TIRS), and the revisit cycle is 16 days. The OLI instrument includes 9 shortwave spectral bands with the resolution of 30 meters, and the TIRS consists of two thermal infrared bands with the resolution of 100 meters. The Landsat-8 image from 7 July and 12 November 2019 were acquired to ensure the consistency in the acquisition time with the Sentinel-1 data.
Methodology
This paper used WCM to estimate the soil backscattering coefficient. The established SM retrieval model estimated soil relative moisture in the vegetation coverage study area. Discussed the effects of elevation, slope and aspect on the retrieval results to remove the data that is not conducive to estimate SM. We considered the influence of terrain factors on the measured results, addicting the radar local incidence angle parameter to improve the model. The illustration of methods for SM retrieval is in Fig. 2.
Water cloud model
The vegetation layer will contribute to the radar backscattering coefficient in the area covered by vegetation. The effect of vegetation on backscattering coefficient must be subtracted when retrieving soil moisture from SAR data. The WCM formula is as follows: Where 0 is total backscattering coefficient of the radar reception; 0 veg , 0 soil are vegetation and soil backscattering coefficient, respectively. is radar incident angle; 2 ( ) is a double attenuation factor for radar waves passing through vegetation; VWC is the vegetation water content; and the values of A and B depend on the vegetation type.
Improved SM retrieval model
Previous studies have shown that there is a close relationship between the soil backscattering coefficient, SM and soil roughness (Ulaby et al. 1981), which can express as: Where pq is H or V polarization, M v is soil moisture, l is correlation length, and s is the root mean square height. Correlation length and root mean square height are essential factors constituting surface roughness. Zribi and Dechambre (2002) proposed the combined soil roughness parameter, Z s = s 2 / l. Therefore, the empirical formula abbreviates as: Based on the data simulation, the relationship between backscattering coefficient, SM, combined soil roughness parameters and incident angle can express as (Kim and Van 2009): In formula 6, the combined soil roughness parameter can be eliminated by combining two polarization data, and the relationship between backscattering coefficient and SM under each polarization combination can be obtained. The SM retrieval formula of VV-VH dual-polarization data is as follows (Wang et al. 2018): Where A VVVH , B VVVH and C VVVH are functions of radar incidence angle. Wang et al. (2018) put the simulated radar and surface parameters into the AIEM model (Wu and Chen (4) ) to fit the A VVVH , B VVVH and C VVVH parameters corresponding to each radar incidence angle. It is worth mentioning that the AIEM model is only applicable to HH and VV co-polarization data, while the AIEM model and Oh model jointly describe HV and VH cross-polarization data (Oh et al. 2002).
In this study, 75% of data are used to fit the formula and use the remaining 25% of data to verify the accuracy of model. The radar incidence angle will change under the influence of terrain, as shown in Fig. 3. Adding the parameter of radar local incidence angle to the formula. The improved SM retrieval formula is as follows:
Results
Based on Sentinel-1 and Landsat-8 RS images, calculate the soil backscattering coefficient by WCM. There are 138 group data, of which 104 data are put into formula seven as training samples. The fitted retrieval formula is as follows: The fitting formula 9 estimated the remaining 34 data and constructed the scatter diagram with the measured 34 data (Fig. 4). The Root Mean Square Error (RMSE) is 0.04, and (8) M v = 10 0.07694⋅cos( )⋅ 0 soil(VV) −0.00934⋅cos( )⋅ 0 soil(VH) + 0.33924⋅cos( ) −0.7194 Fig. 2 The illustration of the SM retrieval model the Pearson correlation coefficient (r) between the estimated and measured soil moisture is 0.80. Without soil roughness parameter, the SM retrieval model can estimate the SM with reasonable accuracy. In order to analyze the influence of topographic factors (elevation, slope, and aspect) on the model, the soil moisture was estimated by formula 9. Divide all estimated SM data into four groups regarding their DEM, slope, and aspect values, respectively. The correlation coefficient values of estimation and measurement of SM under grouping are in Table 1. In the study area, the basin and plain areas have the characteristics of low elevation, flat slope and inconspicuous aspect distribution, while in hilly areas, it is the opposite. From Table 1, conclude that (1)In the area with low elevation (elevation lower than 130 m), flat slope (slope lower than 2°), north and south aspects, the correlation coefficient between observation and estimation of SM is little different, and the topographic factors hardly affect the estimated results of the model. (2)The r between the retrieved and the observed SM in the area with high elevation, steep slope, and east aspect is significantly lower than in other areas. In the area with sizeable topographic relief (steep slope), the radar signal received and reflected in the east aspect is blocked by the terrain, making it unable to express the surface information.
We compared the radar backscattering coefficients in the study area and found that the backscattering coefficients in the north and south aspect were not significantly different, and the values in the east aspect were low. The radar signal in the west aspect was affected by perspective shrinkage and overlap, and the backscattering coefficient in this area was significantly higher than that in other areas.
Combined with the VV-VH dual-polarization data of Sentinel-1 and the optical data of Landsat-8, the improved model was used to retrieve the SM in vegetation areas. Taking the data of 7 July 2019 as an example, Fig. 5 shows the spatial distribution of the estimated SM (Fig. 5a) and normalized vegetation index (NDVI) (Fig. 5b). The blank parts in the figure are clouds, shadows, water bodies, and buildings. The estimated SM is in good agreement with the The scatter plot between measured and estimated soil relative moisture spatial distribution of NDVI. Especially in the low vegetation coverage area, the SM in this area is also relatively low. The slope is steep and the aspect distribution is apparent in the hilly areas. The high and low values of estimated SM in this areas are cross distributed. Due to the radar signal was affected by sizeable topographic relief, the soil backscattering coefficient in the west aspect was too large, and the soil backscattering coefficient in the east aspect was too low.
Conclusion and discussion
The SAR polarization data provides useful information about SM. The Sentinel-1 VV-VH dual-polarization data estimated the SM in the study area using the SM retrieval model without soil roughness parameters. Group the SM data according to the elevation, slope, and aspect, and the correlation between the measured and estimated SM under each grouping was analyzed. According to the Sentinel-1 data used in the study, found that in the area with sizeable topographic relief (large slope and apparent aspect distribution), the radar signal was blocked by the terrain, resulting in the small radar backscattering coefficient value in the east aspect in the study area, and the correlation between the estimated and measured SM in this area was poor.
Considering that the actual radar incidence angle would change under the influence of terrain, add the radar local incidence angle parameter to improve the model. The SM retrieved by the improved model has the highest estimation accuracy, which shows that it was reasonable to consider the radar local incidence angle in the model.
It is worth mentioning that the steep slope and the east aspect areas are not conducive to the model estimation of SM and are not suitable for other SAR data. With the change of SAR imaging mode, the blocked area of the radar signal will change. This study found that the radar signal in the west aspect was affected by perspective shrinkage and overlap, and the value of the radar backscattering coefficient in this area was too large. However, there are no SM observation stations in the study area, distributed in the area with a large slope and west aspect, so the correlation between observation and estimation of SM in this area cannot be verified. In general, the improved SM retrieval model does not need the measured surface parameter but only needs to combine the radar polarization and the measured SM data with building the model. Constructed the model using the relationship between soil backscattering coefficient and SM, so applying this model to bare land is applicable. The SM retrieval method constructed in this paper provides advantages for agricultural irrigation, drought monitoring, and other practical applications, but its application in its area needs to be further studied. At the same time, the paper only discusses the ability of VV-VH polarization combination data to estimate SM, and the effect of other polarization combination data to estimate SM needs to be further confirmed. | 3,938.2 | 2023-03-22T00:00:00.000 | [
"Environmental Science",
"Mathematics"
] |
High resolution femtosecond direct laser writing with wrapped lens
: Wrapped writing mode is a simple, inexpensive approach to multiphoton stere-olithography. Standard ∼ 10 µm thin cling foil shields the objective from direct contact with the photoresist, without compromising writing resolution. A diffraction limited lateral voxel width below 150 nm was demonstrated through ray tracing simulations and electron microscopy using standard polymer photoresist. Wrapped mode, like dip-in printing, is not limited by the objective working distance height. Its utility to prototype new print resists was validated through custom aqueous protein, silver nitrate, and black epoxy based formulations.
Ideal fs DLW modes are unlimited in attainable fabrication height and minimize optical abberations, while avoiding direct contact between photoresist and the objective (Fig. 1).In dip-in mode, the photoresist itself serves as immersion medium to allow for arbitrary build heights [8,24].Disadvantages are the need for suitable index matching of the resist, as well as the delicate and often time-consuming cleaning of the objective to not risk degrading the objective's sealings or coatings.This constrains permissive solvents in engineering novel photoresists, especially when nanocomposite, protein, or metal-deposition chemistry are used [19,[25][26][27][28][29].Alternatively, the laser is focused in immersion through a glass substrate into the photoresist (immersion mode).Here, new resist formulations can be tested by a simple swap of the substrate, but feasible fabrication heights are limited to below the working distance of the objective, and aberrations from polymerized resist reduce print quality.The growing demand for application-tailored photoresist formulations would hence benefit from an immersed printing mode that is no longer restricted in fabrication height.This was first achieved by locating the photoresist in a material vat held at a steady immersion, while the printing substrate is moved out of the vat during fabrication [30].Vat mode printing, however, may be difficult to implement on existing hardware.Also, writing objectives are typically not designed for use in a threefold material system of immersion, cover glass, and photoresist which limits the accessible print resolution.All these considerations motivated us to seek an alternative solution.
Fig. 1. Femtosecond direct laser writing modes. (A)
The writing objective is in direct contact with the photoresist in dip-in mode (left).While enabling large build heights, this configuration exposes the objective to the resist.In immersion mode (right), the objective is protected from contacting the photoresist directly by a cover glass and an immersion medium.However, feasible fabrication heights are limited to below the working distance of the objective.(B) Wrapped mode achieves large build heights without exposing the objective to the resist.A droplet of a standard immersion medium (oil or deionized water), a suitable foil, and an O-ring are assembled around the objective.The advantages of dip-in and immersion mode are thus combined in an inexpensive and easy-to-use approach.
Here, we present a wrapped fs DLW mode (Fig. 1(B)), where the objective is covered by a thin foil and secured in position with a suitable O-ring.This configuration keeps beam paths inside the immersion fluid and the protective foil very short in order to conserve printing resolution.It is simple to retrofit on any system by placing standard polyethylene (PE) kitchen cling foil, or more chemically resistant foils even with poorly matched refractive indices, onto the objective.As a result, any unconventional photoresist can be used in combination with arbitrary fs DLW writing objectives to achieve immersion-mode printing without limiting the fabrication heights by the objective working distance.For matched refractive indices of objective and photoresist, the print resolution is not compromised for a wide range of foil and immersion fluid refractive indices.PE, or if needed pre-sterilized or more solvent resistant foils, can thus facilitate fs DLW of resists that require sterility or harsh solvents.Used objectives are easy to clean as the foil can be directly disposed after printing.Conditions for diffraction limited wrapped mode resolution were assessed in optical simulations and experimentally confirmed.Finally, three custom photoresists were tested.
Simulations of wrapped writing mode performance envelope
Optical propagation (Fig. 2 ) was simulated in Zemax OpticStudio.The wavefront exiting from the writing objective was assumed to be perfectly spherical coming from a propagation medium matched to the refractive index of the photoresist (liquid IP-Dip, n = 1.512 at λ = 780 nm, T = 20 • C [31]).In accordance with our experiments and standard fs DLW configurations, especially Numerical Apertures (NAs) of 1.4 and 0.8 were assessed.The propagation was simulated at 780 nm, the laser wavelength of the 3D-printers used in our experiments (Photonic Professional GT & GT2, Nanoscribe GmbH & Co. KG).Next, we accounted for the gap between foil and writing objective as defined by the protruding objective mount edge and front lens.Confocal microscopy quantified this gap height to be 0-40 µm for our objectives (Table 1, experimental section).Immersion media for this gap were set to immersion oil (Zeiss Immersol 518 F, n = 1.509 at λ = 780 nm) or deionized water (n = 1.329 at λ = 780 nm, T = 20 • C).The subsequent PE foil (n = 1.544 at λ = 780 nm, obtained from [32]) was modeled as a 10 µm thin plate in accordance with confocal microscopy measurements.These parameters reflect the standard configuration also used in our experiments.Sensitivity analyses use this configuration as starting point.Once transmitted through the PE foil, simulated rays enter the photoresist and culminate in the focal spot.The Strehl ratio was evaluated from the Huygens point spread function (PSF) at the best focus position in z which was refocused per data point.Strehl ratios of 0.8 and higher were considered as diffraction limited performance.Simulations explored various objectives, immersion media, foil, and photoresist configurations for wrapped mode.First, the sensitivity to foil and gap thickness variations for different NAs was analyzed for both objectives (Fig. 2(B), (C).The high resolution NA 1.4 setup (config. 1) with almost perfectly matched media achieved a diffraction limited Strehl ratio of 0.897 (Fig. 2(B)).Thicker PE foils and higher objective NA had markedly degraded resolution.The poorly matched low resolution NA 0.8 oil objective (config.2) with water immersion in turn had a diffraction limited Strehl ratio of 0.981 (Fig. 2(C)).A wide range of NAs and water gap thicknesses achieved diffraction limited performance against a 10 µm PE foil.
The sensitivity to refractive index mismatches was compared between high NA 1.4 and low NA 0.8 objectives, with a 25 µm immersion gap and a 10 µm PE foil each (Fig. 3).Clearly, matching the objective wavefront to the photoresist is most critical and should not exceed ∆n = 0.005 for NA 1.4.Thus, similar to dip-in mode, photoresist and objective should be carefully matched for high NAs.Accordingly, our approach of protecting the objective is not designed to overcome this restriction and we refer to the use of objective lenses with immersion adjustment rings here.Optical performance, however, is very insensitive to index mismatches of foil and immersion medium and especially uncritical for the low NA 0.8 setup.Even at high NA 1.4, diffraction limited printing was maintained across a wide range of index mismatches due to the short beam paths which allows our approach to utilize almost arbitrary immersion fluids and foil material combinations.
Overall, we conclude from the simulations that thinner immersion gaps and foils achieved best performance, or in other words shorter beam paths are less sensitive to higher refractive index mismatches.Higher numerical apertures in turn require better index matching for experimentally convenient gap and foil thicknesses.
Experimental wrapped writing mode validation
Objectives were wrapped with low-cost kitchen cling foil (e.g.ALIO Frischhaltefolie, Wentus Kunststoff GmbH ) (Fig. 4(A)).First, the immersion medium was applied to the objective's front lens.Second, the foil was stretched onto a simple 3D-printed fixture (material: polylactide (PLA) filament, fused filament printer: Ultimaker 3, Ultimaker B.V.).Third, the stretched foil was lowered over the objective, until it covered the front lens mount tightly to form an air bubble free thin immersion film between both.This procedure also disposed excess immersion medium to the sides.The assembly was secured with an O-ring of suitable diameter, rolled over the objective before the foil was cut and the clamping fixture removed.Finally, the standard or experimental photoresist was applied to the wrapped objective, shielded from the objective's front lens by the thin foil.Detailed experimental configurations are given in Tables 1 and 2. Experimentally achieved lateral (∆x, ∆y) and axial (∆z) resolutions were identical when comparing wrapped mode with conventional dip-in mode across the objective field of view, as confirmed by comparing different writing field positions (Fig. 4).Woodpile scaffolds were printed from IP-Dip onto indium tin oxide coated substrates (both Nanoscribe GmbH & Co. KG), developed in propylene glycol methyl ether acetate , rinsed with isopropanol, and dried under nitrogen.After printing, the O-ring was removed from the objective to dispose the foil with excess resist.Residual immersion oil was cleaned or reused.Thin DI H 2 O immersion films quickly dried off without residuals.Resulting voxel dimensions were examined by scanning electron Fig. 4. Experimental wrapped mode assembly and resolution limit.(A) Immersion medium is placed onto the objective.A stretching fixture helps to place the foil and to secure it with an O-ring.After trimming the foil, the objective is ready for fs DLW.(B) Dip-in mode (left) and wrapped mode (right) resolution was assessed from fabricated woodpile structures via scanning electron microscopy, both in the writing field center (r = 0) and off axis (r = 156 µm and r = 250 µm) for oil immersion and water immersion with the 40x oil and 25x oil objective, respectively.See Table 1 and 2 for configuration details.
microscopy.The 40× oil, 1.4 NA high resolution achieved config. 1 lateral voxel diameters below 150 nm, suggesting diffraction limited performance in accordance with our simulations.Marginally thinner voxel lines for wrapped mode in the off-center writing field position indicate a slightly higher polymerization threshold in the field.Most importantly, however, achievable print resolution was maintained.The low resolution 25x oil, 0.8 NA objective water immersion config. 2 also achieved voxel dimensions similar to conventional dip-in writing, albeit at marginally higher laser powers.This polymerization threshold increase from the 8% dip-in control to 8.5% suggests an increase of the focal spot size, which however can be easily compensated through laser power adjustments.Both, simulated and experimental data confirm that our inexpensive approach to protect the microscope objective from contact with the photoresist can be readily implemented on existing fs DLW hardware with almost no performance loss across the full writing field of view.
To evaluate the utility of wrapped mode for developing new photoresists, we chose three alternative resist chemistries (Fig. 5).First, fs DLW bio-ink engineering was explored.Protein-based photoresist containing 25 wt% GM10, a gelatin derivative with a high degree of methacrylation, and 2 wt% LAP (lithium phenyl-2,4,6-trimethylbenzoylphosphinate) photo-initiator was prepared in phosphate buffer to print a geometry derived from in vivo mouse lung parenchymal tissue containing entire alveoli, as previously described [19].Resulting cell scaffolds fabricated in water immersion wrapped mode (25x water, NA 0.8 objective) were not distinguishable from dip-in control prints.The ease of replacing the wrapped mode foil reduces biological contamination risks and favors maintained sterile working conditions.Second, a 580 µm high rook was fabricated from highly absorptive IP-Black photoresist.Hence, fabrication of structures extending well beyond the working distance of the writing objective was feasible (210 µm working distance at 170 µm cover glass thickness 25x oil, NA 0.8 objective).Direct exposure in conventional dip-in mode would risk irreversible black stains on the objective's front lens.Conventional immersion mode printing in turn would not allow printing such a 580 µm high structure.Furthermore, continuously changing absorptive beam paths in the black photoresist would be problematic for polymerization threshold conservation in immersion mode printing.As a third example, we fabricated a silver wire grid from a water-based silver precursor (silver nitrate AgNO 3 , ammonia NH 3 , and a trisodium citrate NA 3 C 6 H 5 O 7 initiator [34]) in wrapped mode (40x water, NA 1.2 objective).Depositing a metal film onto an unprotected objective lens in conventional dip-in mode may cause irrevocable damage to the objective, a risk that is highly reduced in wrapped mode.
Conclusion
In conclusion, wrapped writing mode combines the strengths of immersion and dip-in mode fs DLW printing: protecting the objective while maintaining a diffraction limited resolution without working distance limitations.It is simple and inexpensive to implement, has an extensive performance envelope, and is hence ideally suited to spur future photoresist development efforts.
Fig. 2 .
Fig. 2. Simulations of the diffraction limit in wrapped writing mode.(A) Simulation configuration: The objective wavefront was assumed to be perfectly spherical.Immersion gap and PE foil were defined as plane parallel plates and the Strehl ratio was analyzed in the focal point.(B) Strehl ratios simulated for oil immersion and different PE foil thicknesses at a fixed immersion gap thickness of 0.2 µm.A white dotted line delineates diffraction limited performance before writing resolution degrades at higher NA and foil thickness.(C) Strehl ratios for deionized water immersion and different gap thicknesses at a fixed PE foil thickness of 10 µm.Experimentally realized configs. 1 (40x) and 2 (25x) project diffraction limited performance.
Fig. 3 .
Fig. 3. Sensitivity to refractive index mismatches for an objective lens matched to n = 1.512 immersion (simulations).Strehl ratios were evaluated for exemplary high NA 1.4 and low NA 0.8 objectives for a 25 µm immersion gap and a 10 µm PE foil.Refractive indices were varied one at a time for the photoresist, the immersion medium, and the foil, respectively.For each variation, all other refractive indices were set to their standard configuration values given in the text and indicated with blue dashed lines in the graphs.
Fig. 5 .
Fig. 5. Wrapped mode application examples with custom photoresists.(A) Brightfield micrograph during fabrication of a 3D cell scaffold from aqueous protein photoresist (config.3).(B) Micrograph of a developed 580 µm high rook printed from IP-Black prototype resist (config.4).(C) Electron microscopy of a metal wire grid printed from aqueous silver precursor (config.5).CompareTable 1 and 2 for detailed print configurations.
Table 2 . Overview of printed structures with wrapped fs DLW mode. Respective objective and immersion configurations are listed in Table 1.
Table 1 and 2 for detailed print configurations. | 3,242.4 | 2022-08-08T00:00:00.000 | [
"Engineering",
"Materials Science",
"Physics"
] |
Nonwoven polypropylene prosthesis in large abdominal wall defects in rats 1 Tela de polipropileno sem tecelagem na correção de grandes defeitos da parede abdominal em ratos
PURPOSE: To evaluate, in large abdominal wall defects surgically shaped in rats, if a synthetic polypropylene nonwoven prosthesis could be used as a therapeutic option to conventional polypropylene mesh. METHODS: Twenty four (24) Wistar rats were enrolled into three groups. Group 1 (Simulation group) with an abdominal wall defect of 3 X 3 left untreated and Groups 2 and 3, respectively treated with a conventional polypropylene mesh and a polypropylene nonwoven (NWV) prosthesis to cover the breach. At the 45th postoperatively day, adhesion (area and strength) and vascularization of Groups 2 and 3 were evaluated. The histological preparations with Hematoxylin-Eosin, Tricromium of Masson, Pricrosirius red and polarization with birefringence, and also the structural analysis of the prostheses carried on by Thermogravimetry and Differential Scanning Calorimetry were also assessed. RESULTS: There were no significant differences between the Groups 2 and 3. CONCLUSION: In rats, the polypropylene nonwoven prosthesis showed to be safe and has to be considered as an alternative to conventional mesh manufactured by weaving in the treatment of great defects of the abdominal wall.
Introduction
Surgical repair of major congenital or acquired defects of the abdominal wall such as the incisional hernias and certain congenital diseases represents a major challenge for surgeons.
Significantly, the clinical condition of the patient is often adverse and there exists no comparative studies with high clinical and epidemiological evidence to validate one surgical procedure as a golden standard.Often, the biological tissue from the individual patient is used.Alternatively, synthetic material is used with several options available, all based upon evolving scientific and technological advancement.
Reconstruction with pedicle flaps of aponeurosis or muscles like latissimus dorsi, rectus femoris and fascia lata can avoid complications encountered with synthetic material, especially the reaction of foreign body or rejection of the material 1,2 .
However such management often requires the presence of a plastic surgeon in addition to the general surgeon in the operating room.
Moreover, biological materials placed as graft or pedicle flaps may generate new defects in the wall of donor sites.It is estimated that approximately one million implants per year are placed globally for abdominal wall defects correction 3 .Polypropylene monofilament is the most common, yet it must be emphasized that in developing countries such as Brazil, a mesh of 30x30cm costs from US$ 145 (Marlex ® ) to US$ 380 (Prolene ® ).The need to fix major wall defects with prostheses creates a common problem in developing countries and most third world nations.In these countries, and especially in rural areas of such countries where health care infrastructure is not integrated into major population centers, health care systems have budget constraints for the purchase and distribution of imported material.Nevertheless, this problem is not restricted to less privileged population.In Brazil, for instance, the insurance plans and health care systems in general do not allow for reimbursement of prostheses and, therefore, patients must acquire it with their own resources.Thus, whether in public or private health care, patients who cannot afford prostheses purchase usually have their surgeries postponed, with a higher risk of complications and an associated increase of hospital expenses.
The polypropylene used in this study, known as nonwoven, or tecido não tecido (Portuguese), tejido notejido (Spanish), tessuto nontessudo (Italian), tissé nontissé (French), vliesstoffe (German), represents a cheaper alternative with a price level around one dollar and a half (USD), for a size of 60 x 60 cm.The structure of the polypropylene is flat, flexible, continuous, autoclavable, without pores or weft filamentary and with the innovation in the union of the filaments by thermal polymerization process, without weaving.This material has been produced for decades on an industrial scale, and has multiple applications, such as the production of: sheet, soap packaging, inner packaging of shoes (20g/m²) aprons for patients, hats, masks, shoes, protective head seats for airplanes, pillow cases, operative field (30g/m²), pants, mask type duck-billed filters (40g/m²), amongst other applications with greater weight.
This study therefore aimed to evaluate, in large abdominal wall defects in rats, the viability of placement of a synthetic polypropylene nonwoven prosthesis which has a low cost and is easily affordable as an alternative to conventional polypropylene mesh that is widely used as first choice but much more expensive, especially for public health care.
Methods
This study was approved by the Ethics Committee for Use of Laboratory Animals in Research, Education and Extension of Federal University of Rio de Janeiro (UFRJ), registered under number 75/08, according to Brazilian law for animal research and the international standards and guidelines.
The study used 24 female Wistar SPF (free pathogenic species), rats (Rattus norvegicus albinos, Rodentia mammalia), three months old and weighing approximately 200g.The animals came from the Center for Experimental Surgery, Faculty of Medicine Federal University of Rio de Janeiro, where they were housed in environmentally controlled conditions.The animals had free access to food (trade pattern), and water.
The animals were randomly divided into three groups of eight rats each.Group 1 was the Simulation group and went without prosthesis.In Group 1, after a midline abdominal incision 5 cm long, starting 2 cm from the xiphoid process, compromising the skin and subcutaneous tissue, a traumatic defect of the anterior musculoaponeurotic wall and the peritoneum was introduced, covering an area with 3 x 3 cm.The surgical intervention was finished with the synthesis of the skin over the parietal failure with a monofilament nylon 2.0 suture with separate stitches in "x" shape.In Group 2, a synthetic industrial and conventional woven mesh of polypropylene monofilament, macro-heavy, (originally 15 centimeters long by 15 centimeters wide) was used.A traumatic defect in the anterior wall of the abdomen was introduced, similar to Group 1, and a 3 x 3 cm prosthesis was attached to the abdominal wall by a running suture with monofilament polypropylene 3.0, making sure to cover around the entire abdominal defect.Skin synthesis completed the surgical procedure at the same manner described for group 1.In Group 3, a synthetic polypropylene nonwoven prothesis (NWV), weighting 40g/m 2 , with white color was implanted.The material was first cut in the standard size (3 x 3 cm), packed in paper Kraft ® and then sterilized by autoclaving at a temperature of 134°C for 12 minutes at one atmosphere (ATM).
The same surgical abdominal close procedure seen at Group 2 was followed.
Postoperative analgesia with dipyrone (50mg/kg/day), diluted in water was applied for a period of five days.Monitoring consisted of daily inspection of the appearance of the wound searching for hematoma, seroma, local infection, skin dehiscence, evisceration, enventration, incisional hernia, strangulation or death.
At the 45th postoperatively day, the animals were induced to death by sodium thiopental administered intraperitoneally in order to remove fragments of the musculoaponeurotic anterolateral wall of the abdomen, including the prostheses areas (Groups 2 and 3) or surgical scar (Group 1/Simulation).At this time, the presence of any adhesions or other gross intra-abdominal changes such as abscess, volvulus, stenosis, ischemia or necrosis and peritoneal surface vascularization was recorded.(Table 1).
Samples were photographed after cover the abdominal surface with a transparent plastic with square millimetric lines.The results were analyzed with the software Image Pro-Plus Ò , version 2), and characteristics of the granuloma with a grade score from 0 to 3 (absent, exsudative, with predominance of macrophages and epithelioid cells and fibrotic) 6 .
Results
In the first 24 hours surgical wounds were intact in all groups but there was one death in Group 1(Simulation).Seven animals of Group 1 developed ventral hernia after the surgical procedure over the abdominal wall (Figure 1) however, at 48 hours of postoperative period, there was one wound dehiscence.
At 72 hours three other dehiscences were noted, one in Group 3 (nonwoven prosthesis) and two in Group 2 (conventional mesh of polypropylene) with infection associated in one of them.These five rats were excluded from the study.No hematoma, seroma, intracavitary abscess, volvulus, ischemia or necrosis was observed.In Group 1 (Simulation), with respect to the total area of adhesion, all rats had the median score of 1.
Table 3 shows the measurement of the areas of adhesion between intraabdominal structures and the peritoneal surface of the abdominal wall (Figure 2).Significant differences were observed when both group 2 and 3 data were compared with group 1 and with each other (p<0.05).Scores obtained for each animal seen in Table 3 were summarized in Figure 3.All animals of both Groups 2 and 3 showed inflammatory reaction such as a strange body with giant cells, granuloma formation, without significant differences (Figures 4 and 5).In the Simulation Group (Group 1) all were scored as 1.In Group 3 the connective tissue proliferation with fibrosis was the same observed in group 2 (Figure 6).At thermogravimetry the polymer of Group 2 showed a beginning of decomposition at 439ºC and peaked at 457ºC with residual difference of 0.05% (Figure 7).The Group 3 polymer (before autoclaving) procedure revealed the start of decomposition at 435ºC and reached a maximum value at 456ºC, with residual difference of 2%.After autoclaving (Group 3), the results were respectively at 339ºC for the beginning of the decomposition with a peak at 390ºC and a decrease of residual decomposition to 1.5% (Figure 8).161ºC, beginning at 156ºC and heat fusion at 132.4 J/g (Figure 9).The third group polymer presented in the first heating curve one shoulder and two coalescent peaks.The third group freezing curve was started at 119ºC with a peak at 115ºC and heating of crystallization at 101.1J/g.The second heating showed one peak and one shoulder (conversion of the second peak) with a major peak at 157ºC with fusion heat at 92.66 J/g (Figure 10).
Discussion
Treatment of abdominal wall hernias is the most common surgical procedure performed.The physiopathological mechanism consists of weakness of the aponeurosis which creates a local muscular dystrophy or dysmorphisms.Surgical approach is the main cause of large hernias but there exist several others predisposing factors 7 .Congenital anomalies such as gastroschisis and onphalocele are two other relevant wall defects.
Dubay et al. 8 mentioned more than 400.000 cases of incisional hernia diagnosed per year in the United States.These hernias are more common in the first two years after surgery with an incidence of 11 to 20% and risk of incarceration of 25% and strangulation of 8% to 10% 9 .When diagnosed, surgical correction with closure of the parietal defect by reducing the hernial content is recommended, but the reoccurrence of these defects is noted in up to 40% of cases.The repair of large abdominal ventral hernia is still a challenge and in most cases, effective treatment demands a preoperative preparation and the use of prostheses.
Whereas there are many synthetic materials available to fix parietal hernias, there exist few attractive options, especially in the public hospitals.The authors of this experimental research studied a kind of prosthesis similar to a synthetic mesh, cheaper and easily available in the market and even in hospital stock room, that could both be used safely and offer a viable alternative to the treatment of large abdominal wall defects.
The rat was selected as experimental model because it has muscular and aponeurotic parietal layers very similar to human beings.Furthermore, because the animal species used are quadrupeds, their movement increases the pressure placed on prosthesis or mesh in a way much more active than in anima nobile.
The anesthetic protocol applied consisted of the use of ketamine, xylazine and atropine, similar to other experiments.The anesthetic protocol applied provided good analgesia and adequate time to perform the procedure 3,5,10,11 .Euthanasia was induced with a sodium thiopental by intraperitoneal, similar to the method used by Cobb et al. 12 .
Chatzimavroudis et al. 11 , instead of cutting and removing part of muscle and aponeurosis of the abdominal wall, have opted for a large incision in the linea alba with posterior fixation of the mesh.However, this approach does not create a major gap capable of simulating a clinical context of a large incisional hernia with parietal weakening, muscle atrophy or displacement of the aponeurosis.Therefore, the applicability of this model is limited especially concerning to an early formation of ventral hernias.
The synthesis of the skin over the muscularaponeurotic failure in a square shape was effective to create a model of ventral hernia.The Simulation Group (Group 1) showed herniation early in all animals which confirmed the effectiveness of the model.
The treatment of major defect in the ventrolateral abdominal wall usually requires the use of prostheses.Many techniques have been described to minimize the wall tension and to prevent ischemia, disruption of the sutures with recurrence of hernia, eventration or evisceration 13 .Therefore, the decision to place a prosthesis over the large iatrogenic defect in the ventral abdominal wall of rats aimed to mimic a clinical situation.
Significantly, the implant needs to be attached to surrounding tissues with sutures.In the absence of such a procedure, the edges of the implant could bend and the prosthesis may well suffer shrinkage or detachment, leading to a predictable recurrence.
It was observed, as a result of the quadruped posture in animals with short distance between body and paws, that there was constant friction of the abdomen of the rats with the bottom of the cage where they were housed.It causes ischemia and consequently wound dehiscence and exposure of the prostheses as seen in four animals from all groups.Furthermore the rodents usually attempt trying to remove, with their teeth or feet, the foreign bodies (wires and knots).Obviously, these conditions predisposed the wound to infection, seen in one animal of Group 2, but without systemic complications.It should be noted that the NWV prosthesis was previously sterilized in an autoclave and its manipulation took place under aseptic conditions.The one death seen just after the first 24 hours was not associated with the infection but occurred as a consequence of respiratory distress due to the anesthesia procedure.
Ansaloni et al. 13 reported that the infection accelerates the degradation of certain prostheses which could lead to failure of the treatment.Abscesses, enteric fistulas, and eventually elimination of the material with formation of incisional hernias discourage the use of certain meshes in the presence of infection 14 .
Even taking into consideration that the absence of pores in the fabric of NWV prosthesis made of monofilament fibers (unlike multi-filament or pored materials), is less likely to harbor bacteria, no significant differences between the three groups was noticed regarding infected wound dehiscence.
Considering that some parameters evaluated (adhesion and vascularization) may suffer from interpretation bias in the presence of parietal dehiscence or infection with prosthesis exposure or not, all animals with such findings were taken aside from the research.
The conventional polypropylene mesh (Marlex ® ) placed in Group 2, is the most widely prosthesis used for correction of abdominal wall defects.This material has excellent biocompatibility, mechanical stability and elasticity, low tendency to degradation, good integration to the surrounding tissue with the formation of a strong scar tissue and a low susceptibility to infections 15,16 .The NWV prosthesis is composed of the same polymer of Marlex ® mesh but it is not manufactured by a weaving process.Instead, the fibers are joined by heat, which produces a nonwoven fabric.The prosthesis is smooth, has white color, does not fade, has a similar thickness of a sheet of paper and is highly flexible and resilient.It has been used increasingly, with various weights and with amazing applicability.The choice of NWV prosthesis with a weight of 40g/m² was done to demonstrate the application of using a material that was easy to access and handle, extremely flexible and cost effective.This material is the same used in hospital masks and surgical aprons.It is suitable to be shaped in different sizes without difficulty and may be cut with common scissors.Cobb et al. 12 and O`Dwyers et al. 17 The effectiveness, however, is still controversial because of an observed rate of hernia recurrence similar to conventional mesh 18 .
The polypropylene is not indicated to be in contact with the peritoneum considering the formation of firm adhesions 5,11 .
It is noteworthy that development of adhesions is inevitable and independent of the material used 14 .This is due to foreign body reaction but may be exacerbated by the access route, the method for setting the mesh, the visceral or parietal peritoneum desperitonization 5,15 and the presence of infection.Intra-abdominal adhesions can be classified in terms of area, expressed as percentage of the prosthesis covered by the adhesion and the force of adhesion, and the presence or absence of vascularization as described in table 1 2,5,9,14 .
In our study, one animal from the Simulation Group (Group 1) had a score of 4 for area and of 3 for strength but we postulate the cause may well be due to some disperitonization during visceral manipulation.Subjects in Groups 2 and 3 presented some adhesion and vascular growth over the adherent tissue but, considering the area and the adhesion force, differences were not statistically significant between the two Groups (p<0.05).The presence of vascularization indicates the existence of a healing wound in progress, and provides a substrate for deposition of fibroblasts and collagen.Kiudelis et al. 5 reported data similar to our results.
It is known that mesh with micropores or without pores causes fewer adhesions than those with macropores.Our results showed that the absence of pores in the NWV prosthesis did not contribute to the reduction of adhesions.
Amongst the structures that most often adhere to the mesh/prosthesis are the greater omentum and the small intestine as observed in Groups 2 and 3.In an attempt to minimize these problems, some surgeons choose to avoid placing the mesh directly in contact with the viscera and interpose part of the hernial sac, peritoneum or omentum 5,14,15 .
The presence of a synthetic prosthesis increases the risk of complications in the host site such as stiffness, hematoma, seroma, pain, adhesions, abscess or wound infection, mesh shrinkage, intestinal obstruction, fistulas visceral, dehiscence of skin suture, rejection, among others 10,14,[18][19][20][21] .A prosthesis not incorporated or rejected is usually involved in a foreign body reaction.Encysted fluid collections may be manifested under the surgical scar as a benign tumor.Some authors report that mesh without pores reduces the dead space between the tissue and is associated with a lower risk of seroma formation 10,18 .Over time, these serous collections initially aseptic drains to the skin, through a "sinus", and may become infected and purulent contributing to dehiscence of the overlying tissue with partial or full exposure of the prosthesis 21 .The accumulation of serous or blood collections around the prosthesis is frequently observed, especially when the implants are large and associated with extensive areas of detachment.These liquids hinder integration and prevent the arrival of the polymorphonuclear neutrophils, which results in a culture medium.The prophylactic use of antibiotics in reoperations on a prothesis site is indicated to reduce the risk of local infection.In such cases, the partial or total withdrawal of sequestered prosthesis is often required and it demands laborious surgery with risk of other and perhaps more severe complications 21 .In our experiment, no animal showed seroma and the complications seen were the presence of dehiscence and infection in animals excluded from the sample group and the planned incisional hernia in the Simulation Group.
Other studies show that inflammatory response following implantation of light prostheses are significantly smaller than in conventional or heavy meshes, except when the prostheses are lightweight and nonwoven.In such cases, the inflammation is more intense than in the application heavy prostheses 10,18,19 .There exists a lack of studies comparing heavy with light prostheses structures, woven with nonwoven and macro with micropores.Weyhe et al. 10 and Dubova et al. 19 studied the inflammatory response of rats subjected to abdominal wall reconstruction with polypropylene mesh at different intervals of postoperative days.One group received a woven polypropylene heavy mesh with macropores, and the other received a nonwoven fabric, light, with micropores.
Although Dubova et al. 19 agree with Weyhe et al. 10 about the more severe inflammatory reaction which occured in the group of nonwoven fabrics, but they disagree with regard to fibrosis.
Dubova et al. 19 , at the end of the experiment (28 days), reported a less intense fibrosis in nonwoven fabric and attribute this to the fact that the fabric does not have a net, allowing a tissue growth upon a uniform surface.Weyhe et al. 10 found that the differences between the two groups began to decline over time, but until 21 days after surgery they were not statistically significant.However, after 21 days, the concentration of inflammatory cells began to decline in both groups.At 90 days after surgery a decrease in the group of heavy mesh was observed as more significant than in the light ones.In our results the inflammatory reaction in both Groups 2 and 3 was similar (p=0.10).Fibrous tissue covered both kinds of prostheses after 45 days but such scarring process was a little bit intense in Group 3 than Group 2 in comparison with Group 1 of animals.This may be related to the greater collagen proliferation but no statistical differences was found between Groups 2 and 3 (p=0.23).
We emphasize that interpretation of the results has to be considered with caution because of the small sample size.Klinge et al. 3 and Cobb et al. 12 argue that the higher the weight of the prosthesis, the greater the amount of synthetic material and, therefore, the greater likelihood of the presence of inflammatory foreign body.The formation of giant cells and proliferation of connective tissue between the pores are common finding in the microscopic implants of polypropylene 1,3,11 , but no differences were observed between groups 2 and 3, respectively, with heavy or light screen.
Thermogravimetry is one of the tools used to determine whether sterilization in the autoclave would alter the physical properties of polypropylene or melt the synthetic material.
Marlex mesh was sterilized by ethylene oxide.There were no relevant differences between the temperatures at the beginning of decomposition of Group 2 (439ºC) and Group 3, post-autoclaving (339ºC).The temperature of any autoclaving process never goes above 132°C and therefore there is no risk of overlap the prosthesis melting point which can be easily sterilized.Differential Scanning Calorimetry (DSC) is a technique of thermal analysis of differences in materials or tissues under linear variations of temperature, in a controlled environment.It allows checking the structural stability under isothermal exposure.
Polymer of Group 2 was more crystalline than that of Group 3 but this feature does not interfere with the resistance of the non woven fabric because fibrosis itself is sufficient to give parietal protection and to substitute the function of the original tissue.
The amount spent on getting the NWV prosthesis was half a dollar/m 2 , while the polypropylene conventional costs an average of US$ 140/m 2 (almost 300 times greater).It should be noted that the industry offers to purchase meshes of woven polypropylene, 30cm x 30cm, at a cost of approximately US$ 900.This is roughly a hundred times the amount spent on acquisition of the prosthesis used in Group 3 of our study.NWV prosthesis is a material of everyday use in hospitals, found in a series of disposable items and, as already mentioned, autoclaving NWV prosthesis does not alter its composition or structure.
Further studies in anima nobile must be done before its surgical indication but this experimental research endorses its alternative use, especially in remote locations where there are no facilities or resources available to purchase or import conventional woven meshes, such as public hospitals.This is an unprecedented proposal to using a substitute material for conventional meshes in surgical repairs of ventral incisional hernias.
Conclusion
The polypropylene type of nonwoven prosthesis showed a satisfactory cost-effectiveness in the treatment of large abdominal wall defects in rats.
4
Impenetrable like a block of adherences containing solid organ, peritoneum and omentum 76 -100% of the prosthesis area covered by the adhesion ----------Adhesions (strength and size) or presence of vascularity were classified according to an adaptation of the semiquantitative scoring systems used by Jenkins 4 , Kiudelis and collaborators5
4. 5
in order to estimate the total area of the implant covered by adhesions.For each group the sum of individual scores was performed.Statistical comparisons between group averages were made by Student t test considering the distribution of the samples with standard Gaussian graph, according to the Kolmogorov-Smirnov test.The scores of adhesion strength and vascularity were analyzed by the Mann-Whitney and the results considered significant for p<0.05.The samples were fixed in 10% formalin and the prepared sections stained with hematoxylin-eosin (HE), Picrosirius red and Tricromium of Masson for the general evaluation of the inflammatory response, vascular fibrosis, adapted from Soiderer et al. 1 (Table Large aggregates and numerous cells in the prothesis Half of the thickness of the prosthesis Continuous in the subcutaneous tissue with little tissue between the conjunctive fibers 4 -massive Pronounced inflammatory infiltrate More than half of the thickness of the prothesis Continuous in the subcutaneous tissue with abundance of connective tissue between the conjunctive fibers Histopathological examination was accomplished with the study of five to 20 cells per field with 100 or 160 times magnification.For photomicrography, a Nikon microscope was used (LABOPHOT-Pol of the Service of Clinical Pathology, University Hospital Clementino Fraga Filho -UFRJ).The polymers of the two prostheses were compared using the tests of Thermogravimetry (TG) and Differential Scanning Calorimetry (DSC), respectively, using TGA-DSC Q 500 and Q-1000 (dp UNION, BRA).Furthermore, a Transform Infrared Fourier, with the device Varian 3100 FT-IR Excalibur Series was used.These tests were performed in the laboratory at LAPIN-IN, Institute of Macromolecules, COPPE -UFRJ.The scores were analyzed by the Mann-Whitney and the results considered significant for p<0.05.
FIGURE 1 -
FIGURE 1 -The iatrogenic ventral hernia is easily seen as a protrusion in the abdomen of the rat.
FIGURE 2 -
FIGURE 2 -The irregular area inside the circle delineates a peritoneal surface covered by adhesions.
FIGURE 4 -
FIGURE 4 -Granulomatous reaction in Group 2, comprising the fibers of the mesh (A), associated with moderate fibrosis (B) and adherence to the intestinal wall (C).Tricromium of Masson 160x.
FIGURE 5 -
FIGURE 5 -Note numerous collagen fibers (arrow) birefringent with the polarized light amongst the fibers of the mesh (Group 2), featuring moderate fibrosis.Picrosirius red 160x.
FIGURE 6 -
FIGURE6 -The presence of fibrosis analyzed in all groups by the Mann-Whitney with 95% of confidence interval.There were no statistical differences comparing Group 2 with 3.
FIGURE 7 -
FIGURE 7 -Thermogravimetry of Group 2 showing the beginning of decomposition and the peak value.
FIGURE 8 -
FIGURE 8 -Thermogravimetry of Group 3 also showing the beginning of decomposition and the peak value.
FIGURE 9 -
FIGURE 9 -Differential Scanning Calorimetry of Group 2 (Conventional mesh).The bottom curve represents the fusion curve.In the middle the crystallization point and peak.At the top of the graph is the second heating with a peak of fusion.
FIGURE 10 -
FIGURE 10-Differential Scanning Calorimetry of Group 3 (Nonwoven prosthesis).The bottom curve represents the first heating curve.In the middle the crystallization point and peak.At the top of the graph is the second heating.It was observed no significant differences to Group 2.
stated the advantages of such lightweight fabrics which are well adapted to the host site with minimal traction and less restriction of abdominal movements.They also reduce pain in the postoperative evaluation.
TABLE 3 -
Statistical data of area of adhesion (cm 2 ).
N-Number of animals of each group, Min-Minimum area of adhesion, Max-Maximum area of adhesion, SD-Standard deviation, SE-Standard error | 6,389.6 | 2012-10-01T00:00:00.000 | [
"Medicine",
"Materials Science"
] |
Evaluation of Various Scintillator Materials in Radiation Detector Design for Positron Emission Tomography (PET)
The performance of radiation detectors used in positron-emission tomography (PET) is determined by the intrinsic properties of the scintillators, the geometry and surface treatment of the scintillator crystals and the electrical and optical characteristics of the photosensors. Experimental studies were performed to assess the timing resolution and energy resolution of detectors constructed with samples of different scintillator materials (LaBr3, CeBr3, LFS, LSO, LYSO: Ce, Ca and GAGG) that were fabricated into different shapes with various surface treatments. The saturation correction of SiPMs was applied for tested detectors based on a Tracepro simulation. Overall, we tested 28 pairs of different forms of scintillators to determine the one with the best CTR and light output. Two common high-performance silicon photomultipliers (SiPMs) provided by SensL (J-series, 6 mm) or AdvanSiD (NUV, 6 mm) were used for photodetectors. The PET detector constructed with 6 mm CeBr3 cubes achieved the best CTR with a FWHM of 74 ps. The 4 mm co-doped LYSO: Ce, Ca pyramid crystals achieved 88.1 ps FWHM CTR. The 2 mm, 4 mm and 6 mm 0.2% Ce, 0.1% Ca co-doped LYSO cubes achieved 95.6 ps, 106 ps and 129 ps FWHM CTR, respectively. The scintillator crystals with unpolished surfaces had better timing than those with polished surfaces. The timing resolution was also improved by using certain geometric factors, such as a pyramid shape, to improve light transportation in the scintillator crystals.
Introduction
Positron emission tomography (PET) has become commercially available with successful applications in oncology, cardiology and neurology [1,2]. The radiation detector is the core component of any PET system; its performance (timing resolution, depth of interaction measurement, light output, decoding accuracy) determines the performance of the PET system [3][4][5][6]. There are continuous efforts to improve the spatial resolution, sensitivity and signal-to-noise ratio (SNR) in the reconstructed PET images since improvements in these characteristics could significantly facilitate the clinical and preclinical applications of PET imaging [7][8][9][10][11][12].
The SNR in conventional PET images are limited by the sensitivity of the scanner. There are two strategies to improve the sensitivity of a PET scanner. The first strategy is to increase the geometric sensitivity of the scanner by increasing its axial extent to achieve total body coverage [13][14][15][16]. This strategy not only improves sensitivity, but it also allows the collection of metabolic and chemical target information simultaneously from multiple organs in the body, such as the brain, lungs, heart, liver and kidneys. The second strategy is to incorporate the additional time-of-flight (TOF) information into the reconstruction to increase the effective sensitivity and SNR in the reconstructed images [9,10,17].
The timing resolution of a PET system is largely determined by the performance of the individual detector modules. Many factors may affect the timing resolution of the detector modules, including the structure of detector [18][19][20][21][22], the properties of the scintillator crystal (luminosity and decay time) [23,24]; the optical properties (refractive index and optical attenuation length) of the light guides and coupling materials (air, Meltmount TM , optical glues, etc.) [25]; the surface treatment of the scintillator crystals and light guides (saw-cutting, chemical etching and mechanical polishing to varying degrees); the optical reflectance properties (specular and/or diffuse reflection and spectral reflection coefficient) of the reflectors (Teflon tapes, ESR films, Lumirror films, Tyvek papers, titanium dioxide paint, multilayer dielectric high-reflector coating, etc.); the electric and optical characteristics of the photon detectors (photon detection efficiency, size and fill factor, etc.) [26]; and the performance of the readout electronics (bandwidth, slew rate, signal-noise ratio, etc.) [27,28]. Photonic crystals can change the propagation path of scintillation photons by adding microstructures on the crystal surface, thus improving the time and energy performance of PET detector [29].
Enabled by the developments of lutetium oxyorthosilicate (LSO) and lutetium-yttrium oxyorthosilicate (LYSO) scintillators, all three major PET manufacturers have introduced commercial TOF PET cameras that achieve 200~600 ps full-width half-maximum (FWHM) coincidence timing resolution (CTR). Many studies have indicated that a sub-100 ps CTR is achievable. However, there is no literature reported clinic PET systems with a timing resolution better than 200 ps yet.
In order to help break through the barrier, we have performed extensive experimental studies to assess the CTR of PET detectors constructed with samples of different scintillators from different vendors that were fabricated into different shapes with various surface treatments. The basic reasoning of the approach chosen in this study is that the CTR is a function of the photon density detected in the initial moment of an event [20][21][22]. Hence the CTR can be improved through the enhancement of the light collection efficiency by optimizing the geometry and surface treatment of the scintillator. This article not only describes these studies in much greater detail than we previously presented at the IEEE Nuclear Science Symposium and Medical Imaging Conference [30], but also analyzes the experimental data in depth and compares the performances of the detectors constructed with various scintillator materials, vendors, shapes, surface treatments and silicon photomultipliers systematically. Practical conclusions are drawn, based on the in-depth analyses and the systematic comparisons of the experimental data, to provide a useful guidance to the design of PET detectors with high timing resolution.
Type of Scintillators
Twenty-eight pairs of scintillators with various types, sizes, shapes, surface treatments, and manufacturers were tested for the CTR, light output and energy resolution. Six different types of scintillator cuboids-including LYSO (Suzhou Jtcrystal, JTC), LFS (Zecotek), LSO (Siemens), GAGG (Kinheng), LaBr 3 (Saint Gobain, SG) and CeBr 3 (SG)-with various sizes were tested. The coupling surface of the scintillator cubes was polished and the other surfaces were unpolished. As shown in Figure 1a, the scintillators were mounted to the center of two SiPMs (MicroFJ-60035-TSV, SensL) with MeltMount optical glue (refractive index: 1.53). The 6 mm LaBr 3 (Saint Gobain, SG) cube and 2 mm GAGG (Kinheng) cubes are shown in Figure 1b,c. The parameters and labels of those crystals are listed in Table 1.
Crystals 2020, 10, x FOR PEER REVIEW 3 of 16 surface of the scintillator cubes was polished and the other surfaces were unpolished. As shown in Figure 1a, the scintillators were mounted to the center of two SiPMs (MicroFJ-60035-TSV, SensL) with MeltMount optical glue (refractive index: 1.53). The 6 mm LaBr3 (Saint Gobain, SG) cube and 2 mm GAGG (Kinheng) cubes are shown in Figure 1b,c. The parameters and labels of those crystals are listed in Table 1. Eight pairs of LYSO crystals were tested to study the timing resolutions for different sizes and surface treatments. These "label LYSOA" crystals were made of co-doped LYSO: 0.2% Ce, 0.1% Ca provided by JTC. The parameters of the 4 mm and 6 mm cubes (LYSOA-4 and LYSOA-6) are listed in Table 1. The parameters of the other six sample LYSOA crystals are listed in Table 2. These "sample LYSOB" crystals were made of co-doped LYSO: 0.1% Ce, 0.1% Ca provided by JTC. Samples LYSOA and LYSOB were used to compare the timing resolutions of the scintillators with different-doped values, when comparing crystals with the same shape and size (LYSOA-4 to LYSOB-4, LYSOA-6 to LYSOB-6).Similarly, samples LYSOA-6 (LYSOA-4) and LYSOP-6 (LYSOP-4) Eight pairs of LYSO crystals were tested to study the timing resolutions for different sizes and surface treatments. These "label LYSOA" crystals were made of co-doped LYSO: 0.2% Ce, 0.1% Ca provided by JTC. The parameters of the 4 mm and 6 mm cubes (LYSOA-4 and LYSOA-6) are listed in Table 1. The parameters of the other six sample LYSOA crystals are listed in Table 2 were used to compare the timing performance of the crystals of different surface treatments. When testing these 6 mm crystal cubes (LYSOA-6 and LYSOP-6), the bias voltage and trigger level added to the Sensl SiPM ranged from 26 V to 32.5 V and 20 mV to 140 mV, respectively.
Shape
Scintillation crystals were fabricated into different shapes (cubes, cuboids, pyramids and frusta) to investigate the effects of geometric shapes on the detector performance. Cuboid-shaped crystals have the disadvantage of requiring most of the photons to be reflected multiple times before being absorbed by the photodetector, which can reduce timing resolution. Therefore, we also designed and tested some crystals with a pyramid shape. The scintillating photons reflected from the pyramid surface will change their flight angle and emit directly to the coupling surface, which may increase the light output and improve timing resolution. Similarly, scintillating photons in a crystal with a zigzag slope may also be reflected by the slope and directly emit to the coupling surface. Table 3 shows the parameters of the six odd-shaped scintillation crystals, where LYSOP indicates the pyramid-shaped crystal, LYSOH indicates the crystal with a pyramid-shaped top, LYSOF indicates a frustum-shaped crystal, LYSOT indicates a pyramid-shaped top crystal with a sawtooth surface and LYSOTP indicates the crystals with two pyramids. Figure 3a,b show the pictures of LYSOF-6, LYSOH-6, LYSOP-4 and LYSOT-6 and LYSOTP-6 crystals, respectively. Figure 4 shows the design dimensions of various shaped crystals. These "sample LYSOB" crystals were made of co-doped LYSO: 0.1% Ce, 0.1% Ca provided by JTC. Samples LYSOA and LYSOB were used to compare the timing resolutions of the scintillators with different-doped values, when comparing crystals with the same shape and size (LYSOA-4 to LYSOB-4, LYSOA-6 to LYSOB-6).Similarly, samples LYSOA-6 (LYSOA-4) and LYSOP-6 (LYSOP-4) were used to compare the timing performance of the crystals of different surface treatments. When testing these 6 mm crystal cubes (LYSOA-6 and LYSOP-6), the bias voltage and trigger level added to the Sensl SiPM ranged from 26 V to 32.5 V and 20 mV to 140 mV, respectively.
Shape
Scintillation crystals were fabricated into different shapes (cubes, cuboids, pyramids and frusta) to investigate the effects of geometric shapes on the detector performance. Cuboid-shaped crystals have the disadvantage of requiring most of the photons to be reflected multiple times before being absorbed by the photodetector, which can reduce timing resolution. Therefore, we also designed and tested some crystals with a pyramid shape. The scintillating photons reflected from the pyramid surface will change their flight angle and emit directly to the coupling surface, which may increase the light output and improve timing resolution. Similarly, scintillating photons in a crystal with a zigzag slope may also be reflected by the slope and directly emit to the coupling surface. Table 3 shows the parameters of the six odd-shaped scintillation crystals, where LYSOP indicates the pyramid-shaped crystal, LYSOH indicates the crystal with a pyramid-shaped top, LYSOF indicates a frustum-shaped crystal, LYSOT indicates a pyramid-shaped top crystal with a sawtooth surface and LYSOTP indicates the crystals with two pyramids. Figure 3a,b show the pictures of LYSOF-6, LYSOH-6, LYSOP-4 and LYSOT-6 and LYSOTP-6 crystals, respectively. Figure 4 shows the design dimensions of various shaped crystals.
Position and Manufacturer
Four pairs of scintillators were tested to investigate differences in boule position and manufacturers. When a crystal is cut from different positions of the scintillator boule, its performance may also be different. Therefore, we tested two 2 mm, 0.2% co-doped LYSO with Ce and Ca crystal cuboids (LYSOAH-2 and LYSOAT-2), which were taken from the tail or head of the same crystal boule. Finally, sample C crystals were made of LYSO crystal provided by SG. These crystals were used to compare the timing resolution of equivalent LYSO crystals from different manufacturers. The parameters of those crystals are listed in Table 4.
Experimental Setting
An experimental system with excellent timing resolution was constructed in this study. As shown in Figure 5, the system consists of two PET detectors, a Keithley 2400 source meter, two custom-designed amplifier boards, two leading edge discriminators (LEDs), a time-to-amplitude converter (TAC), an NI PCI-7833R board and a PC. Each custom-designed amplifier board split the signal from the SiPM into an energy signal and a timing signal and then amplified them. Two stages of current feedback amplifiers (AD8000, Analog Devices, Inc.) were used to amplify the timing signals with a total gain of 200. The −3 dB bandwidth and the slew rate of the amplifier are 1.5 GHz and 4100 V/µs, respectively. The amplified timing signals were fed to two LEDs (CANBERRA ® , Model 454). Note that the Model 454 is a device with four channels of conventional constant fractional discriminators (CFDs). We have modified its internal circuits and converted the four CFDs into LEDs. The outputs of the LEDs were fed to the TAC (ORTEC ® , Model 566), which measured the time interval between pulses to its start and stop inputs and generated an analog output pulse proportional to the measured time. The full scale of the TAC was set to 50 ns and the FWHM of the timing resolution of the Model 566 TAC was 10 ps for all ranges according to the datasheet. The outputs of the TAC and the amplified energy signals were connected to the NI PCI-7833R board, a PCI-based reconfigurable I/O device with a FPGA and eight analog-to-digital converters on-board.
boule.
Finally, sample C crystals were made of LYSO crystal provided by SG. These crystals were used to compare the timing resolution of equivalent LYSO crystals from different manufacturers. The parameters of those crystals are listed in Table 4.
Experimental Setting
An experimental system with excellent timing resolution was constructed in this study. As shown in Figure 5, the system consists of two PET detectors, a Keithley 2400 source meter, two custom-designed amplifier boards, two leading edge discriminators (LEDs), a time-to-amplitude converter (TAC), an NI PCI-7833R board and a PC. Each custom-designed amplifier board split the signal from the SiPM into an energy signal and a timing signal and then amplified them. Two stages of current feedback amplifiers (AD8000, Analog Devices, Inc.) were used to amplify the timing signals with a total gain of 200. The −3 dB bandwidth and the slew rate of the amplifier are 1.5 GHz and 4100 V/μs, respectively. The amplified timing signals were fed to two LEDs (CANBERRA ® , Model 454). Note that the Model 454 is a device with four channels of conventional constant fractional discriminators (CFDs). We have modified its internal circuits and converted the four CFDs into LEDs. The outputs of the LEDs were fed to the TAC (ORTEC ® , Model 566), which measured the time interval between pulses to its start and stop inputs and generated an analog output pulse proportional to the measured time. The full scale of the TAC was set to 50 ns and the FWHM of the timing resolution of the Model 566 TAC was 10 ps for all ranges according to the datasheet. The outputs of the TAC and the amplified energy signals were connected to the NI PCI-7833R board, a PCI-based reconfigurable I/O device with a FPGA and eight analog-to-digital converters on-board.
A LabVIEW program was developed to control the FPGA to perform event triggering and read out the energy and timing signals. The timing resolution of the readout electronics were calibrated with pulses generated from a signal generator. The timing resolution of the readout electronic system was 12.7 ps ± 0.1 ps (mean ± standard deviation), which is only slightly worse than the timing resolution of the Model 566 TAC. A LabVIEW program was developed to control the FPGA to perform event triggering and read out the energy and timing signals. The timing resolution of the readout electronics were calibrated with pulses generated from a signal generator. The timing resolution of the readout electronic system was Crystals 2020, 10, 869 7 of 15 12.7 ps ± 0.1 ps (mean ± standard deviation), which is only slightly worse than the timing resolution of the Model 566 TAC.
The new high-density (HD) cell SiPM (AdvanSiD) coupled to 6 mm LaBr 3 crystal cubes (Table 1) was tested at different bias voltages and trigger levels. This is a highly sensitive photon detector in the near-ultraviolet (NUV) and blue light regions. The SiPM size was 6 × 6 mm 2 with 40,000 cells of 20 × 20 µm 2 cell pitch. The bias voltage and trigger level added to the AdvanSiD SiPM ranged from 36 V to 39 V and 10 mV to 350 mV, respectively. The bias voltage and trigger level added to the Sensl SiPM ranged from 26 V to 32.5 V and 20 mV to 140 mV, respectively. The energy spectrum and time spectrum of each experiment were recorded.
Two detectors using identical scintillator crystal configurations were mounted head-to-head with a 10 mm gap with a 22 Na point source (Eckert and Ziegler, 0.74 MBq) centrally located between them for coincidence imaging. Unless otherwise stated, the scintillators were wrapped with the same reflector (Teflon tape), coupled with using the same optical glue (MeltMount) with the same pair of SiPMs (6 mm SensL J-series) and tested with the same readout electronics with identical settings in terms of bias voltage (31.5 V), amplifier gain (200) and trigger level (40 mV). Note that we used MeltMount glue to construct the detectors. Thus, we were able to mount and unmount the scintillators conveniently and use the same pair of SiPMs repeatedly.
Approximately one million coincidence events were acquired for each coincidence pair of scintillator crystals within the energy window of 450 keV to 550 keV and were analyzed for the time spectrum and calculation of CTR. The trigger time differs for coincidence events with the same rise time, but different energy peaks. Therefore, the timing measurements were not accurate when the leading-edge discriminator was implemented, especially for the large range of energy windows. Therefore, the energy value of coincidence events was used to correct the time signal. The timing resolution was raised by approximately 10% after compensation. Typically, the FWHM of the peak of the time spectrum was calculated as the timing resolution of the coincidence event.
Saturation Correction
The saturation correction of SiPMs was applied for all the tested detectors based on Tracepro simulation; the correction process is shown in Figure 6a. First, the Tracepro was used to optically simulate the interaction of gamma photons in the scintillators, track the scintillation photons and get the simulated light output. The characteristic parameters of those scintillators in the simulation are shown in Table 5, which was provided by the vendors. The SiPM has different detection efficiency for photons with different wavelength (λ). In the simulation, when λ is 420 nm, the detection efficiency is up to 52%. Depending on the crystal specifications, scintillation photons from 2300 to 7000 (the area between the two red vertical lines) can eventually reach the coupled SiPM.
Second, according to the cross-sectional area of the scintillators, the conversion function between the reached photons number and the detected photons number was obtained through Matlab modeling. The SensL MicroFJ-60035-TSV SiPM has 22,292 microcells. Figure 6b shows the conversion function curves when the crystal coupling area are 2 × 2 mm 2 , 4 × 4 mm 2 and 6 × 6 mm 2 , respectively, taking into account of the influence of the thickness of optical glue (0.1 mm) and protective glass (0.35 mm) on SiPM, corresponding coupling microcells are about 5.8 k, 15.9 k and 22 k, respectively. In the simulation, we assume that the scintillating photons simultaneously reach the avalanche diode in the SiPM.
Third, the light output obtained by the Tracepro was converted into the light output actually detected by SiPM through the conversion function. Finally, the uncorrected measured energy spectrum was converted into corrected energy spectrum by matching the peak position of 511 keV with simulated light output. The corrected light outputs and energy resolutions were calculated from the corrected energy spectrum.
Photodetectors
First, we compared the performance of the 6 mm SensL J-series SiPMs (Figure 7a) with the 6 mm AdvanSiD NUV SiPMs (Figure 7b) by using a pair of 6 mm LaBr3 cubes (LaBr-6). The FWHM CTRs were represented by the colors and contour lines. The SensL SiPM without time walk compensation achieved its best coincidence timing resolution of 77 ps FWHM when the bias voltage was 31.5 V and the trigger level was 40 mV. Similarly, the AdvanSiD SiPM without time walk compensation achieved its best CTR of 75 ps FWHM when the bias voltage was 38.5 V and the trigger level was 75 mV. These results showed that the two SiPMs had no significant differences in timing resolution. Therefore, the 6 mm SensL SiPMs were used in all of the tests described below.
Photodetectors
First, we compared the performance of the 6 mm SensL J-series SiPMs (Figure 7a) with the 6 mm AdvanSiD NUV SiPMs (Figure 7b) by using a pair of 6 mm LaBr 3 cubes (LaBr-6). The FWHM CTRs were represented by the colors and contour lines. The SensL SiPM without time walk compensation achieved its best coincidence timing resolution of 77 ps FWHM when the bias voltage was 31.5 V and the trigger level was 40 mV. Similarly, the AdvanSiD SiPM without time walk compensation achieved its best CTR of 75 ps FWHM when the bias voltage was 38.5 V and the trigger level was 75 mV. These results showed that the two SiPMs had no significant differences in timing resolution. Therefore, the 6 mm SensL SiPMs were used in all of the tests described below.
Photodetectors
First, we compared the performance of the 6 mm SensL J-series SiPMs (Figure 7a) with the 6 mm AdvanSiD NUV SiPMs (Figure 7b) by using a pair of 6 mm LaBr3 cubes (LaBr-6). The FWHM CTRs were represented by the colors and contour lines. The SensL SiPM without time walk compensation achieved its best coincidence timing resolution of 77 ps FWHM when the bias voltage was 31.5 V and the trigger level was 40 mV. Similarly, the AdvanSiD SiPM without time walk compensation achieved its best CTR of 75 ps FWHM when the bias voltage was 38.5 V and the trigger level was 75 mV. These results showed that the two SiPMs had no significant differences in timing resolution. Therefore, the 6 mm SensL SiPMs were used in all of the tests described below.
Surface Treatment
LYSO samples LYSOA-6 and LYSOP-6 were used to compare the timing resolution of the crystals of different surface treatments. For these tests, the bias voltage and trigger level added to the SiPM ranged from 26 V to 32.5 V and 20 mV to 140 mV, respectively. The best CTR of the polished crystal was 146 ps with a bias voltage of 31 V and a trigger level of 40 mV (Figure 8a). The best CTR of the unpolished crystal was 129 ps with a bias voltage of 31.5 V and a trigger level of 40 mV (Figure 8b).
Surface Treatment
LYSO samples LYSOA-6 and LYSOP-6 were used to compare the timing resolution of the crystals of different surface treatments. For these tests, the bias voltage and trigger level added to the SiPM ranged from 26 V to 32.5 V and 20 mV to 140 mV, respectively. The best CTR of the polished crystal was 146 ps with a bias voltage of 31 V and a trigger level of 40 mV (Figure 8a). The best CTR of the unpolished crystal was 129 ps with a bias voltage of 31.5 V and a trigger level of 40 mV (Figure 8b).
Clearly, the timing resolution of the unpolished crystal is better than that of the polished crystal, regardless of the bias voltage and the trigger level. When the cubic crystal surface is absolutely smooth, nearly half of the scintillating photons are not received by the SiPM due to total internal reflection (TIR). In contrast, the unpolished surface can change the flight angle of the scintillating photons, thereby breaking the limit of the TIR and increasing the light output and timing resolution.
Type of Scintillators
The cubic crystals listed in Tables 1 and 2 were used to investigate how the CTR varied with the scintillator material. The CTRs of those cubic crystals are shown in Figure 9a. The timing resolution of the halogen crystal (LaBr-6:77 ps, CeBr-6:74 ps) was the best as shown in Figure 9b and the GAGG crystal (193 ps) was the worst. The timing resolution of the other crystals were at the same level. In detail, the CTRs of LFS-2, LFS-3.7 and LFS-4 were 119 ps, 126.4 ps and 142.8 ps, respectively, which was worse than those of the 0.2% Ce, 0.1% Ca co-doped LYSO for the same size. The CTRs of LYSO-3.7 (SG), LYSO-5 (SG) and LSO-6 were 110.1 ps, 126.7 ps and 132.9 ps, respectively. In general, the larger the cubic crystal, the worse the timing resolution tends to be. The relative light outputs and energy resolutions of cubic crystals with the same surface treatments are shown in Figure 9c,d with corrected for saturation effects of SiPMs. The light output of the 4 mm 0.2% co-doped LYSO cubic (LYSOA-4) crystal was used as a reference and it was set to 100%. Similar, the larger the cubic crystal, the worse the light output tend to be. Clearly, the timing resolution of the unpolished crystal is better than that of the polished crystal, regardless of the bias voltage and the trigger level. When the cubic crystal surface is absolutely smooth, nearly half of the scintillating photons are not received by the SiPM due to total internal reflection (TIR). In contrast, the unpolished surface can change the flight angle of the scintillating photons, thereby breaking the limit of the TIR and increasing the light output and timing resolution.
Type of Scintillators
The cubic crystals listed in Tables 1 and 2 were used to investigate how the CTR varied with the scintillator material. The CTRs of those cubic crystals are shown in Figure 9a. The timing resolution of the halogen crystal (LaBr-6:77 ps, CeBr-6:74 ps) was the best as shown in Figure 9b and the GAGG crystal (193 ps) was the worst. The timing resolution of the other crystals were at the same level. In detail, the CTRs of LFS-2, LFS-3.7 and LFS-4 were 119 ps, 126.4 ps and 142.8 ps, respectively, which was worse than those of the 0.2% Ce, 0.1% Ca co-doped LYSO for the same size. The CTRs of LYSO-3.7 (SG), LYSO-5 (SG) and LSO-6 were 110.1 ps, 126.7 ps and 132.9 ps, respectively. In general, the larger the cubic crystal, the worse the timing resolution tends to be. The relative light outputs and energy resolutions of cubic crystals with the same surface treatments are shown in Figure 9c,d with corrected for saturation effects of SiPMs. The light output of the 4 mm 0.2% co-doped LYSO cubic (LYSOA-4) crystal was used as a reference and it was set to 100%. Similar, the larger the cubic crystal, the worse the light output tend to be. Figure 10a shows the CTR for the cuboid-shaped LYSO crystals listed in Table 2. Investigating the size of the crystal cubes, the CTR of the 2 mm cube crystal was better than that of the 6 mm cube crystal and the CTRs of the 4 mm cube crystals were in between (Figure 10a). In long crystals, the time distribution of the photons (particularly the first photons) reaching the photodetector is wider, due to a larger distribution of the photon pathways. Thus, larger time jitters were introduced in the long crystals. Consistently, the larger the scintillator, the lower the light output (Figure 10b). The 4 mm cubic crystal achieved the best energy resolution as shown in Figure 10c 3.7 (SG), LYSO-5 (SG) and LSO-6 were 110.1 ps, 126.7 ps and 132.9 ps, respectively. In general, the larger the cubic crystal, the worse the timing resolution tends to be. The relative light outputs and energy resolutions of cubic crystals with the same surface treatments are shown in Figure 9c,d with corrected for saturation effects of SiPMs. The light output of the 4 mm 0.2% co-doped LYSO cubic (LYSOA-4) crystal was used as a reference and it was set to 100%. Similar, the larger the cubic crystal, the worse the light output tend to be. Table 2. Investigating the size of the crystal cubes, the CTR of the 2 mm cube crystal was better than that of the 6 mm cube crystal and the CTRs of the 4 mm cube crystals were in between (Figure 10a). In long crystals, the time distribution of the photons (particularly the first photons) reaching the photodetector is wider, due to a larger distribution of the photon pathways. Thus, larger time jitters were introduced in the long crystals. Consistently, the larger the scintillator, the lower the light output ( Figure 10b). The 4 mm cubic crystal achieved the best energy resolution as shown in Figure 10c. Investigating the size of the rectangular-prism crystals, the CTRs of LYSOA-6L3, LYSOA-3L6 and LSO-6L3.7 were 119 ps, 128.4 ps and 127.8 ps, respectively. By comparing LYSOA-6L3 and LYSOA-6, it can be inferred that a short crystal length can achieve a better timing resolution when the cross section is the same. Investigating the doping and surface treatment, the timing resolution of the 0.2% Ce co-doped LYSO crystals (LYSOA-4 and LYSOA-6) were better than that of the matching 0.1% Ce co-doped LYSO crystals (LYSOB-4 and LYSOB-6). However, the light output of the 0.2% Ce co-doped crystals were lower than that of 0.1% Ce co-doped LYSO crystals. The energy resolution of the 0.2% Ce co-doped LYSO were similar with that of 0.1% Ce co-doped LYSO crystals. In addition, the unpolished 4 mm and 6 mm crystal cubes (LYSOA-4 and LYSOA-6, the black line in Figure 10a,b) had better light output and timing performance than that of the equivalent polished crystals (LYSOP-4 and LYSOP-6, the red line in Figure 10a,b).
Shape
Investigating the size of the rectangular-prism crystals, the CTRs of LYSOA-6L3, LYSOA-3L6 and LSO-6L3.7 were 119 ps, 128.4 ps and 127.8 ps, respectively. By comparing LYSOA-6L3 and LYSOA-6, it can be inferred that a short crystal length can achieve a better timing resolution when the cross section is the same.
Shape
The CTR and relative light output of six types of odd-shaped 0.2% co-doped LYSO crystals (LYSOH-6, LYSOP-4, LYSOF-6, LYSOP-6, LYSOT-6, LYSOTP-6) are shown in Figure 11a. The CTR and light output of the LYSOP-4 and LYSOP-6 crystals were better than those of the reference sample LYSOA-6 crystal, which illustrates that the tapered structure may contribute to improve timing resolution and light output. However, the performance of several other odd-shaped crystals (LYSOF-6, LYSOH-6, LYSOT-6, LYSOTP-6) were on the same level as the 6 mm crystal cube. The typical time spectrum of the LYSOP-4 crystal is shown in Figure 11b.
Position and Manufacturer
Investigating the scintillator manufacturers, the CTRs of the cubic crystals LYSOC-3.7 and LYSOC-5.5 supplied by SG were 110.1 ps and 126.7 ps, respectively. This result confirms that the smaller the crystal cube, the better the timing resolution. The crystal was at the same level as the timing resolution and light output of the crystal provided by JTC.
Investigating the position of the crystal within the boule, the CTRs of LYSOAH-2 and LYSOAT-2 were 110.2 ps and 99.1 ps, respectively. These crystals were taken from different positions of the same crystal boule, which shows that crystal taken from the tail of the crystal boule may achieve a better timing resolution.
Summary and Discussion
The CTRs, corrected energy resolution and corrected relative light outputs of the tested scintillator detectors are summarized in Table 6. The sample CeBr-6 achieved the best CTR (74 ps)
Position and Manufacturer
Investigating the scintillator manufacturers, the CTRs of the cubic crystals LYSOC-3.7 and LYSOC-5.5 supplied by SG were 110.1 ps and 126.7 ps, respectively. This result confirms that the smaller the crystal cube, the better the timing resolution. The crystal was at the same level as the timing resolution and light output of the crystal provided by JTC.
Investigating the position of the crystal within the boule, the CTRs of LYSOAH-2 and LYSOAT-2 were 110.2 ps and 99.1 ps, respectively. These crystals were taken from different positions of the same crystal boule, which shows that crystal taken from the tail of the crystal boule may achieve a better timing resolution.
Summary and Discussion
The CTRs, corrected energy resolution and corrected relative light outputs of the tested scintillator detectors are summarized in Table 6. The sample CeBr-6 achieved the best CTR (74 ps) and the GAGG-2 crystal achieved the worst CTR (193 ps). The LaBr-6 crystal achieved the best relative light output (1.75) and the GAGG-2 crystal achieved the worst relative light output (0.65). The LaBr-6 crystal achieved the best energy resolution (6.4%) and the LYSOTP-6 crystal achieved the worst energy resolution (12.9%). Figure 12 shows a comparison of the CTR and the light output for all of test crystals except LaBr-6 and CeBr-6. There is a general trend, that the larger the light output of the crystal, the better the time performance. The timing resolution and light output of several rhenium silicate-based crystals (LYSO, LFS, LFS, etc.) are at the same level.
The CTR of the 2 mm GAGG cubes was 193 ps. However, we note that the SensL SiPM had a much lower photon detection efficiency (PDE) for 530 nm compared to that for 420 nm. Thus, the measured light output from GAGG was 47% lower than that of LYSO. According to the relationship between the CTR and the light output of the crystal, the CTR of the 2 mm GAGG cubes improves to 117 ps if the effect of the low PDE for 530 nm was compensated.
The idea for an odd-shaped crystal came from the study of photonics crystals, which are a kind of micronano structure on the crystal surface that guides and controls the propagation of scintillating photons to increase the light output and time performance of the detector. The macroscopic structure does not meet the expectations, but it is possible when the profiled structure is on the nanometer scale. The CTR of the 2 mm GAGG cubes was 193 ps. However, we note that the SensL SiPM had a much lower photon detection efficiency (PDE) for 530 nm compared to that for 420 nm. Thus, the In this study, the number of samples for all configurations is small, and some results may not be representative. Especially when the crystals were taken from different positions of the crystal boule (LYSOAH-2 and LYSOAT-2), the difference of CTR may not be as big as tested. The sensitivity of the PET scanners is related to the length of the crystal. In a typical commercial PET scanner, the length of the crystal is approximately 20 mm. It is possible to build a TOF-PET detector with three layers of scintillators. While the detector meets the sensitivity requirements of the PET scanner, the measured CTRs are expected to drop below 70 ps.
Conclusions
In summary, we can conclude from the testing results that: (1) a 74 ps FWHM CTR was measured with a pair of 6 mm side CeBr 3 cubes. It is possible to achieve a CTR below 50 ps if the PET detector is constructed by smaller LaBr 3 crystals; (2) an 88.1 ps FWHM CTR was measured with a pair of 4 mm LYSO: Ce, Ca pyramids, which shows that a change in the shape of the crystal can improve the timing resolution; (3) the two SiPMs from SensL and AdvanSiD have no significant differences with respect to timing resolutions; (4) the crystals with unpolished surfaces have better timing than those with polished surfaces; (5) LYSO: Ce, Ca from different venders and LSO from Siemens have similar performances; (6) 0.2% co-doped LYSO crystals have a better CTR than that of 0.1% Ce co-doped LYSO; (7) 0.2% co-doped LYSO crystals have a better timing resolution than that of LFS; (8) the CTR measurements are related to the size of the crystals. The 2 mm crystals have better timing than 4 mm crystals and the 4 mm crystals have better timing than 6 mm crystals.
The conclusions drawn from these experimental studies provide some practical guidance in terms of the design of PET detectors with high timing resolution. However, many other practical factors, including costs, detector efficiency or stopping power, accuracy of the decoding of the positions of gamma interaction and effects of Compton scatters, need to be considered and carefully balanced, when designing PET detectors for different applications such as the whole-body imaging and the organ-specific imaging. | 8,440.6 | 2020-09-25T00:00:00.000 | [
"Materials Science",
"Physics",
"Engineering",
"Medicine"
] |
Rectangular Glass Optical Fiber for Transmitting Sunlight in a Hybrid Concentrator Photovoltaic and Daylighting System
In this paper, we propose to use glass optical fibers with a rectangular cross-section for the application in a concentrator photovoltaic and daylighting system (CPVD) due to the unique characteristics of rectangular fibers with the capability to provide a uniform rectangular beam shape and a top-hat profile at the output. A mathematical model of rectangular optical fibers has been formulated in this study for different incident angles, and the results are compared with those of round optical fibers. Furthermore, the performance of the bundle of RGOFs is compared with that of the bundle of round optical fibers via simulation by using the ray-tracing method. The mathematical modelling and numerical simulation have demonstrated that the RGOF has advantages in terms of the improvement in relative transmission and reduction in energy leakage for the transmission through the optical fiber. The simulation result also shows that a higher flux of sunlight can be transmitted via the bundle of RGOFs as compared to the bundle of round optical fibers due to the higher coupling efficiency. The experiment results on the relative transmission in different incident angles for both round optical fibers and RGOFs have validated both the simulation and the mathematical modelling. The beam profile of our fabricated RGOF has also been measured via our laboratory facility. The flexibility test on the fabricated RGOF has been carried out to bend at a radius of 150 mm and twist at 90° at a fiber length of 2.2m.
Introduction
The initial idea of the optical fiber used for transmitting sunlight can be dated back to forty years ago [1]. Recently, significant advances in the technology of optical fibers have extended the application to transmit the sunlight with a wide band of electromagnetic waves. The application of transmitting sunlight by a round optical fiber and the bundle of round optical fibers have been studied [2][3][4][5][6]. The optical fibers can transmit sunlight with reasonable low loss for a distance fewer than 10 meters, but the optical loss in the optical fibers becomes noticeable at longer distances [7]. Considering the said limitation, there are still many applications especially transmitting daylight via fiber optics for residential and commercial buildings, which are still regarded as a promising method [7][8][9].
In transmitting sunlight through a dish and a round optical fiber, many components such as mirror accuracy and tracker precision, as well as the material, diameter, length, and type of optical fibers, can affect the efficiency of the whole system [10]. The material of the core and cladding of the optical fiber are the major factors to determine the acceptance angle of the optical fiber [11]. A parabolic dish with a high precision sun tracker can provide a solar concentration ratio of more than 8000 [12]. For transmitting the high flux of concentrated sunlight, a larger core diameter is usually preferable. The one-millimeter core diameter of fused silica with a low refractive index of hard polymer resin as cladding can transmit a reasonable flux of sunlight with lower loss than that of polymer optical fibers [13,14].
Transmitting sunlight with a wide spectrum of wavelengths via optical fibers encounters more challenges as compared to the application of optical fibers in telecommunications. The large core diameter of the optical fiber transmits light in multimode. The optical loss of the multimode fiber is higher in comparison to that of single-mode fibers made of the same material and transmitting the same wavelength of light [15]. Attenuation of power transmission in optical fibers with fused silica as the core and a hard polymer as the cladding is independent of the shape of the optical fiber [16]. Dugas et al. found that the leakage of power in sunlight transmission via a round optical fiber was attributed to optical loss due to too many reflections between the core and the clad with angles near the numerical aperture of the optical fiber [17]. To minimize the light leakage, the incident angle of sunlight relative to the numerical aperture of the optical fiber should be significantly less than the acceptance angle of the optical fiber. Feuermann et al. studied the dependence of light leakage within the nominal numerical aperture of the solar fiber optic on several parameters including incidence angle, optical properties of the core and cladding, and fiber length [13].
Moreover, the optical loss can occur when coupling the sunlight to a bundle of optical fibers. The method of bundling optical fibers will determine the amount of coupling loss. If a bundle of round optical fibers is fabricated by fusing all the optical fibers, the loss is lesser than that of the bundle of optical fibers being joined by epoxy adhesive. In the fusing process, the gaps among the optical fibers are diminished by forming one whole solid block, which has improved the coupling efficiency of light to the bundle of optical fibers [18]. However, the method of fusing optical fibers is much more expensive than by simply joining with epoxy adhesive.
A multijunction solar cell with a square dimension can convert sunlight into electricity in a concentrate photovoltaic (CPV) system. The dimensions of the multijunction cells that are available in the market are 3 mm × 3 mm, 5 mm × 5 mm, and 10 mm × 10 mm. Nevertheless, the matching between the concentrated light profile and the geometry of solar cells is essential to optimize the performance of the CPV system [19]. Many works have been carried to study the design of solar concentrators for mapping the focused sunlight with the square shape of multijunction solar cells. Baig et al. and Yu et al. studied the compound parabolic concentrator (CPC) as a nonimaging concentrator to harness solar energy and mapping sunlight to square solar cells [20,21]. A compound truncated pyramid and cone may be used for concentrating and coupling sunlight with the optical fiber. A bundle of optical fibers can be used as a coupler of concentrated sunlight to the multijunction solar cells in the CPVD system [12]. The optical fiber must be made of glass to tolerate the high temperature of concentrated light. A bundle of RGOFs with a square shape can map well the focused sunlight onto square solar cells.
Rectangular fibers were first studied for transmitting Xrays and light-wave circuit. Marcatili studied the rectangular waveguide for integrated optics in 1969 [22]. In the meantime, a square core optical fiber was developed for matching with the laser diode output beam. Cherny et al. (1979) studied waveguide characterization of a rectangular core and round clad for the cases of multi-mode and singlemode waves including the effect of single and double clads on dispersion of a pulse [23]. Blomster and Blomqvist studied square fiber for high-power laser applications in 2007 [24]. Konishi et al. developed a rectangular core optical fiber for a high-power laser in 2010 [25]. Ambran et al. demonstrated a physical micromachining technique to fabricate a flat fiber substrate for a light circuit [26]. The width of the flat fiber was 1612 μm, and the thickness of the core was about 10 μm.
Rectangular core fibers in the market have round clads. The core is made of fused silica for its broadband UV to NIR transmittance while the clad may be made of glass or a low refractive polymer. Figure 1 shows the attenuation of a square core in the market at different wavelengths. The core of the fiber is fused silica, and the clad is a hard polymer. These rectangular fibers are developed for applications in transmitting laser. The published data same as the published data of round optical fibers are extracted from propagating a beam of laser with a specific bandgap. Figure 1 reveals that attenuation is as low as 20 dB/km at 600 nm while the loss of fiber is more than the mentioned loss in transmitting sunlight.
In this paper, we would like to introduce RGOF that is specially designed for a CPVD system to transmit sunlight through the optical fiber. The core of RGOF can be fabricated by drawing a fused silica preform at the temperature of 2250°C. The preform must have a rectangular cross-section before drawing. The clad is a polymer with refractive index of 1.37 that is coated on the fused silica core. The length of International Journal of Photoenergy the rectangular core is between 5 mm and 10 mm with the width ranging from 0.2 mm to 0.5 mm. The thickness of the clad is about 0.1 mm.
The CPVD system has two functions including generating electricity and daylighting. The bundles of RGOF transmit sunlight from the focal point of the solar concentrator to the multijunction cells and the remote target. Furthermore, RGOF can also be used in other applications, i.e. sensors and delivery of a high-power laser beam.
A comprehensive manner composed of three major aspects embracing mathematical modelling, numerical simulation, and experimental verification is used for investigating the mechanism of leakage in transmitting sunlight in the RGOF. Based on previous studies, relative transmission of round optical fibers and RGOF in transmitting sunlight and the loss due to gaps between the fibers in a bundle are also studied. In Section 2, the mathematical model of the relative transmission is presented to compare between the round optical fiber and RGOF for different angles of incidence. In Section 3, the performance of RGOF is simulated by using the ray-tracing method. In Section 4, the effect of gaps is simulated for a bundle of RGOFs and the result is compared with that of a bundle of round optical fibers. In Section 5, the relative transmission, beam profile, and bending of the RGOF are investigated via experiments.
In this work, transmitting sunlight through an optical fiber with a rectangular glass core and a rectangular polymer clad has been investigated. Other researches on rectangular glass core fibers were only focused on the characterizations of the rectangular fiber for transmitting a high-power laser and pulse dispersion that involves a narrow band of wavelengths in the application of optical communication. For the originality of our study, the relative transmission of sunlight with a wide spectrum of wavelengths in the rectangular optical fiber is studied in a comprehensive manner in three major aspects embracing mathematical modelling, numerical simulation, and experimental verification.
Analytical Approach on Leakage of the Optical Fiber during Transmission of Sunlight
The efficiency of an optical fiber under the propagation of a full spectrum is different from the efficiency of the optical fiber under a collimated laser beam with a narrow bandgap. Manufacturers of optical fibers only provide information about the attenuation of light power at specific wavelengths but not the efficiency of transmitting a broad spectrum of light. The optical loss of an optical fiber with a specific attenuation varies with the length of the fiber. The light is coupled with the fiber with an incident angle of 0°. We may consider a source of light beam larger than the diameter of the optical fiber. If the angle of propagation increases up to the acceptance angle, the loss is changed with the cosine of incident angle. The loss of the fiber under the propagation of a wide spectrum for a specific incident angle is less than the expected loss. Feuermann measured the leakage of optical fibers under the propagation of a wide spectrum with different angles of propagation and different ratios of the length of the fiber to the diameter of the core.
International Journal of Photoenergy
For a fiber with a specific numerical aperture and specific angle of propagation, the ratio of the length of fiber to the diameter of the core directly affects the amount of leakage.
The mechanism of leakage in transmitting sunlight by optical fibers was studied, and it was found that the reflection of light between the core and the clad is not perfect and that the number of reflections of light determines the amount of leakage in the optical fiber. Concentrating sunlight leads to an increase in the incident angle between the rays of sunlight and the aperture of optical fibers. The number of reflections increases in such a condition, and the effect of the very small loss due to reflection is noticeable. The number of reflections increases with addition of the angle of incidence and the ratio of the length to the diameter of the fiber.
Although ray-tracing is a popular method, a mathematical analysis of loss is useful for understanding the behavior of fibers in various conditions and for assessing the accuracy of numerical methods. For the mathematical analysis of loss due to the number of reflections between the core and the clad, the optical fibers have been modelled to be exposed to the collimated light of a tilted source, which is likely to happen for the bundle of fibers used as the receiver of a CPVD system. Figure 2 shows the setup of a collimated light with an angle of incidence relative to the axis of the optical fiber. The average number of reflections for all rays is a variation that affects the relative transmission and determines the loss of the fiber due to the angle of incidence. Figure 3(a) shows that the azimuth angle of the rays is 90°a nd the rays skew along the length of the fiber. Figure 3(b) shows the rays in the rectangular fiber. The rays in the round optical fiber skew around the axis of the fiber, but the rays move in a zigzag form in the rectangular fiber. Figure 3(c) shows the relation between 2x, dL, θ, and θ d in a round optical fiber.
2x is the distance between two sequential reflections in the plane normal to the round optical fiber's axis. R is the radius of the optical fiber, and dL is the distance between two sequential reflections in the plane including a line parallel to the axis of the optical fiber and 2x. θ is the angle between dL and the trajectory onto the plane through the dL including to 2x.
International Journal of Photoenergy
where N i is the number of reflections for a ray in the length of the fiber, L is the length of the optical fiber, and d is the diameter of the fiber. The total number of reflections of all rays is where r and ω represent the polar coordinates of the interface of the fiber Considering the uniform distribution of rays on the surface of the interface of the fiber, we have where N av is the average number of reflections for all rays. The angle of α min corresponds to the rays with the highest reflection and the lowest acceptable energy. We may consider that rays with a lower angle than α min are ignored. If the diameter of the propagated light is larger than the diameter of the optical fiber, then the power of incident light is where R av is the arithmetic average of reflectivity and θ d is the angle of incidence relative to the axis of the optical fiber (see Figure 3). τ 0 is the transmission of the optical fiber at the angle of zero degree.
In the flat fiber, we do not have skew rays. The direction of the rectangular fiber to the propagated light determines the transmission of light in the zigzag direction. Figure 4(a) shows the effect of the zigzag direction on the number of reflections. Figure 4(b) shows the relation between the length of rectangle b, dL, and θ in a rectangular optical fiber.
where a and b are the length and the width of the rectangular fiber, respectively. International Journal of Photoenergy where dx and dy represent the Cartesian coordinate of the interface of the rectangular fiber For another side, we have If the diameter of the propagated light is larger than the width of the rectangle in the fiber, then the power of incident light is proportional to the cosine of the incident angle. For one side, the relative transmission is For another side, the relative transmission is The direction of the rectangular fiber to the propagated light determines the zigzag transmission of light direction. Figure 4 shows that the direction of zigzag affects the number of reflections.
The designed RGOF is a glass optical fiber with a rectangular shape of the core and polymer clad; the ratio of the length to width of the rectangular fiber is more than 5 where the width must have a limit to prevent breakage during bending. As an example, the fabricated RGOF has a width or thickness of 0.4 mm and the minimum bending radius of 150 mm. If the diameter of the propagated light is large enough to cover the aperture of the optical fibers and the length of the fiber is to be short, the cosine of the incident angle plays an important role. Figure 5 shows the loss of a 100 mm length of a round fiber and a rectangular fiber where the light covers the aperture of the fibers. The diameter of the light is large enough and the cosine of angle of incidence should be considered. The ratio of the length of the rectangle to the diameter of the round fiber affects the relative transmission of the rectangular fiber. The effect of loss due to the number of reflections between the core and the clad is very low and the trends of optical fibers are near to each other and near to the cosine of the incident angle. Figure 6 shows the relative transmission of fibers with a length of 10,000 mm, and light covers the surface of the fibers. The rectangular fiber with the length of the rectangle 10 times the diameter of the round fiber has a lower loss due to the number of reflections between the core and the clad and shows higher relative transmission than other fibers. The zigzag movement is in the longer trajectory ( Figure 4).
If the diameter of the light is to be equal to the diameter of the round fiber, a rectangular fiber with the length of the rectangle 10 times the diameter of the round fiber shows higher relative transmission as compared to the round fiber. Figure 7 shows the relative transmission of a round and a rectangular fiber. The diameter of the round fiber is one millimeter, and the length of the rectangle of the rectangular fiber is 10 mm. the length of both fibers is 10,000 mm, and the diameter of the light is smaller than the diameter of the round fiber. The difference between the relative transmission of two fibers increases when the source is more tilted relative to the axis of the fiber.
Simulation of RGOF and Round Optical Fiber
The ray-tracing method has been applied to simulate the responses of the flat fiber (RGOF) and the conventional round fiber to a tilted source of light. For both cases of the flat and round fibers that consist of a fused silica core and a low refractive index resin clad, the parameters including the flux, relative transmission, and optical loss of the light have been investigated for different incident angles relative to the axis of the fiber, i.e., from 0°to 30°. 10 International Journal of Photoenergy contains a significant part of solar spectral irradiance that is required in energy harnessing for a high concentrator photovoltaic receiver and daylighting system, where the glass optical fibers with the core material made of fused silica has a high transmission coefficient in this range. Figure 9(a) shows the schematic diagram of the round optical fiber, and Figure 9(b) shows the schematic diagram of RGOF in the simulation. Table 1 shows the input data of the simulation for both the round optical fiber and the RGOF. The schematic diagram of simulation shows that the flat fiber does not produce skew rays. The result of the simulation shows that the leakage of the round fiber for incident angles ranging from 0°to 20°is more than that of RGOF. Figure 10 shows that the relative transmission in the round fiber is 3% less than that in RGOF for the incident angles ranging from 0°to 10°. For the incident angle between 10°a nd 20°, the difference of the relative transmission between the round optical fiber and the RGOF can increase up to 17% at the angle of 20°. Considering NA = 0:39 and an incident angle less than half of the acceptance angle, we conclude that the round optical fiber shows low angular loss similar to the RGOF.
To investigate the angular response and distribution of light at the endpoint of both types of fibers, Figures 11 and 12 show the simulated results at the incident angles 0°, 15°, and 25°for the round optical fiber and RGOF, respectively. The diameter of the source is 2 mm, and the maximum angle of the source with reasonable intensity and uniform output of the round optical fiber occurred at 10°which is less than half of the critical angle. Based on the results of the simulation, collimating the light before the light is transmitted via the optical fiber can increase the relative transmissions significantly for the incident angles 0°to 20°.
For the incident angles 0°-20°, the intensity of light in RGOF was higher than that in the round optical fiber. For an incident angle of 25°, the intensity of light dropped dramatically to nearly zero while the skew rays caused a maximum intensity of 4 watts per steradian in the round optical fiber. However, the amount of intensity is not considerable.
Investigation of the Effects of Gaps for Bundle of RGOFs and Bundle of Round Optical Fibers
In this section, we will assess the performances of the bundle of RGOFs and the bundle of round optical fibers under the same conditions. For the application of optical fibers in transmitting concentrated sunlight, the concentrator photovoltaic and daylighting (CPVD) system encounters several possible optical losses when using the bundle of optical fibers. First, the optical loss can occur during the coupling of sunlight to the aperture of the bundle of optical fibers. Second, the gap spacing between the fibers tied in a bundle can cause the energy loss when the light falls into the gaps. Third is the optical losses during the process of transmitting sunlight through optical fibers. Lastly, at the end of the fibers in a bundle, the geometrical matching between the aperture of fibers in the bundle and the dimension of the solar cell may also cause the energy loss. The optical characteristics of round optical fibers and RGOFs in the bundle have been investigated using the raytracing method via Zemax software. To compare the performance of round and rectangular optical fibers, same core and cladding materials have been used, which are fused silica with a refractive index of 1.458464 at D-line and resin XPC-373 AP clad with a low refractive index of 1.387939 at 852nm [27]. For both cases of fibers, the propagation of light rays has been investigated at the incident angle of 0°relative to the central line of the optical fiber. A 1-watt light source based on blackbody radiation at the temperature of 5780 K (wavelengths ranging from 400 nm to 1600 nm) is applied to illuminate the bundles of optical fibers. The maximum divergence of the light source is 0.27°. 12 International Journal of Photoenergy The active area of the photodetector is square (12 mm × 12 mm) and the thickness of the cladding is 25 μm. The area of the bundle of RGOFs was 101.6064 mm 2 while the area of the bundle of round optical fibers was 101.9172 mm 2 , where the difference between the areas of both bundles is negligible, at about 0.3%. The performance including power transmission and distribution of light intensity and flux of light are evaluated in both cases. Figure 13 shows a row of fifteen units of RGOF with a cross-sectional area of 10:08 mm × 0:67 mm for each fiber to form a total cross-sectional area of 10:08 mm × 10:08 mm. The light is well mapped to the square dimension of the photodetector in both directions of X and Y. For both cases, we have applied the same testing conditions, i.e., light source, photodetector, length of fibers, material, and cross-sectional area of bothbundles. Figure 14(a) shows images of the flux on the active surface of the photodetector for both cases, and Figure 14(b) shows the intensity distribution in the X and Y directions. A comparison between the flux distributions in both cases reveals that the transmitted light rays via flat fibers are more uniform than those via round optical fibers. Figure 15 shows the total powers for both bundles of RGOF and round optical fibers for the lengths between 50 mm and 300 mm. The result shows that the bundle of RGOF fibers transmits more power as compared to the bundle of round optical fibers because of lower optical loss at the entrance aperture of the optical fibers. The effective area of the cores in the bundle of RGOFs is 93.279 mm 2 , and the effective area of the cores in the bundle of roundoptical fibers is 78.539 mm 2 .
Experimental Investigation on a Round Optical Fiber and a RGOF
With regard to the profile of the beam, relative transmission of RGOF for incident angles ranging from 0°to 25°has been investigated experimentally by using collimated white light, focused white light, and the laser beam. A supercontinuum white-light laser of NKT Photonics Company and a beam profiler by Thorlabs Company have been employed as a light source and plotter for the beam profile, respectively. Two samples of RGOF have been fabricated by using two different materials: the first sample has fused silica as the core material and the XPC 373 low refractive index polymer as the clad material; the second sample has borosilicate 3.3 as the core material and Teflon as the clad material. Table 2 lists down the characteristics of the supercontinuum laser. Figure 16 shows the experimental setup of the beam profile measuring system, where the light source illuminates the light from one end side of the RGOF, and the beam profiler is positioned at the other end of the RGOF fiber. Figure 17(a) shows the results of the measured beam profile along the Y -axis. The intensity of light was distributed across the surface of RGOF and the maximum intensity occurred at the center of the fiber. The intensity was distributed from zero to 1000 μm along the Y-axis. The amplitude of the peak point Figure 17(b) shows the measurement of the beam profiler along the X-axis.
Relative transmission of RGOF for incident angles between 0°and 20°has been measured under the propagation of a white light produced by a xenon lamp. Figure 18(a) shows the experiment setup of the test using a xenon lamp, and Figure 18(b) shows the spectral irradiance of the xenon lamp in the test that is extracted by an Ocean 2002 spectrometer. A total length of 740 mm RGOF with a cross-sectional area of 10 mm × 0:4 mm and a total length of 740 mm round optical fiber with 1 mm diameter have been fabricated for measuring the relative transmission of RGOF at different angular propagations of a focused light. Table 3 shows the conditions of the test. Figure 19 shows that round optical fibers follow the cosine of incident light while RGOF has a higher relative transmission. The length of rectangle in RGOF is 10 mm that makes it suitable for a focused light with a diameter of less than 2 mm. The result may be used in harnessing the light around the solar cells in the receiver of a CPVD. The light at the middle of the focal plane is uniform enough for multijunction solar cells, and the light around the cells may be transmitted by bundles of RGOF.
The fabricated RGOF has just a thin layer of polymer as the clad where it has been examined with bending and twisting tests. Figure 20 shows the demonstration on the bending and twisting tests of RGOF. The fabricated fiber is bent on a cylinder with 350 mm diameter and twisted 90°along its longitude axis with a length of 2.2 m. The minimum radius of bending for the fabricated RGOF was 150 mm with a crosssectional area of 10 mm × 0:4 mm. A lower radius may be achieved by an additional coating process.
Conclusion
In this study, the concept of introducing RGOF to transmit sunlight in a CPVD system is proposed and analyzed in detail. Relative transmission of RGOF for incident angles ranging from 0°to 25°has been studied via a mathematical model, numerical simulation, and experiment. The simulation result reveals that a RGOF with a cross-sectional area of 10 mm × 0:5 mm has a higher relative transmission as compared to that of a glass round optical fiber with a core diameter of 1 mm while it is exposed to the focused light with a diameter of spot size less than 2 mm. The results of experiments and simulations are limited to the collimated and focused white-light source with the spectral irradiance close to the standard solar spectrum. Moreover, the second limitation is that the relative transmission of RGOF is measured for the incident angles of light beam less than the acceptance angle of the optical fiber. A bundle of RGOFs can achieve higher efficiency in both coupling and transmitting light power as compared to a bundle of round fibers. The bundle of RGOFs has less gap spacing between fibers. The simulated result shows a good matching between of output flux distribution and the dimension of the solar cell for the case of RGOF, which is consistent with the higher coupling efficiency of RGOF. The beam profiles of both the RGOF and the round glass optical fiber under propagation of a focused light have been validated via analytical formula and numerical simulation. The profile of the output light of RGOF has 14 International Journal of Photoenergy been investigated experimentally. A top-hat profile matches with the result of the propagating laser beam to the rectangular glass optical fiber. In the last section of our study, tests on the flexibility of our designed and fabricated RGOF in both bending and twisting have been carried out. In this test, RGOF can be bent with a radius of 150 mm and twisted 90°a long the axis of the fiber at a fiber length of 2.2 m.
Data Availability
The data will be available upon request.
Conflicts of Interest
The authors declare that they have no conflicts of interest. | 7,128.8 | 2020-11-26T00:00:00.000 | [
"Physics",
"Engineering"
] |
Transient dynamics of cold-rolled and subsequently thermally rejuvenated atactic-polystyrene using broadband dielectric spectroscopy
• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
| INTRODUCTION
One of the most fascinating subjects in condensed matter science is arguably the state of a glass. The frequent use of polymeric glasses in high-level applications, such as medical and aviation applications, makes understanding of their intrinsic mechanical response inevitable. Polymer glasses are out of equilibrium, and their evolution toward equilibrium is generally known as physical aging. [1] The effect of physical aging can be erased by increasing the temperature above the glass-transition temperature of the material, that is, thermal rejuvenation. [1] It is also generally accepted that with deformation far beyond the yield strain, the dynamics of a polymer glass undergo changes that also lead to the erasure of physical aging, a phenomenon called mechanical rejuvenation. [2] Thermally and mechanically rejuvenated glasses have similar macroscopic properties, [3] however microscopically they may be rather different (e.g., anisotropy). A recent investigation on polymer glasses concluded that the thermally and mechanically rejuvenated glasses are in different states, and that mechanical deformation leads to an amorphous-amorphous phase transition. [4] Their results are confirmed by positron-annihilation lifetime spectroscopy experiments on a-PS and polycarbonate (PC) based on the fact that the free volume follows a completely different time-evolution for mechanically rejuvated films compared to the thermally rejuvenated ones. This idea has also been supported theoretically by other studies. [5][6][7] In his thorough review on the subject of mechanical rejuvenation, McKenna [8] discussed the possible interpretations of the erasure of history of glassy materials with deformation below and above the yield point. At least close to T g , the presented results of torsional dilatometry experiments prove that the free volume of the glass is not rejuvenated below the yield point. [8] Deformation above the yield point leads to a different DSC trace as compared to a thermally rejuvenated polymer, a sub-glass transition minimum is observed for the deformed polymer for which the molecular picture is not fully understood. McKenna suggests that deformation above the yield point in the polymer leads to a polyamorphic phase transition and not to rejuvenation, based on the fact that the yield stress does not reach the same value after thermal rejuvenation and aging as compared to mechanical cycling and aging. [8] Intriguing observations have been reported on density measurements on various cold-rolled glassy polymers. [3,9] Thermal rejuvenation is known to cause a decrease in the density, cold rolling, however, shows an increase in density.
Increased segmental mobility upon mechanical deformation has been observed in various studies, [10][11][12][13] and modeling studies argue that the increased segmental mobility is associated to different explored energy landscape regions in contrast to thermal rejuvenation. [14,15] A study by Donth and Michler [16] proposes that the increased molecular mobility is a result of the formation of fibrillar structure crazes. According to their studies, two types of crazes are formed: (a) precrazes which are related to the molecular mobility of a confined flow zone and (b) proper crazes which relate to the molecular mobility of a flow transition zone.
The interpretation of increased mobility with deformation below the yield point should be discussed attentively. McKenna [8] indicates that the glassy structure is independent of the mechanical stress. Specifically, evidence is provided that the mechanical equilibration time of a glassy material is not changed after mechanical perturbation. However, mechanical measurements cannot, possibly, be conclusive, since it is known that the equilibrium time scales property dependent. [17][18][19] Mechanical stress below the yield point accelerates aging and densifies the glass.
Time-strain superposition master-curves for polycarbonate are different than the time-temperature master-curves, implying that temperature and strain influence the relaxation response of the glass in different ways. [20] O'conell et al. [20] states: "Because time-temperature superposition has been successful and deviations from it usually reported to be only subtle, our preliminary conclusion here is that the time-strain master-curve is not the correct mastercurve. Further work needs to be done to establish the apparent validity of the time-temperature master-curve." Regardless of the ongoing research concerning the effect of mechanical rejuvenation on mechanical and thermodynamical properties, there is little understanding from a microscopic viewpoint. Many techniques have been used to study the physical properties of mechanically deformed glass formers; nonetheless, only a minority can probe the dynamics in an extensive frequency or time range. Broadband dielectric spectroscopy is one of these few methods that can easily cover more than 10 orders of magnitude in time/frequency. Most attention has been paid to the study of glassy polymers during deformation [13,21] and is limited to the αand β-transitions. Since a-PS is a weakly polar material resulting in a low strength of the dielectric relaxations, studies using dielectric relaxation spectroscopy are experimentally challenging and hence sparse. [22,23] In this study, we report, for the first time, dielectric relaxation data on a-PS just after cold-rolling, and after subsequent thermal rejuvenation. To the best of our knowledge, no material has been studied in this way before. Supporting FTIR spectroscopy and polarizedlight microscopy studies connect the molecular dynamics with changes in the molecular structure of a-PS.
| Materials
Atactic PS with the commercial name N5000 was kindly supplied in pellet form by Shell. The molecular weight and poly-dispersity index of the a-PS were determined by High-Performance Liquid Chromatography (HPLC) using a Shimadzu HPLC instrument (Prominence-I, LC 2030C 3D). A comparison of these quantities prior to rolling (M w = 320.700 g/mol, PDI = 2.22) and after rolling (M w = 319.200 g/mol, PDI = 2.23) confirmed the absence of any significant change of the molecular weight (distribution) upon cold rolling as for example, caused by chain scission.
| Sample preparation
The preparation of films (0.13 mm thickness) was performed by compression molding at 185 C under vacuum. Initially, the pellets were compressed in three steps of rising pressure from ≈23 MPa up to ≈70 MPa. Thereafter, the mold was cooled down to room temperature at a pressure of approximately 23 MPa between two cold metal plates.
To further reduce the surface roughness, the acquired films were recompressed between two Kapton foils at 185 C at ≈70 MPa for 10 min under vacuum. Eventually, the specimens were cooled down to room temperature at ambient pressure.
| Treatments
Cold rolling of the a-PS films was performed by rolling in a Durston DRM C100 two-roll mill (diameter of rolls 50 mm) until the thickness of the films was reduced by 20-30% of their initial thickness. The samples were then inserted into the dielectric sample cell that was precooled in advance to a temperature of ≈−100 C in order to arrest their cold-rolled state. In order to avoid moisture absorption during mounting of the sample, all sample handling around the dielectric cryostat took place under a flow of dry, gaseous nitrogen. Subsequently the sample was heated well above its T g (thermal rejuvenation) and then cooled down with the same rate of 3 K/min.
| Broadband dielectric relaxation spectroscopy (BDRS)
Employing a high-precision dielectric ALPHA analyzer (Novocontrol Technologies) connected to a Novocontrol Quatro temperature system keeping control of the specimen temperature (≤0.05 K), dielectric measurements were performed from −130 C to 180 C in a continuous frequency-sweep mode from 10 0 Hz to 10 6 Hz, while a temperature ramp at 3 K/min was employed in both heating and cooling stages. The specimens (20 mm in diameter and thickness of ≈60 μm) were clamped between polished stainless steel electrodes.
To determine the relaxation time τ(T) and other relaxation parameters, the dielectric loss spectra ϵ 00 (ω) acquired at various temperatures were fitted to the imaginary part of the empirical Havriliak-Negami (HN) relaxation function, [24] ϵ 00 = −Im Δϵ where Δϵ denotes the relaxation strength, while a and b ("shape parameters") relate to the logarithmic slope of the low-frequency loss tail (a) and the high-frequency loss tail (−ab). The last term accounts for Ohmic conduction, with conductivity σ, vacuum permittivity ϵ ν and angular frequency ω = 2πf. A thorough description of the analysis of dielectric data can be found in the work of Wübbenhorst et al. [25] and Van Turnhout et al. [24] 2.5 | Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) The a-PS films were measured in the range of 400-4,000 cm −1 at a resolution of 4 cm −1 and a total of 20 scans with a FTIR PERKIN ELMER Spectrum Two spectrometer in reflection mode. Two measurements were performed on each sample. For analysis of the data, the baseline-corrected spectra were normalized with the 1,451 cm −1 peak which is conformationally insensitive and therefore used as internal standard. The difference spectrum was obtained by subtraction of the spectrum of the not-rolled from the cold-rolled specimens. Since the FTIR measurements were performed perpendicularly to the polymer film plane, possible effects arising from the in-plane anisotropy of the film are averaged out and are not manifested in the absorption spectra.
| Polarized-light microscopy
Polarizing-light microscopy measurements (Zeiss Axio Imager D1) were performed for observing the internal stresses of the samples. The morphology was captured by a Zeiss AxioCam MRc 5 camera. Figures 1 and 2 show the effect of cold rolling and subsequent quenching to a temperature of approximately −100 C on the molecular dynamics of a-PS. Six processes are detected, which are labeled in order of increasing temperature. Considering the isochronal loss curve for f = 61 Hz, first, at −110 C the γ-relaxation (I) is observed followed by a second, low-temperature process (II) located around −70 C. At higher temperatures, three additional relaxation modes (III), (IV), and (V) can be distinguished around 20 C, 50 C, and 75 C, respectively. Though hard to resolve in the first heating run, process IV becomes clearly visible in the second heating as a low-intensity, isolated relaxation process, (Figure 2a). A fifth transition (V) appears at around 75 C (61 Hz) and is followed by the dynamic glass transition, the α-relaxation (VI) around 120 C. Opposed to the primary α-relaxation (VI) and the γ-process (I) that are known from earlier studies, the other identified processes (II, III, IV and V) have not been reported in literature before. The relaxation-time data, calculated either by the fit of isothermal spectra ϵ 00 (ω) to Equation (1) or by using a 2D fit procedure, [25] are shown in the Arrhenius diagrams, see Figure 3. The main α-process, easily discernable by its characteristic curvature in the temperature dependence of the relaxation time, τ(T), (see Figure 4), was fitted to the Vogel-Fulcher-Tamman (VFT) law, [22]
| Dielectric relaxations
with E V and T V being the Vogel activation energy and the Vogel temperature, respectively. The parameters R and τ ∞ denote the universal gas constant and the limiting relaxation time at T ! ∞.
All processes except the primary α-process and process V show Arrhenius-like behavior, each with different activation energies, E A , according to: The fit parameters for the six relaxations are listed in Tables 1 and 2. The six processes can be classified as follows: Starting from the lowest temperature (Figures 1a and 2), process I can be observed, its low activation energy of 33.8 kJ/mol is typical for a local conformation transition. [23] At a somewhat higher temperature, process II emerges, characterized by an activation energy of 60.6 kJ/mol ( Figure 3). Around 20 C (at 61 Hz), the process III is spotted (Figures 1a and 2) (activation energy of 70.6 kJ/mol), followed by process IV located at around 50 C and characterized by similar activation parameters. At even higher temperatures, at around 75 C the relaxation mode V shows up, but disappears just after passing 80 C (cf. 2D fit clearly revealed VFT-behavior for the relaxation mode V being indicative for a dynamic glass transition. As expected, the main α-relaxation (VI) also obeys a VFT-behavior, characteristic for segmental mobility of bulk a-PS (Figure 4a). Heating the sample above its glass transition, thermal rejuvenation starts, resulting in a removal of the thermomechanical history of the sample and the restoration of the common dynamic pattern of a-PS consisting of two "usual" relaxation processes, namely the primary α-relaxation and γ-relaxation processes (Figure 1b). Although the VFT-parameters for the thermally rejuvenated sample differ significantly from those of the freshly rolled film, the actual differences in the relaxation times are only significant at temperatures just above T g (Table 1 and Figure 4). In the 2nd heating run, the γ-process (I) is again weak in intensity and shows a reduced activation energy around 21 kJ/mol ( Table 2).
The commonly used Arrhenius analysis provides us with information on the activation energies of the new processes, however due to complexity of these processes it is difficult to proceed to a microstructural interpretation. [26] (b) (a) F I G U R E 2 Dielectric spectra of tan δ versus temperature as measured at frequencies of 61 Hz (a) and 976 Hz (b) for the cold-rolled a-PS (blue circles) versus the second heating cycle of the same sample (red circles). The data correspond to the dotted lines in Figure 1 [Color figure can be viewed at wileyonlinelibrary.com] (b) (a) F I G U R E 3 Measured and fitted loss curves ϵ 00 (T) at f = 3.8 Hz (a) and 15 Hz (b) for cold-rolled a-PS, which were fitted to a unique set of three HN functions in combination with a temperature dependent relaxation time τ(T) assuming either Arrhenius-(III, IV) or VFT behavior (V). For this two-dimensional "global" fit procedure described in Wübbenhorst et al., [25] dielectric loss data were used in the temperature range from −30 C to 70 C (orange symbols) at frequencies from 1.9 Hz to 13 kHz. Two examples of fitted data along the T-axis are displayed, however, equally low deviations between measured data and the fit function were achieved in the entire f-and T-range. Note that calculated fit data above 70 C have no physical meaning because of structural changes caused by the fibrillar glass transition (V) and are thus excluded from the fit [Color figure can be viewed at wileyonlinelibrary.com] We therefore further analyzed the activation parameters in terms of their activation entropies (ΔS) and activation enthalpies (ΔH*), using the analysis introduced by Starkweather [26] and applied for example, by Meersman [27] for plastic crystals. Here, ΔH* has the meaning of the theoretical activation enthalpy associated with a zero activation entropy. Table 3 shows the values for T 1Hz , the temperature at which the peak of the corresponding process is located at a frequency of 1 Hz (obtained from fitting), ΔH*, ΔS, T 1Hz ΔS, E A = T 1Hz ΔS + ΔH* and T 1Hz ΔS/E A for the IV-, III-, II-and I(γ)-relaxations of cold-rolled a-PS. A process where T 1Hz ΔS/E A is less than 10% can be considered as "practically non-cooperative", while relaxations substantially exceeding the 10% limit are characterized by a significant entropic contribution to E A . Now, starting from low temperatures, it appears that the I(γ)-relaxation has an entropic contribution T 1Hz ΔS/E A of 7%, supporting its earlier assignment to a non-cooperative, local conformation transition. [26] In contrast, relaxations (b) (a) F I G U R E 4 (a) Activation diagram showing the relaxation times τ α , τ V , τ IV , and τ III for the cold-rolled a-PS either obtained by a conventional fit in the frequency domain (discrete data points, dashed lines), or using the above mentioned two-dimensional fit procedure (solid lines). Here, process III could be fitted by both methods and could also be detected in a second heating scan (blue triangles). T A B L E 1 Activation parameters and their standard deviation for the α-process found in a-PS for different treatments Note: Processes III and IV were fitted using a two-dimensional fitting procedure. [25] II and III clearly show an entropic barrier as indicated by values T 1Hz ΔS/E A of 28% and 15%, respectively. [26] Noteworthy, as indicated by its low T 1Hz ΔS/E A of 3%, the process IV seems to be of noncooperative nature. Figure 5 exhibits the normalized and difference infrared ATR-FTIR spectra for a-PS before and after cold rolling.
| ATR-FTIR spectra
T A B L E 3 Activation parameters (ΔS and ΔH*) fitted according to Starkweather's procedure for the I, II, III, and IV-processes found in cold-rolled a-PS Note: T 1Hz ΔS/E A is the entropic barrier in comparison to the apparent activation barrier (Arrhenius). Processes III and IV are fitted with a two dimensional fitting procedure. [25] (b) (a) The negative bands in the difference spectrum are connected to the vibrational modes of the main chain at 2,848 cm −1 (CH 2 symmetric stretching) [28,29] and 2,923 cm −1 (CH 2 asymmetric stretching). [28,29] The positive bands are associated with the phenyl groups. Two bands that change considerably with cold rolling are the bands appearing at the difference spectrum at around 538 cm −1 and 754 cm −1 which show a positive change. The 538 cm −1 band is associated with the δ-form helical structure of syndiotactic polystyrene [30][31][32] which is considered to be a short helix consisting of 7-12 monomeric units. [33] The 754 cm −1 band is also considered to be associated with δ-form helices. [32] These helices are formed by T 2 G 2 conformational sequences. [34][35][36]
| Polarized-light microscopy
In Figure 6, the polarized-light microscopy photos for a-PS subjected to cold rolling ( Figure 6a) and subsequent thermal rejuvenation (Figure 6b) are shown. The effect of cold rolling on the creation of orientation and internal stresses in the polymer is observed by the color pattern under polarized light. Thermal rejuvenation erases the internal stresses of the a-PS films, as can be seen in Figure 6b.
| DISCUSSION
The wealth of relaxation data obtained for freshly coldrolled a-PS provides the unique chance to derive a microstructural model that rationalizes all molecular dynamics features. A cartoon of our new model is shown in Figure 7 and will be discussed in the following.
(a) γ-process (I). The γ-process, visible in (Figures 1a and 2), is a well-known dielectric relaxation process of a-PS and has been reported by several authors before. [23,37,38] Its strength and activation energy are very sensitive to the microstructure as demonstrated by recent aging experiments [38] as well as by results of this study. While the freshly rolled film showed an activation energy of 33.8 kJ/mol (Table 2), its value substantially dropped to 21 kJ/mol after thermal rejuvenation. Interestingly, such low value was also found by Arrese et al. [39] by neutron scattering experiments, concluding that the γ-relaxation of a-PS is associated with localized lowamplitude motions. The low activation entropy found in this study once more emphasizes the noncooperativity of this relaxation [26,40] (see Table 3).
(b) γ 0 -process (II). As seen in the Arrhenius diagram 4b, another secondary relaxation appears in just rolled a-PS, which is slower than the γ-process and characterized by a substantially higher activation energy of 60.6 kJ/mol (Table 2). Moreover, process II exhibits a very low preexponential factor log(τ ∞ ) = −17.8 that is far beyond any physical meaning in terms of a phonon-frequency being typically around 10 12 Hz. Closer inspection of Figure 4b actually reveals that all three Arrhenius dependences seem to converge to a single point where all curves intersect, a behavior known as compensation law [41] or Meyer-Neldel rule [42] indicating a correlation between the pre-exponential factor and the (apparent) activation energy. In terms of the Eyring and Starkweather approach, compensation behavior links relaxation processes that mainly differ in their activation entropy while the energetic contribution is varying only a little. From Table 3 we indeed see that ΔS is the essential parameter that distinguishes process I from II. Consequently, we F I G U R E 6 Polarized-light microscopy photos of a cold-rolled a-PS film (rolling direction: right to left) (a) versus a subsequently thermally rejuvenated film (b). When no stresses are observed for the rejuvenated sample, the orientation and internal stresses due to cold rolling on the film is evident [Color figure can be viewed at wileyonlinelibrary.com] think that both relaxations essentially share the same molecular mechanism of a γ process (i.e., conformation transition [43] ) originating from chain segments in different conformational states affecting the activation entropy. The limited variation in ΔH* can be rationalized by changes of intermolecular interactions as the result of different chain-packing and thus density, while intramolecular (predominantly rotational) energetic contributions might be maintained. The co-existence of two processes having a common nature, I and II (consequently labeled as γ 0 ) is a first strong hint for the formation of a heterogeneous microstructure in a-PS upon cold-rolling, comprising a moderately deformed matrix together with highly oriented fibrillar structures as reported and extensively studied by Donth and Michler. [16] In this scenario, based on its higher activation entropy (ΔS = 0.092 kJ/(mol K)), the γ 0 -process should be assigned to highly stretched chains located in the fibrillar fraction. Though direct imaging of fibrils was not possible in the framework of this study, experimental evidence for optical anisotropy and heterogeneity was provided by polarized microscopy (Figure 6a) as well as by FTIR showing a negative difference spectrum of the vibrations connected to the symmetric and asymmetric stretching of main-chain bands (Figure 5a).
(c) Process III. Toward higher temperatures, a broad and strong III-relaxation is observed (−16 C to 30 C at 61 Hz) (Figures 1a and 2) with an activation energy of around 70.6 kJ/mol ( Table 2). This unfamiliar process has a similar activation energy as the β 1 -and β 2 -processes found in a-PS and s-PS by Lupaşcu et al., [22] who attributed these relaxation modes to a defect mechanism (helix inversion) of T 2 G 2 helices (Table 4). Despite its very similar activation energy, the process III is about two decades faster than the β 1 -process. The presence of T 2 G 2 helices could indeed be confirmed by ATR-FTIR, see the difference spectra in Figure 5, favoring the idea of defect fluctuations within syndiotactic helices as the molecular mechanism behind process III. [22] An explanation for the high activation energy and substantial activation entropy of process III is a relaxation mechanism involving T 2 G 2 helices. Considering the findings on oriented fibrillar material reported by Li et al., [44] we speculate that the observed helices in the ATR-FTIR spectra ( Figure 5) together with the highly activated III-process may point to helical structures being part of the highly stretched fibrils. Additional support for this idea comes from the observation (cf. Figure 4a) that relaxation III significantly slows-down upon softening of the fibrils around 70 C (see Section 4) suggesting a certain sensitivity of the helix inversion process to chain stresses. Alternatively, the same observations might be rationalized by assuming helices located at the (large) fibrillar surface, resulting in surface enhanced segmental mobility along with a peculiar relaxation mode similar to process III as found for ultrathin films of a-PS. [45] With the removal of strain softening, glassy polymers display ductile behavior. [46,47] The presence of defects in crystals of i-PP (isotactic polypropylene) creates high ductility and flexibility because of polymorphic transformations that occur during deformation. [48] By combining these two observations, we propose that a similar mechanism is responsible for the ductile behavior of mechanically rejuvenated PS in which, during deformation, the trans-trans (amorphous) sequences are forming short-length defect helices that create the macroscopically observed flexibility. (d) Process IV. Inspecting Figure 4a and Table 2, we clearly recognize the similarity between processes III and IV regarding their activation parameters. While process III was actually found to be faster than the β 1 -relaxation known for s-PS, the activation parameters of process IV unambiguously identify this relaxation as β 1 -relaxation [22] ascribed to the helix inversion dynamics of single helices under bulk conditions. This helical fraction might be located either in the polymer matrix or in the inner part of the fibrils.
(e) α*-process (V). This prominent relaxation is a key feature of the dielectric relaxation pattern of just rolled a-PS. According to our two-dimensional fit procedure, process V is characterized by VFT behavior being the signature of a dynamic glass transition (Figures 2, 3, and 7). Below 70 C, this relaxation process becomes visible in a small temperature window as rapidly moving (highly activated) relaxation process, which starts to vanish abruptly after exceeding 70 C. The latter phenomenon is particularly striking and manifests itself as a frequency independent peak in the dielectric loss as seen in the isochronal representation ϵ 00 (f, T) (cf. Figure 2), suggesting the action of a thermal transition at around 75 C.
The observation of a thermal transition around that temperature has been reported before by calorimetry. A series of custom-made Deformation Calorimetry (DC) experiments [49] on glassy polymers such as polystyrene (PS), polycarbonate (PC) and poly (methyl methacrylate) (PMMA) revealed that plastic deformation below the bulk glass transition results in high internal energy storage, that is released upon heating of the sample and appears as an exothermic abnormality in the region below T g in DSC. [49,50] Molecular Dynamic simulations [10] also confirmed that the stored internal energy in PS and PC glasses after plastic deformation is remarkably high. Such behavior is explained in terms of localized shear transformation zones (STZ's). [51] We think that the process V actually represents the onset of segmental dynamics of highly stretched fibrils, which have a substantially lower T g because of their large surfaceto-volume ratio (confinement effect) similar to ultrathin polymer films. [45] Once the fibrils are heated above their T g , the fibrils soften and subsequently collapse by virtue of retraction of stretched segments to their random coil configuration. As a consequence, the fibrillar structures fuses and internal surfaces within the crazes disappear, a process that goes along with a dynamic freezing of the former fibrillar fraction by concurrent up-shifting of its glass transition temperature (physical aging). [16] (f) Primary α-relaxation process (VI). As already discussed above, the α-process of the just rolled sample nearly coincides with that after thermal rejuvenation. Little differences in the relaxation time τ α are restricted to temperatures just above the volumetric glass transition T g , while at about 120 C the relaxation time curves collapse (Figure 4a). This observation is in fact not surprising and just confirms that heating well above the bulk T g restores bulk dynamics at the time-and length scale of segmental motions. In other words, there is no evidence that chain deformations arising from prior plastic deformation persist after high temperature treatment.
| CONCLUSIONS
By the results presented above, yet unknown dynamics of cold-rolled a-PS, a polymer widely used in industry and broadly investigated in academia, have been uncovered. Using fast dielectric relaxation spectroscopy, four new relaxation processes II, III, IV, and V for atactic polystyrene after cold rolling and quenching, are unveiled for the first time. Subsequent thermal rejuvenation suppresses all these peculiar processes and restores the typical relaxation behavior of a-PS, the α-relaxation and a weak γ-process. A detailed discussion of all relaxation processes in the framework of craze formation and multiplicity of the glass transition, [16] supported by an activation enthalpy/entropy analysis by Starkweather, [40] yields a detailed physical picture about the structure/dynamics relationship in cold-rolled PS: (a) processes I (γ) and II (γ 0 ) represent local conformation transitions, referring to chains of two different degrees of stretching (T/G-ratio); (b) processes III and IV were identified as helix-inversion processes of T 2 G 2 helices as reported earlier for syndiotactic-rich PSan assignment that was supported by FTIR results showing indeed the formation of T 2 G 2 helices upon cold rolling. Finally, the relaxation V could be attributed to the onset of the fibrillar glass transition (within crazes) around 70 C, leading to abrupt stress release by collapse of the fibrils and hence dying out of process V. Polarized-light microscopy confirmed the creation of oriented structures and internal stresses upon cold rolling, and their removal upon thermal rejuvenation. This work provides first data and a physical picture regarding the (transient) molecular dynamics in mechanically rejuvenated compared to thermally rejuvenated a-PS, which might help to unravel the mechanism of temporary toughening in a-PS induced by cold-rolling in the near future. A possible mechanism behind the macroscopic ductility of mechanically rejuvenated samples is proposed. Our findings could be corroborated via other experimental techniques to obtain more information on mechanisms underlying the mechanical rejuvenation, for example, X-ray scattering or nuclear magnetic resonance spectroscopy. Moreover, in the context of molecular dynamic simulations, our findings suggest that the initial conditions should be carefully chosen, taking into account the spatial heterogeneities. | 6,808.2 | 2020-07-15T00:00:00.000 | [
"Materials Science"
] |
Study of the adherence capacity of microbial biofilms on titanium versus zirconium dioxide (Zirconia) surfaces
Introduction. An important role in the appearance of acute or chronic infections is played by bacterial biofilms that contain several bacterial species and that develop preferentially on inert surfaces, dead tissues and medical devices. Purpose. In this material we tried to make an interesting study, regarding the adhesion capacity of microbial biofilms characteristic of the oral cavity of human subjects on the surface of materials used for industrial scale manufacturing of dental implants: titanium and zirconium dioxide (Zirconia). Material and methods. For this study were used plates of Ti4 and zirconia, on which adhesion of different bacterial strains belonging to the species Enterobacter cloacae, Klebsiella oxytoca and Klebsiella pneumonia were tested. Results and discussions. A rather high microbial load was observed on both types of materials for all types of bacterial strains studied. For certain types of strains, a lower colonization was noted in the case of zirconium dioxide compared to Ti4 surfaces. Conclusions. Although Zirconia has been reported to have a lower susceptibility to bacterial adhesion, our study contradicts this aspect specified in the literature. Both titanium and zirconium dioxide are promptly colonized by existing bacteria on the teeth left in the oral cavity.
INTRODUCTION
Human being has been the victim of acute epidemic infectious diseases, caused in more than half of the cases of bacterial species, living together on / or in the human body or in the environment, causing chronic in-fections sometimes very serious, such as immuno-compromised patients (1)(2)(3)(4)(5).
An important role in the occurrence of acute or chronic infections is played by bacterial biofilms that contain several bacterial species and that grow preferentially on inert surfaces, dead tissues and often on medical devices, including prosthetic devices and other materials for medical use, for example: sutures (Staphylococcus epidermidis, S. aureus), contact lenses (Pseudomonas aeruginosa, Gram-negative shells), prosthetic restorations on implants or classic (fixed and mobile), occlusal rims, trial dentures, impression materials and dental impressions (various bacteria and fungi), venous catheters (Staphylococcus epidermidis), mechanical valves (Staphylococcus epidermidis, S. aureus), endotracheal tubes (different bacteria and fungi) etc. (6)(7)(8).
Examination by electron microscopy on the surface of medical devices or tissues taken from patients with chronic infections, unrelated with medical devices, revealed the presence of bacterial biofilms, which appear surrounded by a matrix of extracellular polysaccharides (1)(2)(3)(4)(5).
PURPOSE
Titanium has many applications in dentistry, being used in almost all areas of this medical specialty, but especially in implant-prosthetic rehabilitation. In implant-prosthetic rehabilitation, titanium can be used either in the form of dental implants, or in the form of cast or processed (milled) using computerized CAD-CAM systems in the manufacture of metal infrastructure, in the case of fully physiognomic mixed metal-ceramic implant-supported prosthetic restorations.
Another material used successfully in these first decades of the 21 st century in implant-prosthetic rehabilitation is zirconium dioxide (ZiO 2 ) or more simply Zirconia, as it is known in the literature. In implant-prosthetic rehabilitation, this revolutionary material is used, similar to titanium, both for the manufacture of dental implants and for the manufacture of infrastructure for fully physiognomic prosthetic restorations with implant-supported ceramic component. Among the major advantages of using zirconium dioxide (Zirconia) are the following aspects: very good biocompatibility, excellent physiognomic appearance, very good resistance to pressure and abrasion etc. (1)(2)(3)(4)(5)9).
But what should be mentioned in this study is that both materials, titanium and zirconium dioxide (Zirconia) being the only materials actually used in the manufacture of dental implants, both types of tissue integrations (bone and gingival) that occur (gingival integration in human subjects and epithelial-conjunctive integration in experimental studies in animals, but also bone integration in human subjects, as well as in animal studies) are very good. However, in order to achieve a proper tissue integration, a number of conditions need to be met, of which the degree of adhesion to these 2 materials of microbial biofilms must be specified in particular. Basically, depending on the biofilms formed on the surface of dental implants made of tita-nium or zirconium dioxide (Zirconia), their degree of infectivity, etc., the tissue integration (epithelial, conjunctival and bone) of these medical devices can be decisively influenced, in the context of an implant-prosthetic rehabilitation of a greater or lesser extent (10)(11)(12)(13).
Thus, we tried to make a very interesting study, even if it is only a preliminary one, regarding the ability of some microbial biofilms characteristic of the oral cavity of human subjects, on the surface of some materials used for industrial scale manufacturing of dental implants: titanium and zirconium dioxide (Zirconia).
Specifically, the objectives of this study are to obtain methodological and scientific information on bacterial biofilms, relevant to human health, in order to improve the prophylactic and therapeutic methods of infections caused by them, to assess the opportunity and effectiveness of antimicrobial therapy, by studying the resistance of biofilms to the action of antimicrobial substances.
MATERIALS AND METHODS
The study was performed on bacterial strains from the collection of the Research Institute of the University of Bucharest, Department of Life Environment and Earth Sciences. The strains tested are part of the Enterobacteriaceae family and belong to the species Enterobacter cloacae, Klebsiella pneumoniae and Klebsiella oxytoca. These microbial strains have been isolated from a number of 36 patients (we are talking about volunteer subjects who have given their consent for this harvesting maneuver), implant-prosthetic rehabilitated patients in the last 3 years (fixed implant-supported prosthetic restorations) and were identified by MALDI-TOF mass spectroscopy, Bruker.
The tested bacterial strains were harvested using dental scaling instruments from the dental plaque localized below or above gum line, from the aforementioned volunteer patients. After sampling, the samples were kept and transported sterile in RTM (Reduced Transport Medium; -container specially equipped with transport medium) to the Research Institute of the University of Bucharest, Department of Life, Environment and Earth Sciences, where they were processed, entering in the collection of microbial strains of this research institution. Certainty identification of microbial strains was achieved by establishing the biochemical profile, with the help of API tests (Analytical Profile Index) (14)(15)(16)
Evaluation of the microbial biofilms' formation on inert substrate
The quantification of biofilm formation on surfaces represented by commercially pure titanium grade 4 (identified as (Ti4) (presented in the form of plates) and sintered zirconia tablets was determined by evaluating the number of colony-forming units (CFU). The materials used, after pre-sterilization with UV for 30 minutes on each side, were contacted with an inoculum of 1.5 x 105 CFU/mL from each strain for 24 hours.
After incubation, each material was carefully washed to remove unadhered bacteria, deposited in 500 µl saline and vortexed for 30 seconds at maximum speed to remove adherent bacteria on the surface. From the resulting solution, serial decimal dilutions were made and seeded in agar medium to determine the number of CFU/mL.
RESULTS AND DISCUSSIONS
The oral microbiome comprises about 700 phylotypes, of which more than half can be present at any time in the oral cavity of a healthy individual (17).
The initial adhesion of bacteria on the surfaces in the oral cavity occurs very quickly after cleaning (brushing) the teeth. Bacterial adhesion has been reported to occur within 5 minutes after inserting sterile enamel or synthetic carbonic hydroxyapatite surfaces into the oral cavity (18).
Implant-supported prosthetic restorations are a treatment widely used in dental practice. Numerous studies published in the literature report high success rates over time, but late clinical complications have also been reported, which, if not identified and treated in time, can lead to serious implantation failures. Complications are mainly due to peri-implant infections (periimplantitis), as a result of an inflammatory process caused by microbial penetration through the im-plant-abutment interface and colonization of implant surfaces/components (19).
In this study, the bacterial strains were put in contact with the test materials (commercially pure titanium grade 4 -Ti4 and Zirconia) in liquid medium (Figure 1). Their ability to adhere to the surfaces they came in contact with was quantified by determining the number of CFU/ml (Figure 2).
The analysis of the data obtained after determining the number of CFU / mL showed that the bacterial adhesion is similar in terms of the two materials tested, namely the fragments of Ti4 and Zirconia (sintered) (Figure 3).
Specifically, a rather high microbial load was observed on both types of materials for all types of bacterial strains studied, in the context in which in the literature, Zirconia (zirconium dioxide) has been reported as a revolutionary material not only in terms of biocompatibility, physiognomy and/or resistance to pressure and abrasion, but also a material with a strong antibacterial action, on which microbial biofilms adhere with considerable difficulty, but with a very low survival rate. Specifically, Zirconia has been reported to have a lower susceptibility to bacterial adhesion (20). However, the study conducted by us contradicts certain existing data in the literature.
As an example, in our study, in the case of Klebsiella sp. (see especially Klebsiella pneumonia strain 173) there is a slightly lower colonization on zirconium dioxide compared to commercially pure titanium grade 4 (Ti4). However, adhesion to a surface is conditioned by a number of factors, including chemical composition and surface topography.
Adherence is a major advantage for pathogenic bacteria, in terms of nutrient assurance, protection against antibodies and lysozyme, etc. Their multiplication, after adhesion, takes place at a much higher rate than non-adherent cells (21). a b
FIGURE 1. Appearance of Ti4 and Zirconia fragments (samples) in contact with bacterial strains (initial contact -a and appearance after 24 hours -b)
Both titanium and zirconium dioxide are promptly colonized by a bacterial community closely related to the microbial model of the remaining teeth (19).
Studies in the literature have indicated that the surface roughness is a major factor, which influences the adhesion especially in titanium, and much less in zirconium dioxide (22). More specifically, Zirconia is recommended as the material of choice in implant-prosthetic rehabilitation both because of its biocompatibility and because it has a much lower susceptibility to microbial biofilms compared to other materials of major utility in oral implantology (20)(21)(22).
But the oral microbiota is a risk factor when it is associated with dental implants made of two components: the implant itself and the implant abutment. Geodes and cavities inherent in dental implant-implant abutment assemblies can act as highly retentive areas for microbial biofilms (they have been likened in the literature to true caps for microbial biofilms), housing bacterial species that can cause inflammatory reactions in soft tissues around dental implant, which in a relatively short time can evolve and lead to implant failure.
However, studies on microbial adhesion in various materials used in dental practice and the impact over time of complex oral microbial biofilm on the clinical parameters of implant-worn prosthetic restorations are not yet very conclusive (20).
CONCLUSIONS
On both types of materials, a rather high microbial load was observed for all bacterial strains studied.
In the case of Klebsiella sp. (see especially Klebsiella pneumonia 173 strain), a slightly lower colonization of zirconium dioxide compared to commercially pure titanium grade 4 (Ti4) is observed. Although Zirconia has been reported to have a lower susceptibility to bacterial adhesion, our study contradicts this aspect specified in the literature.
Both titanium and zirconium dioxide are promptly colonized by existing bacteria on the teeth left in the oral cavity.
Starting from this very ability to colonize of microbial strains, we tried to find plant extracts with antimicrobial properties that would decisively disorganize the adhesion of microbial biofilms, but at this time we managed only very accurate studies in terms of microbiology and biocompatibility (which we will present in other articles), and in the future we will study the effect of these herbal compounds on possible corrosion processes, especially on titanium and its alloys. | 2,739.8 | 2021-01-01T00:00:00.000 | [
"Medicine",
"Materials Science"
] |
Research on a Micro-Processing Technology for Fabricating Complex Structures in Single-Crystal Quartz
Single-crystal quartz material is widely applied in the manufacture of resonators and sensors, but it is difficult to process because of its high hardness. A novel way to fabricate single-crystal quartz structures is proposed in this paper; the method includes quartz-on-silicon (QoS) technology and inductively coupled plasma (ICP) etching, which makes it feasible to fabricate complex structures with crystal quartz. The QoS method encompasses the bonding of silicon and quartz, followed by the thinning and polishing of quartz, which can enable the fabrication of an ultra-thin quartz wafer on silicon. In this way, instead of the conventional wet etching with hydrofluoric acid, the quartz layer can be easily etched using the ICP dry-etching method. Then, the structure of the pure quartz material is obtained by removing the silicon wafer. In addition, the silicon layer can be processed into the appropriate structure. This aspect overcomes the difficulty of processing a complex structure of single-crystal quartz with different crystal orientations. Thin single-crystal quartz wafers of Z-cut with a thickness of less than 40 μm were obtained by using this method, and a complex three-dimensional structure with an 80 μm width was also acquired by the ICP etching of the quartz wafer. The method can be applied to make both crystal-oriented quartz-based sensors and actuators, such as quartz resonant accelerometers.
Introduction
Single-crystal quartz material has captured significant attention, which is attributed to its outstanding material properties in sensor manufacturing [1,2]. Quartz crystal not only possesses the piezoelectric property, but also has excellent mechanical, electrical, and temperature characteristics. It is designed and manufactured for resonators, oscillators, and filters because of its exceptional performance in frequency stabilization and frequency selection [3,4]. Furthermore, the piezoelectricity of quartz material can be used to excite the resonators into vibration to simplify both sensor structures and excitation circuits [5].
The strong covalent bond characteristic of single-crystal quartz material makes it difficult to alter, and its high hardness and difficult processing characteristics also impede the improvement of device performance. The traditional methods used to process quartz structures mainly include fluoride-based wet etching [6], laser micro-/nano-processing (LMP) [7,8], and inductively coupled plasma (ICP) dry etching [9,10]. The depth of wet-etched quartz can reach 500 µm [11], but because of the anisotropy of quartz, the sidewall crystal edges can only be reduced through continuous experiments, and cannot be eliminated [12][13][14]. Because wet etching requires a specific orientation of quartz crystal, z-cut quartz is
The Design of the Overall Process
In seeking to fabricate a complex three-dimensional structure of single-crystal quartz with a good surface morphology, a novel processing method was proposed that covers the bonding of quartz on silicon (QoS), the thinning and polishing of QoS, and the ICP dry etching of quartz, as shown in Figure 1. Not only was the optimized single-step procedure shown to achieve good results via a sequence of experiments, but the three-step process also proved capable of achieveing excellent compatibility.
Micromachines 2020, 11, x 2 of 11 quartz crystal, z-cut quartz is often used for wet etching. According to the relationship between the cutting angle of the quartz crystal and the frequency-temperature characteristics, it is difficult to find the zero-temperature coefficient point of z-cut quartz within its working temperature range. In this case, the large temperature hysteresis of the sensors causes an additional complicated compensation. There are always some challenges when etching delicate and complex structures with different thicknesses using wet etching. Moreover, wet etching is not an environmentally friendly method. LMP-etched quartz ranges in depth from a few microns to hundreds of microns [15,16]. The local high temperature of LMP may cause the quartz to lose its piezoelectric activity, which is quite detrimental, yet the width of the high-temperature areas (over 15 μm) is difficult to narrow. Furthermore, the quality factor, single frequency, and aging rate of quartz resonators are largely determined by the smoothness, parallelism, and geometric correctness of the quartz's surface.
Inductively coupled plasma dry etching has proved effective for processing single-crystal quartz. The plasma-chemical etching process can etch a single-crystal quartz plate (z-cut) with a thickness of 369 μm through windows with large linear dimensions (3 mm × 10 mm) [17]. A few institutions have used ICP systems to achieve a depth of quartz of over 100 µ m [18,19]. However, small-sized structures are difficult to process in this way and have poor sidewall morphologies. Additionally, the typical single-quartz etching depth (with better morphology) is generally less than 50 μm [20][21][22]. Currently, the thickness of the single-crystal quartz wafer is generally more than 100 μm. Furthermore, considering the increasing fragmentation rate, the processing cost of a thinner quartz wafer will increase. Therefore, it is currently difficult to directly obtain sensors and actuators of crystal quartz using dry etching. The research on the combination of the bonding, thinning, and dry etching of single-crystal quartz in this study aimed to solve these problems by taking advantage of dry etching while avoiding its disadvantages to obtain a favorable device morphology.
The Design of the Overall Process
In seeking to fabricate a complex three-dimensional structure of single-crystal quartz with a good surface morphology, a novel processing method was proposed that covers the bonding of quartz on silicon (QoS), the thinning and polishing of QoS, and the ICP dry etching of quartz, as shown in Figure 1. Not only was the optimized single-step procedure shown to achieve good results via a sequence of experiments, but the three-step process also proved capable of achieveing excellent compatibility.
Bonding of Quartz and Silicon
The silicon wafer was bonded with the quartz wafer via direct bonding or auxiliary bonding to obtain the QoS wafer. The original wafers selected for bonding should have a good thickness uniformity and a low surface roughness. Before bonding, the silicon and quartz wafers should be cleaned ultrasonically using acetone and alcohol.
Bonding of Quartz and Silicon
The silicon wafer was bonded with the quartz wafer via direct bonding or auxiliary bonding to obtain the QoS wafer. The original wafers selected for bonding should have a good thickness uniformity and a low surface roughness. Before bonding, the silicon and quartz wafers should be cleaned ultrasonically using acetone and alcohol.
Direct Bonding
Direct bonding [23,24] involves the bonding of two polished wafers without any other materials. Mature anodic bonding is a well-known method for the bonding of silicon and glass [25,26], but it involves bonding at elevated temperatures (higher than 300 • C) with the assistance of a strong electrostatic field [27]. Furthermore, there are no sufficiently mobile alkali metal ions in single-crystal quartz to drive through the bonding interface under an external electric field. Because of the difference in the thermal expansion coefficients between silicon and quartz crystal, the internal stress mismatch at high temperatures leads to the bonded wafer's breakage. Moreover, quartz crystal loses its piezoelectric character because of the high temperature. Therefore, the low-temperature direct bonding of silicon and quartz was implemented in this work.
(1) The direct bonding process of quartz and silicon The direct bonding procedure entails surface cleaning, surface activation, initial bonding, pressurization, and heat treatment (annealing), as shown in Figure 2. The principle of bonding is Si-OH + Si-OH → Si-O-Si + H 2 O, as shown in Figure 3. A lot of -OH bonds are suspended on the surface of smooth silicon and quartz wafers to generate the surface state of Si-OH. When the two wafers are close enough, intermolecular forces and hydrogen bond forces coordinate to cause the two wafers' mutual attraction. The Si-OH bond attached to the surface of the wafers is dehydrated to form the Si-O-Si bond [28,29]. Thus, the weak intermolecular force is transformed into the strong force of a covalent bond such that the two bonding wafers are firmly bonded together. Direct bonding [23,24] involves the bonding of two polished wafers without any other materials. Mature anodic bonding is a well-known method for the bonding of silicon and glass [25,26], but it involves bonding at elevated temperatures (higher than 300 °C) with the assistance of a strong electrostatic field [27]. Furthermore, there are no sufficiently mobile alkali metal ions in single-crystal quartz to drive through the bonding interface under an external electric field. Because of the difference in the thermal expansion coefficients between silicon and quartz crystal, the internal stress mismatch at high temperatures leads to the bonded wafer's breakage. Moreover, quartz crystal loses its piezoelectric character because of the high temperature. Therefore, the low-temperature direct bonding of silicon and quartz was implemented in this work.
(1) The direct bonding process of quartz and silicon The direct bonding procedure entails surface cleaning, surface activation, initial bonding, pressurization, and heat treatment (annealing), as shown in Figure 2. The principle of bonding is Si-OH + Si-OH → Si-O-Si + H2O, as shown in Figure 3. A lot of -OH bonds are suspended on the surface of smooth silicon and quartz wafers to generate the surface state of Si-OH. When the two wafers are close enough, intermolecular forces and hydrogen bond forces coordinate to cause the two wafers' mutual attraction. The Si-OH bond attached to the surface of the wafers is dehydrated to form the Si-O-Si bond [28,29]. Thus, the weak intermolecular force is transformed into the strong force of a covalent bond such that the two bonding wafers are firmly bonded together. The first step was the surface cleaning. Two-inch, 400-µ m thick silicon wafers (silicon, RDMICRO, Suzhou, China) and 34 mm × 30 mm, 100 μm thick z-cut quartz wafers (quartz, LINDE, Xi'an, China) were selected for direct bonding, where wafers were polished on both sides. Almost all organic and inorganic contaminants on the substrate were completely removed through a series of cleaning steps, which consisted of concentrated sulfuric acid and hydrogen peroxide water bath Direct bonding [23,24] involves the bonding of two polished wafers without any other materials. Mature anodic bonding is a well-known method for the bonding of silicon and glass [25,26], but it involves bonding at elevated temperatures (higher than 300 °C) with the assistance of a strong electrostatic field [27]. Furthermore, there are no sufficiently mobile alkali metal ions in single-crystal quartz to drive through the bonding interface under an external electric field. Because of the difference in the thermal expansion coefficients between silicon and quartz crystal, the internal stress mismatch at high temperatures leads to the bonded wafer's breakage. Moreover, quartz crystal loses its piezoelectric character because of the high temperature. Therefore, the low-temperature direct bonding of silicon and quartz was implemented in this work.
(1) The direct bonding process of quartz and silicon The direct bonding procedure entails surface cleaning, surface activation, initial bonding, pressurization, and heat treatment (annealing), as shown in Figure 2. The principle of bonding is Si-OH + Si-OH → Si-O-Si + H2O, as shown in Figure 3. A lot of -OH bonds are suspended on the surface of smooth silicon and quartz wafers to generate the surface state of Si-OH. When the two wafers are close enough, intermolecular forces and hydrogen bond forces coordinate to cause the two wafers' mutual attraction. The Si-OH bond attached to the surface of the wafers is dehydrated to form the Si-O-Si bond [28,29]. Thus, the weak intermolecular force is transformed into the strong force of a covalent bond such that the two bonding wafers are firmly bonded together. The first step was the surface cleaning. Two-inch, 400-µ m thick silicon wafers (silicon, RDMICRO, Suzhou, China) and 34 mm × 30 mm, 100 μm thick z-cut quartz wafers (quartz, LINDE, Xi'an, China) were selected for direct bonding, where wafers were polished on both sides. Almost all organic and inorganic contaminants on the substrate were completely removed through a series of cleaning steps, which consisted of concentrated sulfuric acid and hydrogen peroxide water bath The first step was the surface cleaning. Two-inch, 400-µm thick silicon wafers (silicon, RDMICRO, Suzhou, China) and 34 mm × 30 mm, 100 µm thick z-cut quartz wafers (quartz, LINDE, Xi'an, China) were selected for direct bonding, where wafers were polished on both sides. Almost all organic and inorganic contaminants on the substrate were completely removed through a series of cleaning steps, which consisted of concentrated sulfuric acid and hydrogen peroxide water bath cleaning, as well as acetone and alcohol ultrasonic cleaning. The second step was the surface activation. Dry activation was implemented first on the surfaces of the quartz and silicon, followed by wet activation. Additionally, the surface of the treated wafers contained hydroxyl groups and was highly hydrophilic, as indicated in Figure 4. Atomic force microscopy (AFM) measurements indicated that the wafer surface treated using dry and wet activation had a root mean square (rms) surface roughness ranging from 0.2 to 0.3 nm.
Micromachines 2020, 11, x 4 of 11 cleaning, as well as acetone and alcohol ultrasonic cleaning. The second step was the surface activation. Dry activation was implemented first on the surfaces of the quartz and silicon, followed by wet activation. Additionally, the surface of the treated wafers contained hydroxyl groups and was highly hydrophilic, as indicated in Figure 4. Atomic force microscopy (AFM) measurements indicated that the wafer surface treated using dry and wet activation had a root mean square (rms) surface roughness ranging from 0.2 to 0.3 nm.
(a) (b) The third step was the initial bonding. First, the activated wafers were initially aligned and bonded in deionized water for preliminary pre-bonding. Then, a cold rolling pressure of 1 MPa in air was externally exerted, thereby removing the unbonded area's gas and water, and ensuring that the two wafers bonded more tightly. The pre-bonding wafer was pressurized and stored in air for 8 h to finalize the pre-bonding process.
The final step was the heat treatment (annealing). The bonding wafer was placed in a programmed oven for low-temperature annealing. The temperature was raised to 140 °C with a gradient of 1 °C/min and was maintained for 8 h.
(2) The detection of the direct bonding effect After the process of bonding the two wafers, the bonding quality was evaluated. The testing criteria mainly included the size of the bonding area, the bonding interface, and the bonding strength.
The size of the bonding area: Because of the transparency of quartz material, the bonding area of QoS could be observed via visual inspection, which is shown in Figure 5a. The quartz and silicon were largely bonded, but a small part of the edge of the quartz could not be bonded completely because of a poor edge flatness and the few inevitable contaminants that arose in the operating environment. The third step was the initial bonding. First, the activated wafers were initially aligned and bonded in deionized water for preliminary pre-bonding. Then, a cold rolling pressure of 1 MPa in air was externally exerted, thereby removing the unbonded area's gas and water, and ensuring that the two wafers bonded more tightly. The pre-bonding wafer was pressurized and stored in air for 8 h to finalize the pre-bonding process.
The final step was the heat treatment (annealing). The bonding wafer was placed in a programmed oven for low-temperature annealing. The temperature was raised to 140 • C with a gradient of 1 • C/min and was maintained for 8 h.
(2) The detection of the direct bonding effect After the process of bonding the two wafers, the bonding quality was evaluated. The testing criteria mainly included the size of the bonding area, the bonding interface, and the bonding strength.
The size of the bonding area: Because of the transparency of quartz material, the bonding area of QoS could be observed via visual inspection, which is shown in Figure 5a. The quartz and silicon were largely bonded, but a small part of the edge of the quartz could not be bonded completely because of a poor edge flatness and the few inevitable contaminants that arose in the operating environment.
The bonding interface: The interface was inspected using an optical microscope and scanning electron microscope (SEM), as shown in Figure 5b,c. The images show that the interface of QoS was completely bonded without any defects.
The bonding strength: To further detect the bonding quality, the bonded wafer was fixed onto a testing machine using a specific fixture to test the tensile strength. It can be seen from Figure 6a that the fractures mainly occurred inside the quartz material after stretching, and partial fractures appeared in the bonding glue; slight partial fractures occurred in the bonding interface, which indicated that the bonding strength was high, but the bonding uniformity was somewhat poor. It can be seen from Figure 6b that the axial force (F) was 1273.35 N. The bonding area (S) was approximately 19.6 × 16.8 mm = 329.28 mm 2 . Substituting the data into σ = F/S, yields a tensile strength (σ) of 3.8 MPa, which was the bonding strength.
(2) The detection of the direct bonding effect After the process of bonding the two wafers, the bonding quality was evaluated. The testing criteria mainly included the size of the bonding area, the bonding interface, and the bonding strength.
The size of the bonding area: Because of the transparency of quartz material, the bonding area of QoS could be observed via visual inspection, which is shown in Figure 5a. The quartz and silicon were largely bonded, but a small part of the edge of the quartz could not be bonded completely because of a poor edge flatness and the few inevitable contaminants that arose in the operating environment. The bonding interface: The interface was inspected using an optical microscope and scanning electron microscope (SEM), as shown in Figure 5b,c. The images show that the interface of QoS was completely bonded without any defects.
The bonding strength: To further detect the bonding quality, the bonded wafer was fixed onto a testing machine using a specific fixture to test the tensile strength. It can be seen from Figure 6a that the fractures mainly occurred inside the quartz material after stretching, and partial fractures appeared in the bonding glue; slight partial fractures occurred in the bonding interface, which indicated that the bonding strength was high, but the bonding uniformity was somewhat poor. It can be seen from Figure 6b Subsequently, the bonding wafers were immersed in water, alcohol, and acetone in sequence for more than 8 h, tested using ultrasonic cleaning, and bombarded with plasma for a long time. The interface between both bonding wafers was well retained without any reduction in the bonded surface. However, the bonding process of quartz and silicon was not mature enough, and its low yield was not conducive to the continued research of the subsequent process. Therefore, auxiliary bonding was proposed for continued research.
Auxiliary Bonding
Auxiliary bonding is the bonding of two homogenous or heterogeneous materials with the assistance of a third material. Common auxiliary bonding methods include the adhesive method, soldering and brazing, low-melting glass paste, and laser thermal fusion welding. Because of its lower cost, simplicity, compatibility with subsequent processes, and better removal of silicon wafers, the adhesive method was selected to research the subsequent process.
Adhesive bonding is the bonding of silicon and quartz wafers using epoxy resin adhesive (CY1003, SIRNICE, Guangzhou, China). Two-inch, 500-µ m thick silicon wafers (silicon, RDMICRO, Suzhou, China) and 300-μm thick Z-cut quartz wafers (quartz, RDMICRO, Suzhou, China) were selected for auxiliary bonding, where both wafers were polished on both sides. The quartz and silicon wafers were required to have good total thickness variation (TTV) and sufficiently clean surfaces without any contaminants. To move forward to the following processes, auxiliary bonding has strict requirements for glue, such as low viscosity, low shrinkage, high-temperature resistance, resistance to acetone corrosion, and good thermal conductivity. Subsequently, the bonding wafers were immersed in water, alcohol, and acetone in sequence for more than 8 h, tested using ultrasonic cleaning, and bombarded with plasma for a long time. The interface between both bonding wafers was well retained without any reduction in the bonded surface. However, the bonding process of quartz and silicon was not mature enough, and its low yield was not conducive to the continued research of the subsequent process. Therefore, auxiliary bonding was proposed for continued research.
Auxiliary Bonding
Auxiliary bonding is the bonding of two homogenous or heterogeneous materials with the assistance of a third material. Common auxiliary bonding methods include the adhesive method, soldering and brazing, low-melting glass paste, and laser thermal fusion welding. Because of its lower cost, simplicity, compatibility with subsequent processes, and better removal of silicon wafers, the adhesive method was selected to research the subsequent process.
Adhesive bonding is the bonding of silicon and quartz wafers using epoxy resin adhesive (CY1003, SIRNICE, Guangzhou, China). Two-inch, 500-µm thick silicon wafers (silicon, RDMICRO, Suzhou, China) and 300-µm thick Z-cut quartz wafers (quartz, RDMICRO, Suzhou, China) were selected for auxiliary bonding, where both wafers were polished on both sides. The quartz and silicon wafers were required to have good total thickness variation (TTV) and sufficiently clean surfaces without any contaminants. To move forward to the following processes, auxiliary bonding has strict requirements for glue, such as low viscosity, low shrinkage, high-temperature resistance, resistance to acetone corrosion, and good thermal conductivity.
The glue must have a low viscosity to ensure that it is evenly and thinly applied to the surface of the wafer. The viscosity of the glue should be under 5000 mPa·s. Here, glue with a viscosity of 1500 mPa·s was selected. A curing time of 1-2 h was suitable. The choice of curing time should be sufficient to evacuate and apply pressure while avoiding a reduction efficiency due to too long of a curing time.
The method used for curing the glue should be room-temperature curing or ultraviolet curing (because quartz material is transparent). After the experiments, when the tensile strength was greater than 0.8 MPa and the shear strength was greater than 0.5 MPa, the bonded wafers could be used for thinning and polishing without de-bonding or fragmenting.
The bonding process is shown in Figure 7. In an ultra-clean room, the bonding glue was evenly spun onto the silicon using a spin coater with a low speed of 500 r/min for 9 s and a high speed of 4000 r/min for 40 s. The silicon wafer was placed in a special fixture with the glue facing up. The quartz wafer was placed on the silicon wafer, aligned with the silicon wafer, and placed in a vacuum press-bonding machine (machine type: TWB-100, RDMICRO, Suzhou, China; the maximum pressure was 7 bar and the pressure uniformity was ±5%). Then, the bonder was sealed. The bonding temperature was set to 30 • C. The vacuum was set to 0.1 mbar. The bonding pressure was set to 2 bar. Then, the device was turned on for automatic bonding. The bonding time was kept for 2 h (according to the curing time of the glue). Then, the bonded wafer was removed from the bonder.
Micromachines 2020, 11, x 6 of 11 mPa·s was selected. A curing time of 1-2 h was suitable. The choice of curing time should be sufficient to evacuate and apply pressure while avoiding a reduction efficiency due to too long of a curing time.
The method used for curing the glue should be room-temperature curing or ultraviolet curing (because quartz material is transparent). After the experiments, when the tensile strength was greater than 0.8 MPa and the shear strength was greater than 0.5 MPa, the bonded wafers could be used for thinning and polishing without de-bonding or fragmenting.
The bonding process is shown in Figure 7. In an ultra-clean room, the bonding glue was evenly spun onto the silicon using a spin coater with a low speed of 500 r/min for 9 s and a high speed of 4000 r/min for 40 s. The silicon wafer was placed in a special fixture with the glue facing up. The quartz wafer was placed on the silicon wafer, aligned with the silicon wafer, and placed in a vacuum press-bonding machine (machine type: TWB-100, RDMICRO, Suzhou, China; the maximum pressure was 7 bar and the pressure uniformity was ±5%). Then, the bonder was sealed. The bonding temperature was set to 30 °C. The vacuum was set to 0.1 mbar. The bonding pressure was set to 2 bar. Then, the device was turned on for automatic bonding. The bonding time was kept for 2 h (according to the curing time of the glue). Then, the bonded wafer was removed from the bonder. (2) The detection of auxiliary bonding After a couple of experiments, in addition to determining the appropriate glue, a perfectly bonded wafer was acquired, as shown in Figure 8. It can be inferred from the SEM images (zoom-in of the cross-section at the bonding interface) that the bonding uniformity achieved the desired result. The bonding strength was ensured by the adhesive strength of the glue itself. According to the performance parameters of the glue, its tensile strength and shear strength were greater than 0.8 MPa and 0.5 MPa, respectively. (2) The detection of auxiliary bonding After a couple of experiments, in addition to determining the appropriate glue, a perfectly bonded wafer was acquired, as shown in Figure 8. It can be inferred from the SEM images (zoom-in of the cross-section at the bonding interface) that the bonding uniformity achieved the desired result. The bonding strength was ensured by the adhesive strength of the glue itself. According to the performance parameters of the glue, its tensile strength and shear strength were greater than 0.8 MPa and 0.5 MPa, respectively.
After a couple of experiments, in addition to determining the appropriate glue, a perfectly bonded wafer was acquired, as shown in Figure 8. It can be inferred from the SEM images (zoom-in of the cross-section at the bonding interface) that the bonding uniformity achieved the desired result. The bonding strength was ensured by the adhesive strength of the glue itself. According to the performance parameters of the glue, its tensile strength and shear strength were greater than 0.8 MPa and 0.5 MPa, respectively.
The Thinning of Quartz
By reducing the thickness of the quartz, the quartz wafer could be etched through directly from one side. There were four steps used for thinning the quartz: bonding, thinning, polishing, and cleaning of the QoS wafer.
QoS with a good TTV (<10 µm) was selected for this experiment. The QoS wafer was bonded to the glass substrate using wax. The wax was easily controlled to maintain a uniform thickness of the bonding between the QoS and glass substrate and was conveniently cleaned from the QoS wafer. Then, after the QoS was bonded with the glass substrate, the TTV was measured again. If the flatness of the bonded wafer is in the range of several microns after being glued to the glass substrate, then it was suitable for grinding and polishing. If the flatness difference was too large (greater than 10 microns), then the bonded wafer needed to be re-bonded.
Then, the QoS wafer was lapped and polished on a precision lapping machine (PM5, Logitech, UK), as shown in Figure 9. The speed and quality of the thinning were controlled by controlling the dripping speed of the slurry, the rotational speed of the turntable, and the pressure of the grinding. When the thickness and surface roughness of quartz were 40 µm (or another required thickness) and less than 5 nm, respectively, the entire process of thinning and polishing was completed.
Micromachines 2020, 11, x 7 of 11 By reducing the thickness of the quartz, the quartz wafer could be etched through directly from one side. There were four steps used for thinning the quartz: bonding, thinning, polishing, and cleaning of the QoS wafer.
QoS with a good TTV (<10 μm) was selected for this experiment. The QoS wafer was bonded to the glass substrate using wax. The wax was easily controlled to maintain a uniform thickness of the bonding between the QoS and glass substrate and was conveniently cleaned from the QoS wafer. Then, after the QoS was bonded with the glass substrate, the TTV was measured again. If the flatness of the bonded wafer is in the range of several microns after being glued to the glass substrate, then it was suitable for grinding and polishing. If the flatness difference was too large (greater than 10 microns), then the bonded wafer needed to be re-bonded.
Then, the QoS wafer was lapped and polished on a precision lapping machine (PM5, Logitech, UK), as shown in Figure 9. The speed and quality of the thinning were controlled by controlling the dripping speed of the slurry, the rotational speed of the turntable, and the pressure of the grinding. When the thickness and surface roughness of quartz were 40 μm (or another required thickness) and less than 5 nm, respectively, the entire process of thinning and polishing was completed. Afterward, a qualified QoS was obtained. The QoS was taken from the glass substrate to melt the wax via heating. Then, the QoS was immersed in a special de-waxing liquid at a temperature of 120 °C for 10-20 min to remove the residual wax from the surface of the QoS. Then, the QoS was washed using acetone, alcohol, and deionized water. Thus, the QoS wafer was prepared for the next step. Afterward, a qualified QoS was obtained. The QoS was taken from the glass substrate to melt the wax via heating. Then, the QoS was immersed in a special de-waxing liquid at a temperature of 120 • C for 10-20 min to remove the residual wax from the surface of the QoS. Then, the QoS was washed using acetone, alcohol, and deionized water. Thus, the QoS wafer was prepared for the next step.
The ICP Dry Etching of Quartz
The ICP dry etching of quartz was a huge challenge because of its hardness characteristic of quartz. The ICP dry etching research in this paper mainly focused on study of the etching mask and etching gas. The desired etching result was achieved by the selection of materials and thickness of the structure's masks, the composition and ratio of the etching gas, the etching power, and the chamber temperature.
After comparing the etching effects of a series of materials, such as aluminum, nickel, chromium, and a special photoresist, especially the selection ration, chromium was selected as the etching mask. The quartz structure etching mask of Cr was deposited using a standard micro-electromechanical systems (MEMS) process with a thickness of more than 3 µm, as shown in Figure 10. Because the mask was too thick, it was sputtered in a "sandwich" form to increase the adhesion between the mask and the substrate and to release the internal stress of sputtering. That is, the "sandwich" mask was alternately composed of chromium and aluminum. Moreover, the material of the uppermost layer of the mask was aluminum oxide to increase the etching selectivity ratio.
Micromachines 2020, 11, x 8 of 11 systems (MEMS) process with a thickness of more than 3 μm, as shown in Figure 10. Because the mask was too thick, it was sputtered in a "sandwich" form to increase the adhesion between the mask and the substrate and to release the internal stress of sputtering. That is, the "sandwich" mask was alternately composed of chromium and aluminum. Moreover, the material of the uppermost layer of the mask was aluminum oxide to increase the etching selectivity ratio. (2) The ICP etching process of quartz The fact that a micro quartz structure was obtained using ICP dry etching proved the rationality of the processing method. The etching process was continuously adjusted using various ratios of the etching gas, chamber temperature, and bias power to obtain vertical sidewalls, a small roughness, a high selectivity ratio, and a high etching rate [30].
After a sequence of experiments, the experimental parameters were selected: CF4 etching gas with flow rate of 100 sccm, etching temperature of 80 °C, Radio Frequency (RF) power of 1200 W, and a bias power of 120 W. Eventually, the etching depth was above 40 μm, the etching selectivity was above 13, and the etching rate was above 280 nm/min, as shown in Figure 11. (2) The ICP etching process of quartz The fact that a micro quartz structure was obtained using ICP dry etching proved the rationality of the processing method. The etching process was continuously adjusted using various ratios of the etching gas, chamber temperature, and bias power to obtain vertical sidewalls, a small roughness, a high selectivity ratio, and a high etching rate [30].
After a sequence of experiments, the experimental parameters were selected: CF 4 etching gas with flow rate of 100 sccm, etching temperature of 80 • C, Radio Frequency (RF) power of 1200 W, and a bias power of 120 W. Eventually, the etching depth was above 40 µm, the etching selectivity was above 13, and the etching rate was above 280 nm/min, as shown in Figure 11. etching gas, chamber temperature, and bias power to obtain vertical sidewalls, a small roughness, a high selectivity ratio, and a high etching rate [30].
After a sequence of experiments, the experimental parameters were selected: CF4 etching gas with flow rate of 100 sccm, etching temperature of 80 °C, Radio Frequency (RF) power of 1200 W, and a bias power of 120 W. Eventually, the etching depth was above 40 μm, the etching selectivity was above 13, and the etching rate was above 280 nm/min, as shown in Figure 11.
Results and Discussion
After the etched quartz structure was obtained, the auxiliary layer of silicon was removed to obtain a structure of pure quartz, as shown in Figure 12, or the silicon layer was further processed to obtain a composite structure containing quartz and silicon materials.
Results and Discussion
After the etched quartz structure was obtained, the auxiliary layer of silicon was removed to obtain a structure of pure quartz, as shown in Figure 12, or the silicon layer was further processed to obtain a composite structure containing quartz and silicon materials. In the final stage of removing the silicon wafer, the adhesive glue layer in the middle of the QoS (obtained via auxiliary bonding) also needed to be removed. This problem could be avoided if direct bonding was substituted for auxiliary bonding. In addition, direct bonding, without the participation of a third material, is more conducive to controlling the TTV of the bonded wafer, which is conducive to the subsequent thinning, polishing, and dry etching of quartz. In the future, the auxiliary bonding will be replaced with direct bonding to complete the entire process.
Conclusions
A new processing technique, including the bonding of quartz and silicon, as well as the thinning and dry etching of quartz, was introduced and proven to be feasible. With the assistance of the silicon layer, ultra-thin quartz materials were obtained and complex three-dimensional quartz structures with a good morphology and steep sidewalls were obtained by using this process. Then, the structure of the pure quartz material was obtained by removing the silicon wafer. Compared with the separated structure, the integrated structure has many advantages. The single material is beneficial for improving the performance of the device without inconsistent thermal expansion coefficients or assembly error. Without the problem of the thermal expansion coefficient, the effect of temperature on the device's performance can be sufficiently reduced. The glue caused neither moisture or an aging problem during assembly. In addition, the silicon layer was processed into the appropriate structure. A similar method could also be introduced to process other quartz-based sensors and actuators. Moreover, it provides a feasible idea for fabricating multilayer structures of heterogeneous materials. In the final stage of removing the silicon wafer, the adhesive glue layer in the middle of the QoS (obtained via auxiliary bonding) also needed to be removed. This problem could be avoided if direct bonding was substituted for auxiliary bonding. In addition, direct bonding, without the participation of a third material, is more conducive to controlling the TTV of the bonded wafer, which is conducive to the subsequent thinning, polishing, and dry etching of quartz. In the future, the auxiliary bonding will be replaced with direct bonding to complete the entire process.
Conclusions
A new processing technique, including the bonding of quartz and silicon, as well as the thinning and dry etching of quartz, was introduced and proven to be feasible. With the assistance of the silicon layer, ultra-thin quartz materials were obtained and complex three-dimensional quartz structures with a good morphology and steep sidewalls were obtained by using this process. Then, the structure of the pure quartz material was obtained by removing the silicon wafer. Compared with the separated structure, the integrated structure has many advantages. The single material is beneficial for improving the performance of the device without inconsistent thermal expansion coefficients or assembly error. Without the problem of the thermal expansion coefficient, the effect of temperature on the device's performance can be sufficiently reduced. The glue caused neither moisture or an aging problem during assembly. In addition, the silicon layer was processed into the appropriate structure. A similar method could also be introduced to process other quartz-based sensors and actuators. Moreover, it provides a feasible idea for fabricating multilayer structures of heterogeneous materials. | 8,678.6 | 2020-03-01T00:00:00.000 | [
"Materials Science"
] |
On Max-Plus Algebra and Its Application on Image Steganography
We propose a new steganography method to hide an image into another image using matrix multiplication operations on max-plus algebra. This is especially interesting because the matrix used in encoding or information disguises generally has an inverse, whereas matrix multiplication operations in max-plus algebra do not have an inverse. The advantages of this method are the size of the image that can be hidden into the cover image, larger than the previous method. The proposed method has been tested on many secret images, and the results are satisfactory which have a high level of strength and a high level of security and can be used in various operating systems.
Introduction
Recently information systems are developing very quickly, especially information systems through the Internet. It happens because the Internet can be accessed by anyone, anytime, and anywhere. Access to information through the Internet does not always bring benefits but also risks to the accuracy of information. This risk is vulnerable when information is accessible by hackers.
Many efforts have been made to protect data transferred over the Internet, including encryption (protecting data before being transferred over the Internet) and authentication (verifying whether the received data is the same as the sent data). There is knowledge or art of data protecting transferred over the Internet, that is, cryptography (data encoding) and steganography (data disguise). The data to be discussed in this paper is image data.
Many steganography methods in protecting information into an image have been published. The data or information that is hidden into an image can be text data or image data. Generally, to hide text data or image data into another image, the original text and original image should be converted into binary digits (bits). Then each digit of the original image or original text is substituted into the last bit of the cover image pixel. By using this method, information could be hidden into the cover image with little difference between the image stego image and the cover image. In this algorithm, every character (for text) or pixel (for image) is hidden into three pixels of cover image. The consequence of this method is, for the text data, the maximum number of characters that can be hidden into the cover image is one-third of the total pixels of the cover image. For image data, the image size that can be hidden into the cover image is one-third the size of the cover image (either long or wide).
In modern world, all information communication is done online. It causes the security system when data transfer becomes very important. Steganography has its own mechanism in data protecting [1,2]. In steganography, the information to be sent is hidden into other media, so that no one knows where the information is hidden. Watermarks and fingerprints are two technologies related to steganography, where steganography tends to hide data in other media [3].
Currently research on image encoding generally focuses on the following aspects: image encoding with spatial domains, 2 The Scientific World Journal image coding with domain transformation, image coding based on neural network, chaotic image coding, image coding based on cellular automata, and quantum technology [4]. In cryptography, encoding is the process of transforming information using certain algorithms that make it unreadable by anyone except the one who knows the special information, commonly called a key. The result of this process is called encrypted information [5]. Bouquard et al. have introduced the image encoding algorithm using affine transformation [6]. In this algorithm, the encryption and decryption process pass through two stages; that is, the first stage encodes the image using XOR operations with four key bits and the second stage encodes the encoded image using affine transformation. The conclusion of the study states that the correlation of pixel values between the original image and the encrypted image decreased after transforming the affine transform.
Tom has implemented data disguise using stenographic techniques. To make the technique safer they added a level of security by applying cryptography to confidential data before using steganography [7]. For cryptography, they use the Caesar algorithm while for steganography they use the adjacent pixel differences algorithm. Kulkarni and Jatgap substituted secret messages using a 14-square substitution algorithm [8].
Once the text was substituted, then this message was encoded with the RSA algorithm. The next step, this encoded message was hidden into an image by LSB (Least Significant Bit) method. This image works as a carrier file, which will be sent to the recipient. The receiver decrypts to get the original message by performing the same method but in reverse order.
Here, it appears that they do two coding techniques, so the system becomes more powerful and secure in the face of hacker attacks. This technique makes it difficult for the troublemakers to manipulate the image and takes a long time to encrypt the message, so it is safe from various attacks through the Internet network.
In measuring quality of an image objectively, some data are statistically calculated to determine quality of the reconstruction image. Image quality could be seen from how close the relationship of image forming pixels or by looking at how much the difference in pixel values are statistically distributed. In general, to compare two images, one could use mean square error (MSE) and Peak to Signal Noise Ratio (PSNR) [9,10]. Choudhary applied the optimization process to a stego image by using the LSB method, so that quality of the stego can get better with lower computational complexity [11]. MSE between stego image and cover image can be derived. Experimental results show that visually the stego image cannot be distinguished from the cover image. The results also showed improvement compared to the previous one.
In this paper, we propose a new steganography method to hide an image into another image using matrix multiplication operations on max-plus algebra. This is especially interesting because the matrix used in encoding or information disguises generally has an inverse, whereas matrix multiplication operations in max-plus algebra do not have an inverse. Another advantage of this method is the size of the image that can be hidden into the cover image which is greater than using the previous method.
Max-Plus Algebra
Max-plus algebra can be used to model disk events related to synchronization and time delays. The application of this theory has a very strong association with production problems [12,13].
The max-plus algebra [7] is a sequential pair ( , ⊕, ⊗), where is the set of all real numbers, whereas ⊕ and ⊗ are binary operations on defined as ⊕ = max ( , ) , for every , ∈ . Operations ⊕ and ⊗ are extensions of matrices and vectors in the same way as conventional linear algebra.
In addition, there is −∞ such that max( , −∞) = max(−∞, ) = and + (−∞) = −∞ + = −∞. For any ∈ max , there is a small number such that Let ∈ × and ∈ . In general, the system of linear equations in max-plus algebra will have no solution, if is square matrix or if the number of columns in is more than the number of rows in . Therefore, subsolutions concepts are introduced [7].
Operator ⊗ is a commutative operator. Except 0, every element has an inverse. The inverse of is denoted by −1 or 1/ . More precisely, we denote / or ⊗ −1 . ⊗ multiplication could be denoted by . The operator allows it to be expanded to a × matrix on max [14].
Let and be two matrices of × , operator ⊕, and we define The Scientific World Journal 3 It is not difficult to prove that the × matrix exists in max . Based on the triangular matrix of size × , where , = 0 for > , it is indicated that the set of × triangular matrices exists in max , but the operator ⊗ is not commutative. Furthermore, not all elements in max-plus algebra have inverse [6].
Literature Review
The image data character is very different from the text data because an image contains very large data, and all data has a very strong relationship and contains very high data loops [15].
Conceptually, the difference between text data and image data can be seen in Table 1.
An image is defined as a two-dimensional function, ( , ), where and are spatial coordinates and is the light intensity at coordinates ( , ) known as the gray degree. An image is called a digital image if, in position ( , ), there is an amplitude value. A digital image constitutes a finite number of elements, each of which has a particular location and a particular value. These elements are called picture elements or images of elements or pixels [16].
The pixel of an image can be converted into 8 binary digits (bits). The first to fourth bit is called LSB (Least Significant Bit) where the bit value changes in this position have no impact on the image. The fifth to eighth bit is called MSB (Most Significant Bit), where changes in bit values in this position have an effect on image. Figure 1 shows the bit positions of MSB and LSB.
The maximum deviation of an image can be found by making a grayscale histogram and calculating its area. The larger the deviation is, the better the encoding will be. To find the area of deviation image can be seen from the following formula [17]: Here, is the area of deviation; ℎ is the number of pixels that have gray degree; is the value of pixels.
A simple example of hiding data into an image is called insertion of least significant bit (LSB). For 24-bit colored images, the number of changes will be minimized so that it is difficult to distinguish by the human eye. For example, suppose we have three adjacent pixels (nine bytes) by using RGB encoding. Suppose we will hide data 101101101. Put 9 bits of data in the LSB position, so the following pixels are obtained (bold font shows the changed bits): Based on the formula, here is a snippet of the steganography process (see Figure 2).
Application of stenographic LSB uses secret key. Kulkarni and Jatgap [8] take a binary representation to hide information and replace the LSB of each cover image bit. Here, a secret key is introduced to protect the hidden information by using the formula: Cover image + secret key + hidden information = stego image.
To hide information, one should use cover image. Cover image is divided into three matrices (Red, Green, and Blue).
Secret key is converted to 1D bit stream array. Secret key and 4 The Scientific World Journal Red matrix are used as decision-makers to replace hidden information into the Green matrix or Blue matrix. Every bit of the secret key is operated by operators XOR with every LSB bit on the Red matrix. The result of the XOR operation is used to determine the bit of the hidden information to be replaced in the Green matrix LSB or the Blue matrix. The same process is done until all information is successfully hidden [18]. In this method, every character (plain text) or every pixel (plain image) is hidden into three pixels of cover image. As a consequence of this method, for plain text, the maximum number of characters that can be hidden into the cover image is 1/3 of the total pixel cover image. The maximum size of plain image that can be hidden is 1/3 of the size of the cover image (for length and width).
In the previous method, it is required that the size of the secret image should be smaller than the size of the cover image. In this article, we propose a new method so that the size of the secret image can be increased to the same size as the cover image.
The Proposed Method
The following algorithm is how to hide secret image into another image with maximal size equal to cover image size: (1) Convert pixels from secret image and cover image into bitwise form.
(2) Change the MSB from the pixel cover to the 2 × 2 matrix form. Here is the element of matrix of the secret image at row and column .
MSB sc is the MSB of secret image.
LSB st is the LSB of stego image.
For more details, the proposed coding system can be illustrated through the flowchart as in Figure 3.
Here is an algorithm to display the secret image of the stego image.
(1) Convert pixels of stego image into 8-bit form. For more details, decryption algorithm that can be made through the flowchart as in Figure 4.
In Table 2, the example pixel data from the secret image and the cover image is presented.
The Scientific World Journal In the matrix column in Table 3, if element of the left matrix is larger than element of the right matrix, then the element will be exchanged. The results of the operation process in Table 3 are given in Table 4.
Experimental Results and Analysis
To test our method, an experiment was performed. Here the test is done by using a laptop with microprocessor core i3 and Microsoft Windows 10 operating system. Computer program was created by using MATLAB R2016b and it applied to an image of good quality. The results of our algorithm are shown in Figure 5. We use the balloon image as a secret image and carrot image as the cover image. Cover image and secret image have the same size that is 163 × 133. Figure 5 shows that the stego image ( Figure 5(c)) is similar to the cover image ( Figure 5(a)), although visually inside the cover image contains a secret image ( Figure 5(b)). The result of stego image has a size of 163 × 133. It is proved that this method can hide the secret image that has size as same as the cover image. This needs to be demonstrated by using statistical analysis. Therefore, an ideal encoding must have power when there is an attack through its statistical model. 6 The Scientific World Journal (X(i, j, k), 2) To prove the power of this proposed method, we performed a statistical analysis by displaying a histogram and computing the correlation coefficient between two neighboring pixels on the cover image and stego image. The abscissa histogram shows the pixel value and the ordinate showing the frequency or how often the pixel value appears. The histogram of the cover image shown in Figure 6(a) has a larger area. This area shows how often the pixel value appears in an image. Histogram of the secret image shown in Figure 6(b) has a smaller area. This shows that the cover image is clearer than the secret image. Histogram of the stego image shown in Figure 6(c) has a pattern similar to the cover image. This shows that the cover image has not significantly changed.
In addition to histogram analysis, we also analyze the correlation coefficients of two vertically neighboring pixels, two horizontally neighboring pixels, and two pixels diagonally adjacent to the stego image and cover image. First, we select 10000 pixels on a neighboring image. Then we calculate the correlation coefficient with the following formula: Here, and are the values of two neighboring pixels. In numerical computation, the correlation coefficient can be calculated using the following formula [19]: Based on the proposed method, the correlation coefficient between two vertically neighboring pixels for the cover image and stego image is 0.91432 and 0.91039, respectively. Similarity of the results to the vertical and diagonal directions is shown in Table 5. It is apparent in Table 5 that there is a strong correlation between two neighboring pixels, or in other words the stego image and cover image are difficult to distinguish.
In the image processing mean square error (MSE) is often used to determine how big the image quality difference between before and after coding process. The formula is presented as follows [15]: Based on the calculation, the MSE between the cover image and stego image is 361.7734 Improving the visual quality of digital image can be subjective. Saying that one method provides better quality image could vary from person to person. Using same tests images, different image enhancement algorithm can be compared by peak signal to noise ratio (PSNR). The mathematical representation of the PSNR is as follows: where MAX is the maximum signal value that exists in our original "known to be good" image. Two identical images will have a zero MSE value and an infinite PSNR value so the smaller the difference between the two images, the smaller the MSE value and the larger the PSNR value [19]. From the calculation results obtained PSNR for cover image is 21.8295 and PSNR for stego image is 21.8142. Here it looks very small value difference so it can be said that the image between cover image and stego image is similar. With this similar result it can be said that the coding result goes well.
Based on analysis of time, this algorithm has the time complexity ( ). This shows that the algorithm has execution time that increases linearly according to the number of pixels (image size). coding method, we use koala image (1024 × 768) as a secure image and tulips image (1024 × 768) as cover image. From Figures 7 and 8, we can see that the encoding between the max-plus and the previous method produces the same stego image. Both methods can be used to hide the secret image that has same image size between the secret image and the cover image. Figures 9 and 10 show the results of decoding by max-plus and previous methods. Hence, we conclude that the decoding process of the Max-Plus method can return the stego image same as the secret image, while in the previous method it cannot return the stego image to the secret image perfectly but only a quarter of the part. It makes the previous method display a quarter of the secret image during the description process.
Conclusions
The proposed method has been tested on many secret images, and the results are satisfactory which have a high level of strength and a high level of security and it can be used in various operating systems. A pixel of the secret image is hidden in a cover image pixel by matrix multiplication operations in max-plus algebra, so that the message becomes safer. Maximum secret image size that can be hidden is the same as the size of cover image. This is the novelty of this method where, in the previous method, size of secret image is always smaller than the cover image. In our future research, we will construct an algorithm to hide a text into an image by using max-plus algebra. | 4,414.2 | 2018-05-15T00:00:00.000 | [
"Computer Science",
"Mathematics"
] |
Engineering stop gaps of inorganic-organic polymeric 3 D woodpile photonic crystals with post-thermal treatment
A method is reported for improving the spatial resolution and engineering the stop gaps of the inorganic-organic 3D woodpile photonic crystals (PhCs). The approach is based on the two-photon polymerization (2PP) of an inorganic-organic hybrid material and a post-thermal treatment (PTT) process. The effects of PTT on polymerized 1D, 2D and 3D structures have been characterized. Ultimately, the feature size of the suspended rods has been reduced to ~33 nm and the spatial resolution of inorganic-organic 3D woodpile PhCs has been improved from ~150 nm to ~86 nm. The approach is also demonstrated as a powerful tool to engineer the stop gaps of 3D PhCs. In particular, a combination of PTT and the threshold fabrication technique leads to the stop gap of a 3D woodpile PhC that can be tuned over a large wavelength range of ~318 nm from the nearinfrared to visible region. ©2008 Optical Society of America OCIS codes: (230.5298) Photonic crystals; (220.4000) Microstructure fabrication; (160.5470) Polymers; (120.6810) Thermal effects. References and links 1. S. Maruo, O. Nakamura, and S. Kawata, “Three-dimensional microfabrication with two-photon-absorbed photopolymerization,” Opt. Lett. 22, 132-134 (1997). 2. S. Kawata, H. B. Sun, T. Tanaka, and K. Takada, “Finer features for functional microdevices,” Nature 412, 697-698 (2001). 3. S. Wu, J. Serbin, and M. Gu, “Two-photon polymerisation for three-dimensional micro-fabrication,” J. Photochem. Photobiol., A 181, 1-11 (2006). 4. M. Straub and M. Gu, “Near-infrared photonic crystals with higher-order bandgaps generated by twophoton photopolymerization,” Opt. Lett. 27, 1824-1825 (2002). 5. M. Deubel, G. Von Freymann, M. Wegener, S. Pereira, K. Busch, and C. M. Soukoulis, “Direct laser writing of three-dimensional photonic-crystal templates for telecommunications,” Nat. Mater. 3, 444-447 (2004). 6. K. K. Seet, V. Mizeikis, S. Matsuo, S. Juodkazis, and H. Misawa, “Three-dimensional spiral-architecture photonic crystals obtained by direct laser writing,” Adv. Mater. 17, 541-545 (2005). 7. L. H. Nguyen, M. Straub, and M. Gu, “Acrylate-based photopolymer for two-photon microfabrication and photonic applications,” Adv. Funct. Mater. 15, 209-216 (2005). 8. S. Wong, M. Deubel, F. Pérez-Willard, S. John, G. A. Ozin, M. Wegener, and G. von Freymann, “Direct laser writing of three-dimensional photonic crystals with a complete photonic bandgap in chalcogenide glasses,” Adv. Mater. 18, 265-269 (2006). 9. J. Serbin, A. Egbert, A. Ostendorf, B. N. Chichkov, R. Houbertz, G. Domann, J. Schulz, C. Cronauer, L. Fröhlich, and M. Popall, “Femtosecond laser-induced two-photon polymerization of inorganic-organic hybrid materials for applications in photonics,” Opt. Lett. 28, 301-303 (2003). 10. J. Li, B. Jia, G. Zhou, and M. Gu, “Fabrication of three-dimensional woodpile photonic crystals in a PbSe quantum dot composite material,” Opt. Express 14, 10740-10745 (2006). 11. N. Tetreault, G. V. Freymann, M. Deubel, M. Hermatschweiler, F. Perez-Willard, S. John, M. Wegener, and G. A. Ozin, “New route to three-dimensional photonic bandgap materials: silicon double inversion of polymer templates,” Adv. Mater. 18, 457-460 (2006). 12. B. Jia, S. Wu, J. Li, and M. Gu, “Near-infrared high refractive-index three-dimensional inverse woodpile photonic crystals generated by a sol-gel process,” J. Appl. Phys. 102, 096102 (2007). #103289 $15.00 USD Received 27 Oct 2008; revised 13 Nov 2008; accepted 14 Nov 2008; published 20 Nov 2008 (C) 2008 OSA 24 November 2008 / Vol. 16, No. 24 / OPTICS EXPRESS 20073 13. K. Takada, H.-B. Sun, and S. Kawata, “Improved spatial resolution and surface roughness in photopolymerization-based laser nanowriting,” Appl. Phys. Lett. 86, 1 (2005). 14. S. Juodkazis, V. Mizeikis, K. K. Seet, M. Miwa, and H. Misawa, “Two-photon lithography of nanorods in SU-8 photoresist,” Nanotechnology 16, 846-849 (2005). 15. D. Tan, Y. Li, F. Qi, H. Yang, Q. Gong, X. Dong, and X. Duan, “Reduction in feature size of two-photon polymerization using SCR500,” Appl. Phys. Lett. 90, 071106 (2007). 16. S. Juodkazis, V. Mizeikis, K. K. Seet, H. Misawa, and U. G. K. Wegst, “Mechanical properties and tuning of three-dimensional polymeric photonic crystals,” Appl. Phys. Lett. 91, 241904 (2007). 17. W. Haske, V. W. Chen, J. M. Hales, W. T. Dong, S. Barlow, S. R. Marder, and J. W. Perry, “65 nm feature sizes using visible wavelength 3-D multiphoton lithography,” Opt. Express 15, 3426-3436 (2007). 18. Y. Jun, P. Nagpal, and D. J. Norris, “Thermally stable organic-Inorganic hybrid photoresists for fabrication of photonic band gap structures with direct laser writing,” Adv. Mater. 20, 606-610 (2008). 19. J. Serbin and M. Gu, “Experimental evidence for superprism effects in three-dimensional polymer photonic crystals,” Adv. Mater. 18, 221-224 (2006). 20. J. Serbin and M. Gu, “Superprism phenomena in waveguide-coupled woodpile structures fabricated by twophoton polymerization,” Opt. Express 14, 3563-3568 (2006). 21. J. Li, B. Jia, G. Zhou, J. Serbin, C. Bullen, and M. Gu, “Spectral redistribution in spontaneous emission from quantum-dot-infiltrated 3D woodpile photonic crystals for telecommunications,” Adv. Mater. 19, 3276-3280 (2007). 22. J. Li, B. Jia, G. Zhou, and M. Gu, “Direction-dependent spontaneous emission from near-infrared quantum dots at the angular band edges of a three-dimensional photonic crystal,” Appl. Phys. Lett. 91, 254101 (2007). 23. R. Buestrich, F. Kahlenberg, M. Popall, P. Dannberg, R. Müller-Fiedler, and O. Rösch, “ORMOCER®s for optical interconnection technology,” J. Sol–Gel Sci. Technol. 20, 181-186 (2001). 24. R. Mohamed, N. Razali, A. A. Ehsan, and S. Shaari, “Characterisation and process optimisation of photosensitive acrylates for photonics applications,” Sci. Technol. Adv. Mater. 6, 375-382 (2005). 25. B. Lange, J. Wagner, and R. Zentel, “Fabrication of robust high-quality ORMOCER® inverse opals,” Macromol. Rapid Commun. 27, 1746-1751 (2006). 26. T. Kerle, Z. Lin, H. -C. Kim, and T. P. Russell, “Mobility of polymers at the air/polymer interface,” Macromol. 34, 3484-3492 (2001). 27. Y. Li, F. Qi, H. Yang, Q. Gong, X. Dong, and X. Duan, “Nonuniform shrinkage and stretching of polymerized nanostructures fabricated by two-photon photopolymerization,” Nanotechnology 19, 055303 (2008).
Introduction
Direct laser writing (DLW) is an effective and flexible approach to inducing two-photon polymerization (2PP) in various photoresists and has been intensively studied for the fabrication of three-dimensional (3D) arbitrary micro-structures including 3D photonic crystals (PhCs) [1][2][3][4][5][6][7][8][9][10].The use of all-organic materials such as SCR and SU-8 [1,5] can not only produce 3D PhCs with stop gaps in the near-infrared (NIR) wavelength range [4][5][6][7], but also serve as templates for further preparations of "inverted" PhCs with high refractive index [11,12].Though the feature size of the two-dimensional (2D) polymerized rods can be reduced down to less than 30 nm by employing pre-treatment methods [13][14][15], their poor thermal and mechanical stability [13, 16,17] makes them less applicable for fabricating 3D PhCs and 3D templates of high quality [18].These problems do not exist in all-inorganic photoresists, such as chalcogenide glasses [8].However, the feature size of the fabricated 3D PhCs is much poorer than the diffraction limit of the laser writing beam because of the high refractive index of those materials, which restricts the writing depth and increases the structure distortion due to optical aberrations [8].The inorganic-organic hybrid materials [9,10,18] combine the advantages of both organic and inorganic materials.With the reliable thermal and mechanical stability, such hybrid materials have been successfully applied in the fabrication of functional 3D PhCs [19][20][21][22].However the incorporation of the inorganic part in the polymerized structures has limited the fabrication resolution to approximately 150 nm [20].
Here we use a post-thermal treatment (PTT) method to improve the spatial resolution of the 3D 2PP fabrication in an inorganic-organic hybrid material.Ultimately, the feature size of the suspended rods is reduced to ~33 nm and the spatial resolution of 3D woodpile PhCs is improved to ~86 nm.Moreover, the PTT process can efficiently engineer the stop gaps of the PhCs.A combination of PTT and the threshold fabrication technique leads to the stop gap of a 3D woodpile PhC that can be tuned over a large wavelength range of 318 nm from the NIR to visible region.
Experimental details
Film samples for material characterizations were prepared by illuminating spin-coated photosensitive resins on cover glass with a UV lamp, followed by washing with 4-methyl-2pentanone and rinsing with isopropanol [9,19].The photosensitive resin we used is Ormocer ® which is a kind of the silicate-based inorganic-organic hybrid material.The polymerized structures are stable upon heating at temperature (T) up to 270 o C [23].Before the PTT process, the polymerized films (and all the following samples fabricated by 2PP) were hardbaked at 150 o C for 3 h.Then the samples were put onto a hot plate under certain temperature for the PTT process.After each heating process, the samples were naturally cooled down to room temperature for measurements.The absorption spectra of the polymerized films were characterized with a Fourier-transform IR spectrometer (FTIR, Thermo Nicolet) in conjunction with an infrared microscope (Continuum).The choosing of temperature for PTT is critical.Here the temperature we used for PTT is 300 o C, where the thermal gravimetric analysis curve of Ormocer® shows a slow weight loss of less than 1% and the overall structures are stable under heating for 10 hours (h) [24,25].In fact, our PTT experiments under 300 o C showed the best performance on PhC engineering among the tests with temperatures ranging from 150 o C to 450 o C. The reason is that at this temperature, some organic parts of the polymerized structures starts to be decomposed slowly while the inorganic part is well preserved, behaved as backbones to support the whole structure.As shown in Fig. 1, at 300 o C, C-H groups belonging to alkyl terminations of Ormocer® molecules are decomposed and Si-OH group are formed [25].Meanwhile, the methacrylic phase is further polymerized as depicted by the decrease in absorbance of C=O and C=C groups.As a consequence, the structures result more condensed with improved mechanical stability.Meanwhile, the refractive index of the polymerized films, measured with Becke line method [10], was 1.554±0.002before PTT and increased to 1.566±0.002at the PTT time of 3 h and then remained nearly unchanged from 3 h to 48 h.
The micron-scale samples in the article were fabricated with 2PP method, in which femtosecond pulses (~200 fs) operating at wavelength 580 nm were focused into the photosensitive resin with an oil immersion objective (Olympus, numerical aperture 1.4, 100×) [10,21].A serial of one-dimensional (1D) and 2D structures were fabricated with variable exposure power and fabrication speed for comparison purposes.3D woodpile PhCs of different rod spacing were fabricated with various exposure power under a constant fabrication speed of 60 μm/s [21].The transmission spectra (>900 nm) of the woodpile PhCs in the stacking direction were characterized with a pinhole-assisted FTIR [10].The transmission spectra of PhCs which had a stop gap below wavelength 900 nm were measured with a CCD (Pixis 100, Princeton Instruments): a broadband light source (Oriel Apex QTH Source) was focused into the PhCs by an apochromatic objective and the transmitted signals were then collected by another apochromatic objective, dispersed by a spectrograph (Acton Spectropro 300i), and finally detected by the CCD.A small aperture was inserted before the back aperture of each objective to confine the divergence angle to 10 o with respect to the stacking direction of the PhCs.
PTT effects on 1D and 2D inorganic-organic structures
To study the effects of PTT on polymerized structures, firstly, we heated a laser-generated thin film for 3 h at temperature 300 o C. As shown in Figs.2(a, b), after 3-h PTT the surface roughness of the polymerized film is improved significantly by 45% from 10 to 5.5 nm, which is similar to the thermal annealing effects on other polymers [26].Meanwhile, the maximum height of the features is reduced.The effect of PTT on the height of the polymerized structures was then tested on an array of the fabricated parallel rods with ascending heights (Fig. 3(a)).The truncated rods were heated with several steps and the sample was characterized by an atomic force microscope (AFM) after each process.As shown in Figs.3(b-d), both the height (H) and width (W) of the rods are significantly reduced after PTT, different for rods with different initial heights (Fig. 3(d)).In particular, the amount of reduction reaches 79% for a 69.6-nm-high rod, of which the height is reduced to 14.4 nm after 36-h PTT (see another sample in the inset of Fig. 3(e)).The plots of the height ratio (H/H 0 ), where H 0 is the height of the rod before PTT, as a function of the heating time reveal that the lower the rod, the larger the reduction (see Fig. 3(e)).However, the exponential decay behavior of the plots shows that the lower rod has a decay speed slower than that of the higher one after 3 h.This is because the lower rods have larger surface-to-volume ratios, which leads to faster heat dissipation and slower PTT effects in the case of thermal conduction.
We further studied the effect of PTT on the suspended rods fabricated between two solid supporters.Figures 4(a-b) show the SEM images of the rods with a length of ~1.5 μm before and after 3-h PTT, respectively.One can see that the width of the rods is significantly reduced without cracks (the nonuniform sizes of the rods were induced by the stretches from the solid supporters [27]).For comparison, we plot the rod width before and after 3-h PTT as a function of the fabrication speed and power in Figs.4(c-d), respectively.It can be seen that the rod width is monotonically reduced but thicker rods are reduced by a larger percentage than the thinner ones.This is because the thicker rods have a smaller surface-to-volume ratio that results in slow heat dissipation, which makes the PTT effect more efficient.One important feature of the rods after 3-h PTT is that the suspended thin rods can preserve a good mechanical property such as rods with a long length of ~5.5 μm shown in Fig.
PTT effects on inorganic-organic 3D woodpile PhCs
The reliable mechanical properties of the structures after PTT lead to a new way to engineer 3D inorganic-organic PhCs.As the images shown in Figs.5(a-b), the periodical structures of the PhCs are well preserved after heating at 300 o C for 3 and 20 h, respectively, showing a good mechanical strength under PTT.The rod spacing of the woodpile, initially designed and fabricated at 1.1 μm, was reduced to 1.0 μm after the PTT (Fig. 5(b)).Meanwhile, the measured transmission spectra of a woodpile PhC, as shown in Fig. 5(c), reveal that the center of the stop gap is shifted from 1621 to 1458 nm after 3-h PTT, indicating that the periodicity in the stacking direction is significantly reduced.Moreover, one can notice that the transmission at shorter wavelengths increases, which means less scattering losses of the heated structures due to the improved surface roughness.Another improvement is that unwanted "defects" within the stop gap, induced by the residual stresses inherent in the fabrication process, can be cured by the PTT process that release these residual stresses, as noted in Fig. 5(c).The blue-shift effect of stop gaps induced by PTT can be applied to tune the stop gaps of PhCs.As shown in Fig. 5(d), the stop gap of a PhC can be continuously tuned from 1596 to 1345 nm with increasing the PTT time, which covers the important telecommunication wavelengths.During this process, the suppression rate of the stop gap reaches a maximum at the heating time of 3 h.On the other hand, the gap/midgap ratio of the stop gap, which is related with the symmetry of the PhC, keeps constant around 7.63% with a small fluctuation of less than 0.37% for heating up to 9 h, indicating the internal symmetry of the PhC was perfectly preserved within 9 h.After 9 h, small modifications have been observed (Fig. 5(d)) in the shapes of stop gaps, which indicates the original geometry of part of the woodpile was slightly changed.Nevertheless, the position of stop gaps was consistently shifted towards shorter wavelengths.Figure 5(e) shows the relative blue-shift of the stop gap (Δλ c /λ c0 , λ c0 is the center wavelength of the stop gap before PTT) as a function of the heating time.One can see that the experimental data beyond 3 h fit well an exponential decay curve, which is similar to the change in heights of 2D rods on the cover glass (see Fig. 3(e)).Since the refractive index of the polymerized structures has no noticeable change when the PTT time is longer than 3 h, the value of λ c is proportional to the lattice period in the stacking direction.Thus, the change in Δλ c /λ c0 reasonably reflects the change in the period in the stacking direction and the corresponding fitting relation consistently indicates a smooth reduction in size without much distortions and cracks inside the structure.Meanwhile, in the in-layer plane, a microscope image of the PhC after 38-h heating (inset of Fig. 5(e)) shows the lateral size of the woodpile is reduced by ~16.3 %, similar to the corresponding value of Δλ c /λ c0 (15.7%), which indicates that the overall 3D structure is symmetrically reduced during PTT.
It should be emphasized that the measured transmission spectra of the PhCs were very sensitive to the structure geometry.Any effect of PTT, including the influence of the substrate, can be reflected in the changes of stop gaps of PhCs.Deviation of PTT temperature from 300 o C would result in no engineering effects (T<300 o C) or distortions of the stop gaps (T>300 o C).That is why it is very important to perform the PTT process at 300 o C to realize symmetric engineering of PhCs.The combination of PTT and the threshold laser writing method [2,3,19] can improve the resolution in fabricating inorganic-organic 3D PhCs and thus realize the operation in the visible wavelength range.As shown in Fig. 6(a), the stop gap of a 700-nm-lattice woodpile PhC, fabricated by the threshold method at a power of 1.3 mW, can be tuned from 1007 to 746 nm after 21-h PTT.For comparison, a PhC with a rod spacing of 800 nm was fabricated along with the 700-nm PhC and experienced the same process.As shown in Fig. 6(b), its stop gap was finally tuned to 831 nm but shows a smoother and deeper gap than that in Fig. 6(a), which reveals that the PhC with a larger lattice constant can maintain better performance for long-time PTT.Moreover, the appearance of a higher order gap [4] at wavelength 531 nm (in Fig. 6 reduced to ~86 nm, which is reduced by a factor of two compared with the previously reported value of ~150 nm in the inorganic-organic hybrid polymer [20].
Improving the spatial resolution of inorganic-organic 3D woodpile PhCs
Since the PTT speed is related to the surface-to-volume ratio of the initial rods (see Figs. 4(c-d)), we fabricated another 700-nm-lattice PhC with a slightly higher power of 1.35 mW, which results in thicker rods than those of the PhC in Fig. 6(a).It is noted that the stop gap of this PhC, initially at wavelength 1041 nm, is tuned to 723 nm after PTT only for 6 h (Fig. 6(c)).The fast tuning in the stop gap is caused by the more efficient PTT of the thick rods due to their slow heat dissipation, which results in the large speed in the overall size reduction.It should be mentioned that the Δλ c /λ c0 of this PhC reaches ~30%, which is the largest ratio in gap tuning of 3D PhC to our knowledge.
Conclusions
In conclusion, we have proposed and demonstrated a PTT method to improve the fabrication resolution of the structures fabricated with 2PP in inorganic-organic hybrid materials.In the cases of the 2D truncated rods on cover glass, the 2D suspended rods and the 3D woodpile PhCs, the limits of the feature size reach ~14.4,~33 and ~86 nm, respectively.This PTT method results structures with high mechanical stability and has been successfully applied to substantially tune the stop gaps of the woodpile PhCs.In particular, a continuous 251-nmtuning range of the stop gap of a 3D PhC has been achieved.The integration of this PTT method with the threshold fabrication method has resulted in a 3D woodpile PhC operating at visible wavelengths.This work provides a useful option for producing smaller templates for the fabrication of NIR or visible high refractive-index inverse woodpile PhCs [11,12] as well as a constructive platform for promising applications of 3D visible woodpile PhCs.Varying the ratio between organic and inorganic parts in the hybrid polymers provides another dimension to engineer the structures to meet different demands through a temperaturedependent PTT process.
Fig. 1 .
Fig. 1.Absorption spectra of the polymerized films upon heating at temperature 300 o C for different heating time.Spectra are normalized and translated for better view.The schematic on the right side is based on the observed changes in absorbance of organic functional groups.
Fig. 2 .
Fig. 2. (a, b) AFM images of the top surface of a laser-generated thin film (a) before and (b) after 3-h heating at 300 o C.
4(e), while the #103289 -$15.00USD Received 27 Oct 2008; revised 13 Nov 2008; accepted 14 Nov 2008; published 20 Nov 2008 (C) 2008 OSAreported all-organic polymer structures are less robust under such high temperature (300 o C).Furthermore, it is found that the minimum rod width of ~50 nm with 2PP by direct laser writing can be efficiently reduced to ~33 nm with PTT for only 3 h, as shown in Figs.4(f-g).
Fig. 3 .Fig. 4 .
Fig. 3. (a) Schematic of truncated rods on cover glass (side view).(b) and (c) AFM images of the rods before and after 18-h PTT.(d) Corresponding cross-sections of the rods taken from (b) and (c).(e) Height ratio H/H 0 as a function of the PTT time for rods with different H 0 .The data beyond 3 h are fitted with the exponential decay curve.The fitted decay speeds are 0.162, 0.199 and 0.223 h -1 for rods with H 0 of 193, 287 and 361 nm.Inset: Cross-sections of rods before and after 36-h PTT.
Fig. 5 .
Fig. 5. (a) and (b) SEM images of 3D woodpile PhCs after PTT for 3 and 20 h, respectively.(c) Measured transmission spectra of a 32-layer woodpile PhC in the stacking direction before and after 3-h PTT.The four areas noted by dashed circles indicate the increased transmission at shorter wavelengths.The two vertical arrows point out the "defect" within the stop gap, which disappears after PTT.(d) Baseline corrected transmission spectra of a 32-layer woodpile PhC at different heating time (from right to left): 0, 3, 6, 9, 15, 38 h.(e) Relationship between Δλ c /λ c0 and the heating time.Experimental data beyond 3 h are fitted well with the exponential decay model with a decay speed of 0.117 h -1 .Inset: Microscope image of the PhC after PTT.The outer dashed square and the inner solid square mark the woodpile before and after heating for 38 h, respectively.
Fig. 6 .
Fig. 6.(a) Measured transmission spectra of a 20-layer woodpile PhC with a rod spacing of 700 nm.The centers of the stop gaps before and after 21-h heating are located at wavelengths 1007 and 746 nm, respectively.(b) and (c) Measured transmission spectra of 20-layer PhCs with rod spacings of 800 and 700 nm after PTT for 21 and 6 h, respectively.The centers of the stop gaps are located at wavelengths 831 and 723 nm, respectively.Inset of (c): SEM image of the PhC in (c).The width of the rod is reduced to ~86 nm.
(b)) indicates that the symmetry of the woodpile is well preserved.The SEM image depicted in the inset of Fig. 6(c) shows that the width of the rods of the 3D PhC can be #103289 -$15.00USD Received 27 Oct 2008; revised 13 Nov 2008; accepted 14 Nov 2008; published 20 Nov 2008 (C) 2008 OSA | 5,458.6 | 2008-11-24T00:00:00.000 | [
"Materials Science",
"Physics"
] |
Penetrance rate estimation in autosomal dominant conditions
Accurate estimates of the penetrance rate of autosomal dominant conditions are important, among other issues, for optimizing recurrence risks in genetic counseling. The present work on penetrance rate estimation from pedigree data considers the following situations: 1) estimation of the penetrance rate K (brief review of the method); 2) construction of exact credible intervals for K estimates; 3) specificity and heterogeneity issues; 4) penetrance rate estimates obtained through molecular testing of families; 5) lack of information about the phenotype of the pedigree generator; 6) genealogies containing grouped parent-offspring information; 7) ascertainment issues responsible for the inflation of K estimates.
Introduction
Human autosomal dominant diseases are extremely rare conditions in which affected individuals are heterozygotes. Many of these heterozygous genotypes exhibit the phenomenon of incomplete penetrance. For this set of rare conditions the penetrance rate is therefore understood as the probability of a heterozygote presenting the disease (or, at least, presenting a minimum number of signs and symptoms that enable his/her identification as a carrier of the deleterious allele). Other details, as well as a full review of the subject can be found in Horimoto and Otto (2008). Accurate estimates of the penetrance value K are important not only for determining genetic disease risks in families with segregating cases of autosomal dominant disorders, but also for performing linkage studies. Crude penetrance estimates can be derived by dividing the observed number of diseased (penetrant) individuals by the number of obligate carriers (penetrant as well as obligate non-penetrant, that is, normal individuals with several affected offspring or normal individuals with affected parent and child). Presently the penetrance parameter can be estimated on a routine basis by computer programs that perform segregation analysis or the estimation of linkage based on complex pedigree structures that cannot be expressed in closed form, such as the classical S.A.G.E. (S.A.G.E., 2009) and LINKAGE (Lathrop et al., 1985) programs. Rogatko et al. (1986) provided a simple but efficient methodology for dealing with the problem, but neither their solution nor more complex alternatives, such as the abovementioned computer programs, take into account many of the details we discuss here. These concern specificity and heterogeneity issues (section 3), penetrance rate estimates from families undergoing molecular testing (section 4), lack of information about the phenotype of the pedigree generator (section 5), genealogies containing grouped parent-offspring information (section 6), and ascertainment issues responsible for the inflation of K estimates (section 7). In section 1 we briefly review the method for estimating the penetrance rate from pedigree data, and in section 2 we make a digression on the determination of the exact credible interval for this estimate.
(1) Method for Estimating the Penetrance Rate K More details on the method described below are found in the original paper by Rogatko et al. (1986) and Horimoto et al. (2010). The first step of the method consists in trimming or filtering the pedigree information, that is, replacing the original pedigree with one containing only individuals that are informative or relevant with respect to penetrance estimation. Expressions like trimming and trimmed seem to be more appropriate, but we shall keep the nomenclature coined originally by Rogatko et al. (1986). As an example we will consider the hypothetical filtered pedigree shown in Figure 1, with several individuals affected by a rare autosomal dominant condition. The individual of the first generation is the genealogy or pedigree generator. The symbols marked with a point indicate obligate normal (non-penetrant) heterozygous carriers of the gene, and the darkened symbols represent affected (penetrant) heterozygotes.
The filtered pedigree contains four affected individuals, four normal obligate carriers, three normal offspring of obligate carriers, and one tree of normal individuals descendants from an obligate carrier (one normal female with two normal male offspring, shown at the leftmost position of the pedigree). Letting K be the penetrance rate value, the probabilities associated with each of these four different structures are, respectively, K/2, (1-K) in the case of the pedigree generator, or (1-K)/2 in the case of the other three normal obligate carriers, (2-K)/2, and {1/2 + (1-K)/2. [(2-K)/2] 2 }.
The likelihood function, that is the probability of occurrence of the pedigree conditional to the observed structures occurring in it, is derived from the quantities associated with these structures. In the present case, by neglecting constant values unimportant in the maximization procedure that will follow, the likelihood function takes the form p = K 4 (1-K) 4 (2-K) 3 [4+(1-K)(2-K) 2 ]. By solving the equation dP/dK = 0 (or, more conveniently, dL/dK = dlog(P)/dK = 4.log(K)+4.log(1-K)+3.log(2-K)+log[4+(1-K)(2-K) 2 ] = 0), we obtain the maximum likelihood estimate of the penetrance value K, which for this family takes the value of 0.418.
Heterozygosis probabilities and the corresponding risks for the offspring of all individuals of the filtered pedigree can then be determined without difficulties. Obligate carriers (known non-penetrant carriers and affected penetrant heterozygotes) have genotype Aa and the risk for their offspring is simply R 1 = K/2 = 0.418/2 = 0.209, or approximately 21%, for the above shown example. The probability of heterozygosis for normal individuals born to obligate carriers (three of which occur in the family used as example) is taken directly from the quantity (2-K)/2 = 1/2+(1-K)/2 as P(het) = [(1-K)/2]/ [(2-K)/2] = (1-K)/(2-K) = 0.582/1.582 = 0.368. The probability of affected offspring for these individuals is then R 2 = (1-K)/(2-K).K/2 = 0.368 x 0.209 = 0.077, or approximately 8%. The heterozygosis probabilities for all three individuals of the single tree of normal individuals occurring in the worked pedigree can be obtained from the term {1/2 + (1-K)/2.[(2-K)/2] 2 } by applying simple Bayesian reasoning, or by means of computer programs. In an earlier work (Horimoto et al., 2010) we describe two self-contained computer programs that perform most calculations necessary to estimate the penetrance rate. These are the programs PenCalc for Windows and PenCalc Web, which can be obtained free of charge from the web page http://www.ib.usp.br/~otto/software.htm. Both programs are described in detail in the above mentioned article as well as in the PDF-guide included in the zipped file of the program PenCalc for Windows.
(2) Construction of Exact Credible Intervals for K Estimates Rogatko et. al. (1986) also used an exact credible interval associated with a given K estimate. This interval can be obtained by finding the area that corresponds to a given proportion (v.g., 95%) of the total area under the graph of the likelihood function. Mathematically, the problem is reduced to integrating the function y = f(K) between two limits a and b with the same ordinate value , an operation which can be accomplished by simple computer programs using numerical integration techniques such as Romberg's oscullatory method. The lower and upper limits of the exact 95% credible interval for the estimate K = 0.418 of the example above are 0.163 and 0.725, respectively. This credible interval is so large that it might seem to be impractical in a clinical setting. The reason for this particular extreme range is that it was derived from the few data of the small family used as example. In practice, larger pedigrees are usually used. The ideal situation is one where several pedigrees of the same condition are available for analysis, and the pooled data are used to perform the calculations of the penetrance rate and of its 95% credible interval. For instance, from the analysis of 21 different published pedigrees on the autosomal dominant ectrodactyly-tibial hemimelia syndrome, penetrance estimates and their corresponding credible intervals varied from 0.191 (0.044-0.574) to 0.750 (0.329-0.973), while the global (pooled) penetrance value estimate was 0.392, with a 95% credible interval of 0.339 to 0.447 (Horimoto, 2009).
(3) Specificity and Heterogeneity Issues
Another point that merits discussion is whether the K value is specific for the family in which the disease segregates or for the condition itself, independently from the family. The non-penetrance of a genetic trait is assumed to represent the lack of its phenotypic manifestation exclusively or predominantly due to environmental factors (Murphy and Chase, 1975; Praxedes and Otto, 2000) or random 584 Otto and Horimoto genetic and epigenetic processes linked to the disease locus.
Of course penetrance can also be affected by a number of events that include the epistatic action of modifying genes and even temporal modifications of diagnostic criteria. Therefore, to a certain extent, penetrance estimates might be family-specific. Another complicating issue is that genetically heterogeneous conditions can be merged in the pooling process. Nevertheless, since the statistical credible intervals of isolated pedigrees usually are large, pooled estimates of the parameter should be preferred, unless statistical tests disclose the existence of great amounts of heterogeneity among penetrance estimates from various pedigrees.
(4) Penetrance Rate Estimates from Families Undergoing Molecular Testing In this section we discuss the comparison of estimates obtained from families without molecular testing as to those for which DNA testing has been used for classifying nonpenetrant heterozygotes and normal homozygotes. In the latter case, if molecular testing discloses all non-penetrant heterozygotes inside normal trees of individuals descending from obligate carriers, and if there are n 1 affected (penetrant) individuals and n 2 non-penetrant heterozygotes in the family, the likelihood function reduces to L = log(P) = n 1 .log(K)+n 2 .log(1-K). The maximum likelihood estimate is then K = n 1 /(n 1 +n 2 ), with binomial sampling variance of var(K) = K(1-K)/(n 1 +n 2 ). This would be an ideal situation in which, besides providing a better estimate of K, the corresponding 95% credible interval of the penetrance value thus evaluated will be much smaller than the one provided by the analysis of the family without DNA testing.
(5) Lack of Information about the Phenotype of the Pedigree Generator
In some published pedigrees there is a lack of phenotypic information about the genealogy generator (affected or non-affected?). Furthermore, the likelihood function P may not include the parameter K or (1-K) corresponding to the genealogy generator.
In order to evaluate whether the inclusion of the pedigree generator significantly alters this K estimate, it is not necessary to repeat the calculations for the two configurations possible (penetrant or non-penetrant common ascendant), because the likelihood function P, derived without information on the pedigree generator, is correct, and thus cannot be improved. In fact, if one wants to refer to the pedigree founder, one can say that she/he was affected with probability K and unaffected with probability (1-K). The resulting likelihood is KP + (1-K)P = P.
(6) Genealogies Containing Grouped Parent-Offspring Information within Trees of Normal Individuals Descending from Obligate Carriers
Certain published pedigrees present grouped parentoffspring trees of normal individuals, without informing the corresponding offspring numbers of all individuals in a given sibship, as is the case of the pedigree with cases of the ectrodactyly-tibial hemimelia syndrome (Majewski et al., 1985) shown in Figure 2. This tree of normal individuals represented by individuals II.8 to II.11 and III.14 to III.28 does not detail individual offspring numbers, and only the total number of 15 is given.
Incomplete pedigree information is a simple but interesting problem in combinatorial analysis that can be straightforwardly solved by means of the theory of difference operators. Table 1 lists the numbers of possible genealogy structures for a case of incomplete parent-offspring information as a function of both parent and offspring numbers. Therein, with four parents, the number of possible structures is given by y 4 (n) = (n+1) 2 + (n+1)n(n-1)/6, where n is the total offspring number of the four parents. For n = 15, the outcome is y 4 (15) = 816 of such structures.
For each combination {i, j, l, m} of offspring number the likelihood function of the whole tree is: where i, j, l, and m are the unknown numbers of children for each of the individuals II-8, II-9, II-10, and II-11, respec-Penetrance rate estimation 585 tively. In a population of approximately stable size, the average offspring number per couple does not differ from two and it is known that the number of children per couple adequately fits a Poisson distribution g(x) = e -2 2 x /x! . If each possible configuration is weighed by its probability (according to the Poisson distribution for the number of children per couple), this gives a credible interval on K in a straightforward manner. This can be achieved as follows using the function: and considering all 816 possible configurations referred to above. For each configuration one can then obtain not only a K ijlm estimate but also its exact 95% credible interval. Estimates for the penetrance value K, as well as for its exact 95% lower and upper credible limits L K and U K, corresponding to the given tree structure can be straightforwardly obtained by averaging the estimates K ijlm , as well as those for the lower and upper limits L K ijlm and U K ijlm , as: K = S(K ijlm .e -2 2 i /i!.e -2 2 j /j!.e -2 2 l /l!.e -2 2 m /m!) / S(e -2 2 i /i! . e -2 2 j /j! . e -2 2 l /l! . e -2 2 m /m!) The numerical procedure is herein detailed using as an example the simple hypothetical pedigree represented in Figure 3. Table 2 shows the penetrance rate estimates for all possible configurations contained in the grouped tree of normal individuals of Figure 3. The final estimates for the penetrance rate and for the lower and upper limits of its 95% credible interval are 0.4377, 0.1471 and 0.7813, respectively.
(7) Ascertainment Issues
The general method proposed by Rogatko et al. (1986) does not take into account any ascertainment biases. The authors are correct in their paper in stating that their approach gets around the sample space problem by using only the likelihood of the parameters, given the actual observations. Yet if ascertainment is not included, that likelihood itself will not be correct. Advanced computer programs that perform segregation analysis or estimate linkage, such as the classical S.A.G.E. (S.A.G.E., 2009) and LINKAGE (Lathrop et al., 1985) programs we referred to in the introduction section, do not apply any ascertainment bias to the penetrance rate they indirectly estimate.
By using a very simple example we could show that the crude K estimates obtained from genealogies are actually inflated. Figure 4 lists all possible trees of offspring size = 2 with a pedigree generator carrier of the pathologic gene (affected in A, B and C, and non-penetrant heterozygous in D, E and F) disclosed by an (impossible) ascertainment devoid of any bias. The probabilities associated with each tree are shown in Figure 4.
Let now n A , n B , n C , n D , n E , and n F be the numbers of structures A, B, C, D, E, and F observed in an ideal, large sample collected without any ascertainment bias. Then, the corresponding likelihood function in logarithmic form would be: L 1 = (3n A +2n B +2n D +n E ).ln(K) + (n D +n E +n F ).ln(1-K) + (n B +2n C +n E +2n F ).ln(2-K), from which the maximum likelihood estimate of K is obtained without difficulties.
A careful collection of a large number of families with offspring number 2 and a tree-generator carrier of the gene would consist only of structures A, B, C and D. Configuration E would not be included, as the only affected individual would be, with a large probability, the result of a new mutation; and configuration F would never be ascer-586 Otto and Horimoto i, j: offspring numbers of the two parents; P ij : normalized product (weighing factor) obtained through P ij = e -2 2 i /i!.e -2 2 j /j!/S(e -2 2 i /i!.e -2 2 j /j!); average estimates for K ij , L K ij and U K ij are shown in bottom line. tained, because it contains only normal individuals. The corresponding (logarithmic) likelihood expression would then be given by: L 2 = (3n A +2n B +n C +2n D ).ln(K) + n D .ln(1-K) + (n B +2n C ).ln(2-K), from which, as in the previous case, the maximum likelihood estimate can be easily obtained.
Let us now take the following numerical example. Let the actual (unknown) value of K be 0.8; then the probabilities associated with structures A, B, C, D, E, and F would take the values P(A) = 0.128, P(B) = 0.384, P(C) = 0.288, P(D) = 0.032, P(E) = 0.096, and P(F) = 0.288. In a sample of size 1000 we would therefore expect to find the sample numbers n A = 128, n B = 384, n C = 288, n D = 32, n E = 96, and n F = 72. The unbiased estimate would then take the value K = 0.8, as expected. In the case of an incompletely ascertained sample, the biased estimate of K' would take the value 0.951825 > 0.8.
It is not possible to obtain an exact solution in simple analytical form for the function K' = f(K), where K' is the biased maximum likelihood estimate and K the true one (unknown, completely unbiased estimate of the penetrance value), but we can evaluate K' estimates for any given fixed value of K by means of likelihood expression L 2 . For any true value of K the biased estimate, K' is an inflated value, as we could guess intuitively. Using a program on nonlinear regression analysis, such as the NLREG software (Sherrod, 2000), we can adjust the observed set of points to the generalized empirical function y = ax b .e cx (Bronshtein and Semendiaev, 1973) where y = K' and x = K.
We then estimated sets of pairs of values K and K' varying offspring size from 2 to 10, and in each case we obtained corresponding generalized empirical functions y i = a i x bi .e cix , where y = K' and x = K. as in the case of the previous example. The functions corresponding to offspring sizes from 2 to 10, all showing a perfect statistical fitting with the corresponding observed biased estimates, are plotted in Figure 5, where y stands for K' and x for K. The graph also shows the function K' = K that corresponds to the case of an offspring with infinite size.
As expected, with sibship size increasing the difference between corresponding estimates K' and K becomes negligible, mainly in relation to values of K in its usual range (K > 0.8). This is a result that certainly can be generalized for any homogeneous or heterogeneous set of Penetrance rate estimation 587 Figure 5 -Relation between unbiased (K) and biased (K') penetrance values, shown at abscissa and ordinate axes respectively, depending on offspring size (2, 3, 4, 5, 6, ..., infinite). pedigrees. Since optimized K estimates are obtained from large filtered pedigrees, or from the pooling of many pedigrees, the ascertainment bias just discussed will only produce slightly inflated K estimates. In the case the actual values of K, as well as the total number of informative individuals (penetrant, obligate non-penetrant and those belonging to normal trees descending from obligate carriers) are both small, the K estimates will not be reliable, as shown in Figure 5. For offspring sizes of 10 (total of 11 informative individuals) or more, it is also easy to conclude that estimated values of K in the range of 0.5 or more are reliable and do not need to be corrected. In any case, estimate corrections can be performed by enumerating all possible filtered pedigrees corresponding to a given tree structure and comparing the estimated K values to the inferred actual ones, just as we did before using the very simple examples discussed above. | 4,615.8 | 2012-07-01T00:00:00.000 | [
"Biology"
] |
The relationship between awareness and behavioural change in the context of the issue of violence against women from the perspective of digital public relations and online events
Aim. The research objective is to implement a scale which has been developed for digital public relations, online events and awareness concepts, on persons who participated in 7 different Webinars themed on women and violence, hence to put forward the power of creating any behavioural change in awareness extent of online events in the scope of digital public relations. Methods. For this research study, a scale has been devised based on the online event model designed as per digital public relations. In this context, the survey method, one of the quantitative research methods, has been used. Results. Research findings reveal that the higher online event driven awareness is, the more behavioural changes are in digital public relations; that women, when compared to men, are more responsive to digital public relations applications and have a better level of awareness in comparison; that 18-25 age group is more responsive with a higher level of awareness to digital public relations applications when compared to 26-33 age group; and that parents’ educational background makes no difference in this regard. Conclusions. In light of the research findings, it can be seen that digital public relations applications help to create awareness in terms of online events, and also pave the way for behavioural changes. In this context, it needs highlighting that digital public relations applications should be further improved in particular mat - ters, such as violence against women, in which creating awareness is crucial.
Introduction
I n broad terms, we observe an intense effect of digital-online tools on the concept of communication as a consequence of the unavoidable change and transformation of the century we are living in. In consideration of the concept of public relations in this context, the effect of digital-online transformation emerges as an undeniable fact, as in all means of communication. According to We Are Social 2020 report, Internet, social media and mobile user statistics comprise 4.54 billion internet users corresponding to 59% of world population, 3.80 billion social media users corresponding to 49% of world population, and 5.19 billion mobile users corresponding to 67% of world population (We Are Social, 2020). From this aspect, the reason for the ability of individuals and organisations to easily move on, by quickly engaging in digital-online communication during the Covid-19 social isolation period experienced throughout the world and in Turkey, is revealed.
Based on the data in We Are Social 2020 report, it can be suggested that the need for implementation of digital public relations applications is quite important in terms of creating social awareness. In this context, according to Marshall McLuhan, who predicted that digital transformation of the concept of communication would have an impact on social life, every new media tool adds certain social values to and improves individuals, enabling them to adapt to new cultural structures and get shaped according to these new values (McLuhan, 1964). From this aspect, it can be concluded that digital communication may have quite an impact on creating awareness. At this point, it can be suggested that underlining the concept of online event management would be especially important to implement digital public relations applications in the process of creating social awareness.
Digital public relations applications and awareness
Filiz Balta Peltekoglu (2018) underlines the concept of public relations as a strategic communication management process; when a large and corporate establishment desires to adapt to the mentality of social responsibility, respond to expectations of its employees, and reach a common ground with mutual communication, two-way symmetrical model is ideal (Balta Peltekoglu, 2018). In parallel with this definition in the context of digital communication, James E. Grunig, who indicates that social media was "a new form of public relations," underlines that social media would "realise the practice of public relations in a more global strategic, two-way and interactive manner" (Grunig, 2009, p. 1). According to Grunig, from the aspect of a strategic management paradigm in the context of public relations, it is a very important factor for new digital media to have two-way mutual communication and also interaction (Grunig, 2005).
Grunigand Todd Hunt (1984) indicates that within the scope of two-way symmetrical model, a communication process, which is a mutual feedback with target audiences, is extremely important in public relations. In this context, in implementation of digital public relations events, the use of online networks is extremely important in terms of sharing services provided by the organisation with stakeholders, informing them, and receiving feedback (Gifford, 2010).
While Dmitrii Gavra and Alyona Savitskaya (2012) define digital public relations as applications performed through online media, search engines or social networks, created as communication and interaction channels on online media, Jill Dyche (2002) states that many opportunities to establish two-way communication between consumer and establishments have arisen upon digital implementation of public relations applications, which has made interaction between establishments and their consumers much more quicker and easier. At this point, Janet Gifford remarks that traditional means of public relation were transcended by reaching very wide audiences thanks to the concept of digital public relations (Gifford, 2010). In consideration of digital public relations concept within the scope of available literature, remarks about the concept reveal that the importance of digital public relations concept in processes for creating awareness should be underlined within the new media. In consideration of digital public relations applications (webinar, online congress, conference, etc.) during the social isolation period, it is observed that the participants considered new media as a new public relations environment and adopted such applications quite easily. Grunig, who predicted in 2009 that the environment in question would be formed, remarked that "new media has the potential to make the profession of public relations more global, strategic, two-way and interactive, symmetrical or dialogical, and socially responsible" (Grunig, 2009, p. 1).
According to Çiğdem Kağıtçıbaşı (1999), the concept of awareness is used to indicate the extent, to which people are aware of their attitudes and behaviours. In case of high awareness, before acting, people think about what is right and what is not regarding the situation that they are aware of, and act, i.e. exhibit behaviours, when they consider it to be the right time (Kağıtçıbaşı, 1999). Based on this, it can be suggested that creating awareness with public relations applications could have an impact on behavioural change of the person after the application. At this point, digital public relations emerge as a factor, the need for which should be particularly underlined at the present day.
In the 2030 Agenda of the United Nations, we see the titles improving gender equality and empowerment of women, providing skill changing and employment opportunities for refugees and immigrants, protecting the planet, building risk management and flexibility, preventing severe conflicts and building peaceful communities (Achieving Agenda 2030, 2018). Based on the titles in question, implementation of digital public relations applications becomes crucial in creating social awareness and taking action particularly at the present time, as we are going through the social isolation process.
Online event management
According to Balta Peltekoglu (2018), the concept of event management, which is extremely important for public relations, defines rituals, presentations, performances, or celebrations, conducted upon planning all details in advance, to serve social, cultural or corporate purposes. In terms of their purposes, events can be categorised as social events, charitable events and corporate events; however, it is possible to diversify these categorisations (Wolf et al., 2005, as cited in Balta Peltekoglu, 2018, p. 325). On the other hand, Johnny Allen, et al., addressed events in terms of their magnitude. In this context, events are addressed under four titles, i.e. local, major, regional and mega events. It is particularly underlined that the most important impact of the hallmark events (hallmark events can also be referred to as milestone or branded events) concerning public relations is creating awareness (Allen et al., 2005, as cited in Balta Peltekoglu, 2018, p. 323).
Improvement of communication technologies and digitalisation of communication affected public relations applications as well, transforming digital communication platforms into alternative communication media for public relations events. At this point, it has become crucial to underline the importance of online events and their effect on awareness. Based on the available literature on the concept, online event management in digital public relations can be defined as a field of application based on creativity, intending to create awareness in lines with objectives and purposes of establishments or organisations. At this point, it should be underlined that one of the most important points in event management is the factor of creativity. It can be suggested that this is extremely important in terms of ensuring memorability of events. An ordinary event can by no means be expected to attract attention, thus creating awareness on the target audience. Particularly at the present time, when technology has been advancing very rapidly, current digital factors in online event management should be pursued and, in this context, creative events should be implemented to create awareness.
In the online event model within the scope of digital public relations (see Fig. 1) set forth in line with online events observed today in the light of available literature, it is prescribed that individuals, establishments and organisations manage online events in four dimensions. These events were categorised as social, cultural, charitable, and corporate. Celebrations may be included in the scope of online social events. Online celebration of holidays on political platforms during the social isolation period due to Covid-19 can be given as an example. Concerts without audiences, which were performed online, can be included in the scope of online cultural events. Online charitable events may include events organised on the basis of online fundraising system by various establishments and organisations. On the other hand, online corporate events should be considered in two dimensions. These are events organised for internal target audiences and external target audiences. Events organised for internal target audiences can be exemplified with online personnel motivation events (pilates etc.), while events organised for external target audiences can be exemplified with corporate social responsibility events. It was asserted that the events performed on four dimensions in the online event model within the scope of digital public relations created in line with the available literature, can be organised as Local, Major, Regional and Mega according to their scopes. However, they cannot be expected to have strict boundaries from an online point of view towards event management. Therefore, in consideration of the speed of online spreading, it should be considered that the event could spread over a wide area by reaching too many people than anticipated in the beginning. Cultural activities involving residents of the area, organised by Istanbul Metropolitan Municipality during the social isolation period, can be given as an example within the scope of the model. An example for online major events could be the online jazz festival organised by Istanbul Foundation for Culture and Arts. Others could involve online organisation of International Adana Altin Koza Film Festival as an example of online regional events, and online organisation of the Academy Awards as an example of online mega events. The model contains the factors of awareness, followed by behavioural changes, created by online events. The factors in question were positioned within the model on the basis of available literature and the information that awareness is effective on behavioural change, as set forth by Çiğdem Kağıtçıbaşı (1999). In this regard, it is possible to estimate that there may be a significant relationship between awareness creation and behavioural change aspects of events organised within the scope of digital public relations.
The issue of violence against women
If addressed in a conceptual aspect, violence can be defined as a fact with multiple variables, which can be encountered in all socio-economic structures. In this context, it is possible to state that violence is directly associated with many factors (such as economic, political, socio-cultural, educational, etc.). "Violence, manifested in personal, interpersonal and collective forms, is, by its nature, addressed under four main titles as physical, sexual, psychological, deprivation and neglect" (World Health Organisation, 2002). Encountering violence under four main titles can be inherently defined as likewise self-propagating factors in violence against women as well. However, it can be said that the most qualitatively measurable aspect is, unfortunately, physical violence. This is because legal implications can be determined in the context of data. Most cases are referred to the judicial system following physical violence; therefore, measurable data is obtained. We encounter such data sometimes as murders committed by men, and sometimes as criminal complaints arising from grievous bodily harm. Violence against women is increasing day by day. As of March, after Covid-19-related social isolation processes started, news regarding violence against women were frequently covered by the media, and 131 femicides and 95 suspicious deaths took place according to the reports by the We Will Stop Femicide Platform, covering the months between April and August 2020. The data reveals the large extent of violence against women during the period in question. At this point, it is necessary to underline the importance of implementing digital public relations applications about creating social awareness. In this context, in consideration of the fact that incidents of violence against women quantitatively increased during the social isolation period, it can be argued that it is extremely important to address the concept from a point of view of online event management in terms of implementing digital public relations applications to create awareness about the issue.
Purpose of the study
Frequent coverage of news about violence against women in mass media after the beginning of Covid-19-related social isolation process in Turkey reveals the large scale of the issue. In consideration of the data in this context, the data from "We Will Stop Femicide Platform" (non-governmental organisation established to prevent violence against women in Turkey), covering the months between April and August 2020, reveals the importance of implementing digital public relations applications concerning creation of social awareness about violence against women. The purpose of the study is to apply the scale developed within the scope of social responsibility activities towards external target audience, under the title "Online Corporate Events" in the online event model within the scope of digital public relations (see Fig. 1) suggested in line with online events observed at the present day in the light of available literature, on people attending 7 webinars about women and violence, and to set forth the power of online events, within the scope of digital public relations, to create behavioural changes in terms of awareness.
Sample and method of the study
Sample of the study includes 97 of 150 people in total who attended 7 webinars about women and violence ("Strong Women Working Mothers," "Solidarity at Home During Social Isolation," "Life Fits into Home Unlike Violence," "No to Social Distance in Housework," "Don't be a Bystander," "We are Responsible at Home," "Your Beauty Your Choice"), organised by the Department of Public Relations and Advertising and the Gender Research and Application Center of Istanbul Gelisim University in one hour between the dates May 27, 2020 and June 05, 2020 during the social isolation process. In this context, survey method, one of the quantitative research methods, was used. Obtained data was transferred to Statistical Package for the Social Sciences (SPSS) for Windows 21.0 statistical package software and evaluated with this software. A 5-point likert scale, comprising a total of 21 items in 2 aspects, was used. 5 represents completely agree, while 1 represents completely disagree. There was no disqualified survey and no unanswered question. To fulfil reliability-validity criteria, Cronbach Alpha value was used to test reliability of the survey, and Kaiser-Meyer-Olkin statistic was used to test value and validity. Scales within the scope of the study were generally in the range of 0.90 < KMO ≤ 0.80' (general awareness and behavioural change scale value addressed within the scope of the study was 0.896) according to scale validity table of Kaiser-Meyer-Olkin (KMO) Statistic. This indicates that validity of the scale was good. General Cronbach Alpha value of scales, addressed within the scope of the study, was 0.949. Upon evaluation of the scale reliability coefficient in the study based on general criteria scales, it is observed to be highly reliable. All tests were conducted at 0.05 significance level, which is preferred in social sciences.
Hypotheses developed within the scope of the study are as follows: H1.There is a significant relationship between the variable of awareness creation by online events and the variable of behavioural change in the context of digital public relations. H2. There is a significant difference between the variable of awareness creation by online events and the variable of gender in the context of digital public relations. H3. There is a significant relationship between the variable of awareness creation by online events and the variable of age in the context of digital public relations. H4. There is a significant relationship between the variable of awareness creation by online events and the variable of mother's educational background in the context of digital public relations. H5. There is a significant relationship between the variable of awareness creation by online events and the variable of father's educational background in the context of digital public relations.
Demographic Attributes of Study Participants
Demographic attributes of surveyed workers are indicated in the following table. In consideration of the average scores of awareness creation stage frequency analysis results and behavioural change frequency analysis results, it can be suggested that the participants, with 4.37 and 3.92 values, agree with opinions in 21 statements developed within the scope of the scale. Based on such data, it is possible to reach the finding that digital public relations applications have an impact on creating awareness with online events. According to the results of Pearson Product-Moment Correlation Analysis, it was found that there was a positive and significant relationship between the average score received from awareness creation variable and the average score received from behavioural change variable (r=0.611; p< 0.05). In this case, H1 is accepted. Based on this, it can be suggested that behavioural change increases as awareness increases. According to the results of Mann-Whitney U Difference Analysis, scores of awareness creation variable scale exhibit significant difference according to gender variable (p < 0.05). In this case, H2 is accepted. It is seen that awareness variable mean rank of women (58.14) is higher than men (39.67). Based on this, it can be suggested that women are affected more by digital public relations applications and have higher awareness than men, according to the scores of awareness creation variable scale. According to the results of Kruskal Wallis Difference Analysis, awareness creation variable scores exhibit significant variation than age variable (p < 0.05). In this case H3 is accepted. It is seen that awareness variable mean rank of 18-25 age group (52.64) is higher than 26-33 age group (23.25). Based on this, it can be suggested that 18-25 age group is affected more by digital public relations applications and has higher awareness than 26-33 age group, according to the scores of awareness creation variable scale. Awareness creation variable scale scores do not exhibit significant difference according to mother's educational background variable (p > 0.05). In this case, H4 is rejected. Based on this, it can be suggested that awareness affected by digital public relations applications is not associated with mother's educational background variable.
Conclusion and recommendations
Development in communication technologies and digitalisation of communication affected public relations practices as well, converting digital communication platforms into a public relations communication medium. The introduction of digital public relations applications gained prominence, particularly upon the beginning of Covid-19 social isolation process. At this point, the concept of event management, which is a field of application intertwined with public relations, should be underlined. Upon transformation of public relations applications into digital public relations, the concept of event management was thus transformed into the concept of online events. It is a fact that creative online events may increase the awareness creation power of digital public relations. In this context, creative online events are needed within the scope of digital public relations applications to create awareness at the present day. At this point, the foremost issue, for which awareness should be created, is violence against women.
Particularly, violence against women in Turkey is a significant social issue awaiting solution. The reports prepared by the We Will Stop Femicide Platform between April and August 2020 indicate that this issue was complicated even further during the Covid-19 social isolation process. Study results demonstrate that immediate implementation of digital public relations applications to create awareness and organisation of online events within this scope would be a first and important step to solve the issue.
According to study results, in consideration of the average scores of awareness creation stage frequency analysis results and behavioural change frequency analysis results, it can be suggested that the participants, with 4.37 and 3.92 values, agree with opinions in 21 statements developed within the scope of the scale. Based on such data, it is possible to reach the finding that digital public relations applications have impact on creating awareness with online events. According to the results of Pearson Product-Moment Correlation Analysis, it was found that there was a positive and significant relationship between the average score received from awareness creation variable and the average score received from behavioural change variable (r=0.611; p< 0.05). In this case, H1 is accepted. Based on this, it can be suggested that behavioural change increases as awareness increases.
According to the results of Mann-Whitney U Difference Analysis, scores of awareness creation variable scale exhibit significant difference according to gender variable (p < 0.05). In this case, H2 is accepted. It is seen that awareness variable mean rank of women (58.14) is higher than men (39.67). Based on this, it can be suggested that women are affected more by digital public relations applications and have higher awareness than men according to the scores of awareness creation variable scale.
According to the results of Kruskal Wallis Difference Analysis, awareness creation variable scores exhibit significant variation than age variable (p<0.05). In this case H3 is accepted. It is seen that awareness variable mean rank of 18-25 age group (52.64) is higher than 26-33 age group (23.25). Based on this, it can be suggested that 18-25 age group is affected more by digital public relations applications and has higher awareness than 26-33 age group according to the scores of awareness creation variable scale.
The results of the study show that the scores on the awareness formation variable scale do not differ significantly (p >0.05) depending on the mother's education. H4 is rejected in this case. From this perspective, the state of being aware as a result of being affected in digital public relations practices is unrelated to the mother's education variable. The scores of the awareness formation variable did not differ significantly according to the father's education variable (p >0.05) in another analysis. H5 is rejected in this case. From this perspective, it can be deduced that being aware of being influenced by digital public relations practices has nothing to do with the father's education.
Based on the findings of the study, it is can be observed that digital public relations applications have awareness creating and also behaviour changing effects within the scope of online events. The power of this effect may vary for circumstances such as field of application, time, participants, subject, etc.; however, the presence of the effect is an undeniable fact. In this context, it should be underlined that digital public relations applications should be developed in areas such as violence against women, where it is extremely important to create awareness, during the Covid-19 social isolation process that spread throughout the world and during which we must adapt to a new world system. | 5,555.2 | 2021-09-25T00:00:00.000 | [
"Computer Science"
] |
Two‐dimensional Reconstruction of a Time‐dependent Mirror Structure from Double‐polytropic MHD Simulation
A new reconstruction method incorporated with pressure anisotropy parameter, α(B) , has recently been developed for magnetohydrostatic equilibria and successfully applied to recovering a two‐dimensional (2‐D) magnetic field map of mirror structures observed in the Earth's magnetosheath. Here, α(B)=μ0(p∥−p⊥)/B2 is assumed to be a function of magnetic field strength, B , alone. The fundamental reconstruction theory assumes that the magnetic field and plasma configurations are time‐independent and 2‐D, which may not be fulfilled in the real applications to satellite observations. When the 2‐D structure is time‐dependent, the intrinsic field‐line invariant Fz=(1−α)Bz is violated so that the quantity Fz is not constant for the same field line. This paper aims to examine the performance of the α(B) reconstruction of a time‐dependent mirror structure, using data from a 2‐D, double‐polytropic Magnetohydrodynamics (MHD) simulation. With a single‐branched fitting function for the field‐line invariant, results show that the geometry of time‐dependent mirror structure can be reasonably reconstructed, including the distribution maps of gyrotropic pressures p∥ and p⊥ . As expected, the assumption of α(B) is well satisfied for the mirror structure. Additionally, another two reconstruction methods are also tested, namely, the Grad‐Shafranov reconstruction and the α(A) reconstruction. The former is considered isotropic pressure, while the latter assumes that α is function of vector potential A alone. As expected, these two reconstruction methods fail to recover the geometry of the mirror structure. We suggest that use of a single‐branched fitting function is more appropriate for reconstruction of a time‐dependent, wave‐like structure, regardless of which magnetohydrostatic reconstruction method is applied.
Introduction
The Grad-Shafranov (GS)-based reconstruction method is a useful tool of satellite data analysis to recover time-independent, two-dimensional (2-D) magnetic field and plasma configurations of a coherent structure in space. The original reconstruction method was based on the well-known GS equation that describes the magnetohydrostatic equilibria with isotropic pressure. Hereafter, it is called the GS reconstruction. The GS reconstruction scheme is to integrate the GS equation as a spatial initial-value problem with data taken from a single spacecraft. The GS reconstruction has been successfully implemented to examine the geometry of magnetopause structures (e.g., Hasegawa et al., 2004Hasegawa et al., , 2006Hau & Sonnerup, 1999;Hu & Sonnerup, 2000;Sonnerup et al. 2004;Teh et al., 2010;Teh & Hau, 2007), and the magnetic flux ropes and magnetic clouds in the solar wind (e.g., Hu, 2017;Hu & Sonnerup, 2001, 2002.
Recently, the reconstruction theory has been applied to the magnetohydrostatic equilibria with gyrotropic pressure. The degree of the pressure anisotropy can be described by a parameter, where p and p are the plasma pressures perpendicular and parallel to the magnetic field, respectively. Assuming that is function of vector potential A alone, that is, , Teh (2018aTeh ( , 2018b) derived a GS-like equation in a simple formulation, for which three fitting functions of vector potential A are required for reconstruction. Later, Teh (2019) realized that the simple GS-like formulation with pressure anisotropy for reconstruction can also be achieved by assuming that the gyrotropic pressure is function of magnetic field strength alone and thus leading to has recently been developed for magnetohydrostatic equilibria and successfully applied to recovering a two-dimensional (2-D) magnetic field map of mirror structures observed in the Earth's magnetosheath.
is assumed to be a function of magnetic field strength, B, alone. The fundamental reconstruction theory assumes that the magnetic field and plasma configurations are timeindependent and 2-D, which may not be fulfilled in the real applications to satellite observations. When the 2-D structure is time-dependent, the intrinsic field-line invariant is violated so that the quantity z F is not constant for the same field line. This paper aims to examine the performance of the B reconstruction of a time-dependent mirror structure, using data from a 2-D, double-polytropic Magnetohydrodynamics (MHD) simulation. With a single-branched fitting function for the fieldline invariant, results show that the geometry of time-dependent mirror structure can be reasonably reconstructed, including the distribution maps of gyrotropic pressures p and p . As expected, the assumption of B is well satisfied for the mirror structure. Additionally, another two reconstruction methods are also tested, namely, the Grad-Shafranov reconstruction and the A reconstruction. The former is considered isotropic pressure, while the latter assumes that is function of vector potential A • A time-dependent mirror structure from two-dimensional doublepolytropic MHD simulation is successfully recovered using alpha(B) reconstruction method • The Grad-Shafranov and alpha(A) reconstruction methods fails to recovery the mirror structure • Use of a single-branched fitting function is more appropriate for reconstruction of a time-dependent wave-like structure field-line invariant and z B is the magnetic field component along the invariant axis of the structure.
In the paper of Teh (2019), the B reconstruction was applied to recovering 2-D geometry of mirror structures in the Earth's magnetosheath and he found that the assumption of B is well satisfied for the mirror structure. It is noteworthy that using double-polytropic laws proposed by , Sonnerup et al. (2006) developed a reconstruction method incorporated with the gyrotropic pressure and field-aligned flow. Recently, Chen and Hau (2018) applied it to the magnetopause structures with field-aligned flows, while Tian et al. (2020) used it to recover the Pc5 compressional waves for magnetohydrostatic condition. This reconstruction method for magnetohydrostatic equilibria requires four fitting functions for four intrinsic field-line invariants and has to deal with a 6 × 6 sparse matrix. As compared with the A and B reconstructions, it requires more fitting functions and more physical quantities to solve.
The fundamental reconstruction theory assumes that the coherent structure in space is time-independent and 2-D. When the time-independent assumption is violated, the intrinsic field-line invariant, for example, z F , is no longer satisfied. Such a time-dependent structure may happen in the real applications to the satellite observations. Recent works by Liu et al. (2020) demonstrate that the evolution of magnetic cavity structure has a key role in the particle energization and energy dissipation. Understanding the configuration of time-dependent magnetic field structure can therefore provide insights into the process of the energy conversion. This paper aims to examine the performance of the B reconstruction of a time-dependent mirror structure, using data from a 2-D, ideal, double-polytropic MHD simulation (Teh & Zenitani, 2019). In addition, both the GS and A reconstruction methods are also tested. We note that the time-aliasing effect on the reconstruction studies by Hasegawa et al. (2014) is not considered in this study. The paper is organized as follows. Section 2 describes the B reconstruction theory and scheme. Section 3 describes the 2-D, double-polytropic MHD simulation and shows the reconstruction results for the three different reconstruction methods. Finally, summary and discussion are given in Section 4.
α B Reconstruction Theory and Scheme
With the assumption that the gyrotropic plasma pressure is solely dependent on the magnetic field strength, a 2-D coherent structure in the magnetohydrostatic equilibria can therefore be described by a GS-like equation as follows, The invariant axis of the 2-D structure is directed along the z axis. The quantity z F is an intrinsic field-line invariant and thus is function of vector potential A alone, while the pressure anisotropy parameter, , is function of magnetic field strength alone, based on the assumption. Here the magnetic field B is expressed as For the detailed derivation of Equation 1, the reader can find it in the paper of Teh (2019). It is noteworthy that when goes to zero, that is, the plasma pressure is isotropic, Equation 1 is thus reduced to the GS equation for force-free condition (i.e., the thermal pressure gradient force is neglected), instead of the original GS equation. This is because the gyrotropic plasma pressure is assumed to be solely dependent on the magnetic field strength. In this study, the absolute value of is well greater than zero.
To reconstruct a 2-D magnetic field map in the reconstruction plane (i.e., x-y plane), three unknowns are to be solved, namely, 2 By rewriting Equation 1 and differentiating z F and 2 B with respect to the variable y, three equations for reconstruction are obtained as follows: , where the superscript T denotes the matrix transpose. The row matrix The 2 × 2 matrix is therefore expressed as The / z dF dA and / d dB terms in the Y and can be determined numerically from the measurements and the x derivatives in the Y can also be calculated. Therefore, the two unknowns in the matrix X can be solved by inverting the matrix .
are known, the magnetic field map in the x-y plane can be reconstructed by integrating the vector potential A, x B , y B , and z B as follows: The initial values of vector potential A at y = 0 are computed as and 0 V is the motion of the structure. Note that the contour of vector potential A represents the magnetic field line. The distribution map of p can be reconstructed by integration of which is Equation 6 in the paper of Teh (2019). With the p distribution, the pressure p can then be calculated from the distribution, which is calculated from the function B .
Simulation Data and Reconstruction Results
The mirror structure for reconstruction is produced by the 2-D, ideal, double-polytropic MHD simulation (Teh & Zenitani, 2019). The advantage of using 2-D MHD model for this study is that we can rule out other effects (e.g., three-dimensional and non-ideal MHD) that can violate the fundamental assumptions of the reconstruction method.
The simulation codes are mainly inherited from the 2-D isotropic MHD codes by Zenitani andMiyoshi (2011) andZenitani (2015). In the double-polytropic laws, two polytropic exponents, and , are used as parameters to describe various thermodynamic conditions in the gyrotropic plasma . For example, = 3 and = 2 for double-adiabatic and = 1 and = 1 for double-isothermal. Teh and Zenitani (2019) have demonstrated that using the empirical values of = 1.14 and = 0.94 for magnetosheath plasma , the variations of temperatures T and T in the mirror structures observed by the Magnetospheric Multiscale Mission (MMS; Burch et al., 2016) in the magnetosheath can be reproduced. Note that using the empirical values of = 1.14 and = 0.94, the mirror instability TEH AND ZENITANI for double-polytropic MHD is different from the kinetic one (e.g., Hasegawa, 1969). As illustrated in Figure 1b of the paper of Teh and Zenitani (2019), the plasma unstable regime of the mirror structures observed by the MMS spacecraft in the magnetosheath is consistent for these two conditions. Similar results for the magnetosheath mirror structures are also concluded by Hau et al. (2020). (2019) is adopted in this study, except that a small and uniform z B is incorporated into the initial magnetic field profile of a uniform x B , instead of z B = 0. This modification allows us to examine the field-line invariant z F . The initial plasma beta Figure 1a. The characteristics of the mirror structure are evident in Figures 1e and 1f, that is, (1) the plasma density is anticorrelated with the magnetic field strength, and (2) both the pressures p and p are enhanced in the magnetic dip but depressed in the magnetic peak (e.g., Balikhin et al., 2009Balikhin et al., , 2010. Figures 1g-1i show the distribution maps of the time-dependent term /
The simulation setup implemented by Teh and Zenitani
color. It can be found that the time-dependent term is mostly larger than the inertial term, indicating that the time-dependent effect is dominant, the same result for the y component (not shown). In Figure 1j, the time evolution of the average of is demonstrated for the mirror structures. One can find that the mirror structures start to grow around t = 20 and the simulation time t = 40 is in the transition between the two main growth phases. The mirror structures at t = 40 will then be growing in later time. Figures 2a and 2b show plots of z F versus the vector potential A and versus the magnetic field strength, with a fitting curve in yellow. In Figure 2a, the red and blue dots denote the data associated with 0 y B and 0 y B , respectively. It is evident that there are two values of z F for the same vector potential A, indicating that the quantity z F is not constant along the magnetic field line. In the previous GS reconstruction studies of magnetopause structures, Hu and Sonnerup (2003) for the two sides of the magnetopause. The idea of double-branched function is not suitable for the mirror structure, because a clear boundary between two separate plasma regimes does not exist in the mirror structure. Therefore, a single-branched function of z F is used for reconstruction. A further discussion on this issue will be given in the next section. Unlike z F , the variations of the pressure anisotropy parameter are well correlated with the magnetic field strength, as shown in Figure 2b, indicating that the assumption of B is well satisfied for the mirror structure. Moreover, Figure 2c indicates that the variations of the pressures p and p are also well correlated with the magnetic field strength for the mirror structure. Figure 3 shows the reconstructed magnetic field maps of the time-dependent mirror structure, with z B , p , and p in color, using the magnetic field and plasma pressure data as shown in Figures 1d and 1f white dashed line denotes the original data line. As compared with the simulation results in Figures 1a-1c, the magnetic field configuration of the mirror structure is found to be successfully recovered and the reconstructed distributions of z B , p , and p are reasonable and acceptable. Figure 4 shows the quantitative comparisons of the reconstruction results (in red) with the simulation results (in black) for the data points along the two pink dashed lines in Figure 3. The correlation coefficient (cc) between them is also calculated and shown for each physical quantity. Overall, high cc values are achieved for the reconstruction results, indicating that the B reconstruction method performs well for the time-dependent mirror structure. We note that when the time-dependent effect becomes large, for example, in the second growth phase at t = 46, the deviation of the z F value at the same field line increases and thus the relationship between z F and the vector potential A is much less correlated (not shown). These results can therefore degrade the reconstruction performance. Figure 3. Obviously, the reconstructed magnetic field map and distributions of z B , p , and p are different from those for the leading part of the mirror structure in Figure 1. Overall, each reconstructed field component has cc< 0.6. Figure 6 shows the GS reconstruction results using the same data set as the and one can find that they also have the double-valued issue. However, there is no problem of using a single-branched function for the GS reconstruction because the TR p and z B quantities are not required during the integration and only the / TR dp dA is required. As compared with Figure 1a, the GS reconstruction map as well as the z B distribution are different from the simulation results. Overall, each reconstructed field component has 0.5 cc . While the GS and A reconstructions fail to recover the geometry of the mirror structure, the GS field map is qualitatively better than the A field map.
Summary and Discussion
To examine the performance of the field-line invariant is mainly caused by the time-dependent effect rather than the inertial effect. With a single-branched function z F , results show that the geometry of the time-dependent mirror structure can be reasonably reconstructed, including the distribution maps of z B , p , and p . As expected, the assumption of B is well satisfied for the mirror structure. Additionally, the GS and A reconstruction methods are also tested. As expected, these two reconstruction methods fail to recover the geometry of the mirror structure.
It is found in Figure 2a that the fitting curve of z F is not fitted well with the data. How would it affect the B reconstruction results? To answer that, Figure 7 shows the B reconstruction results only for the data associated with 0 y B . As seen in Figure 7a, the fitting curve is now well fitted with the data. One can find that the magnetic field map in Figure 7 is similar to that for the leading part of the mirror structure in Figure 3, including the distribution maps of z B , p , and p . For comparison, the two fieldline maps are overlaid in Figure 7e, where the yellow dashed lines represent the magnetic field lines for the leading part of the mirror structure in Figure 3. While most small deviations happen near the upper right corner of the map, the two field-line maps are mostly identical. From Equation 1, one can realize that the quantities of and z B are required during integration. Note that the quantity z B is advanced by Equation 10, while the quantity is advanced by the function B . Thus, this examination reveals that the / z dF dA term, which only appears in the matrix Y, plays a minor role in the reconstruction of the mirror structure.
It has been previously mentioned that the use of double-branched function for the field-line invariant is not suitable for the mirror structure. From the data set of reconstruction, the sign of y B is the indicator for branch selection. However, the sign of y B is not suitable for branch selection, because the y B changes sign more than once in the region below the original data line, which is evident in the real map in Figure 1. When using double-branched function for the GS reconstruction, the lower part of the reconstructed field map becomes more different from the real map (not shown). Therefore, it is suggested that use of a single-branched fitting function is more appropriate for reconstruction of a time-dependent, wave-like structure, regardless of which magnetohydrostatic reconstruction method is applied. TEH AND ZENITANI 10.1029/2020EA001449 8 of 10 | 4,405.8 | 2021-02-01T00:00:00.000 | [
"Physics"
] |
Calmodulin Binding to Dfi1p Promotes Invasiveness of Candida albicans
Candida albicans, a dimorphic fungus, undergoes hyphal development in response to many different environmental cues, including growth in contact with a semi-solid matrix. C. albicans forms hyphae that invade agar when cells are embedded in or grown on the surface of agar, and the integral membrane protein Dfi1p is required for this activity. In addition, Dfi1p is required for full activation of mitogen activated protein kinase Cek1p during growth on agar. In this study, we identified a putative calmodulin binding motif in the C-terminal tail of Dfi1p. This region of Dfi1p bound to calmodulin in vitro, and mutations that affected this region affected both calmodulin binding in vitro and invasive filamentation when incorporated into the full length Dfi1p protein. Moreover, increasing intracellular calcium levels led to calcium-dependent, Dfi1p-dependent Cek1p activation. We propose that conformational changes in Dfi1p in response to environmental conditions encountered during growth allow the protein to bind calmodulin and initiate a signaling cascade that activates Cek1p.
Introduction
Invasive candidiasis is the fourth most common nosocomial bloodstream infection in the United States. The dimorphic fungus C. albicans is responsible for the vast majority of these cases [1]. C. albicans can switch from a yeast to filamentous morphology in response to a wide variety of environmental conditions, including growth in contact with an agar matrix [2], and these changes in morphology are important for C. albicans pathogenesis (reviewed in [3,4,5,6]).
Several C. albicans signaling pathways are involved in sensing environmental cues and promoting filamentation. The mitogen activated protein kinase (MAPK) Cek1p plays an important role in hyphae development on solid media (reviewed in [7]). The protein kinase A pathway is a second pathway that also regulates hyphae development (reviewed in [8]).
When cells are grown in contact with agar, either by embedding the cells within the agar matrix or by culturing cells on the surface of medium, filamentous growth of cells within the agar is observed [2]. Two different MAPKs, Cek1p and Mkc1p, are activated when cells are growing in contact with agar [2,9,10,11]. Activation of Cek1p under these conditions is partially dependent on Dfi1p, an integral membrane protein that is important for filamentation in response to growth in contact with an agar matrix [12]. Dfi1p is also important for growth of C. albicans in the presence of cell wall targeting agents such as caspofungin or Congo red [12].
To understand the mechanism by which growth in contact with agar activated Dfi1p-dependent Cek1p activation, the sequence of the Dfi1p protein was analyzed. The C-terminal tail was found to contain a putative calmodulin binding motif, raising the possibility that Dfi1p binds calmodulin. Calmodulin, a ubiquitous eukaryotic protein involved in sensing and responding to calcium levels, is involved in filamentation in both C. albicans and the model yeast Saccharomyces cerevisiae [13,14,15,16]. Despite this similarity in function of C. albicans and S. cerevisiae calmodulin, C. albicans calmodulin shares more sequence homology with mammalian calmodulin than with S. cerevisiae calmodulin and contains four calcium binding sites [17].
The goal of this study was to demonstrate a connection between Dfi1p and calmodulin and to understand the role this connection plays in the functions of Dfi1p. We show that the C-terminal tail of Dfi1p binds calmodulin. Furthermore, we demonstrate that mutations that disrupt the calmodulin binding domain of Dfi1p affect filamentation and MAPK activation in response to contact with an agar matrix and in response to increased intracellular calcium levels. We propose that during signaling, Dfi1p binds at least transiently to calmodulin; binding to calmodulin then allows Dfi1p to initiate a signaling cascade that activates Cek1p.
Binding of calmodulin to the cytoplasmic tail of Dfi1p in vitro
Many different calmodulin binding motifs have been characterized. One of the main types of calcium-dependent calmodulin binding motifs, found in calcineurin and many other Ca 2+ / calmodulin-binding proteins, is the 1-5-8-14 motif, characterized by hydrophobic residues at amino acids 1, 5, 8 and 14 and several basic residues conferring a net positive charge [18]. As shown in Fig. 1A, the C-terminal, cytoplasmic tail of Dfi1p contains a putative 1-5-8-14 calmodulin binding motif. To determine whether this region of Dfi1p binds to calmodulin, the 44-amino acid C-terminal tail of Dfi1p was dually tagged with glutathione Stransferase (GST) and Strep-tag (strep), translated in vitro and incubated with immobilized bovine calmodulin in the presence of calcium. Bovine calmodulin has 72% protein sequence identity with C. albicans calmodulin [19]. Proteins bound to the calmodulin beads were eluted using the calcium chelator EGTA to release proteins that bound to calmodulin in a calcium-dependent manner and detected by Western blotting. When GST-Dfi1 tail-Strep was incubated with calmodulin, the elution fraction contained 25% of the total protein that was recovered from the column (Fig. 1B, WT). When a construct containing a linker region in place of the Dfi1p tail was used, no protein was detected in the elution fraction, indicating that the Dfi1p tail, not the protein tags, bound to calmodulin in vitro (Fig. 1B, ctl).
Mutations in Dfi1p affect calmodulin binding
To demonstrate that the putative calmodulin binding motif of Dfi1p was the region responsible for binding to calmodulin in vitro, three different mutants were constructed. The dfi1 R309A,K310A mutation (dfi1-RKAA) changes the charge of the region to be further from the consensus sequence, from a net +1 to a net -1; the dfi1 E302,312R mutation (dfi1-EERR) increases the net positive charge from +1 to +5, and the dfi1 W305,308Q mutation (dfi1-WWQQ) substitutes two critical hydrophobic residues at positions 5 and 8 within the 1-5-8-14 motif (Fig. 1A). Based on the effects of similar mutations in the V2 vasopressin receptor [20] and sphingosine kinase 1 [21], the dfi1-RKAA and dfi1-WWQQ mutations were predicted to disrupt calmodulin binding, whereas the dfi1-EERR mutation should retain calmodulin binding activity.
Mutant forms of the Dfi1 tail tagged with GST and Strep were translated in vitro and incubated with immobilized bovine calmodulin in the presence of calcium as before. The dfi1-RKAA and dfi1-WWQQ mutant proteins exhibited markedly reduced binding to calmodulin (Fig. 1B, 3% and 0% of the protein was eluted with EGTA) whereas the dfi1-EERR mutant protein retained the ability to bind calmodulin (30% of the protein was eluted with EGTA, Fig. 1B). Therefore, the predicted calmodulin binding motif of Dfi1p was important for binding to calmodulin in vitro; the features that define the motif must be intact in order for the Dfi1p tail to bind to calmodulin.
Calmodulin binding motif of Dfi1p is important for invasion of agar medium
To determine whether the calmodulin binding domain of Dfi1p was important for the function of Dfi1p, the dfi1-RKAA, dfi1-EERR, and dfi1-WWQQ point mutations were introduced into the full-length DFI1 gene with a 39 epitope tag (TAP) and the mutant constructs were integrated into the DFI1 locus of C. albicans. These mutant strains were then grown on the surface of or embedded within YPS 1% agar medium and incubated at 25uC. Under these conditions, wild type C. albicans filamented and invaded the agar, whereas Ddfi1 null mutants did not ( Figure 2A and reference [12]). The dfi1-WWQQ-TAP (2.2% filamentous colonies), dfi1-RKAA-TAP (2.5% filamentous colonies), and dfi1-EERR-TAP (1.9% filamentous colonies) mutants were defective in invading the agar in comparison with the wild type DFI1-TAP (89% filamentous colonies) ( Fig. 2A). All strains grew at a rate similar to that of the wild type strain in liquid medium. In addition, these strains germinated and elongated hyphae similarly to the wild type strain in YPD liquid medium supplemented with serum (10%) or Spider liquid medium at 37uC (data not shown), demonstrating that the mutants were capable of forming filamentous hyphae when stimulated by different cues.
The Dfi1p protein was expressed at similar to WT levels in the mutant strains. The amount of extractable Dfi1p was slightly higher in the dfi1-EERR-TAP strain and slightly lower in the dfi1-RKAA-TAP strain as compared to the wild type DFI1-TAP strain (Fig. 3A), although these minor differences were not statistically significant (paired t-test; dfi1-EERR-TAP mean 2.2-fold DFI1-TAP expression, p = 0.07; dfi1-RKAA-TAP mean 0.74-fold DFI1-TAP expression, p = 0.40). Also, despite the presence of autofluorescent spots (clearly seen in the strain lacking GFP), expression of mutant and wild type DFI1 tagged with GFP resulted in fluorescence at the periphery of the cells (Fig. 3B), demonstrating that the mutant proteins, like the wild type protein, were localized to the cell surface. Therefore, the normal production and localization of mutant proteins showed that the calmodulin binding motif of Dfi1p was important for invasive filamentation in response to growth in contact with agar.
Growth on cell wall targeting agents
In the absence of Dfi1p, strains are hyper-susceptible to cell wall targeting agents caspofungin and Congo red [12]. To determine whether these mutations alter growth in the presence of these compounds, the mutant strains were grown to late exponential phase in YPD and plated on YPD or YPD supplemented with either 90 ng/mL caspofungin or 200 mg/mL Congo red (Fig. 2B). All strains yielded colonies when plated on YPD only (Fig. 2B) but the Ddfi1 null exhibited low plating efficiency (reduced numbers of colonies for a given number of cells) on media containing caspofungin or Congo red. The dfi1-RKAA-TAP and dfi1-EERR-TAP mutants produced colonies on media containing caspofungin or Congo red, like the wild type DFI1-TAP strain. However, the Numbers below blot indicate the amount of protein in each lane as a percentage of the total protein that was recovered from the column. All samples were run on the same gel; the order of the WT lanes was changed for clarity. doi:10.1371/journal.pone.0076239.g001 dfi1-WWQQ-TAP mutant was more susceptible to these agents. Interestingly, the colonies in all of the mutant strains were smaller on media containing caspofungin or Congo red than on YPD alone, suggesting a slight growth defect on these agents even though the plating efficiencies for the dfi1-RKAA-TAP and dfi1-EERR-TAP mutants were similar to the wild type Dfi1-TAP strain. Therefore, mutations that change the charge of the calmodulin binding motif did not affect growth on cell wall targeting agents, but mutational change of the hydrophobic residues resulted in sensitivity to the agents. Interestingly, the dfi1-WWQQ-TAP mutant was more sensitive to Congo red than to caspofungin, indicating a difference in the effect of these two agents.
Mutations in the calmodulin binding motif of Dfi1p compromise Cek1p activation during growth in contact with agar medium
The MAP kinase Cek1p is activated when cells are grown in contact with agar medium and Dfi1p is required for full activation under these conditions [12]. To determine whether mutation of the calmodulin binding motif would affect the activation of Cek1p, the mutant strains were grown on YPS 1% agar at 25uC for four days. Cells were scraped off of the agar and extracted. Activated Cek1p was detected by Western blotting with antibody that recognizes the dually-phosphorylated form of p42/44 MAP Kinases; the Cek1p band was identified by its apparent molecular weight, absence in the Dcek1 null mutant strain and hyperphosphorylation in the Dcpp1 null mutant strain, as observed previously [12]. Levels of activated Cek1p were normalized to actin and compared to levels in strains carrying the wild type DFI1-TAP allele. When grown on the surface of agar medium, the Ddfi1 null mutant strain (Fig. 4, lane 1) showed low levels of activated Cek1p in comparison with the strain carrying WT DFI1-TAP ( Fig. 4 lane 2). In contrast, levels of phospho-Cek1p are undetectable during growth in liquid medium, as shown previously [12,22]. Similarly, the dfi1-RKAA-TAP (p = 0.009, paired t-test;
Increasing intracellular calcium results in Dfi1pdependent Cek1p activation
To show that interaction between Dfi1p and calmodulin promotes Dfi1p signaling in the cell, we asked whether an increase in intracellular calcium would lead to the activation of Cek1p in a Dfi1p-dependent manner in the absence of contact with agar medium. To increase intracellular calcium, the calcium ionophore A23187 was used and Dfi1p-dependent Cek1p activation was used as a read-out for Dfi1p signaling. In wild type cells, treatment with A23187 resulted in a 1.8-fold increase in Cek1p activation that was
Increased intracellular calcium does not lead to Cek1p activation if Dfi1p is defective in calmodulin binding
To demonstrate that calmodulin binding to Dfi1p is required for Cek1p activation in response to increased intracellular calcium, dfi1 mutants altered in calmodulin interaction were studied. The experiment was conducted as in Fig. 5A, using dfi1-RKAA-TAP, dfi1-EERR-TAP or dfi1-WWQQ-TAP mutant strains as well as WT DFI1-TAP and the Ddfi1 null mutant strain. As shown in Fig. 5A, Cek1p activation did not increase in the dfi1-RKAA-TAP and dfi1-WWQQ-TAP strains upon treatment with A23187 in the presence of calcium. Therefore, calmodulin binding to Dfi1p is required for Cek1p activation in response to increased intracellular calcium concentration.
The dfi1-EERR-TAP mutant retains the ability to bind calmodulin. In this mutant strain, Cek1p activation increased upon A23187 exposure in the presence of calcium. Therefore, Dfi1p dependent activation of Cek1p in response to increased intracellular calcium requires the ability of Dfi1p to bind calmodulin.
Dfi1p-dependent Cek1p activation requires calcium
To demonstrate that the effect of A23187 on Cek1p activation requires calcium, cells were grown in media without calcium. This growth condition resulted in Cek1p activation in the absence of A23187 (Fig. 5B, lane 1), which was reduced by the addition of calcium (Fig. 5B, lane 3). However, previous studies showed that activation of Cek1p in the absence of calcium is dependent on calcineurin and can be inhibited by treatment of cells with FK506, a calcineurin inhibitor [23]. Therefore, wild type cells grown without calcium were incubated with FK506 or 100% ethanol as a vehicle control. As shown in Fig. 5B lane 2, inhibiting calcineurin with FK506 reduced background levels of activated Cek1p in medium lacking calcium. Therefore, we inhibited calcineurin with FK506 in order to test the importance of calcium for Cek1p activation in response to A23187 treatment. Cells were grown in the absence or presence of calcium and treated with FK506 together with either A23187 or 100% ethanol (Fig. 5C). Under these conditions, cells grown without calcium and without A23187 had low levels of Cek1p activation (Fig. 5C, lane 1). Cells treated with calcium and A23187 in the presence of FK506 showed increased levels of Cek1p activation (Fig. 5C, lane 4). Importantly, cells grown in the absence of calcium and treated with A23187 and FK506 showed lower levels of Cek1p activation (Fig. 5C, lane 2). Therefore, under these conditions, A23187 did not stimulate high levels of Cek1p activation unless extracellular calcium was present. Some increase in activation of Cek1p was observed with the addition of calcium alone (Fig. 5C, lane 3). These results also showed that FK506 did not inhibit Cek1p activation in response to treatment with A23187 in the presence of calcium (Fig. 5B, lanes 5, 6). Thus, these data demonstrate that, in the presence of FK506, activation of Cek1p by A23187 treatment is dependent on calcium and not dependent on calcineurin.
albicans systemic infection
To determine whether Dfi1p-dependent signaling was important for C. albicans virulence, the murine model of disseminated candidiasis was used. Previous results demonstrated that deletion of DFI1 attenuates the virulence of C. albicans [12]. To test the importance of calmodulin-dependent signaling, we studied the virulence of the dfi1 point mutants. To test the effects of these mutations on C. albicans virulence, the wild type strain, the Ddfi1 null mutant, the complemented DFI1-TAP strain, and the three point mutants were inoculated intravenously into mice and survival was monitored. The wild type strain and the DFI1-TAP complemented strain caused lethal infections and all mice succumbed (Fig. 6). Consistent with previous results [12], the Ddfi1 null strain was attenuated in virulence (p = 0.0239, log rank test vs. the DFI1-TAP complemented strain; Fig. 6). Mutants that were altered in the calmodulin binding motif were indistinguishable from the DFI1-TAP strain, indicating that mutation of this region does not compromise virulence (Fig. 6). Therefore, calmodulin-dependent signaling is not required for lethal infection in this model.
Discussion
Calmodulin is a ubiquitous and well-characterized eukaryotic protein with many roles in mammals and fungi [13,14,16,24,25]. Previous work has shown that calcineurin, which is activated by calmodulin, plays a role in drug tolerance and regulating the cell wall, and there is cross-talk between the calcineurin and Mck1p MAPK pathways in mammals, S. cerevisiae, and S. pombe [26,27,28]. However, this work represents the first time calmodulin has been shown to bind to a plasma membrane protein in C. albicans. To the authors' knowledge, this is the first report that calcium calmodulin signaling leads to Cek1p activation independently of calcineurin.
We propose that when cells are grown in contact with an agar matrix, changes in the cell wall or plasma membrane are sensed by Dfi1p, which alters its conformation, binds to calmodulin and relays a signal that activates Cek1p. dfi1 mutants that are defective in interacting with calmodulin are defective in activating Cek1p to wild type levels in response to contact with an agar matrix.
Dfi1p may change conformation upon calmodulin binding. Other proteins such as the Epidermal Growth Factor Receptor (EGFR) and SNARE proteins are known to function in this way [25,30]. The mammalian v-SNARE VAMP2, yeast v-SNARE Nyv1p, and Dfi1p share similar 1-5-8-14 calmodulin binding motifs near their transmembrane domains [29]. In VAMP2, this region binds to calmodulin or to membrane lipids in a mutually exclusive manner that is important for membrane fusion and exocytosis [29]. Similarly, the membrane-juxtaposed region of Dfi1p may bind alternatively to calmodulin and another partner, such as another protein or lipids in the plasma membrane. Binding to calmodulin may allow Dfi1p to respond to an extracellular signal, generated by growth on an agar matrix, and relay the signal through the cell to phosphorylate the MAP kinase Cek1p.
Our results suggest that calmodulin binding to Dfi1p leads to Cek1p activation in the presence of A23187 and calcium. Disrupting the calmodulin binding motif affects Cek1p activation in the presence of A23187. In addition, mutations in the calmodulin binding motif of Dfi1p render the protein unable to support filamentous invasion. Mutation of the calmodulin binding motif of Dfi1p so that the net charge changed from +1 to +5 resulted in defective filamentous invasion. The +1 net charge of the Dfi1p calmodulin binding motif is lower than the charge of many calmodulin binding motifs and may facilitate quick release of calmodulin. Therefore, the defect in filamentous invasion and Cek1p activation of the dfi1-EERR-TAP mutant suggests that the interaction between Dfi1p and calmodulin is transient; Dfi1p must both bind to and release calmodulin in order to change conformation and signal to Cek1p to support filamentation. Interestingly, in liquid conditions when intracellular calcium is increased, the dfi1-EERR-TAP mutant protein supports Cek1p activation. This result suggests that the dfi1-EERR-TAP mutant protein is capable of signaling to Cek1p but does not respond normally during growth in contact with an agar surface. During growth in contact with agar, the number of activated Dfi1p molecules may be low and efficient binding and release of calmodulin may be needed. Alternatively, the dfi1-EERR-TAP mutation may affect the binding of other Dfi1p binding partners that affect the ability of the strain to filament during growth in agar.
In the mouse model of disseminated candidiasis, the calmodulin-binding mutants are virulent. Therefore, Dfi1p may be able to become activated via more than one mechanism in the animal. Interestingly, a different mutant, dfi1 G273,277L -TAP, that has been shown previously to be defective in invasive filamentation and Cek1p activation in response to contact with an agar matrix [12], is attenuated for virulence (T.R.D. and C.A.K., unpublished observations), arguing that some Dfi1p functions are important for pathogenicity. Thus, signaling pathways are more complex in the host than in laboratory growth and although calmodulin signaling is important for Dfi1p function in laboratory conditions, redundant mechanisms may allow Dfi1p to function without calmodulin binding during host infection.
Many pathways regulate filamentation in Candida albicans. Likewise, C. albicans virulence is controlled by numerous pathways. Redundancy in the mechanisms that promote virulence is a common theme in C. albicans biology and probably contributes to the success of the organism as a pathogen.
All PCR reactions used Hi-Fi polymerase (Invitrogen) or Taq polymerase (Phoenix Lab, Tufts Medical Center) and were confirmed by sequencing. All restriction enzymes and ligase were purchased from New England Biolabs.
In vitro calmodulin binding assay
Two-round PCR protocols (Qiagen) were used to generate DNA fragments for in vitro translation reactions. pGEX-GST-ctDFI1 constructs were amplified using primers PZ326 and either PZ352 (GST-STREP control) or PZ330 (GST-ctDFI1-STREP and all mutants). All primers contained linker sequences needed for the second round of PCR, which was performed following the manufacturer's recommendations and introduced a c-terminal STREP tag to the constructs (Qiagen EasyXpress Linear Template Kit). PCR reactions were gel purified using Qiaex II resin and 250 ng DNA used in each translation reaction (PURExpress In vitro Protein Synthesis Kit, New England Biolabs E6800S). Translation reactions were performed with 20 U of murine RNAse inhibitor (NEB M0314S) according to the manufacturer's instructions. Protein production was confirmed by Western blot with Strep-Tactin-HRP (IBA GmbH).
For the binding assay, calmodulin affinity resin (Stratagene 214303-52) was washed three times with 5 bed volumes wash buffer (PBS, 2 mM CaCl 2 , 0.05% Tween 20), centrifuging for 2 minutes at 500 xg between washes. Beads were then resuspended in wash buffer to make a 50% slurry. In vitro translated protein (10 mL) was mixed with 40 mL wash buffer, added to 80 mL of the 50% slurry and allowed to rotate at 4uC for 4 hours. The incubation was then transferred to Micro Bio-Spin Chromatography Columns (Bio-Rad 732-6204) and spun at 500 xg for 30 seconds to collect flow through. Resin was washed twice by adding 100 mL wash buffer to the column, letting the resin sit at room temperature for 1 minute, and spinning at 500 xg for 30 seconds. Protein was eluted by adding elution buffer (PBS, 0.05% Tween, 4 mM EGTA) to the column, incubating at room temperature for 1 minute and spinning at 500 xg for 30 seconds. Each fraction was boiled in protein loading buffer (60 mM tris pH 6.8, 2% SDS, 2% glycerol, 0.005% bromophenol blue, 300 mM b-mercaptoethanol, 10 mM dithiothreitol), and half of each fraction was loaded on an SDS-PAGE. An equivalent amount of in vitro translation reaction for the input was also loaded. After electrophoresis, the proteins were transferred onto 0.2 mm PVDF, blocked in PBS 0.1% Tween 3% BSA and probed with Strep-Tactin-HRP (IBA GmbH). The signal was produced using Pierce ECL Western Blotting Substrate (32209) and detected on Kodak X-OMAT Blue XB film. Experiments were performed at least 3 times per construct, and a representative experiment is shown. Quantification was performed using a Gel Logic 100 Imaging System with the program Kodak 1D, version 3.6.
Invasion of agar medium
C. albicans strains were grown to early exponential phase and mixed with molten agar (YPS 1% agar) as described previously [12]. Plates were incubated for 4 days at 25uC, at which point 100% of colonies from WT strains were filamentous, and colonies visualized at 46 magnification. Colonies were scored as filamentous if 20 or more filaments protruded from the colony. Three independent isolates of each strain were tested in triplicate; representative colonies are shown.
Growth in the presence of cell wall targeting agents
Candida albicans strains grown at 30uC in YPD were diluted and allowed to grow to OD600 = approximately 1.5. Cultures were serially diluted and 5 mL of each dilution spotted on YPD with or without caspofungin (90 ng/mL) or Congo red (200 mg/mL). Plates were incubated at 30uC for 72 hours. Three independent isolates of each strain were tested in triplicate.
Protein extraction with detergent C. albicans cells were grown in YPD overnight at 30uC, washed with PBS and resuspended in lysis buffer (50 mM Tris pH 7.5, 100 mM NaCl, 0.5 mM EDGA) with or without 1% Triton-X100 and 0.5% Na deoxycholate with 0.5 mm zirconia silica beads. Cells were broken on a Turbomix vortex attachment (Fisher) with 6 cycles of 30 seconds on the vortex and 1 minute on ice. Protein concentration was determined using a Pierce micro BCA protein concentration kit (Pierce 23235) and 80 mg (Dfi1-HA) or 20 mg (actin) was run on a 4-15% SDS-PAGE gel (Bio-rad), transferred onto 0.2 mm PVDF and Western blotted with mouse anti-HA (Covance 16B12, 1:1000 overnight incubated at 4uC) or rabbit anti-actin (Sigma A5060, 1:10000 overnight incubated at 4uC). Goat-anti-mouse-HRP (Bio-rad 170-6516) or Goat-anti-rabbit-HRP (Invitrogen 656120) was used as a secondary antibody and the signal was produced using Pierce ECL Western Blotting Substrate (32209) and detected on Kodak X-OMAT Blue XB film. Experiments were performed 3 times, and a representative experiment is shown. Quantification was performed using a Gel Logic 100 Imaging System with the program Kodak 1D, version 3.6.
GFP localization
Exponentially growing C. albicans strains were washed with PBS, mounted on glass slides and visualized with Openlab (Improvision, version 5.5.1) on a Zeiss Axiovert 200 M microscope with a 40x lens and standard FITC fluorescent filter cube (Chroma Technology Corp.). Pictures were taken with a camera (C4742-95-12ERG; Hamamatsu Photonics) controlled by Openlab version 5.5.1 (PerkinElmer).
Cek1p activation in response to contact with agar medium Cells were grown and protein extracted as previously described [12]. Briefly, exponentially growing Candida albicans cells were plated for single colonies on YPS plates with 1% agar and incubated at 25uC for 4 days. Colonies were washed off the plates with cold PBS and collected over ice. Total protein was extracted in RIPA buffer supplemented with phosphatase and protease inhibitors (50 mM tris pH 8, 150 mM NaCl, 0.1% SDS, 1% NP40, 0.5% Na deoxycholate, 20 mM NaF, 10 mM Na orthovanadate, 50 mM b-glycerol phosphate, 50 mM Na pyrophosphate, 2 mM PMSF, 10 mL/mL fungal specific protease inhbitor (Sigma P8215), 1 Complete tablet/10 mL (Roche 04693116001)) using 0.5 mm zirconia silica beads on a Turbomix vortex attachment (Fisher) with 6 cycles of 30 seconds on the vortex and 1 minute on ice. Protein concentration was determined using a Pierce micro BCA protein concentration kit (Pierce 23235) and 120 mg (Cek1p) or 20 mg (actin) total protein loaded on an 8.5% (Cek1p) or 10% (actin) SDS-PAGE and transferred onto 0.2 mm PVDF. Blots were blocked with 5% milk in TBS 0.05% tween and probed with anti-p42/44 (Cek1p-Pi 2 , Cell Signaling 4370, 1:1000, overnight incubated at 4uC) or anti-actin (Sigma A5060). HRP-conjugated goat anti-rabbit (Invitrogen 656120) was used as a secondary antibody. Amersham ECL Plus Western Blotting Detection System (GE Healthcare RPN2132) was used to produce the signal, which was detected on a Syngene G:Box Chemi-XT4 GENESys imager. Blots were quantified using GeneTools (SynGene, version 4.02) using a standard curve run on each gel. This experiment was replicated 3 times and a representative blot is shown. Signals obtained with WT or dfi1 mutant strains were compared using a paired t-test (Graphpad).
Treatment with calcium ionophore A23187 C. albicans strains were grown for 8 hours at 30uC in complete minimal media without uridine (CM-U, [30]). For some experiments, CM-U was made with yeast nitrogen base lacking divalent cations and potassium phosphate (Sunrise Science Products 1540-250) and supplemented with 1 g/L potassium phosphate and 100 mM MgSO 4 . Cultures were then diluted 1:1000 into 80 mL of the same fresh media and grown overnight. When the cultures reached approximately OD600 = 1, they were treated with 4 mM A23187 or an equivalent volume of 100% ethanol as a vehicle control for 30 minutes. Cultures were treated with 2 mg/mL FK506 or an equivalent volume of ethanol as a vehicle control and 10 mM CaCl 2 or an equivalent volume of water as a vehicle control where indicated. Cells were collected over ice, washed with cold PBS and total protein extracted as described above. Equal amounts of protein (60 mg for Cek1p-Pi 2 or 20 mg for actin) were loaded on an SDS-PAGE gel and Western blotted as described above. Experiments were performed 3 times per strain and condition; representative blots are shown.
Mouse model of disseminated candidiasisis
C. albicans cells (WT, pcz24; DFI1-TAP, trd7; Ddfi1 null (pcz25); dfi1-RKAA-TAP trd9; dfi1-EERR-TAP, trd10; dfi1-WWQQ-TAP, trd8) were grown at 30uC in CM-U for 24 hours, then washed 3 times in PBS. Cells were then resuspended in PBS at 3610 6 cells per mL and 3610 5 cells injected into the tail vein of 10 mice per strain. Survival time (days) was recorded. Mice were euthanized when moribund. The protocol was approved by the Tufts University School of Medicine Institutional Animal Care and Use Committee (Animal Welfare Assurance Number A-3775-01). Statistics were performed using a log-rank test from a Kaplan-Meier plot by Robin Ruthazer at the Tufts Medical Center Biostatistics Research Center. | 6,682.2 | 2013-10-14T00:00:00.000 | [
"Biology",
"Medicine"
] |
Effect of TiO2 rutile nanorods on the photoelectrodes of dye-sensitized solar cells
In order to enhance the electron transport on the photoelectrodes of dye-sensitized solar cells, one-dimensional rutile nanorods were prepared using electrospun TiO2 nanofibers. The grain size of the nanorods increased with increasing temperature. Electrochemical impedance spectroscopy measurements revealed reduced interface resistance of the cells with the one-dimensional rutile nanorods due to the improved electron transport and the enhanced electrolyte penetration. Intensity-modulated photocurrent/photovoltage spectroscopy showed that the one-dimensional rutile nanorods provided the electrons with a moving pathway and suppressed the recombination of photogenerated electrons. However, an excessive quantity of rutile nanorods created an obstacle to the electrons moving in the TiO2 thin film. The photoelectrode with 7 wt.% rutile nanorods optimized the performance of the dye-sensitized solar cells.
Background
One-dimensional (1-D) structured TiO 2 nanorods show improved electrical and optical properties in the photoelectrodes of dye-sensitized solar cells (DSSCs) [1]. They can provide straight moving paths for electrons and reduce the e − /h + recombination [2][3][4]. Further, they scatter sunlight so that the incident light stays longer in the cell [5]. As these properties enhance the solar energy conversion efficiency, much research into the effects of the 1-D structured TiO 2 on the photoelectrode have been conducted [6][7][8].
In principle, photoexcited electrons from dye molecules move on a TiO 2 nanocrystal undergoing a series of trapping and de-trapping events during diffusion. The 1-D nanorods, which are densely packed TiO 2 nanoparticles, could act as a single crystal and be involved in rapid electron transport, thereby reducing the chances for electron recombination. Furthermore, the TiO 2 film with random packing of 1-D rods helps the electrolyte to penetrate into the photoelectrode because of the porosity [9,10]. The enhanced interpenetration of electrolyte leads to the dye regeneration by redox process of the electrolyte and enhances the energy conversion efficiency with improved photocurrent.
Few grain boundaries in the TiO 2 nanorods induce fast electron transport and decrease the electron recombination due to the reduced number of trapping sites in the interfaces [11]. In order to reduce grain boundaries in the nanorods, the crystal size should be increased. TiO 2 crystal structure (anatase and rutile) and size can be controlled by sintering temperature. The anatase phase has been reported to be developed at temperatures below 800°C, and above the temperatures, it transforms to the more stable rutile phase [12]. Also, the TiO 2 nanorods sintered at a high temperature have high crystallinity, meaning reduced grain boundaries and decreased trap sites. Electrons moving through the rutile structure undergo less stress because of the reduced number of trap sites on the grain boundaries [13,14]. In addition, the transported electrons can easily migrate from the rutile to anatase phase [15,16]. As the conduction band of the pure anatase phase is typically 0.2 eV more negative than that of the rutile phase, photoexcited electrons injected into the rutile phase migrate to the conduction band of the anatase phase, before passing through the external circuit. The resulting synergistic effects between the anatase and rutile phases lead to energetic electron flows and enhanced photocurrents [17][18][19].
However, even though the rutile 1-D nanorods provide the electrons with a better moving path and improve electrolyte penetration, a large number of rutile phases simultaneously can become a barrier for electron transport [8]. The increased amount of rutile phase increases the probability of the moving electrons facing a higher energy level, which increases the internal resistance.
In this study, in order to make photoelectrodes with the 1-D rutile nanorods, the electrospun TiO 2 nanofibers were sintered at various temperatures. The photoelectrodes considerably improved the DSSC energy conversion efficiency, depending on the amount of TiO 2 nanorods. The intensity-modulated photocurrent spectroscopy, intensity-modulated photovoltage spectroscopy, charge-transfer resistance, and I-V characteristics of the DSSCs were investigated in order to study the effects of the rutile TiO 2 nanorods on the cell performance. The purpose of this study is to investigate the effects of the crystal size and amount of the rutile TiO 2 nanorods on the electron transport in the photoelectrodes of dye-sensitized solar cells.
Preparation of electrospun nanorods
Three grams of polyvinylpyrrolidone (PVP K90, M W = 130,000) was dissolved in 27 g of ethanol (Daejung Chemical & Metal Co., Ltd., Shiheung, South Korea), while the TiO 2 precursor was prepared by adding 12 ml of acetic acid (Kanto Chemical Co., In., Tokyo, Japan) and 12 ml of ethanol into 6 ml of titanium(IV) isopropoxide (Junsei Chemical Co., Ltd., Tokyo, Japan), successively. The solutions were mixed and stirred for 12 h to obtain homogeneity. The solution was loaded into a syringe (SGE Analytical Science, Ringwood, Victoria, Australia) under an applied voltage of 9 kV. TiO 2 nanofibers were electrospun on Al foil. The spinning rate was controlled by a syringe pump (KDS-100, KD Scientific, Holliston, MA, USA) at 2 ml/h. The tip-to-collector distance was maintained at 20 cm. The obtained TiO 2 nanofibers were calcined at 450°C, 650°C, 750°C, 850°C, and 1,000°C. Transmission electron microscopy (TEM) was used to examine the TiO 2 nanorods, and the crystal structures were characterized by X-ray diffraction (XRD).
Fabrication of DSSCs with the TiO 2 nanorods
The ground nanorods, sintered at 450°C, 650°C, 750°C, 850°C, and 1,000°C, were mixed into a homemade TiO 2 (P25, Degussa-Hüls, Frankfurt/Main, Germany) paste at a loading of 3 wt.% as a preliminary experiment in order to choose the best nanorod. The ground nanorods sintered at 850°C were chosen and mixed into a commercial TiO 2 anatase paste (Dyesol, Queanbeyan, New South Wales in Australia) at ratios of 0, 3, 5, 7, 10, and 15 wt.%. The TiO 2 paste with the electrospun nanorods was cast on pre-cleaned fluorine-doped tin dioxide (FTO; Pilkington TEC glass, 8 Ω cm −2 , Pilkington Group Limited, St Helens, UK) using a squeeze printing method. The TiO 2 films were sintered at 450°C for 30 min. The thickness of the TiO 2 films was about 10 μm, and the active area of the TiO 2 electrode was 0.25 cm 2 . The obtained TiO 2 film was immersed in 0.5 mmol ethanol solution of N719 dye (Solaronix, Aubonne, Switzerland) for 24 h to adsorb the dye molecules. A Pt counter electrode was fabricated by squeeze printing of the Pt-Sol (Solaronix) on an FTO substrate. The sandwich-type solar cell was assembled by placing a Pt counter electrode on the dye-sensitized TiO 2 electrode. The redox electrolyte (Dyesol) was injected between the electrodes.
Results and discussion
TEM images and XRD data of the TiO 2 nanorods sintered at various temperatures are shown in Figure 1.
The phase transition of the TiO 2 was observed depending on the sintering temperatures. With increasing sintering temperature, the amorphous TiO 2 underwent phase transition to anatase and rutile structures. The crystallinity increased and the crystal size in the nanorods grew with increasing temperature. Comparison with the XRD peaks of P25, which contains both anatase and rutile phases, confirmed that the sintered nanorods at 750°C, 850°C, and 1,000°C had rutile peaks. During the high-temperature thermal treatment, the average crystal size increased, reducing the grain boundaries and crystal defects. The decreased number of trap sites on the nanorods reduced the number of obstacles on the fast electron moving paths. These effects influenced the charge trap conditions and consequently increased the electron diffusion speed [20]. Among the nanorods sintered at various temperatures, those sintered at 850°C had the highest energy conversion efficiency in DSSCs. The photoelectrodes using a homemade paste with P25 TiO 2 and 3 wt.% nanorod sintered at 450°C, 650°C, 750°C, 850°C, and 1,000°C exhibited efficiencies of 3.32%, 3.12%, 3.16%, 3.47%, and 3.41%, respectively. The internal resistance was investigated by EIS. The impedance spectra of the cells prepared using various amounts of nanorods sintered at 850°C are presented in Figure 2. The semicircles are related to the electron transfer resistance and the tendency of recombination at the TiO 2 /electrolyte interface [21]. The arc decreased with increasing amount of nanorods until 7 wt.% and then increased. The 1-D nanorods improved the charge transport and decreased electron recombination by providing fast moving paths for electrons. Although 1-D nanostructured nanorods have been proven to deliver a higher short-circuit photocurrent density (J sc ) than TiO 2 nanoparticles, too many large rutile nanorods could become a barrier for the electrons due to the higher energy level of the rutile phase. Figures 3 and 4 show the electron diffusion coefficients (D n ) and lifetimes (τ r ) of the rutile TiO 2 nanorods as a function of J sc . The D n and τ r values were determined by the photocurrent and photovoltage transients induced by a stepwise change in the laser light intensity controlled with a function generator. The trends of diffusion coefficients by TiO 2 structures are known to be reasonably consistent with the resistances in the TiO 2 film determined by EIS [22,23]. In Figure 3, all the DSSCs with 1-D rutile nanorods have a higher J sc than the 0 wt.% TiO 2 electrode. Table 1 shows that the diffusion coefficients of the electrode with the 1-D rutile nanorods are higher than those of the electrode without the nanorods. However, the value of the diffusion coefficient at the electrode with 15 wt.% nanorods decreased due to the higher energy level of the rutile phase in the nanorods. In Figure 4, the J sc of the electrode with the 1-D nanorods is also increased. The lifetime of the electrodes with rutile nanorods is relatively similar to the 0 wt. % electrode at 3, 5, and 15 wt.% and higher at 7 and 10 wt.%. The 1-D nanorods with the increased τ r values can provide an electron pathway. The improved diffusion coefficient and the provided electron pathway result in a synergistic effect that increases the J sc . Table 2 shows the performances of the DSSCs with the 1-D structured rutile nanorods. The J sc value increased with increasing amount of nanorods until 10 wt.% and then decreased at 15 wt.%. The conversion efficiency of the cells using the rutile-phase nanorods was improved depending on the amount of nanorods. In the cells with nanorods, more electrons could move along the 1-D rutile nanorods due to the enhanced electron diffusion and the reduced electron recombination. Furthermore, the conversion efficiency was improved due to the enhanced electrolyte penetration. The electrolyte could easily penetrate into the photoelectrode due to the random packing of 1-D nanorods because of the porosity. The enhanced interpenetration of the electrolyte led to dye regeneration by redox process of the electrolyte and thus enhanced the energy conversion efficiency with improved photocurrent. As a result, the increased J sc affected the enhancement of the energy conversion efficiency. However, the efficiency of the cell with 15 wt.% nanorods was decreased because the random distribution of a large number of rutile nanorods created a barrier to the electron transport due to the higher energy level of the rutile phase. An excessive amount of 1-D TiO 2 nanorods can limit the DSSC performance.
Conclusions
1-D rutile nanorods can provide a fast moving pathway for electrons and decrease electron recombination. In this study, the nanorods with high crystallinity showed enhanced energy conversion efficiency with reduced TiO 2 /electrolyte interface resistance. However, an excessive amount of randomly distributed rutile nanorods could create an obstacle to the moving electrons and reduce the internal surface area, even though they provided the electron moving paths. The charge-transfer resistance was decreased with increasing rutile nanorod loading up to 7 wt.%, but the electrical resistance was increased as the loading exceeded 10 wt.%. A 7 wt.% loading of 1-D rutile nanorods was considered the best condition for optimizing the performance of the DSSCs. The energy conversion efficiency of the optimized cell was 6.16%. | 2,744 | 2013-01-19T00:00:00.000 | [
"Engineering",
"Materials Science",
"Physics"
] |
Fiber Bragg Grating Sensor Networks Enhance the In Situ Real-Time Monitoring Capabilities of MLI Thermal Blankets for Space Applications
The utilization of Fiber Bragg Grating (FBG) sensors in innovative optical sensor networks has displayed remarkable potential in providing precise and dependable thermal measurements in hostile environments on Earth. Multi-Layer Insulation (MLI) blankets serve as critical components of spacecraft and are employed to regulate the temperature of sensitive components by reflecting or absorbing thermal radiation. To enable accurate and continuous monitoring of temperature along the length of the insulative barrier without compromising its flexibility and low weight, FBG sensors can be embedded within the thermal blanket, thereby enabling distributed temperature sensing. This capability can aid in optimizing the thermal regulation of the spacecraft and ensuring the reliable and safe operation of vital components. Furthermore, FBG sensors offer sev eral advantages over traditional temperature sensors, including high sensitivity, immunity to electromagnetic interference, and the ability to operate in harsh environments. These properties make FBG sensors an excellent option for thermal blankets in space applications, where precise temperature regulation is crucial for mission success. Nevertheless, the calibration of temperature sensors in vacuum conditions poses a significant challenge due to the lack of an appropriate calibration reference. Therefore, this paper aimed to investigate innovative solutions for calibrating temperature sensors in vacuum conditions. The proposed solutions have the potential to enhance the accuracy and reliability of temperature measurements in space applications, which can enable engineers to develop more resilient and dependable spacecraft systems.
Introduction
In space system engineering, the thermal load is one of the fundamental aspects to be taken into account during the design and testing phase [1]. The operating temperature can vary from a few Kelvin to several hundred Kelvin according to the exposure to solar radiation. It is then mandatory to have an efficient thermal control system that deactivates components when the temperature reaches high peaks and activate cooling or warming systems if they are present onboard. For this reason, sensors that can guarantee high performances even working in harsh conditions (i.e., high temperature, electromagnetic radiation, etc.) comprise an important strategy in space applications [2][3][4][5].
Optical fiber refers to a cylindrical glass material that is capable of transmitting light through its core. Its utilization has proliferated at a significant pace, finding widespread applications across several industrial domains such as telecommunications, medical diagnostics, lighting, and the Internet, among others. As a result of its versatile functionality and wide-scale applicability, optical fiber has emerged as a pivotal technology that is extensively deployed in daily life and has permeated the global economic landscape.
Due to the extensive capabilities presented by optical fiber, Fiber Bragg Gratings (FBGs) are well-suited for the measurement of a wide range of technical characteristics in both static and dynamic modes. These sensors hold potential to replace numerous conventional sensors in aerospace applications [6][7][8], including structural monitoring, temperature regulation, and compensation. FBG sensors have already been integrated into various space systems, primarily for temperature measurement, vibration analysis, and vacuum testing for the thermal characterization of specific components. For instance, in a recent space application, FBGs were utilized to regulate the temperature of a propulsion tank owing to the fiber's resistance to electromagnetic radiation and electrical inactivity. Furthermore, the European Space Agency's (ESA) mission, Probe-2, employed FBG sensors for in-orbit thermal testing, while other studies have employed optical technology to detect the temperature of specific space systems [9,10].
The integration of Fiber Bragg Grating (FBG) sensors into Multi-Layer Insulation (MLI) blankets for space use offers numerous advantages in terms of monitoring and controlling the environmental conditions of spacecraft [6][7][8][9][10]. The use of FBG sensors in MLI blankets [11][12][13][14][15] enables the measurement of key parameters such as pressure, integrity, and temperature, which are critical for ensuring the proper functioning of spacecraft systems [16][17][18].
Structural health monitoring is another important application of FBG sensors in MLI blankets. By monitoring the strain and deformation of the spacecraft's cover, FBG sensors can detect and diagnose potential failures or impacts, allowing for timely intervention and repair [19]. This can help to improve the overall reliability and safety of spacecraft, especially in the harsh and unpredictable space environment [15,20]. FBG sensors can provide pointwise temperature evaluation in MLI blankets. This is crucial for optimizing the thermal management of spacecraft systems, as temperature fluctuations can affect the performance and longevity of various components. By monitoring temperature variations at specific points in the MLI blanket, FBG sensors can enable precise control (closed-loop), deactivating the heating system or activating the radiation mechanism of the spacecraft's thermal environment.
Finally, FBG sensors in MLI blankets can also serve as structural health sensors against hypervelocity impacts [21,22]. The harsh environment of space is fraught with hazards such as micrometeoroids and space debris, which can cause serious damage to spacecraft. FBG sensors can detect and analyze the impact of such objects, providing critical information for designing more robust and resilient spacecraft structures. The integration of FBG sensors into MLI blankets (as reported in Figure 1) offers numerous advantages for space use, including pressure and temperature monitoring, structural health monitoring, pointwise temperature monitoring, and structural health sensing against hypervelocity impacts. These benefits can help to enhance the safety, reliability, and performance of spacecraft, making them more effective in achieving their scientific and exploratory missions. The presented application of modern in situ monitoring techniques embedded into structures could provide future benefits also in Earth infrastructure monitoring [23][24][25][26].
Materials and Methods
Optical fiber is composed of multiple concentric layers: the core, cladding, and coat ing [27]. The core is the innermost layer and enables the transmission of light signals con
Materials and Methods
Optical fiber is composed of multiple concentric layers: the core, cladding, and coating [27]. The core is the innermost layer and enables the transmission of light signals containing vital information. Typically manufactured from glass or polymeric materials, the core has a thickness not exceeding 50 µm. The intermediate layer, the cladding, is crucial to ensuring proper fiber operation and has a diameter of 125 µm. The coating is the outermost layer, which serves to safeguard the structure from potential damage resulting from the fiber's low bending resistance. To enhance the mechanical strength, multiple additional outer layers may be incorporated due to the fiber's high brittleness. An artistic scheme of the optical's fibres is reported on Figure 2.
Materials and Methods
Optical fiber is composed of multiple concentric layers: the core, ing [27]. The core is the innermost layer and enables the transmission taining vital information. Typically manufactured from glass or poly core has a thickness not exceeding 50 µm. The intermediate layer, the to ensuring proper fiber operation and has a diameter of 125 µm. The most layer, which serves to safeguard the structure from potential dam the fiber's low bending resistance. To enhance the mechanical stren tional outer layers may be incorporated due to the fiber's high bri scheme of the optical's fibres is reported on Figure 2. The sensors employed in this work were Fiber Bragg Gratings created in the fiber itself by employing a laser method to create a per the core's refractive index. At the conclusion of this process, with a fi there were some core bands with a new refractive index, resulting in of the parties with the changed refractive index was separated by a c noted by the grating period ΛG. This mechanism allowed the sensor when light passes through it, the FBG reflects a certain wavelength, k frequency, according to: where is the wavelength reflected by the FBG, is the refracti (after the remodulation), and is the pitch of the grating, as show Bragg frequency represents the output of the FBG sensor. The depen frequency on the grating pitch, which is a physical distance, is shown that the fluctuation in the reflected wavelength is always related to generated on the grating period by an external component. The sensors employed in this work were Fiber Bragg Gratings (FBGs). They were created in the fiber itself by employing a laser method to create a periodic modulation in the core's refractive index. At the conclusion of this process, with a fiber of about 1 cm, there were some core bands with a new refractive index, resulting in n f = n i + ∆n. Each of the parties with the changed refractive index was separated by a certain distance, denoted by the grating period Λ G . This mechanism allowed the sensor to work as a filter: when light passes through it, the FBG reflects a certain wavelength, known as the Bragg frequency, according to: where λ B is the wavelength reflected by the FBG, n EFF is the refractive index of the fiber (after the remodulation), and Λ G is the pitch of the grating, as shown in Figure 3. The Bragg frequency represents the output of the FBG sensor. The dependency of the Bragg frequency on the grating pitch, which is a physical distance, is shown in (1): this indicates that the fluctuation in the reflected wavelength is always related to a mechanical strain generated on the grating period by an external component. As a result, it is simple to understand that loads applied to the sensor (in terms of induced strain) or thermal excursion create a significant variation in the reflected wavelength of the FBG, and so, (1) might be expressed as follows: In this way, the reflected wavelength is directly proportional to the strain and temperature variation applied to the sensor: the above-mentioned relation is then crucial in the process of sensor calibration conducted in the current study.
For the experimental test campaign, the subsequent hardware material was used: a data acquisition system composed of optical fibers and FBGs, a laser FBG interrogator, electronic temperature sensors (SHT85 or thermocouples), structural supports, and a thermo-vacuum chamber.
The FBG interrogator is a component that can automatically identify and interrogate FBGs present in fibers connected to various channels, while simultaneously collecting and analyzing their responses. The interrogator communicates independently with each sensor, reducing the likelihood of data misinterpretations arising from multiple FBGs. It transmits a laser beam through the fiber and detects the reflected wavelengths. For this application, a SmartScan SBI laser interrogator developed by the Smart Fibres company (Bracknell RG12 9BG, United Kingdom) was utilized, and is visually reported on Figure 4. The system executes a data acquisition loop once every minute, with each loop lasting one second and sampling at a variable frequency between 2.5 and 25 kHz. The average of all the data obtained for a particular measurement on a given fiber Bragg grating is computed to produce the associated instantaneous wavelength value. The data are transmitted to the PC through a LAN connection. A schematic picture of the acquisition system is reported on Figure 5. As a result, it is simple to understand that loads applied to the sensor (in terms of induced strain) or thermal excursion create a significant variation in the reflected wavelength of the FBG, and so, (1) might be expressed as follows: In this way, the reflected wavelength is directly proportional to the strain and temperature variation applied to the sensor: the above-mentioned relation is then crucial in the process of sensor calibration conducted in the current study.
For the experimental test campaign, the subsequent hardware material was used: a data acquisition system composed of optical fibers and FBGs, a laser FBG interrogator, electronic temperature sensors (SHT85 or thermocouples), structural supports, and a thermo-vacuum chamber.
The FBG interrogator is a component that can automatically identify and interrogate FBGs present in fibers connected to various channels, while simultaneously collecting and analyzing their responses. The interrogator communicates independently with each sensor, reducing the likelihood of data misinterpretations arising from multiple FBGs. It transmits a laser beam through the fiber and detects the reflected wavelengths. For this application, a SmartScan SBI laser interrogator developed by the Smart Fibres company (Bracknell RG12 9BG, UK) was utilized, and is visually reported on Figure 4. The system executes a data acquisition loop once every minute, with each loop lasting one second and sampling at a variable frequency between 2.5 and 25 kHz. The average of all the data obtained for a particular measurement on a given fiber Bragg grating is computed to produce the associated instantaneous wavelength value. The data are transmitted to the PC through a LAN connection. A schematic picture of the acquisition system is reported on Figure 5. As a result, it is simple to understand that loads applied to the sensor (in induced strain) or thermal excursion create a significant variation in the reflecte length of the FBG, and so, (1) might be expressed as follows: In this way, the reflected wavelength is directly proportional to the strain a perature variation applied to the sensor: the above-mentioned relation is then c the process of sensor calibration conducted in the current study.
For the experimental test campaign, the subsequent hardware material was data acquisition system composed of optical fibers and FBGs, a laser FBG inter electronic temperature sensors (SHT85 or thermocouples), structural support thermo-vacuum chamber.
The FBG interrogator is a component that can automatically identify and int FBGs present in fibers connected to various channels, while simultaneously collec analyzing their responses. The interrogator communicates independently with e sor, reducing the likelihood of data misinterpretations arising from multiple transmits a laser beam through the fiber and detects the reflected wavelengths. application, a SmartScan SBI laser interrogator developed by the Smart Fibres c (Bracknell RG12 9BG, United Kingdom) was utilized, and is visually reported o 4. The system executes a data acquisition loop once every minute, with each loo one second and sampling at a variable frequency between 2.5 and 25 kHz. The av all the data obtained for a particular measurement on a given fiber Bragg grating puted to produce the associated instantaneous wavelength value. The data are tran to the PC through a LAN connection. A schematic picture of the acquisition s reported on Figure 5. In the evaluation of the FBGs' performance, thermocouples were employed in the thermo-vacuum chambers. Thermocouples are temperature transducers that operate based on the Seebeck effect. The thermo-vacuum chamber is utilized to recreate the environmental conditions present in space. A picture of the chamber used in the experiments is reported on Figure 6. By concurrently controlling the pressure and temperature within a well-defined volume of space, the only modes of heat transfer are conduction and radiation, just as in space. The chamber can depressurize the test environment to values as low as 1 × 10 −8 mbar, while operating within temperature ranges of −190 °C to +160 °C, and the minimum temperature value is dictated by the use of nitrogen. These temperature and pressure ranges may be altered based on the thermal and pumping capabilities of the vacuum chamber. For instance, the temperature ranges can be expanded using heating lamps (IR or solar simulation) and/or cryo-coolers, which utilize helium thermodynamics, enabling temperatures similar to deep space to be reached theoretically. For the test campaign, four fibers with polyimide coating were selected. The polyimide coating was selected as the only material, which is easily available on the market, able to satisfy the thermal and outgassing requirements necessary to carry out the tests in the thermo-vacuum chamber. The fibers were affixed to the metal surface exclusively using a simple adhesive film, requiring no further preparation before testing. A positioning detail picture and an experimental setup in thermos-vacuum chamber are reported on Figure 7. In the evaluation of the FBGs' performance, thermocouples were employed in the thermo-vacuum chambers. Thermocouples are temperature transducers that operate based on the Seebeck effect. The thermo-vacuum chamber is utilized to recreate the environmental conditions present in space. A picture of the chamber used in the experiments is reported on Figure 6. By concurrently controlling the pressure and temperature within a welldefined volume of space, the only modes of heat transfer are conduction and radiation, just as in space. The chamber can depressurize the test environment to values as low as 1 × 10 −8 mbar, while operating within temperature ranges of −190 • C to +160 • C, and the minimum temperature value is dictated by the use of nitrogen. These temperature and pressure ranges may be altered based on the thermal and pumping capabilities of the vacuum chamber. For instance, the temperature ranges can be expanded using heating lamps (IR or solar simulation) and/or cryo-coolers, which utilize helium thermodynamics, enabling temperatures similar to deep space to be reached theoretically. In the evaluation of the FBGs' performance, thermocouples were employed in the thermo-vacuum chambers. Thermocouples are temperature transducers that operate based on the Seebeck effect. The thermo-vacuum chamber is utilized to recreate the environmental conditions present in space. A picture of the chamber used in the experiments is reported on Figure 6. By concurrently controlling the pressure and temperature within a well-defined volume of space, the only modes of heat transfer are conduction and radiation, just as in space. The chamber can depressurize the test environment to values as low as 1 × 10 −8 mbar, while operating within temperature ranges of −190 °C to +160 °C, and the minimum temperature value is dictated by the use of nitrogen. These temperature and pressure ranges may be altered based on the thermal and pumping capabilities of the vacuum chamber. For instance, the temperature ranges can be expanded using heating lamps (IR or solar simulation) and/or cryo-coolers, which utilize helium thermodynamics, enabling temperatures similar to deep space to be reached theoretically. For the test campaign, four fibers with polyimide coating were selected. The polyimide coating was selected as the only material, which is easily available on the market, able to satisfy the thermal and outgassing requirements necessary to carry out the tests in the thermo-vacuum chamber. The fibers were affixed to the metal surface exclusively using a simple adhesive film, requiring no further preparation before testing. A positioning detail picture and an experimental setup in thermos-vacuum chamber are reported on Figure 7. For the test campaign, four fibers with polyimide coating were selected. The polyimide coating was selected as the only material, which is easily available on the market, able to satisfy the thermal and outgassing requirements necessary to carry out the tests in the thermo-vacuum chamber. The fibers were affixed to the metal surface exclusively using a simple adhesive film, requiring no further preparation before testing. A positioning detail picture and an experimental setup in thermos-vacuum chamber are reported on Figure 7. vacuum chamber for measurements across a broad temperature range of approximately −150 °C to 200 °C, based on the outcomes of the laboratory tests conducted in the climate chamber. The sensors were mounted on a Kapton [30] thermal blanket, which is typically employed in space applications, such as thermal blankets for thermal control systems. Specifically, no tension was exerted on the fibers, and no adhesive was placed near the sensors, reproducing the free fiber conditions observed in the initial climate chamber test. Several preliminary measurement cycles were conducted in a climate chamber to determine the optimal data acquisition technique, in order to minimize unwanted effects and errors.
The evaluation of the FBG's performance encompassed multiple stages, comprising: • Acquiring raw data.
•
Converting the FBG output into temperature values. • Determining the error.
Initially, raw data were collected by plotting the information stored in the .log files generated by the interrogator using MATLAB©. Subsequently, the sensor's characteristic λ(T) relation was established from the raw data, elucidating the relationship between increasing temperature and sensor output, independent of the chronological time history of the setup temperature.
The λ(T) relation is explained in terms of: where K T and λ 0 are the angular coefficients and the known term of the linear fit calculated from the experimental data. Moreover, considering that sensors have different nominal Bragg wavelengths, the relation could be normalized as follows: From this calibration, it was possible to convert the FBG reflected wavelength into a temperature value using the equation: To generalize the relation, the temperature could be calculated from the normalized relation as follow: After the preliminary analysis, the FBG sensor network was placed in the thermovacuum chamber for measurements across a broad temperature range of approximately −150 • C to 200 • C, based on the outcomes of the laboratory tests conducted in the climate chamber. The sensors were mounted on a Kapton [30] thermal blanket, which is typically employed in space applications, such as thermal blankets for thermal control systems.
Specifically, no tension was exerted on the fibers, and no adhesive was placed near the sensors, reproducing the free fiber conditions observed in the initial climate chamber test.
The same aforementioned procedures were followed during this test, encompassing: • Collecting raw data.
•
Converting the FBG output into temperature values. • Determining the error.
The equations employed to convert the raw data into temperature values were identical to those described previously in this section. Since the objective was to utilize FBGs for dependable monitoring of space components, the thermal cycles carried out here were more intricate. Specifically, the experiment comprised distinct steps of approximately 15 min at a stable temperature, followed by a transitional phase to attain a new stable step. The test campaign was divided into three sections: During the first two experiment sessions, each FBG was paired with a thermocouple, and the calibration coefficients were determined. In the final session, the thermal cycle from the second session was repeated to verify the accuracy of the FBG response. As specified before, optical fibers with a polyimide coating were utilized to withstand the high thermal excursion. A simplifying flow chart of the overall activity described is disclosed on Figure 8. The same aforementioned procedures were followed during this test, encompassing: • Collecting raw data.
•
Converting the FBG output into temperature values. • Determining the error.
The equations employed to convert the raw data into temperature values were identical to those described previously in this section. Since the objective was to utilize FBGs for dependable monitoring of space components, the thermal cycles carried out here were more intricate. Specifically, the experiment comprised distinct steps of approximately 15 min at a stable temperature, followed by a transitional phase to attain a new stable step. The test campaign was divided into three sections: During the first two experiment sessions, each FBG was paired with a thermocouple, and the calibration coefficients were determined. In the final session, the thermal cycle from the second session was repeated to verify the accuracy of the FBG response. As specified before, optical fibers with a polyimide coating were utilized to withstand the high thermal excursion. A simplifying flow chart of the overall activity described is disclosed on Figure 8.
Results
The findings derived from the test campaigns are expounded hereafter, based on the two distinct thermal cycles and a repeatability analysis, as outlined in the preceding Section 2.
Thermal Cycle 1: Temperature Range 0 to 200 °C
Initially, the sensors underwent a testing phase where they were subjected to a temperature range of 0 °C to 200 °C. The objective of this testing was to examine the linear relationship between the temperature and the output of the Fiber Bragg Grating (FBG). The results demonstrated that the T(λ) characteristic exhibited a linear correlation between the temperature and the variation of the FBG output. Additionally, the coefficient
Results
The findings derived from the test campaigns are expounded hereafter, based on the two distinct thermal cycles and a repeatability analysis, as outlined in the preceding Section 2. The results demonstrated that the T(λ) characteristic exhibited a linear correlation between the temperature and the variation of the FBG output. Additionally, the coefficient K T was found to be similar to that detected in previous tests performed in a climate chamber.
This finding suggested that the FBG outcomes can be applied in a vacuum environment in the same manner as in atmospheric conditions, making them useful for both aeronautical and space applications. Furthermore, the errors detected after converting the sensors' outputs into temperature data were minimal, and the vacuum environment effectively eliminated the mechanical disturbances caused by convective motion that were previously present in non-vacuum measurements [31]. The experimental outcomes derived from the first session of experiments are reported on Figure 9. KT was found to be similar to that detected in previous tests performed in a climate chamber. This finding suggested that the FBG outcomes can be applied in a vacuum environment in the same manner as in atmospheric conditions, making them useful for both aeronautical and space applications. Furthermore, the errors detected after converting the sensors' outputs into temperature data were minimal, and the vacuum environment effectively eliminated the mechanical disturbances caused by convective motion that were previously present in non-vacuum measurements [31]. The experimental outcomes derived from the first session of experiments are reported on Figure 9. Ultimately, with regard to the bonding technique, it was imperative to choose materials with thermally stable properties, even in a vacuum environment. The application of adhesive directly onto the sensors was avoided to prevent the generation of mechanical stresses. The error trends and the boxplot of the K(T) are reported on
Tests Cycle 2: Temperature Range −150 to 200 °C
Building upon the positive outcomes obtained from the initial segment of the experiment, the entire optical sensor network was subjected to negative temperatures, reaching −150 °C, to investigate potential non-linear phenomena in the calibration curve [32][33][34]. The principal outcome of this test was that all the Fiber Bragg Grating (FBG) sensors demonstrated an analogous λ(T) calibration curve trend (Figure 10a). Specifically, the curve exhibited essentially linear behavior up to a transition point of approximately −50 °C. Subsequently, the slope of the calibration curve λ(T) reduced for all sensors by the same amount. The sole disruption detected was a minor delay in the response time of the FBG in comparison to the thermocouple for the points located in close proximity to the heater. The consistent trend facilitated the approximation of the λ(T) curve with a linear stroke. In particular, one KT coefficient was employed for temperatures above −50 °C, and a second, lower coefficient was employed for temperatures below this threshold. The linear stroke approximation already demonstrated a high level of accuracy and dependability. Nevertheless, the accuracy of the calibration process was further refined by applying numerical approximation methodologies, as illustrated in Figure 11. In conclusion, the observations made regarding positive temperatures can be extended to low temperatures by altering the Kt coefficient below −50 °C for the present configuration. Ultimately, with regard to the bonding technique, it was imperative to choose materials with thermally stable properties, even in a vacuum environment. The application of adhesive directly onto the sensors was avoided to prevent the generation of mechanical stresses. The error trends and the boxplot of the K(T) are reported on Figure 10. Building upon the positive outcomes obtained from the initial segment of the experiment, the entire optical sensor network was subjected to negative temperatures, reaching −150 • C, to investigate potential non-linear phenomena in the calibration curve [32][33][34].
The principal outcome of this test was that all the Fiber Bragg Grating (FBG) sensors demonstrated an analogous λ(T) calibration curve trend (Figure 10a). Specifically, the curve exhibited essentially linear behavior up to a transition point of approximately −50 • C. Subsequently, the slope of the calibration curve λ(T) reduced for all sensors by the same amount. The sole disruption detected was a minor delay in the response time of the FBG in comparison to the thermocouple for the points located in close proximity to the heater. The consistent trend facilitated the approximation of the λ(T) curve with a linear stroke. In particular, one K T coefficient was employed for temperatures above −50 • C, and a second, lower coefficient was employed for temperatures below this threshold. The linear stroke approximation already demonstrated a high level of accuracy and dependability. Nevertheless, the accuracy of the calibration process was further refined by applying numerical approximation methodologies, as illustrated in Figure 11. In conclusion, the observations made regarding positive temperatures can be extended to low temperatures by altering the K T coefficient below −50 • C for the present configuration.
Repeatability and Accuracy Analysis
The reliability of the Fiber Bragg Grating (FBG) measurements is contingent on their repeatability, making it a crucial requirement for thermal testing. Therefore, a final test was conducted to verify the previously obtained thermal characterization. In this experiment, all the thermocouples, except one, were removed, and the overall thermal cycles were repeated.
To ensure consistency, the chamber was stabilized at the same temperatures, and the temperature was calculated by employing the calibration coefficients derived from the previous campaign. The raw data obtained from both tests were initially compared, and it was observed that the FBG recorded stabilization on the same previous wavelength when the chamber imposed the same temperature.
Repeatability and Accuracy Analysis
The reliability of the Fiber Bragg Grating (FBG) measurements is contingent on their repeatability, making it a crucial requirement for thermal testing. Therefore, a final test was conducted to verify the previously obtained thermal characterization. In this experiment, all the thermocouples, except one, were removed, and the overall thermal cycles were repeated.
To ensure consistency, the chamber was stabilized at the same temperatures, and the temperature was calculated by employing the calibration coefficients derived from the previous campaign. The raw data obtained from both tests were initially compared, and it was observed that the FBG recorded stabilization on the same previous wavelength when the chamber imposed the same temperature. Figure 12 depicts the perfect coherence between the two tests, with the only differences being the duration of the steps and the final return to environmental conditions after the lower step, due to the manually controlled process.
Micromachines 2023, 14, x FOR PEER REVIEW 10 of 14 Figure 12 depicts the perfect coherence between the two tests, with the only differences being the duration of the steps and the final return to environmental conditions after the lower step, due to the manually controlled process. The final outcome pertained to the level of accuracy achieved in the temperature reading following stabilization. As shown in Figure 13, an accuracy capable of detecting a stability of less than 0.2 • C/h, a typical requirement in the space industry, was attained. Furthermore, the moving average value of the fiber over a 60 min period is plotted with a tolerance band of ±0.1 • C (i.e., 0.2 • C/h amplitude). The graph illustrates that the oscillations remained within the tolerance band. As demonstrated in the graph on the right, the error committed with respect to the anticipated mean value was less than 0.1 • C/h in absolute terms, which is significantly below the required constraint. The final outcome pertained to the level of accuracy achieved in the temperature reading following stabilization. As shown in Figure 13, an accuracy capable of detecting a stability of less than 0.2 °C/h, a typical requirement in the space industry, was attained. Furthermore, the moving average value of the fiber over a 60 min period is plotted with a tolerance band of ±0.1 °C (i.e., 0.2 °C/h amplitude). The graph illustrates that the oscillations remained within the tolerance band. As demonstrated in the graph on the right, the error committed with respect to the anticipated mean value was less than 0.1 °C/h in absolute terms, which is significantly below the required constraint.
Discussion
The experimental campaign conducted in this study yielded highly favorable and promising results, indicating that Fiber Bragg Grating (FBG) sensors can be exceptionally useful for the thermal characterization of components in space applications. These sensors possess high sensitivity, enabling them to detect even minor temperature variations, and they are smaller in size compared to traditional sensors such as thermocouples, allowing a low weight and flexibility to the MLI, ideal for deployable or inflatable structures. Additionally, FBGs exhibit a shorter response time and can instantaneously detect sudden thermal changes, unlike thermocouples. Moreover, the presence of multiple Bragg sensors on a single optical fiber allows for precise information at numerous points with only one cable, whereas electronic thermocouple sensors necessitate one device per point, resulting in greater interference.
Consequently, the measurement cycle was conducted in a vacuum, using a free fiber solely affixed to the specimens at temperatures typical of the space environment. This approach facilitated the integration of the instrument onto the tested supports, such as metal plates and/or thermal protection coatings, without compromising measurement accuracy. Under stable mechanical conditions, the measurement cycles demonstrated the high reliability of the outputs and the complete elimination of interferences and noise in the data. The ease of the integration strategy adopted in this study has significant implications for potential industrial applications in the future.
The final measurement campaigns revealed that FBGs can be safely used at operating temperatures of up to 200 °C, a value that is seldom supported by traditional electronic sensors, other than thermocouples. However, special attention must be paid to negative temperatures. In all the tests conducted, the linear characteristic of T(λ) underwent significant changes. During the tests, a critical temperature of −50 °C was identified, below
Discussion
The experimental campaign conducted in this study yielded highly favorable and promising results, indicating that Fiber Bragg Grating (FBG) sensors can be exceptionally useful for the thermal characterization of components in space applications. These sensors possess high sensitivity, enabling them to detect even minor temperature variations, and they are smaller in size compared to traditional sensors such as thermocouples, allowing a low weight and flexibility to the MLI, ideal for deployable or inflatable structures. Additionally, FBGs exhibit a shorter response time and can instantaneously detect sudden thermal changes, unlike thermocouples. Moreover, the presence of multiple Bragg sensors on a single optical fiber allows for precise information at numerous points with only one cable, whereas electronic thermocouple sensors necessitate one device per point, resulting in greater interference.
Consequently, the measurement cycle was conducted in a vacuum, using a free fiber solely affixed to the specimens at temperatures typical of the space environment. This approach facilitated the integration of the instrument onto the tested supports, such as metal plates and/or thermal protection coatings, without compromising measurement accuracy. Under stable mechanical conditions, the measurement cycles demonstrated the high reliability of the outputs and the complete elimination of interferences and noise in the data. The ease of the integration strategy adopted in this study has significant implications for potential industrial applications in the future.
The final measurement campaigns revealed that FBGs can be safely used at operating temperatures of up to 200 • C, a value that is seldom supported by traditional electronic sensors, other than thermocouples. However, special attention must be paid to negative temperatures. In all the tests conducted, the linear characteristic of T(λ) underwent significant changes. During the tests, a critical temperature of −50 • C was identified, below which a new linear fit could be obtained from the experimental data. Nevertheless, this more complex calibration enabled accurate detection of low temperatures by FBGs.
The last segment of the tests demonstrated the ability of FBGs to autonomously detect temperature, with a remarkably high level of accuracy.
Conclusions
The favorable outcomes of the comprehensive test campaigns suggested that Fiber Bragg Grating (FBG) sensors have considerable potential for space applications, especially for thermal characterizations, owing to the substantial number of sensors available and the extremely compact size of the cable. Additionally, the FBGs' high sensitivity enabled them to detect not only temperature variations, but also other measurements such as strain or damage due to micrometeoroid impact.
Further investigations are necessary to examine the behavior of FBGs in cryogenic cases and to gain a better understanding of the transition phase between the two linear fits determined by the experimental data.
Finally, this study emphasized the importance of establishing precise standards for developing specific sensor packaging. This is a challenging task due to the fiber's exceptional sensitivity to the environmental conditions, including the temperature and mechanical conditions.
Overall, the potential of FBG sensors for space applications, particularly in thermal characterizations, offers a promising avenue for advancing technology in the field, with further research and development poised to yield even more impressive results. | 8,432.2 | 2023-04-25T00:00:00.000 | [
"Physics"
] |
Effect of Stop-Loss Reinsurance on Primary Insurer Solvency
: Stop-loss reinsurance is a risk management tool that allows an insurance company to transfer part of their risk to a reinsurance company. Ruin probabilities allow us to measure the effect of stop-loss reinsurance on the solvency of the primary insurer. They further permit the calculation of the economic capital, or the required initial capital to hold, corresponding to the 99.5% value-at-risk of its surplus. Specifically, we show that under a stop-loss contract, the ruin probability for the primary insurer, for both a finite- and infinite-time horizon, can be obtained from the finite-time ruin probability when no reinsurance is bought. We develop a finite-difference method for solving the (partial integro-differential) equation satisfied by the finite-time ruin probability with no reinsurance, leading to numerical approximations of the ruin probabilities under a stop-loss reinsurance contract. Using the method developed here, we discuss the interplay between ruin probability, reinsurance retention level and initial capital.
Introduction
The environment in which general insurance companies currently operate is challenging in at least two aspects. First, investment income is squeezed by unprecedented low levels of interest rates. Second, for some classes of businesses, premium rates are relatively low due to an abundance of industry capacity. Risk management is therefore relied upon not only for monitoring risks but also to inform management decisions.
A risk management tool often used by insurance companies is reinsurance, especially for very large risks or risks which are difficult to assess, for instance hurricanes, earthquakes or wildfires. Under a reinsurance contract, the reinsurer company agrees to compensate the primary insurer (or ceding company) for part of its insurance losses in exchange for a reinsurance premium. In short, reinsurance is when an insurance company transfers part of its underwritten insurance risks to a reinsurance company. By entering a reinsurance contract, the primary insurer should attain a reduction in the probability of incurring large losses and reduce the capital required to keep its insolvency risk at an acceptable level. There are different forms of reinsurance treaties, and for a review of their properties, we refer the reader to Albrecher et al. (2017). The choice of reinsurance treaty is complex, often relying on some optimality criteria related to profit, solvency and cost of capital (see, e.g., Haas 2012;Kull 2009) and taking into account the availability and price of the contract, market competition and regulatory constraints: see Albrecher et al. (2017) and references therein.
One form of reinsurance is stop-loss, under which the aggregate loss, over a given time period, is capped at an agreed retention level and the reinsurer is liable for the excess. This type of contract has been found to be optimal under different decision criteria, for instance, if the primary insurer wants to minimize the variance of the retained risk as per Borch, Kahn and Pesonen (e.g., see Pesonen 1984) or when maximizing expected utility in the context of risk-averse utility functions as per Arrow (1963) or Borch (1975). One can also model the solvency of a reinsurance strategy using the concept of ruin probability. Considering a ruin condition as the decision criterion allows to find the optimal reinsurance treaty for the insurer. Indeed, a stop-loss type of reinsurance contract is optimal when the criterion is to minimize the ruin probability: see Gajek and Zagrodny (2004). Minimizing the ruin probability and maximizing the expected utility are in fact related, as shown by de Lourdes Centeno (2008, 2010) who again find that a stop-loss type of reinsurance contract is optimal under certain conditions.
Because it is based on the aggregate losses, compared with other types of reinsurance contracts, stop-loss is useful when it is difficult to allocate individual claims to particular events due to their nature, as can happen, for instance, in agriculture. From the risk management point of view, this type of treaty is special in the sense that it completely relieves the primary insurer from tail risk, a major concern for solvency. In this article, we introduce a methodology that allows us to study how stop-loss reinsurance affects the level of capital a primary insurer must hold to sustain a low level of insolvency risk determined by a strategic decision or regulatory directive. The regulatory solvency approach, under Solvency II, focusses on the one-year 99.5% value-at-risk, meaning that the probability that the aggregate loss over the year is larger than the available capital is 0.5%. Hence we use the 0.5% ruin probability to determine the level of economic capital necessary to cover the losses over the next year.
We first introduce a relationship between the finite and infinite-time ruin probability for a portfolio with stop-loss reinsurance, and the finite-time ruin probability for a portfolio with no reinsurance. Then, using a classical risk theory result, namely that the finitetime probability of ruin in a classical no-reinsurance contract satisfies an integro-partial differential equation (see Pervozvansky 1998), we proceed to numerically solve the equation and thus derive the finite-time-no-reinsurance ruin probability that leads to the finite and infinite-time ruin probability with stop-loss reinsurance. We can then evaluate the level of risk faced by the primary insurer when covered by a stop-loss contract compared with the risk faced without taking on reinsurance. The risk cover provided by the reinsurance contract depends on the length of the contract. Remarkably, the stop-loss contract provides an upper bound to the ruin probability for a sufficiently long contract. In our numerical example, for a given set of parameters of the risk process, ruin probability plateaus for contracts longer than four months, showing that a realistic length of contract already provides such cap on the insolvency risk faced by the primary insurer. This shows the relevance of our results under realistic assumptions within a dynamic framework where the stop-loss contract can be regularly redefined in a finite (and not excessively large) time horizon.
As in any financial enterprise, the solvency of an insurer depends on its initial capital. Hence, it is important to understand the role of the initial capital on the solvency of the primary insurer and how it interacts with the amount of business ceded via a stop-loss contract. To that end, we evaluate the change in ruin probability, corresponding to different amounts of initial capital and different reinsurance retention levels. On the one hand, we conclude that ruin probability, and hence the risk of insolvency, is far more sensitive to the retention level for lower than higher levels of initial capital. On the other hand, decreasing the stop-loss retention level (or increasing the amount of risk ceded) does not imply a linear decrease in the initial capital required to maintain a chosen level of insolvency risk. At higher retention levels, the extra amount of initial capital necessary to compensate for retaining extra risk is lower than at lower retention levels. This implies that the motivation for the primary insurer to cede more risk to the reinsurer as a way of lowering the need of capital, and associated cost, reduces as the retention level increases. This is a convenient result in the sense that the primary insurer has diminishing incentive to seek an unlimited stop-loss contract. In fact, unlimited stop-loss contracts are not sold systematically (except under certain obligatory arrangements or captive solutions) because once the aggregate claim losses exceeds the agreed retention level the contract is a catastrophe for the reinsurer. In a dynamic finite-time horizon setting, a possible solution is for reinsurance companies to create side-car structures, spreading the risk among third-party private investors seeking high-yields such as hedge funds or equity firms.
The effect of stop-loss on the primary insurer solvency is then measured by its effect on the so-called economic capital, which is the amount of capital the insurer must hold in order to absorb losses in excess of the average loss. The economic capital is then defined by the value-at-risk, typically at a very high confidence level and for a one-year time horizon. We develop a numerical example where we determine the level of initial capital necessary to ensure that the insurer can cope with losses up to a 99.5% value-at-risk, which, in our framework, corresponds to a 0.5% ruin probability. Our main finding is that entering into a stop-loss reinsurance contract allows for a striking reduction in the initial capital the primary insurer must hold to keep the desired low level of insolvency risk.
The paper is organised as follows. In the following section, we introduce the risk process model used throughout this article. In Section 3, we show that the probability of ruin under a stop-loss reinsurance contract can be seen as a special case of ruin probability in finite-time. In Section 4, we propose a numerical method for approximating solutions to the finite-time ruin probability problem. In Section 5, we apply the numerical method to the stop-loss reinsurance model. Section 6 follows with an evaluation of the interplay between finite-time ruin probability, stop-loss retention level and initial capital. Section 7 illustrates the application to the economic capital required by Solvency II, and Section 8 contains the conclusions.
The Risk Process Model
To assess the insurance risks in a mathematical framework, we consider an insurance portfolio as follows. Assuming (Ω, F , P) to be a probability space, let (N(t)) t≥0 be a counting process and (X k ) k∈N a sequence of independent and identically distributed random variables representing, respectively, the number of claims an insurance company received up to and including time t and the size of claim k. The classical collective risk model, introduced by Lundberg and Cramér, defines the surplus at a given time t as which describes the evolution of the capital of an insurance company over time, starting with an initial capital u, receiving premiums at rate c > 0 and paying out claims X k as they arrive. This model captures the insurer's capital dynamics, keeping analytical and numerical tractability, and enables us to calculate solvency indicators while maintaining adequate amount of assumptions regarding the real world applications. A measure of risk which takes into account the aspects of the risk process inherent to the insurance business is ruin probability, considered over a finite or infinite time horizon. One defines "ruin" as the event of the surplus becoming negative for the first time. To ensure that ruin is not certain, one requires that ct > E(N(t))E(X), the so-called net profit condition, which in case the counting process (N(t)) t≥0 is Poisson with intensity λ and the claim sizes have mean µ, becomes c > λµ; see, for example, Asmussen and Albrecher (2010). Throughout the paper we consider a Poisson counting process.
The probability of ruin Ψ, as a function of the initial capital u, is defined as This is the probability that the insurer's capital balance will become negative for the first time. This is referred to as the infinite-time ruin probability, or ruin probability in an infinite horizon, or simply ruin probability. One may also consider the probability of ruin in finite time, defined as a function of the initial capital u and the time horizon T, describing the probability that ruin occurs by time T. One way of deriving the ruin probabilities in insurance portfolios is as solutions of integro-differential equations for infinite horizon ruin, respectively, integro-partial differential equations for finite-time ruin. By specifying the claims distribution, one can further reduce these equations to differential (see, e.g., Albrecher et al. 2010), respectively, partial-differential equations (see e.g., Pervozvansky 1998), which in specific instances have analytic solutions.
Stop-Loss Reinsurance and (In)Finite-Time Ruin Probability
We consider the following stop-loss reinsurance contract. A time T (may be infinite) is agreed upon between the ceding company and the reinsurer; until then, the reinsurer agrees to cover all the aggregate losses that exceed a certain level B ≥ 0. Let S denote the aggregate loss up to and including time t. That is, Then, the amount the reinsurer pays to the ceding company, up to and including time t, is R(t) = (S(t) − B) + , where we use the notation a + := max(a, 0) for a real number a. Moreover, let U R denote the surplus of the ceding company who entered such contract with the reinsurer. Clearly, where c R is the adjusted premium income, which equals the original premium income from the classical model c (i.e., the premium when there is no reinsurance in the model) minus the cost of the reinsurance contract. Let Ψ R denote the probability of ruin before time T with initial capital u under this stop-loss reinsurance contract, that is, Let Ψ 0 be the classical ruin probability with no reinsurance where the premium rate is c R instead of the original c.
and let T * := (min(t 0 , T)) + . Then Proof. By definition, S(t) − R(t) = B ∧ S(t) is the retention part of aggregated claims under the stop-loss reinsurance at time t > 0. Hence, for t ≥ t 0 , which means ruin will not occur after t 0 .
On the other hand, on the set The identities above show that in the event of finite time survival, the two models coincide for every T < t 0 .
In other words, for every T > 0, Remark 1. Note that in the presence of a stop-loss contract, for T = ∞, ruin would never happen So far we have shown that the ruin probability of a certain type of stop-loss reinsurance contract can be expressed in terms of the ruin probability in finite-time for an insurer without reinsurance for a given T * dependent on T. To further explore finite-time ruin probability with stop-loss reinsurance, we recall the partial integro-differential equation for the finite-time ruin probability, derived by Pervozvansky (1998) under very general conditions. Here we present the result for the convenience of the reader. This will be the basis for the finite-difference numerical scheme of Section 4. Theorem 2. Let (N(t)) t≥0 be a Poisson process with constant intensity λ > 0. Let the claims (X k ) k∈N be independent and identically distributed with cumulative distribution function F. Assume that X k has a density which is once continuously differentiable.
with the boundary conditions For proof of (6), see Pervozvansky (1998, Theorem 1). Note that the first boundary condition comes from the assumption of a positive net profit, c > λE(X). The second one follows from the definition of Ψ.
Remark 2.
There is an analytic solution to (6) in the particular case when claim sizes X k have an exponential distribution with the parameter β. Let J(x) := I 0 (2 √ x), where I 0 (x) denotes the modified Bessel function; see, e.g., Rolski et al. (1999, p. 197). Then,
Description of the Numerical Scheme
Let T > 0 be the greatest time for which we wish to calculate the ruin probability in finite-time. We will use the finite-difference method to approximate solutions to the above partial integro-differential equations for Ψ(u, t), u ∈ (0, ∞), t ∈ (0, T]. Let N ∈ N be the number of time steps used in the approximation, and let τ := T/N. This is the step size used in the temporal discretization. Let h > 0 denote the step size used in the spatial discretisation. Let g be some function defined on [0, ∞) × [0, T]. Then, and Care has to be taken when approximating the integral term, as f will typically be unbounded at 0. Thus, we propose three possible approximations corresponding to "leftpoint", "mid-point" and "right-point" approximation: We see that for S ∈ {L, M, R}, The last approximation lies in restricting the domain (0, ∞) × (0, T] to a bounded domain, say, (0, u max ] × (0, T]. For this, we need an "artificial" boundary condition. We use the fact that Ψ is monotonically decreasing as a function of u and the boundary condition lim u→∞ Ψ(u, t) = 0 to impose an artificial boundary condition. Let us denote by u 0 the largest initial capital for which we wish to approximate the probability of ruin in finite time. Let K ∈ N denote the multiple of u 0 , which we use to define the size of the interval on which the computation is carried out. Thus, we choose u max := min{ih : ih ≥ Ku 0 , i = 0, 1, . . .}.
We will define Ψ S : G h,τ,K → R, for S ∈ {L, M, R}, as the function that satisfies, for i = 0, 1, . . . , u max /h − 1 and n = 0, 1, . . . , N − 1 together with the initial and boundary condition See Figure 1 for a graphical illustration of the dependence structure of the scheme. We can see that (7) is a semi-implicit approximation of (6) and . . . Regarding the stability of the scheme, we present the following estimate in the energy norm.
Lemma 1. Let M := u max /h and let Then, there is a constant C independent of h, τ and K such that for any n = 1, . . . , N E n ≤ C.
Numerical Experiments Verifying Convergence
We will use Remark 2 to obtain an analytical solution to (6). This can be compared to numerical approximations of the solution to verify convergence. The numerical method can then be applied for other distributions of claim size X k . The constants used in the numerical experiments are in Table 1. Table 1. Constants used in the numerical experiments: T > 0 is the (finite) time horizon, c is the premium rate, λ is the claim intensity, 1/β is the mean claim size and u 0 is the largest initial capital for which we wish to approximate the probability of ruin in finite time.
Parameter u 0 T c λ β Value 5 5 20 5 0.5 Figure 2 demonstrates the convergence of approximation with different schemes S ∈ {L, M, S} as h → 0 with other parameters fixed. One observes that as the number of space steps increases, all three methods converge.
Figures 2-4 demonstrate convergence as h → 0, τ → 0, u max → ∞. When running the experiment, the other parameters were kept as small (for h, τ) or as large (for K) as necessary to introduce no discernible error. We note in particular that taking K = 10 (which results in u max ≈ Ku 0 = 50) results in an error of order 10 −4 .
Results for Finite-TIME Ruin Probability Ψ(u, T)
Until now, we have analysed the stability and checked the convergence of the numerical scheme. In this section, some by-products of our algorithm will be introduced. One advantage of applying the finite-difference method is that we will have the dynamics of the PDE system when we solve it. We are not yet applying in this section the algorithm to calculate the ruin probability under the stop-loss reinsurance setting.
Instead of solving a single setting of ruin probability Ψ(u, T) directly, we separate the time horizon into many small time intervals, and this actually provides us additional information about the ruin process with respect to the time at least when the grid size is chosen large enough. For each of the Ψ n i s, we approximated inside the process until reaching the final Ψ N I . We also approximate how ruin probability will behave in each of these finite-time horizons (with accuracy decreasing while n becomes smaller). The same by-product also comes when we divide the initial capital u into segments. These byproducts can be justified by the deterministic property of the PDE system, as in Equation (6).
If the arguments of reaching a decent accuracy when approximating a Ψ(u, T) via this scheme stand, then one can say that any Ψ(s, t) where s ∈ [0, u] and t ∈ [0, T] can be approximated to the same accuracy. Thus, in one run, a large enough grid size can be found to approximate Ψ(s, t) with the required accuracy. Here, the convergence is exponential. It appears that K of 10 already produces errors of order 10 −4 in the ruin probability, and the choice of τ and h are the determining factors for producing the required accuracy.
One can also study the dynamics of finite-time ruin probability more directly by iterating our algorithm on several Ψ(s, t) where s ∈ [0, u] and t ∈ [0, T]. Figure 5 gives a comprehensive view of how the finite-time ruin probability Ψ(u, T) varies as a function of the initial capital u and time horizon T 1 . One can observe that the finite-difference method approximation gives a ruin probability that increases as the time horizon increases and decreases as the initial capital increases, as expected. Table 1.
We can also analyse the finite-time ruin probability under different parameter settings. By changing the initial capital u, premium rate c, Poisson intensity λ, and claim average size 1/β separately, we can analyse the behaviour of the finite-time ruin probabilities as well as compare these with the infinite-time ruin probability. As one can see from Table 2, the finitetime ruin probabilities increase with time and converge to the infinite-time ruin probability in all settings we have considered. We can further confirm that the numerical method is working as it should as the approximate ruin probability increases with claims intensity and claim average size, and decreases when initial capital and premium rate increases. Table 2. Finite and infinite-time ruin probability under different parameter settings. For the parameters, u is the initial capital, c is the premium rate, λ is the claim intensity, and 1/β is the mean claim size.
Finite-Time Ruin Probability with and Without Stop-Loss Reinsurance
A direct application of the above algorithm is to calculate the finite and infinite-time ruin probability when stop-loss reinsurance is considered. For simplicity, in this study, we assume that the premium for the reinsurance contract is determined by the pure risk premium principle. By definition, the pure premium principle allocates to the reinsurer a certain proportion of the difference between the expected claims and the retention level as its premium, i.e., α(E[S(t)] − B), where α (usually we have α ∈ (0, 1)) is the premium rate for reinsurance. Denote by B α the retention level of a stop-loss reinsurance contract with premium rate α. Given the result in (3), determining the ruin probability under stop-loss reinsurance reduces itself to the finite-time ruin probability, i.e., Ψ R (u, T) = Ψ 0 (u, T * ), with T * the only parameter left unknown. However, as shown in Theorem 1, T * = (min(t 0 , T)) + , with t 0 = B−u c R , where T is the length of the reinsurance contract. We can visualise the effect of buying stop-loss reinsurance on the ruin probability by plotting in Figure 6 the ruin probability for different time horizons, with and without reinsurance. Here, the stop-loss reinsurance contract is T years long. One can see from the plot that, up to a certain time horizon, the ruin probability with stop-loss reinsurance is larger than the ruin probability without stop-loss reinsurance. This can be explained by the costs associated with the reinsurance contract. Meanwhile, if the ceding company has not faced ruin before this particular time horizon, it will not face ruin probability for longer horizons, since the reinsurance is capping the claims to be paid. This feature that we observe here is consistent with the argument used in the proof of Theorem 2. Indeed, in the same figure, one can observe that the finite-time ruin probability will not increase for time horizons longer than marked by the red dashed line in the plot, the moment when the stop-loss reinsurance starts to pay claims. There is a time horizon such that, as expected, for horizons longer than that, the finite-time ruin probabilities are smaller when reinsurance is present.
Finite-Time Ruin Probability, Stop-Loss Retention Level and Initial Capital
Next, we study the dynamics of the ceding company's ruin probability under a stoploss reinsurance contract. The 3-d graph in Figure 7 shows how initial capital u, and stop-loss retention level B affect the finite-time ruin probability. When the initial capital is large and the stop-loss retention level is small (corner further away in the plot), the ruin probability equals zero (i.e., there is no ruin). In fact, when the stop-loss retention level B is smaller than (or equal to) the initial capital u, we obtain from Theorem 1 that T * = (min(t 0 , T)) + = 0, and hence the probability of ruin Ψ(u, 0) is zero. Then, as the retention level increases, which indicates that the reinsurer takes fewer risks and the ceding company may face more risks itself, the ruin probability for the ceding company increases. Figure 7. Plot of finite-time ruin probability with stop-loss reinsurance: this is a numerical approximation showing how initial capital and stop-loss retention level influence finite-time ruin probability. Initial capital varies from 3 to 10, the retention level from 5 to 20, h = 0.005, τ = 0.01, K = 12, and all other parameters are as in Table 1.
We can also observe in the plot that the reduction in the initial capital increases the ruin probability as we expected. We do not know exactly how ruin probability will behave without accurate parameter estimates and the exact reinsurance pricing mechanism. However, in the case studied here, the ceding company's premium is relatively high; as a matter of fact, it is so high, that for longer time horizons, with the help from the reinsurance company, it will not face ruin. We can observe these finite-time ruin probability dynamics in Figure 7.
Moreover, Figure 7 tells us an even more interesting story, namely how the initial capital will compensate for the choice of stop-loss retention level, which, consequently, compensates for the cost of buying stop-loss reinsurance. Telling from the colour, choosing any fixed retention level, the increase in initial capital will drop the ruin probability, and for any fixed initial capital, the increase in retention level will boost the ruin probability up to some point. Moreover, the curves in the initial capital versus retention level plain, which help us tell the height of the surface, are actually a measure of how the initial capital compensates for the stop-loss retention level and thus ensure the efficiency of the stop-loss reinsurance contract.
For example, for relatively low initial capitals, say the high retention level and low initial capital corner, the small size of initial capital requires a small retention level of stop-loss reinsurance to keep it in the lower ruin probability region, i.e., the dark blue part. This small retention level of stop-loss reinsurance means an expensive contract, as the reinsurer takes more risks. On the other hand, with relatively large initial capitals, the ceding company can stay safe (i.e., small ruin probability) even with large retention levels, which means cheaper reinsurance contracts, but more risk for the ceding company. One sees here how initial capital and retention level compensate for each other. In reality, it all depends on the ceding company itself to choose between buying a more expensive reinsurance contract or just raising more capital (rather than spending on reinsurance).
Furthermore, one can easily observe that, whenever the company targets a certain ruin probability, as the retention level becomes larger, the increase on itself will compensate less and less for the increase in the initial capital, thus exhibiting "diminishing returns". This indicates a low sensitivity of ruin probability to retention level when the latter is large.
Stop-Loss Reinsurance and The Primary Insurer Solvency
Risk of insolvency has sustained an increase in risk regulation for the insurance industry over the last decades. In the United States, the National Association of Insurance Commissioners supports the development of insurance regulations by individual states and has promoted the notion of risk-based capital for insurance companies. In Europe, the European Insurance and Occupational Pensions Authority oversees the development of the Solvency II framework. Under Solvency II, insurance companies must calculate their Solvency Capital Requirement, or Solvency II Economic Capital (EC), where all assets and liabilities should be valued on a market-consistent basis. According to this regulatory framework the EC ensures that the probability of insolvency over a one-year period does not surpasses 0.5%. To calculate their portfolio overall capital requirement, an insurance company must consider all the risks and their interactions. The methodology developed in this article can be used in the calculation of the capital requirement for a homogeneous insurance segment. According to Solvency II, the capital requirement for the all insurance company can then be calculated using an internal model or a simpler standard formula where the aggregation of risks is done using correlation parameters. A discussion of the aggregation properties of the two different approaches is out of the scope of this article.
From a risk measurement perspective, the EC, being an estimate of the capital necessary to keep the probability of insolvency below 5%, can be calculated as the one-year market-value based value-at-risk (VaR). In our framework, we take the initial capital corresponding to a one-year horizon ruin probability of 0.5% as the required EC. By simulation and interpolation of the results from our algorithm, we can calculate the initial capital corresponding to a ruin probability of 0.5% with a one-year time horizon. The results are in Table 3.
In panel A, we list, for different parameter values and when there is no reinsurance contract in place, the value of the initial capital corresponding to a 0.5% ruin probability for a time horizon ranging from about 5 weeks to 8 years. The initial capital necessary to maintain the desired level of ruin probability increases with the average aggregate claims and decreases when the premium rate increases. In panel B we list, for two values of reinsurer premium rates, the value of the initial capital corresponding to a 0.5% ruin probability for a one-year time horizon when there is a stop-loss reinsurance contract in place. We observe that reinsurance substantially lowers the amount of initial capital (economic capital) required in relation to the no-reinsurance case. Interestingly, once there is a stop-loss reinsurance contract in place, increasing the reinsurance premium rate from α = 0.3 to α = 0.9 does not increase the required initial capital that much when compared with the significant reduction implied by the introduction of reinsurance. Table 3. Initial capital corresponding to a 0.5% ruin probability for different parameter values of the risk process. For the parameters, c is the insurer premium rate, λ is the claim intensity, 1/β is the mean claim size, and α is the reinsurer premium rate.
Conclusions
We employ ruin probability as a measure of the risk of an insurance company solvency. We propose a relationship between the finite and infinite-time ruin probability for a portfolio with stop-loss reinsurance and the finite-time ruin probability for a portfolio with no reinsurance contract. This can be found in Theorem 1. According to Remark 1, ruin would never happen for a time horizon longer than a certain T * for a portfolio with stop-loss reinsurance, which is illustrated in Figure 2. When employing aggregate stoploss reinsurance, we build on two novel approaches: firstly, the connection introduced here between the finite and infinite-time ruin probability of a stop-loss portfolio and the finite-time ruin probability of a classical reinsurance free portfolio, and secondly, on the adaptation of the finite-difference method normally used for solving partial differential equations to solve the integro-partial differential equation the finite-time ruin satisfies. With the results at hand, a risk analysis is performed, identifying the combination of initial capital and retention level for which ruin is no longer possible, the diminishing returns of the balancing of initial capital and retention level and, not last, the variations on solvency for different time horizons. Analysing these dynamics between the parameters involved proves relevant to the risk management of an insurance portfolio. The methodology presented in this article allows us to identify the level of the primary insurer capital and corresponding retention level under a stop-loss contract necessary to keep a desired low level of insolvency risk. By entering in a stop-loss contract, the primary insurer can significantly reduce the capital without increasing the level of insolvency risk. In most cases, employing reinsurance is always better than not in terms of ruin probabilities and solvency capital requirements. | 7,593.6 | 2022-10-10T00:00:00.000 | [
"Mathematics"
] |
Quantum process semantics
The paper describes a model of subjective goal-oriented semantics extending standard «view-from-nowhere» approach. Generalization is achieved by using a spherical vector structure essentially supplementing the classical bit with circular dimension, organizing contexts according to their subjective causal ordering. This structure, known in quantum theory as qubit, is shown to be universal representation of contextual-situated meaning at the core of human cognition. Subjective semantic dimension, inferred from fundamental oscillation dynamics, is discretized to six process-stage prototypes expressed in common language. Predicted process-semantic map of natural language terms is confirmed by the open-source word2vec data.
Introduction
Problem While effective in many recognition, classification, and combinatorialtype tasks, modern artificial intelligence does not approach human-level performance in several vital areas. Making decisions in novel situations, solving ill-defined problems, extracting knowledge from data, understanding of natural language, and other cognitive routines of humans are very difficult to algoritmize Brachman (2002); Sheth et al. (2019); Sowa (2015). Taking into consideration computational powers thrown at these tasks, incomparable to 10-20 watts of average human brain, this indicates that the encountered obstacle is of deep conceptual nature.
Root of the issue is identified by noting that the mainstream approaches simulate meaning of visual, textual, and other information types as their objective quality -a «content». Classical and contemporary studies, in contrast, indicate that semantics of a sign is not a property that can be discovered by a measurement algorithm; instead, it is constructed by a subject from the context perceived through stereotypes of his own mind Bruner (1990); Cornejo (2004);De Saussure (1959); DeGrandpre (2000); Firth (1935); von Glasersfeld (1995); Kintsch & Mangalath (2011); Langleben (1981); Ogden & Richards (1923); Stokhof (2002). Ignorance of this basic fact explains inefficiency of modern AI in cognitive tasks of inherently subjective nature.
Approach Fundamental problems need fundamental solutions. The approach developed below consists in finding a unit of information addressing subjectivity in explicit way and stimulating the algorithms to deal with this aspect of cognition. The candidate structure is already developed in physics to model atomic-scale phenomena nearly a century ago. It accounts for the novel type of information, carried by electrons, photons, and other well-isolated individual systems, that currently is the basis of quantum communication and computing Jaeger (2019); Nielsen & Chuang (2010).
Applicability of quantum information is not limited to elementary physical systems. With intuitive correspondence to psychological terms, quantum theory allows to describe irrational decision making, unexpected game equilibria, collective behavioral patterns, and understanding of natural language challenging classical modeling approaches Asano et al. (2015); Busemeyer & Bruza (2012); Khrennikov (2010Khrennikov ( , 2015; Khrennikov et al. (2019). Here, contextuality of quantum information allows to account for dependence of meaning on the context of an individual cognitive act Aerts et al. (2000); Basieva et al. (2018); Blacoe et al. (2013); Bruza (2008); Surov et al. (2019), thereby providing subjective ingredient missing in the classical approaches to semantic modeling.
Requested combination of objective and subjective aspects of information is achieved already in the simplest quantum-theoretic structure called qubit. In particular, qubit state allows to represent information contexts in spherical structure where polar coordinates stand for objective and subjective dimensions of cognition. This enables novel methods of analysis revealing regularities of semantics and decision making invisible from objectivist perspective Surov (2020). This work develops the qubit information structure supplementing it with a map of subjective dimension. The result is a scheme of semantic representation explicitly accounting for subjective contextuality of meaning.
Plan of the paper Section 2 introduces essential background, including quantum representation of contexts and the qubit semantic space following Surov (2020). Section 3 describes the main innovation of this paper, namely a scheme of subjective semantic dimension based on a circular process structure. Section 4 reports experimental testing of the model. The predicted process-semantic structure is found in 300-dimensional word2vec data by original analysis method. The result is compared with the existing semantic maps.
Section 5 shows how quantum semantics integrates aspects of human cognition discovered by diverse schools of research. In particular, process-causal and pragmatic-relativity views of semantics find expression in the quantum approach. Further, qubit semantic structure is shown to have qualities of dynamic archetype ubiquitously manifested in culture and science. Outlook section 6 indicates several implications of the result in philosophical and practical perspectives.
The Qubit
The announced unit of information accounts for the simplest behavioral situation -a choice between two mutually exclusive alternatives, imposed on a subject as external constraint. Simplification of this setup leads to singleoption dynamics typical for inert deterministic systems; prolonged behavioral processes including multiple-option decisions, on the other hand, are expressible through sequences or trees of binary choices. The considered setup therefore constitutes an elementary behavioral prototype, absent in classical behaviorist approach Watson (1913).
This section describes mathematics and geometry of the considered information unit, known in quantum theory as qubit Jaeger (2007); Nielsen & Chuang (2010), following methodology of its application to behavioral modeling as described in Surov (2020). Sections 2.1 and 2.3 introduce relevant aspects of the model, with necessary generalization developed in Section 2.2.
Pure context representation space
The considered behavioral situation is formalized as a choice between two options labeled as "1" and "0". Making of this decision requires estimation of the corresponding probabilities p(1) and p(0) that sum to 1 since the outcomes are mutually exclusive. The required computation is based on the information received by the considered subject (behavioral system) from its environment. All this information called context is subjectively mapped to a point on a three-dimensional unit-radius sphere built on the poles representing outcomes 1 and 0 as shown in Figure 1. In the following, this sphere developed in physics by A. Poincaré and F. Bloch is referred to as Bloch sphere.
Basic math
Any point on the Bloch sphere corresponds to a vector |ψ superposing the basis vectors |0 and |1 representing the decision alternatives: where θ and φ are polar and azimuthal angles defining position of the point. Vector |ψ thus represents context within which choice between basis alternatives |0 and |1 is being made. The space containing context representation vectors (1) then functions as task-specific cognitive space of the subject. Contrary to the standard Euclidean geometry where orthogonality of vectors is visualized by right angle between them, in the Bloch sphere basis vectors |0 and |1 are opposite to each other. The difference arises due to complexity of coefficients exemplified in (1) by complex exponent e iφ = cos φ + i sin φ. Sphere in real three-dimensional space is thereby equivalent to the two-dimensional complex (Hilbert) space of vectors |ψ .
In the context |ψ , probabilities of alternative decisions are computed as where ·|· denotes overlap (scalar product) of the two vectors, so that e.g. 0|1 = 0, 0|0 = 1|1 = ψ|ψ = 1. Probabilities (2) are proportional to the lengths of segments to which projection of |ψ divides the diameter 1-0. That is, the closer context representation |ψ is to the north pole of a sphere, the higher is probability p(1), and the lower is probability p(0). In representation (1), polar angle θ thus quantifies subjective conduciveness of contexts for choosing the alternative behavioral options, measurable through decision probabilities (2).
Decision and collapse of representation space
According to the model just described, a particular potential decision 0/1 generates the task-specific Hilbert space where any context is subjectively represented by some qubit state (1). Equivalently, the latter represent different points of view, from which behavioral alternative 0/1 can be considered. (1) pointing to the surface of the sphere represents the context of decision relative to behavioral alternatives 1 and 0 defining poles of the sphere. θ and φ are polar and azimuthal spherical coordinates.
At the moment of actual decision, however, one of the potential alternatives 0/1 actualizes while the other is irreversibly discarded. The basis alternative disappears and representation space collapses, so that different contexts and points of view cease to make their task-specific sense. The collapsing process can be visualized as projection of the initial vector (1) from the surface to the diameter of the Bloch sphere. For observers aware of the decision made, the final point is either the north or the south pole representing the actualized option. Otherwise, the point lies somewhere on the diameter of the Bloch sphere dividing it according to subjective judgment of probabilities. In the case of no bias, this position is given by probabilities (2) defined by orthogonal projection of vector |ψ to the diameter.
Partially-coherent context representation
The above model of pure, i.e. maximally coherent context representation is developed for an ideal behavioral case, exemplified e.g. by choice where to turn on a T-shaped crossroad made by a subject right on the spot. To account for realistic situations, this extreme is generalized at least in the following aspects.
Degree of subjective control
A subject's control over his behavior is not necessarily full. For exam-ple, upon approaching the crossroad a traveler may follow a navigator selecting either of the two options according to its program. In this case, the true subject is author of the navigation algorithm, while a person on the ground merely executes his decision. Resolution of such behavioral uncertainty is (partially) predetermined in advance and therefore is not (fully) affected by contextual information perceived by the traveler.
Cognitive fragmentation
A subject may be unable to fit all the perceived contextual information to a single cognitive representation (1). In the above example, the right track may have poor surface, while the left one may pass over a broken bridge. If these factors are not accommodated in a single mindpicture (also known as psychological gestalt Köhler (1992)), then the corresponding fragments i of a unitary context are mapped to separate cognitive representations |ψ i .
Under-defined basis
The target behavioral alternative generating context representation space itself can be ambiguous. For example, rainy weather favors going for mushrooms but is bad to mow hay, so that corresponding representations |ψ i of this context differ for different basis alternatives. Accordingly, when the behavioral basis is underdefined, the effective representation of contexts has to be averaged over multiple pure states analogous to the previous case.
In all of these cases, representation of the behavioral context does not lie on the surface of the Bloch sphere as shown in Figure 1. The first case is analogous to the already-made, but subjectively unknown decision considered in Sect. 2.1.2, so that corresponding context representation has to be located closer to the diameter of the Bloch sphere. Second and third cases require averaging over several context representations, leading to the similar effect called decoherence Zurek (1991). Corresponding representation of contexts requires extension of the pure case considered in Section 2.1 to the mixedstate formalism developed below.
Matrix formalism for incoherent representations
According to the above, the required generalization is expected to allow context representations to populate not only the surface of the Bloch sphere, but also its interior. This is achieved by extending pure state (1) to matrix form via the outer product of vector |ψ with itself where ψ| = |ψ † is complex-conjugate (Hermitian) transpose of |ψ . Diagonal elements of pure-state matrix (3) are decision probabilities (2), while its off-diagonal elements are cross-products of vector components. Going beyond the pure state limit is achieved by considering mixtures of several pure matrices (3). For example, describes projection of pure state (3) shown in Figure 1 to the diameter of the Bloch sphere. In general, any trace-one mixture of several pure represen- is valid context representation. Compared to fully decoherent (4) and pure state (3)
1 In optics, these values called Stokes parameters are used to quantify polarization states of light Mandel & Wolf (1995). For the pure state (3), these coefficients with R = 1 are Cartesian coordinates of the unit-length vector shown in Figure 1. For 0 < R < 1, point with coordinates (7) is located below the Bloch sphere's surface, while R = 0 corresponds to the center of the sphere and maximally incoherent state (4) with θ = π/2. Parameter R defining length of vector S thus quantifies coherence of the context representation (6). This is a third dimension introduced by matrix formalism in addition to spherical angles θ and φ defining pure state (1), (3).
Geometry of Stokes vectors allows to visualize mixing of several pure representations producing incoherent mixture described in Section 2.2.1. This is exemplified in Figure 2, where seven vectors |ψ i shown by black arrows uniformly occupy an arc on the Bloch sphere defined by azimuthal range 0 • ≤ φ ≤ φ max = 180 • and constant polar angle θ = 120 • . With identical weights w i , the resulting mixed stateρ (5) is shown by Stokes vector (7) depicted as gray arrow. Its Z component s z = − cos 120 • = 0.5 is the same as for all |ψ i , s y ≈ 0.46, and s x = 0 due to symmetry.
Qubit semantic space
In the model developed above, the Bloch ball functions as a subjective context representation space generated by a particular behavioral alternative with outcomes 1 and 0 defining the two poles. In this cognitive space, the contexts are represented by variables 0 ≤ θ ≤ π, 0 ≤ φ ≤ 2π, and 0 ≤ R ≤ 1 according to their subjective relation to the considered behavioral choice. In particular, polar angle θ quantifies subjective favorability of contexts for the potential decisions via probability relations (2), while radial dimension R accounts for mixing of several representations due to factors discussed in Section 2.2.1. This value-based representation qualifies the Bloch ball as a particular type of semantic space De Jesus (2018); Gärdenfors (2014); Kharkevich (1960); Kolchinsky & Wolpert (2018). Taken alone, polar and radial dimensions θ, R function within the classicalprobabilistic modeling paradigm, limitations of which are noted in the Introduction. However, quantum-theoretic structure of the qubit state space includes this pair only as a part of a broader spherical geometry where an additional, azimuthal dimension φ is indispensable. This results in unique features of quantum semantic model reported in this paper. Without loss of generality, these properties are described in the rest of this section for the case of maximal coherence with | S| = R = P = 1 (11).
Objective and subjective dimensions of the qubit semantic space
Qubit representational space is subjective by definition; in this space, both polar and azimuthal dimensions are not objective features of the contexts per se, but defined relative to the basis behavioral uncertainty within individual cognition of the considered subject. Still, in certain sense polar dimension can be called objective and azimuthal one can be called subjective. This difference in "second-order" subjectivity, fundamental for function of the qubit semantic space, is explained in this subsection. As expressed by relations (2), polar angle θ is one-to-one mapped to measurable decision probabilities p(i). Once the latter are known, θ is uniquely defined as 2arccos p(0) = 2arcsin p(1) with no interpretational freedom. In this sense, polar dimension of qubit space (1) is objective in nature. The same absence of interpretational freedom is fundamental feature of classical (Kolmogorovian) probability spaces, unambiguously defined by observable data. In fact, polar angle range 0 ≤ θ ≤ π is isomorphic to the diameter 0-1 of the Bloch sphere as shown in Figure 2(a) visualizing classical probability space of binary random variable 0-1.
Azimuthal dimension of the qubit semantic space is of different quality. As evident from Figure 1, azimuthal dimension φ of the qubit state (1) is orthogonal to Z axis and therefore does not enter decision probabilities (2) directly; for any θ (except degenerate cases θ = 0, π and R = 0) there is continuous range of possible representations with 0 ≤ φ ≤ 2π corresponding to the same decision probabilities p(i). In other words, azimuthal location of the context is not uniquely defined by observable behavior. Azimuthal phase φ thus functions as internal degree of freedom affecting the outside only indirectly through composition relations between different contexts illustrated below. This dimension of the qubit state space thus represents subjective aspect of semantics uniquely accounted by quantum approach.
Semantic triad
As noted above, "double-subjective" azimuthal dimension of the qubit semantic space does not affect observable decision probabilities as far as a single context is considered by any subject. It comes into play when several contexts have to be organized jointly in relation to the same decision alternative.
The minimal example is composition of three representations, enacted e.g. in perception of, and decision making in a novel context c based on known contexts a and b Surov (2020). This is realized via linear combinations of type called superpositions, where |ψ i are pure qubit states (1) and x a,b are complexvalued coefficients. In the composed context c, decision probabilities (2) given by polar angle θ c depend on azimuthal phases of vectors |ψ a and |ψ b , as well as on parameters x a,b . Simplest example of composition (13) is where zero azimuth φ = 0 is identified with representation |ψ a of context a, while φ = ±2π/3 correspond to contexts b and c. Vectors (14) form an equilateral triangle in the equatorial plane of the Bloch sphere.
Superposition of type (13) relate any three non-degenerate representations; this linear-algebraic feature of quantum states allows a subject to accommodate any number of contexts in a single qubit space, establishing subjective relations between them as explained in Section 3. Triple of representations (13),(14) thus functions as a minimal carrier of meaning, called semantic triad Surov (2020). Triadic nature of semantics and natural cognition in general (Sowa, 2000, ch.2) is the basis for the quantum process structure described in the following.
Process-based map of the qubit semantic space
This section specifies type of subjective relations between context representations accounted by azimuthal dimension mentioned in Section 2.3. The result is fully interpretable structure of the qubit semantic space.
Main principle
From the times immemorial, activity of humans was structured by cycles of nature. Hunting-gathering, agriculture, building, and other practices gave result only when performed in particular order synchronized with the year and day-night cycles. For every climate-geographical zone, this produced natural order of events violation of which threatened survival of individuals and species. Proper distribution of activities and resources over environmental cycles was therefore of vital importance. Process-based cognition of humans and other species developed to address this task by prognostic and planning activities Bubic et al. (2010).
Technology largely relieved us from environmental press, but not from the need for prognostic and planning activity; rather, in modern technogenic environment these tasks became even more critical and complex. On evolutionary scale, however, these changes happened nearly instantly. Modern human mind runs on the same neuronal hardware and uses the same cognitive heuristics as millennia ago Harari (2014).
Process cycle in azimuthal dimension Central idea of this paper is that cyclical processes of nature mentioned above are ingrained in human cognition to boost its prognostic capabilities. Common circular topology of these processes condenses to a universal process-based template shown in Figure 3(a), unconsciously shaping cognition and behavior of living organisms. This principle is readily incorporated in the quantum model of context representation developed in Section 2. In particular, cyclical process template is mapped to the azimuthal coordinate φ of the qubit semantic space as shown in Figure 3. The contexts are mapped to distinct ranges of φ according to their process-based functional relation to the basis behavioral alternative generating the qubit representation space. Logic of this mapping is explained in Section 3.2.
Discretization, process stages, and context classes Akin to other cognitive domains, continuous process dimension of the qubit semantic space is discretized to a limited number of (more or less) natural categories Rosch (1975) 2 . Accordingly, the contexts are sorted to the same number of processsemantic classes as in standard categorization tasks Rehder (2010); Vergne & Wry (2014), with central prototypes of the categories represented by vectors |ψ i as exemplified in Figure 3 In choice of the process categories, the simplest approach would be to divide the azimuthal dimension in the base of two, generating 2,4,8...-item taxonomies depending on the required detalization. Binary oppositions, however, do not align with triadic nature of subjective semantics; closed and stable semantic structures are formed not by pairs, but by triples of cognitive states represented by semantic triads of type (13) Surov (2020). In this work, azimuthal process dimension is discretized to six stages generating the same number of the process-semantic context classes. This number, located at the safe side of attention capacity for 7 ± 2 objects at once Miller (1956); Saaty & Ozdemir (2003), is chosen as balance between resolution and simplicity 3 .
Three primary stages
The basic day-night cycle structuring human activity (Section 3.1) has the following distinct stages: 1. The cycle begins in the morning that is a time to face novelty. Newly setting daylight facilitates assessment of the situation, recognition on problems and tasks to be addressed throughout the day.
2.
A midday is a period of maximum activity. In the pre-industrial age, daylight hours were the most conducive period for hunting, gathering, building, agriculture, and other vital activities.
3. The cycle is finished in the evening. Diminished working energy and lighting are appropriate for soft indoor activities like estimation of the results and preparation for the next cycle.
The year cycle is structured analogously with spring, summer and fall roughly corresponding to the above stages of the day. Winter (in the northern hemisphere) corresponds to night when cognition is shut down and activity is at minimum; this recovery period goes mainly in an automated mode with minimal behavioral optionality and decision making. Each of three cycle stages defines a specific class of contexts describing stage-specific activities. Accordingly to the description above, these classes are called Novelty, Action, and Result as shown in Figure 3(a) and have the following functions:
Novelty
Contexts describing new factors motivating the behavioral uncertainty resolved by a subject.
3 Refined structures like a clock with 12-mark dial might be useful for technicallyassisted cognitive applications akin to signal processing technologies Goodman & Silvestri (1970)
Action
Contexts describing activities realizing the considered decision.
Result
Contexts describing the outcomes, implications, and consequences of the considered decision.
According to Section 3.1, contexts allocated to either of these classes map to specific ranges in the azimuthal dimension of the qubit semantic space.
Semantic triad of main process stages In the simplest case, central prototypes of Novelty, Action, and Result context classes are represented by vectors |ψ nov , |ψ act , and |ψ res forming symmetric configuration shown in Figure 3(b). Choice of zero azimuth is a matter of convenience. This paper follows setting φ(N ovelty) = 60 • so that φ(Action) = 180 • and φ(Result) = 300 • .
Triple of vectors |ψ nov , |ψ act , |ψ res forms semantic triad described in Section 2.3.2, with composition rules (13),(14) reflecting relations between the process-semantic prototypes. In natural language, these relations are expressed by circular definitions of the basis context classes: 1. Novelty is a Result of previous Action; 2. Action is a move from Novelty to Result; 3. Result of Action leads to a potential Novelty.
Process-based classes Novelty, Action, and Result thereby form a minimal process-semantic taxonomy where each element is necessary to define the other two.
Three intermediate stages
In practice, Novelty is often not obvious; it results from diagnostics and/or analysis of the current state of affairs that is an elaborate process by itself Rasiel & Friga (2002). Similarly, Action does not follow the Novelty immediately, but requires setting goals regarding the newly identified factor and developing a plan for their achievement. The Result also does not follow Action at once. Usually, the first and major part of effort goes without any considerable outcome; when it arrives, the action moves to a distinct stage responding to the received feedback.
These three additional stages, further referred to as Sensing, Goal-Plan, and Progress, supplement the basic process structure shown in Figure 3 generating three new classes of contexts. This refinement of the process taxonomy is validated by distinctive difference of the new stages from three primary ones.
Relation to the primary stages Continuing the symmetric configuration shown in Figure 3(b), central prototypes of three intermediate context classes |ψ sens , |ψ gp , |ψ prog are positioned halfway between the primary ones as shown in Figure 4. Sensing thus falls opposite to Action, Goal-Plan is opposite to Result, and Progress opposes Problem, so that whereÛ is phase flip operator rotating the process stage by 180 • in the azimuthal dimension, realizing a particular kind of process-semantic negation.
In sum, azimuthal dimension of the Bloch sphere is now discretized to six process-semantic bands Sensing -Novelty -Goal-Plan -Action -Progress -Result covering azimuthal sectors of 60 • each. The same structure holds for incoherent context representations as described in Section 2.2.3. Stokes vectors S corresponding to each context class then occupy sector areas defined by the same range of the φ as for pure states, including interior of the circle shown in Figure 4.
Example
Organization of contexts based on this process structure is illustrated by the following example.
Consider a subject choosing whether to go for a PhD (1) or not (0). This binary alternative defines a Hilbert space for context representation described in Section 2. The following list exemplifies how the contexts are mapped to the azimuthal dimension φ of this space according to the scheme shown in Figure 4.
This range accommodates contexts pointing to the novelty that is addressed by the considered behavioral alternative. Inefficient behavior, wrong decisions, failures and defeats (likely resulting from previous actions) are placed here.
Cartesian axes of semantic space
Although qubit semantic space is more naturally introduced in spherical coordinates as it is done above, Bloch-sphere picture also allows to interpret is in terms of three Cartesian dimensions X, Y, Z indicated in Figure 1. Semantic function of these axes is outlined below.
Z axis: Evaluation
The contexts of each process stage are subjectively evaluated by personal measure of appropriateness (conduciveness, favorability) in relation to the considered decision. In the PhD example described above, entertainment can be considered as bad motivation for studying, in contrast e.g. to the need for skills and expertise. This subjective goal-directed estimation is quantified by probability of the positive decision p(1), computed from the polar coordinate θ according (2); both are lower in the first case and higher in the second. Both for coherent and incoherent context representations, the corresponding measure is Z component of Stokes vector −1 ≤ s z ≤ 1 defining decision probabilities as visualized in Figure 2(a). This identifies Z axis of the Bloch sphere as evaluative dimension in the qubit context representation.
By themselves, six process stages introduced above are neither positive nor negative. The corresponding representations |ψ sens , |ψ nov , |ψ gp , |ψ act , |ψ prog , |ψ res thus have s z close to zero, so that the process circle shown in Figure 4 lies near to equatorial XY plane of the Bloch sphere.
Y axis: Activity
Meaning of Y axis is obvious from definitions of the six stages and their mapping to the azimuthal XY plane shown in Figure 4. In accord with archetypal day-night and year cycles shown in Figure 3, maximally active Action context class opposes minimally active Sensing class. Y axis thus discriminates contexts according to the amount of associated (external) activity. Both in pure and mixed representations activity is measured by Y component of the Stokes vector −1 ≤ s y ≤ 1, so that horizon s y = 0 divides three active context classes Goal-Plan, Action, Progress from three passive classes Result, Sensing, and Novelty.
X axis: Potency
Horizontal axis in Figure 4 quantifies ability of the corresponding contexts to influence the whole process, and also behavioral freedom of the subject in these contexts. In a single word, this is further referred to as potency. Potency is at maximum between Novelty and Goal-Plan stages, where formulation of goals affects subsequent stages in the most profound way; at this point, a subject has maximal freedom to set direction of the process in deliberately chosen way. In contrast, after the Progress has been made, subsequent Result contexts unfold in largely predetermined manner, leaving to the subject a minimal freedom to change the course of events.
Both in pure and mixed representations, potency of a context is measured by X component of Stokes vector −1 ≤ s x ≤ 1 that in Figures 3 and 4 is positive on the left and negative on the right. Vertical s x = 0 divides positivepotency contexts where the activity is increasing and negative-potency contexts where the activity is decreasing. Accordingly, positive-activity contexts decrease potency, while negative-activity contexts increase potency. Fundamental role of this oscillation pattern in human cognition is further discussed in Section 5.
Experiment
The quantum process model of semantics described above is tested on natural language contexts pervading human cognition. The consideration is limited to single words being the most concise of linguistic contexts.
Process semantics of single words
Context-dependent semantics As noted in Section2.3.1, meaning of no context is defined by itself; it always requires broader context, within which it is subjectively perceived and made sense of. This is also the case for single-word contexts considered in this section.
Consider, for example, the word DOOR. When accompanied by the word broken, it can entail an option to fix it (1) or not (0), to seek the intruder (1) or not (0), and countless other basis alternatives in relation to which the DOOR context would be ascribed to the Problem-class. Alternatively, installation of the DOOR can be a Progress for building a house. Just as easy, opening or closing the door may take part in the Goal-Plan, Action, Result, and Reflection-class contexts both in positive and negative value.
Taken alone, the context DOOR thus bears little process information. Averaging over different usage cases degrades coherence of its representation by "cognitive fragmentation" and "underdefined basis" mechanisms described in Section 2.2.1. The resulting representation of the single-word DOOR context therefore lies close to the origin of the Bloch ball, having | S| = R 1 and purity (11) close to the minimum.
Average-stable semantics However, not all words are as neutral. Perception, Emergency, Idea, Strategy, Advantage, Outcome, Conclusion clearly classify to definite context classes described in Section 3, thus carrying reliable process information largely irrespective of their linguistic environment. Corresponding quantum-state representations are therefore expected to have high process-semantic coherence even after averaging over multiple usage cases.
This observation allows to study process semantics on the existing lexical databases like WordNet Miller (1995) and Word2vec Mikolov et al. (2013) that summarize statistics of words' usage from large corpora of texts. Further discussion focuses on Word2vec data that align with the dimensional semantic structure considered in this paper more directly.
Source data: word2vec Word2vec data contain high-dimensional vector representations w i of individual words and phrases w i , obtained from a neural network trained to predict their neighbors throughout the corpus of natural language texts Mikolov et al. (2013). This implies averaging of all available usage cases, erasing context-sensitive semantics as described above. The remaining average-stable semantics still reflects useful relations between words, so that for example This is the basis for expecting process semantics introduced in Section 3 to be found in the word2vec data. 300-dimensional vectors for 3 million of English words trained on the Google News corpus were taken from official source Google Code Archive (2013).
Building the qubit semantic space
Simplest way to observe process semantics in word2vec data would be to identify among 300 word2vec dimensions three corresponding to X, Y, and Z axes described in Section 3.3. However, this was not found possible; sorting 1000 most used English words by any of the first 10 word2vec dimension did not reveal any obvious regularity. Next, qubit semantic dimensions could be sought among the principal components of word2vec data. This also did not yield a result. Although the first several PCs do have interpretable meanings, the latter are not recognized as Evaluation, Activity, or Potency. In the 300 word2vec space, the process semantic axes are therefore not specific in their variance properties. They were identified with a different method based on the notion of semantic prototypes Lieto et al. (2017).
Z axis
Evaluation axis Z (Section 4.2.1) was found by requiring that average-stable positive and negative single-word contexts have positive and negative values of Z, respectively. Corresponding sets of four words for each evaluation extreme are listed in the first two lines of Table 1. Analogous to semantic differences (16), the requested axis was set to where W [i] are averages among four vectors within the positive and negative sets. For any word2vec word-vector w, evaluation is now determined as where dot denotes scalar product in 300-dimensional word2vec space. This calculation was tested on 1000 of the most used English words. Sorting them on the value (18) returned top five words being flag, salute, capable, god, champ, while five words with lowest s z are evil, dark, corrupt, rotten, greed. Figure 4.
Context class
Individual terms 1 good light well god 0 bad dark poor evil Sensing reflection deliberation expectation feeling perception intuition ponder observation rumination perspective attention insight prediction introspection Novelty factor issue shock surprise problem reason doubt query dilemma puzzle riddle mystery concern question Goal-Plan idea concept theory innovation strategy principle project design map plot motive intent purpose aim Action deal work compete cooperate engage solve maneuver implement execute fight manage strive construct develop explore Progress advance attain achieve gain regress accomplish fulfill produce increase earn yield recede output reach Result ending expiration completion harvest summation conclusion defeat victory score record final finish outcome aftermath
XY plane
The process semantic plane formed by X and Y axes was found as a single 300dimensional complex-valued vector Ω with real and imaginary components standing for Potency X and Activity Y dimensions of process semantics. Analogous to (18), any word2vec representation is mapped to this plane by taking scalar product of the corresponding vector w with Ω: where s x and s y are Activity and Potency components of Stokes vector (7) in the qubit semantic space representing a single-word context w in the quantum model described in Section 2. In particular, azimuthal phase φ computed as argument of complex-valued scalar product (19) determines position of the context in circular process dimension shown in Figure 4.
Vector Ω was found by requiring that relation (19) works for six context classes described in Section 3 of the main text. To that end, Sensing, Novelty, Plan, Action, Progress, and Result classes were each populated by 15 class-specific terms listed in Table 1. Average of the corresponding meannormalized word2vec vectors w in each class produced six 300-dimensional vectors used as word2vec representations of six context classes. Due to decoherence mechanism described in Sections 4.1 and 2.2, this averaging decreases norms | W k | relative to the mean-normalized individual terms with | w i | = 1 to | W k | = 0.53 ± 0.02. For vectors (20), proper categorization to the process stages implies that where expected azimuthal phases Φ k of process-class prototypes are taken from Figure 4. To satisfy (21), Ω was set to which essentially is two-dimensional generalization of (17). Justification of this choice is given in Supplementary Material.
Process-semantic map
Relations (18) and (19) allow to map any word2vec representation w to the qubit space of averaged semantics (Section 4.1). By construction, the obtained vectors s are identified with Stokes vectors (7) visualizing qubit context representations of limited-coherence. This procedure was applied to six process-semantic prototypes (20) including total of 90 individual words listed in Table 1.
Z position of process-semantic prototypes Z positions of six prototypes S k obtained from (20) and (18), −0.0075 ± 0.01, are practically equal to zero, as expected for evaluation-neutral process-semantic prototypes; the largest deviation of −0.04 is observed for the Novelty prototype populated with unbalanced negatively evaluated terms doubt, shock, problem, and issue. Smallness of Z positions allows reduces qubit semantic space to the process XY plane that is of primary interest. Corresponding positions of individual terms s and central-class prototypes S k are calculated as described in Section 4.2.2. The resulting graphic is shown in Figure 5. Table 1 to the process semantic plane Ω n identified in 300-dimensional word2vec space. Terms belonging to Sensing, Novelty, Goal-Plan, Action, Progress, and Result context classes are colored in cyan, blue, magenta, red, yellow, and green consistently with the above. Radii of color circles indicate coordinate variance of 1200 points within each context class as in Figures 5 and ??. Mean scattering of individual terms around their center-prototype vectors S k is 17 • on average. Figure 5, individual terms specific to each of six process-stage context classes Sensing, Novelty, Plan, Action, Progress, and Result are shown by cyan, blue, magenta, red, yellow, and green dots positioned in the XY plane by coordinates s x and s y found from (19). Large circles with radii r k = var(s k x ) + var(s k y ) equal to 0.14 ± 0.01 reflect scattering of the terms in each context class.
Scattering of individual terms In
Mean-class semantic vectors In the same color notation, vectors S k (21) are projections of mean word2vec prototypes W i (20) to the (normalized) process semantic plane Ω n . Azimuthal phases of these vectors deviate from the ideal center-class positions by 3 • on average. Together with nearlyidentical lengths | S k | = 0.33 ± 0.01 this indicates good agreement with the ideal symmetric scheme shown in Figure 4.
Phase-resolution quality measure Quality of process semantic map is measured by ability to correctly categorize an individual term based on its position in the angular dimension φ. This is quantified by standard angular deviation of individual terms φ k i from their center-class positions Φ k ∆φ = 1 6 where N = 15 is the number of terms per context class. Reliable categorization requires ∆φ to be less than half of angular distance between process stages The map in Figure 5 with ∆φ = 17 • satisfies this condition as seen from nonoverlapping scattering circles of the neighboring context classes. Tight layout of prototypes in Figure 5 supports choice of discretization of the processsemantic dimension motivated in Section 3.1.
Testing
Robustness and accuracy of semantic mapping procedure described in Section 4.2 was probed in the following tests.
Randomization
In this test, 90 terms listed in Table 1 were assigned to six context classes in random way. Word2vec representations in each of the obtained sets were averaged analogous to (20) to obtain six new prototypes W k . The latter were used to find the process plane Ω that would satisfy the phase requirement (21) in the same way as the original prototypes W k (22). All 90 terms were then projected to this new plane. As shown in Supplementary Material, randomization procedure degrades angular resolution (23) of the resulting map in drastic way. Thus, imposing the ideal azimuthal phases Φ k to the representation vectors in (21) produce the expected semantic structure if the latter is not supported by regularities in source data. This constitutes statistically significant evidence for existing of the expected process-semantic regularities among single-word contexts within English language.
Mapping of novel terms
In this test, 15 terms populating each context class according to Table 1 were divided to N seed and 15 − N probe items. The process plane Ω n was identified based on 6N seed terms, while the remaining 6(15 − N ) probe terms were mapped to this plane by the procedure used above. With seed size N = 3, that is, three seed terms per semantic class randomly selected from Table 1, this procedure was repeated M = 100 times. The resulting scattering of 6M (15 − N ) = 7200 probe terms is shown in Figure 6(a). For seed sizes N from 0 to 14, mean angular positions of M (15 − N ) points belonging to each context class agrees with the ideal values Φ k as in Figure 6(a). Angular resolution of the map, as expected, depends on N . When semantic prototypes W k are formed by randomly chosen N = 1 seed word each, the resulting map strongly depends on this random choice. This produces angular deviation (23) of 52 • below the threshold (23) that is insufficient for reliable process-stage categorization of individual terms.
Increasing of the seed size N suppresses this noise by virtue of more stable semantic prototypes (20). As shown in Figure 6(b), discrimination threshold (23) is reached near N = 4 when the mean scattering radius |R k | drops below one half on the mean amplitude | S k |. The map shown in Figure 6(a) is close to this borderline regime.
Self-organized semantic map
The qubit semantic space discussed above is remarkably close to the selforganized semantic map (SSM) build from single-word synonym-antonym relations via physical minimum-energy principle Samsonovich & Ascoli (2010). First agreement is dimensionality of the map. In SSM it was not restricted apriori, but determined empirically to properly account for similarity relations. 95% of the corresponding data variance is found representable in three dimensions, with distribution of 15 thousands of individual word vectors similar to the Bloch ball shape polarized in Z dimension (Figures 1 and 2 in Samsonovich & Ascoli (2010)). Second, three main SSM dimensions closely match the meaning of the qubit's Cartesian axes described in Section 3.3. Valence (good-bad), arousal (calm-exciting), and freedom (open-closed) dimensions of SSM correspond to Z (evaluation), Y (activity) and X (potency) axes of the qubit semantic space.
Semantic structures of verb contexts
The above results also agree with semantic structures of verb contexts discovered via multidimensional scaling of similarity grouping Wolff & Song (2003) and multi-language grammatical regularities Croft & Poole (2008). In the latter case, basis of the obtained two-dimensional space is formed by tense and aspect dimensions corresponding to the X and Y axes of the process-semantic plane. Namely, Future/Past related contexts are maximally/minimally potent, while perfective/imperfective contexts are minimally/maximally active. In Wolff & Song (2003), the obtained clustering of verbs into cause, enable, and prevent functional types realizes the main process-semantic triad shown in Figure 3. In terms of the authors Croft & Poole (2008), Figures 4 and 5 show universal conceptual structure relating the clustered situation types in full agreement with quantum semantic description.
Towards context-sensitive semantics
For both of the above approaches to semantic mapping, quantum theory offers fundamental explanation for the topology and structure of human representational space, established earlier by purely empirical means. More importantly, quantum approach opens a prospect for going beyond average-stable semantics accounted by SSM Samsonovich & Ascoli (2010) and classical approaches Croft & Poole (2008); Gärdenfors (2014); Osgood (1952); Osgood et al. (1957), that is a limiting case of context-sensitive word meanings in particular usage contexts. In the quantum approach, contextual subjectivity of is not a side effect, but the very essence of semantics indicated in the Introduction Surov (2020). Efficiency of the quantum qubit structure for this kind of context-sensitive semantic modeling follows from fundamental reasons discussed in Section 5.
Machinery of meaning
In Section 3, process structure of semantics is introduced via year and daynight cycles mapped to azimuthal dimension of the Bloch sphere. Possibility of this mapping can be seen as following from the equivalence of classical oscillation and precession of spin-1/2, shown in Supplementary Material. However, physical essence of quantum dynamics is different from classical case. This difference, lying in the core of quantum mechanics, is that qubit state accounts for potential future of the system, rather than to its actual properties like position and momentum described by classical mechanics and logic Aerts (2010); Baltag & Smets (2011); Gabora & Aerts (2005);Jaeger (2012Jaeger ( , 2017.
In semantics, this feature of quantum theory results in particular relations between uncertainty, process, and meaning described in this section. Quantum theory appears as a unique framework integrating these notions in strict quantitative terms. The concluding subsection 5.4 extends view of the qubit's geometry as an archetypal semantic structure pervading human cognition and culture as illustrated on several examples.
Task-oriented semantics
In the living nature, pragmatics of life limits allocation of scarce cognitive resources only to vital behavioral tasks to maximize probability of the desired events; from the start, meaning of cognitive and communicative symbols is determined by their practical use Glenberg (1997); Graben (2006); Greenberg & Harman (2009);Hadley (1989); Peirce (1997). Up to recent times, thinking of things out of direct survival value was a privilege of a few philosophers and scientists in the most prosperous societies. Even abstract philosophical thought, however, shapes the resulting theoretical paradigms, applied science and technology, eventually coming to the level of real decisions on the ground, irrespectively of whether this influence is realized or not.
Quantum model presented above subscribes for this pragmatic stance, so that meaning of a theory, idea, or any single factor reflected by human cognition is determined by how it contributes to resolution of a particular behavioral uncertainty. Recognition of this potentiality, the possibility of choice, on the background of reality is requisite for the very notion of meaning Frankl (1984); Sanz et al. (2012).
Consider for example the possibility to go fishing (1) or not (0). Then, • presence of hunger is important because fish is eatable and therefore can be used to resolve the problem; • the weather, season, and the daytime are important because they affect the biting; • distance to the lake or river is important because it defines the travel's cost; • trekking, seeking, camouflage, and other skills are important because the fish has to be found and outfoxed; • the fishing method is important because the pike does not bite on the bread; • facilities for accumulation, transportation, processing, and storage are needed because otherwise the product will go waste, and so on. Meaning of the hunger, weather, distance, skills, methods, and facilities is created and defined by their subjective value for the considered decision.
Semantic relativity
As indicated in Section 4.1, meaning of the same context-factors can be different for different behavioral uncertainties; meaning of the rain for fishing is not the same as e.g. for haymaking. This semantic relativity is at the core of quantum semantics, where the very Hilbert space used for context representation is constructed on the basis of particular decision alternatives. Quantum semantics is thus fundamentally contextual in drastic contrast with classical approaches mentioned in Section 4.4. Averaging over multiple bases destroys meaning of the most contexts, as in the rain example above. The remaining average-stable part (Section 4.1) is accounted by the classical notion of meaning considered as intrinsic property of contexts Osgood (1952). This objectified, absolute semantics is a limiting case of semantic relativity ingrained in the quantum approach. As in physics, this limit is achieved by averaging over «macroscopic» amount of individual usage cases as in the word2vec data used in Section 4.
Causality
Connection between process and meaning follows from the same pragmatic nature of human cognition referred to in Section 5.1; now, however, the essential aspect is that behavioral efficiency motivates cognition to work in causal-prognostic mode allowing for pro-active strategic behavior Barrett & Simmons (2015); Barsalou (2009) Perrykkad et al. (2021). Tasks ranging from maintenance of single-cell allostasis to cross-national cosmic missions require from subjects reflection of causal if-then links between goals, events, and environmental factors. For successful outcome of the considered task, meaning of a particular factor or event then is determined by its function in multistage, goal-oriented causal chain of process stages. The process sequence then functions as a meaning-generating structure in cognition of a subject.
Exactly this approach is formalized in the quantum model of context representation. In the fishing example above, contextual factors are organized by the process-stage sequence shown in Figure 4. Stages of this structure are linked by causal relations so that each stage is allowed by the previous and necessary for the following one. Namely, hunger -Novelty -is only possible if perception, expectation, or prognosis took place at Sensing stage; subjective Goal regarding this novelty is the object of Planning stage taking into account weather, distance, time, and other factors. The plan allows for Action, Progress, and Result stages to which methods, skills, and facilities contexts are mapped.
In the above list, importance (i.e. subjective value -meaning) of each contextual factor is explained after beCAUSE flag, stressing the fundamental role of causality in human thought Chalmers (2011). The following part of each sentence refers to a particular fragment in the causal structure of the fishing process. In this manner, each represented factor is linked to others via the part-whole relations essential for semantic phenomena Stadler (2020).
In Whiteheadian terms, process-semantic representation of information corresponds to the type of perception called «causal efficacy», identified as fundamental mode of cognition in nature Chater & Oaksford (2013); Shalizi & Crutchfield (2001); Whitehead (1929); Young (2016). It opposes «presentation immediacy» denoting passive, abstract information unrelated to any subjective goal. This latter case corresponds to the object-based representation mode addressing actual, static states of nature, where objects are related by correlation instead of causality Bareinboim & Pearl (2016); Pearl (2000); Pearl & Mackenzie (2018). In the above experiment, raw word2vec data W k are of «presentation immediacy» type, while vectors S k shown in Figure 5 are their (average-stable) causal-semantic counterparts (cf. semantic pointers of Crawford et al. (2016)).
Objective restrictions on semantic subjectivity
As indicated in Section 2.3.1, process-semantic representation is subjective in nature. Meaning of the same information is different for different subjects, so that semantic relativity discussed above includes subject-to-subject variation Kelly (2005). In the same example, for someone who knows nothing about fishing, feeling of hunger has no relation with the fish, lake, and other contexts mentioned above. Alternatively, a subject might try to get a salmon from a water well if his personal theory predicts this possibility.
The latter example shows that subjective causal structures can be both correct and incorrect. Faulty theories ignoring objective causality decrease efficiency of behavior, providing a feedback for the learning process van Ments & Treur (2021). An experienced fisherman, as any other professional, is bound to respect regularities of nature involved in his activity. The latter restrict subjective cognitions to a limited range of objectively efficient process-semantic causal structures.
Unifying quantum structure
As follows from Section 5.1, meaningful information necessarily refers to a particular decision alternative with (objectively) observable outcomes. Taken alone, the process-based representation discussed in Section 5.2 therefore does not make sense out of data; to be meaningful, it should be supplemented with a dimension encoding value of information for the target decision alternative. This is achieved by vertical (θ, Z) dimension of the qubit semantic space. Although represented by orthogonal spherical coordinates, objective and subjective aspects of meaning (Section 2.3.1) are therefore inseparable; linear and circular dimensions of qubit state space carry semantics only in pair.
Geometry of the qubit semantic space thereby establishes relation between process and uncertainty -two fundamental concepts of natural science. This relation is seen right in Figure 1, where diameter of the Bloch sphere represents classical Kolmogorovian probability space of binary uncertainty Kolmogorov (1956); equator of the sphere represents (virtual) oscillatory process subjectively associated with the basis distinction, as envisioned in Kauffman & Varela (1980). Qubit representation space thus can be seen as development of circumplex models of cognition Bezembinder & Jeurissen (2003); Fabrigar et al. (1997);Nagy et al. (2019);Tracey (2000), capturing the process aspect of semantics.
Neural substrate
Qubit representation of contexts has similarity with the neural-based model of intellectual operations Sokolov (2001a,b). Akin to the latter, qubit representation of contexts can be seen as universal mechanism encoding excitation of the corresponding neuronal ensembles as vectors within interpretable spherical space. Points in the Bloch ball then map to the surface of a fourdimensional hypersphere considered by Sokolov. Via this mapping, quantum approach accompanies model Sokolov (2001a,b) with semantic perspective explicated in this Section, cf. Vartanov (2011). Specific encodings for actual and potential types of information, distinguished in the quantum approach and further discussed in the Section 6.2, are observed on the neurophysiological level Abe & Lee (2011) in the Rock-Paper-Scissors game. In agreement with Section 2.3.2, the latter exemplifies minimal three-context setup requiring context-sensitive cognition Basieva et al. (2019);Falk et al. (2021).
Archetype of meaning
As a fundamental template of human cognition, qubit semantic space has properties of Jungian archetype Frye (1957);Jung (2014). Though Jung was aware of cyclical processes of nature ingrained in human mythology and psyche, his list of archetypes (Anima, Animus, Hero, Enemy, Wiseman, etc.) only contains static entities. By virtue of its process aspect, qubit semantic structure extends classical notion of the archetype to the dynamical realm.
Archetypal qualities of the qubit semantic structure
Qubit semantic structure has the following distinguishing features of classical archetype:
Empty-form universality
Archetypes are empty forms filled by situation-specific content in each individual life, remaining useful in different circumstances across epochs. This agrees with the function of qubit semantic structure applicable to any binary decision, not even necessarily human: adequate reflection of the goal-related factors enabling correct behavioral prognosis is beneficial to any individual.
Unconscious nature
This basic quality of archetypes explains robustness and speed of their operation by impossibility of conscious control. Archetypes are not consciously learned or individually invented, but inherited from the ancestors as hard-wired cognitive patterns. In the case of qubit semantic structure grounded in oscillatory neurodynamics, this property is taken to the extreme, since cognition in other anatomical basis would amount to inventing a different form of life. In this respect, qubit semantic structure is more fundamental than social-and personalityrelevant archetypes.
3. Simple and intuitive By virtue of unconscious basis, archetypes have simple and intuitive use. On conscious level, they are easily understood e.g. as folk tale characters and their roles Booker (2004). Similarly, simplicity of the qubit semantic structure stems from the basic regularities of nature it reflects Piantadosi (2020). Binary alternative 1-0 abstracts basic duality of human nature exemplified by oppositions of good-bad, up-down, do-not do, etc. Circular dimension is easily grasped from ubiquitous oscillatory processes observed in daily life; this is the basic «causal topology» Chalmers (2011), an innate «theory of causality», explaining ease of causal learning and thinking Goodman et al. (2011), Section 5.2.1. In particular, azimuthal phase φ of the qubit semantic space literally corresponds to the phase of a (virtual) context-organizing process, as it would be said in plain non-scientific English and Russian.
Geometrical expression
Empty-form universality mentioned above is conveniently expressed in geometric form, establishing relations between abstract elements that are instantiated only in each particular case. Such archetypal schemes called mandalas, reflecting traditional views of nature, are known in big variety Brauen (2009) 4 . Qubit semantic structure operates in similar way. This paper essentially expounds a single stereometric mandala shown in Figure 1, visualizing innate human structure for representation of semantics Zhuge (2010).
Dynamical nature of the qubit semantics complements classical archetypes of static kind. Akin to thematic/semantic roles Feldman et al. (2020); Rissman & Majid (2019); Schank & Abelson (1977), the latter facilitate fragmentary recognition tasks, while the process-causal relations between them are accounted by process dimension of the qubit semantic structure. This process-based embedding does not override innate representations for objects, actions, and places Gärdenfors (2014), but integrates them even across object-specific domains of experience (Carey, 2009, ch.6). With Lakoff's invariance hypothesis Lakoff (1990) extended to the process domain, models for analogy and metaphoric cognition Gentner (1983); Gibbs (1992)
Examples
Story structure As any archetype, qubit semantic structure pervades human culture. However, contrary to static archetypes, it can not be recognized in discrete characters, situations, and events. Rather, process aspect of the qubit semantic space shapes the narrative in fiction, movies, and artwork. In particular, classical set of screenplay acts Setup -Development/Confrontation -Resolution Field (2005); Seger (2010) reflect the basic triad of process stages shown in Figure 3(a). Further discretization, limited by capacities of human attention as mentioned in Section 3.1, is done in many ways Brütsch (2015). The difference between alternative approaches is illustrated by six-and sevenstage categorizations Introduction of setting and characters -Explanation of a state of affairs -Complicating action -Ensuing events -Outcome -Ending Bordwell (1985), Weakness and Need -Desire -Opponent -Plan -Battle -Selfrevelation -New equilibrium Truby (2008), both of which map to the process semantic structure shown in Figure 4 in obvious way.
Organizing contexts according to this system amounts to narrative-based representation of the world Akimoto (2021); León (2016) as manifested in stories from ancient myths to present-day movies Booker (2004); Truby (2008); four types of mythos, namely Comedy -Romance -Tragedy -Irony/satire, map to four seasons of the year, each further represented by sequence of six phases Frye (1957), (Lucas, 2018, ch.2). Distilled form of this «dramatic code» is seen in scientific writing, where navigation in the process semantic dimension is facilitated by paper structure.
In metaphorical manner, the archetypal story structure translates from the journey of a fairytale's hero to the «archetypal customer journey» addressed by significant sector of data science van der . In this view, the classical product life-cycle curve Cao & Folan (2012) is projection of the circular phase-plane process trajectory to the activity dimension.
Outlook
As noted in the Introduction, this paper expands boundaries of the classical approach to cognitive modeling to access subjective dimension of meaning. This section provides a broader perspective of the achieved result facilitating further steps in this novel terrain. Section 6.1 outlines methodological difference between classical and quantum approaches to semantic modeling. Section 6.2 discusses practical implications of this difference.
Object philosophy Object philosophy sees the universe as composed of discrete entities, whereas processes are derivative notions labeling motion of entities in space. Ascending to ancient Greece and Egypt Schrödinger (1954), this philosophy epitomized in Newtonian and statistical mechanics. In both, nature is a set of inert bodies, or particles, interacting by contact forces; following deterministic laws, ensembles of particles are defined by positions, velocities, masses, pressures, and temperatures. Existing independently of measurement procedures, the latter exemplify static, objective quantities constituting classical description of nature. As illustrated by classical part of natural sciences, this approach effectively reveals quantitative regularities of inert matter.
Process philosophy Process philosophy, in contrast, comprehends nature in terms of continuous dynamics of transformation and change embodied by substances and objects, specification of which is of secondary importance Shaviro (2014); Whitehead (1929). This view of nature, preferred in non-European cultures Harrison (2013); Maffie (2013), is suitable to discover qualitative regularities of the living Nicholson & Dupre (2018). Theories of human nature and the associated practice systems developed in the East constitute humanitarian science and technology parallel to their «hard» counterparts of Western kind.
Integrative quantum view Quantum process semantics incorporates both object-and process-based views of nature. As indicated in Section 5.3.1, one side of the quantum model is an objective behavioral uncertainty bound to end in one of several alternative states; result of this experiment will be recorded in the environment, becoming objective property of nature verifiable by subject-independent measurement procedures. The choice, however, relies on the process-based logic of a subject representing the decision context not as actual thing in itself, but by relation to the potential future and other contexts via subjectively constructed virtual process. The two kinds of philosophy capture objective and subjective aspects of quantum semantics described in Section 2.3.1, cf. Mugur-Schächter (2002).
Account of both objective and subjective aspects of nature 5 explains universality of quantum theory valid both or inert particles and living organisms Aerts (1995); Atmanspacher et al. (2002); ; Khrennikov (2010); Mugur-Schächter (1993); ; Peres & Zurek (1982); Wendt (2015). Methodology of quantum behavioral-semantic Table 2: Properties of objective and subjective aspects of information. Meaning arises from combination of the two, where subjective process structure is used to organize contexts in relation to objective behavioral alternative. Corresponding mathematical structure is qubit state visualized in Figure 1. (2020); dropping of any of the two complementary aspects produces largely incompatible, marginal objectand subject-based worldviews of limited applicability Galton & Mizoguchi (2009) realized e.g. in classical physics and naive psychology Wellman & Gelman (1992). The former, objective «view from nowhere» description Nagel (1986) appears as a limiting case of subjective embodied cognition involved in active sense-making Clark (2019); Cosmelli & Ibáñez (2008); De Jesus (2018); Glenberg (1997); Pinker (2008); Wilson (2002), accounted by the developed model.
Practical perspective
Object-and process-based descriptions of nature involve specific types of information compared in Table 2.
Classical-objective informatics
Contemporary informatics embodies the mindset underlying natural science of 17-19 centuries. Its keystone element, the bit, represents dichotomic alternative in which 1 indicates presence of a particle, force, electric current etc, and 0 labels absence thereof (or vice versa). This is objective property of nature endorsed by the classical worldview; it is changed neither by composition of multiple bits, nor by subjective uncertainty about actual state of the bit represented by Kolmogorovian probability Kolmogorov (1956). As indicated in Section 6.1, objective information is appropriate to record actual states of nature Gärdenfors (2020); Kemp (2012), including objects and features like positions of bodies, velocities, mechanical forces, and other well-defined quantities (Whitehead, 1929, p.169), called by Einstein «elements of physical reality» Einstein et al. (1935); Khrennikov (2017); word2vec data w k i (20) (as well as other high-dimensional semantic representations Günther et al. (2019)) comprising averaged, decontextualized statistics of the words' use, are of this type. Information of this «presentation immediacy», objective kind, appropriate to simulate behavior of inert systems, dominates modern information technologies.
Limitations However, as mentioned in the Introduction, when applied to the living, non-predetermined behavior, objectivist simulation runs aground Kaehr (2017). The reason (Section 5.2) is that always subjective natural cognition, by design oriented towards causal-prognostic modeling of behavior, works both with actual (context-independent) and potential (contextdependent) domains of nature. Accordingly, limiting the simulation to objective information is insufficient; it should be supplemented with subjective counterpart operating in the process representation mode Rowe (2005).
Transition to the novel type of information is naturally achieved in quantum computing, where electrons' spins, photons' polarizations and other spin-1/2 systems are encoded in qubit states (1), while processing is realized by the laws of atom-scale physics Jaeger (2019); Nielsen & Chuang (2010). As indicated above, this encoding accounts for potential states of the future that are intrinsically context-sensitive Jaeger (2012). The achieved «quantum supremacy» essentially results from this contextual information type Amaral Selesnick & Piccinini (2018), and mechanisms mentioned in Section 5.3.2. This uncertainty, however, does not interfere with methodology quantum cognitive modeling: as befits abstract information-level algorithmic description, this approach works well without specification of a hardware. Similarly to computer simulation of quantum phenomena routinely done in physics, quantum cognitive modeling is based on complex-valued linear algebra tractable by any laptop Abraham (2019); Johansson et al. (2013). Quantum-inspired algorithms implemented on classical hardware are the essence of quantum models of cognition and behavior mentioned in the Introduction.
Is Hilbert-space linear algebra «quantum» in nature? Not at all. It can be used with no reference to quantum theory altogether; the regularities discovered in quantum cognition could be found by blind search or automated discovery methods Alhousseini et al. (2019); Iten et al. (2020). Quantum approach to cognitive modeling simply takes advantage of mathematical structure better aligned with the nature of human cognition Longo (2003), further facilitated by solid conceptual structure of quantum theory. The latter merely serves as an algorithm developer's guide suggesting solutions and methods Manju & Nigam (2014); Montiel Ross (2020); Surov et al. (2021). This is another kind of the «quantum speedup» hardly suitable for quantification.
Towards semantic information science Quantum-semantic modeling compatible with classical computation hardware is not limited to elementary tasks considered above. As the concept of material atom opened the door for countless phenomena of physics, quantum-theoretic qubit structure is the key for process-semantic domain of nature. | 14,959 | 2021-01-01T00:00:00.000 | [
"Physics",
"Computer Science"
] |
Binding Curve Viewer: Visualizing the Equilibrium and Kinetics of Protein–Ligand Binding and Competitive Binding
Understanding the thermodynamics and kinetics of the protein–ligand interaction is essential for biologists and pharmacologists. To visualize the equilibrium and kinetics of the binding reaction with 1:1 stoichiometry and no cooperativity, we obtained the exact relationship of the concentration of the protein–ligand complex and the time in the second-order binding process and numerically simulated the process of competitive binding. First, two common concerns in measuring protein–ligand interactions were focused on how to avoid the titration regime and how to establish the appropriate incubation time. Then, we gave examples of how the commonly used experimental conditions of [L]0 ≫ [P]0 and [I]0 ≫ [P]0 affected the estimation of the kinetic and thermodynamic properties. Theoretical inhibition curves were calculated, and the apparent IC50 and IC50 were estimated accordingly under predefined conditions. Using the estimated apparent IC50, we compared the apparent Ki and Ki calculated by using the Cheng–Prusoff equation, Lin–Riggs equation, and Wang’s group equation. We also applied our tools to simulate high-throughput screening and compare the results of real experiments. The visualization tool for simulating the saturation experiment, kinetic experiments of binding and competitive binding, and inhibition curve, “Binding Curve Viewer,” is available at www.eplatton.net/binding-curve-viewer.
1 Solutions of differential equations and equilibrium concentrations Throughout this section, we describe the binding process initiated by mixing an arbitrary volume of protein with an arbitrary volume of ligand.This meant that there was no protein-ligand complex at the start of the binding process.The binding of the protein and ligand was 1:1 stoichiometry and had no cooperativity.In the dissociation process, we assumed that there was no rebinding.
Kinetics of the second-order binding process
The binding of the protein and ligand is described by the following equation,
PL
The concentration of the protein-ligand complex changes during the binding process and where the [P] and [L] are the concentrations of the unbound protein and ligand, the k on and k off is respectively the association rate constant and dissociation rate constant.The concentration of the total protein and ligand, [P] 0 and [L] 0 , and the concentration of the unbound protein and ligand, [P] and [L] are related by on d = [PL] 2 -( [P] 0 + [L] 0 + off on ) [PL] + [P] 0 [L] 0 The coefficients and discriminant of the right-hand side quadratic equation are = on d From the expression of [PL] 1 , we know that [PL] 1 > 0. When [PL] increases from 0 to [PL] 1 , decreases from the maximum value to 0, i.e., , the binding process approaches equilibrium, so .Thus, the above equation gives When t = 0, [PL] = 0. Thus , substituting the above equation gives
Thermodynamics of the second-order binding process
The equilibrium state of the binding process is described by the following equation, where the [P] eq , [L] eq , and [PL] eq is the equilibrium concentration of the unbound protein and ligand and the equilibrium concentration of the protein-ligand complex.The total protein and ligand concentration, [P] 0 and [L] 0 , and the equilibrium concentration of the unbound protein and ligand [P] eq and [L] eq are related by Thus, This equation is the same as the right-hand side of equation 1.2, its coefficients and discriminant are From the expressions of [PL] eq1 and [PL] eq2 , we know that 0 > [PL] eq1 > [PL] eq2 .We assume that the [PL] increases from 0 to the first real root to make the quadratic equation zero.So, [PL] eq1 should be the equilibrium concentration of the protein-ligand complex.It should be noted that the thermodynamic process of the binding reaction is independent of the initial concentrations of the binding species.Hence, we can calculate the total concentration of the protein and ligand from the initial binding system and use the approaches presented here to calculate the equilibrium concentration of the protein, ligand, and protein-ligand complex.
Kinetics of the pseudo-first-order binding process
The binding of the protein and ligand is described by the following equation, , the binding process is effectively first-order since the [L] is hardly affected by the [L] 0 ≫ [P] 0 binding process, then the equation can be transformed to
PL
The concentration of the protein-ligand complex changes during the binding process and During the binding process, , then The total protein concentration ([P] 0 ) and the concentration of the unbound protein ([P]) are related by Thus, When [PL] increases from 0 to [PL] eq , decreases from the maximum value to 0. and Because the right-hand side of equation 1.6 is greater than 0, When .Thus, , substituting the above equation gives Substitute equation 1.8 with equation 1.7 gives Define the observation rate constant k obs by
Thermodynamics of the pseudo-first-order binding process
The equilibrium state of the binding process is described by the following equation, [PL] eq where [P] eq , [L] eq , and [PL] eq are the equilibrium concentrations of the unbound protein and ligand and the equilibrium concentration of the protein-ligand complex.If , or strictly speaking, , .Hence, the [L] 0 is hardly affected by the binding process, then the equation can be transformed to The total protein concentration ([P] 0 ) and the equilibrium concentration of the unbound protein ([P] eq ) are related by Thus, In either the second-order binding process or the pseudo-first-order binding process, the [PL] eq is the same calculated by the thermodynamic and kinetic approaches.But the equations calculated from the second-order binding process are different from the equations calculated from the pseudo-first-order binding process.
Kinetics of the dissociation process
The dissociation of the protein-ligand complex with no rebinding is described by the following equation, The concentration of the protein-ligand complex changes during the dissociation process and . Thus, , substituting the above equation gives
association and dissociation
We simulated the competitive binding of association and dissociation with the denominator of the time step being 200,000 and 400,000 respectively in duration of shorter t 0.99 plus 10×longer t 0.99 (see Methods).The theoretical [PL] eq-theo was calculated by Wang equation 1 .In the competitive binding of dissociation, the volume ratio was 1, i.e., the volume of the protein and ligand was the same as the volume of the inhibitor.For example, in exp.No. 1d, after mixing, the total concentration of the protein, ligand, and inhibitor is 0.1, 1, and 10, respectively.The experiment conditions and results are shown in the Table S1 and S2.In all experiments, the difference between the [PL] eq-theo and [PL] eq-sim was less than 0.1% of the [PL] eq-theo .
Table S1.Comparison of the simulated [PL] eq and theoretical [PL] eq under four experiment conditions Exp.No.
Hypothetical association and dissociation kinetic experiments
We first demonstrated two ligands with the same thermodynamic property but different kinetic properties (Table S3).The ligand in experiment No. (hereafter referred to as exp.No.) 1 was fast-onfast-off, its k on was 1e6 M -1 s -1 and k off was 0. approached the [PL] eq .When the [L] 0 was the largest in exp.No. 5, the [PL] pseudo-eq and [PL] eq was the most approximate to each other.This was consistent with the condition "[L] 0 >> [P] 0 " of the pseudofirst-order binding process.As shown by exp.No. 5, 6, 7, and 8, increasing either the k on or k off by 10fold accelerated the binding process to 99% equilibrium, whereas increasing k on had a more obvious effect on the acceleration of the binding process.
For the ligand in exp.No. 1, the k off was 0.1 s -1 , the half-life for dissociation (i.e., ln(2)/k off ) equaled 7 seconds and the time to 99% complete dissociation equaled 46 seconds.For the ligand in exp.No. 2, the k off was 0.01 s -1 , the half-life for dissociation equaled 69 seconds and the time to 99% complete dissociation equaled 461 seconds.
Table S3. The association kinetic experiments in different conditions
Exp. No.
[P] 0 (nM) [L] 0 (nM) k on (M -1 s - 1 ) [PL] eq (nM) [PL] pseudo- eq (nM) t S3 and S4).The consistent t 0.99 suggested that the competitive binding process could be accurately approximated by numerical simulation.The simulations of four competitive binding experiments also showed that the errors between the simulated [PL] eq and theoretical [PL] eq were less than 0.1% of the theoretical [PL] eq in our default setting (Table S1 and S2).
We changed the concentrations and kinetic parameters in the competitive binding of association to compare the numerical simulation of the second-order process and the analytical integration of the pseudo-first-order process (Table S4).As shown in exp.No. 10a, we decreased the [P] 0 from 100 nM to 10 nM, which was less than the [L] 0 and [I] 0 , with the kinetic properties being constant, the equilibrium concentration ([PL] pseudo-eq ) of the protein-ligand complex of the pseudo-first-order binding process approached that of the second-order binding process (the theoretical [PL] eq ).The t pseudo-0.99 of the pseudo-first-order binding process also approached the t 0.99 of the second-order binding process.In exp.No. 11a and 12a, with the increment of the [L] 0 from 75 nM to 150 and 300 nM, and other parameters being constant, the t 0.99 decreased and the IC 50 increased.In exp.No. 13a and 14a, with the increment of the [I] 0 from 75 nM to 150 and 300 nM, and other parameters being constant, the t 0.99 also decreased.Compared with exp.No. 13a and 14a, the t 0.99 of the slow-on-slow-off inhibitors in exp.No.
15a and 16a increased.Furthermore, the larger the [I] 0 was, the less the t 0.99 was.The t 0.99 of the fast- No. 19d, 20d, 21d, and 22d.The t 0.99 being 0 meant that the instantaneous concentration of the proteinligand complex after 1:1 mixing with the inhibitor had already been in the range of [0.99×theoretical [PL] eq , 1.01×theoretical [PL] eq ].
Table S4. Competitive binding experiments of association and dissociation in different conditions a
Exp. No.
[P]0 (nM) [L]0 (nM) kon-inhibitor (M -1 s - a For easy comparison, the [P]0, [L]0, and [I]0 in the competitive binding of dissociation have been converted to the total concentration of the protein, ligand, and inhibitor after mixing in the volume ratio of 1.
[PL] curves in "Competitive Binding Kinetics -Dissociation"
showed S-shape in increasing concentrations of free protein The volume ratio of the protein and ligand to the inhibitor was 1, 10, and 100 in (A), (B), and (C).From (A) to (C), at the time of mixing, the concentration of the free protein increased.the inhibitor could bind more free proteins, so the concentration of the protein-ligand complex decreased more slowly.
In the competitive binding experiment, the binding of the protein and ligand and the binding of the protein and inhibitor are described by the following equations, The K d is the dissociation constant of the protein and ligand.The K i is the dissociation constant of the protein and inhibitor.At equilibrium, the total concentration of the protein ([P] 0 ) is the sum of the equilibrium concentration of the protein ([P] eq ), the equilibrium concentration of the protein-ligand complex ([PL] eq ), and the equilibrium concentration of the protein-inhibitor complex ([PI] eq ). (8.1) At equilibrium, [PL] eq (8.2) i = [P] eq [I] eq [PI] eq Equation 8.2 can be written as We substitute equation 8.3 into equation 8.1 and obtain [P] 0 = P eq + [PL] eq + [P] eq [I] eq i (8.4) We multiple on both sides of equation 8.4 and obtain Equation 8.5 can be transformed into equation 8.6 When 50% of the "initial binding" of the protein and ligand is inhibited, the concentration of the free competing inhibitor ([I] eq ) is defined as the IC 50 and the concentration of the total competing inhibitor ([I] 0 ) is defined as the apparent IC 50 .The initial binding means the equilibrium concentration of the protein-ligand complex in the blank control in the competitive binding of either association or dissociation.In association, the blank control was the mixture of the protein and the solution with ligand and no inhibitor.In dissociation, the blank control was the mixture of the equilibrated protein and ligand and the solution without inhibitor.The blank control is important to eliminate the equilibrium concentration change of the protein-ligand complex upon the volume change after mixing.At the equilibrium state of 50% inhibition of the protein-ligand binding, the concentration of the protein-ligand complex ([PI] eq-50 ) can be written as (8.7) [PL] eq -50 = [P] 0 [L] eq -50 In this work, we used the Wang equation 1 to simulate the theoretical inhibition curve, and estimated the IC 50 and apparent IC 50 (see Methods), without the restrictions of concentrations.[PL] eq -50 ≈ [P] 0 [L] 0 Thus, IC 50 is almost equal to [I] 0 .From equation 1.13, we know that in the absence of the inhibitor and when , the equilibrium concentration of the protein-ligand complex ([PL] eq-0 ) equals At the time of 50% inhibition of the protein-ligand binding, , so [PL] eq -0 = 2 × [PL] eq -50 K i in higher numerical precision (Figure S10).9 Protein and ligand with optimal K d showed the highest sensitivity in primary screen To theoretically access the sensitivity of the competitive binding assay in the primary screen, we conducted simulation experiments using different combination of the K d and K i .In experimental groups, after mixing, the initial working concentration of the inhibitor was 10 μM.The equilibrium concentration of the protein-ligand complex in blank controls ([PL] 0 ) was 3.0, 5.0 nM, and 7.0 nM, which was respectively 30%, 50%, and 70% of the total concentration of the ligand (10 nM).The K d was from 1 to 5,000 nM and the K i was from 1 to 10,000 nM.Both K d and K i were increased by a step size of 1, which resulted in a 5000×10000 K d -K i matrix.
Under the conditions of [PL] 0 = 3.0, 5.0, and 7.0 nM, the ratio of the equilibrium concentrations of the protein-ligand complex in experimental groups ([PL] eq ) to [PL] 0 are shown in Figure S11A-C.With the K d being constant, inhibitors possessing larger K i showed lower levels of inhibition (i.e., larger [PL] eq /[PL] 0 ).As the K d increased, the corresponding K i on each contour line first increased and then decreased.The increasing and decreasing trends were more obvious in the case of [PL] 0 = 7.0 nM.At a preferred level of inhibition, the K d corresponding to the largest K i is expected to represent the most sensitive configuration in the primary screen.We graphed the most sensitive K d at all inhibition levels (Figure S11D-F).We simulated a series of competitive binding experiments under different conditions.We kept the [PL] eq in blank controls 5.0 nM, half of the total concentration of the ligand (10 nM).The relationship between the equilibrium concentration of the protein-ligand complex in experimental groups and the concentration of the inhibitor under different K d and K i is shown in Figure S12.At lower K d values, the apparent IC 50 was closer to the IC 50 .When the [P] 0 was larger, the more inhibitors were needed to inhibit the binding of the protein and ligand.
Figure S12.
The inhibition curves under different experimental conditions.The total concentration of the ligand was10 nM.In blank controls, the [PL] eq equaled 5.0 nM.The units of all parameters in the legends were nM.
In this section, we reanalyzed some of the data from Jarmoskaite et al.'s radioactive binding assays 5 .In their affinity measurements, the labeled RNA was used as the fixed component, the concentrations of the RNA-binding protein Puf4 were varied.We used the kinetic parameters (in Table 2 of their paper) and related concentrations to calculate the time to reach 99% equilibrium at 25℃ and 0°C (Figure S13 and Table S5).We used the lower limit of the labeled RNA concentration (0.002 nM, see Figure 4 of their paper) as the initial concentration of the fixed component.The gradient concentrations of the Puf4 were 0.001, 0.01, 0.1, 1, 10, and 100 nM.The longest time to reach 99% equilibrium should be used as the incubation time.At 25℃ and 0°C, across all the concentrations of Puf4, the longest time was 3.03e+2 and 1.64e+4 s (i.e., 0.1 and 4.6 h) respectively.Our results of the analysis agree with their results in Section "Time dependence of Puf4 binding at 25°C and 0°C" (see Figure 4 of their paper).
Next, we analyzed the RNA concentration dependence of Puf4 binding at 25°C and 0°C.We used the lower limit of the labeled RNA concentration shown in Figure 6 of their paper as the initial concentration of the fixed component.The K d calculated by using the quadratic equation (in Table 2 of their paper) was used in our analysis.At 25°C and 0°C, the K d was 120 and 1 pM, respectively.Under different labeled RNA concentrations, the apparent K d s calculated by using Binding Curve Viewer were shown in Table S6.Users can easily compare K d and apparent K d with the tool.S6.
Figure S1 .
Figure S1.The relationship between k obs _fit/k obs and [L] 0 in the condition of [P] 0 = 100 nM, k off = 0.01 s -1 , k on = 1e5 M -1 s -1 and in different pre-equilibrium termination states of the kinetic experiments.
Figure S2 .
Figure S2.The relationship between k off _fit/k off and [L] 0 in the condition of [P] 0 = 100 nM, k off = 0.01 s -1 , k on = 1e5 M -1 s -1 and in different pre-equilibrium termination states of the kinetic experiments.
Figure S3 .
Figure S3.The relationship between k on _fit/k on and [L] 0 in the condition of [P] 0 = 100 nM, k off = 0.01 s -1 , k on = 1e5 M -1 s -1 and in different pre-equilibrium termination states of the kinetic experiments.
Figure S4 .
Figure S4.The relationship between k off _fit/k off and [L] 0 in the condition of [P] 0 = 100 nM, k off = 0.01 s -1 , k on = 1e5 M -1 s -1 and in different [L] 0 between two measurements of the kinetic experiments.The end-point measurement was 99% of the equilibrium.
Figure S5 .
Figure S5.The relationship between k on _fit/k on and [L] 0 in the condition of [P] 0 = 100 nM, k off = 0.01 s -1 , k on = 1e5 M -1 s -1 and in different [L] 0 between two measurements of the kinetic experiments.The end-point measurement was 99% of the equilibrium.
Figure S7 .
Figure S7.The binding processes in the same K d .
Figure S8 .
Figure S8.The binding processes in constant k off and changing k on .
Figure S9 .
Figure S9.Three screenshots of the customized webpage of Competitive Binding Kinetics -Dissociation.The concentrations of the protein and ligand were 200 and 150 nM, respectively.The k off of the ligand and inhibitor was 0.01 s -1 , the k on of the ligand and inhibitor was 1e5 M -1 s -1 .In each screenshot, the concentration of the inhibitor was 200, 2000, and 20000 nM in (A), (B), and (C).The volume ratio of the protein and ligand to the inhibitor was 1, 10, and 100 in (A), (B), and (C).From (A) to (C), at the time of mixing, the concentration of the free protein increased.the inhibitor could bind more free proteins, so the concentration of the protein-ligand complex decreased more slowly.
Figure S10 .
Figure S10.The relationship of the K i calculated by using the Wang's group equation and the [L] 0 in higher precision.
Figure S11 .
Figure S11.Competitive binding assays in the primary screen under different conditions.The initial working concentration of the inhibitor was 10 μM.(A-C) The contour lines and filled contours of the ratio of the [PL] eq in experimental groups to [PL] 0 under the experimental condition of the equilibrium concentration of the protein-ligand complex in blank controls [PL] 0 = 3.0, 5.0, and 7.0 nM in the K d -K i matrix.The points of the largest K i on each [PL] eq /[PL] 0 contour line were shown in blue, orange, and green line, which are magnified in Figure D, E, and F. (D-F) The relationship of the K d and the [PL] eq /[PL] 0 with the largest K i in the K d -K i matrix under the conditions of [PL] 0 = 3.0, 5.0, and 7.0 nM.It should be emphasized that each [PL] eq /[PL] 0 value corresponds to a K d value.
Figure S13 .
Figure S13.The screenshot of the Binding Curve Viewer -Kinetics of Association and Dissociation.The concentration of the labeled RNA was 0.002 nM.At 25°C (A) and 0°C (B), the time to reach 99% equilibrium in 2nd-order binding reaction was recorded in TableS5when the gradient concentrations of the Puf4 were 0.001, 0.01, 0.1, 1, 10, and 100 nM.
Figure S14 .
Figure S14.The screenshot of the Binding Curve Viewer -Determination of Dissociation Constant (K d ).At 25°C (A) and 0°C (B), the K d was 120 and 1 pM, respectively.The labeled RNA was used as the fixed component.The concentrations of the labeled RNA and apparent K d s were recorded in TableS6.
Table S2 .
Comparison of the simulated [PL] eq and theoretical [PL] eq under four experiment conditions Exp. No.
1 s -1 .Compared with exp.No. 1, the ligand in exp.No.2was slow-on-slow-off, its k on was 1e5 M -1 s -1 and k off was 0.01 s -1 .The K d of both ligands equaled 100 nM the same as the "K d in the K d and apparent K d can be shown in theoretical saturation curves" section in the article.In exp.No. 1 and 2, the [P] 0 equaled 100 nM, and the [L] 0 equaled 150 nM.In both experiments, the equilibrium concentration of the free ligand equaled the K d , i.e., [L] eq = 100 nM and [PL] eq = 50 nM.The time to reach 99% equilibrium in the second-order binding process (t 0.99 ) was 18 seconds and 177 seconds for exp.No. 1 and 2 respectively.If we calculated by using the pseudo-first-order binding process, the time to reach 99% equilibrium (t pseudo-0.99 ) was 18 seconds and 184 seconds for exp.No. 1 and 2 respectively.The ratio of the t pseudo-0.99 to t 0.99 (t pseudo- 0.99 /t 0.99 =1.06) was 1.04 for both exp.No. 1 and 2.In TableS3, as shown by exp.No. 2, 3, 4, and 5, increasing the [L] 0 with the other parameters being constant accelerated the binding process to 99% equilibrium, the t 0.99 decreased from 177 seconds to 30 seconds.From exp.No. 2 to 5, both [PL] pseudo-eq and [PL] eq increased and the [PL] pseudo-eq We conducted competitive binding experiments of association and dissociation by simulation (see TableS4).The association and dissociation experiments were specified by #a and #d, using a and d as suffix, respectively.In exp.No. 9a, the total concentration of the ligand and inhibitor ([L] 0 + [I] 0 ) was the same as the [L] 0 in exp.No. 2. Additionally, the kinetic and thermodynamic properties of the ligand and inhibitor in exp.No. 9a and the ligand in exp.No. 2 were the same.The time to 99% equilibrium (t 0.99 ) of the competitive binding in exp.No. 9a estimated by numerical simulation was the same as the t 0.99 of the association process in exp.No. 2 calculated by analytical integration (Table ) but was larger than the t 0.99 in exp.No. 13a and 14a (moderate-on-moderate-off).In contrast to exp.No. 15a and 16a, in exp.No. 17a and 18a, the larger the [I] 0 was, the larger the t 0.99 was.This suggested that although both ligand and inhibitor had the same thermodynamic property, the different kinetic properties (both fast or slow on and off) could prolong the equilibrium process of the competitive binding.Compared with exp.No. 19a, if we decreased the K d (exp.No. 21a) or K i (exp.No. 22a) tenfold or increased the [L] 0 tenfold (exp.No. 20a), the IC 50 increased similarly tenfold in each of the three experimental changes.From exp.No. 9a and 9d to No. 22a and 22d, most competitive bindings of dissociation had a larger t 0.99 than the corresponding competitive bindings of association, except exp.
Table S6 .
The apparent K d calculated by using Binding Curve Viewer under different experimental conditions. | 5,695.2 | 2024-05-08T00:00:00.000 | [
"Biology",
"Chemistry",
"Computer Science"
] |
HARMONIC AND INTERMODULATION PERFORMANCE OF ENVELOPE DETECTORS
Analytical expressions are obtained for predicting the amplitudes of the harmonics and
intermodulation products at the output of an envelope detector excited by a signal
formed of a carrier plus a number of sidebands. These expressions are in terms of the
ordinary Bessel functions with arguments dependent on the modulations indecies.
Comparison between results obtained using the proposed technique and previously
published results is performed to establish the accuracy of the proposed technique.
INTRODUCTION
Envelope detectors are widely used in electronic systems [1,2].While envelope detector circuits are generally simple, their analysis is not.This is attributed to the nonlinear characteristics of the diode(s) and the reactive components involved [3][4][5][6].Of particular interest here is the prediction of the harmonic and intermodulation performance of envelope detectors [7][8][9][10].This problem is of special interest in color- television reception where a vestigial sideband signal is demodulated by an envelope detector [8][9][10].
Using numerical methods, the nonlinear differential equation of a simple envelope detector can be solved in the time-domain.Then, applying FFT the output spectrum resulting from an input formed of a SSB plus carrier can be obtained [7].The method can be easily extended to predict the intermodulation performance of an envelope detector excited by a SSB plus carrier plus interfering signals.
On the other hand, through direct integration of the envelope detector output, closed-form analytical expressions, in terms of the complete elliptic integrals of the first and second kinds, can be obtained for the dc and harmonic contents [8].Alternatively, through the repeated use of power series expansions, approximate power series expressions can be obtained for the dc and harmonic contents of the envelope detector output [10].In both cases the input signal to the envelope detector is formed of a SSB plus carrier.
While the use of closed-form expressions, for evaluating the output spectrum of the envelope detector, is more attractive than numerically- based methods, it appears that the expressions obtained in [8] and [10] cannot be used for evaluating the intermodulation performance of the envelope detector.
Thus, there is a need for a new technique for predicting the output spectrum of an envelope detector excited by a carrier plus a number of sidebands.The technique would be attractive if it can yield closedform analytical expressions for the output dc, harmonics and intermodulation components.It is the major intention of this paper to present such a technique.
ANALYSIS
Figure 1 shows the phasor diagram of an input signal formed of a carrier plus a number of sidebands.At the input of the envelope detector, this signal can be represented by vi(t) V sin o + mk sin (Wo k) k=l (1) where Wo is the carrier frequency, Wo-Wk is the frequency of the k th sideband and V is the amplitude of the carrier.The output of the tort.,,x
FIGURE
Carrier and sidebands phasors at the input.
envelope detector can be expressed as where Ok COk t.
Eq. ( 2) can be rewritten in the form 2mimj cos (Oi-Oj)) ( where and Eq. ( 3) is in the form y (1 + x)1/2 (4) Eq. ( 4) can be approximated by a Fourier-series of the form N y= Co+ (Cn cos (--x)+fln sin (2-x)) where the parameters Co, cn and fin can be obtained using FFT algorithms or curve-fitting techniques.Alternatively, following the procedure described in [11] and [12], first the offset at x 0 is removed and the resulting function is mirror imaged to obtain a complete period of the periodic function f(x)=y- 1.Secondly, a number of data points is chosen and connected using straight line segments joind end to end as shown in Figure 2. Denoting the slope of each segment by "Yt, the parameters OZ n and n can be expressed as [11, 12] FIGURE 2 The function of Eq. ( 4) after removing the offset at x 0 and mirror imaging.
On '71 --'7L-1 + ('7l+1 --'7l) COS Xl+I (6) 2 (nn') 2 1=1 /3n 2 (n 7r) 2 ('71+1 'Tt) sin 2 Xl+I (7) k,l=l where T is the period of the periodic function.The parameter '7o can be easily obtained by calculating the area under the curve in Figure 2 using any numerical integration method.Thus, '70 can be expressed as 1(1 From ( 6) and ( 7) one can see that calculation of the parameters Cn and /3, requires only simple mathematical operations, without recourse to sophisticated algorithms for FFT or curve-fitting techniques.Also, inspection of ( 6) and ( 7) suggests that as n becomes infinite, the Fourier-series parameters c, and/3 always approach zero.In fact, the number of terms in ( 5) can be increased until the inclusion of the next term is seen to make a negligible contribution towards a best fit criterion; for example the minimum relative mean-square (RRMS) error.Table I shows the parameters of the first 21 terms of (5) used for approximating (4).
Using the parameters of Table I and Eq. ( 5) calculations were made and are summarized in Table II which shows the change of the RRMS error with the number of terms of the Fourier-series.It is obvious that increasing the number of terms improves the accuracy of the Fourier- series approximation.
HARMONIC AND INTERMODULATION PRODUCTS
One of the potential application of the proposed model of ( 5) is in the prediction of the amplitudes of the harmonics and intermodulations products at the output of the envelope detector.Thus, combining (4) and (5) and using the trigonometric identities sin (z cos b) 2 (J1 (2) cos t J3 (z) cos 3 q ---... and cos (z cos ) Jo (z) 2 J2 cos 2 + 2 J4 cos 4 where Jk(z) is the Bessel function of order k, and after simple mathematical manipulations it is easy to show that the amplitude of an output product of frequency E :=1 6k a;k + I 6ij 0" and order i=l,j=l,j>i I kl / r _l,j_,j>ilSej l, where 6k and 6/ are positive, negative integers or zeros, will be given by n=l k=l i=l,j=l,j>i Note that a unity is introduced into (11) to restore the removed offest at x 0. Eqs. ( 9) and (10) can be used for calculating the amplitudes of the harmonics and intermodulation products at the output of an envelope detector excited by a carrier plus a number of sidebands.
SPECIAL CASE
In this section the special case of an input signal formed of a carrier plus a single sideband will be considered in detail and the results will be compared with previously published results to establish the accuracy of the proposed technique.Under these conditions, the dc output component will be g(1 + m2) 1/2 + ao + n=l OnJo al (12) Ref. [8] Ref. [10] N= 31 N 21 N= 11 Vdc/V Using ( 12)-( 14) the output dc, fundamental and second-harmonic components can be calculated for any value of m.The results obtained for m 1, together with the results obtained using the techniques pro- posed in [8] and [10] are shown in Table III.It appears from Table III that the results obtained using the present technique are in excellent agreement with the results obtained using previously published techniques.This establishes the accuracy of the present technique.
CONCLUSION By approximating the envelope detector characteristic of Eq. ( 2), using a Fourier-series, analytical expressions can be obtained for the harmonic and intermodulation performance of an envelope detector excited by a signal formed of a carrier plus a number of sidebands.The Fourier-series coefficients and the amplitudes of the output components can be evaluated using simple calculations without recourse to numerical integration or FFT.Comparison with previously published results confirms the validity of the proposed technique.
TABLE II
Variation of the RRMS with the number of terms N
TABLE III
Comparison between previously published and present results | 1,804.6 | 1998-01-01T00:00:00.000 | [
"Physics"
] |
Financial Crisis and Impairment Recognition in Non-Financial Assets
Purpose – To analyse the impact of the financial crisis on the recognition of non-financial asset impairments in European listed companies. Theoretical framework – The study explores the impact of the theory of measuring the economic value of non-financial assets on managers’ decisions to recognize impairments, especially in the context of an economic crisis. Design/methodology/approach – Logit and ordinary least squares models were estimated to analyse the probability of recognition and the amount of impairment recognized, respectively, over a 10-year period. Findings – The results show that European companies recognized less impairments during the crisis, including companies in countries that have used external financial aid, suggesting that managers may use impairment recognition as a way of practicing earnings management. Research Practical & Social implications – The results are of interest to several stakeholders, namely: creditors, investors, financial market regulators, entities that prepare and oversee the application of accounting and auditing standards, and ultimately European leaders in terms of structural reforms and investor protection laws. Originality/value – The study contributes to the literature that analyses the impact of the financial crisis on the recognition of impairments in non-financial assets and, in particular, in the context of greater financial fragility. It also contributes to the literature on the use of discretion in the recognition of impairments and earnings management practices. Moreover, it adds to the theoretical debate regarding the principles of measurement in the context of impairment, and how this may affect assessments of the economic values of non-financial assets. Keywords – financial crisis ; European listed companies; non-financial asset impairments; earnings management.
Introduction
During 2008 and 2009, European companies faced probably the worst financial crisis ever. The 2008-2009 financial crisis, commonly referred to as the subprime crisis, led to strong turbulence in the financial markets and a sharp contraction of the economy, considered to be the largest economic contraction since the Second World War (Barth & Landsman, 2010). This crisis had a heavy impact on the European business environment, being considered by many as the worst crisis since the Great Depression of 1930 (Gunn, Khurana, & Stein, 2018).
Financial crises affect not only the financial sector, but also the business sector. According to Kousenidis, Ladas and Negakis (2013), financial crises affect firms through two interacting pathways: unfavourable macroeconomic conditions lead to a decline in firms' sales and level of operational performance; and the financial collapse of banking and capital markets limits financing opportunities by reducing firms' liquidity. Although financial institutions may have been the most affected by the 2008-2009 financial crisis, the effects of the crisis also spread to non-financial firms (Gonçalves, Gaio, & Robles, 2018). In this period, many companies had to review their businesses, as well as the value of their assets, since these might not have been reflecting their true economic value.
In fact, in periods of economic recession, there is a high probability of rapid deterioration of assets and the decision to recognize impairments is of the utmost importance, as negative changes in the economy (such as a financial crisis) are one of the external indications referred to in the provisions of IAS 36 -Impairment of Assets, which may imply lost economic return capacity of assets.
The consequences of macroeconomic changes, specifically turbulent economic periods, on the quality of accounting information are still poorly explored (Filip & Raffournier, 2014). Studies analysing the impact of the financial crisis on the recognition of impairments in non-financial companies and, in particular, in nonfinancial assets, remain scarce. Examples of these scarce studies are those of Vanza, Wells and Wright (2011), Wirtz (2013), Yammine and Olivier (2014) and Zhang (2011). Additionally, most of the literature focuses on analysing goodwill impairments, and the remaining non-financial assets do not tend to be investigated, despite their predominance among corporate assets. There are even fewer studies analysing companies in countries with greater financial fragility, which, as such, may feel the negative impact of a financial crisis on their performance levels and on the economic value of their assets more intensely. Examples of such studies are those of Albuquerque, Almeida and Queiroz (2011), Izzo, Luciani and Sartori (2013) and Sant'Ana, Gonçalves, Guerreiro and Nobre (2016). On the other hand, the scarce studies there are do not present consensual conclusions.
Thus, this study has two major objectives. First, it aims to analyse whether European listed companies recognized more impairments in non-financial assets during the 2008-2009 financial crisis, and if, when recognizing impairments, the amount considered, i.e. the magnitude of the impairment, was higher due to the negative consequences of the crisis. Secondly, it seeks to analyse the behaviour of companies from countries that resorted to external financial aid, specifically Greece, Italy, Ireland, Portugal and Spain (the so-called "PIIGS"). These objectives may be framed in the measurement theory, as they consider the intended effects (or not) of the recognition and measurement of impairments, in the context of a financial crisis, where the relevance of financial statements is subject to greater volatility.
A sample was analysed consisting of 1383 listed companies from 14 European countries and covering a 10-year period (2005 to 2014). In terms of methodology, logit and ordinary least squares (OLS) models were estimated to analyse the probability of recognition and the amount of impairments recognized, respectively, both for the total sample and for the two subgroups of countries: intervention and non-intervention.
The results indicate that during the financial crisis European firms recognized fewer impairments of non-financial assets, which may suggest that managers avoided recognizing impairments in order to perform better, using the discretion underlying the recognition and calculation of impairments to manage earnings upwards and thus mitigate the low performance characteristic in times of crisis.
Through the results obtained it is also possible to conclude that companies whose countries resorted to financial aid also recognized fewer impairments during the crisis period and that, unlike in the non-intervention countries, the level of enforcement of accounting and Cristina Gaio / Tiago Gonçalves / Anabela Pereira auditing standards was positively associated with the magnitude of impairments recognized.
The research findings are thus relevant both at the theoretical level and at the level of financial reporting practices. From a theoretical point of view, the evidence found allows for an understanding of the unintended effects of the measurement theory, regarding the recognition of impairments. Thus, in terms of measurement theory and the disclosure of relevant financial statements for the purpose of economic decisions, we found evidence of manager discretion that limits this relevance of financial information, especially when economic values are more volatile. We also contribute to the theoretical debate concerning the principles of measurement in the context of impairment, and how this may affect assessments of the economic values of non-financial assets. From a practical point of view, we contribute with positivist evidence that will inform regulators and investors about the economic relevance (or loss of this) of financial information on impairments, particularly in a context of greater volatility in the economy.
This study also contributes to the literature that analyses the impact of financial crises on the quality of financial reporting in general, and on the recognition of asset impairments in particular, essentially for two reasons: (1) most studies analyse the impact of the crisis on financial assets or goodwill (Carvalho, Rodrigues, & Ferreira, 2013;Glaum, Landsman, & Wyrwa, 2015;Zhang, 2011), whereas we analyse the impact on nonfinancial, tangible and non-tangible assets; (2) we analyse the impact of the crisis on a particular set of countries with greater financial fragility, i.e. the intervention countries. We also expect to contribute to the literature that analyses the use of asset impairment recognition in earnings management practices.
This study is divided into five sections. The second section provides a brief literature review, where we provide evidence of the main studies that support this research. In the third section the hypotheses of the study are formulated, the sample is described and the methodology adopted is presented. Section four presents and discusses the results obtained. Finally, the last section presents the main conclusions, limitations and possible suggestions for future research.
Impairment of assets and accounting information quality in the context of a financial crisis
The accounting concept of "impairment" can be defined as a reduction or loss of the recoverable value of an asset that should lead to an adjustment of its value to reflect its real economic return capacity. Companies must perform impairment tests whenever there is any internal or external event where assets may have lost economic value, with the exception of indefinite life intangible assets, which must be tested annually. Impairment losses must be recognized in the event that the book value of assets is greater than the estimated recoverable amounts. In other words, this procedure prevents assets from being overstated in the financial statements and underlies the objective of measurement theory to provide relevant information for the decision-making of the different users of financial information (Gonçalves & Coelho, 2019;Larson, 1969).
However, there is evidence of some conditional conservatism in the recognition of impairments in European listed companies, this being less expressive in countries where the effectiveness of institutions and the level of disclosure is lower (Amiraslani, Iatridis, & Pope, 2013;Pinto, Gaio, & Gonçales, 2019). In fact, in a study covering 235 European listed companies relating to 2011, the European Securities and Markets Authority (2013) concluded that few companies recognize goodwill impairment losses (only 36%), with recognition for other intangible assets being even more limited.
On the other hand, the fact that recognizing impairments and calculating the amount to be recognized involves value judgements and the use of estimates creates opportunities for managers to practise earnings management. There is empirical evidence that managers manage earnings by recognizing impairment losses and their respective reversals in subsequent periods (Duh, Lee, & Lin, 2009;Riedl, 2004). Earnings management through the recognition of excessive impairment losses and subsequent reversal may thus negatively affect the quality of the information reported by companies (Pinto et al., 2019).
The use of impairment recognition and its impact on accounting information quality may be even more evident in periods of financial crisis. In fact, the Financial Crisis and Impairment Recognition in Non-Financial Assets high volatility in financial markets and the substantial drop in company profitability and share values, which usually occur in periods of crisis, can cause losses in the economic value of assets and the need for recognition of impairment losses, with a subsequent negative impact on reported net income (Vanza et al., 2011). In periods of financial crisis, due to the increased asymmetry of information, assets tend to generate lower cash flows than expected, an effect that reinforces the recording of asset impairment (Amiraslani et al., 2013;Gonçalves, Gaio, & Lélis, 2020). Thus, a financial crisis can be considered as an indicator of impairment, since there may be a tendency for companies' assets to deviate from their fundamental value and not reflect their true value.
However, based on the discretion underlying impairment calculations, companies may take advantage of the time of crisis, and the greater market tolerance of low results, to recognize more impairments than necessary, enabling them to show to the market a slight recovery in the post-crisis period as they no longer have to recognize more impairments and/or reverse those they previously recognized in excess (Masruki & Azizan, 2012). Hassine and Jilani (2017) find evidence that French companies took advantage of the financial crisis to use goodwill impairment recognition to practise earnings management techniques such as income smoothing and big bath accounting. Also, based on an international sample, Glaum et al. (2015) conclude that there is scope for practising earnings management through the recognition of goodwill impairment losses in a context of financial crisis, even in countries with a rigorous level of enforcement in terms of the application of accounting and auditing standards.
The 2008-2009 financial crisis and the recognition of impairments
The 2008-2009 financial crisis, also known as the subprime crisis, was triggered by the bankruptcy of the US investment bank Lehman Brothers, which led to strong turbulence in the financial markets and to the spread of the crisis to many countries (Bordo, 2008). This caused a sharp contraction of the economy, both in the last months of 2008 and in 2009, representing the largest economic contraction since World War II (Barth & Landsman, 2010). In fact, this crisis had a strong impact on the European business environment and is considered by many as the worst crisis since the Great Depression of 1930 (Gunn et al., 2018). Amiraslani, Iatridis and Pope (2013) refer to a study conducted by Ernst & Young in 2010 on 60 European listed companies, which suggests that the increased financial instability experienced in Europe at the end of the first decade of this century may have contributed to the recognition of impairments. This is due to the high number of companies that reassessed their impairment test procedures, models and assumptions in order to reflect the lost economic value of their assets in a timely manner.
However, regarding goodwill, which is one of the most studied assets in the literature in terms of impairments, a study by PricewaterhouseCoopers (2011) reveals that less than half of European listed companies (about 40.1%) recognized impairment losses in goodwill in 2009. This result was not expected as, in periods of crisis, there is greater uncertainty and companies have to review their business plans and reduce their estimates of assets. Therefore, a greater recognition of impairments would have been expected, also due to the acquisitions that were made in previous years, when estimates of future cash flows were higher. Another conclusion of this study is that during the crisis period companies resorted to the discretion underlying impairment tests, with the aim of securing their market position and thus achieving the desired results, capital positions and financial ratios.
Of the still scarce studies that analyse the impact of the crisis on the recognition of impairments in non-financial assets, most do not find evidence of a positive association. Vanza et al. (2011) find no evidence that asymmetric information led to asset impairment recognition in Australian listed companies during the period from 2007 to 2009. Also, Wirtz (2013) shows that few companies recognized asset impairment losses during the financial crisis. The author also reveals that during the crisis auditors advised managers to recognize small impairment losses and more frequently, due to the greater scrutiny of financial statements. Yammine and Olivier (2014) study the impact of the financial crisis in terms of the recognition and magnitude of impairments, in a sample composed of listed companies from 17 European countries, for the time interval 2005-2011. The authors show that in the crisis period there was a decrease in the recognition of impairments, despite there being an increase in their magnitude. They argue that during the crisis period managers tended to resort to practising earnings management, in order to achieve a certain strategic objective and not show underperformance, and as such, avoid the recognition of asset impairments. They also concluded that, during the crisis, companies from countries with low levels of governance indicators, such as rule of law, legal transparency, quality of regulations, government effectiveness, and corruption index, decreased the recognition of impairment in order to prevent a reduction in results, which were already below normal due to the effect of the crisis. In turn, in the group of countries with a high level of governance indicators, there was an increase in the magnitude of asset impairments, as a way for companies to create reserves in the post-crisis period.
In turn, when analysing which factors led to the recognition of goodwill impairments, in a sample of listed companies from 21 countries covering the period from 2005 to 2011, Glaum et al. (2015) conclude that the timely recognition of impairments is associated with the level of application of accounting and auditing standards (enforcement). That is, companies in countries with a higher level of enforcement tend to recognize impairments in a timelier manner (before, during and after the crisis). On the other hand, firms in countries with a low level of enforcement tend to postpone the recognition of impairments. In addition, the authors conclude that there is room for earnings management, even in countries with a strict level of enforcement. Zhang (2011) also analyses the recognition of impairments in goodwill in listed companies in Germany and the United Kingdom, during the period from 2005 to 2010. The author concludes that during the crisis companies were less likely to recognize impairments in order to show better results and that the main determinant of the recognition of impairments was the companies' level of performance, measured by return on assets. More profitable companies tended to recognize fewer impairments and in smaller magnitudes. This can be explained by the fact that managers recognize impairments in order to achieve less unfavourable results.
The 2008-2009 financial crisis did not affect the different Eurozone countries in the same way and in some of them contributed to the development of a sovereign debt crisis (Huang, 2013). A sovereign debt crisis is mainly characterised by a reduction in the amount of credit available in countries and the existence of austerity policies. Due to high budget deficit and public debt levels, some countries, such as Greece, Italy, Ireland, Portugal and Spain, had to seek financial assistance from international institutions.
From 2010, the European Union (EU), the International Monetary Fund (IMF) and the European Central Bank (ECB) started to provide financial assistance to some countries, the so-called bailout countries. Greece was the first country to request assistance in 2010, followed by Ireland. The following year it was Portugal and Italy's turn, with Spain requesting help in 2012.
Analysing the recognition of impairments in non-financial assets by Portuguese listed companies in 2008, Albuquerque et al. (2011) verify that there were as many companies that recognized impairments as those that did not (47.6% against 52.4% of the sample, respectively) and that most impairments were recognized in the last quarter of the financial reporting period, as a consequence of possible earnings management. In addition, when analysing the recognition of impairments in Portuguese and Spanish listed companies, Sant'Ana et al. (2016) found an income smoothing effect through impairments, which was more pronounced in IBEX35 entities. Carvalho et al. (2013) study goodwill impairment losses in Portuguese listed companies from 2005 to 2012 in order to assess whether the 2008 economic crisis increased the frequency and magnitude of impairment losses. The results suggest that more profitable companies tended to recognize less goodwill impairment losses due to earnings management, while companies with negative results and lower goodwill are the ones that recognized more impairment losses. In addition, the results suggest that the financial crisis did not lead to a significant increase in goodwill impairment losses. Regarding the frequency of goodwill impairment losses, in 2011 and 2012 there was a higher number of these losses recorded, which suggests that recognition of impairments was not higher during the crisis but rather after three years. This is because the decision to recognize impairments may depend on economic and financial factors as well as management interests. Hayn and Hughes (2006) also conclude that impairment losses are only recognized three or four years after the respective impairment, but this can extend up to ten years.
In turn, when analysing listed Italian companies in the time interval 2007-2011, Izzo et al. (2013) found that in the first year of the crisis (2008) about 43% of the sample companies recognized goodwill impairment Financial Crisis and Impairment Recognition in Non-Financial Assets losses, while in the previous year only 19% had done so. In 2009, approximately 22% of the companies recorded a goodwill impairment loss, while in 2010 this percentage increased to 35%, and in 2011 it rose to approximately 60%, the highest value for the period analysed. In terms of the impairment ratio, which is defined by the authors as the ratio between the goodwill impairment loss and the book value of goodwill, the value increased from 1.73% in 2008 to 23% in 2011.
In short, although there are few studies that address the recognition of impairments in non-financial assets other than goodwill, especially in countries with greater financial fragility, such as the intervention countries, there is some evidence that the recognition of impairments can be used as a way to manage earnings in the context of a financial crisis. This therefore jeopardizes the objective of the measurement theory of providing relevant information for the decision-making process.
Research hypotheses
Although there are already studies that analyse the recognition of impairments of non-financial assets, there are still few that study the possible impact of the last global financial crisis, and the results found are mixed. Additionally, most of these studies analyse one asset in particular: goodwill. Wirtz (2013) and Zhang (2011) argue that in periods of crisis firms tend to recognize less or even avoid recognizing asset impairments. Yammine and Olivier (2014) highlight that during a financial crisis the recognition of asset impairments can be used by managers as a means to achieve their strategic objectives. Managers would be expected not to recognize impairments so as not to worsen the low performance that is characteristic of times of crisis, and to thus convey the image that they are performing better than they would if they recognized impairment losses. Thus, the first study hypothesis is formulated as follows: H1: During the financial crisis, firms avoided recognizing asset impairments.
The discretionary decision to recognize impairments involves not only their postponement (avoiding their recognition in moments of crisis), but also a reduction in the magnitude of impairments when they are recognized. Thus, we formulate an extension of Hypothesis 1 with regard to the magnitude of the impairments recognized: H1A: During the financial crisis, firms recognized a smaller magnitude of asset impairments.
In addition, we intend to analyse whether, during the crisis, companies in countries receiving financial aid also avoided recognizing asset impairments, given that these countries suffered the most from the crisis. Thus, based on studies that focus on some of the intervention countries, namely those of Albuquerque et al. (2011), Carvalho et al. (2013 and Izzo et al. (2013), which found that there were few companies that recognized impairments in assets during the crisis, and that some companies tended to postpone this recognition to the post-crisis period, the second hypothesis studied will be: H2: During the financial crisis, firms whose countries received financial aid avoided recognizing asset impairments.
Data collection and sample description
The firm-level financial data were collected from the Thomson Reuters database, while the macroeconomic variables (GDP and inflation) were taken from the Pordata database.
As in the study by Filip and Raffournier (2014), which analyses the impact of the financial crisis on earnings management practices in European listed companies, 2008 and 2009 are considered to be the crisis period, as it was in this period that there was the greatest turbulence in financial markets and the biggest economic contraction (Barth & Landsman, 2010;Bartram & Bodnar, 2009;Zhang, 2011), as shown in Figure 1. This decision makes our results directly comparable with other studies using the same crisis period.
The sample is composed of listed companies from 14 EU member states, covering the window from 2005 to 2014. The study period starts in 2005, since it was from January of that year that it was mandatory for all listed and consolidated companies in the EU to adopt the International Financial Reporting Standards. This guarantees that all the companies analysed prepare their financial statements according to the same standards and that the results obtained will not be affected by regulatory diversity between countries. Additionally, this time window enables a balance between the pre-crisis, crisis and post-crisis periods.
Cristina Gaio / Tiago Gonçalves / Anabela Pereira Financial sector companies were excluded from the sample given the specificities of their operations and financial reporting. Firms with insufficient data were also excluded from the sample. Thus, the final sample was composed of 1,383 companies and 13,830 companyyear observations. Tables 1 and 2 present the composition of the sample by country and by activity sector, respectively. The most representative countries in the sample are the United Kingdom with 21.33% of the total number of firms, followed by France with 18.73% and Germany with 15.11%.
Models and variables
Based on the work of Yammine and Olivier (2014), two empirical models were developed: a logit regression model (1) and an OLS regression model (2): The dependent variable used in model (1), IMP DUM, represents the decision to recognize impairment or not. Thus, IMP DUM is a binary variable that assumes a value equal to 1 when the company recognizes an impairment in assets (tangible and intangible, including goodwill), and 0 otherwise. The dependent variable used in model (2), IMP RACIO, represents the magnitude of asset impairment, measured by the ratio between total asset (tangible and intangible, including goodwill) impairments, net of impairment reversals, and total underlying assets.
The variable of interest, CRISIS, is also a binary variable that takes a value equal to 1 if the observation of firm i in year t belongs to the crisis period, and 0 otherwise. In this study, following similar studies, the peak of the financial crisis corresponds to the interval between 2008 and 2009. Based on the results obtained (2014), which suggest that in crisis periods firms are less likely to recognize impairments, the sign of the coefficient of the CRISIS variable is expected to be negative. The SIZE variable aims to control for the impact of firm size on impairment recognition, including the ability of the firm to apply more complex impairment testing procedures. Large companies have more resources to carry out more complex impairment calculations and tests and thus are more prepared to discover possible impairments and comply with regulatory requirements (AbuGhazaleh, Al-Hares, & Roberts, 2011; Giner & Pardo, 2015;Ramanna & Watts, 2012;Sant'Ana et al., 2016). Additionally, several studies show that asset impairments are more likely to occur in large firms (Kvaal, 2005;Saastamoinen & Pajunen, 2016). Thus, the sign of the coefficient of the SIZE variable is expected to be positive.
The DEBT variable intends to control for the effect of the level of debt on the recognition of impairments. Previous studies suggest that the association between debt and asset impairment recognition can be both negative and positive. That is, on one hand, more indebted firms may avoid recognizing impairments with the aim of not violating debt contract covenants (Hassine & Jilani, 2017;Ramanna & Watts, 2012), given that if the covenants are violated the firm may face several consequences, such as a bad reputation, greater difficulty in obtaining loans and higher financing costs. On the other hand, firms with higher debt levels may be under tighter control by creditors and investors, leaving less room for earnings management in impairment decisions (Elliott & Shaw, 1988;Korošec, Jerman, & Tominc, 2016;Saastamoinen & Pajunen, 2016;Strong & Meyer, 1987), which may lead to higher impairment recognition. Thus, we have no expectation regarding the coefficient of the DEBT variable.
Regarding the EBTI variable, it represents the result that would be reported if the firm had not recognized impairments. Kvaal (2005) argues that the association between this variable and the recognition of impairments reflects earnings management. Similarly to in the study by Yammine and Olivier (2014), this variable is only included in model (2). Firms that have higher impairment-adjusted earnings are expected to recognize fewer asset impairments, because impairments are an item that reduces the firm's earnings.
In terms of institutional and macroeconomic variables, the real gross domestic product (GDP) growth rate, the inflation rate (INF) and the level of enforcement of international accounting standards (ENF) were included in the models. To measure the level of enforcement of international accounting standards, an index was created, based on the work of Preiato, Brown, and Tarca (2015) for 2008, which reflects the level of enforcement of accounting and auditing standards. As Preiato et al. (2015) state, this index may be more useful and have greater explanatory power than those usually used in the literature, in that it is more focused and enables countries to be differentiated according to their enforcement capacity in terms of accounting requirements.
In countries where the level of enforcement is higher, companies recognize asset impairments in a timelier and more frequent manner (Amiraslani et al., 2013;Glaum et al., 2015), which can be explained by the reduction in earnings management practices (Houqe, Van Zijl, Dunstan, & Karim, 2012). Managers are encouraged to follow the expected accounting standards, and thus increase the accuracy of estimates and reduce analysts' uncertainty (Hope, 2003). Therefore, the higher the value of the enforcement index the more effective the enforcement practices are, and the higher the quality of information in financial reports. Assuming that firms may recognize more impairments than necessary in order to manage their earnings downwards (Yammine & Olivier, 2014), and since a high level of enforcement may be associated with a reduction in earnings management practices, a high level of enforcement is expected to lead firms to write off the additional amount recorded as impairment that was above what would be economically necessary (Yammine & Olivier, 2014). As such, we expect a negative coefficient for this variable. Finally, the SET dummy variable was introduced, in order to control for the effect of different characteristics at the industry level, as well as the COUNTRY dummy variable, which serves to control for the effect of different characteristics at the country level. A summary of the description, calculation, expected sign and literature supporting the choice of the variables is presented in Appendix. Table 3 presents the mean of the dependent and independent variables of the models for the crisis (2008 to 2009) and non-crisis (2005 to 2007 and 2010 to 2014) periods, for all firms (Panel A), for the firms in intervention countries (Panel B) and for the firms in non-intervention countries (Panel C).
Descriptive statistics
In panel A it can be seen that, on average, the value of asset impairments is higher in the crisis period.
Financial Crisis and Impairment Recognition in Non-Financial Assets
The ratio of impairments also presents, on average, a higher value in the crisis period (2.22%) in comparison with the non-crisis period (1.65%).
In panel B it is found that companies in the intervention countries present, on average, a significantly lower value of asset impairments in the crisis period (around 69%) than in the non-crisis period. During the crisis period, the intervention countries present an average impairment ratio of 0.82%, while in the non-crisis period this group of countries presents an average of 1.25%.
On the other hand, companies in non-intervention countries show higher average values in the crisis period, both in terms of amount and impairment ratio (Panel C).
Tests of equality of means of the dependent variables by period (crisis and non-crisis) and by country (intervention or non-intervention) were carried out. The results in Table 4 show that, for the IMP DUM variable, there are statistically significant differences between the crisis and non-crisis periods, suggesting that the probability of companies recognizing impairments is higher in the crisis period.
Regarding the analysis of intervention versus non-intervention countries, the results also suggest that the differences are statistically significant at the level of the IMP DUM variable, with evidence that the firms in intervention countries tend to recognize more impairments. Table 5 presents the matrix of correlations between the variables of the models. In general, the variables show a weak correlation, suggesting that there are no multicollinearity problems. Table 6 summarizes the results obtained for two different specifications of models (1) and (2), with and without the inclusion of the ROA variable, since the level of profitability is considered in the literature as an important determinant of impairment recognition.
Impact of crisis on impairment recognition and magnitude
We can see that when the dependent variable is IMP DUM, shown in columns 1 and 2, the CRISIS variable presents a statistically significant negative coefficient, which suggests that during the crisis period firms tended to reduce the recognition of asset impairments, thus validating H1.
The results also suggest that larger firms with higher debt levels were more likely to recognize asset impairments, which is consistent with the results obtained in previous studies (Glaum et al., 2015;Verriest & Gaeremynck, 2009;Zhang, 2011).
In line with the literature, the coefficients of the institutional and macroeconomic variables suggest
Nonintervention
When the dependent variable is the magnitude of recognized impairments, RATIO IMP, shown in columns 3 and 4, the results suggest no statistically significant association between impairment recognition and the crisis, thus not validating hypothesis H1A. Consistently with the results obtained by Yammine and Olivier (2014), the coefficient of the CRISIS variable presents a positive sign, suggesting that during the crisis period companies recognized a higher amount of impairments, but it is not statistically significant.
The inclusion of the ROA variable (ratio of net income to total assets) in both models, shown in columns 2 and 4, which is considered by many to be one of the main determinants of impairment recognition (Glaum et al., 2015;Zhang, 2011), does not change the previous findings. That is, the probability of recognizing losses during the crisis decreased and there is no evidence that firms recognized higher amounts of impairments in the crisis period. The higher the profitability of the firm, the lower the probability that firms will recognize impairments and the lower the magnitude of the recognized impairments, as according to Zhang (2011).
Finally, it should be noted that the adjusted R 2 of model (2), shown in column 4, increases substantially when the ROA variable is introduced, which reveals the strong explanatory power of the firm's performance level in relation to the magnitude of impairments recognized by European firms (Gonçalves, Gaio, & Santos, 2019). In sum, the results suggest that there is a lower probability for the recognition of impairments in periods of crisis, but it is not possible to conclude that the crisis had an impact on the magnitude of impairment losses recognized.
Intervention versus non-intervention countries
In order to analyse whether the probability of recognition and magnitude of impairments were affected by the crisis differently in countries that requested financial assistance, we divided the sample into two groups, intervention and non-intervention countries, and estimated models (1) and (2) for each group. Table 7 summarizes the results obtained.
The results are broadly consistent with those previously reported. In terms of impairment recognition, shown in columns 1 and 3, the coefficient of CRISIS is negative and statistically significant, suggesting that during the crisis firms tended to recognize fewer impairment losses, both in the intervention and nonintervention countries. This coefficient is, however, higher in the group of intervention countries, which may suggest that firms whose countries received financial aid were less likely to recognize asset impairments, thus validating H2.
Discussion of the results
The results obtained suggest that firms may choose not to recognize impairments in order to report "better" results, offsetting the economic difficulties experienced during a crisis and their negative impact on results. This is consistent with the results obtained by Zhang (2011) for German and UK listed firms, by Vanza et al. (2011) for German listed firms and by Yammine and Olivier (2014) for a set of European listed firms. The results are also consistent with those obtained in the study by PricewaterhouseCoopers (2011), which revealed that most European listed companies did not recognize impairment losses in goodwill during the crisis. The findings are also in line with those obtained in the study by the European Securities and Markets Authority (2013), which, based on the year 2011, concluded that few companies recognized impairment losses in goodwill, with recognition for other intangible assets being even more limited. In fact, there is evidence of a certain level of conditional conservatism in the recognition of impairments by European listed companies (Amiraslani et al., 2013).
Thus, in periods of crisis, companies may use the discretion and subjectivity underlying asset impairment recognition with the aim of delivering better results and not jeopardizing their market position. Consequently, there is scope for earnings management practices to minimize the effects of the crisis.
Additionally, the literature suggests that the market reacts negatively to announcements of the recognition of impairment losses, since their recognition means that the expected future economic benefits of investments in assets will not be fully realized (Sant'Ana et al., 2016, among others), which may contribute to decisions to avoid recognizing impairments in periods of crisis.
The results also suggest that larger and more indebted firms, which are under tighter control and scrutiny, are more likely to recognize impairment losses. Also, firms in countries where the level of enforcement of accounting and auditing standards is higher are marginally less likely to recognize impairment losses. This impacts the quality of financial reporting, consistently with a stream of literature that argues that the quality of institutional factors, such as the level of investor protection, the efficiency of judicial systems and the level of enforcement of accounting and auditing standards, lead to higher quality financial reporting, specifically in the recognition of impairment losses (Glaum et al., 2015;Yammine & Olivier, 2014).
The results of the comparative analysis between the companies from intervention and non-intervention countries reveal that the trend towards lower recognition of impairment losses in the crisis period occurs across all companies, reinforcing the previous findings. However, the results suggest a higher probability of not recognizing impairments in companies from intervention countries, where the greater scrutiny resulting from the intervention mitigates the opportunistic use of impairment recognition.
A higher tendency to avoid impairment recognition in the intervention countries is consistent with the results obtained in previous studies that have analysed goodwill impairment recognition in some of these countries, namely those of Albuquerque et al. (2011), Carvalho et al. (2013 and Izzo et al. (2013), which found that few firms recognized asset impairments during the crisis, and that some firms tended to postpone this recognition to the post-crisis period.
Robustness analysis
The results obtained are robust in terms of the absence of multicollinearity, as the correlations between the variables are low. Additionally, the large sample size adds asymptotic robustness to the data, and the residuals of the estimations performed follow the normality assumption.
Two additional analyses were also performed in order to assess the robustness of our main results. First, firms from the three most representative countries, the UK, France and Germany, were excluded from the sample. The results (not tabulated) are broadly similar to those obtained previously, reinforcing our main conclusion that there is a lower probability for the recognition of impairments in periods of crisis.
In the second analysis performed, only observations with impairments were considered. Again, consistently with the results of the main analysis, the CRISIS variable does not prove to be statistically significant (results not tabulated), thus we cannot conclude that the crisis affected the amount of impairments of European listed companies.
Conclusions
This study aimed to analyse the impact that the 2008-2009 financial crisis had on the recognition of impairments in non-financial assets by listed companies in the European Union. In addition, we analysed the particular case of countries that used the Economic and Financial Assistance Program (Ireland, Portugal, Spain, Italy and Greece), the so-called intervention countries.
The results suggest that European listed companies avoided recognizing asset impairments during the crisis period, which is in line with the findings of previous Financial Crisis and Impairment Recognition in Non-Financial Assets studies (Yammine & Olivier, 2014;Zhang, 2011), and that the magnitude of impairments recognized was not affected by the crisis, consistently with the conclusions reached by Yammine and Olivier (2014). These results may indicate earnings management practices to improve reported results in order to offset the negative effect of the financial crisis on firms' performance. That is, managers may use the discretion underlying the recognition and calculation of impairments to manage earnings upward and thus mitigate the underperformance characteristic in times of crisis, counteracting the intended effects of measurement theory regarding the disclosure of financial statements in a way that facilitates economic decision making.
It is also concluded that during the financial crisis years, the probability of recognizing asset impairments was lower, regardless of whether the company belonged to an intervention country or not. However, it should be noted that during the crisis firms in countries that received financial aid were less likely to recognize impairments than those in non-intervention countries.
We contribute to the scarce literature that analyses the impact of the financial crisis on the recognition of impairments in non-financial assets and, in particular, in a context of greater financial fragility. We also contribute to the literature on the use of discretion in the recognition of impairments and earnings management practices, with the resulting impact on accounting information quality.
Given that in periods of financial crisis assets may not truly and reliably reflect their future economic benefits, this topic is of great importance in the current context of financial reporting and has relevant practical implications. Thus, the results of the study are of interest to the various stakeholders in the financial reporting process, namely: creditors, investors, financial market regulators, entities that prepare and oversee the application of accounting and auditing standards, and ultimately European leaders with respect to structural reforms and investor protection laws.
The main limitation of this study is the lack of data, namely the impossibility of disaggregating the value of impairments by nature of assets. As future research lines, it would be interesting to consider other variables, such as the company's share price and variables related to the corporate governance system, as well as further studying the influence of macroeconomic variables on the recognition of impairments. Additionally, it would be interesting to analyse the same topic in the context of unlisted companies, given their predominance in the European business structure. | 9,724.4 | 2021-06-20T00:00:00.000 | [
"Business",
"Economics"
] |
Effects of heat treatment on microstructure and creep properties of a laser powder bed fused nickel superalloy
Nickel-based superalloy C263 has been consolidated with Laser Powder Bed Fusion (LPBF) with two perpendic- ular build orientations and exposed to either of two heat treatment programmes. This study analyses the effects of build orientation and heat treatment on the resulting microstructures produced in LPBF C263 variants, evalu- ated against a cast equivalent. Results show that although a strongly anisotropic microstructure was present in standard heat-treated (HT1) LPBF material, this was eradicated following an alternate heat treatment regime (HT2) through recrystallisation, aided by high local strain. Subsequently, their mechanical properties have beenassessedbymeansoftheSmallPunch(SP)creeptest.Acontrastingpresenceof Σ 3formationswasobserved between the two LPBF heat treatment programmes with the resulting random grain boundary network (RGBN) revealingshorterpotentialintergranularcrackpathsintheHT2material,althoughgrainboundarycarbideswere found to be the dominant strengthening mechanism for improved creep resistance. Adapted Wilshire equations have been implemented to predict the long-term creep lives of the C263 variants and their apparent activation energies have been determined.
used to life variants of Ni-based superalloy C263 produced via laser powder bed fusion • A method of statistically measuring connectivity of the random boundary network is described and correlated to creep response • Grain boundary carbides were found to be the dominant strengthening mechanism for improved creep resistance • Higher temperature solution heat treatments were found to alleviate microstructural anisotropy produced in the LPBF process G R A P H I C A L A B S T R A C T a b s t r a c t a r t i c l e i n f o
Introduction
Additive manufacturing (AM) is a process that has advanced significantly over the last decade due to its potential for considerable cost benefits in terms of lean manufacture and complex component design for a range of industrial applications. Extensive research has been conducted on a range of AM processes to assess the influence of the process inputs upon structure and properties in metallic components [1,2]. One such process is Laser Powder Bed Fusion (LPBF). Typically, LPBF exhibits features such as epitaxial grain growth promoting textured microstructures parallel to the build direction and in some cases residual stresses due to the high thermal gradients present in the process [3,4]. Postprocessing techniques can be applied in an attempt to alleviate some of the residual stresses, anisotropic microstructure and directional properties present after the process, typically through optimised heat treatments [5].
Ni based superalloys are prominently utilised for applications within aerospace and industrial gas turbine engines where good mechanical properties are required at high temperatures. Much of these high temperature properties are derived from γ' precipitates, with superior creep rupture strength influenced by grain boundary carbides [6,7]. In particular, the Ni based superalloy C263 gains a large proportion of its high temperature properties from a fine globular dispersion of Cr-rich M 23 C 6 carbides, typically precipitating following casting or as a result of heat treatments [8]. However, the successful precipitation of this phase following an AM processing route is yet to be determined in this alloy.
Given the anisotropic microstructure and dependence on geometry in the LPBF process, representative mechanical testing of such material can prove difficult. Moreover, the abundance of process parameters exacerbates constraints on the availability of LPBF processed alloys. Therefore, a more feasible option for mechanical testing needs to be applied. The Small Punch (SP) test is a small-scale mechanical test technique involving the biaxial deformation of a miniature disc specimen. Originally developed in the 1980s for remnant life assessments of alloys in the nuclear industry [9], it has since been applied across a wide range of materials, including single crystal nickel alloys [10], steel weldments [11] and intermetallic compounds [12]. The benefits of employing this approach for AM material stems from the ability to test small volumes of material, with the possibility of extracting specimens from discrete locations [12].
The purpose of this study is to evaluate the effects of build orientation and post-process heat treatment on the microstructure of C263 produced via LPBF. Various microstructural considerations have been explored such as grain boundary features and texture through electron microscopy. The influence of microstructural dissimilarities on mechanical performance was assessed with the SP creep test method. In particular, the effect on apparent activation energies for creep across each C263 variant was investigated after applying a modified Wilshire equation lifing approach.
Material
Five C263 build variants were the focus of this study. A nominal chemical composition of this alloy is summarised in Table 1. Four LPBF variants were built using an EOS M270 machine from gas atomised powder, with parameters that are broadly in line with industry. However, specific process parameters are considered proprietary. Two were consolidated with a horizontal (0°) build orientation and two with a vertical (90°) build orientation, as illustrated in Fig. 1. Two specimens from each orientation were exposed to either the standard heat treatment programme for C263, HT1 [13], or an experimental heat treatment schedule including a higher temperature solution heat treatment, HT2, as detailed in [14]. This higher temperature was implemented to recrystallise the microstructure and remove the as built texture. Deposition parameters were identical across LPBF builds. Cast C263, heat treated with HT1 was also examined as part of this study to allow comparisons with LPBF variants. Due to the strong bimodal nature of the cast microstructure and the anisotropic columnar grain structure in the HT1 0°material, the elliptical fit method was used for a more accurate representation of grain size and aspect ratio in these variants. Grain size and aspect ratio measurements of all other variants were collected through the mean linear intercept method. Both methods excluded twin boundaries in recrystallised grain size calculations. Grain data for each C263 type is listed in Table 2.
The LPBF SP specimens were extracted from the threaded ends of conventional test specimens which had been turned to Ø9.5 mm. Cast C263 SP specimens were taken from extruded cylinders, removed from larger sections via wire electrical discharging machining (EDM) as shown in Fig. 1c. In each instance the Ø9.5 mm cylinders were sectioned into approximately 800 μm slices, before being ground by progressively finer silicon carbide abrasive papers to the required specimen thickness of 500 μm ± 5 μm with a 1200 grit finish, in line with the recommendations defined in the European Code of Practice for Small Punch Testing [15].
Small punch creep test
SP creep tests were performed on a series of high temperature SP creep frames developed at Swansea University, in accordance with the Code of Practice [15]. In this arrangement, the miniature disc specimen is located between an upper and lower die, securely clamping the specimen in place. Loading was typically applied through the central axis of the rig via an upper load pan arrangement, in line with a 2 mm diameter hemispherical ended Nimonic 90 punch. Heat was applied using a single zone digitally controlled furnace and was maintained to within ±1°C of the test temperature of 780°C. The temperature was constantly monitored throughout the test by two Type K thermocouples located in a drilled hole in the upper die, close to the surface of the disc. Two linear variable displacement transducers (LVDTs) were utilised at either side of the disc to monitor the displacement; one transducer located below the load pan to measure the displacement upon the top surface of the disc, the other transducer measuring displacement directly from the base of the disc via a quartz rod.
Microscopy
All microscopy was performed on sectioned and mounted specimens from each C263 variant, polished to a mirror finish. Large scale optical micrographs were captured for each variant and selected areas were scanned using Electron Backscatter Diffraction (EBSD), conducted on a Hitachi SU3500 Scanning Electron Microscope (SEM) operated at 20 kV and 100 μA. Data for grain size, texture, local misorientation and random grain boundary network analyses were collected through EBSD. Carbide micrographs and Energy Dispersive X-ray Spectroscopy (EDS) data for carbide type determination were collected using a JEOL 7800F Field Emission Gun (FEG) SEM and Oxford Instruments SMax 50. Fig. 2a. This plane is orientated normal to the loading direction during SP testing. The IPF map disclosed in 2b highlights the bimodal microstructure apparent in the cast C263 variant; grain measurements for which are reported in Table 2. Bands of finer grains containing Σ3 boundaries sit amongst significantly coarser grains with no special boundaries. Fig. 2c and d presents the microstructures and crystallographic orientations of the HT1 0°and 90°LPBF variants respectively. Fig. 2c exhibits a strongly anisotropic and elongated microstructure associated with this heat treatment and build orientation (0°), typical of LPBF consolidated material [1,13]. The 90°counterpart shows a seemingly equiaxed grain morphology perpendicular to the columnar grain length, as shown in Fig. 2d, providing an insight in to the three-dimensional microstructure of HT1 variants. Table 2 provides grain size measurements and, more importantly, grain aspect ratios, used to quantify the extent of elongation in these materials. Aspect ratios further from 1, associated with HT1 0°C263, and what would be HT1 90°on the longitudinal plane, numerically identify that a columnar grain structure exists. IPF maps and IPFs in Figs. 2c and 3b respectively show that a strong 〈101〉 texture parallel to the TP (Z) normal is present in the HT1 0°variant, with HT1 90°builds having a preferential 〈001〉 and 〈101〉 crystallographic orientation, as shown in Figs. 2d and 3c.
Grain structure & texture analysis
IPF maps for HT2 LPBF variants are displayed in Fig. 2e for the 0°b uild direction and 2f for the 90°orientation. These two maps of the HT2 material show a more equiaxed microstructure, as seen in the aspect ratios reported in Table 2 of 0.23 and 0.94 for HT1 0°and HT2 0°respectively, as well as a higher proportion of annealing twins. Concomitantly the grains have a smaller average local misorientation spread of 0.19°for HT2 90°compared to 0.47°average kernel average misorientation (KAM) for HT1 90°, Table 2. Both indicate that the higher heat treatment HT2 was successful in recrystallising the as-built columnar microstructure. Fig. 2e and f also shows how recrystallisation has given rise to the abundance of Σ3 annealing twins in HT2 microstructures, comparably with the finer cast grains seen in Fig. 2b, which is reflected in the Σ3 proportions presented in Table 2, e.g. b1% Σ3 proportion for HT1 90°compared to 67.7% Σ3 proportions for HT2 90°. Additionally, Fig. 3 shows a reduced overall texture in both build directions for the HT2 variants, with IPF maxima reducing from 4.64MUD in HT1 0°to 1.92MUD in HT2 0°and from 2.30MUD in HT1 90°to 1.71MUD in HT2 90°.
Random grain boundary network
For high temperature deformation mechanisms such as creep, it is common for failures to occur in an intergranular manner [16]. Typical defects such as pores and lack of fusion can be found in LPBF materials, which can then have a detrimental effect on mechanical properties [2]. Nevertheless, these features were uncommon in the materials in this study. As such, the grain boundary character is considered as the main parameter for potential crack paths. Interfaces between special boundaries, such as Σ3s and grain boundaries can inhibit intergranular failure by retarding or diverting crack growth [17,18]. The Random Grain Boundary Network (RGBN) may be considered the preferential path for crack propagation where intergranular failure is the dominant mechanism [19,20]. As such the RGBN has been quantified.
EBSD data was used to highlight Σ3 boundaries, selected according to the Brandon criteria [21], on a plain mapped background. ImageJ digital image processing, specifically the 'Find Connected Regions' plugin [22] was used to measure the RGBN through determining the average grain boundary segment length in microns for each sample, as displayed in Fig. 4 and reported in Table 2. The data clearly shows that the cast variant has a larger grain boundary average segment length, 267.3 μm linked to the bimodal nature of the microstructure. The main difference in grain boundary connectivity is between the HT1 (Fig. 4a, b) and HT2 variants (Fig. 4c, d). Both the HT2 0°and 90°samples have shorter random boundary line segments of 17.6 μm and 13.6 μm respectively compared to 86.0 μm and 74.0 μm for HT1 equivalent and is linked to the Σ3 boundary proportions. As a result, the RGBN for HT2 has become more disrupted in comparison to the HT1 samples.
Local misorientation
It has been discussed that residual stress is commonly manifested in LPBF components; a detrimental characteristic which requires postprocess relieving. This has therefore been assessed in terms of internal microstructural strain across all variants, given in Table 2. KAM maps have been produced to provide a visual representation of local misorientation within variant microstructures, translating in to strained regions. These are given in Fig. 5, showing only the 0°orientation for LPBF variants.
The KAM map in Fig. 5a reveals that strained regions lie predominantly within the larger grains of the cast bimodal structure, concentrating as horizontal bands. The smaller of the two-grain types contain little indication of local misorientation. The HT1 0°KAM map in Fig. 5b displays an obvious array of local misorientation distributed within all grains of the observed area, averaging at approximately 0.33°. However, Fig. 5c appears to show reduced local misorientation for the HT2 0°variant, with an average of 0.20°.
Carbides
As a further investigation into grain boundary influences, carbide distribution between C263 build variants has been considered. Micrographs in Figs. 6 and 7 exhibit differences in carbide formation across the material variants. Fig. 6a and b shows clear precipitation of grain boundary carbides in cast C263, with Fig. 6a displaying coarser Ti-MC and Mo-rich M 6 C type carbides of various sizes [23]. As expected for cast material, a fine globular dispersion of Cr-rich M 23 C 6 carbides form as discrete particles of approximately 300 nm in diameter at grain boundaries. In contrast, the micrograph of the HT1 variant in Fig. 7a shows little evidence of grain boundary carbides forming. Instead, there appears to be a fine dispersion of Ti and Al segregates suspended in the γ-matrix with an average diameter of b0.1 μm. Whereas HT2 shows evidence of carbide formations (Fig. 7b), mainly of the Ti-MC and Mo-rich M 6 C types [23]. Nevertheless, some Ti and Al segregates can still be found within HT2 grains as in HT1 variants. Fig. 2; a) cast, b) HT1 0°, c) HT1 90°, d) HT2 0°, e) HT2 90°. Fig. 8 illustrates the experimental data generated for the HT2 0°variant at 780°C through the SP creep test, showing itself to be an effective method to distinguish the sensitivity of C263 to load at high temperature, with the shortest rupture times for the highest loads. The response is comparable to that from uniaxial creep tests with an initial decaying displacement rate during primary deformation, followed by an accelerating tertiary phase where displacement rate increases until rupture.
SP creep
The Wilshire equations are a contemporary creep lifing methodology that originates from the assumption that t f → 0 as σ → σ TS while t f → ∞ as σ → 0 [24]: where σ is the applied stress, σ TS is the ultimate tensile stress, t f is the time to rupture, Q c ⁎ is the apparent activation energy for creep, R is the gas constant (8.314 J·mol −1 ·K −1 ) and T is the temperature [24]. The parameters Q c ⁎ , k 1 and u are then derivable from a relatively comprehensive set of rupture data as is the case here. However, for this research the fundamental Wilshire equation is adapted and normalised through load as opposed to uniaxial stress, meaning t f → 0 as F → F m while t f → ∞ as F → 0: where F is the applied load and F m is the ultimate load from a small punch displacement controlled test. F m values for these materials are found in the authors' previous work [14]. Fig. 9 presents the load-time to rupture results along with the as-determined fits from the modified Wilshire equations; the apparent activation energies for the alloy variants are given in Table 2.
Recrystallisation
IPF maps of LPBF variants in Figs. 2 and 3 have established that complete recrystallisation has been achieved as a result of the higher temperature heat treatment programme (HT2). In order for recrystallisation to occur, an appreciable degree of temperature and deformation is required to activate the process, where the recrystallisation temperature is dependent on the amount of strain already present in the material [25]. KAM data reported in Table 2 show that local misorientation is noticeably reduced in HT2 C263 compared to the HT1 microstructure. Therefore, it has been established that the deformation present in HT1 is an additional driving force for recrystallisation, in line with previous research [25]. Fig. 5a is illustrative of this phenomenon, as congregations of finer recrystallised grains in the cast microstructure follow bands of high local misorientation. Furthermore, these grains also contain little deformation as this strain has been relieved, or contributed to recrystallisation, as is the case in LPBF variants.
Random grain boundary network variation
The majority of recrystallised grains in cast and HT2 variants contain annealing twins (Σ3s). Increasing Σ3 proportions has been shown to improve grain boundary sensitive properties by becoming incorporated into the random boundary network and acting to impede the transport of cracks along it [17]. This has led to the use of the connectivity of the RGBN as a measure of the degree of disconnection of the higher angle grain boundaries. However, a quantitative method for reporting RGBN connectivity has yet to be agreed upon. Therefore, an image processing methodology is described in Section 3.2. The average RGBN segment lengths, reported in Table 2 and shown in Fig. 4, reveal that the increase in Σ3 proportions between the HT1 and HT2 microstructures has resulted in a reduction of RGBN average section length from 86 μm for HT1 0°to 17.6 μm for HT2 0°for example. Therefore, crack propagation would be more difficult for a more disconnected random boundary network such as those in HT2 samples. This is supported by the creep data shown in Fig. 9 where the two HT2 samples show a higher load required for similar rupture times compared to the HT1 material.
Carbide morphology and distribution
Carbide distribution has been considerably influenced by the processing route and heat treatment of C263. Carbides found in cast C263, as in Fig. 6a and b, do not appear in HT1 LPBF variants, even though the same heat treatment has been applied, alternatively leaving a fine dispersion of Ti and Al segregates suspended in the γ-matrix. M 23 C 6 and M 6 C carbides typically precipitate from the breakdown of coarser MC carbides [23]. MC carbides largely form during the melt of a given process or as a result of high temperatures in a supersaturated solid solution [23]. In the case of LPBF, the rapid heating and solidification [2,3] would limit the time at liquidus compared with a casting process, narrowing the window for MC carbides to form, rendering limited opportunity for the precipitation of other carbide types. The Ti and Al segregates have likely formed as a result of microsegregation in interdendritic regions from the rapid solidification process [4,25]. In HT2 variants, MC and M 6 C carbides have precipitated. The higher temperature solution heat treatment for these variants have encouraged the growth of MC carbides from what is likely a supersaturated solid solution, developing in to M 6 C carbides following ageing. The higher temperature heat treatment has also resulted in a reduction in Ti and Al segregates by dissolving them in the γ-matrix by solid-state diffusion or by their reaction to contribute to MC carbides. Fig. 8 shows the SP creep results for the C263 alloy variants with the cast material displaying the greatest resistance to creep loading. HT2 variants exhibit a significantly reduced resistance although similar to one another, followed by a further reduction in HT1 0°and finally the least resistance shown by HT1 90°. This trend is supported by the microstructural analysis in terms of grain size, texture, RGBN and carbide formations.
SP creep: influence of microstructure, carbides and apparent activation energies
The role and influence of carbides has previously been controversial [7] although it is accepted that high temperature creep properties improve with the presence of carbon where the formation of carbides at grain boundaries is likely. This research corroborates this perception, with a large increase in rupture strength observed for cast material where there are clear grain boundary carbide precipitates (M 23 C 6 ), in comparison to the LPBF alloys where little or no M 23 C 6 carbide formations are present to inhibit grain boundary deformation. The scatter observed in the cast properties is understood to be due to the bimodal microstructure and the sensitivity of the small specimen test size meaning the number and type of grains being tested could be considerably different.
Examining the LPBF material performance reveals the HT1 90°variant ranks lowest; this is recognised as a combination of the smallest grain size and the relative absence of carbides and Σ3 type boundaries. The improvement seen in the HT1 0°variant is believed to be due to a slight increase in grain size and an aspect ratio further from 1. In the SP test, deformation occurs in a biaxial manner, causing membrane stretching across the transverse plane [26], in directions parallel and perpendicular to the columnar grain alignment in the HT1 0°variant. Therefore, the probability of intercepting a grain boundary is reduced, thus improving resistance to creep parallel to the columnar grain structure.
It has been shown that Σ3 type boundaries can act to retard or deflect crack growth so it would be expected that the HT2 materials would demonstrate better creep properties compared to HT1 material, with over 67% length Σ3 type boundaries. The result of this is a large reduction in the RGBN average segment length from 74-86 μm in HT1 to 13.6-17.6 μm in HT2. The scale of which these Σ3 boundaries, and the resulting RGBN act to improve properties is clear with the near order of magnitude increase in rupture life between HT1 and HT2 as shown in Fig. 8. The SP creep life of HT2 0°and HT2 90°is found to be very similar, although with values of grain size, aspect ratio, Σ3 and RGBN lying closely to one another, this is expected. Nonetheless, it demonstrates that the experimental heat treatment schedule with a higher temperature solution heat treatment has largely alleviated microstructural differences and improved mechanical properties in terms of creep resistance when compared to HT1.
Overall, based on the microstructural analysis and SP creep results it is suggested that the influence of carbide formations on rupture life is found to be more prominent than the retardation caused by Σ3 type boundaries due to the vast difference between cast and HT2 materials, although both act to improve creep properties. However, the bimodal grain structure in the cast material and its contribution to the scatter in the results in these small sample size tests must be considered.
In determining the constants for the adapted Wilshire equations for these materials, in the first instance a value of activation energy, Q c ⁎ , must be employed. The activation energy for self-diffusion (Q SD ) in polycrystalline nickel alloys is typically considered to bẽ 300 kJ·mol −1 [16]. The mechanical characterisation carried out in this research through SP creep revealed grain boundary deformation to be the dominant mechanism in these variants, thus providing preferential diffusion along these favoured paths, which in turn results in an activation energy of Q c against ln[−ln(F / F m )] constants u and k 1 were easily determined for the best fit (R 2 = 0.88), with a range of apparent activation energies, Q c ⁎ = 140-175 kJ·mol −1 as given in Table 2, all of which sensibly fall in the region for preferential diffusion. The differences in these Q c ⁎ values are thought to be attributed to the variant microstructures, specifically boundary densities which likely have a significant role in these miniaturised tests. For instance, the cast material will have a relatively low boundary density, particularly in regions of the larger grains, resulting in the highest apparent Q c ⁎ . While the HT1 variants have the smallest grain size and therefore the highest grain boundary density, the increase in grain size in the HT2 variants is coupled with an abundance of special boundaries meaning HT2 variants have the highest overall boundary density thus producing the lowest apparent Q c ⁎ . Overall, the high R 2 values produced through this approach suggests that the Wilshire equations are an effective tool for predicting creep life in these advanced materials.
Conclusions
In this study, an in-depth analysis of five C263 variants was conducted to determine the influence of heat treatments on their microstructures and mechanical properties. Advanced microscopy methods as well as the SP creep test have been utilised and the following conclusions have been drawn: • The SP creep test has successfully ranked the high temperature mechanical performance of C263 build variants, with adapted Wilshere equations effectively determining the long-term creep lives and apparent activation energies. • The higher temperature solution heat treatment in HT2 has successfully alleviated microstructural anisotropy by reducing texture and the columnar grain structure in LPBF variants. The higher temperature combined with the high degree of local misorientation evident in HT1 provides an additional driving force for recrystallisation and twinning. • Random Grain Boundary Networks reveal shorter potential intergranular crack paths in HT2 variants as a result of Σ3 boundaries, further strengthening their resistance to creep deformation. • The presence of grain boundary carbides acts to significantly improve the creep resistance of the cast material, and has been revealed as the dominant strengthening mechanism considering the RGBN is found to be larger than in all LPBF material variants.
Author contribution
The research presented in this paper was carried out as a collaboration between all authors. The research theme was defined by Robert Lancaster, Spencer Jeffs, Mark Coleman and Sean Davies. Sean Davies and Mark Coleman performed the SEM and EBSD analysis. Spencer Jeffs performed the mechanical testing. Sean Davies, Spencer Jeffs, Mark Coleman and Robert Lancaster co-worked on the discussion and interpretation of the results with respect to the material's microstructure. All authors have contributed to, edited and approved the final manuscript.
Acknowledgements
The current research was funded under the EPSRC Rolls-Royce Strategic Partnership in Structural Metallic Systems for Gas Turbines (grants | 6,192.2 | 2018-12-01T00:00:00.000 | [
"Materials Science"
] |
Inflating in a Trough: Single-Field Effective Theory from Multiple-Field Curved Valleys
We examine the motion of light fields near the bottom of a potential valley in a multi-dimensional field space. In the case of two fields we identify three general scales, all of which must be large in order to justify an effective low-energy approximation involving only the light field, $\ell$. (Typically only one of these -- the mass of the heavy field transverse to the trough -- is used in the literature when justifying the truncation of heavy fields.) We explicitly compute the resulting effective field theory, which has the form of a $P(\ell,X)$ model, with $X = - 1/2(\partial \ell)^2$, as a function of these scales. This gives the leading ways each scale contributes to any low-energy dynamics, including (but not restricted to) those relevant for cosmology. We check our results with the special case of a homogeneous roll near the valley floor, placing into a broader context recent cosmological calculations that show how the truncation approximation can fail. By casting our results covariantly in field space, we provide a geometrical criterion for model-builders to decide whether or not the single-field and/or the truncation approximation is justified, identify its leading deviations, and to efficiently extract cosmological predictions.
Introduction
Scalar fields have long been posited by particle physicists and cosmologists, although experimental evidence for their existence has come only very recently [1]. Their discovery has likely taken so long because in the absence of any symmetries that prevent them, quantum corrections often make it difficult to make scalars very light compared with other particles, an observation that is called the 'hierarchy problem' when applied to scalars associated with electroweak symmetry breaking.
Cosmologists also frequently invoke scalar fields because certain features of their classical dynamics are known to be useful for describing the very early universe. For instance, although Hot Big Bang cosmology provides an excellent account of current observations [2], it also provides evidence for there being two separate epochs during which the expansion of the universe accelerated rather than decelerated with time. We appear to have entered one of these epochs comparatively recently (dominated by Dark Energy), while another (possibly Inflationary [3]) epoch of primordial acceleration seems to have taken place at a much earlier time. Scalar fields are usually proposed to provide the dynamics that could drive such accelerated expansion, though the propensity of scalars to be heavy has made it difficult to embed these models convincingly into a fundamental theory. At present, string theory provides the most precise framework for doing so [4], although not yet with decisive success [5].
Yet one lesson does emerge from attempts to marry cosmology with fundamental physicsfundamental theories contain many scalars in their low-energy spectrum, and although it is hard to make them light enough to be interesting for cosmologists, once a mechanism succeeds in doing so for one it usually also does so for others. Furthermore, heavy fields can sometimes play surprisingly large roles in low-energy dynamics [6,7,8,9], requiring a refined understanding of how decoupling is operative in multiple-field and time-dependent contexts [10,11].
In this paper we embrace the point of view that multiple scalars are likely to be relevant to cosmology (and elsewhere), and explore as systematically as possible the dynamics of light scalar fields in the presence of other, heavier scalars. To this end we start with multi-scalar interactions whose scalar potential has the shape of a trough or ditch: shallow in the general direction of the light fields, but steeply rising in the transverse, heavy directions. By explicitly integrating out the heavy scalars, we identify which parameters control its decoupling and which features of the heavier scalars influence low-energy dynamics in potentially observable ways.
We find, as already noted in [7], that when the trough is not straight 1 the low-energy theory generally is not well-described by the 'truncation approximation', within which the heavy fields are simply set to vanish. Perhaps more surprisingly, this can remain so even as the mass, m, of the heavy field goes to infinity. This is possible because potentials that support curved troughs necessarily involve multiple scales, including the radius of curvature of the trough's bottom (relative to a target-space geodesic) and the curvature scale of the target space's Riemann tensor, as well as how quickly these quantities vary along the trough.
Generically all of these scales must be large to ensure that heavy fields decouple, and so justify a low-energy effective theory.
Concretely, we explicitly construct the leading effective couplings within the effective theory for the case of one heavy (h) and one light (ℓ) scalar, defined by the eigenbasis of the mass matrix at a particular point at the trough's bottom. 2 Even in this simple case there are at least three important scales in the low-energy potential: the heavy mass, m; and both the target-space radius of curvature, ρ, and the curvature, κ, of the trough's bottom (relative to a target-space geodesic). Because these are geometrical, they are covariant under field redefinitions and so can be computed equally well in any coordinate system that is convenient.
Our main result is the effective description that captures all of the low-energy effects of the heavy field. This is given by a single-scalar theory with the following action, out to 4-derivative level: where (expanding out to quartic order in ℓ) the effective coupling functions are and H eff = H 0 + · · · and so on. More generally, were we to work to higher order in fields and derivatives, we would arrive at a low-energy effective theory that would be a higher-order polynomial function of X := − 1 2 (∂ℓ) 2 (with ℓ-dependent coefficients, in general): a so-called P (ℓ, X) model -or k−inflationary theory [12] in a cosmological context 3 . The regime of validity of the expansions made in obtaining the effective theory (1.1) are discussed in §3. 1 More precisely, when the trough bottom is not a geodesic of the target-space metric (see below). 2 As we see below, this basis need not coincide with the tangent and the normal to the trough at this point. 3 Such an effective description was previously advocated in [6], where the effective coupling H ef f was generated by non-canonical kinetic couplings in the parent theory (see also [13], which studied the regimes of validity of this effective description). In what follows we generalize and give context to these findings in a manner that is invariant under field redefinitions.
What is important is that the effective couplings of the low energy theory are explicitly calculable as functions 4 of m, κ and ρ, evaluated as an expansion about a particular point, ϕ, on the trough's bottom. The leading contributions are given by and where U (ϕ) is the value of the scalar potential at the trough's bottom, and primes denote differentiation with respect to arc length (as measured by the target-space metric) along the trough. The quantity λ nnn measures how the walls of the trough deviate from a perfect parabola.
Provided κ, ρ and m are sufficiently large, these effective interactions describe any lowenergy process, including (but not restricted to) predictions for -and fluctuations aboutcosmological evolution. Because the low-energy theory is a single-scalar model, these predictions are very easily obtained by specializing well-known formulae for single-field inflationary models to the above couplings, thereby extending these single-field predictions to a broader class of multi-field models.
In particular, the implications for fluctuations about cosmological solutions -such as for non-gaussianity -can be obtained in either of two equivalent ways. When the above theory is directly viewed as the effective theory of inflation -in the spirit of Weinberg [14] -predictions for fluctuations can be simply extracted using existing single-field calculations [16,17,18] for general P (ℓ, X) models. Alternatively, one can use the effective theory for single-field cosmological fluctuations 5 [14,15], for which we provide the leading contribution to the effective coefficients, M n (t), as functions of g eff , λ eff and H eff .
The remainder of the paper is organized as follows. The next section, §2 (with details in Appendix B) shows how to characterize shallow troughs geometrically in order to identify the relevant scales in a way that is covariant under field redefinitions (see Appendix A). §3 (with 4 Strictly speaking, at this order in 1/m the parameter ρ turns out to appear among interactions involving more than 4 powers of ℓ, although it can arise in quartic (or lower) powers of ℓ at higher order in 1/m. 5 The authors of ref. [7]
Covariant characterization of multi-field troughs
This section defines the multi-scalar action of interest and quantifies what it means for the scalar potential to have a trough along which the potential is constant or slowly varying. The goal is to characterize covariantly the geometrical properties of the slowly varying directions of the potential in terms of derivatives of the potential V .
General form for multi-scalar actions
Consider the following general action describing N mutually interacting scalar fields, φ a within a curved spacetime: 6 This describes the most general Lorentz-invariant interactions possible amongst these scalars at the two-derivative level, 7 and is completely characterized by the interaction potential, V (φ), and the target-space metric, G ab (φ) (which is a positive-definite symmetric matrix). Here M p is the reduced Planck mass defined in terms of Newton's constant by M 2 p = (8πG N ) −1 which only plays a role for applications where couplings to gravity are important (such as to cosmology).
Our interest is in making perturbative (typically semi-classical) predictions in the immediate vicinity of a field-point, ϕ a , and so usually at this juncture we would expand the action in powers of φ a − ϕ a . However it is useful to emphasize the invariance of physical predictions under field redefinitions, and this is not well-served by such a linear split between φ a and ϕ a . A nonlinear alternative exists -δφ a = δφ a (φ, ϕ) with δφ a → 0 as φ a → ϕ a -that 6 Conventions: our metric is 'mostly plus' and we adopt Weinberg's curvature conventions [21], that differ from MTW conventions [22] only by an overall sign in the definition of the Riemann tensor. 7 We do not write the non-minimal coupling F (φ) R, where R = g µν Rµν is the spacetime Ricci scalar, because this can be removed by transforming to Einstein frame through an appropriate Weyl rescaling: gµν → A(φ) gµν .
preserves covariance under field redefinitions, where δφ a geometrically represent Gaussian normal coordinates in field space. A brief review of this formalism is given in Appendix A.
Recall that under a generic local field redefinition, φ a → φ a +ζ a (φ) (for ζ a (φ) an arbitrary, infinitesimal, locally invertible collection of functions), V (φ) transforms as a scalar: δV = V , a ζ a , while G ab (φ) transforms as a metric tensor: δG ab = G ab, c ζ c + G ac ζ c , b + G cb ζ c , a , where commas denote differentiation (V , a := ∂V /∂ϕ a and so on). When expanded in terms of the covariant quantity δφ a , the Lagrangian can be written in terms of covariant derivatives and curvatures of the metric G ab . For instance, the expansion of the scalar potential gives where semicolons denote covariant derivatives constructed using the Christoffel symbols, γ a bc (ϕ), built from first derivatives of the target space metric, G ab (ϕ). An expansion of the metric to quartic order similarly gives the standard normal-coordinate expression [23] where R a bcd is the Riemann tensor built from G ab .
In the special case where there are only two fields -a case we explore in more detail below -the target-space curvature tensor is particularly simple: characterized by a single function, the target-space radius of curvature, 8 ρ(ϕ).
We next suppose the scalar V has a trough-like shape with a local minimum in several strongly varying directions, but varying slowly along others. For simplicity we describe in detail here a system involving only N = 2 fields, but the generalization to more than two is straightforward. We first characterize more precisely what it means for the potential V to have a trough. Because this is most easy to do when the trough is perfectly leveli.e. when V is perfectly constant along its bottom -we first do so in this simpler case.
Perfectly level troughs
Given any smooth potential it is always possible to define equipotential curves, i.e. trajectories in field space, φ a = χ a (σ), along which V is constant: V [χ(σ)] = V 0 for all σ. We define a level trough as an equipotential curve, χ a (σ), with two additional properties: 8 In our conventions if the target space were a two-sphere, then ρ 2 > 0.
(i) The potential gradient vanishes everywhere along the curve: V , a [χ(σ)] = 0 for all σ and for all a; (ii) All eigenvalues of the 'mass' matrix A a b := G ac V ; cb are non-negative, and at least one eigenvalue is strictly positive. This condition is required to distinguish troughs from ridges. Notice that because the eigenvalue condition, A a b e b = λ e a , is a tensor equation the eigenvalues λ are scalars under field redefinitions.
As is shown in detail in appendix B these conditions imply that the two independent eigenvectors of A a b can be cleanly identified. geodesic, Dχ a /dσ = 0.) In terms ofχ a := G abχ b and n a := G ab n b we therefore have everywhere along the trough's bottom, where m 2 (ϕ) = V ; ab n a n b > 0 is the nonzero eigenvalue of A a b required by condition (ii) above.
As shown in detail in Appendix B, differentiating eq. (2.7) with respect to σ along the bottom of the trough, gives the following expression for the potential's third covariant derivatives, V ; abc = 2 mṁ n a n bχc + n b n cχa + n c n aχb 9 Using the target-space metric, G ab . 10 In decomposing field excitations with respect to the basis defined by the tangent and normal to the trough of the potential, we derive independent Frenet-Serret relations [24] to those introduced in [25], who define excitations tangent and normal to a background solution (in the context of inflation). We do so as we are interested in understanding how the scales of the parent theory enters the effective theory that describes all low energy processes, and not just those corresponding to perturbations around cosmological evolution. − m 2 κ n aχbχc + n bχaχc + n cχaχb + V nnn n a n b n c , (2.8) where V nnn := V ; abc n a n b n c andṁ := dm/dσ. This uses that V ; abc is completely symmetric when evaluated along the trough's bottom, since vanishes because V , d also vanishes there, using condition (i) above. Among other things, eq. (2.8) gives the quantitiesṁ and κ in terms of derivatives of V , with V ; abc n a n bχc := V nnt 2 m . (2.10) Expressions for higher derivatives of V are similarly obtained by repeated differentiation, with explicit expressions for the fourth derivatives given in appendix B. Notice that these higher derivatives need not be completely symmetric in their indices if the target-space metric is not flat, since (for example) and so on.
Tilted troughs
Of more interest, particularly in cosmology, is the situation where the trough is not completely level, but with a slope along the trough that is much shallower than the directions up the trough's sides.
This situation is handled as above, but with the generalization that derivatives along the trough direction are parametrically small rather than zero. Defining U (σ) as the value of the potential along the trough bottom, we have and because the curve χ a (σ) runs along the bottom of the (no-longer level) trough, its tangent is parallel to the potential gradient along the bottom:χ a ∝ G ab V , b . Because of this we replace condition (i) of the flat trough with the following conditions for the potential gradient V , aχ a =U and V , a n a = 0 , (2.13) everywhere along the valley floor.
Successive differentiation -see appendix B -of these equations again allows the derivation of expressions for higher derivatives of the potential. In particular, differentiating eqs. (2.13) gives the following expression for the second-derivative matrix V ; ab =Üχ aχb +U κ n aχb + n bχa + m 2 n a n b , (2.14) where, as before, we define m 2 (σ) := V ; ab n a n b and the radius of curvature by Dχ a /dσ = n a /κ, withχ a and n b being the orthonormal basis adapted to the trough bottom.
In particular, eq. (2.14) shows that n a andχ a need no longer be eigenvectors of the matrix A a b , and m 2 need no longer be an eigenvalue. Explicit diagonalization gives the eigenvalues with corresponding (orthonormal) eigenvectors e a + = n a cos θ +χ a sin θ e a − = −n a sin θ +χ a cos θ , and .
These simplify once restricted to the regime of interest: m 2 much bigger than derivatives of U . In particular, in this limit and so the 'heavy' eigenvalue becomes while the 'light' one is The mixing angle is similarly small in this limit, and so the corresponding eigenvectors take the approximate forms: e a + ≃ n a + 1 2 βχ a + O(β 2 ) and e a − ≃χ a − 1 2 βn a + O(β 2 ). Formulae for the third derivatives of V are obtained by successive differentiation, and are derived in detail in appendix B. Because the trough is not precisely flat, the third derivatives are in general no longer completely symmetric. Specializing eq. (2.9) to tilted troughs gives (for two fields) V ; abcχ aχb n c − V ; abcχ a n bχc = 0 , V ; abc n aχb n c − V ; abc n a n bχc =U 2ρ 2 , (2. 23) which shows that ordering only matters when V ; abc is contracted with two n's and oneχ.
Appendix B shows that the third derivatives evaluate to V ; abc n a n bχc = 2 mṁ + 2U κ 2 V ; abcχ a n b n c = V ; abc n aχb n c = 2 mṁ + 2U and V ; abc n a n b n c is not in general related to κ, m and derivatives of U .
For later purposes it is useful also to have expressions for the completely symmetrized derivatives: V (tnn) := V ; (abc) n a n bχc = 2 3 V ; abcχ a n b n c + 1 3 V ; abc n a n bχc as well as the contractions of the symmetrized derivative, V ; (abc) , with the eigenvectors e a ± , in the small-β limit. For instance V h := V , a e a + ≃ 1 2 βU ≃ (U 2 /κm 2 ) and V ℓ := V , a e a − ≃U , V hh = M 2 , V ℓℓ = µ 2 and V ℓh = V hℓ = 0. For small β the third derivatives are where the quantity λ nnn defined by typically remains bounded as m 2 gets large. Notice that these reduce to the usual expressions for straight troughs, κ → ∞, with a flat target space, ρ → ∞. For some extensions of these expressions to higher derivatives and to 1/m 2 corrections, see appendix B.
The low-energy effective theory
The previous section shows that there are three separate, possibly large, scales that instantaneously characterize the properties of a trough-shaped potential along its bottom: the scale m 2 (ϕ) defining the trough's transverse steepness; the scale κ(ϕ) defining the radius of curvature of the trough's valley floor; and the Riemann radius of curvature, ρ(ϕ), of the target-space geometry. There are also the derivatives of these quantities along the trough, as well as third and higher derivatives of V in the direction(s) normal to the trough.
Light and heavy states in a trough
We now assume all of these scales to be much larger than the energy scales of interest, such as the fractional rates of change of quantities along the trough's bottom. We wish to identify the low-energy effective theory that governs the dynamics along the trough in this limit.
Our goal is to trace the leading way that each of these scales shows up in the low-energy effective interactions once heavy degrees of freedom are integrated out (at the classical level).
In particular, we wish to see how their presence alters the naive truncation approximation, in which the heavy fields are simply set to zero.
In order to do so we must identify the heavy and light degrees of freedom, and integrate out the heavy one. To this end we expand the expansion field, δφ a in a basis that diagonalizes the mass matrix, A a b = G ac V ; cb , writing (3.1) By virtue of the above definitions the expansion, eq. (2.2), of the scalar potential becomes: − e c + and so on are the symmetric derivatives of V as evaluated at the end of the previous section. In terms of these fields the expansion of the kinetic term, eq. (2.3), similarly is which uses eq. (2.4) for the target-space curvature.
Integrating out the heavy fields
The next step is to integrate out the heavy field to obtain the low-energy effective theory of the light field along the bottom of the trough. In the classical approximation the heavy field is integrated out by eliminating it from the action using its equations of motion: 11 is the adiabatic ground state satisfying δS/δh = 0 [10]. We summarize the main steps here, with more details given in Appendix C.
To start, it is useful to integrate by parts in order to write the classical action as follows, where the 'truncated' potential is and we couple an external current, j, to the light field, ℓ. The kinetic operator for h is Finally, the J (i) are given by and J (4) : The equation of motion of the field h then is, which can be solved iteratively to give h = ∆ −1 h J (1) + · · ·, where the ellipses involve powers of J (3) and J (4) . We insert this back into the classical action, and expand ∆ −1 h in powers of 1/M 2 to get the following expression (see Appendix C for details) and so on.
Finally, we trade the explicit derivatives of V appearing in these expressions -including the mass eigenvalues M 2 and µ 2 -in favour of the trough-related quantities U (ϕ), m(ϕ), κ(ϕ) and their derivatives along the trough, as well as ρ(ϕ) and transverse derivatives like V hhh and so on, using the following results from earlier sections (and Appendix B) while V hℓ = 0. Third derivatives are similarly given by which extends the earlier expressions to higher order in 1/m 2 , and where λ nnn is as defined in eq. (2.31). Expressions for fourth derivatives are similarly given in Appendix C.
The results obtained by substituting these expressions into eqs. (3.10) through (3.12) are most succinctly expressed in terms of an expansion in derivatives of ℓ. As is shown in detail in Appendix C, it is always possible to perform a local field redefinition so that the result up to four derivatives has the form and so the content of the above calculation is to give expressions for the leading contributions to the functionsV eff , G eff and H eff . (The freedom to perform field redefinitions ensures that only two of these functions are independent, as we show in detail below.) We now quote the expressions for these functions that are relevant for terms in L eff involving at most four powers of the light field, ℓ.
The effective scalar potential is given by (see Appendix C for details) while the kinetic function is 17) and the 4-derivative term has coefficient (3.18) As remarked above, since there is only a single light field only two of these three functions are independent. This is usually expressed by performing a field redefinition, ℓ →l to a 'canonical' basis chosen to set the kinetic function to unity: G eff (ℓ)(∂ℓ) 2 = (∂l) 2 . The required redefinition satisfies which has as solutionl Notice that once this is used (and dropping the 'caret' over ℓ) the effective scalar potential changes to where the ellipses denote terms involving higher powers ofl or 1/m 2 , and the new term involving j is absorbed into a redefinition of j. Expression (3.18) for H eff remains unchanged by this field redefinition to the order in ℓ to which we work.
Notice that there are two interesting special cases for which all of the differences between V eff (ϕ, ℓ) and U (ϕ+ℓ) vanish. First, they do so (even for finite m and κ) for a level trough with all derivatives of U vanishing. This is required in order for the full theory and the effective theory to agree on the value of the potential at its minimum (and so also on measurable quantities like the curvature of spacetime, say). Second, they also vanish in the limit of a straight trough, where κ → ∞, in which case a truncation of V (ℓ, h) to h = 0 would have been a good approximation. What is perhaps noteworthy is the appearance of terms that are suppressed only by 1/κ and not by 1/m, and so which survive even for infinitely steep troughs for which m 2 → ∞ with κ fixed.
Of course, we equally well could have made an alternative choice of variables,l →ľ for which V eff (ϕ,ľ) = U (ϕ +ľ) +ǰľ, at the expense of making the kinetic term non-canonical.
For troughs that are not flat, what counts physically is neither V eff or G eff separately, but their relative form and we see that generically either V eff = U (ϕ + ℓ) or G eff = 1.
In summary, we see that (for two scalar fields) the most general possible effective interactions governing the dynamics of the light field at low energies (and out to quartic order in ℓ) along a potential trough are given by eq. (3.15) with G eff (ℓ) = 1, H eff = 1/(2κ 2 m 2 ) and V eff given by eq. (3.21). What makes this effective theory so useful (as for any low-energy effective theory) is that these interactions can be used to describe all physical processes involving at most quartic interactions that can appear at low energies in the full theory. In particular, it identifies that only the combinations of κ, m and ρ that appear in eqs. (3.18) and (3.21) can be relevant at low energies for a broad class of physical situations.
Domain of validity
Before applying this effective theory to some simple illustrative examples it is worth recapping the approximations on which its validity relies.
Semiclassical limit
First, because it is derived purely within the classical approximation, the effective field theory implicitly relies on there being small parameters that parametrically suppress quantum corrections. In the full theory this is often assured through the existence of small dimensionless couplings, like gauge or quartic-scalar couplings. It implicitly also relies on a low-energy approximation, both to justify the low-energy, single-field approximation (see below) and to justify semiclassical methods in the full theory. For instance, the energies to which the full two-field theory are applied must be small relative to the higher energy scales being ignored (such as -but not restricted to -the Planck scale) in order to suppress loops, and so is a precondition for justifying the semiclassical treatment of gravity.
Low energies
The additional condition required to replace the full two-scalar system with its one-scalar effective theory in the trough requires the energies of interest to be low enough not to dynamically excite any heavy quanta. 12 In practice, the validity of the derivative expansion used in (3.15) requires all derivatives to be much smaller than the high-energy scales. As we saw when inverting the heavy-field operator ∆ h = Ω − M 2 as a power series in Ω/M 2 , the relevant scale controlling this low-energy expansion is set by rather than directly by κ and m. In particular, the low-energy approximation (and the effective field theory description derived here) can fail if the various terms in M 2 cancel, even if they are separately large. This is the reason the effective single-field approximation fails in explicit examples [8], and we see it here as arising for the usual reason: a breakdown of the large hierarchy of scales on which the decoupling of high scales is based.
Furthermore, even when an effective single-field description exists, it need not be the one obtained by simply truncating the heavy fields [7]. As we see above, setting h = 0 requires V h to vanish, but because V h ≃ (U /κm) 2 this need not be a good approximation. For time-dependent problems, since effective theories only capture adiabatic evolution the low-energy limit also requires the time scales for significant changes to low-energy classical fields to be much larger than those, such as 1/m and 1/κ, set by high-energy scales.
Small fields
The explicit form given for the effective Lagrangian in eq. (3.15) also relies on expanding in powers of ℓ, and in the presence of shallow troughs in the scalar potential this is (by assumption) not required by the low-energy approximation. In practice the need to expand in powers of ℓ arises from the complexity of solving the full field equations, even in the limit where m is very large.
This complexity has two logically different sources. First, for the kinetic energies the small-field limit enters when evaluating the target-space curvature only at the background, ϕ, rather than also as a function of ℓ. This approximation implicitly requires ℓ not to be large compared with the target-space radius of curvature: ℓ ≪ ρ.
Secondly, and more generally, because J (1) ∼ m 2 ℓ 2 /κ grows with m 2 there could be contributions to the effective action to order 1/m 2 coming from what are formally much higher orders in the 1/m expansion, such as those arising from contributions like ∆L ∼ J n (1) J (n) /M 2n ef f . However, these are also higher order in ℓ -being at least of order ℓ 2nshowing how ℓ ≪ κ is implicitly required to justify their neglect. This of course is an artefact of having expanded around the point ϕ. In order to analyse the system far away from ϕ (i.e. for large ℓ), it suffices to simply shift the expansion base point, ϕ.
Some flat examples
It is useful to compare the above expressions with concrete examples, to check their validity against known systems before seeking new applications to cosmological models.
The mexican hat
Consider first the most familiar case of a curved trough: two scalar fields with a flat target space mutually coupled through an O(2)-invariant 'Mexican hat' or 'wineglass' potential: The target-space metric for this model is flat, as is explicit when written in terms of X and Y, for which the target-space Christoffel symbols vanish. Consequently, in these coordinates V ; a 1 ..an = V , a 1 ..an and so on.
In this section we choose the potential to have the explicit form which has a level trough at V = V 0 along the curve Z = √ X 2 + Y 2 = ν/λ. The unit tangent and normal to this trough are where cos ϑ := X /Z and sin ϑ := Y/Z. These are also eigenvectors of the mass matrix, . Evaluated at the bottom of the trough these reduce to where c := cos ϑ and s := sin ϑ. Evaluated at the trough's minimum, √ X 2 + Y 2 = ν/λ, this allows κ to be simplified to as expected. In particular, the O(2) symmetry ensures physical quantities do not vary along the trough, soκ =ṁ = 0 and so on. For reference, we list all the symmetrized derivatives, V i 1 ···i k , (evaluated at the trough minimum) for the mexican hat potential: and V i 1 ···i k = 0 for k ≥ 5.
Specializing the low-energy effective Lagrangian, eq. (3.15), to this case we find where the second line uses the above calculations of m and κ. Notice that the symmetry ℓ → ℓ + c of the low-energy theory ensures the existence of a conserved Noether current, which corresponds (up to a constant normalization, N ) to the current due to O(2) invariance in the full theory (4.11)
Slowly rolling solutions
As an application of this Lagrangian, consider next the energetics of the slowly rolling solution where the field Φ rotates around the bottom of the potential at constant angular speed: i.e.
Z is constant but ϑ = ωt. In this case the centrifugal force shifts Z away from the minimum so that Z 2 = X 2 + Y 2 = (ν 2 + ω 2 )/λ 2 . The potential evaluated at this shifted position is and so the total energy density is The conserved 'angular momentum' of this motion is similarly given by where in this section we temporarily use dots to denote time derivatives.
We next calculate this same energy density and conserved charge in the effective field theory, to see how it arises there. For the slowly-rolling field configuration in the low-energy theory, we solve ℓ = 0 using the leading-order solution ℓ = f ωt, for whichl = ∂ t ℓ = f ω is a constant. Evaluating L eff at this solution then gives To find the energy of this solution we compute the effective Hamiltonian density for this system, which is where the canonical momentum is defined by Using this the Hamiltonian density becomes and so the energy density obtained by evaluating this atl = f ω is where the second equality uses f = ν/λ to secure agreement of the ω 2 term with its counterpart in the exact result obtained from the full theory. Once this is done the ω 4 term also agrees.
The conserved charge is similarly given by
The cowboy hat
An instructive variation on the previous example is the case of an O(2)-breaking potential, wherein the circular trough is deformed to an ellipse. 13 This deformation is simply achieved by deforming the potential of eq. (4.2) to which reduces to the case considered above if λ x = λ y = λ and v 2 = ν 2 /λ. 13 And so with the sombrero shape deforming into a cowboy hat, hence the name.
The trough minimizing V in this case is the ellipse where λ := 1 2 (λ x + λ y ), λ ′ := 1 2 (λ x − λ y ) and, as before, X + i Y := Z e iϑ . The mass matrix along the trough has eigenvalues M 2 − = 0 and M 2 + = m 2 , with The corresponding eigenvectors are also the tangent and normal to the trough, and are given by Notice in particular that if λ ′ = 0 thenṁ = 0 along the trough's bottom.
The trough's radius of curvature is given by κ = −m 2 /V ,ijk t i t j n k , where the required third derivatives now are After some algebra this gives which reduces to the mexican-hat expression, eq. (4.7), when λ ′ = 1 2 (λ x − λ y ) → 0 and v = ν/ √ λ. From this we see thatκ does not vanish along the trough bottom becauseṁ does not, and thatκ The low-energy effective Lagrangian derived for physics near the trough's bottom again satisfies U = V 0 and soU =Ü = 0, and because of this variables can be found for which simultaneously G eff = 1 and V eff = V 0 . The leading contribution to the effective theory in these variables is therefore again eq. (4.9): A potential puzzle with this result is that to within the accuracy it is written it shares the shift symmetry, ℓ → ℓ + c, of the circular case, which implies the existence of the conserved current to within the same level of accuracy Assuming there to be a term in H eff (ℓ) of order ℓ 2 /m 2 κ 4 we are led to expect failure of current conservation to first arise at the 4-derivative level: The potential puzzle arises once we ask at what level the previously conserved current, J µ , fails to be conserved in the full theory. This is governed by the ϑ field equation, which states where ϑ ≃ ωt. This seems to have the dependence on f = ν/λ and ω that would come from the contribution to ∂ µ J µ eff of a term like λ ′ ℓ 2 (∂ℓ) 2 in the effective Lagrangian. However, we used the freedom to redefine fields to set G eff = 1 in order to find a current conserved up to order ω 4 in the effective theory, so we should see if we can also do so in the full theory. To this end imagine redefining the low-energy angular variable, and defineĴ µ := − Z 2 ∂ µθ ≃ −Z 2 ∂ µ ϑ 1 + a 2 cos 2ϑ , where the last approximate equality works to linear order in λ ′ , assumes a = O(λ ′ ) and linearizes as before about the λ ′ = 0 solution ϑ ≃ ωt and Z 2 ≃ (ν 2 + ω 2 )/λ 2 . We see that the choice a = λ ′ /λ defines a current,Ĵ µ , whose non-conservation first arises at O(ω 4 ) when linearized in λ ′ , just as was the case for the low-energy effective theory.
Applications to inflationary models
We next consider non-flat troughs and ask whether and how the effective analysis presented here can be used to describe the dynamics of multi-field inflationary models. Our goal is twofold. First, we provide simple criteria for when a given multi-field model with a trough is well-described by our effective Lagrangian. Second, we show how our effective action provides a simple shortcut for calculating inflationary observables for multi-field models using wellknown results for single-field models.
Our starting point is the effective field theory computed out to quartic order in ℓ and up to order 1/m 2 : eqs. (3.15), (3.18) and (3.21), which we repeat here for convenience (with and and so on. In this section only we switch to using primes to denote differentiation with respect to trough arc length: e.g. κ ′ := dκ/dσ = (dκ/dϕ)dϕ/dσ, and reserve over-dots for FRW time derivatives.
For cosmological applications we expect this kind of single-field description to apply whenever all time-dependence scales are smaller than the parameters m, κ, ρ and so on. In particular, we do not expect this type of single-field model to capture the 'quasi-single-field models' [19] that satisfy m ≃ H 14 .
Basic inflationary observables
Suppose we now imagine ℓ to be the inflaton, with inflation driven by a slow roll along the trough's bottom. Imagine also choosing ϕ so that ℓ = 0 denotes the epoch of horizon exit of some reference comoving scale. In this case the action, (5.1), is equivalent to a singlefield inflationary model, with scalar potential V eff and non-minimal Lagrangian function [12] P (X, ℓ) = −V eff (ℓ) + X + 4H eff X 2 . We may therefore use standard single-field formulae for a P (X, ℓ) theory [17,18] when making inflationary predictions.
In particular, it is clear that the presence of both H eff and δV imply the inflationary slow-roll differs from a naive analysis that simply uses U as the inflationary potential along the trough's bottom. These differences track the influence of the heavy second field on the low-energy inflationary dynamics. For instance, the slow-roll parameters defined by the scalar potential at horizon exit are showing ǫ V agrees with ǫ U while η V and η U can differ. Notice that η V < η U because U > 0 during inflation, and (if ǫ U and η U are comparable in size) the correction is sizeable if U is comparable to κ 2 m 2 .
Furthermore, the presence of H eff in P (X, ℓ) implies an effective 'speed of sound', 14 See however [20] for an interesting case study of the regimes that interpolate between those of [19] and those of the single field effective description.
which is smaller than unity because X = 1 2l 2 > 0. In terms of the trough and slow roll parameters, using 3Hl ≃ −U ′ and 3M 2 p H 2 ≃ U we find that The Hubble scale as a function of the rolling field ℓ is [18] whose time-dependence governs the slow-evolution parameters relevant to basic inflationary observables. We imagine this evolution to be slow because of the shallowness of the trough bottom, and so take X/V eff ≪ 1. We then follow the small corrections from slow roll arising from the effective interactions induced by the heavy field.
The relevant first rate of change of H is given by which may be inverted to give X as a function of ǫ: where to leading order in the slow-roll approximation we would have had (3X/V eff ) ℓ=0 ≃ ǫ V = ǫ U .
A second useful slow roll parameter is given by η :=ǫ ǫH which is related to the parameters η V and ǫ above, and can be rewritten to leading order as [18] η =ǫ ǫH = −2η V + 4ǫ Furthermore, we have s :=ċ s /(c s H) ≃ 0, which vanishes in our case as H eff is ℓ-independent only as a consequence of our having expanded L eff to quartic order in fields. The effective theory obtained to all orders in fields (but to quartic order in derivatives) would in general exhibit a varying speed of sound along the trough.
The utility of these expressions lies in the following general results for properties of the spectra of primordial scalar and tensor fluctuations [18]: where (· · ·) k denotes evaluation at horizon exit for mode k. These expressions are valid so long as the parameters ǫ, η, and in particular c s vary slowly enough 15 (to quartic order in fields, the latter is satisfied by default). Of particular observational interest are the following We note that were we to compute the effective theory to all orders in fields (alternatively, recompute the effective expansion to quartic order at each instant the mode of interest k crosses the horizon), we could infer from the above the presence of features in the scalar spectrum generated by a varying speed of sound. By current observational constraints [2]: n s = 0.968 ± 0.012 and r < 0.2 with no significant evidence for any spectral running.
Nongaussianity
We note that in addition to gravitational non-linearities, there are three sources of nonlinearity in the action (5.1) that can give rise to primordial non-gaussianity: the cubic scalar potential term with coupling g eff ; the quartic scalar potential term with coupling λ eff ; and the quartic derivative interaction with coefficient H eff . General bispectrum and trispectrum predictions for the multi-scalar trough model are straightforwardly obtained by combining the above expressions for these couplings with existing single-field calculations [16,17,18], whose validity relies on the condition that c s varies sufficiently slowly (ċ s ≪ c s H).
For example, for the primordial bi-spectrum we quote these as where K := k 1 + k 2 + k 3 and the coefficients A i are given by 15 We must go beyond quartic order in ℓ when the speed of sound varies more rapidly, while remaining within the effective theory and preserving slow roll. (See also [7,9].) 16 The k dependence of the spectral indices and the tensor to scalar ratio can be obtained (accurate up to terms that are second order in the slow roll parameters) by simply evaluating the first order expressions at the instant of horizon crossing.
where γ = 0.577... is the Euler-Mascheroni constant and the k i -dependent functions,Ā λ ,Ā c , It is clearly a great simplification to be able to use standard single-field results such as these to extract predictions for the broad class of multi-scalar models to which our effective theory applies.
Relationship with the EFT of Cheung et al.
For the simple effective theory we have derived here, there is a direct relation with the effective expansion of [15], where it was shown that the most general form for the action for the adiabatic mode (for example, in unitary gauge 17 ) can be parametrized as: where δK µ ν is the variation of the extrinsic curvature of the constant time hypersurfaces with respect to the background FRW metric. The first three terms in the expansion above ensure tadpole cancellation.
Were we to minimally couple a scalar field with the Lagrangian density L = P (X, ℓ) to gravity and expand the action around a background homogeneous solution ℓ 0 , we would deduce the co-efficientsM n ≡ 0 and M 4 n (t) = (−1) n X n ∂ n P ∂X n ℓ 0 , (5.18) and so M 4 2 ≃ 8H eff X 2 to the order to which we work in the above. Evidently, our effective expansion to quartic order furnishes the leading M n co-efficients of the effective theory of [15].
Proceeding to higher orders in the derivative and field expansion would successively yield the higher order M 4 n coefficients.
Conclusions
To summarize, in this paper we show how to identify covariantly the effective theory that captures the low-energy limit of a multi-scalar system slowly evolving along a shallow trough in the scalar potential. We illustrate this for a simple two-scalar system by explicitly integrating out the heavy field to obtain the single-scalar low-energy effective theory, (3.15), with effective couplings, (3.18) and (3.21).
We give explicit covariant expressions for the scales that must be large in order for the truncation approximation to be valid, and see why it is not sufficient for the heavier field merely to be heavy. In particular, it is also necessary for the trough not to be too strongly curved, and for the heavy mass and trough curvature not to vary too strongly along the trough's bottom. Because these criteria are covariant under field redefinitions, they can be computed for specific theories using any convenient field parametrization.
By comparing the effective theory with the full theory in several simple (non-gravitational) examples, we show that H eff precisely captures the centrifugal energy caused when slow motion along a curved trough forces the fields to climb a small distance up the trough walls.
Finally, we show how simply inflationary observables can be computed for multi-field models whenever such an effective description applies, by using well-known predictions for single-field models with a quartic effective scalar potential. This extends these single-field predictions by showing that they also apply to a broad class of multi-field models, and identifies which features of the multi-field potential are relevant to observations. In particular, we find that the effective theory contains an effective higher-derivative coupling, H eff , that contributes to cosmological observables as a contribution to the effective speed of sound of the primodial cosmological fluid.
A. Covariant field expansions
As in the main text we consider the action describing N mutually interacting scalar fields, φ a , written in the Einstein frame Our interest is in analyzing the theory in the immediate vicinity of a field-point, ϕ a , in a way that emphasizes the invariance of physical predictions under field redefinitions.
This section describes how to do so explicitly, but contains only standard material that the cognoscenti should feel free to skip [26]. Recall that under generic infinitesimal local field redefinitions the potential, V (φ), transforms as a scalar while the kinetic coefficient, G ab (φ), transforms as a symmetric covariant tensor. That is, if φ a → φ a + ζ a (φ), the potential, V (φ), transforms as V → V + V , a ζ a and G ab (φ) transforms so δG ab = G ab, c ζ c + G ac ζ c , b + G cb ζ c , a . Here commas denote differentiation (V , a := ∂V /∂ϕ a and so on).
The goal is to define a field expansion of the action, φ a = ϕ a +δφ a , about a particular field point, ϕ a , that makes manifest this target-space covariance. To this end imagine constructing the target-space geodesic, ψ a (σ), that connects ϕ a to φ a . It is useful to use as parameter target-space arc-length along the curve, and so Dψ a dσ :=ψ a + γ a bcψ bψc = 0 , where over-dots denote d/dσ and γ a bc are the Christoffel symbols γ a bc := built from the target-space metric G ab . Defining ψ a (0) = ϕ a and ψ a (ǫ) = φ a , we consider the point φ a to be near ϕ a to the extent that ǫ is small (compared with other scales in the problem).
The covariant formulation of the quantity δφ a is then ǫ ξ a , where ξ a :=ψ a (0) is the tangent to this geodesic evaluated at ϕ a . Although in principle any family of curves could be used in this way to define δφ a , the utility of using geodesics can be seen once physical quantities are expanded in powers of ξ a . For instance, expanding ψ a in powers of ǫ gives where η a := [Dψ a /dσ](0) vanishes for a geodesic, and so on. Evaluating the scalar potential in the same way then gives where the last line repeatedly uses Dψ a /dσ = 0. This ensures all coefficients involve only tensor quantities; in this case covariant derivatives built from the target-space metric: V ; ab := V , ab − γ c ab V , c and so on. This simplicity arises because the expansion in powers of ξ a is equivalent to the use of Gaussian normal coordinates for the target space, for which the first derivative of the metric at ϕ a vanishes. To see this, evaluate the term cubic in ǫ in the scalar kinetic term using the expansions G ab [ψ(ǫ)] = G ab (ϕ) + ǫ G ab, c (ϕ) ξ c + · · · and ∂ µ ψ a (ǫ) = ǫ ∂ µ ξ a − ǫ 2 γ a bc ξ b ∂ µ ξ c + · · · (where the last expansion specializes to constant background fields, ∂ µ ϕ a = 0), to get Continuing on to quartic order in the kinetic term gives the standard normal-coordinate where R a bcd is the Riemann tensor built from G ab .
In the special case where there are only two fields -a case we explore in more detail below -the curvature tensor is particularly simple: characterized purely by a single function ρ, related to the Ricci scalar 18 as R(ϕ) = R ab ab = −1/ρ 2 .
B. Geometry of a trough
This appendix computes in detail the properties of V , assuming it has a trough-like shape for a system involving only N = 2 fields. Following the main text, we do so first for the case of a perfectly level trough, and then for the general case where the trough is slightly tipped.
Perfectly level troughs
As discussed in the main text, a potential with a level trough is one for which there is an equipotential curve, χ a (σ), with two defining properties. Property (i) states that V , a [χ(σ)] = 0 for all σ; and property (ii) states that all eigenvalues of the 'mass' matrix A a b := G ac V ; cb are non-negative, and at least one eigenvalue is strictly positive.
To see what these conditions imply, imagine differentiating the condition V , a [χ(σ)] = 0 with respect to the arc-length, σ, along the trough. This gives Eq. (B.1) states that (for all σ) the vectorχ a is a zero eigenvector of the mass matrix: A a bχ b = 0, showing that this matrix must have a zero eigenvalue.
Repeatedly differentiating with respect to σ gives the further identities involving higher derivatives of V : and so on. In general the second term does not vanish, since the direction defined by the bottom of the trough need not be a geodesic of the target-space metric, G ab .
The radius of curvature, κ(σ), of the trough's valley floor is also easily computed in terms of derivatives of the potential V . This is because the tangent,χ a , is a unit vector, 18 Given the Weinberg curvature convention [21] in which we work, the Ricci scalar is negative for a target space two-sphere of radius ρ.
G abχ aχb = 1, provided the parameter, σ, along the curve is arc-length. This ensures that it must be orthogonal to its derivative along the curve: and so defining the unit vector in the Dχ a /dσ direction by n a , the radius of curvature of the trough's valley floor is defined by When there are only two fields the same arguments just given also give a simple expression for D n a /dσ. Since n a is a unit vector, G ab n a n b = 1, its derivative along χ a (σ) must be perpendicular to itself: G ab n a (D n b /dσ) = 0, and so D n a /dσ must be parallel toχ a . The coefficient can be found by differentiating the condition G ab n aχb = 0 along the curve, giving When there are only two fields, let m 2 (σ) denote the strictly positive eigenvalue of the mass matrix that is required by condition (ii) above, and let e a + be the corresponding normalized eigenvector. Then we have where the first equality holds becauseχ a is a zero eigenvector of the mass matrix. Since m 2 (σ) is strictly positive, it follows that e a + is orthogonal toχ a , and thus e a + = n a . Therefore, We can obtain another interesting identity by differentiating equation (B.8) with respect to σ: Using (B.6), and the fact thatχ a is a zero eigenvector of the mass matrix, this becomes Contracting equation (B.13) with n a yields the identity V ; abc n a n bχc = dm 2 (σ) dσ , (B.14) whereas contracting equation (B.13) withχ a yields equation (B.10).
Now, writing the commutator of two covariant derivatives in terms of the curvature, we find that where (· · ·) denotes the normalized completely symmetric product: V ; (a 1 ..an) = 1 n! (V ; a 1 ..an + permutations). It is important to note that unlike the identity V ; ab = V ; (ab) , which holds everywhere, equation (B.16) only holds along the curve χ a (σ).
In summary, we have obtained formulas for all possible contractions of third covariant derivatives of V withχ a or n a , in terms of m,ṁ, κ, and V nnn ≡ V ;abc n a n b n c . This last quantity measures how the walls of the trough deviate from a perfect parabola. . On the other hand, contracting with n a yields V ; abcd n a n bχcχd Finally, another identity is obtained by differentiating V nnn along the trough, and using (B.14): Now, to find the symmetries of V ; abcd we use In summary, it is possible to obtain formulas for all possible contractions of fourth covariant derivatives of V withχ a or n a , in terms of m,ṁ,m, κ,κ, ρ, V nnn ,V nnn , and V nnnn ≡ V ; abcd n a n b n c n d .
Tilted troughs
We next turn to the situation where the trough is not completely level, but with derivatives along the trough assumed to be parametrically small rather than zero. shows that n a andχ a need no longer be eigenvectors of the matrix A a b . Instead, we have where we define m 2 (σ) := V ; ab n a n b . (B.31) In matrix notation, Diagonalizing this matrix, we find the heavy eigenvalue with corresponding eigenvector = n a cos θ +χ a sin θ , The light eigenvalue similarly is Also, we introduce the following notation for non-symmetrized (NS) derivatives: V NS tnn ≡ V ; abcχ a n b n c , V NS ntn ≡ V ; abc n aχb n c , etc. (B.45) In this new notation, we have Combining the second equation of (B.51) with (B.49) yields Therefore, the first equation of (B.51) finally becomes In summary, we have obtained formulas for all possible contractions of third covariant derivatives of V withχ a or n a , in terms of m,ṁ, κ,κ,U ,Ü , Ü˙, ρ, and V nnn .
Now, let us define
These quantities are important, because they appear in the low-energy effective Lagrangian.
It is useful to expand these complicated expressions in inverse powers of m. We find where we define It is sometimes convenient to expand in inverse powers of M 2 ≡ M 2 + ≈ m 2 +U 2 /κ 2 m 2 , the physical mass of the heavy field, rather than m 2 . These are related by Employing the above relations to re-express (B.60) in terms of M yields The first and second derivatives of V , when expanded in inverse powers of M , simply become Before going on to calculate the fourth derivatives, we make a remark about dimensional analysis, which becomes useful due to the proliferation of terms as one takes more derivatives.
We use canonical relativistic units, in which = c = 1. Also, for simplicity, we take d = 4. Then Differentiating equation (B.42) and simplifying yields where we have written V nnn = (m 2 /κ)λ nnn . Finally, differentiating the definition V nnn ≡ V ; abc n a n b n c and using (B.52) yields Now we look at the symmetries of the fourth derivatives. The generalization of (B.25) to tilted troughs is and the generalization of (B.26) is: where ρ ,n ≡ n a ∇ a ρ is the normal derivative of the target-space curvature radius. Now, we Combining this equation with the first equation of (B.70) and the first equation of (B.71) where in the second equality we have used the expression for V NS nttt given by equation (B.67).
Next, let's calculate Using the third equation of (B.70), and the second and fourth equations of (B.71), we may write this as where in the second equality we have used the expression for V NS nntt given by equation (B.68), and recall that V nnn = (m 2 /κ)λ nnn . Finally, let's calculate Using the second equation of (B.70) and the third equation of (B.71), we may write this as where in the second equality we have used the expression for V NS nnnt given by equation (B.69). The next step, is to calculate the fourth derivatives in the light and heavy directions.
Expanding these in inverse powers of m 2 yields obtained by repeatedly integrating by parts the two-derivative interactions Finally, the J (i) are given by and J (4) := 1 6 V hhhh .
Integrating out h
To integrate out the h field we compute and so (C.13) Here the superscript E indicates that this is an expansion 20 in powers of M −1 (as opposed to our later expansions in inverse powers of M ).
We next assume that the scale M 2 dominates all of the others in M 2 , and gather terms that are suppressed by a fixed power of 1/M 2 . This leads to where Notice that this expansion, and the effective field theory to which it leads, would break down if the terms in M 2 were to cancel one another so that M 2 were small.
Expressions in terms of U , κ and ρ The final step is to trade symmetrized derivatives like V ℓ , V h , V ℓℓℓ , as well as the mass eigenvalues M 2 = M 2 + and µ 2 = M 2 − , for U , m, κ and ρ and their derivatives. This step is a crucial one because some of the interactions -like V ℓℓh in eq. (2.28) or the quartic interactions V ℓℓhh and V ℓℓℓℓ computed in appendix B -contain terms proportional to a positive power of m 2 , allowing them to contribute to higher order in the 1/m 2 expansion than naively expected.
The formulae relevant for performing this replacement are given in earlier sections and the Appendices, but are reproduced here for convenience of reference: Inserting these into the effective Lagrangian leads to the following, intermediate, form for the action out to four-derivative order In all of these expressions we keep only sufficient powers of the light field to track the action out to quartic order in ℓ. The detailed form of the two functions K 1 and K 2 is less important for later purposes, but they are formally given by The action quoted above is only 'intermediate' because the terms involving ℓ can be absorbed into the others by making the field redefinition [10] ℓ → ℓ + ∆(ℓ) , (C. 26) which changes the action by a term ∆L eff = Ĝ ℓ − V ′ eff +Ĝ ′ 2 (∂ℓ) 2 ∆(ℓ) (C.27) where primes denote differentiation with respect to ℓ, and the approximate equality assumes ∆(ℓ) is at least quadratic in ℓ and drops terms in ∆L that involve more than four derivatives or four powers of ℓ.
and so after integrating the last term in (C.30) by parts, one arrives at the effective action | 14,813.4 | 2012-09-25T00:00:00.000 | [
"Physics"
] |
Removal of asbestos as an intrusive contaminant from concrete construction waste
The construction industry is the world's largest and fastest‐growing industry due to the increase in population, standards of living, and the higher demand for infrastructure. This fast growth generates huge amounts of construction and demolition waste (C&D waste), which amounts to more than 25% of the total generated waste, which has become a serious environmental challenge that needs to be addressed. The asbestos content in C&D waste poses a health risk and is entitled to special care, however, disposal of asbestos as hazardous waste is the only option by law. The present paper suggests the selective demolition of asbestos‐containing demolished waste rubble to be disposed of in compliance with all local and state regulations and proposes non‐asbestos rubble fraction to be recycled as an alternative sustainable management option that mitigates different adverse environmental impacts of the presently used conventional C&D waste management method.
Introduction
To consummate the necessity of a growing world population, the need for urban expansion, the connection between cities, and demand for the construction of buildings, residences, paving, urban maintenance, roads, and train lines are the least.The existing constructions need to be updated according to the updated and environmentally friendly construction laws, therefore rebuilding is often observed.The execution of such extensive engineering works requires the usage of millions of tons of natural resources, for example, aggregates, cement, water, wood, and various metals to name a few.To manage the need, exploration of natural resources reserve is carried out however, with this large amount of natural resource extraction, potential environmental impacts must be considered.At the same time, the scarcity of virgin raw materials has enhanced the importance of recycling building materials manyfold.The fast-growing need for construction and demolition generates huge construction and demolition waste (C&D waste).In general, the C&D waste amounts are more than a quarter of the total generated solid waste [1] [2].To manage huge amounts of C&D waste and to be able to be reused back in material flow is the absolute need of the current time.
Since the demolition of buildings and other infrastructure produces much more waste than construction activities, demolition projects often create 20 to 30 times as much waste as construction projects [3], the development of processes to effectively reuse and recycle demolition materials is important for reducing landfilled C&D waste as well as promoting circular economy.In the context of demolition waste, Crushed Concrete in particular is a popular recycling material.Recycling of concrete is often restrained due to the hazardous impurity contents, that are hard to separate as well as to recycle.Particularly, asbestos contamination came into focus after law enforcement and as an impact of various studies worldwide.Asbestos is found in various mineral products such as wall reinforcements, spacers, and tile adhesives, and poses unusually difficult to detect and separate as they form a strong bond with concrete.
As asbestos is categorized as carcinogenic and thus dangerous for human health therefore a ban is imposed on asbestos use since 1993 in Germany.The complete exclusion of asbestos must be observed in any new construction, as well as the rejection of asbestos in any of its fibrous configurations from the recycling route of concrete is mandatory.Eliminating asbestos in concrete recycling will result in increased concrete recycling with a better circular material flow cycle.
Using the deconstruction of the quay wall as an example, this paper presents different life cycle assessments for practicable sustainable options that focus on the potential CO2 footprint of the entire process from detection to the
Abstract
The construction industry is the world's largest and fastest-growing industry due to the increase in population, standards of living, and the higher demand for infrastructure.This fast growth generates huge amounts of construction and demolition waste (C&D waste), which amounts to more than 25% of the total generated waste, which has become a serious environmental challenge that needs to be addressed.The asbestos content in C&D waste poses a health risk and is entitled to special care, however, disposal of asbestos as hazardous waste is the only option by law.The present paper suggests the selective demolition of asbestos-containing demolished waste rubble to be disposed of in compliance with all local and state regulations and proposes non-asbestos rubble fraction to be recycled as an alternative sustainable management option that mitigates different adverse environmental impacts of the presently used conventional C&D waste management method.
removal of asbestos and recycling of concrete.The application of Life Cycle Assessment in the building sector has improved a lot in recent years [4].The increased interest is due to the comprehensiveness of the LCA method for considering many aspects of the environmental impacts of a building [5].This paper uses the ReThiNK EPD app (developed by Kiwa Deutschland) to quantify the potential CO2 footprint and other environmental impact factors.
Life cycle assessment
There are different ways to gauge the amount of pollution emitted during every step of the life cycle of a building, however, the current paper focuses on the demolition and end-of-life stage in the construction industry.The Life Cycle Assessment (LCA) is an internationally standardized methodology for environmental assessment, applied to evaluate the environmental impact of a product or system [6][7].
This methodology can be used for modeling and simulation of waste management scenarios, in the present paper the ReThiNK app [8] is used for the assessment, while the required data for the life cycle inventory is either from the literature, the lab-scale experiments or surveying the recycling facilities [9][10].
Goal and Scope
The present study aims to quantify different environmental impact factors in the process of recycling the demolition waste produced, to assess impact categories for the two scenarios: selective demolition of asbestos-containing segment followed by wrecking the whole structure and recycling the non-asbestos part whereas the asbestos parts end up in controlled landfills; compared with asbestos contained construction that demolished at once and ends up at landfill that deal with hazardous waste: the scenarios are pictorially described in Fig. 1.The focal point is the selective demolition to restrict asbestos content to go further in material flow.
System Boundary
In the first step of LCA, the boundaries of systems are defined to identify inputs and outputs, to consider all processes, the input data on energy flows and material flows, and output data related to specific issues.In the present work, the system boundary falls into the end-of-life category, which comprises the demolition phase and evaluation of the recycling possibilities.
Inventory analysis
The inventory phase is collecting all sorts of information using surveys, calculations, and analyzing comparatively with studies from literature, for all the sectors involving materials, energy, and fuels.After data inventory collection and data normalization to the functional unit, the environmental impact was evaluated.
The designated demolition company and recycling facility were interviewed, and a survey was carried out, moreover, machine specifications and construction guidelines for specific asbestos-containing parts used were referenced for the literature data needed for the analysis.
Life cycle impact assessment
Life cycle impact assessment is the phase in the LCA aiming at understanding and evaluating the magnitude and significance of the potential environmental impacts of a product system.The life cycle of a product ranges from resource extraction via material processing, manufacturing, and product use or service delivery, to recycling, and the disposal of any remaining waste [11].In the present paper Global warming potential, ozone layer depletion, acidification of soil and water, eutrophication, and human toxicity are the environmental impact factors that are taken into account and assessed in the case of demolition and disposal or recycling of asbestos-contained construction.
Result and Discussion
Fig. 1 illustrates the two different scenarios with their system boundaries addressed and discussed in this paper.Scenario 1 depicts the demolition of a concrete structure that contains asbestos, after the inspection, the majority of dismantled concrete rubbles were landfilled in different landfill sites as per their hazardous nature.Whereas the second scenario describes the demolition of asbestos-contained parts after inspection that is disposed of in a controlled landfill designated for hazardous wastes leaving the non-asbestos concrete rubbles to be further recycled and reused.
Traditional demolition practices in which all building materials are mixed create a waste stream that is difficult and costly to recycle, in contrast, the separation of materials at the demolition site through selective demolition or other means is often the most effective way to ensure a clean, uncontaminated product [12].Since carcinogenic asbestos is involved in the present work, precise separation is obliged and proper handling is imposed by the law.
Global Warming Potential
Global warming potential, abbreviated as GWP, is a term used to describe the relative potency of a greenhouse gas, taking into account how long it remains active in the atmosphere.
Fig: 2 shows the global warming potential of both addressed scenarios, as calculated with the help of ReTHiNK web-based LCA software.The global warming potential for scenario 1 is 68,190876 kg CO 2 eq whereas for scenario 2 it is 87,7916149 kg CO 2 eq.It is evident that the recycling of a non-asbestos fraction of the demolished waste contributes an additional amount of GWP, however, a more circular material can be achieved with the recycling and reuse of non-asbestos demolished waste rubble i.e in scenario 2.
Ozone layer depletion
The ozone-depleting potential is a measure of how much damage a chemical can cause to the ozone layer compared with a similar mass of trichlorofluoromethane (CFC-11).CFC-11, with an ozone-depleting potential of 1.0, is used as the base figure for measuring ozone-depleting Potential [13].landfilling of huge C&D waste has an adverse effect on ozone layer depletion as one of the foremost environmental impacts.With a huge percentage of the pollution that can be attributed to the construction industry on a global scale reaching 50% in landfill waste, ozone depletion, and climate change gases, it is pivotal that the construction and demolition industry move forward in implementing preventive measures to decrease catastrophic effects [14].With a little high ozone layer depletion potential Scenario 2 limits landfill activities by choosing to recycle non-asbestos concrete rebel fraction to be reused further in the building industry, leaving behind only the asbestos part to be landfilled in a controlled, designated facility, and thus scenario 2 is a better situation to opt and practice.
Acidification of soil and water
Soil acidification is a process where the soil pH decreases over time and effect adversely soil and subsoil.The process is accelerated by human activities, unconscious agricultural activities, uncontrolled waste management, and dated landfilling actions to name a few.
Fig. 4 shows the soil and water acidification potential of both scenarios assessed in the present work.Scenario 1 has the value 0,45689576 Kg SO2 Equivalent, whereas a small increased value of 0,68325713Kg SO2 Equivalent is for scenario 2. Scenario 2 comprises a recycling activity and therefore it has a slight increase in acidification potential, however, in scenario 1 almost all the concrete rubble ends up in landfill sites that deal with asbestos and other hazardous material.It has been reported that more than 50% of construction and demolition waste is deposited in landfill sites, which forms a real environmental challenge for every country, that needs to be addressed [15].The enormous requirement of land for landfill purposes for growing demolition waste is a previously pointed problem, in addition, the probability of high pH leachate leaching from these landfill sites is another threatening issue to handle over time.Therefore, it is beneficial to recycle concrete rubble to enhance circularity rather disposing at a landfill site.
Eutrophication
An overabundance of nutrients, primarily nitrogen, and phosphorus in a water body leads to a process called eutrophication that has harmful health and environmental effects.
Figure 5 Eutrophication The eutrophication potential is presented in Fig. 5.The eutrophication potential for scenario 1 is 0,10328768 Kg PO4 Equivalent whereas for scenario 2 it is 0,14671303 Kg PO4 Equivalent.The difference in eutrophication potential for both scenarios is negligible even though the second scenario steps up substantially in circularity and as a result, the asbestos-free material flow can be achieved.
Human toxicity
The human toxicity potential (HTP), is used to weigh emissions inventoried as part of a life-cycle assessment, a calculated index that reflects the potential of a unit of chemical released into the environment.As asbestos exposure has carcinogenic potential and is thus banned from a major fraction of the developed world, quantifying the human toxicity associated with both scenarios is needful to perform.fraction, however, the recycling of non-asbestos fraction i.e, the asbestos-free material flow orients well with the aim of the present work as well as satiate the growing need for production of energy incentive construction materials.
Conclusion
Life cycle assessment with the help of the ReTHiNK app of asbestos-containing concrete demolition waste was done and demonstrated based on the primary data collected, for five main environmental impact categories.The study demonstrates two different scenarios, where in the first the major fraction of demolished waste ends up in a controlled landfill while the second one fosters the recycling of non-asbestos fraction and landfill only the asbestoscontaminated rubble.The five environmental impact factors that are assessed in the present study are slightly increased for the second scenario, however, the increased value corresponds to the recycling activity which facilitates better circularity in a bigger perspective.
The removal of carcinogenic asbestos content from the material flow can be achieved by selective demolition and disposal in compliance with all local and state regulations followed by the recycling of non-asbestos C&D waste contributes significantly to achieving sustainable development through the following gains: • Reducing the demand for primary materials by replacing them with secondary recycled (asbestosfree) materials.
•
Cut down energy consumption that corresponds to primary materials extraction, transport, and production energy costs, and reuses waste that can otherwise be lost to landfills and may lead to the severe environmental problem over an extended period such as toxic leachate leaches to soil, or water.Consequently, the land used, and several long-term adverse environmental effects can be avoided by limiting the landfilled waste quantity.
•
Although landfills will continue to be an important disposal option, especially for the asbestos-contained fraction until the proper recycling technique is developed and practiced for the same, the recycling of C&D waste will reduce the possible environmental risk by minimizing the amounts going to landfilling.
Figure 1
Figure 1 System boundaries for the scenarios
Figure 2
Figure 2 Global warming potential
Fig. 3
Fig.3shows the ozone layer depletion potential of both scenarios assessed in the present paper.Scenario 1 has the value of 1,32E-05 Kg CFC-11 Equivalent while scenario 2 has a little potential of 2,72E-05 Kg CFC-11 Equivalent.The slight increase in the second scenario is given the fact of the additional recycling process.
Figure 3
Figure 3 Ozone layer depletion
Figure 4
Figure 4 Acidification of soil and water
Figure 6
Figure 6 Human toxicityFig.6illustrates the human toxicity (cancer) potential for scenario 1 is 4,91E-07 CTUh while a slight increase is evident for scenario 2 and the value is 5,92E-07CTUh.The slight increase in toxicity potential resulting from the various activities involved in recycling and transporting the nonasbestos demolished | 3,480.4 | 2023-12-01T00:00:00.000 | [
"Environmental Science",
"Engineering"
] |
LSTM-CRF Neural Network With Gated Self Attention for Chinese NER
Named entity recognition (NER) is an essential part of natural language processing tasks. Chinese NER task is different from the many European languages due to the lack of natural delimiters. Therefore, Chinese Word Segmentation (CWS) is usually regarded as the first step of processing Chinese NER. However, the word-based NER models relying on CWS are more vulnerable to incorrectly segmented entity boundaries and the presence of out-of-vocabulary (OOV) words. In this paper, we propose a novel character-based Gated Convolutional Recurrent neural network with Attention called GCRA for Chinese NER task. In particular, we introduce a hybrid convolutional neural network with gating filter mechanism to capture local context information and a highway neural network after LSTM to select characters of interest. The additional gated self-attention mechanism is used to capture the global dependencies from different multiple subspaces and arbitrary adjacent characters. We evaluate the performance of our proposed model on three datasets, including SIGHAN bakeoff 2006 MSRA, Chinese Resume, and Literature NER dataset. The experiment results show that our model outperforms other state-of-the-art models without relying on any external resources like lexicons and multi-task joint training.
I. INTRODUCTION
Named entity recognition (NER) plays a critical role in the field of natural language processing (NLP).This task aims to extract and categorize entities with specific meanings in the unstructured text, such as person (PER), location (LOC), and organization (ORG), etc. NER is one of the most widely used and key technologies in information extraction.Also, it is the chief work of NLP tasks such as relation extraction [1], event extraction [2], and question answering system [3].Therefore, it has a high value of utility to conduct in-depth research on the NER task.
Compared with the NER of Indo-European languages represented by English, Chinese NER task is more complicated.
The associate editor coordinating the review of this manuscript and approving it for publication was Qichun Zhang .
There are apparent inflections in English (singular, plural, tense, etc.), but Chinese lacks these inflections.Besides, Chinese has the problems of fuzzy word boundaries, complex entity structure, and various forms of expression, which make the Chinese NER task more difficult.Therefore, the correct identification of named entities in Chinese text is of great significance for subsequent Chinese information processing tasks.
At present, a mature method to solve the NER task is to model the NER problem into a sequence labeling problem.The standard method of existing state-of-the-art models for English NER can effectively capture context feature information by using BiLSTM-CRF models [4]- [7].However, there are no apparent delimiters between words in Chinese sentences, and we usually perform word segmentation before the sequence is fed into the word-based model.Each segmented word is mapped to fixed-length word representation.Then we use the word-level sequence labeling model, which is the same as the method of dealing with English NER.
However, entity boundaries are associated with segmentation results.The performance of subsequent NER task is limited by the incorrect NER labeling, which results from segmentation errors.Moreover, many named entities are considered as OOV words in the word-based model because of the large number of Chinese words.Besides, after the word segmentation of the word-based model, the parameter size of the embedding layer is significantly increased, which result in data sparsely problems and lead to overfitting.Let's take '' (Nanjing Yangtze River Bridge)'' as a typical example.Due to the limitations of Chinese linguistic features, the boundaries of characters (words) are often ambiguous.The same sentence may have distinct segmentation after performing word segmentation.For different word segmentation granularity, the sequence '' '' can be divided into '' (Nanjing City)/ (Yangtze River Bridge)'' and '' (Nanjing City)/ (Mayor)/ (Daqiao Jiang)'' respectively.As shown in Table 1, after performing word segmentation, we may get completely different recognition boundary information, which leads to two distinct sequence labeling outcomes.The word-based models cannot judge right or wrong, which results in incorrect entity recognition.Recently, studies have shown that character-level representation can avoid many of the listed above problems.And researchers found word-based models underperform character-based models in deep learning-based Chinese NER task [8]- [11].Due to the polysemy and polymorphism of Chinese characters, the NER based on the pure character only focuses on the per-character information for losing the latent word and word sequence information.For this problem, it is worth exploring how to effectively integrate segmentation information into character-based models for better semantic understanding.
To overcome the shortcomings of the traditional characterbased models, we propose a new neural network, called the GCRA, to improve the performance of Chinese NER task.Firstly, for the embedding layer, we apply the label segmentation vector softly concatenating into character embeddings.It uses word sequence information indirectly.So the model can not only avoid the problem of error propagation caused by word segmentation error but also achieve excellent results based on character and word information.Next, the character representation is fed into the hybrid gated convolutional layer to carry out detailed feature extraction and generate implicitly local feature information connection.Further, the highway neural network [12] is utilized to refine the hidden representation of BiLSTM.Finally, the self-attention layer is employed to capture context-related information in different multiple subspaces, which can better understand the sentence structure and ultimately improve the performance.
In this paper, we compare our model with the state-of-theart methods on three datasets, including SIGHAN bakeoff 2006 MSRA, Chinese Resume, and Literature NER dataset.The three datasets come from news domain, social media domain, and literature domain respectively.
The main contributions of this paper can be summarized as follows: • We propose a novel neural model called the GCRA model for Chinese NER task.The model can not only exploit local context features effectively but also capture the global dependencies of the whole character sequence.
• We design a character-level hybrid gated convolutional neural network which combines the dilated gated convolution with the standard gated convolution.It can effectively generate local feature information connection and avoid gradient vanishing during training.
• We conduct our experiment on various Chinese NER datasets in different domains.The experimental results demonstrate that our model outperforms other stateof-the-art models without using any external lexicon resources and multi-task joint training.The remainder of the paper is organized as follows.Section II reviews the related work on Chinese NER.Section III presents the main idea of the proposed GCRA model.Section IV demonstrates the experimental results and analysis.Section V concludes our works.
II. RELATED WORK
Significant research has devoted to the NER task.The NER system in early was mainly based on rules and dictionaries, which has the shortcoming of poor expansibility and absent ability in finding OOV words.With the advent of statistical machine learning, the NER task is abstracted into a sequence labeling problem.Traditional sequence labeling models extensively utilized Hidden Markov Models (HMM) [13] and Conditional Random Fields (CRF) [14] in the NER task.However, all these models are heavily relying on feature engineering and external resources.
In recent years, deep learning has provided a new approach to solve the problems of natural language processing, which has attracted considerable critical attention.Given the shortcomings of feature engineering, deep learning is proposed as a useful tool for automatic learning, distributed representation of words, and deep feature extraction.Deep neural networks are used in deep learning to replace the artificial feature engineering model of traditional machine learning.To address the NER problems in the English field, models based on neural network demonstrate their excellent performance in identifying entities.Collobert et al. [15] proposed CNN-CRF model to extract the depth feature for sequence labeling tasks automatically.Huang et al. [16] proposed a bidirectional LSTM-CRF network structure for sequence tagging task.But their models use the feature connection tricks to combine the hand-crafted spelling features and context features with word embeddings as the input vectors to the neural network.Lample et al. [4] presented a bidirectional LSTM-CRF architecture which combines wordlevel features with character-level features, and they applied another LSTM layer to generate character-level features.Similarly, Ma and Hovy [5] conducted the character Convolutional Neural Network (CNN) to extract English characterlevel features based on the LSTM-CRF network structure.Chiu and Nichols [6] reported a hybrid of bidirectional LSTM and CNNs structure, which automatically detects word-level and character-level features.
The development of Chinese NER research is relatively late, and the related research is more difficult because of the particularity of Chinese word information.Some researchers also consider Chinese NER task as a character sequence labeling problem and take advantage of external data to compensate for insufficient annotated corpus resources.In particular, in Collobert et al. [15], Passos et al. [17], Huang et al. [16], and Luo et al. [18], the researchers leveraged lexicon features to improve performance.Peters et al. [19] pre-trained a neural bidirectional language model to augment word representations by introducing character-level knowledge.
The existing research indicates that the character-based methods are considered as an empirically better choice than word-based methods [8]- [11].However, the characterbased NER models carry only a limited amount of character information and cannot fully exploit latent word and word sequence information.To solve this problem, some researchers have studied how to better leverage wordlevel information for Chinese NER task.Some proposed to use segmentation information as soft features for NER task [20], [21].Peng and Dredze [22] and Cao et al. [23] designed a multi-task learning model for joint learning Chinese NER tagging and Chinese word segmentation task simultaneously.Zhang and Yang [24] integrated latent wordlevel information into a character-based LSTM-CRF model by identifying candidate lexicon words from the sentence using a lattice-structured LSTM model.Zhang et al. [25] investigated a dynamic meta-embeddings method and applied it to Chinese NER task.They utilized the attention mechanism to combine features of both character and word granularity in the embedding layer.In the work of Zhu and Wang [26], they proposed a Convolutional Attention Network model, which used word segmentation vector as soft features to improve Chinese NER model performance.Their work precluded any external word embeddings and lexicon resources dependencies.
In our work, we enhance the input representation by utilizing the segmentation label vector concatenating into character embeddings directly.Besides, we design the hybrid gated convolution layer and gated self-attention network, which can effectively alleviate gradient vanishing during training and capture depth detailed feature.Experiments on several series of datasets show that our proposed GCRA model can significantly improve the performance of the Chinese NER task.
III. MODELS
As with most named entity recognition methods, our work also turns NER task into a sequence labeling problem.To eliminate the effects of word segmentation error propagation, we utilize character-level BiLSTM-CRF as our basic structure and apply the BIOES tagging scheme for the Chinese NER task.The overview architecture of our proposed model is shown in Figure 1.The model mainly consists of five layers: embedding layer, hybrid gated convolution layer, highway BiLSTM layer, gated self-attention layer, and CRF decode layer.Each part of our proposed model will be presented in detail in the following sections.
A. EMBEDDING LAYER
Most research shows that applying segmentation as soft features for character-based Chinese NER models can lead to improved performance [20], [21].In this work, we concatenate the segmentation label vector into character embedding for augmenting the input representation.The word segmentation information is represented by BIOES scheme.Formally, in the Chinese NER task, we denote a input sentence as X = {x 1 , x 2 , . . ., x n }, where x i represents the ith character in the sentence X .Then, we map discrete characters into the distributed feature representations on the embedding layer.The input representation for each character is embedded in distributional space as x c i : where e c and e s denote a pre-trained character embedding lookup table and a BIOES scheme segmentation label embedding lookup table, respectively.And the ⊕ is the connection operator.The formula seg (x i ) represents the segmentation label of each character x i which is given by a word segmenter.
B. HYBRID GATED CONVOLUTION LAYER
We use hybrid gated convolutions to extract local feature information connection and context information.As shown in Figure 2, it has two separate blocks.The left block is the dilated gated convolution block, which consists of two layers of dilated convolution and a gated filtering mechanism.It is similar to the highway network.The right block is the normal gated convolution block, which has a standard convolutional layer with gated linear units [27].We splice the two separate outputs together as the final output of the hybrid gated convolution layer.
1) NORMAL GATED CONVOLUTION
Dauphin et al. [27] have shown that the gating mechanism can improve the performance of language modeling tasks.The gated convolutional network adds a gating switch to control the information flow.These gates can alleviate gradient vanishing during training since there is a convolution without any activation function.For the embedding output X , the gated convolution layer output can be expressed as: where * denotes convolution operator, W and V with b and c denote kernels and biases respectively, which are parameters to be learned.σ represents the sigmoid function, and ⊕ means the element-wise product between the matrix.With dilation d, the convolutional operator is applied to each token x t with output c t is defined as: where dilation d = 1 is equivalent to a normal convolution.Wu et al. [29] proposed gated linear dilated residual network for reading comprehension task, which mainly consists of dilated convolution and gated linear units with the residual connection.For our dilated gated convolution block, we also use dilated convolution instead of normal convolution to extend the receptive field.But for gated filtering mechanism, it is more similar to the highway network.We combine the residual connection and gated convolutional neural network to achieve selective multi-channel transmission of information.We use C(X ) to represent the output of the dilated convolution.The final dilated gated convolution block output can be expressed as: where X is the input of this layer, C 1 (X ) and C 2 (X ) mean different dilated convolution output respectively.σ represents the sigmoid function, and ⊗ denotes the element-wise product between the matrix.After comparing to experimental results with the different dilated rate, we use two-layer dilated gated convolutions with dilated rate 1 and 2. So the output of a hybrid gated convolution is as follows: where the ⊕ represents the connection operator.
C. HIGHWAY-LSTM LAYER
Hochreiter and Schmidhuber [30] proposed LSTM to solve gradient vanishing and exploding of traditional recurrent neural network.The key role is to utilize adaptive gating mechanism and the memory cell.A typical LSTM cell structure is depicted in Figure 3. signal strength flowing to the next unit, and the forget gate f t is used to control the cell state before forgetting.Defining g = [g 1 , g 2 , . . ., g n ] outputted by CNN layer as input.Then, the LSTM units at step t could be expressed as: where The unidirectional LSTM only retains information from the past sequence of vectors, because the hidden state flow is passed from the front to back.To leverage the past and future sequence information, we use a bidirectional LSTM to capture the context features for sentence.So the hidden state of BiLSTM is as follows: where − → h t ∈ R d h and ← − h t ∈ R d h are the hidden states of the forward and backward LSTM at position t, respectively.The ⊕ represents the connection operator.
Highway network allows information to pass through layers of the deep neural network at high speed, which effectively slows down the problems of the gradient.In this paper, we use the highway network to control the information flow with an adaptive gate network.The overview architecture of highway-LSTM is illustrated in Figure 4.The output of highway-LSTM layer is calculated as follows: where σ is the element-wise sigmoid function, ⊗ is the element-wise product, and f is the rectified linear unit.The W g , W h and b g , b h represent the weight matrix and bias vectors, respectively.The tg denotes the transform gate, which controls how much information is converted and passed to the next layer.And the (1 − tg) is called carry gate, which allows the input to be passed to the next layer directly.Therefore, the highway network input h and output z require to be the same shape.
D. GATED SELF-ATTENTION LAYER
Self-Attention is a mechanism of attention that relates different locations of a single sequence to calculate an interactive representation of the sequence.Recent evidence suggests that it performs well on a variety of tasks, such as machine translation [31], semantic role labeling [32], and relation extraction [33].Inspired by these works, we utilize the multihead self-attention mechanism to capture the global sequence information from multiple subspaces and exploit the inner features contained in the text.Attention is essentially a mapping function consisting of many Queries and Key-values.For self-attention, we use the highway-LSTM output Z = [z 1 , z 2 , . . ., z n ] to initialize Q, K, and V.The scaled dotproduct attention could be calculated as: where Q ∈ R n×2 d h , R ∈ R n×2 d h and V ∈ R n×2 d h denote query matrix, keys matrix and value matrix respectively.√ d k equals the dimension of hidden units of BiLSTM, and plays a regulating role, controlling the inner product of Q and K not too large.
The essence of multi-head attention is to perform multiple self-attention calculations, which can make the model capture more features from different representation subspaces.The multi-head attention mechanism will linearly project the Q, K, and V through the parameter matrix without the sharing of parameters, and then perform the scaled dot-product attention.This process repeats for m times in parallel, and finally splices the results and linearly projects to get the new representation.The final result of S could be expressed as: where The tag of each position in the sentence has different degrees of dependence on the context.We introduce a gating mechanism to generate a representation combining context features and self-features.The gated output representation can be expressed as: where σ is the sigmoid function, ⊗ is the element-wise product, and ⊕ represents the connection operator.Finally, we carry out a fully connected layer to compute the probability scoring matrix.It can be described as: where W p ∈ R |k|×4 d n and b p ∈ R |k| are the trainable parameters.|k| denotes the number of output labels, and n is the length of the input sequence.O is the output probability matrix, whose size is n × k.
E. CRF LAYER
In the NER sequence labeling task, there is a strong dependency between the tags of adjacent characters.For example, the I-PER (I-person) tag should be followed by a B-PER (B-person) tag or I-PER tag.Also, the I-LOC (I-location) tag cannot appear behind the B-PER tag or S-PER (S-person) tag.Therefore, instead of making independent tagging decisions using the output of the fully connected layers, we utilize CRF to inference the entity tags outputs of a sequence jointly.The CRF can express this dependence and add some constraints to the final predicted tag sequence effectively.
The CRF layer is trained to predict the most possible tag sequence y = {y 1 , y 2 , . . ., y n } for a given sentence X = {x 1 , x 2 , . . ., x n }.The score of the tag sequence can be calculated as: where O i,y i represents the score of the y i th tag of the ith character x i in the sentence.T is a transition score matrix, which denotes the scores of transition from tag i to tag j. y 0 and y n+1 in the formula represent the start and end tags of a sentence, and we add them to the possible tag sets.Therefore, T is a square matrix of size k + 2.Then, the probability of the ground-truth label sequence y is defined as: where ỹ denotes an arbitrary label sequence, and Y x is the set of all possible output label sequences for the input X .
In decoding, we use the Viterbi algorithm [34] to predict the best path that obtains the highest scoring mark sequence: Given a set of manually labeled data {(x i , y i )}| N i=1 , we add L2 regularization to the negative log-likelihood loss for training.The specific loss function is as follows: where λ is the L2 regularization hyper-parameter, and θ denotes the parameter set.For training, we minimize the loss function L through shuffled mini-batches stochastic gradient descent method with the Adam update rule.
IV. EXPERIMENTS
In this section, to evaluate the effectiveness of the proposed GCRA model, we compare our model with previous state-ofthe-art methods on different Chinese NER datasets.We will describe the details of different datasets, settings of parameters, and results of our experiments.
A. DATASETS
We evaluate our proposed model on three Chinese NER datasets, which include MSRA NER dataset [35], Literature NER dataset [36], and Chinese resume dataset [24].
Table 2 provides detailed statistic information for each dataset.
• MSRA dataset comes from SIGHAN 2006 shared task for Chinese NER [35].This dataset is news in simplified Chinese, which contains three annotated named entity types: PER (Person), ORG (Organization) and LOC (Location).The development set is not available in the MSRA dataset.Therefore, we sample 10% data of training set as the development set.
• Literature dataset is annotated from hundreds of Chinese literature articles, which contain seven entity types: Thing, Person, Location, Time, Metric, Organization, and Abstract.The training, development, and test sets have been divided on the Literature dataset.
• Resume dataset consists of resume of senior executives from listed companies in the Chinese stock market, which contains eight types of named entities: CONT (Country), EDU (Educational Institution), LOC, PER, ORG, PRO (Profession), RACE (Ethnicity Background), and TITLE (Job Title).
B. EXPERIMENTAL SETTINGS
We adopt BIOES tagging scheme where each character in the corpus is labeled as one of B (Begin), I (Inside), O (Outside), E (End), and S (Single).Studies have suggested that BIOES scheme is remarkably better than BIO scheme since BIOES can get more detailed position information [37].Table 3 shows the values of hyper-parameters for our model.In particular, we make our parameter selection according to the performance on the development set of datasets.We set the character embedding size, hidden sizes of CNN and Bi-LSTM to 300 dims.The sliding window size of all convolutional layers is set to 3. The highway gate bias is initialized with −1 vector.We exploited Adam [38] as the model optimization with an initial learning rate of 0.001, and the gradient norms clipped at 5.0.The projection number of self-attention m is 8.To avoid overfitting, we set the L2-norm regularization parameter as 0.005, and apply dropout to embedding layer with a rate of 0.5.The batch normalization is utilized to the outputs of the self-attention layer.For the batch size, we set the batch size of MSRA dataset as 64 and other datasets as 20, respectively.The character embeddings utilized in our proposed model are from Chinese-Word-Vectors [39], which are pre-trained on Baidu Encyclopedia corpus by Skip-Gram with Negative Sampling (SGNS).
For evaluation, same as most of the previous work, we also use the Precision (P), Recall (R), and F1 score as metrics to evaluate the recognition effectiveness of the model.
C. EXPERIMENT RESULTS
We compare our experimental results with previous state-ofthe-art methods on MSRA dataset, Literature dataset, and Chinese Resume dataset, respectively.Besides, we propose two baselines and a GCRA model.In introduced multi-prototype embeddings features to Chinese NER task and Dong et al. [44] exploited neural LSTM-CRF with radical features in Chinese character.Yang et al. [45] proposed a five-stroke based CNN-BiRNN-CRF model for Chinese NER task by considering the semantic information as well as n-gram features.Cao et al. [23] used Adversarial Transfer Learning and self-attention to joint train Chinese NER task with Chinese word segmentation for better performance.Zhang and Yang [24] constructed a lattice LSTM structure to exploit word information in character sequence with incorporate lexicon information into the neural network.Although the model achieves state-of-the-art F1-score of 93.18%, it leverages external lexicon data, and the result may be affected by the quality of the lexicon.Zhang et al. [25] investigated a dynamic meta-embeddings method and applied it to Chinese NER task.Zhu and Wang [26] proposed a Convolutional Attention Network model to improve Chinese NER model performance and preclude word embedding and additional lexicon dependencies.
The second block in Table 4, we list the results of baselines and our proposed model.Our baseline model achieves an F1-score of 91.36% using only character embedding and softword information.We add a highway network for purifying the hidden representation of Bi-LSTM, and the experimental results show that the Baseline + Highway model has surpassed most of the previous methods.Compared with the state-of-the-art model proposed by Zhang and Yang [24], our character-based model gives a highly competitive accuracy of 93.71% without external lexicon data and multi-task joint training.Compared with state-of-the-art result among the character-based models proposed by Zhu and Wang [26], our GCRA model achieves higher F1-score of 93.08% to the character-based on the MSRA dataset.[25] proposed DME-SUM model, which applied dynamic meta-embeddings method to combine the character and word vectors.Zhang et al. 2019(b) [25] presented DME-attention based model, which implemented two attention layers to integrate character and word information with a combination method of elementwise summation.
2) LITERATURE DATASET
The results of our baselines and proposed models are listed in the second block of Table 5.Our baseline Bi-LSTM + CRF achieves an F1-score of 72.79%, and adding a highway network can improve F1-score to 73.48% which better than previous methods.Compared with the state-of-the-art model proposed by Zhang et al. 2019(b) [25], our GCRA model outperforms the state-of-the-art model without using external data and leads 1.26% increment of F1-score.In the second block of Table 6, the results show that our proposed baseline + highway model achieves highly competitive F1-score of 94.87%.We can observe that our proposed character-based GCRA model outperforms the previous methods and achieves the state-of-the-art F1-score of 95.54% for Chinese Resume dataset, which demonstrates the effectiveness of our proposed model.
D. RESULTS ANALYSIS
With the introduction of the gating mechanism, our model can effectively avoid gradient vanishing during training and achieve the selective multi-channel transmission of information.Shown by Table 4, 5, and 6, we can observe that the baseline + highway model gains significant improvement in F1-score compared with the baseline model.It indicates that the gate network can perform more detailed feature extraction and learn more complicated dependencies.Our proposed GCRA model outperforms previous methods on Chinese Literature and Resume dataset and gives highly competitive results on MSRA dataset without utilizing any external resources.Compared with the baseline model, our proposed GCRA model lead 1.72%, 1.5%, and 1.26% noticeable improvements on MSRA dataset, Literature dataset and Resume dataset, respectively.It demonstrates that the effectiveness of our proposed model for Chinese NER task, which will better understand a sentence and achieve better recognition effect.However, the overall performance on Literature NER dataset is relatively low.And previous methods all get higher precision and lower recall.The lower recall rate means a lot of unknown entities cannot be recognized.It may be explained by the reason that there are various rhetorical devices and a large number of ambiguous cases in Chinese literature text.Nevertheless, the remarkable improvement on Literature NER dataset suggests that our proposed model can efficiently handle the problem of unknown entities.
V. CONCLUSION
In this paper, we propose a new model (GCRA) for Chinese NER task, which utilizes the gated filtering to refine the hidden representation and avert the problems of the gradient.In our model, we apply hybrid gated convolutions and highway-LSTM, and gated self-attention mechanism to learn the inner features of the sentence and capture the context information from multiple subspaces.Compared with previous state-of-the-art methods, the experiments on three datasets demonstrate that our proposed model can achieve better performance.Furthermore, our model does not depend on any external resources and domain-specific knowledge.Thus, it can be easily extended to other sequence labeling tasks, such as Chinese Word Segmentation and Part-of-Speech Tagging.
In the future, we will consider using transfer learning to integrate the knowledge of other NLP tasks in Chinese named entity recognition task to improve performance.
FIGURE 1 .
FIGURE 1.The whole architecture of our proposed GCRA model.
FIGURE 2 .
FIGURE 2. The architecture of hybrid gated convolution layer.
2 )
DILATED GATED CONVOLUTIONStrubell et al.[28] applied the iterated dilated convolutions to expand the receptive fields, which have better capacity than traditional CNNs for NER task.To enable the CNN model to capture farther distances without increasing the model parameter number, we use a dilated convolution.In normal CNN, each kernel window consists of adjacent inputs, whereas dilated convolutions define wider effective input width by introducing dilation between inputs.Given a 1-D convolutional filter w = {w −r , w −r+1 , . . ., w r } of a widow size l = 2r + 1 and the input sequence X = {x 1 , x 2 , . . ., x n }.
FIGURE 4 .
FIGURE 4. The architecture of highway network layer.
d h represent the projection matrix, and d k = 2 d h /m.The ⊗ is the element-wise product and ⊕ represents the connection operator.
TABLE 1 .
Examples of word segmentation.
TABLE 2 .
Detailed statistics of datasets.
Table 4 ,
5, and 6, we use the Baseline to represent the BiLSTM + CRF model and Baseline + Highway to indicate Highway-LSTM + CRF model.The best experiment results in tables are in bold.
Table 4
[43]s the experimental results conducted on the MSRA dataset.The first block is the results of previous models for Chinese NER on MSRA dataset.Chen et al.[40], Zhang et al.[41], and Zhou et al.[42]who employed the statistical model with rich hand-crafted features.Lu et al.[43]
TABLE 4 .
Experimental results on MSRA dataset.
Table 5
Zhang et al. 2019(a)e results on the Literature dataset.Xu et al. 2018(a)[36]employed bi-directional LSTM for Chinese Literature NER, andXu et al. 2018(b)[36]used CRF with the features template, which includes unigram and bigram features.The first two rows in the first block clearly show that CRF achieves better performance than bi-directional LSTM, which probably attributed to the feature template.Zhang et al. 2019(a)
TABLE 5 .
Experimental results on Literature dataset.
Table 6
[26]s the comparative results on the Chinese Resume dataset.The result in the first three rows of the first block respectively represents the char-based LSTM model, the word-based LSTM model, and the Lattice model proposed by Zhang and Yang[24].Zhu and Wang 2019(a)[26]used BiGRU + CRF model and Zhu and Wang 2019(b)[26]leveraged CNN-BiGRU + CRF model for the Chinese Resume NER.Zhu and Wang 2019(c)[26]presented a Convolutional Attention Network model and achieves F1-score of 94.94% for Resume dataset.
TABLE 6 .
Experimental results on Chinese Resume dataset. | 7,095.2 | 2019-09-19T00:00:00.000 | [
"Computer Science"
] |
Numerical Investigation of Vortex Induced Vibration for Submerged Floating Tunnel under Different Reynolds Numbers
: A 2D numerical model was established to investigate vortex induced vibration (VIV) for submerged floating tunnel (SFT) by solving incompressible viscous Reynolds average Navier-Stokes equations in the frame of Abitrary Lagrangian Eulerian (ALE). The numerical model was closed by solving SST k - ω turbulence model. The present numerical model was firstly validated by comparing with published experimental data, and the comparison shows that good achievement is obtained. Then, the numerical model is used to investigate VIV for SFT under current. In the simulation, the SFT was allowed to oscillate in cross flow direction only under the constraint of spring and damping. The force coefficients and motion of SFT were obtained under different reduced velocity. Further research showed that Reynolds number has not only a great influence on the vibration amplitude and ‘lock-in’ region, but also on the force coefficients on of the SFT. A large Reynolds number results in a relatively small ‘lock-in’ region and force coefficient.
Introduction
Submerged floating tunnel (SFT) is a new type of traffic structure that crosses the strait, bay and lake. It is usually suspended more than 30 m below the water. The SFT has a large internal space, which is sufficient to meet the requirements of roads and even railways. For some fjords with harsh natural conditions, due to environmental conditions and technical constraints, traditional spanning methods (such as: cross-sea bridges, immersed tunnels) are not feasible, and SFT offers the possibility of crossing. Since the SFT is always in a deep-water depth, whose location is more the half wave length of normal wave, the normal wave has less influence on it. In addition, due to severe natural environment in the fjord, the flow velocity is usually fast, which has a greater influence on the SFT.
In view of the coupled analysis of flow and SFT, many scholars have done the relevant researches. Mai [1] considered the fluid-structure interaction effect, and studied the effects of surface velocity, tunnel section form and support form on the dynamic response of the SFT. It is found that the surface velocity would significantly affect the response displacement of the SFT, but it did not affect the stress distribution along the axial direction. Wang [2] analysed the variation law of the load on the SFT structure under the lateral lift force of the flow with the submerged depth, water depth, flow velocity and section size. Long [3] studied the dynamic response of SFT in different Buoyancy Weight Ratios (BWRs), and proposed the optimal range of BWRs for SFT under flow loading. The empirical lift formula based on Morison's formula was used in the above studies when discussing the flow load, but the effect of SFT on the flow field was not considered in detail. In order to find the optimal section of SFT, Luo et al. [4,5] compared the flow field distribution and force acting on the fixed SFT with different cross-section forms by large eddy numerical simulation. It was found that the ear-shaped ( Figure 1) SFT structure had smaller lift coefficient and drag coefficient, which was the most reasonable cross-section shape, followed by circle, ellipse, hexagon and rectangular. Since the SFT is suspended in the sea via the mooring system, it will move under the flow action. The periodically varying lift makes the SFT with elastically support vibrate perpendicular to the inlet flow direction, that is, 'Vortex-Induced Vibration' (VIV). When the vortex shedding frequency is close to the natural frequency of the structure, the phenomenon of resonance or lock-in occurs, which reflects the complex interaction between the fluid and the structure. Therefore, when frequency lockin occurs in the SFT under the flow action, the fatigue damage of the structure will be significantly increased, which will have a negative impact on the safety of the project. Many experimental researches and numerical simulations on the VIV problem were carried out, such as Morse and Williamson [6], Govardhan and Williamson [7], Yan et al. [8], Luo et al. [9], Zheng et al. [10]. VIV experiment of rigid cylinder with elastically support under wind load was successfully studied by Feng [11]. Williamson and Khalak [12,13] and Govardhan et al. [14] performed VIV experiments on rigid columns with low mass ratio and elastic support in the wave tank, which became the verification test for many subsequent numerical simulations. Lu and Dalton [15] numerically studied the cylindrical VIV problem with cross-flow motion in the case of Reynolds number Re = 13,000, and the model used large eddy simulation to close the turbulence equation. Dong and Karniadakis [16] used direct numerical simulation (DNS) to study the force vibration of cylinders with a Reynolds number of 10,000. For the vibration analysis of SFT, Ge et al. [17] and Kang et al. [18] applied the von der Pol equation to simulate the VIV of the SFT in flow, and studied the influence of the spacing of the anchor chain on the vibration amplitude of the tunnel. Su and Sun [19] utilised the wake oscillation model to simulate the VIV of the SFT. It was found that the vortex-induced vibration resonance occurred and the axial stress of the structure increased significantly. Chen et al. [20] proposed a simplified theoretical model for vibration analysis of the coupled SFT tube-cable system under wave and current.
In general, the empirical formulas are employed in most research about the VIV of SFT, and the study based on computational fluid dynamic (CFD) are limited on a specific Reynolds number. For this reason, the investigation of VIV based on CFD in a serious of Reynolds number under a specific engineering background should be proceeded here. The vibration phenomenon of SFT under different Reynolds number is different because the size of the structure and flow velocity vary greatly in different situations. Based on the above background, this study aims to analyse the coupled motion of flow and SFT in the range of Reynolds number from 1000 to 100,000, and study the influence of different Reynolds numbers on the vibration of SFT as well as force coefficient under the flow action, so as to provide reference value for practical engineering.
Numerical Model
For underwater SFT, the flow around the structure is usually turbulent due to the large scale of the structure itself and the relatively fast flow velocity. At present, the simulation of turbulence can be approximated by direct numerical simulation (DNS) or by using a suitable turbulence model, and the turbulence model is used to simulate the problem in this paper. At the same time, since the length of the SFT structure is much larger than the section size, we can simulate this problem as a twodimensional (2D) flow-structure interaction problem approximately. Although it is well known that the flow is indeed three-dimensional (3D) effect for large Reynolds number, however, 3D simulation cost a lot of computational resources. Therefore, a 2D numerical model was adopted in this study. Although 2D numerical model will overpredict the numerical results, it still can reveal the relationship between reduced velocity, vibration amplitude and force coefficient. In addition, many other researchers have also adopted 2D numerical model to solve similar problems (Lu and Dalton [15], Dong and Karniadakis [16]).
Governing Equation and Turbulence Model
The two-dimensional incompressible Reynolds-Averaged Navier-Stokes equations are adopted to describe the turbulence flow of incompressible viscous fluid. The governing equations in the Arbitrary Lagrangian-Eulerian (ALE) frame can be written as (Liu et al. [21]) where x1 = x, x2 = y are the horizontal and vertical coordinates, respectively, ui is the fluid velocity in the xi-direction, t is the time, m j u is the velocity of moving grid in the xj-direction, p is the pressure, ρ is the fluid density, υ is the kinematic viscosity of the fluid, Sij is the mean strain rate tensor with ( ) The Reynolds stress term in Equation (1) reads can be expressed as where υt is the turbulent eddy viscosity, k is the turbulence kinetic energy and δij is the Kronecker operator.
In order to close the governing equations, the Shear Stress Transport (SST) k-ω turbulence model (Menter [22]; Menter et al. [23]) is adopted. The parameters in the equation have been widely accepted and successfully applied, which has shown good performance in simulating the boundary layer flows with significant adverse pressure gradient. The governing equation of the SST k-ω turbulence model can be written as follows: where Pk is the production of turbulent kinetic energy and the related parameters in Equations (4) and (5) are calculated as follows where Ω is the absolute value of vorticity, y* is the distance to the nearest solid wall, and the parameters F2 and Dkω are By using the blending function F1, the following parameters can be calculated, i.e., The model constant in the SST k-ω model are listed in Table 1. When the flow field and the pressure field are obtained, the fluid force acting on the structure can be obtained by integrating the surface pressure and the viscous shear force over the body surface. The dimensionless drag coefficient CD and the lift coefficient CL are respectively
Motion Response of SFT
For the vibration problem of the SFT under the flow action, since it is necessary to ensure the anchor cable is always in the elastic range, the whole system can be simplified as a mass-dampingspring system. In this paper, only the vibration response of the SFT in cross flow direction is considered, and its motion equation can be expressed as follows.
where ξ is the damping ratio of structure, fn is the natural frequency and m* is mass ratio.
The following dimensionless relationship can be defined further At the same time according to the definition of lift coefficient, Fy = 0.5ρU 2 DCL, Equation (9) can be transformed in dimensionless form ( ) By introducing the definition of the reduced velocity Ur = U/fnD, the motion equation of the SFT can also be expressed as a dimensionless equation in the form of reduced velocity.
The lift coefficient at the right end of the above formula has been given before, and the dynamic response of the SFT can be calculated by the above formula.
Calculation Model and Boundary Conditions
The calculation model and boundary conditions are shown in Figure 2. Let the origin of the coordinate be at the initial centre of the cylinder, and the dimensionless cylinder diameter D = 1. The dimensionless velocity u = 1, v = 0 are set up at inlet. Symmetrical boundary conditions are applied at side wall ∂u/∂y = 0, v = 0. The outlet velocity boundary condition is ∂ui/∂t + c∂ui/∂xi = 0, where c is local average flow velocity. non-slip boundary conditions applied to the cylindrical surface u = dx/dt, v = dy/dt. In the calculation, in order to ensure the first layer of the grids is in the viscous boundary layer, the distance between the surface of the circular cylinder and the first layer of the grids is less than 0.05% D. In addition, the choice of boundary layer can be employed by the method of Palm et al. [24]. In the calculation, the pressure at outlet p = 0 and the pressure boundary condition ∂p/∂n = 0 is applied at other boundary conditions, n is unit normal vector pointing out the fluid domain. At initial time, the velocity and pressure in the fluid domain are set up to zero, i.e., the initial velocity field satisfies the continuous equation.
Numerical Dispersion and Grid Update
The convection-diffusion equation is solved by streamline upwind/petrov-galerkin finite element method in this paper (Brooks and Hughes [25]), and this method has been applied in the solution of impressive flow problem successfully (Mochida and Murakami [26], Kim et al. [27], Guilmineau and Queutey [28]). The distribution method is utilised in the time integration of the momentum equation. First, the pressure term is neglected, and the intermediate velocity of convection and diffusion term is considered; then the pressure equation is solved to calculate the pressure of the next time step; finally, the pressure gradient term is considered to correct the flow field. Streamline upwind method is used to predict the velocity.
The Newmark-β method is used to solve the motion equation of the structure. Given the displacement, velocity and acceleration at an initial moment, the time step Δt, the parameters β and γ are selected, and then the equivalent stiffness is formed. The effective load at time t + Δt is obtained, and the displacement at the time t + Δt can be solved. For time advance, according to CFL (Courant-Friedrichs-Lewy) conditions, the following dynamic time steps are adopted: where Sc is the mesh area, ue is the flow velocity at grid centre, min indicates the minimum in the computational domain, Cs is the safe coefficient, Cs = 0.2. Due to the reciprocating motion of the SFT under the flow action, the dynamic grid method based on ALE is used to simulate the fluid-structure coupling problem. In this paper, the mesh in the computational domain is assumed to be an elastic one, as shown in Figure 3, in order to achieve the purpose of adapting to the movement of the grid boundary nodes and internal nodes. The motion and deformation of the mesh can be obtained by solving the governing equation of linear elastodynamics (Johnson and Tezduyar [29]). The mesh updating method make the displacement of the mesh nodes more uniform and improve the stability of numerical calculation. In addition, the possibility of mesh distortion can be reduced by controlling the elastic modulus of the computing element. Specifically, the balance length of the mesh is equal to the length of the mesh itself at the initial moment. When the two ends of the joint move relative to each other, the mesh will be stretched or compressed, correspondingly. The mesh still satisfies Hooke's law, so the total force vector of any node i is ( ) where Fi is the total force vector on node i, αij is the mesh stiffness between the nodes, υi represents the number of nodes connected to node i, j = [i, υi], δi and δj are displacement vector of node i and j.
In order to avoid collisions of mesh nodes, the following expression is usually used to calculate the mesh stiffness where xi, xj are the position vectors of nodes i and j, that is, the value of αij is considered to be the reciprocal of the side length. This mesh updating method has also been widely used in the VIV research (Tang et al. [30], Lu et al. [31]).
Model Validation
In order to obtain reliable numerical results, this paper firstly uses the free vibration cylinder problem under Re = 30,000 and Ur = 6.00 as an example to verify the mesh convergence of the numerical model. Four different meshes are considered in Table 2. From Table 2, it can be seen that the numerical results under the four meshes are very close, indicating that the numerical results have converged under the current grid density. Considering the computational efficiency, the latter numerical calculation takes mesh 3 (Figure 4) as the benchmark. In the table, Ymax denotes the maximum vibration amplitude of the cylinder, Dismin denotes the minimum distance between the circular cylinder and the first layer gird, M D C is the mean drag coefficient, RMS L C is root mean square (RMS) of lift coefficient. [32] and the numerical results of Dong and Karmiadakis [16], Zhao et al. [33], Song [34], which are shown in Table 3. Table 3 Reynolds number. The problem of flow around a fixed cylinder is actually only a unilateral hydrodynamic calculation problem. It does not involve the motion response calculation of the circular cylinder itself, so it is not a true fluid-structure coupling problem. The vibration of cylinder with elastic support under the flow action involves fluid-structure coupling problem. There have been many experimental results on the VIV of rigid cylinders with elastic supports under the flow action, such as Khalak and Williamson [12], which have done systematic experimental studies. In order to facilitate comparison with the experimental results, the same calculation parameters as in the tests of Khalak and Williamson [12] were used. The Reynolds number Re = 12,000, the mass ratio m* = 2.4, and the mass damping ratio m*ξ = 0.013, and the maximum dimensionless vibration amplitudes versus reduced velocity are calculated in the paper.
From the comparison results in Figure 5, it can be seen that the maximum dimensionless vibration amplitude is close to 1 and the 'lock-in' region is from Ur = 4.0~10.0. In addition, the upper branch and lower branch can also be described in the numerical model clearly as shown in the experiment. Therefore, the results in the numerical model agree well with the experimental results of Khalak and Williamson [12]. It is illustrated that the model established in this paper can be used to investigate the fluid-structure coupling problem with high Reynolds number.
Example Analysis
Based on the above numerical model, this paper calculates the motion of the SFT under different constraint stiffness and different Reynolds numbers. The Reynolds number is calculated from 1000 to 100,000. Firstly, the time history curves of the cross-flow direction under the conditions of Reynolds number 50,000, mass ratio m* = 2.5, damp ξ = 0.007 and reduced velocity Ur = 2.0, 5.0 and 12.0, respectively, are introduced, as shown in Figure 6. Then, the Fast Fourier Transform (FFT) is utilised in the lift force coefficient time history, and the result is displayed in Figure 7.
From Figure 5, it can be found that when reduced velocity are 2.0 and 12.0, the vibration amplitude in cross flow direction of the SFT is small, and when the reduced velocity is 5.0, the vibration amplitude is large. Subsequently, the flow field is analysed in the case of larger and smaller vibration amplitudes, as shown in Figures 8 and 9. From Figure 6, it can be seen that the vortex shedding frequency is about 0.23 Hz. According to the definition of Ur = U/fnD, the natural frequencies (fn) of SFT in the case here are 0.5 Hz, 0.2 Hz and 0.083 Hz, respectively. Therefore, it can be seen that when the reduced velocity of the SFT are 2.0 and 12.0, the vortex shedding frequency is far away from the natural frequency, and the VIV of the SFT is not obvious. The wake pattern is shown in Figure 9, and the wake shape is also regular in one vibration period. However, when the reduced velocity is 5.0 by adjusting the spring stiffness, the frequency of vortex shedding is close to the natural frequency. Under the action of flow lift force, a large VIV phenomenon occurs in the SFT. The vibration amplitude is larger, even reaching 0.7 times of the outer diameter of the SFT, whose wake pattern is shown in Figure 8. It can be seen that the wake has a long 'tail' after being separated, and the wake shape is irregular. Next, we compare the coupling effect of the flow and the SFT versus different reduced velocity under this Reynolds number, and the maximum dimensionless vibration amplitude of the SFT has been statistically obtained, as shown in Figure 10. It can be seen from the calculation results that when the reduced velocity is from 4.0 to 10.0, the structure is 'locked' under the flow action, while at other reduced velocity, the vibration amplitude of the structure is small. Then the VIV of the SFT under different Reynolds numbers are compared, and the calculation results are shown in Figure 11. From the results of VIV of SFT under different Reynolds numbers, it can be seen that Reynolds number has not only a great influence on the vibration amplitude, but also on the 'lock-in' region. In general, the lower the Reynolds number is, the larger the amplitude is out of the 'lock-in' region. The minimum vibration amplitude in the 'lockin' region is about 0.4D, while the maximum vibration amplitude in the 'lock-in' region can reach to 0.8D. It can also be seen that larger Reynolds number leads to narrow 'lock-in' region in Figure 10. Therefore, when the size of the SFT is small or the inlet flow velocity is slow, VIV 'lock-in' phenomenon is more likely to occur for SFT because of lower Reynolds number. Figure 11. Vibration amplitude of SFT versus natural frequency in different Reynolds numbers. Figure 12 is the force coefficient on SFT versus reduced velocity at different Reynolds numbers. It can be seen that reduced velocity has a greater influence on the mean drag coefficient and RMS of lift coefficient. When the Reynolds number is low, the mean drag coefficient and RMS of lift coefficient of the SFT are relatively large from 1000 to 10,000. As the Reynolds number increases, the mean drag coefficient and RMS of lift coefficient become smaller. Therefore, when the size of the SFT is small or the inlet flow velocity action on the structure is slow, the force coefficient is large, and when the size is large or the flow velocity is fast, the mean drag coefficient and lift force coefficient of the structure are small.
Conclusions
Based on the FEM solution of incompressible viscous Reynolds average Navier-Stokes equations, combining the frame of Abitrary Lagrangian Eulerian, through accurate computational fluid dynamic numerical simulation, the vortex-induced vibration problems of submerged floating tunnel with different Reynolds numbers are studied. Main conclusions are as follows: Firstly, the analysis of uniform flow and fixed single cylinder proves the accuracy of the model in the case of high Reynolds number. Then, by simulating the vortex-induced vibration of a cylinder at high Reynolds number and comparing with other scholars' experimental results, it is proved that the model established in this paper can be used to study the fluid-structure coupling problem at high Reynolds number.
Through the research of vortex-induced vibration of SFT under the flow action, the force coefficient and motion of the SFT versus different reduced velocity at different Reynolds numbers are analysed. The results show that the Reynolds number has not only a great influence on the vibration amplitude and 'lock-in' region, but also on the force coefficient on the SFT. When the Reynolds number is low, the 'lock-in' region, the mean drag coefficient and RMS of lift coefficient of the SFT are relatively large. As the Reynolds number increases, the 'lock-in' region, the mean drag coefficient and RMS of lift coefficient become smaller. Therefore, when the size of the SFT is small or the flow velocity action on the structure is slow, the force coefficient and 'lock-in' region are relatively large, while when the size is large or the flow velocity is fast, the force coefficient and 'lock-in' region are relatively small. | 5,317.2 | 2020-01-07T00:00:00.000 | [
"Physics",
"Engineering"
] |
Urea as a Cocrystal Former—Study of 3 Urea Based Pharmaceutical Cocrystals
Cocrystallization is commonly used for its ability to improve the physical properties of APIs, such as solubility, bioavailability, compressibility, etc. The pharmaceutical industry is particularly interested in those cocrystals comprising a GRAS former in connection with the target API. In this work, we focus on the potential of urea as a cocrystal former, identifying three novel pharmaceutical cocrystal systems with catechin, 3-hydroxyl-2-naphthoic and ellagic acid. Interestingly, the stability of catechin under high humidity or high temperature environment is improved upon cocrystallization with urea. Moreover, the solubility of ellagic acid is improved about 17 times. This work displays the latent possibility of urea in improving the physical property of drug molecules using a cocrystallization approach.
Introduction
Cocrystals have drawn increasing attention in recent years due to their ability to improve physical properties of active pharmaceutical ingredients (APIs) without changing the chemical structure of the original drug [1][2][3][4]. Although still in debate, a well-accepted definition describes cocrystals as "solids that are crystalline single-phase materials composed of two or more different molecules and/or ionic compounds generally in a stoichiometric ratio which are neither solvates nor simple salts" [5]. More specifically, pharmaceutical cocrystals combine a drug compound and a pharmaceutically acceptable coformer. There have been eight pharmaceutical cocrystals marketed up to date, with an even more important number undergoing clinical trials [6].
Indexed as a GRAS (General Regarded As Safe) compound, urea is an excellent choice of coformer from the pharmaceutical (safe) and economic (inexpensive) point of view. High water solubility coformers in general increase the solubility of the API when the cocrystal is formed [2,7,8]. Urea cocrystals are therefore expected to strongly impact the API solubility. Urea furthermore has functional groups frequently encountered in cocrystal hydrogen bonding patterns, and therefore forms an ideal candidate for co-crystal screening [9,10]. Various contributions already show the potential of urea for the improvement of physical properties compared to the original API [11][12][13][14]. Urea cocrystals raised the solubility of agomelatine 2.2 times [15]. Urea also improved the intrinsic dissolution rate of bumetanide [11], febuxostat [13] and niclosamide [14] in a variety of solvents.
We here present, three novel urea comprising pharmaceutical cocrystals with catechin, 3-hydroxyl-2-naphthoic acid and ellagic acid, all of which show interesting bioactivity. Specifically, ellagic acid is widely used in food and pharmaceutical industry owing to its antioxidant and anti-inflammatory effect [16,17]. The anti-diabetic effect of 3-hydroxyl-2naphthoic acid has also been proved by previous reports [18]. Catechin is a flavanol which has been effectiveness as an antioxidant, and for improvement of the immune system response [19][20][21][22]. In this work we show how cocrystallization with urea, leads to a 17-fold solubility increase of ellagic acid, as well as an improvement of the physical stability of catechin. This work therefore further underlines the potential of urea for the improvement of physical properties of API through cocrystallization.
Cocrystal screen. In a typical cocrystal screening experiment, 0.25 mmol urea and an equimolar amount of API are placed in an Eppendorf adding one stainless steel ball. After that, grinding was performed using a RETSCH Mixer Mill MM 400 with a beating frequency of 30 Hz for 90 min. Subsequently, the PXRD of the ground material is compared to that of the parent compounds. Upon apparition of novel peaks, grinding is performed under various ratios as well. When neat grinding did not lead to a full transformation, liquid assisted grinding was performed in parallel, adding 20 µL of solvent to the initial mixture of urea and target compound prior to grinding (solvents include methanol, ethanol, water, acetonitrile and isopropanol).
Single crystal growth. Methanol is added in a drop-wise manner to a vial containing 25 mg of catechin and 24 mg urea (1:5 molar ratio) until full dissolution is achieved. After that, the solution is left to evaporate. After one week, UC crystals are obtained of sufficient quality for SC-XRD. In a similar approach, single crystals of UH are obtained by evaporating an undersaturated methanol solution of urea and 3-hydroxyl-2-naphthoic acid (in a 1:3 molar ratio).
Powder X-ray diffraction and variable temperature X-ray powder diffraction (VT-XRPD). Powder X-ray diffraction of all samples are conducted on a Siemens D5000 diffractometer equipped with a Cu X-ray source operating at 40 KV and 40 mA (λ = 1.5418 Å) from 2 to 50 degree at the rate of 0.6 degree per minute. VT-XRPD of catechin hydrate is collected on a PANalytical X'Pert PRO automated diffractometer from 3 to 40 degree, equipped with an X'Celerator detector and an Anton Paar TTK 450 system for measurements at controlled temperature. Data were collected in open air in Bragg-Brentano geometry, using Cu-Kα radiation without a monochromator.
Structure Determination. Single crystal diffraction data for UC and UH were collected on a MAR345 image plate detector using Mo Kα radiation (λ = 0.71073 Å), generated by a Rigaku Ultra X18S rotating anode (Xenocs fox3d mirrors). For UC the crystal was flash frozen at 150K in a N 2 flow prior to data collection. Data integration and reduction was performed by CrystAlisPro [23] and the implemented absorption correction was applied. Structure solution was performed by the dual-space algorithm in SHELXT [24] and the structure was further refined against F 2 using SHELXL2014/7. All non-hydrogen atoms were refined anisotropically and hydrogen atoms were placed at calculated positions with temperature factors set at 1.2U eq of the parent atoms (1.5U eq for methyl and OH hydrogens).
For UE the structure was solved from powder diffraction measured on a STOE STADI P diffractometer using monochromated Cu Kα1 radiation in transmission mode (with the sample placed between zero scattering foils). Unit cell determination was performed by DICVOL and the structure was solved by DASH [25], the structure was subsequently optimized by Rietveld refinement in Fullprof [26]. The Rietveld profile is shown in Figure S15.
Thermogravimetric Analysis (TGA). Typically, the TGA analyses of all samples are performed from 30 to 450 • C using a heating rate of 5 • C/min with a continuous nitrogen flow of 50 mL/min, on a Mettler Toledo TGA/SDTA851e. Differential Scanning Calorimetry (DSC). DSC measurements are performed on a TA DSC2500. Deposited in an aluminum Tzero pans with punctured hermetic lid, samples were heated from 20 • C up to 240 • C using a heating rate of 2 • C/min under a 50 mL/min continuous nitrogen flow.
Congruence experiments. Stoichiometric amounts of urea and API were added to 1 mL of solvent until dissolution no longer occurred and a suspension was obtained. After that, ground traces of cocrystal material were added to the suspension as seed material. After 3 days of slurrying at room temperature, the suspension was filtered and the solid analyzed by PXRD.
Solubility measurement. The solubility measurement is conducted in ethanol at room temperature. An excess amount of solid is added to 2 mL of ethanol and the suspension is left to slurry for 2 days reaching saturation. After that, the suspension is filtered, and the filtrate weighed and left for evaporation. Weighing the recovered solids, allows determining the amount of solvent as well as solid present in the filtrate, and hence the solubility.
Cocrystal Screening
As our main goal was to show the potential of urea as a pharmaceutical cocrystal former, a screen involving 62 APIs was performed (Table S1). Seven positive hits were identified in agreement with literature reported success rates of about 10% (Figure 1) [27]. From this data, APIs containing a phenol group have a higher likelihood of forming a cocrystal with urea. Four cocrystals were already reported in literature (Figures S1-S4) (theophylline, nicotinamide, salicylic acid, and hydroquinone) [28][29][30]. We report here three new cocrystal systems with catechin, ellagic acid, and 3-hdyroxyl-2-naphthoic acid, which are discussed in detail.
Urea-Catechin Cocrystal (UC)
Urea and catechin cocrystallize in the monoclinic P2 1 space group ( Table 1). The unit cell contains two urea and two catechin molecules. As a hydrogen bond acceptor, the oxygen atom of each urea molecule is connected to a N-H group of a second urea molecule and to a phenolic hydroxyl of catechin. Furthermore, all hydroxyl groups are engaged in hydrogen bonds with hydroxyl groups of neighboring catechin molecules (Figure 2). Figure 3 shows a PXRD overlay of the ground and starting materials (catechin is not displayed because the used catechin was amorphous), as well as the pattern simulated from the single crystal structure. As shown in this figure, the ground material matches the one from single crystal analysis, corresponding to the 1:1 cocrystal. Urea shows a single melting point with onset at 134 • C immediately followed by a degradation as illustrated by the TGA analysis, similar to previous report [31]. The UC cocrystal shows a melting temperature of 176 • C with a corresponding heat of fusion of 162.78 J/g (Figure 4), which is followed by a degradation endotherm. Comparing the UC and the amorphous catechin material in terms of humidity stability, one notices the UC cocrystal to remain stable at 75% RH at 25 • C for a period of two weeks ( Figure S5), whilst storing the amorphous material, leads to crystalline catechin hydrate under these conditions. Catechin hydrate in turn starts losing water at temperatures above 50 • C ( Figure S6), transforming into the amorphous phase upon dehydration ( Figure S7). Cocrystallization with urea, therefore, leads to a solid form of catechin which is much less moisture or thermo-sensitive.
Urea-3-Hydroxyl-2-Naphtoic Acid (UH)
Urea and 3-hydroxyl-2-naphthoic acid crystallize in the monoclinic C2/c space group in a 1:1 ratio. The carboxylic acid of 3-hydroxyl-2naphthoic acid, is connected to the amide group of urea through an amide-acid hetero-synthon. The phenyl hydroxyl forms an intramolecular hydrogen bond, as well as an intermolecular hydrogen bond with urea ( Figure 5). Other hydrogen bonding patterns involve different urea molecules and are of the C = O-H-N type ( Figure 5). Figure 6 shows a PXRD overlay of the ground and starting materials, as well as the simulated pattern from the single crystal data. As shown in this figure, the ground material matches the single crystal phase, corresponding to a 1:1 cocrystal. Further, 3-hydroxyl-2-naphthoic acid shows a single melting point with onset at 218 • C and an associated 173.3 J/g heat of fusion. The cocrystal in turn shows a single melting temperature at 155 • C with a heat of fusion 156.78 J/g followed by immediate degradation. As common for cocrystals, this melting point lies between that of both parent compounds. TGA confirms degradation upon melting for all phases (Figure 7).
Urea-Ellagic Acid (UE)
The UE cocrystal can be obtained by liquid assisted grinding of two equivalents of urea and one equivalent of ellagic acid using water (Figure 8). Grinding a 1:1 ratio, leads to cocrystal material with excess amount of ellagic acid. As attempts at growing a single crystal failed, the structure was resolved from the powder pattern. Urea and ellagic acid cocrystalize in the P-1 space group, with two urea and one ellagic acid molecule in the unit cell (Table S2). Ellagic acid is found on a crystallographic inversion center. For ellagic acid, the oxygen atoms in the ester group of ellagic acid serve as hydrogen bond acceptor, connecting to amide groups from urea molecules. On the other hand, the phenolic hydroxyl groups in ellagic acid serve as hydrogen bond donor to the carbonyl oxygen of a urea molecule (Figure 9). Thermal analysis of ellagic acid showed our initial powder to contain a mixture of the hydrate and anhydrate phase as shown in Figure 9. TGA of ellagic acid shows a mass loss of 2.5% at 103 • C, suggesting a quarter of ellagic acid used here is under the dihydrate form. DSC confirms this water loss. Ellagic acid has a reported melting temperature of 350 • C [32]. The co-crystal shows a single endotherm peak at 222 • C, corresponding to the melting point of the cocrystal. TGA shows melting to be followed by immediate degradation (Figure 10).
Solution Behavior
The solution behavior of the novel phases was evaluated in various solvents. Initially, the cocrystals were suspended in a solvent to evaluate their congruency. Congruency implies that stoichiometric amounts of the cocrystal components lead to the cocrystal as the only stable phase in suspension, while non-congruency means that one of the parent compounds crystallizes out (or a mixture of cocrystal and a parent compound). UH behaves congruently in ethanol, acetonitrile and isopropanol, whereas it is not congruent in water or methanol ( Figure S8), with 3-hydroxyl-2-naphthoic acid crystallizing out. UE behaves congruently in methanol, ethanol, acetonitrile and isopropanol. In water, ellagic acid hydrate is obtained ( Figure S9). UC crystalizes congruently in all organic solvents used here and incongruently in water, with catechin hydrate crystallizing out ( Figure 11). In mixed water/methanol solvents, UC behaves congruently for solvent mixtures of 1:9 to 4:6 water/methanol ratios ( Figure S10). When the water/methanol ratio varies from 5:5 to 6:4, a recently identified catechin methanol solvate-hydrate crystallizes out (catechin:water:methanol 2:2:1) ( Figure S11) [33]. With an even higher water/methanol ratio, a PXRD profile different from any known form is obtained (Figures S12 and S13). Drying this phase under ambient conditions yields catechin hydrate, suggesting another solvate of catechin was likely obtained. Slurrying catechin on its own in water/methanol ratios from 7:3 to 9:1, only gives the catechin hydrate, which means urea likely plays a role in the stabilization of the yet unknown catechin solvate ( Figure S14). As all three new cocrystals behave congruently in ethanol, solubility measurements were conducted in this solvent. For UC and UH cocrystal, a solubility of 0.595 mol/L and 0.439 mol/L is obtained, which is lower than that of the parent compound (0.736 mol/L and 0.599 mol/L respectively). For ellagic acid, the behavior is inverted, with the solubility being raised from 0.52 mmol/L to 9.04 mmol/L, showing the potential of cocrystallization to strongly impact the solubility behavior of poorly soluble drugs. Solubility of a cocrystal depends on the free energy of the novel cocrystal as well as the solution free energy of dissolved compounds and their solution interaction. Predicting this solubility merely on the structure is not feasible. The increase in solubility for ellagic acid is not surprising as the solubility of ellagic acid is extremely low. Very likely a variation of free energy of the solid structure as well as a positive interaction between both components in solution needs to be taken into account.
Conclusions
In this work, three novel cocrystals involving urea were identified, targeting catechin, ellagic acid, and 3-hydroxyl-2-naphthoic acid. Urea is a GRAS compound that is a promising coformer with a potential strong impact on the solubility of the target compound, as shown here for a 18-fold solubility increase for ellagic acid. Furthermore, we showed how the stability of the target compounds can be impacted and improved upon by cocrystallization with urea. | 3,456.6 | 2021-05-01T00:00:00.000 | [
"Materials Science"
] |
A new method for obtaining the magnetic shape anisotropy directly from electron tomography images
A new methodology to obtain magnetic information on magnetic nanoparticle (MNP) systems via electron tomography techniques is reported in this work. The new methodology is implemented in an under-development software package called Magn3t, written in Python and C++. A novel image-filtering technique that reduces the highly undesired diffraction effects in the tomography tilt-series has been also developed in order to increase the reliability of the correlations between morphology and magnetism. Using the Magn3t software, the magnetic shape anisotropy magnitude and direction of magnetite nanoparticles has been extracted for the first time directly from transmission electron tomography.
S1
Data volume thresholding aims to find an optimal value according the which the data is separated in two classes (background and objects). This is performed using Otsu's method, which reduces the problem to that of maximizing the inter-class variance: where: are the probabilities of class occurrence and are the class averages.
It assumed that the data is represented as gray levels, with p(i) the normalized histogram.
A distance map is an image where each object voxel is labeled with the distance to its closest background voxel. It is obtained using a technique called weighted-distance transform, which is computed in two passes. The image is inspected from left to right, top to bottom, and front to back during the forward inspection and from right to left, bottom to top, and back to front during the backward inspection. The forward inspection mask is made of the voxels in the neighborhood of the current voxel that have not yet been reached, and the backward inspection mask is made of the voxels which have been already reached.
In Figure S1, the voxels involved in the two inspections are shown. Underlined voxels are used in the backward inspection mask and the remaining voxels in the forward inspection mask. The weights in the mask are added to the temporary distance labels of the voxels. The weights are chosen such that a good approximation to the Euclidian distance is obtained. The computation of the distance map of an image I can be summarized by the following pseudo-code: S2 for z = 1 to n for y = 1 to n for x = 1 to n I (
Particle separation is done using watershed-segmentation. It uses the distance transform of the object and a seed image, which consist of the local maxima of the distance map that should represent the center region of the particles. The segmentation is achieved using a priority-flood algorithm. Priority-flood is a depression-filling algorithm, which means that it fills an elevation image starting from seeds located at the lowest points. Our code uses a modified version that does the opposite, that is, it fills the image (which is the distance map of the object) starting at seeds located at the maxima of the distance map, that is, near the centers of the particles which make up the object, and going downwards. Initially, each seed has been labeled. The algorithm relies on the use of a priority queue, which is an ordered queue such that the voxels with the highest value are processed first and then removed from the queue. The pseudo-code of the procedure is presented below:
Let Q be a priority queue Let Closed have the same dimensions as IDM (distance map image) Let Closed be initialized to false Let S be the seed image for all c in S do push c onto Q with priority IDM (c) Closed(c) ← true while Open is not empty do c ← pop(Open) for all neighbors n of c do if Closed(n) == false IDM(n) ← min(IDM(n), IDM(c)) Closed(n) ← true Push n onto Open with priority IDM (n) return IDM
The returned data now has each particle of the object labeled differently.
The shape and orientation evaluation procedure consist of fitting each separated particle with an ellipsoid and recovering information about size, axis ratios, and orientation of the long axis from the fit.
The fit procedure is performed as follows: First the center of mass of each particle is found. Then the inertia tensor is calculated using the following the expression: where r i are x, y, z coordinates of each voxel with respect to the center of mass.
The eigenvalues and eigenvectors of the inertia tensor are the found: = While the directions of the ellipsoid semi-axes are along the eigenvectors, their magnitude is related to the eigenvalues by the following relation: | 1,051.4 | 2022-07-05T00:00:00.000 | [
"Physics",
"Materials Science"
] |
Differences between phytophagous and predatory species in Pentatomidae based on the mitochondrial genome
Abstract Pentatomidae includes many species of significant economic value as plant pests and biological control agents. The feeding habits of Pentatomidae are closely related to their energy metabolism and ecological adaptations. In this study, we sequenced the mitochondrial genomes of 12 Asopinae species using the next‐generation sequencing to explore the effect of dietary changes on mitochondrial genome evolution. Notably, all sequences were double‐stranded circular DNA molecules containing 37 genes and one control region. We then compared and analyzed the mitochondrial genome characteristics of phytophagous and predatory bugs. Notably, no significant difference was observed in the length of the mitochondrial genomes between the predatory and phytophagous bugs. However, the AT content was higher in the mitochondrial genomes of phytophagous bugs than that of predatory bugs. Moreover, phytophagous bugs prefer codon usage patterns ending in A/T compared with predatory bugs. The evolution rate of predatory bugs was lower than that of phytophagous bugs. The phylogenetic relationships across phytophagous bugs' lineages were largely consistent at depth nodes based on different datasets and tree‐reconstructing methods, and strongly supported the monophyly of predatory bugs. Additionally, the estimated divergence times indicated that Pentatomidae explosively radiated in the Early Cretaceous. Subsequently, the subfamily Asopinae and the genus Menida diverged in the Late Cretaceous. Our research results provide data supporting for the evolutionary patterns and classification of Pentatomidae.
A typical insect mitochondrial genome is a circular doublestranded DNA molecules, consisting of 37 genes (13 protein-coding genes (PCGs), 22 transport RNA genes (tRNAs), and two ribosomal RNA genes (rRNAs)), and one control region (Roger et al., 2017;Wang et al., 2015).Currently, insect mitochondrial genomes are widely used for species identification, population genetics, and phylogenetic analysis (Chen, Zheng, et al., 2020;Vico et al., 2020;Wang et al., 2017).Furthermore, we can test traditional classification systems and systematically understand the evolution of classification by analyzing and studying the mitochondrial genomes of different species.
To date, many studies have investigated the phylogenetic relationships of the bugs.Jiang (2017) Nevertheless, clear and robust evidence exists of Pentatomidae monophyly, involving most of the currently assigned species in the family.Moreover, cyrtophorides are proposed to belong to an independent lineage and be upgraded to Cyrtophoridae.Genevcius et al. (2021), through their study of the tribe Chlorocorini (Pentatominae) using combined DNA and morphological data, revealed that this tribe is not monophyletic.Although phylogenetic studies, including those on representatives of Pentatomidae (Lian et al., 2022;Roca-Cusachs et al., 2022;Zhao, Zhao, et al., 2019), provide a basic framework, phylogenetic relationships within Pentatomidae remain unclear.
In the present study, we sequenced the complete mitochondrial genomes of 12 Asopinae species.We then compared the mitochondrial genomes of phytophagous and predatory bugs, constructed phylogenetic trees, and evaluated the divergence time of Pentatomidae.Our findings could be beneficial for a better understanding of the evolutionary patterns of Pentatomidae and provide a basic theoretical basis for research on biodiversity and biological control.
Specimens were identified based on their morphological characteristics.All specimens were initially stored in 100% ethanol at −20°C, prior to DNA extraction.Voucher specimens were deposited at the Institute of Entomological, Shanxi Agricultural University, Taigu, Shanxi, China.Total genomic DNA was extracted from the thoracic tissue using the Genomic DNA Extraction Kit (Sangon Biotech, Shanghai, China).
| Sequencing, assembly, annotation, and bioinformatics analysis
A whole genome shotgun strategy was employed to construct libraries, that were paired-end (PE 250) sequenced using the Illumina MiSeq sequencing platform.The Fastp software (Chen et al., 2018) was used to obtain high-quality data.The Geneious v.11.0 software (Kearse et al., 2012) was used for sequence assembly and annotation.The reference sequence Arma custos (Fabricius, 1794;NC_051562;Wu et al., 2020) used for the assembly and annotation of the mitogenome of each species was obtained from the NCBI database.The PCGs were identified by open reading frame (ORF; http:// www.ncbi.nlm.nih.gov/ gorf/ gorf.html) using invertebrate mitochondrial genetic codes.The clover secondary structures of the transfer ribonucleic acids (tRNAs) were predicted using the MITOS web server (http:// mitos.bioinf.unileipz ig.de/ ; Bernt et al., 2013).The boundaries of the two rRNAs genes were determined by comparing them with other published rRNA genes in Pentatomidae.The circular maps of the Asopinae mitogenomes were generated using the CGView Server (https:// proks ee.ca/ proje cts/ new).
The PCGs of 64 Pentatomidae species were extracted using Geneious v.11.0, and the amino acid sequences for protein secondary structures were predicted using the SOPMA online website (https:// npsa.lyon.inserm.fr/ cgi-bin/ npsa_ autom at.pl? page=/ NPSA/ npsa_ sopma.html; Geourjon & Deleage, 1995).The codon usage and nucleotide composition of these PCGs were statistically analyzed using MEGA v.11.0 (Tamura et al., 2021).AT and GC skew were calculated as follows: AT (Perna & Kocher, 1995).The effective number of codons (ENC) values, which are commonly used to measure codon bias, of 13 PCGs were calculated using Codon W1.4.2 (Peden, 2000).In order to study the evolutionary patterns between the mitogenomes of phytophagous and predatory bugs, the non-synonymous substitution rate (Ka) and synonymous substitution rate (Ks) of each PCG were calculated using DnaSP v.6.12.03 (Rozas et al., 2017), and the Ka/Ks values were used to determine whether there were natural selection and mutation pressure acting on the protein coding genes.Datamonkey (http:// www.datam onkey.org/ ) was used to perform selective pressure analysis on the PCGs dataset (Murrell et al., 2012(Murrell et al., , 2013)).The tandem repeat sequence of the control region was obtained using the Tandem Repeats Finder server (http:// tandem.bu.edu/ trf/ trf.html; Benson, 1999).
| Phylogenetic analysis
We analyzed phylogenetic relationships among 64 Pentatomidae species with two Scutelleridae species as outgroups (Table 1).
We performed base substitution saturation analysis and sequence composition heterogeneity analysis on the two datasets to determine the feasibility of the phylogeny before constructing a phylogenetic tree.The base substitution saturation index was calculated using DAMBE v.7.0.35 (Xia & Xie, 2001).Heterogeneity analysis was performed using AliGROOVE 1.0.8(Kück et al., 2014).
The phylogenetic trees were generated using the Bayesian Inference (BI) and Maximum likelihood (ML) methods.BI analyses were performed using MrBayes v.3.2.6 (Ronquist et al., 2012), with the GTR + I + G model.The runs were set for 2 × 10 7 generations, with sampling every 1000 generations.The first 25% of generations were removed as burn-in, when the average standard deviation of split frequencies was below 0.01.The ML trees were reconstructed using IQ-TREE v. 2.2.0 (Minh et al., 2020), and the support values for each node were evaluated using the standard bootstrap (BS) algorithm, which was tested 50,000 times.
| Divergence time estimate
Divergence times of Pentatomidae were estimated using the PCGs dataset with a relaxed clock lognormal model in BEAST 1.8.4 (Drummond & Rambaut, 2007).We adopted the GTR + I + G partitioning model and the calibrated Yule model for the prior tree.
| The structure of Asopinae mitochondrial genome
The mitochondrial genome features were comparatively analyzed using 19 Asopinae species (12 newly and 7 previously reported species).All the mitochondrial genomes were double-strand circular DNA molecules (Figure 1), containing 37 genes (13 PCGs, 22 tRNAs, and two rRNAs) and one control region.The arrangement of 37 genes was consistent with the original gene arrangement of Drosophila yakuba Burla, 1954.The general structural characteristics of the mitochondrial genomes are shown in Table S2.The total length of the mitochondrial genome of Asopinae ranged from 15,479 bp (Z.caerulea) to 19,587 bp (Pic.lewisi).In addition, the nucleotide composition of 19 Asopinae species showed a trend of A > T > C > G with a significant AT bias, with the highest (77.14%) and lowest (71.69%)AT content in Z. caerulea and Pic.griseus, respectively.Moreover, all the mitochondrial genomes exhibited a slightly AT-skew (ranging from 0.08 to 0.12, mean = 0.10) and CG-skew (ranging from 0.12 to 0.19, mean = 0.15; Table S3).
The control region of 19 Asopinae species, located between rrnS and trnI (GAT), was the longest non-coding region (661-4651 bp) in the mitochondrial genome (Table S2).C. horvathi and Pic.viridipunctatus exhibited the highest (81.43%) and lowest (67.35%)AT content in the control region, respectively (Table S3).The statistical analysis of tandem repeats in the control region of Asopinae did not reveal any tandem repeat sequences were found in Pin.sanguinipes and Z. caerulea; however, one to six tandem repeat units were found in the other species (Figure 3).
| Genome sizes
We compared and analyzed the mitochondrial genomes lengths (ranging from 14,000 to 20,000 bp) of 19 and 45 species of predatory and phytophagous bugs, respectively (Figure S3).Among the predatory bugs, Z. caerulea and Pic.lewisi exhibited the shortest (15,479 bp) and longest (19,587 bp) mitochondrial genomes, respectively.Among the phytophagous bugs, Graphosoma rubrolineatum (Westwood, 1837) and Nezara viridula (Linnaeus, 1758) exhibited the shortest (15,633 bp) and longest (16,889 bp) mitochondrial genomes, respectively.Notably, differences in genome length may be attributed to non-coding regions among species.In most species of Pentatomidae, the length of the mitochondrial genome ranged from 15,000 to 17,000 bp.However, no significant difference was observed in the mitochondrial genome length between the predatory and phytophagous bugs.
In addition, we compared the lengths of the PCGs between phytophagous and predatory bugs, and found that the length of nad2 in phytophagous bugs was longer than that in predatory bugs (982 ± 13.47 > 959 ± 8.47), indicating significant differences (Figure 4).We then predicted the secondary structures of the PCGs in Pentatomidae.Our findings revealed alpha helix, extended strand, beta turn, and random coil structures (Figures S1).We also compared the mean percentages of these four structures (Figure 5).The percentage of alpha helices in the proteins encoded by atp8, cox3, and nad2 genes in phytophagous bugs was higher than that in predatory bugs.The percentage of extended strands in the proteins encoded by atp8, cox2, and nad2 genes in predatory bugs was higher than that in phytophagous bugs.The percentage of beta turns in the proteins encoded by cytb and nad2 genes in predatory bugs was higher than that in phytophagous bugs.The percentage of random coils in the proteins encoded by nad1 gene in predatory bugs was higher than that in phytophagous bugs.No significant differences were observed in the secondary structures of other proteins.
| Nucleotide composition
The mitochondrial genomes of phytophagous and predatory bugs exhibited a high AT content (Figure S17).Among the predatory and Erthesina fullo (Thunberg, 1783) exhibited the highest (78.94%) and lowest (73.36%)AT content, respectively, with an average AT content of 76.29%.The AT content of the phytophagous bugs was slightly higher than that of the predatory bugs.In addition, the nucleotide composition of the mitochondrial genomes of phytophagous and predatory bugs exhibited AT-skew and CG-skew (Figure 6).Notably, the AT-skew F I G U R E 1 Mitochondrial genomes maps of Asopinae species in this study.
of phytophagous bugs was higher than that of predatory bugs, but there is no significant difference was found in the GC-skew.
In addition, the conserved overlapping regions (trnH/nad4) were found in predatory bugs but not in phytophagous bugs.The longer gene spacers were found between trnS2 and nad1 (20-35 bp) in Pentatomidae, whereas predatory bugs exhibited longer gene spacers between trnM and nad2.
| Codon usage bias
We conducted a comparative analysis of the relative synonymous codon usage (RSCU) between phytophagous and predatory bugs.
We studied the relationships between the ENC and the total codon GC content (GC), first codon GC content (GC1), second codon GC content (GC2), and third codon GC content (GC3) to further investigate codon usage in Pentatomidae (Figure 8).The ENC of the PCGs in phytophagous and predatory bugs exhibited a strong positive correlation with GC and GC3 and a weak positive correlation with GC1 and GC2.
| Evolution rate
By comparing and analyzing the evolutionary rates of phytophagous and predatory bugs, we found that the 13 PCGs of both exhibited Ks > Ka, and Ka/Ks < 1, indicating the evolution of both phytophagous and predatory bugs under purified selection (Figure 9).Among the 13 PCGs in Pentatomidae, the Ka/Ks ratio of atp8 and cox1 was the highest and lowest, respectively.In addition, among the 13 PCGs, it was found that the synonymous substitutions in predatory bugs were higher than those in phytophagous bugs, and the nonsynonymous substitutions of the predatory bugs were lower than those in phytophagous bugs.
F I G U R E 8
Evaluation of codon bias in phytophagous and predatory species in Pentatomidae.
| Phylogenetic analysis
The saturation analysis indicated no saturation in sequences of the two datasets (Iss < Iss.c, and p < .05),and heterogeneity analyses revealed low heterogeneity in sequences (Figures S19 and S20).
Therefore, the two datasets were considered suitable for subsequent phylogenetic analysis.
The phylogenetic trees obtained using the two methods (BI and
| Divergence time estimation
The BEAST analysis indicated that the divergence time of Pentatomidae was 122.78 Mya (95% HPD: 99.15-146.23Mya;
| D ISCUSS I ON AND CON CLUS I ON S
In this study, we sequenced the complete mitochondrial genomes of 12 Asopinae species using second-generation sequencing technology.No gene rearrangements occurred in the mitochondrial genomes of Asopinae, and the sequences were consistent with those of other published Pentatomidae species (Wang et al., 2015;Yuan et al., 2015).The mitochondrial genome size of Pentatomidae is 14-20 kb, with the total lengths in most species ranging from 15 to A comparison of the length of the PCGs and secondary structure of proteins revealed significant differences in the nad2 gene between predatory and phytophagous bugs.Furthermore, phytophagous bugs exhibited a slightly higher AT content than predatory bugs.Moreover, phytophagous bugs tended to prefer codon usage patterns ending in A/T to those of predatory bugs.Different amino acids may cause changes in protein function, thereby affecting organisms and their coevolution with the environment (Hernández- et al., 2008;Liu et al., 2010).In addition, we also found significant differences in the use of Leu between the predatory and phytophagous bugs.Notably, these differences may contribute to the changes that occur in the species to adapt to the environment.The main factors affecting codon bias were mutation pressure and natural selection, with natural selection being the main factor.As insects evolve, the role of natural selection also increases (Behura & Severson, 2013;Nyayanit et al., 2020;Sang, 2019;Wang et al., 2018).The evolutionary rate Ka/Ks < 1 and the selective pressure analysis of Pentatomidae indicated that they are under purified selection.The evolution rate of atp8 was the fastest, whereas that of cox1 was the slowest, which is consistent with the results of the previous studies (Chen, 2022;Ding et al., 2023;Lian et al., 2022).
Montes
Although our results showed that synonymous substitutions in predatory bugs were higher than those in phytophagous bugs, and the non-synonymous substitutions in predatory bugs were lower F I G U R E 1 0 Phylogenetic relationships inferred by the Bayesian Inference (BI) and Maximum likelihood (ML) method based on the protein-coding genes (PCGs) and PRT datasets.Numbers on nodes are the posterior probabilities (PP).
than those in phytophagous bugs, considering that phytophagous bugs have earlier divergence than predatory bugs, it is expected that this relatively young lineage will accumulate more synonymous mutations rather than non-synonymous mutations compared to older phytophagous lineages.Therefore, we may need more factors in the future to explain this result.
We obtained highly consistent topologies of the phylogenetic the genus Plautia of the Antestiini, which is temporarily placed in this tribe.Notably, we could not determine the relationship between Antestiini and Nezarini, and further research is warranted in this area.
We included three genera-Neojurtina, Pentatoma, and Placosternumof Pentatomini, which is the non-monophyletic poorly defined tribe.
Neojurtina was temporarily identified as a member of Pentatomini (Rider et al., 2018), and Pentatoma formed a monophyletic clade with strong support (1/100/1/100) in our analysis.Therefore, further evidence is required to determine the phylogenetic position of each Pentatomini member.
Phyllocephalinae has a complicated taxonomic history, with the single most diagnostic character being a distinctively short rostrum that does not or only barely surpasses the procoxae.Our analyses, including four representative species of Phyllocephalini, strongly supported its monophyly, which has also been confirmed by Roca-
Cusachs et al. (2022).
The taxon Podopinae is defined as a monophyletic group based on specific morphological characteristics (Rider et al., 2018) Hoplistoderini, Menidini and Asopinae are grouped into one clade.In the previous research (Lian et al., 2022;Roca-Cusachs et al., 2022), it supports the sister-group relationship between Menidini and Asopinae.Moreover, issues in the classification of the tribes in Asopinae remain unresolved.Although various suprageneric names have been proposed, they are not included in the current formal classification (Rider et al., 2018).In addition, our results supported a sister-group relationship between the genus Picromerus and the genus Eocanthecona, whereas enlarged protibia is their distinguishing feature in the traditional classification (Zhao, 2013).The phylogenetic results of this study will provide a good reference for further research on the taxonomic status of Pentatomidae.
Evaluation of the divergence time of Pentatomidae is beneficial for studying its evolutionary history.Notably, the Cretaceous period may have been an important period for the evolution of this group owing to the emergence of warmer and wetter climate conditions globally, as well as the increase in diversity and ecological expansion of angiosperms during this period (Berendse & Scheffer, 2009;Chaboureau et al., 2014;Liu et al., 2019;Yao et al., 2012).During In this study, we conducted a comparative analysis of the mitochondrial genomes of phytophagous and predatory species in the Pentatomidae to explore their evolutionary patterns and understand their evolutionary history, providing data to support research on phylogeny, biodiversity, and biological control.However, the evolutionary information of the mitochondrial genome has not been fully explored, including the genetic information contained in tRNA genes, rRNA genes, and the control regions, as well as the functions, has not been fully explored and requires further in-depth research.
Additionally, the fossil information points of Pentatomidae need further supplementation.Moreover, characterizing, the mitochondrial genome sequences of more species and combining morphological characteristics and molecular evidence is imperative to further explore Pentatomidae evolution.
The two rRNA genes (rrnL and rrnS) were encoded on the Nchain in Asopinae.51.07% of the conserved sites in rrnL were located TA B L E 1 List of sequences used to reconstruct the phylogenetic relationships within Pentatomidae.
F
Organization of the control region in the mitochondrial genomes of Asopinae.The tandem repeats are showed by the green circle with repeat length inside.The orange boxes indicate the length of the sequence of the control region.F I G U R E 4 Sizes of the protein coding genes between phytophagous and predatory bugs.*, ** and *** indicate significant difference between phytophagous and predatory bugs at p < .05,p < .01 and .001,respectively (Nonparametric Tests).All values are mean ± SEM unless otherwise designated.F I G U R E 5 The mean percentages of Alpha helix, Extended strand, Beta turn, and Random coil between phytophagous and predatory bugs.*, ** and *** indicate significant difference between phytophagous and predatory bugs at p < .05,p < .01 and .001,respectively (Nonparametric Tests).All values are mean ± SEM unless otherwise designated.
F
I G U R E 6 AT skew and GC skew of the mitochondrial genomes of Pentatomidae.F I G U R E 7 Use of codons of phytophagous and predatory species in Pentatomidae.| 11 of 18 DING et al.We identified codons under positive selection in the PCGs dataset based on FUBAR and MEME to further analyze the role and direction of selection as the driving force for mitochondrial PCGs evolution.We found pervasive positive/diversifying selection at seven sites and pervasive negative/purifying selection at 3349 sites in FUBAR, with a posterior probability of 0.9.Moreover, we found pervasive positive/diversifying selection at 149 sites in the MEME, with a p-value threshold of .1.
ML) based on the two datasets (PCGs and PRT) demonstrated highly consistent topologies, and most branches exhibited high posterior probability and bootstrap values (Figure 10).The results showed that the phylogenetic relationships of tribes within Pentatominae are relatively chaotic.Notably, Neojurtina typica Distant, 1921 was the earliest diverging lineage within Pentatomidae, and representatives of Nezarini and Antestiini formed sister-groups.Moreover, Caystrini and Halyini also exhibited sister-group relationships.As well as representatives of Strachiini and (Sephelini + Pentatoma) formed sister-group relationships.The subfamily Phyllocephalinae clustered as a monophyletic group and also exhibited a sister-group relationship with the genus Placosternum.Furthermore, G. rubrolineatum and Dybowskyia reticulata (Dallas, 1851) also exhibited a sister-group relationship, and Scotinophara lurida (Burmeister, 1834) and Catacanthus incarnatus (Drury, 1773) were clustered together.The subfamily Asopinae clustered as a monophyletic group and exhibited a sister-group relationship with the tribe Menidini.The relationships within Asopinae were as follows: ((Zicrona + (Troilus + A rma)) + ((Dinorhynchus + Cazira) + (Picromerus + Eocanthecona))).
Figure 11 )
Figure 11), occurring in the Barremian Stage of the Early Cretaceous period in the Mesozoic Era.As the earliest species to separate, the divergence time of N. typica was 97.87 Mya (95% HPD: 73.48-123.12Mya), occurring in the Cenomanian period of the Late Cretaceous in the Mesozoic Era.The divergence time of the subfamily Asopinae and the genus Menida was 67.84 Mya (95% HPD: 50.94-86.16Mya), occurring in the Cretaceous Maastricht period of the Mesozoic Era.The subfamily Asopinae started diverging at 56.20 Mya (95% HPD: 41.78-71.30Mya), occurring in the Cenozoic Paleogene Paleocene Tannitian period.The divergence time of the genus Cazira and D. dybowskyi was 51.51 Mya (95% HPD: 41.78-71.30Mya), occurring in the Eocene Epoch of the Paleogene in the Cenozoic Era.The divergence time of the genus Arma and T. luridus was 33.04 Mya (95% HPD: 23.78-44.03Mya), occurring in the Neogene Oligocene Ruperian period.The divergence time of the genus Picromerus and the genus Eocanthecona was 45.24 Mya (95% HPD: 33.35-57.83Mya), occurring in the Lutai period of the Neogene Eocene in the Cenozoic Era.The divergence time between Pic. lewisi and Pic.bidens was 1.08 Mya (95% HPD: 0.66-1.59Mya), occurring in the Calabrian Stage of the Quaternary Pleistocene in the Cenozoic Era.
F
I G U R E 9 Evolution rate of predatory and phytophagous species in Pentatomidae.| 13 of 18 DING et al. 17 kb.No significant difference was observed in the mitochondrial genome size, which was mainly determined based on the number and length of non-coding regions of phytophagous and predatory bugs belonging to the family Pentatomidae.
F
I G U R E 11 Chronogram with estimated divergence time based on fixed rate calibration among Pentatomidae using BEAST 1.8.4.Horizontal bars represent 95% credibility intervals of time estimates.Numbers on the nodes indicate the mean divergence times.
the evolution of Pentatomidae, three subfamilies (Pentatominae, Phyllocephalinae, and Podopinae) retained phytophagy, and Asopinae shifted to zoophagy.The divergence of the subfamily Asopinae occurred during the Late Cretaceous period of the Mesozoic Era, with subsequent diversification of the most speciose clades in the Cenozoic Era.Although many species exhibit some degree of specialization, none of the Asopinae species are truly host-specific(De Clercq, 2002).Moreover, basic driving factors and evolutionary processes in Pentatomidae are not fully understood and require further research. | 5,202.4 | 2024-09-01T00:00:00.000 | [
"Biology",
"Environmental Science"
] |
A comprative study of sol-gel and solid-state prepared La 3+ doped multiferroic BiFeO 3
La x Bi 1- x FeO 3 (LBFO) samples were prepared by sol-gel route using citric acid as chelating agent for x = 0.0 - 0.4. The structure, dielectric and magnetic properties of the LBFO compounds were studied and compared with the corresponding properties of the materials prepared by a conventional solid state reaction. The use of the sol–gel method in preparation lowered the reaction threshold temperature by 200 °C. Effects of the preparation routes and conditions on the phase and microstructures of the materials were investigated in this study using XRD and SEM. The pure BFO without bismuth loss, which cannot be prepared by the solid state reaction, was obtained by the sol–gel method. Sol-gel synthesis could yield a pure phase material at relatively lower temperatures while the solid state method yielded powder with a small amount of the secondary Bi 25 FeO 40 phase. Single phase LBFO prepared by sol-gel method (SG) revealed huge value of dielectric constant than same obtained by the solid state reaction method (SS). Maxwell-Wagner type dielectric dispersion is observed in sol-gel method. Dielectric constant and loss tangent are found to be higher for SG as compared to SS. Huge coercivity (H C ) of the order of ~ 15 kOe is observed in both SG and SS samples due to the high anisotropy in these samples. The increase in the magnetization is observed due to the destruction of spin cycloid structure. The enhanced properties made LBFO a promising candidate for the applications in novel memory devices and spintronics. Copyright © 2014 VBRI press. residue obtained finally, was heated at 600 ºC for 1h to form the desired compound. These powders are made into pellets and sintered for densification at 750 ºC for 4 h.
Introduction
Multiferroics, having the coexistence of magnetic and ferroelectric orders, have attracted the attention of many researchers due to its potential applications for magnetoelectric devices [1]. Among various types of multiferroic materials, perovskite-type BiFeO 3 (BFO) is the only room temperature multiferroic till today having the ferroelectric T C = 1043 K and T N = 647 K. However, the narrow synthesis area of single-phase BFO would result in the formation of secondary phases such as Bi 2 Fe 4 O 9 and Bi 25 FeO 40 along with BFO. In addition, leakage current and low magnetization in BFO limits its usage in multifunctional devices. The multiferroic properties of BFO are very sensitive to its intrinsic defects, such as vacancies. Highly dense materials without impurities are essential to avoid the leakage current and to exhibit good ferroelectric properties. The densification of these materials very much relies on synthesis route and sintering temperature. Many studies have focused on the synthesis of single phase BFO using different techniques. The BiFeO 3 ceramics with R3c phase can be made at different temperatures including liquid phase sintering by a conventional solid-state reaction (SS) [2, 3]. But, this method often leads to the volatilization of bismuth oxide and phase decompositions as SS method involves extensive heating of oxide mixture at higher temperature for densification. On the other hand, the ceramics prepared using sol-gel technique (SG) shows better reactivity than solid state reaction and fully densified samples can be obtained at a relatively lower temperature (~750°C). The sol gel procedure involves molecular level mixing and results in the homogeneous material [4]. The SG technique also has an advantages over SS like low cost, generates less carbon residue and easy to prepare. Hence sol-gel has been considered as an alternative method for the preparation of BFO. It is also noted that the La doping in BFO is a very effective way to reduce the leakage current and also to release the potential magnetization locked in the spiral spin structure [5,6].
In this study, the focus is to understand the effect of the synthesis routes on (i) the structural transition with respect to the La content, (ii) the dielectric properties and (iii) magnetic behaviour of these compounds. To achieve above mentioned objectives, we have synthesized La x Bi 1-x FeO 3 (x = 0 -0.4) ceramics using SS and SG methods and refined the structure considering the R3c and Pbnm structural models for the bulk samples. The observed structural changes and the effect of the synthesis route are correlated with dielectric and magnetic studies on these samples.
Synthesis of LBFO using solid-state reaction
The La2O3, Bi2O3 and Fe2O3 were taken in stoichiometric proportions and thoroughly mixed thoroughly under ethanol medium using a ball mill for 4 h. The ball milling was carried out in a Retsch single station (PM-100) planetary ball milling system in air. A 125 ml tungsten carbide vial and tungsten carbide balls with a diameter of 10 mm, 5 mm and 3 mm were used. The milling speed was set at 350 rpm, and it was stopped for every 30 min of milling for a duration of 2 min to cool down the system, and the balls direction was reversed for further grinding. Then the mixture was pre-calcined at 600 ºC for 30 min followed by the calcination at 820 ºC for 1 h. Further, pellets were made and sintered at 800 ºC for 4 h.
Synthesis of LBFO using sol-gel method
The precursors in a stoichiometric molar ratio were dissolved in 1:5 HNO 3 to form an aqueous solution. Citric acid was then added in appropriate proportion and stirred for 2 h at RT. Then, the mixture was heated at 250 ºC on a hot plate with stirring, which leads to the evolution of gases. The brownish colour residue obtained finally, was heated at 600 ºC for 1h to form the desired compound. These powders are made into pellets and sintered for densification at 750 ºC for 4 h.
Characterization
Room temperature X-ray diffractogram was recorded on these ceramics using Bruker D8 X-ray diffractometer with Cu K α wavelength (1.5418 Å). The samples were characterized for its microstructure using Carl Zeiss Ultra 55 Field emission scanning electron microscopy (FE-SEM) and for chemical composition using Energy dispersive Xray fluorescence (EDS) analysis. For electrical measurements, silver electrodes were formed on both sides of the sample discs to make capacitor geometry. Dielectric constant (є r ) measurements were carried out using Agilent E4980A LCR meter at room temperature (RT). Hysteresis loops were recorded using Quantum Design PPMS-VSM at 300 K by sweeping the external field between -7T to +7T.
X-ray diffraction
The X-ray diffraction patterns of LBFO prepared using solid state synthesis as well as sol gel route, are shown in Fig. 1. XRD data for pure samples shows a minor secondary phase corresponding to Bi 25 FeO 40 for SS where as a clear single phase is found for SG prepared sample. From the figure, the pure BFO is easily indexed as rhombohedral structure with the R3c symmetry and it matches with the standard data (JCPDS card no. 86-1518). The secondary phase is absent for all the dopant samples for SS and SG as La doping helps in stabilization of R3c phase of BFO even for x = 0.05. A small section of XRD pattern in the range of 31º-33º (inset of Fig. 1) shows that the intensity of (1 0 4) diffraction peak suppresses while the intensity of (1 1 0) peak rises as x increases accompanied by a shift towards higher angles seen more prominently in the case of SG sample. These occurrences are due to a gradual structural phase transition from the distorted rhombohedral R3c to orthorhombic Pbnm. The larger ionic substitution of La 3+ (r = 1.22 Å) for Bi 3+ (r = 1.14 Å) results in the large crystal distortion and results in the structural transition. The Rietveld refinement carried out on the LBFO reveals it in R3c phase up to x = 0.2 and the structure changes to Pbnm for x > 0.2 and these are consistent with earlier reports [7]. The pure samples fit well for the R3c symmetry and obtained refinement parameters for the SS and SG samples are a=b= 5.62 Å, c= 13.69 Å and a=b= 5.57 Å, c= 13.87 Å respectively. Whereas for x=0.4, a better fit is observed with orthorhombic Pbnm symmetry with the lattice parameters; a= 5.49, b= 5.53Å, c= 7.59 Å and a=5.60 Å, b=7.81 Å, c=5.43 Å for SS and SG samples.
Morphology
In order to find the grain size distribution in La doped BFO, the morphology of LBFO has been studied using FE-SEM. The density of SG prepared samples is higher as compared to the SS preparation. As shown in the Fig. 2, morphological characteristic on these smples exhibited that the sol-gel synthesis resulted in materials with a finer average particle size (~0.6 μm) compared to powder synthesized via the solid state reaction method (~0.9 μm). It is clear that the grain growth found to be suppressed with increase in La content and helps in densification. The
Dielectric properties
The variation of dielectric constant (ε′) of these samples as a function of frequency in the range 20Hz-2MHz prepared by SS as well as SG route is shown in Fig. 3. The dielectric constant of sol gel synthesized samples is very much higher as compared to solid state synthesized samples ( Table 1). From the figure, the maximum value of dielectric constant can be observed at x = 0.05 in case of SG whereas a maximum in ε′ is observed for x = 0.4 for SS. It is clearly observed that all the SG prepared samples have a very high value of dielectric constant in low frequency region in comparison with the previous reports in other RE doped BiFeO 3 [8,9]. Similar kind of dielectric behaviour with large value of dielectric constant has been found in citric acid route prepared SmFeO 3 [10] and also in other materials prepared using hydrothermal synthesis [11]. This kind of behaviour exhibiting high dielectric constant at low frequency and the low value at high frequency is a mark of large Maxwell-Wagner type dielectric dispersion [12]. The space charge polarization in these samples may result into such high value of dielectric constant at low frequencies.
Magnetic properties
The magnetic hysteresis loops of LBFO samples with x = 0.0, 0.05, 0.2 and 0.4 are measured by applying a field of 7T at 300K is shown in Fig. 4. The M-H curve of the x = 0.0 sample show a linear field dependence of magnetization (M) indicating the antiferromagnetic nature of undoped BFO. The G-type AFM in BFO limits the higher magnetization; however the canting angle between the spins of Fe sub-lattices results in a net residual magnetic moment [13]. The potential magnetization locked in the spin cycloid of the BFO can be released by destroying the cyclic spin structure upon La doping. Remarkable enhancement in the coercivity (H C ) and remanence (M r ) is observed with La, which is a clear indication of the transition from antiferromagnetic to ferromagnetic behaviour. The systematic increase in M r with x is due to the gradual collapse of the space-modulated spin structure of BFO. The M measured at 7 T increases linearly with x and a maximum value is found for SG samples (0.81 emu/g for x = 0.4). M r for BFO at RT almost vanishes and increases gradually with x reaching maximum value for x = 0.4 (0.274 emu/g, 0.24 emu/g for SG and SS respectively). This is in good agreement with the change in the crystal structure caused by La doping. For x ≤ 0.2 the structure remains in R3c, whereas a change in the structure to Pbnm is observed for 0.2 < x ≤ 0.4. Thus, both the canting angle of the spins and the cycloid spin structure has been modified due to the doping. As x increases, the approach to the saturation in M-H loops starts at lower fields.
The maximum H C ~19 kOe is observed for SG samples whereas SS sample shows 14.8 kOe for x = 0.4. All the measured magnetic parameters are listed in the Table 1.
The observed H C in both the preparation methods is the highest reported to the best of our knowledge for the RE doped BFO system. The huge coercivity of the order of ~15 kOe at RT is also observed in the other non RE dopant systems [14,15]. The increase in the H C is associated to the doping-driven increase in the magnetic anisotropy [16]. La substitution changes the crystal field of ligands there by induce the anisotropy and the change in anisotropy can also be interpreted due to the change in spontaneous polarization through the chemical pressure [17,18]. The enhanced magnetic anisotropy mainly comes from magneto crystalline anisotropy and magnetoelastic anisotropy [19]. Further studies are needed to compliment the details of the high magnetic anisotropy in La-doped BFO.
Conclusion
Lanthanum doped bismuth powders were prepared using solid state as well as sol gel method using citric acid as complexing agent. The R3c structure changes to orthorhombic Pbnm phase as the La doping increases. The smaller particle size ~0.4 μm of SG prepared samples results in the high densification and the dielectric constant increases. A large dielectric constant of the order of 10 5 is observed for the SG samples which required further understanding. M-H loops show a huge coercivity in both SG and SS samples due to the high anisotropy in LBFO samples. The increase in the magnetization of these samples is due to the destruction of spin cycloid structure. | 3,152.8 | 2014-02-02T00:00:00.000 | [
"Materials Science"
] |
Ear your heart: transcutaneous auricular vagus nerve stimulation on heart rate variability in healthy young participants
Background Transcutaneous auricular vagus nerve stimulation (taVNS) stimulating the auricular branch of the vagus nerve along a well-defined neuroanatomical pathway, has promising therapeutic efficacy. Potentially, taVNS can modulate autonomic responses. Specifically, taVNS can induce more consistent parasympathetic activation and may lead to increased heart rate variability (HRV). However, the effects of taVNS on HRV remain inconclusive. Here, we investigated changes in HRV due to brief alteration periods of parasympathetic-vagal cardiac activity produced by taVNS on the cymba as opposed to control administration via the helix. Materials and Methods We compared the effect of 10 min of active stimulation (i.e., cymba conchae) to sham stimulation (i.e., helix) on peripheral cardiovascular response, in 28 healthy young adults. HRV was estimated in the time domain and frequency domain during the overall stimulation. Results Although active-taVNS and sham-taVNS stimulation did not differ in subjective intensity ratings, the active stimulation of the cymba led to vagally mediated HRV increases in both the time and frequency domains. Differences were significant between active-taVNS and both sham-taVNS and resting conditions in the absence of stimulation for various HRV parameters, but not for the low-frequency index of HRV, where no differences were found between active-taVNS and sham-taVNS conditions. Conclusion This work supports the hypothesis that taVNS reliably induces a rapid increase in HRV parameters when auricular stimulation is used to recruit fibers in the cymba compared to stimulation at another site. The results suggest that HRV can be used as a physiological indicator of autonomic tone in taVNS for research and potential therapeutic applications, in line with the established effects of invasive VNS. Knowledge of the physiological effect of taVNS short sessions in modulating cardiovagal processing is essential for enhancing its clinical use.
Despite the emerging consensus, the reliability of commonly taVNS protocols has been questioned, and the mechanisms of action are only partially defined at the moment, mainly considering controversial reports or null taVNS-related changes (Borges et al., 2021;Keute et al., 2021;Warren et al., 2019).
Therefore, taVNS protocols often do not apply a crossover design or have adopted numerous variations (Badran et al., 2018a;Burger et al., 2019) for the stimulation target of the auricular branch of the vagus nerve (cymba conchae and the tragus targets (Butt et al., 2020;Colzato et al., 2018a)). Other parameters, such as current intensity, pulse width, and stimulation duration, also vary.
Similarly, the physiological processes underlying the effects of taVNS remain largely unknown (Burger et al., 2020a;Wolf et al., 2021). Excitation of afferent fibers of the peripheral vagus nerve triggers brainstem activity that promotes cardiac activity (Badran et al., 2018b;Rush et al., 2000). Increased efferent vagal activity excites neurons projecting to the sinoatrial node of the heart to release acetylcholine, which decreases the heart rate and increases vagal-mediated heart rate variability (vmHRV) (Burger et al., 2020a). Rapid beat-to-beat variations, such as root mean square of successive differences (RMSSD) and high-frequency power (HF, 0.15-0.40 Hz), reflect vmHRV (Laborde, Mosley & Thayer, 2017) as an indirect measure of (efferent) vagal function. However, recent studies of vmHRV as a biomarker of taVNS have yielded controversial results, often reporting multiple null findings, as suggested in a Bayesian meta-analysis by Wolf et al. (2021), which has cast doubt on the reliability of the marker of autonomic tone.
Several studies have reported an increase in vmHRV (Antonino et al., 2017;Clancy et al., 2014;Lamb et al., 2017;Tran et al., 2019), whereas others have found no increase (Burger et al., 2020a;Burger et al., 2019;Teckentrup et al., 2020). Kaniusas et al. (2019) questioned the effects of taVNS on vmHRV (Kaniusas et al., 2019). Burger et al. (2020b) and Butt et al. (2020) did not find solid evidence in their reviews and meta-analyses and concluded that there is no evidence to support the hypothesis that vmHRV is a reliable biomarker for online taVNS. Even narrative reviews on the modulation of vmHRV are inconclusive (Wolf et al., 2021). Possible explanations for the heterogeneity of the effects may be attributed to the excitation of afferent fibers via taVNS that innervate the heart indirectly via brainstem nuclei, rather than directly (De Couck et al., 2017;Kaniusas et al., 2019;Safi, Ellrich & Neuhuber, 2016;Vuckovic, Tosato & Struijk, 2008). The reviews also emphasized significant methodological differences between studies (e.g., experimental design and implementation, optimal stimulation sites and parameters, and reported HRV parameters). Considering that the stimulation has shown beneficial effects in the reduction of symptoms in psychopathology (e.g., depression (Fang et al., 2016;Koenig et al., 2021)) and in other medical conditions (e.g., heart failure, pain, epilepsy) (Aihua et al., 2014;Napadow et al., 2012;Stavrakis et al., 2020), it is critical to understand its potential for research and therapeutic applications as well as to evaluate its limitations. From a safety perspective, besides alternating on-off stimulations, vulnerable patients could be subjected to short sessions of taVNS (De Martino et al., 2021). Consequently, the aim of this study was to evaluate how taVNS stimulation applied to the cymba conchae and helix affects vmHRV parameters after a brief session of 10 min. Clinical applicability depends on knowledge of the physiological role of taNVS in modulating cardiovagal processing. If taVNS increases HRV, our work can be used as a comprehensive reference to advance future treatment of diseases with low HRV.
Participants
Sample size was determined using G Ã Power 3 software (Faul et al., 2007).
The computation parameters included setting a to 0.05, desired power (1 − β) to 0.95, and a moderate effect size (d = 0.25) expected for the effects of taVNS on HRV based on a previously published study (Wolf et al., 2021). Accordingly, a sample size of at least 25 was estimated. However, considering the potential for cardiac rhythm alteration, a sample of 30 participants was considered adequate.
Participants were eligible if they were between 18 and 30 years of age, right-handed, free of extensive ear piercings, and not taking medications that might affect the autonomic nervous system.
According to the guidelines (Farmer et al., 2021), participants also had no contraindications to taVNS: (a) pregnancy; (b) active implants (e.g., pacemakers, cochlear implants) or brain shunts; (c) previous neurological or psychiatric diagnoses; (d) history of addiction or substance abuse; (e) trauma and/or brain surgery; (f) cardiac disease; (g) acute or chronic use of medications and/or drugs; (h) susceptibility to headaches and seizures.
Of the 30 participants included in the study, two individuals who reported altered HRV values with high noise levels were excluded from data analysis of the study. A total of 28 participants (mean age: 23.15 years ± SD = 3.16, 23 female) in condition of normal weight (BMI < 25.0) completed the study. All participants had to be naive to the purposes and experimental procedure. No participant had previously received any type of vagal stimulation. Data were collected from September 2021 to January 2022.
The protocol was approved by the Ethics Committee of the University of Rome "La Sapienza" (Protocol number: 0001541), and all participants signed the informed consent. Recruitment of participants took place on a voluntary basis (dissemination of advice) at "Sapienza" University of Rome. Prior to each experimental session, to voluntaries were given some general information of the study and the instructions to follow in order to comply with the International Guidelines for the Assessment of HRV (Malik, 1996): abstaining from nicotine and caffeine consumption in the two 2 h before the assessment and from alcohol consumption and intense physical activity in the 12 h before the experiment.
Auricular transcutaneous vagus nerve stimulation
The taVNSÒ L device developed by tVNS Technologies GmbH (Erlangen, Germany) was used. The approved device (CE certification) consists of a programmable stimulation unit connected to two titanium electrodes located in an earphone-like structure. Stimulation was applied to the left ear to avoid stimulation of fibers to the heart (Kreuzer et al., 2012;Sperling et al., 2010) and parameters are pre-set, with a biphasic impulse frequency delivered at a rate of 25 Hz, width of 200-300 ms and an on-off cycle of 30 s (Borges, Laborde & Raab, 2019;De Couck et al., 2017).
For the active taVNS condition, the electrode was placed at the cymba conchae, which has been shown to have the highest density of projections from the auricular branch of the vagus nerve (Badran et al., 2018b;Peuker & Filler, 2002;Safi, Ellrich & Neuhuber, 2016) and to cause greater activation of the vagal pathway (Yakunina, Kim & Nam, 2017a). For the active sham condition, electrodes were placed at the helix without overlapping the other innervation areas, which are not expected to elicit vagal activation (Ellrich, 2019; Peuker & Filler, 2002). Stimulation loci were cleaned with alcohol cotton swabs to reduce skin resistance, and the electrode head was placed according to the characteristics of the participants' ears.
Cardiac vagal activity
The Firstbeat Bodyguard two heart rate monitoring system (Firstbeat Analytics, Jyväskylä, Finland) was adopted to assess cardiac vagal activity. The signal was acquired by two Ag/AgCl electrodes (Ambu BlueSensor L, Ballerup, Denmark), one applied under the right collarbone and the other under the left rib cage. Both the time and frequency domains were analyzed. The time domain included the standard deviation of the RR intervals (SDNN) and the square root of the mean of the square of successive differences between adjacent R-R intervals (rMSSD). In the frequency domain, the low-frequency range (LF; 0.04-0.15 Hz), reflecting a mix of sympathetic and vagal influences, and the high frequencies (HF; 0.15-0.40 Hz), an index of the parasympathetic cardiac tone (Laborde, Mosley & Thayer, 2017), were considered. The ratio of power in these frequency bands, LF/HF, was calculated. However, it is important to consider that the ratio may be influenced by different aspects (e.g., body position), complicating the use of the LF /HF as a reliable index of parasympathetic-sympathetic balance (Billman, 2013;von Rosenberg et al., 2017). HRV signals were analyzed using Kubios software (Tarvainen et al., 2014) (ver. 3.4.3., Kubios Oy, Kupio, Finland) and adopting a custom correction according to previous studies and HRV guidelines (Forte, Favieri & Casagrande, 2019;Forte et al., 2021;Laborde, Mosley & Thayer, 2017). This procedure allows the exclusion of possible outlier measurements. For each participant, HRV was evaluated at rest (baseline) and during active/sham stimulation conditions.
Self-reported adverse reaction
Potential side effects of the applied stimulation were assessed at the time of stimulation and at the conclusion of the stimulation periods by asking participants to report their taVNS-related sensations. Each sensation was rated on a numerical rating scale, from 0 (not at all) to 100 (the highest unpleasant sensation/very high feeling of tension). A baseline requirement for the procedure was that the stimulation was perceptible but not disturbing or painful. At the end of the experiment, participants were asked to inform the investigators about possible side effects to avoid interference from unpleasant/painful sensations and to ensure an appropriate level of comfort. In addition, screening for any adverse effects was also ensured between the two sessions and at the end of the procedure for any problems that may arise, but no side effects were reported.
Procedure
To remove inter-subject variability from the comparison between groups frequently encountered in HRV analysis, we adopted a sham-controlled, single-blinded, randomized crossover within-subject design (Quintana & Heathers, 2014) that reduced the effect of covariates, for instance, age and gender related effects on HRV (Bretherton et al., 2019;Clancy et al., 2014;Deuchars et al., 2018;Koenig et al., 2021). In order to ensure greater comparability of the cardiac signal, the two experimental sessions were scheduled at the same hour and day of the week so as to best control for variations related to circadian rhythms or other activities of the participants.
All measurements were performed in a quiet room with dimmed lighting conditions. After a 20-min adaptation period, standard HRV resting recordings were collected for 5-min at rest before of the stimulation. Participants were asked to sit with knees at a 90 angle, both feet flat on the floor, hands on thighs, with palms facing upward, and keep the eyes closed. After a brief interview, sensors and stimulation devices were attached to the subject's body, and then the experimental session started. In the within-subject experiment, each session consisted of a preliminary HRV recorded in the resting phase (baseline, 5 min) and consecutive phases of an active/sham stimulation (S1, 10 min), separated by a 1-week interval.
These sessions differed only for the stimulation (active-taVNS vs. sham-taVNS) in two 1-week-apart sessions that were randomly assigned in a counterbalanced order across participants.
After the HRV-resting, the current intensity was determined by each participant by using the threshold method to adjust the intensity of taVNS/sham stimulation intensity according to the participant's sensitivity.
This procedure systematically identifies the maximal comfortable stimulation levels for each individual, as in the studies by Yakunina, Kim & Nam (2017b), and Ventura-Bort et al. (2018). To adjust before each session of stimulation for each participant intensity, the stimulation started with an intensity of 0.2 mA, and increasing in each trial by 0.1 mA, until the participant clearly felt a tingling but not painful perception to selectively stimulate afferent mechanoreceptive Aβ-fibers but not pain-related Aδ-fibers. This procedure was conducted twice for each stimulation location and the average of the intensities rated as not painful was used as the stimulation threshold.
taVNS electrodes were placed on the cymba conchae and on the helix for the active and sham condition, respectively. The same parameters, except for the intensity and site of stimulation on the ear, were used during active-taVNS and sham-taVNS, thus ensuring participants' blinding to the type of stimulation. After the taVNS setup was completed, the neurostimulation was administered for 10 min while participants completed a demographic questionnaire. HRV measurement was performed to measure cardiac vagal activity during the overall active/sham stimulation condition. Self-reported rating scales were administered to assess tension pre and post each experimental condition (active/sham stimulation).
Data analysis
Outliers (less than 1% of the data) were removed. According to previous studies (Forte et al., 2021;Forte et al., 2022a), HRV data were log-transformed for approximately following normal distribution.
A repeated measures (rest, active and sham stimulation condition) ANOVA was conducted on all HRV indices as dependent variables. We set p = 0.05 as a statistical significance level. Age and gender, considered as moderators, were also tested.
RESULTS
Participants were stimulated with an average intensity of 1.2 mA (SD ± 0.4). For each participant, the intensity of stimulation levels was comparable for active and sham treatment (F 1,27 = 2.90; p = 0.11). There was no significant difference in stimulation levels between males and females (F 1,27 = 1.26; p = 0.28). In addition, no significant differences were found between males and females in baseline HRV measurements (F 1,27 = 0.02; p = 0.88). Table 1 summarizes results of analyses with log-transformed data on HRV for the three conditions (resting, active-taVNS and sham-taVNS).
Self-reported side effect
Regarding side effects, the differences between the active-taVNS and sham-taVNS were not significant (F 1,27 = 0.32; p = 0.57), allowing us to rule out possible confounding effects due to participants' disposition under the two stimulation conditions. None of the volunteers reported any discomfort during and after the stimulation and no adverse effects occurred during the stimulation period, or within a week after each session. Overall, stimulation was well tolerated, participants reported a low level of tension (mean score of 27.91) and there were no significant differences between conditions (active/sham stimulation) (F = 0.28; p = 0.58).
DISCUSSION
This study demonstrated that, in contrast to sham-taVNS, active-taVNS might modulate the HRV of young healthy individuals, resulting in significantly better RMSSD, SDNN, and HF power values. Studies have investigated the effects of vagus nerve stimulation on HRV, with controversial (Wolf et al., 2021) or null findings (Vosseler et al., 2020). For example, De Couck et al. (2017) found that taVNS significantly increased SDNN compared to baseline without the effects on RMSSD, HF, or LF/HF, while other have found an increase in these parameters reflecting cardiac vagal modulation (Bretherton et al., 2019;Gauthey et al., 2020;Geng et al., 2022;Keute et al., 2019). In contrast, some studies have indicated that taVNS significantly decreased the LF/HF ratio without significant effects on other indexes of HRV (Clancy et al., 2014;Weise et al., 2015). This discrepancy, as mentioned in the introduction, may be explained by the variability in study design, which might affect how results are interpreted (Badran et al., 2018b). Indeed, some studies compared active stimulation to a "stimulation off" sham condition (Clancy et al., 2014;De Couck et al., 2017). Pain sensation or stressful emotions caused by taVNS, as well as respiration, can affect HRV (Laborde, Mosley & Thayer, 2017) and thus might result in confounding variables that potentially affect the interpretation of results. Therefore, we stimulated the helix (i.e., relatively free of vagal afferents) with the same parameters for the sham-taVNS and active-taVNS conditions. In addition, in the present study, self-reported side effects showed no significant difference; therefore, it is assumed that the potential influence of irrelevant variables was controlled, with consequently increased comparability between the active and control stimulation. Accordingly, these aspects might explain the inconsistencies with previous studies.
With 10 min of stimulation, in terms of indices for HRV, we observed a significant increase in RMSSD and SDNN for active-taVNS compared to sham-taVNS in the temporal domain. While SDNN reflects both sympathetic and parasympathetic influences, RMSSD is thought to represent vagally mediated HRV, and both are less influenced by changes in respiratory parameters than frequency indices.
Additionally, a significant change in the parasympathetic activity of HF was observed in the frequency domain when compared to sham-taVNS. Thus, we confirmed enhancement of the measurements of RMSSD, SDRR, and HF power described in healthy young people in a previous study (Geng et al., 2022) for short (5 min) taVNS stimulation.
Individual stimulation patterns, however, showed no differences between active-taVNS and sham-taVNS for LF and distinct LF/HF tendencies. On different autonomic pathways, short taVNS may have a specific impact. HF power is mediated largely via respiration and mainly reflects cardiac parasympathetic nerve activity, while LF is a more complex power hypothesized to indicate a measure of mainly cardiac autonomic outflow by baroreflexes, sympathetic drive, and other yet unidentified factors (Billman, 2013;Goldstein et al., 2011). We observed a tendency to see a higher absolute increase in LF power compared to the increase in HF power, which led to an increase in the LF/HF ratio, presumably due to already low sympathetic and high parasympathetic prevalence. The change in LF power or LF/HF ratio may occur not by affecting cardiac autonomic outflows directly but by affecting modulation of these outflows by baroreflexes, as has been shown (Antonino et al., 2017). Moreover, the difference between sham-taVNS and baseline, in both LF and LF/HF, could suggest higher sympathetic activity during sham stimulation. Also, active-taVNS improves sympathetic activity compared to baseline but, in concomitance, it involves an increase in parasympathetic activity. This suggests an activating role of stimulation, which should be controlled. Additionally, Geng et al. (2022) proposed that the baseline LF/HF ratio was a significant predictor of participants' responses to taVNS: a higher baseline LF/HF ratio was associated with a greater LF/HF ratio decrease. This evidence could be better analyzed in further studies despite the issues related to these measures. Indeed, the physiological source and meaning of LF power are difficult to discern, justifying agreement among the scientific community that HF is the most effective and reliable index of the frequency domain in the interpretation of HRV (Billman, 2013;von Rosenberg et al., 2017). Such predictions could enable the selection of optimal individuals for taVNS, considering the number of conditions that influence sympathetic prevalence/autonomic imbalance, e.g., pain, inflammation, and even position.
Studies on the effect of taVNS on LF and LF/HF have provided controversial results (Wolf et al., 2021). Interestingly, De Couck et al. (2017) found no effects on LF/HF for short (10 min) stimulation, but taVNS significantly increased LF and LF/HF in prolonged stimulation (35 min), suggesting a period of 'adaptation' to stimulation. An increased LF/HF ratio was confirmed after longer stimulation (60 min) (Tran et al., 2019) but not after brief stimulation (5 min) (Geng et al., 2022). By contrast, other studies have indicated that taVNS significantly decreases the LF/HF ratio without significant effects on other indexes of HRV (Clancy et al., 2014;Weise et al., 2015). Notably, these studies compared different stimulation targets and parameters, which might affect interpretation of the results.
Recently, the effect of specific taVNS parameters on these markers of parasympathetic vagal activity has been examined. Lower pulse duration values (<500 ms) seem to allow for a more selective nerve fiber type of recruitment (Machetanz et al., 2021). These results support the role of the choice of stimulation parameters, considering that the vagus nerve comprises myelinated and unmyelinated fibers with disparate diameters and activation thresholds (Deuchars et al., 2018). In a study by Machetanz et al. (2021), variations in pulse width parameters corresponded to changes in stimulation intensity. In contrast, we adjusted the latter according to the participants' perceptual threshold.
In conclusion, our study can be considered as part of a dynamic and developing empirical background. Although several authors have explored the effects of taVNS and speculated on its neurophysiological mechanism, the direction of the results is unclear.
This study provides evidence that taVNS may increase cardiac vagal activity, although the findings should be considered with caution. taVNS effects are indirect considering that the auricular branch of the vagus nerve consists only of afferent fibers. Specifically, as proposed by some authors (Komisaruk & Frangos, 2022;Murray et al., 2016;Sawchenko, 1983), taVNS may increase input to the NTS, thereby increasing the activity of NTS neurons projecting to the two vagal efferent nuclei: the dorsal motor nucleus and the nucleus ambiguus. Increased activation in these nuclei may, in turn, increase vagal control of cardiac activity (Komisaruk & Frangos, 2022;Sawchenko, 1983).
taVNS may have neuromodulatory effects on vmHRV that are not mediated by the NTS but instead via sensory afferent projections to the upper cervical spinal cord (Mahadi et al., 2019). Similarly, increased vagal control of HRV during auricular stimulation correlates with frequency-specific increases and decreases in oscillatory activity in various brain areas (i.e., frontal and frontoparietal areas (Machetanz et al., 2021)). Finally, taVNS appears to increase spontaneous cardiac baroreflex sensitivity and indirectly influence parasympathetic efferent innervation of the heart (Antonino et al., 2017).
However, despite the anatomical and physiological plausibility of the indirect effects of taVNS on HRV, many steps to validation remain before HRV may be considered a relevant index of taVNS efficacy. Considering the evidence provided for both mental health and cognitive functions of taVNS (Colzato, Ritter & Steenbergen, 2018b;Thakkar et al., 2020) and HRV (Forte, Favieri & Casagrande, 2019;Forte et al., 2021;Forte et al., 2022a;Forte et al., 2022b), these results open the way to potential clinical trials.
Limitations
Despite the encouraging results, this study has limitations. The complex nature of LF power could explain the results (Shaffer, McCraty & Zerr, 2014). LF oscillations provide information about blood pressure control mechanisms, such as the modulation of vasomotor tone (Berntson et al., 1997;Taylor & Sarno, 1998). HF and LF power showed rather slight changes of conditions compared to baseline, which suggests that markers of overall HRV are more sensitive to a presumable autonomic activation than specific increases following taVNS, presumably due to already low sympathetic and high parasympathetic prevalence. Therefore, unclear knowledge about the dominance of HRV indices, in particular LF, has been highlighted, as they may be inaccurate measures of SNS activity and of SNA in general (Laborde, Mosley & Thayer, 2017).
Despite the lack of a clear consensus, to optimize the effects of taVNS-related HRV, we stimulated the cymba conchae of the left ear. However, some taVNS studies have shown significant results for right tragus stimulation (Badran et al., 2018b;Badran et al., 2022;Yakunina, Kim & Nam, 2017b). Considering safe parameters, conventionally, the left side is the preferred stimulation site due to concerns about cardiac side effects (Borges, Laborde & Raab, 2019;Burger et al., 2019). However, it might be interesting to test the short-term effects of adopting variations of stimulation target (left/right, cymba/tragus).
In accordance with the range suggested by recent recommendations for experiment planning with HRV in psychophysiological research, it is unnecessary to use recordings longer than 120 s to obtain accurate measures of RMSSD (Laborde, Mosley & Thayer, 2017). However, future studies might test the long-term effects of taVNS on HRV parameters, e.g., in multiple stimulation sessions spread over a longer period (longer than a 24-h period). Furthermore, the mediating role of physiological covariates, such as baroreflex and respiratory changes as well as blood pressure, could be evaluated in further studies. Moreover, vmHRV could be compared with additional appropriate biomarkers of taVNS efficacy, such as somatosensory evoked potentials (Fallgatter et al., 2003), pupillary dilation, event-related potential P300, and salivary alpha-amylase (Burger et al., 2019;Warren et al., 2019).
Finally, although the study employed a within-subject crossover design, we adopted a straight control of taVNS intensity for each participant and measured the absence of gender differences in resting HRV parameters, the study is not exempt from gender limitations due to recruitment from a female-dominated field. Future studies may answer the question of gender differences with a more heterogeneous sample.
CONCLUSION
In conclusion, our results indicate a rapid increase in several HRV parameters when taVNS is used to recruit fibers in the cymba compared with taVNS stimulation administered via the helix. Future studies should examine the effect with a heterogeneous sample and with other appropriate biomarkers to support our findings. A shortened stimulation time may be useful to evaluate the acute effects of taVNS on HRV, which may be used as a physiological indicator of autonomic tone for safe clinical applicability. Investigation of taVNS-mediated changes in brain networks that promote cardiac activity is necessary to better understand the physiological mechanism of action of taVNS and to establish meaningful protocols for research and clinical trials.
ADDITIONAL INFORMATION AND DECLARATIONS Funding
This work was supported by the Italian Ministry of Health, grant number RF-2018-12365682. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Grant Disclosures
The following grant information was disclosed by the authors:
Human Ethics
The following information was supplied relating to ethical approvals (i.e., approving body and any reference numbers): The protocol was approved by the Ethics Committee of the Department of Dynamic and Clinical Psychology and Health Studies of the University of Rome "La Sapienza" (Protocol number: 0001541). | 6,154.4 | 2022-11-21T00:00:00.000 | [
"Biology",
"Medicine"
] |
Calderón Strategies for the Convolution Quadrature Time-Domain Electric Field Integral Equation
In this work, we introduce new integral formulations based on the convolution quadrature method for the time-domain modeling of perfectly electrically conducting scatterers that overcome some of the most critical issues of the standard schemes based on the electric field integral equation (EFIE). The standard time-domain EFIE-based approaches typically yield matrices that become increasingly ill-conditioned as the time-step or the mesh discretization density increase and suffer from the well-known DC instability. This work presents solutions to these issues that are based both on new Calderón strategies and quasi-Helmholtz projectors regularizations. In addition, to ensure an efficient computation of the marching-on-in-time, the proposed schemes leverage properties of the Z-transform—involved in the convolution quadrature discretization scheme—when computing the stabilized operators. The two resulting formulations compare favorably with standard, well-established schemes. The properties and practical relevance of these new formulations will be showcased through relevant numerical examples that include canonical geometries and more complex structures.
I. INTRODUCTION
T IME domain boundary integral equations (TDIEs) are widely used in the simulation of transient electromagnetic fields scattered by perfectly electrically conducting (PEC) objects [1]- [4].Like their frequency-domain counterparts, the spatial discretization of these equations is often performed via the boundary element method.The time discretization, however, can be tackled in different ways.A popular approach leverages time basis functions either within a Marching-On-in-Time (MOT) scheme [5]- [7] or within a Marching-On-In-Order procedure [8].The convolution quadrature (CQ) approach [9], [10] is an attractive alternative to these methods in which only space basis functions are explicitly defined.The approach has been applied to several equations in elastodynamics and acoustics [11], [12] and then in electromagnetics [13].It provides an efficient time-stepping scheme with matrices derived from the spacediscretized Laplace domain operators.
Another advantage of the CQ method is the use of implicit schemes (e.g.Runge Kutta methods [14]- [18]), which are generally more stable and typically allow for a better accuracy control of the solution over time [19], [20].However, the CQ time stepping scheme is solved via a computationally expensive MOT algorithm.Nowadays, fast solvers can reach quasi-linear complexity in time and space [21], [22].Usually, this fast technology uses iterative solvers, resulting in an overall computational cost that is proportional to the number of iterations which is low for well-conditioned systems.Working with well-conditioned matrices is therefore essential to reduce the computational cost of the solution process, in addition to being necessary to obtain accurate results [23].
Lamentably, however, the CQ discretized time domain electric field integral equation (EFIE) is plagued by several drawbacks.Indeed, the matrices resulting from the discretization of the EFIE are known to become ill-conditioned for large time steps or at dense mesh discretizations: the condition number of the MOT matrices grows quadratically with the time step and with the inverse of the average mesh edge length.These two phenomena are the CQ counterparts of what for standard MOT schemes are known as the large time step breakdown [24]- [27] and the dense discretization breakdown (or ℎ-refinement breakdown) [28], [29].Another challenge in handling the CQ EFIE is that it involves operators whose definitions include a time integration.To avoid dealing with this integral, the time-differentiated counterpart of this formulation is often used [13], [30], but this differentiation is subject to a source of instability in the form of spurious linear currents living in the nullspace of the operator that degrades the solution [28], [31]; this phenomenon is known as the direct current instability (DC instability).
In this work, we propose new Calderón-preconditioned and quasi-Helmholtz regularized formulations free from the limitations mentioned above.The Calderón identities they rely on are already a well-established preconditioning approach in both the frequency domain [32] and time domain discretized by the Galerkin method [28], [29], [33], [34] that is extended in this work to convolution quadrature discretizations and complemented with quasi-Helmholtz regularization.The contribution of this paper is twofold: (i) we present a first approach to tackle the regularization of the EFIE operator and to address the DC instability resulting in a new operator that presents no nullspace on simply connected geometries, thus stabilizing the solution, and (ii) we build upon this first regularized form of the EFIE to obtain an equation that, at the price of a higher number of matrixvector products, is stable in the case of multiply connected geometries.
This article is structured as follows: the time domain formulations of interest are summarized in Section II along with the convolution quadrature method and the boundary element method for spatial discretization; in Section III, the new Calderón and projectors-based preconditioning strategies are presented; finally, Section IV presents the numerical studies that confirm the effectiveness of the different approaches before concluding.Preliminary studies pertaining to this work were presented in the conference contribution [35].
A. Time Domain Integral Formulations
In this work, we consider the problem of time-domain scattering by a perfectly electrically conducting object that resides in free space.The object is illuminated by an electromagnetic field ( inc , inc )(, ) which induces a surface current density on its boundary that is the solution of the time-domain EFIE Here, n is the outpointing normal to and 0 is the characteristic impedance of the background.The electric field operator T includes the contributions of the vector and scalar potentials, respectively denoted T s and T h [30] T (, ) = − 1 where 0 is the speed of light in the background.The temporal convolution product * and the temporal Green function G are defined as with the time Dirac delta.
B. Marching-On-In-Time with Convolution Quadratures
Let be a placeholder for any of the integral operators previously presented and let (, ) be a causal function (∀ < 0, (, ) = 0).With these notations, most time domain integral equation take the form where c is the solution to be solved for.The first step of the Marching-On-in-Time solution scheme with convolution quadratures is to apply the boundary element method [3], [36], [37] as spatial discretization.Assuming separability between the space and time variables, the unknown function c is expanded as a linear combination of spatial basis functions such that [38] c (, ) ≈ where src are the source spatial basis functions and their associated time coefficients are stored in the vector f ().
Then, the equation ( 7) is tested by the spatial basis functions tst leading to the time-dependent matrix system where for and in ⟦1, ⟧, we have, with The second step is the discretization in time with the convolution quadrature method [9], [10], [12]- [14], [38].First, the system (9) must be transformed in the Laplace domain [39] and we denote θ L , f L and k L the Laplace transform of θ, f and k .The system (9) is then equivalent to Then, a representation on the Z-domain discretizes the system (12).The Laplace parameter, in the operator θ L , is replaced by the matrix-valued parameter diagonalizable for the considered values, with the following eigenvalue decomposition s cq () = Q()()Q −1 ().The elements of the diagonal matrix () are the eigenvalues of s cq () and the columns of Q() are their associated eigenvectors.The time step size is denoted and the matrix A and the vectors 1 , c, b of size are determined by the implicit scheme used [40].The discretized Z-domain operator θ Z is defined such that for any for and in ⟦1, ⟧ and for and in ⟦1, where , = (−1)+ is an appropriate indexing function and θ , () is a diagonal matrix defined as The vectors f Z and k Z are the Z-domain representation [40] of the respective time-discretized vectors yielding to the following discretization of the system (12) Finally, the equivalent time discretized system of ( 9) is obtained by applying the inverse Z-transform on ( 17) where Z θ, = Z −1 → θ Z () are the time domain interaction matrices and * is the sequence convolution product.The system sequence ( 18) is rewritten in the following Marching-On-In-Time that can be solved for
C. Classic Integral Marching-On-In-Times
In this subsection, the discretization scheme described above will be applied to the specific case of the EFIE.The Rao-Wilton-Glisson (RWG) basis functions rwg [37], [41] are used to expand the current density as where the current coefficients are gathered in an unknown vector function of time j ().The EFIE is then tested with rotated RWG basis functions n × rwg , leading to the following Marching-On-In-Time where the vector sequences j and e inc , and the time domain interaction matrices Z T , are respectively generated by the convolution quadrature method described in Subsection B of j () and the following space-discretized vector and matrix However, the time integral contribution of this operator T involves an unbounded number of non-vanishing matrices Z T , (21), leading to a prohibitive quadratic complexity with the number of time steps [42].Historically, the time differentiated formulation is preferred because it is not afflicted by this drawback [13], [30], and leads to the following MOT [30] Z T ,0 j = − −1 0 e inc − where e inc and Z are respectively the time domain vectors and interaction matrices generated by the convolution quadrature method described in Subsection B of
D. EFIE DC instability
The electric field integral operator suffers from the DC instability: since for all constant-in-time solenoidal current cs we have ∇ • j cs = 0 and cs = 0, we can conclude that T cs = 0 .
Therefore, the EFIE solution is only determined up to a constant solenoidal current [30].Its time differentiated counterpart inherits these drawbacks and amplifies the DC instability by further adding linear in time solenoidal currents to the nullspace.This latter deteriorates the late time simulation in which spurious currents grow exponentially in the operator nullspace [43].This behaviour is predicted by the polynomial eigenvalues analysis of the MOT: a stable MOT has all its eigenvalues inside the unit circle in the complex plane while a MOT that suffers from the DC instability has some eigenvalues that cluster around 1 [44].The eigenvalue distribution of the time differentiated EFIE MOT is represented in Figure 1 in which such a cluster is clearly visible around 1.
E. Quasi-Helmholtz projectors
Previous works show that the electric field integral equation discretized in space using RWG basis functions can be stabilized by the quasi-Helmholtz projectors [30], [34].These projectors are formed from the star-to-rwg transformation matrix, denoted Σ and defined in [45], which maps the discretized current into the non-solenoidal contributions [46], [47].The quasi-Helmholtz projectors on the non-solenoidal space and its complementary (the one on solenoidal/quasiharmonic space) are respectively where + denotes the Moore-Penrose pseudoinverse [45].
III. Calder ón preconditioning of the EFIE
EFIE formulations based on the quasi-Helmholtz projectors cure the DC instability and the conditioning at large time steps.However, these formulations still suffer from a dense discretization breakdown.One appealing strategy could be to apply standard preconditioning schemes to the Marching-On-In-Time matrices directly to cure the matrix conditioning issues.However, the solution currents would remain unaltered and subject to DC instabilities as the original scheme.This is why the preconditioning has to be performed on the continuous equations to build a new operator without nullspace and then discretize the formulation to obtain a well-conditioned scheme.In this part, Calderón preconditioning strategies are proposed to cure the DC instability and the conditioning breakdowns.
A. A Convolution Quadrature Calder ón time-domain EFIE
Calderón preconditioners are based on the Calderón identity [29], [48] where • is the composition operator, I is the identity operator and K is defined as The operator −I/4 + K 2 is a well-behaved operator for increasing discretization densities.As a consequence, with a proper discretization, T 2 is well-conditioned for large time steps and dense meshes for simply connected structures [45].
In practice, a discretization of T 2 is used in which the right EFIE operator is discretized with RWG basis functions and the left preconditioner is discretized with Buffa-Christiansen (BC) basis functions bc The preconditioning leads to the following space-discretized formulation where the matrix G is the mixed gram matrix linking the the two discretizations Then, the convolution quadrature leads to the MOT scheme where Z T, are the time domain interaction matrices of the space-discretized operator T () (31) generated by the convolution quadrature method described in Subsection B, the sequence convolution quadrature product * is the discretization of the space-discretized temporal convolution product * and The Kronecker product ⊗I is required to match with the convolution quadrature method where I is the identity matrix of size .Unfortunately, the MOT in (34), involves operators with temporal integrations leading to a time consuming MOT.A more favorable scheme can be obtained by noticing the following commutative properties and the cancellation property T 2 h = 0 [32], we have This is advantageous since, besides not involving any time integration contribution, the operator −2 0 2 2 T 2 s − T s T h − T h T s has no nullspace for simply connected geometries leading to a DC-stable discretization ("dottrick TDEFIE") [52].By extending the previous notations on T s and T h the proposed space-discretized operator is denoted ) yielding to the following space-discretized formulation The right-hand side operator still involves a temporal integration in (41).However, given the commutative properties (37), the temporal integral on the scalar potential T ℎ is evaluated with the incident field where Therefore, the previous MOT is rewritten as where the time domain interaction matrices Z T c , , Z T s , and Z T h , are respectively generated by the convolution quadrature method described in Subsection B of the space- As in (34), the interaction matrix sequence Z T c , involves computationally expensive sequence convolution products * , however, the convolution quadrature method allows the substitution of the sequence convolution products * by matrix multiplications in the Z-domain, that can be evaluated at a lesser cost.By extending the notations of the convolution quadrature described in Subsection B on the space-discretized operators T s/h and T s/h and by using the Z-domain properties, the matrix sequence Z T c , is equal to where the matrix s cq () = I ⊗ s cq () is the Z-discretization of the time derivative and I is the identity matrix of size .The formulation ( 44) is a good candidate to obtain a stable current solution, however, the proposed operator T 2 has static nullspaces for multiply connected geometries [33].As such, ( 40) is still subject to DC-instabilities for multiply connected geometries.The polynomial eigenvalue analysis on a sphere and on a torus (respectively Figure 2 and Figure 3) illustrate this phenomenon.While all the eigenvalues cluster in 0 in the spherical case, an analysis on a torus highlights four eigenvalues of this MOT clustered around 1, corresponding to the four constant regime solutions [33].
B. A Convolution Quadrature Calder ón time-domain EFIE regularized with quasi-Helmholtz projectors
The previous Calderón formulation is perfectly adapted to simply connected geometries, ensuring that the new operator has no nullspace.However, on multiply-connected geometries, the harmonic subspace is non-empty, thus enlarging the nullspace of T which is a new source of DC instability in (44) [33].The discretized EFIE operators can be regularized using the quasi-Helmholtz projectors to address this issue.
Because the regularization is based on projectors, it does not compromise the ℎ-refinement regularizing effect of the original Calderón scheme.The regularized EFIE spacediscretized operators are where the BC quasi-Helmholtz projectors are defined with the loop-to-RWG transformation matrix Λ [45] such that and where the scaling 0 with defined as the maximal diameter of the scatterer, ensures consistent dimensionality and helps reduce the conditioning further.This application of the projectors is equivalent to differentiating the nonsolenoidal contributions on the left and in time integrating the solenoidal contributions on the right of each EFIE operator [30].The regularized Calderón operator in the spacediscretized time domain is At first sight, ( 46) and ( 47) seem to involve unpractical temporal integrals.However, the problematic contributions in the regularized EFIE operator T reg will vanish, since P T h = T h P = 0 and P T h P = T h , and we have Similarly, the dual EFIE operator simplifies as The space-discretized formulation of the regularized Calderón EFIE is where The right-hand side of (52) has a temporal integral which is directly evaluated on the incident field to avoid quadratic complexity with the number of time steps.This leads to the following MOT where P = P ⊗ , P = P ⊗ , the vector sequence y is the time discretization of y (), and the time domain interaction matrices Z T reg c , and Z T reg , are respectively generated by the convolution quadrature method described in Subsection B of the space-discretized operators T reg c and Once the computation of y is done, the current j still has to be evaluated.The convolution quadrature discretization of the time derivative is where ,0 is the Kronecker delta, [30].Therefore, the current solution is obtained as
IV. Results
To test the effectiveness of the proposed schemes, simulations have been realized with different geometries, excited by a Gaussian pulse plane wave where = 6/(2 bw ), p = x, k = − ẑ, 0 = 1 V m −1 and bw is the frequency bandwidth.Notice that this frequency bandwidth is proportional to the maximal frequencies excited by the pulse Gaussian.In this work, the Runge-Kutta Radau IIA method of stage 2 is used for all simulations [17], [18].The time step size has been chosen equal to ( max ) −1 where max is the upper frequency of the excitation and = 3 is an oversampling parameter.
A. Canonical geometries
To illustrate the key properties of the newly proposed schemes, namely the Calderón preconditioned formulation (44) and the and the Calderón preconditioned formulation regularized by the quasi-Helmholtz-projectors (54), they are compared in the case of modelling of canonical scatterers to other formulations present on the literature: the EFIE MOT schemes (MOT EFIE) (21), the time-differentiated one (MOT TD-EFIE) (24), the formulation regularized by the quasi-Helmholtz-projectors (MOT qH-EFIE) [30].In this subsection, the excitation parameters have been chosen not to excite the first resonant mode of the geometries.The first set of numerical tests were performed on the unit sphere, discretized with 270 RWG functions.The intensity of the resulting currents at one point of the geometry are shown in Figure 4.As expected, the time differentiated and the non-differentiated EFIEs are the only formulations suffering from DC-instabilities on this simply connected scenario.In addition, the condition number of the matrices to invert for each MOT are presented in Figure 5 and Figure 6 with respect to the time step size and the mesh density ℎ −1 .The standard EFIE formulation and its time-differentiated counterpart suffer from ill-conditioning at large time steps while the stabilized ones remain well-conditioned.Instead, only the Calderón preconditioned formulations presented in this work remain well-conditioned for dense discretizations (Figure 6).The second set of tests focused on the stability of the different formulations when modelling multiply connected scatters, here a torus with inner radius of 0.2 m and outer radius of 0.5 m.The current densities at the probe point are shown in Figure 7 and the conditioning studies are represented in Figure 8 and Figure 9.In line with the polynomial eigenvalue analysis of the non-regularized Calderón EFIE formulation (Figure 3), the formulation (44) suffers from DC instability.Moreover, the static nullspace of the continuous operator deteriorates the condition number of the matrix to invert for large time steps (Figure 9).However, the newly proposed regularized Calderón formulation ( 52) is stable and remains well-conditioned at large time steps and dense meshes for this geometry.
B. Non-canonical geometries
The final set of numerical tests is dedicated to more complex test structures (Figure 10).In addition, instead of direct solver we rely on the iterative solver GMRES with different relative target tolerances [53] .For practical reason, the maximum number of iteration has been limited to 200 without restart.
All the structures have been illuminated by a pulse Gaussian plane wave with bw = 1.6MHz.Table 1 shows the condition number and the number of iterations needed.The Calderón preconditioned formulation (CP-EFIE) (44) and the Calderón preconditioned formulation regularized by the quasi-Helmholtz-projectors (qH-CP-EFIE) (52) are the only formulations requiring less than 200 iterations to converge at each time steps.As expected, the condition number of the CP-EFIE is high on non-simply connected geometries because of the presence of the operator DC nullspace on these structures.Even if, in this case, the number of iterations remains low, the solution is corrupted by DC instability arising from this nullspace.This phenomenon is absent for the qH-CP-EFIE formulation which is free from high conditioning or DC instability and yields stable solutions up to the target precision of the iterative solver.
Conclusion
In this paper, novel Calderón preconditioned techniques have been presented for the time domain Electric Field Integral Equations solved with Marching-On-In-Time with convolution quadratures.These formulations eliminate the DCinstability for simply and multiply connected geometries.In addition, they cure the ℎ-refinement and large time step breakdowns and generate well-conditioned Marching-On-In Time.Finally, numerical results on complex geometries showcased the effectiveness of the proposed schemes.
FIGURE 3 .
FIGURE 3. Polynomial eigenvalues of the Calder ón EFIE MOT scheme on a torus with a inner and outer radii respectively equal to 0.2 m and 0.5 m, = 387 and = 3 ns.Near 1, four eigenvalues are clustered, superposed two by two on this figure.
FIGURE 8 .
FIGURE 8. Condition number with respect to the mesh size ℎ ( = 4.5 ns) on a torus of the EFIE MOT schemes. | 5,021.8 | 2023-11-27T00:00:00.000 | [
"Engineering",
"Physics"
] |
Investment Decision for Long-Term Battery Energy Storage System Using Least Squares Monte Carlo
: The use of renewable energy sources to achieve carbon neutrality is increasing. However, the uncertainty and volatility of renewable resources are causing problems in power systems. Flexible and low-carbon resources such as Energy Storage Systems (ESSs) are essential for solving the problems of power systems and achieving greenhouse gas reduction goals. However, ESSs are not being installed because of Korea’s fuel-based electricity market. To address this issue, this paper presents a method for determining the optimal investment timing of Battery Energy Storage Systems (BESSs) using the Least Squares Monte Carlo (LSMC) method. A case study is conducted considering the System Marginal Price (SMP) and Capacity Payment (CP), which are electricity rates in Korea. Revenue is calculated through the arbitrage of a 10 MW/40 MWh lithium-ion BESS, and linear programming optimization is performed for ESS scheduling to maximize revenue. The ESS revenue with uncertainty is modeled as a stochastic process using Geometric Brownian Motion (GBM), and the optimal time to invest in an ESS is determined using an LSMC simulation considering investment costs. The proposed method can be used as a decision-making tool for ESS investors to provide information on facility investments in arbitrage situations.
Introduction
In response to climate change, the Paris Agreement was adopted to keep the global temperature rise below 2 • C compared to pre-industrial times and limit it to within 1.5 • C. Subsequently, the Intergovernmental Panel on Climate Change published a Global Warming of 1.5 • C report, suggesting a global path to achieve carbon neutrality by 2050 to meet the goals of the Paris Agreement [1,2].
Aligned with these trends, South Korea has established the 2030 National Greenhouse Gas Reduction Goals.The expansion of renewable energy generators and a reduction in coal generators are methods for achieving this goal [3].To reduce greenhouse gas emissions, the Ministry of Trade, Industry, and Energy announced a basic plan for electricity supply and demand, setting targets to increase the share of renewable energy generation from 6.2% in 2018 to 21.6% by 2030 and 30.6% by 2036 [4].The potential of renewable energy in Korea is 6,180,571 GWh/year of solar thermal, 2,337,875 GWh/year of solar photovoltaic, and 1,691,704 GWh/year of geothermal energy [5].
However, with the increase in variable renewable energy resources, such as wind and solar power, problems in power systems are increasing.The expansion of solar power generation increases the output volatility during sunrise and sunset, requiring adjustments in thermal power generation to accommodate these fluctuations.
Securing flexible resources is necessary to solve the problems that occur in power systems [6].An ESS, a low-carbon resource, is a representative flexible resource [7].Various Energies 2024, 17, 2019 2 of 15 countries are actively installing ESSs, and the forecast based on each country's energy plans is expected to increase to 370 GWh by 2030 and 3400 GWh by 2050.To maintain global temperature increases below 2 • C, it is forecasted that 754 GWh of ESSs will be installed by 2030, and by 2050, this capacity is expected to reach 9000 GWh [8].The U.S. Department of Energy announced the goal of accelerating the development and commercialization of next-generation ESSs and reducing ESS installation costs by 2030.In Korea, as of 2021, a total of 10.3 GWh has been installed, including 5674 MWh for renewable energy and 4349 MWh for peak reduction purposes [9,10].Table 1 lists the ESS facilities to be configured by 2036 based on the basic plan for electricity supply and demand [11].An ESS is used effectively for peak shaving, frequency regulation, and renewable energy support [12].The role of an ESS is classified depending on its duration; a short-term ESS supplies power within a short period or shifts the surplus power to peak demand hours.A long-term ESS addresses the output limitations of renewable energy on a daily to weekly basis, and a seasonal ESS enables energy storage and supply on a seasonal basis, contributing to power planning [13].
However, Korea's fuel-based electricity market is unsuitable for investment-centric sources, such as ESSs.Due to limited investments in ESSs, the renewable energy system was reduced to 96 MW in 2021, 2 MW in 2022, and 0 MW in 2023.Consequently, only 107 MW of ESSs were installed in 2023 [10].To address this issue, ESSs are being installed through the Jeju BESS central contract market, a long-term contract market aimed at expanding ESSs.Similarly, the UK's National Grid is installing ESSs through long-term contracts, such as the Network Options Assessment Stability Pathfinder.PG&Es in the United States are expanding their ESS facilities through long-term contracts [14][15][16].To achieve the goal of the basic plan for electricity supply and demand, a method must be developed to determine the optimal investment timing of ESSs and research on ESS market participation is being conducted [17].
In the past, research has been conducted to model the optimal investment timing of ESSs along with economic evaluations [18][19][20].Future uncertain demand has been modeled using GBM, and studies have been conducted on the arbitrage of Vanadium Redox Batteries [21].Nguyen analyzed energy arbitrage considering the congestion of transmission and distribution systems, and Sang examined the prediction of electricity prices to maximize ESS arbitrage [22,23].A Monte Carlo simulation was used to mitigate uncertainty in revenue [24].Various studies explored ESSs using machine learning techniques such as genetic algorithms and Long Short-Term Memory (LSTM) [25,26].An ESS investment analysis was also conducted by studying Locational Marginal Price variations in the MISO energy market and Korea's electricity market [27,28].
The revenue of the ESS varies depending on the charging and discharging scheduling models and the investment cost.Yoon utilized a Genetic Algorithm, and M. M. Alam planned the charging and discharging schedules of an ESS through LSTM [29,30].Research was also conducted using Dynamic Programming, a Mixed-Logit model, and Mixed-Integer Linear Programming [31][32][33][34][35]. Mauricio B. C. Salles studied the potential arbitrage of ESSs by choosing parameter values anticipated for future mature flow battery technology but did not consider actual installed costs [36].Optimal scheduling algorithms for non-central dispatch ESSs were studied in the South Korean power market; however, the discussion did not cover the determination of the investment timing of ESS facility expansion [37].
•
Using the GBM model for ESS arbitrage revenue to consider future revenue uncertainty.• Analysis of ESS revenue and investment costs using LSMC simulations to determine optimal investment timing.
The proposed method for determining the optimal ESS investment timing provides incentives to ESS investors.This research analyzes lithium-ion battery ESSs to consider the development costs and revenue through SMP and CP in the Korean electricity market.ESS charging and discharging scheduling that maximizes the arbitrage revenue is derived through linear programming optimization.ESS arbitrage revenue over 22 years is analyzed to create a probabilistic model of uncertain ESS revenue.To determine the optimal investment timing in an ESS, using LSMC simulations that activate options when arbitrage returns can recover actual investment costs.The proposed method contributes to securing the ESSs required to respond to volatile resources.
The remainder of this paper is organized as follows: Section 2 presents the problems that must be addressed.Section 3 introduces a method for determining the optimal investment timing for the ESSs.Section 4 describes the results of the proposed method, based on a case study.Finally, Section 5 concludes this paper with suggestions for future research.
Problem Formulation
ESSs have emerged as a promising solution to mitigate the variability of renewable generation and improve grid performance.However, its installation is constrained.One of the primary problems with installation is the discrepancy between the high investment costs of ESS installation and the relatively low revenue.This paper aims to solve the problems of ESS installation by proposing a method to determine the optimal timing for ESS investments.To provide insight into the investment timing for ESS infrastructure by considering both profitability and investment costs.
Optimal Investment Considering ESS's Revenue and Investment Cost
The optimal investment of the ESS requires the revenue to exceed the installed costs and expenditures.The formula used is as follows: where Rev Discharging is the revenue from the ESS discharge.Cost Charging is the cost of charging ESS.Cost Install and Cost O&M are the costs of installing the ESS and operational maintenance costs, respectively.The installation cost of ESSs decreases with technology development, and the gap between the maximum and minimum SMP also increases.The ESS earns revenue through SMP's arbitrage trading of the SMP, and the maximum and minimum SMP determines the revenue.
GBM Model of Revenue Reflecting Uncertainty
The GBM models the probabilistic components by reflecting the uncertainty of the ESS revenue.The GBM stochastic process model is expressed as follows: where R is the revenue, µ is the expected rate of return on revenue, t is the period, σ r is the volatility of revenue, and z reflects the uncertainty of revenue changes.
The method for generating revenue process in a risk-neutral world is as follows: where the r is the risk-free interest rate, σ rt is the year-to-year volatility of revenue, m is the number of revenue rate observations, x i represents the log returns from day i − 1 to day i, and x is the mean of x i .
The method for generating the process of revenue is as follows: where ε represents a random number, and the stochastic process of ln R, the natural logarithm of revenue, is converted into a discrete-time model.
LSMC Simulation to Determine the Investment Timing
The optimal investment timing of the ESS is determined using an LSMC simulation.Using the LSMC, the number of simulations required for computation can be reduced compared to traditional probabilistic simulation methods.Additionally, it allows for the analysis of interactions with ESS investment costs.The activation value function for the LSMC option is expressed in Equation (10).
where R is ESS's arbitrage revenue, and ESS cost is ESS investment cost.The profit path is generated using the GBM, and the activation value at option maturity is calculated.Subsequently, the holding value for the in-the-money path just before maturity is calculated, and the equation is as follows: where Payo f f (t + 1) is the activated value at maturity and Payo f f (t) is the activated value just before maturity.To determine the exact decision for LSMC, a regression analysis between revenue and holding value just before maturity is performed using Laguerre Polynomials.The equation for the regression model using the least squares method is as follows: To estimate the regression model, the coefficients are obtained by minimizing the following equation for revenue and holding value: where Val hold is the holding value and a, b, c, and d are the correlation coefficients.The regression coefficient is obtained using the estimated regression equation, and the holding value immediately before maturity is recalculated to determine the activate decision.This process is reversed until the initial year is reached to determine the optimal investment timing.
The next section describes in detail the method used to determine the optimal investment timing when the ESS arbitrage revenue exceeds installation costs and expenditures.This method derives effective strategies for ESS investments and increases renewable energy utilization.
LSMC-Based Method for ESS Investment Decision
The ESS scheduling results are used to set the discharge and charge amounts, and the revenue from discharge and expenses for charging are calculated using the SMP and CP data in the Korean electricity market [38,39].Subsequently, the stochastic component reflecting the uncertainty of the ESS revenue variation is modeled using the GBM, and the optimal investment timing of the ESS is determined through an LSMC simulation.
ESS Scheduling for Arbitrage Revenue Calculation
ESS scheduling significantly affects ESS revenue.The ESS revenue is calculated as the SMP arbitrage and CP.SMP is the market price applied to power transactions in the Korean electricity market, which varies by power trading time and represents the market clearing price for the electricity system.CP is the capacity payment paid to the central dispatch ESS.
To maximize the ESS arbitrage is the objective of scheduling.The equation is as follows: ESS daily and annual revenue from arbitrage are as follows: where 21) and ( 22).The cycle constraints, which are the 1 Day/1 Cycle constraints considering the battery's life, are expressed by Equations ( 23) and (24).
The constraint that discharges accord to the amount of charge is expressed by Equation (25).
ESS Installed Costs
The ESS installation cost includes a storage system and batteries.The storage system is a DC storage block [$/kWh], DC storage BOS [$/kWh], and the batteries include the power equipment [$/kW] and system integration [$/kWh].Other ESS installation costs include the EPC, project development, and grid integration.Fixed O&M and warranty are also considered.
The installed cost is the total cost over 20 years; therefore, the Capital Recovery Factor (CRF) is used.The CRF is a ratio used to calculate the annual amount that can evenly recover investment over future years and is multiplied by the investment amount.The CRF equation is as follows: where ESS invest cost is the initial investment, a is the annual equal recovery amount, and r is the discount rate.
Overview Diagram of the Proposed Method
Figure 1 presents an overview of the proposed optimal ESS investment timing method.
The detailed steps of the paper are as follows: Step 1: This paper starts with the ESS setting.Information regarding ESS type, capacity, discharge duration, DoD, and RTE is collected and an ESS is set to conduct research using the collected information.The detailed steps of the paper are as follows: Step 1: This paper starts with the ESS setting.Information regarding ESS type, capacity, discharge duration, DoD, and RTE is collected and an ESS is set to conduct research using the collected information.
Step 2: Perform ESS scheduling to calculate annual revenue.An objective function that maximizes the revenue from arbitrage trading is used.The constraints on the economic operation of the ESS are used.Scheduling uses the SMP and CP data.
Step 3: GBM modeling is performed to stochasticize the uncertain ESS revenue.A 20year ESS revenue process in a risk-neutral world is created.An analysis of 22 years of revenue is conducted to determine the annual volatility of the ESS revenue.
Step 4: The investment value for the 20-year revenue scenario is calculated by considering the ESS investment cost.Subsequently, the estimated T−1 holding value is calculated by applying a risk-free interest rate in year T.
Step 5: The investment value in T−1 is calculated using least squares regression analysis of the value in year T and the estimated holding value in year T−1.Least squares regression minimizes the sum of the residual squares between the actual and estimated values.
Case Study 4.1. ESS Parameter and CRF Setting
ESSs should consider the aging of facilities due to long-term use, and in Korea, an End-of-Life (EOL) system has been introduced to prepare for the safety of ESSs.EOL is the battery capacity up to the facility warranty period, considering ESS degradation.The initial design capacity of the ESS must satisfy the capacity demanded by the owner until the end of the warranty period, and additional design capacity to extend the warranty lifespan should not be added during operation [40,41].In accordance with Korea's EOL system and the characteristics of lithium-ion batteries, the DoD is set to 80% [42][43][44].The RTE is the ratio of the electricity generated to the electricity input and is set at 85% based on the characteristics of lithium-ion batteries [45][46][47].A lithium-ion battery ESS is used to consider the actual investment costs.In Korea, a central dispatch ESS is defined as a device that operates based on dispatch orders of electricity exchange, with a maximum operating time of more than 2 h and a maximum discharge capacity exceeding 10 MW.In addition, the device only provides primary reserve services based on separate criteria [48].In this paper, a long-term ESS of 4 h is analyzed.Therefore, the ESS capacity is set to 40 MWh.According to the Jeju long-term BESS contract market introduced in Korea, the PCS capacity is set at 10 MW.Table 3 represents the ESS parameters.Table 3. Parameters for the ESS used in the method for determining the optimal investment timing.
ESS Parameter Value
Depth The installed cost applied to the CRF, according to Equation ( 26) in Section 3.2, is $311,880.37.The learning rate is applied based on technological advancements.Using investment costs in 2030, the learning rate is set to 2.76%, and the investment costs after 2030 are the same as those in 2030 [49].Figure 2 shows the installed cost with the CRF applied according to the learning rate.
Arbitrage Revenue for Lithium-Ion Battery ESS Using Scheduling
Linear programming solvers are used for ESS scheduling optimization to calculate the ESS revenue.The optimization uses the objective function and constraints described in Section 3.1.
Table 5 lists the charging and discharging amounts based on the 1 January 2022.
Arbitrage Revenue for Lithium-Ion Battery ESS Using Scheduling
Linear programming solvers are used for ESS scheduling optimization to calculate the ESS revenue.The optimization uses the objective function and constraints described in Section 3.1.
Table 5 lists the charging and discharging amounts based on the 1 January 2022.Charging occurs during low-SMP hours at 12:00, 13:00, 14:00, and 15:00, and discharging occurs during high-SMP hours at 19:00, 20:00, 21:00, and 23:00.Figure 3 shows the ESS charging and discharging amounts from 1 January 2022 to 7 January 2022.On 5th January, charging and discharging are not performed when profits are not generated from arbitrage, whereas on 1st January, charging and discharging are performed when profit is generated from arbitrage.The discharge capacity does not exceed 32 MW due to the DoD constraints.In addition, the number of charge and discharge cycles is limited to one due to the 1 Day/1 Cycle constraints.Using Equations ( 18) and ( 19) in Section 3.1, the revenue over 22 years is calculated to determine the revenue volatility required for the GBM model computation.Using Equations ( 18) and ( 19) in Section 3.1, the revenue over 22 years is calculated to determine the revenue volatility required for the GBM model computation.3)-( 6) in Section 2.2 generates revenue in a risk-neutral world.The risk-free interest rate r is 3.627%, which is the 180-day average for the Korea Overnight Financing Repo Rate [50].The annual revenue volatility σ rt for ESS arbitrage is 43.368%, as calculated from the annual returns in Table 6.Table 7 shows the logarithmic returns x i of the ESS over 21 years.To convert the stochastic process of the natural logarithm of the ESS revenue into a discrete-time model, logarithmic returns are calculated according to Equations ( 7)-( 9) in Section 2.2.Using the GBM model in MATLAB, 1,000,000 revenue scenarios are generated.Random numbers ε from a normal distribution are generated using the random function.Figure 4 illustrates the ESS revenue process over 20 years using the GBM.All Revenue Paths refer to the individual revenue scenarios; Revenue Mean denotes the mean of the generated revenue.
discrete-time model, logarithmic returns are calculated according to Equations ( 7)-( 9) in Section 2.2.Using the GBM model in MATLAB, 1,000,000 revenue scenarios are generated.Random numbers from a normal distribution are generated using the random function.Figure 4 illustrates the ESS revenue process over 20 years using the GBM.All Revenue Paths refer to the individual revenue scenarios; Revenue Mean denotes the mean of the generated revenue.
Determining of Optimal ESS InvestmentTiming
The option activation rate of LSMC determines the optimal investment timing of the ESS.The LSMC method approximates the optimal investment policy at each exercise opportunity using least squares regression and determines whether to exercise early based on approximation.It estimates the expected payoff for ESS investors using the least squares method.Simulation is used as a valuation and risk management of ESSs [51].
Determining of Optimal ESS InvestmentTiming
The option activation rate of LSMC determines the optimal investment timing of the ESS.The LSMC method approximates the optimal investment policy at each exercise opportunity using least squares regression and determines whether to exercise early based on approximation.It estimates the expected payoff for ESS investors using the least squares method.Simulation is used as a valuation and risk management of ESSs [51].
The investment value is calculated by Equation ( 10) in Section 2.3.R in Equation ( 10) represents the 20-year ESS revenue generated through the GBM in Section 4.3, and the ESS cost are shown in Figure 2 in Section 4.1.The estimated T−1 holding value is calculated by Equation (11).Subsequently, the investment value in T−1 calculated using least squares regression analysis of the value in year T and the estimated holding value in year T−1.Least squares regression minimizes the sum of the residual squares between the actual and estimated values.The regression analysis formula utilizes Equations ( 12)-( 16). Figure 5 presents the results of the LSMC simulations.
The horizontal axis represents years, and the vertical axis represents the option activate rate.Among the 1 million simulations, the highest option activate rate is 30.1% in 2027, and the frequency of option occurrence decreases as the years go on.From 2024 to 2025, the LSMC option is not activated.The earned profit does not exceed the installed cost.
𝐸𝑆𝑆
are shown in Figure 2 in Section 4.1.The estimated T−1 holding value is calculated by Equation (11).Subsequently, the investment value in T−1 calculated using least squares regression analysis of the value in year T and the estimated holding value in year T−1.Least squares regression minimizes the sum of the residual squares between the actual and estimated values.The regression analysis formula utilizes Equations ( 12)-( 16). Figure 5 presents the results of the LSMC simulations.The horizontal axis represents years, and the vertical axis represents the option activate rate.Among the 1 million simulations, the highest option activate rate is 30.1% in 2027, and the frequency of option occurrence decreases as the years go on.From 2024 to 2025, the LSMC option is not activated.The earned profit does not exceed the installed cost.Table 8 presents the active options ratios by year.
Conclusions
This paper is used for ESS investors as a decision-making tool to determine investment timing.Previous study has shown some limitations in using option theory to find the timing of ESS investments.It has simply found that investment is delayed as the operating period increases due to higher volatility in revenue.Furthermore, it has shown that investment is delayed as the cost of ESS investment increases, without considering the learning rate and actual investment cost [18].Therefore, the optimal investment timing
Conclusions
This paper is used for ESS investors as a decision-making tool to determine investment timing.Previous study has shown some limitations in using option theory to find the timing of ESS investments.It has simply found that investment is delayed as the operating period increases due to higher volatility in revenue.Furthermore, it has shown that investment is delayed as the cost of ESS investment increases, without considering the learning rate and actual investment cost [18].Therefore, the optimal investment timing is determined through a least squares simulation model considering these factors; economical and reliable ESS scheduling is used for revenue calculation, and the optimal investment timing is determined using the regression model that considers actual investment costs and the learning rate.This paper analyzes the optimal investment of a 10 MW/40 MWh lithium-ion BESS and addresses the following conclusions: • Analyze revenue through economic ESS operational constraints in the Korean electric- ity market, and consider future revenue uncertainty using GBM.
•
Determine the optimal investment timing of ESSs using LSMC simulation considering the actual investment cost.
ESSs are important for managing volatile energy resources.Delays in ESS installation can lead to problems in power systems because of volatile resources.The proposed model provides advantages for expanding ESS facilities.The installation of ESSs through the government's long-term contract market is also important.However, ESS investors should be able to invest in the facilities themselves.The ESS can be installed on time using LSMC models, enabling a stable power system operation.
Figure 1 .
Figure 1.Schematic diagram of the proposed optimal ESS investment timing method.
Figure 1 .
Figure 1.Schematic diagram of the proposed optimal ESS investment timing method.
Energies 2024 ,
17, x FOR PEER REVIEW 9 of 15 are the same as those in 2030 [49].Figure2shows the installed cost with the CRF applied according to the learning rate.
Figure 2 .
Figure 2. ESS installed cost with CRF according to the learning rate.
Figure 2 .
Figure 2. ESS installed cost with CRF according to the learning rate.
Figure 3 .
Figure 3.The ESS charging and discharging amount results from 1 January 2022 to 7 January 2022.
Figure 5 .
Figure 5. Results of the optimal ESS investment timing determination method.
Figure 5 .
Figure 5. Results of the optimal ESS investment timing determination method.
Table 1 .
Energy Storage Mix by 2036 in Korea.
Table 2 .
Annual ESS installation capacity in Korea.
Round Trip Efficiency (RTE) is the ratio of the electricity generated to the electricity input, SMP C t is the SMP [$/kWh] during charging at time t, EP C t is the charge amount [MW] at time t.The constraint equations for scheduling are as follows: SOC init = SOC f inal (20) SOC init and SOC f inal are the initial-and final-state constraints of the ESS, respectively.State of Charge is expressed by dividing the current available battery capacity by the total capacity.This is expressed in Equation (20).PCS max is the maximum Power Conditioning System (PCS) capacity [MW], ESS max is the maximum ESS capacity [MW], and Depth of Discharge (DoD) is the ratio of the discharge capacity to the total capacity of the ESS batteries.The ESS output for 4 h limitations are expressed by Equations ( The installation cost for a 10 MW/40 MWh lithium-ion battery ESS that can be operated for 20 years is $4,056,920[49].Table4lists the ESS installation costs.
Table 5 .
ESS charging and discharging amounts on 1 January 2022.
Table 6
presents the annual revenue for ESS arbitrage from 2002 to 2023.The highest revenue is $403,451.64 in 2010, and the lowest revenue is $54,903.17 in 2016.
Table 6 .
Annual revenue from ESS arbitrage from 2002 to 2023.
Table 6 presents
the annual revenue for ESS arbitrage from 2002 to 2023.The highest revenue is $403,451.64 in 2010, and the lowest revenue is $54,903.17 in 2016.
Table 6 .
Annual revenue from ESS arbitrage from 2002 to 2023.To generate the ESS revenue process, the initial revenue R 1 is set at $349,631.05 in 2023.Setting the variables in Equations (
Table 7 .
ESS log returns from 2003 to 2023.
Table 8
presents the active options ratios by year.
Table 8 .
Option activation rate of the proposed LSMC model.
Table 8 .
Option activation rate of the proposed LSMC model. | 6,133.4 | 2024-04-25T00:00:00.000 | [
"Engineering",
"Environmental Science",
"Economics"
] |
Endicheck: Dynamic Analysis for Detecting Endianness Bugs
Computers store numbers in two mutually incompatible ways: little-endian or big-endian. They differ in the order of bytes within representation of numbers. This ordering is called endianness. When two computer systems, programs or devices communicate, they must agree on which endianness to use, in order to avoid misinterpretation of numeric data values. We present Endicheck, a dynamic analysis tool for detecting endianness bugs, which is based on the popular Valgrind framework. It helps developers to find those code locations in their program where they forgot to swap bytes properly. Endicheck requires less source code annotations than existing tools, such as Sparse used by Linux kernel developers, and it can also detect potential bugs that would only manifest if the given program was run on computer with an opposite endianness. Our approach has been evaluated and validated on the Radeon SI Linux OpenGL driver, which is known to contain endianness-related bugs, and on several open-source programs. Results of experiments show that Endicheck can successfully identify many endianness-related bugs and provide useful diagnostic messages together with the source code locations of respective bugs.
Introduction
Modern computers represent and store numbers in two mutually incompatible ways: little-endian (with the least-significant byte first) or big endian (the most-significant byte first). The byte order is also referred to as endianness.
Processor architectures typically define a native endianness, in which the processor stores all data. When two computer systems or programs exchange data (e.g., via a network), they must first agree on which endianness to use, in order to avoid misinterpretation of numeric data values. Also devices connected to computers may have control interfaces with endianness different from the host's native endianness.
Therefore, programs communicating with other computers and devices need to swap the bytes inside all numerical values to the correct endianness. We use the term target endianness to identify the endianness a program should use for data exchanged with a particular external entity. Note that in some cases it is not necessary to know whether the target endianness is actually little-endian or big-endian. When the knowledge is important within the given context, we use the term concrete endianness.
If the developer forgets to transform data into the correct target endianness, the bug can often go unnoticed for a long time because software is nowadays usually developed and tested on the little-endian x86 or ARM processor architecture. For example, if two identical programs running on a little-endian architecture communicate over the network using a big-endian protocol, a missing byte-order transformation in the same place in code will not be observed. Our work on this project was, in the first place, motivated by the following concrete manifestation of the general issue described in the previous sentence. The Linux OpenGL driver for Radeon SI graphics cards (the Mesa 17.4 version) does not work on big-endian computers due to an endianness-related bug 1 , as the first author discovered when he was working on an industrial project that involved PowerPC computers in which Radeon graphic cards should be deployed.
We are aware of few approaches to detection of endianness bugs, which are based on static analysis and manually written source code annotations. An example is Sparse [11], a static analysis tool used by Linux kernel developers to identify code locations where byte-swaps are missing. The analysis performed by Sparse works basically in the same way as type checking for C programs, and relies on the usage of specialized bitwise data types, such as le16 and be32, for all variables with non-native endianness. Integers with different concrete endianness are considered by Sparse as having mutually incompatible types, and the specialized types are also not compatible with regular C integer types. In addition, macros like le32 to cpu are provided to enable safe conversion between values of the bitwise integer types and integer values of regular types. Such macros are specially annotated so that the analysis can recognize them, and developers are expected to use only those macros.
The biggest advantage of bitwise types is that a developer cannot assign a regular native endianness integer value to a variable of a bitwise type, or vice versa. Their nature also prevents the developer from using them in arithmetic operations, which do not work correctly on values with non-native byte order. On the other hand, a significant limitation of Sparse is that developers have to properly define the bitwise types for all data where endianness matters, and in particular to enable identification of data with concrete endianness -Sparse would produce imprecise results otherwise. Substantial manual effort is therefore required to create all the bitwise types and annotations.
Our goals in this whole project were to explore an approach based on dynamic analysis, and to reduce the amount of necessary annotations in the source code of a subject program. We present Endicheck, a dynamic analysis tool for detecting endianness bugs that is implemented as a plugin for the Valgrind framework [6]. The main purpose of the dynamic analysis performed by Endicheck is to track endianness of all data values in the running subject program and report when any data leaving the program has the wrong endianness. The primary target domain consists of programs written in C or C++, and in which developers need to explicitly deal with endianness of data values.
While the method for endianness tracking that we present is to a large degree inspired by dynamic taint analyses (see, e.g., [8]), our initial experiments showed that usage of existing taint analysis techniques and tools does not give good results especially with respect to precision. For example, an important limitation of the basic taint analysis, when used for endianness checking, is that it would report false positives on data that needs no byte-swapping, such as single byte-sized values. Therefore, we had to modify and extend the existing taint analysis algorithms for the purpose of endianness checking. During our work on Endicheck, we also had to solve many associated tech-ical challenges, especially regarding storage and propagation of metadata that contain the endianness information -this includes, for example, precise tracking of single-byte values.
Endicheck is meant to be used only during the development and testing phases of the software lifecycle, mainly because it incurs a substantial runtime overhead that is not adequate for production deployment. Before our Endicheck tool can be used, the subject program needs to be modified, but only to inform the analysis engine where the byte-order is being swapped and where data values are leaving the program. In C and C++ programs, byte-order swapping is typically done by macros provided in the system C library, such as htons/htonl or those defined in the endian.h header file. Thus only these macros need to be annotated. During the development of Endicheck, we redefined each of those macros such that the custom variant calls the original macro and defines necessary annotations -for examples, see Figure 1 in Section 4 and the customized header file inet.h 2 . Similarly, data also tend to leave the program only through few procedures. For some programs, the appropriate place to check for correct endianness is the send/write family of system calls.
Endicheck is released under the GPL license. Its source code is available at https: //github.com/rkapl/endicheck.
The rest of the paper is structured as follows. Section 2 begins with a more thorough overview of the dynamic analysis used by Endicheck, and then it provides details about the way endianness information for data values are stored and propagated -this represents our main technical contribution, together with evaluation of Endicheck on the Radeon SI driver and several other real programs that is described in Section 5. Besides that, we also provide some details about the implementation of Endicheck (Section 3) together with a short user guide (Section 4).
Dynamic Analysis for Checking Endianness
We have already mentioned that the dynamic analysis used by Endicheck to detect endianness bugs is a special variant of taint analysis, since it uses and adapts some related concepts. In the rest of this paper, we use the term endianness analysis.
Algorithm Overview
Here we present a high-level overview of the key aspects of the endianness analysis. Like common taint and data-flow analysis techniques (see, e.g., [4] and [8]), our dynamic endianness analysis tracks flow of data through program execution, together with some metadata attached to specific data values. The analysis needs to attach metadata to all memory locations for which endianness matters, and maintain them properly. Metadata associated with a sequence of bytes (memory locations) that makes a numeric data value then capture its endianness. Similarly to many dynamic analyses, the metadata are stored using a mechanism called shadow memory [7] [9]. We give more details about the shadow memory in Section 2.2.
Although we mostly focus on checking that the program being analyzed does not transmit data of incorrect endianness to other parties, there is also the opposite problem: ensuring that the program does not use data of other than native endianness. For this reason, our endianness analysis could be also used to check whether all operands of an arithmetic instruction have the correct native endianness -this is important because arithmetic operations are unlikely to produce correct results otherwise. Note, however, that checking of native endianness for operands has not yet been implemented in the Endicheck tool.
The basic principle behind the dynamic endianness analysis is to watch instructions as they are being executed and check endianness at specific code locations, such as the calls of I/O functions. We use the term I/O functions to identify all system calls and other functions that encapsulate data exchange between a program and external entities (e.g., writing or reading data to/from a hard disk, or network communication) in a specific endianness. When the program execution reaches the call of an I/O function, Endicheck checks whether all its arguments have the proper endianness. Note that the user of Endicheck specifies the set of I/O functions by annotations (listed in Section 4).
In order to properly maintain the endianness information stored in the shadow memory, our analysis needs to track almost every instruction being executed during the run of a subject program. The analysis receives notifications about relevant events from the Valgrind dynamic analysis engine. All the necessary code for tracking individual instructions (processing the corresponding events), updating endianness metadata (inside the shadow memory), and checking endianness at the call sites of I/O functions, is added to the subject program through dynamic binary instrumentation. Further technical details about the integration of Endicheck into Valgrind are provided later in Section 3.
Two distinguishing aspects of the endianness analysis -the format of metadata stored in the shadow memory and the way metadata are propagated during the analysis of program execution -are described in the following subsections.
Shadow Memory
A very important requirement on the organization and structure of shadow memory was full transparency for any C/C++ or machine code program. The original layout of heap and stack has to be preserved during the analysis run, since Endicheck (and Valgrind in general) targets C and C++ programs that typically rely on the precise layout of data structures in memory. Consequently, Endicheck cannot allocate the space for shadow memory (metadata) within the data structures of the analyzed program.
When designing the endianness analysis, we decided to use the mechanism supported by Valgrind [7], which allows client analyses to store a tag for each byte in the virtual address space of the analyzed program without changing its memory layout. This mechanism keeps a translation table (similar to page tables used by operating systems) that maps memory pages to shadow pages where the metadata are stored.
The naive approach would be to follow the same principles as taint analyses, i.e. reuse the idea of taint bits, and mark each byte of memory as being either of native endianness or target endianness. However, our endianness analysis actually uses a richer format of metadata and individual tags, which improves the analysis precision.
Rich Metadata Format. In this format of metadata, each byte of memory and each processor register is annotated with one of the following tags that represent available knowledge about the endianness of stored data values.
-native: The default endianness produced, for example, by arithmetic operations.
-target: Used for data produced by annotated byte-swapping function.
-byte-sized: Marks the first byte of a multi-byte value (e.g., an integer or float).
In addition to these four tags, each byte of memory can also be annotated with the empty flag, indicating that the byte's value is zero. Now we give more details about the meaning of these tags, and discuss some of the associated challenges.
Single-byte values. Our approach to precise handling of single-byte values is motivated by the way arithmetic operations are processed. Determining the correct size of the result of an arithmetic operation (in terms of the number of actually used bytes) is difficult in practice, because compilers often choose to use instructions that operate on wider types than actually specified by the developer in program source code. This means the analysis cannot, in some cases, precisely determine whether the result of an arithmetic operation has only a single byte. Our solution is to always mark the leastsignificant byte of the result with the tag byte-sized. Such an approach guarantees that if only the least-significant byte of an integer value is actually used, it does not trigger any endianness errors when checked, because the respective memory location is not tagged as native. On the other hand, if the whole integer value is really used (or at least more than just the least-significant byte), there is one byte marked with the tag byte-sized and the rest of the bytes are marked as native, thus causing an endianness error when checked.
Empty byte flag. Usage of the empty flag helps to improve performance of the endianness analysis when processing byte-shuffling instructions, because all operations with empty flags are simpler than operations with the actual values. However, this flag can be soundly used only when the operands are byte-wise disjoint, i.e. when each byte is zero (empty) in at least one of the operands. Arithmetic operations are handled in a simplified way -they never mark bytes as empty in the result. Consequently, while the empty tag implies that the given byte is zero, the reverse implication does not hold.
Unknown tag. We introduced the tag unknown in order to better handle data values, for which the analysis cannot say whether they are already byte-swapped. Endicheck uses this tag especially for uninitialized data. Values marked with the tag unknown are not reported as erroneous by default, but this behavior is configurable. We discuss other related problems, concerning especially precision, below in Section 2.4.
Propagation of Metadata
An important aspect of the endianness analysis is that data values produced by the subject program are marked as having the native endianness by default. This behav-ior matches the prevailing case, because data produced by most instructions (e.g., by arithmetic operations) and constant values can be assumed to have native endianness.
In general, metadata are propagated upon execution of an instruction according to the following policy: -Arithmetic operations always produce native-endianness result values.
-Data manipulation operations (e.g., load and store) propagate tags from their operands to results without any changes.
Endicheck correctly passes metadata also through routines such as memcpy and certain byte-shuffling operations (e.g., shift <<= and >>=). Complete details for all categories of instructions and routines are provided in the master thesis of the first author [3].
The only way to create data with the target tag is via explicit annotation from the user. Specifically, the user needs to add annotations to byte-swapping functions in order to set the target tag on return values.
Discussion: Analysis Design and Precision
The basic scenario that is obviously supported by our analysis is the detection of endianness bugs when the target and native endianness are different. However, the design of our analysis ensures that it can be useful even in cases when the native endianness is the same as the target endianness. Although byte-swapping functions then become identities, the endianness analysis can still find data that would not be byte-swapped if the endianities were different -it can do this by setting the respective tags when data pass through the byte-swapping functions. In addition, the endianness analysis can be also used to detect the opposite direction of errors -programs using non-native endianness data values (e.g., received as input) without byte-swapping them first.
Endicheck does not handle constants and immediate values in instructions very well, since the analysis cannot automatically recognize their endianness and therefore cannot determine whether the data need byte-swapping or not. Constants stored in the data section of a binary executable represent the main practical problem to the analysis, because the data section does not have any structure -it is just a stream of bytes. Our solution is to mark data sections initially with the tag unknown. If this is not sufficient, a user must annotate the constants in the program source code to indicate whether they already have the correct endianness.
A possible source of false bug reports are unused bytes within a block of memory that has undefined content, unless the memory was cleared with 0s right after its allocation. This may occur, for example, when some fields inside C structures have specific alignment requirements. Some space between individual fields inside the structure layout is then unused, and marked either with the tag unknown or with the tag left over from the previous content of the memory block.
Implementation
We distribute the Endicheck tool in the form of an open source software package that was initially created as a fork of the Valgrind source code repository. Although tools and plugins for Valgrind can be maintained as separate projects, forking allowed us to make changes to the Valgrind core and use its build/test infrastructure. Within the whole source tree of Endicheck, which includes the forked Valgrind codebase, the code specific to Endicheck is located in the endicheck directory. It consists of these modules: ec main: tool initialization, command-line handling and routines for translation to/from intermediate representation; ec errors: error reporting, formatting and deduplication; ec shadow: management of the shadow memory, storing of the endianness metadata, protection status and origin tracking information (see below); ec util: utility functions for general use and for manipulation with the metadata; endicheck.h: public API with annotations to be used in programs by developers.
In the rest of this section, we briefly describe how Endicheck uses the Valgrind infrastructure and a few other important features. Additional technical details about the implementation are provided in the master thesis of the first author [3].
Usage of Valgrind infrastructure. Endicheck depends on the Valgrind core (i) for dynamic just-in-time instrumentation [6] of a target binary program and (ii) for the actual dynamic analysis of program execution. The subject binary program is instrumented with code that carries out all the tasks required by our endianness analysis -especially recording of important events and tracking information about the endianness of data values. When implementing the Endicheck plugin, we only had to provide code doing the instrumentation itself and define what code has to be injected at certain locations in the subject program. Note also that for the analysis to work correctly and provide accurate results, Valgrind instruments all components of the subject program that may possibly handle byte-swapped data, including application code, the system C library and other libraries. During the analysis run, Valgrind notifies the Endicheck plugin about execution of relevant instructions and Endicheck updates the information about endianness of affected data values accordingly. Besides instrumentation and the actual dynamic analysis, other features and mechanisms of the Valgrind framework used by Endicheck include: utility functions, origin tracking, and developer-friendly error reporting.
Origin tracking [1] is a mechanism that can help users in debugging the endianness issues. An error report contains two stack traces: one identifies the source code location of the call to the I/O function where the wrong endianness of some data value was detected, and the second trace, provided by origin tracking, identifies the source code location where the value has originated. In Endicheck, the origin information (identifier of the stack trace and execution context) is stored alongside the other metadata in the shadow memory for all values. We decided to use this approach because almost all values need origin tracking, since they can be sources of errors -in contrast to Memcheck, where only the uninitialized values can be sources of errors.
During our experiments with the Radeon SI OpenGL driver (described in Section 5.1), we have noticed that the driver maps the device memory into the user-space process. In that case, there is no single obvious point where to check the endianness of data that leave the program through the mapped memory. To solve this problem and support memory-mapped I/O, we extended our analysis to automatically check endianness at all writes to regions of the mapped device memory. We implemented this feature in such a way that each byte of a device memory region is tagged with a special flag protected -then, Endicheck can find very quickly whether some region of memory is mapped to a device or not. Note that the flag is associated with a memory location, while the endianness tags (described in Section 2.2) are associated with data values. Therefore, the special flag is not copied, e.g. when execution of memcpy is analyzed; it can be only set explicitly by the user.
User Guide
The recommended way to install Endicheck is building from the source code. Instructions are provided in the README file at the project web site. When Endicheck has been installed, a user can run it by executing the following command: Annotations In order to analyze a given program, some annotations typically must be added into the program source code. A user of Endicheck has to mark the byte-swapping functions and the I/O functions (through which data values are leaving the program), because these functions cannot be reliably detected in an automated way.
The specific annotations are defined in the C header file endicheck.h. Here follows the list of supported annotations, together with explanation of their meaning: -EC MARK ENDIANITY(start, size, endianness) This annotation marks a region of memory from start to start+size-1 as having the given endianness. It should be used in byte-swapping functions. Target endianness is represented by the symbol EC TARGET. -EC CHECK ENDIANITY(start, size, msg) This annotation enforces a check that a memory region from start to start+size-1 contains only data with any or target endianness. It should be used in I/O functions. Unknown endianness is allowed by passing the -allow-unknown option.
Marks the given region of memory as protected. This should be used for mapped regions of device memory.
Marks the given memory region as unprotected.
Dumps endianness of a memory region. This is useful for debugging. Figure 1 shows an example program that demonstrates usage of the most important annotations (EC MARK and EC CHECK). If the call to htobe32 inside main is removed, Endicheck will report an endianness bug. This example also demonstrates possible ways to easily annotate standard functions, like htobe32 and write.
Evaluation
We evaluated the Endicheck tool -namely its ability to find endianness bugs, precision and overhead -by the means of a case study on the Radeon SI driver, several opensource programs and a standardized performance benchmark. For the Radeon SI driver and each of the open-source programs, we provide a link to its source code repository (and identification of the specific version that we used for our evaluation) within the artifact that is referenced from the project web site.
Case Study
Our case study is Radeon SI, the Linux OpenGL driver for Radeon graphics cards, starting with the SI (Southern Islands) line of cards and continuing to the current models.
Since these Radeon cards are little-endian, the driver must byte-swap all data when running on a big-endian architecture such as PowerPC. However, the Radeon SI driver (in the Mesa 17.4 version) does not perform the necessary byte-swapping operations, and therefore simply does not work in the case of PowerPC -it crashes either the GPU or OpenGL programs using the driver. In particular, endianness bugs in this version of the Radeon SI driver cause the Glxgears demo on PowerPC to crash. We give more details about the bugs we have found in Section 5.2.
An important feature of the whole Linux OpenGL stack is that all layers, including the user-space program, communicate not only using calls of library functions and system calls, but they also extensively use mapping of the device memory directly into the user process. Given such an environment, Endicheck has to correctly handle (1) the flow of data through the whole OpenGL stack by instrumenting all the libraries used, and (2) communication through the shared memory that is used by the driver. This is why the support for mapped memory in Endicheck, through marking of device memory with a special flag, as described above in Section 3, is essential.
Search for Bugs
For the purpose of evaluating Endicheck's ability to find endianness bugs, we picked a diverse set of open-source programs (in addition to the Radeon SI driver), including the following: BusyBox, OpenTTD, X.Org and ImageMagick. All programs are listed in Table 1. The only criterion was to select programs written in C that communicate over the network or store data in binary files, since only such programs may possibly contain endianness bugs. We also document our experience with fixing the endianness bugs in the Radeon SI driver and other programs.
One of the stated goals for Endicheck was to reduce the number of annotations that a user must add into the program source code in order to enable search for endianness bugs. Therefore, below we report the relevant measurements and discuss whether (and to what degree) this goal has been achieved.
In the rest of this section, first we discuss application of Endicheck on the Radeon SI driver (our case study) and then we present results for other programs.
Radeon SI case study. Within our case study, we have used the Glxgears demo program as a test harness for the Radeon SI driver. Initially we have run Glxgears on the x86 architecture, and after fixing all the issues found and reported by Endicheck, we moved the same graphics card to a PowerPC host computer and continued testing there.
In the case of the Radeon SI driver, all byte-swapping functions are located in a single file of one library (Gallium) on the OpenGL stack. Therefore, to enable search for endianness bugs in Radeon SI, we had to make just two changes: (1) annotate the function radeon drm cs add buffer as I/O function and (2) annotate the byte-swapping functions in Gallium. Overall, we had to add or change about 40 lines of source code, including annotations, in a single place. All our changes are published in the repository https://rkapl.cz/repos/git/roman/mesa. It contains the source code of Mesa augmented with our annotations and fixes for the endianness-related bugs in Radeon SI described below. For fixes of bugs found by Endicheck, we included the original Endicheck report in the commit message, under the ECNOTE header. Figure 2 contains an example bug report produced by Endicheck with enabled origin tracking on Glxgears. The error report itself has three main parts (in this order): the problem description, origin stack trace (captured when the offending value is created) and point-of-check stack trace (recorded when some annotated I/O function is encountered). We show only fragments of stack traces for illustration (and to save space).
The problem description identifies the currently active thread, the nature of the error and the memory region containing the erroneous value. The memory region is identified by its address and an optional name provided by the program ("radeon add buffer" in Thread 9 gallium_drv:0: Memory does not contain data of Target endianness Problem was found in block 0x41BF000 (named radeon_add_buffer) at offset 0, size 8: 0x41BF000: N N N N N This particular error report ( Figure 2) indicates that an array of floating-point values describing the multisampling pattern is not byte-swapped. Note that IEEE 754 floating point values also obey the endianness of the host platform, at least on the architectures x86, x64 and ARM. To repair the corresponding bug, we had to insert calls of byteswapping functions at the code location where the floating-point array is produced.
During our experiments with Radeon SI and Glxgears, four endianness bugs in total were detected by Endicheck on the x86 architecture before testing on PowerPC. After we fixed the bugs, the Glxgears demo did successfully run. This shows that Endicheck detected all bugs it was supposed to and provided reports useful enough so that the bugs could be fixed. Here we also need to emphasize that the Glxgears demo, naturally, does not exercise all code in the Radeon SI driver, and fixing the whole driver would require lot of additional work.
Other programs. As we said at the beginning of this section, we evaluated Endicheck's ability to find endianness bugs and precision on a set of realistic programs. Our primary goal in this part of the evaluation was to assess the following aspects: the extent of annotations that is required for Endicheck to work properly, whether Endicheck is able to detect a bug in a given kind of programs, and how many false warnings are reported.
Before trying to answer these questions, we wanted to be sure that the subject programs contain endianness bugs. However, some of the programs that we considered (OpenTTD, OpenArena and ImageMagick) are written in such a way that realistic endianness bugs cannot be injected into their codebase. ImageMagick uses a C++ abstraction layer for binary streams, which also handles endianness. OpenArena uses bitoriented encoding for most parts of the network communication. OpenTTD uses an abstraction layer too, but the developer can still make an endianness-related mistake in certain cases, such as storing an array of uint16 t values as an array of uint8 t values. We manually injected synthetic endianness bugs into the code of all the programs where this was possible. In this process, we also annotated the byte-swapping functions (like htonl). The bugs were created by removing one usage of byte-swapping functions.
The results of experiments are summarized in Table 1. For each program, the table provides the following information: whether it was possible to analyze the program at all, whether some endianness bugs were found, overhead related to false warnings, and how many lines of source code were added or changed in relation to Endicheck annotations. Data for the Radeon SI driver are also included in the Table 1 show that Endicheck could find the introduced bug in all the cases. Furthermore, Endicheck found two genuine endianness-related bugs in X.Org. The bugs were confirmed by the developers of X.Org and fixed in upstream 3 .
Endicheck also reports some false warnings, but their numbers are not overwhelming. Four cases in total occured for the Radeon SI driver and OpenTTD (two in each). This is a manageable amount, which can be even suppressed using further annotations.
Performance
In this section, we report on the performance of Endicheck in terms of execution time overhead it introduces. We compare the performance data for programs instrumented with Endicheck, programs instrumented by the Memcheck plugin for Valgrind and programs without any instrumentation. For the purpose of experiments, we used the standardized benchmark SPEC CPU2000. Even though SPEC CPU2000 is a general benchmark, not tailored for endianness analysis, results of experiments with this benchmark indicate the performance of Endicheck when doing a real analysis, because the controlflow paths exercised within Endicheck and the Valgrind core during an experiment do not depend on the specific metadata (tag values).
We run all experiments on a T550 ThinkPad notebook with 12 GiB of RAM and an i5-5200 processor clocked at 2.20 GHz, under Arch Linux from Q2 2018. The SPEC2000 test harness was used for all the runs, with iteration count set to 3. We compiled both Memcheck and Endicheck by GCC v7.3.0 with default options. Note that we had to omit the benchmark program "gap", because it produced invalid results when compiled with this version of GCC.
In the description of specific experiments, tables with results and their discussion, we use the following abbreviations: -EC: Endicheck (valgrind -tool=endicheck) -MC: Memcheck (valgrind -tool=memcheck) --OT: with precise origin tracking enabled (-track-origins=yes) --IT: with origin tracking enabled, but not fully precise (-precise-origins=no) --P: with memory protection enabled (-protection=yes) Execution time. We divided our experiments designed for measuring the execution time into two groups. Our motivation was to ensure that all experiments, including the EC-OT configuration that incurs a large overhead, finish within a reasonable time limit. In the first group, we run the full range of configurations on the "test" data set provided by SPEC CPU2000, which is small compared to the full "reference" set, and used MC as the baseline for comparisons. Table 2 shows results for experiments in this group. All execution time data provided in this table are relative to MC, with the exception of data for the native configuration. The second group of experiments uses the full "reference" data set from SPEC CPU2000. Results for this group are provided in Table 3. In this case, we used the data for native (uninstrumented) programs as the baseline. Table 3. Execution times for the SPEC CPU2000 reference data set, relative to native runs. Table 3 indicate that the average slowdown of Memcheck is by the factor of 16.59. Endicheck, in comparison, slows down the analyzed program by the factor of 35.31. This means Endicheck has roughly two times higher overhead than Memcheck with default options. According to data in Table 2, the same relative slowdown of Endicheck with respect to Memcheck is 1.65x. This difference between the results for the reference and test data sets is caused by the different ratio of the time spent instrumenting the code versus time spent running the instrumented code.
Data in
However, data in both tables also show that the performance of Endicheck with origin tracking is lacking compared to Memcheck with the same option. It was still usable for our Radeon SI OpenGL tests, but measurements indicate that there is a space for optimization. Nevertheless, certain relative slowdown between the configurations EC-OT and MC-OT probably cannot be avoided, because Endicheck must track origin information for much more data than Memcheck. Based on our experiments, we observed that creating the origin information is the most expensive operation involved. When the origin tags are created for each superblock, instead of every instruction, the execution times drop roughly by a factor of two (see the columns EC-OT and EC-IT).
Discussion
Based on the case study and results of experiments presented in the previous sections, we make the following general conclusions: -Endicheck can find true endianness bugs in large real programs, assuming that the user correctly annotates all the byte-swapping functions and I/O functions. -Using fairly complex metadata is feasible in terms of performance and encoding.
-Performance of Endicheck is practical even on large programs, despite the overhead and given that its current version is not yet optimized as well as Memcheck. -Although Endicheck, due to precise dynamic analysis, requires less annotations to be specified manually than static analysis-based tools (e.g., Sparse), still it puts certain burden on the user.
Regarding the annotation burden, we already mentioned that the user has to carefully mark in particular all the I/O functions and byte-swapping functions, so that Endicheck can correctly update endianness tags associated with memory locations during the run of the analysis. While it would be possible to recognize byte-swapping functions automatically, e.g. by static code analysis, then the endianness analysis would have to be run on a machine with the native endianness different from the target endianness, so that actual byte-swaps will be present. Another limitation of Endicheck from the practical perspective is handling of complex data transformations, a problem shared with taint analysis. The metadata cannot be correctly preserved through transformations such as encryption/decryption and compression/decompression. However, in many cases, the problem could be avoided by requiring an endianness check to be performed just before the respective transformation.
Related Work
As far as we know, the Sparse tool [11] used by Linux kernel developers, which we already mentioned, is the only one publicly available specialized tool tackling the problem of finding endianness bugs. The main advantage of Endicheck over Sparse is better precision in some cases, i.e. fewer false bug reports, since dynamic analysis, which observes actual program execution and runtime data values, is typically more precise than static analysis. Endicheck also does not require so many annotations of functions and variables as Sparse -when using Endicheck, typically just few places in the program source code need to be annotated manually. More specifically, Sparse expects that an input program code involves (i) the specialized bitwise data types (e.g., le32) for all variables where endianness matters and (ii) the macros for conversion between regular types and bitwise types (e.g., le32 to cpu). With Endicheck, developers only have to annotate the byte-swapping functions used by the program (e.g., htons and htonl from the C library). On the other hand, Sparse has better coverage of program code, as it is based on static analysis.
The Valgrind dynamic analysis framework [6] comes bundled with a set of bug detection tools. Very popular is the Memcheck tool [5] for detecting memory access errors and leaks, which also served as an inspiration for the design and implementation of Endicheck. We mention the tool here, because it actually performs a variant of dynamic taint analysis -it marks each bit of the program memory as valid or invalid (tainted).
Closely related is also the runtime type checker Hobbes [2] for binary executables, which can detect some kinds of type mismatch bugs common in C programs. In order to reduce the number of false bug reports and to delimit integer values, Hobbes uses the mechanism of continuation markers -the first byte of each value has the marker unset, and the remaining bytes are set to indicate that they represent a continuation of an existing value. The analysis technique used by Hobbes could be modified to track endianness of integer values instead of distinguishing between pointers and integers, since one can model integers of different endianness as values that have different types (also like in the case of Sparse).
Another approach with functionality similar to Endicheck has been implemented within the LLVM/Clang plugin called DataFlowSanitizer [10]. It is a dynamic analysis framework that (i) enables programs to define tags for data values and check for specific tags, both through its API functions, and (ii) propagates all tags with the data.
Conclusion
We have presented a new dynamic analysis tool, Endicheck, for detecting endianness bugs in C/C++ programs. The tool is built upon the Valgrind framework. Endicheck provides a useful, and in many settings also preferable, alternative to static analysis tools like Sparse, because (1) it reports quite precise results (i.e., a low number of false warnings) due to the nature of dynamic analysis and (2) requires less annotations (and other changes) in the source code of the subject program in order to be able to detect missing byte-swap operations. The results of our experimental evaluation show that Endicheck can (1) handle large complex programs and (2) identify actual endianness bugs, and it has practical performance overhead. Endicheck could also be used in automated testing scenarios, as a useful alternative to testing programs on both little-and big-endian processor architecture. A testing environment based on Endicheck might be easier to set-up than the environment based, for example, on virtual machines.
Future Work
Possible extensions of Endicheck, which could improve its precision and practical usefulness even further, include: -More complex analysis approach based on explicit tagging of each byte in an integer data value with its position. -Reporting arithmetic instructions that use data with target endianness. -Automatically checking system calls such as write for correct endianness.
-Suppression files for endianness bug reports to eliminate false positives.
Another way to detect endianness bugs more precisely is to use comparative runs (i.e, a kind of equivalence checking). The key idea is to run a program on two machines, where one has a big-endian architecture and the other has a little-endian architecture, and compare the data leaving both variants of the program. This approach has the potential to be the most accurate, because it can even detect problems in cases when data leaving the program are encrypted or compressed. On the other hand, it cannot always detect situations when the program forgets to byte-swap input data, unless the error affects one of the output values with concrete endianness. | 9,511.6 | 2020-03-13T00:00:00.000 | [
"Computer Science"
] |
Position Paper: The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management
The uneven utilisation of modes of transport has a big impact on traffic in transport pathway infrastrutures. For motor vehicles for instance, this situation explains rapid road deterioration and the large amounts of money invested in maintenance and development due to overuse. There are many approaches to managing this problem; however, the impact of individual users in infrastructural maintenance is mostly ignored. In this position paper, we hypothesise that important changes torwards a more efficient use of the transport network start with its users and their behavioural changes. To this end, we introduce our vision on how to employ data driven, intelligent agent-based modelling, incorporating human factors aspects, as a toolset to understand travellers and to stimulate behavioural changes. The aim is to achieve better balanced and integrated mobility usage within the transport network. The idea is explored with a few guided questions, and a methodology is proposed. We employ 1) cognitive work analysis to investigate the reasons for travellers' mode choice; 2) computational intelligence to extract and represent knowledge from related datasets; 3) agent-based modelling to represent the real-world and to observe both individual and emergent behaviours. Future directions to adapt our methodology to alternative smart mobility projects are also discussed.
I. INTRODUCTION
Globally, transport infrastructure is one of the key set of assets enabling the development of the economy. Nowadays, billions of dollars are being invested in its development and maintenance in response to increased demands as a result of population growth and the needs for mobility. Apart from the huge costs, the rapid growth in demand and maintenance of transport networks brings threats to the environment, economy, safety [1], [2], and social life. Transport infrastructure management has been mostly focusing efforts on minimising maintenance [3], [4] and development costs [5], while keeping safety, availability and reliability at acceptable levels. Achieving these objectives, however, is becoming increasingly challenging due to the shrinking global financial status, the ageing and subsequent deterioration of infrastructures [3] due to heavy usage. More importantly is also the fact that the roles of transport users in infrastructural maintenance is often ignored. All these factors combined impact heavily on the health and lifecycle of transport networks and should be considered by the stakeholders during decision making. Our interest is to propose ways of incorporating human factors, human behaviour and computational intelligence into simulation tools to help promote societal changes that positively impact on transport infrastructure health. The transport system is a sociotechnical system with people as one of its essential components. Regarding transport demand, people tend to choose a transport mode that (i) answers their mobility needs; (ii) is easy to use; (iii) is reliable and safe; and (iv) ensures access to markets and resources [6]. Travellers' mode choice decision processes are complex, depending on many interdependent factors, most of which are not crisp, but uncertain/fuzzy and subjective to the decision maker [7]. Individuals' preferences in mode choice over time have resulted in an uneven usage of available transport modes [8], [9], which make some infrastructures being under pressure due to heavy usage, and others underutilised. In order to tackle this problem, detailed investigations and surveys into users' operations within the transport system is essential, because decision-makers need to understand why individuals choose a travel mode over another [10]. In addition, it is important to identify what effects those choices have on the transport infrastructure lifecycle and on users' safety and economy. It is also necessary to understand how intervention to promote changes in users' behaviour can improve the health and life of transport infrastructures. Consequently, a few questions arise: How can reliable data be obtained to provide insights into the activities of the heterogeneous transport users? How can this information be incorporated into a simulation system for decision making? Are there adaptive intelligent systems to extract information from the large interdependent data stream constantly gathered from users and their user-transport infrastructural survey? How can uncertainty in data due to human nature and structural relationship be addressed? Our position is that the questions raised can be tackled using data-driven agent-based computational intelligence modelling approaches. This position paper therefore proposes an intelligent travel mode integration methodology that relies on cognitive work analysis, computational intelligence techniques, agent-based modelling and data mining algorithms to achieve a datadriven intelligent integrated mobility decision tool set to promote good health of transport infrastructure. Integration in transport mode involves interoperability between travel modes and within transport systems. Transport users are autonomous entities who have habits, interact, make intelligent decisions and adapt to a changing complex transport system's environment. Consequently, our approach investigates the dynamic transport environment using a Human Factors analytical framework called the cognitive work analysis [11], [12] with a view to identifying the constraints the system imposes on users. We also explore knowledge discovery with appropriate data mining algorithms to understand patterns emerging from the system; as well as a fuzzy logic systems to capture uncertainty in data imprecision. Also to model populations of heterogeneous, autonomous travellers that have behaviour and ability to interact with other travellers within the system using agentbased modelling technique. The individual traveller is created as an agent equipped with rules of behaviour extracted from the real-world data and simulated within the agent-based environment. The final objective is to obtain a system where it is possible to observe the emergent behaviour arising from the interacting entities within a simulation environment and their possible responses to new travel policies. We hope that the emerging behaviour of the simulation systems assisted with the knowledge unveil by the computational techniques, our methodology can provide information to aid efficient strategic development for mode integration that can lead to improvement in the health of the transport infrastructure.
II. BACKGROUND INFORMATION
Transport infrastructure includes physical networks, terminals and intermodal nodes, information systems and refuelling and electrical supply networks [13]. The investments in transport infrastructure across the world are on the rise [14][8] [15]. Available data show that road and rail infrastructure attract large investments [15] [8]. Despite the considerable investment in rail infrastructure, 73% of domestic freight moved in Great Britain in 2014, for instance, was done by road through heavy goods vehicles (HGVs); and this percentage increased to 76% in 2015 [9], [16]. Furthermore, a larger percentage of passenger mobility in the UK is done by road. Car use accounts for 78% of total distance travelled either as a driver or a passenger in 2014 [9]. The situation is not different in the US. Trucks have the largest shares of freight by values, ton, and ton-miles for shipment moved up to 750 miles [8]. Also, nearly four-fifths of person-miles of travel (PMT) was in cars or other personal vehicles while domestic air travel accounted for 11%.
It is therefore evident that some transport modes attract more freights and passengers' mobility than the others. It is also clear that there are uneven distributions in the shares of services across the travel modes. Hence, this has made some modes such as road transport more problematic regarding infrastructural usage, traffic congestions, safety, reduced economy and its overall infrastructure health. There are several approaches to mitigate the many challenges of the transport system regarding mode choice and better use of the infrastructure. Among the possible solutions is integrated mobility or the travel mode integration approach. Although mode integration was suggested to curb greenhouse gas emissions (GHG) [13], with the appropriate deployment of specialised knowledge gathering innovations and data-driven computational techniques, it can be used to resolve issues of serious concern such as infrastructural deterioration due to accumulated effects of uneven travel mode distributions. Consequently, an in-depth understanding of transport system's entities and their interactions is essential to enhance proper strategic policies formulation to propel necessary changes. But access to accurate and complete datasets and proper harnesses of relevant methodologies to support knowledge discovery is necessary for the achievement of efficient transport infrastructure management through mode integration.
A. Sociotechnical Transport System
The sociotechnical theory is based on the idea that the design and performance of an organisational system can only be understood and improved if both 'social' and 'technical' aspects are brought together and are treated as interdependent parts of a complex system [17]. The social aspect of the transport domain as a sociotechnical system comprises, among other things, of heterogeneous human beings with behaviour and capabilities to adapt to changes in the environment. But the technical systems might not be perfect and, as such, not able to cope with the demands of changing environments in which human are situated [18], that explains changes in humans' reactions when a situation needs improvement or when things go wrong in a system [10]. Human activities can be understood in terms of constraints that restrict them, and the goals that provide direction to their actions, procedures and decision. It is therefore important to understand the performance-shaping factors of the domain within which users' operations are performed. Such understanding according to Bisantz et al. [19] will not only be helpful but will also be necessary to make sense of and support performance in complex, unpredictable environments. Consequently, Human Factors (HF) investigates factors and the development of tools that facilitate the achievements of enhancing performance, increasing safety and increasing user satisfaction [20]. The application of HF analytical techniques is key to understanding the factors that shape users' travel mode choices.
B. Human Factors approaches to complex system analysis
There are several analytical techniques in Human Factors. The methods include normative task analysis that prescribes how a system should behave [12], [21]; there is also the descriptive task analysis [22], [19] that focus on analyzing how a system behaves in practice. The two techniques work by decomposing activities into a set of task sequences, which can rarely be extended beyond stable and repeatable systems [23]. Thus, those techniques are not suitable for unanticipated events that occur in a dynamic transport environment. Consequently, the formative approach has the capabilities to handle inherent complexity and adaptability. It also allows the examination of unpredicted, and unanticipated actions within a system. Cognitive Work Analysis (CWA) [11], [12] is a well-established formative task analysis model that had been used in Human Factors and Ergonomics to investigate the constraints imposed on the users by the system's environments.
CWA is a five-phase model that offers deep insight into the work analysis of complex systems by defining what is needed to perform the task, regardless of the actors, the situation and the environment of the system. Details of CWA can be found in [12], [24]. It has been applied successfully in many domains such as process control [12], transport [25], [26]. This paper discusses only the first phase of CWA, i.e. work domain analysis (WDA) which is relevant to the proposed methodology. The WDA defines the reasons for behaviour within the system (functional properties) and defines the resources available for the behaviour (physical properties) [22]. WDA models system with the Abstraction Hierarchy (AH) which uses 'how-what-why' triads to describe the relationship among the elements within the system domain across five conceptual levels in the WDA. An illustrative example of how AH works is given in Section III (step 4). The emergent behaviours arising from individual autonomous traveller is key to understanding the system's response to interventions. The next section discusses the modelling of individuals within a complex adaptive system.
C. Agent-Based Modelling and Travellers' Heterogeneity
Beanland et al. [27] describe agent-based modelling (ABM) as a way to model the dynamics of complex systems and complex adaptive systems. It models a system from the perspective of agents, i.e., viewing any system as consisting of agents. Agents are entities within a system that have behaviours, can interact with other entities and the environment. Their interactions with other entities can influence their behaviours [28]. Individual behaviour and their interactions are explicitly represented in a program or even in another physical entity such as robot [29]. Such agent is capable of changing its behaviour during the simulation in an adaptive system as agents learn, encounter novel situations, or as populations adjust their composition to include larger proportion of agents who have successfully adapted [30]. However, to mimic the behaviour of humans they represent, agents require to be equipped with the right, and adequate set of rules developed from extracted real-life data representing the observed population. The techniques for abstracting knowledge from datasets are reviewed in the following section.
D. Computational Intelligence Techniques
The nature of transport system as a sociotechnical system, and the heterogeneity in travellers' attributes, as well as possible uncertainties that can arise in their mode choice decision process, require computational techniques that can perform well in the complex and adaptive system environment. Such techniques are necessary to handle the huge volumes of interdependent data arising from human activities and operations within the transport domain. The objective is to assist understanding and to mimick 'intelligent behaviour'. Engelbrecht [31] describes Computational intelligence (CI) as the study of adaptive mechanisms to enable or facilitate intelligent behaviour in complex and changing environments. Any methodology that is capable of assisting computers to behave intelligently in addressing complex world problems involving large and interdependent data, as well as imprecision and uncertainty information is part of CI. For our methodology, within CI we include the use fuzzy logic systems (FLS) [32]. They concern with how people describe the world around them [33] and represents decisions that are rather ambiguous and blurred [32]. In practice, travellers have in mind the vague idea of their preference in travel mode with a multitude of attributes and factors that have no distinct boundaries; such complex situations are often best handled with the application of the fuzzy system. These systems will be used to mimick travellers decisions. Evolutionary computation [34] and the swarm intelligence [31] can assist optimising parameters, modelling social networking among the agents (travellers) and also selecting neighbour agents to engage in interaction. Furthermore, machine learning methods will assist extracting data patterns, clustering behavior and predicting classes or outcomes. CI techniques will therefore provide the support to extract and incorporate knowledge from interdependent datasets into agents and their environment.
The next section describes the processes involved in the methodology to support transport infrastructure management through mode integration.
III. PROPOSED SOLUTION
This section describes our proposed solution by bringing together various modelling techniques earlier discussed. Illustrative example of freight mobility from the origin-todestination is used to work through the stages in the methodology process.
The process flow diagram depicted in Figure 1 provides a guide to understanding how the methodology can be used to promote transport infrastructure through mode integration.
Step 1 of the process flow is the starting point.
Step 2 is to investigate what constitutes the reasons for the choice that people make when selecting a mode for their freight mobility. Knowledge gathering methods such as interviews, questionnaires, document analysis etc., in addition to specialized vehicular data collection devices, such as video vehicle detection, pneumatic road tube counting, piezoelectric sensor that measure vehicular flows and weights can be used. The focus of the data gathering should reflect the reasons for the preferences in a mode and people's perceptions on the available existing infrastructure that support their journey, as well as their likely responses to interventions if provided.
Step 3 focuses on the exploration of collected data to extract and identify infrastructures, procedures etc., within the system that are of concern of the participants. The data exploration will assist the construction of the abstraction hierarchy in step 4 in order to describe the relationships that exist within the system.
Figure 1. Mode Integration Methodology Process Flow
Step 4 is inspired by [35] and thus explained with the aid of the AH in Figure 2 which shows our vision of infrastructure and resources that support travellers' activities to achieve the purpose of goods delivery to the destination.
Starting from the top level (see Figure 2), the Functional purpose (top-left box on level 1 of Figure 2) of a transport system is to provide necessary infrastructural support for a comfortable and efficient movement of goods from the origin to the destination. The level below the functional purpose level (level 2) is the Values and priority measures that have Reliability, Journey time and Cost and value for money as the criteria defined to evaluate how the system progresses towards its functional purposes. For instance, moving goods from origin to destination can be impacted by route networks hence, prompt the traveler to show preference for alternative travel modes that has better network connections. The middle level (level 3) is the Purpose-related functions, which describe the general functions necessary for a system to achieve the functional purpose. Among the general functions for our example are cater for tasks needs, which refers to the system capability to provide necessary support for freight transfer functions; origin-destination connections which include efficient routes connection of origin-depotsdestination; information provision that can enhance smooth travels; and drivers and freight protections for general safety within the system, all are to assist the achievement of efficient and comfortable freight movement. The Object-related processes (level 4) refer to the functional capabilities and limitations of the current objects and infrastructural resources within the system which affect achievements of the efficient and comfortable freight delivery, and lastly, the Physical objects and Resources (level 5) which consist of the actual available infrastructural objects and resources within the system that the object-related processes refer. The AH nodes are connected by the means-ends links that describe the relationships among the boxes such that when a node is taken within the hierarchy as the 'what', nodes linked in the hierarchical level above the node indicate 'why' the chosen node is necessary within the system. Any connected nodes on the level immediately below that node can be taken to answer the question of 'how' that function is to be achieved or fulfilled [12]. For example, tracing through the highlighted links and boxes in Figure 2, if 'cater for task needs' (box 3 in level 3) is taken as 'what' at the purpose related functions level. The links connecting the node up to the value and priority measures level show that it can support 'cost and value for money' node. i.e. it occurs to forms part of the considerations to evaluate the costs of moving the good to the destination as well as the value for money (i.e. why). Also, to show how 'cater for task needs' (what) has been derived. The level below i.e. the object related processes level that has 'route/networks connections', 'wayfinding', 'general border processes', and 'energy supply' highlighted (i.e. how) showing how the cater for needs node was derived.
In step 5, the information provided by the AH components' relationships will be used to organize the survey data with the related functions they support. Then the data will further be analyzed for travellers' stereotypes elucidation using clustering algorithms such as K-Means. CI techniques extract useful information from the survey data. These techniques will involve the use of overlay analysis due to possible differences in the formats of the collected survey data. 1) Data collected from both human and vehicles will require fusion; in addition, different sources will require weighting factors based on their importance to the overall objective of the system. 2) Correlation analysis of the multiple sources of data will establish the relationship of all inputs before combining the data for further pattern identification. 3) the challenges of the uncertainties and imprecision in the data are better handled with a Type-1 fuzzy logic by using precise membership functions describing the agents decision based on the data analysis and stereotypes defined previously [36].
Investigate travellers' mode choice decision process with respect to available infrastructures, policies and regulations etc.
Explore the survey data to identify functions of concerns to the participants.
Construct Abstraction Hierarchy to reveal the relationships among functions of concerns and the transport system's functional purpose Use the AH means-ends links to relate the survey data to corresponding functions and prepare datasets for further analysis such as learn the stereotypes. [35] Duch [37] argues that an important challenge for CI is to create flexible systems that can use their modules to explore various ways to solve a given problem, proposing a different solution that may have different advantages. With agentbased simulation, each of the agents (virtual traveller) in the system will be preloaded with rules of behaviour which often are the products of series of analysis carried out in step 6.
In step 7, the agents' stereotypes are calibrated accordingly using the information from the previous analysis, and the model is simulated in step 8. Based on the parameterisations in step 7, the simulated settings represent the system base scenario with which further experimentation can be compared. The knowledge gained from the CI applications in step 6 will also provide support for strategic interventions development in step 9, which is for the purpose of stimulating travellers behaviours towards the reduction in the share of road transport in freight mobility. In step 10, the interventions can be applied to the already known base scenario agents' behaviours (i.e. step 8). Several experimentation of such interventions can be performed, and individual autonomous agent's behaviour, as well as the aggregate emergent behaviours, can be observed to better understand travellers' behaviour in response the interventions.
IV. DISCUSSIONS AND FUTURE DIRECTIONS
Effective mode integration through appropriate interventions to stimulate travellers mode choice behaviour positively impact the whole transport infrastructure lifecycle. It reduces for instance development time, maintenance, costs, emmissions and violation of land use acts. However, the objective of achieving travel mode integration could be difficult to accomplish within the current transport policies operations in many countries. For instance, in some countries including the UK, freight mobility services are autonomous, stand-alone, and information about goods movement are preserved within each company [38], while the infrastructures are owned by both private and public organisations. In the future, there is a need for comprehensive information sharing among transport companies for the integration of larger regional and continental mobility systems so as to promote sustainable and efficient linkages among infrastructures and other facilities that include all travel modes. Also, policies and regulations that encourage collaborative transport solutions should be put in place.
Currently, transport users are embracing digitalisation with the use of web applications, smartphones, social media etc. These new lifestyles can be explored further in the future to promote and improve passengers' journey experience, tailored to their individual needs and preferences. Furthermore, actions such as promoting public awareness about the needs for modal integration, providing information about various mode services and infrastructures such as route networks, intermodal terminals, park and ride services, transfer yards, and depots for goods can potentially have significant transformative effects on passenger's behaviour. Such information can be embedded within smart devices to enable door-to-door smart mobility and increase resources efficient utilisation. The need to increase integrated management of services such as integrated ticketing and document processing system, real-time information that cover all modes, will encourage mobility across all travel modes.
V. CONCLUSION
A proposed methodology to promote transport infrastructure health and lifecycle through travel mode integration was introduced in this paper. There has been an increase in the mobility demand and increasing share of road travel modes while other modes were underutilised for freight and passenger mobility. The situation has impacted negatively on the health of road infrastructures. However, to achieve mode integration, decision-makers need to understand why individuals choose a travel mode over another, and also, they need to identify what effects those choices have on transport infrastructure lifecycle and on users' economy. It is also important to understand how stimulating changes in users' behaviour can improve the health and life of transport infrastructures. The structure and activities within the transport system environment are both complex and consist of elements that exhibit adaptive behaviours. Hence, useful ideas from related branch of disciplines such as CWA, ABM and CI that deal with complex adaptive systems are carefully investigated and harnessed to provide answers to the issues raised. A methodology was developed with each of its components addressing a part of the concerns as follows: the inclusion of Human Factors CWA and its WDA abstraction hierarchy provided investigative opportunity to answer the question 'How can reliable data be obtained to provide insights into the activities of the heterogeneous transport users?'. Features extraction methods and agent-based modelling techniques supported with the rules of behaviour generated through the application of appropriate computational intelligence knowledge which are necessary to observe agents' behaviour will explain 'How can this information be incorporated into a system for decision making?'. The integration of CI techniques into the methodology process for knowledge extraction provide the needed technical support that answers the question 'Is there any technical supporting system with an adaptive mechanism to obtain useful information from the vast non-linear data constantly gathered from users and the user-transport infrastructural survey? The Fuzzy logic system as a CI technique is an established tool for dealing with uncertainty in data imprecisions which could be a major challenge in representing travellers' perception. The fuzzy system incorporation provided solutions to 'How can uncertainty in data due to human nature and structural relationship be addressed?' Lastly, due to the trend in the smart mobility projects ongoing globally. Some future directions of making mode integration method to be continually relevant to impact on infrastructural health and lifecycle are suggested. | 5,915 | 2018-11-01T00:00:00.000 | [
"Computer Science",
"Business"
] |
Cyclodextrins: Only Pharmaceutical Excipients or Full-Fledged Drug Candidates?
Cyclodextrins, representing a versatile family of cyclic oligosaccharides, have extensive pharmaceutical applications due to their unique truncated cone-shaped structure with a hydrophilic outer surface and a hydrophobic cavity, which enables them to form non-covalent host–guest inclusion complexes in pharmaceutical formulations to enhance the solubility, stability and bioavailability of numerous drug molecules. As a result, cyclodextrins are mostly considered as inert carriers during their medical application, while their ability to interact not only with small molecules but also with lipids and proteins is largely neglected. By forming inclusion complexes with cholesterol, cyclodextrins deplete cholesterol from cellular membranes and thereby influence protein function indirectly through alterations in biophysical properties and lateral heterogeneity of bilayers. In this review, we summarize the general chemical principles of direct cyclodextrin–protein interactions and highlight, through relevant examples, how these interactions can modify protein functions in vivo, which, despite their huge potential, have been completely unexploited in therapy so far. Finally, we give a brief overview of disorders such as Niemann–Pick type C disease, atherosclerosis, Alzheimer’s and Parkinson’s disease, in which cyclodextrins already have or could have the potential to be active therapeutic agents due to their cholesterol-complexing or direct protein-targeting properties.
Introduction
Cyclodextrins (CDs) are cyclic oligosaccharides composed of six (αCDs), seven (βCDs) or eight (γCDs) α-1,4-D-glucopyranoside units with the shape of a toroidal, hollow, truncated cone. Their exterior is hydrophilic due to the OH-6 primary groups on the narrow rim and OH-2 and OH-3 secondary hydroxyl groups on the wide rim, while their cavity is hydrophobic lined with H-3, H-5 and H-6 hydrogens and O-4 ether oxygens, which gives CDs the ability to encapsulate hydrophobic molecules or moieties in their cavities ( Figure 1). The glucose molecules in the ring structure are arranged rather rigidly in a 4 C 1 chair conformation. The molecular structure is stabilized by intramolecular hydrogen bonds between the secondary hydroxyls of the neighboring units, creating a complete belt of bonds in the case of βCD resulting in its remarkably poor water solubility. However, chemical substitution at the belt-forming hydroxyls increases aqueous solubility arising from the formation of hydrogen bonds with surrounding water molecules. A great variety of chemical modifications of CDs has been described (for example in βCD the 21 hydroxyl groups make 2 21 -1 possible combinations for substitution, and the introduction of an optically active center results in an enormous number of geometrical and optical isomers for even one type of chemical substituent) and the addition of functional groups at the hydroxyls fine tunes their size and solubility. The cavity sizes of the basic compounds are 4.7/5.3 Å, 6.0/6.5 Å and 7.5/8.3 Å for αCD, βCD and γCD, respectively, as measured as Figure 1. Molecular structure of randomly methylated β-cyclodextrin (MβCD). As a prototypic βCD derivative, the truncated cone-shaped structure of MβCD consists of seven α-1,4-D-glucopy ranoside units and it is characterized by a hydrophobic central cavity and a hydrophilic outer su face suitable for forming inclusion complexes with hydrophobic groups in aqueous solution MβCD, the most commonly applied derivative for cholesterol depletion in vitro, is randomly meth ylated at hydroxyl groups as indicated by R groups in the figure.
Complexation abilities of CDs resulting from their unique and diversified structur provide the basis for their widespread application, such as in agrochemicals, pharmaceu ticals, fragrances and foods. Their biocompatibility, good tolerability, water-solubility non-immunogenicity and resistance to degradation enable their use in pharmaceutica formulations, which is highly favorable especially in light of the newly emerging dru candidates having continuously increasing molecular mass, lipophilicity and reduced wa ter solubility. Currently, up to 100 drug formulations contain CDs and two functionalize derivatives, HPβCD and SBEβCD, are available in FDA (United States Food and Dru Administration) and EMA (European Medicines Agency)-approved products for huma parenteral use due to their favorable safety profile [1,2,4]. Recently, novel directions of CD development emerged such as design and synthesis of novel CD derivatives, CD nano sponges, covalent CD-peptide/protein conjugates, CD-based polymers formed by cova Figure 1. Molecular structure of randomly methylated β-cyclodextrin (MβCD). As a prototypical βCD derivative, the truncated cone-shaped structure of MβCD consists of seven α-1,4-Dglucopyranoside units and it is characterized by a hydrophobic central cavity and a hydrophilic outer surface suitable for forming inclusion complexes with hydrophobic groups in aqueous solutions. MβCD, the most commonly applied derivative for cholesterol depletion in vitro, is randomly methylated at hydroxyl groups as indicated by R groups in the figure.
Complexation abilities of CDs resulting from their unique and diversified structure provide the basis for their widespread application, such as in agrochemicals, pharmaceuticals, fragrances and foods. Their biocompatibility, good tolerability, water-solubility, non-immunogenicity and resistance to degradation enable their use in pharmaceutical formulations, which is highly favorable especially in light of the newly emerging drug candidates having continuously increasing molecular mass, lipophilicity and reduced water solubility. Currently, up to 100 drug formulations contain CDs and two functionalized derivatives, HPβCD and SBEβCD, are available in FDA (United States Food and Drug Administration) and EMA (European Medicines Agency)-approved products for human parenteral use due to their favorable safety profile [1,2,4]. Recently, novel directions of CD development emerged such as design and synthesis of novel CD derivatives, CD nanosponges, covalent CD-peptide/protein conjugates, CD-based polymers formed by covalent bonds, or CD-based polyrotaxanes that can be characterized by more favorable properties compared to monomeric CDs, which include higher complexation efficiency, enhanced bioavailability, improved solubility and stability in drug formulations, better targeted delivery and release, more favorable pharmacokinetic profiles, more efficient penetration through the blood-brain barrier and even lysosomal targeting, as reviewed elsewhere [5][6][7][8].
While a lot is known about the pharmaceutical applications of CDs as excipients, their potential medical use as biologically active therapeutic agents is a more neglected area of CD research and development. Although their cholesterol-complexing ability has been known for decades, their modulatory actions in diseases characterized by pathologically relevant elevations in cholesterol levels such as Niemann-Pick type C disease, atherosclerosis, or Alzheimer's disease have only recently been recognized. Even more scarcely documented aspects of CDs are their potential interactions with cellular proteins in spite of the fact that these compounds are often used in many peptide/protein formulations. Such potential direct CD effects on protein functions can be of substantial biological relevance considering the high CD concentrations reached when CDs are applied as vehicles of therapeutically active agents. While most recent reviews focus on the excipient actions of CDs, this review is devoted to shed light on the sovereign therapeutic relevance of CDs, which could be based on their well-known cholesterol-extracting effects and ligand-like actions on proteins that are only recently being explored experimentally but are still ignored in clinical practice. To that end, we summarize general molecular patterns of CD binding to proteins and collect the numerous examples existing in literature in which direct CDprotein interactions are revealed in detail and carry functional consequences of potential but unexploited therapeutic relevance. We further intend to emphasize the applicability of CDs as active compounds in the treatment of human disorders related to membrane cholesterol elevations, such as Niemann-Pick type C disease, atherosclerosis and neurodegenerative disorders such as Alzheimer's and Parkinson's diseases.
Cholesterol Complexation by Cyclodextrins
CDs can extensively interact with a large variety of both hydrophobic and amphiphilic lipids including cholesterol, fatty acids, phospholipids, or sphingolipids by forming hostguest type inclusion complexes. The extent of encapsulation is determined by the characteristics of both the CD such as cavity size and chemical microenvironment of the cavity entrance due to substitutions, and the lipid such as chain length, presence of double bonds or polarity of the headgroup region. In general, fatty acids, phospholipids and sphingolipids show preferential complexation with the smallest αCD since their acyl chains fit tightly into its narrow hydrophobic cavity while loosely interacting with larger βCDs and γCDs. While direct interactions between CDs and fatty acids, phospholipids, or sphingolipids can be utilized in a variety of applications in food, nutraceutical or pharmaceutical industry as reviewed elsewhere [9,10], cholesterol-CD interaction is undoubtedly the most extensively studied area of lipid-CD research carrying established medical relevance, therefore, it will be in the focus of the current review.
As opposed to free fatty acids and phospho-or sphingolipids, cholesterol is complexed most efficiently with βCD and its derivatives, particularly MβCD and HPβCD [11]. Although the cavity of a single βCD is too small to shield the hydrophobic region of a cholesterol molecule from water, two stacked βCDs can provide an ideal steric fit. In a typical 1:2 (mol/mol) cholesterol:βCD complex, the almost planar cholesterol is completely encapsulated from both ends of the molecule, as its ring A and ring B are included in one βCD cavity while ring D and the side chain by the other βCD with the wider ring of the two βCDs facing each other [9]. Such a cholesterol-CD interaction can be used to manipulate cholesterol levels in biological membranes through a CD-mediated cholesterol extraction from bilayers as was demonstrated by a large number of cellular studies. In these reports, the extent of membrane cholesterol depletion was determined by various factors including the type and concentration of the applied βCD, cell type, incubation time and temperature [10,12,13]. In the original model describing the mechanism of βCDinduced cholesterol efflux, cholesterol molecules were proposed to spontaneously leave the cell membrane by an aqueous diffusion mechanism involving the initial desorption of cholesterol molecules from the membrane followed by binding to βCDs localized in the aqueous phase without binding or inserting into the bilayer [12]. In a modified version of the theory, βCDs were proposed to diffuse into the immediate proximity of the membrane so that cholesterol molecules can enter directly into the hydrophobic pocket of a βCD, without the necessity of completely desorbing through the aqueous phase [13]. According to a recently described molecular extraction model based on molecular dynamics simulations summarized in Figure 2, βCDs have a tendency to form aggregates including dimers that can bind to the membrane surface in a tilted conformation that is unable to extract cholesterol. However, further accumulation of βCD dimers on the bilayer surface stabilizes a perpendicular orientation of dimers suitable for the extraction process to occur. Once an interfacially-embedded βCD dimer is positioned above a cholesterol molecule, the latter can enter the hydrophobic cavity of βCDs rapidly, which is followed by desorption of the βCD dimer-cholesterol complex from the interface. Although βCD monomers can also bind to the membrane and capture cholesterol headgroups, they fail to induce extraction due to inadequate shielding of the whole hydrophobic cholesterol molecule. Only the last step of the process involves a substantial energy barrier and the extraction efficiency substantially depends on the lipid composition of bilayers, mainly their cholesterol content and the degree of unsaturation of phospholipids [14,15]. In these reports, the extent of membrane cholesterol depletion was determined by various factors including the type and concentration of the applied βCD, cell type, incubation time and temperature [10,12,13]. In the original model describing the mechanism of βCD-induced cholesterol efflux, cholesterol molecules were proposed to spontaneously leave the cell membrane by an aqueous diffusion mechanism involving the initial desorption of cholesterol molecules from the membrane followed by binding to βCDs localized in the aqueous phase without binding or inserting into the bilayer [12]. In a modified version of the theory, βCDs were proposed to diffuse into the immediate proximity of the membrane so that cholesterol molecules can enter directly into the hydrophobic pocket of a βCD, without the necessity of completely desorbing through the aqueous phase [13]. According to a recently described molecular extraction model based on molecular dynamics simulations summarized in Figure 2, βCDs have a tendency to form aggregates including dimers that can bind to the membrane surface in a tilted conformation that is unable to extract cholesterol. However, further accumulation of βCD dimers on the bilayer surface stabilizes a perpendicular orientation of dimers suitable for the extraction process to occur.
Once an interfacially-embedded βCD dimer is positioned above a cholesterol molecule, the latter can enter the hydrophobic cavity of βCDs rapidly, which is followed by desorption of the βCD dimer-cholesterol complex from the interface. Although βCD monomers can also bind to the membrane and capture cholesterol headgroups, they fail to induce extraction due to inadequate shielding of the whole hydrophobic cholesterol molecule.
Only the last step of the process involves a substantial energy barrier and the extraction efficiency substantially depends on the lipid composition of bilayers, mainly their cholesterol content and the degree of unsaturation of phospholipids [14,15]. βCDs determined by molecular dynamics simulation. The main steps include 1. formation of βCD dimers from monomeric βCD rings in the aqueous solution; 2. binding of βCD dimers at the bilayerwater interface in a tilted conformation; 3. reorientation of the membrane-associated βCD dimers resulting in a configuration perpendicular to the plane of the membrane; 4. gliding of a cholesterol into the hydrophobic cavity of βCD dimers; 5. desorption of the βCD dimer-cholesterol complex from the membrane [14,15].
While empty βCDs are used to deplete membrane cholesterol, βCDs can also be precomplexed with cholesterol and, depending on the ratio between the amounts of βCD and cholesterol in the complex, they can act as cholesterol acceptors or even donors to replen- Figure 2. Molecular events of β-cyclodextrin (βCD)-mediated cholesterol extraction from biological membranes. The figure lists molecular events of membrane cholesterol depletion in response to βCDs determined by molecular dynamics simulation. The main steps include 1. formation of βCD dimers from monomeric βCD rings in the aqueous solution; 2. binding of βCD dimers at the bilayer-water interface in a tilted conformation; 3. reorientation of the membrane-associated βCD dimers resulting in a configuration perpendicular to the plane of the membrane; 4. gliding of a cholesterol into the hydrophobic cavity of βCD dimers; 5. desorption of the βCD dimer-cholesterol complex from the membrane [14,15].
While empty βCDs are used to deplete membrane cholesterol, βCDs can also be pre-complexed with cholesterol and, depending on the ratio between the amounts of βCD and cholesterol in the complex, they can act as cholesterol acceptors or even donors to replenish or overload membrane cholesterol. The application of these βCD-cholesterol complexes, typically the most effective MβCD-cholesterol, can help understanding the roles of cholesterol in the modulation of cellular functions. First, repletion of cholesteroldepleted cells can revert functional alterations induced by cholesterol extraction, which can corroborate the role of cholesterol in the given process and rule out off-target βCD effects. However, the repletion procedure has to be optimized for the given experimental system to avoid effects induced by cholesterol levels far above control. Second, pre-loaded complexes can lead to cholesterol enrichment of biological membranes providing a possibility to investigate functional effects of elevated cholesterol levels mimicking human pathological conditions such as hypercholesterolemia [10,[16][17][18].
Besides cholesterol, MβCD can form inclusion complexes with other sterol derivatives as well, which can be used to selectively load a given sterol into the membrane. For example, chiral analogues of cholesterol such as epi-and ent-cholesterols can be applied this way and their effects can be compared. Since these derivatives generally modify membrane biophysical parameters and lateral heterogeneity of the cell membrane in a similar manner, a stereospecific effect strongly argues in favor of modulation of protein function through direct binding [10,17,19]. Additional information about the mechanism of cholesterolinduced effects can be gained when applying MβCD complexes formed with various sterols including 7-dehydrocholesterol or 6-ketocholestanol that induce distinct changes in membrane biophysical parameters, and, therefore, can be applied to examine the possible contribution of these factors to functional effects [18,20].
Cyclodextrin Effects on Biophysical Parameters of Cellular Membranes
Cholesterol is a major component of biological lipid bilayers and its level substantially determines the biophysical properties of membranes including fluidity, rigidity, thickness, lateral pressure, lipid order and dipole potential. Cholesterol increases lipid order and thus reduces fluidity (i.e., increases the degree of motional constraints of macromolecules) in model membranes in the biologically relevant fluid phase, and living cells as well, due to stretching of phospholipid acyl chains and decreased average cross-sectional area per lipid molecule [21][22][23]. Cholesterol-induced decreases in membrane fluidity are also mirrored by reductions in the degree of membrane hydration (i.e., penetration of water molecules to deeper layers of membranes) [24][25][26][27]. In keeping with stretching induced in lipid acyl chains, cholesterol increases the thickness of bilayers [21,28]. In parallel, the amount of membrane cholesterol positively correlates with the interfacial elastic area expansion/compressibility moduli of bilayers implying elevated stiffness [29,30]. Furthermore, cholesterol also increases the elastic bending modulus of bilayers referring to enhanced bending rigidity [31,32], and modifies the intrinsic spontaneous curvature of membranes [33,34]. Dipole potential is an enigmatic membrane biophysical parameter, a largely positive intramembrane potential generating an immense electric field, which originates from the non-random alignment of molecular dipoles of carbonyl groups, cholesterol and water molecules at the membrane-water interface [17,35,36]. Its magnitude is determined by the lipid composition of bilayers with cholesterol being the most important determinant. The level of cholesterol shows unequivocal positive correlation with the value of dipole potential due to its intrinsic dipole moment, effects on lipid order and water penetration into the membrane [37,38]. As can be seen from the above, the level of cholesterol essentially influences the biophysical properties of cellular bilayers, which can in turn modulate the function of proteins in an indirect manner as discussed below.
Due to their cholesterol-extracting abilities, CDs can change the above-mentioned cholesterol-dependent membrane biophysical parameters ( Figure 3). For example, MβCD treatment of living cells was shown to increase membrane fluidity [22,23] and hydration [25,27], and reduce the magnitude of dipole potential [20,[39][40][41][42]. On the contrary, treating cells with MβCD pre-complexed with cholesterol reduced membrane hydration [27] and elevated dipole potential [20]. in substantial alterations of membrane biophysical parameters including increased fluidity (lower degree of motional constraints of macromolecules), hydration (penetration of water molecules represented with dark blue spheres into deeper layers of membranes) and elasticity, and decreased lipid order (represented as straightened acyl chains of phospholipids), bilayer thickness (represented as increased d distance) and dipole potential (represented as enlarged red sphere of positive charge in the central region of the membrane). On the contrary, cholesterol loading of membranes using cyclodextrins pre-complexed with cholesterol (bottom arrow) leads to opposite changes such as reduced fluidity, hydration and elasticity, and enhanced lipid order, thickness and dipole potential of cellular membranes.
Cyclodextrin-Induced Disruption of Lipid Raft Microdomains
As can be seen above, cholesterol is an essential structural constituent of biological membranes; however, its lateral distribution is not homogenous due to its interactions with other membrane components including lipids and proteins. Preferential interactions between cholesterol and (glyco)sphingolipids, together with the active contribution of certain transmembrane proteins and the actin cytoskeleton, provide the basis for the formation of lipid rafts that are dynamic supramolecular clusters of various size characterized by elevated levels of cholesterol, phospholipids with saturated chains and (glyco)sphingolipids [17,43,44]. Various transmembrane proteins tend to accumulate in these microdomains that serve as concentrating platforms for molecules that interact with each other. In that way, raft residency facilitates the efficiency of various signaling pathways, thereby modulating a multitude of cellular functions including regulation of apoptosis, cell adhesion and migration, synaptic transmission, pathogen entry or formation of extracellular vesicles. Therefore, changes in the distribution of proteins between raft and non-raft membrane regions can lead to alterations in signaling mechanisms potentially contributing to the pathogenesis of various disorders [45][46][47][48][49].
Although cholesterol is present at higher concentrations in lipid rafts, it can also be found in non-raft regions of biological membranes. Therefore, cholesterol-complexing CDs could theoretically deplete both raft and non-raft membrane regions. Initial studies with model and cellular membranes suggested that CDs preferentially extract raft cholesterol especially in cases of short exposures and low applied concentrations, which leads to a selective removal of cholesterol from these regions eventually resulting in the consequent disruption of these ordered microdomains [10,[50][51][52][53]. Subsequent reports using model giant unilamellar vesicles and molecular dynamics simulations questioned preferential cholesterol extraction from rafts and suggested that CDs rather deplete cholesterol from disordered non-raft domains of bilayers with higher efficiency. However, reduction , hydration (penetration of water molecules represented with dark blue spheres into deeper layers of membranes) and elasticity, and decreased lipid order (represented as straightened acyl chains of phospholipids), bilayer thickness (represented as increased d distance) and dipole potential (represented as enlarged red sphere of positive charge in the central region of the membrane). On the contrary, cholesterol loading of membranes using cyclodextrins pre-complexed with cholesterol (bottom arrow) leads to opposite changes such as reduced fluidity, hydration and elasticity, and enhanced lipid order, thickness and dipole potential of cellular membranes.
Cyclodextrin-Induced Disruption of Lipid Raft Microdomains
As can be seen above, cholesterol is an essential structural constituent of biological membranes; however, its lateral distribution is not homogenous due to its interactions with other membrane components including lipids and proteins. Preferential interactions between cholesterol and (glyco)sphingolipids, together with the active contribution of certain transmembrane proteins and the actin cytoskeleton, provide the basis for the formation of lipid rafts that are dynamic supramolecular clusters of various size characterized by elevated levels of cholesterol, phospholipids with saturated chains and (glyco)sphingolipids [17,43,44]. Various transmembrane proteins tend to accumulate in these microdomains that serve as concentrating platforms for molecules that interact with each other. In that way, raft residency facilitates the efficiency of various signaling pathways, thereby modulating a multitude of cellular functions including regulation of apoptosis, cell adhesion and migration, synaptic transmission, pathogen entry or formation of extracellular vesicles. Therefore, changes in the distribution of proteins between raft and non-raft membrane regions can lead to alterations in signaling mechanisms potentially contributing to the pathogenesis of various disorders [45][46][47][48][49].
Although cholesterol is present at higher concentrations in lipid rafts, it can also be found in non-raft regions of biological membranes. Therefore, cholesterol-complexing CDs could theoretically deplete both raft and non-raft membrane regions. Initial studies with model and cellular membranes suggested that CDs preferentially extract raft cholesterol especially in cases of short exposures and low applied concentrations, which leads to a selective removal of cholesterol from these regions eventually resulting in the consequent disruption of these ordered microdomains [10,[50][51][52][53]. Subsequent reports using model giant unilamellar vesicles and molecular dynamics simulations questioned preferential cholesterol extraction from rafts and suggested that CDs rather deplete cholesterol from disordered non-raft domains of bilayers with higher efficiency. However, reduction of cholesterol levels in non-raft areas might in turn be followed by a rapid re-equilibration of cholesterol between raft and non-raft domains leading to reduced raft cholesterol levels and consequent disappearance of these microdomains [15,54]. Most probably, CDs can deplete cholesterol from both raft and non-raft bilayer regions and the efficiencies of the two processes may depend on experimental conditions such as concentration and duration of CD treatment or lipid composition of target membranes. Nevertheless, extraction from both membrane domains eventually leads to the disruption of lipid rafts in response to CDs, which can modulate the functions of transmembrane proteins localized in these regions, as discussed below.
Indirect Modulation of Protein Functions by Cyclodextrins via Alterations in Biophysical Parameters or Lateral Heterogeneity of Membranes
Given that molecular rearrangements associated with the activation of transmembrane proteins are mediated through the permission and cooperativity of the surrounding bilayer, lipids of the cell membrane in general, and cholesterol in particular, can actively modulate their structure and functional activity through a mixture of direct, ligand-like mechanisms and indirect effects. While the former are mediated by direct binding at cholesterol binding sites, the latter can occur via alterations in the biophysical properties or the lateral heterogeneity, i.e., the microdomain organization of cellular membranes [17].
From among effects exerted on membrane biophysical parameters, changes in membrane thickness induced by cholesterol can be highly relevant for the functional regulation of proteins, since, according to the hydrophobic mismatch theory, differences between the hydrophobic thickness of lipid constituents and transmembrane domains of proteins are energetically highly unfavorable. Thus, a larger extent of such mismatch induces adaptation mechanisms that may involve lipids such as changes in stretching of acyl chains or aggregation into preferential assemblies, for example, lipid rafts, and proteins as well. The latter include aggregation, homo-or heterooligomerization of proteins to minimize the exposed hydrophilic area, tilt of transmembrane helices or adaptation of other conformations, all of which might result in changed functional activity of the given protein. Cholesterol extraction in response to CDs and cholesterol enrichment with CD-cholesterol complexes could favor protein configurations with shorter and longer hydrophobic thickness, respectively, which can be associated with different activities [55][56][57][58].
Membrane curvature is a property of lipid bilayers strongly related to hydrophobic matching. In a membrane, when two molecules such as lipids and proteins are in the vicinity of each other, attractive and repulsive forces arise between them, which are of different type and magnitude at different depths in the membrane. As a result of these forces, there is an energetically favorable equilibrium distance between the molecules, which can be different close to the membrane-water interface and at the center of the bilayer, leading to a spontaneous curvature of the membrane. However, if the spontaneous curvature cannot be fulfilled due to steric constraints (for example because of hydrophobic mismatch) curvature elastic stress (frustration) arises. In a mutual relationship, the presence of transmembrane proteins can increase or decrease elastic stress of lipids, while the intrinsic curvature of lipids can influence the proteins. In this way, CD-induced changes in membrane cholesterol levels can modify elastic coupling between proteins and lipids, and consequently alter the stabilities of protein conformations thereby affecting their functional activity [56,58,59].
Through these mechanisms, i.e., increased fluidity and hydration, and reduced thickness and elastic stiffness, CD-induced cholesterol depletion was demonstrated to cause shifts in the voltage dependence of steady-state inactivation of Na V 1.4 channels towards hyperpolarized potentials [72], reduce ATPase and pumping activity of P-glycoprotein [73], diminish ligand binding of cholecystokinin receptors [74] and enhance activation of rhodopsin [75]. When examined, cholesterol repletion or enrichment using CD-cholesterol exerted opposing effects [72,74,75]. Furthermore, by increasing membrane tension due to cholesterol extraction, CDs were suggested to act as universal activators of mechanosensitive channels [76].
Indirect effects on protein function exerted by cholesterol and CDs can also be mediated through alterations in membrane dipole potential. Since the charge distribution is typically non-uniform in proteins, and their conformational changes involve transitions of their transmembrane domains localized in the intramembrane region of the dipole potential, its associated enormous electric field can substantially modify the conformational stability of proteins [17,35,77]. In keeping with this hypothesis, the dipole potential was shown to modulate the function of bacterial ionophores [78], voltage-gated ion channels [79], Na + -K + ATPase [80], ErbB proteins [81] and the cellular entry of cell-penetrating peptides [20,82]. Therefore, CD-induced cholesterol depletion can affect protein functions via decreases in dipole potential as shown by decreased ligand binding of P-glycoprotein [40] or serotonin receptors [39,41] in response to CDs. On the other hand, increasing cholesterol levels with cholesterol-CD complexes typically results in dipole potential-dependent changes of opposite direction [41].
A large variety of transmembrane proteins preferentially reside in lipid raft microdomains that serve as concentrating platforms for interacting molecules and are characterized by unique biophysical properties including decreased fluidity, hydration and elevated lipid order and dipole potential [22,23,25,83,84]. This unique microenvironment can differentially affect the stability of certain protein conformations and, therefore, the functional activity of proteins can be different when residing in raft or non-raft regions, as reviewed recently [17]. CD-induced disruption of lipid rafts can induce relocalization of proteins into disordered phases of cellular membranes and consequently modify their activity. Such CD effects have been described for a multitude of transmembrane proteins including various voltage-gated (K V ) potassium channels such as K V 1.3 [85], K V 1.4 [86], K V 1.5 [87], K V 4.2 [88,89], K V 4.2 [86], K V 10.1 [90] and K V 11.1 [91]. In these channels, raft localization was proposed to generally exert inhibitory effects on channel function, while a CD-mediated disruption of these microdomains rather resulted in increased activity such as elevated current amplitudes or leftward shifts in voltage dependence of activation. On the other hand, loss of raft-mediated clustering might interfere with the mostly unknown non-canonical signaling roles of ion channels [90,92]; however, this assumption remains to be proven. On the contrary, cholesterol replenishment or enrichment of the cell membrane can lead to enhanced raft partitioning, which may lead to functional changes opposed to those observed after cholesterol depletion including decreases in current amplitudes and rightward shifts of voltage dependence, as demonstrated for K V 1.3 [18,85], K V 1.4 [86], K V 4.2 [89], K V 10.1 [18] and K V 11.1 channels [91]. Similar to K V s, BK channels were also found to preferentially localize into lipid rafts, and CD treatment induced their relocalization into non-raft regions, which was associated with increased current densities and leftward shifts in the voltage dependence of current activation, while cholesterol loading had opposite effects when examined [93][94][95][96]. On the other hand, disruption of caveolar microdomains in response to CD reduced functional coupling between BK channels in the plasma membrane and ryanodine receptors in the sarcoplasmic reticulum in smooth muscle cells resulting in disappearance of Ca 2+ microdomains at plasma membrane-sarcoplasmic reticulum junctions [97]. Similarly, CD-induced disassembly of lipid rafts and concomitant relocalization of Na V 1.8 resulted in impaired neuronal excitability and inability to conduct mechanically-and chemically-evoked depolarizations [98], while such treatment also led to the impaired signaling activity of Na + /K + ATPase [99], TRPC1 (transient receptor potential Pharmaceutics 2022, 14, 2559 9 of 36 canonical 1) [100] or TRPA1 (transient receptor potential ankyrin 1) [101] ion channels that were suggested to occur through diminished signaling platforms. These observations emphasize the importance of CD-induced effects on lateral membrane organization affecting the proper signaling function of ion channels. Piezo channels represent a mechanosensitive group of channels that are also localized in lipid rafts. CD-mediated disruption of these microdomains accompanied by a softening of the bilayer was shown to attenuate clustering and mechanosensitivity of these channels [102,103].
Besides ion channels, cell surface receptors comprise another large group of proteins that are modulated by raft partitioning and its changes induced by cholesterol removal or enrichment. ErbB proteins are the best-characterized historically prototypical members of receptor tyrosine kinases, which preferentially localize into lipid rafts that generally are thought to exert inhibitory roles on receptor functions [104]. In accordance, CD-induced cholesterol removal and consequent raft disruption was shown to enhance ligand binding affinity [105,106], subsequent receptor dimerization and clustering [106][107][108], autophosphorylation [105,107,109] and downstream signaling activation [105,110]. When examined, these effects were reverted by cholesterol replenishment using CD-cholesterol complexes [105][106][107]109]. Raft partitioning is also a common feature in G protein coupled receptors constituting the largest protein superfamily involved in practically all cellular functions. Cholesterol depletion in response to CDs affects the activity of these proteins, as CDs were demonstrated to reduce the ligand binding affinity of CXCR4 (C-X-C chemokine receptor type 4) [111], metabotropic glutamate receptors [112] and opioid receptors [113], and inhibit the downstream signaling of metabotropic glutamate receptors [114] and opioid receptors [115] in a lipid raft integrity-dependent manner. These changes were generally abolished by CD-cholesterol supplementation, underlining the importance of cholesterol-dependent membrane microdomains in the regulation of G protein coupled receptors [111,112,114].
As can be seen, due to their ability to form complexes with lipids, CDs can efficiently modulate the lipid profile of cellular membranes. Therefore, through the selective removal or loading of certain lipids, these compounds are invaluable tools for the examination of cell functions and their dependence on lipid levels. Furthermore, their application can contribute to a better understanding of the pathomechanism of diseases characterized by alterations in membrane lipid compositions and can even provide relevant therapeutic alternatives in the treatment of these disorders, as described in Section 4 of the current review.
General Mechanisms of Direct Cyclodextrin-Protein Interactions
Direct interactions between CDs and peptides or proteins were first suggested based on observations that CDs, and particularly βCD, could remove certain proteins from the cell membrane of erythrocytes [116]. While this observation was first attributed to an extrusion process resulting from CD-lipid interactions, subsequent studies confirmed the existence of inclusion complexes between CDs and amino acids, mainly βCD derivatives and hydrophobic and aromatic residues. This conclusion is in keeping with the cavity diameter of βCD compounds allowing an appropriate fit of the aromatic ring of Phe, Tyr, His and Trp (~2.5 Å in diameter between the C-3 and C-5 with an effective diameter of 5 Å when considering hydrogens as well) into the hydrophobic moiety, while the cavity of αCDs and γCDs might enable only shallow and loose, or deep and loose inclusion, respectively [2,3]. In the first of such in vitro studies, competitive spectrophotometry demonstrated hydrophobic interactions between βCD (and to a lesser extent MβCD and HPβCD) and Phe, either when present alone or in oligopeptides in spite of steric constraints provided by the peptide backbone in the latter. Interestingly, the stability of complexes of Phe-containing oligopeptides was higher than that of the amino acid itself, which suggested that the presence of appropriate neighboring residues can contribute to the stability of the CD-peptide complex [117]. When comparing different residues, electrospray ionization mass spectrometry (ESI-MS) showed preferential CD-mediated complexation of aromatic amino acids (Trp, Phe and Tyr) over aliphatic ones (Val), with βCD more efficiently accommodating amino acids than αCD or γCD [118]. A potentiometric titration method determining binding constants between CDs and individual amino acids corroborated the complexation between aromatic Trp, Phe and Tyr (but not the more hydrophilic His) and βCD, while αCD only showed binding of Trp. In contrast, no inclusion of aliphatic amino acids (Ala, Val, Ile) was found with the exception of Leu. Dipeptides Ala-Phe and Ala-Tyr had higher affinities, indicating that the extension by a peptide moiety may result in stronger binding [119]. When examining binding between βCD and nine designed tripeptides obtained by permuting positions of two Ala with that of one Trp, Phe or Tyr using UV-visible and NMR spectroscopy combined with molecular docking analysis, these tripeptides showed stronger interactions than single amino acids, with Tyr-containing ones having the largest binding constants. The position of the aromatic side chain modulated βCD-tripeptide affinity, which highlighted the role of stabilizing interactions mediated by neighboring amino acids with the upper rim of βCD. It appeared that the hydrophobic aromatic rings form inclusion complexes with the hydrophobic cavity with the extent of embedding depending on the type and location of the aromatic group, and the flanking residues contribute to the stabilization of the complex interacting with the hydroxyl groups of βCD and aiding the right orientation of the aromatic ring in the cavity [120]. Recent molecular dynamics simulations also found that HPβCD can interact extensively with most apolar and polar but not charged side chains of individual amino acids with a special preference for the aromatic rings of Tyr, Phe and Trp. Furthermore, simulations also suggested the role of potential hydrogen bonds to HPβCD-amino acid interactions [121]. Examination of longer model oligopeptides also supported the existence of functionally relevant CD-amino acid interactions. Again, first reports emphasized the exclusive importance of aromatic amino acids. For example, according to UV absorption and fluorescence spectroscopy, the luteinizing hormone releasing hormone (LHRH) agonist deslorelin ([D-Trp 6 , Des-Gly 10 ] LHRH) directly bound HPβCD via its Trp and circular dichroism spectroscopy revealed that this interaction resulted in the stabilization of its native conformation and protection from enzymatic degradation [122]. Similarly, fluorescence, circular dichroism and IR spectroscopy showed that the lone aromatic Trp residue of the melittin peptide of bee venom can also be intercalated into the cavity of HPβCD leading to an inhibition of its aggregation [123]. However, subsequent studies later recognized the importance of additional interactions such as hydrogen bonds in the formation of CD-peptide complexes. For example, electron capture dissociation high resolution tandem mass spectrometry located βCD binding sites on model peptides including substance B, bombesin, angiotensin I and II, which were formed by a variety of amino acids including Tyr, Asp, Asn, Gln, Lys, Arg, and Pro, and the importance of hydrogen bonds was emphasized instead of exclusive hydrophobic interactions with aromatic groups [124].
Based on findings obtained in these in vitro studies examining direct interactions between CDs and individual amino acids or short model peptides, a common complexation mechanism emerged according to which the CD-peptide association is mediated by a central stacking inclusion of an amino acid residue, mainly an aromatic one into the cavity of CDs, particularly βCD and its derivatives due to their size appropriate for an optimal steric fit. This model was based on results gained with individual amino acids or short simple model peptides; however, more complicated three-dimensional structures of longer peptides and proteins and the presence of a vast number of chemical groups in these molecules potentially interacting with CDs might add further levels of complexity of CD-peptide/protein associations. In these more complex structures, the stacking association between the CD inner cavity and the interacting central aromatic residue can be substantially stabilized by additional interactions including hydrogen bonds, hydrophobic and van der Waals interactions with neighboring residues. Subsequent determination of crystal structures of bacterial, fungal and plant carbohydrate-binding proteins in complex with CDs acting as substrates, competitive or allosteric regulators provided insights into these detailed molecular mechanisms of CD-protein binding, which are to be discussed in the following section.
Bacterial, Fungal and Plant Carbohydrate-Binding Proteins
The first group of carbohydrate-binding proteins that extensively interact with CDs are cyclodextrin glycosyltransferase (CGT) enzymes that produce CDs via intramolecular transglycosylation of α(1-4)-glucans such as amylose of starch. During the enzyme reaction, the product CD is attached to the enzyme, providing a possibility for the examination of molecular details of CD-protein bonds. X-ray crystallography of such a snapshot with a βCD derivative, S-(α-D-glucopyranosyl)-6-thio-β-CD bound in the active site of CGT from Bacillus circulans revealed molecular details of the CD-protein interaction. The contact was dominated by essential stacking interactions with aromatic Phe and Tyr residues (Tyr89, Tyr100, Phe183, Tyr195, Phe259), which were complemented by an extended network of direct and water-mediated hydrogen bonds involving a catalytic Asp residue (Lys47, Tyr89, Tyr97, Trp101, Asp196, His233, His327, Asp328, Asp371, Arg375 and the catalytic Asp229) [125].
CGT enzymes show high structural similarity with α-amylases acting as endoamylases, i.e., starch-hydrolyzing enzymes that can recognize and cleave α-1,4 glycosidic bonds at random positions along the starch chain. Certain members of the α-amylase enzyme family can bind and efficiently hydrolyze CDs. The structure of one such protein, α-amlyase II from Thermoactinomyces vulgaris, with a substrate MβCD located in its active cleft showed binding position and orientation identical to that of the S-(α-D-glucopyranosyl)-6-thioβ-CD in its complex with Bacillus circulans CGT. Very similar stacking interactions with aromatic residues (His202, Tyr204, Phe286, Trp356) and a network of hydrogen bonds (with Tyr45, His244, Glu354, Asp421, Asp465, Arg469) mediated the association [126]. While the Thermoactinomyces vulgaris α-amlyase II shows comparable affinity towards CDs and starch, the structurally similar maltogenic amylase of Thermus sp. IM6501 exhibits a strong preference for CDs. X-ray crystallography of the enzyme in complex with βCD suggested that this difference originates from a domain-swapped homodimer configuration resulting in the formation of a narrow and deep active-site groove optimal for CD binding, which is distinct from the wide and shallow active-site groove of the smaller α-amylases. Furthermore, stacking interactions between an additional Trp residue and βCD were found essential for the preferential CD association [127]. CD binding was also described in exoamylases that hydrolyze outer α-1,4 glycosidic bonds in the starch chain and this association often results in the inhibition of their enzyme activity. X-ray crystallographic structures of βCD bound to exoamylases revealed similar molecular patterns of binding with the presence of stacking interactions with aromatic residues and an extensive network of hydrogen bonds and van der Waals or hydrophobic contacts with amino acids in proximity. Typically, in these structures the βCD sits at the base of the substrate-binding cleft occupying the cleft entrance and thus inhibiting catalysis by blocking substrate access to the more deeply located reaction center. Such associations were revealed between βCD and structurally homologous soybean β-amylase [128], maltodextrin-binding protein of Escherichia coli [129], cyclo/maltodextrin-binding protein of Thermoactinomyces vulgaris [130], and the granular starch-binding domain of glucoamlyase 1 of Aspergillus niger, that is structurally similar to the CD binding region of CGTs [131]. Debranching amylases, members of the third major group of amylases that cleave α-1,6 linkages, can also bind CDs resulting in a competitive inhibition of enzyme activity. CDbinding mechanisms of these proteins follow the same principles as demonstrated by crystal structures of complexes between βCD and various debranching amylases such as barley limit dextrinase [132], and pullulanase from Klebsiella penumoniae [133,134].
While molecular details of crystallographic structures of carbohydrate-binding proteins in complex with CDs showed subtle differences, CD-protein interactions were characterized by highly similar molecular patterns. In general, the association was mediated by stacking interactions leading to the inclusion of an aromatic amino acid into the cavity of the CD, which is enabled by an appropriate configuration of other residues in sterical proximity leading to the formation of a network of hydrogen bonds, hydrophobic and van der Waals interactions stabilizing the structure. Data obtained with human peptides and proteins to be described in the next sections are strongly consistent with this complexation mechanism.
Aggregation-Prone Human Peptides and Proteins
While the molecular details of direct CD-protein interactions are most extensively documented in carbohydrate-binding proteins of bacteria, fungi and plants, various human peptides or proteins were also reported to form complexes with CDs as well. The first group of such molecules with well-documented CD interactions is composed of aggregationprone human peptides and proteins. Their aggregation is generally thought to occur due to a temporary exposure of hydrophobic regions to the surface of the molecule, which leads to formation of intermolecular associations to bury hydrophobic chemical groups and avoid their energetically unfavorable contacts with water molecules. By virtue of their hydrophobic cavity, CDs might place a hydrophilic "cap" on exposed hydrophobic residues that participate in intermolecular peptide-peptide interactions to prevent aggregation by sterically hindering association of monomers [2,135]. In one of the first studies providing definite proof for this hypothesis, NMR spectroscopy of non-carbohydrate-binding model proteins demonstrated that βCD could bind to solvent-exposed aromatic hydrophobic sites on the surface of chymotrypsin inhibitor 2 and S6 proteins, which might inhibit their association or influence functionally relevant conformational changes of proteins by modifying stabilities of certain configurations [135]. Accordingly, various βCD derivatives were shown to efficiently inhibit the chemically or thermally induced denaturation and aggregation of lysozyme and basic fibroblast growth factor [136]. A recent computational approach demonstrated stabilization of granulocyte colony-stimulating factor in response to βCD and HPβCD at air-water interfaces and also in bulk water by complexing of peptide residues. However, according to this study, CDs might include not only moieties of aromatic side chains but polar or even charged amino acids as well. Based on these observations, a general inclusion mechanism was suggested with the involvement of peptide backbones and solvent accessibility as a decisive factor for the interaction [137].
Human Peptide Hormones
Besides the model compounds mentioned above, pharmaceutically or pathophysiologically relevant peptides and proteins were also shown to directly bind various CDs, mainly through their aromatic residues. A peptide exposing its aromatic amino acids even in its native form, thus being prone to misfolding and aggregation, is the human growth hormone (hGH). NMR spectroscopy showed its pronounced tendency to interact with mainly βCDs such as HPβCD and SBEβCD (and to a much lesser extent with αCD or γCD). This binding was suggested to involve H-3 and H-5 atoms on βCDs and Phe and Tyr residues on hGH, and resulted in decreased aggregation of the peptide [138].
Similar to hGH, ESI-MS showed complex formation between insulin and MβCD, and NMR spectroscopy suggested that this phenomenon can be mediated by aromatic residues (Tyr14 of the A chain and His5, His10 and Tyr26 of the B chain) leading to reduced self-association of the peptide [139]. Subsequent NMR studies demonstrated that βCD can bind insulin at these specific solvent-exposed aromatic Tyr and Phe sites (TyrA14, PheB1, TyrB16, PheB25). In this study, four interaction sites on monomeric insulin and one interaction site per insulin molecule in its dimeric form were detected, preferentially stabilizing the monomeric form and thus acting against aggregation [135]. As shown by NMR spectroscopy, HPβCD can also bind insulin, and while the largest chemical shift changes were found at the previously proposed Tyr and Phe residues (TyrA14, TyrA19, PheB1, TyrB26), two additional His (HisB5, HisB10) were also suggested to contribute to the complexation with this more hydrophilic CD [140]. Molecular docking analysis between insulin and various CDs corroborated complex formation with native CDs, MβCD, HPβCD and SBEβCD as well, which was mediated by inclusion of the previously described aromatic sites (PheB1, HisB10, TyrB16), and additional non-aromatic side chains (LeuA13, LysB29, ThrB30), and these complexes were stabilized by hydrogen bonds with a variety of other residues [141].
Amyloid-Forming Peptides and Proteins
Anti-aggregative effects of CDs can be highly relevant for cellular aggregation-prone peptides and proteins that, by entering the so-called amyloid state, can form elongated fibers with spines consisting of many-stranded β-sheet structures. The process is suggested to be mediated through the exposure of backbone amide groups. Accumulation of such amyloid-state fibrils can be toxic and may lead to a great variety of human disorders such as Alzheimer's, Parkinson's or prion diseases, characterized by the assembly of amyloid β (Aβ) peptides, α-synuclein and abnormal prion proteins, respectively [142]. CD-mediated shielding of exposed hydrophobic groups of these molecules might interfere with the aggregation process. Consistently, ESI-MS demonstrated that βCD can form complexes with Aβ peptides, proposedly via their Tyr and Phe amino acids, which might prevent their fibrillation and diminish substantially their neurotoxic effects [143]. Analysis of CD spectra of Aβ (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28) in the presence and absence of CDs demonstrated that βCD (but not αCD or γCD) inhibited the conformational transition of the peptide from random coil to the aggregation-prone β-sheet structure, which, according to NMR spectroscopy, was mediated by insertion of Phe19 and Phe20 to the inner CD ring from the broad side. Chemical shift changes in the methyl groups of Val18 of the peptide suggested that this residue can also play an important role in the stabilization of the interaction [144]. Subsequent NMR studies using Aβ and Aβ(12-28) revealed two βCD binding sites, at Phe19 and/or Phe20 and Tyr10 with the two peptides showing similar affinities. Emphasizing the role of Phe residues, the Aβ(12-28)Gly19Gly20 variant did not bind βCD, while the Aβ(12-28) fragment did not interact with αCD or γCD, which supported the requirement of the good steric fit between the CD and the aromatic rings of Phe and Tyr [145]. In a subsequent study, a βCD dimer, consisting of two βCD monomers connected by a flexible pentaethylene glycol-based linker, showed increased affinity towards Aβ in similar measurements, which also revealed additional potential interactions with His residues of the peptide. Both the βCD monomer and particularly the dimer affected Aβ aggregation and transmission electron microscopy showed altered structural morphology of the aggregates with potentially different neurotoxic activities [146]. When examining interactions between HPβCD, a physiologically more relevant CD, and Aβ(1-42), molecular docking analysis and molecular dynamics simulations confirmed the role of Phe19 in HPβCD binding; however, additional non-aromatic residues (Lys16, Ala21, Ile31 and Met35) were reported to contribute to complexation. In addition, supporting the biological relevance of this interaction, HPβCD treatment inhibited peptide self-aggregation mainly by impeding elongation and lateral association of peptide oligomers, prevented structural transition into β-sheet structures and reduced Aβ-induced toxicity. Once the inner hydrophobic cavity of HPβCD was blocked by a small hydrophobic molecule, the compound lost these protective abilities [147].
CDs, besides binding short Aβ peptides and thus interfering with their fibrillization, can also directly inhibit association of longer amyloid-forming polypeptide chains. For example, according to in vitro experiments, βCD bound to PrPC prion proteins and inhibited their conversion to the abnormal PrPSc isoform. In scrapie-infected neuroblastoma cells, βCD and MβCD treatment resulted in largely reduced cellular levels of the pathogenic PrPSc, while αCD and γCD showed much lower antiprion activity [148]. Furthermore, in transmission electron microscopy and size exclusion chromatography experiments βCD, both when applied alone or in a synergistic combination with curcumin, resulted in reduced aggregation and even dissolution of pre-formed aggregates of α-synuclein. Secondary structural analysis showed that βCD reverted α-syunclein aggregates back to the native unstructured conformation of the protein [149]. Similar synergistic anti-aggregative and disaggregating effects were found between βCD and naturally occurring polyphenols (curcumin, resveratrol, baicalein and (-)-epigallocatechin gallate) even in the presence of macromolecular crowding agents mimicking more (patho)physiological conditions, and these effects were associated with impeded cellular toxicity of the prefibrillar α-synuclein aggregates on a mouse neuroblastoma cell line [150].
As can be seen, CD interaction mechanisms of human peptide hormones and amyloidforming proteins are similar to those described above for model oligopeptides, and usually involve inclusion of an aromatic residue. In most cases, the connection is further strengthened by hydrogen bonds and hydrophobic or van der Waals interactions with nearby amino acids. The CD-peptide interaction typically results in decreased aggregation tendency of the peptides, in some cases even dissolution of aggregates already formed, which can be favorably utilized in the medical practice as discussed in Sections 4.1 and 4.2.
AMP-Activated Protein Kinase
AMP-activated protein kinase (AMPK) is an evolutionarily conserved metabolic stress sensing protein kinase functioning as a critical focal point for whole-body and cellular mechanisms to maintain energy homeostasis, and therefore a promising drug target for the treatment of diabetes, obesity, and cancer. AMPK is typically activated by a drop in the ratio of ATP to AMP/ADP reflecting energy stress, which promotes ATP production by increasing the activity or expression of proteins involved in catabolism while conserving ATP by switching off biosynthetic pathways [151]. It is a heterotrimeric protein complex with an α subunit containing the serine/threonine kinase domain (KD), an adenine nucleotide sensor loop (α-RIM), a kinase activation loop and an autoinhibitory domain (AID). The β subunit acts as a subcellular targeting subunit and a molecular scaffold responsible for membrane binding while having a glycogen-binding domain, and the γ subunit with two pairs of AMP/ADP/ATP-binding cystathionine β-synthase-like (CBS) domains sensitively detects shifts in the AMP/ATP ratio (Figure 4) [152]. X-ray crystallographic examination of the glycogen-binding domain of the β subunit similar to the amylase domain structures described above in Section 3.2 revealed direct interactions with five glucose units of βCD in a carbohydrate-binding module (CBM). In the structure, the βCD was held in a pincer-like grasp with two tryptophan residues cradling two glucose units and a leucine residue piercing the ring of βCD. The first glucose moiety of AMPK (G1) was involved in stacking interactions with Trp100 and the O2 and O3 atoms formed hydrogen bonds with Asn150, while G2 was stacked against Trp133 and formed a hydrogen bond with Lys126. G7 participated in a water-mediated hydrogen bond with Gln124. In addition, Leu146 and Thr148 formed hydrophobic interactions with the G7-G1-G2 sugar units, and the O2 and O3 atoms of G4 and G5 created hydrogen bonds with Gln145 and Leu146. As a result, similarly to that observed in carbohydrate-binding proteins described in Section 3.2, the AMPK-βCD association was mediated by hydrophobic stacking interactions between the sugar and the aromatic side chains of the protein, and a network of direct and water-mediated additional hydrogen bonds and hydrophobic interactions between sugar units and protein residues [153]. Supporting the functional relevance of this interaction, in a cell-free assay, similarly to glycogen, βCD binding to the glycogen-binding domain resulted in an allosteric inhibition of AMPK enzyme activity with a half-maximal effect at 1.6 mM, which was abolished by mutating Trp100 and Trp133 residues involved in βCD-AMPK binding [154]. Subsequent studies using X-ray crystallography to compare low-resolution structures of non-phosphorylated and active phosphorylated holo-AMPK bound to AMP and βCD, and luminescence proximity assay revealed molecular details of AMPK activation. According to the suggested model, the AID binds to the KD arresting it in an inactive open conformation. In the AMP-bound active state, the AID rather interacts with the α-RIM, which is induced by AMP binding to CBS-3, thereby pulling away the AID and releasing inhibition of the KD. ATP counteracts activation by competitively inhibiting AMP binding and also by destabilizing AID-α-RIM interaction ( Figure 4 on the left). This process can be dynamically modulated by the CBM of the glycogen-binding domain (capable of βCD binding) that is suggested to bind the kinase domain in the active configuration and become dissociated in the inactive state. This association can be modulated as phosphorylation enhances, while the presence of glycogen or 2 mM βCD destabilizes the interaction. Consistently, mutation of the crucial Trp residue abolishes the effects of glycogen and βCD [152].
rather interacts with the α-RIM, which is induced by AMP binding to CBS-3, thereby pu ing away the AID and releasing inhibition of the KD. ATP counteracts activation by com petitively inhibiting AMP binding and also by destabilizing AID-α-RIM interaction (F ure 4 on the left). This process can be dynamically modulated by the CBM of the glycoge binding domain (capable of βCD binding) that is suggested to bind the kinase domain the active configuration and become dissociated in the inactive state. This association c be modulated as phosphorylation enhances, while the presence of glycogen or 2 mM βC destabilizes the interaction. Consistently, mutation of the crucial Trp residue abolishes t effects of glycogen and βCD [152]. In this configuration, t carbohydrate-binding module (CBM) of the β subunit (purple) is dissociated from the KD, and t γ subunit (red) binds ATP. In the active state (on the right), AMP induces binding of the nucleoti sensor loop (α-RIM) of the α subunit to the AMP-binding site on the γ subunit. This in turn pu the AID away from the inhibitory interaction with the KD. AMPK can also be activated by bindi of compounds to the CBM inducing its association with KD, which helps to stabilize the close active conformation of KD. CDs (blue truncated cones) were proposed to modulate the activati by direct binding to CBM. While βCD-CBM was shown to stabilize the inactive state [152], MβC treatment resulted in increased CBM-KD association leading to AMPK activation [155]. Elucidati of the functional effects of CDs and the mechanisms of their actions would facilitate further progr of CD application in Niemann-Pick type C disease, and possibly in other human AMPK-relat pathological conditions, such as diabetes, obesity, and cancer. Cellular thermal shift assay and isothermal dose-response fingerprint experimen further showed the association between AMPK β subunits and a CD derivative, MβC However, examination of the functional consequences of this association revealed that 1 µM MβCD in fact resulted in increased phosphorylation of AMPK α subunits and e vated phosphorylation of substrates referring to AMPK activation ( Figure 4 on the righ Consistent with the activation of AMPK and its involvement in the upstream regulati In this configuration, the carbohydrate-binding module (CBM) of the β subunit (purple) is dissociated from the KD, and the γ subunit (red) binds ATP. In the active state (on the right), AMP induces binding of the nucleotide sensor loop (α-RIM) of the α subunit to the AMP-binding site on the γ subunit. This in turn pulls the AID away from the inhibitory interaction with the KD. AMPK can also be activated by binding of compounds to the CBM inducing its association with KD, which helps to stabilize the closed, active conformation of KD. CDs (blue truncated cones) were proposed to modulate the activation by direct binding to CBM. While βCD-CBM was shown to stabilize the inactive state [152], MβCD treatment resulted in increased CBM-KD association leading to AMPK activation [155]. Elucidation of the functional effects of CDs and the mechanisms of their actions would facilitate further progress of CD application in Niemann-Pick type C disease, and possibly in other human AMPK-related pathological conditions, such as diabetes, obesity, and cancer. Cellular thermal shift assay and isothermal dose-response fingerprint experiments further showed the association between AMPK β subunits and a CD derivative, MβCD. However, examination of the functional consequences of this association revealed that 100 µM MβCD in fact resulted in increased phosphorylation of AMPK α subunits and elevated phosphorylation of substrates referring to AMPK activation ( Figure 4 on the right). Consistent with the activation of AMPK and its involvement in the upstream regulation of autophagy, this led to a restoration of impaired autophagy flux in various cellular models of Niemann-Pick type C disease. Molecular docking analysis confirmed the molecular details of binding and the involved AMPK amino acids proposed by earlier studies, as key hydrogen bonds with residues Lys126 and Asn150, and aromatic stacking interactions with Trp100 and Trp133 were conserved. However, when comparing MβCD binding to β1 and β2 subunits, slight differences were observed in the conformation of Trp100 and Leu146, two residues substantially involved in CD interactions. It was suggested that the degree and localization of CD substituents such as methylation in MβCD might promote or impair conformational shifts, and these effects can be distinct in different β subunits [155]. Considering these findings and the widely accepted potential role of another CD derivative, HPβCD, in Niemann-Pick type C disease therapy as discussed in Section 4.4, further understanding of AMPK-CD binding and its functional consequences depending on the degree and localization of CD substituents can be highly relevant in diseases associated with AMPK.
Bacterial Pore-Forming Proteins
Besides professional carbohydrate-binding enzymes, pore-forming proteins comprise the second major group of proteins that were previously described to extensively interact with CDs through direct binding. Such interactions were first proposed by studies examining the possible interactions between Staphylococcus aureus exotoxin α-haemolysin and CDs. Due to their size and steric characteristics, CDs were hypothesized to comfortably fit inside the pore of the heptameric α-haemolysin given that the outer diameter of CDs (12.7-14.0 Å, 14.6-15.5 Å and 17.6-17.5 Å for αCD, βCD and γCD, respectively) is comparable to the narrowest internal diameter (~14 Å) of the pore at the region of the Met113 residue. Consistently, planar bilayer recordings obtained with patch-clamp revealed that βCD can enter the channel and induce reversible partial blocks of the ionic current even at micromolar concentrations. The blocking kinetics were consistent with a single binding site inside the lumen of the channel and molecular modeling suggested that βCD can bind to the restriction site, which comprises Met113, Lys147 and Glu111 residues [156]. While the average residency time for the βCD in the lumen of the wild-type α-haemolysin pore was relatively short, site-directed mutagenesis showed that mutation of Met113 to Asp, Asn, Val, His, Phe or Tyr resulted in 10 4 -fold increases in occupancy time due to reduced dissociation rate constants without any changes in the association. Remarkably, the side chains of the latter six amino acids bear little resemblance to one another, which suggested the co-existence of alternative βCD binding modes [157]. Consistent with this hypothesis, single-channel electrical recording, protein engineering including unnatural amino acid mutagenesis, and high-resolution X-ray crystallography revealed different binding modes for three groups of tight-binding mutants that comprise at position 113: (i) hydrogen-bonding amino acids Asp or Asn, and possibly His; (ii) aromatics Phe, Tyr, and possibly His, and more weakly Trp; and (iii) the β-branched amino acid Val. In homoheptamers formed by Met113Asn, a representative mutant of the first group, primary hydroxyls on the top of the CD ring face the trans entrance of the pore. In each glucose unit of the βCD, the secondary 2-hydroxyl is hydrogen bonded to the side-chain amide of an Asn113, while the 3-hydroxyl is hydrogen bonded to the -amino group of Lys147 that is also bound to the carbonyl of Asn113 in a bifurcated manner. In Met113Phe, a representative of the second group, the βCD is in the opposite orientation as secondary hydroxyls on the bottom of the CD ring face the trans entrance and each 6-hydroxyl group is in stacking CH-π interactions with the aromatic Phe113 side chain. The existence of the above two distinct binding mechanisms was corroborated by experiments with α-haemolysin heteroheptamers, which showed that while in heteromers containing WT (Met113), Met113Asn and Met113Phe subunits, replacement of the Met gradually increased affinity for βCD, heteromers formed from similar numbers of Met113Asn and Met113Phe subunits can bind βCD only weakly confirming the "opposing" effects of the two residues. The α-haemolysin with Val113 can bind βCD in a third way, as in heteromers with Met113Val, both Met113Phe and Met113Asn reduce the affinity of the pore for βCD excluding both stacking CH-π and hydrogen bonds. It was suggested that Val side-chains interact with the sides of the glucose ring, which might occur in one or both orientations of the CD ring [158]. βCD lodging into the channel lumen of α-haemolysin can in turn alter the ion selectivity of the transmembrane pore as the originally weak anion selectivity is substantially enhanced by βCD in various mutants of the channel [159]. Molecular dynamics free energy simulations and potential of mean force calculations subsequently showed that the βCD can affect selectivity through locally reducing the pore radius and causing a partial desolvation of ions and affecting the orientation of nearby charged residues, mainly the ring formed by positively charged Lys147 side chains. These changes lead to an increased electrostatic interaction between the ion and the channel due to a reduction in dielectric shielding by the solvent, resulting in augmented anion selectivity [160]. Besides α-haemolysin, the function of other bacterial pore-forming proteins can also be modulated by CDs. For example, CymA of the outer membrane component of the CD uptake and metabolism system of Klebsiella oxytoca can also directly bind various CDs including αCD, βCD and γCD at a binding site located inside the pore of the channel, which results in a dose-dependent block of ion transport [161].
3.6. Human Pore-Forming Proteins 3.6.1. Connexins Pore-forming proteins of eukaryotic cells can also directly interact with CDs and these protein-CD associations were demonstrated to affect channel function as summarized in Table 1. In the first of such reports, measurements of urea and sucrose permeation using transport-specific fractionation identified CDs as reversible pore blockers for connexin channels composing gap junctions. In these experiments, purified rat or mouse connexin-32 (Cx32) and/or connexin-26 (Cx26) proteins were reconstituted into unilamellar phospholipid liposomes not containing cholesterol, and CD treatment typically in the range of 5-20 mM resulted in a reversible complete block of conductance. The characteristics of CDinduced inhibition changed as a function of the size of the CD relative to the pore diameter, as homomeric Cx32 channels having a wider limiting diameter were completely blocked by the smaller αCD and βCD according to a step-change nature of the block-concentration relation, while the larger γCD exerted an effect in a graded fashion with increasing CD concentration. Similarly, when the narrower homomeric Cx26 channels were examined, with increasing size of CD, the block changed from steep in the case of αCD to gradual in response to βCD, while the largest γCD was without substantial effect. CD effects on Cx26/Cx32 channels were intermediate in keeping with its limiting pore diameter between that of homomeric Cx32 and homomeric Cx26. These results were explained by a simple homogenous step-like block occurring via CD entry into the pore lumen and occlusion of the permeability pathway resulting from a perfect fit of smaller CDs into the pore (as for Cx32-αCD/βCD and Cx26-αCD complexes). However, if the external width of a CD exceeds the minimal pore width of connexin channels, the imperfect fit of CD can lead to a heterogeneity of less well-defined ligand-channel interactions with an imperfect lodging into the pore and/or sideways in multiple configurations, which is mirrored by the complex, graded inhibition (for Cx32-γCD and Cx26-βCD interactions). On the other hand, a too large CD can simply fail to enter the pore thus not cause any inhibition (as in the case of Cx32-γCD). These results suggested that, similarly with bacterial pore-forming proteins, in connexin channels the pore is the primary site of CD action. This hypothesis was also supported by potentiation of the block when organic analytes were sequestered in the hydrophobic interior of CDs [162]. While direct CD effects on channels are most extensively described in non-selective pore-forming proteins, these compounds can also interact with mildly or highly selective ion channels as well. Patch-clamp measurements on rat cultured hippocampal neurons and model simulations demonstrated that βCD modulated the function of GABA A (γ-aminobutyric acid type A) receptors, anion-selective ligand-activated channels responsible for neuronal inhibition in the adult brain (Table 1). While CDs generally inhibit channel function, βCD was found to increase GABA A receptor responses to ultrafast GABA applications, which was accompanied by a profound deceleration of current deactivation kinetics by slowing down the unbinding rate of the ligand and a decreased rate and extent of desensitization reflecting strong alterations in conformational transitions. βCD effects were attributed to direct interactions since the compound was applied at low concentrations (0.15-1.5 mM) at which depletion of membrane cholesterol is expected to be minor and changes were fully reversible in the given patch after an incubation of 2 min in the absence of βCD [163].
TASK Ion Channels
A recent study [164] found that MβCD directly blocked TASK(TWIK-related acidsensitive K + channel)-1 and TASK-3 channels, two members of the two-pore-domain potassium channels, which play central roles in modulating neuronal excitability in the central nervous system by providing voltage-independent background potassium currents [165]. As demonstrated by patch-clamp measurements in rat primary cultured cerebellar granule neurons and HEK293 cells heterologously expressing these channels, 5 mM of MβCD or non-cholesterol-depleting αCD reduced currents of TASK-1 and TASK-3 channels and the heterodimer TASK-1/TASK-3 by~40%, while the cholesterol-depleting agent filipin III exerted no effects, suggesting a direct blocking mechanism independent of cholesterol complexation (Table 1). MβCD exerted no inhibitory effects on TWIK-1 (tandem of pore domains in weak inward rectifier K + channel) and TRESK (TWIK-related spinal cord K + channel) currents. Consistently, molecular docking analysis identified residues potentially interacting with MβCD and αCD in the extracellular cavity close to the entry of TASK-1 channel, and another independent one in the intracellular cavity of the pore. The interacting amino acids in the most favorable binding mode at the extracellular site are Arg68 and Gly97 in the A chain and Glu37, Lys70, Trp184, Gly203, Asp204 and Lys210 in the B chain ( Figure 5A). Both the extracellular and intracellular binding sites are organized by a network of hydrogen bonds and hydrophobic interactions in a configuration similar to that described in Section 3.1.
K V 1.3 Ion Channel
Consistent with the pore-blocking ability of CDs in TASK channels [164], a recent study revealed that MβCD can bind the K V 1.3 ion channel and inhibit its current in a cholesterolindependent, ligand-like manner [42]. This channel has structural properties and gating mechanisms prototypical for most members of the voltage-gated potassium channel (K V ) superfamily, and pathophysiological relevance in various autoimmune and neurodegenerative disorders [166]. In this study [42] patch-clamp measurements demonstrated that MβCD dose-dependently and partially reversibly reduced K V 1.3 currents (5 mM MβCD reduced currents by~40%). The inhibition was apparent within 15 s and it was completed in 90 s (Table 1). Notably, according to time-resolved flow cytometry examination of the extraction of exogenously loaded cholesterol, no significant changes in membrane cholesterol level occurred within this time frame. In addition, non-cholesterol-complexing per(3,6-anhydro)-α-and -γCDs characterized by an inverted structure with a hydrophilic interior and a hydrophobic outer surface more potently decreased K V 1.3 currents. On the other hand, cholesterol-depleting HPβCD and HPγCD, and non-cholesterol-depleting per(3,6-anhydro)-βCD did not inhibit K V 1.3. These findings strongly suggested a cholesterol extraction-independent ligand-like CD action since it has been described in the literature that MβCD-induced cholesterol depletion increases K V 1.3 currents [85]. Furthermore, CD-induced effects on K V 1.3 showed no statistically significant correlations with alterations in membrane fluidity, hydration or lipid order further arguing against cholesterol-mediated mechanisms [42]. In the same study, in silico molecular docking analysis between MβCD and K V 1.3 supported potential direct binding of MβCD to the extracellular orifice of the pore domain. Multiple binding modes were recorded, which identified a common pattern of direct interactions mainly organized by His399, a residue representing a molecular target for pore-blocking tetraethyl-ammonium [167] and a variety of scorpion toxins [168]. The basis of interaction is provided by a hydrogen bond formed by His399, which is further strengthened by a network of hydrogen bonds and hydrophobic interactions with Gly396, Asp397 and Thr372 of the same subunit and stabilized by contacts with His399 and Gly396 of one neighboring subunit, and Gly396 and Asp397 of the opposing subunit ( Figure 5B) [42].
When comparing these molecular docking results with those obtained in TASK-1 [164], significant overlap can be observed between MβCD binding sites in the extracellular regions of their pore domains as indicated in Figure 5C. Comparing the two most favorable binding modes identified in the channels, we found that Gly396 and Asp397 residues of the K V 1.3 subunit containing the crucial His399, and Gly396 of the neighboring subunit are identical with Gly203 and Asp204 of the B chain, and Gly97 of the A chain of TASK-1. Besides these identical residues (yellow and orange, bold), the other highlighted amino acids (red in K V 1.3 and blue in TASK-1) involved in binding also suggest a highly similar extracellular MβCD binding pocket in the pore domains. While in the case of TASK-1, an intracellular MβCD binding site was also described, in K V 1.3 the possibility of such an intracellular site was ruled out based on the prompt current-inhibitory effect (significant current decrease after~15 s for K V 1.3 vs.~80-100 s for TASK-1). The fact that these structurally different channels share similar binding sites for MβCD proposes that CDs could possibly bind to a variety of other ion channels as well, and consequently modify their ionic currents, which is worth being investigated in the future in parallel with mutagenesis studies to confirm the functional relevance of the proposed identical binding residues. ) pore-forming S5 and S6 helices are visualized for each subunit (magenta) between residues 340 and 440. (C) Structural alignment between TASK-1 and KV1.3 ion channels were performed using PyMol. The region of the selectivity filters is indicated by an asterisk. Slight differences between the orientation of helices of the two channels can be attributed to the fact that the KV1.3 is with an open activation gate, while TASK-1 is in a closed conformation. Amino acids contributing to the MβCD binding are indicated by red spheres for KV1.3 [42] and blue spheres for TASK-1 [164]. Gly396 (yellow, bold) and Asp397 (orange, bold) residues of the KV1.3 subunit and Gly396 (yellow, bold) of the neighboring subunit are identical with Gly203 (yellow, bold) and Asp204 (orange, bold) of the B chain, and Gly97 (yellow, bold) of the A chain of TASK-1 as revealed by the structural alignment.
When comparing these molecular docking results with those obtained in TASK-1 [164], significant overlap can be observed between MβCD binding sites in the extracellular regions of their pore domains as indicated in Figure 5C. Comparing the two most favorable binding modes identified in the channels, we found that Gly396 and Asp397 residues of the KV1.3 subunit containing the crucial His399, and Gly396 of the neighboring subunit are identical with Gly203 and Asp204 of the B chain, and Gly97 of the A chain of TASK-1. Besides these identical residues (yellow and orange, bold), the other highlighted amino acids (red in KV1.3 and blue in TASK-1) involved in binding also suggest a highly similar extracellular MβCD binding pocket in the pore domains. While in the case of TASK-1, an intracellular MβCD binding site was also described, in KV1.3 the possibility of such an intracellular site was ruled out based on the prompt current-inhibitory effect (significant current decrease after ~15 s for KV1.3 vs. ~80-100 s for TASK-1). The fact that these structurally different channels share similar binding sites for MβCD proposes that CDs could possibly bind to a variety of other ion channels as well, and consequently modify their ionic currents, which is worth being investigated in the future in parallel with mutagenesis studies to confirm the functional relevance of the proposed identical binding residues.
Cyclodextrins as Anti-Aggregative Excipients in Peptide and Protein Drug Formulations
In the last decades, a continuously growing number of therapeutic peptide and protein drugs became available to combat a variety of human diseases. However, the application of such peptide-and protein-containing formulations is hampered by various fac- (C) Structural alignment between TASK-1 and K V 1.3 ion channels were performed using PyMol. The region of the selectivity filters is indicated by an asterisk. Slight differences between the orientation of helices of the two channels can be attributed to the fact that the K V 1.3 is with an open activation gate, while TASK-1 is in a closed conformation. Amino acids contributing to the MβCD binding are indicated by red spheres for K V 1.3 [42] and blue spheres for TASK-1 [164]. Gly396 (yellow, bold) and Asp397 (orange, bold) residues of the K V 1.3 subunit and Gly396 (yellow, bold) of the neighboring subunit are identical with Gly203 (yellow, bold) and Asp204 (orange, bold) of the B chain, and Gly97 (yellow, bold) of the A chain of TASK-1 as revealed by the structural alignment.
Cyclodextrins as Anti-Aggregative Excipients in Peptide and Protein Drug Formulations
In the last decades, a continuously growing number of therapeutic peptide and protein drugs became available to combat a variety of human diseases. However, the application of such peptide-and protein-containing formulations is hampered by various factors, including chemical, enzymatic and physical instability, poor absorption through biological membranes, rapid plasma clearance and immunogenicity. Among these, protein aggregation can be considered the most problematic, as it can happen at almost any stage of manufacturing, processing, storage, shipment and administration, and it can largely influence the other above-mentioned factors. These obstacles, particularly the unwanted aggregation, can be at least partially overcome with the use of adjuvants and CDs were shown as attractive alternatives for this purpose by acting as solubilizers, stabilizers, artificial chaperone mimics and absorption enhancers for a variety of substances [1,2,4,7,8,169].
Since peptides and proteins are generally too large to be wholly included in the cavity of CDs, these beneficial effects are rather mediated by the formation of inclusion complexes with solvent-accessible hydrophobic amino acids of peptide chains. Depending on the exact molecular arrangement, masking of these temporarily exposed hydrophobic residues by CDs may in turn influence the conformation, aggregation, folding, degradation, surface adsorption and, consequently, the functional activity of peptides. For example, inclusion of exposed hydrophobic residues can prevent their intermolecular interactions that are typically mediated by these amino acids, thereby providing the opportunity for an aggregation-prone partially unfolded intermediate to fold back to its native, functionally active form, protecting it from aggregation or adsorption [2,117,135].
Consistent with this hypothesis, mainly βCD and its derivatives such as MβCD, HPβCD and SBEβCD were found to reduce aggregation tendency of pharmaceutically relevant peptides and even through interaction with aggregated/denatured forms to induce their natural refolding as previously shown for insulin [139,170], hGH [138,171] or granulocyte colony-stimulating factor [137].
While CDs are invaluable tools for the pharmaceutic formulations of peptide and protein drugs, such applications are thoroughly reviewed elsewhere [2,169] and, therefore, their detailed description is beyond the scope of the current review. Thus, in the next subsections, we limit our discussion to a short analysis of potential therapeutic effects of CDs in human pathological conditions.
Cyclodextrins as Active Anti-Aggregative and Cholesterol-Depleting Agents in Human Amyloid-Related Neurodegenerative Diseases
The favorable anti-aggregative effects of CDs can be utilized in human amyloid-related diseases characterized by an accumulation of aggregation-prone cellular peptides and proteins capable of forming neurotoxic amyloid fibrils [142]. Alzheimer's disease is the most common neurodegenerative disorder that eventually leads to progressive dementia and it is casually linked to the extracellular deposition of aggregated fibrils built up by Aβ peptides [172,173]. CDs can interfere with various steps of Alzheimer's disease pathogenesis as reviewed recently [174]. As described in Section 3.3.2, these compounds can directly bind Aβ peptides, inhibit their aggregation and even induce altered morphology and break-up of pre-formed amyloid fibrils leading to reduced cytotoxicity [144,146,147]. Besides these anti-aggregative effects, lipid raft disruption is also highly relevant for potential favorable actions of CDs in Alzheimer's disease. Aggregation-prone Aβ peptides are produced from the amyloid precursor protein (APP) in the amyloidogenic pathway by sequential proteolytic degradation catalyzed by βand γ-secretase enzymes. Alternatively, APP is cleaved by α-secretase in the nonamyloidogenic pathway that prevents amyloid plaque formation. The two pathways are separated in space since the nonamyloidogenic cleavage happens in non-raft domains of the cell membrane, while amyloidogenic hydrolysis occurs in the endolysosomal compartments after lipid raft-mediated endocytosis from the cell surface [175,176]. In cellular models of the disease cholesterol extraction and the consequent lipid raft disruption in response to MβCD consistently reduced Aβ production that was accompanied by elevated levels of the neuroprotective products of nonamyloidogenic cleavage [177][178][179][180][181][182][183]. These effects were attributed to decreased proximity between elements (lipid rafts, APP, βand γ-secretase and endosomes) of the amyloidogenic pathway [179,180,182,184,185]. Cholesterol-MβCD treatments induced opposite effects [181,[184][185][186]. In keeping with favorable effects of cholesterol depletion in cellular studies, in vivo experiments demonstrated that cholesterol extraction with well-tolerated HPβCD alleviated clinical symptoms, histopathological alterations and autophagosomallysosomal abnormalities accompanied by enhanced clearance of Aβ peptides in animal models of Alzheimer's disease [187][188][189][190]. Based on the promising results obtained in in vitro and in vivo studies, a randomized, placebo-controlled, double-blind phase 2 clinical study was launched recently to assess the safety, tolerability, and potential efficacy of intravenous HPβCD infusion (500-1000 mg/kg every 28 days) in early Alzheimer's disease (NCT05607615).
Parkinson's disease, the second most frequent neurodegenerative disease, is pathogenically coupled to the misfolding and aggregation of α-synuclein resulting in neuronal loss especially in the dopaminergic neurons of substantia nigra [191][192][193]. As described in Section 3.3.2, in vitro experiments demonstrated that βCD can inhibit aggregation of αsynuclein and even dissolve its pre-formed aggregates [149], and cellular studies showed that this is accompanied by reductions in the toxicity of prefibrillar α-synuclein aggregates [150]. Furthermore, MβCD was found to lower α-synuclein accumulation in cellular and animal models of the disease [194]. While this effect was suggested to occur through cholesterol extraction, a subsequent study suggested an alternative mechanism of action by demonstrating that in a cellular Parkinson model 1 mM HPβCD activated TFEB (transcription factor EB), a major regulator of lysosomal functions. This resulted in a promotion of autophagic clearance of aggregated α-synuclein, suggesting potential beneficial CD effects via activation of the autophagy-lysosomal pathway [195].
Cyclodextrins as Active Cholesterol-Extracting Agents in Atherosclerosis
Atherosclerosis, a major cause of cardiovascular mortality worldwide, is caused by the subendothelial accumulation and sclerotic aggregation of cholesterol and other lipids in the wall of arteries and formation of macrophage-derived foam cells leading to chronic inflammation and life-threatening cardiovascular events. Considering the central role of cholesterol in the pathogenesis of the disease, cholesterol-extracting CDs can be regarded as potential therapeutic agents targeting various steps of the pathogenesis, as reviewed recently [174]. In accordance, using cellular models of the disorder various CDs, including βCD, MβCD and HPβCD were found to effectively induce cholesterol efflux from cells with elevated cholesterol levels [12,[196][197][198]. CDs can also reduce elevated cellular levels of 7-ketocholesterol and other oxysterols, major products of cholesterol oxidation that accumulate in plaques and play important roles in disease pathogenesis [199]. CDs are able to favorably influence the inflammatory components of atherosclerosis as well by reducing adhesion of immune cells to endothelial cells by decreasing expression of cell adhesion molecules of the latter [200], limiting enhanced proliferation and cytokine secretion of activated lymphocytes [201], modulating cholesterol crystal-induced complement activation, reactive oxygen species production and proinflammatory cytokine and chemokine secretion of immune cells [202], and inhibiting foam cell formation from macrophages [203,204]. While all these effects induced by CDs typically applied at concentrations between 1 and 10 mM were previously attributed to cholesterol complexation, a potential contribution of direct actions on proteins involved in the regulation of cellular metabolism or pro-and anti-inflammatory cascade pathways has not been examined yet.
In vivo studies also corroborated the potential use of cholesterol-complexing CDs in atherosclerosis. In an early study, intravenous or parenteral HPβCD reduced serum cholesterol levels and aortic atherosclerotic lesions in rabbits with hyperlipidemia of genetic origin [205] and improved intracellular cholesterol distribution in Kupffer cells in LDLR (low-density lipoprotein receptor) knockout mice on a high-fat high-cholesterol diet [206]. Intraperitoneal application of MβCD resulted in normalized serum lipid profiles, reduced aortic plaque lesions and decreased intraplaque inflammation in apolipoprotein E-deficient mice on a high-cholesterol diet [201]. Similar effects were found in New Zealand white rabbits on a high-fat diet after oral HPβCD [207]. In apolipoprotein E-knockout mice on a cholesterol-rich diet HPβCD applied subcutaneously solubilized extra-and intracellular cholesterol crystals in macrophages, prevented the formation of atherosclerotic lesions in the aorta and even induced regression of established advanced plaques. These effects were accompanied by complex liver X receptor-dependent transcriptional reprogramming of macrophages leading to their stimulated reverse cholesterol transport and attenuated inflammatory phenotype [208]. While exact mechanisms of CD-induced effects in atherosclerosis and their applicability in the human disease are unknown, promising results of these preclinical studies propose CDs as potentially efficient therapeutic alternatives in the disease. An encouraging direction of development is represented by nanoscopic CD formulations, such as luminol-conjugated βCD with good tolerability and efficient cellular internalization through the endo-lysosomal system, which was shown to efficiently inhibit proinflammatory cytokine production of macrophages in cellular studies and alleviate plaque injury and inflammation in a mouse model [209]. In apolipoprotein E-deficient mice, βCD polymers with a diameter of approximately 10 nm showed superior characteristics when compared to monomeric HPβCD in terms of better pharmacokinetics, plaque targeting and tolerability [210]. Affinity-driven cargo-switching nanoparticles composed of a core made of an MβCD-simvastatin inclusion complex and a shell of phospholipids demonstrated improved pharmacokinetics, more extensive colocalization with macrophages and cholesterol crystals in plaques, better clinical efficacy to dissolve cholesterol crystals and reduce plaque growth, and in cases of chronic application, even dissolution of existing lesions [211].
Cyclodextrins as Active Cholesterol-Extracting Agents and Direct Modulators of Protein Function in Niemann-Pick Type C Disease
Niemann-Pick type C is a rare, monogenic lysosomal storage disease characterized by the accumulation of free unesterified cholesterol especially in the late endosomes and lysosomes (LE/LY) of cells in both peripheral tissues (mostly liver, spleen and lung) and in the central nervous system typically leading to progressive neurodegeneration, severe neurological symptoms and eventually an early death. The disorder is caused by lossof-function mutations in NPC1 or NPC2 proteins normally involved in the transfer of free cholesterol out of LE/LY towards the endoplasmic reticulum or the cell membrane. The lack of NPC1 or NPC2 activity results in the disruption of intracellular trafficking and consequent accumulation of free unesterified cholesterol mainly in LE/LY, which is accompanied by enhanced cholesterol uptake and endogenous synthesis [212][213][214]. Cellular defect of autophagy represents another characteristic alteration associated with Niemann-Pick type C disease, which typically manifests as impaired autophagosomelysosome fusion and consequent accumulation of autophagosomes contributing to neuronal damage [155,215].
Given that cholesterol accumulation is pathognomic for Niemann-Pick type C and βCDs can efficiently form inclusion complexes with cholesterol it is reasonable to assume that these compounds can represent biologically relevant therapeutic tools by depleting the accumulated cholesterol in the disease [174]. βCD-mediated cholesterol extraction can occur through direct binding either at the plasma membrane leading to replenishment from intracellular pools eventually decreasing cholesterol levels in LE/LY, or directly in LE/LY after the cellular entry of βCDs via pinocytosis or others form of endocytosis. Consistent with this hypothesis, studies using cellular Niemann-Pick type C models demonstrated beneficial effects of βCDs including HPβCD and MβCD typically applied at concentrations between 100 µM and 1 mM. In human fibroblast cell lines with NPC1 or NPC2 deficiency, HPβCD and more potently MβCD, decreased LE/LY cholesterol accumulation and experiments suggested that cholesterol complexation by these βCDs mainly occurs in LE/LY and not in the plasma membrane [216]. Similarly, MβCD and HPβCD ameliorated lysosomal cholesterol accumulation in primary cultured neurons and glial cells from NPC1 mutant mice [217], human induced pluripotent cells carrying NPC1 mutation differentiated towards neural stem cells [218] and hepatic cells [219]. Based on experimental results, βCDs can actually act as direct shuttle for cholesterol towards the endoplasmic reticulum for esterification [220] or to the cell membrane and subsequently to the extracellular space [221], thereby filling in the role of mutant NPC1 or NPC2.
While the above-mentioned studies proposed cholesterol complexation as the principal mechanism of βCD action in Niemann-Pick type C disease, subsequent reports demonstrated that these compounds could activate alternative signaling pathways through the direct modulation of protein function, which finally result in decreasing lysosomal cholesterol levels [174]. One such mechanism can be the restoration of impaired autophagy flux. In NPC1 patient-derived fibroblasts, and induced pluripotent stem cells differentiated into neurons, 100 µM MβCD was found to activate AMPK via direct binding to its β subunits as discussed in detail in Section 3.4, which in turn activated downstream signaling and restored the impaired autophagosome-lysosome fusion and autophagy flux. These changes were accompanied by decreases in cellular cholesterol levels, which may also partially result from AMPK activation-induced ABCA1 (ATP binding cassette transporter A1)-mediated cholesterol efflux or inhibition of sterol-regulatory element-binding proteins (SREBPs). MβCD-induced cholesterol reduction was nearly abolished after knockdown of AMPK β subunits or treatment with AMPK inhibitor, while it was mimicked by AMPK activators, supporting the central role of AMPK in MβCD effects [155]. Another mechanism related to βCD effects on proteins was demonstrated by cellular studies in which 700 µM HPβCD induced cholesterol secretion from LE/LY into the extracellular space via a mechanism requiring the activation of MCOLN-1 (mucolipin-1 or TRPML1 (transient receptor potential mucolipin 1)) lysosomal calcium channels [222]. A recent study using NPC1-deficient cells and a metabolically traceable cholesterol derivative followed the route of the exogenously applied cholesterol and suggested that the lysosomal cholesterol secretion induced by HPβCD applied at the concentration of 500 µM involves trafficking to the plasma membrane and a transfer of cholesterol to extracellular lipoproteins. In the absence of these acceptors, cholesterol can be rather re-esterified in the endoplasmic reticulum [223]. Recently, proteomic comparison of NPC1 patient-derived and wild-type fibroblasts identified the lysosome-associated membrane protein 1 (LAMP-1) as a target of CD action since it was induced by 1 mM HPβCD and suggested to replace the function of mutant NPC1 protein to facilitate cholesterol export from the LE/LY compartments [224]. As demonstrated by these studies, additional mechanisms of action involving direct protein targets might synergistically complement cholesterol sequestering effects of βCDs to alleviate NPC1 alterations; however, such processes are not taken into consideration in human clinical studies. Interestingly, another CD derivative, HPγCD applied at 1 mM can reduce cholesterol levels in experimental models of NPC [224][225][226] in spite of its much lower ability to form inclusion complexes with cholesterol [11]. Furthermore, in NPC1 patient-derived fibroblasts 1 mM HPγCD (but not HPβCD) was able to activate TFEB, a master regulator of lysosomal functions, which resulted in an increase in lysosome-endoplasmic reticulum association and simultaneously enhanced the impaired autophagy-lysosomal pathway [227]. Favorable effects of HPγCD further underlines the importance of protein-mediated actions of CD derivatives in Niemann-Pick type C disease.
The therapeutic potential of CDs was demonstrated not only in cellular Niemann-Pick type C models but in vivo studies as well. In such cases, HPβCD is more frequently applied because of its better in vivo tolerability. In animal Niemann-Pick type C models, HPβCD-induced decreases in lysosomal cholesterol levels, reduced neurodegeneration and concomitant improvements in lifespan, and delays in the occurrence of symptoms were demonstrated after a single subcutaneous dose [228,229], chronic subcutaneous [230][231][232], intraperitoneal [230,233] or intrathecal [233] administration, or a combined subcutaneous and intrathecal application [234,235]. Based on promising data obtained in cellular and animal studies, HPβCD recently became involved in many clinical trials. In the first clinical cases, it was applied intravenously at doses as high as 2500 mg/kg/week, however, without significant stable improvements in the neurological status due to poor penetration through the blood-brain barrier [236][237][238]. Therefore, subsequent studies applied intrathecal (via lumbar injection) and intracerebroventricular (via an Ommaya reservoir at a dose of 200 to 400 mg every two weeks) administrations to deliver HPβCD to the central nervous system and better results were observed [239,240]. Due to its effectiveness and the lack of an FDA-approved drug to treat Niemann-Pick type C disease in the United States, FDA granted an orphan drug status to HPβCD for the treatment of Niemann-Pick type C, and it is a current subject of various ongoing clinical trials examining the safety, tolerability, pharmacokinetics and efficacy of two different HPβCD formulations (Trappsol ® Cyclo™ or VTS-270 having degrees of substitutions of~7 and~4.3, respectively) to alleviate neural and hepatic manifestations ( Table 2). The applicability of HPβCD is limited by its side effects including tinnitus, chemical meningitis, renal toxicity, psychiatric symptoms, fever and the most extensively studied adverse reaction, sensorineural hearing loss [238,241,242]. As demonstrated by animal studies, such side effects could be attenuated by the application of HPγCD, SBEβCD or SBEγCD; however, the therapeutic efficiency of these derivatives is smaller than that of HPβCD [231]. While current CDs and treatment regimes show promising results, further studies are required to enhance the potential of CDs to treat Niemann-Pick type C disease. Possible routes of development involve optimization of treatment protocols, for example, through combined intravenous and intrathecal administration [243], utilization of other βCD derivatives [244,245], application of CD macromolecules such as covalently linked derivatives [246], epichlorohydrin-derived, stable HPβCD crosslinks [247] or noncovalent tethering into a linear polymeric polyrotaxane chain [248], which can provide better pharmacokinetic profiles, more efficient penetration through the blood-brain barrier and even lysosomal targeting. Further understanding of the detailed molecular mechanisms of CD actions including their effects on pathophysiologically relevant protein functions would substantially help the design of more effective CDs and application schemes.
Conclusions
Due to their unique structure characterized by a hydrophilic outer surface and a hydrophobic cavity, CDs can associate with a variety of biological macromolecules, which provides the basis for their widespread industrial and pharmaceutical applications. While the molecular background of their utilization as excipients in drug formulations is generally well known, their potential use as active therapeutic agents is scarcely documented in spite of their ability to bind cholesterol and proteins. As summarized in Figure 6, favorable effects of CDs of potential therapeutic relevance can be based on three different mechanisms. First, CDs can form inclusion complexes with aggregation-prone hydrophobic groups of molecules resulting in solubilizing and anti-aggregative effects that can be utilized in peptide and protein drug formulations or in amyloid-related disorders such as Alzheimer's or Parkinson's disease. Second, through complexation, CDs can deplete membrane cholesterol. Based on this cholesterol-complexing ability, HPβCD was the first CD applied as an FDA approved active agent under the designation of an orphan drug in the therapy of Niemann-Pick type C disease. In parallel with cholesterol depletion, the disruption of lipid raft microdomains serving as signaling platforms can result in substantial alterations in biophysical parameters and lateral organization of the cell membrane, which can in turn indirectly modify the functional activity of proteins. However, such mechanisms of action represent currently completely unexploited therapeutic aspects of CDs. Third, CDs can directly bind proteins having an appropriate configuration of amino acids suitable for forming a CD binding site, such as those in AMPK, amyloid-forming β-amyloid peptides and α-synuclein, or pore-forming connexin, TASK-1 and K V 1.3 channels. These direct CD-protein associations are generally mediated by a stacking inclusion between the CD inner cavity and an interacting central aromatic residue, and a network of hydrogen bonds, hydrophobic and van der Waals interactions with certain amino acids with appropriate configuration in sterical proximity in the three-dimensional structure. These direct effects can be biologically relevant even in pharmaceutical applications of CDs as excipients or therapeutically active agents in Niemann-Pick type C disease when local concentrations in the millimolar range are reached. Such millimolar CD levels can modify protein functions, as demonstrated in AMPK, TFEB and channels including connexin, K V 1.3 and TASK. While anti-aggregative and membrane cholesterol-lowering properties are recognized to a certain degree in the literature of human diseases, indirect and direct mechanisms of protein function modulation are almost completely neglected by such studies. While CDs are considered well-tolerated and safe agents in vivo, still unexplored direct protein effects can not only be therapeutically beneficial, but they can even contribute to side effects as off-target actions, which could hinder their autonomous therapeutic use potentially necessitating the development of selective CD derivatives. Examples of CD-mediated functional effects on proteins collected in this review suggest that deeper understanding of molecular patterns of direct and indirect CD-protein interactions can reveal currently unexplored protein targets and pathological conditions where CDs can be efficiently utilized. | 21,663.6 | 2022-11-22T00:00:00.000 | [
"Biology",
"Chemistry"
] |
Characterization of the Interactions between the Nucleoprotein and the Phosphoprotein of Henipavirus*
The Henipavirus genome is encapsidated by the nucleoprotein (N) within a helical nucleocapsid that recruits the polymerase complex via the phosphoprotein (P). In a previous study, we reported that in henipaviruses, the N-terminal domain of the phosphoprotein and the C-terminal domain of the nucleoprotein (NTAIL) are both intrinsically disordered. Here we show that Henipavirus NTAIL domains are also disordered in the context of full-length nucleoproteins. We also report the cloning, purification, and characterization of the C-terminal X domains (PXD) of Henipavirus phosphoproteins. Using isothermal titration calorimetry, we show that NTAIL and PXD form a 1:1 stoichiometric complex that is stable under NaCl concentrations as high as 1 m and has a KD in the μm range. Using far-UV circular dichroism and nuclear magnetic resonance, we show that PXD triggers an increase in the α-helical content of NTAIL. Using fluorescence spectroscopy, we show that PXD has no impact on the chemical environment of a Trp residue introduced at position 527 of the Henipavirus NTAIL domain, thus arguing for the lack of stable contacts between the C termini of NTAIL and PXD. Finally, we present a tentative structural model of the NTAIL-PXD interaction in which a short, order-prone region of NTAIL (α-MoRE; amino acids 473–493) adopts an α-helical conformation and is embedded between helices α2 and α3 of PXD, leading to a relatively small interface dominated by hydrophobic contacts. The present results provide the first detailed experimental characterization of the N-P interaction in henipaviruses and designate the NTAIL-PXD interaction as a valuable target for rational antiviral approaches.
Hendra virus (HeV), 3 the first known member of the genus Henipavirus within the Paramyxoviridae family, emerged in 1994 as the causative agent of a sudden outbreak of acute respiratory disease in horses in Brisbane, Australia. Nipah virus (NiV), the second known member of the genus Henipavirus, came to light as the etiologic agent of an outbreak of respiratory and central nervous system disease in pigs and humans in Malaysia in 1998 through 1999. The initial NiV outbreak in Malaysia resulted in 265 human cases of encephalitis, including 105 deaths. The virus reemerged in Bangladesh in 2001, and outbreaks of encephalitis have occurred in that country almost every year since, with a case fatality rate approaching 75% (see (1) and references cited therein).
Although the genome of HeV and NiV shares the same overall organization of members of the Paramyxovirinae subfamily, a few distinctive properties, including their much larger size, led to the creation of the Henipavirus genus to accommodate these newly emerged zoonotic viruses (2). Currently this genus contains two virus species and a number of strains isolated from humans, bats, horses, and pigs over a wide geographic area and during a period of 10 years. Notably, henipaviruses have recently also been found outside of Australia and Asia, thus extending the number of endemic regions of one of the most pathogenic virus genera known in humans (3). The susceptibility of humans, the wide host range, and interspecies transmission, together with the absence of therapeutic agents, led to the classification of HeV and NiV as biosecurity level 4 (BSL4) pathogens (4).
As in all Mononegavirales members, the negative-strand, non-segmented RNA genome of Henipavirus is encapsidated by the nucleoprotein (N) within a helical nucleocapsid that has the characteristic herringbone-like structure typically observed in other Paramyxoviridae members (5)(6)(7)(8)(9)(10). This helical nucleocapsid, rather than naked RNA, is the substrate used by the polymerase complex during both transcription and replica-tion. Minigenome replicon studies showed that in henipaviruses the nucleoprotein, the phosphoprotein (P) and the large protein (L) proteins are necessary and sufficient to sustain replication of viral RNA (11). By analogy with other Paramyxoviridae members, the polymerase complex is assumed to consist of the L protein and the P protein, with this latter serving as a tether for the recruitment of L onto the nucleocapsid template. As in all Mononegavirales members, Henipavirus N and P proteins have been shown to interact with each other being able to form both homologous and heterologous N-P complexes (12). In addition, recent studies by Omi-Furutani et al. (13) allowed NiV N and P proteins to be visualized in live cells and unveiled their co-localization in the cytoplasm.
The genome organization of Henipavirus resembles that of the Respirovirus and Morbillivirus genera. The extra length of the Henipavirus genome arises mainly from additional unique, long untranslated sequences at the 3Ј-end of five of the six genes. Despite the much larger genome size of henipaviruses, the genome length is divisible by 6, and reverse genetics studies have confirmed that NiV obeys the "rule of six" (i.e. the genome length must be a multiple of 6 to replicate efficiently) (11). Overall, the proteins of henipaviruses share the same features as cognate proteins in the Paramyxovirinae subfamily. The Henipavirus P protein however is significantly larger, with a larger P N-terminal domain accounting for the extra length (14).
So far, structural and molecular information on Henipavirus proteins is scarce. Indeed high-resolution structural data are limited to their surface proteins, where crystallographic studies led to the determination of the three-dimensional structure of Henipavirus fusion (F) and attachment (G) proteins (15)(16)(17)(18). As for the N and P proteins, the only available data come from studies carried out by Chan et al. (12) and from our recently published studies (14). Although Chan et al. (12) reported the bacterial expression of Henipavirus N and P proteins and performed interaction studies by protein-blotting protein-overlay assays that led to the mapping of the reciprocal N-P binding sites, those studies did not embrace any biochemical characterization of the proteins. On the other hand, in our previous studies, by combining computational and experimental approaches, we deciphered the modular organization of Henipavirus N and P proteins and showed that the C-terminal region of N (N TAIL ; amino acids 400 -532) and the N-terminal region of P (amino acids 1-404/406) belong to the family of intrinsically disordered proteins (IDPs), although they both contain short, orderprone segments (14). The occurrence of some residual transient secondary and/or tertiary structure within the N TAIL and the N-terminal disordered domain of P led to their classification within the premolten globules (PMG) subfamily within the family of IDPs (19 -24). IDPs are ubiquitous proteins that lack highly populated secondary and tertiary structure under physiological conditions and in the absence of a partner/ligand (25) (for recent reviews on IDPs, see Ref. 26 -30). IDPs exist as dynamic ensembles of interconverting conformers (31,32).
Many IDPs have been shown to undergo a disorder-to-order transition upon binding to a partner, a phenomenon termed "induced folding" or "folding coupled to binding" (23,(33)(34)(35)(36)(37)(38)(39). IDPs recognize their partner(s) through molecular recognition elements (MoREs); these are short, order-prone regions within intrinsically disordered regions with a propensity to undergo induced folding upon binding to partners (40 -43). Using bioinformatics approaches, we have previously identified, within both the HeV and NiV N TAIL domains, four putative MoREs, with at least two of them (amino acids 408 -422 and 473-493) exhibiting a clear ␣-helical nature (14). By analogy with the closely related measles virus (MeV) (44 -55), we have previously speculated that the C-terminal X domain of the Henipavirus P protein (P XD ) may constitute a possible partner of Henipavirus N TAIL , with the MoREs of this latter being involved in partner recognition (14).
In the present study, we report the bacterial expression, purification, and characterization of P XD from both HeV and NiV and show that they both are structured and have a predominant ␣-helical content. We also show that the X domains of Henipavirus P proteins bind to the intrinsically disordered N TAIL domain of the nucleoprotein, thereby providing a means to tether P onto the nucleocapsid template. We provide evidence for the disordered nature of N TAIL domains bseng also in the context of the full-length N proteins, and show that binding to P XD triggers ␣-helical folding of N TAIL . The present studies, beyond confirming the predicted modular organization of Henipavirus P proteins, provide the first detailed experimental characterization of the N-P interaction and highlight the importance of disorder and induced folding in molecular recognition by Paramyxoviridae proteins.
EXPERIMENTAL PROCEDURES
Construction of Expression Plasmids-The Henipavirus N and P XD constructs, encoding full-length N (residues 1-532) and residues 660 -709 (NiV) or 657-707 (HeV) of P, with a hexahistidine tag fused to their C termini, were obtained by PCR using either Pfx (Stratagene) or Phusion (Finnzymes) polymerase and synthetic N and P genes (GenScript), optimized for the expression in Escherichia coli, as templates. Primers (Operon) were designed to introduce a hexahistidine tag encoding sequence at the 3Ј-end of the DNA fragments, as well as an AttB1 and AttB2 sites at the 5Ј-and 3Ј-ends, respectively. The rationale for the choice of the tag position was to avoid purification of truncated forms arising from possible abortive translation. After digestion with DpnI (New England Biolabs) to remove the methylated DNA template and purification (PCR purification kit, Qiagen), the PCR products were cloned into the pDest14 vector (Invitrogen) using the Gateway recombination system (Invitrogen).
The Henipavirus pDest14/N TAILHN constructs encoding residues 400 -532 of N with a hexahistidine tag fused to their N termini have been described (14). The NiV and HeV N TAIL F527W constructs, encoding N-terminally hexahistidine tagged N TAIL bearing a F527W substitution, were obtained by PCR using pDest14/N TAILHN (encoding for either NiV or HeV N TAIL, respectively) as template, Turbo-Pfu polymerase (Stratagene), and a pair of complementary mutagenic primers of 39 nucleotides in length (Operon). After digestion with DpnI to remove the methylated DNA template, the amplified PCR product was used to transform E. coli.
Selection and amplification of DNA constructs was carried out using CaCl 2 -competent E. coli TAM1 cells (Active Motif). The sequence of the coding region of all expression plasmids was verified by sequencing (GATC Biotech) and found to conform to expectations.
Bacterial Expression and Purification of Henipavirus N, P XD , and N TAIL Constructs-Expression of Henipavirus N and N TAIL constructs was carried out as described previously (14). The expression of P XD constructs was carried out by growing the E. coli Rosetta (DE3) pLysS strain (Novagen) in 2YT medium (Triptone 16 g/liter, yeast extract 10 g/liter and NaCl 5 g/liter).
Isotopically labeled ( 15 N) N TAIL samples were prepared by growing transformed Rosetta pLysS (Stratagene) cells in a 3-liter fermenter (MiniFors) at 37°C with minimal batch medium (56) containing 100 g/ml ampicillin and 34 g/ml chloramphenicol and supplemented with 15 NH 4 Cl (1 g/liter), and glucose (2 g/liter). A 300-ml preculture grown overnight to saturation in LB medium containing 100 g/ml ampicillin and 34 g/ml chloramphenicol was harvested, washed in minimal batch medium, and inoculated into the fermenter. When A 600 nm was between 0.8 and 1.0, protein expression was induced by the addition of 1 mM isopropyl -D-thiogalactopyranoside, and the cells were grown overnight at 37°C. The induced cells were harvested, washed, and collected by centrifugation (5000 ϫ g, 10 min). The resulting pellets were frozen at Ϫ20°C.
All recombinant proteins were purified using the protocol already described for Henipavirus wt N TAIL proteins (14) with minor modifications. Briefly, cellular pellets were resuspended in 5 volumes (v/w) of buffer A (10 mM Tris/HCl, pH 7.5, 300 mM NaCl, 10 mM imidazole, and 1 mM PMSF) supplemented with 0.1 mg/ml lysozyme, 10 g/ml DNase I, 20 mM MgSO 4 , and protease inhibitor mixture (either one tablet (Roche Applied Science)/50 ml of bacterial lysate or 1 ml (Sigma)/25 ml of bacterial lysate depending on whether standard or isotopically labeled proteins were purified, respectively). After a 20-min incubation with gentle agitation, the cells were disrupted by sonication (using a 750W sonicator and four cycles of 30 s each at 45% power output). The lysate was clarified by centrifugation at 30,000 ϫ g for 30 min. Starting from a 1-liter culture, the clarified supernatant was incubated for 1 h with gentle shaking with 2 ml of chelating Sepharose Fast Flow resin preloaded with Ni 2ϩ ions (GE Healthcare) equilibrated previously in buffer A. The resin was washed with buffer A supplemented with 20 mM imidazole, and the recombinant protein was eluted in buffer A supplemented with 250 mM imidazole. Eluates were analyzed by SDS-PAGE for the presence of the desired protein product. The fractions containing the recombinant protein were combined and then loaded onto either a Superdex 200 HR 16/60 column (N and N TAIL proteins; GE Healthcare) or a Superdex 75 HR 16/60 column (P XD proteins). In the case of isotopically labeled N TAIL samples, a protease inhibitor mixture (Sigma) was added (1 l/ml of protein solution) prior to size-exclusion chromatography (SEC). The elution buffer for N TAIL and P XD proteins was either 10 mM sodium phosphate, pH 7, or 10 mM Tris/HCl, pH 7.5, in both cases supplemented with 200 mM NaCl. N proteins were eluted in 10 mM Tris buffer, pH 8, and 300 mM NaCl. Note that in the case of Henipavirus wt N TAIL proteins, the elution from the SEC column was followed by monitoring the absorbance at 254 nm instead of 280 nm because of the lack of Trp and Tyr residues.
The proteins were concentrated using a Centricon Plus-20 (molecular cutoff of 3,000 Da for P XD , 5,000 Da for N TAIL , and of 10,000 Da for N) (Millipore). A protease inhibitor mixture (Sigma) was added (1 l/ml of protein solution) to concentrated 15 N-labeled samples before storage. All proteins were stored at Ϫ20°C either in the absence (N TAIL ) or presence of glycerol (10% for P XD and 20% for N). Dialysis D-tubes (molecular cutoff of 3,500 Da) (Novagen) were used to exchange the buffer and adjust it to the ensuing analyses. All purification steps, except for gel filtrations, were carried out at 4°C.
The apparent molecular mass of proteins eluted from preparative SEC columns was deduced from a calibration carried out with low molecular weight calibration kits (GE Healthcare). The hydrodynamic radius of a protein (Stokes radius (R S )) can be deduced from its apparent molecular mass (as seen by SEC) (57). The theoretical Stokes radii (in Å) of a natively folded (R S NF ), fully unfolded, random coil state in urea (R S U ), and natively unfolded PMG (R S PMG ) protein with a theoretical molecular mass (MM theo ) (in daltons) were calculated according to Uversky (34) as follows.
Protein concentrations were estimated using the BCA protein assay reagent (Pierce), because estimations based on the theoretical absorption coefficients at 280 nm, as obtained using the program ProtParam at the ExPASy server, were found not to be fully reliable. The presence of RNA in Henipavirus N samples was assessed as it follows. The theoretical ratio of absorptions at 260 versus 280 nm of a sample composed by 95% protein and 5% nucleic acid is 1.06, whereas it is 0.57 for a nucleic acid-free protein sample (58). In the nucleocapsid, because each N monomer (59 kDa) binds six ribonucleotides (330*6 ϭ 1980 Da) (11), N represents 96% of the total nucleocapsid mass. Accordingly, the A 260 /A 280 ratio of N samples containing RNA is expected to be close to 1.06 (see also Ref. 5).
Analytical SEC Combined with On-line Multi-angle Laser Light Scattering and Refractometry (SEC-MALLS-RI)-Analytical SEC was carried out on a high-pressure liquid chromatography system (Alliance 2695, Waters) using silica-based columns (Shodex). A 15-ml KW-802.5 column was used for the characterization of P XD and N TAIL proteins as well as for monitoring complex formation between N TAIL and P XD . Proteins were eluted with a 10 mM Tris/HCl, pH 7.5, and 200 mM NaCl buffer at a flow of 0.5 ml/min. Separation was performed at room temperature. Typically, 30 l of a protein solution in the 0.3-1.5 mM concentration range was injected. Detection was performed using a triple-angle light-scattering detector (MiniDAWN TM TREOS, Wyatt Technology), a quasi-elastic light-scattering instrument (Dynapro TM , Wyatt Technology), and a differential refractometer (Optilab rEX, Wyatt Technol-ogy). Molecular mass and R S determinations were performed by the ASTRA V software (Wyatt Technology) using a dn/dc value of 0.185 ml/g. The column was calibrated with proteins of known Stokes radii and molecular masses.
Limited Proteolysis of Henipavirus N-Proteolysis of purified N proteins (each at 16 M) was performed in 10 mM Tris/HCl buffer, pH 8, at room temperature with trypsin (Promega Corp.). The final enzyme:substrate molar ratio was 1:400. The extent of proteolysis was evaluated by SDS-PAGE analysis of 10-l aliquots that were removed from the reaction mixture over a time course (0, 2, 5, 10, 20, and 60 min), added to 10 l of 2ϫ Laemmli sample buffer, and boiled for 5 min to inactivate the protease.
Mass Spectrometry (MALDI-TOF)-Mass analysis of all Henipavirus proteins was performed using an Autoflex II TOF/ TOF. Spectra were acquired in the linear mode. Samples (0.7 l containing 15 pmol) were mixed with an equal volume of sinapinic acid matrix solution, spotted on the target, and then dried at room temperature for 10 min. The mass standard was either myoglobin or BSA depending on whether N TAIL and P XD or N proteins were analyzed, respectively. Proteins were analyzed in the Autoflex matrix-assisted laser desorption ionization/time of flight (MALDI-TOF; Bruker Daltonics, Bremen, Germany).
The identity of all purified Henipavirus proteins was confirmed by mass spectral analysis of tryptic fragments. The latter was obtained by digesting (with 0.25 g of trypsin) 1 g of purified recombinant protein obtained after separation onto SDS-PAGE. The tryptic peptides were analyzed as described above, and peptide fingerprints were obtained and compared with an in silico protein digest (Biotools, Bruker Daltonics). The mass standards were either autolytic tryptic peptides or peptide standards (Bruker Daltonics).
Circular Dichroism (CD)-CD spectra were recorded at 20°C on a Jasco 810 dichrograph equipped with a Peltier thermoregulation system, using either 1-mm (N TAIL F527W variants) or 0.01-mm (wt N TAIL , P XD and wt N TAIL ϩ P XD mixtures) thick quartz cells. The buffer was either 10 mM sodium phosphate, pH 7, for N TAIL F527W, or 10 mM Tris/HCl, pH 7.5, and NaCl 200 mM for wt N TAIL , P XD , and wt N TAIL ϩ P XD mixtures. CD spectra were measured between 190 and 260 nm with a scanning speed of 20 nm/min and a data pitch of 0.2 nm. Spectra were averaged from three scans. Moreover, for each protein sample, at least three independent acquisitions were carried out so as to estimate the experimental error arising from sample preparation. The contribution of buffer was subtracted from experimental spectra. Spectra were smoothed using the "means-movement" smoothing procedure implemented in the SpectraManager package. Structural variations were measured as a function of changes in the initial CD spectrum upon addition of either 20% 2,2,2-trifluoroethanol (TFE) (Fluka) to N TAIL F527W proteins or of molar excesses of P XD or lysozyme (Sigma) to wt N TAIL proteins.
Mean ellipticity values per residue ([⍜]) were calculated as [⍜] ϭ 3300 m ⌬A/(lcn), with l (path length) in cm, n ϭ number of residues, m ϭ molecular mass in daltons, and c ϭ protein concentration expressed in mg/ml. The number of residues (n) is 140 for all N TAIL proteins, 58 for HeV P XD , 57 for NiV P XD , and 129 for lysozyme, and m values are 15,241 Da for HeV N TAIL , 14,949 Da for NiV N TAIL , 15,280 Da for HeV N TAIL F527W, 14,988 Da for NiV N TAIL F527W, 6,871 Da for HeV P XD , 6,733 Da for NiV P XD , and 14,300 Da for lysozyme. Protein concentrations of 0.1 mg/ml were used when recording the spectra of N TAIL F527W proteins either in the presence or absence of 20% TFE. Protein concentrations of 10 mg/ml were used when recording the CD spectra of either individual wt N TAIL and P XD proteins or protein mixtures (i.e. N TAIL ϩ P XD and N TAIL ϩ lysozyme). In the case of protein mixtures, mean ellipticity values per residue ([⍜]) were calculated as [⍜] ϭ 3300 ⌬A/{[(c 1 n 1 )/m 1 ) ϩ (c 2 n 2 /m 2 )]l}, where l (path length) ϭ 0.001 cm, n 1 or n 2 ϭ number of residues, m 1 or m 2 ϭ molecular mass in daltons, and c 1 or c 2 ϭ protein concentration expressed in mg/ml for each of the two proteins in the mixture. The theoretical average ellipticity values per residue ([⍜] avg ), assuming that neither unstructured-to-structured transitions nor secondary structure rearrangements occur, were calculated as follows: 1 and [⍜] 2 correspond to the measured mean ellipticity values per residue, n 1 and n 2 to the number of residues of each of the two proteins, and R to the excess molar ratio of protein 2.
The experimental data in the 190 to 260-nm range were analyzed using DICHROWEB (supported by grants to the Biotechnology and Biological Sciences Research Council (BBSRC) Centre for Protein and Membrane Structure and Dynamics (59, 60)). The CDSSTR deconvolution method was used to estimate the content in ␣-helical and disordered structure using the reference protein set 7. Reconstructed curves superimposed very well on the experimental ones, thus attesting the reliability of the inferred ␣-helical percentages (data not shown).
Two-dimensional NMR-P XD samples at 80 M (NiV) or 575 M (HeV) in 10 mM sodium phosphate, pH 7, 150 mM NaCl, and 10% D 2 O were used for the acquisition of bidimensional nuclear Overhauser enhancement (2D-NOESY) spectra on either a 600-MHz ultra-shielded-plus Avance-III Bruker spectrometer equipped with a TCI cryoprobe or a 500-MHz ultrashielded-plus Avance-III Bruker spectrometer equipped with a QXI probe, respectively. The temperature was set to 300 K, and the spectra were recorded with 2048 complex points in the directly acquired dimension and 512 points in the indirectly detected dimension. Two-dimensional heteronuclear single quantum coherence (HSQC) spectra of both HeV and NiV wt N TAIL proteins, either alone or after the addition of various amounts of the corresponding unlabeled P XD protein, were recorded at 283 K on an ultra-shielded-plus Avance-III Bruker spectrometer equipped with a cryoprobe operating at a 1 H resonance frequency of 600 MHz. All labeled N TAIL samples were dissolved in 50 mM sodium phosphate, pH 7, containing 150 mM NaCl. The unlabeled P XD samples were dissolved in the same buffer supplemented with 10% glycerol. The spectra were recorded with 1024 complex points in the directly acquired dimension and 64 points in the indirectly detected dimension. These NMR titration experiments were carried out first by recording the 1 H-15 N HSQC spectra of 15 N-N TAIL proteins alone and then by successively recording the spectra of mixtures resulting from the addition of increasing amounts of the unlabeled protein. For the NiV N TAIL -P XD couple, the N TAIL :P XD molar ratios used were: 1:0.219, 1:0.438, 1:0.657, 1:0.876, 1:1.316, 1:1.754, and 1:2.63. For the HeV N TAIL -P XD couple, the N TAIL :P XD molar ratios used were: 1:0.97, 1:1.56, 1:2.14, 1:3.89, 1:8.55, and 1:13.24. In the course of titration, the concentration of the labeled sample dropped from 135 to 84 M in the case of NiV 15 N-N TAIL and from 53 to 31 M in the case of HeV 15 N-N TAIL . The number of scans was adjusted to take into account this gradual dilution. Solvent suppression was achieved by using excitation sculpting with gradients (61). The data were processed using NMRPipe (62) and analyzed using the CCPN software (63).
Quantitative analysis of NMR titration data was performed as described by Bernard et al. (53). The dissociation constant (K D ) can be estimated from the changes in chemical shifts of the 15 N-labeled protein (P) caused by the addition of the unlabeled binding partner (L), by fitting the chemical shift changes to the following equation for a two-state model in fast exchange, where ⌬␦ ppm is the combined chemical shift variation, ⌬␦ max is the maximum chemical shift deviation between the free and the bound state of protein (P), and [P] and [L] are the total protein and ligand concentrations, respectively. Curve fitting over experimental data was performed by using the XCRVFIT program (R. Boyko and B. D. Sykes, University of Alberta, Edmonton, Alberta, Canada). Fluorescence Spectroscopy-Fluorescence spectra of the single tryptophan in both the HeV and NiV N TAIL F527W variants were recorded by using a Cary Eclipse (Varian) equipped with a front face fluorescence accessory at 20°C, with 5 nm excitation and 5 nm emission bandwidths. The excitation wavelength was 290 nm, and the emission spectra were recorded between 300 and 450 nm. Titrations were performed in a 1-ml quartz fluorescence cuvette containing 1 M N TAIL F527W in 10 mM Tris/ HCl, pH 7.5, 200 mM NaCl and by gradually increasing the P XD concentration from 1 to 60 M. Experimental fluorescence intensities were corrected by subtracting the spectrum obtained with the corresponding P XD protein (note that P XD is devoid of tryptophan residues). Data were analyzed by plotting either the relative fluorescence intensities at the maximum of emission or the wavelength at the maximum emission as a function of increasing P XD concentrations.
Isothermal Titration Calorimetry (ITC)-ITC experiments were carried out on an ITC200 isothermal titration calorimeter (Microcal, Northampton, MA) at 20°C. In these studies, the concentration of N TAIL proteins was initially adjusted to 150 -200 M in the microcalorimeter cell (0.2 ml). The corresponding P XD protein (stock solution at 1.5-2.2 mM) was added from a computer-controlled 40-l microsyringe via a total of 19 injections of 2 l each at intervals of 180 s. Whatever the binding reaction being studied, the pair of proteins used in each binding assay was dialyzed against a 10 mM Tris/HCl, pH 7.5, buffer, supplemented with either 0.2 or 1 M NaCl to minimize undesirable buffer-related effects. The dialysis buffer was used in all preliminary equilibration and washing steps. For each binding reaction, a control experiment was carried out by injecting the ligand in a cell containing only the buffer. In that way, possible heat dilution effects of the ligand could be taken into account. A theoretical titration curve was fitted to the experimental data using Origin software (Microcal). This software uses the relationship between the heat generated by each injection and ⌬H°(enthalpy change in cal mol Ϫ1 ), K A (association binding constant in M Ϫ1 ), n (number of binding sites/ monomer), total protein concentration, and free and total ligand concentrations. The variation in the entropy (⌬S in cal mol Ϫ1 deg Ϫ1 ) of each binding reaction was inferred from the variation in the free energy (⌬G), where this latter was calculated from the following relationship: ⌬G ϭ ϪRTln 1/K A .
Surface Plasmon Resonance (SPR) Studies-Binding between purified NiV N TAIL and NiV P XD proteins was analyzed by using BIAcore 3000 (Amersham Biosciences). Purified NiV P XD (1.4 g/ml in acetate buffer, pH 5.5) was covalently bound to carboxy-methyl groups of CM5 sensor chips using amine-coupling chemistry (Amersham Biosciences). The levels of immobilized NiV P XD were between 45 and 67 RU (1000 RU equal a change in mass of 1 ng/mm 2 on the sensor surface). Kinetic and equilibrium constants were calculated from global kinetic and steady state analyses of reactions using a range of NiV N TAIL analyte concentrations (i.e. 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, and 50 M) in HBS-P buffer (10 mM Hepes, pH 7.4, 150 mM NaCl, and 0.005% surfactant P-20). Reactions were performed at 25°C. Sensorgrams plotted changes in surface plasmon resonance (measured in RU) as a function of time. Multiple sensorgrams representing various analyte concentrations were analyzed by using the BIAevaluation 3.1 software. Background interaction of the NiV N TAIL analyte with the sensor surfaces was measured on flow channels that were activated and subsequently blocked under buffer conditions used to immobilize P XD . This background was subtracted from all binding curves prior to the analyses. Immobilized lactoferrin was used as a specificity control, and the resultant sensorgrams ruled out high affinity interactions between NiV N TAIL and this irrelevant protein ligand (data not shown).
For the kinetic analysis, global fitting of experimental data to well characterized binding reactions was used to define the reaction rate and equilibrium constants. Curves generated with serial analyte concentrations were applied globally to the 1:1 Langmuir binding model with or without correction for baseline drifting depending on base-line status. For steady state analysis, the equilibrium response (R eq ) as a function of mobile analyte concentration ([A]) was fit to the equation expected for a simple 1:1 Langmuir binding model using non-linear least squares (64,65).
In the expression above, R max is the SPR response when binding is saturated, and K D is the equilibrium dissociation constant governing the binding reaction.
For both kinetic and equilibrium analyses, the 2 value and residual values were used to evaluate the quality of fit between experimental data and individual binding models. Plots of residuals indicate the difference between the experimental and reference data for each point in the fit. The 2 value represents Henipavirus N TAIL -P XD Interaction APRIL 15, 2011 • VOLUME 286 • NUMBER 15 the sum of squared differences between the experimental data and reference data at each point. A good fit between experimental and reference data has small residuals in the Ϫ2 to ϩ2 range that randomly distribute about the x axis and 2 values that are less than 10.
Bioinformatics Analyses-Sequences for this study were obtained from the VaZyMolO database (66). Sequence accession numbers for P XD are VaZy83 (HeV), VaZy2 (NiV), and VaZy91 (MeV). Sequence accession numbers for N TAIL are VaZy82 (HeV), VaZy1 (NiV), and VaZy90 (MeV). Sequence similarity and identity were calculated using the EMBOSS program. Multiple sequence alignments were obtained using ClustalW (67) and drawn using ESPript (68). Secondary structure predictions were carried out using the PSIPRED server (69).
Structural Modeling-Henipavirus P XD models were generated using the SAM-06 server that uses iterative hidden Markov model-based methods for constructing protein family profiles, using only sequence information (70 -72). SAM-06 is a fully automated server that generates a three-dimensional structural model by making use of a set of (distantly) related homologous structures.
For both HeV and NiV, the ␣-helical models of the N TAIL region, predicted to adopt an ␣-helical conformation within the putative ␣-MoRE encompassing residues 473-493 (see Fig. 1A and Ref. 14), were obtained using Swiss PdbViewer (73). This software was also used to generate the models of the NiV and HeV complexes consisting of P XD and of the above mentioned ␣-helix of N TAIL. This latter helix was modeled at the P XD surface by using the crystal structure of a measles virus chimeric construct encompassing P XD and residues 486 -504 of N TAIL (PDB code 1T6O) (74) as the template for structural alignment and the "explore fragment alternate fits" function of Swiss PdbViewer. Energy minimization of the models was carried out using the GROMOS96 implementation (75) of Swiss PdbViewer. Twenty steps of steepest descent energy minimiza-tion were performed. Models were further refined manually to avoid steric clashes using the idealization restraint of Coot (76). The quality of the final models was evaluated using MolProbity (77).
The Protein Interfaces, Surfaces, and Assemblies (PISA) server (78) was used to analyze the interface in the models of both complexes. The server PDBeFold from EMBL-EBI was used to compute root mean square deviations (r.m.s.d.) between the models and the template. The molecular graphics software PyMOL was used to visualize and draw the models (79).
Purification of Henipavirus N Proteins and Assessment of the Disordered State of Their N TAIL Domains-
We recently showed that the nucleoproteins of henipaviruses consist of an N-terminal region predicted to be structured (N CORE ; amino acids 1-399) and a C-terminal region (N TAIL ; amino acids 400 -532) that is mostly disordered in solution, although it contains some residual transient secondary structure (see Fig. 1A) (14). As a first step in view of assessing whether these N TAIL domains are also disordered in the context of the full-length nucleoproteins, we have cloned both NiV and HeV N genes (with a hexahistidine tag-encoding fragment) into the pDest14 expression plasmid, which allows expression in E. coli of recombinant proteins under the control of the T7 promoter.
Both HeV and NiV N proteins were recovered from the soluble fraction of bacterial lysates and purified to homogeneity (Ͼ95%) in two steps: immobilized metal affinity chromatography (IMAC) and preparative SEC (data not shown). The final purified proteins migrate in SDS-PAGE with an apparent molecular mass close to the value expected from their primary structure (ϳ59 kDa) (see Fig. 1, B and C, lanes 0). The identity of the final purified proteins was confirmed by mass spectrometry analysis of the tryptic fragments obtained after digestion of the purified proteins excised from SDS-polyacrylamide gels (data not shown). Both purified N proteins were found to be partially degraded in their C-terminal moieties (see Fig. 1, B and C, lanes 0), as judged from mass spectrometry (data not shown). Both nucleoproteins were eluted in the dead volume of the preparative SEC column (not shown). This indicates a molecular mass greater than 1300 kDa, which could correspond either to unspecific aggregates or to high degree multimers of N. Because N proteins from Paramyxoviridae members, including MeV (5) and NiV (80), are well known to form nucleocapsid-like particles when expressed in heterologous hosts, we examined the ratio between the absorbance of purified nucleoproteins at 280 and at 260 nm which gives indications on their RNA content. The A 260 /A 280 ratio for N devoid of RNA is 0.57, whereas it is Ն1.06 for the N-RNA complex containing six ribonucleotides/N monomer (see "Experimental Procedures"). The ratios measured for the HeV and NiV purified recombinant N proteins are 1.35 and 1.17, respectively, suggesting the presence of RNA within these nucleoproteins. We next investigated both N proteins by limited proteolysis. We had shown previously that both isolated N TAIL domains are highly susceptible to proteolysis (14). Herein we used limited proteolysis to assess whether the N TAIL domains were similarly sensitive to proteolysis in the context of the full-length proteins. To establish the proteolytic pattern of the HeV and NiV nucleoproteins, we incubated them in the presence of trypsin for increasingly longer periods up to 60 min (see Fig. 1, B and C). After only 2 min of incubation, both N proteins began to be degraded, giving rise to three discrete protein fragments also detectable as minor bands in the undigested N samples (see Fig. 1, B and C). Upon increasing incubation times, a resistant fragment of ϳ43 kDa was obtained (see Fig. 1, B and C, lanes 60 and arrows 2). Mass spectrometry analysis of this fragment showed that, for both NiV and HeV, it is composed of the N-terminal moiety of N (data not shown). On the other hand, no fragment corresponding to the remaining N TAIL domain was detected, indicating that it is hypersensitive to proteolysis and entirely degraded in the context of the entire N proteins either.
Purification and Characterization of Henipavirus P XD -We recently deciphered the modular organization of Henipavirus phosphoproteins using bioinformatics approaches and showed that they both contain a C-terminal X domain (referred to as P XD ) predicted to be folded and to adopt an ␣-helical conformation (see Fig. 2A and supplemental Fig. S1A) (14). To assess the ability of Henipavirus P XD to interact with the disordered N TAIL domains of the N proteins, we cloned the P XD -encoding P gene fragments into the pDest14 expression plasmid and expressed them as a fusion with a C-terminal hexahistidine tag.
Both NiV and HeV P XD were found to be soluble in E. coli and were purified to homogeneity (Ͼ95%) in two steps: IMAC and preparative SEC (data not shown). The final purified proteins migrate in SDS-PAGE with an apparent molecular mass close to the value expected from their primary structure (ϳ6.6 kDa) (see Fig. 2B and supplemental Fig. S1B). The identity of the final purified proteins was confirmed by mass spectrometry analysis of the tryptic fragments obtained after digestion of the purified proteins excised from SDS-polyacrylamide gels (data not shown). The molecular masses measured by MALDI-TOF for NiV P XD (6740 Ϯ 3 Da) and for HeV P XD (6737 Ϯ 3 Da) are consistent with the values expected for full-length proteins in which the initial methionine is either conserved (NiV) or cleaved off (HeV). These findings are in agreement with previous studies showing that in proteins expressed in E. coli the initial methionine is generally cleaved off when followed by small residues such as glycine or alanine (81).
The oligomeric state of both P XD proteins was investigated by using analytical SEC-MALLS-RI. HeV P XD was found to be monomeric even when loaded onto the SEC column at concentrations as high as 1.1 mM. Under these conditions, its observed molecular mass is 7222 Ϯ 620 Da (see Fig. 2C) and its measured R S is 13.1 Ϯ 1.9 Å, in agreement with the theoretical value (14.4 Å) expected for a folded protein (57). Furthermore, the sharpness and symmetry of the obtained peak indicates the presence of a well defined molecular species, demonstrating the homogeneity (e.g. monodispersity) of the sample. Conversely, NiV P XD was found to be trimeric even at concentrations as low as 0.3 mM and up to 1.1 mM, a condition in which the estimated molecular mass is 19,820 Ϯ 650 Da and the R S is 29.2 Ϯ 2.7 Å (see supplemental Fig. S1C). This value, although higher than the value expected for a folded trimer (21.6 Å), is nevertheless significantly lower than the value expected for an unfolded trimer (39 Å) (57). Notably, although the major peak is sharp and symmetric, a minor peak at 9.6 ml is also detectable (see supplemental Fig. S1C). The estimated molecular mass (ϳ18 kDa) of this peak excludes the possibility that it might correspond to a dimer or a monomer.
The two-dimensional NOESY spectra of both P XD proteins indicate that they are both folded, as judged from the spread of the resonance frequencies for amide protons and from the abundance of NOE signals in the amide-amide region (see Fig. 2D and supplemental Fig. S1D). The NOESY spectra also indicate that both NiV and HeV P XD adopt a predominantly ␣-helical conformation, as judged from the upfield shifting of several HN chemical shifts (see Fig. 2D and supplemental Fig. S1D).
Binding of P XD to N TAIL -The ability of the X domains of both Henipavirus members to bind to N TAIL was investigated by mixing purified N TAIL and P XD and analyzing complex formation by SEC-MALLS-RI. To this end, we incubated a fixed amount of N TAIL (0.3 mM) with increasing concentrations of P XD (0.3, 0.6, 0.9, and 1.2 mM) and then investigated complex formation using SEC-MALLS-RI. NiV and HeV N TAIL domains were eluted at 8.1 and 8.2 ml, respectively, corresponding to an R S of either 33.8 Ϯ 2.4 Å (NiV) or 31.2 Ϯ 2 Å (HeV). These values are consistent, within the error bar, with previous SEC and dynamic light scattering data (14) and are close to the theoretical value (28 Å) expected for monomeric PMG forms (57).
In the case of the study of the NiV N TAIL -P XD complex, upon addition of stoichiometric amounts of P XD , the N TAIL peak shifted toward a lower elution volume (from 8.1 to 7.75 ml), indicating the formation of an N TAIL -P XD complex, as also judged from the estimated mass (25,610 Ϯ 80 Da), a value consistent with the binding of one P XD molecule/N TAIL (expected mass ϳ 22 kDa) (data not shown). Upon adding a 2-fold molar excess of P XD , no further significant shift in the elution volume of N TAIL was observed, indicating that saturation was achieved for a 1:1 complex. Note however that under these conditions no peak corresponding to free P XD was detected, with this latter becoming detectable only in mixtures containing a 3-or 4-fold molar excess of P XD (see Fig. 3 and data not shown). The measured R S of the complex is 35.4 Ϯ 3.1 Å, a value larger than expected (22.3 Å) for a fully folded complex with a molecular mass equal to the sum of the masses of N TAIL and P XD (ϳ22 kDa) (57), arguing for a complex that is not fully compact and hence retains a considerable flexibility.
Strikingly, in the case of the HeV N TAIL -P XD complex, the addition of P XD molar excesses as high as 4 systematically resulted in no change in the elution profile of N TAIL (data not shown). This indicated that under these experimental conditions no complex was formed, possibly reflecting a higher dissociation constant (K D ) for the HeV couple as compared with the NiV one.
ITC and SPR Studies-To estimate precisely the equilibrium dissociation constants and to ascertain possible differences in affinity between the two N TAIL-P XD complexes, the N TAIL -P XD binding reaction was further investigated by ITC, an approach that gives access to the stoichiometry, equilibrium association constant, and variation in enthalpy and entropy (82). Purified Henipavirus N TAIL domains were loaded into the calorimeter sample cell and titrated with the corresponding P XD , achieving molar ratios of 2 (NiV pair) and 3.5 (HeV pair) at the end of the titration. The data, following integration and correction for the heats of dilution, were fit with a standard model allowing for a set of independent and equivalent binding sites (Fig. 4). The estimates for the model parameters (see Table 1) confirm a 1:1 stoichiometry and reveal that the binding reaction is both enthalpy-and entropy-driven, with the exception only of the NiV N TAIL -P XD couple for which a small unfavorable entropic contribution was found. The measured K D was 2.1 Ϯ 0.18 M for the NiV pair and 8.7 Ϯ 0.01 M for the HeV pair. Similar experiments carried out in the presence of 1 M NaCl (data not shown) yielded similar results (see Table 1), suggesting that the N TAIL -P XD interaction relies mainly on hydrophobic interactions.
In the case of NiV, we also studied the N TAIL -P XD interaction by SPR. Changes in SPR were monitored in real time as the NiV N TAIL protein passed over sensor chips to which NiV P XD was covalently coupled. Association and dissociation rates were found to be slow enough (k on ϭ 2.33 ϫ 10 3 M Ϫ1 s Ϫ1 , k off ϭ 2.13 ϫ 10 Ϫ2 s Ϫ1 ) to allow the equilibrium constant to be inferred from both kinetic and steady state analyses (see supplemental Fig. S2). Indeed, as specified by the manufacturer of the BIAcore 3000, good estimations of k on and k off can be calculated for the values in the range 10 3 to 10 6 M Ϫ1 s Ϫ1 and 10 Ϫ5 to 10 Ϫ2 s Ϫ1 , respectively. Binding affinities between P XD and N TAIL were established using 45-67 RU of immobilized P XD and N TAIL concentrations ranging from 0.1 to 50 M (see "Experimental Procedures"). Dosage-dependent binding was observed in this range. The binding reaction conformed to a 1:1 ligand-substrate (Langmuir) binding model, exhibiting an excellent fit (i.e. 2 Ͻ 1 and residuals within the range of Ϯ2) following global kinetic analysis of sensorgrams as well as when plotting mean equilibrium responses of the data in the steady state analysis. The equilibrium dissociation constant (K D ) derived from the kinetic analysis was 9.1 M, and the value derived from the steady state analysis was 7.3 M (see Table 2), in good agreement with that measured by ITC (cf . Tables 1 and 2).
Induced Folding of Henipavirus N TAIL in the presence of P XD -The N TAIL domains from the closely related MeV and Sendai
. SEC-MALLS-RI analysis of NiV N TAIL and NiV P XD and an N TAIL / P XD mixture containing a 4-fold molar excess of P XD .
The left y axis represents the molecular mass, and the right y axis represents the differential refractive index. The horizontal traces show the molecular masses calculated from light-scattering intensity at different angles and differential refractive indexes as a function of the elution volume. The concentratio.ns of N TAIL and P XD were 0.3 and 1.2 mM, respectively. virus (SeV) have been shown previously to undergo ␣-helical induced folding in the presence of the cognate X domains (44 -55, 83, 84). To investigate whether Henipavirus N TAIL domains undergo induced folding in the presence of P XD either, we used far-UV CD spectroscopy.
As expected from the NOESY spectra, the far-UV CD spectra of both P XD proteins (Fig. 5, A and B, gray lines) are typical of structured proteins with a predominant ␣-helical content, indicated by the positive ellipticity between 190 and 200 nm and by the two minima at 208 and 222 nm. Conversely, the CD spectra of both N TAIL proteins are typical of predominantly unfolded proteins, as seen by their large negative ellipticity at 198 nm and low ellipticity at 190 nm (Fig. 5, A and B, black lines). Nevertheless, and as already reported (14), the observed ellipticity values at 200 and 222 nm of both Henipavirus N TAIL proteins are consistent with the existence of some residual secondary structure typical of IDPs adopting a PMG conformation (21). To each N TAIL domain we added a 2-fold molar excess of the corresponding P XD . Under these experimental conditions, the N TAIL and P XD concentrations (350 and 700 M, respectively) were well above the estimated K D and hence were expected to lead to 100% complex formation. Indeed, the observed CD spectra of the mixtures differed from the corresponding theoretical average curves calculated from the individual N TAIL and P XD spectra (Fig. 5). As the theoretical average curves correspond to the spectra that would be expected if no structural variations occur, deviations from these curves indicate structural transitions. The experimentally observed spectra of the mixtures support a random-coil to ␣-helix transition, as judged by the much more pronounced minima at 208 and 222 nm and by the higher ellipticity at 190 nm of the experimentally observed spectra compared with the corresponding theoretical average curves (see Fig. 5, A and B). In particular, (i) the experimental CD spectra of the mixtures deviate considerably from the average curves in the 190 -195 region, with this deviation being more pronounced in the case of the HeV N TAIL ϩ P XD mixture; and (ii) mixture spectra display a pronounced decrease in the ellipticity at 208 and 222 nm with respect to the average curves, with this decrease being more significant in the case of the NiV N TAIL ϩ P XD mixture (Fig. 5, A and B). A quantitative analysis of the spectra (see "Experimental Procedures") allowed an estimation of the percentages of ␣-helical and disordered structure in all of the spectra (Fig. 5, C and D). This analysis indicated a significant increase in the ␣-helical content of the mixtures as compared with average spectra, with this gain in ␣-helicity being paralleled by a decrease in the content of disordered structure (see Fig. 5, C and D). As a control, we recorded the CD spectra of both N TAIL in the presence of a 2-fold molar excess of lysozyme (data not shown). The absence of significant structural variations in the presence of lysozyme confirms the specificity of the deviations observed upon the addition of P XD to the corresponding N TAIL protein.
Two-dimensional Heteronuclear Nuclear Magnetic Resonance Titration Studies-To further explore the nature of the interaction established by Henipavirus N TAIL and P XD , we used NMR spectroscopy. We recorded the HSQC spectra of uniformly 15 N labeled N TAIL before and after the addition of increasing amounts of unlabeled P XD . These studies, by allowing chemical shift changes in the backbone amide and proton resonances to be followed upon the addition of unlabeled P XD , yielded an estimation of the number of N TAIL residues involved in the interaction with P XD . For both titrations, most resonances in the HSQC experienced no chemical shift changes, and only a few resonances underwent fast to intermediate exchange ( Fig. 6 and supplemental Fig. S3). Saturation (i.e. no changes in chemical shifts upon further addition of the partner to 15 N-labeled N TAIL ) was achieved with N TAIL :P XD molar ratios of 1:1.75 and 1:1.56 for NiV and HeV N TAIL , respectively. This finding is in line with what could be expected from the experimentally determined dissociation constants, from which the percentage of bound N TAIL was estimated to be 80% in the case of the HeV titration and 100% for that of NiV.
In the case of HeV N TAIL , ϳ100 peaks were detectable in the HSQC, including the 10 expected N TAIL glycines and at least 18 Ser/Thr residues (see supplemental Fig. S3). Following the addition of P XD , around 15 peaks disappeared from the spec- trum of N TAIL , consistent with an intermediate exchange regime (i.e. the exchange rate between free and bound N TAIL is comparable with the chemical shift difference between the free and the bound forms). The 15 residues that disappeared do not imply any Gly but include 4 -5 Ser/Thr. Notably, even with P XD molar ratios as high as 8.5, no new peaks reappeared corresponding to the fully bound form of N TAIL (see supplemental Fig. S3) nor could they be observed upon further increasing the molar excess of P XD up to 13 (data not shown). In addition, 3-4 peaks (including 2 of the 10 glycines) showed chemical shift changes upon the addition of P XD according to a fast to intermediate exchange regime (see supplemental Fig. S3). These observations could be accounted for by assuming that P XD binds to N TAIL in close proximity of the ␣-MoRE predicted to encompass residues 473-493, although other binding scenarios cannot be ruled out.
In the case of NiV N TAIL , similar results were obtained (Fig. 6). The peaks that disappeared upon the addition of P XD imply 5-6 Ser/Thr (see Fig. 6A), and at least two peaks underwent fast to intermediate exchange (see Fig. 6, A and B). We also performed a quantitative analysis of the NMR titration data. We plotted the chemical shift variation as a function of the partner molar ratio for those peaks that undergo fast exchange (see Fig. 6C). When applied to the peak shown in Fig. 6B, this analysis yielded an apparent dis-sociation constant (K Dapp ) of 2 Ϯ 0.06 M, a value in very good agreement with the K D determined by both ITC and SPR studies. A very similar K Dapp value (5 Ϯ 0.2 M) was obtained by performing this quantitative analysis on another similarly behaving peak (data not shown). Interestingly, in the case of the NiV N TAIL titration, but not of the HeV one, among the correlation peaks that were displaced by P XD , eight underwent an upfield shift (see Fig. 6A) consistent with a random coil to ␣-helix transition.
In conclusion, these experiments revealed that complex formation between N TAIL and P XD implies both fast and intermediate exchange. In addition, in the case of NiV, binding to P XD triggers a gain of ␣-helicity for at least eight residues.
Generation of Single-site Trp N TAIL Variants and Fluorescence Spectroscopy Studies-To assess the possible contribution of the C-terminal region of N TAIL to binding to P XD , we designed a single-site Trp variant for both NiV and HeV N TAIL in view of intrinsic fluorescence studies. For both NiV and HeV N TAIL we targeted a unique, naturally occurring aromatic residue (Phe-527) and generated an N-terminally hexahistidinetagged N TAIL variant (referred to as N TAIL F527W) bearing the F527W substitution. Introduction of a tryptophan residue in both N TAIL domains was conceived to allow binding events to be followed by fluorescence spectroscopy while maximizing the conservative nature of the substitution (note that the two X domains contain no tryptophan residues). Both NiV and HeV N TAIL F527W variants were purified from the soluble fraction of the bacterial lysate by IMAC and preparative SEC (see Fig. 7, A and B, insets). The identity of the recombinant products was confirmed by mass spectrometry analysis of tryptic digests of fragments obtained after digestion of the purified proteins excised from SDS-polyacrylamide gels (data not shown). Both N TAIL proteins display an abnormally slow migration in SDS-PAGE with an apparent molecular mass of 20 kDa (expected MM 15 kDa) (see Fig. 7, A and B, insets). This abnormal migratory behavior has already been documented for both native N TAIL domains, where mass spectrometry analyses gave the expected results (14). Hence, this anomalous electrophoretic mobility is rather due to a rather high content of acidic residues, as already observed for other intrinsically disordered domains (for examples see Ref. 6, 45, and 85) and, more generally, in other IDPs (86). Indeed, because of their biased amino acid composition, often leading to enrichment in negatively charged residues, IDPs bind less SDS than naturally folded proteins. As a result, their apparent molecular mass is often 1.2-1.8 times higher than the real one calculated from sequence data or measured by mass spectrometry (86).
Both N TAIL variants displayed the same SEC elution profile as the wt form (data not shown), being eluted from a Superdex S200 column as sharp peaks with an apparent molecular mass (43 kDa) well above the expected one and leading to an estimated R S of 28 Ϯ 2 Å (see "Experimental Procedures"). Note that the elution behavior was found to be buffer-independent, as the same elution profiles were obtained regardless of whether a sodium phosphate or Tris/HCl buffer was used for elution and irrespective of the NaCl concentration. Thus, both variants exhibit hydrodynamic properties similar to those of the wt forms, suggesting that they both adopt a PMG conformation. In further support of this observation, the far-UV CD spectra of N TAIL F527W proteins are typical of predominantly unfolded The amino acid sequence of NiV N TAIL is shown above the spectra, with Gly and Thr/Ser residues shown in bold letters. The predicted ␣-MoRE encompassing residues 473-493 is framed. The inset shows purified NiV 15 N-N TAIL and P XD . B, changes in the chemical shift of the backbone amide 15 N resonance of one NiV N TAIL peak in fast exchange during the titration. Bound and free chemical shift positions are indicated in blue and red, respectively. The positions obtained with N TAIL :P XD molar ratios of 1:0.219 and of 1:0.657 are shown in green and black, respectively. Note that saturation was achieved for a 1:1 complex. C, chemical shift variations of the backbone amide 15 N resonance of the peak shown in B as a function of P XD molar excess. The solid line represents the fitted model. All spectra were recorded at 283 K. ppm, quotes for resonance shifts in parts per million of the spectrophotometer frequency.
forms devoid of stable, highly populated secondary structure (see Fig. 7, A and B) and are almost perfectly superimposable on those of both native N TAIL domains (data not shown). These observations indicate that the tryptophan residue does not affect the overall secondary structure content of the protein. To test the potential of both N TAIL variants to undergo folding, we recorded their CD spectra in the presence of 20% TFE, a condition where both Henipavirus wt N TAIL proteins undergo dramatic structural transitions (14) (Fig. 7, A and B). The solvent TFE is widely used as an empirical probe of hidden structural propensities of peptides and proteins, as it mimics the hydrophobic environment experienced by proteins in protein-protein interactions (87)(88)(89). Both proteins show an increasing gain of ␣-helicity upon the addition of TFE, as indicated by the characteristic maximum at 190 nm and double minima at 208 and 222 nm (Fig. 7, A and B). Under these conditions, the ␣-helicity was estimated to be ϳ40% for both variants (see Fig. 7, C and D), a value close to that observed for both native N TAIL domains (14). These results indicate that the Phe to Trp substitution does not affect the folding abilities of the two N TAIL variants, thus supporting their biochemical relevance. That the single-site Trp variants behave like the native forms was also demonstrated by ITC studies showing that the variants bind to P XD with K D values close to those observed with the wt N TAIL forms (Table 1).
Fluorescence spectroscopy studies showed that the NiV variant has a maximum of emission at 351 nm, while the maximum of emission of the HeV variant is at 355 nm, indicating that in both N TAIL variants the Trp-527 is fully exposed to the solvent. The addition of gradually increasing P XD molar excesses (up to 60) did not trigger any coherent, dose-dependent increase or decrease in the fluorescence intensity (data not shown), nor did it cause any significant shift in the emission maximum (see supplemental Fig. S4). Because in these studies the N TAIL and P XD concentrations in the course of the titration were well above the estimated K D , these results argue for the lack of significant variations in the chemical environment of the unique Trp residue at position 527 upon P XD binding.
Structural Models of Henipavirus N TAIL -P XD Complexes-NMR titration studies suggested that P XD might bind to an N TAIL region close to the predicted ␣-MoRE spanning residues 473-493, an hypothesis also supported by previous studies carried out by others showing that P binds to residues 468 -496 of N (12,13). In addition, both NMR and far-UV CD studies revealed a gain of ␣-helicity within N TAIL upon binding to P XD , and ITC studies showed that the interaction does not rely on electrostatic contacts, as the K D was not affected by NaCl concentrations as high as 1 M. On the other hand, fluorescence spectroscopy studies indicated a lack of impact of P XD on a Trp residue at position 527 of N TAIL , arguing for the lack of stable contacts between the region in close proximity to this Trp residue and P XD . On the basis of all of these considerations, and also by analogy with the related MeV, we built a model of the N TAIL -P XD complex involving the ␣-MoRE encompassing residues 473-493 and implying hydrophobic contacts.
The structural models of both NiV and HeV P XD were obtained using the SAM-06 server. In both cases, the crystal structure of P XD from the related MeV (PDB code 1OKS) (44) was found to be the best hit, with E-values of 5.333 e Ϫ3 (NiV) and 2.257 e Ϫ2 (HeV). Note that an automated search of the PDB database (90) for homologous structures using either the ESyPred3D (91) or the Swiss-Model (92) servers failed to generate a structural model, as the sequence identity between either HeV or NiV P XD and MeV P XD (19.6 and 15.7%, respectively) is lower than the threshold used by these servers.
The ␣-MoRE encompassing residues 473-493 in both Henipavirus N TAIL domains can be modeled as an ␣-helix with one side mostly hydrophobic. After having obtained the structural model of both P XD proteins, we modeled the ␣-helical ␣-MoRE of N TAIL in the hydrophobic cleft delimited by helices ␣2 and ␣3 of P XD to yield a pseudo-four-helix arrangement similar to that already observed for the closely related MeV N TAIL -P XD complex (74) (Fig. 8).
After energy minimization and manual refinement, a good shape complementarity between the ␣-MoRE and P XD was observed for both Henipavirus complexes. For the final structural model of the NiV complex, 98.5% of the residues were found to lie in the favorable region of the Ramachandran plot, with a final MolProbity score of 1.77 and an overall clashscore of 18.6. For the final structural model of the HeV complex, 98.5% of the residues were found to lie in the favorable region of the Ramachandran plot, with a final MolProbity score of 1.76 and an overall clashscore of 18.4.
The resulting models are loosely packed, with an interface area of 439 Å 2 for the NiV complex and 337 Å 2 for the HeV complex. The HeV complex is stabilized by hydrophobic interactions between side chain carbon atoms of the interacting pairs P Ile-702/N Ile-488 and P Tyr-682/N Ala-484, as well as by a hydrogen bond between the backbone oxygen of P Asp-681 and the NH1 group of N Arg-480. The NiV complex is stabilized by a hydrogen bond between the backbone oxygen of P Lys-687 and the NH1 group of N Arg-480 and by several hydrophobic contacts involving side chain atoms from the interacting pairs P Ala-688/N Leu-477, P Ile-697/N Ala-484, P Ile-704/N Ala-488, and P Ile-704/N Ala-491.
The final structural models are quite close to the structure of the MeV template; for the NiV complex, the pairwise r.m.s.d. is 0.67 Å for the P XD chain (over 47 aligned residues out of 50) and 0.79 Å (over 18 aligned residues out of 21) for the ␣-MoRE. In the case of the HeV complex, the pairwise r.m.s.d. is 2.0 Å (over 46 aligned residues out of 51) for P XD and 0.68 Å (over 18 aligned residues out of 20) for the ␣-MoRE. The most significant structural differences concern the loop between helices ␣2 and ␣3 of HeV P XD , with the maximal deviation occurring between MeV Lys-489 and HeV Asp-687 (C␣ distance of 5.2 Å). In the case of the NiV complex, this loop deviates much less from that of MeV P XD , and the maximal deviation between the two models concerns the ␣-MoRE, with a C␣ distance of 4.4 Å between NiV N Asn-474 and MeV N Asp-487.
Henipavirus N Proteins Form Nucleocapsid-like Particles in
Which the N TAIL Domain Is Disordered-The SEC profile of Henipavirus N proteins, together with their A 260 /A 280 ratio, supports the formation of nucleocapsid-like particles upon expression in E. coli, in agreement with previous findings showing that NiV N self-oligomerizes upon expression in insect cells (80) and forms speckles in live transfected BHK cells (13) in accordance with the general behavior of nucleoproteins from Mononegavirales members.
In a previous study, by combining computational and biochemical approaches, we showed that both NiV and HeV N TAIL domains are mostly unstructured in solution although they contain some residual, transiently populated, secondary structure (14). Whether these domains were also disordered in the context of the full-length nucleoproteins was however still a matter of debate. Herein we used limited proteolysis to address the disordered state of N TAIL within the entire N proteins. Because disordered regions are highly sensitive to proteolysis, limited proteolysis is a powerful tool for investigating protein structural properties (see Refs. 93-95 and 96 and references cited therein). The results presented here show that both N proteins undergo proteolytic cleavage within their N TAIL domains, thus supporting the disordered nature of these domains not only in isolation but also in the context of the entire N proteins.
The X Domains of Henipavirus P Proteins Are Autonomously Folding Units Adopting an ␣-Helical Conformation-Previous bioinformatics analyses by our laboratory allowed us to propose a modular organization of Henipavirus P and to designate the X terminal domain as a putative globular domain that, by analogy with the closely related MeV, might interact with Henipavirus N TAIL . We therefore targeted both NiV and HeV P XD for expression in E. coli. Indeed, both X domains were found to be expressed in the soluble fraction of the bacterial lysate, suggesting that P XD do represent bona fide domains, i.e. autonomously folding units. In further support of this observation, both CD and NMR studies showed that both of the P X domains are folded and adopt a predominantly ␣-helical conformation. Strikingly, although HeV P XD was found to be monomeric and eluted as a unique, very sharp peak, NiV P XD was found to be trimeric and eluted in two peaks: a major, very sharp peak and a minor peak in which the estimated molecular mass is consistent with a trimeric form possibly adopting a slightly more compact conformation. The possibility that the major elution peak of NiV P XD might correspond to a monomeric form adopting a molten globule conformation, as in the case of the C-terminal X domain of the mumps virus (97,98), was checked and ruled out by NMR studies, where the NOESY spectrum clearly showed that the NiV P XD is folded. Whatever the origin of the minor elution peak, it is noteworthy that the slight heterogeneity of NiV P XD did not, however, impair complex formation with N TAIL .
Our ability to obtain large amounts of purified P XD , beyond validating the reliability of the prediction of the modular organization of Henipavirus P, highlights the general interest of a domain approach for the biochemical and structural study of viral proteins. This has already been well illustrated in the case of the P proteins from measles (44) and Sendai viruses (83, 99 -102) as well as for the phosphoproteins from Rhabdoviridae members (103)(104)(105)(106)(107), and, more generally, for viral proteins targeted by large scale structural genomics projects (for examples see Refs. 108 -116). FIGURE 8. A and B, structural models of the NiV (A) and HeV (B) complexes between P XD and the N TAIL region predicted to adopt an ␣-helical conformation (amino acids 473-493 for NiV and 473-492 for HeV) within a predicted N TAIL ␣-MoRE. P XD is shown in blue with surface representation, and the ␣-MoRE of N TAIL is shown in red in ribbon representation. Hydrophobic residues are shown in yellow. The amino acid sequence of P XD and of the N TAIL region that was modeled in the complex is shown with the same color code. C, superimposition of the structural models (ribbon representation) of the P XD -N TAIL complexes of HeV (green) and NiV (orange) onto the crystal structure of a MeV chimeric construct (red) encompassing P XD (amino acids 459 -507 of P) and residues 486 -504 of N (PDB code 1T6O) (74). A multiple sequence alignment of Henipavirus and MeV P XD as obtained using ClustalW and ESPript is also shown. Residues corresponding to a similarity greater than 60% are boxed and shown in red. Identical residues are boxed and shown in white on a red background. The numbers written in front of the sequences correspond to the amino acid positions in the P and N sequences. Dots above the alignment indicate intervals of 10 residues. Predicted secondary structure elements of HeV and NiV P XD , as obtained using the PSIPRED server, are shown above the multiple sequence alignment. Secondary structure elements, as observed in the crystal structure of the MeV chimeric construct (PDB code 1T6O) are shown below the alignment. All structural models were drawn using PyMOL (79).
The X Domains of Henipavirus P Proteins Bind to the Intrinsically Disordered N TAIL Domains and Form a 1:1 Complex-Although NiV P XD was found to be trimeric, SEC-MALLS studies indicated that this latter binds to N TAIL as a monomer, as judged from the molecular mass (ϳ25 kDa) of the observed N TAIL -P XD complex. The lack of detection of free P XD in the N TAIL :P XD mixture containing a 2-fold molar excess of P XD likely arises from the limited resolution of the KW-802.5 SEC column for small protein molecules, where these latter can escape detection unless they are highly concentrated. Accordingly, a peak corresponding to free (trimeric) P XD becomes detectable in mixtures with P XD concentrations of 0.9 -1.2 mM. The fact that the elution volume of the NiV N TAIL -P XD complex remains the same, even with P XD molar excesses as high as 4, could be accounted for by either the formation of a 1:1 stoichiometric complex or by a more complex binding scenario in which binding of the first P XD molecule would occur with a relatively high affinity, whereas putative binding of additional P XD molecules would be governed by a much lower affinity. This latter hypothesis is rather unlikely, however, as it would imply a K D higher than the highest P XD concentration used in these studies (1.2 mM) and would hence not be physiologically relevant. In further support of the first binding scenario, formation of a 1:1 complex was further confirmed by both ITC and SPR studies that also revealed a K D in the M range for both complexes.
Surprisingly, in the case of HeV, SEC-MALLS studies failed to unveil complex formation, as no shift in the elution volume of N TAIL was observed even with P XD molar excesses as high as 4. These findings are puzzling, because these experiments were carried out under the same buffer conditions used for the ITC studies, which not only clearly revealed the formation of a 1:1 complex but also indicated a K D comparable with that observed for the NiV N TAIL -P XD binding reaction. Because detection of protein complexes by SEC is notoriously challenging for complexes characterized by K D in the M range, these results might reflect more subtle differences between the HeV and NiV complexes, despite the similar K D values. That the two complexes do behave differently is further supported by the different HeV N TAIL resonance behavior in titration studies with respect to NiV N TAIL , as well as by the smaller interface of the HeV complex, as judged from the structural models (for a more detailed discussion of these two points, see below).
Binding to P X Domains Triggers ␣-Helical Folding of the Intrinsically Disordered N TAIL Domains-Far-UV CD spectroscopy has been proved to be a method sensitive enough to detect unstructured-to-structured transitions of MeV N TAIL upon binding to P XD (6,44,46). Using the same approach, we showed that both NiV and HeV N TAIL undergo ␣-helical induced folding upon binding to the corresponding P X domain. Binding of Henipavirus N TAIL domains to P XD results in the same type of structural transitions as observed with the MeV N TAIL -P XD couple (6,44,46) and is in agreement with the strong ␣-helical propensity of Henipavirus N TAIL (14). Note however that these studies remain qualitative; if the estimated ␣-helical content is useful for comparative purposes, deconvolution approaches notoriously lead to estimations that cannot be taken as fully reliable, i.e. they often significantly deviate from the actual con-tent in secondary structure as observed in the experimentally determined structures (for examples see Refs. 44,117).
The NMR titration experiments of Henipavirus N TAIL with increasing amounts of P XD confirmed that a complex is formed between the two partners. For both NiV and HeV, around 15 peaks disappeared from the N TAIL spectrum upon the addition of P XD , whereas only very few peaks underwent chemical shift changes. These observations point toward the intermediate exchange regime often observed for IDPs undergoing foldingupon-binding events (for examples see Refs. 39, 54, 83, and 118). Indeed, although IDPs give rise to sharp NMR resonances because of fast internal motions and short effective correlation times, interactions of disordered regions with folded proteins lead to resonance line broadening of interacting residues because of a larger effective correlation time, restricted local motion, and possible exchange between free and bound states on millisecond to microsecond time scales. Interestingly, in the case of the Hendra couple, no new peaks appeared in the N TAIL spectrum even with saturating amounts of P XD , i.e. under conditions in which the fraction of bound N TAIL , as inferred from the measured K D , was 100%. This behavior, which is in contrast to that observed with the NiV and MeV couple (54), suggests that even when bound to P XD , HeV N TAIL remains dynamic, undergoing exchange between different conformers on the P XD surface. The vanishing of resonances within IDPs upon the addition of a partner protein without the reappearance of the signals at saturation is frequently observed (for examples see (Refs. 119 -121). Definite answers about the N TAIL residues that are involved in the interaction with P XD would require the assignment of the NMR spectrum of the free and bound forms, a work that is currently in progress and will be addressed in future studies.
Despite the ␣-helical transition that both NiV and HeV N TAIL undergo upon binding to P XD , the experimentally determined R S of the NiV N TAIL -P XD complex suggests that binding to P XD does not imply formation of a compact complex, with this latter rather retaining a considerable flexibility. In further support of this observation, the many observable and relatively sharp NMR resonances in both NiV and HeV N TAIL -P XD complexes, displaying chemical shifts that are nearly unaltered, provide evidence that N TAIL remains significantly disordered even in the bound form. Therefore the final complex is likely endowed with flexible appendages in a structural arrangement possibly reminiscent of that observed in the case of the MeV complex (44) and also proposed for SeV (84).
Structural Models of Henipavirus N TAIL -P XD Complexes and Functional Implications for Transcription and Replication-By analogy with the related MeV (44,74) and also based on ITC studies carried out in the presence of 1 M NaCl, which showed that the N TAIL -P XD interaction does not rely on polar contacts, we reasoned that the burying of apolar residues of N TAIL at the P XD surface could be the driving force in the P XD -induced folding of N TAIL . Indeed, although globular proteins contribute most of their hydrophobic residues to the protein core, IDPs expose their few hydrophobic residues to the surface, thereby allowing interaction with binding partners. As a result, IDP interfaces make more hydrophobic contacts (33% for IDPs and 22% for ordered proteins), whereas ordered interfaces make more polar interactions (122). A notable exception is provided by the SeV N TAIL -P XD complex that mainly relies on polar contacts and is therefore impaired by high salt concentrations (83).
We therefore modeled the more hydrophobic side of the amphipathic ␣-MoRE of N TAIL at the hydrophobic surface delimited by helices ␣2 and ␣3 of P XD (74). We emphasize that the proposed models are only a tentative description of a possible mode of interaction. Precise structural information on the molecular mechanism of the induced folding of N TAIL upon binding to P XD awaits the availability of the crystal structure of at least one of the two N TAIL -P XD complexes. Nevertheless, it is noteworthy that interactions similar to those occurring in our models take place not only in the related MeV complex that was used as template but also in many other protein complexes, as well as within individual proteins. Indeed, a search for homologous proteins using the DALI server (123) resulted in numerous hits (Z-score Ͼ 2.0), including a complex between an affibody and protein Z (PDB code 1LP1), IgG-binding proteins A and G (PDB codes 2JWD and 1Q2N), and Ebola virus VP35 (PDB code 3L27). These proteins, although exhibiting no significant sequence identity with our models, possess a similar four-helix bundle arrangement, with nevertheless some differences in the angles between the helices and the loops connecting them, leading to r.m.s.d. values ranging from 1.0 to 3.5 Å. The broad occurrence of this type of structural arrangement reflects the fact that the triple helical bundle is a very common structural motif used as a recognition scaffold (124).
Search of the Protein Data Bank database for complexes exhibiting interfaces similar to those of the NiV and HeV complex using the PISA server led to the retrieval of two protein complexes (PDB codes 2IZX and 2D2C, respectively) exhibiting an interface area of 384 and 445 Å 2 . The rather small buried interface area of the NiV and HeV complexes (439 and 337 Å 2 , respectively) is in agreement with previous reports indicating that the interfaces of complexes involving IDPs are generally smaller than those occurring in ordered complexes (42).
The surface buried in P XD by the ␣-helix of N TAIL in both Henipavirus complexes is smaller than that observed in the MeV complex (634 Å 2 ), suggesting a less stable complex. That a relationship exists between interface buried surface area and complex stability is commonly accepted and has been clearly established by a recent survey of subunit interfaces of weakly associated protein-protein complexes. Those studies reveal that weak complexes (e.g. K D in the M range) have loosely packed interfaces that are smaller (by a factor of 2.4 on average) than in tight complexes (125).
The lower buried surface area of the Henipavirus N TAIL-P XD complex is consistent with the lower affinity of the binding reaction as compared with the MeV N TAIL -P XD couple. In this latter case, indeed, our previous SPR and fluorescence spectroscopy studies indicated a K D in the 100 nM range (46), contrary to ITC and SPR studies carried out by Kingston and colleagues (98,126) that revealed a K D of 7.4 -13 M. It should be noted however that these latter studies were carried out using N TAIL peptides encompassing residues 477-505 or 477-525 rather than full-length N TAIL (98,126).
In further support of a less tightly bound complex in henipaviruses, the addition of P XD has no notable impact on the chem-ical environment of Trp-527 of both NiV and HeV N TAIL , contrary to what was observed in the case of MeV N TAIL where the addition of P XD led to a dose-dependent impact on the fluorescence intensity of Trp-518 (the counterpart of Trp-527) (46). This observation is consistent with a higher conformational flexibility of the C-terminal region of the Henipavirus N TAIL domains in the bound form as compared with MeV N TAIL .
Considering that the contact between P XD and N TAIL within the replicative complex has to be dynamically made/broken to allow the polymerase to progress along the nucleocapsid template during both transcription and replication, as well as to deliver N monomers to the nascent RNA chain, the N TAIL -P XD complex cannot be excessively stable for this transition to occur efficiently at a high rate. A relatively labile complex can result either from a tight complex the strength of which is modulated by co-factors or from an inherently lower affinity of the binding reaction. MeV would provide an example of the first scenario, where the high affinity N TAIL -P XD complex is modulated by the major inducible heat shock protein (Hsp70), which acts by destabilizing the complex, thereby promoting cycles of binding and release of the polymerase complex that lead to increased transcription and replication (127)(128)(129)(130). A similar high affinity complex has also been observed in the case of rabies virus, where the K D between N-RNA rings and the C-terminal domain of the phosphoprotein was found to be 160 nM (107). In this latter case, a mechanism different from cartwheeling has been evoked, however, whereby the P protein would be permanently bound to the nucleocapsid template, and the polymerase would jump between adjacent P dimers (see Ref. 131 and references cited therein). On the other hand, SeV (83) and Henipavirus would provide examples of the second scenario, with K D values in the M range. These findings would support a cartwheeling mechanism for the polymerase complex of Henipavirus, as already proposed for other Paramyxoviridae members (132,133). Whatever the mechanism by which the polymerase moves along the template, the present studies, by revealing that P is recruited onto the nucleocapsid template via the N TAIL -P XD interaction, designate this latter as a promising target for antiviral therapies. The relevance of the N TAIL -P XD complex as a target for antiviral drugs is further underscored by recent reports showing that protein-protein interactions mediated by disordered regions are valuable drug discovery targets with the potential to increase significantly the discovery rate for new compounds (see Refs. 134 -136 and references cited therein). | 18,842.6 | 2011-02-11T00:00:00.000 | [
"Biology",
"Chemistry"
] |
Impact Velocity Prediction in a Traffic Accident
Reconstruction of traffic accidents has been so crucial scientific process in order to make impartial and judicious decisions. This study focuses on impact speed prediction of accident sufferers just before the collision in a comprehensive scientific way by using an accident reconstruction software called "vCrash" and Function Fitting Neural Network (FITNET) artificial intelligence method (predictor) in case of absence of skid marks or other clues about calculating impact speeds. A sample real world accident was simulated on the software several times by changing collision speeds to form different deformation on the collision regions of the vehicles in every simulation. Every single deformation amount corresponding to each impact velocity was recorded and used as teaching data for FITNET prediction model. Using 10-fold cross validation, mean squared error (MSE) and multiple correlation coefficients (R) were observed to exhibit performance of the prediction model. The model performed high R (close to 1) and acceptable MSE values. This method aims that, in a probable similar accident scene in future, it will be possible to analyze the impact speeds just by entering average deformation amounts into an application on a portable device at the accident scene without requirement of expensive reconstruction tools and it will be a guide for analysis of other accident types.
Introduction
Traffic engineering focuses on safety and efficiency in transportation.Public agencies strive to reduce traffic accidents on roadways in most countries all over the world.Financial burden of traffic accidents places another problem on society.Driver and roadway design are the major factors in a traffic accident.Safety strongly depends on the gender and the age of the driver [1].Death rates related to diseases are prone to fall in developed countries in which deaths due to traffic accidents represent a notable exception.As a country flourishes, growing economy brings a substantial increment in motor vehicles which causes substantial probable accidents.Traffic accidents are the first cause of injury-related deaths all around the world.April 7 was devoted to prevention of traffic injuries by World Health Organization (WHO) in 2004.As in many countries, in Turkey, fatalities and injuries due to traffic accidents are major problems for public [2].Reckless driving with excessive speed gives rise to most of the traffic accidents [3].According to WHO, traffic fatalities will be the sixth leading cause of death worldwide by the year 2020 [4].
According to 2002 annual reports, traffic accidents are the 11th reason for fatalities in Turkey.Traffic accidents have the 2nd priority for fatalities at the age interval of 5-29 and the 3rd for the age interval of 30-44.In 1999, while the number of registered traffic accidents was 466000, it was 501000 in year 2000.General Directorate of Highway reports indicate 2954 fatalities and 94497 injuries involving 409407 accidents in year 2001 and 570419 accidents in year 2005 [5].
Transport policy substantially corresponds to accessibility, safety and environmental issues.Safety policies are of great importance almost for all countries worldwide [6].There are some methods in evaluating plans based on infrastructure and Cost-Benefit Analysis (CBA) is now deemed the standard method in most countries [7].
Almost all of the passenger and freight transportation are carried out by highway in Turkey.In Western countries, this load on highways is shifted to railway and seaway, thus lowered highway accidents can be provided.In Turkey, highway transportation constitutes the biggest place within transportation types which unfortunately results increased number of highway vehicles [8].
Rapid increment in motor vehicles is inevitable especially during the last decades which leads to increased traffic density, several traffic accidents.Therefore, accident reconstruction is crucial in terms of solving the question of liability for these accidents.Accident experts investigate accident scenes and generally conclude about causes and procession of the accident referring to police reports.However, growing vehicle numbers and accidents make challenges for police officers to report the scene accurately.Furthermore, anti-lock braking system (ABS) in modern vehicles, when it is active, avoids locking wheels by controlling wheel slip which entails missing brake traces left on the road surface.However, brake traces are one of the most important clues for accident investigators to reconstruct the vehicle motion leading to an accident.More complex situations occur for vehicles equipped with vehicle dynamic control (VDC).Moreover, there are systems interfering the latest systems into the steering system to manipulate the steering system automatically [9].There are many uncertain factors in road traffic accidents.It is necessary to consider the uncertainty influence of these factors by random theory to improve the analysis veracity.In order to improve the precision and reliability of traffic accident analysis and reconstruction, random theory and the probabilistic perturbation method are introduced for the uncertainty analysis of traffic accident.Precision and uncertainty analyses of accidents yield expedient results within expected confidence levels which also aid accident reconstruction [9].
There have been many studies about traffic accident analysis and reconstruction.Kallberg [10] conducted an analysis in Finland and made a report related to his investigations.The report is mainly for the use of the Finnish road accident investigation teams.Formulas for calculating pre-crash speeds from skid marks are presented as well as other methods for estimating speeds and locations of vehicles during different phases of the accident process.Instructions for graphic description of the pre-crash movements of vehicles are also presented.A method for determining the causes of the accident on the basis of accident reconstruction is suggested.Buck et al. [11] showed the benefits of the 3D documentation and computer-assisted, drawn-to-scale 3D comparisons of the relevant injuries with the damages to the vehicle in the analysis of the course of accidents, especially with regard to the impact situation on two examined cases.Davis also [12] studied on attempts to explain the probable reasons of accidents with physical properties and Bayesian networks statistical models together with the aid of artificial intelligence.Xu et al. [13] studied on effects of vehicle impact speed in pedestrian-vehicle accident by comprising reconstruction model and they verified their analysis by ten real-world accident cases to validate their results and to yield an approach for investigators.Raedt and Ponjaert [14] made investigations on predicting atfault car accidents of older drivers and they concluded that although accident prediction is difficult, the predictability of car accidents by neurocognitive measurements and a road test increases when the kind of accident is specified.Yannis et.al.conducted [15] an analysis on driver age and vehicle engine size effects on fault and severity in young motorcyclists accidents.They concluded that accident severity modeling revealed a significant second-order interaction between severity, driver age and two-wheeler engine size.On the contrary, no second-order effects were identified in fault risk modeling.Moreover, a significant effect of driver age on accident fault risk was identified.The effect of engine size was not significant.
Analysis of a sample accident
A passenger car (Aston Martin DB9) and a bus (Volvo B10B) were crashed into each other on an intersection within simulation software.A sample snapshot and instant data related to vehicles are shown in Fig. 1 and Fig. 2 (specifications that are not legible in the figure are depicted under figure captions in italic).
In case of absence of skid marks (mostly anti-lock braking system equipped vehicles), the biggest clue about the speeds was the damage formed on the vehicles.More damage on the vehicle(s), more energy transformed into deformation energy which is defined as crush depth (ε) in terms of meters.For the scenario, vehicles were crashed into each other at angle of 90º with estimated initial speeds and deformations were recorded.Coefficient of friction (μ) on the road surface was assumed as 1.Vehicles with features similar to those in real-world accident were exposed to different deformations (minimum of 500 data for each scenario) that also corresponded to varied speed values.While one of speeds was kept constant, the other's was increased by 5 km/h.Currently in Turkey, determination of impact velocities is conducted by examining skid marks "if applicable".Considering most of the vehicles are equipped with antilock braking system, skid marks may not form on the road surface.In this case, speed analysis cannot be achieved and the situation avoids having contact with scientific analysis.Thus, in simulation, for every speed value, the simulation was repeated and the crush depths were recorded from the simulation report.One of the speed values was kept constant and the other was changed every 20 trials until 500 data were obtained for the scenario to obtain more accurate prediction values.The data were randomly divided into two disjoint subsets using 10-fold cross.The training set had 450 observations (90% of data) and testing set had 50 (10% of data).Consequently, the data of each deformation datum corresponding to each speed value were achieved to be used as teaching data for FITNET model.Two phases can be distinguished during the crash of a vehicle: there is a compression phase and a restitution phase.The compression phase lasts from the contact of the vehicle with an obstacle (another vehicle or anything else) to the point of maximum compression.During this phase, the energy is stocked until the maximum deformation.The restitution phase begins when deformation is maximum and ends when the vehicle separates from the obstacle.During this phase, the deformation energy is released [16].
Overview of FITNET model
The FITNET model consists of 3 layers (input, hidden and output).The input, hidden and output layers have 4, 10 and 2 neurons respectively (Fig. 4).The tan-sigmoid activation function is used in FITNET model in the hidden layers.A pure-linear activation function is used in the output layer and Levenberg-Marquardt (LM) algorithm is utilized for training the networks.FITNET is also a modified form of Multilayer Feed Forward (MFFNN) with the default tan-sigmoid transfer function (Fig. 3a) in the hidden layer and linear transfer function (Fig. 3b) in the output layer.The other important parameters of the FITNET model are the number of epochs, the learning rate and momentum which were selected as 1000, 0.02 and 0.5, respectively.within FITNET were used in order to compare the R and MSE values."trainlm" is a network training function that updates weight and bias values according to Levenberg-Marquardt optimization."trainlm" is often the fastest backpropagation algorithm in the toolbox, and is highly recommended as a first-choice supervised algorithm, although it does require more memory than other algorithms."trainrp" is a network training function that updates weight and bias values according to the resilient backpropagation algorithm.Multilayer networks typically use sigmoid transfer functions in the hidden layers.These functions are often called "squashing" functions, because they compress an infinite input range into a finite output range.Sigmoid functions are characterized by the fact that their slopes must approach zero as the input gets large.This causes a problem when you use steepest descent to train a multilayer network with sigmoid functions, because the gradient can have a very small magnitude and, therefore, cause small changes in the weights and biases, even though the weights and biases are far from their optimal values.The purpose of the resilient backpropagation (Rprop) training algorithm is to eliminate these harmful effects of the magnitudes of the partial derivatives.Only the sign of the derivative can determine the direction of the weight update; the magnitude of the derivative has no effect on the weight update.The size of the weight change is determined by a separate update value.The update value for each weight and bias is increased by a factor "delt_inc" whenever the derivative of the performance function with respect to that weight has the same sign for two successive iterations [18].It was observed that best validation performance and R values were achieved within trainlm training algorithm compared to trainrp function (Fig. 5, Fig. 6, Fig. 7 and Fig. 8).2were utilized in order to observe the prediction performance of the developed model by using MATLAB software [18].
Results and discussion
Deformation is the key parameter to estimate impact velocities.In simulation, 3 parameters related to crash analysis were also examined with deformation (ε) which were deformation energy (E), pre-impact velocity (ν 1 ) and post-impact velocity (ν 2 ).Descriptive statistics for the dataset are given in Table 1.However, for predicting the impact speeds using FITNET models, deformations formed on vehicles (ε1, ε2) were used as input variables (training data) due to its bigger effect on speed analysis than the others and impact speeds (learning data) were the output variables.It was aimed that, in case of absence of clues about impact speed analysis such as skid marks, police reports, witnesses etc., deformation could be used as the main parameter for speed prediction.It may be possible that an application that can run on portable devices may be coded in order to estimate impact speeds by entering average deformations on the collision regions of vehicles.Within performance analysis of FITNET model, it was observed that average of MSE values was in acceptable range and average of R values was close to 1 (Table 2).The results showed that FITNET model with trainlm training function is an appropriate impact velocity predictor.
Conclusions
This study focuses on exhibiting new aspect and scientific approach for determining impact speeds of involvements in a sample most frequent accident occurring in Turkey without regarding to initiative and/or experience of experts.As subject matter, referring to direct proportion between speed and deformation energy, a new systematic approach for determining impact velocities was carried out.vCrash software was used to simulate the accident scene several times.The obtained dataset consisted of 4 parameters related to accident scene where deformations were used as main input parameter for FITNET model.The model was developed to predict impact speeds in which R and MSE values were also calculated.For the scenario, the FITNET model gave acceptable MSE and R values.Based on these approaches, various speed studies may be conducted within different prediction methods in a probable similar accident scene.It will be possible to analyze the impact speeds just by entering average deformation amounts into an application on a portable device at the accident scene without requirement of expensive reconstruction tools and it will be a guide for analyses of other accident types.
Figure 1 .Figure 2 .
Figure 1.Sample snapshot from the first contact moments of the vehicle (Volvo) Pre-impact velocity: 25 km/h Post-impact velocity: 21.3 km/h Deformation: 0.20 m (average on collision region) Friction: 1.00 Figure 2. Sample snapshot from the first contact moments of the vehicles (DB9) Pre-impact velocity: 50 km/h Post-impact velocity: 26.2 km/h Deformation: 0.25 m (average on collision region) Friction: 1.00
expQ
: observed value; cal Q : predicted value _ exp Q : mean predicted value; N: number of data points 4
Table 1 .
Descriptive statistics of the dataset
Table 2 .
Descriptive statistics of the dataset | 3,340.4 | 2016-01-01T00:00:00.000 | [
"Engineering",
"Computer Science"
] |
Energy Flux Characterisation of Atmospheric Pressure Plasma Spray Torches with Passive Thermal Probes
Passive thermal probes were applied on two different plasma spraying devices to gain a detailed understanding of the energy flux towards the substrate under atmospheric pressure. The challenge of very high thermal load was solved by using an advanced time-resolved measuring and evaluation technique. The combination with a controlled movement of the jets allowed to obtain insightful radial profiles. The energy flux to the substrate changes linearly to the electrical input power. When adding diatomic gases (H2/N2) to the gas mixture the energy flux increases significantly, suggesting a more efficient energy transport. For increasing the axial distance, the energy flux shows a quadratic reduction. The obtained radial profiles are exemplarily utilized to show the inhomogeneous effect of powder injection on the energy flux distribution.
Introduction
Plasma spraying is a well-established coating process for various coating materials and substrates. The high deposition rates and unique coating properties have led to a broad use in science and industry ( Ref 1,2). The areas of application range from thermal barrier coatings for energyefficient turbines to wear and corrosion-resistant coatings as well as biocompatible layers in medicine (Ref [3][4][5][6][7][8][9]. Due to the strong dependence of coating properties on process parameters several diagnostic tools have been already used to study aspects of the plasma spray process in the past. Thus, diagnostics play an important role of process control and optimisation. The plasma itself or the effluent, respectively, have been analysed mainly by optical methods, e.g., optical emission spectroscopy, Rayleigh and Raman spectroscopy, schlieren imaging as well as computer tomography (Ref [10][11][12][13][14]. The very high densities of an arc discharge and atmospheric pressure conditions prevent the application of established probe-based diagnostics like Langmuir probes or retarding field analysers. The only exception is enthalpy probes (Ref 15,16) which are remotely related to the passive thermal probes present in this study. The usually injected powder particles have been studied with regard to their temperature and velocity distributions with high-speed cameras, pyrometers or electrical low-pressure impactors (Ref [17][18][19]. Selvan should be mentioned as well, as they measured the radial profile of energy flux as boundary conditions for their model on thermomechanical behaviour. However, to the authors knowledge, there are no diagnostics already available which are capable of describing the interaction of the effluent and powder with the surface of a substrate during deposition. That issue is motivation for the application of passive thermal probes in this study. Passive thermal probes (PTPs) provide insight into the calorimetric interaction between the plasma and the particles and a surface ( Ref 22,23). The probe acts as a regular substrate while depositing, hence the results are directly useful for application-related uses. Via the change of temperature during a deposition process the energy flux can be deduced. This flux is composed of many contributions which among others are related to gas temperature, plasma properties as well as mass and temperature of the layer material.
More recent studies showed the applicability of PTPs in atmospheric pressure plasmas (Ref [24][25][26][27][28]. This present study focuses on the results obtained with PTPs at two different atmospheric plasma spraying sources and on the necessary requirements and development in data processing. The results cover the variation of input power and the addition of molecular gases. Furthermore, several spatial measurements were performed and used for verification of a new time-resolved evaluation procedure. When a substrate is located next to a plasma environment its temperature usually rises due to the higher energy density of a plasma compared to the surrounding. The energy transfer is a sum of several contributions and surface interactions. Figure 1 shows a schematic of a substrate energy balance ( Ref 22). The main contributions during atmospheric plasma spraying are the following: (i) Fast particles, i.e., electrons, ions or neutrals, which impact on the substrate surface and deposit their kinetic energy P part . (ii) Absorbed radiation P rad which is composed of thermal radiation due to elevated temperatures and transitions of excited atoms and molecules. (iii) Due to the high flow of hot gas at atmospheric pressure, forced convection P conv plays an important role when investigating plasma spraying. (iv) In the case of thermal plasma spraying the layer formation consists of macroscopic molten droplets. Their thermal energy and transition enthalpy P mat can raise the substrate temperature as well. (v) The last main contribution stems from chemical reaction happening at the substrate surface P chem . These can be exothermic reactions like conversion reactions or released binding energies during layer formation. Additionally, one has to mention the recombination of dissociated atoms, as molecular gases like hydrogen are regularly added to increase the energy flux ( Ref 29).
To measure the integral energy flux consisting of the mentioned contributions passive thermal probes (PTPs) as illustrated in Fig. 2 are used. A copper plate which acts as a substrate is spot-welded to a type K thermocouple and bias wire. This allows for an accurate and fast monitoring of the substrate temperature. Furthermore, no additional connection to the surrounding leads to a minimal thermal conduction. The steel shielding around the backside of the substrate plate ensures that no additional energy flux is collected. Thus, the only surface exposed to the plasma is the frontside of the copper plate. This well-defined area A S allows for the normalisation of the incoming power P in to an energy flux J in = P/A S which will be discussed in section ''Experimental Setup''.
The results are focused on the applicability of passive thermal probes and the obtained insight into general, process-related dependencies to evaluate the possibilities and limits of this plasma diagnostic. The performed measurements were primarily done without a coating material (i.e., powder injection) to prevent the formation of a layer on the probe substrate which would change its heat capacity. However, some exemplary results with added powders are shown using the time-resolved evaluation method. In particular, the dependence of the energy flux on several discharge parameters of the plasma spraying devices will be discussed.
Experimental Setup
In order to measure the energy flux with a PTP, a specific sequence of different temporal temperature changes is needed as shown in Fig. 3. A single measurement starts with a heating phase when the probe is exposed to the plasma and its temperature increases rapidly followed by a subsequent cooling phase when the exposure is suppressed. This distinct change in probe temperature due to the energy flux can either be caused by turning the plasma on and off or by using a shutter (Ref 31). The time derivative of the substrate temperature T S during the heating phase T S,h and during the cooling phase T S,c is used to calculate the energy influx with the heat capacity of the substrate C S (Ref 27). The assumptions and derivation for that equation can be found in in previous studies (Ref 31,32). The adaption of this measuring principle to plasma spraying devices would make it necessary to turn the plasma on and off instantaneously as a shutter is not provided. However, a DC-jet usually experiences some fluctuation directly after start-up before it reaches a steady state. For that reason, the jet has to be started far off the probe until it has reached its final state. Therefore, the start of the heating phase is realized by moving the jet at its maximum velocity of 500 mm/s to the probe position. Figure 4(a) shows the temporal change of temperature (dT/dt) over the substrate temperature. This way of depicting a temperature course like in Fig. 3 is a helpful tool for analysing the energy flux since the difference of temperature derivations in Eq. 1 can be directly deduced. The measuring procedure begins with the substrate at room temperature. When the jet gets closer the temperature rises, i.e., the derivation becomes positive. To ensure a constant energy flux the jet stops at the substrate position for defined time. Under this condition, the temperature change is almost constant. After the defined waiting time, in this example 0.5 s, the jet continues its movement and moves away from the substrate, thereby decreasing the energy flux. Without the energy flux from the jet, the energy loss induced by the temperature difference between substrate and environment becomes dominant. This leads to a decreasing substrate temperature, thus, a negative derivative until the room temperature is reached again.
This approach allows for the calculation of the energy flux by averaging over the time of constant energy flux. Because the idea of this method goes back to the dTmethod in (Ref 32) it will be referred to as the established method.
The very high energy flux for certain experimental conditions, e.g., short distance or added molecular gases, results in temperatures that could damage the probe. The thermal load can be limited by reducing the stationery time but a duration of at least 0.5 s is needed for a reliable evaluation of the T S (t) curve. That is the incentive to modify the measuring approach for harsh plasma environments as for plasma spraying.
The change is rather simple but has heavy implications on the thermal load and the evaluation of the energy flux in general. Instead of resting the jet at the probe position, the The experiments resulting in Fig. 4(b) and (d) respectively were performed under the same conditions. The average energy flux in Fig. 4(b) is 66 W/cm 2 , the energy flux in the centre of Fig. 4(d) is 63.5 W/cm 2 . They show a good agreement with a difference below 5%. In comparison, the radial profiles of the time-resolved method provide additional information, which can only be deduced by multiple measurements from the established method.
Besides analysing the actual shape, it is possible to determine the width of the profile and its integrate. The integrate can be used to extrapolate the total deposited energy onto a substrate area larger than the probe itself since the entire profile is considered.
The plasma source InoCoat developed by the Co. INOCON Technologie GmbH, Attnang-Puchheim, Austria is a DC-based plasma spraying source with a maximum input power of 12 kW. To achieve a stable plasma an Ar flow between 5 slm and 20 slm is used. Additionally, hydrogen as molecular gas can be added to increase energy flux towards the substrate like in other commercial sources ( Ref 33). The injection of coating material is done radially, thus, probably leading to an inhomogeneous powder distribution as described by Kavka et al. (Ref 34). The jet itself is mounted on a robotic arm to enable free spatial movement. The precise and reproducible movement of the jet is crucial for a homogeneous coating and measurements with PTPs alike. A single PTP is placed in a horizontal guide plate (25 9 17 cm) in an axial distance of 50 mm (Fig. 5 a). For the energy flux measurement, the jet is moved with a velocity of 100 mm/s across the probe as described beforehand.
The second plasma spraying system studied is the F4MB-XL available from OC Oerlikon Management AG, Pfäffikon, Switzerland. It utilizes a DC arc as well but with a much higher input power of up to 55 kW. Thus, a direct comparison is not suitable. Ar is used as main process gas with a flow of up to 100 slm with an optional addition of the molecular gases hydrogen or nitrogen. Again, a robotic arm enables free spatial movement across a passive thermal probe mounted in a slightly larger guide plate (30 9 40 cm), see Fig. 5(b). Side-mounted air nozzles are optionally used for substrate cooling and changing the shape of the effluent. The axial distance is usually kept constant at 120 mm as typical coating distance and the jet is moved with a velocity of 200 mm/s.
Electrical Power and Molecular Gases
The electrical input power is one of the main process parameters for control of the deposition properties. A higher electrical power increases the energy density of the plasma as heat source for the melting of the deposition material. Thus, an adjustment of electrical power has a profound effect on the temperature distribution of particles and their degree of melting. On the other hand, this changes the temperature load of the substrate which can become critical when dealing with heat sensitive materials, e.g., polymers. Figure 6 shows the changing energy flux with only Ar as process gas (black crosses) in dependence on the electrical power increasing from 8 to 34 kW with F4MB torch. It has to be mentioned that the device is not power-but currentregulated, i.e., the setpoint for the current is chosen manually and the applied voltage is adjusted accordingly. This regime leads to slight fluctuations of the power and, hence, a restricted reproducibility for the same current. The electrical power is simply calculated by multiplying the current and voltage.
The evaluation of electrical power and energy flux shows a distinct linear dependence. Therefore, a linear fit is conducted. This result shows a good agreement with similar investigations of a hot plasma jet done by Kewitz et al. (Ref 24). To investigate the influence of additional molecular gases different flows of hydrogen and nitrogen are added. The flows are in the range of 2-14 slm H 2 and 2-10 slm N 2 . The value of the arc current intensity during these measurements is always 600 A. However, an increasing flow of additional molecular gas increases the voltage, thus, increasing the electrical power simultaneously. For that reason, these results are displayed over the power axis in Fig. 6 as well. The measured energy flux increases linearly similar to pure Ar but with a greater slope of (5.9 ± 1.1) W/cm 2 /kW for H 2 and (4.5 ± 1.0) W/cm 2 /kW for N 2 compared to (3.3 ± 0.2) W/cm 2 /kW for Ar. At the same electrical power, e.g., 30 kW, the energy flux of both molecular gases is significantly higher compared to pure Ar. This is related to the increased thermal conductivity of mixtures of Ar with molecular gases (see e.g. Ref 35). The effect is associated also with the released binding energy when dissociated hydrogen or nitrogen atoms recombine with molecules on the substrate surface. Comparing the two molecular gases, H 2 generates a higher energy flux than N 2 at the same electrical power. A possible reason for that is the difference in dissociation energy. Hydrogen has a much lower binding energy of 4.5 eV per molecule than nitrogen (8.7 eV). Thus, hydrogen is more likely to get dissociated and recombined in the process.
Axial Distance
The (axial) distance between the plasma jet and the substrate (probe) is an important and crucial parameter to handle thermal load on the substrate, control layer formation and resulting film properties as well as changing the coating area. At a fixed current of 600 A the distance is varied from 160 mm to the minimal feasible distance using the time-resolved evaluation method. Since the energy flux increases considerably this minimal distance is dependent on gas mixture and represents the limitation of the temperature measurement. The upper limit for probes in the current study is reached for an energy flux of about 1500 W/cm 2 , thus, the minimal distances are 10 mm for 40 slm Ar and 40 mm for additional 10 slm H 2 or N 2 .
The energy flux in Fig. 7 shows a strong decrease with increasing distance. Addition of 10 slm H 2 or N 2 shows an increased energy flux at each distance. The course can be interpolated in good agreement with a square fit and is marked as well. With such quadratic function taken as a basis it can be assumed that the energy flux distribution is cone-shaped with the jet as its origin. In other words, the same power is spread over an area which increases quadratically with the distance, thus, the measured energy flux density decreases accordingly ( Ref 24). The inset in Fig. 7 depicts the energy flux ratios of added H 2 and N 2 compared to pure Ar. The ratios are slightly higher for low distances but are almost constant for distances above 60 mm. An increased ratio suggests an additional transport mechanism for energy at lower distances. A possible mechanism could be the recombination of molecules which should occur predominantly in close vicinity to the jet. As the measurements in Fig. 7 were performed using the time-resolved evaluation method discussed in section ''Experimental Setup'', the associated calculated radial profiles can be analysed likewise. The full with half maximum (FWHM) of the radial profiles is displayed in Fig. 8. The distance between the radial positions left and right of the centre where the energy flux is as close as possible to half the maximum value is used for FWHM. This additional information reveals a linear increase of the FWHM for all gas mixtures. This result confirms the assumption of a cone-shaped energy flux distribution because a linearly increasing diameter matches a quadratically increasing
Radial Profile
A further investigation of the radial profiles was done in order to support the validity of the time-resolved evaluation method. Figure 9 depicts the energy flux of nine repeated measurements using this method compared with the established method which was performed at different radial positions. The good agreement approves the validity of the new method. The radial dependence shows a rapidly decreasing energy flux from the centre (about 60 W/cm 2 ) to remote radial positions. This corroborates the results of Selvan et al. (Ref 20) because their radial profiles show the same shape despite simulating a non-identical plasma source. They calculated a thermal flux of about 150 W/cm 2 in the centre for an identical arc current of 600 A but a smaller axial distance of 8 cm and different gas mixture (25 slm Ar and 3 slm N 2 ). These differences would result in a higher thermal flux in comparison to the parameters used for Fig. 9 and could explain the difference at least partially.
Chen et al. (Ref 15) used optical emission spectroscopy and an enthalpy probe to measure the temperature distribution of a comparable plasma jet. These radial temperature distributions resemble this characteristic shape as well.
Since it is expected that the high gas temperature is one of the main energy flux contributions, the radial energy flux and radial temperature distributions seem to be correlated directly.
The radial distribution of energy flux is utilized for the characterization with injected powder material also. Figure 10 shows the radial energy flux distribution of the InoCoat source under industrial parameters for the deposition of a wear-resistant zinc layer. The investigation of the effect of coating material consists of two separate iterations. One without adding the zinc powder and one with additional powder. This procedure allows to analyse the influence of the powder directly because any change in energy flux is caused by the coating material. An increase in the energy flux is clearly visible in the centre of the jet but not at the edges below -20 mm or above 20 mm (Fig. 10). This indicates that the hot, molten zinc particles are primarily present in the centre of the effluent. The shape of two separate maxima could be observed when injecting the zinc particles. It suggests that the different shape is related to the radial insertion of the powder with a mean particle size of 30 lm from two opposing directions. It was already reported that these circumstances can lead to an asymmetrical material distribution (Ref 34). Due to the additional layer being very thin compared to the copper substrate of the probe, no change in heat capacity could be (InoCoat, flow 10 slm Ar, current \ 100 A, axial distance 50 mm, powder rate 6 g/min) determined afterwards. The application of PTPs is proposed as a reliable diagnostic to evaluate the spatial distribution of coating material from the substrate perspective.
Profile Tailoring
For the purpose of testing further potential applications of the advanced time-resolved evaluation method, two-dimensional studies were performed. This characterization exploits the spatial information of two separate measuring passes. By changing the path of the jet movement across the probe, different axis of the energy flux can be incorporated. In this case, one horizontal and one vertical path is chosen. This allows for the calculation of a 2-D profile. To illustrate a change in the jet profile, two side-mounted air nozzles are used. They make it possible to manually change the shape of the effluent and are usually used for substrate cooling. Figure 11 displays the integrated 2-D profile jet profile for two different air nozzle positions at an air pressure of 2 bar. The first position in Fig. 11(a) is almost parallel to the jet direction, the second one in Fig. 11(b) is focused on the substrate surface at a distance of 120 mm. A parallel orientation of the air nozzles seems to have a minor influence on the shape as the profile is still similar to a rotationally symmetrical course of a 1-D profile in Fig. 9. The other depiction, however, shows a severe deformation. The profile is broadened and resembles a mountain ridge. Related to the deposition process this implies a coverage of a wider area at the same energy flux, hence, reducing the inhomogeneity on the substrate.
In addition, the deposited power can be derived by integrating the 2D profiles over the area. For a quadratic area with a side length of 400 mm around the centres in
Conclusions and Outlook
This study shows the applicability of passive thermal probes for the characterisation of high-power plasma spraying jets under atmospheric pressure. The capability to measure the energy flux from the point of view of an ordinary substrate provides insight into the interaction between the plasma source and substrate surface. The newly time-resolved evaluation method supplies additional spatial information about the process. The calorimetric measurements show a linear dependency of the energy flux on the electrical power. Compared to pure argon plasma, the addition of molecular gases results in steeper slopes, suggesting a more efficient energy transport. A coneshaped spatial distribution is present for most parameters and not altered by adding molecular gases. Measurements with coating material should reveal the spatial distribution of the powder in the effluent. Moreover, two-dimensional spatial profiles are used to illustrate the influence of external air nozzles. When correlated with other diagnostics, e.g., thin film analysis, optical methods, passive thermal probes could be used as versatile and powerful diagnostic also for plasma spraying.
Funding Open Access funding enabled and organized by Projekt DEAL.
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. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. | 5,455.8 | 2022-11-09T00:00:00.000 | [
"Physics",
"Engineering"
] |
Kinetic Study and Catalytic Activity of Cr3+ Catalyst Supported on Calcium Silicate Hydrates for VOC Oxidation
Volatile organic compounds (VOCs) are pollutants that pose significant health and environmental risks, necessitating effective mitigation strategies. Catalytic oxidation emerges as a viable method for converting VOCs into non-toxic end products. This study focuses on synthesizing a catalyst based on calcium silicate hydrates with chromium ions in the CaO-SiO2-Cr(NO3)3-H2O system under hydrothermal conditions and evaluating its thermal stability and catalytic performance. A catalyst with varying concentrations of chromium ions (10, 25, 50, 100 mg/g Cr3+) was synthesized in unstirred suspensions under saturated steam pressure at a temperature of 220 °C. Isothermal curing durations were 8 h, 16 h, and 48 h. Results of X-ray diffraction and atomic absorption spectroscopy showed that hydrothermal synthesis is effective for incorporating up to 100 mg/g Cr3+ into calcium silicate hydrates. The catalyst with Cr3+ ions (50 mg/g) remained stable up to 550 °C, beyond which chromatite was formed. Catalytic oxidation experiments with propanol and propyl acetate revealed that the Cr3+ catalyst supported on calcium silicate hydrates enhances oxygen exchange during the heterogeneous oxidation process. Kinetic calculations indicated that the synthesized catalyst is active, with an activation energy lower than 65 kJ/mol. This study highlights the potential of Cr3+-intercalated calcium silicate hydrates as efficient catalysts for VOC oxidation.
Introduction
Environmental pollution causes various negative effects not only on living organisms but also on plant life [1].Pollutants can persist in the environment for extended periods, causing more significant and widespread environmental damage [2].One of the main air pollutants is volatile organic compounds (VOCs) [3].VOCs are various organic chemicals that have a high vapor pressure at room temperature [4].They typically contain elements such as hydrogen, oxygen, chlorine, bromine, sulfur, fluorine, or nitrogen, and are mostly emitted during the production of various organic compounds (paints, glues, solvents, additives, etc.) and the burning of fuels such as gasoline, wood, coal, or natural gas [5].Due to their negative effect on the environment and human health, it is important to find ways to mitigate their concentration.Various research efforts have been directed towards technologies to remove VOCs from the environment and decrease their emissions from industry.
VOCs removal methods can be classified into two main categories: recovery methods and destructive methods.Recovery methods are technologies that recover VOCs through physical separation [6], such as adsorption [7], absorption [8], condensation [9], and membrane separation [10].These technologies are effective for recovering valuable VOCs but are expensive, energy-inefficient, complex, and often create secondary waste [6].Destructive methods convert VOCs into carbon dioxide and water, i.e., harmless end products, via various chemical and biological processes.These technologies include thermal and catalytic incineration [11], photolysis [12], catalytic combustion [13], electrochemical oxidation [14], microwave-assisted catalysis [15], photocatalytic decomposition [16], biodegradation [17], and catalytic oxidation [18].Each method has advantages and disadvantages; however, one of the most effective and economically feasible methods is catalytic oxidation.Using this method VOCs are oxidized using suitable catalysts at much lower temperatures (250-500 • C) compared to thermal oxidation processes [19].Catalytic oxidation also works at low concentrations and with large amounts of VOCs.Usually, catalysts used for VOC oxidation are noble-metal-based, such as platinum, gold, and palladium [20].Unfortunately, these metals are very expensive and have limited availability, creating a demand for catalysts based on transition metals.
Chromium is a heavy metal known to be a transitional element with many industrial uses [21].Chromium-based catalysts are well known in organic compound production.They are essential for ethylene polymerization and are widely applied in the industrial production of polyethylene and 1-hexene [22].Chromium-based catalysts show high structural diversity while also being selective and active [23].Typically, these catalysts consist of chromium supported on oxide with a high surface area and porosity, most often silica [22,24].Calcium silicates and calcium silicate hydrates can be considered as innovative and environmentally friendly catalyst supports because, after usage, they can be used as additives for ordinary Portland cement, thereby avoiding secondary pollution by landfilling spent catalysts [25,26].Calcium silicate hydrates (CSH) are silicic acid salts, whose basicity depends on the calcium oxide (CaO) and silicon dioxide (SiO 2 ) ratio, marked as C/S.This system has an exceptional level of structural complexity.It is known that there are more than 40 crystalline calcium silicate hydrate phases with C/S ratios varying from 0.44 to 3 [27,28].Due to the varying basicity of CSH, it is possible to create different chromium-based catalysts using a diverse range of C/S ratios.However, research on chromium catalysts supported by calcium silicate hydrates is scarce [29,30].Niuniavaite et al. [29] investigated the catalytic activity of semi-crystalline calcium silicate hydrate (CaO/SiO 2 = 1.5) with intercalated chromium ions for propanol oxidation, determining that a 95% conversion degree of propanol into carbon dioxide was reached at around 240 • C.
Even though there are studies on chromium-based catalysts with CSH supports, there appears to be a lack of kinetic research on the effectiveness of such products.Highlighting the novelty, this research addresses the gap by investigating the kinetic parameters of VOC oxidation using a chromium catalyst supported on CSH.We used a lower molar ratio of CaO/SiO 2 (1.0) to synthesize more stable calcium silicate hydrates, aiming to enhance the stability and efficiency of the catalyst.Unlike previous work, this study includes detailed kinetic calculations, such as determining the Arrhenius constant and activation energy, which are crucial for understanding the catalytic mechanisms and for the future evaluation and optimization of the catalyst.While the previous study focused on propanol [29], this study extends the investigation to other VOCs, providing a broader scope of application for the catalyst.Understanding these kinetic parameters is essential for optimizing catalytic processes, enabling better modeling of VOC behavior, optimizing industrial processes, and contributing to the development of safer and more efficient catalytic systems for VOC mitigation [19,31].
Therefore, the aim of this work was to synthesize a catalyst based on calcium silicate hydrates and chromium ions in the CaO-SiO 2 -Cr(NO 3 ) 3 -H 2 O system under hydrothermal conditions and determine its thermal stability and catalytic activity.
Materials and Synthesis
In this work, the following reagents were used:
Hydrothermal synthesis: For the synthesis, the mixture of amorphous silicon dioxide and calcium oxide was used with the molar ratio of CaO/SiO 2 equal to 1.0.The dry primary mixture was mixed with a chromium nitrates solution to reach a water-to-solid ratio of 10.0:1.0.The metal ion content for 1 g of the solid mixture was 10, 25, 50, or 100 mg.The hydrothermal synthesis was carried out in unstirred suspensions in 25 mL polytetrafluoroethylene cells, placed in a stainless-steel autoclave (Moline, IL, USA), under saturated steam pressure at a temperature of 220 • C. Isothermal curing durations were 8 h, 16 h, and 48 h. and additional argon gas pressure of 4 bar was used.The temperature was reached within 2 h.After hydrothermal treatments, the autoclave was quenched to room temperature.The suspensions were filtered, and the products were rinsed with acetone to prevent carbonization, dried at 80 • C ± 5 for 24 h, and sieved (<80 µm).
Methods
A Nabertherm LH 15/13 (Nabertherm GmbH, Bremen, Germany) high-temperature furnace was used for the calcination of the synthesis products in a temperature range of 250-1000 • C, at a heating rate of 500 • C per hour, with a 1 h duration at the selected temperature.
Phase composition of synthesis products was determined using X-ray diffraction (XRD) powder analysis on a D8 Advance diffractometer (Bruker AXS, Karlsruhe, Germany) operating at a tube voltage of 40 kV and tube current of 40 mA.The X-ray beam was filtered with Ni 0.02 mm filter to select the CuKα wavelength.Diffraction patterns were recorded in a Bragg-Brentano geometry using a fast-counting detector, Bruker LynxEye (Bruker AXS, Karlsruhe, Germany), based on silicon strip technology.Specimens were scanned over a range of 3-70 • (2θ) at a scanning speed of 6 • /min using a coupled two theta/theta scan type.
XRD spectra were used to calculate the degree of crystallinity.For the calculations, Topas 4.1 software (Bruker AXS, Karlsruhe, Germany) and the following equations were used: Crystallinity, % = 100% − Amorphous, % The measurements of thermal stability conducted using a Linseis PT1000 instrument (Linseis Massgeraete GmbH, Selb, Germany) were under the following conditions: heating rate of 15 • C/min, temperature range 30-1000 • C, nitrogen atmosphere, ceramic sample handlers, platinum crucibles, and sample mass of approximately 13 mg.
The concentration of Cr 3+ ions was determined using a Perkin-Elmer Analyst 4000 atomic absorption spectrometer (Perkin Elmer, Waltham, MA, USA) with parameters as follows: wavelength-357.87nm, hollow cathode lamp current (I)-30 mA, flame type-C 2 H 2 -air, oxidant air flow-10 L/min, and acetylene flow = 2.5 L/min.All tests were repeated three times.
Propanol (purity > 98%) and propyl acetate (purity > 98%) were used as the comparative volatile organic compounds (VOCs) for the catalytic oxidation experiments.The experiments were conducted using 0.2 g of catalyst placed inside a fixed-bed quartz reactor with a coil preheater operating in steady state conditions.This reactor was housed within a Nabertherm tube furnace LH 15/13 (Nabertherm GmbH, Bremen, Germany) to ensure a stable temperature, which was accurately monitored by a K-type thermocouple positioned inside the reactor.The reactor's inlet and outlet were equipped with specialized points for collecting gas flow samples and measuring CO and CO 2 concentrations, which were directly connected to a TESTO 445 unit (Testo, Titisee-Neustadt, Germany).The catalytic oxidation process was carried out with various airflow rates ranging between 200 and 370 mL/min, saturated with VOC concentrations ranging from 800 to 1000 ppm.The concentration of VOCs in the gas stream was analyzed using a Perkin Elmer Clarus 500 GC/MS system (Perkin Elmer, Waltham, MA, USA), fitted with a COL-ELITE 5MS (Perkin Elmer, Waltham, MA, USA) capillary column that was 30 m in length and 0.25 mm in internal diameter.Standards of VOCs were prepared by evaporating a measured volume of liquids in a measured volume of air.
Hydrothermal Synthesis of Calcium Silicate Hydrates with Intercalated Cr 3+ Ions
According to the scientific literature [32], the formation of calcium silicate hydrates depends on the synthesis conditions and the nature of the raw materials.Thus, to determine the influence of Cr 3+ ions on the formation of calcium silicate hydrates, firstly, the formation of calcium silicate hydrates in a pure calcium oxide, silicon dioxide, and water system was investigated.The phase composition of the synthesis products was determined by XRD analysis, with results presented in Figure 1.Prolonging the synthesis duration to 16 h led to the formation of the higher basicity calcium silicate hydrates, hillebrandite (Ca2SiO3(OH)2) and foshagite (Ca4Si3O9(OH)2), in the synthesis product (Figure 1a).Small diffraction peaks characteristic of xonotlite were still identified.It is worth noting that the molar ratio of CaO/SiO2 in hillebrandite (Ca/SiO2 = 2.0) and foshagite (Ca/SiO2 = 1.33) is higher compared to the initial mixture (Ca/SiO2 = 1.0).This is likely due to lower reactivity and solubility of amorphous silicon dioxide compared to calcium oxide, resulting in an excess of calcium oxide in the liquid medium, which led to the formation of higher basicity silicates.Similar results have been presented in the literature [27].As expected, prolonging the synthesis duration to 48 h negatively affected the stability of hillebrandite and foshagite (Figure 1a).Foshagite fully and hillebrandite partially recrystallized into xonotlite, whose molar ratio corresponds to the initial mixture.Additionally, small-intensity diffraction peaks characteristic of gyrolite were also identified.It was determined that after 8 h of synthesis at 220 1a).It is worth mentioning that semicrystalline calcium silicate hydrate C-S-H(I) can also form in the synthesis products; however, its diffraction peaks overlap with other CSH phases.Additionally, under these conditions, intensive diffraction peaks characteristic of unreacted portlandite were identified.
Prolonging the synthesis duration to 16 h led to the formation of the higher basicity calcium silicate hydrates, hillebrandite (Ca 2 SiO 3 (OH) 2 ) and foshagite (Ca 4 Si 3 O 9 (OH) 2 ), in the synthesis product (Figure 1a).Small diffraction peaks characteristic of xonotlite were still identified.It is worth noting that the molar ratio of CaO/SiO 2 in hillebrandite (Ca/SiO 2 = 2.0) and foshagite (Ca/SiO 2 = 1.33) is higher compared to the initial mixture (Ca/SiO 2 = 1.0).This is likely due to lower reactivity and solubility of amorphous silicon dioxide compared to calcium oxide, resulting in an excess of calcium oxide in the liquid medium, which led to the formation of higher basicity silicates.Similar results have been presented in the literature [27].As expected, prolonging the synthesis duration to 48 h negatively affected the stability of hillebrandite and foshagite (Figure 1a).Foshagite fully and hillebrandite partially recrystallized into xonotlite, whose molar ratio corresponds to the initial mixture.Additionally, small-intensity diffraction peaks characteristic of gyrolite were also identified.
Cr 3+ ions strongly affected the phase composition of synthesis products (Figure 1).XRD results showed that, after 8 h of synthesis, in the system with 25 mg/g of Cr 3+ ions, a mixture of calcium silicate hydrates, xonotlite, tobermorite, and gyrolite, was formed (Figure 1b).Although the phase composition of the product was the same as in the pure system, the intensity of diffraction peaks was significantly higher in the system with chromium ions.On the other hand, the diffraction peaks characteristic of portlandite were less intensive.The intensity of diffraction peaks characteristic of all formed calcium silicate hydrates increased while those of portlandite decreased with prolonged synthesis duration at 16 h.Finally, after 48 h of synthesis, xonotlite was the only calcium silicate hydrate formed in the products (Figure 1b).However, quite intensive diffraction peaks characteristic of unreacted portlandite were still identified in the XRD pattern.
The results of atomic absorption spectroscopy showed that the concentration of Cr 3+ ions in the liquid medium obtained after synthesis slightly depends on the duration of synthesis.It was measured that, after 8 h and 16 h of synthesis, the concentration of Cr 3+ ions in the liquid medium was 1.67 mg/L and 3.7 mg/L, respectively.Since the initial concentration of metal ions in the liquid medium was 2500 mg/L, it can be stated that only an insignificant part of these ions was not intercalated into the structure of calcium silicate hydrates.Due to formation of a highly crystalline calcium silicate hydrate-xonotlite-the concentration of Cr 3+ ions in the liquid medium increased to 42.7 mg/L.However, the amount of these ions in the liquid medium still did not exceed 2% of the initial amount.It can thus be stated that during hydrothermal synthesis, more than 98% of Cr 3+ ions were incorporated into the structure of the synthesis product.
Further analysis of the liquid medium showed that the amount of calcium ions released from solid compounds increased from 9.7 mg/g to 16.2 mg/g with an increase in synthesis duration from 8 h to 48 h.It was calculated that the moles of intercalated chromium ions (25 mg = 0.48 mmol) correspond to the moles of released calcium ions (0.24-0.41 mmol).Probably, during synthesis, the chromium ions replaced calcium ions in the structure of calcium silicate hydrates.Similar findings have been presented in the literature [33].
The simultaneous thermal analysis results of synthetic xonotlite with intercalated chromium ions are presented in Figure 2a.The first intensive endothermic effect at 124 • C can be assigned to the removal of adsorbed water.The second intensive doublet at 445 • C and 477 • C can be attributed to the dehydration of unreacted portlandite.The third effect (685 • C), during which the sample lost 1.6% of its mass, can be assigned to the decomposition of calcium carbonate or the formation of chromium-containing compounds.Theoretically, based on mass loss, the possible amount of calcium carbonate in the system is lower than 3.6%, thus.due to the low amount and overlapping of peaks, diffraction peaks of this compound were not identified in the XRD pattern (Figure 1b).Finally, the effect at 806 • C can be assigned to solid phase sintering (Figure 2a) [34].It is worth noting that no exothermic effect was observed in the temperature range of 800-900 • C, indicating that semicrystalline calcium silicate hydrates such as C-S-H(I) and C-S-H(II) were not formed during hydrothermal synthesis.Further increasing the Cr 3+ ion concentration to 100 mg/g negatively affected the formation of CSH because, after 8 h and 16 h of synthesis, only traces of xonotlite and gyrolite were obtained (Figure 3b).After 48 h of synthesis, the intensity of diffraction peaks characteristic of gyrolite and xonotlite increased; however, they remained of low intensity.The analysis of the liquid medium showed that the concentration of Cr 3+ ions in the liquid medium was lower than 10 mg/L under all experimental durations.Thus, more than 99.9% (99.9 mg/g) of chromium ions were combined by the synthesis products.As in the previous case, the moles of intercalated chromium ions (1.92 mmol) correspond to the moles of calcium ions released into the liquid medium (1.93 mmol).Increasing the chromium ion concentration in the system to 50 mg/g positively affected the reactivity of portlandite because it was fully reacted at the beginning of synthesis (8 h) (Figure 3a).It was determined that after 8 h of synthesis, a mixture of xonotlite and lower basicity compounds (gyrolite and Z-phase) was formed.By prolonging synthesis duration to 16-48 h, Z-phase became metastable and recrystallized to xonotlite and gyrolite.It is worth mentioning that the diffraction peaks characteristic of these compounds were quite low in intensity compared to previously discussed systems.The analysis of the liquid medium showed that, despite the duration of synthesis, all Cr 3+ ions (50 mg/g) were intercalated into the structure of the synthesis products because their concentration in the liquid medium did not exceed the detection limit of AAS.Meanwhile, the concentration of calcium ions was 3680 mg/L, corresponding to 36.8 mg of Ca 2+ per gram of the solid mixture.It was calculated that 0.96 mmol of chromium was combined per gram of solid material and 0.92 mmol of calcium was released.
The obtained results are in good agreement with the STA data (Figure 2b).The first effect can be attributed to the removal of adsorbed water and partial dehydration of gyrolite.The second effect (298 • C) is not typically associated with either gyrolite or xonotlite.It is probably related to the removal of intercalated nitrate anions from the structure of gyrolite [35] or dehydration of amorphous compounds.Small endothermic effects at 558 • C and 685 • C are related to the formation of compounds containing chromium ions and the decomposition of calcium carbonate, respectively.The exothermic effect at 853 • C is typical of the recrystallization of lower basicity calcium silicate hydrates to wollastonite.
Further increasing the Cr 3+ ion concentration to 100 mg/g negatively affected the formation of CSH because, after 8 h and 16 h of synthesis, only traces of xonotlite and gyrolite were obtained (Figure 3b).After 48 h of synthesis, the intensity of diffraction peaks characteristic of gyrolite and xonotlite increased; however, they remained of low intensity.The analysis of the liquid medium showed that the concentration of Cr 3+ ions in the liquid medium was lower than 10 mg/L under all experimental durations.Thus, more than 99.9% (99.9 mg/g) of chromium ions were combined by the synthesis products.As in the previous case, the moles of intercalated chromium ions (1.92 mmol) correspond to the moles of calcium ions released into the liquid medium (1.93 mmol).Further increasing the Cr 3+ ion concentration to 100 mg/g negatively affected the formation of CSH because, after 8 h and 16 h of synthesis, only traces of xonotlite and gyrolite were obtained (Figure 3b).After 48 h of synthesis, the intensity of diffraction peaks characteristic of gyrolite and xonotlite increased; however, they remained of low intensity.The analysis of the liquid medium showed that the concentration of Cr 3+ ions in the liquid medium was lower than 10 mg/L under all experimental durations.Thus, more than 99.9% (99.9 mg/g) of chromium ions were combined by the synthesis products.As in the previous case, the moles of intercalated chromium ions (1.92 mmol) correspond to the moles of calcium ions released into the liquid medium (1.93 mmol).Summarizing the obtained data, it is possible to state that ion exchange reactions between calcium and chromium proceeded during the hydrothermal synthesis of calcium silicate hydrate.As a result, the molar ratio of CaO/SiO 2 in the final product decreases, leading to the formation of lower basicity CSH.This is in good agreement with data in the literature, which observed that CSH with a molar ratio of CaO/SiO 2 lower than 1.0 is formed in the mixtures with CaO/SiO 2 = 1.5 [29].
Thermal Stability of Calcium Silicate Hydrates with Intercalated 50 mg/g of Cr 3+ Ions
The thermal stability of catalysts is a crucial parameter that can determine their potential application.For this reason, the sample obtained after 16 h of synthesis in the mixture with 50 mg/g of Cr 3+ ions was calcined in the temperature range of 250-1000 • C.This sample was chosen because portlandite was fully reacted and two stable calcium silicate hydrates (gyrolite and xonotlite) were formed.
It was determined that after calcination at 250 • C, the intensity of diffraction peaks characteristic of gyrolite decreased due to the removal of interlayer water (Figure 4) [36].A further increase in temperature to 400 • C led to the full dehydration of gyrolite.It is worth noting that during dehydration of gyrolite, truscottite, which has diffraction peaks close to those of gyrolite, is formed [36].However, in XRD spectra of products calcined at 250-350 • C, truscottite was not identified due to the low intensity of diffraction peaks and insignificant shifts in their position.Probably, this is the result of the intercalated chromium ions in the structure of gyrolite.
After calcination at 550 • C, chromium ions reacted with calcium silicate hydrates and formed calcium chromatite (CaCrO 4 ) (Figure 4).Similar results have been obtained by other authors in similar systems [37].It is worth mentioning that the formation of chromatite leads to the decrease in the catalytic activity of synthesis products for VOCs [29].It was determined that a further increase in calcination temperature to 700 • C led to further dehydration of xonotlite (only the main peak was identified) and an increase in intensity of diffraction peaks characteristic of chromatite.Meanwhile, after calcination at 800 • C, xonotlite fully dehydrated and wollastonite (CaSiO 3 ) was formed.Finally, after calcination at 1000 • C, intense diffraction peaks characteristic only of wollastonite and chromatite were identified in the XRD pattern (Figure 4).formed calcium chromatite (CaCrO4) (Figure 4).Similar results have been obtained by other authors in similar systems [37].It is worth mentioning that the formation of chromatite leads to the decrease in the catalytic activity of synthesis products for VOCs [29].It was determined that a further increase in calcination temperature to 700 °C led to further dehydration of xonotlite (only the main peak was identified) and an increase in intensity of diffraction peaks characteristic of chromatite.Meanwhile, after calcination at 800 °C, xonotlite fully dehydrated and wollastonite (CaSiO3) was formed.Finally, after calcination at 1000 °C, intense diffraction peaks characteristic only of wollastonite and chromatite were identified in the XRD pattern (Figure 4).The temperature of calcination influences the crystallinity of materials, which can determine the activity of materials.For the calculations of crystallinity, the global area and reduced area of XRD patterns was calculated using Topas 4.1 software.Using these values, crystallinity was calculated by Equations ( 1) and ( 2), and the obtained data are presented in Figure 5.It was calculated that the crystallinity of the sample obtained after synthesis was 66.5%.This value slightly decreased to 59% with an increase in calcination temperatures up to 350 • C. The decrease in crystallinity is related to the removal of adsorbed water and partial dehydration of gyrolite (Figures 2b and 4).Due to the full dehydration of gyrolite and partial dehydration of xonotlite, a sharp decrease in crystallinity (to 24.4%) was observed at temperatures from 400 • C to 500 • C (Figure 5).The formation of crystalline chromatite led to the increase in crystallinity to 38.6% at 600 • C; however, this value decreased to 25% at 700 • C. The second decrease in crystallinity can be explained by the dehydration of xonotlite.The formation of wollastonite at temperatures above 800 • C led to an increase in crystallinity, and after calcination at 1000 The temperature of calcination influences the crystallinity of materials, which can determine the activity of materials.For the calculations of crystallinity, the global area and reduced area of XRD patterns was calculated using Topas 4.1 software.Using these values, crystallinity was calculated by Equations ( 1) and ( 2), and the obtained data are presented in Figure 5.It was calculated that the crystallinity of the sample obtained after synthesis was 66.5%.This value slightly decreased to 59% with an increase in calcination temperatures up to 350 °C.The decrease in crystallinity is related to the removal of adsorbed water and partial dehydration of gyrolite (Figures 2b and 4).Due to the full dehydration of gyrolite and partial dehydration of xonotlite, a sharp decrease in crystallinity (to 24.4%) was observed at temperatures from 400 °C to 500 °C (Figure 5).The formation of crystalline chromatite led to the increase in crystallinity to 38.6% at 600 °C; however, this value decreased to 25% at 700 °C.The second decrease in crystallinity can be explained by the dehydration of xonotlite.The formation of wollastonite at temperatures above 800 °C led to an increase in crystallinity, and after calcination at 1000 °C, only crystalline phases were present in the sample.
Catalytic Activity of Calcium Silicate Hydrate with Intercalated Cr 3+ Ion
The catalytic activity of the synthesized (220 °C, 16 h) and additionally calcined (350 °C) sample was evaluated through the complete oxidation of propanol and propyl acetate in an air stream.A calcination temperature of 350 °C was chosen to obtain a stable structure of the catalyst in the investigated temperature interval.Meanwhile, propanol
Catalytic Activity of Calcium Silicate Hydrate with Intercalated Cr 3+ Ion
The catalytic activity of the synthesized (220 • C, 16 h) and additionally calcined (350 • C) sample was evaluated through the complete oxidation of propanol and propyl acetate in an air stream.A calcination temperature of 350 • C was chosen to obtain a stable structure of the catalyst in the investigated temperature interval.Meanwhile, propanol and propyl acetate were chosen for comparison to identify the more suitable candidate for subsequent kinetic experiments.Since the catalytic activity is highly dependent on the type of VOC, selecting a contaminant that can be completely oxidized within the operating temperature range is advantageous.The primary product of complete oxidation is carbon dioxide, making the key performance parameter the reduction in VOC concentration relative to CO 2 formation.Due to slight variations in the initial concentration of contaminants, all measured concentration values were normalized and are reported per gram of catalyst per gram of propanol or propyl acetate in the incoming stream.The reduction in VOC concentration is presented as a conversion, in percentage units, while the selectivity of the catalysts was assessed based on the amounts of intermediates detected in the outgoing flow.The experiments were conducted within a temperature range of 150 to 300 • C, with the temperature increasing by approximately 25 • C every hour.
At an initial temperature of 150 • C, both samples exhibited apparent performance in reducing the concentration of VOCs (Figure 6).However, this reduction can be attributed to adsorption rather than catalytic oxidation, as indicated by the absence of CO 2 in the outgoing stream.The catalyst showed greater adsorptive affinity towards propyl acetate, with a reduction of 69% in its concentration compared to 31% for propanol.This could be explained by the higher boiling point and molar mass of propyl acetate.Adsorption influenced the overall process even at temperatures up to 250 • C. As the temperature in the catalyst bed increased, there were sharp rises in CO 2 concentrations and sudden temperature spikes due to the exothermic nature of the oxidation reaction.CO 2 production began to increase at 200 • C for both volatiles, indicating similar light-off temperatures.This was supported by the appearance of CO in the outgoing stream, suggesting that incomplete catalytic oxidation reactions were occurring alongside the formation of CO 2 .The catalyst demonstrated higher catalytic activity towards propyl acetate, evidenced by a sharper increase of CO 2 concentration.The convergence of the conversion and CO 2 accumulation curves suggests a transition from adsorption to catalytic oxidation with rising temperature.The catalyst achieved 97% conversion at around 300 • C for propyl acetate, while for propanol, it reached only 76%.This indicated that propyl acetate would be the better option for kinetic experiments because it achieved higher conversion and, with a slight increase of temperature, the complete oxidation of VOCs will occur.
Monitoring the outgoing gas stream with a CO probe and GC/MS revealed the presence of incomplete catalytic oxidation products, specifically intermediates (Figure 7).Carbon monoxide (CO) typically forms at the onset of catalytic oxidation and is rapidly oxidized to CO 2 as the temperature rises.Thus, CO formation can serve as an indicator of catalytic activity.The synthesized sample began producing CO at the same temperatures for both propanol and propyl acetate, peaking at 273 and 190 mg/m 3 at 300 • C, respectively.By comparing CO formation curves, it is clear that the oxidation of propyl acetate produced less CO, reflecting its higher apparent selectivity.
However, GC/MS analysis indicated more intermediates were produced during the complete oxidation of propyl acetate, namely propanol and acetic acid (Figure 7).Both intermediates formed because of a hydration reaction on the surface of the catalyst, and their formation was detected at the initial temperature of 150 • C.This indicates that the hydration reaction does not require high activation energy and is probably favored by adsorption.Both compounds reached their peak concentrations at 200 • C and were completely oxidized together with propyl acetate when the temperature was increased.It is noticeable that acetic acid was apparently oxidized much more easily on the surface of the catalyst, as its detected concentrations were three times lower.This suggests that acetic acid has a higher oxidation rate compared to propanol, contributing to the overall efficiency of propyl acetate oxidation.
suggesting that incomplete catalytic oxidation reactions were occurring alongside the formation of CO2.The catalyst demonstrated higher catalytic activity towards propyl acetate, evidenced by a sharper increase of CO2 concentration.The convergence of the conversion and CO2 accumulation curves suggests a transition from adsorption to catalytic oxidation with rising temperature.The catalyst achieved 97% conversion at around 300 °C for propyl acetate, while for propanol, it reached only 76%.This indicated that propyl acetate would be the better option for kinetic experiments because it achieved higher conversion and, with a slight increase of temperature, the complete oxidation of VOCs will occur.Monitoring the outgoing gas stream with a CO probe and GC/MS revealed the presence of incomplete catalytic oxidation products, specifically intermediates (Figure 7).Carbon monoxide (CO) typically forms at the onset of catalytic oxidation and is rapidly oxidized to CO2 as the temperature rises.Thus, CO formation can serve as an indicator of catalytic activity.The synthesized sample began producing CO at the same temperatures for both propanol and propyl acetate, peaking at 273 and 190 mg/m 3 at 300 °C, respectively.By comparing CO formation curves, it is clear that the oxidation of propyl acetate produced less CO, reflecting its higher apparent selectivity.However, GC/MS analysis indicated more intermediates were produced during the complete oxidation of propyl acetate, namely propanol and acetic acid (Figure 7).Both intermediates formed because of a hydration reaction on the surface of the catalyst, and their formation was detected at the initial temperature of 150 °C.This indicates that the hydration reaction does not require high activation energy and is probably favored by adsorption.Both compounds reached their peak concentrations at 200 °C and were completely oxidized together with propyl acetate when the temperature was increased.It is noticeable that acetic acid was apparently oxidized much more easily on the surface of the catalyst, as its detected concentrations were three times lower.This suggests that acetic acid has a higher oxidation rate compared to propanol, contributing to the overall efficiency of propyl acetate oxidation.
The catalytic oxidation of propanol produces a peculiar intermediate-isopropanol.Isopropanol formation occurred at the same point where catalytic oxidation overtook adsorption, with a peak concentration at 275 °C (Figure 7).Isopropanol is more challenging to oxidize than propanol, thus its concentration decreased only slowly with increasing temperature in the catalyst bed, not disappearing from the stream even at 300 °C.Isopropanol forms through the interaction between propanol and the catalyst surface, specifically via the dehydration of propanol.The results of the catalytic oxidation of both compounds indicate that water vapor played a crucial role in the reactions occurring on The catalytic oxidation of propanol produces a peculiar intermediate-isopropanol.Isopropanol formation occurred at the same point where catalytic oxidation overtook adsorption, with a peak concentration at 275 • C (Figure 7).Isopropanol is more challenging to oxidize than propanol, thus its concentration decreased only slowly with increasing temperature in the catalyst bed, not disappearing from the stream even at 300 • C. Isopropanol forms through the interaction between propanol and the catalyst surface, specifically via the dehydration of propanol.The results of the catalytic oxidation of both compounds indicate that water vapor played a crucial role in the reactions occurring on the surface of the catalyst.Structural water acted in cycles in both hydration and dehydration reactions.Since higher conversion was achieved for propyl acetate oxidation, this volatile was used for kinetic experiments.
Kinetics of Propyl Acetate Complete Oxidation Reaction on the Surface of Calcium Silicate Hydrate with Intercalated Cr 3+ Ions
The kinetic parameters of propyl acetate complete catalytic oxidation were determined with a constant concentration stream (1000 ppm) flowing through a catalyst bed at varying flow rates of 200-370 mL/min.Flows for catalytic oxidation were prepared by mixing vapors of VOCs into an air stream.By adjusting the flow rates of these streams, desired concentrations of VOCs were achieved, which were analyzed by GC/MS.These flow rates were used to calculate the contact duration of propyl acetate, which ranged from 3.79 to 7.44 s (Figure 8).By varying the flow rates and hence the contact durations, the relationship between these variables and the catalytic oxidation efficiency was observed.As expected, longer contact times allow for more complete oxidation of propyl acetate due to prolonged exposure to the catalyst surface.Additionally, higher temperatures facilitate more efficient catalytic reactions, contributing to the overall increase in conversion rates.These experiments were used to determine reaction rate constants and to assess the activation energy of complete oxidation.According to the law of mass action, the rate of oxidation of propyl acetate is directly proportional to the concentrations of the volatile compound and oxygen: where r-reaction rate, CPA-concentration of propyl acetate, CO2-concentration of oxygen, and n and m-partial orders of reaction.Since oxygen is comparatively in excess, its concentration change is negligible, so it can be assumed that the reaction rate does not depend on it.The reaction can be calculated as a pseudo first order reaction.
When integrated, the equation becomes as follows: For a PFR (plug flow reactor), the contact time is a product of the flow rate of the reactant, the initial concentration of the reactant, and the void volume of the catalyst: where G-flow rate of propyl acetate, CPA-concentration of propyl acetate, and V-void volume of catalyst.Contact times were calculated by assuming the volume of the fixed bed and a void fraction of the catalyst particle.For 30-60 µm particles, the void fraction was determined These experiments were used to determine reaction rate constants and to assess the activation energy of complete oxidation.According to the law of mass action, the rate of oxidation of propyl acetate is directly proportional to the concentrations of the volatile compound and oxygen: where r-reaction rate, C PA -concentration of propyl acetate, C O2 -concentration of oxygen, and n and m-partial orders of reaction.Since oxygen is comparatively in excess, its concentration change is negligible, so it can be assumed that the reaction rate does not depend on it.The reaction can be calculated as a pseudo first order reaction.
When integrated, the equation becomes as follows: For a PFR (plug flow reactor), the contact time is a product of the flow rate of the reactant, the initial concentration of the reactant, and the void volume of the catalyst: where G-flow rate of propyl acetate, C PA -concentration of propyl acetate, and V-void volume of catalyst.Contact times were calculated by assuming the volume of the fixed bed and a void fraction of the catalyst particle.For 30-60 µm particles, the void fraction was determined to be 0.43.Reaction rate constants can be determined by varying the contact times.The catalytic oxidation results in semi-logarithmic coordinates allow the reaction rate constants to be calculated as the slope of the received straight lines (Figure 9).The results indicate that the reaction rate constant increases with increasing temperature, thus it can be used to determine the activation energy of the complete oxidation of propyl acetate on the surface of the catalyst.The calculated reaction rate constants are presented in Table 1.Kinetic data plotted in a semi-logarithmic Arrenius plot gives a straight line whose slope can be used to calculate the activation energy of the reaction (Figure 10).The calculated activation energy of 63,847 J/mol is comparable to and falls in the middle between those of other catalysts whose activation energies usually range between 20 and 100 kJ/mol.The activation energy defines the reaction s sensitivity to the temperature.The pre-exponent factor or Arrhenius constant defines the frequency of reactant collisions that lead to the formation of new products.The calculated Arrhenius constant was 238,948 s −1 , which is lower when compared to other catalysts, and can be attributed to a relatively low surface area.The results indicate that the reaction rate constant increases with increasing temperature, thus it can be used to determine the activation energy of the complete oxidation of propyl acetate on the surface of the catalyst.The calculated reaction rate constants are presented in Table 1.Kinetic data plotted in a semi-logarithmic Arrenius plot gives a straight line whose slope can be used to calculate the activation energy of the reaction (Figure 10).The calculated activation energy of 63,847 J/mol is comparable to and falls in the middle between those of other catalysts whose activation energies usually range between 20 and 100 kJ/mol.The activation energy defines the reaction's sensitivity to the temperature.The pre-exponent factor or Arrhenius constant defines the frequency of reactant collisions that lead to the formation of new products.The calculated Arrhenius constant was 238,948 s −1 , which is lower when compared to other catalysts, and can be attributed to a relatively low surface area.In comparison with the scientific literature (Table 2), the synthetic Cr 3+ catalyst supported on calcium silicate hydrate demonstrated significant catalytic activity for VOC oxidation, specifically for propyl acetate and propanol.The synthetic catalyst achieved a 97% conversion degree for propyl acetate at 300 °C and a 76% conversion degree for propanol with an activation energy of 63.85 kJ/mol.These results are competitive with previously reported catalysts based on transition metal ions that show a conversion degree for VOCs ranging from 90% to 100% at temperatures above 240 °C (Table 2).It is worth noting that the literature is scarce regarding the reaction rate or activation energy of catalysts based on transition metal ions.The activation energy of such catalysts typically ranges around 50 kJ/mol but can exceed 250 kJ/mol.Since the obtained data show promising results, future research will focus on further optimization of the synthesis conditions to enhance the stability and efficiency of the catalyst.Additionally, the performance of the Cr 3+ catalyst supported on calcium silicate hydrates will be investigated with a wider range of VOCs and under different In comparison with the scientific literature (Table 2), the synthetic Cr 3+ catalyst supported on calcium silicate hydrate demonstrated significant catalytic activity for VOC oxidation, specifically for propyl acetate and propanol.The synthetic catalyst achieved a 97% conversion degree for propyl acetate at 300 • C and a 76% conversion degree for propanol with an activation energy of 63.85 kJ/mol.These results are competitive with previously reported catalysts based on transition metal ions that show a conversion degree for VOCs ranging from 90% to 100% at temperatures above 240 • C (Table 2).It is worth noting that the literature is scarce regarding the reaction rate or activation energy of catalysts based on transition metal ions.The activation energy of such catalysts typically ranges around 50 kJ/mol but can exceed 250 kJ/mol.Since the obtained data show promising results, future research will focus on further optimization of the synthesis conditions to enhance the stability and efficiency of the catalyst.Additionally, the performance of the Cr 3+ catalyst supported on calcium silicate hydrates will be investigated with a wider range of VOCs and under different environmental conditions will be investigated for broader applications.The long-term stability and reusability of the catalyst will also be determined to allow evaluation for practical applications.
Conclusions
Cr 3+ ions promote the reaction of portlandite and lead to the formation of lower basicity calcium silicate hydrates during hydrothermal treatment at 220 • C. In the pure system, portlandite did not fully react even after 48 h, while in the system with 50 mg/g of Cr 3+ , portlandite fully reacted after 8 h.Additionally, Cr 3+ ions stoichiometrically replaced calcium ions in the structure of calcium silicate hydrates, resulting in the formation of lower basicity compounds.Despite the initial concentration of Cr 3+ ions (up to 100 mg/g), the intercalation efficiency by calcium silicates hydrates was more than 98% under all experimental conditions.
The Cr 3+ catalyst supported on calcium silicate hydrates (16 h, 220 • C, 50 mg/g) remained stable up to 350 • C during calcination in an air atmosphere.At higher temperatures, the decomposition of gyrolite (~350 • C) and xonotlite (~700 • C) and the formation of chromatite (~550 • C) and wollastonite (800 • C) proceeded.The lowest degree of catalysts crystallinity was obtained after calcination at 500 • C and 700 • C, i.e., when the sample intensively lost structural water.
The evaluation of the Cr 3+ catalyst supported on calcium silicate hydrates revealed that the reaction with propyl acetate exhibited higher adsorptive affinity and catalytic activity compared to propanol, achieving a 97% conversion rate at 300 • C versus 76% for propanol.The reaction rate constants, calculated from semi-logarithmic plots, increased with temperature and were used to determine an activation energy of 63.847 kJ/mol.
Figure 3 .
Figure 3. XRD patterns of synthesis products formed in the system with 50 mg/g of Cr 3+ ions (a) and 100 mg/g of Cr 3+ ions (b) under hydrothermal synthesis conditions.Indexes: G-gyrolite; X-xonotlite; Z-Z-phase.
Figure 6 .
Figure 6.Conversion and produced amounts of CO2 during complete oxidation of propyl acetate (1) and propanol (2) at various temperatures.
Materials 2024 ,
17, 3489 12 of 17temperatures facilitate more efficient catalytic reactions, contributing to the overall increase in conversion rates.
Figure 10 .
Figure 10.Arrhenius plot for the complete oxidation of propyl acetate on the surface of the catalyst.
Figure 10 .
Figure 10.Arrhenius plot for the complete oxidation of propyl acetate on the surface of the catalyst.
• C, only crystalline phases were present in the sample.
Table 1 .
Calculated reaction rate constants of propyl acetate oxidation at various temperatures.
Table 1 .
Calculated reaction rate constants of propyl acetate oxidation at various temperatures.
Table 2 .
Activity of different catalysts for VOC oxidation.
Table 2 .
Activity of different catalysts for VOC oxidation. | 10,019.8 | 2024-07-01T00:00:00.000 | [
"Chemistry",
"Environmental Science"
] |
Clustering Based Optimal Cluster Head Selection Using Bio-Inspired Neural Network in Energy Optimization of 6LowPAN
: The goal of today’s technological era is to make every item smart. Internet of Things (IoT) is a model shift that gives a whole new dimension to the common items and things. Wireless sensor networks, particularly Low-Power and Lossy Networks (LLNs), are essential components of IoT that has a significant influence on daily living. Routing Protocol for Low Power and Lossy Networks (RPL) has become the standard protocol for IoT and LLNs. It is not only used widely but also researched by various groups of people. The extensive use of RPL and its customization has led to demanding research and improvements. There are certain issues in the current RPL mechanism, such as an energy hole, which is a huge issue in the context of IoT. By the initiation of Grid formation across the sensor nodes, which can simplify the cluster formation, the Cluster Head (CH) selection is accomplished using fish swarm optimization (FSO). The performance of the Graph-Grid-based Convolution clustered neural network with fish swarm optimization (GG-Conv_Clus-FSO) in energy optimization of the network is compared with existing state-of-the-art protocols, and GG-Conv_Clus-FSO outperforms the existing approaches, whereby the packet delivery ratio (PDR) is enhanced by 95.14%.
Introduction
Every object should be smart in today's technological world. The IoT is a new paradigm that gives common objects and things a whole new dimension. Wireless sensor networks, particularly LLNs, are essential components of IoT. It has a high impact on usage in everyday life [1]. The usage at home, industry and institutions is growing exponentially every day. It is considered one of the most influential technologies of the modern era. The devices added to IoT are growing in leaps and bounds every day. Homes, classrooms and cities are becoming smart with IoT [2,3].
•
The RPL due to its wide usage and popularity has become the de facto standard routing protocol for LLNs in IoT. A wide range of research is going on to enhance the RPL for various environments.
•
The enhancement methods are based on various components of RPL. The research work in this article is based on energy hole rectification-based transmission enhancement and energy-efficiency improvement mechanism for RPL. • The main focus of research is on enhancement for reliability in critical environments. A study on the research gap also suggests this as one of the focus areas of research.
•
To formulate a grid across the network and generate clusters in the area of grids formed in the network.
•
To select CH, a bio-inspired approach is introduced; a Graph-Grid-based Convolution clustered neural network with fish swarm optimization (GG-Conv_Clus-FSO) is utilized.
The rest of the research work is arranged as follows: the related mechanism in energy hole detection and their drawbacks are reviewed in Section 2; the proposed grid-based clustering with FSO for the detection of energy holes is illustrated in Section 3; simulation results are illustrated in Section 4; the research is concluded in Section 5.
Literature Review
Several reports have been published in 2009 and 2010 [15,16] to identify the routing requirements for the standardization of RPL based on its application in various routing environments. The widespread usage of RPL and its customisation has necessitated substantial study and development. The control packets in the network are necessary to establish a connection and maintain the network. The frequent change and resetting of the network in a mobile setup led to overhead in the link. An efficient way of detecting and controlling congestion is required [17]. LLNs are backbone networks of IoT. They are constrained by energy, memory and processing capacity. The traditional and popular network protocols are not suitable for LLNs due to these constraints. Among the existing routing protocols, RPL is more suitable for LLNs, due to its special features such as auto configuration, self-healing, loop avoidance, multiple edge routers and robustness [18]. RPL is also easily malleable to various environments of LLNs. This section presents an overview of RPL with the background, characteristics and various components.
The Internet Engineering Task Force (IETF) envisioned the standardization of IPv6RPL and started the Routing over Low-power and Lossy networks (ROLL) working group in 2008. The working group aimed at the standardization of RPL, which has the following implicit characteristics [19]: (i) LLNs are constituted by hundreds of nodes that are constrained by energy, size, processing power and memory. (ii) The constrained nodes of LLNs are connected to each other through lossy links, which have low data rates and are unstable. (iii) The traffic patterns of these LLNs may be point-to-multipoint, multipoint-to-point or, in some cases, point-to-point [20], such as urban settings [21], industrial settings, home automation and building automation [22].
Multi-hop WSN node restrictions are closer to BS's demand to infuse traffic from some other channel, enabling their energy to be spent quicker and possibly leading to very high remaining energy. As a consequence, Distributed Wedge Merging in Multi-Hop Access (DWMA) is presented here as a possible solution to the energy hole problem and routing. The major objective is to remove energy gaps while reducing the likelihood of them emerging in the future. To avoid energy holes from occurring, this DWMA method is combined with a nearby wedge [23].
In heterogeneous networks, violating the response and broadcast buffer specifications has resulted in uneven traffic loads, congestion and, as a result, packet loss in RPL, according to the author. This paper discusses the CBR-RPL technique, which uses a unique drop-aware Objective Function (OF) to arrange nodes into route data. The newly defined OF takes into account both queue occupancy and node transceiver drop rates [24]. The Energy Hole problem, which is common in WSN, drastically affects the lifetime of any established network. The energy diffusion required for data packet forwarding between HN is reduced when a good Head Node (HN) selection technique is used [25].
PEGASIS (Power-Efficient Gathering in Sensor Information Systems) is an energysaving protocol that tries to extend the network's lifespan by reducing energy consumption. This research proposes a modification of the PEGASIS approach. SNs are sorted into groups, clustering is carried out using the k-means method and every group is assigned the PEGASIS label. Rechargeable sensor nodes were also used in the suggested strategy. The sensor node's Euclidean distance from the base station and the sensor node's residual energy are utilised to determine the chain leader. Every CH's datum is instantly forwarded to the BS [26]. Various surveys on energy use, energy gaps and attacks on RPL and LLP systems can be found in [27][28][29][30]. The glowworm swarm-based approach cast-off energy-based transmission strategy has been presented to decrease energy consumption caused by control overhead [31]. A least-square support vector machine (LS-SVM) based on modified particle swarm optimization (MPSO) is developed. To begin, the MPSO's inertial weight is adjusted to accomplish faster iterations, and an LS-SVM-based MPSO's prediction model is constructed. Second, the predictive simulation was performed and confirmed using the MPSO's optimised parameters, and the MPSO and PSO predicted values were compared [32]. This work introduces a resilient clustering routing mechanism for WSNs. To estimate the number of cluster heads and identify the best cluster heads, the technique employs the Locust Search (LS-II) approach. After the cluster heads have been identified, other sensor elements are allocated to the cluster heads that are closest to them [33]. Based on the Optimal Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol, a methodology for an energy-efficient clustering algorithm for gathering and transferring data is developed. The new optimised threshold function is used in the selection of CH. LEACH, on the other hand, is a hierarchy routing protocol that picks cluster head nodes at random in a loop, resulting in a higher cluster headcount but higher power consumption. In order to improve the energy per unit node and packet delivery ratio with less energy use, the Centralised Low-Energy Adaptive Clustering Hierarchy Protocol is the best [34]. WSNs are designed for specialised applications, such as monitoring or tracking, in both indoor and outdoor conditions, where battery capacity is a major issue. Several routing protocols are designed to solve this problem. A sub-cluster LEACH-derived approach is also proposed in order to improve performance. The Sub-LEACH with LMNN surpassed its competitors in terms of energy efficiency, according to simulation data [35].
Proposed Graph-Grid-Based Clustering for Energy Hole Detection
Grid cells of equal length are used to partition the whole network. Every grid cell represents the square territory. Every grid cell has only static nodes. The Sink can be either stationary or moveable for gathering data. The grid cell CH is the one that is closest to the mid-point of the grid cell. Every grid cell has a node ID as well as an associated grid ID that identifies nodes. The sink is responsible for the initial cluster setup, which includes calculating node IDs and grid IDs, establishing the CH for each grid cell and scheduling data transmission and reception for nodes in the grid cells. The GG-Conv_Clus-FSO protocol uses double disjoint anchor group nodes for packet forwarding, and node nomination is based on the clustering method. To locate holes quickly, a grid-based hole identification method is utilised. Data packets are accurately routed to the anchor and destination nodes while consuming the least amount of energy.
Grid Formation
The whole network is divided into equal-sized rectangle-shaped grid cells. Each grid keeps track of the exact location of each cell relative to its border, which is subsequently used to determine the size of the holes. In this, D a × D b denotes the grid cell dimension where the length is determined by D a and width is determined by X b . Equation (1) [31] indicates the grid cell generation process. The grid-building procedure is completed by where the count of a horizontal line is indicated by g, and the count of the vertical line is indicated by r. The process of grid construction is given in Algorithm 1.
Algorithm 1: Construction of Grid
for g = 0 to p = s for r = 0 to r = t f(g, r) = ((g 0 + g × D a , r 0 + r × D b )) end for end for Selection of Cluster Head (CH): In the actual world, fish can identify nutrient-rich places by searching on their own or by swimming near other fish; the region with the most fish often has the most nutrition. Artificial fish swarm optimization (AFSO) is based on mimicking fish behaviour, such as preying, swarming and tracking local fish hunts to attain global optima. The solution space and the states of other artificial fishes are generally the areas where an Artificial Fish (AF) dwells. The subsequent behaviour is determined by the current state as well as the immediate environment, such as the current quality of query responses and the status of nearby neighbours. The movements of an artificial fish, as well as the actions of its neighbours, have an impact on the ecosystem. If fish are discovered in a water area with more food, they will migrate quickly to that area. Equation (2) may be used to describe this behaviour.
During preying mode, fish behaviour is represented by Equation (3): where rand is the random function with range [0, 1]. The behaviour of the swarm is represented in Equation (4) Swarm In the follow stage, behaviour is given by equation The three processes outlined above guarantee that both global and local searches are conducted, as well as a search direction that leads to the greatest food source. The suggested approach differs from the AFSA in two significant ways. The solutions are split at random and behave in one of two ways: swarming or following. The best fish are chosen via tournament selection, and preying processing begins. Fish who are very good at preying are chosen and allowed to breed amongst themselves. The best fish and the new solution are carried to the next iteration. The answers are represented as binary numbers in this study, and the distance between fish is calculated utilizing Hamming distance. The number of locations where two strings u and v differ is the hamming distance between them. The best fish are chosen by spinning the roulette wheel. The likelihood of a fish being picked on a roulette wheel is exactly proportional to its fitness. Equation (6) computes the probability of a fish, To enhance QOS, a multi-objective function based on E2E delay as well as energy is proposed and represented by Equation (7): where d ri is the E2E delay, D td is the total delay to reach BS, D m is the maximum delay, E ri is the remaining energy in CH and E i is the initial energy. Subsequent assumptions are made: • The nodes in the network are distributed arbitrarily; • Starting energy of every node is the similar; • In ecology, all fishes are unisex; • Because fish are unisexual, mating among any two fish is feasible; • Because the free space radio method is utilised, the energy needed to transmit one bit of data grows as distance improves.
The flowchart for FSO-based CH selection is shown in Figure 1. Because solution space is binary, a transfer function is required to fill the bit as the fish swims. In this paper, a novel transfer function for flipping the bits described by Equation (8) is, Hole Detection: The grid hole is found by comparing the cell coordinates to SNs radius as well as closest count (SN). SN count is closer to the sensor's radius, which is used to determine the hole's coverage area. The region in which a hole has developed is said to be Bi. Equations (10) and (11) show the position of the hole in the cell and the grid.
Data propagation across selected CH: Send data around the borders of the hole and transfer it to the correct location. The sensor nodes in the region are clustered, and the CH is selected as the node closest to the grid's centre. In the GBC-SS, the Static Sink is in charge of coordination, whereas in the GBC-MS, Mobile Sink is in charge of data gathering. The information is transmitted to nearby sensor nodes, and the position is recorded for future To attain flipping, a random number between 0 and 1 is generated, and if the random number is less than the transfer function provided by Equation (8), the bit is flipped.
Hole Detection: The grid hole is found by comparing the cell coordinates to SNs radius as well as closest count (SN). SN count is closer to the sensor's radius, which is used to determine the hole's coverage area. The region in which a hole has developed is said to be B i . Equations (10) and (11) show the position of the hole in the cell and the grid.
Data propagation across selected CH: Send data around the borders of the hole and transfer it to the correct location. The sensor nodes in the region are clustered, and the CH is selected as the node closest to the grid's centre. In the GBC-SS, the Static Sink is in charge of coordination, whereas in the GBC-MS, Mobile Sink is in charge of data gathering. The information is transmitted to nearby sensor nodes, and the position is recorded for future data transfer.
where the density is indicated by ρ, the transmission rate of data is characterized by a dot and the determined location is shown as gl. Instead of complex exponentials, the eigenvectors { ℓ } /=0 −1 of the Laplacian matrix L that meet the orthogonality criterion are employed as decomposition bases for graphstructured data. On a graph, the Fourier transform of a given signal f(n) is defined as Equation (15): Inverse Fourier transformation is represented by Equation (16): Convolution is turned into a point-wise product in the Fourier domain as well as reconverted into the vertex domain utilizing the graph Fourier transform as well as the convolution theorem, as in Equation (17): A convolution kernel is the graph convolution operation of two graph signals, f(n) and g(n), and its transform, (Λ). A set of free parameters in the Fourier domain, i.e., Laplacian eigenspace, is used to construct this kernel. Convolution is then written as Equation (18): (Λ) as an eigenvalue polynomial function: As illustrated in Equation (19), a rapid localised convolution based on low-order polynomial approximation was proposed: which { } =0 is the polynomial order, and Ki is a vector of polynomial coefficients. K is is a normalised version [1,1]. Instead of complex exponentials, the eigenvectors {χ } N−1 /=0 of the Laplacian matrix L that meet the orthogonality criterion are employed as decomposition bases for graphstructured data. On a graph, the Fourier transform of a given signal f(n) is defined as Equation (15): Inverse Fourier transformation is represented by Equation (16): Convolution is turned into a point-wise product in the Fourier domain as well as reconverted into the vertex domain utilizing the graph Fourier transform as well as the convolution theorem, as in Equation (17): A convolution kernel is the graph convolution operation of two graph signals, f(n) and g(n), and its transform, G(Λ). A set of free parameters in the Fourier domain, i.e., Laplacian eigenspace, is used to construct this kernel. Convolution is then written as Equation (18): G(Λ) as an eigenvalue polynomial function: As illustrated in Equation (19), a rapid localised convolution based on low-order polynomial approximation was proposed: which {θ k } K k=0 is the polynomial order, and Ki is a vector of polynomial coefficients. K is a tiny positive integer, such as 3, for example. Convolution is then rewritten as Equation (20): The convolution is performed by K multiplications of the sparse matrix L, which speeds up computation by avoiding the composition procedure.
The following is the updated version of Equation (21) for layer l: with Q k,l , K k,l , V k,l , E k,l ∈ Rd k , O l h, , O l e ∈ R d×d , k ∈ {1, 2, . . . , H} relates the number of attention heads, and where O l h ∈ R d×d , V k,l ∈ R d k ×d , d k H denotes the number of heads. Note that h l i is i-th node's feature at l-th layer in Equation (22).
where S k is k-th set of a given graph, S k indicates the remaining sets, except S k , and e v i , v j is the edge between vertices v i and v j . When referring to multiple sets, the cut issue is represented as Equation (23): The issue of less cuts is extensively studied in the literature in Equation (24): where vol(S k , V) ∑ = v i ∈ S k , v i ∈ v e v i , v j is the total degree of nodes from S k in graph g. The normalised cut problem utilizing DL optimisation, transforming the minimum cut issue into a DL format, as in Equation (25): A is the adjacency matrix, and, finally, Γ is evaluated by Equation (26): where (·) relates a non-linear activation function, e.g., ReLU (·) max(0, ·) = ; Hi [ ]l indicates ith input graph; ijk, and bj [ ] l are trainable F F in out × vector of K-order polynomial coefficients and 1 × Fout vector of bias in l th layer.
Result and Discussion
In this section, the simulation outcome of the proposed Graph-Grid-based Convolution clustered neural network with fish swarm optimization (GG-Conv_Clus-FSO) is compared with the existing techniques such as DWMA for 6LowPAN RPL, CBR-RPL, CCS and WEMER and PEGASIS. The simulation of the above-mentioned approaches is investigated with the assistance of the number of rounds vs. alive nodes, the number of rounds vs. dead nodes, PDR, energy consumption and delivery delay. The simulation setup is given in Table 1.
Energy Consumption
Every sensor node in the data transmission environment in the WSN is equipped with rechargeable batteries that consume the least amount of energy, making battery recharging difficult. The cluster and duty cycle scheduling mechanisms start the data transfer. The data transmission process is completed without interruption, and data are transmitted in the quickest way possible while consuming the least amount of energy. The transmission nodes' energy consumption is minimized as a result of this condition is given in Table 2. In Figure 2, energy consumption during data transmission for a different number of nodes is illustrated. The energy consumption of the proposed approach is minimal than existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS. In Figure 2, energy consumption during data transmission for a different number of nodes is illustrated. The energy consumption of the proposed approach is minimal than existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS.
End to End Delay
It is time takes to transport data from source to destination node. A protocol that has the shortest transmission delay is considered to be effective, the comparisons are given in Table 3. In Figure 3, end-to-end delay during data transmission for various numbers of nodes is illustrated. E2E delay of the proposed technique is minimal than existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS.
End to End Delay
It is time takes to transport data from source to destination node. A protocol that has the shortest transmission delay is considered to be effective, the comparisons are given in Table 3. In Figure 3, end-to-end delay during data transmission for various numbers of nodes is illustrated. E2E delay of the proposed technique is minimal than existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS.
Packet Delivery Ratio
PDR is determined by dividing the total number of data packets sent from source to destination node by the number of data packets delivered. Data communication technology that delivers most packets is deemed the best. The packet delivery ratio of the different method is mentioned in Table 4.
Packet Delivery Ratio
PDR is determined by dividing the total number of data packets sent from source to destination node by the number of data packets delivered. Data communication technology that delivers most packets is deemed the best. The packet delivery ratio of the different method is mentioned in Table 4. In Figure 4, PDR during data transmission for different numbers of nodes is illustrated. PDR of the proposed approach is higher than existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS.
Packet Loss
Packet loss can be triggered by a mixture of circumstances, including signal deterioration owing to multi-path fading on the network media. In WSNs, packet loss is conceivable. In order for attackers to simply acquire the data. Packet loss occurs when one or more sent packets fail to reach their intended destination. The Packet Delivery Ratio is reduced when packets are lost. The packet loss of the different method is compared and its mentioned in Table 5 Table 5. Comparison of packet loss. 0 0 0 0 0 20 89 76 59 31 40 143 137 147 98 60 221 226 204 149 80 349 358 269 223 100 520 440 320 282
No of Nodes DWMA CBR-RPL WEMER GG-Conv_Clus-FSO
In Figure 5, packet loss during data transmission for different number of node is illustrated. The packet loss of proposed approach is minimal than existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS.
Packet Loss
Packet loss can be triggered by a mixture of circumstances, including signal deterioration owing to multi-path fading on the network media. In WSNs, packet loss is conceivable. In order for attackers to simply acquire the data. Packet loss occurs when one or more sent packets fail to reach their intended destination. The Packet Delivery Ratio is reduced when packets are lost. The packet loss of the different method is compared and its mentioned in Table 5 Table 5. Comparison of packet loss. DWMA CBR-RPL WEMER GG-Conv_Clus-FSO 0 0 0 0 0 20 89 76 59 31 40 143 137 147 98 60 221 226 204 149 80 349 358 269 223 100 520 440 320 282 Energies 2022, 15, 4528 12 of 14
No of Nodes
In Figure 5, packet loss during data transmission for different number of node is illustrated. The packet loss of proposed approach is minimal than existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS.
Throughput
The amount of data that is efficiently sent/received through a communication channel is referred to as throughput. Throughput is calculated in kilobits per second, megabits per second or gigabits per second and might differ from bandwidth owing to a variety of technical issues such as packet loss, latency, jitter, and more. The quantity of data that is moved from one location to another in a given length of time is referred to as throughput. The comparisons of previous methods and proposed method is mentioned in the below Table 6. In Figure 6, the throughput during data transmission for different numbers of nodes is illustrated. The throughput of the proposed approach is minimal compared to the existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS.
Throughput
The amount of data that is efficiently sent/received through a communication channel is referred to as throughput. Throughput is calculated in kilobits per second, megabits per second or gigabits per second and might differ from bandwidth owing to a variety of technical issues such as packet loss, latency, jitter, and more. The quantity of data that is moved from one location to another in a given length of time is referred to as throughput. The comparisons of previous methods and proposed method is mentioned in the below Table 6. In Figure 6, the throughput during data transmission for different numbers of nodes is illustrated. The throughput of the proposed approach is minimal compared to the existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS.
Throughput
The amount of data that is efficiently sent/received through a communication channel is referred to as throughput. Throughput is calculated in kilobits per second, megabits per second or gigabits per second and might differ from bandwidth owing to a variety of technical issues such as packet loss, latency, jitter, and more. The quantity of data that is moved from one location to another in a given length of time is referred to as throughput. The comparisons of previous methods and proposed method is mentioned in the below Table 6. In Figure 6, the throughput during data transmission for different numbers of nodes is illustrated. The throughput of the proposed approach is minimal compared to the existing approaches, namely DWMA, CBR-RPL, WEMER and PEGASIS.
Conclusions
The Internet of Things has a significant influence on daily living. For IoT and LLNs, the RPL has become the standard protocol. It is not only extensively utilised, but it has also been studied by diverse groups of individuals. The widespread usage of RPL and its customisation has necessitated substantial study and development. There are certain flaws with the existing RPL mechanism, one of which is an energy hole, which is a major problem in the context of IoT. Fish swarm optimization is used to initiate Grid creation among sensor nodes, which can help in cluster formation and Cluster Head (CH) selection with energy optimization by calculating the energy consumption of the network. The performance of a Graph-Grid-based Convolution clustered neural network with fish swarm optimization (GG-Conv_Clus-FSO) is compared to existing state-of-the-art protocols, and the GG-Conv_Clus-FSObeats the existing techniques, with a 95.14 percent increase in the packet delivery ratio (PDR). Data Availability Statement: Data will be shared for review based on the editorial reviewer's request. | 6,428.8 | 2022-06-21T00:00:00.000 | [
"Computer Science",
"Engineering",
"Environmental Science"
] |
Instant green synthesis of silver-based herbo-metallic colloidal nanosuspension in Terminalia bellirica fruit aqueous extract for catalytic and antibacterial applications
In the present study, microwave-assisted, optimized, instant, Terminalia bellirica fruit extract-mediated green synthesis of colloidal silver nanoparticles (AgNPs) has been reported. The synthesized AgNPs were characterized by UV–Vis spectroscopy, FTIR, Zetasizer, FESEM, EDX and XRD. The characteristic surface plasmon peak of reaction mixture at 406 nm confirmed the synthesis of AgNPs. The FTIR studies confirmed phytoconstituents were responsible for the synthesis and stability of AgNPs. The FESEM, EDX and XRD analysis revealed the presence of spherical silver nanoparticles of mean diameter ≤20.6 nm with face-centered cubic crystalline structure. These AgNPs showed notable catalytic activity in reduction of 4-nitrophenol to 4-aminophenol in the presence of NaBH4. The synthesized AgNPs showed potential antibacterial and antibiofilm activity against bacterial pathogens like Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. Thus, these synthesized AgNPs can open avenues for the development of AgNP-based efficient nanocatalyst and potent nanomedicine in future. Electronic supplementary material The online version of this article (doi:10.1007/s13205-016-0589-1) contains supplementary material, which is available to authorized users.
Introduction
Silver nanoparticles have found remarkable applications in the field of drug delivery, food industries, agriculture, textile industries, water treatment, redox catalysis, green housing construction and medicine (Jagtap and Bapat 2013;Kuunal et al. 2016). Several approaches exist for the synthesis of silver nanoparticles (AgNPs) including; thermal decomposition, sonochemical, electrochemical and photochemical reactions, chemical reduction and biological route (Ahmad et al. 2010). Physical and chemical methods could effectively produce pure and distinct nanoparticles; however, these methods are quite costly and possibly harmful to the environment due to use of harsh chemicals (Kumar and Yadav 2009). This necessitates cost-effective, commercially feasible, non-toxic and environment friendly process for the synthesis of AgNPs. Biological materials such as microbes, enzymes, plant materials, etc., offer ecofriendly approach for the synthesis of nanoparticles (Velmurugan et al. 2011). Synthesis of nanoparticles using microorganisms has limitations due to its slow rate of synthesis (Shahverdi et al. 2007); hence, plant-based materials are receiving more attention due to its simplicity, ready scalability, ecofriendliness, cost-effectiveness and relatively high reproducibility (Iravani 2011). The key active agents in such nanoparticles synthesis were speculated to be polyphenols, flavonoids, reducing sugars, sterols, essential oils, starch, cellulose, pectins, gums, resins, lectins, etc. These biomaterials act as reducing agents as well as capping agents in the synthesis of silver nanoparticles (Gangula et al. 2011).
In recent days there has been a growing interest in developing nanomaterial-based antimicrobial agents to combat the emerging resistance to antimicrobial agents by pathogenic bacteria (Seil and Webster 2012). Ability of bacterial pathogens to form biofilms offers 1000 times more resistance against antimicrobial agents (Mah and O'Toole 2001). Hence there is a necessity to develop antimicrobial agents which have broad-spectrum activity and potential to combat against antibiotics resistant biofilms.
The present work deals with instant green synthesis of biocapped AgNPs by using Terminalia bellirica (Roxb.) fruit aqueous extract. This plant is wild and grows throughout the Indian subcontinent, Nepal, Srilanka, Malaysia and South East Asia (Ramesh et al. 2005). In traditional Indian Ayurvedic medicine, T. bellirica fruit is used in the popular Indian herbal rasayana treatment triphala. T. bellirica is used to protect the liver, reduce high cholesterol, and treat digestive as well as respiratory disorders (Latha and Daisy 2011). It has a well-established antioxidant potential and presence of polyphenolic compounds such as ellagic acid, gallic acid, tannins, ethyl gallate, galloyl glucose, chebulagic acid, 7-hydroxy 3 0 4 0 (methylene dioxy) flavones, etc., as well as reducing sugars such as glucose and rhamnose (Nampoothiri et al. 2011). Hence, this plant was chosen for the synthesis of AgNPs. To the best of our knowledge, the use of T. bellirica fruit aqueous extract has not been reported before for the synthesis of AgNPs.
In these studies, the microwave-assisted rapid synthesis of colloidal AgNPs using TB extract has been reported. The process variables such as the relative concentrations of the extract and metal salt(s) in reaction mixture, pH, and time of reaction which controls the key properties of nanoparticles have been optimized. Furthermore, applicability of these AgNPs as a nanocatalyst in the reduction of 4-nitrophenol was explored. Besides biomedical application of these AgNPs such as antibacterial and antibiofilm agents against human pathogenic bacteria were also assessed.
Chemicals and collection of plant material
Chemicals such as silver nitrate, sodium borohydride, 4-nitrophenol used in this research work used were of high grade and purchased from HiMedia, Mumbai. The dried fruits of T. bellirica were collected from local market and are available throughout India. The plant material was authenticated by an expert botanist.
Preparation of aqueous extract of Terminalia bellirica fruit
The dried fruits of T. bellirica were cleaned with distilled water, shade dried, and ground to a fine powder and then sieved through 60 mesh size sieve. The aqueous extract was prepared by boiling under pressure in an autoclave which involved the addition of 20 g of powdered fruits with 200 mL of distilled water, autoclaved for 12 min at 121°C under pressure 15 psi. Further, the extract was centrifuged at 10,000 rpm for 15 min and then filtered through a membrane having 0.2 lm pore size. The filtrate was stored in the refrigerator at 4°C until its use. The dry weight of TB extract per mL of filtrate was determined. Total phenolic content, total flavonoid content, total reducing sugars and total reducing capacity of TB extract were determined using colorimetric assays (Wojdyło et al. 2014).
Synthesis of AgNPs
The synthesis of AgNPs was carried out in two different sets each having 100 mL of 3 mM AgNO 3 solution with 1.5 mL of extract. In the first set AgNP synthesis was monitored under normal conditions at room temperature and in another set the reaction mixture was irradiated in a domestic microwave oven (GMS 17M 07 WHGX Godrej, India), at working frequency 2450 MHz and power output 900 W, for 5 min. For both the sets, separate controls were run without addition of extract to 100 mL of 3.0 mM AgNO 3 solution. Formation of silver nanoparticles was visually observed by color change of the reaction mixtures as well as scanning UV-Vis spectra of it from 250 to 750 nm range using UV-Vis spectrophotometer (UV-1800, Shimadzu, Japan), in both the sets. The samples were diluted twofold by deionized distilled water for UV-Vis spectral analysis. Process parameters involved in the synthesis of AgNPs such as pH of the reaction mixture, ratio of concentration of TB extract with AgNO 3 solution and time of microwave irradiation were optimized by one factor at a time method (Online Resource).
Spectroscopic and microscopic characterization of synthesized nanoparticles
Synthesis of AgNPs by reducing Ag ? ion solution with TB extract may be easily monitored by UV-Vis spectroscopy. Using a UV-Vis spectrophotometer (UV-1800, Shimadzu, Japan) absorption spectra were measured in the 250-750 nm range against deionized distilled water as blank. In order to determine the involvement of bioactive functional groups in reduction, capping and stabilization of Ag ? ions, Fourier transform infrared (FTIR) spectra of TB extract and AgNPs were recorded by KBr pellet method on FTIR spectrometer (Spectrum Two, FTIR-88522, Perkin Elmer, USA). Average particle size and stability of green synthesized AgNPs were analyzed using the Malvern Zetasizer (NanoZS-90, UK) instrument. The surface morphology and the presence of elemental silver in green synthesized AgNPs were analyzed by field emission scanning electron microscopy (FESEM) and energy-dispersive X-ray spectroscopy (EDX) using instrument FESEM (S4800 Type II, Hitachi, Japan) equipped with EDX (X Flash detector-5030, Bruker, Germany). To determine crystallinity X-ray diffraction (XRD) data were acquired by an X-ray diffractometer (Bruker; D8 Advance, Germany).
Catalytic activity of AgNPs
The catalytic reduction reaction of 4-nitrophenol was carried out in aqueous solution. Initially, 5.0 mM 4-nitrophenol (5 mL) and 0.2 M NaBH 4 (6.25 mL) were mixed in a 100-mL conical flask; the volume was adjusted to 50 mL with deionized distilled water to get overall concentrations of 4-nitrophenol and NaBH 4 0.5 and 25 mM, respectively. Immediately after change in color from light yellow to yellow green, the UV-Vis absorption spectra of the solution were recorded with a time interval of 1 min with a scanning range of 200-750 nm at 25°C on UV-Vis spectrophotometer (UV-1800, Shimadzu, Japan). Similarly same sets of reaction were carried out separately with the addition of 0.25 mL of TB extract (1.5% v/v) and AgNPs before adjusting reaction volume to 50 mL.
Assessment of biomedical applications of AgNPs
Antibacterial activity of phytosynthesized AgNPs was evaluated by agar well-diffusion method (Gupta et al. 2014) against the pathogenic bacteria Pseudomonas aeruginosa (ATCC 9027), Escherichia coli (ATCC 8739), Staphylococcus aureus (ATCC 6538) and Bacillus subtilis (ATCC 6633) which were available in our laboratory. In brief, test sample of 50 lL (pH 7.0) was loaded in each well and incubated at room temperature against the said pathogens spread on nutrient agar. Antibacterial activity was expressed in terms of the inhibition zone (in mm). Deionized distilled water was used as a negative control. The antibiotic streptomycin (20 lg mL -1 ), AgNO 3 solution (1.25 mM) and TB extract (150 lg mL -1 ) were used as positive controls. Minimum inhibitory concentration (MIC) was determined by the standard micro-dilution method recommended by the Clinical Laboratory Standardization Institute (CLSI) guideline (CLSI 2008).
The antibiofilm activity of AgNPs was evaluated by using crystal violet microtiter plate assay (Gupta et al. 2014). The lowest concentration that produced maximum biofilm inhibition was considered to be the biofilm inhibitory concentration (BIC). The potential of AgNPs to disrupt the established biofilms was also evaluated by treating pre-formed biofilms with the AgNPs under nutrient-limited and nutrient-rich conditions as described by Bakkiyaraj et al. (2013). These experiments were performed three times, with replicates of six, and average values were calculated.
Statistical analysis
All experiments related to phytochemical analysis were performed in replicates of six while others were performed in triplicates. Results were expressed as the mean ± standard deviation (SD). Origin Pro 8 statistical program was used for graph design and data analysis.
Results and discussion
Total phenolic, flavonoid and reducing sugars content of TB extract and its reducing power Recently, interest of nanotechnology is focused towards the green synthesis of nanoparticles (Park et al. 2011). Therefore, discovering natural reducing agents; especially those of plant origin become crucial, including mainly polyphenols, flavonoids and reducing sugars (Iravani 2011). Presence of polyphenols in T. bellirica (Nampoothiri et al. 2011) provoked to explore its potential in green synthesis of AgNPs. The total phenolic, flavonoid and reducing sugars content of TB extract were measured to be 20.54 ± 1.02 mg mL -1 (gallic acid equivalent), 3.78 ± 0.06 mg mL -1 (rutin equivalent) and 10.10 ± 0.15 mg mL -1 (maltose equivalent), respectively. The reducing power of TB extract, which could serve as a potent bioreductant in synthesis of metallic silver nanoparticles, was comparable with that of chemical reducing agents like ascorbic acid (Online Resource Fig. S1) suggesting that the TB extract possessed a stronger electron donating capacity. Thus, owing to strong reducing capacity of TB extract, it was exploited as reducing agent in biomimetic synthesis of AgNPs.
Synthesis of AgNPs using TB extract
Synthesis of silver nanoparticles was easily determined and monitored by UV-Vis spectroscopic analysis due to their surface plasmon resonance phenomenon (SPR) (Kora et al. 2012). SPR is the interaction of electromagnetic radiation and the electrons in the conduction band around the nanoparticles (Ringe et al. 2010) giving well-defined absorption band in the visible region which is a manifestation of optical response of materials at different scales (Noguez 2007). The AgNPs show strong absorption peak in the range of 400-440 nm in a visible region (Shivaji et al. 2011). In the current work, after incubation of 100 mL of reaction mixture (pH 7) containing 3 mM AgNO 3 and 1.5 mL of TB extract AgNPs were formed (Fig. 1a). However, it took longer time, about 4 days, for complete reduction of Ag ? to AgNPs. The AgNP synthesis was evident from the development of dark brown color (Online Fig. S2) with its k max in the range of 400-450 nm. A typical brown colored silver solution was obtained due to excitation of the SPR in the metal nanoparticles. These results are in good agreement with the findings of Edison and Sethuraman (2012) in the plantmediated synthesis of silver nanoparticles. Microwave irradiation is an advantageous approach as a part of green chemistry in plant extract-mediated instant synthesis of nanoparticles (Yallappa et al. 2013). In the present study, the irradiation in microwave oven has minimized the time of AgNP synthesis initially to 5 min which resulted in complete reduction of Ag ? and rapid synthesis of AgNPs (Fig. 1b). The AgNP synthesis under normal and microwave irradiation is a function of time (Online Resource Fig. S3); therefore, with increase in time of incubation or irradiation up to complete reduction of Ag ? to AgNPs there was an increase in SPR. TB extract-mediated synthesis of AgNPs was an instant green process involving direct interaction of silver ions with plant extract in presence of microwave radiations without any byproduct. Similarly, this process did not require any chemical stabilization material because plant secondary metabolites mainly polyphenols create robust coating over nanoparticles making them stable against aggregation (Kumar and Yadav 2009). Moreover, the rate of synthesis of silver nanoparticles was very high (within 5 min), which supports the use of plants over microorganisms in biological synthesis methods (Iravani 2011). In the current research work, the optimum parameters for the green synthesis were found to be pH 10 (Fig. 1c), AgNO 3 concentration 5 mM (Fig. 1d) with TB extract concentration 1.5% (v/v) of reaction mixture, and microwave irradiation for 3 min (Fig. 1e). The optimized process variables supported the maximum synthesis of AgNPs with smaller particle size and having stability in very short time. These results are in agreement with the earlier findings of Krishnaraj et al. (2012).
Spectroscopic and microscopic characterization of green synthesized AgNPs
In the current research work, the AgNPs were rapidly formed at pH 10 after the addition of TB extract, obvious from the appearance of dark brown color from pale yellow color with strong absorbance peak at k max 412 nm (Fig. 1b). The IR spectra identify the possible functional groups responsible for the reduction of ions and also the capping agents responsible for the stability of the biogenic nanoparticles (Thirunavukkarasu et al. 2012). In the present work, FTIR spectra of plant extract (TB extract) and biosynthesized AgNPs were analyzed (Fig. 2). IR spectrum of TB extract showed a characteristic peak at 3400 cm -1 which represents -OH stretch of phenolic compounds. The signals at 2919 and 2855 cm -1 were aroused possibly by asymmetrical and symmetrical stretching vibrations of C-H groups such as CH 2 and CH 3 . The major peaks at 1712 and 1031 cm -1 corresponded to C=O stretch and C-O stretch of carboxylic acids, respectively. Peak at 1619 cm -1 was due to N-H bend of primary amines. The sharp peaks at 1431 and 1213 cm -1 indicated C-C stretch (in-ring) of aromatics and C-O stretch of esters. The band at 1041 cm -1 was related to C-N stretch of aliphatic amines. Absorption bands at 3400, 1712, 1634, 1213 and 1081 cm -1 appeared in FTIR spectrum of TB extract indicated the presence of polyphenolics such as gallic acid, ellagic acid, tannins, and ethyl gallate compounds (Vijayalakshmi and Ravindhran (2012). Similarly the peaks at 3400, 2919, 2855, 1712, 1619, 1390 and 1041 cm -1 are the characteristic peaks of lignocellulosic materials comprising reducing sugars as their building blocks (Sanchez et al. 2012) in TB extract. The absorption peaks that appear in the IR spectrum of TB extract could also be seen in the IR spectrum of green synthesized phytocapped AgNPs with minor variation in the positions of the absorption bands. This suggests the involvement of phytoconstituents in the synthesis of AgNPs and preventing them from aggregation.
Particle size analysis and stability study
In order to reveal the size of green synthesized AgNPs particle size analysis was performed in aqueous solution of AgNPs with Zeta analyzer. Particle size distribution histogram of AgNPs is shown in Fig. 3a. From these results, it was clear that the size of particles ranged from 6.50 to 24.36 nm with average size of 20.74 nm. These nanoparticles were having corresponding average zeta potential value -19.1 mV with good quality, indicating the stability of AgNPs (Fig. 3b). This significant negative potential value might be attributed to involvement of polyphenolic phytoconstituents for capping of nanoparticles (Vivek et al. 2012). Many plant extracts have been reported to have Rauwel et al. (2015) reported that different plant extracts mediated synthesis of AgNPs having size from 2 to 100 nm and in the present work also the size of AgNPs was within similar range.
SEM analysis of AgNPs
The surface morphology of green synthesized AgNPs was investigated by FESEM analysis. These micrographs revealed more or less spherical shaped nanoparticles with quite a uniform particle size up to 20.6 nm with a few instances of larger particle size and thus confirmed the formation of nanoparticles (Fig. 4). Interestingly, close observation indicated that synthesized nanoparticles were not in direct contact with each other even within aggregates, suggesting stabilization of AgNPs by phytoconstituents.
EDX analysis
Presence of elemental silver was revealed by chemical analysis accomplished by means of EDX analysis (Fig. 5). This was due to reduction of silver ions by TB extract to AgNPs. The existence of 'O' in EDX spectrum might be due to involvement of phytoconstituents in stabilizing AgNPs through 'O' related groups (Dauthal and Mukhopadhyay 2013;Ajitha et al. 2015).
X-ray diffraction
The XRD pattern of the AgNPs (Fig. 6) which showed four intense diffraction peaks at 37.7°, 43.8°, 63.7°, and 76.4°in the whole spectrum of 2h value ranging from 10 to 80 which can be indexed to (111), (200), (220) and (311). These peaks are characteristic of metallic face-centered cubic (FCC) phase of silver and matching with database of Joint Committee on Power Diffraction Standards (JCPDS, 3-065-8428) confirmed the crystalline nature of AgNPs. Some unidentified peaks (34.8°, 38.7°and 45.01°) also appeared in the XRD pattern of AgNPs, which might be due to the phytoconstituents in the extract involved in synthesis and stabilization of the AgNPs.
Mechanism of formation of AgNPs
The possible mechanism for the synthesis of AgNPs after reduction of Ag ? is illustrated in Fig. 7. Polyphenolic compounds can exist in two tautomeric forms; enol (phenolic) and keto (quinine) form. Under alkaline conditions (CpH 8), the most unstable enolic form of molecule predominates where its -OH group plays a principal role. This form has a strong tendency to donate electrons and undergo oxidation (Basnet and Skalko-Basnet 2011). The Ag ? ions form an intermediate complex with -OH, which upon oxidation forms quinone and leads to a subsequent reduction of Ag ? ion to Ag 0 (AgNPs).
Catalytic activity of AgNPs
In the present study, catalytic action of biosynthesized AgNPs has been evaluated using model reaction, reduction of 4-nitrophenol to 4-aminophenol. The addition of NaBH 4 to a 4-nitrophenol solution changed the color of solution from light yellow to intense yellow (Online resource Fig. S4) with bathochromic shift from 316 to 400 nm (Fig. 8a). This could be explained by a fact that the addition of NaBH 4 to a 4-nitrophenol causes a change in pH from acidic to highly basic due to formation of the 4-nitrophenolate ions (Saha et al. 2009). On monitoring this reaction by UV-Vis spectroscopy, it was found that in the presence of only NaBH 4 intensity of absorption at 400 nm for the 4-nitrophenolate ion remained unchanged even after 30 min (Online Resource Fig. S5). This result confirmed that the reduction of 4-nitrophenol does not proceed without a catalyst. Its reduction was carried out in presence of AgNPs as a catalyst and monitored at different time intervals (Fig. 8b). Very low concentration of AgNPs was used to avoid interference in the absorption of 4-nitrophenolate ion, because both have absorbance at around 400 nm (Online Resource Fig. S6). After the addition of AgNPs to reaction mixture, NaBH 4 reduced 4-nitrophenol to 4-aminophenol having typical absorption maxima of 298 nm (Chi et al. 2012). The intensity of the absorption peak at 400 nm gradually decreased with time which fully disappeared after *12 min while in the meantime, a new Fig. 7 Schematic mechanism of synthesis of AgNPs using polyphenol-rich TB extract Fig. 8 UV-Vis absorption spectra showing a formation of 4-nitrophenolate ion from 4-nitrophenol (0.5 mM) in presence of 25 mM NaBH 4 and b catalytic reduction of 4-nitrophenol to 4-aminophenol using AgNPs as a catalyst. Reaction was monitored up to complete reduction of 4-nitrophenol (reaction mixture contained 0.5 mm 4-nitrophenol, 25 mm NaBH 4 and 0.5% green synthesized AgNPs as catalyst) absorption peak appeared at 298 nm progressively with increasing intensity (Fig. 8b). However, addition of TB extract did not decrease the absorption at 400 nm of 4-nitrophenolate ions which remained unchanged even after 30 min (Online Resource Fig. S7). This result confirmed that TB extract did not catalyze the reduction of 4-nitrophenol to 4-aminophenol. The reduction reaction of 4-nitrophenol using AgNPs as catalyst exclusively yielded 4-aminophenol, without any other side products which is evident from existence of isosbestic points (Saha et al. 2009) at 251, 277 and 316 nm in UV-Vis spectra (Fig. 8b).
In this reaction, NaBH 4 acted as a reducing agent. To achieve complete or maximum reduction of 4-NP, the overall concentration of NaBH 4 was kept about 50 times higher (25 mM) than 4-nitrophenol (0.50 mM) making this reaction to follow the pseudo-first-order kinetic to determine the catalytic activity of AgNPs.
Catalytic reduction of 4-nitrophenol by NaBH 4 in presence of AgNPs was a time-dependent process as evident from a plot of concentration of 4-nitrophenol vs. reaction time (Online Resource Fig. S8). Concentration of 4-nitrophenol at any given time in the reaction was calculated from calibration curve of absorbance of 4-nitrophenolate ion at 400 nm vs. respective concentration of 4-nitrophenol.
The rate constant (k) of the reduction reaction of 4-nitrophenol using AgNPs as a catalyst was determined from the linear plot of -ln (A t /A 0 ) vs. reduction time in seconds (where A t and A 0 are the concentrations of 4-nitrophenol at time t and 0 s, respectively). It was estimated to be 4.60 9 10 -3 s -1 . To compare the catalytic potential of green synthesized AgNPs with previously reported nanomaterials, the activity parameter (K = k/mass of catalyst) was determined. Volume of AgNPs used in catalytic reduction of 4-nitrophenol was 0.25 mL of 5 mM AgNPs which corresponds to 0.212 mg, thus using this value k was calculated and found to be 21.698 s -1 g -1 . Activity parameter of green synthesized AgNPs (in this study) was greater than that of nanomaterials reported earlier (Rashid and Mandal 2007;Chi et al. 2012).
Smaller average particle size (20.74 nm), well monodispersed solution and good stability of the biosynthesized AgNPs attributed to the good catalytic activity of nanoparticles. The smaller size consists of a high surfaceto-volume ratio and better exposed Ag atoms on the surface where such atoms act as the potent catalytic sites (Baruah et al. 2013). The reaction mechanism for the reduction of 4-nitrophenol to 4-aminophenol by NaBH 4 in the presence AgNPs as a catalyst can be well explained by widely accepted Langmuir-Hinshelwood (LH) model (Online Resource Fig. S9). These results indicated that AgNPs might have a significant application in the field of heterogeneous catalysis.
Antibacterial and antibiofilm potential of AgNPs
The AgNPs synthesized by TB extract showed considerable antibacterial activity against the human pathogenic bacterial strains. The zone of inhibition measured (Table 1) suggested that, P. aeruginosa was more sensitive to the AgNPs, followed by E. coli; while B. subtilis and S. aureus showed comparatively minimal sensitivity toward the AgNPs. This was also confirmed from the MIC of AgNPs measured against these bacteria (Table 2). P. aeruginosa showed the least MIC than others. This could be explained by higher affinity of P. aeruginosa cells to colloidal AgNPs than the other tested bacterial strains (Bondarenko et al. 2013). These results showed that AgNPs have a more significant effect on growth of Gram-negative bacteria than that of Gram-positive bacteria. This might be due to differences in the structure and composition of the cell wall of these bacteria (Fayaz et al. 2010). Development of biofilms increases the antibiotic resistance among the microorganisms, which makes it very difficult to control the infections (Mah and O'Toole 2001). The AgNPs have already been effective against planktonic microbial cells; however, the effect of these nanoparticles on formation and eradication of biofilm remains the thrust area. In the present study, the antibiofilm activity of AgNPs was assessed by crystal violet microtiter plate assay. The AgNPs showed higher ND not detected * Values were expressed as the mean ± standard deviation (SD) of n = 3, with P B 0.05 were considered to be statistically significant antibiofilm activity against the Gram-negative bacterial strains than Gram-positive (Fig. 9). In E. coli and P. aeruginosa, 20 lM and 39 lM concentrations of AgNPs inhibited biofilm formation by more than 98%, respectively. However, in S. aureus and B. subtilis 78 lM concentrations of AgNPs were needed to inhibit biofilm formation by 98%. This observation may be a result of the structural differences in the composition of the cell wall of these bacteria which supports earlier reports (Martinez-Gutierrez et al. 2013). Among the Gram-negative bacteria, E. coli was more susceptible to biofilm inhibitory effect of AgNPs than P. aeruginosa. The probable mechanism by which AgNPs reduce/inhibit the formation of biofilms could be an interference or inhibition in the production of extracellular polymeric substances (EPS) by the bacteria (Kalishwaralal et al. 2010) or inhibition of synthesis of quorum-sensing related factors triggering signals in the biofilm formation. The ability of the AgNPs to disrupt pre-formed biofilms of selected strains was tested at their BIC. It was found that pre-formed biofilms of all four bacterial strains were significantly disrupted under both nutrient-limited (supplemented with SDW ? AgNPs) as well as nutrient-rich (supplemented with media ? AgNPs) conditions (Fig. 10). However, greater disruption was observed under nutrientrich conditions. In biofilm, bacterial growth rate as well as metabolism get reduced or altered. Slow-growing or nongrowing cells within the biofilm can shut down their metabolism due to limited nutrient conditions and become resistant to antibacterial treatments (Durmus et al. 2013). Therefore, adding nutrients along with AgNPs to the biofilm can stimulate metabolic microenvironment of the biofilm and may facilitate disruption by better penetration of AgNPs in the biofilm. These results indicated that AgNPs might have a significant application in the field of nanomedicine. However, further studies are needed for their actual implication.
Conclusion
An efficient and rapid method for the green synthesis of colloidal silver nanoparticles has been established using medicinally important T. bellirica fruit aqueous extract. The spectroscopic as well as microscopic properties of biocapped AgNPs were studied. The polyphenolic compounds present in the fruit extract have acted as an effective reducing agent as well as stabilizing agent, resulting in Fig. 9 The effect of AgNPs on the formation of bacterial biofilms [values were plotted as a mean ± standard deviation (SD) of n = 3 and in a group, bars denoted with same letter from 'a-d' do not differ significantly from each other where P B 0.05] Fig. 10 The potential of the AgNPs to disrupt pre-formed biofilms; NL nutrient-limited condition and NR nutrient-rich condition [values were plotted as the mean ± standard deviation (SD) of n = 3] the formation of stable AgNPs of 20.74 nm average size. The synthesized colloidal AgNPs were efficiently used as catalyst for the reduction of 4-nitrophenol to 4-aminophenol which is evident from the spectrophotometric studies. These AgNPs showed potential antimicrobial as well as antibiofilm efficacy against human bacterial pathogens. This work also states the significance of medicinally important plant T. bellirica in the development of future AgNP-based nanocatalyst and nanomedicines. | 6,535.2 | 2017-04-13T00:00:00.000 | [
"Chemistry",
"Environmental Science",
"Materials Science"
] |
Dielectric Slab Photonic Crystals Containing Metallic Components for E Polarization Mode
By using plane wave expansion method, we calculated the photonic band structure of metal cylinders in a dielectric medium. The photonic crystal is an identical, symmetrical structure with an infinite array of metallic rods. Arrangement of the metallic rods used is square lattice. The dielectric function of the metal from which the cylinders are formed has a simple, free electron form ε(ω)=1-(ωp/ω) where ωp is the plasma frequency of the conducting electron. We manage to show the band structure of the square lattice. We found the relation between the band gap size and the filling fraction for some widely used material. For an example, FR-4, silicon, resin, teflon etc. The relation between the band gap size and the dielectric constant of the medium was studied.
Introduction
Photonic crystals are periodic dielectric structures.They were studied by Yablonovitch (Yablonovitch, 1993) where the analogy between the electromagnetic wave propagation in periodic crystals and electron propagation in real crystals was found when the photonic crystals energy is solved using the Maxwell Equation.In his study, the importance of the band gap in the band energy of the photonic crystals is emphasized.The existence of the band gap can help to mould the flow of the light by localizing and guiding the flow of photon in the structure.Non-frequency dependant material and frequency dependant material have been used in the investigation of band gap.Some important information can be obtained from the band energy graph.For example: transmittance spectra (Sakoda, 1995), refractive index (Pendry, 2000) and propagation mode (Reinhard et al., 2008).There are many methods proposed to calculate the band energy structures (Hermann et al., 2001, Plihal and Maradudin, 1991, Kuzmiak et al., 1994, Zhou et al., 2004, Parui and Das, 2004, Guo and Albin, 2003, Rambabu et al., 2007) which include the plane wave expansion method (PWE), finite differences time domain (FDTD), super cell and finite differences frequency domain (FDFD).Each method has its own limitations of finding the band structure.Kuzmiak and etc(Kuzmiak and Maradudin, 1998, Kuzmiak and Maradudin, 1997, Kuzmiak et al., 1994) reported a band structure calculation using PWE method.They successfully calculated the band structure of metallic component in the vacuum medium.Sakoda andetc(Sakoda et al., 2001, Ito andSakoda, 2001) also reported an investigation of metallic photonic crystals using FDTD which brought to the surface plasmon investigation.Their was limited to the vacuum medium.So, above two different methods of investigation has showed that only vacuum medium was chosen.It is very obvious that dielectric medium was neglected.As a result, we used the PWE method to generalize or to complete the investigation of band structure which include dielectric medium for metallic photonic crystals.This is a very pivotal because photonic crystals should not limit in vacuum medium.This can lead the scientist to further investigation in different applications.For an example, waveguide, antenna, filters and so on.
In this study, we focused on generalizing the equation from PWE method for calculating the band structure.In the PWE method, simple free electron form of dielectric function is chose, where ω p is the plasma frequency of the conduction electrons.The collision frequency γ is neglected because it is extremely too small compare to the plasma frequency.Detail mathematical formulation is discussed in section 2.Then, we investigated the effect of band gap size with different dielectric medium and discussed in section 3.
The mode considered here is the E polarization mode.
Basic
The 2D structure is shown in Figure 1.The periodic structure is assumed along the x axis.
From Figure 1 and 2, a periodic function of x || is derived as below It can be expanded into a two dimensional Fourier series as below where || G is a vector of the lattice reciprocal and Fourier coefficients of the || ( )
Dielectric Function for E Polarization
The dielectric periodic function is modified and constructed to meet the requirement of the metallic structure proposed in Figure 1.It is formulated into equation( 5).
is inside the cross section of the cylinder centered at the origin of coordinates and S(x)=0 if x || outside this cross section.ε 0 is the dielectric constant of the medium and ε(ω) is the free electron dielectric function for metallic cylinders.We expand equation ( 5) in Fourier Transform where the integral is now over the entire 1 2 x x plane and || G is reciprocal lattice.
Therefore, equation ( 6) can be rewritten in the form below where is the filling fraction.So, in the particular case of metallic cylinders where cross section is in a circle of radius R, where J 1 is the Bessel function.
Application
To find the band structure, Maxwell's equation is applied.In E polarization mode, we seek solutions of Maxwell's Equation, which have the forms So, E 3 can be obtained from the Maxwell curl equations for the non-zero field as below Equation ( 14) is solved by using the expansion (3) and write in the form below ( ) where k is the wave vector of the wave.Equation ( 16) is obtained which satisfied the coefficients ( | ) The use of the results of equations ( 7) and ( 8) into the equation ( 16) which transforms the latter into
Results and discussion
Equation ( 17) is a nonlinear problem of the second order (Kuzmiak and Maradudin, 1997).So, the equation is rewritten in the form below.
where the equivalent matrix has the form In our derivation, we found that there is a new part in equation ( 19).This part is Obviously, when the medium is changed to vacuum, (22) will vanish in equation ( 17).This correlates with Kuzmiak finding.So, the equation is reduced to the diagonalization of the non-Hermitian matrix which yields eigenvalues.In this study, FR-4 is used as the dielectric medium with dielectric constant ε 0 =4.9 and copper as metallic cylinder with plasma frequency ω p =1914THz (El-Kady et al., 2000).Both of them are very common materials that are being used in electronic industry.A simple investigation had been carried out to study effectiveness of both materials as photonic crystals.Meanwhile, the lattice parameter a for which the primitive translation vectors of square lattice are while the vectors of the reciprocal lattice, G are The filling fractions of the square lattice metallic rods in dielectric medium are The calculation of band energy when dielectric constant ε 0 =4.9 as shown in Figure 3(a), 3(b) and 3(c) has been done.The energy band graph is scanned through with different filling fraction.When filling fraction is extremely small, it is an ordinary band energy graph of FR-4 as shown in Figure 3(a).We found that band gap occurs in between first and second energy band for filling fraction f>0.2.But the band gap was vanished when f>0.4.We plotted the band energy with f=0.4 and f=0.9 as shown in Figure 3 Figure 3(b) showed that the first energy become flat.This is due to the metal cyclinders is almost being filled up the dielectric medium and energy is unable to transfer to another point.This cause the wave's group velocity slow down in all direction in the medium.In this investigation, a total of 121 waves were used to find the band structures.The existence of band gap has proved that FR-4 and copper can act as photonic crystals in certain filling fraction.It can be used for moulding the flow of wave in printed circuit board.
In Figure 4, various filling fraction has been used to investigate the change of band gap size in FR-4.We noticed that there is band gap when 0.2≤f≤0.4.But there is a small gap exist when f=0.9.The sizes of the band gap is very small and can be ignored.
Relationship between dielectric constant and band gap size at for all filling fraction f was also investigated.We only study the band gap occurred in between the two lowest band.The range of dielectric constant used is from 1 to 12 as shown in Figure 5.In this range, it included silicon ε 0 =3.2, Teflon ε 0 =2, resin ε 0 =3.4.From the graph, interestingly we found that when 2≤ε 0 ≤4.There is no gap occurs for all filling fraction.Band gap only appear when dielectric constant ε 0 >4.It increase with the dielectric constant.But it only avalaible for filling fraction f≤0.6.Beyond this filling fraction, there is no band gap exist.So, it will become a normal artificial material.
From the graph, we know that existence of metallic component in the dielectric medium may be considered as another photonic crystal.
Conclusion
We generalized and completed the calculation of band structure of dielectric medium containing metallic component.We used the plane wave expansion method and successfully calculated the band gap structure for infinite dielectric medium containing metallic structure.A total of 121 waves are needed to obtain a very accurate result for E polarization.Investigation has been done for FR-4, ε 0 =4.9.From this investigation, band energy of E polarization regardless of filling fraction does not tend to become zero at Γ.The band gap appears when 0.2≤f≤0.4.Therefore FR-4 and copper can act as photonic crystals.Interestingly, we also found that when dielectric constant 2≤ε 0 ≤4, band gap does not exist for all filling fraction and values of dielectric constant.It exist when dielectric constant ε 0 >4 and filling fraction f≤0.6.The method of calculation here can be extended to find the band gap structure of defect mode and waveguide mode of photonic crystals which is made of dielectric medium containing metallic cylinders.
Figure 1 .Figure 2 .Figure 4 .Figure 5 .
Figure 1.Cross section view from zx plane of the 2D periodic structure where ε 0 is the dielectric constant of the medium and ε(ω) is the free electron dielectric function of the metallic cylinder | 2,245.6 | 2010-10-19T00:00:00.000 | [
"Physics",
"Materials Science"
] |
A New Distribution-Free Approach to Constructing the Confidence Region for Multiple Parameters
Construction of confidence intervals or regions is an important part of statistical inference. The usual approach to constructing a confidence interval for a single parameter or confidence region for two or more parameters requires that the distribution of estimated parameters is known or can be assumed. In reality, the sampling distributions of parameters of biological importance are often unknown or difficult to be characterized. Distribution-free nonparametric resampling methods such as bootstrapping and permutation have been widely used to construct the confidence interval for a single parameter. There are also several parametric (ellipse) and nonparametric (convex hull peeling, bagplot and HPDregionplot) methods available for constructing confidence regions for two or more parameters. However, these methods have some key deficiencies including biased estimation of the true coverage rate, failure to account for the shape of the distribution inherent in the data and difficulty to implement. The purpose of this paper is to develop a new distribution-free method for constructing the confidence region that is based only on a few basic geometrical principles and accounts for the actual shape of the distribution inherent in the real data. The new method is implemented in an R package, distfree.cr/R. The statistical properties of the new method are evaluated and compared with those of the other methods through Monte Carlo simulation. Our new method outperforms the other methods regardless of whether the samples are taken from normal or non-normal bivariate distributions. In addition, the superiority of our method is consistent across different sample sizes and different levels of correlation between the two variables. We also analyze three biological data sets to illustrate the use of our new method for genomics and other biological researches.
Introduction
Confidence interval estimates of individual parameters are more informative than simple point estimates and thus they are widely used in statistical inference [1,2,3]. However, a joint confidence region (CR) for two or more parameters is often needed in practical applications. Classical applications include the joint CR for two or more regression coefficients in a typical multiple regression analysis [2]. More recently, there have been calls for the use of the joint CRs to ascertain superior genotypes identified for target environments in biplot analysis of genotype-by-environment interaction [4,5] or to unambiguously infer about population stratification in human admixtures [6,7,8,9,10].
Construction of the confidence intervals or regions for parameters often assumes that the data are from a normal distribution and they are balanced. For example, for bivariate normally-distributed data, the required CR is an ellipse whose shape depends largely on the level of the correlation between the two variables. However, when the distribution is unknown or hard to be characterized, several nonparametric procedures are available for construction of the confidence intervals or regions. Data peeling is a valuable approach to inspecting the structure of multivariate data [11]. The predominant implementation of data peeling is based on the convex hull of the data [12]. In convex hull peeling, the outmost convex hull is identified, the observations in the convex are assigned with index value of one and then these observations are removed from the data. This procedure is iterated but the index value is increased by one for each iteration until all observation are assigned with indexes. A CR can be determined by identifying the layer of peeling with the indexes higher than the threshold (preset significant level). The peeling approach is further developed by considering data depth [13,14] to address the inquiry to the effectiveness of the procedure [11,15]. HPDregionplot [16] is another nonparametric method for constructing CR. The fundamental behind the HPDregionplot is to use the contour that embraces the desired proportion of the capacity based on the two-dimensional kernel density estimates [17] as CR.
One of the key limitations with these parametric and nonparametric methods is the inaccurate estimation of the coverage rate by the CRs with the data of unknown distributions. All the non-parametric methods are computationally demanding [18] and some of them (e.g., HPDregionplot) are sensitive to small sample sizes. In this paper, we introduce a simple distribution-free geometry-based procedure that allows for constructing the CR for two or more parameters when there is no knowledge about the sampling distributions of the estimated parameters. We examine statistical properties of the new method through computer simulations and illustrate its use through two biological examples.
Quantile for a single parameter
For a single parameter, the distribution-free approach to computing a percentile is quite straightforward. Although different definitions for percentiles exist [19], all the definitions would lead to similar results given a large number of the random samples [20]. After obtaining estimates from individual random samples, three basic steps are followed to construct a distribution-free confidence interval: (1) to sort the N estimates in the ascending order; (2) to search for the nearest ranks for p th percentile by picking up the closest integers to N|p; and (3) to estimate the desired percentile by linear interpolation between the two consecutive ranks.
Quantiles for multiple parameters
Although the above procedure considers one variable only, it can be extended to the calculation of the CR simultaneously for two or more variables. For simplicity, let us consider the case of two variables. Let x and y be the two vectors of size (N|1). The values in vector x are the Euclidean distances, in geometry, between the observed points and the vertical coordinate (i.e., the reference line at x~0). Similarly, the values in vector y are the Euclidean distances between the observed points and the horizontal coordinate (i.e., the reference line at y~0). Thus the quantiles estimated for a single parameter are also the quantiles of the relative distances between the observed points and the reference line at x~0 or y~0. However, with unknown joint sampling distribution of variables x and y, all potential reference lines across the entire plane need to be considered while constructing the distribution-free CR.
Here we describe a general geometry-based approach to constructing the CR for any bivariate data. As mentioned earlier, the confidence interval for one variable can be regarded as a special case in which the reference line has been set to either vertical or horizontal coordinate axis (x~0 or y~0). Now let us consider the confidence interval for an arbitrary reference line (cf. Figure 1). Since the positions of the observations in relation to a reference line, i.e., the distances with directions, are used to obtain the percentile, all reference lines have the same slopes but with different intercepts. We simplify the derivation by assuming all reference lines through the origin of the coordinates. The arbitrary reference line is expressed as where h is the angle between the reference line and the horizontal abscissa (see section A of Appendix S1 for detailed derivation). It is also evident from Figure 1 that the relative position (distance) of the i th observations (x i , y i ) to the reference line as given in eq (1), is calculated as (see section A of Appendix S1 for detailed derivation), Applying eq. (2) repeatedly for all N observations, we obtain the relative positions that are stored in vector d. If the d vector is viewed as a single variable, then the algorithm described earlier can be directly applied to calculate the required quantiles. Here we consider that the statistical inference is based on the two-tailed tests. For a specified significance level a, the confident interval of a single parameter is flanked by the observed lower-and upperboundaries, i.e., the (N|a=2) th and ½N|(1{a=2) th percentiles. In geometry view, the boundaries l h,1~d N|a=2 and l h,2~d N|(1{a=2) represent the distances between two parallel lines and the reference line to ensure that 95% of the total data points lie within the boundaries and 5% outside the boundaries in the direction hzp=2 (see Figure 1). The function of the i th boundary line in an arbitrary direction in the plane is given as (see section B of Appendix S1 for detailed derivation) Let us denote the subset of all out-of-boundary points in the direction with the angle of h as P h . The observed significant level in this direction is expected to approximate the specified significant level for a single parameter (a), where n h is the number of out-of-boundary points in the direction with the angle of h in P h . Using the same strategy, we obtain the boundary lines in all directions by rotating the reference line in all directions over the plane. By taking all boundaries jointly into consideration, we construct a CR as a polygon in the plane under the assumption that the significant level for each direction is a. To the newly constructed region, the observations outside the polygon are counted as Since the directions with angles of h and hzp are actually the same reference line, we require the slope of the reference lines to increase monotonically with the angle while rotating the reference line with the range of h being h [ ½{p=2,p=2.
It should be noted that the method described above can also be viewed as a set of multiple tests and thereby the observed significant level for the CR is actually greater than the a level that is specified for each test, i.e., where n is the number of observations in P, d is the difference between the expected and the desired significant levels ( Figure 2). Thus, the a value that is actually specified to calculate the CR for each test should be lower than the desired significant level for multiple tests. Although it is difficult to provide a general function to describe the relationship between the two values, the desired a value can be obtained iteratively from the follow equation where a k is the assigned value of the significant level required for generating the CR in each direction, a 0 k denotes the actually significant level for the CR bounded by the polygon as showed in eq (6), and a 0 is the desired significant level for the overall test.
In this study, we construct the CR that is approximated by a polygon in a two-dimensional plane for the two variables. In each direction, the polygon is bounded by the lower-and upperboundaries as given in eq (3). The vertices of the polygon are the crossover points of all adjacent boundary lines. The vertice between two adjacent reference lines with the angle of d is a point in the plane whose two coordinate values are given by, Distribution-Free Approach for Confidence Region where, i~1,2 (see section C of Appendix S1 for detailed derivation).
Simulation studies
The performance of our new method is evaluated by analyzing simulation data. We simulate bivariate data with two variables x and y. Three bivariate sampling distributions are considered in our simulations. In simulation I, x and y are sampled from a bivariate normal distribution N(m,S), where m~0 0 and S~1 r xy r xy 1 with r xy being the correlation between variables,x and y. In simulation II, the two variables (x and y) are generated from a bivariate noncentral F-distribution following the approach of Song and Hsiao [21]. The marginal F-distribution of each of the two variables is specified asF (d 1 ,d 2~3 0,l~10), where d 1 and d 2 are degrees of freedom and l is the noncentrality parameter. In simulation III, the two variables (x and y) are generated from a mixture of two bivariate normal distributions which is given by . In all three simulations, the correlation r xy takes three values of 0, 0.5 and 0.9.
In each simulation, we take n = 200 and n = 10,000 pairs of x2y observations from the distribution to represent small and large samples, respectively. For each data, empirical CRs are constructed using our new method (distfree.cr/R, http://statgen.ualberta.ca), the classical ellipsoidal confidence region approach [2] implemented by the CAR package [22] in R [23] and other three nonparametric methods, the HPDregionplot in the emdbook/R package [16], the classic convex hull peeling [12], and data peeling based on the Tukey's depth [24]. The CRs are constructed for seven significance levels, a~0.005, 0.01, 0.025, 0.05, 0.1, 0.2 and 0.5. However, only one level of significance a~0:5 is used for the peeling approach based on the Tukey's depth because we use the bagplot approach [24], via the bagplot function in the aplpack/R package [25], to implement the peeling based on Tukey's depth, but both the method [24] and the software implementation [25] are developed exclusively for a~0:5 (Dr Peter Wolf, private communication). We develop an R code to implement the classical convex hull peeling approach based on its definition (available at http://statgen.ualberta.ca). The adequacy of the CRs is measured using coverage discrepancy plots [26] for each simulation run, i.e., Distribution-Free Approach for Confidence Region PLOS ONE | www.plosone.org the deviation of the realized-aestimate of each method to its real value. The realized-ais calculated as the proportion of the observations outside an empirical confidence polygon, which is determined using the pnt.in.poly function in the SDMTools/R [27].
In all three simulations, our method outperforms other methods (Figures 3, 4, and 5) as the realized-a estimates by our method is close to or coincides with the true significance levels for both small (n = 200) and large (n = 10,000) samples with all three r xy values. The classic ellipsoidal method provides overestimation when a is low and underestimation when a is high. All methods including the ellipsoid approach produce similar 95% CRs for the data from the bivariate normal distribution as in simulation I ( Figure 6). However, the CRs determined by the ellipsoid approach fail to account for the actual shapes of non-normal sampling distributions as in simulations II and III (Figures 7 and 8). The HPDregionplot is the most sophisticated strategy in capturing the shape of nonnormal sampling distribution in all simulations. However, the realized-a estimates by the HPDregionplot approach are constantly lower than the true significance levels; the underestimation tends to increase with the significant level and the correlation (r xy ), and it is more pronounced for non-normal data in simulations II ( Figure 4) and III ( Figure 5) than for normal data in simulation I (Figure 3). It is somewhat surprising to note that the bagplot method performs as well as our method with small sample (n = 200) but it performs poorly with the large sample (n = 10,000) particularly when r xy is high.
Empirical examples
We also analyze three empirical examples to illustrate the use of our new method for the analysis of real data sets. The first data set is taken from Table 4.3 of Rawlings et al. [2]. Since the data set was already described and analyzed by Rawlings et al. [2], we will only recapitulate the essential details of the data. The original data set consisted of physical fitness measurements on 31 men involved in a physical fitness program at the North Carolina State University. The variables measured were age (years), weight (kg), oxygen uptake rate (ml per kg body weight per minute), time to run 1.5 miles (minutes), heart rate while resting, heart rate while running (at the same time oxygen uptake was measured), and maximum heart rate while running. Rawlings et al. [2] carried out the multiple regression analysis to investigate the response of oxygen uptake to the change of time to run 1.5 miles (minutes), heart rate while resting, heart rate while running (at the same time oxygen uptake was measured), and maximum heart rate while running.
For illustration, we only show the CRs of the pairwise regression coefficients as constructed by our new method and the classic methods. The CRs are constructed using the convex hull data peeling approach [12], the classical ellipsoidal method as implemented using the CAR package in R [22], the HPDregionplot in the emdbook/R package [16] and our new geometry-based method (distfree.cr/R, http://statgen.ualberta.ca). Bootstrapping is used to generate 10,000 random samples from the original data. The size of each bootstrap sample is set to 31, the number of individuals as used in the original study. The multiple regression analysis is done for each bootstrap sample. The pairwise regression coefficients as well as their CRs (a~0:05) calculated by the four approaches are plotted (Figure 9). The realized-avalues are calculated as the proportions of the total observations that lie outside the CRs determined by our new method and the classical methods for all six pairs of regression coefficients. For each pair, the chi-square test statistics is computed to examine the significance of coverage discrepancies of the empirical CRs under the preset significance level of a~0:05. The testing results show the superiority of our new method over the classic methods because the deviations of the realized-avalues from a~0:05 by our new method are not biased from 0.05 in all pairs whereas there are 4, 6, and 2 pairs with biased realized-a estimates for convex hull peeling, ellipse, and HPDregionplot, respectively. The second data set is obtained from the 1000 Genomes project [28]. This data set consists of 1,092 human individual records from four super populations, which include 246 Africans (AFR), 181 Ad Mixed Americans (AMR), 286 East Asians (ASN), and 379 Europeans (EUR). For each record, there is an integrated haplotype map of 38 million single nucleotide polymorphisms (SNPs), 1.4 million short insertions and deletions and 14,000 larger deletions. Prior to the analysis, we use the PLINK software [29] to remove the SNPs with minor allele frequency (MAF) of ,0.05 and the SNPs with interval sizes smaller than 50 k base pairs in order to have a manageable subset of data. After the removal, a total of 51,529 SNPs remain and we use this subset of the data for the subsequent analysis. Principal component analysis (PCA) as implemented in the EIGENSTRAT software [9] is carried out. The first two principal components are used to generate the scatter plots as well as to construct the 95% confidential regions for individual super populations using the new method as well as the classical methods ( Figure 10).
It is evident from Figure 10 that the four methods generate distinctly different CRs particularly for the AFR and AMR populations. The four methods also reveal different patterns of population differentiation. The CRs constructed by the ellipse and HPDregionplot methods suggest that the EUR population is largely contained within the AMR population. In contrast, the CRs constructed by our new method and convex hull peeling approach suggest that the EUR population is somewhat distinguishable from the AMR population. In addition, the realized-a values derived from our new methods are always closer to the prescribed significance level of a = 0.05 than those from the classical methods.
The third empirical example is the winter wheat (Triticum aestivum L.) data set that has been used (e.g., Yan et al. [30]) for the biplot analysis of genotype6environment interaction. We (Yang et al. [31] and Hu and Yang [32]) have recently analyzed this data set as well to illustrate the application of our bootstrapping approach to statistical inference about genotypic and environmental scores obtained from singular value decomposition (SVD) of the two-way genotype6environment table. Here the example serves to show how the CRs constructed for individual genotypic and environmental scores corresponding to the first two principal components (PC1 and PC2) are valuable in pointing out the uncertainty around the mega-environments delineated by the earlier studies. Briefly, the data set consists of the yields of 18 winter wheat genotypes (G1 to G18) tested at nine environments (E1 to E9) in Ontario, Canada. Prior to the analysis, the deviations of cell means for all 162 (1869) genotype-environment combinations from location means are calculated. The resultant matrix is the basis for bidirectional bootstrapping, SVD and Procrustes rotation as explained in Hu and Yang [32].
The biplot of PC1 vs. PC2 genotypic and environmental scores along with the 95% CR is presented in Figure 11. The PC1 and PC2 account for about 78% of the total variability. To highlight key features in the biplot, the CR are displayed only for those scores that are significantly different from the origin of the biplot [i.e., the CR of the scores that do not include the point of (0,0)]. A hexagon is drawn to connect six genotypes (G3, G7, G8, G12, G13 and G18) that are located at the corners (i.e., vertices) of the hexagon in the biplot. To further facilitate the interpretation of the biplot, six line segments perpendicular to different sides of the polygon are drawn through the origin to subdivide the polygon into six sectors involving different subsets of environments and genotypes: the genotype at the corner of each sector is considered as the 'best' performer in the environments included in that sector as often claimed in the earlier studies (e.g., Yan et al. [30]). However, it is evident from the 95% CR of the scores that the 'best' genotypes are often not statistically different from other genotypes. For example, genotype G8 at the upright corner is indistinguishable from genotypes G4 and G10 in the same sector, judging from their overlapped CR. Simple visual inspection of the biplot [30] claimed that genotype G18 yielded more than genotype G8 in eastern Ontario (represented by E5 and E7) and G8 yielded more than G18 in southwestern Ontario (represented by the other seven environments). With the 95% CR being now attached to individual scores (Figure 11), this claim is no longer true because the CRs for G8 and G18 overlap. Thus, identification of superior genotypes or mega-environments based on the initial inspection of biplots is simply a curious visual observation only and it must be substantiated by subsequent parametric or non-parametric statistical assessments before being recommended for practical utility.
Discussion
In this study, we develop a new geometry-based, distributionfree approach to constructing the CR for two or more variables. Our new method is based only on a few basic geometrical principles and accounts for the actual shape of the distribution (Figures 1 and 2). Thus, it should be a significant complement to the existing parametric (ellipsoidal [2]) and nonparametric methods including bagplot [16], convex hull peeling [12], and HPDregionplot [25]).
Our method outperforms other parametric and non-parametric approaches to constructing CRs judging from coverage discrepancy plots of realized-a estimates. It is evident from Figures 3, 4, and 5 that our method always provides more accurate estimates of a than the other methods regardless of whether the sampling distribution is normal (simulation I) or not (simulations II and III). In addition, the superiority of our method is consistent over different levels of correlation between the two variables. So why is our method better? Simply put, it is the only method that accommodate for the actual shape of the distribution and allows for adjusting the realized-avalue to an individual data point level. While the convex hull peeling and data peeling based on Tukey's depth can also account for the shape of the actual distribution represented by the original data, the realized-avalue may still be different from the true a because the CR is determined by a 'peeling' layer. Thus, all the data points on the same layer have to be included or excluded simultaneously once the layer is determined as the border of the CR. The true a value can be under-or over-estimated unless each peeling layer consists of only one data point, an unlikely scenario for not too small samples or unless, by chance, the peeling layer along with outer layers constitute the exact a value.
The realized-a estimates by the parametric ellipsoidal method and semi-parametric HPDregionplot may also be biased, but for a different reason. In these methods, the original data are used merely to estimate parameters. It is these estimated parameters along with assumed normal distribution, rather than the original data that are used for constructing CRs. If the data is normally distributed, an unbiased estimate of a can be achieved; if, on the other hand, the data is from a non-normal distribution, the estimate of a may be biased upward or downward. If the true CR is a concave polygon or a crescent moon or the union of disjoint convex areas, then the HPDregionplot is the only method that is capable of capturing the true shape of the CR(e.g., the shape of the simulated distribution in simulation III). However, the HPDregionplot may produce the CRs with multiple isolated polygons for small sample sizes (e.g., simulation II for n = 200). Furthermore, in the current version of the emdbook/r package (version 1.3.2.1) on CRAN [16], the HPDregionplot function may also generate unclosed rather than closed polygons for CRs. In an attempt to address this issue, Dr. Ben Bolker, the author of the emdbook/r package, provided us with a set of new parameters for HPDregionplot function (private communication). While the use of these new parameters guarantees the closed polygons by extending the regions for the kde2d function, the polygons derived by the new HPDregionplot function are slightly larger than that calculated by the previous version, thereby leading to the underestimation of the realized-a values. Unfortunately, there is currently no solution to the issue. The HPDregionplot approach works well with accurate estimates of the empirical kernel density. High information content in the original data would be especially important for accurate estimation. This is probably why higher correlation between the two variables has caused greater discrepancy between the realized and true a values (Figures 3, 4, and 5). However, no similar trend is observed when the autocorrelation within the variables is considered (Figures S1-S4).
As shown above, the coverage discrepancy is a necessary criterion for evaluating the performance of different methods for constructing CRs. Nevertheless, it is not a sufficient criterion. For example, it is evident from Figure 4 that, in simulation II, the realized a estimates by the ellipsoidal method are biased upward with low a, but downward with high a. An inflexion point exists near a = 0.05 where there is little coverage discrepancy. However, this coincidence does not necessarily mean that the ellipsoidalbased CR can be used to approximate the CR for the sample taken from an F-distributed data because there is bias at all other a levels. It is shown ( Figure S5) that the point of the transition from over-to under-estimation of a changes with the degrees of freedom for the F-distributions, but there is little dependence on the noncentrality parameter.
Since each curve in the coverage discrepancy plot (Figures 3, 4, and 5) is calculated from a single random sample, the repeatability of the coverage discrepancy patterns revealed by the plots may be questioned [26]. To confirm the results in Figures 3, 4, and 5, ten additional random samples are generated from the three simulated bivariate distributions described earlier. The coverage discrepancy curves by the five methods are displayed in Figure S6. The plots show that the patterns revealed by the coverage discrepancy curves are fairly stable across different samples.
We provide detailed descriptions of our new distribution-free approach to constructing CR for two parameters only. This does not mean that it works only for the two-dimensional data. In fact, our method can be extended to higher-dimension situations. In constructing a CR for three or more parameters, we need to calculate the distances between the data points and reference planes (three variables) or reference hyperplanes (four or more variables). For example, the formula for the distance between the ith point in the three-dimensional space fx i ,y i ,z i g and the reference plane (axzbyzczze~0) is given by Korn and Korn [33], d i~j ax i zby i zcz i zej ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi a 2 zb 2 zc 2 p j cos w x x i z cos w y y i z cos w z z i ze 0 j ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi cos 2 w x z cos 2 w y z cos 2 w z q ð9Þ The second part of equation (9) is obtained using the 'normal' form of the reference plane (a normal line is the line perpendicular to the reference plane), cos w x x i z cos w y y i z cos w z z i ze 0~0 where cos w x~a ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi a 2 zb 2 zc 2 p , cos w y~b ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi a 2 zb 2 zc 2 p , cos w z~c ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi a 2 zb 2 zc 2 p , e 0~e ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi with w x , w y and w z being the angles between the normal line and axis x, axis y and axis z, respectively, and e 0 being the distance between the reference plane and the origin. The actual implementation requires the following two considerations: (1) the sample size required to construct a reliable CR is exponentially increased with the addition of variables; and (2) the amount of computation under higher dimension circumstances is escalating as more reference lines need to be taken into account while constructing the high-dimensional CR. Nevertheless, further research is needed for implementing and interpreting the multidimensional CRs. Although the normal distribution has been widely assumed in the past [1,2], the joint sampling distribution of the pairwise regression coefficients that are obtained from the data of the oxygen intake experiment by bootstrapping is evidently deviated from a bivariate normal distribution (Figure 9). Thus the basic assumption required for constructing ellipsoidal CRs may often be incorrect and this might lead to distorted CRs and thus to incorrect practical uses.
The second empirical example serves to demonstrate the use of our new method for adding the statistical inference capability to one of the most popular tools currently used in human population genomics. The correction for population stratification is an essential step towards eliminating spurious genetic effects in the genome-wide association study (GWAS) of admixed populations [34]. Cavalli-Sforza et al. [6] proposed the use of the principal component analysis (PCA) for detecting the stratification among human populations. Recently, the strategy has been further developed and adopted in using genomic data for the analysis of population stratification in human [7,8,9,10]. The effectiveness of such PCA-based detection depends on correct inference about the ancestry and population structure. Currently, the commonly used means of inferring the population stratification is the use of scatter plots of the first few principal components known as "radiation of circular or elliptic clines from a specification area" or the "principal-component map" [6]. However, the determination of population sharing or membership based on these plots or maps is somewhat arbitrary because it is based solely on visual inspection. Since the sampling distributions of the principal component scores derived from SNP markers are unknown, the use of the classical ellipsoidal method for constructing the CRs may not be adequate. The third example shows further utility of our new method for strengthening the biplot analysis of genotype6environment interaction. Thus, our distribution-free approach to constructing any multivariate CRs provides a statistical basis for such determination. Figure S1 The impact of autocorrelations (0, 0.5 and 0.9) on the coverage discrepancy plots for small sample n~200 in simulation I which is detailed in Figure 3.
Supporting Information
(EPS) Figure S2 The impact of autocorrelations (0, 0.5 and 0.9) on the coverage discrepancy plots for large sample n~10,000 in simulation I which is detailed in Figure 3.
(EPS) Figure S3 The impact of autocorrelations (0, 0.5 and 0.9) on the coverage discrepancy plots for small sample n~200 in simulation II which is detailed in Figure 4. (EPS) Figure S4 The impact of autocorrelations (0, 0.5 and 0.9) on the coverage discrepancy plots for large sample n~10,000 in simulation II which is detailed in Figure 4.
Author Contributions
Conceived and designed the experiments: ZH R-CY. Performed the experiments: ZH. Analyzed the data: ZH. Contributed reagents/ materials/analysis tools: R-CY ZH. Wrote the paper: ZH R-CY. | 7,401.8 | 2013-12-04T00:00:00.000 | [
"Biology",
"Mathematics"
] |
Coupled molecular dynamics mediate long- and short-range epistasis between mutations that affect stability and aggregation kinetics
Significance Incomplete understanding of the mechanisms of epistasis between two or more substitutions in a protein can hamper protein-engineering strategies. With Escherichia coli transketolase as a model, we explore the epistatic interactions between a set of stabilizing mutations from across two different domains within the protein structure. Surprisingly, not all pairwise effects between distant mutations from the surface and core regions of different domains were additive. Additionally, the epistatic behaviors observed were dependent on the type of stability measured. We found single mutations that altered local protein dynamics, which then induced correlated changes in the dynamics of a second domain of the same monomer. This mechanism mediated epistasis between distant mutations.
Multiple mutations are typically required to significantly improve protein stability or aggregation kinetics. However, when several substitutions are made in a single protein, the mutations can potentially interact in a nonadditive manner, resulting in epistatic effects, which can hamper protein-engineering strategies to improve thermostability or aggregation kinetics. Here, we have examined the role of protein dynamics in mediating epistasis between pairs of mutations. With Escherichia coli transketolase (TK) as a model, we explored the epistatic interactions between two single variants H192P and A282P, and also between the double-mutant H192P/ A282P and two single variants, I365L or G506A. Epistasis was determined for several measures of protein stability, including the following: the free-energy barrier to kinetic inactivation, ΔΔG ‡ ; thermal transition midpoint temperatures, T m ; and aggregation onset temperatures, T agg . Nonadditive epistasis was observed between neighboring mutations as expected, but also for distant mutations located in the surface and core regions of different domains. Surprisingly, the epistatic behaviors for each measure of stability were often different for any given pairwise recombination, highlighting that kinetic and thermodynamic stabilities do not always depend on the same structural features. Molecular-dynamics simulations and a pairwise cross-correlation analysis revealed that mutations influence the dynamics of their local environment, but also in some cases the dynamics of regions distant in the structure. This effect was found to mediate epistatic interactions between distant mutations and could therefore be exploited in future protein-engineering strategies. dynamics | epistasis | stability | protein engineering | transketolase P roteins and enzymes are increasingly used as therapeutics, as diagnostics, and for industrial biocatalysis. These applications often require function at elevated temperatures or after longterm storage, and so the development of efficient strategies to enhance their stability remains a major goal in protein engineering. High thermal stability is also strongly correlated with expression yield, in vitro half-life, and in vivo serum survival time (1)(2)(3). Additionally, thermostable proteins tolerate more mutations than mesophilic ones, which makes them a better starting point in protein engineering (3,4).
Directed evolution is a powerful strategy for engineering protein stability through the accumulation of beneficial substitutions. The desired property is obtained by screening or selection of a library of randomly mutated variants. However, it is often necessary to screen large numbers of mutants in several rounds of evolution to obtain a desired level of change (5). Where there is no highthroughput screen for the target property, such as aggregation kinetics of purified enzymes, then random mutagenesis approaches become inaccessible. By contrast, smart-library design and semirational site-directed mutagenesis has gained popularity due to improved efficiency (6) and improvements in the prediction accuracy with which computational or rational design strategies can propose stabilizing mutations. For example, reconstructed ancestor or consensus sequences from multiple protein sequence alignments can propose mutations based on the hypothesis that they are more thermostable than extant homologs (7,8). Statistical analysis of protein secondary-structure sequences also found that proline prefers to be at the second position of β-turns (9). The strategy of inserting proline mutations is also well known to stabilize many enzymes (10,11). Meanwhile, structural information has been critical for computational design methods. Many algorithms apply geometrical or energy constraints when analyzing 3D structures, to optimize the surface charge of proteins, or introduce disulfide bonds that increase protein stability (12,13). Recently, several computational protein design algorithms have been developed to predict the impact of mutations upon stability to global unfolding, including Rosetta (14), FoldX (15), and SDM (16).
While site-directed mutagenesis is widely used to engineer protein stability, single-point mutations usually contribute relatively little, and multiple mutations are typically required to stabilize large proteins (17). Many mutations contribute independently to fitness, and their collective contributions (Δ AB for A and B) are found to be mathematically additive, where Δ AB = Δ A + Δ B . The contributions of some are affected by mutations made at other sites in the protein, in a phenomenon known as intragenic epistasis (18). Therefore, when mutations that contribute positively on their own (Δ A > 0) are combined into a single protein, two or more mutations often interact in a nonadditive manner. This epistatic behavior can be measured via its effect on various protein properties and can have either positive epistasis, where Δ AB = Δ A + Δ B + X; negative epistasis (partially additive), where (Δ A and Δ B ) < Δ AB < Δ A + Δ B ; negative sign epistasis, where Δ AB < (Δ A or Δ B ); or reciprocal sign epistasis, where Δ AB < 0 (19)(20)(21). Additive effects are most likely when the structural regions influenced by each mutation do not Significance Incomplete understanding of the mechanisms of epistasis between two or more substitutions in a protein can hamper proteinengineering strategies. With Escherichia coli transketolase as a model, we explore the epistatic interactions between a set of stabilizing mutations from across two different domains within the protein structure. Surprisingly, not all pairwise effects between distant mutations from the surface and core regions of different domains were additive. Additionally, the epistatic behaviors observed were dependent on the type of stability measured. We found single mutations that altered local protein dynamics, which then induced correlated changes in the dynamics of a second domain of the same monomer. This mechanism mediated epistasis between distant mutations. substantially overlap (22). It is well known that epistasis is most likely for mutated residues that are in direct contact with each other (23,24). However, epistasis has also been observed between mutations of structurally distant residues, with their effects proposed to be mediated through a network of interactions (25). How such networks mediate epistasis between distant mutations remains poorly understood and thus hampers the development of more effective rational or semirational protein-engineering strategies (26).
Dynamics potentially mediate long-range communication in proteins (27). Several studies have investigated the impact of point mutations upon protein dynamics using NMR (28) or computational algorithms (29,30), and found that changes in the dynamics due to single point mutations could be frequent, significant, and long-ranged. Most studies have focused on the impact of longrange dynamics on allostery, ligand binding, and the effect of mutations distant from sites normally associated with function (31). However, little is known about the role of dynamics in longrange epistasis between mutations, or their impact on conformational stability, and even less for aggregation kinetics.
With Escherichia coli transketolase (TK) as a model, we investigated how the combination of stabilizing mutations influenced various measures of protein stability, including thermal transition midpoint (T m ), aggregation onset temperature (T agg ), rates of irreversible thermal inactivation at elevated temperature, and the fraction unfolded at that temperature (f T ). For each, we explored the additivity for pairs of mutations, compared their structural locations, and investigated their impact on protein flexibility to determine the role of dynamics in epistasis. TK, a thiamine diphosphate-dependent (ThDP) enzyme, catalyses the reversible transfer of a C2-ketol unit from D-xylulose-5-phosphate to either D-ribose-5-phosphate or D-erythrose-4-phosphate in living cells (32,33). TK is a homodimer of two 70-to 74-kDa monomers, each composed of a pyrophosphate (PP)-binding domain, pyrimidine (Pyr)-binding domain, and a C-terminal domain. A Mg 2+ or Ca 2+ ion, and ThDP cofactor binds into each active site formed at the two identical interfaces between the PP and Pyr domains of opposite subunits. TK has considerable industrial biocatalytic potential for the stereospecific synthesis of carboncarbon bonds in complex carbohydrates and other high-value compounds (34,35). Use of β-hydroxypyruvate (HPA) as the ketol donor renders the donor-half reaction irreversible, thus increasing the atom efficiency of the reaction favorably for industrial syntheses. E. coli TK converts HPA with a rate of 60 U/mg, significantly higher than the 2 and 9 U/mg reported for its orthologs from spinach and yeast (36).
Directed evolution has expanded the ability of E. coli TK to accept a wide range of nonnatural substrates (37)(38)(39)(40). However, as a mesophilic enzyme, E. coli TK suffers from poor stability at elevated temperatures and extremes of pH, which has hampered its wide application in industrial processes (41). Recently, we constructed mutants focused at different regions of E. coli TK to increase its thermostability. First, by mutating residues in the flexible cofactor-binding loops toward those found in Thermus thermophilus at equivalent positions, the H192P mutation was found to double the half-life at 60°C (42,43). Using the rigidifying flexible sites strategy (44), 49 single mutations were individually targeted to flexible loops on the surface, which led to several more stable variants including D143K, I189H, and A282P. Combining H192P with A282P extended the half-life at 60°C to triple that of WT (42). In a separate study, consensus mutations were targeted to protein hydrophobic core regions, and six single mutants including I365L, G506A, and V228I showed significantly improved thermostability compared with WT (45).
Here, we created a set of variants along different evolutionary pathways from WT to H192P/A282P/I365L/G506A, based on four individually thermostabilizing single mutations identified previously. H192P and A282P were located 33 Å apart on the surface of the PP-binding domain, whereas I365L and G506A were located 12 Å apart in the hydrophobic core of the Pyr-binding domain, and at least 25 Å from H192P or A282P. The PP and Pyr domains from opposite chains interact strongly with each other in the homodimer, and so mutations in each domain might be expected to influence those in the other through either an interchain or intrachain mechanism. We generated four new variants, I365L/G506A, H192P/ A282P/I365L, H192P/A282P/G506A, and H192P/A282P/I365L/ G506A, and then investigated the epistatic interactions among the four mutation sites by analyzing the kinetics and free energy of thermal inactivation, T m , T agg , and f T , for all variants. Molecular-dynamics (MD) simulations were analyzed using a dynamics cross-correlation matrix to reveal the role of dynamics in mediating the observed epistasis between mutations.
Comparison of Kinetic and Thermodynamic Stability. For industrial enzymes, kinetic stability is critical for retaining activity during the time course of the bioconversion at a given operating temperature. The kinetic stability of TK at elevated temperatures relates to the rate of inactivation due to irreversible aggregation, promoted by increased partial unfolding of the native protein upon heating (41). The kinetic stability of TK variants was determined from the activity retained after incubation at 60°C for 1 h. The combined variants all retained higher activities than the WT and respective single-mutant parents. The quadruple mutant, H192P/A282P/I365L/G506A, retained 66.2% activity after incubation at 60°C for 1 h, representing a 10.2-fold improvement over WT ( Fig. 2A). To probe the kinetic stabilities of the TK combined variants in more detail, we measured their half-lives, t 1/2 , for loss of enzyme activity at 60°C, by incubating them at 60°C for different periods of time ( Fig. 2B and SI Appendix, Fig. S1). Whereas, in previous work, inactivation profiles were fit with less accuracy to single-exponential decays (42,43), giving longer estimates of half-lives, the current analysis revealed better fits to a second-order reaction equation. The half-lives for WT, H192P, A282P, and H192P/A282P were now determined as 4, 15.2, 7.7, and 19.3 min, respectively ( Table 1). All three newly combined variants shown in Fig. 2B deactivated more slowly than both WT and H192P/A282P, indicating an increased resistance to high temperature. The two triple-mutant variants, H192P/ A282P/I365L and H192P/A282P/G506A, had similar half-lives, 50.6 and 53.2 min, respectively ( Table 1). The quadruple variant, H192P/A282P/I365L/G506A, had the highest half-life of 82.5 min, representing a 21-fold improvement over that of WT (4 min). Enzyme kinetic studies revealed that H192P/A282P/I365L, H192P/A282P/G506A, and H192P/A282P/I365L/G506A did not appear to impact significantly on the kinetic parameters k cat and K m , indicating their improved potential to be used for biocatalysis (SI Appendix, Table S1).
The quadruple-variant and WT TK were also incubated at different temperatures from 22 to 65°C for 15 min, and the retained activities measured after cooling to 22°C were calculated relative to those incubated throughout at 22°C. No significant differences in residual activity were observed with incubations below 50°C (Fig. 2C). However, incubation at 57°C reduced the activity of WT 71.7%, whereas the quadruple variant retained 90.0% of the original activity. The temperature required to reduce the initial enzyme activity by 50% within 15 min (T 50 15 ), for WT was around 58.5°C, which was 2.5°C lower than that of the quadruple variant (61.0°C) ( Table 1). At 50°C, the retained activity of the quadruple variant increased by 5% compared with lower temperatures. As we have observed previously, heat treatment at 50°C improved the activity of WT E. coli TK by 50% after 0.5 h, and by 100% after 1 h (41), while heat treatment at 55°C increased the activity of H192P by 2.5-fold after 1 h (43). The more limited activity improvement after incubation at 50°C in the present work was due to the shorter incubation time of only 15 min.
We also investigated the thermal transition midpoint temperatures, T m , a measure of thermodynamic conformational stability obtained from intrinsic fluorescence measurements, for all variants. Their aggregation onset temperatures, T agg , were simultaneously determined from static light scattering measurements (Fig. 2D). All variants had increased T m and T agg compared with those of WT (Fig. 2D). The three variants H192P, A282P, and H192P/A282P had T m values 0.8, 0.6, and 1.7°C higher, respectively, than that of WT. The quadruple mutant had the highest thermodynamic stability, with T m and T agg values 3.2 and 3.6°C higher, respectively, than those of WT. T agg values were ∼0.2-0.5°C lower than T m in all cases, except for the quadruple mutant, for which T agg was 1°C higher than T m . This close link indicated that, on the timescale of the thermal ramping experiment, heat-induced aggregation only began when the protein had become significantly unfolded. The quadruple mutant was stabilized in such a way that greater unfolding could occur before aggregation was observed. This could result from increased colloidal stabilization, normally associated with increased net charge or decreased surface hydrophobicity. However, the I365L mutation, which induced the observed effect was not expected to alter either property. Alternatively, the increase in T agg above T m could result from the selective stabilization of a region of structure required to unfold for aggregation to occur, or otherwise from a decrease in the inherent propensity of a local sequence region to form stable intermolecular interactions within aggregates.
The fraction of protein unfolded at 60°C (f 60 ) was determined for the WT and mutant TKs, to evaluate the extent to which global protein unfolding influenced the inactivation rates at 60°C. Surprisingly, f 60 did not show any clear correlation with the T m values (Fig. 2D). For example, I365L/G506A had the highest f 60 of 0.24, around 0.1 higher than that of WT, and H192P/A282P/G506A had an f 60 of 0.04, around 0.1 lower than that of WT, whereas both variants had higher T m and T agg values than WT. The lack of correlation between T m and f 60 indicated that the cooperativity of unfolding was variable across the mutants, as reflected in their ΔS vh values (Table 1). We examined the linear correlations between T m and ΔS vh value, which indicated that variants with im-proved T m generally had lower ΔS vh values, and so apparently lower unfolding cooperativity (SI Appendix, Fig. S2). During the thermal unfolding process, the holo-TK homodimer undergoes unfolding of all three domains in each monomer, cofactor release, and also dimer dissociation, apparently at the same time (46). The decreased unfolding cooperativity for variants with increased T m could indicate the decoupling of at least one of these events from the rest, due to selective stabilization of one structural element.
Correlation Between Kinetic Stability and Thermodynamic Stability.
The heat-induced kinetic inactivation of TK proceeds through a second-order reaction, which implies an interaction between at least two molecules, consistent with the observation of aggregation as the end product. Aggregation could proceed through a number of potential mechanisms, including the following: (i) molecular reorganization after interaction of native states; (ii) partial local unfolding of native states before interaction; or (iii) global unfolding before interaction. Thermodynamic stability, as measured by T m , and more specifically by f 60 , can reveal the extent to which global unfolding is important in inactivation by aggregation (47). The deactivation rate constants at 60°C, expressed as ln(k d ), are shown in Table 1. T m gave a good linear correlation to the kinetics of inactivation, with an R 2 value of 0.93 (SI Appendix, Fig. S3A), indicating a clear link between kinetic and thermodynamic stability. By contrast, the correlation between f 60 and ln(k d ) was poor (SI Appendix, Fig. S3B), indicating that global unfolding was not the only factor to influence inactivation by aggregation, and likely also involved the decoupling of local unfolding events that manifested as changes in ΔS vh . In particular, the inactivation rate at 60°C for H192P/A282P/I365L and H192P/A282P/I365L/G506A decreased significantly, while their fraction unfolded remained at 11-13%, similar to those of H192P/A282P and WT. These two variants had the lowest ΔS vh values and also the highest T m values of those tested kinetically ( Table 1), suggesting that the I365L mutation in particular led to selective stabilization of at least one structural feature that also had a particularly strong stabilizing influence on the inactivation rate.
Analysis of Epistatic Interactions Between Mutations. Epistatic interactions between mutations were evaluated for kinetic deactivation (ΔΔG ‡ ) based on the activities retained after heat treatment at 60°C for 1 h, and also for changes in thermodynamic stabilities, ΔT m and ΔT agg . Fitness landscapes containing the two mutagenic pathways from WT to H192P/A282P (AB), and the six further mutagenic pathways that formed the quadruple-mutant H192P/A282P/I365L/G506A (ABCD), were constructed for all three properties. All pathways were favorable in all three properties, with no local minima due to sign epistasis or reciprocal sign epistasis (SI Appendix, Fig. S4). The epistatic interactions between mutations were quantified using Eq. 6 to determine any positive, negative (partially additive), sign, or reciprocal sign epistasis, as shown for ΔΔG ‡ , ΔT m , and ΔT agg in Fig. 3 A-C, respectively. H192P (A) and A282P (B) were located on the surface of the PPdomain (2-322 aa) but were 33 Å apart (SI Appendix, Fig. S5). Despite this long distance, they showed a strong negative epistasis for ΔΔG ‡ , a moderately positive epistasis for ΔT m , and an additive effect for ΔT agg . The two single variants, I365L (C) and G506A (D), were located in the Pyr domain (323-539 aa). The ΔΔG ‡ of the double mutant, CD (4.88 kJ·mol −1 ), was higher than the 4.09 kJ·mol −1 expected from additivity between I365L (C) and G506A (D), indicating a moderately positive epistasis (Fig. 3A). The combination of the PP-domain mutations in H192P/A282P (AB), with core mutant (C) to form variant ABC, gave an observed ΔΔG ‡ of 7.21 kJ·mol −1 , with 8.97 kJ·mol −1 expected from additive effects, indicating negative epistasis between AB and C. Variant ABD gave the ΔΔG ‡ expected from the additive effects of G506A (D) and H192P/A282P (AB). The final variant ABCD was formed via three combinations, ABC+D, CD+AB, and ABD+C. The observed ΔΔG ‡ for ABCD was 9.30 kJ·mol −1 , which was as expected for ABC+D (9.01 ± 0.3 kJ·mol −1 ), but lower than the expected values for CD+AB (11.34 kJ·mol −1 ) and ABD+C (10.19 kJ·mol −1 ), consistent with the negative epistasis found above for AB+C (Fig. 3A).
Improvements in T m and T agg upon combination of I365L (C) and G506A (D) were both negatively epistatic, in contrast to the moderately positive epistasis observed for ΔΔG ‡ in Fig. 3A. The different types of epistasis observed for kinetic (ΔΔG ‡ ) and thermodynamic (T m and T agg ) stabilities of C+D fits with the observation that kinetic and thermodynamic stabilities were correlated, but that global unfolding was not the only factor to influence kinetic inactivation. I365L and G506A were only 12 Å apart within the same hydrophobic core of the Pyr domain (SI Appendix, Fig. S5) and packed onto opposite faces of the indole ring of W503 (SI Appendix, Fig. S6). This indirect structural interaction could readily mediate their negative epistasis in ΔT m and ΔT agg , and also their positive epistasis in ΔΔG ‡ . The combination of D+AB showed additive effects for ΔT m and ΔT agg , consistent with ΔΔG ‡ (Fig. 3). This was expected given that the two mutations in H192P/ A282P (AB) were each located on the surface of the PP domain, and nearly 50 Å away from the single mutation G506A (D) in the hydrophobic core of the Pyr domain (SI Appendix, Fig. S5). The combination of C+AB showed additive effects for ΔT m and ΔT agg , again in contrast to ΔΔG ‡ , which was negatively epistatic.
The three possible final combination steps leading to ABCD showed distinctly different epistatic effects for ΔΔG ‡ , ΔT m , and ΔT agg. As described above, for ΔΔG ‡ , the combination of I365L (C) and H192P/A282P (AB) in any context (C+AB, CD+AB, C+ABD) was negatively epistatic. By contrast, for ΔT m , negative epistasis was observed, but now for the combination of I365L (C) with G506A (D) in any context (C+D, C+ABD, ABC+D). Finally, for ΔT agg , while C+D was negatively epistatic, and C+AB was additive, the combination of C and AB at the final step was positively epistatic, particularly for CD+AB. For the pathway to the quadruple mutant, ABCD, all epistatic effects involved I365L (C) and either AB or D, but never occurred specifically between AB and D. As discussed above, the I365L mutation, in the presence of H192P/A282P, also appeared to have a particularly strong stabilizing influence on the inactivation rate, and this contributed to the epistatic effect found between AB+C, AB+CD, and ABD+C. For example, the selective stabilization by I365L of an aggregationprone motif in the quadruple mutant (ABCD) could lead to the positive epistasis in T agg , while remaining additive for T m .
Cross-Correlations Between Dynamics of Local Regions Mediate
Epistatic Interactions. To understand how the mutations interacted to produce both short-and long-range epistasis, we investigated and compared the flexibilities of the WT, H192P, A282P, H192P/ A282P, I365L, H192P/A282P/G506A, H192P/A282P/I365L, and the quadruple mutant, H192P/A282P/I365L/G506A, using MD simulations at 370 K. Root-mean-square fluctuation (RMSF) values for each residue indicated a complex interdependence between the dynamics around each mutation, whereby mutations changed their local dynamics, but also sometimes altered the dynamics of certain other, often distant regions (Fig. 4). Previously for the WT TK at 370 K, the PP-binding domain and the C-terminal domain were found to be more flexible by RMSF than the Pyr-binding domain (42). Compared with WT, H192P/A282P had lower flexibility in the PP domain, indicating local stabilization by H192P and A282P mutations (Fig. 4), but increased flexibility in the Pyr domain where residue I365 was located. The introduction of I365L into H192P/A282P led to decreased flexibility around the I365L mutation as expected, but also decreased flexibility within the neighboring C-terminal domain, and conversely increased the flexibility around H192P and A282P. Assuming that increased flexibility at high temperature is correlated with low stability, then this complex interaction between the flexibility of each mutated region would explain the epistasis observed between even distant mutations, such as between I365L and H192P/A282P. Dynamics Cross-Correlations Were Consistent Across Variants. Networks of interactions have been hypothesized to underpin long-range epistasis between mutations, while protein dynamics are known to mediate long-range allostery (25,27,29,30). We therefore computed dynamics cross-correlation matrices (DCCMs) for the WT and variants. Pairwise cross-correlation coefficients (C ij ) indicate the extent to which the fluctuation of an atom is correlated (or anticorrelated) with one other atom, and dynamics cross-correlation maps show the correlation coefficients (C ij ) between all C α atom pairs. Most cross-correlations were between structural neighbors ( Fig. 5 and SI Appendix, Fig. S7), in agreement with the previous observation that cross-correlations decreased with distance (48). Cross-correlations were weak between atoms of the two different monomers, but strong cross-correlations were observed between certain regions within the same monomer. Therefore, we averaged the coefficients from the two chains and investigated the dynamics correlations within the same monomer (Fig. 5). The dynamics of most regions of structure were not correlated to any other region, as seen from significant areas of white space in the DCCM maps. Therefore, any pairwise correlations between distant regions represented an unusual coupling. The locations for correlated dynamics were largely consistent between the WT and variants, such that the mutations did not usually create or remove correlations, although some variants had more anticorrelated zones than the WT (Fig. 5). This indicated that while the mutations modified the RMSF in local and correlated regions, they did not cause any significant disruption to structure or in the networks of interactions linking the mutated regions. Pairs of regions with significantly correlated dynamics included between 325-375 and 480-530 aa, between 100-230 and 360-425 aa, and between 0-100 and 240-320 aa. A strong anticorrelation (indicating correlated movement but in opposite directions) was also found between 270-300 and 190-210 aa. Apart from at 0-100 aa, these regions coincided with the four mutation sites, and so the cross-correlated dynamics linked several pairs of mutations (Fig. 6). Specifically, correlation between 325-375 and 480-530 aa linked I365L and G506A, while that between 100-230 and 360-425 aa linked H192P and I365L. The anticorrelation between 270-300 and 190-210 aa linked H192P and A282P. These observations suggest that, while each mutation could modify the local dynamics (RMSF), they could also then alter the dynamics of those regions that were correlated with it. As a result, this would alter the stabilizing impact of a second mutation within that correlated region, if its dynamics were already changed by the presence of the first mutation. This is the basis by which the correlated dynamics between two regions could mediate epistatic interactions between mutations designed to decrease their local flexibilities based upon the WT structure.
The mutations tended to cause significant changes in RMSF (ΔRMSF) only within regions that were strongly correlated to the mutation site via dynamics. A plot of C ij against the ΔRMSF in all residues resulting from each mutation showed that (i) most residues do not have dynamics that are strongly correlated with the mutation sites, (ii) significant ΔRMSF (>0.2 or less than −0.2) mostly occurs in regions with a strong dynamics correlation coefficient (>0.2) with the mutation site, and (iii) the absolute strength and direction of ΔRMSF were not predictable from the pairwise correlation coefficients for the dynamics (SI Appendix, Fig. S8). This demonstrates that the correlated dynamics between two regions manifest via specific networks of interactions that induce changes in RMSF within the paired second region, upon mutation within the first region. The link between dynamics correlation and epistasis for several pairs of mutations is described in detail below. By way of example, we examined the impact of each mutation on the local RMSF at only the four mutation sites. This articulates how coupled changes in local RMSF can mediate epistasis between the mutations. Although changes in flexibility in these local regions are expected to contribute to changes in ΔT m , ΔT agg , and ΔΔG ‡ , these stability parameters would also depend on the RMSF from other regions of the protein, in a complex manner. Also, the underlying epistasis on local RMSF may manifest in different ways for ΔT m , ΔT agg , and ΔΔG ‡ . Therefore, we did not attempt to determine any precise relationship between these and RMSF.
Dynamics Correlation Between H192P (A) and A282P (B). The dynamics around H192P were strongly anticorrelated with those around A282P in the WT (Fig. 5). Anticorrelation simply means that atomic motions are correlated such that they move in phase, but in opposite directions (47). The relationship between dynamics correlation and epistasis for the local RMSF at the four mutation sites is outlined schematically in Fig. 6A, for the interaction between H192P and A282P. The observed anticorrelation between the local regions around His192 and Ala282 is consistent with the observation that the H192P mutation decreased its local flexibility as anticipated and yet also increased that around A282P, even though it was 33 Å away ( Fig. 4 and SI Appendix, Fig. S5). By contrast, the A282P mutation decreased its local flexibility and yet also increased that around H192P (Fig. 4). Clearly, this would alter the ability of the H192P or A282P to impart the same stabilizing effects locally within WT, A282P, or H192P, and explains the negative epistasis on ΔΔG ‡ between H192P and A282P. In both H192P and A282P, the RMSF increased around Ile365 and decreased around Gly506 (Fig. 4), even though the dynamics of His192 were correlated only to those of Ala282 and Ile365, but not to those around Gly506 (Fig. 5). When H192P/A282P was generated from WT, the regions around both Ile365 and Gly506 showed increased flexibility (Fig. 4). As depicted in Fig. 6, the correlations formed a linear network from Ala282 to His192, then on to I365, and finally to G506. Ile365 therefore connected H192P to Gly506 indirectly, consistent with its position in the monomer structure between these two sites. For the total aggregated impact in the four local regions around the mutations (Fig. 6A), there was a negative epistasis between H192P and A282P on ΔRMSF.
Dynamics Correlation Between I365L (C) and G506A (D). A strong cross-correlation was found between the regions containing Ile365 and Gly506, with a correlation coefficient higher than 0.3 for the WT and all variants (Fig. 5). They are located 12 Å apart in the structure on opposite edges of the indole ring of residue W503 (SI Appendix, Figs. S5 and S6). This short network of interactions would readily mediate the correlated dynamics and the epistasis observed between I365L and G506A for all measures of stability, except the T m within H192P/A282P. The relationship between dynamics correlation and epistasis for local RMSF is outlined schematically in Fig. 6B for the interaction between I365L and G506A within H192P/A282P by way of example. The G506A mutation was locally stabilizing in H192P/ A282P, with decreased RMSF in the local region. This led to stabilization at Ile365, then destabilization of H192P and A282P, through the chain of pairwise correlated dynamics between Gly506 and Ile365, Ile365 and H192P, and finally H192P and A282P. Thus, G506A led to a net increase in the RMSF (approximately +0.3 on a normalized scale) aggregated over the four mutation sites (Fig. 6B). When the I365L mutation was introduced into H192P/A282P, the RMSF around I365L decreased (Figs. 4 and 6B). Correlated dynamics between Ile365 and Gly506 resulted in decreased RMSF around Gly506. Simultaneously, the correlated dynamics between Ile365 and His192 increased the RMSF around H192P, which in turn increased the RMSF at A282P through their anticorrelation. Overall, I365L led to a net increase in the RMSF of approximately +0.1 across the four mutation sites. Both of the single mutations above decreased their own local RMSF but also altered that of other regions coupled by their dynamics. This changes the local baseline RMSF into which the second mutation is made, and therefore leads to epistasis. For example, when G506A was introduced into H192P/A282P/I365L, Gly506 had already been partially stabilized by I365L through their correlated dynamics, and so G506A had only a small impact on the magnitude of the local RMSF. However, the chain of correlated dynamics resulted in increased RMSF at I365L, and decreased RMSF at H192P/ A282P, as a result of the G506A mutation. The total ΔRMSF across only the four sites was approximately −0.1, which therefore revealed reciprocal sign epistasis between G506A and I365L. For comparison, these mutations exhibited additivity for ΔT m , negative epistasis for ΔΔG, and positive epistasis for ΔT agg . This reemphasizes that the type of epistasis observed for different properties from a given mutational pair are not necessarily the same.
Ile365 is located 25 and 46 Å from His192 and Ala282, respectively (SI Appendix, Fig. S5). In this case, only the coupling of dynamics through a long network of interactions could be expected to cause the observed negative epistasis for ΔΔG and ΔT m , and positive epistasis for ΔT agg , between I365L and H192P/ A282P. The relationship between dynamics correlation and epistasis for local RMSF is outlined schematically in Fig. 6C for the interaction between I365L and H192P/A282P. As above, H192P/A282P were locally stabilizing but led to increased RMSF at both Ile365 and Gly506 (Fig. 4), via the network of correlated dynamics that linked His192 to Ile365, and Ile365 to Gly506 (Fig. 6C). Overall, H192P/A282P gave no net change in the local RMSF across the four mutation sites. The I365L mutation decreased the local RMSF when introduced into WT, which then led to stabilization at Gly506, and destabilization around His192 and A282, through their respective pairwise correlated dynamics to I365L. Thus, I365L also gave no net change in local RMSF across the four mutation sites. By contrast, the introduction of H192P/A282P into I365L decreased the RMSF around H192P but induced an RMSF increase around I365L and then Gly506 due to their correlated dynamics, giving a net RMSF increase of approximately +0.2 across the four mutation sites. Therefore, the interaction between H192P/ A282P and I365L resulted in positive epistasis for the local ΔRMSF, as a result of coupling between the dynamics of the four local regions. Specifically, the destabilization of H192 and A282 by the distant I365L mutation could no longer be fully rescued by the H192P and A282P mutations, compared with the degree of stabilization that they achieved within WT.
Insights for the H192P/A282P/I365L/G506A Variant. A positive epistatic behavior in T agg was found between I365L/G506A and H192P/A282P. In contrast to all other variants, the T agg of the quadruple mutant, H192P/A282P/I365L/G506A, was higher than its T m , implying that more unfolding could occur before aggregation was observed. This indicated the selective stabilization of a region of structure required to unfold before aggregation. The MD simulations at high temperature indicated that a remote fragment D81-K96 was rigidified in the quadruple mutant (SI Appendix, Fig. S9). The DCCM analysis revealed a strong correlation between this fragment and the region around the A282P mutation, which provided a long-range mechanism through which the mutation could have stabilized the fragment (Fig. 5). This fragment was close to an aggregation hot spot, predicted by three different algorithms (SI Appendix, Fig. S9). Stabilization of this region could therefore decrease the propensity of H192P/A282P/I365L/G506A to aggregate, and explain the unusually high T agg .
Concluding Remarks. In this work, we explored the epistatic interaction between the mutations H192P and A282P, located on the surface of the PP domain, and then between the doublemutant H192P/A282P and two single mutations, I365L and G506A, located distantly in the core region of the Pyr domain. Surprisingly, not all pairwise effects between distant mutations from the surface and core regions of different domains were additive. This study has identified and characterized MD that mediated long-range epistatic interactions between mutations for various measures of protein stability. We found that the protein dynamics between the four mutations sites were correlated via a network of interactions that then mediated the observed long-range epistasis. These effects have the potential to be exploited for developing improved protein-engineering strategies. For example, the strategy of rigidifying flexible sites has been proven to be a powerful method to improve the stability of enzymes. When combining mutations that independently improve protein stability, an absence of epistatic interactions might be preferred as this would lead to predictable increases in performance. As mutations with correlated dynamics could potentially interact with each other, protein-engineering strategies could consider combining only those mutations in regions that have no cross-correlated dynamics to maximize the likelihood of additive improvements. Alternatively, experimental and computational protein-engineering approaches may also benefit from deliberately identifying cross-correlated sites. Targeting mutagenic libraries to two or more of these sites simultaneously has the potential to exploit positive epistasis and to rapidly evolve stability via a small number of residues that form a critical network.
Methods
Site-Directed Mutagenesis, Overexpression, and Purification of Enzymes. Primers were designed using the web-based QuikChange Primer Design Program (https://www.agilent.com/genomics/qcpd). Site-directed mutagenesis of tktA within plasmid pQR791 (46), overexpression, and purification of enzymes were carried out as in ref. 42. Protein concentration was measured using the Bradford method (49) and OD 280 measurements, independently.
Temperature Inactivation of Holo-TK. Thermal inactivation was measured as in ref. 42. T 50 15 , the temperature required to reduce the initial enzyme activity by 50% within 15 min, was measured by placing 100 μL of enzymes at various temperatures, from 22 to 65°C, for 15 min. T 50 15 was determined from the inflection point of residual activities vs. temperature using a sigmoidal Boltzmann fit in OriginPro 9.0 (50). The half-life of enzyme activity was measured by placing 100 μL of enzymes at 60°C. Samples were removed at different times and then cooled to 22°C. Second-order thermal deactivation was fitted to Eq. 1, where A (t) is the activity at time t of the heat treatment, A 0 is the initial activity before heat treatment, and k is the inactivation rate constant. Half-life (t 1/2 ) at 60°C was calculated as t 1/2 = 1/(100*k d ). Retained activity (RA) after time t of heating was calculated as A (t) /A (0) : Enzyme Kinetics. Kinetic parameters were obtained at saturating 50 mM Li-HPA and 4-80 mM glycolaldehyde as in ref. 42.
Thermal Transition Midpoint (T m ) and Aggregation Onset Temperature (T agg ).
Intrinsic protein fluorescence (266-nm excitation, 280-to 450-nm emission scan) and static light scattering (SLS) at 266 and 473 nm, were measured simultaneously with a UNit (Unchained Laboratories) at every 1°C for 30-90°C after 30-s equilibration at each temperature. Microcuvettes were loaded with 9 μL of 0.1 mg/mL samples in triplicate. T agg was determined from SLS counts at 266 nm using the instrument software. Fluorescence intensity ratio at 350 nm: 330 nm vs. temperature was fitted to a two-state transition model using Eq. 2 (51,52) in OriginPro 9.0 (Origin Lab Corporation): where I T is the observed signal; I N and I D , the native and denatured baseline intercepts; a and b, the native and denatured baseline slopes; T, the temperature; ΔH vh , the van't Hoff enthalpy; R, the gas constant (1.987 cal·mol −1 ·K −1 ); and T m , the thermal transition midpoint. The van't Hoff entropy was calculated using Eq. 3, and the mole-fraction, f T , of unfolded protein at any temperature T was calculated from Eq. 4: Analysis of Epistatic Interactions Between Mutations. Epistasis was quantified using Eq. 5 (53), where ΔΔG(X), ΔΔG(Y), and ΔΔG(X,Y) are changes in free energy relative to WT for single mutations X and Y, and double mutant XY, respectively. ΔG I is the coupling energy for interaction between X and Y: ΔΔG ðX,YÞ = ΔΔG ðXÞ + ΔΔG ðYÞ + ΔG I . [5] The change in free energy of inactivation relative to WT was calculated from Eq. 6, where RA variant and RA WT are the activities retained for the variant and WT after the same heat treatment, and A 0 = 100%: Epistatic interactions between mutations X and Y were quantified for T m and T agg using Eq. 7, and ΔT (X) , ΔT (Y) , and ΔT (X, Y) for single mutants X and Y, and double mutant, respectively. ΔT I is the epistatic interaction between X and Y: ΔT ðX, YÞ = ΔT ðXÞ + ΔT ðYÞ+ ΔT I . [7] MD Simulations. MD simulations of WT TK (Protein Data Bank ID code 1QGD) and variants constructed with the Pymol Mutagenesis Wizard (Schrödinger) were carried out in triplicate at 370 K using Gromacs, version 5.0, exactly as in ref. 42. RMSFs were calculated using the last 10-ns trajectory for analysis of local flexibility.
Dynamics Cross-Correlation Map. DCCMs were computed using Bio3D (54,55). The last-10 ns trajectory from MD simulation was saved at every 10 ps and converted to a dcd file type with the VMD plugin CatDCD (56), input to Bio3D, and the C α atoms selected for calculating the correlation coefficients. Dynamics correlation matrices were averaged from triplicate trajectories and visualized using OriginPro9.0. | 9,602.6 | 2018-11-07T00:00:00.000 | [
"Biology"
] |
Essential Quantum Einstein Gravity
The non-perturbative renormalisation of quantum gravity is investigated allowing for the metric to be reparameterised along the RG flow, such that only the essential couplings constants are renormalised. This allows us to identify a universality class of quantum gravity which is guaranteed to be unitary, since the physical degrees of freedom are those of general relativity without matter and with a vanishing cosmological constant. Considering all diffeomorphism invariant operators with up to four derivatives, only Newton's constant is essential at the Gaussian infrared fixed point associated to the linearised Einstein--Hilbert action. The other inessential couplings can then be fixed to the values they take at the Gaussian fixed point along the RG flow within this universality class. In the ultraviolet, the corresponding beta function for Newton's constant vanishes at the interacting Reuter fixed point. The properties of the Reuter fixed point are stable between the Einstein--Hilbert approximation and the approximation including all diffeomorphism invariant four derivative terms in the flow equation. Our results suggest that Newton's constant is the only relevant essential coupling at the Reuter fixed point. Therefore, we conjecture that quantum Einstein gravity, the ultraviolet completion of Einstein's theory of general relativity in the asymptotic safety scenario, has no free parameters in the absence of matter and in particular predicts a vanishing cosmological constant.
The non-perturbative renormalisation of quantum gravity is investigated allowing for the metric to be reparameterised along the RG flow, such that only the essential couplings constants are renormalised. This allows us to identify a universality class of quantum gravity which is guaranteed to be unitary, since the physical degrees of freedom are those of general relativity without matter and with a vanishing cosmological constant. Considering all diffeomorphism invariant operators with up to four derivatives, only Newton's constant is essential at the Gaussian infrared fixed point associated to the linearised Einstein-Hilbert action. The other inessential couplings can then be fixed to the values they take at the Gaussian fixed point along the RG flow within this universality class. In the ultraviolet, the corresponding beta function for Newton's constant vanishes at the interacting Reuter fixed point. The properties of the Reuter fixed point are stable between the Einstein-Hilbert approximation and the approximation including all diffeomorphism invariant four derivative terms in the flow equation. Our results suggest that Newton's constant is the only relevant essential coupling at the Reuter fixed point. Therefore, we conjecture that quantum Einstein gravity, the ultraviolet completion of Einstein's theory of general relativity in the asymptotic safety scenario, has no free parameters in the absence of matter and in particular predicts a vanishing cosmological constant.
I. INTRODUCTION
Wilson's exact renormalisation group (RG) [1] provides a framework to construct a consistent quantum field theory (QFT) that describes gravity. This possibility, known as asymptotic safety, relies on the gravitational couplings exhibiting an ultraviolet (UV) fixed point that allows the UV cut-off to be removed while keeping physical quantities finite [2]. The theory can then be defined as a perturbation of the fixed point along a renormalisable trajectory that leaves the UV fixed point and evolves towards the infrared (IR), where it is identified with the renormalised theory. In this framework [3,4], the number of free dimensionless parameters is one fewer than the number of relevant couplings at the fixed point, which parameterise the UV critical surface formed from all renormalisable trajectories.
So far, the evidence suggests that there is such a fixed point, known as the Reuter fixed point [5][6][7][8][9], and that it possesses three relevant couplings in pure gravity [10][11][12][13][14][15][16][17][18][19][20][21]. However, not all couplings need to reach a fixed point for the theory to be asymptotically safe, since one has the freedom to perform field reparameterisations which can be used to eliminate the so-called inessential couplings from the RG equations [2]. The inessential couplings do not appear in expressions for observables, such as cross sections and reaction rates, and, therefore, can take different values without affecting the physics. Couplings, therefore, fall into two classes: the essential couplings λ a which enter into expressions for observables and the inessential couplings ζ α which are scheme dependent and unphysical. Consequently, the scaling behaviour of inessential couplings is entirely scheme dependent and they must not be included in the set of relevant couplings [22]. It follows that a coupling that may appear relevant could turn out to be inessential and, therefore, does not contribute to the counting of free parameters. Although the potential existence of inessential couplings has been pointed out [3,4,[23][24][25], they have been almost universally ignored in investigations of asymptotic safety. In particular, attempts to find a suitable fixed point have required fixed points for all gravitational couplings, included in a given approximation, instead of incorporating field reparameterisations into the RG equations and checking which of the couplings are inessential. Here we shall remedy this oversight by incorporating field reparameterisations in the gravitational RG equations which allow us to eliminate the inessential couplings from the flow equations. To do so we will utilise the essential RG approach, which has been put forward in [26], where we only compute the flow of the essential couplings.
Our strategy will be to adapt the minimal essential scheme devised in [26], in the context of scalar field theories, to remove all inessential couplings in pure gravity. This can be carried out order by order in the derivative expansion, where only terms with up to s-derivatives of the fields are included in the effective action. At each order s the minimal essential scheme is implemented by identifying the inessential couplings at a Gaussian fixed point of the theory and fixing their values, such that one obtains beta functions for the essential couplings only. An important point is that this scheme involves a specification of the kinematical degrees of freedom, since it assumes that the degrees of freedom are those of the Gaussian fixed point. This implies that the minimal essential scheme can break down a finite distance from the Gaussian fixed point and, thus, cannot describe all possible non-perturbative behaviour. However, one can then instead identify inessential couplings at other points in theory space, which, while technically more involved, would allow the essential RG to describe all regions of theory space.
For a scalar field there are Gaussian fixed points associated to kinetic operators (−∂ 2 ) s 2 for every even integer s, which involve different degrees of freedom. As such, there is a minimal essential scheme associated to each Gaussian fixed point, that is physically distinct since they are associated with different degrees of freedom. Within a given minimal essential scheme, the RG flow is then constrained to the physical theory space associated to those degrees of freedom. In other words, the minimal essential scheme restricts the RG flow to a universality class that contains the corresponding Gaussian fixed point. Although, typically, RG studies are concerned with the universality class involving the Gaussian fixed point for which s = 2, one can also study universality classes associated to higher derivative theories [27,28]. When one utilises the minimal essential scheme for s = 2, the Gaussian fixed points for higher derivative theories are excluded. Therefore, this choice is not without physical consequences since by adopting a minimal essential scheme we focus our attention on possible fixed points in a specific universality class rather than attempting to find all possible fixed points.
For quantum gravity, we will consider the universality class of quantum Einstein gravity (QEG) meaning that it is associated to the quantisation of the physical degrees of freedom associated to Einstein's theory of gravity. As such, in this paper by the Gaussian fixed point (GFP) in the context of gravity we refer to the one associated to the linearised Einstein-Hilbert action unless otherwise stated. Here we should point out that we mean something more specific (but perhaps more deserving of the name) by QEG than the more broad definition given, e.g., in [29]. In particular, we do not only specify the fields and symmetries, in terms of which we parameterise the theory, but also the physical degrees of freedom. For example, a quantisation of higher derivative gravity [30] can be carried out by quantising the metric assuming diffeomorphism invariance, but it is a quantisation of more degrees of freedom than Einstein's theory. This shift of emphasis to the physical degrees of freedom and the physical essential couplings will bring our investigation of asymptotic safety closer to the original formulation [2] by S. Weinberg: a move which has been strongly encouraged recently [31].
To set the stage, in the Section II we give a short review of the essential RG technique, which generalises the usual approach to the exact (aka the non-perturbative functional) RG (see [32][33][34][35][36][37][38] for reviews) for the effective average action (EAA) by allowing for field to be reparameterised along the RG flow. In Section III we revisit S. Weinberg's formulation of asymptotic safety which emphasises the manner in which essential couplings enter expressions for observables. In Section IV we derive the generalised flow equation for quantum gravity that takes into account the freedom to reparameterise the quantum metric along the RG flow. Indeed, the flow equation will contain a new ingredient: the RG kernel. This quantity encodes the description about how the fields are reparameterised along the flow. Then, we write down a systematic derivative expansion of the diffeomorphism invariant part of the EAA and the covariant RG kernel. In particular, we expand the EAA to fourth order in derivatives and the RG kernel to second order. In Section V, we analyse the GFP properties: in particular, from this analysis we determine that the vacuum energy is inessential. The advantage of studying the GFP consists of the fact that it is a free fixed point and the results can be obtained without relying on approximations. After having found the inessential couplings at the GFP, in Section VI we discuss the properties of the universality class that contains the GFP and all the trajectories that have the same essential couplings. In such a subspace of the theory space, the propagator evaluated on conformally flat spacetime possesses the same form as the one at the GFP. Up to order four in the derivative expansion (apart from the topological Gauss-Bonnet term) only Newton's constant is essential in this universality class. In particular, any fixed point on these trajectories has the degrees of freedom of the GFP. In Section VII, we study the RG flow of QEG in the minimal essential scheme at orders two and four of the derivative expansion. Our investigation confirms the existence of the Reuter fixed point: this implies that higher derivative terms coming from the operators √ det g R 2 and √ det g R µν R µν are inessential in the universality class of the GFP. Moreover, this means that, contrary to the expectations based on perturbative renormalisability, the existence of the Reuter fixed point in the minimal essential scheme suggests that a possible UV-completion of the gravitational theory does not require additional degrees of freedom. In Section VIII we draw our conclusions and discuss the outlook for future investigations of quantum gravity using the essential RG. The derivation of RG equations in the minimal essential scheme for QEG at fourth order in the derivative expansion for a generic dimension and a generic regulator cut-off are presented in Appendix A 1.
II. ESSENTIALS OF THE ESSENTIAL RENORMALISATION GROUP
In this section we review the essential RG approach [26] using the case of a single scalar field to avoid overloading notation and technicalities. The generalisation for gravity will be developed in the rest of the paper starting in Section IV.
Ultimately in QFT we are interested in expectation values of observables which implements the coarse-graining procedure, cutting off low momentum modes in the functional integral (2.3) that defines the EAA. This is achieved by choosing the dimensionless function R(p 2 k 2 ) such that it vanishes in the limit p 2 k 2 → ∞, while for p 2 k 2 → 0 it has a non-zero limit R(0) > 0, ensuring the suppression of IR modes. This realises Wilson's picture of the RG which integrates out UV modes successively as k is lowered. The second source of k dependence comes from the liberty to perform field reparameterisations along the flow parameterised by a k-dependent diffeomorphismφ k [χ] of configuration space which we integrate over in (2.1). This is achieved by considering a generating functional for correlation functions of the k-dependent fieldsφ k [χ] rather than the k-independent fieldsχ. Explicitly this functional is the generalised EAA action Γ k [φ] defined by the functional integro-differential equation from which it follows that is the φ and k dependent expectation value. In the limit k → 0 the cut-off vanishes and EAA reduces to the one-part irreducible effective action Γ[φ] = Γ 0 [φ] for the fieldφ 0 . In the opposing limit k → ∞ the EAA reduces to the bare action written in terms of the fieldsφ ∞ . Let us note that we could additionally make a change of integration variables in the RHS of (2.3) which keeps Γ k [φ] invariant provided we make this change everywhere including in the measure. Here we are keeping the integration variablesχ and the bare action S[χ] k-independent, such that the k-dependence comes only from the regulator and the composite fieldsφ k [χ]. Since we are ultimately interested in computing observables (2.5) at vanishing regulator and on the equations of motion for Γ 0 [φ] we will recover (2.1) independently of the regulator and the parameterisationφ k [χ]. For more details we refer the reader to [26].
In general, Γ k [φ] will depend on all couplings compatible with the symmetries of the theory. Incorporating k-dependent field reparameterisations into the EAA formalism has first been considered in [39] to describe bound states. In the essential RG, the utility ofφ k [χ] is that we may choose to reparameterise the field to fix the values of inessential couplings which, by definition, are simply those couplings that depend on the form ofφ k [χ]. Since observables (2.1) are invariant under a change inφ k [χ], they do not depend on the inessential couplings. Any scheme which fixes or otherwise specifies the flow of all inessential couplings is an essential scheme. Thus, in an essential scheme we only compute the flow of essential couplings λ a (k), i.e., those which ultimately enter into observables (2.1).
The generalised flow equation satisfied by Γ k [φ] is given by [35] where t ∶= log(k k 0 ), with k 0 some physical reference scale, under the trace appearing in the RHS is the IR regularised propagator, with Γ (2) k [φ] denoting the hessian of the EAA with respect to the field φ(x), and is the RG kernel which takes into account the k-dependent field reparameterisations. The flow Equation (2.6) reduces to the standard flow for the EAA [40,41] when Ψ k = 0 and can be understood as the counterpart to the generalised flow for the Wilsonian effective action [22]. By choosing Ψ k [φ] we can specify the flow of inessential couplings ζ, which by their definition are those for which [26] for some quasi-local field Φ[φ]. Equation (2.9) follows from the definition of an inessential coupling and, therefore, allows them to be identified. The operator appearing on the RHS of (2.9) is the redundant operator conjugate to the inessential coupling ζ. The first term in the RHS of (2.9) is tree-level and is simply proportional to the equation of motion for Γ k [φ] and survives in the limit k → 0. The second term instead vanishes as when the regulator vanishes as k → 0. Within perturbation theory, in the vicinity of a Gaussian fixed point the second term will be sub-leading, since it is loop correction being proportional to Planck's constant ̵ h. In general, there will be an inessential coupling associated to every linearly independent quasi-local field Φ k [φ] which generates an independent field reparameterisation. Although the possible field reparameterisations Φ k [φ] are themselves independent of the position in theory space, it is important to stress that the redundant operator depends on the EAA Γ k [φ] and, thus, the identification of inessential couplings will depend on the form of the EAA. Thus, couplings which may be inessential at one fixed point can be essential at others. As an example at the GFP the coefficient of ζ of the kinetic term is inessential. This can be understood since on the equations of motion ∂ 2 φ = 0 the kinetic term vanishes. Changing the value of ζ corresponds to moving along a line of equivalent fixed points. However, if we consider the fourth order GFP the operator 1 2 ∫ d d x φ(−∂ 2 )φ is not redundant since it does not vanish on the equations of motion (∂ 2 ) 2 φ = 0 for (2.11). Here we also see the connection between inessential couplings and the number of degrees of freedom. For the fourth order theory we have two propagating degrees of freedom which are massless at the fixed point (2.11). By adding the term with two derivatives, the action becomes where m 2 is an essential coupling being identified as a mass for one of the degrees of freedom. Let us also note that at the GFP (2.10) the higher order term ∫ d d x φ(−∂ 2 ) 2 φ is redundant since it vanishes on the equations of motion ∂ 2 φ = 0. This reflects the fact that by starting with only one propagating degree of freedom we cannot gain more degrees of freedom along the RG flow.
Since the terms involving Ψ k [φ] in (2.6) have the form of a redundant operator, the liberty to choose Ψ k [φ] is precisely the liberty to specify the flow of all inessential couplings. Thus, for each inessential coupling we specify an RG condition, understood as a constraint on the form of Γ k [φ] along the RG flow, then we solve the flow equation under this condition for the beta functions of the essential couplings and gamma functions which parametrise Ψ k [φ]. Different essential schemes correspond to different sets of RG conditions for the inessential couplings. From a geometric point of view, we can think of reparameterisations as local frame transformations on configuration space that are analogous to gauge transformations [26,42]. RG conditions are, therefore, analogous to gauge fixing conditions which fix a particular frame, as with gauge conditions we typically want to find RG conditions that minimise the complexity of a given observable.
Since the form of the redundant operators (2.9) depend on Γ k [φ] in practice the simplest scheme to implement is the minimal essential scheme which sets all inessential couplings at the GFP (2.10) to zero (apart from the coefficient of the kinetic term which is canonically normalised). One can show that this is achieved by setting all terms in the Γ k [φ], which can be brought into the form ∫ d d x Φ ∂ 2 φ by an integration by parts, to zero. In other words, in the minimal essential scheme we put to zero any term in Γ k [φ] that vanishes when we apply the equations of motion at the GFP apart from the canonically normalised kinetic term (2.10) itself. Thus, while at order ∂ 2 in a derivative expansion, Γ k can assume the form in the minimal essential scheme, the EAA reduces to which involves only one function, namely the effective potential V k (φ). In order to solve the flow equation up to order ∂ 2 in the essential RG, the RG kernel must have the form Although typically we would have a non-linear dependence on z k (φ) in the flow equation coming from the propagator G k , in the minimal essential scheme this dependence is absent. Thus, by adopting the minimal essential scheme we trade a non-linear dependence on z k (φ) in the flow equation for a linear dependence of F k (φ). More generally, in the minimal essential scheme the G k [φ] evaluated at any constant value of the field φ(x) =φ has the form is the second derivative of the potential. The simplified form of the propagator (2.16), which continues to hold at any order of the derivative expansion, produces simplifications in practical calculations, and maintains a form that manifestly contains only physical degrees of freedom which are present at the GFP (2.10). This implies, for example, the absence of ghosts and tachyons, and it constraints our theory to stay in the subspace of the theory space where the degrees of freedom are the same of the GFP. As we will see, these features can also be guaranteed for the graviton propagator. What cannot be guaranteed is that there also exists other fixed points apart from the GFP in this subspace. Thus, by adopting the minimal essential scheme, we limit our search for additional fixed points by constraining the propagating degrees of freedom.
III. WEINBERG'S FORMULATION OF ASYMPTOTIC SAFETY
Having reviewed the essential RG, let us now discuss the criteria of asymptotic safety as formulated by Weinberg [2] and how it is realised by solving the flow equation for the EAA within an essential scheme. The criteria necessitate that we have a UV-complete QFT where there is no UV cut-off, which is achieved if the theory lies on an RG trajectory that originates from a UV fixed point. However, as has been emphasised recently [31], Weinberg's formulation is more precise since it is concentrated on the absence of unphysical UV divergences in physical quantities, such as reaction rates, rather than on the behaviour of correlation functions of fieldsφ. This is important since correlation functions depend on inessential couplings ζ α . In a scheme where we do not specify the values of inessential couplings but compute their flow, we are at the very least making our life harder unnecessarily. In the worst-case, an inessential coupling may not reach a fixed point and thus in such a scheme asymptotic safety could be obscured. In an essential scheme, we only compute the flow of the essential couplings and, thus, avoid these matters.
The divergences, which are absent in asymptotic safety, are those we expect to appear if we only have an effective theory that involves an artificial UV cut-off Λ UV , characterising our ignorance of physics on small distances < 1 Λ UV . An effective theory will break down as energies approach the cut-off scale and we will, therefore, encounter unphysical divergences. In an asymptotically safe theory, such divergences should be absent since we have sent Λ UV → ∞. Indeed, the form of the flow Equation (2.6) assumes that the limit Λ UV → ∞ has been taken and would take a modified form if an independent UV cut-off were introduced [41,43]. Asymptotic safety requires that as we take some characteristic energy scale E → ∞ observables (such as reaction rates) scale as where D is the dimension of O. This means in particular that dimensionless quantities will not diverge even when we take E → ∞ and, thus, at high energies the theory is scale invariant. Note that asymptotic safety is a rather generic requirement that we impose to be "reasonably sure" that there are no divergences in physical quantities related to the theory breaking down at a finite energy scale. On the one hand, asymptotic safety does not rule out all divergent behaviour, since unobservable correlation functions can diverge at finite energies even if the theory is well defined at all energies. On the other hand, asymptotic safety does not guarantee that a theory is physically acceptable since, for example, there can be asymptotically safe theories that are not unitary [44], the simple example being a free theory with four derivatives. If we were handed the full quantum effective action Γ and computed observables from it directly, the coupling constants entering the expression for an observable would be the essential couplings λ phys. a ≡ λ a (0) evaluated at k = 0. One may then wonder what the link is to a fixed point of the exact RG obtained in the opposing limit k → ∞. In particular one may worry that observables can depend on additional energy scales E n in addition to the scale E which we take to infinity. To understand the connection, note that if we supply an initial condition for the flow at a scale k = µ, the flow equation supplies a function since by integrating the flow for a given initial condition we will obtain λ a when we arrive to k = 0. Therefore, we can write any observable which depends on energy scales E and {E n } and the physical couplings λ phys.
a as a function where O(E, λ a (µ), µ, E n ) is independent of µ by construction meaning. On the other hand, dimensional analysis means that we can also write whereλ a (µ) = µ −da λ a (µ) are the dimensionless couplings and d a is the mass dimension of the coupling λ a . Generically, the functions for the dimensionless observablesÕ will be finite for finite values of its arguments, while if one argument were to diverge then generically we expectÕ to become singular. Now, since O is independent of µ, we can set µ = E, such that Then, it is clear that the limit E → ∞ only exists if the limit lim µ→∞λa (µ) exists. If a subset of the dimensionless essential couplingsλ a (E) diverges at some finite E = Λ UV , then we expect the observable to be singular at this point. However, if all the couplingsλ a (µ) remain finite for µ → ∞, such that they reach a UV fixed point lim µ→∞λa (µ) = λ ⋆ a , then which is exactly the requirement of asymptotic safety. An important point is that, since the RHS of (3.4) is independent of µ, if we would send E n to infinity instead of E we could then identify µ = E n and reach the conclusion that O ∼ E D n as E n → ∞. Crucially, it is only the essential couplings that need to attain a UV fixed point. Indeed, inessential couplings ζ α are simply not present in physical observables (3.3) and, therefore, their behaviour is not restricted a priori. All of these remarks apply to asymptotically safe theories in general, in the remainder of this paper we will develop the formalism to investigate asymptotic safety in quantum gravity within an essential scheme.
IV. GENERALISED FLOW EQUATION AND ESSENTIAL SCHEMES FOR QUANTUM GRAVITY
In this section, we will derive the generalised flow equation for quantum gravity from which we use to apply the essential RG method in order to investigate asymptotic safety. This construction generalises the formalism introduced in [5] by allowing for the field redefinitions at the heart of the essential RG. For quantum gravity the EAA is denoted Γ k [f ;ḡ], where f = {g µν , c µ ,c µ } denotes the set of mean fields, g µν is the (mean) metric, and c µ andc µ are the (mean) anti-commuting ghost and anti-ghost. In addition to the mean fields, Γ k [f ;ḡ] also depends on an auxiliary background metricḡ µν in order to conserve background covariance. The EAA for gravity is defined analogously to the case of the scalar field (2.3) through the functional integral whereχ are a set of fields which parameterise the fieldsf }, such that the latter defines a k-dependent diffeomorphism of the configuration space to itself. Formally, since the configuration space involves the ghost fields, it is a super-manifold. The background field dependence enters in two places. First, the action S[χ;ḡ] includes gauge fixing and ghost terms and secondly the cut-off R k [ḡ] depends on covariant derivatives and a tensor structure which are built from the background metric. Similarly to the case of the scalar field, it follows from (4.1) that where the expectation value of any functional of the fieldsÔ[χ] is defined by The generalised flow equation for Γ k [f ;ḡ] is given by where f = ⟨f ⟩ are the mean fields and G k [f,ḡ] denotes the propagator with ← δ signifying that the derivative acts to the left. The ⋅ implies a continuous matrix multiplication including sum over all field components and integration over spacetime. The STr denotes a supertrace in the same sense with a minus sign inserted for anti-commuting fields. For gravity the RG kernel now has component for each field Ψ k = {Ψ g µν , Ψ cµ , Ψc µ }, such that Ψ k = ⟨∂ tfk ⟩ f,k . By setting Ψ k = 0 we obtain the flow equation for gravity derived in [5], however in this case we would have to also compute the flow of inessential couplings. Using the background field method [45], one is ultimately interested in identifyingḡ µν = g µν and setting c µ = 0 =c ν . It is, therefore, convenient to write the action as is a diffeomorphism invariant action andΓ k [g, c,c;ḡ] contains terms which depend on the ghosts and the two metrics separately, including the ghost and gauge fixing terms. The diffeomorphism invariant action has the derivative expansion Here G k and ρ k are the running Newton's constant and vacuum energy, respectively, and a k , b k and c k multiply the O(∂ 4 ) terms with E = R µναβ R µναβ − 4R µν R µν + R 2 . It will also be useful to define the cosmological constant as since it is this combination that appears in the canonically normalised propagator. In four dimensions the integral ∫ d 4 x √ det gE is a topological invariant, so c k will not enter into any derivative ofΓ k [g] and, as such, c k does not appear in any beta function [21,46].
At a non-trivial fixed point required by asymptotic safety, the RG flow of dimensionless couplings in units of k will become independent of k. As such, it is convenient to define the dimensionless couplingsG where we will omit to make the t-dependence of the dimensionless couplings explicit in the following.
Here we shall use the commonly used background field approximation wherê Γ k [g, c,c;ḡ] is approximated by a BRST invariant action consisting of the background covariant gauge fixing and ghost terms. In particular, we shall takê where, to simplify calculations, we adopt background covariant harmonic gauge and κ k denotes the dimensionful coupling The ghosts operator is then given by (4.14) In the background field approximation, we will choose Ψ cµ = 0 = Ψc µ , while we choose the RG kernel for the metric to be given by where γ i with i = {g, R, Ricci} are the 'gamma functions' which, along with the beta functions, will be determined as functions of the couplings that appear inΓ k [g]. Each gamma function allows us to impose a renormalisation condition which fixes the flow of an inessential coupling. Thus, retaining three gamma functions allows us to impose three renormalisation conditions which are constraints on the form ofΓ k [g] that we impose along the RG flow. We note that γ g is dimensionless while γ R and γ Ricci have mass dimension −2, thus we define dimensionless gamma functionsγ R ∶= k 2 γ R andγ Ricci ∶= k 2 γ Ricci . As with the derivative expansion for a scalar field, if we work at order ∂ s in the derivative expansion, we include all terms of order ∂ s−2 in the RG kernel (4.15).
In our approximation the flow for the diffeomorphism invariant actionΓ k [g] is given by where ∆ gh and ∆ gf denote the differential operators and (4.20) We then choose the regulators to be of the form where ∆ = −g µν ∇ µ ∇ ν is the Laplacian. The redundant operators forΓ k [g] are given by where Φ g are symmetric covariant tensors composed of the metric, curvature tensors and their covariant derivatives, e.g., Φ g µν = g µν , Rg µν , R µν . The minimal essential scheme for quantum gravity, which we will further elaborate on in Sections V and VI, closely follows the perturbative scheme put forward in [47,48]. The scheme puts to zero any term that vanishes when the vacuum Einstein equations apply apart from the Einstein-Hilbert term itself. The reasoning is that the fixed point wherẽ G = 0 andΛ = 0 is the analog of the GFP for a scalar field theory. This means that can we set to zero both a k = 0 and b k = 0, while leaving c k non-zero since this term is topological in d = 4.
As with the GFP (2.10) in the scalar field theory the fact that any operator that vanishes on the equations of motion (4.23) can be removed by a field redefinition is a property of the fixed point whereG = 0 andΛ = 0. A higher derivative Gaussian fixed point, more analogous to the fourth order fixed point (2.11), is achieved by instead writing and sending λ → 0. At this fixed point the degrees of freedom are those of Stelle's higher derivative gravity rather than Einstein gravity. Furthermore, since the equations of motion for higher derivative gravity do not imply (4.23) the couplings a k and b k (or equivalently λ and ω) are essential at the higher derivative Gaussian fixed point.
Here we concentrate on Einstein gravity where a k and b k are inessential in the vicinity of the GFP whereG = 0 andΛ = 0. Thus, after setting a k = 0 and b k = 0 and neglecting all terms with more than four derivatives inΓ k , while retaining γ g , γ R , and γ Ricci we expand the Equation (4.4) to order ∂ 4 to obtain five flow equations from the independent tensor structures present in (4.8) using off-diagonal heat kernel techniques [49]. The evaluation of the traces and the resulting flow equations are presented in appendix A 1. The equations are presented for arbitrary cut-off function R k (∆) and in arbitrary dimension d neglecting terms proportional c k in the traces: this is justified in d = 4 since in this case the corresponding invariant is topological. For the remainder of the paper we will take d = 4. For explicit calculations, we will use the Litim cut-off function where Θ(x) is the Heaviside theta function.
V. THE VACUUM ENERGY IS INESSENTIAL
Having set a k and b k to zero, we can solve the equations for γ R and γ Ricci , given in (A22) and (A23). What is less clear is which renormalisation condition we should apply to freeze the inessential coupling associated to γ g , that must be some combination of G k and ρ k . As has been pointed out in [23], to find a non-trivial fixed point in gravity must actually requireG to have a fixed point. Indeed, by rescaling the metric, or, in other words, choosing a system of units, one cannot set G k = 1 and k = 1 simultaneously. This is still the case even with γ g present since one does not find a non-trivial fixed point forΛ if we try to fix the condition that G k = G 0 . The reason is that the beta function forΛ still depends on k 2 G 0 which diverges as k → ∞. However, one still has the freedom to apply one RG condition afforded by the presence of γ g . What is evident is that the dimensionless inessential coupling will still need a fixed point value. Thus, we should instead fix a dimensionless coupling to one value along the RG flow. However, one finds that doing so can prevent the GFP from being present itself. For example if we setG = 1 orΛ = 1, the GFP, which in dimensionless variables is atG = 0 andΛ = 0, cannot be attained. This is a consequence of the fact that with a specific renormalisation condition we cannot explore all universality classes contained in the theory space. In particular, since we will consider trajectories inside the subspace of theory space which contains the GFP, we will take into account the values ofG andΛ at the GFP. Therefore, to determine which dimensionless coupling we should fix, we analyse the GFP to understand which particular combinationG andΛ is inessential. However, we should understand this limit as the approach to a free theory on flat spacetime whereΓ k [g] reduces to the linearised Einstein-Hilbert action. To see this limit properly we have to decompose the metric as 1 where g µν is a flat metric. We callφ µν the graviton field since it is a fluctuation around a flat metric g µν , allowing one to define asymptotic states as free gravitons. In the parameterisation (5.1), it becomes clear that κ k is the coupling constant that measures the strength of self interactions of the graviton. The GFP corresponds to the theory where κ k = 0. As we shall show later γ R and γ Ricci are both proportional to κ 2 k . Taking a derivative of (5.1) with respect to t, we obtain where η N ∶= ∂ t log G k . The factor of κ k ensures that the fieldφ µν is canonically normalised. The expectation value of ∂ tφµν is, therefore, given by where φ µν = ⟨φ µν ⟩, and inserting the expression for Ψ g we obtain are the anomalous dimension of the graviton field and the gamma function related to a shift of the graviton field by a constant. Imposing that γ shift is finite when κ k = 0, we deduce that γ g = 0 at the GFP. Defining the flow Equation (4.4) can be rewritten as where the canonically normalised regularised propagator is (5.8) Inserting g µν = g µν + κ k φ µν intoΓ k [g] and then expanding in κ k , we find that at the GFP the EAA has the formΓ where we anticipate that for κ k = 0 the vacuum energy is ρ k = k 4ρ GFP andρ GFP denotes the dimensionless fixed point value for the vacuum energy, which we will determine shorty. Inserting (5.9) into the LHS of (5.7) we obtain while on the RHS we have, using that γ g = 0, which is independent of φ µν and, as such, we find that η φ = 0 at the GFP which together with γ g = 0 implies η N = 0. We then see that the GFP value of the dimensionless vacuum energy is Using the Litim cut-off we obtain the valueρ We conclude that the GFP is characterised uniquely byG = 0, η N = 0, γ g = 0 and a scheme dependent value for the dimensionless vacuum energyρ =ρ GFP . The fact that η N = 0 means that we arrive at the GFP in dimensionless variables when G k → G 0 is a constant, such thatG vanishes asG ∼ k 2 G 0 in the limit k → 0. Thus the GFP is an IR fixed point forG. Two remarks are in order concerning the vacuum energy. First, let us note that we could also choose a more general cut-off scheme allowing for different cut-off functions for the ghosts and gravitons in such a manner thatρ GFP would vanish [50]. At the exact level no physics should depend on the choice of cut-off so the value ofρ GFP should be of no significance. Secondly, we note that it may seem we could satisfy the flow with ρ k = k 4ρ GFP + ρ 0 allowing for a non zero cosmological constant, since ρ 0 is a constant of integration that will not appear in (5.10). However, only with ρ 0 = 0 do we have a fixed point. Now, away from the GFP, γ g needs not be equal to zero, so we can now write the linearised ansatz for γ g around the GFP as where w 1 and w 2 are free parameters which we are free to choose and the dots are non-linear terms in the expansion around the GFP. Expanding the beta functions forG andρ we obtain and, thus, we see that the linearised flow ofG around the GFP is scheme independent, while the linearised flow ofρ is scheme dependent. Since scheme dependence is the hallmark of an inessential coupling, we can conclude that Newton's couplingG is an essential coupling in the vicinity of the GFP, whileρ is inessential. We are free to specify the flow forρ instead of computing it and we can freely choose the corresponding scaling dimension rather than assuming it should have dimension 4. In fact, we can even make the vacuum energy, which canonically is the most relevant coupling, an irrelevant coupling simply by choosing w 1 > 12π. Let us stress that these are exact statements since we are at the GFP and terms at order ∂ 6 arise at two loops. A remarkable consequence of the vacuum energy being inessential is that we may simply choose that ρ k=0 = 0 and, thus, the vanishing of the vacuum energy is achieved by a renormalisation condition. Thus, at least in pure gravity, there is no fine tuning problem related to the cosmological constant once we apply this condition. However, this condition dictates the vanishing of the cosmological constant and by imposing it we are restricting which theories we can have access to. This suggests that there is a universality class of quantum gravity where the cosmological constant is zero. This universality class possesses the IR GFP where G 0 is a constant and ρ 0 = 0. Although there may be other universality classes where the cosmological constant is non-zero, here we will explore this one to see if there is also a non-trivial fixed point that can be used to define the interacting QFT.
Before ending this section, let us stress two points regarding the interpretation of couplings in gravity and the possible (imperfect) analogies we can make with couplings in, e.g., φ 4 -theory.
First, despite appearances, G k is not the inverse wave-function renormalisation, but a coupling, more analogous to the interaction coupling λ in φ 4 -theory. In particular, while the wave-function renormalisation is an inessential coupling in φ 4 -theory, G k is an essential coupling like λ. Secondly, again despite appearances, Λ k = ρ k G k is not a mass squared. A more clear interpretation of the vacuum energy comes if we choose to parameterise the metric, such that ρ k √ det g is linear in the field σ which parameterises conformal fluctuations [51]. This can be achieved by setting The fact that ρ k couples also to the purely vacuum term is what is crucial for ρ k to be inessential. Thus ρ k , rather than being analogous to a mass in a scalar theory which is essential, can better be interpreted as a constant source which couples linearly to the field in the broken phase of diffeomorphisms.
VI. MINIMAL ESSENTIAL SCHEME FOR QUANTUM EINSTEIN GRAVITY
Since the vacuum energy is inessential coupling at the GFP, we can fix it by a renormalisation condition. In particular, we can pick a condition which ensures that we are in the universality class which possesses the GFP and removes the vacuum energy from the set of couplings we must compute the flow of. We will adopt the simplest RG condition of this type which sets for all scales k = k 0 e t . The RG condition (6.1) identifies the vacuum energy with cut-off scale ρ k = k 4ρ GFP . Having applied (6.1), then the dimensionless product τ k ∶= ρ k G 2 k is given by and, therefore, the flow ofG(t) completely determines the flow of τ k . In classical general relativity, in the absence of matter, τ k is the only meaningful coupling since one can rescale the metric. This can be seen explicitly from the flow equation by observing that, when the RHS is neglected, the beta function for τ k is independent of γ g . More generally, when k = 0 it is evident that only dimensionless ratios couplings can be essential since a rescaling of the metric will change the values of dimensionful couplings. As such, τ 0 is the physical cosmological constant in Planck units which can be considered as an observable, which vanishes in the universality class we are considering. Let us stress, however, that although ρ k will vanish at k = 0, its presence in the action is still needed to consistently solve the flow equation for non-zero k. If we would simply neglect the flow of ρ k entirely, then G k would appear to be inessential since we could instead use γ g to dictate the flow of G k instead.
In addition to (6.1), we specify an infinite set of renormalisation conditions which exclude all terms that are dependent on the Ricci curvature R µν from the ansatz fromΓ k apart from the Einstein-Hilbert action and the topological Gauss-Bonnet term. This defines the minimal essential scheme for quantum gravity. At second order in curvature, the most general diffeomorphism invariant action can be written as 3) and, hence, in the minimal essential scheme we set W R,k (∆) = 0 = W Ricci,k (∆). Since, furthermore, all the higher terms depend only on the Weyl curvature C µνρλ , the propagator evaluated on any conformally flat spacetime, i.e., those where C µνρλ = 0, is just that of classical general relativity [48]. Consequently, the regularised propagator evaluated on a conformally flat background takes the form This ensures that the theory at k = 0 describes massless gravitons only.
Here, we shall only consider pure gravity. However, in [47], general arguments for spin 0, 1 2, 1, 3 2, and 2 fields suggest that terms which would modify the propagator by introducing new poles are redundant in the vicinity of the GFP. For example if we consider a scalar tensor theorȳ then we can still use both the equations of motion for the metric and the scalar to remove inessential couplings. Out of all terms with up to four derivatives, the only additional terms which do not vanish when the equations of motion apply are neither of which enter the propagator evaluated on a conformally flat spacetime and for constant values of φ.
The fact that we can remove the terms which lead to extra poles in the propagator along the RG flow indicates that the poles encountered in other schemes are spurious [52]. Let us stress however that nothing is wrong with using a scheme where the form factors do not vanish, such that the propagator at k = 0 with ρ 0 = 0 has the form where Z(∆) is a wave function renormalisation factor related to the form factors W R,k (∆) and W Ricci,k (∆), which have been computed in various approximations in [18,[53][54][55][56][57] and the physical implications for scattering amplitudes have been discussed in [58][59][60][61]. (In principle there can be another independent wave function renormalisation related to the scalar degree of freedom that is introduced in theories such as f (R) gravity. For simplicity, we discuss the case where there is only one wave function renormalisation which implies a linear relation between W R,k (∆) and W Ricci,k (∆)). There are two cases, either Z introduces new poles into the propagator, or it does not. In the latter case, we can remove Z by a reparameterisation since it must be an entire function, and thus it is just a momentum-dependent wave function renormalisation. In this case, we will find the same physics as in the minimal essential scheme, namely, although the field redefinition would modify the vertices of the theory, the propagator would return to the minimal form (6.4). The case where Z is not an entire function corresponds to a universality class not accessible to the minimal essential scheme for pure gravity. In particular, it would include particles other than the massless graviton. Thus, on one hand, the minimal essential scheme for quantum gravity, like its counterpart of scalar field theories [26], does put a restriction on what physics we can access by following the corresponding RG flow. On the other hand, this is a feature of the scheme, and not a bug, since the restricted theory space has a physical meaning, describing the interactions of gravitons which are fluctuation around a flat spacetime. Moreover, there is no reason why these fluctuations can not be strongly interacting, in particularG can become of order unity.
It may of course be that this universality class, which only includes a massless graviton, does not contain a suitable UV fixed point and that one would need more degrees of freedom to describe a consistent theory of quantum gravity. For example, it could be the case that one would need the extra degrees of freedom which are present in higher derivative gravity and are needed to make the theory perturbatively renormalisable, or that one would need to add an √ det gR 2 which includes an extra scalar degree of freedom in addition to the graviton. Here we will test the hypothesises that these extra degrees of freedom are not necessary for non-perturbative renormalisability.
VII. THE REUTER FIXED POINT IN THE DERIVATIVE EXPANSION
To test the aforementioned hypothesis, the minimal essential scheme can be carried out at each order in the derivative expansion. Here we will study the RG flow at order ∂ 2 , where the action is the Einstein-Hilbert action with (6.1), and at order ∂ 4 where the action takes the form with the only order ∂ 4 term being the topological one. At order ∂ 2 we set γ R and γ Ricci to zero, along with all higher-order terms in Ψ k , and expand the flow equation for (7.1) to order ∂ 2 solving for which are functions ofG alone. At order ∂ 4 we include all order ∂ 4 tensor structures in the flow equations but solve for γ R and γ Ricci instead of the running of the higher derivative couplings a k and b k , which are set to zero. Thus, at order ∂ 4 the minimal essential flow is characterised by five dimensionless functions ofG, namely Let us stress that calculation is vastly simpler than the calculation where higher derivative couplings a k and b k do not vanish [21,46] and that the final form of the beta and gamma functions only depend on one coupling rather than four in the standard scheme. As a first check we can analysis the behaviour around the GFP at G k = 0 to see how the universal one-loop divergencies are accounted for. In particular, the one-loop divergencies encountered in dimensional regularisation in our chosen gauge with Λ = 0 are given by three terms Upon replacing 1 d−4 → log(k k 0 ) and taking a derivative with respect to k the same three terms will appear in the flow equation on the RHS of Equations (A22)-(A24), respectively. However, the terms that would renormalise a k and b k are, instead, absorbed into γ R and γ Ricci , while c k will still be renormalised. Indeed, expanding in G k we find that which precisely account for the divergences (7.5).
The non-perturbative beta functions βG(G) at orders ∂ 2 and ∂ 4 are plotted in Figure 1 and are seen to closely agree forG in the plotted region. At both orders there exists a UV fixed point whereG which we can identify as the Reuter fixed point [5,6]. The Reuter fixed point splits the phase diagram of quantum gravity into a weakly coupled and strongly coupled regions for 0 <G <G ⋆ and G >G ⋆ , respectively. The critical exponent at the Reuter fixed point is given by which can be compared to the canonical scaling dimension of θ can = 2 which is obtained at oneloop, and, therefore, receives a small correction. This suggests that the Reuter fixed point is weakly non-perturbative [16,62]. The gamma function γ g (G), plotted in Figure 2 at orders ∂ 2 and ∂ 4 , also appears stable between the two approximations and is approximately linear in weakly coupled phase. At the Reuter fixed point γ g takes the values The stability between the orders can be understood by looking at the gamma functions γ R (G) and γ Ricci (G), which are zero at order ∂ 2 , and remain small at order ∂ 4 in the region 0 < G <G ⋆ , as can be seen in Figures 3 and 4. At the Reuter fixed point γ R and γ Ricci take the values Thus, we observe a remarkable stability as the order of the approximation is increased. At order ∂ 4 we also find the beta function of c k which is plotted in Figure 5. Let us stress that the values of the gamma functions are not universal quantities and will depend on the RG scheme. We note that atG ≈ 3 the beta functions βG(G) calculated at orders ∂ 2 and ∂ 4 begin to differ substantially. This indicates that the derivative expansion may not converge in the strong coupling phaseG >G ⋆ . However, since we undoubtedly live in a weakly coupled phase, this should have few phenomenological consequences.
Finally, we note that at the Reuter fixed point the redundant operators (4.22) are given by at order ∂ 2 , and by at order ∂ 4 . It is straightforward to show that these operators (7.16) and (7.17) are linearly independent of the terms in the Reuter fixed point action and form a complete basis at orders ∂ 2 and ∂ 4 , respectively. This confirms that the RG conditions which we choose to fix the inessential couplings at the GFP continue to fix the values of the inessential couplings at the interacting Reuter fixed point.
VIII. DISCUSSION AND OUTLOOK
We have investigated the non-perturbative renormalisability of gravity [2] taking care to disregard the running of inessential couplings for the first time. The consequences of doing so are profound: not only are calculations much simpler in the minimal essential scheme, but we also reveal that only Newton's constant is essential and relevant in our approximation.
Although this conclusion could change by including higher-order terms, this seems unlikely since all higher-order terms are canonically irrelevant and, thus, the quantum correction to their scaling dimensions would have to be large. Additionally, the stability of the fixed point going from order ∂ 2 to order ∂ 4 indicates that our approximations do not miss another relevant coupling. Moreover, the Goroff-Sagnotti term, which is the only ∂ 6 term that is independent of the Ricci curvature, has been found to be irrelevant at the Reuter fixed point [63]. As a result we expect that the qualitative picture obtained here at order s = 4 will not change as we go to higher orders. Ultimately, this can be confirmed by systematically increasing the order of the derivative expansion. This program will be technically simpler within the minimal essential scheme since there will be less terms in the EAA than in the standard approach [46], which does not remove redundant operators. Furthermore, it has been argued that additional poles in the propagator can prevent the convergence of the derivative expansion in quantum gravity [57]. However, in the minimal essential scheme we can avoid such poles and thus we expect to see convergence of the derivative expansion as is observed for scalar field theories [64]. Apart from strengthening the evidence in favour of the existence of the Reuter fixed point, we can also give a straightforward argument in favour of the theory being unitary, since the terms that contain four derivatives are redundant. This property will be true of all higher derivatives if the fixed point can be found in the minimal essential scheme, which assumes their absence from the beginning. Consequently, the minimal essential scheme provides a frame work to address some of the open problems for the asymptotic safety program [31,65] which concern the form of the propagator. We should stress that by using the minimal essential scheme we can dictate which physical degrees of freedom we are attempting to renormalise, and, thus, ensure that we are dealing with a unitary theory, rather than searching in a space of theories littered with non-unitary ones. In calculations that retain terms outside of those in the minimal essential scheme, we expect to find many fixed points which lie in different universality classes. Indeed, studies that include many powers of the Riemann curvature have found fixed points with as many as four relevant directions [66]. Perhaps most profoundly, we have identified the vacuum energy as inessential coupling which agrees with other arguments [67]. The fact that it is true at the GFP makes this a property of perturbative quantum gravity. One can show that the contributions proportional to w 1 and w 2 in the linearised beta function (5.16) come from the terms proportional to Ψ k in the RHS of the flow Equation (4.4) and terms proportional toρ GFP from the LHS of the flow equation. Reinstating powers of Planck's constant ̵ h, one sees that both contributions vanish when ̵ h = 0. This means that the inessential nature of the vacuum energy is a quantum effect. Indeed, in a scheme whereρ GFP = 0 the classical term in the redundant operator would vanish at the GFP, but the contributions due to Ψ k in the RHS of the flow equation mean ρ k is anyway inessential. The elementary understanding of this effect is that a rescaling of fieldĝ → Ωĝ produces an infinite factor ∼ ∏ x Ω in the functional measure which when regularised will renormalise the vacuum energy [50]. In the flow equation for the EAA, this manifests in the term proportional to γ g in the RHS of the flow equation. Thus, simply by renormalising the quantum metric field, we can adjust the renormalisation of the vacuum energy. Since, in the universality class we have investigated the vacuum, energy is inessential both at the GFP and the Reuter fixed point, no physical meaning can be attributed to its flow. However, there can be other universality classes, both for pure gravity and for gravity coupled to matter, where the cosmological constant is essential and its flow has physical consequences [68][69][70].
Since there is only one relevant essential coupling at the Reuter fixed point, it would appear that the vanishing of the cosmological constant in Planck units τ 0 = Λ k G k k=0 at k = 0 must be a prediction of the Reuter fixed point. Thus, if a different scheme would find a non-vanishing τ 0 it would be a contradiction that could only be explained as an artefact of an approximation. To investigate this, one can refrain from fixing the renormalisation ofρ, as in the minimal essential scheme, but instead only assume γ g vanishes atG = 0. Then, expanding ∂ t τ k aroundG = 0 while keeping τ k , one finds at order ∂ 2 that which implies that τ 0 could take a non-zero value. Studying the full beta functions with γ g = 0 one finds trajectories leaving the Reuter fixed point and ending at any value τ 0 < 0, contradicting the minimal essential scheme. However, going to order ∂ 4 one finds instead that which only vanishes at τ k = 0 and thus no contradiction with the minimal essential scheme can occur. Thus, the vanishing of the observable τ 0 appears to be a robust prediction of the Reuter fixed point.
Here we have only treated pure gravity and thus to properly address the cosmological constant problem we should understand the situation when matter is coupled to gravity [71]. Indeed, arguably there was never a cosmological constant problem in pure gravity since if we adopt dimensional regularisation only terms proportional to ρ k would renormalise ρ k and we can simply set ρ k = 0. What will remain true even in the presence of matter is that there is an inessential coupling related to a rescaling of the spacetime metric. This might shed new light on the cosmological constant problem [72].
This work can be extended in several directions. A crucial test is to make sure that the qualitative picture is stable when the form of the cut-off function is modified. Moreover, to obtain the best numerical estimate of the critical exponent θ, the principle of minimal sensitivity (PMS) can be applied by studying the dependence of θ on unphysical parameters, such as those which enter a class of cut-off functions or the values of inessential couplings, such as the vacuum energy. The PMS selects the value of θ where this dependence is minimal (for a recent application of the PMS to the critical exponents of the Ising model see [64]). Furthermore, the dependence on the parameterisation of the metric tensor and the choice of gauge [73][74][75][76] can also be investigated within the minimal essential scheme. In the background field approximation, we neglect the running of these parameters, while a proper treatment of these parameters should identify them with inessential couplings since they cannot enter expressions for observables. Thus, going beyond the background field approximation, the minimal essential scheme should include extra gamma functions in order to impose renormalisation conditions for each unphysical parameter. As an alternative, one can use diffeomorphism and parameterisation invariant exact renormalisation equations, such as those based on the geometrical effective action [77,78] or the background independent exact renormalisation group [79].
The finding that there appears to be only one relevant essential coupling in QEG is an encouraging sign for attempts to make contact with other methods which can be used to investigate asymptotic safety. In particular, it would be very interesting if perturbative methods based on expansions around two dimensions [50,80,81] could also calculate the critical exponent θ by performing a two-loop calculation in the minimal essential scheme. Additionally, the value of θ can be computed in lattice and tensor model approaches to quantum gravity [82][83][84][85].
evaluate the trace using off-diagonal heat kernel techniques [49]. We then choose the regulator to be given by where K µν,αβ and the following relation holds with η N = ∂ t G k G k . The Hessian in the gravity sector is where and the indices in the round brackets are symmetrised. Then the gravitational trace is given by where we have written , T gg is composed by nine traces, which read below we report the evaluation of these traces and finally
Calculation of ghost trace
In this subsection we calculate the ghosts contribution to the quantum part of the flow equation (4.4): like in the previous subsection, we insert the regulator in such a way that ∆ → P k ≡ ∆+R k (∆), we calculate the Hessian, we expand the argument of the trace to quadratic order in curvature and finally we evaluate the trace. We then choose the regulator to be given by where K µν cc = √ 2 κ k det gg µν , (A17) and the following relation holds Since the Hessian in the ghost sector is the ghost trace is given by
Beta and gamma functions
In this subsection we put all the contributions inside the flow equation together and we write down the beta functions for ρ k , G k and c k and the equations for the gamma functions γ Ricci and γ R . In order to express everything in the curvature basis R 2 , R µν R µν , E , we have expressed the Riemann tensor square as R µναβ R µναβ = E + 4R µν R µν − R 2 in the equations contained in A 1 and A 2. From the coefficient of √ det g, we can find the beta function of ρ k by solving Note that (A20) can be also understood as an equation for γ g : in fact, it is possible to fix the value of ρ k tuning γ g . As we discussed in section V, this procedure corresponds to impose a renormalisation condition that fix the value of the vacuum energy.
From the coefficient of √ det g R, we can find the beta function of G k and the coefficient of Note that (A22) and (A23) are the equations for the gamma functions γ Ricci and γ R , which are the parameters of the RG kernel that fix to zero the value of the couplings associated to the operators √ det g R 2 and √ det g R µν R µν . Finally, from the coefficient of √ det g E we can find the beta function of c k | 15,316 | 2021-07-01T00:00:00.000 | [
"Physics"
] |
The Business of Open Source Software: A Primer
This article is meant as a primer for those interested in gaining a basic understanding of the business of open source software. Thus, we cover four main areas: i) what motivates businesses to get involved in open source; ii) common open source licenses and how they relate to community and corporate interests; iii) issues regarding the monetization of an open source program; and iv) open source business models currently employed. This article is particularly suitable for people who want a general understanding of the business of open source software; people who want to understand the significant issues regarding an open source program's potential to generate income; and entrepreneurs who want to create a company around open source code. Ideology isn't what has sold the open source model. It started gaining attention when it was obvious that open source was the best method of developing and improving the highest quality technology.
Introduction
In a world built on openness, in which licensing dictates that the product is not only free of charge, but can be freely copied, modified, and redistributed by enthusiasts and competitors alike, how can anyone possibly make money on open source?The question of how one can monetize open source software is a significant one.The quest for, and dissemination of, its answer was the spark that started what was to become the Technology Innovation Management Review (Lavigne, 2007: timreview .ca/article/92;McPhee, 2011: timreview.ca/article/465).
Although much has been learned during the years since the emergence of open source and the business that grew to surround it, there are still few articles that attempt to summarize its dynamics.Perhaps the most well known of those efforts is Hecker's "Setting up Shop" (1998;tinyurl.com/28n7o3), which largely focused on what strategies could be employed utilizing open source.Now that open source is a much more mature field than it was back then, we can focus on documenting what entrepreneurs have done rather than could do.
The goal of this article is to concisely explain the nuts and bolts of how the business of open source works, including sufficient detail to serve as a useful primer on the topic -a springboard for further reading.Our focus is on approaches that generate income based on open source software and its development (e.g., not hardware manufacturers with an open source involvement).
The article is structured as follows.First, we offer a brief look at some of the main corporate motivations in open source.Second, we cover the most common types of open source licenses and the main aspects and concerns for businesses and programmers regarding licensing.Third, we outline the most significant points in a piece of software's earning potential.Finally, we briefly describe the more common business models in use today, and we examine their pros and cons from the standpoints of both the developers and entrepreneurs.Included at the end of the article is a list of recommendations for further reading.
Background: Corporate Motivations
The adoption of open source code allows businesses to harness the creativity and labour of both their employees and their customers in a way that is not available to firms employing only proprietary software licenses.Indeed, where developer motivations include many social motivations, firms have tended to emphasize economic and technological reasons for entering and contribut-
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The Business of Open Source Software: A Primer
Open source licensing also enables a faster average time from discovery to solution (Schindler, 2007;tinyurl.com/mv8eea9).Indeed, open source products have been often shown to be superior to their proprietary counterparts (e.g., Wheeler, 2007;tinyurl.com/r1yk).Furthermore, companies can see development of their product in directions they did not realize was significant to their users, as well as the development of features that are too far from the firm's core business to receive in-house funding for development.As an example, only two of the more than 20 language connectors for MySQL were programmed in house; the rest were developed and submitted by the community.
By joining an open source development effort, corporations can also influence the direction of its development.Furthermore, open source has been identified as a strategy for implementing long-term sustainable software systems (e.g., Lundell and Gamalielsson, 2011;tinyurl.com/n24dw4u).Open source can also be adopted as a competitive strategy, for example through making the functionality of a competitor's product freely available (Fitzgerald, 2006;tinyurl.com/al995aj).Open source can also be of value to companies that offer products other than software, for example by promoting open source in areas that facilitate the deployment of their hardware (Fitzgerald, 2006;tinyurl.com/al995aj).
Open Source Licenses
A basic understanding of licensing is important for entrepreneurs and programmers alike.Note, however, that the AGPL license has some minor restrictions, which will be discussed later.
One of the most important elements of, and differences between, open source license types relates to a concept called license compatibility.License compatibility is a term used to describe the issue of which licenses can be combined.Particularly, from a business perspective, license compatibility considers which licenses can be combined with proprietary software.A further issue, though one of lesser interest, is that of the right to change the license, in particular whether one is allowed to change an open source license to a proprietary one.
For businesses, this may be of interest as a source of free code.The issue of changing to a proprietary license splits the developer community into two camps.Those who are for it generally want to ensure (or at the very least do not mind) that their code is as valuable to corporate interests as possible.Those who are against it generally want to ensure that the open source project remains a freely available community good in perpetuity.The issue of license combining (including embedding) and license change is summarized in Table 1.
Permissive licenses
Permissive licenses allow a high degree of freedom to use and reuse (or fork) the code.It is not an extreme oversimplification to distil the permissive licenses down to the message: "here's the code, do whatever you want with it".(Commonly, one needs to distribute a copy of the copyright with the code, but in practice,
Table 1. Post-distribution rights of open source license types
The Business of Open Source Software: A Primer Michael "Monty" Widenius and Linus Nyman this need not be more complicated than including a readme file.)In other words, it is possible to fork a permissively licensed program and make it closed source.
(As an example, both Apple's OS X and iOS operating systems contain code that was copied from permissively licensed open source projects, most notably BSD: tinyurl.com/kffrf.)An issue which sets the permissive licenses apart from the copyleft licenses is that, once the source code is compiled, one does not need to distribute the original source code with the compiled (i.e., binary) version of the program.Among the more common permissive licenses are the Apache (tinyurl.com/kmenxch), MIT (tinyurl.com/3vfsyal),and BSD (tinyurl.com/lejoxn7) licenses.
Weak copyleft licenses (LGPL)
Weak copyleft licenses, such as the GNU Lesser General Public License (LGPL; tinyurl.com/mp4w4lw),can be combined with proprietary code, but cannot be relicensed under a proprietary license.So, although a firm's proprietary program can remain proprietary, even when combined with the LGPL, the LGPL-licensed program cannot be made proprietary.Furthermore, any modifications to an LGPL program must also be licensed under the LGPL.The Mozilla Public License (MPL; mozilla.org/MPL/) is also a weak copyleft license.
Strong copyleft licenses (GPL)
Much like the LGPL is synonymous with weak copyleft, the GNU General Public License (GPL; tinyurl.com/2459b5) is synonymous with strong copyleft.Hence, we will focus our discussion of strong copyleft licenses on the GPL.Although use of the GPL is in decline (Aslett, 2011; tinyurl.com/7ujq7sj),as of the writing of this article, it is still the most common open source license overall (Black Duck Knowledgebase; tinyurl.com/nl4z94t).The GPL requires any modifications to the code to also be licensed under the GPL.From a business perspective, the key issue to be aware of is that combining or embedding a program with the GPL necessitates the (re)licensing of all connected software so that it is also under the GPL.In practice, this means open sourcing any proprietary programs connected to a GPL-licensed program, and is therefore something many firms seek to avoid.Importantly, programs licensed under a GPL license cannot be re-licensed under a more permissive license (i.e., neither as LGPL or permissive).
A general comment regarding license change is that one can commonly change a license to a more restrictive license type but not to a more permissive one.Furthermore, only the permissive licenses can be changed to proprietary.
With the rise of cloud computing, a variation of the GPL license worth special mention is the Affero General Public License (AGPL; tinyurl.com/lzmmq8n).The AGPL differs from the GPL in that online use of a program is considered distribution, thus triggering the requirement for license compliance (i.e., source code access is required) even though a physical copy of the program has not been distributed.In other words, using an AGPL-licensed program in the cloud necessitates distribution of source code.
Choosing a license
Open source licensing is a more complex topic than can be covered in detail here.Furthermore, because legal precedent is rather limited, there are issues regarding licensing that are still subject to interpretation and that are coloured, among other things, by pragmatic versus ideological concerns.Thus, what may and may not be done under certain conditions is to some extent a matter of opinion.We recommend a close study of licensing before any final licensing decisions are made.For further reading, please refer to the links at the end of this article.
Ownership of code
A company or person that owns the rights to the code they develop can sell closed source copies of the code, which is a standard practice with proprietary programs.The dual licensing, business source, and (to a lesser extent) open core business models, which will be described in further detail later, require ownership of the code.
Location in the software stack (and "embedded" programs) Most software relies on other software to run.This concept of software codependence is most apparent in the so-called software stack.On the top of the stack is the application: a word processing program, a photo edwww.timreview.ca The Business of Open Source Software: A Primer Michael "Monty" Widenius and Linus Nyman itor, a game, etc. Digging deeper, one can find elements such as databases, middleware, and an operating system.It is not important for the purposes of this article to understand the layers or functions of a software stack; it is merely enough to know that such layers exist and that a program's location in the stack is significant to its overall importance to the stack.Programs higher up in the stack rely on programs lower down to function, but not the other way around.Whereas a word processor needs an operating system to be able to run, an operating system does not need a word processor for it to function.One way for an open source program to gain potential value is having other programs rely on it: by being embedded in the software stack and by being a required component for applications and other programs to function properly -or even run at all.
Business Models
Although a business model can usefully be seen as something much more complex than merely a revenue source (e.g., West, 2007: tinyurl.com/dxsemd;Bailetti, 2009: timreview.ca/article/226),at its essence is the question of how the firm can create value for the customer while simultaneously extracting some of that value for itself (West, 2005; tinyurl.com/ov69jb8).For the purposes of this article, we make use of very broad brush strokes in our interpretation, using the term "business model" to indicate the way in which a company delivers value to a set of customers at a profit (e.g., Johnson, 2010; tinyurl.com/m9uf6xe).Recommended reading for more indepth analyses of questions related to business models are offered at the end of the article.
The business models of open source can be divided in two main categories: those that require complete (or at least partial) ownership of the code and those that do not.Table 2 outlines the criteria for selecting an open source business model; however, it should be noted that these business models need not be mutually exclusive.
Support contracts and services
Support and services are closely related approaches; in fact, companies that provide one commonly also provide the other.Thus, although they could be separated, we have chosen to group them under one heading.The services business model is one in which income is generated by offering services in the form of, for example, training, consulting, or extensions development around an open source product.Companies that offer services will commonly also offer long-term support contracts, thereby achieving a more stable income than by merely focusing on one-off services.Two of the main challenges with the support and services approach are the lack of scalability and that the typical profit margin of 20-30% is not enough to pay for fulltime developers for the project.
The availability of support and services is an important factor for customers (e.g., Shanker, 2012; timreview.ca/article/635) and can be considered a necessary element for software to become truly successful.Bear in mind that, although support should be offered, it need not be provided by the same company that develops the software.Examples of a support and services providers are Red Hat (redhat.com) and SkySQL (skysql.com).For more information on Red Hat's approach, see Suehle (2012; timreview.ca/article/635).
Open core or commercial extensions
Open core is a business model in which the core of a program is open source, with additional closed source features provided for a fee.Open core has gained much momentum over the past few years.However, it is an approach primarily focused on appealing to the venture capitalist rather than the end user (Prentice, 2010; tinyurl.com/pqpmptk).The economic rationale is clear-cut, but the reaction of the community and customers may not be as easy to estimate.Although pragmatic firm motivations are accepted by the community provided they comply with the rules of the community (Bonaccorsi and Rossi, 2003;tinyurl.com/lfx847l),some developers see However, it should be noted that there are successful open core projects, which show that the approach can work.
If considering an open core approach, it is worth bearing in mind that the more useful the core product is, the greater the potential community interest will be.Thus, making non-critical parts of the program closed will lessen the potential negative effect on developer interest in the project.A time-limited hybrid licensing (Sprewell, 2010; tinyurl.com/n8zeoqr), in which the closed source components of open core become open source after a 1-5 year delay, has been proposed to help meet the demands of both users and developers.However, we posit that the business source approach explained below may be a more mutually beneficial means to the same end.Examples of open core are not as easy to come by as the frequent discussion of the topic over the past few years would imply.Perhaps the best-known example is MySQL (mysql.com),which offered dual licensing of an identical product (a closed source and a GPL version) under its previous owners, but has changed to an open core approach for its free version after it was purchased by Oracle (Young, 2011; tinyurl.com/3hyxttc).
Business source
Business source is a business model that employs two different licenses with a time delay.In this business model, the source code is openly distributed and freely editable.However, for a set amount of time, a predefined segment of users (0.1-1% is suggested) have to pay to be allowed to use it.The Business of Open Source Software: A Primer Michael "Monty" Widenius and Linus Nyman
Conclusion
Through this primer, we have given a brief answer to the question: "How can one make money on open source?"To the uninitiated, financing a business based solely around the development of open source code may perhaps seem somewhat enigmatic.Although challenging, it is nonetheless possible.Our goal in this article was to clarify this enigma by explaining some of its most significant parts.
The possibilities for monetization of a program are dependent on many factors, and key among them are ownership of code, choice of license (including the issue of license compatibility), and location in the software stack.These factors in turn affect the choice of business model.
As a primer, this article will hopefully provide a useful introduction to the business of open source.It is not intended to cover every aspect of open source businesses in full detail, nor can it provide conclusive recommendations that will apply in every case.However, in Table 3, we have included a list of recommended reading for those that want to dive deeper into the topic.
7.
Significant enabling factors for creating a successful business around open source are ownership of code and embeddedness (a program's location in the software stack).These same factors also largely determine what business models one can choose from.Figure1provides a flowchart to help choose a business model based on ownership, embeddedness, and intentions for further development.If the flowchart recommends against starting a business, consider either partnering, or releasing the code (e.g., under an Apache or BSD license) for someone else to continue developing the software.
Figure 1 .
Figure 1.Flowchart for choosing an open source business model This article is meant as a primer for those interested in gaining a basic understanding of the business of open source software.Thus, we cover four main areas: i) what motivates businesses to get involved in open source; ii) common open source licenses and how they relate to community and corporate interests; iii) issues regarding the monetization of an open source program; and iv) open source business models currently employed.This article is particularly suitable for people who want a general understanding of the business of open source software; people who want to understand the significant issues regarding an open source program's potential to generate income; and entrepreneurs who want to create a company around open source code.
Establishing a sufficient, steady income is a significant challenge in creating a company around open source software.Thus, although open source is a superior development model, there is no guarantee that one's program will make enough money to fund its continued development.Of particular significance to the business of open source are the questions of program ownership and location in the software stack, because these factors affect what business models one can choose from.In particular, the answers to these questions help decide whether one can employ what is arguably the most lucrative open source business model: dual licensing.
of Open Source Software: A Primer
After this initial time period (3 years is suggested), the license automatically changes to an open source license.Business source is a new entrant in the field of open source licensing, which we first detailed in the June 2013 issue of the Technology Innovation Management Review (Widenius and Ny-man, 2013; timreview.ca/article/691).It was created to help simultaneously meet the needs of both the open source Before starting a new open source project, check if a similar project already exists.Participating in an active program is preferable to starting a new fork.If there are similar programs that have been abandoned, do some research to find out why they were abandoned.Repositories such as GitHub (github.com) and SourceForge (sourceforge.net)have a myriad of abandoned programs.If you plan to rely on community participation, remember to use community-creating tools to reach and communicate with them: web pages, a forum or knowledge-base, email lists, bug system, build systems, source code repository, etc.You can start by hosting your project on GitHub, SourceForge, or another repository, but you will eventually want to host it yourself.
2. Find a company or a group of users that want to work with you to define the scope of the project.From the start, you will want to have users using the product while it is still in development. | 4,541.6 | 2014-01-28T00:00:00.000 | [
"Computer Science"
] |
ROLE OF LCAT ACTIVITY CHANGES IN ATHEROSCLEROSIS RISK
Lecithin cholesterol acyltransferase (LCAT) is a key enzyme that catalyzes the esterification of free cholesterol in plasma lipoproteins and plays a critical role in high density lipoprotein (HDL) metabolism. LCAT deficiency leads to accumulation of nascent pre-HDL due to impaired maturation of HDL particles, whereas enhanced expression is associated with the formation of large, apoE-rich HDL 1 particles. In addition to its function in HDL metabolism, LCAT was believed to be an important driving force behind macrophage reverse cholesterol transport (RCT) and, therefore, has been a subject of great interest in cardiovascular research since its discovery in 1962. Although half a century has passed, the importance of LCAT for atheroprotection is still under intense debate.
LCAT STRUCTURE AND FUNCTION
The human LCAT primarily produced by the liver, although it is also expressed in small amounts by intestine and in astrocytes in the brain, where it is involved in the cholesterol esterification in glia-derived apoE-containing lipoproteins [20,24,39,41]. The plasma concentration of LCAT is about 6 μg/ml and varies little in adult humans with age, gender, and smoking [1]. LCAT binds to lipoproteins and is primarily found in association with HDL, which likely prevents its uncontrolled clearance from the circulation [34]. The human LCAT half-life in plasma has been estimated to be 4-5 days [36] ApoAI is the most potent activator of LCAT, which enables it to synthesize cholesteryl esters from the free cholesterol on HDL by a transesterification reaction involving the transfer of a fatty acid at the sn -2 position of lecithin to the free hydroxyl group of cholesterol [14,24]. During this reaction, lecithins are converted into lysophosphatidylcholines. Firstly, apoAI concentrating the lipid substrates near LCAT and presenting it in an optimal conformation to LCAT. The conformation of these apoAI complexes is affected by the fluidity of the lipid bilayer [27,35]. The binding of LCAT to the apoAI is affected by the charge and size of the HDL particles [13]. The second step is the cleavage of the sn -2 ester bond of lecithin, wich leads to the release of a fatty acyl [22]. This step is influenced by the LCAT phospholipase activity and depends on the lecithin composition [13]. The last step is the transacylation of the fatty acyl moiety to the sulfur atom of a cystein residue forming a thioester, which subsequently donates its fatty acyl to the 3 _ -hydroxy group of the cholesterol molecule and forming cholesteryl ester [22]. Other apolipoproteins, such as apoAII, apoCI-III, apoAIV, and apoE, also can activate LCAT, although with less efficiency [25].
Therefore, only a minor ammount of LCAT in the circulation can be found in binded to apoB-containing lipoproteins. In 1966, Glomset identified LCAT as an important driving force in the RCT pathway, a process that describes the HDL-mediated removal of excess cholesterol from peripheral tissues, including macrophages from the arterial wall, and subsequent delivery to the liver for biliary excretion. The first step of the RCT pathway involves production of apoAI in the liver or intestine and its further release into the plasma [32]. Interaction with ATP-binding cassette transporter (ABC)A1 primarily on the intestine and liver induces the formation of nascent discoidal HDL (ndHDL) particles that can stimulate cholesterol efflux from the macrophages in the arterial wall [23,38]. Upon association of cholesterol with the ndHDL particle, it is esterified by LCAT, leading to the conversion of the ndHDL into a more mature HDL 3 particle by partitioning of the cholesterol esters into the core of the particle. This particle gains the ability to induce the efflux of cellular cholesterol via ABCG1 and SR-BI [23,38]. HDL particles being transformed into larger HDL 2 particles upon further enrichment with cholesteryl ester [32]. Several studies indicate that LCAT activity decreases correlatively with the enlargement of the HDL particle, particularly on large apoE-rich HDL 1 particles [7,28,33,40]. This could be explained by the fact that LCAT is subject to product inhibition [26], but it has also been suggested that sphingomyelin enrichment of HDL prevents binding of LCAT to the lipoprotein [6,28]. Notably, upon esterification of cholesterol in HDL, LCAT maintains the gradient of free cholesterol between the cellular membrane and the surface of the HDL particle, which is thought to pre-vent the transfer of cholesterol back to the cell by generating a continuous efflux of cholesterol from the cell to lipoproteins [12,17,31]. Importantly, the effect of LCAT on the flux of cholesterol may depend both on the environment of HDL in the extracellular medium and the type and metabolic status of the cells [16]. Therefore, in addition to its essential role in the first step of the RCT pathway, LCAT also enhances the delivery of cholesterol to the liver [16].
LCAT AND ATHEROSCLEROSIS
IN ANIMAL STUDIES Rabbits express CETP and can develop spontaneous atherosclerosis. Therefore, rabbits are often thought to be a better model for studying atherosclerosis than mice. In 1996, Hoeg et al. described the generation of transgenic New Zealand White rabbits with a 6.2 kb genomic fragment consisting of the entire human LCAT gene. To study the effects of human LCAT expression on atherosclerosis susceptibility, the rabbits were fed a daily ration of 120 g diet containing 0.3 % cholesterol for a period of 17 weeks [21]. Plasma LCAT activity was 101 ± 11 nmol/ml/h in controls and 1.593 ± 101 nmol/ml/h in the transgenic rabbits on chow. On the cholesterol diet, LCAT activity remained more than 3-fold that of controls. Total cholesterol and triglyceride levels were 28 % and 24 % lower, respectively, in the transgenic rabbits compared with controls. The reduction in total cholesterol was the consequence of a 2.6-fold decrease in non-HDL cholesterol levels, and HDL cholesterol was 5-fold higher. Quantification of atherosclerosis showed that 35 ± 7 % of the surface of the aortas of the control group were covered with lesions. For comparison, only 5 ± 1 % of the aortic surface in the LCAT transgenic rabbits was covered by lesions [21]. Overexpression of human LCAT thus protects against atherosclerosis in rabbits, probably due to the combined effect of the marked lowering of proatherogenic apoB-containing lipoproteins and the increase in HDL cholesterol. During the vivo kinetic experiments it was confirmed that LCAT increased the catabolism of apoB-containing lipoproteins, which was opposite to what was seen for apoAI catabolism [10]. To investigate the role of the LDL receptor in this enhanced catabolism, the LCAT transgenic rabbit was cross-bred with the Watanabe heritable hyperlipidemic (WHHL) rabbit with a lack of functional LDL receptors due to an amino acid deletion in the cysteine-rich ligand-binding domain of the protein [8,9]. As expected, circulating LDL levels were markedly higher in rabbits lacking the LDL receptor. Interestingly, no lowering of LDL cholesterol was seen upon overexpression of LCAT. This relults might indicate that the enhanced catabolism of apoB-containing lipoproteins upon overexpression of LCAT is mediated via the LDL receptor. It must, however, be noted that the HDL cholesterol levels and LCAT activity was 5-fold lower in animals lacking the LDL receptor compared with controls [8]. Analysis of atherosclerosis at 22 months of age showed that in both WHHL rabbits and WHHL cont-rol rabbits overexpressing LCAT, 84 ± 3 % of the surface of the aorta was covered with lesions. This lack of protection despite the high HDL cholesterol levels is likely due to the overwhelming presence of apoB-containing lipoproteins in plasma. Furthermore, the massive lesion coverage of the aorta indicates that the disease was in a very advanced stage. It might be that different effects would have been found if the effects were determined at an earlier age.
The results of the mice studies differ signifcantly from the results shown in the rabbit studies. Although most of the rabbit studies largely confirm an antiatherogenic role for LCAT, mouse studies suggest an unanticipated proatherogenic role for LCAT in the development of atherosclerosis. In both models, it appears that the influence of LCAT on atherosclerosis mostly depends on its effects on proatherogenic apoB-containing lipoproteins. Furthermore, the effects found are highly dependent on the presence of additional key proteins involved in RCT, such as LDL receptor and CETP. Notably, viral overexpression of LCAT in nonhuman primates also resulted in an antiatherogenic profile characterized by decreased levels of apoB-containing lipoproteins and increased level of HDL cholesterol [3], similar to that observed in the transgenic rabbits.
THERAPEUTIC REGULATION OF LCAT
In the recent years, therapeutic upregulation of LCAT function has gained interest, not only as enzyme replacement therapy for LCAT deficiency syndromes but also as a potential new therapeutic strategy for reducing atherosclerosis. Strategies for therapeutically raising LCAT activity include small-molecule activators of LCAT, viral expression of LCAT, and recombinant LCAT protein administration. Van Craeyveld et al. investigated the effects of adenoviral LCAT overexpression in liver on established complex fiboratheromatous atherosclerotic lesions induced by feeding heterozygous LDL receptor knockout rabbits (62.5 % New Zealand White and 37.5 % Japanese White) a 0.15 % cholesterol diet for 420 days [37]. Non-HDL cholesterol was not affected whereas denoviral LCAT overexpression increased HDL cholesterol 1.9-fold. No significant effects were observed in the intima/media ratio, macrophage, collagen content, or smooth muscle cell compared with baseline at 120 days after gene transfer. However, the intima/media ratio was lower compared with the animals treated with an empty adenovirus, indicating that LCAT overexpression had the inhibiting effect on the progression of atherosclerosis. Adenoviral LCAT overexpression also induced cholesterol unloading of the lesions, consistent with enhanced RCT from the arterial wall [37], but considering the complex interaction of LCAT with lipoproteins in the circulation, extensive studies on the effects on atherosclerosis susceptibility should help us to draw any conclusions on the therapeutic applicability of these new studies. Intravenous infusion of recombinant LCAT in LCAT knockout mice with or without expression of human apoAI rapidly restored lipid abnormalities such as raised HDL cholesterol [34]. Furthermore, a preliminary report indicated that subcutaneous injection of recombinant LCAT attenuated atherosclerosis progression in New Zealand White rabbits and stimulated RCT [43]. Notably, a phase 1 clinical trial was announced recently in which the effects of intravenous recombinant human LCAT infusion (ACP-501) in subjects with coronary artery disease will be evaluated [2].
Small molecule activation of LCAT modulates lipoprotein metabolism Specific LCAT activator increased LCAT activity in vitro in plasma from mouse, rhesus monkey, hamster, and human.
C57Bl/6 mice and hamsters received a single dose (20 mg/kg) of LCAT activator to assess the acute pharmacodynamic effects of LCAT activator. Both species displayed significant decrease in triglycerides and non-HDLc and a significant increase in high-density lipoprotein cholesterol (HDLc) acutely after dosing. To examine LCAT activator's chronic effect on lipoprotein metabolism, during the period of two weeks hamsters received a daily dosing of vehicle or of 20 or 60 mg/kg of LCAT activator. Activator treatment resulted in a significant reduction in very low-density lipoprotein cholesterol and asignificant increase HDL particle size, in amount of HDLc, plasma apolipoprotein A-I level, and plasma cholesteryl ester (CE) to free cholesterol ratio. Triglycerides trended toward a dose-dependent decrease in very low-density lipoprotein and HDL, with multiple triglyceride species reaching statistical significance. The increase in plasma CE resulted the increase in HDL CE. Gallbladder bile acids content displayed the more than 2-fold increase with the 60 mg/kg treatment. Plasma LCAT was activated from multiple species in vitro LCAT activator was spiked into plasma from C57Bl/6 mouse, rhesus monkey, hamster, and human at different concentrations.
To assess the effects of chronic activation of LCAT by by small molecule activator on lipoprotein metabolism, vehicle control (0.5 % methyl cellulose), LCAT activator at 60 mg/kg, or LCAT activator at 20 mg/kg was administered by oral gavage daily into high fat diet-fed hamsters for 14 days. LCAT activator treatment resulted in a significant dose-dependent increase in plasma CE and plasma CE/FC ratio and increase in plasma TC and plasma FC. Plasma LysoPC displayed a significant increase at both doses. Plasma PC showed no significant difference for both doses. Plasma TG showed a trend toward a dose-dependent decrease without reaching statistical significance. LCAT activator treatment also resulted in a significant significant decrease in VLDL cholesterol (VLDLc) and a significant increase in HDLc at both doses, whereas LDL cholesterol (LDLc) level remained unchanged. The FPLC analysis revealed a dose-dependent leftward shift of the HDL peaks, indicating that LCAT activator treatment resulted in a significant, dose-dependent increase in HDL particle size. Plasma apoA-I was significantly increased at both doses, whereas plasma apoB was unchanged.
In genetic or somatic LCAT overexpression models, including those in higher animal species, LCAT gain of function is associated with increased HDLc wich consistent with an antiatherosclerotic benefit [5,42]. LCAT activator enhanced plasma LCAT activity with micromolar potency (EC50 range of 1-10 μmol/L for all d6-CEproducts). It had been postulated that this activity increase was induced by interacting with the free sulfhydryl group in cysteine (C)31 near its catalytic site. C31 appears to be a conserved residue in LCAT from multiple species. Observation of the similar activity of LCAT activator across multiple species proves that LCAT activator is acting via a similar mechanism in all species from the study. It also has been shown that LCAT from baboon and hamster has similar positional specificity and substrate as human LCAT, in contrast to the mouse [30]. For in vivo characterization, an acute single-dose experiment was conducted in C57Bl/6 mice to establish a relationship between downstream plasma lipid profile (pharmacodynamics) and target engagement (activation of LCAT). After a single dose of LCAT activator (20 mg/kg), the increase in ex vivo plasma LCAT activity within 1 to 5 hours following dosing correlated with changes in HDL particle size, CE/FC ratio and plasma HDLc levels. The "rebound" of non-HDL at 24 to 48 hours suggests that chronic treatment with LCAT activator in C57Bl/6 mice may result in increased non-HDL. It had been reported that LCAT transgenic mouse had increased non-HDL and exacerbated atherosclerosis, whereas further introduction of CETP transgene decreased non-HDL and reduced atherosclerosis in the LCAT transgenic background [4,15]. Analysis of downstream pharmacodynamics markers revealed a significant reduction in non-HDLc and TG in the early time points and a significant increase in HDLc throughout the time course, which tracked with the changes in LCAT activity increase and suggest that the effects on lipids were likely due to LCAT activation by small putative activator. Observation on non-HDL suggests that CETP needs to be present to extrapolate effects of LCAT activation to human. The above results establish a relationship between pharmacodynamic markers and target engagement under acute conditions and are consistent with the current understanding of the role of LCAT in RCT and HDL metabolism. Therefore, a chronic study in hamsters was pursued to characterize the effect of LCAT activation by small molecule activator on lipid profiles in detail. A significant increase in HDL particle size, HDLc level and plasma apoA-I level was observed as well as dose-dependent decreases in multiple TG species and VLDLc. Low-density lipoprotein cholesterol remained the same, possibly because the baseline LDL level in this model is modest and thus givesa small window for reduction. Epidemiological studies have suggested that increased HDLc, decreased VLDLc, and decreased plasma TG are all associated with risk reduction for atherosclerosis [19]. In addition, increased plasma apoA-I level and lipid-rich, large HDL particle are also associated with re-duced risk for coronary heart disease [11,18,19]. The global changes in the lipoprotein can potentially be atheroprotective. Additional analyses indicated that liver microsomal stability and the plasma stability of LCAT activator were poor, which indicates the short duration of LCAT activation observed ex vivo. Nonetheless, the correlation between and LCAT activity and pharmacodynamic markers strongly supports the conclusion that small molecule activators elicited global changes in lipoprotein metabolism via activation of LCAT. In summary, the results from the current study demonstrate that activation of LCAT via these molecules produces concomitant changes in the lipoprotein profile in hamsters and mice and raise the possibility for small molecule therapeutic intervention of atherosclerosis and dyslipidemia via modulating LCAT activity. The findings of decreased TG and enhanced HDLc are are in line with observations from humans with LCAT deficiency and consistent with previous LCAT overexpression studies in higher animal species. This similarity between the LCAT-deficient human phenotype and the preclinical findings offers the possibility that the changes induced by a LCAT activator might translate into humans, and the finding of decreased VLDL may translate into decreased LDL in human. The detailed characterization from the current study of lipoprotein particle composition also sheds new light on LCAT's mechanism of action in lipoprotein metabolism.
CONCLUSIONS
Although a half a century of extensive research has passed since the discovery of LCAT as a key enzyme in the esterification of cholesterol in 1962, it has not (yet) fulfilled the promise as a new therapeutic target for atherosclerosis. Over the years, many studies have been performed investigating the role of LCAT in atherosclerosis in animal models and humans, with many conflicting data as a result. From the animal studies, it can be concluded that the effects of LCAT on atherosclerosis and lipoprotein metabolism largely depend on the animal model used and the presence of additional proteins involved in the RCT pathway, like LDL receptor and CETP. All the studies performed during the last 50 years have made it clear that LCAT plays a role in the pathogenesis of atherosclerosis. Newly developed activator(s) of endogenous LCAT, recombinant LCAT and small putative molecules LCAT activators infusions in humans and animals will provide valuable information to establish whether targeting of LCAT is a promising therapeutic strategy to reduce cardiovascular risk. | 4,082.4 | 2016-06-13T00:00:00.000 | [
"Biology"
] |
Evolution of limb development in cephalopod mollusks
Cephalopod mollusks evolved numerous anatomical novelties, including arms and tentacles, but little is known about the developmental mechanisms underlying cephalopod limb evolution. Here we show that all three axes of cuttlefish limbs are patterned by the same signaling networks that act in vertebrates and arthropods, although they evolved limbs independently. In cuttlefish limb buds, Hedgehog is expressed anteriorly. Posterior transplantation of Hedgehog-expressing cells induced mirror-image limb duplications. Bmp and Wnt signals, which establish dorsoventral polarity in vertebrate and arthropod limbs, are similarly polarized in cuttlefish. Inhibition of Bmp2/4 dorsally caused ectopic expression of Notum, which marks the ventral sucker field, and ectopic sucker development. Cuttlefish also show proximodistal regionalization of Hth, Exd, Dll, Dac, Sp8/9, and Wnt expression, which delineates arm and tentacle sucker fields. These results suggest that cephalopod limbs evolved by parallel activation of a genetic program for appendage development that was present in the bilaterian common ancestor.
Introduction
Animal appendages have widely varying morphologies and perform a multitude of functions, including locomotion, feeding, and reproduction (Nielsen, 2012;Ruppert et al., 2004). Limbs evolved on multiple occasions, and the absence of shared ontogenetic or morphological precursors of appendages in many animal lineages is consistent with their independent origins (Minelli, 2003;Pueyo and Couso, 2005;Shubin et al., 1997). This has led to the view that appendages in different clades of Bilateria are non-homologous morphological innovations that arose by convergent evolution (Nielsen, 2012;Ruppert et al., 2004). However, despite more than 500 million years of divergence, the independently evolved limbs of arthropods and vertebrates share developmental genetic similarities (Pueyo and Couso, 2005;Shubin et al., 1997;Tabin et al., 1999).
These discoveries led to debate over whether the genetic program for appendage development evolved in the common ancestor of all bilaterians in the early Cambrian, or whether arthropod and vertebrate appendages have undergone rampant convergence of developmental programs (Minelli, 2000;Minelli, 2003;Panganiban et al., 1997;Pueyo and Couso, 2005;Shubin et al., 1997;Tabin et al., 1999). A major obstacle to resolving this question is that the evidence of a conserved program derives almost exclusively from Ecdysozoa and Deuterostomia (Pueyo and Couso, 2005;Shubin et al., 1997), and little is known about molecular mechanisms of limb development in Spiralia, the third major superphylum of Bilateria (Grimmel et al., 2016;Prpic, 2008;Winchell and Jacobs, 2013;Winchell et al., 2010).
Within spiralians, the phylum Mollusca is the largest lineage, displaying a rich diversity of body plans ( Figure 1A) dating back to the Cambrian explosion (Ruppert et al., 2004;Smith et al., 2011). The evolution of arms and tentacles in cephalopod mollusks contributed to the successful adaptive radiation of these agile marine predators (Krö ger et al., 2011;Ruppert et al., 2004). Cephalopod limbs are highly muscular appendages that bear cup-shaped suckers on their ventral sides. Arms are short and have suckers along the entire ventral surface ( Figure 1B and C), whereas tentacles are longer, retractable appendages with suckers restricted to a distal pad ( Figure 1D and E). Tentacles are thought to be specialized serial homologs of the arms (Arnold, 1965;Lemaire, 1970;Shigeno et al., 2008) and are present in decapods (squid and cuttlefish) but absent in nautilids and octopods. Limbs likely evolved de novo in cephalopods ( Figure 1A), since no homologous precursor structures have been identified in any other mollusk lineages (Lee et al., 2003;Shigeno et al., 2008). To test the hypothesis that cephalopod limbs evolved by recruitment of an ancient gene regulatory network for appendage development that is conserved across Bilateria, we investigated arm and tentacle development in embryos of the cuttlefish, Sepia officinalis.
Development of arms and tentacles in the cuttlefish (Sepia officinalis)
Cuttlefishes are decapod cephalopods that have eight arms and two tentacles (Figure 1B-E; Figure 1-videos 1 and 2). Fertilized cuttlefish eggs undergo superficial cleavage, and scanning electron microscopy and optical projection tomography show that most embryonic development is restricted to the animal pole ( Figure 1H and I). The first sign of limb formation is observed at stage 16, when all ten limb primordia (five on each side) can be detected as small swellings around the periphery of a flat-shaped embryo, which lies at the top of the large yolk mass ( Figure 1H eLife digest Legs, wings, flippers and tentacles are just some examples of the diverse variety of animal limbs. Despite striking differences in form and function, all limbs develop in embryos using similar fundamental processes, like producing an outgrowth from the body and placing structures such as fingers, feathers, or suckers at appropriate positions. Animals have solved this problem multiple times during the history of life on Earth, in that limbed animals have arisen from limbless ancestors on many separate occasions. It is not clear, however, whether the same genetic instructions shape the developing limbs of all species.
Species that have limbs fall under three main groups of animals: arthropods, such as insects and crustaceans; vertebrates, like amphibians, reptiles and mammals; and a specialized group of mollusks known as cephalopods, which includes squid, cuttlefish and octopuses. It has been over two decades since the discovery that the limbs of vertebrates and insects develop using a similar molecular recipe, but the mechanisms responsible for the limbs of cephalopods had not been determined.
Tarazona et al. have now established that the genetic mechanisms that control how cuttlefish limbs develop are the same as those used by the limbs of vertebrates and insects. These mechanisms are also applied for similar purposes in each animal group. Notably, a signaling pathway called hedgehog, which controls the number of fingers that develop on a hand, also dictates the number of suckers on a cuttlefish arm. This may mean that an ancient system for creating limbs emerged over 500 million years ago in the earliest animals with bilateral symmetry (i. e., animals with mirror image halves), and activating this ancient genetic program resulted in the evolution of limbs in different animal lineages.
The extent of the genetic similarities between cuttlefish, mammals and insects suggests that this mechanism is likely to provide instructions about where cells position themselves in the developing limb. The next step is to examine how these common systems are interpreted differently to give arms, legs, wings and other limb forms. , and by stage 24, the differential length and morphology of arms relative to tentacles is apparent ( Figure 1L; Figure 1-video 5).
Analysis of sucker development showed that a sucker field primordium initially forms as a narrow proximodistal ridge along the ventral surface of each limb (evident by stage 21; Figure 1P). At later stages, the sucker field ridge cleaves superficially, segregating sucker buds from proximal to distal ( Figure 1Q). As the arms elongate, the sucker buds are laid down on the entire ventral surface of each arm (
Molecular analysis of cuttlefish limbs reveals conservation of proximodistal, anteroposterior, and dorsoventral patterning networks
To test the hypothesis that cuttlefish limb development is regulated by the same molecular mechanisms that pattern arthropod and vertebrate limbs, despite their independent evolutionary origins, we cloned and characterized cuttlefish orthologs of genes that pattern the three axes of vertebrate and arthropod limbs, and then analyzed their expression patterns during cuttlefish limb development ( Figure 2 and Partial sequences of cuttlefish cDNAs (Sepia officinalis and Sepia bandensis) were isolated by rt-PCR, and preliminary identities were determined by comparison with NCBI sequence databases, including the octopus genome. Molecular phylogenetic reconstructions were then made by maximum likelihood phylogenetic inference using the best amino acid substitution model for each gene . We also identified numerous homeobox genes, which phylogenetic analyses confirmed to be Dll, a pro-ortholog of vertebrate Dlx genes, Exd, a pro-ortholog of vertebrate Pbx genes, Hth, a pro-ortholog of vertebrate Meis1 and Meis2, and Engrailed, a pro-ortholog of vertebrate En1 and En2 (Figure 2-figure supplement 5).
In addition, we cloned the Wnt extracellular inhibitors Notum and Sfrp-1/2/5, and the Wnt coreceptor Fzd9/10 ( Figure 2-figure supplements 6 and 7). Cuttlefish possess a Bmp-2/4 gene that is an ortholog of arthropod Dpp and a pro-ortholog of vertebrate Bmp2 and Bmp4 (Figure 2-figure supplement 8), a Hh gene (Grimaldi et al., 2008) that we show to be a pro-ortholog of the vertebrate hedgehog family (Figure 2-figure supplement 9), and a gene encoding the Hh receptor Patched, a pro-ortholog of vertebrate Ptch1 and Ptch2 (Figure 2-figure supplement 10). The cuttlefish Sfrp ortholog that we identified as Sfrp1/2/5 was annotated incorrectly in the octopus genome as Frizzled1 (Figure 2-source data 1). We also found two Sp8/9 genes in the octopus genome ( Figure 2-source data 1), and the cuttlefish Sp8/9 gene shows clear orthology to only one of the two octopus genes (Figure 2-figure supplement 4), suggesting that the Sp8/9 gene underwent a duplication in cephalopod mollusks. Therefore, we designate the octopus Sp8/9 paralogs as Sp8/9a and Sp8/9b, and the cuttlefish Sp8/9 gene that we isolated is the ortholog of Sp8/9a. We next investigated the spatial and temporal expression patterns of these genes during cuttlefish limb development. Genes that pattern the proximodistal axis of arthropod and vertebrate limbs (Lecuit and Cohen, 1997;Mercader et al., 1999;Panganiban et al., 1997;Pueyo and Couso, 2005) showed similarly polarized patterns of expression along the proximodistal axis of cuttlefish limb buds, with Exd and Hth restricted proximally ( Figure . At stages 20-21, the distal expression boundaries of Exd and Hth and the proximal expression boundaries of Dll and Sp8/9a appear to mark the morphological boundary between the proximal sucker-free and the distal sucker-forming regions (compare right panels in Figure 2F-H and J with Figure 1P). Indeed, at stages when arms and tentacles begin to develop their distinctive morphologies -tentacles are longer and have an extensive proximal sucker-free domain -the Exd/Hth expression domains were found to extend further distally in tentacles ( Figure 3B,D) compared to arms ( Figure 3A and C). This distal expansion of the Exd/Hth expression domain matches the expanded sucker-free region and the distal restriction of suckers in tentacles ( Figure 3E).
Our finding that the proximodistal axis of cuttlefish limbs shares patterns of molecular regionalization with arthropod and vertebrate limbs led us to examine whether anteroposterior and dorsoventral axis development are also conserved. Posteriorly polarized activation of Hedgehog signaling in arthropod and vertebrate limbs is essential for proper patterning of the anteroposterior axis, and ectopic activation of the Hedgehog pathway induces anterior duplication of posterior structures (Basler and Struhl, 1994;Kojima et al., 1994;Riddle et al., 1993). We analyzed Hh expression during cuttlefish limb development at stages 16 to 20 and found that Hh expression is also polarized to one side of cuttlefish limb buds. In cuttlefishes, however, Hh expression is restricted to the anterior margin of the limb bud, whereas in arthropods and vertebrates, Hh/Shh is expressed posteriorly ( Figure 2D and K; and Figure 3-figure supplement 2D). Consistent with the anterior localization of Hh, we detected expression of Patched, which serves as a readout of Hedgehog signal transduction, in an anterior-to-posterior gradient ( Figure 2L). Thus, anteroposteriorly restricted activation of the Hedgehog pathway is a conserved feature of cephalopod, arthropod, and vertebrate limb development, but the polarity of the signaling center is reversed in cephalopod limbs. By stage 21, the anteriorly restricted Hh domain has diminished and a new, central expression domain appears in the location of the brachial nerve primordia (Figure 3-figure supplement 1F,K).
We then examined the dorsoventral axis, which is controlled by the antagonistic actions of wg/ Wnt and dpp/Bmp signaling in arthropods and vertebrates (Brook and Cohen, 1996;Cygan et al., 1997;Diaz-Benjumea et al., 1994;Jiang and Struhl, 1996;Parr and McMahon, 1995). In arthropods, the Wnt ligand wg is expressed ventrally, whereas the Bmp2/4 ortholog dpp is expressed dorsally (Basler and Struhl, 1994;Diaz-Benjumea et al., 1994). Expression and function of the Wnt- Bmp network is conserved, albeit with inverted polarity, in vertebrate limbs; Wnt7a is expressed dorsally (Parr and McMahon, 1995) and Bmp signaling activates Engrailed1 (En1) ventrally (Ahn et al., 2001), and these interactions regulate development of dorsal and ventral limb structures (Cygan et al., 1997;Parr and McMahon, 1995). Figure 2O; Figure 3M). This dorsal expression of Wnt antagonists suggests a mechanism for restriction of Wnt signaling to the ventral side of the cephalopod limb buds. Taken together, these results suggest that the genetic pathways active along the proximodistal, anteroposterior, and dorsoventral axes of cephalopod limbs are homologous (specifically, orthologous) to the networks that regulate limb development in arthropods and vertebrates.
In order to further test this hypothesis, we next performed a series of functional experiments to determine whether polarized expression of these signaling molecules is involved in patterning the anteroposterior and dorsoventral axes of cuttlefish limbs (described below). We developed a method for ex-ovo culture of cuttlefish embryos (see Material and methods) to allow in vivo manipulations of genetic pathways in early limb buds.
Bmp signaling controls dorsoventral patterning of cuttlefish limbs
A hallmark of dorsoventral polarity is the restriction of sucker buds to the ventral surface of the limb ( Figure 1C,D and S), and this is preceded by ventral expression of Notum in the sucker-forming region at stage 21 ( Figure 3N-Q). We asked whether polarized expression of Bmp2/4 on the dorsal side of cuttlefish limb buds is required for the specification of dorsal identity. To repress dorsal Bmp activity, we implanted carrier beads loaded with Noggin (Nog), a secreted Bmp inhibitor protein, on the dorsal side of stage 17 limb buds ( Figure 4A). Implantation of Nog beads on the dorsal side of cuttlefish limb buds resulted in ectopic, dorsal expansion of the Notum mRNA domain (n = 3/3; control PBS [phosphate buffered saline] beads had no effect on Notum expression [n = 3/3]) ( Figure 4G,H). To determine whether inhibition of dorsal Bmp signaling respecifies dorsal cells to form ventral structures, we repeated the experiment and allowed embryos to develop to stage 26-27. Analysis of limb morphology by scanning electron microscopy revealed the presence of ectopic sucker buds on the dorsal surface of Nog-treated limbs (n = 8/12; Figure 4B; Figure 4-figure supplement 1A and B). The ectopic dorsal suckers extended around the distal tip of the limb and joined the ventral sucker field. By contrast, in limbs that received control PBS beads dorsally, sucker buds were restricted to ventral surface and terminated at the normal dorsal-ventral boundary at the tip of the limb (n = 15/15; Figure 4C). Our finding that antagonism of Bmp signaling results in Arthropod gene expression is a compound reconstruction from chelicerate, myriapod, and hexapod limb development in order to consolidate a complete set of pro-orthologous genes comparable to vertebrate and cephalopod lineages. Cephalopod gene expression is based on findings in this study from the cuttlefish Sepia officinalis and Sepia bandensis. The figure illustrates the conserved and divergent expression patterns of homologous (orthologous) genes, some of which share equivalent roles in patterning the limb axes. The proximodistal axis displays conserved expression of transcription factors at opposite ends; Hth (proortholog of vertebrate Meis genes) and Exd (pro-ortholog of vertebrate Pbx genes) are restricted proximally, whereas Dll (pro-ortholog of vertebrate Dlx genes), Wnt5 (pro-ortholog of Wnt5a) and Sp8/9 (pro-ortholog of vertebrate Sp8 and Sp9 genes, known as Sp6-9 in some arthropods) show distally restricted expression. The typical expression pattern of Dac seen in arthropods (between proximally and distally restricted genes) is not strictly conserved in vertebrates (Dac is the pro-ortholog of vertebrate Dach genes) or cephalopods. However, Dac expression in non-locomotory arthropod appendages (e.g., mandibles) is distally restricted, resembling cephalopod Dac expression (Donoughe and Extavour, 2016). Expression patterns of the diverse family of Wnt genes shows interesting variation. Although, some members of the family show variation in their expression pattern (Wnt1 and Wnt7), there is a general pattern of distal restriction of Wnt expression (represented here by Wnt5, but also seen in many other Wnt ligands) in the three lineages. At the level of individual Wnt members, Wg (pro-ortholog of vertebrate Wnt1) is restricted ventrally in arthropods but not in vertebrates or cephalopods, and Wnt7a (arthropod and cephalopod Wnt7 genes are pro-orthologs of vertebrate Wnt7a) is restricted dorsally in vertebrates but not in arthropods or cephalopods. Restricted expression of Wnt ligands either dorsally or ventrally has not been reported in cephalopods, but the dorsally restricted expression of the Wnt repressor Sfrp1/2/5 suggests a role of polarized Wnt pathway activation in the control of the dorsoventral axis of cephalopod limbs, similar to vertebrates (by dorsal Wnt7a) and arthropods (by ventral Wg). There is a clear restriction of at least one Bmp ligand (vertebrate Bmp7 and cephalopod Bmp2/4; pro-orthologs of arthropod Dpp) and the transcription factor En along the dorsoventral axis in these three lineages. Finally, polarized expression of Hh is conserved in the three lineages (posterior in vertebrates and arthropods, but anterior in cephalopods), which, together with the functional manipulations, indicates conservation of Hh signaling in patterning the anteroposterior limb axis in the three lineages. The asterisk (*) in arthropod Dac indicates that some mouth appendages show a distal expression domain (Donoughe and Extavour, 2016) (Angelini and Kaufman, 2005) more similar to cephalopod Dac limb expression than to Dac expression in arthropod legs. Two asterisks (**) indicate that Wnt5 expression shows variation in arthropods, with a sub-distal expression in chelicerates (Damen, 2002) but distal in hexapods (i.e. flour beetle) (Bolognesi et al., 2008). Three asterisks (***) indicate that Dpp shows variation in its expression domain in arthropods, with some hexapods and Figure 5 continued on next page development of ventral structures (sucker buds) on the dorsal side of the limb indicates that dorsal Bmp2/4 activity is required for the early specification of dorsal identity in cephalopod limb development.
Hedgehog signaling at the anterior margin of cuttlefish limb buds controls anteroposterior patterning of the sucker field
We then investigated whether the mechanism of anteroposterior patterning is conserved between cephalopod and vertebrate/arthropod limbs. To determine whether the anterior expression of Hh in cuttlefish limb buds controls anteroposterior patterning, we grafted Hh-expressing cells from the thickened funnel epithelium (Tarazona et al., 2016) to the posterior side of stage 17 limb buds, which created an ectopic source of Hh opposite the endogenous Hh expression domain ( Figure 4D). We used Hh-expressing cells from the funnel, rather than the anterior side of the limb bud, to exclude the possibility of grafted limb cells undergoing self-differentiation. Transplantation of Hhexpressing cells to the posterior side of cuttlefish limb buds resulted in posterior limb duplications (n = 7/12; Figure 4E and Figure 4-figure supplement 1C,D). Analysis of morphology and gene expression in host limbs approximately 10 days after receiving the graft revealed that the posterior duplications even contained sucker buds, which were marked by Notum expression (Figure 4I and J). By contrast, limbs that received control grafts of stage 24 funnel epithelium that lacks Hh expression (Tarazona et al., 2016) developed normally (n = 8/8; Figure 4F). Although these results suggest that Hh is sufficient to re-specify anteroposterior polarity in cuttlefish limbs, we wanted to exclude the possibility that posterior identity was induced by other factors that could be present in the graft. Therefore, we tested whether Hh signaling is necessary for anteroposterior patterning of cephalopod limbs by specifically repressing endogenous Hh signaling. A notable morphological feature of cephalopod limbs is the anteroposterior arrangement of parallel sucker rows on the ventral surface ( Figure 1C,D and S). Based on the results of the transplantation experiments, we reasoned that Hh signaling could regulate the number of sucker rows along the anteroposterior axis of cephalopod limbs, similar to the manner in which Hh specifies digit number along the anteroposterior axis of vertebrate limbs (Lewis et al., 2001;Scherz et al., 2007;Zhu et al., 2008).
Discussion
Our finding that the proximodistal, dorsoventral, and anteroposterior axes of cuttlefish limb buds are patterned by the same pathways that regulate arthropod and vertebrate limb development suggests that the independent evolution of limbs in cephalopod mollusks involved recruitment of an ancient genetic program for appendage development. Discovery of this appendage developmental circuit within Spiralia demonstrates its deep conservation across all three branches of Bilateria (i.e., Deuterostomia, Ecdysozoa, and Spiralia), suggesting its presence in the common ancestor of all bilaterians ( Figure 5). Parallel recruitment of this ancient developmental genetic program may have played a role in the independent evolution of a wide diversity of appendages in many bilaterian lineages (Moczek and Nagy, 2005;Shubin et al., 2009).
The discovery that cephalopod, arthropod, and vertebrate appendages develop using conserved developmental mechanisms does not exclude the possibility that other types of appendages evolved by recruiting a different set of developmental tools (or by utilizing the same tools but in different patterns). Examination of gene expression in lateral parapodial appendages of the polychaete worm Neanthes, also a spiralian, led to the suggestion that the molecular mechanisms of polychaete appendage development might not be conserved with ecdysozoans and deuterostomes (Winchell and Jacobs, 2013;Winchell et al., 2010). However, given that relatively few genes were examined in Neanthes parapodia, it is difficult to conclude whether the reported differences between parapodia and arthropod/vertebrate/cephalopod limbs reflect the unique nature of parapodia or lineage-specific divergences that occurred after recruitment of the core developmental program. A study of a different polychaete, Platynereis dumerilii, showed that gene expression is generally conserved in appendages that form during regeneration of caudal trunk segments, although some divergent patterns were observed and these were suggested to reflect taxon-specific differences in appendage morphology (Grimmel et al., 2016). How parapodia fit into the picture of animal appendage evolution will require additional studies of spiralian appendages to increase the diversity of species, types of appendages, and number of genes/pathways interrogated. Nonetheless, our discovery that cephalopod arms and tentacles evolved by parallel recruitment of the same genetic program that orchestrates appendage formation in arthropods and vertebrates suggests that this program was present in the bilaterian common ancestor.
Activation of this ancient developmental program could also underlie the origin of other morphological innovations, including non-locomotory appendages such as beetle horns (Moczek and Nagy, 2005;Moczek et al., 2006) and external genital organs of amniote vertebrates (Cohn, 2011;Gredler et al., 2014). We propose that the genetic program for appendage formation was stabilized in Bilateria, including those lineages that lack limbs, for development of appendage-like structures. This hypothesis implies that the ancestral appendage developmental program was not a latent developmental feature that was redeployed each time that limbs evolved, but rather it might have been a continuously activated network that controlled formation of outgrowths in general.
One of our observations raises the possibility that the gene network that controls appendage formation could be conserved in non-cephalopod mollusks, despite the absence of arms and tentacles in those lineages. During cuttlefish funnel/siphon development, we found asymmetric expression of Hh (Tarazona et al., 2016) and proximodistally polarized expression of Wnt5 and Exd, which partially mirror their expression patterns during arm and tentacle development ( Figure 5-figure supplement 1). If this gene network is found to be active in the developing funnel/siphon of noncephalopod mollusks, then the funnel/siphon would represent a more primitive site of expression in mollusks, given that evolution of the molluscan funnel/siphon predates the origin of cephalopod limbs (Nielsen, 2012;Ruppert et al., 2004). Further studies of gene expression and function during funnel/siphon development in mollusks will be needed to determine if this clade shows conservation of the appendage development program beyond cephalopod arm and tentacle development.
Although the bilaterian common ancestor may have used this genetic program to control development of rudimentary outgrowths (e.g., appendages, funnel/siphon, genitalia), it is also possible that it predates the evolution of locomotory and non-locomotory appendages. Studies of cephalic neuroectoderm showed that gene expression patterns controlling the anteroposterior axis of the neuroectoderm mirror the organization of gene expression territories along the proximodistal axis of locomotory appendages, including polarized expression of Sp8, Dll, Dac and Hth (Lemons et al., 2010). Similarly, Minelli has suggested that the appendage patterning program could reflect cooption of a more ancient (pre-bilaterian) program for patterning the main body axis and, therefore, bilaterian appendages are simply secondary body axes (Minelli, 2000;Minelli, 2003).
Cephalopod arms and tentacles have no direct structural homologs in non-cephalopod mollusks; however, they likely formed from the ventral embryonic foot, a morphological and embryological hallmark of the molluscan bodyplan (Nö dl et al., 2016). Therefore, cephalopod arms and tentacles may be considered evolutionary novelties that are derived from a structure that is conserved across Mollusca. This raises the question of whether other foot-derived outgrowths/appendages (e.g., in sea slugs) evolved by co-option of the same developmental program that cephalopods, arthropods, and vertebrates use to build appendages.
Although the results presented here suggest that an ancient and conserved developmental genetic program facilitated the origin of cephalopod limbs, they also indicate that fine-scale regulatory changes may have played a role in the diversification of cephalopod limb morphologies. For example, evolution of specialized tentacles from serially homologous arms may have resulted from a distal shift in the expression of proximal identity genes, such as Exd and Hth, which could have extended the proximal sucker-free domain and restricted suckers to a distal pad (see Figure 3A-E). Likewise, the results of functional manipulations of Hh signaling in cuttlefish limbs suggests that the diversity in the number of sucker rows in cephalopod limbs (i.e. four rows in squids and cuttlefishes, two in octopus, and one in vampire squid and glass octopus) could be explained by modulation of Hh signaling, in the same way that gradual changes to Shh regulation has led to variation in digit number in tetrapod vertebrates (Scherz et al., 2007;Shapiro et al., 2003;Zhu et al., 2008).
Finally, we note that while the data presented here point to the existence of a deeply conserved genetic program for appendage development across Bilateria, this does not imply that the limbs of cephalopods, arthropods, and vertebrates are homologous structures, or that limbs were present in the common ancestor. Rather, these results show that homologous developmental mechanisms underlie the multiple parallel origins of limbs in bilaterians.
Materials and methods
No statistical methods were used to predetermine sample size. Embryos were randomized in each experiment. The investigators were not blinded to allocation during experiments and outcome assessment.
Embryo collection and preparation
Sepia officinalis and Sepia bandensis eggs were purchased from commercial suppliers, incubated until they reached the required stages (Lemaire, 1970), and prepared for in situ hybridization (ISH) and immunohistochemistry as described (Tarazona et al., 2016).
Optical projection tomography (OPT)
Three-dimensional reconstructions of gene expression in cuttlefish embryos were performed as previously described (Tarazona et al., 2016).
Scanning electron microscopy
Cuttlefish embryos were fixed in 4% paraformaldehyde in phosphate buffered saline (PBS) overnight at 4˚C and were washed with PBS the next day. Embryos were fixed in 1% osmium tetroxide solution in PBS for 30 min and then washed three times in PBS, dehydrated through a graded ethanol series, critical point dried, and sputter coated with gold. Embryonic samples were scanned using a Hitachi SU5000 and Hitachi TM3000.
Gene cloning and molecular phylogenetic analysis RNA extraction from Sepia officinalis and Sepia bandensis embryos at stages 15-26 was performed using TRIzol reagent (Ambion) following the manufacturer's instructions. cDNA synthesis was performed by an AMV reverse transcriptase (New England Biolabs) following the manufacturer's instructions. PCR amplification was carried out on Sepia cDNA pools, amplicons were cloned into TA vectors and sequenced. We then performed multiple sequence alignments (MSA) with ClustalW (PMID: 7984417) using the predicted amino acid sequence of our cuttlefish cDNA fragments, and putative metazoan orthologous genes downloaded from NCBI RefSeq protein databases (Figure 2source data 1). We performed nine MSA for Wnt, Tcf, Sfrp, Notum, Patch, Hh, Bmp, Sp and Homeodomain families. Each of the nine MSA was analyzed by ProtTest (PMID: 15647292), in order to determine the best combination of amino acid substitution model and other free parameters (amino acid site frequency, site heterogeneity and invariant sites), using Akaike information criterion (Figure 2-source data 1). We applied the best model in RaXML (PMID: 18853362) for each MSA and performed maximum likelihood phylogenetic inference, estimating branch support by bootstrap, and then majority consensus of the trees from all bootstrap partitions was performed to compute the final tree topology. All sequences have been deposited in Genbank under accession numbers MK756067-MK756082 (complete list of entries is provided in Figure 2-source data 1).
In situ hybridization (ISH) and immunohistochemistry
Whole-mount ISH was performed using digoxigenin-and fluorescein-labeled antisense (or sense control) RNA probes according to protocols described previously (Tarazona et al., 2016). Due to limited availability of embryonic material at relevant early developmental stages, only a limited number of S. bandensis embryos were used for ISH. Thus, the majority of ISH were performed in S. officinalis embryos using S. officinalis antisense RNA probes, however, some ISH were performed in S. officinalis embryos using S. bandensis antisense RNA probes. We validated the specificity of S. bandensis probes in S. officinalis embryos by comparing the gene expression domains marked by these probes in embryonic material from both species at stages 20 and 21. This comparison shows that gene expression territories identified by these probes at these stages were indistinguishable between the two species (Figure 3-figure supplement 2), consistent with their high level of sequence similarity (Figure 3-source data 1). Excluding the S. bandensis ISH mentioned above, all the experiments described in this work were carried out with S. officinalis embryos. Proliferating cells were detected by immunolocalization of Histone H3 Serine 10 phosphorylation using an antibody against H3S10p/PHH3 (06-570, EMD Millipore) and brachial nerve tissue was detected using an antibody against acetylated alpha tubulin (ab24610, Abcam).
Cuttlefish ex-ovo embryo culture and embryo manipulations A protocol for ex-ovo cuttlefish embryo culture was established for this study, as a modified version of previous descriptions of ex-ovo embryo culture in squid (Arnold, 1990). Briefly, to minimize the problem of bacterial and fungal contamination we started the protocol by taking 10 cuttlefish eggs at the appropriate stage, placing them in a 50 ml tube, and washing them with 0.22 mm filtered artificial sea water (FASW) five times. Eggs were then cleaned with a freshly prepared 5% bleach solution (0.25% sodium hypochlorite in FASW) for 5 s and immediately washed with FASW five times. The bleaching and washing steps were repeated two to three times. Five additional washes with FASW were carried out before incubating the eggs in 2X antibiotic/antimycotic solution (A5955, Sigma) in FASW for 2 hr at ambient temperature.
Each cuttlefish egg was then transferred to a 50 mm diameter petri dish that was coated with a~5 mm layer of 0.5% low melting point agarose (16520050, ThermoFisher), and filled with culture medium (components described below). The agarose layer had a hemispherical depression in the center of the dish made with a sterile 10 mm acrylic necklace bead before gel solidification. The 10 mm hemispherical depression is essential to maintain the normal shape of the yolk mass once the embryos are outside their egg case. Embryos were then extracted from their egg cases (S. officinalis are housed individually, one embryo per egg case) very slowly and with extreme care to avoid rupturing the yolk mass at the vegetal pole of the egg and were carefully placed in the hemispherical depression in the agarose. To extract the embryo, a single 5 mm diameter hole was created in the egg case, which generates a burst of the vitelline liquid and part of the embryo out from the egg case. With the hole kept open, the spontaneous shrinkage of the egg case aided in the expelling of the large cuttlefish embryo. Of every ten eggs prepared this way, between two and five embryos were damaged and had to be discarded. Embryos were cultured at 17˚C.
Protein carrier beads and tissue grafting
For protein carrier bead implantation, 150 mm diameter Affi-Gel Blue Gel beads (153-7301, Biorad) were selected and transferred to 1 mg/ml recombinant human Noggin protein (6057 NG, R and D Systems) in PBS and incubated for 30 min to 1 hr at ambient temperature before being implanted in embryos. Control beads were incubated in PBS only.
Grafts of Hh-expressing tissue were performed using stage 24 donor embryos and carefully dissecting the funnel side of the mantle-funnel locking system, which carries the Hh-expressing thickened funnel epithelium (Tarazona et al., 2016). The dissected tissue was transferred to 10 mg/ml Dispase II (D4693, Sigma) in cuttlefish culture medium and incubated for 40 min or until the thickened epithelium was easily detaching from the underlying mesenchyme with the aid of forceps. Tissue was then transferred to cuttlefish culture medium without Dispase II, where they were washed and then grafted into limb buds of stage 17 host embryos. Control grafts were performed using the non-Hh expressing epithelium of the funnel.
After bead implantation or tissue grafts, embryos were incubated at 17˚C until control embryos reached stage 26, at which point all embryos were collected and prepared for SEM or ISH.
Treatments with small-molecule inhibitors
Cyclopamine treatments were performed as described previously (Tarazona et al., 2016) with the following modifications; stage 16 embryos were treated with 10 mM cyclopamine (C988400, Toronto Research Chemicals) for 2 days, then washed thoroughly ten times with FASW. Embryos were then washed five more times every hour and one time every day before collecting the embryos for SEM. Control embryos were treated with 0.1% DMSO and then washed as described above. | 7,722.4 | 2018-07-31T00:00:00.000 | [
"Biology",
"Environmental Science"
] |
Searches for anomalous $tqZ$ couplings from the trilepton signal of $tZ$ associated production at the 14 TeV LHC
We investigate the observability of the top anomalous $tqZ$ couplings via the trilepton signatures at the Large Hadron Collider~(LHC) with the center-of-mass energy of 14 TeV. We focus on signals of the $tZ$ associated production with the decay mode $t\to W^{+}b\to b\ell^{+}\nu_{\ell}$, $Z\to \ell^{+}\ell^{-}$, and $t\bar{t}$ production with the decay mode $\bar{t}\to Z(\to \ell^{+}\ell^{-})\bar{q}$ and $t\to b\ell^{+}\nu_{\ell}$, where $\ell=e, \mu$ and $q$ reflects up and charm quarks. It is shown that at $3\sigma$ level, the FCNC top quark decay branching ratios can be probed at, respectively, about $Br(t\to uZ) \leq 1.3\times 10^{-4}$ and $Br(t\to cZ) \leq 4.2\times 10^{-4}$ with the integrated luminosity of 100 fb$^{-1}$, and probed down to $Br(t\to uZ) \leq 2.2\times 10^{-5}$ and $Br(t\to cZ) \leq 8\times 10^{-5}$ for the high-luminosity LHC with 3000 fb$^{-1}$.
I. INTRODUCTION
As the most massive particle in the standard model (SM), the top quark is generally considered as an appropriate probe for the new physics (NP) beyond the SM [1]. In particular, its flavor-changing neutral current (FCNC) interactions are extremely weak in the SM due to the Glashow-Iliopoulos-Maiani (GIM) mechanism [2]. For instance, the branching ratios of t → Zu(c) are predicted at the order of 10 −17 (10 −14 ) in the SM [3]. However, several extensions of the SM such as the SUSY models [4,5], two-Higgs-doublet models [6], extra dimensions [7], and the other miscellaneous models [8] predict much higher branching ratios up to 10 8 − 10 10 order of magnitude larger than SM predictions. Therefore, any signal for these rare FCNC processes at a measurable rate would be a robust evidence for NP beyond the SM.
Over the years, the top quark FCNC interactions has been studied intensively via the tt production processes with the anomalous decays of top quarks or anomalous production of single top quark [9][10][11]. Furthermore, the anomalous top quark interactions affect b quark FCNC decays through loop diagrams as mentioned in Ref. [12]. Very recently, both the ATLAS and the CMS experiments have obtained the limits on the branching ratios of the top anomalous decays through different channels (for an updated review, see [13]). The current upper limits for Br(t → Zq) at 95% confidence level (CL) have been found to be [14,15]: The most stringent bounds on the strengths of anomalous couplings tqZ come from the CMS experiment with √ s = 8 TeV, using the recent combination with anomalous tZ production [14].
It is notable to mention here that, even at the future facilities, these bounds resulting from tt production would not be improved considerably. The organization of this paper is as follows. In Sec. II, we present the theoretical framework which describes the FCNC tZq couplings. In Sec. III, we discuss the signals of tZ associated production with the decay mode t → W + b → ℓ + νb and Z → ℓ + ℓ − , and tt production with the decay modet → Z(→ ℓ + ℓ − )q and t → bℓ + ν ℓ . Then we analyze the sensitivity of 14 TeV LHC to anomalous tqZ couplings in detail. Finally, we conclude in Sec. IV.
II. CALCULATION FRAMEWORK
In general, the effective Lagrangian describing the interactions between the top quark and a light up-type quark (u or c) and the Z boson can be written as [17] − where g is the SU(2) L gauge coupling constant, C W = cos θ W and θ W is the Weinberg angle, , and Λ is the new physics scale, which is related to the cutoff mass scale above which the effective theory breaks down. The effects of new physics contributions are quantified through the dimensionless parameters κ tqZ and λ tqZ together with the complex chiral parameters κ L,R and λ L,R , which are normalized as The above effective Lagrangian can be used to calculate both production cross sections and the branching ratios of the t → qZ decays. Note that we do not consider the FCNC tqg couplings because the sensitivity is poor in comparison to other channels [18]. On the other hand, the λ tqZ couplings lead to very small cross sections [19]. We thus only consider the cases where κ tqZ /Λ = 0, and no specific chirality is assumed for the FCNC interaction vertices, i.e.
At the leading order (LO) and the next-to-leading order (NLO), the decay widths of the dominant top quark decay mode t → W b could be found in Ref. [20]. The partial decay widths of t → qZ with flavor-violating interactions are given by After neglecting all the light quark masses and assuming the dominant top decay width t → bW , the branching ratio of t → qZ can be approximately given by: Here the NLO QCD correction to the top quark decay via model-independent FCNC couplings is also included and the k-factor is taken as 1.02 [21]. The SM input parameters relevant in our study are taken as follows [22]:
III. SIGNAL AND DISCOVERY POTENTIALITY
In this section, we perform the Monte Carlo simulation and explore the sensitivity of 14 TeV LHC to the tqZ FCNC couplings through the tZ-FCNC and tt-FCNC processes. The representative Feynman diagrams for the signal processes are shown in Fig. 1.
Obviously, the signal is taken as the trilepton plus one b-jet and missing energy. The main backgrounds which yield the identical final states to the signal are tt, ttV (V = W, Z), W Z+ jets and the irreducible tZj, where j denotes non-bottom-quark jets. In the tt case (both top quarks decay semi-leptonically), a third lepton comes from a semi-leptonic B-hadron decay in the b-jet. Here we do not consider multijet backgrounds where jets can be faked as electrons, since they are very negligible in multilepton analyses [23]. On the other hand, the SM tth and tri-boson events can also be the sources of backgrounds for our signal. We have not included these backgrounds in the analysis due to very small cross sections after applying the cuts. The high order corrections for the dominant backgrounds are considered by including a k-factor, which is 2.07 for W Z+ jets [24], 1.27 for ttV [25] and 1.7 for tZj [26], respectively. The LO tt samples are normalized to the theoretical cross-section value for the inclusive tt process of 953.6 pb performed at next-to-next-to-leading order (NNLO) in QCD and including resummation of next-to-next-to-leading logarithmic (NNLL) soft gluon terms [27]. On the other hand, the MLM matching scheme is used, where we included up to three extra jets for W Z + jets and tZj in the simulations [28]. Here it should be mentioned that the k-factor for the LO cross section of σ tZ is chosen as about 1.4 at the 14 TeV LHC [29,30].
In order to simulate and generate the signal events, the κ Lagrangian terms presented in Eq.
(2) are implemented in MadGraph5-aMC@NLO [31] by means of the FeynRules package [32]. All of these signal and backgrounds events are generated at LO with the CTEQ6L parton distribution function (PDF) [33], and the renormalization and factorization scales are set dynamically by default. The events are then passed to Pythia 6 [34] for parton showering and hadronization, and the fast detector simulation in Delphes [35] with CMS detector card is used to include the detector effects. Finally, events are analyzed by using the program of MadAnalysis5 [36].
Further, we apply some general preselections as follows.
Since the third lepton, ℓ 3 , is assumed to originate from the leptonically decaying top quark, the top quark transverse cluster mass could be defined as [37] where p T,ℓ 3 and p T,b are the transverse momentums of the third charged leptons and b-quark, respectively, and / p T is the missing transverse momentum determined by the negative sum of visible momenta in the transverse direction. In Fig. 3 In Fig. 4, we present the normalized spectrum of the rapidity of the reconstructed resonances for the signal and backgrounds. It can be seen the Z boson from the ug → tZ process concentrates in the forwards and backwards regions. This is because the momentum of initial up quark is generally larger than that of gluon, the partonic center-of-mass frame is highly boosted along the direction of the up quark. This case is similar with the top-Higgs associated production process [38]. Thus we impose rapidity cut on reconstructed Z boson for the signal of ug → tZ process as • Cut-4: |y Z | > 1.0.
The cross sections of the signal and backgrounds after imposing the cuts are summarized in Table I, the anomalous couplings are chosen to be κ uZ (1TeV)/Λ = κ cZ (1TeV)/Λ = 0.1. One can see that all the backgrounds are suppressed very efficiently after imposing the selections. However, the cross section of the process pp → tt → tZc is about two times larger than that of cg → tZ process after cuts. As stated before, we should include these two processes when discussing the tcZ couplings. On the other hand, since the momentum of initial charm quark is much smaller than that of the initial up quark, the Z boson from cg initial states is not boosted as from ug initial states. Therefore, we do not apply the cut-4 when it comes to the cg → tZ process. The statistical significance is calculated after final cut by using [39]: where σ S and σ B are the signal and background cross sections and £ int is the integrated luminosity. Here we define the discovery significance as SS = 5, the possible evidence as SS = 3 and the exclusion limits as SS = 2. In Fig. 5, the 2σ, 3σ and 5σ lines are drawn as a function of the integrated luminosity and the branching ratios t → qZ. We do not consider the theoretical and systematic uncertainties for simplicity. One can see that the 5σ CL discovery sensitivity of Br ( It is remarkable that even with the high-luminosity of 3000 fb −1 , the branching ratios would not be measured better than 10 −5 . The recent phenomenological studies in Ref. [40] have shown that the 95% CL upper limits on the branching ratios Br(t → qZ) probed down to Br(t → uZ) ≤ 4.1 × 10 −5 and Br(t → cZ) ≤ 1.6 × 10 −3 . Thus our results are comparable with those for the HL-LHC, but they are below the sensitivity limits of the future 100 TeV pp circular collider (FCC-hh) [41].
IV. CONCLUSION
In this letter, we have investigated the signal of the tZ associated production via the FCNC tqZ couplings at the LHC with √ s = 14 TeV. We focus on trilepton final signals of the pp → tZ process with the decay mode t → W + b → bℓ + ν ℓ , Z → ℓ + ℓ − , and tt production process with the decay modet → Z(→ ℓ + ℓ − )q and t → bℓ + ν ℓ , where ℓ = e, µ and q reflects up and charm quarks. It is shown that the branching ratios Br(t → uZ) and Br(t → cZ) are, respectively, about Br(t → uZ) ≤ 1.3 × 10 −4 and Br(t → cZ) ≤ 4.2 × 10 −4 at 3σ level with the integrated luminosity 100 fb −1 , and probed down to Br(t → uZ) ≤ 2.2 × 10 −5 and Br(t → cZ) ≤ 8 × 10 −5 for the future HL-LHC, which are significantly better than the current experimental results. | 2,725.8 | 2017-12-10T00:00:00.000 | [
"Physics"
] |
The Ithildin library for efficient numerical solution of anisotropic reaction-diffusion problems in excitable media
Ithildin is an open-source library and framework for efficient parallelized simulations of excitable media, written in the C++ programming language. It uses parallelization on multiple CPU processors via the message passing interface (MPI). We demonstrate the library’s versatility through a series of simulations in the context of the monodomain description of cardiac electrophysiology, including the S1S2 protocol, spiral break-up, and spiral waves in ventricular geometry. Our work demonstrates the power of Ithildin as a tool for studying complex wave patterns in cardiac tissue and its potential to inform future experimental and theoretical studies. We publish our full code with this paper in the name of open science.
Introduction
With the Ithildin framework, we want to open up new gateways in the numerical simulation of reaction-diffusion systems, such as the electrical activation patterns in the heart.(In this way, it is similar to its namesake in the Lord of the Rings, where Ithildin is an Elven substance that reveals a hidden gateway to another realm after a spell is cast [1]).
Our motivation to write a reaction-diffusion solver comes from the numerical study of electrical patterns inside the heart [2].These patterns, which are incompletely understood, are a main cause of death and even as a chronic disease, they complicate people's lives.In the past decades, computer models of arrhythmia have allowed mechanistic insight in the origin and control of arrhythmias [3].On the longer term, it is thought that digitized versions of patients' hearts could help offer better diagnostics and planning of procedures; such personalized heart models are called cardiac digital twins [4][5][6][7].In view of open science, we have decided to share the code that has been steadily developed in our group since 2007 with the scientific community.
A flowchart outlining the functionality of Ithildin can be found in Fig 1 .Ithildin is designed to comply with the 2011 version of the ISO-C++ standard [8], but it compiles with all newer versions, including the current 2023 ISO-C++ standard [9][10][11][12].The software facilitates forward Euler and Runge-Kutta finite-difference solutions for reaction-diffusion systems in Ndimensional space, such as the monodomain equation for cardiac electrophysiology, with specified boundary conditions [2].
The framework offers quick computation through CPU parallelization using OpenMPI [13].It also boasts decent documentation of available features, made accessible through Doxygen [14].Ithildin writes easy-to-parse YAML log files to document simulation setups [15].Additionally, it allows convenient output of frames of recorded variables at regular intervals in the form of NumPy NPY files [16].The software supports easy and powerful post-processing with the Python module for Ithildin [17], including integration with Scientific Python [18], 2D visualization with Matplotlib [19], and 3D visualization with ParaView [20].
Ithildin also allows the recording of pseudo-electrograms (EGMs) and state variables at full numerical time resolution, as well as the tracking of filaments, which represent the instantaneous rotation axes of rotors.The software features a flexible setup for in-silico experiments, also called simulations, through a simple class-based C++ interface.
Various types of geometries are implemented, ranging from a simple 1D cable and spirals in 2D tissue to whole-heart geometry and even 4D hyperspace.The space can be partitioned to use multiple cell models in the same experiment via Model_multi.Realistic stimulation protocols can be added as Stimulus objects and may be started by a Trigger.Ithildin also includes a logging system with minimal impact on computation speed and various levels of verbosity.
In this paper, we provide an overview of this framework, guiding the reader through its components.Results from several in-silico experiments are presented as the main components Ithildin can be used to solve reaction-diffusion problems in excitable media.Required inputs for the software are: the diffusion tensor and geometry of a medium-such as the heart muscle, a reaction term-the so-called model, and source terms-typically a stimulation protocol.Ithildin can then calculate the evolution of the model variables in the medium over time.During calculation, Ithildin records relevant spatio-temporal data and metadata, as well as detecting rotor cores as filaments.The data visualized here are taken from several simulations which will be discussed below.https://doi.org/10.1371/journal.pone.0303674.g001 of Ithildin are introduced.The details of these so-called simulations are outlined towards the end of this paper in section 5, along with a tabular overview in Table 4.
Reaction-diffusion system
The diffusion of electrical signals in cardiac tissue can be modelled as a reaction-diffusion system, where the diffusion tensor D represents the anisotropic properties of the medium.This tensor encapsulates the spatial orientation of fibers in the medium and the effects of inhomogeneities on signal propagation.With the local unit vectors along the fibers e f , normal to fibers in the sheet plane e s , and normal to both of these e × = e f × e s , forming a orthonormal basis, the fiber orientation is encoded using diffusivities D f,s,× (x) in each of these directions [2]: The core equation governing the evolution of the state variable vector u is the reaction-diffusion equation: or in index notation: for m, m 0 2 {1, . .., M} with the number of state variables M, and n, n 0 2 {1, . .., N} with the number of spatial dimensions N, using the notation @ n ¼ @ x n for the spatial partial derivatives.
Here, u is the state variable vector and r ðu Þ accounts for the reaction term and is called the model.We refer to the first component of u as u, which for electrophysiological models is the transmembrane voltage V m or a rescaled version of it, see also section 4.2.For two-variable models, the second component of u is often referred to as the restitution or recovery variable v.In the term representing diffusion, D is determined by the geometry of the medium and the presence of inhomogeneities, see section 4.1.The projection matrix P is typically a diagonal matrix describing whether or not a variable is diffused.For instance, only the first variable of the AP96 model [21] is diffused, such that P ¼ diagð1; 0Þ.
Different notation is used to distinguish between vectors x and matrices D in physical space in bold font, and underlined vectors u and matrices P with respect to state variables.We use lowercase letters for vectors and uppercase for matrices.An overview of the most relevant quantities in Ithildin is given in Table 1.Ithildin obtains approximate solutions of the reaction-diffusion equation (Eq 2) via a finitedifferences approach: Time t and space x are discretized on a grid and values u ðt; xÞ are associated with the vertices of this grid.We choose a fixed temporal resolution, the time step Δt, and constant spatial grid spacing Δx.The values u ðt þ Dt; xÞ at a subsequent time-step are computed based on the previous ones, according to discretized versions of the governing equations, i.e., the reaction-diffusion equation (Eq 2), together with boundary and initial conditions.
Time integration
Starting from an initial state, the state variable vector u is integrated over time using a so-called time stepping scheme leading to an approximate solution of the reaction-diffusion system using finite differences.Ithildin implements two main stepping schemes to choose from: forward Euler and the classic Runge-Kutta method (RK4) [22,23].
Defining f as the right hand side of the reaction-diffusion equation (Eq 2), the forward Euler method takes the form [23]: This method is the default time integration scheme in Ithildin.Despite its numerical error being of order O(Δt 2 ), with a sufficiently small time step, the accuracy of the Euler method is adequate for our use cases.
Due to the Courant-Friedrichs-Lewy condition (CFL), a stability criterion for the integration of the reaction-diffusion equation, Δt needs to be chosen sufficiently small [24].Ithildin automatically chooses an appropriate time step based on the CFL condition for the different supported geometries, cf.section 4.1.For example, for the most simple implemented geometry contained in Ithildin, i.e., isotropic diffusion (see Geometry_Iso in section 4.1 and Table 2), the CFL condition is enforced by setting [25]: where D nn are the diagonal components of D and max P is the maximum value of P .Higher accuracy at the cost of more computations per time step, can be achieved with the RK4 method [23]: Note that f needs to be evaluated four times for the RK4 method and only once for the Euler method.While RK4 is still an explicit method subject to instability at too large Δt, a larger Δt value than for the Euler method can typically be used.
The stepping scheme to be used can be chosen in Ithildin on a per-variable level via Model::steppings.
Numerical spatial derivatives
For the numerical solution of the reaction-diffusion equation (Eq 2), the spatial derivative in its right hand side must be computed, i.e., the diffusion operator P r � Dru .This is implemented as weighted sums of the value of u at neighboring vertices on the grid of the discretized domain.The weights for the calculation of the stencil depend on the chosen type of diffusion (section 4.1).The two main types in this software are a first order stencil, including only the nearest neighbors, and a second order stencil, including also the next to nearest neighbors.
In the simplest case (see Geometry_Iso in section 4.1 and Table 2), we consider isotropic and homogeneous diffusivity.The diffusion operator can then be computed via the Laplacian operator r 2 .This is done with a 5-point stencil for the 2D case, a 7-point stencil for the 3D case, etc., see also Fig 2,panel (a).Consequently, the weights are calculated as: where N is the number of dimensions and Δx n is the grid resolution in the direction of the neighbor corresponding to weight w i , e.g., Δx 5 = Δz.Note that the indices correspond to those displayed in Fig 2 .For the more general orthotropic diffusion, the stencil for numerical differentiation includes the nearest and diagonal neighbors of a grid point, see Fig 2,panel (b).The weights for orthotropic diffusion are obtained by a combination of central differences approximations to derivatives and linear interpolation of values between two grid points.For more details, the reader is referred to the documentation of Geometry_OrtAniso.
Implementation
The source code of Ithildin is written in the C++ programming language, following the 2011 version of the ISO-C++ standard [8].This was chosen to facilitate programming at a level relatively close to the hardware, but also using some of the useful data-structures that are contained in the standard template library (STL).
Ithildin is designed to run in parallel on multiple CPU cores using MPI, specifically Open-MPI [13].Using the mpirun command, multiple instances, also known as processes, of the same compiled executable are started that run across different processor cores.The processes are then coordinated such that there is one so-called manager process, that manages a bunch of so-called worker processes.The manager does an equal share of the computational work, just like a worker.The only difference is that the manager distributes and directs information to be exchanged from one process to another.In Ithildin, the memory is not shared across processes, instead each process works on its share of the computational domain.We split the domain in the x-direction, such that each process is responsible for computations on a roughly equal share of vertices inside the to-be-simulated medium.Even when some parts of the domain are classified as exterior points, i.e., points on which no calculations need to be performed, they are taken into account when splitting the domain between processes.This splitting is possible because the reaction-diffusion systems to be studied with Ithildin are local, meaning that the temporal evolution at each time t and each point x in space depends only on the current state vector uðt; xÞ at that position and its spatial derivatives (Eq 2).Internally, a layer of so-called ghost points is added around each process' part of the domain such that the spatial derivatives can still be calculated in the same way as for any other point in the domain (section 2.3).The values u on these ghost points are exchanged with the neighboring processes, as coordinated by the manager process.Additional ghost points are also used to enforce Neumann boundary conditions, which is done by setting the weights for the calculation of the numerical spatial derivatives accordingly.
To run a simulation in Ithildin, the user needs to define a main() function that is to be called by all subprocesses.This is usually done using a C++ file calling the required components of the Ithildin library defining the main() function, a so-called main file.Ithildin can be installed as a shared library on Unix-based systems that is required by executables obtained from compiling main files.Alternatively, it is also possible to statically compile the Ithildin library with a main file into a stand-alone executable.
Besides the necessary preparations for using MPI, running a simulation using Ithildin's Sim class requires three main components, which are instances of three classes: 1. Model: the reaction term r ðuÞ, typically a cell model, 2. Geometry: the discretized diffusion term P r � Dru for a chosen geometry of the medium, and 3. Source: the stimulus protocol to use as well as inhomogeneities in the medium.
In the following section 4, an overview is given for each of these classes and their derived classes.Combining all of the components, an illustrative, minimal main file can be obtained, in which a planar wave crosses the medium in positive x-direction: More detailed examples for main files can be found in the S1 Appendix, where we set up the numerical examples used throughout this paper.
We consider the geometry, the model and the source to be the inputs of Ithildin, see also Fig 1. Upon running the simulation, Ithildin produces a variety of outputs, as files in easy-toparse standardized data formats.The names of these files all begin with the so-called stem, consisting of a descriptive series name and a serial number, which defaults to a time-stamp.In the following, an overview of the usual output files of Ithildin by suffix appended to the stem is provided: • _log.yaml:The log file contains metadata describing the setup of the simulation, as well as metadata about the conditions under which the simulation was run.This file is always output by Ithildin and is considered the central file of the results, as it points to the relevant other files that are only conditionally written during the simulation.While earlier versions of Ithildin used a non-standard format for the log files, in current versions, the YAML format is used, making it easy to parse by both: humans and machines [15].
• _main.cpp:A copy of the C++ code in the main file may be included in the results for reproducibility.
• _git.diff:If run in a Git-repository with changes since the last commit, a patch file of these changes will be included in the results.
• _*.txyz.npy:For each of the state variables u, a so-called var file in the NumPy NPY format will be written [16].These files contain the N+ 1-dimensional floating-point number array of the evolution of a state variable u in the whole computational grid over time.Note that the order of indices is (t, x, y, z), meaning that time is the slowest varying index and the x-axis the second slowest varying index.This order was chosen because the domain is split across processes along the x-axis, such that the processors can open and write to these files sequentially.For 2-dimensional simulations, the third spatial dimension, the z-axis, is one vertex thick, such that each var file still has four dimensions.For higher-dimensional simulations, more axes are added, leading to more dimensions in the var files.
• _inhom.txyz.npy:The inhom field, see details in section 4.3, is also stored in the NPY format, but with integer values, and only for the initial time-step.This file hence has the shape (1, N x , N y , N z ) with N n denoting the number of vertices in each of the spatial dimensions.
• _hist*.csv:Comma-separated value (CSV) files describing the temporal evolution of uðt; x s Þ at a chosen sensor position x s 2 O � R N , see details in section 4.5.
• _egm*.csv:CSV files containing the recorded pseudo-EGM F(t, x e ) at a chosen electrode location x e 2 R N , see details in section 4.6.
• _tipdata.yaml:This YAML file is written if filament-tracking is turned on, see also section 4.7, and contains the detected phase singularities in regular time intervals.
While we have selected these file formats to be easy to read using a wide variety of software, we have also developed the Python module for Ithildin to facilitate interacting with the results of an Ithildin simulation and converting them to a variety of file formats, for instance writing files in the extensible data model and format (XDMF) that can be used to view simulation results in ParaView [17,20,26,27].The Python module also offers post-processing and analysis methods, for instance the computation of action potential duration (APD), conduction velocity (CV), various phases, phase defect detection, functions acting on filaments and filament trajectories, and several plotting functions [17,26].
Diffusion term
The diffusion term in the reaction-diffusion equation (Eq 2) is stated as P r � Dru.The conduction in cardiac tissue and hence the diffusion is stronger along the fiber direction than normal to the fibers [2].This is encoded in the diffusion matrix D.
As an example, in Fig 3, the fiber direction is drawn on the surface of the ventricular geometry used in Sim 4. The fibers are additionally colored by their fiber helix angle [28].The voxelbased representation of this geometry was obtained by cutting a human heart into 1 mm-thin slices, digitizing and stacking them [29,30].
While the projection matrix P is managed by the Model class, see section 4.2, the diffusion matrix D and the handling of the spatial derivatives is implemented in the Geometry class.The most important things the Geometry class takes care of, are: • Initialization of the computational grid, along with the strides and pointers, which are important for efficient computing; • Computation of the entries of the diffusion tensor, based on the main directions of diffusion and the respective diffusion values; • Computation and storage of the weights for the stencils of the numerical spatial derivatives (section 2.3) respecting the Neumann boundary conditions; and • Handling the upper bound for the time step due to the CFL condition (section 2.2).
The Geometry class is a base class and should not be used directly to construct a computational domain.Instead, there are several subclasses, each representing a different type of diffusion or extrinsic shape.An overview of the Geometry subclasses is given in Table 2.
The Geometry_ND class is a subclass of Geometry_Iso and the Ellipsoid, Hyperboloid, and Paraboloid classes are subclasses of QuadricSurface.The details on how the extrinsic and intrinsic curvature affect the diffusion tensor and hence the weights for the discretized differential operator, are discussed in the documentation of the code.There, the different ways to initialize the available domain types are given as well.
Note that some additional features are implemented in the Geometry class, that do not have a direct link with the diffusion term, such as inhomogeneities (section 4.3) and filament detection (section 4.7).
Reaction term
The Model class serves as the base class for all cardiac electrophysiology models in the Ithildin framework.It encapsulates common functions and variables used across different models.Key features of the Model class include: • Implementation of the reaction term r ðuÞ in the reaction-diffusion equation.
• Storage of model-specific metadata such as relevant citations.
• Handling of variable-related information, including their names, indices, and resting values.
• Management of the values of the projection matrix P .
Derived classes extend the Model class to implement specific cardiac electrophysiology models in the reactionterm function.
An overview of the cell models that are currently included in the source code of this project is provided in Table 3.More models may be added as additional classes.
The Ithildin framework also introduces several ModelWrapper classes that provide additional functionality and allow for the combination of models.These wrappers enable the recording of diffusion terms, reaction terms, local activation times (LAT), and local deactivation times (LDT) as additional state variables.This is done by adding code to the reaction term calculations of the underlying model.The wrappers inherit from the base ModelWrapper class, which is a wrapper that leaves the model unchanged.The primary ModelWrapper classes are: • ModelWrapper_RecordDiffusion records diffusion terms of selected variables as additional variables.• ModelWrapper_RecordReaction records reaction terms of selected variables as additional variables.
• ModelWrapper_RecordActivationTime records LAT for selected variables.
• ModelWrapper_RecordDeactivationTime records LDT for selected variables.
• ModelWrapper_RescaleTimeSpace linearly rescales the wrapped model in time and space.
• ModelWrapper_RescaleVars linearly rescales selected state variables of the wrapped model.
The Model_multi class enables the combination of multiple submodels into a single model.The behavior of the combined model may vary depending on the location x and is determined by one of its submodels.Which model is to be used depends on the integer value of the inhom field, which is used to describe spatial inhomogeneities, such as obstacles.Inhomogeneities will be further explained in the following, cf.section 4.3.This class is particularly useful for simulating scenarios where different regions of cardiac tissue exhibit distinct behaviors.
The Ithildin C++ framework provides a structured and modular approach to modeling cardiac electrophysiology.The Model class serves as the base for different models, while various ModelWrapper classes and the Model_multi class offer extended functionalities for recording and combining different model aspects.
Inhomogeneities
In simulations of cardiac electrophysiology, accurately modeling the spatial properties of the cardiac tissue is essential.Inhomogeneities represent variations in the tissue's characteristics, such as its electrical conductivity or cellular properties, that influence the propagation of electrical signals.
An inhomogeneity in the Ithildin framework is a distinct region within the simulation domain with different properties compared to its surroundings.In the context of cardiac electrophysiology, these properties could correspond to variations in the electrical conductivities of cells, cellular properties, or even the absence of excitable cells altogether.Inhomogeneities are defined by an integer field called inhom associated with each point in the domain.Grid points with a non-zero inhom value are considered interior points, indicating that the reaction-diffusion equation needs to be solved on these points.If the selected reaction term is a Model_multi (see also section 4.2), for an inhom value of n, the nth submodel will be used for this point.For example, in To incorporate inhomogeneities into the simulation, the framework provides methods to add them to the domain.These methods allow specifying the shape, location, and properties of each inhomogeneity.For example, a rectangular inhomogeneity could be added by specifying its width, height and location.
Stimulation protocols
Ithildin provides a flexible way to define stimulation protocols using the Stimulus and Trigger classes, as well as the scheduling functionality of the Source class.
The Stimulus class enables the specification of temporal and spatial characteristics of voltage-based or current-based stimuli.It allows defining which state variables should be affected directly, the associated values, and whether the stimulus sets the variable directly or whether it is additive and hence behaving like a current source.Temporal modulation of stimulus strength is achieved through the amplitude function, while spatial constraints are managed by the shape function, an instance of the Shape class.
The Shape class describes a geometric shape via its characteristic function which can be used to define regions of interest in a simulation domain.The core principle is that the function evaluates a given position vector and returns a value: 1 if the position is inside the defined shape, and 0 if it is outside.However, values in the range [0, 1] may also be used to create a smooth transition.A smoothly varying characteristic function may be useful to create morerealistic stimuli that deposit current in a smooth profile.This simple yet powerful concept forms the basis for constructing intricate spatial configurations.
The Shape class provides several pre-defined shape functions, though additional shapes can easily be added by defining a characteristic function: • Ellipsoid: Defined by radii, a center and optionally the Euler angles, this shape represents a general three-dimensional ellipsoid with the specified orientation.
• Sphere: A special case of an ellipsoid where all radii are equal, forming a three-dimensional sphere.
• Ellipse in xy-plane: This two-dimensional shape resembles an ellipse lying on the xy-plane, defined by radii and a center.
• Cylinder along z-axis: Representing a three-dimensional cylinder centered along the z-axis, this shape is defined by a radius and a center.In 2D, it defines a disk.• Rectangular cuboid: Defining a three-dimensional region, this shape is specified by two opposing corner points, creating a cuboid.In 2D, it defines a rectangle.
• Half plane: A plane defined by an origin and an outward normal vector splits the threedimensional space into a half-space.In 2D, a straight line splits the plane in a similar way.
Characteristic functions can also be loaded from files in the NPY format [16].This feature facilitates the incorporation of custom shapes derived from external data sources.
The scheduling functionality via Source::schedule offers the ability to execute functions at specified points in time during the simulations.This feature greatly enhances experimental flexibility by allowing the execution of arbitrary code snippets at chosen moments during simulations.The scheduler is especially useful for introducing dynamic changes to the simulation environment, such as modifying stimuli or conditions midsimulation.
The Trigger class provides a means to orchestrate actions based on specific conditions.Triggers encapsulate the decision-making process of when to execute a particular action, influenced by condition checks and coordination modes.Different coordination modes allow for the synchronization of trigger actions across multiple processes, facilitating complex simulations of activation waves.These modes are to trigger on each process individually once the condition is met, once the condition is met in a specific process, once the condition is met in any process, or once it is true in all processes.
Within the framework of cardiac electrophysiology, triggers are essential for defining stimulation protocols, e.g. for the S1S2 protocol, which is illustrated in Fig 5 : After a first excitation wave passes a sensor position, a second wave is triggered behind a part of the first waveback to stimulate spiral waves.
Recording temporal evolution of variables at sensor positions
Besides the sensors for triggering stimuli, sensors in the context of this simulation framework are components that monitor and record the state variables of the simulated system at chosen positions during the simulation.We call this the history at a given sensor position.
These sensors are used to gather data about the behavior of the system at particular time intervals, regulated by the sensorlag parameter.This parameter controls the frequency at which sensor data is collected, allowing for flexibility in recording intervals.Notably, the recording frequency set by sensorlag need not align with the simulation's time step or the duration between frames.The data will be recorded at the first time step after the specified sensorlag duration.This high-resolution temporal data can be used to study individual points in the medium in detail.
The recorded data are then written to designated comma separated value (CSV) output files associated with each sensor.These files are used to store the collected data over the course of the simulation.
The first four panels of Fig 6 contain time traces of the transmembrane voltage u, the restitution variable v, the recorded value of the diffusion term, and the LAT at a given sensor position for Sim 1.The times of the three stimuli are indicated by the black vertical lines.The other panels will be explained in the subsequent sections.
Pseudo-EGMs
The EGM is a measurement of the potential generated by the charge distribution in cardiac tissue over time at a point in space, outside the tissue.In theory, this is a measurement of the extracellular potential F e .However, since Ithildin is a monodomain solver, the extracellular potential is not part of the model equations [2].The code therefore calculates an approximation of the extracellular potential at points outside the mesh using the Egm class.To obtain this approximation, the pseudo-bidomain theory is used [48].The approximation, referred to as a pseudo-EGM, uses the simplifications that the intracellular and extracellular conductivities are proportional, such that there is an explicit formula to calculate the extracellular potential, and that the bath conductivity is homogeneous.The first and third row display the transmembrane voltage u at selected frames in time, and the second and fourth row the state space phase [17,47].The first stimulus is applied in the first frame in the hatched region at the left edge.The sensor location is marked with a cross.Right after the third frame, the sensor triggers the second stimulus in the hatched region at the bottom edge.A spiral wave forms.The phase singularity at the center of the spiral is tracked as the white curve, which is dotted for the entire trajectory of the phase singularity, and solid for its trajectory since the previous frame.The extracellular potential F e at position x e over time is then calculated as: where O denotes the computational domain, i.e., the simulated heart muscle tissue, u is a state variable of the model representing the transmembrane potential, which is usually encoded as the first variable in the state vector u .Furthermore, D is the diffusion matrix from the reaction-diffusion equation (Eq 2), and τ e is a proportionality factor with units ms.
Essentially, the used approximation for the EGM is a convolution of the diffusion term r � Dru for the first variable with a kernel kx e − xk −1 .Depending on the choice of the diffusion tensor, made by the user in the Geometry class (section 4.1), a different prefactor of the integral is required.Hence, the prefactor t e 4p is user-defined and can be changed using the function set_prefactor.
The integral in Eq 13 is discretized and its calculation is implemented such that the additional amount of storage and number of calculations is limited as much as possible.For instance, as the required diffusion term r � DrV m is already computed during the forward stepping of the reaction-diffusion equation, it can be stored as an additional state variable using a ModelWrapper_RecordDiffusion and subsequently used in the pseudo-EGM calculation.This model wrapper is essential for the functioning of the Egm class and hence is a requirement when setting up a simulation with pseudo-EGM calculation.
The result is a CSV file with the pseudo-EGM data for each electrode that is defined by the user.The computed pseudo-EGM at a given position for Sim 1 is displayed in the fifth panel of Fig 6.
Filaments
Formally, filaments can be understood as a line of wave break, i.e., a line where an activation and recovery surface come together [49,50].The activation surface can be seen as the wavefront, while the recovery surface can be seen as the waveback.When considering an excitable system in 2D, filaments become tips, being the point of intersection between the activation and recovery curve.Since a point cannot be excited and recovering at the same time, points on a filament are also called phase singularities.
Using this definition of filament points, detection algorithms have been designed.Our code relies on the one described by Fenton et al. [3].Additionally, this algorithm has been extended to grids in any dimension, where the generalization of filaments are called superfilaments [31].
The filament point detection algorithm is included in the Geometry class.Its goal is to compute the points where the wavefront and waveback meet.While looping over all coordinate planes and grid points, it is checked whether there is an intersection of isolines in the adjacent voxel faces of a grid point.The location of the filament point is then estimated by bilinear interpolation.An illustrative sketch of this method is given in Fig 7.
The last panel in Fig 6 displays the number of rotors over time for Sim 1, which are found via filament detection.It can be seen that at the S2 stimulus, a single rotor is formed, and subsequently pairs of rotors as figure-of-eight spiral pairs.More details of this process can be seen in Fig 4 which shows the trajectories of these filaments in Sim 1 tracked using the Python module for Ithildin.The trajectories are colored by time and the formation of a new tip is denoted by stars and their decay by crosses.Tips that still persist at the final frame of the simulation are indicated by points.The tip trajectory denoted with index 0 is formed by the S1S2 protocol and meanders around the medium.It persists until the end of the simulation.The figure-of-eight spiral wave pair denoted by indices 1 and 2 is formed by a conduction block breaking up.The spiral tip with index 2 runs into the boundary to disintegrate there.
Phase defects
While a phase singularity can be seen as points where all phases meet-in mathematics called a pole, a phase defect is a point at which there is a discrete jump from one phase value to another in an otherwise continuously varying phase.While phase defects are well known in physics, they were only recently identified in excitable media, within linear-core rotors and conduction block regions [47,51].Phase defects are lines in 2D and surfaces in 3D.
In Ithildin, the phase defect detection is done with its Python module.For instance, during simulation, Ithildin can record the local activation times (LAT) which can then be used to compute the activation time phase in post-processing [17,47].A variety of methods exist to then localize the phase defect [17,51].
Two examples for phase defect detection in Sim 1 are given in Figs 8 and 9.Both display four frames over time of the transmembrane voltage V m , the activation time phase φ, and the phase defect % computed via the cosine method [17,51].In Fig 8, the phase defect of a single spiral wave is tracked.It can be seen that the phase defect extends due to conduction block such that the spiral wave moves across the domain.In Fig 9, the break-up of a conduction block line into a figure-of-eight spiral wave pair can be seen.The conduction block line is a phase defect of zero topological charge [52][53][54] which, in this case, reaches a critical length breaking apart into two oppositely charged spiral waves with much shorter phase defect lines. In
Further documentation
More complete documentation of Ithildin can be generated with Doxygen [14] and can be also found online, see the data availability statement for details.The documentation contains detailed information on how to get started installing and working with Ithildin.
Results
Ithildin is used for numerical experiments in various use cases.For instance, it was used to study the structure of the core of rotors emerging in in-silico cardiac-electrophysiology cell models, leading to the description of phase defect lines [17,47,54,55].Also, higher-dimensional rotors waves were simulated and the emerging super-filaments were detected using Ithildin [31].In the creation of novel data-driven cell models using state space expansion, Ithildin was used to generate synthetic training data sets [26].
Five simulations were conducted for this paper to illustrate the features of Ithildin.An overview of the simulations is given in Table 4, along with references to the figures that were generated with these data sets while details on their simulation setup can be found in their C++ code in the S1 Appendix.
Cardiac electrophysiology benchmark
Niederer et al. proposed a benchmark problem that is now used by the in-silico modelling community to validate and compare cardiac electrophysiology solvers [56,57].Ithildin passes the benchmark as implemented in Sim 5.In the benchmark problem an excitation wave travels through a cuboid-shaped medium following the cell model by Ten Tusscher and Panfilov (2006) [46].In Fig 11, we present the results from the benchmark in a similar way as in the original publication introducing the benchmark [56]: Point P 1 = [0, 0, 0] T is the corner of the cuboid where the stimulus is applied and P 8 = [20, 7, 3] T mm the furthest-away opposite [17,51] can be computed (middle row).Where this phase is discontinuous, a phase defect is localized.This is visualized as the phase defect density % (bottom row).In these four frames, a single rotor is tracked shortly after its formation.Due to conduction block, which can be seen as an extended phase defect line, the spiral moves through the medium.Afterwards, the spiral remains mostly stationary, leading to a shorter phase defect line.https://doi.org/10.1371/journal.pone.0303674.g008corner.Consider the plane going through P 1 and P 8 as well as P 10 = [0, 7, 1.5] T mm.We call the distance along the long axis of the plane slicing through the cubioid ξ 1 and the short axis ξ 2 .In the panels (a), the LAT on this plane is shown for the benchmark simulation at high and low resolution in space, Δx = 0.1 mm and Δx = 0.5 mm respectively, at the same temporal resolution Δt = 0.005 ms.Panel (b) also shows the LAT on the line from P 1 to P 8 for the different spatial resolutions Δx 2 {0.1 mm, 0.2 mm, 0.5 mm} at the same temporal resolution.In panel (c), the LAT value at P 8 is compared across all the combinations of spatial and temporal resolution.Just like for most other solvers which are compared in the benchmark paper, it can be seen that at the coarsest spatial resolution, the excitation wave is slowed down significantly in the transversal direction [56].Similarly to the other finite-difference solvers, the simulation fails at Δt = 0.05 mm and Δx = 0.1 mm [56], due to numerical instability.When a check of the CFL condition is enabled (Eq 5), Ithildin suggests to lower Δt to 0.03 ms given this spatial resolution, leading to a simulation at which no instability is observed.
Panel (d) of Fig 11 shows the speed-up in computation time from parallelization by comparing the computation time for Sim 5 at Δx = 0.2 mm and Δt = 0.01 ms on an 8-core Intel i7-10875H processor using 1, 2, 4, and 8 processes.In the double-logarithmic plot, it can be seen with linear regression that the computational speed increases almost linearly going from one to four processes, t sim / N À p proc with p � 1. Going to eight processes leads to diminishing returns, resulting in a smaller speed-up in computational time, as the overhead due to the boundaryexchange between processes grows.On this system using eight processes, at Δx = 0.2 mm and Δt = 0.01 ms, solving the benchmark problem takes 65.733 s of computation time in Ithildin, while it takes 611.231 s in cbcbeat [58].For both codes, we have turned off output to the disk and included the initial setup of the problem, such as compilation and memory allocation.
Discussion
The Ithildin framework is a tool for the simulation of cardiac electrophysiology.The code offers a number of assets that allow for simulations targeting a variety of phenomena.For example, there are many instances available to set the local anisotropy of the myocardium via the Geometry class.Please refer to the example presented in section 4.1 for further details.The Geometry class also allows for the simulation and filament tracking in a domain with an arbitrary number of spatial dimensions [17,31,47,54,55].
These include the ability to define inhomogeneities, which can be used to model domains of any shape and with any kind of obstacles.This is used in Sim 1 and Sim 4. Furthermore, the user can define a variety of stimulation protocols, of which some are showcased in the example simulations.We also note the following options: EGM calculation, the possibility of recording the temporal evolution of variables at sensor positions, and the Python module for post-processing and analysis.
It is evident that Ithildin represents but one instance of software designed for the simulation of cardiac electrophysiology.Another finite-differences solver is BeatBox [59], which also relies on domain splitting.A non-exhaustive list of examples of established simulation software based on the finite element method (FEM) are Chaste [60], openCARP [61], lifex-ep [62], cbcbeat [58], GEMS [63], CEPS [64], and simcardems [65].Besides the methods of finite differences, elements, and volumes, approaches from computational fluid dynamics such as the lattice Boltzmann method may be used [57].Several of these packages have more advanced features than our software.In addition, some have broader applications than cardiac electrophysiology.More software can be found in [56].
Limitations of our software are the fact that, in the context of cardiac electrophysiology, Ithildin only supports the monodomain model as it is a reaction-diffusion problem conforming with Eq 2, and the fact that the domain decomposition happens solely in one coordinate direction.Further limitations are that Ithildin is fundamentally voxel-based and hence does not support tetrahedral meshes, and that only Neumann boundary conditions are implemented.Additionally, it is only maintained by a small research team.This paper serves to enhance the visibility of the software and to invite fellow cardiac modelers to use and contribute to the project.We believe that the GitLab environment is an effective medium for facilitating interaction between users, identifying issues and suggesting improvements.
Our work with Ithildin has demonstrated its ability to study complex wave patterns in cardiac tissue [17,26,31,47,54,55], but it is important to acknowledge the limitations of the fully explicit numerical scheme used: High resolution in time and space may be required for numerical stability.Nevertheless, there are use cases where Ithildin is practical in the context of clinical applications.For example, it can be used to study rotor waves and their implications for cardiac function, which have important implications for diagnosing and treating cardiac diseases.Additionally, Ithildin can be used to develop new models or simulations that are tailored to specific experimental conditions or clinical scenarios.
Conclusion
In this work, we introduced Ithildin, an open-source library that allows for numerical simulation and analysis of rotor waves.We demonstrated the versatility of Ithildin through a series of simulations, including spiral break-up in the Smooth-Karma model, the S1S2 protocol in the AP96 model, and 2D and 3D spiral waves in the BOCF model in ventricular geometry.Our simulations highlighted several key features of Ithildin, such as the different implemented geometries and reaction terms, inhomogeneities, and stimuli, as well as recording data such as the pseudo-EGM or filament trajectories.These findings contribute to the growing [56] and is implemented in Sim 5. To ease comparisons with the paper introducing the benchmark, we present our results in a similar style.In panels (a)-(c), we present the LAT in the medium at different spatial and temporal resolutions.Coloring according to LAT is consistent across these panels.In panel (d), we measure the computational speed of Ithildin at different number of used processes.A linear fit is shown in the double-logarithmic plot which excludes the data point at N proc = 8. https://doi.org/10.1371/journal.pone.0303674.g011understanding of rotor waves in cardiac electrophysiology and have the potential to inform future experimental and theoretical studies.
Overall, our work demonstrates the power of Ithildin as a tool for studying complex wave patterns in cardiac tissue.We hope that this library will be useful to researchers seeking to better understand the dynamics of rotor waves and their implications for cardiac function.
Fig 1 .
Fig 1.Ithildin can be used to solve reaction-diffusion problems in excitable media.Required inputs for the software are: the diffusion tensor and geometry of a medium-such as the heart muscle, a reaction term-the so-called model, and source terms-typically a stimulation protocol.Ithildin can then calculate the evolution of the model variables in the medium over time.During calculation, Ithildin records relevant spatio-temporal data and metadata, as well as detecting rotor cores as filaments.The data visualized here are taken from several simulations which will be discussed below.
Fig 4 ,
the inhom field for Sim 1 is visualized.Two different cell models are used for the values 1 and 2. The points where inhom has the value 0, are considered exterior points.The set of all interior points is the physical domain O.At the boundary of the physical domain, Neumann boundary conditions are applied.
Fig 4 .
Fig 4. Inhomogeneities in Sim 1.The field inhom describes where unexcitable obstacles or exterior points are located with the value inhom = 0 and which cell model is to be used inside if inhom > 0. This figure also visualizes the filament trajectories colored by time, cf.section 4.7.Birth of a tip is denoted by stars, their deaths by crosses, and tips that are still around at the end of the simulation by points.The three trajectories with the longest lifetime are numbered by indices 0 through 2. https://doi.org/10.1371/journal.pone.0303674.g004
Fig 5 .
Fig 5.The S1S2 protocol illustrated for Sim 2.The first and third row display the transmembrane voltage u at selected frames in time, and the second and fourth row the state space phase[17,47].The first stimulus is applied in the first frame in the hatched region at the left edge.The sensor location is marked with a cross.Right after the third frame, the sensor triggers the second stimulus in the hatched region at the bottom edge.A spiral wave forms.The phase singularity at the center of the spiral is tracked as the white curve, which is dotted for the entire trajectory of the phase singularity, and solid for its trajectory since the previous frame. https://doi.org/10.1371/journal.pone.0303674.g005
Fig 6 .
Fig 6.Extracted time traces of Sim 1.The first two panels (a, b) contain the model variables u and v, followed by data computed by model wrappers, namely the diffusion term r � Dru (c) and the LAT (d), at an interior point, cf.section 4.5.Panel (e) contains the pseudo-EGM at an exterior point, next to the 2D domain, cf.section 4.6.The last panel (f) contains the number of rotors detected via phase singularities, cf.section 4.7.The black vertical lines indicate times at which a stimulus was applied.https://doi.org/10.1371/journal.pone.0303674.g006 Fig 10, we present the final frame of Sim 4 in ventricular geometry, visualized with Para-View [20].It is colored by the normalized transmembrane voltage.Both, the classical tip and the phase defect surface are visualized.The spiral waves revolve around the phase defect surfaces.
Fig 7 .
Fig 7. Illustration of the filament point tracking algorithm.Each coordinate plane adjacent to a grid point (i, j, k) is checked for an intersection of two surfaces (purple and orange lines) which are usually isosurfaces of state variables in u .In this example, a filament point (white dot) will be found in the yz-face.https://doi.org/10.1371/journal.pone.0303674.g007
Fig 8 .
Fig 8. Phase defect detection for a single meandering spiral in Sim 1.By recording the activation times of the transmembrane voltage V m (top row), the activation time phase φ[17,51] can be computed (middle row).Where this phase is discontinuous, a phase defect is localized.This is visualized as the phase defect density % (bottom row).In these four frames, a single rotor is tracked shortly after its formation.Due to conduction block, which can be seen as an extended phase defect line, the spiral moves through the medium.Afterwards, the spiral remains mostly stationary, leading to a shorter phase defect line.
Fig 9 .
Fig 9. Phase defect detection during figure-of-eight spiral wave pair creation in Sim 1. Visualization in the same style as Fig 8.A long conduction block line breaks apart into two rotors.https://doi.org/10.1371/journal.pone.0303674.g009
Fig 10 .
Fig 10.Final frame of Sim 4 of the BOCF model in ventricle geometry.The classical filament is plotted as the purple lines.The phase defect surface is contained in the gray contour.https://doi.org/10.1371/journal.pone.0303674.g010
Fig 11 .
Fig 11.Results of the cardiac electrophysiology benchmark.The benchmark was proposed by Niederer et al. (2011)[56] and is implemented in Sim 5. To ease comparisons with the paper introducing the benchmark, we present our results in a similar style.In panels (a)-(c), we present the LAT in the medium at different spatial and temporal resolutions.Coloring according to LAT is consistent across these panels.In panel (d), we measure the computational speed of Ithildin at different number of used processes.A linear fit is shown in the double-logarithmic plot which excludes the data point at N proc = 8. | 11,041.8 | 2024-05-04T00:00:00.000 | [
"Engineering",
"Medicine",
"Computer Science"
] |
IEC 60909 and ANSI standards comparison with ASCC based fault calculations of Iraqi power system
Abstract The calculation of short circuit (SC) current has to be accurate because of their importance in power protection system’s design and to determine the capacity of the protective devices. Therefore, there are many standards and programs to estimate SC calculation. The aim of this paper is to provide further calculation methods’ understanding for determining SC current in PSS/E program. Here, the characteristics of SC at the busbars of Al-Nassiriya power plant; with 400/132 KV local transformers; which is part of Iraqi power system is analyzed using PSS/E program methods such as automatic sequence fault calculation (ASCC), IEC 60909 and (ANSI) standards. The finding of results comparison between the three methods refers that IEC standard result was the most accurate one in subtransient current calculation. This paper concludes that IEC have the best method to be followed in subtransient current calculations for Iraq power grid expansion studies and planning.
PUBLIC INTEREST STATEMENT
Calculating short-circuit current level is important for electrical power engineers to renew protection devices and assess stability.Several criteria have emerged to study fault current such as ASCC, IEC, and ANSI.
The electrical systems expansion and the calculation accuracy importance require the development of calculation programs to study the system performance explicitly.One of these programs is the PSS®E, which deals with all the criteria, taking into account the factors affecting current calculation.
ASCC calculates all faults related to each home bus before proceeding to the next one in the specified subsystem.
This research investigates a factual and realistic comparison of these standards using the PSS®E program for 400/132 kV Nasiriyah busbar which represents a part of Iraq electrical grid.The comparison shows proximity in results, but it is recommended to use ANSI when the system does not contain generators as machine reactance; however, when the system expansion is intended it is recommended to use the IEC because it is more accurate.
Introduction
Power Network represents dynamic system that may be a subject of various disturbances including short circuit (SC), which affects the performance of power system (Lakshmi Sankar & Mohamed Iqbal, 2015).Fault occurrence causes an increase of SC current creating undesirable impact on nearby parameters; protective devices malfunction and system stability.Within disturbance instant, protective equipment capacity must be proportional to disturbance level (Yousefikia, Gharibreza, & Baledi, 2015).Fault current and voltages of power system during disturbance are provided by SC calculations.SC modules are number of calculation algorithms to meet the various needs of SC analyses.
Applications of SC Modules are American National Standards Institute (ANSI)-C37 and International Electrotechnical Commission (IEC)-60909.They support conventional SC studies regardless of any specific standards.Output information of SC modules are essential in designing suitable protective relaying system, also to determine required interrupting capacity at each switching location.ANSI/IEEE std.141-Red Book-was introduced by ANSI in North America in 1986, which convoy C37; the parent standard.The standard is related ultimately to SC current calculation but immediately to suitable protective devices selection (Kaloudas, Papadopoulos, Papadopoulos, Marinopoulos, & Papagiannis., 2010).ANSI in conforming with C37.5 1979 standard Calculates: symmetrical fault MVA, symmetrical fault current, asymmetrical fault current, ANSI X/R ratio, and multiplying factor.IEC-60909 is the European counterpart, which is derived from German VDE Standard (Kaloudas et al., 2010;Rodolakis., 1993).It is concerned ultimately with protective devices sizing, but mainly with fault current calculation.Some of SC calculation algorithms are embedded in PSS®E module to meet various requirements of fault studies such as ASCC, IEC, and ANSI.These algorithms require a convergent power flow and for the simulation of unsymmetrical faults, sequence data of the system should be provided.
Using PSS/E in proper sequence could handle various investigations for planning studies and operating analyses of electric power system (Habbi & Alhamadani, 2018).As PSS/E represents an effective module and user pleasant tool to implement power system analyzes, it was chosen for simulating Nassiriya power plant with auto transformers 400/132 KV in this paper as it represents part of south region of Iraqi electrical power system (Lafta, Shalash, Abd, & Al-Lami., 2018).
When system evaluation process is to be established especially for system planned expansion, there is a need to adjust grid protection by using the appropriate method that calculates SC current with high accuracy; affecting protective devices ratings; to judge the "propriety" of system final configuration (Gallucci, 2018).
Most researches that use PSS®E to calculate SC current they apply ASCC algorithm, which is embedded as a default PSS®E SC current method of calculation (Choi, Park, Cho, & Lee, 2019;Ding, Ge, Cao, Qi, & Yang, 2011).However, IEC and ANSI had approved standard calculation of SC capability for protective devices.
Our paper introduces an important comparative study between these three methods; by developing faults which are fast and has high convergence (Jahanirad & Karam, 2017); and which of them is to be used by the Ministry of electricity in Iraq for future plan studies.This paper is structured as follows; Section 2 describes in general fault analysis in power systems.Section 3 demonstrates IEC 60909 standard, while ANSI standard is demonstrated in Section 4. Automatic sequence calculation-ASCC-is described in Section 5. Section 6 is comparing ASCC with standards in PSS/E application.The case study is in Section 7, and the obtained results in Section 8 which is concluded in Section 9.
AC fault current is named steady state or symmetrical fault current which is calculated using Equation (1).
Where V is the RMS voltage, Z represents circuit impedance that forms suitable output currents (Ahmedi & Azhari, 2018).
Aperiodic or Dc fault current is considered in Equation (2).
Where α is switching angle, and T is the reactance to resistance ratio.
Total SC current, asymmetrical fault current, is the sum of ac symmetrical component and aperiodic component as in Equation (3).
The corresponding root mean square value is: The mathematic equation relates the asymmetrical component to the symmetrical one is: Sequence voltages are: Adding the three rows of Equation (6) yields Equation ( 7) for 3 phase fault: But: Then: Figure 1 shows balanced three phase (3-PH) fault which represents severe type of fault and probability of occurrence is minimum (Najafi et al., 2011) that is solved as: Where the system voltages of symmetrical components are: Solving Equation ( 7) for line to ground (L-G) faults assume phase A is faulty: Then It is clear that the ratio X/R for line-to ground fault is: Transient conditions develop SC current I sc , depending on SC impedance Z sc : To calculate SC current, the sequence illustrated in Figure 2 is followed.
The earliest prospect of saved power flow must incorporate fault analysis data for all sequences to be handled together.This step minimizes error caused by mistaken fault analysis data update through matching data changes.
Solving power flow pre switching system provides the base for initiating conversion of generators and loads as constant admittance.The research methodology to study and comparing the results to judge which is suitable to use in developing Iraq power system is clarified at the flow chart shown in Figure 3.
3. IEC 60909 (Berizzi, Massucco, Silvestri, & Zaninelli, 1994;Das, 2012;De Metz-Noblat et al., 2005;International Standard Iec, 2016;Nedic, Bathurst, & Heath, 2007;Schlabbach, 2008;Sweeting, 2012) For low, medium, and high voltage, 3-PH ac systems with frequency of (50 or 60) Hz; this standard is applicable for SC calculation.Initial symmetrical SC current I k ″ is the rms SC current of the ac symmetrical component at the instant of the SC because a defined value is required and the ac component may decay for faults near the generator, while I dc is the decayed component of SC current.The same X/R ratio is useful to calculate dc SC component I dc as in Equation ( 13): Where Ik″ is the symmetrical SC current, f is the frequency, t is time.
The maximum instantaneous, peak, SC current is I p , which depends on X/R value and phase angle; R/X≈ cosØ; at fault starting can be calculated using Equation ( 14): is the rms value of ac symmetrical SC breaking current at contact separation' instant to open switching device which is evaluated using Equation ( 15): Where: µ is the minimum time of delay.
The most important differences from other SC calculation methods are the use of a voltage correction factor, as shown in Table 1, and impedance correction factors.
IEC SC current calculation activity in PSS/E version 32 needs additional data for demonstrating machines and transformers.Figure 4 shows main screen of IEC fault calculation in PSS/E with some parameters that can be selected.
ANSI
In PSS/E, this standard fault current calculation makes use of input data files that have fault locations, maximum operating voltages, and contact parting times; besides ignoring fault resistance.
This standard studies the original network twice: one using equivalent Thevenin resistance only and the other uses equivalent Thevenin reactance only to determine X/R at fault point which is useful for asymmetrical fault current calculation.This is achieved for subtransient and steady state SC current (IEEE, 2006;Lakshmi Sankar & Mohamed Iqbal, 2015).Correction factors of rotary machines' impedance have significant effect on SC calculation.SC current is calculated using two methods (Das, 2012): With prefault voltage V behind the transient reactance which is equal to the terminal voltage at no load; the calculated value of V/X is compared with symmetrical interrupting capability of the protective devices, as long as the circuit X/R ratio equal 17 or less, for three-phase faults.In this case, it is impossible that asymmetrical SC duty exceeds the symmetrical SC duty because the asymmetrical rating of the circuit protective devices exceeds the symmetrical capability.
b: X R >17 SC current' dc component may increase SC duty to the extent that exceeds protective devices rating.These devices might be instantly applied without calculating resistance, X/R ratio, and fault location (remote or local) of the system as long as V/X value doesn't exceed 80% of symmetrical interrupting capability of the protective switch.
When V/X is found and X/R ratio is known, then protective devices interrupting duty could be estimated by means of multiplying the resultant SC current by a suitable multiplying factor.The multiplying factor depends on: X/R ratio, protective devices contact parting time and decaying effects of ac and dc (Das, 2012).ANSI calculation of SC current activity in PSS/E needs the data of maximum operating voltages, fault positions, and contact parting times.ANSI main screen for fault calculation in PSS/E with some parameters that may be selected is shown in Figure 5.
Automatic sequence calculation (ASCC) (PSS/E, 2015)
ASCC offers automatic standard events coverage at all buses contained in a section of the system.Only three-phase and line-to-ground SC can be handled by ASCC.Line-connected shunt devices and charging capacitance can be included in the system model.Apparent impedance at each branch is calculated as follows: Where i seq , i phase represent current flowing through branch that include line-charging current and current of line-connected devices.
The reciprocal of apparent impedances represents apparent admittances.
ASCC uses existent full working case detail, and generator internal sources' setup is handled automatically to harmonize conditions just before disturbance application.Mutual and phase selfimpedances of each branch are assumed to be balanced when ASCC is applied.
If FLAT option of ASCC is chosen; then data of working case is ignored, all bus voltages are set to (1 + j0), all generator outputs; (PGEN + jQGEN); are set to zero and all phase-shift angles of transformer is to be zero.Beside setting all loads to zero, load current before and after event solution, is ignored.
Data need is specified according to various fault and report options in SC calculation activities in ASCC. Figure 6 illustrates main screen of ASCC fault calculation in PSS/E.
Comparing ASCC with standards in PSS/E
Each method implements SC studies with PSS/E version 32; ASCC, IEC, and ANSI; requires specific input information, which may differ from one method to another beside those which may met in.
The input information that they met in some methods are shown in Table 2, and input information dissimilarities are shown in Table 3.Each method owing its output information is presented in Table 4.
Case study
Nassiriya power station is taken as the case study of this paper which have busbar number (25,403) of 400KV that is connected to Nassiriya (4 × 210 MW) power plant and (1 × 40 MW) on 132KV side is connected to busbar number (25,304).SC response has been studied for (L-G) fault and (3PH) fault on busbars (25,403) and (25,304).ANSI C37.5, IEC 60909 standards and ASCC are used to analyze SC response of the system.
Results
It is obvious from previous sections that ASCC doesn't deal with DC components thus asymmetrical current is not calculated in this method.
For Nassiriya power plant as part of 400 KV, grid is examined with 3-PH and single L-G fault occurrence.SC current results, X/R ratios and factors associated with standards and ASCC is shown in Table 5 and the results is clarified in Figure 8, which illustrates that the maximum X/R and factor values was used by ANSI for L-G fault while the maximum asymmetrical current occurs during ANSI appliance in case of 3-PH fault.
ASCC
Transformer phase shift angles are assumed to be zero.Any transformer impedance, which is a function of phase shift angle, is assumed to be at nominal value.
Transformer turns ratios are assumed to be one.
Voltage factor c = 1.05 for bus base ≤1 KV and c = 1.1 for bus base >1 KV.IEC Zero Sequence Mutual Impedances and Grounding Impedances with R = 0 Not SCaled Using SCaling Factors.
ANSI
Zero Sequence Mutual Coupling Unchanged.
For machines in positive and zero sequence network = 80.
For branches in positive and zero sequence network = 40.
Protective switches are rated on a total current basis.
Output Format = Summary output using ANSI R and X or consider X Only.
Account for both Ac and Dc decrements (Fault multiplying factors).
Table 2. Input information that are common in some methods of fault calculation in PSS/E
Input information Fault calculation methods
Set generator positive sequence reactance to synchronous or sub transient/ transient.
Transformer tap ratios and phase shift angles unchanged.Instantaneous SC current are calculated for a series of faults with and without including initial system conditions ASCC For Line End (LEND) fault cases, in addition to selection of fault to display and display quantity, specify the branch connected to faulted bus whose far end (from faulted bus) is being faulted.
For Line Out (LOUT) fault cases, in addition to selection of fault to display and display quantity, specify the branch or three winding transformer that is intentionally outage.
Contour diagram of maximum fault current at each faulted bus considered.
Total fault current and fault current contributions at home bus.
Total fault current for all faulted buses and for all fault types considered.
Initial symmetrical SC current I″k in (r.m.s) including phase and sequence.
IEC components of fault current: ip(B) Peak SC current using method B of IEC standard 60909.ip(C) Peak SC current using method C of IEC standard 60909.ib(DC) DC component of asymmetrical breaking current using method C R/X ratio.ib(ASYM) Asymmetrical breaking current (r.m.s.).ib(SYM) Symmetrical breaking current (r.m.s.).
L-G fault results: symmetrical fault current (kA), asymmetrical fault current (kA), multiplying factor, and the ANSI X/R ratio.
ANSI
L-L-G fault results: symmetrical phase current (kA), and three times the zero sequence symmetrical fault current (kA).
The positive sequence Thevenin impedance as obtained from the decoupled positive sequence admittance matrices.
The bus number, name and base voltage of the faulted bus, along with the maximum operating voltage and contact parting time input values.For Nassiriya, as part of 132 KV grid, Table 6 shows SC current results, X/R ratios and factors associated with standards and ASCC; corresponding to 3-PH and single L-G fault on Nassiriya 132 KV and results are clarified in Figure 9 which illustrates that the maximum X/R, highest factor, and maximum asymmetrical current occurs during the use of ANSI method.
The following types of faults are examined on Nassiriya 400 KV and132 KV.SC current and X/ R ratio of the connected buses to the faulted bus in ANSI, IEC, and ASCC are shown as below: (1) Three phase fault in Nassiriya 400 KV: results are listed in Table 7 and cleared in Figure 10 showing that the highest X/R value is within the use of both standards ANSI and IEC at Nassiriya busbar while during the application of ASCC, X/R high value is at Simawa busbar.The ultimate SC current value is also at Nassiriya busbar using IEC standard.
(2) Line to ground fault on Nassiriya 400 KV: results in Table 8 and clarified in Figure 11 showing that IEC SC current value is the highest at Nassiriya busbar.8.1.Fault on Nassiriya 400 KV (3) Three phase fault on Nassiriya 132 KV: the ultimate SC current value is by IEC usage as illustrated in Table 9 and Figure 12.
(4) Line to ground fault on Nassiriya 132 KV: also results ensure that IEC is the highest SC value at Nassiriya busbar as shown in Table 10 and Figure 13.As pointed out in the introduction that there are several programs which calculate the SC by both the ANSI and IEC standards.Lakshmi Sankar and Mohamed Iqbal (2015) reviewed the study of these standards by ETAP for thermal power station by testing the system at different locations such as bus network and bus generator.
It is important to compare Sankar and Iqbal results with the obtained PSS/E results for symmetrical and asymmetrical Fault; Single line to ground and for both the IEC and ANSI standards.
Table 11 shows the SC results of the IEC and ANSI standards by PSS/E for the same system and their results by ETAP in Lakshmi Sankar and Mohamed Iqbal (2015).Comparison results represent a convergent benchmark.
Conclusion
Paper results are obtained by using ANSI, IEC 60909 standards and ASCC using PSS/E version 32.Standards give methods to calculate symmetrical steady state current that is multiplied by a factor for the purpose of finding the peak value of asymmetrical current; ANSI output gives the value of that factor while it was a hand calculation in IEC in Tables 5 and 6.Giving that ASCC doesn't deal with dc current; thus asymmetrical current is not calculated in that method and also the factor.In L-G fault, X/R of Nassiriya 400 KV and 132 KV buses is not given by IEC method and was a hand calculation in Tables 8 and 10, respectively.
ANSI adjusts machine reactance using a multiplier; these multipliers don't take into account fault position and break parting time, while IEC recommends including parting time and making machine proximity to SC.
However, ASCC and ANSI are accepted methods for SC calculation.But when studies for the grid expansion are held, it is important to use IEC fault current calculation for its high accuracy resulting in a protected grid, as the instantaneous SC current are used for determining breaking capacity.
Figure 1.Three phase balanced fault.
Figure 2 .
Figure 2. Sequence of SC current calculation in PSS/E.
Figure 3 .
Figure 3. Procedure of finding SC current by the three methods IEC, ASCC, and ANSI in PSS/ E.
Figure 7
Figure7shows pwer flow in Nassiriya power plant interconnected to other buses.
Facts
and Dc lines are blocked.Impedance corrections to transformer zero sequence impedances are applied.Set pre-fault voltage on all buses to one Pu at zero phase shift angle.ASCC & ANSI Line charging represented in ± & zero sequences set to zero.Line/fixed/switched shunts and transformer magnetizing admittance represented in ± & zero sequences set to zero.Load represented in ± & zero sequences set to zero.ASCC & IEC Set induction machine positive sequence reactance to subtransient.
Figure 10 .
Figure 10.Buses SC current and X/R in ANSI, IEC and ASCC; for three-phase fault on Nassiriya 400 KV.
Figure 11.Buses SC current in ANSI, IEC and ASCC for L-G.
Figure 13 .
Figure 13.Buses SC current in ANSI, IEC, and ASCC for Nassiriya 132 KV L-G fault.
Table 3 .
Input information dissimilarities in fault calculation methods in PSS/EConstant power, current, and admittance loads are neglected in positive and negative sequence networks.Grounded loads are represented in zero sequence networks.
Table 4 .
Output information dissimilarities in fault calculation methods in PSS/E
Table 5 .
SC current, X/R and factors of faulted Nassiriya 400 KV in ANSI, IEC standards & ASCC
Table 7 .
SC current and X/R results in ANSI, IEC, and ASCC for 3-PH fault on Nassiriya 400 KV
Table 8 .
SC current and X/R ratios in ANSI, IEC, and ASCC for L-G fault on Nassiriya 400 KV
Table 11 .
Results of the IEC and ANSI standards by PSS/E and ETAP results for symmetrical and unsymmetrical Fault Table10.SC current and X/R results in ANSI, IEC, and ASCC for L-G fault on Nassiriya 132 KV | 4,828.6 | 2019-01-01T00:00:00.000 | [
"Physics",
"Engineering"
] |
Capillary Effects in Guided Crystallization of Organic Thin Films
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Guided crystallization of solution-processed organic semiconductor thin films via substrate patterning can enable the control of material properties with fine spatial resolution and be used to preferentially orient molecules along a given direction. 1,2Potential applications of guided crystallization on pre-specified templates include the fabrication of patterned optical coatings or conductive paths with arbitrary shapes 1 as well as dense arrays of organic thin-film transistors. 2In addition, the ability to control the alignment of organic semiconductor small molecules has been employed to study the effect of grain boundary orientation mismatch on electrical properties. 35][6] Spherulites are polycrystalline superstructures that are composed of crystalline grains of different orientations and grow outwards in a radially symmetric manner. 7Recently, it has been shown that the crystallization rate of TES ADT can be controlled by varying the substrate surface energy, allowing growth to be guided along patterns on the millimeter length scale, 1 but application of this technique to smaller length scales has not previously been studied.More fundamentally, exploration of crystallization confined along narrow paths provides an opportunity to probe thermodynamic and interfacial properties 8,9 in such molecular semiconductor thin films.Often such a<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>d<EMAIL_ADDRESS><EMAIL_ADDRESS>mhaataja@princeton.edu2166-532X/2015/3(3)/036107/5 information is not known for materials other than metallic alloys. 10An improved understanding of organic semiconductor molecular interactions and ordering behavior is also beneficial for better linking processing conditions to final structures. 11n this paper, we investigate how the rate of guided crystal growth in an initially disordered thin film along a pre-patterned two-dimensional (2D) channel of fixed width w is reduced with decreasing channel widths due to capillary effects.We first derive an analytical expression for the steady-state growth front velocity as a function of channel width and validate it against numerical simulations of a diffuse-interface model.We show that, below a characteristic channel width, capillary effects strongly affect crystallization.In particular, in the case of perfect confinement of the crystal growth front within the channel, this characteristic channel width determines the smallest feature size that can be achieved by guided crystallization.Finally, analytical results are employed to determine the characteristic channel width (given by the ratio of interfacial energy to bulk thermodynamic driving force) for solvent-vapor-annealed TES ADT from channel crystallization experiments.
Our starting point is the observation that the growth velocity normal to the interface ( n) of a crystallization front, V n , and its shape are affected by both interfacial and bulk thermodynamic driving forces 8,[12][13][14] Here, M( n) is a kinetic coefficient related to the molecular mobility (in general anisotropic) of an interface, γ( n) denotes the so-called interface stiffness 15 given by Γ + Γ , where Γ( n) denotes interfacial tension (in general anisotropic) and Γ ( n) its second derivative with respect to interface inclination, κ is the curvature of the interface, and E is the bulk driving force.For effectively isotropic systems (such as spherulites 16,17 ), the interface equation of motion simplifies to ( We note that bulk measurements of V n only report the product M E and not M or E independently.Now, for guided crystallization in the configuration shown in Fig. 1(a), Eq. ( 1) in steady-state reduces to w c V has eluded us, the dependence of V on w can be obtained in terms of an implicit formula without any approximations, 18 where Equation ( 2) constitutes the central analytical result of this paper.It can be readily deduced that (a) at the characteristic width w = w c = 2Γ E , growth becomes completely arrested due to capillary effects for r = 0, in agreement with exploratory simulations reported in Ref. 19.(b) For w w c , V → rV max .In this limit, growth is dominated by bulk crystallization outside the channel.(c) For w w c , V → V max = M E, as expected for bulk crystallization within the channel.(d) Perhaps most importantly, experimentally measuring V = V (w) and fitting to Eq. ( 2) allows the characteristic width w c = 2Γ/E to be determined.(e) Finally, a more convenient-yet-accurate approximation can be derived by assuming that the growth front takes on an elliptical shape, yielding 18 We note that in the limit where r = 0, indicating perfect confinement, Eq. ( 3) implies a simple scaling relation To validate Eq. ( 2), we turn to numerical simulations of a simple diffuse-interface model, 20 wherein a continuously varying order parameter φ(r,t) is introduced to track the locations of different phases as they evolve over time.The free energy of the system is described by a Ginzburg-Landau free energy functional that accounts for both interfacial and bulk free energies via F = dr As usual, the spatio-temporal evolution of φ is governed by the Allen-Cahn equation ∂φ ∂t = − M(r) δ F δφ = M(r) 2 ∇ 2 φ − ∂ f ∂φ .In the limit of a sharp interface between the phases, 13 this evolution equation leads to phase boundary motion described by Eq. ( 1) with spatially modulated M and constant Γ.
We numerically solve the diffuse-interface equations using finite differences and explicit time stepping on a uniform grid with non-dimensionalized parameters N y = 1500, Δx = 0.01, N t = 420 000, Δt = 2 × 10 −6 , M = 2 × 10 5 , 2 = 4 × 10 −5 , and m = 0.01.In our simulations, we model the effect of a surface-energy-defined channel by setting the molecular mobility M outside of the channel to be a fraction r = M out /M in of the mobility inside of the channel; the effects reported herein are the same if the bulk driving force were spatially modulated instead of the mobility.Note that in this paper, mobility always refers to molecular motion rather than to electrical mobility.We model the film as 2D and initialize the film in the metastable amorphous phase (φ = 0) everywhere except for a circular seed of the crystalline phase (φ = 1) at the center of the channel.
First, we perform simulations with r = 0.1 such that the emerging crystalline phase is only partially confined within the channel.Several simultaneously captured configurations of the crystalline phase for different channel widths are shown in Fig. 1(b).In these configurations, the crystalline phase is shown in gray, while the white regions correspond to the amorphous phase.It can be seen that the growth front is flatter and thus moves faster for wider channels.Figure 1(c) in turn shows that the velocity of the growth front is quantitatively described by Eq. ( 2) and approaches the outside growth rate rV max as w → 0. Finally, in the case of perfect confinement corresponding to r = 0, the growth front velocity vanishes below the characteristic channel width w c [cf. Fig. 1(c)].This observation implies that w c sets the smallest feature size that can be obtained via guided crystallization.
In order to observe these capillary effects experimentally, we tracked the crystallization of thin films of TES ADT on patterned substrates during solvent vapor annealing, following the experimental procedure outlined in the supplementary material. 18Since crystal growth occurs several times faster on SiO 2 than on pentafluorobenzenethiol (PFBT)-treated Au, crystallization can be guided along channels defined on the substrate by regions of SiO 2 surrounded by regions of PFBT-treated Au. Figure 2(a) shows optical micrographs of TES ADT as crystallization takes place along channels with widths of 75 ± 0.33 and 2 ± 0.33 μm during solvent vapor annealing, demonstrating qualitatively that growth velocity decreases for narrower widths.Since crystallization also proceeds on PFBT-treated Au regions, confinement of crystal growth to the surfaceenergy-defined channel is not perfect and leads to shapes that resemble those of the numerical simulations shown in Fig. 1(b).Furthermore, in solvent-vapor-annealed TES ADT, the crystalline phase is actually polycrystalline with many differently oriented grains separated by grain boundaries, 1 so the shape of the growth front is not completely smooth.To explore the effects of polycrystallinity and interfacial roughness on channel growth kinetics, we performed additional numerical simulations of the diffuse-interface model described in Ref.21, which has previously been applied to study growth of spherulites in organic thin films.We use non-dimensionalized parameters N t = 26 000, M max = 5 × 10 4 , Δt = 2.4 × 10 −5 , N y = 1024, Δx = Δ y = 0.01, 2 = 2 × 10 −5 , α = 0.12, δ θ = 0.2, Δ = 20, k B T = 1.6 × 10 −6 , l 2 = 3.2 × 10 −4 , and r = 0.1.Figure 2(b) shows simulated morphologies demonstrating qualitatively that capillary slowing is still observed for polycrystalline growth.In addition, Fig. 1(d) shows that across five independent simulations of polycrystalline growth, growth front velocity is quantitatively described by Eq. ( 2) within the scatter of the data.
Finally, we quantitatively compare the experimentally measured crystal growth velocity behavior against our theoretical predictions.To this end, Fig. 3 shows that for channel widths greater than approximately 20 μm, capillary effects are negligible and the growth velocity is effectively constant, but growth rate falls rapidly for smaller w.The solid blue curve in Fig. 3 shows a fit of the experimental data to Eq. ( 2) with rV max fixed to equal the average measured growth rate on PFBT-treated Au.The fit yielded a characteristic channel width of w c = 2Γ/E = 3.7 ± 1.2 μm, where the error bar represents a range of reasonable fits based on visual quality of the fit.
In order to estimate the physical value for E, we can use Turnbull's empirical formula 22 to estimate the solid-liquid interfacial energy of a material from its heat of fusion, giving Γ ≈ 7 mJ/m 2 for TES ADT.Since this represents only a rough estimate, 9,23 we can more conservatively hypothesize (based on the solid-liquid surface energies of several other organic compounds 23 ) that the TES ADT crystal-amorphous interfacial energy ranges from Γ ≈ 5 to 50 mJ/m 2 .Using this range of values for Γ along with the value for w c extracted from the experimental data, we find that the free energy difference between the as-spun disordered phase and the more stable spherulitic phase ranges from E ≈ 1.3 to 13 J/mol for TES ADT, corresponding to an equivalent undercooling of TES ADT of 0.05-0.5 • C. Interfacial mobility M in turn is estimated to range from M ≈ 1.3 × 10 −6 to 1.3 × 10 −5 m mol/J s for the same system.In summary, we have derived an analytical expression for interfacial velocity when a phase transformation is guided along a straight channel defined by differential growth rates.We verified our theoretical predictions with simulations of a diffuse-interface model and employed analytical expressions to extract the characteristic channel width (that is, the ratio of the surface energy of the crystal-amorphous interface to the bulk thermodynamic driving force for crystallization) below which capillary effects strongly influence crystallization in TES ADT.More broadly, we expect that our approach will enable the quantification of important material parameters for crystallization in a wide range of organic thin-film systems.
2 d 2 y/dx 2 [
FIG. 1.(a) Schematic of guided crystallization.Inside (outside) a channel of width w, the growth front propagates at velocity V (V out ) and adopts a curved (planar) shape.(b) Simultaneously captured steady-state growth morphologies from numerical simulations of isotropic single crystal systems with channel widths w/w c = 5.4, 2.0, 1.4, and 1.1 for leakage rate r = 0.1.(c) Normalized growth velocity as a function of w/w c .The blue dashed and red solid curves are fits to Eq. (2) for r = 0 and r = 0.1, respectively, while the black dotted line indicates V /V max = 0.1, where V max denotes the asymptotic growth velocity achieved for w/w c → ∞.(d) Normalized growth velocity from simulations of polycrystalline systems with five different initial conditions, for r = 0.1.The red solid curve again is a fit to Eq. (2).
FIG. 2 .
FIG. 2. (a) Optical micrographs of TES ADT crystallization show that crystal growth occurs preferentially on bare SiO 2 (green) compared to PFBT-treated Au substrate (orange).The crystal-amorphous interface is traced in white.Crystallization proceeds faster in the 75 ± 0.33 μm-wide channel (top) than in the 2 ± 0.33 μm-wide channel (bottom).(b) Numerical simulations of polycrystalline growth exhibit similar behavior.Colors represent differently oriented crystalline grains, while the yet-to-crystallize regions are shown in white.
036107- 5 FangFIG. 3 .
FIG. 3. Experimentally measured growth front velocity V as a function of channel width w.As w approaches zero, V approaches the growth rate on PFBT-treated Au, indicated by the thick gray line whose thickness indicates one standard deviation about the average.Horizontal error bars represent ±0.33 μm channel width resolution and vertical error bars indicate one standard deviation of velocity measurements.The solid blue curve is a fit to Eq. (2) and the light-blue dashed curves show Eq.(2) with w c = 2Γ/E = 3.7 ± 1.2 μm.
A.F. and A.K.H. acknowledge the National Science Foundation for Graduate Research Fellowships under Grant No. DGE 1148900.A.G. acknowledges the Princeton Environmental Institute through the Grand Challenges Program for summer funding.Y.-L.L. and J.E.A. acknowledge NSF funding through the SOLAR Initiative (Nos.DMR-1035217 and DMR-1035257) and Y.-L.L. acknowledges MRSEC funding through the Princeton Center for Complex Materials (No. DMR-0819860).The authors would also like to thank Dr. Srevatsan Muralidharan for helpful discussions and his contributions during the initial stages of this work. | 3,242.4 | 2015-03-19T00:00:00.000 | [
"Materials Science",
"Physics"
] |
Parallel Multi-Deque Partition Dual-Deque Merge sorting algorithm using OpenMP
Quicksort is an important algorithm that uses the divide and conquer concept, and it can be run to solve any problem. The performance of the algorithm can be improved by implementing this algorithm in parallel. In this paper, the parallel sorting algorithm named the Multi-Deque Partition Dual-Deque Merge Sorting algorithm (MPDMSort) is proposed and run on a shared memory system. This algorithm contains the Multi-Deque Partitioning phase, which is a block-based parallel partitioning algorithm, and the Dual-Deque Merging phase, which is a merging algorithm without compare-and-swap operations and sorts the small data with the sorting function of the standard template library. The OpenMP library, which is an application programming interface used to develop the parallel implementation of this algorithm, is implemented in MPDMSort. Two computers (one with an Intel Xeon Gold 6142 CPU and the other with an Intel Core i7-11700 CPU) running Ubuntu Linux are used in this experiment. The results show that MPDMSort is faster than parallel balanced quicksort and multiway merge sort on the large random distribution data. A speedup of 13.81\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times$$\end{document}× and speedup per thread of 0.86 can be obtained. Thus, developers can use these parallel partitioning and merging algorithms to improve the performance of related algorithms.
Sorting is a well-known algorithm that can be implemented in other algorithms to solve biological, scientific, engineering, and big data problems. The popular sorting algorithm is Quicksort 1 . It is an important algorithm that uses the divide-and-conquer concept to sort the data. It partitions the data into smaller sizes (divide) and then sorts those data (conquer). Basically, there are 2 steps in the Quicksort algorithm. The first step is partitioning, which divides the data using their pivot recursively into smaller sizes. This step runs until the data are smaller than the algorithm's cutoff size. Finally, the sorting step is executed to sort the data.
There are several works study in parallel sorting algorithm on multi-core CPU [2][3][4][5][6] , and branch misprediction and cache misses in parallel sorting algorithm [7][8][9][10] . It should avoid branch misprediction and reduce cache misses by improving locality while develop parallel sorting algorithm on multi-core CPU. These concepts are used to design our parallel sorting algorithm to improve its performance.
In this paper, we propose the parallel Multi-Deque Partition Dual-Deque Merge Sorting algorithm, which consists of three phases: the Multi-Deque Partitioning phase, which is block-based parallel partitioning. Each thread contains a double-ended queue (deque), which keeps the boundaries of each block. This phase partitions the data of each block and pushes the new boundaries of the partitioned data in the dual deque. Then, the Dual-Deque Merging phase is executed to merge data into the correct positions using the new boundaries of the dual deque without compare-and-swap operations. These two phases are recursively executed until the data are sufficiently small. Finally, the Sorting phase is executed to sort the data independently.
This work uses the OpenMP library 11 to execute the parallel sorting algorithm. There are several metrics to measure the performance of this algorithm and compare it with the sequential sorting algorithm, such as Run time, Speedup, and Speedup per thread. Moreover, we switch Hoare's partitioning 12 to Lomuto's partitioning algorithm in the Multi-Deque Partitioning phase. Finally, the Perf profiling tool 13 is run to measure the metrics to analyze the performance of this algorithm.
Our proposed parallel sorting algorithm uses the block-based partitioning concept which has the problem while merging the data in each block. Most of solutions compare and swap the leftover data to the middle of the array. Then, they use the sequential or parallel partitioning algorithm to partition it again. In this paper, Dual-Deque Merging phase is proposed as the main contribution to solve this problem to reduce compare-and-swap operations in the algorithm which consume run time. www.nature.com/scientificreports/ In this paper, the contributions are as follows: (1) the parallel sorting algorithm called the Multi-Deque Partition Dual-Deque Merge Sorting algorithm (MPDMSort), which contains Multi-Deque Partitioning, Dual-Deque Merging, and Sorting phases, is proposed. (2) The partitioning algorithms in the Multi-Deque Partitioning phase, such as Hoare's and Lomuto's partitioning algorithms, are compared. (3) Run time, Speedup, Speedup/core and thread, and other metrics that can be measured from the Perf profiling tool of MPDMSort, Parallel Balanced Quicksort, and Multiway merge sort are compared and analyzed. We organized this paper as follows: Background and related work are shown in section "Background and related work". The Multi-Deque Partition Dual-Deque Merge Sorting algorithm is proposed in section "Multi-Deque Partition Dual-Deque Merge Sorting algorithm". Section "Experiments, results and discussions" shows the experiments, results, and discussions of parallel sorting algorithms. Finally, the conclusion and future work are shown in section "Conclusions".
Background and related work
This section introduces a sequential standard sorting algorithm called STLSort and parallel standard sorting algorithms called Parallel Balanced Quicksort (BQSort) and Multiway merge sort (MWSort). Finally, we proposed and compared related parallel sorting algorithms. Sequential and parallel standard sorting algorithms. There is a sorting standard library function that can sequentially sort the data. STLSort 14 is an important sorting function in the C++ language. Developers can implement this function by declaring < algorithm > directive. It contains the Introsort algorithm, which consists of quicksort and heapsort. While the data are sufficiently small, the insertion sort is executed to sort those data.
There are two standard sorting algorithms in parallel mode. Parallel Balanced Quicksort (BQSort) 15 is the parallel sorting algorithm. It uses block-based partitioning concepts such as Tsigas and Zhang's algorithm 16 . Each block runs a compare-and-swap operation and swaps all leftover to the middle of those data. Then, the sequential partitioning algorithm is executed. Multiway merge sort (MWSort) separates data equally and sorts them independently. Then, a parallel multiway merge algorithm is called to merge the data in parallel. Note that it requires an array that is used to store the temporary data. This algorithm is more stable than the quicksort algorithm.
Related parallel sorting algorithms. The performance of many quicksort algorithms is improved by parallel algorithm techniques, which can be executed on shared memory systems. The parallel quicksort algorithm concept begins with partitioning the data in parallel. Next, the partitioned data are merged. While the data are smaller, they are sorted by any sorting algorithm independently.
In 1990, a parallel quicksort algorithm on an ideal parallel random access machine using Fetch-and-Add instruction was proposed 17 . The speedup of this parallel quicksort is up to 400× on 500 processors when sorting 2 20 data. Tsigas and Zhang 16 proposed PQuicksort in 2003. This sorting algorithm divides the data into blocks and neutralizes them in parallel. A speedup of 11× with a 32-core processor can be obtained. In 2004, the implementation of parallel quicksorting using pthreads and OpenMP 2.0 was presented 18 . A multicore standard template library was proposed 19 , which contains a parallel sorting algorithm that is similar to Tsigas and Zhang's concept 16 . A speedup of 3.24× is achieved on a 4-core processor. Then, a parallel introspective sorting algorithm using a deque-free work-stealing technique was proposed 20 . In 2009, Multisort, which is a parallel quicksort algorithm that partitions data, sorts them independently using quicksort and merges them in parallel, was presented 21 . A speedup of 13.6× is achieved when sorting data using this algorithm on a 32-core processor. Man et al. 22 proposed a parallel sorting algorithm named psort. It divides the data into several groups and sorts them locally in parallel. Then, those sorted groups of data are merged and finally sorted sequentially. Its speedup is up to 11× on a 24-core processor. Meanwhile, Parallel Introspective quicksort was developed and run on an embedded OMAP-4430, which consists of a dual core processor 23 . Its speedup is up to 1.47× . Mahafzah 24 shows a parallel sorting algorithm with a multipivot concept that partitions the data up to 8 threads. Its speedup is up to 3.8× on the 2-core with hyperthreading technology processor. In 2016, Parallel Partition and Merge Quick sort (PPMQsort) was proposed 25 . A speedup of 12.29× with 8 cores with the hyperthreading technology Xeon E5520 can be obtained. Taotiamton and Kittitornkun 26 presented the parallel Hybrid Dual Pivot Sort (HDPSort) in 2017. Its partitioning function uses two pivots to partition data. Moreover, Lomuto's and Hoare's partitioning algorithms are implemented, and the performance is compared. Speedups of 3.02× and 2.49× can be obtained on AMD FX-8320 and Intel Core i7-2600 machines, respectively. In the same year, Marszałek 27 introduced Parallel Modified Merge Sort Algorithm based on Parallel Random Access Machine. It was proved that it can sort n elements in the maximum time 2n − log 2n − 2 . One year later, Marszałek et al. 28 proposed a fully flexible parallel merge sort algorithm which the computational complexity is optimized. The operational time is equal to O( √ N) and it is flexible to an increasing number of processor cores.
In 2020, a block-based sorting algorithm named the MultiStack Parallel Partition Sorting algorithm (MSPSort) was presented 2930 . Each thread uses left and right stacks to keep the boundaries of each block. It partitions from the leftmost and rightmost of the array to the middle of the array. Its run time is better than those of BQSort and MWSort on the Intel i7-2600, AMD R7-1700 and R9-2920 processors. Moreover, a parallel quicksort algorithm for OTIS-HHC optoelectronic architecture was proposed by Al-Adwan et al. 31 . Its average effeciency on 1,152 processors is up to 0.72. Langr and Schovánková 32 developed a multithreaded quicksort named CPP11sort. A parallel speedup of 44.2× can be obtained on the 56-core server and 14.5× on the 10-core Hyperthread machine.
Recently, the Dual Parallel Partition Sorting algorithm (DPPSort) 33 was proposed in 2022. It divides data into two parts and partitions them independently in parallel using OpenMP. Then, the Multi-Swap function is called to merge the data without the compare-and-swap operation. A speedup of 6.82× can be obtained on a 4-core Hyperthread Intel i7-6770 machine. www.nature.com/scientificreports/ There are several methods to improve the performance of sorting algorithms. Marowka 34 investigated sorting algorithm proposed by Cormen 35 which is vector-based quicksort algorithm. This work is implemented using process-based and thread-based models. However, it did not exhibit good scalability because of its overhead. Gebali et al. 36 proposed a Parallel Multidimensional Lookahead Sorting algorithm which is suitable for GPGPU and massively parallel processor systems. Cortis et al. 37 developed Parallelised Modified Quickselect algorithm which used the same concept of quicksort algorithm. Then, this algorithm was implemented into their parallel quicksort algorithm. The results showed that their algorithm is faster than the original quicksort. Helal and Shaheen 38 enhanced iHmas algorithm which is parallel partitioning and sorting algorithm using MPI 39 . The bottleneck and single point of failure are reduced compared with their Hams algorithm. Mubarak et al. 40 proposed a preprocessing techniques before run on any sorting algorithm. Insertion sort and quicksort are run using these methods. The time complexities of the proposed sorting algorithms are reduced. Multi-Deque partitioning phase. It begins with selecting the pivot to divide the data into smaller subarrays. The median of five algorithm which is the pivot selection algorithm, is called (Line 6, Algorithm 1). Then, the parallel partitioning function (MPDMPar) is executed and returns a new pivot position (Line 6, Algorithm 1). The MPDMSort is called recursively with the divide and conquer concept (Lines 8 and 10, Algorithm 1) in parallel using the omp task (Lines 7 and 9, Algorithm 1).
Multi-Deque Partition Dual-Deque Merge Sorting algorithm
The median of five function or MedianOf5 (Line 5, Algorithm 1) is the pivot selection function. It selects the mid position by calculating the left and right positions of that subarray (Line 1, Algorithm 1). The positions of quarter (qt1) and third-quarter (qt3) are calculated using the left, mid, and right positions (Lines 2 and 3, Algorithm 2). Then, the data of left, qt1, mid, qt3, and right are sorted (Line 4, Algorithm 2). Finally, the mid position is returned to MPDMSort.
In this paper, MPDMPar is the parallel partitioning algorithm in this paper. It begins with swapping the pivot and left data of that subarray (Line 1, Algorithm 3). Then, the InitBlocks function is executed to initial multiple blocks using a double-ended queue (deque) with Blocksize size (Line 2, Algorithm 3). Note that this function returns deq, which keeps the boundary of blocks that can be used to partition the data in each block. After that, www.nature.com/scientificreports/ Hoare's partitioning in block is executed using omp parallel for (Lines 5-6, Algorithm 3). Every deq in each thread is popped for the left i and right j boundaries in the critical section (Lines 8-9, Algorithm 3). Note that the left and right boundaries that pop from deq are assigned to temp and temp2, respectively (Line 10, Algorithm 3). Moreover, Hoare's partitioning algorithm in each block is run in parallel (Lines 11-22, Algorithm 3). After that, the partitioned boundaries are pushed to dual-deque. The first deque dl keeps the boundaries of data that are less than or equal to pivot (Line 25, Algorithm 3). The second dg keeps the boundaries of data that are greater than pivot (Line 26, Algorithm 3). Then, both dl and dg are passed to the DualDeqMerge function to merge the data without the compare-and-swap operation (Line 29, Algorithm 3) and return the leftover boundary to run sequential partitioning (Line 30, Algorithm 3). Finally, the new_pivot from sequential partitioning and data at the left position of that subarray are swapped and then returned (Lines 31-32, Algorithm 3).
In this paper, the multideque data structures are created before parallel partitioning. It keeps the boundaries of each block. First, the number of blocks is calculated (Lines 1-2, Algorithm 4). The multideque array deq is created with thread length (Line 3, Algorithm 4), and then the boundaries are pushed into each deq (Lines 5-8, Algorithm 4). Note that if there is remaining block, the last boundaries of block will be pushed into the deq (Lines 9-12, Algorithm 4). www.nature.com/scientificreports/ Dual-Deque merging phase. The previous phase shows the block-based parallel partitioning concept using multideque as its data structure to keep the block boundaries. It provides the data that are less than or equal to pivot and greater than pivot in each block. Therefore, we push the boundaries of data that are less than or equal to pivot value and greater than pivot value in dl and dg deques, respectively. The data will be merged in this phase without the compare-and-swap operation.
The dl and dg deques keep the boundaries of data in the Multi-Deque Partitioning phase. Therefore, the boundaries are not sorted. First, dl and dg are sorted before merging the data (Lines 1-2, Algorithm 5). Then, j is popped back from dl, and i is popped front from dg. j is an index used to swap the data that are less than or equal to pivot value in the right block of the array. i is an index used to swap the data that are greater than pivot www.nature.com/scientificreports/ in the left block of the array. The data of the left and right blocks are swapped, where j is greater than or equal to the boundary of its block and i is less than or equal to the boundary of its block (Lines 8-12, Algorithm 5). If there are leftover data on the left block, the boundary of the left block will be pushed front to dg (Lines 13-15, Algorithm 5). On the other hand, on the right block, the boundary of the right block will be pushed back to dl (Lines 16-18, Algorithm 5). This iteration will be run until index i is equal to j and then return dltemp and dgtemp to run the sequential partitioning function. The Multi-Deque Partitioning phase and Dual-Deque Merging phase are illustrated in Fig. 1.
Sorting phase. The parallel sorting algorithm with the divide and conquer concept consists of two parts.
The divide step is parallel partitioning, which is the Multi-Deque Partitioning and Dual-Deque Merging phases in this work. While the data are divided and smaller than the cutoff, the Sorting phase (Conquer) is executed in parallel using the omp task (Lines 1-4 MPDMSort is the parallel block-based sorting algorithm. Each thread runs its partitioning algorithm in each block. Therefore, block size b is an important parameter that affects the run time of MPDMSort. Table 1 shows the average run time of each block size b of random distribution on the Intel Gold 6142 machine vs. the i7-11700 machine at cutoff = 4. The best sorting run time is at b = 0.5 MB while sorting 200 and 500 million data on the Intel Xeon Gold 6142 machine. While the data are increased to 1000 and 2000 million, the b values are increased to 1 and 2 MB, respectively. On the other hand, the b values are between 1 MB and 4 MB on the i7-11700 machine. Its b values are increased when n increases, which is similar to the Intel Xeon Gold 6142 machine.
Experiments, results and discussions
MPDMSort is developed by the divide and conquer algorithm concept. Therefore, it needs to switch the divide part into the conquer part. The parameter used to switch to the conquer part is the cutoff. Table 2 shows the average run time of each cutoff of random distribution on the Intel Xeon Gold 6142 machine vs. the i7-11700 machine at b = 1 MB. www.nature.com/scientificreports/ The best run time values in each n of MPDMSort are between 16 MB and 32 MB. Note that the cutoff is 32 MB at n = 2000 million data on the Intel Xeon Gold 6142 machine. It can be noticed that most of the run time of the smaller cutoff is more stable than that of the larger cutoff. On the other hand, the Intel i7-11700 machine's best run time values are increased from 16 MB to 64 MB. Its cutoff is proportional to n. Table 3 shows the average run time of random, reversed, nearly sorted distributions for sorting Uint64 200, 500, 1000, and 2000 million data on the Intel Xeon Gold 6142 machine at b = 2 MB and cutoff = 32 MB.
BQSort is the fastest algorithm while sorting the random distribution at n = 200 and 500 million data. However, MPDMSort can sort the random data faster than BQSort and MWSort at 1000 and 2000 million data. On the other hand, MWSort and BQSort are the fastest when sorting the reversed and nearly sorted distributions, respectively. This means that our MPDMSort can sort the larger random distribution data better than the other sorting algorithms. This is the limitations of MPDMSort. The first limitation is sorting the reversed and nearly sorted distributions. It can be noticed that run time of BQSort is the best while sorting nearly sorted distribution and MWSort run time is the best for reversed distribution. This can be dued to the Multi-Deque Partitioning phase is the block-based partitioning concept which uses the Hoare's partitioning in each block. However, this concept uses compare-and-swap operation in each block every level of the subarray. This consumes run time greater than the Multiway-Merge algorithm in the MWSort. The second limitation of MPDMSort is sorting the small random distribution data. We can notice that run time of BQSort is the best while sorting smaller data such as 200 and 500 million random data. This can be dued to the overhead of our sequential region of MPDMSort, for example Dual-Deque Merging Phase and critical section in the parallel region such as push and pop operations of deques. Moreover, the average run time of two machines are very similar. It can be dued to the number of cores on virtual machine of Intel Xeon Gold 6152 are set to 16 cores. There are 16 hardware threads which are equal to Intel Core i7-11700 machine.
Speedup. In this paper, we measure the run time metric of each algorithm and calculate them using the run time of STLSort and the run time of MPDMSort, BQSort, and MWSort. Figure 2 shows the speedup of any parallel sorting algorithm with a random distribution on the Intel Xeon Gold 6142 machine. The speedup metrics of all algorithms are proportional to n. The best speedups of MPDMSort and BQSort are at n=2000 million data. However, the best speedup of MWSort is at n=1000 million data. The Speedup of our MPDMSort is proportional to the input size. It can be due to the overhead of the OpenMP library and fraction between the sequential and parallel regions of the parallel algorithm. Figure 3 shows speedup of MPDMSort vs b vs cutoff sortss random Uint32 data on the Intel Xeon Gold 6142 machine. We can notice that the best speedup of n = 200 M which is small dataset as shown in Fig. 3a is at b = 1 and cutoff = 16 MB. When n = 500 M and 1000 M, b is increased between 2 and 4 with cutoff = 16 MB as shown in Fig. 3b and c. Figure 3d shows speedup of MPDMSort vs b vs cutoff at n=2000 million data where b = 0.5, 1, 2, 4, 8 MB and cutoff = 16, 32, 64 MB. The best speedup is up to 13.42× at b = 2 and cutoff = 32 MB. It can be noticed that n is increased, b grows from 1 to 2. After that, cutoff is incresed from 16 to 32 while n=2000 million data. b=2 and cutoff=32 are the set of parameters which can be choosen to sort the data by our MPDMSort.
Lomuto's vs. Hoare's partitioning in Multi-Deque partitioning results. Table 4 shows the best speedup of MPDM-Sort with Lomuto's vs. Hoare's partitioning in the Multi-Deque Partitioning phase. We note that Speedups of Lomuto's partitioning in our algorithm are greater than Hoare's in all parameters. This can be due to the block size of our work. Our algorithm uses a block-based parallel partitioning concept in which every block is small and residents the cache. The indices of Lomuto's partitioning are increased and run from left to right. However, Hoare's partitioning uses two indices. The first index runs from left to right, and the second index runs from right to left, and its locality is not better than that of Lomuto's partitioning algorithm. www.nature.com/scientificreports/ www.nature.com/scientificreports/ Speedup per thread. Speedup per thread is the metric that can be used to measure the performance of the parallel algorithm. When Speedup per thread is greater, the processor core can be used efficiently. Speedup per thread is the fraction of Speedup of the algorithm and hardware threads in any processor. We can use this metric to compare the parallel algorithms because this metric cannot be greater than 1.00. Table 5 shows the best speedup per thread of each parallel sorting algorithm. Note that MPDMSort, BQSort, and MWSort are run on the same machine in this experiment. We note that Speedup per thread of both MPDMSort Lomuto uses the block-based partitioning concept in Multi-Deque partitioning phase and implements Lomuto's partitioning inside. It improves the locality of partitioning algorithm while it executes in parallel. This technique is used in the algorithms with high Speedup per thread metric such as BQSort, Introqsort, PPMQSort, CPP11Sort, and DPPSort STL . Note that, PPMQSort and DPPSort STL begins with 2 blocks in parallel partitioning phase. Moreover, most of block-based partitioninig algorithms merge the unpartitioned data by moving them to the middle. Then, partitioning them in sequential or paralell which consumes compare-andswap operations that affects run time. However, our MPDMSort Lomuto uses the Dual-Deque Merging phase to merge the partitioned data in each block which reduces compare-and-swap operations. Therefore, speedup per thread of MPDMSort Lomuto is greater than the other algorithms.
Perf Profiling tool. The Perf profiling tool is the Linux tool 13 that can profile the metrics that affect the performance of the sorting algorithm. MPDMSort Lomuto , MPDMSort Hoare , BQSort and MWSort are run to sort the data and profile the metrics. Table 6 shows the Perf results of four parallel algorithms on the Intel i7-11700 machine.
In this experiment, we increase b into 2 MB, 4 MB and 8 MB to show the effect of block size in each algorithm. Note that the cutoff values are set to 16 MB, 32 MB and 64 MB. The important metrics that affect the run time of any parallel sorting algorithm are branch load misses and cache misses 33 .
We note that b is proportional to cache misses. If b is increased, cache misses are increased. Moreover, the cutoff is proportional to the branch load misses value. If the cutoff value is increased, the branch load misses value is increased. www.nature.com/scientificreports/
Conclusions
In this paper, the Multi-Deque Partition Dual-Deque Merge sorting algorithm, which is a parallel block-based sorting algorithm on a shared-memory system, is proposed. Its concept of MPDMSort is to partition in the Multi-Deque Partitioning phase. The Hoare's and Lomuto's partitioning are compared in this phase and found that Lomuto's partitioning is faster than the Hoare's partitioning algorithm. Then, the partitioning result is merged in the Dual-Deque Merging phase. The Dual-Deque Merging phase is the main contribution of this work which reduces compare-and-swap operations which can solve the problem of parallel block-based partitioning. This parallel algorithm executes recursively until the data are smaller than the cutoff parameter. Finally, the partitioned data are sorted independently using STLSort, which is a sequential standard sorting function.
MPDMSort is implemented and executed on 2 computers: one with an Intel Xeon Gold 6142 processor running Ubuntu Linux, and the other with an Intel Core i7-11700 processor also running Ubuntu Linux. The MPDMSort run time is faster than those of BQSort and MWSort. Its speedup of 13.81× and speedup per thread of 0.86 can be obtained while sorting random distribution data. Speedup per thread of MPDMSort is greater than the other paralell sorting algorithms. Its speedup of MPDMSort depends on the block size, cutoff, data size, type, and distribution. The important metrics which affect the performance of parallel sorting algorithm are cache misses that is proportional to b and branch load misses that is proportional to cutoff. This method can be used to merge the data in the paralell algorithm with block-based concept.
Data availability
In this paper, we use the datasets generator which can generate random, reversed, and nearly sorted 32-bit and 64-bit data. The newinitData() can be called after it is implemented in the source code. Then, it will generate the datasets in the array which is passed into the newinitData(). The source code of datasets generator during the current study are available in the DataSetGenerator repository, https://www.github.com/apisitjoe/DataSetGenerator or request from the corresponding author, Apisit Rattanatranurak. Table 6. Perf results of MPDMSort Lomuto , MPDMSort Hoare , BQSort, and MWSort on the Intel i7-11700 machine at n = 1000 million Uint64 data. | 6,293 | 2023-04-19T00:00:00.000 | [
"Computer Science"
] |
In Situ Vitrification of Lung Cancer Organoids on a Microwell Array
Three-dimensional cultured patient-derived cancer organoids (PDOs) represent a powerful tool for anti-cancer drug development due to their similarity to the in vivo tumor tissues. However, the culture and manipulation of PDOs is more difficult than 2D cultured cell lines due to the presence of the culture matrix and the 3D feature of the organoids. In our other study, we established a method for lung cancer organoid (LCO)-based drug sensitivity tests on the superhydrophobic microwell array chip (SMAR-chip). Here, we describe a novel in situ cryopreservation technology on the SMAR-chip to preserve the viability of the organoids for future drug sensitivity tests. We compared two cryopreservation approaches (slow freezing and vitrification) and demonstrated that vitrification performed better at preserving the viability of LCOs. Next, we developed a simple procedure for in situ cryopreservation and thawing of the LCOs on the SMAR-chip. We proved that the on-chip cryopreserved organoids can be recovered successfully and, more importantly, showing similar responses to anti-cancer drugs as the unfrozen controls. This in situ vitrification technology eliminated the harvesting and centrifugation steps in conventional cryopreservation, making the whole freeze–thaw process easier to perform and the preserved LCOs ready to be used for the subsequent drug sensitivity test.
Introduction
Tumor cell lines have been used worldwide as primary tools for anti-cancer drug development due to their relevance to cancers (i.e., mutations in oncogenes), unlimited proliferation capacities, and well-developed high-throughput culture and analysis systems from multi-well plates to liquid handling robots. However, cell lines cannot resemble the three-dimensional (3D) structure and the heterogeneity of real tumor tissues, leading to differences in drug responses between cell lines and in vivo models. In recent years, patient-derived organoids (PDOs) have attracted much attention due to their similarity to in vivo tumor tissues and are recognized as a promising in vitro model to fill the gap between cell lines and in vivo models. PDOs are self-organized three-dimensional cultures of patient tumor cells, retaining the 3D structure and genetic mutations of the parental tumor tissues [1]. PDOs can be established from many different types of tumor tissues, including colorectal cancers [2], breast cancers [3], lung cancers [4], ovary cancers [5], etc. Previous reports in colorectal cancer organoids demonstrated that PDOs captured patient's responses to anti-tumor therapies [6,7]. PDO-based drug candidate validation has been explored and promising results were reported [8][9][10].
Although the potentials of PDOs have been recognized, suitable culture and analysis systems have to be developed to facilitate the application of PDOs in cancer research and anti-tumor drug development. Firstly, culturing and manipulating PDOs are more complex and expensive than that of the cell lines due to the requirement of the 3D culture matrix. Secondly, PDOs show tremendous diversities in genetic mutation, morphology, and proliferation potency due to the heterogeneity of the parental tumors. In addition, the proliferation capacity of tumor organoids is limited compared to cell lines. For instance, it has been reported that lung cancer organoids (LCOs) were overtaken by normal cells in long-term culture at a high frequency [11]. Our study also found that lung cancer organoids stopped growing at high passages. Although the proliferation of LCOs can be improved by optimizing the culturing conditions, a robust cryopreservation technology compatible with organoid culture and analysis will facilitate the usage of PDOs in anticancer drug development.
To date, cryopreservation strategies are mainly divided into the slow freezing and vitrification methods [12]. The most common and traditional slow freezing techniques feature a low concentration of cryoprotectants (CPA) and a slow cooling rate, which usually needs to be optimized for different cell types. Thus far, most of the reported biobanks of PDOs have been cryopreserved using the slow freezing methods [13]. On the contrary, the vitrification method employs high concentrations of CPA together with an extremely fast rate of cooling. Owing to the advantage of ice-free solution in the process of freezing, the vitrification method is regarded as the most promising way to achieve organ cryopreservation in the future [14]. Vitrification of cancer organoids has also been investigated in recent years [15][16][17][18] and has shown promising results.
In our previous studies, we developed the superhydrophobic microwell array chip (SMAR-chip) [19][20][21] and demonstrated the feasibility of PDO culture and analysis on the SMAR-chip [22]. Owning to the nanoliter-scale culture volume on the SMAR-chip, the requirement for the number of PDOs is largely reduced comparing to conventional multi-well plates. In order to facilitate the high-throughput PDO-based drug testing on the SMAR-chip, here we developed an in situ vitrification method to freeze the LCOs on the SMAR-chip using simple procedures. We proved LCOs frozen on the chip had similar viability and growth rate as those frozen in conventional cryovials. More importantly, the freeze-thaw process did not affect the responses of the organoids to anti-cancer drugs. The in situ cryopreservation together with the subsequent high-throughput drug sensitivity analysis provide a promising platform for the future application of PDOs in anti-cancer drug development.
The Fabrication of the SMAR-Chip
The SMAR-chip was fabricated by casting a layer of superhydrophobic paint on the top of the polycarbonate microwell array-chip [22]. The chip was manufactured by standard injection molding by Mudu Qingyuan (Jiangsu, China). The superhydrophobic paint was prepared following Lu's protocol [23]. Briefly, 1 g of 1H, 1H, 2H, 2Hperfluorooctyltriethoxysilane (Sigma-Aldrich, St. Louis, MO, USA) was added into 99 g of absolute ethanol and mechanically stirred for 2 h. Then, 6 g of titanium oxide (TiO 2 ) nanoparticles (~60 to 200 nm) (Sigma-Aldrich, St. Louis, MO, USA) and 6 g of P25 TiO 2 (~21 nm) (Degussa, Essen, Germany) were added into the solution to make a paint-like suspension. The paint was then pipetted onto the top surface of the microwell array chip into the spaces between the microwells and air-dried completely. The SMAR-chip was autoclaved before use.
Culture, Passaging and Harvesting of Lung Cancer Organoids
To culture LCOs in a multi-well plate, LCOs in suspension were first centrifuged for 5 min at 500× g at 4 • C and resuspended in pre-cooled (4 • C) Matrigel (BD Biosciences, San Jose, CA, USA). Then, 50 µL drops of the organoid suspension were inoculated in 24-well plates and allowed to solidify at 37 • C for 20 min. The seeding density was adjusted to approximately 500 organoids per well. Subsequently, 600 µL of LCO culture medium (LCOM) was added into the wells and the plate was transferred to a cell culture incubator at 37 • C with 5% CO 2 . A detailed recipe of LCOM can be seen in Table S1. The culture medium was replenished every 3 days. To harvest the LCOs, the culture medium was removed and 10× volumes of cold Organoid Harvesting Solution (R&D Systems, Minneapolis, MN, USA) were added into each well. The plate was shaken on an orbital shaker at 0 • C for 2 h to dissolve the Matrigel. Once the Matrigel was digested completely, the organoid suspension was sheared by pipetting, followed by washing with Advanced DMEM/F12, and centrifugation (500× g, 5 min, 4 • C) to collect the LCOs.
For the on-chip organoid culture, 0.4 µL of Matrigel solution containing 3-5 organoids was loaded into each microwell with an electronic pipette (Rainin E4 XLS, Mettler-Toledo, Columbus, OH, USA) working in a low-speed multi-dispense mode. Each Matrigel droplet in the microwell was overlaid with 2.4 µL of LCOM, which was replenished daily.
Vitrification of LCOs
For the in-vial vitrification, following 48 h of culturing, organoids were harvested, washed, and vitrified using a vitrification freeze kit (Nanjing Aibei biotech, Nanjing, China) according to manufacturer's instructions. Briefly, the organoids were harvested and suspended in the equilibration solution for 5 min, then resuspended in vitrification reagent after centrifugation and transferred into liquid nitrogen. To thaw the LCOs, a thawing kit (Nanjing Aibei biotech, Nanjing, China) was used, following the manufacturer's instructions. Briefly, the cryovial was removed from the liquid nitrogen and placed in a 37 • C water bath and agitated until only a pea-sized piece of ice remained. After centrifugation, organoids were mixed with thawing solution and incubated for 5 min followed by three washes with the LCOM. Then, the LCOs were mixed with Matrigel, loaded into a 24-well plate, and cultured under normal conditions.
For the in situ vitrification on the SMAR-chip, Matrigel with organoids was first loaded as described above. After 2 h of incubation in the CO 2 incubator, 2 µL of equilibration solution (Nanjing Aibei biotech, Nanjing, China) was added on top of the Matrigel droplets and incubated for 5 min. Then, the equilibration buffer was removed with a piece of filter paper and replaced by 2 µL of vitrification solution (Nanjing Aibei biotech, Nanjing, China). After 2 min of liquid exchange, the chip was sealed and placed into liquid nitrogen. When thawing, the chip was put into a 37 • C incubator for 20 s followed by removal of the vitrification solution by gentle wiping with a piece of filter paper. Then, 2 µL of thawing solution (Nanjing Aibei biotech, Nanjing, China) was added onto the Matrigel droplets followed by three washes with the LCOM. After washing, the chip was transferred to the 37 • C incubator under normal on-chip organoid culture conditions.
Slow Freezing of LCOs
Briefly, organoids were suspended in cell cryopreservation medium (CELLBANKER TM , ZEN OAQ, Fukushima, Japan) and transferred into cryovials. Cryovials were sealed and cooled to −80 • C in Corning CoolCell Containers (Corning, NY, USA). After 24 h, cryovials were transferred to liquid nitrogen. To thaw the LCOs, the cryovial was removed from the liquid nitrogen, placed in a 37 • C water bath, and agitated until only a pea-sized piece of ice remained. Then, 1 mL of pre-warmed LCOM was added into the cryovial and the LCOs were centrifuged at 1000 rpm for 5 min, resuspended in Matrigel, and cultured under normal conditions.
Evaluation of Cell Viability
Organoid viability was determined using the LIVE-DEAD cell viability kit (YEASEN biotech, Shanghai, China). Calcein AM at a concentration of 2 µM and propidium iodide at a concentration of 4 µM were added to the LCOs and incubated for 15 min, followed by imaging of the LCOs with an Olympus IX83 inverted fluorescence microscope.
Quantitative Real-Time Polymerase Chain Reaction
Total RNA of each sample was extracted using TRIzol Reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's instructions. After that, 50 ng of RNA for each reaction was used to perform one-step RT-qPCR following the manufacturer's instructions (Takara, Dalian, China). The reactions were performed in the CFX96 Touch Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA) with three replicates for each sample. The relative mRNA levels of the target genes were analyzed using the ∆∆CT method with the internal reference gene, GAPDH. Primers used in this reaction are listed in Table S2.
Flow Cytometry Analysis
Organoids were digested into single cells with trypsin. Then, cells were fixed with a
Drug Sensitivity Test on the SMAR-Chip
A drug sensitivity test on the SMAR-chip was performed following the procedures developed in our other study [22]. The viability of the LCOs was measured both before and after the addition of the anti-cancer drugs using the alamarBlue™ Cell Viability Reagent (Invitrogen, Carlsbad, CA, USA). After culturing on the SMAR-chip for 3 days, the medium was removed, and 800 nL of 10% alamarBlue reagent was added onto the Matrigel droplets. Then, the chip was incubated for 2 h in a 37 • C incubator. A slide covered on the microwell array to flatten the top of the droplets in the microwells in order to eliminate the variation in the fluorescent signal in the microwells. After that, the SMAR-chip was scanned, and the fluorescence signal was measured using an Olympus IX83 inverted fluorescence microscope. The fluorescent intensity of each microwell was measured using Image J software. Next, the alamarBlue solution was removed and the chip was submerged in culture medium for 4 h in order to completely wash away the residual alamarBlue inside the Matrigel. Next, 2.4 µL of fivefold serial diluted drugs were added in each microwell. The concentration ranges were 0.002-15.625 µM for AMG510 and 0.02048-1600 µM for doxorubicin, respectively. To eliminate the background noise introduced by the alamarBlue reagent itself, Matrigel without LCOs was used as a negative control where the alamarBlue reagent was added and the fluorescent intensity was measured. After 3 days of drug treatment, the post-treatment viability measurement was performed using the same procedure. The relative viability (the post-treatment viability divided by the pretreatment viability) of each condition was calculated and normalized by the vehicle control (0.1% DMSO).
A drug sensitivity test on the SMAR-chip was performed following the procedures developed in our other study [22]. The viability of the LCOs was measured both before and after the addition of the anti-cancer drugs using the alamarBlue™ Cell Viability Reagent (Invitrogen, Carlsbad, CA, USA). After culturing on the SMAR-chip for 3 days, the medium was removed, and 800 nL of 10% alamarBlue reagent was added onto the Matrigel droplets. Then, the chip was incubated for 2 h in a 37 • C incubator. A slide covered on the microwell array to flatten the top of the droplets in the microwells in order to eliminate the variation in the fluorescent signal in the microwells. After that, the SMAR-chip was scanned, and the fluorescence signal was measured using an Olympus IX83 inverted fluorescence microscope. The fluorescent intensity of each microwell was measured using Image J software. Next, the alamarBlue solution was removed and the chip was submerged in culture medium for 4 h in order to completely wash away the residual alamarBlue inside the Matrigel. Next, 2.4 µL of fivefold serial diluted drugs were added in each microwell. The concentration ranges were 0.002-15.625 µM for AMG510 and 0.02048-1600 µM for doxorubicin, respectively. To eliminate the background noise introduced by the alamarBlue reagent itself, Matrigel without LCOs was used as a negative control where the alamarBlue reagent was added and the fluorescent intensity was measured. After 3 days of drug treatment, the post-treatment viability measurement was performed using the same procedure. The relative viability (the post-treatment viability divided by the pretreatment viability) of each condition was calculated and normalized by the vehicle control (0.1% DMSO).
Statistical Analysis
Statistical tests were performed as indicated in the individual figure legends using GraphPad Prism 7.02 software. The data are presented as the means ± standard deviations, medians, or quartiles, as appropriate. Normally distributed variables were analyzed by Student's t-tests. Results were considered significant with p-value ≤ 0.05.
In Situ Cryopreservation Process
We developed an in situ cryopreservation method where LCOs were frozen on the SMAR-chip, ready for the subsequent drug sensitivity test. As shown in Figure 1, LCOs suspended in Matrigel solution were inoculated into the microwells, followed by cryopreservation of the whole chip, which can be stored in liquid nitrogen for a long time. To perform the drug sensitivity test, the chip was removed from liquid nitrogen and thawed by placing it in a 37 • C incubator. After a short period of culturing, drugs were delivered into the microwells and the responses of LCOs to the drugs were measured. The whole freezing and thawing process eliminates the centrifugation and resuspension steps required in conventional cell freezing methods and injury to the LCOs due to these steps.
Micromachines 2021, 12, x FOR PEER REVIEW 5 of 12 medium for 4 h in order to completely wash away the residual alamarBlue inside the Matrigel. Next, 2.4 μL of fivefold serial diluted drugs were added in each microwell. The concentration ranges were 0.002-15.625 μM for AMG510 and 0.02048-1600 μM for doxorubicin, respectively. To eliminate the background noise introduced by the alamarBlue reagent itself, Matrigel without LCOs was used as a negative control where the alamarBlue reagent was added and the fluorescent intensity was measured. After 3 days of drug treatment, the post-treatment viability measurement was performed using the same procedure. The relative viability (the post-treatment viability divided by the pretreatment viability) of each condition was calculated and normalized by the vehicle control (0.1% DMSO).
Statistical Analysis
Statistical tests were performed as indicated in the individual figure legends using GraphPad Prism 7.02 software. The data are presented as the means ± standard deviations, medians, or quartiles, as appropriate. Normally distributed variables were analyzed by Student's t-tests. Results were considered significant with p-value ≤ 0.05.
In Situ Cryopreservation Process
We developed an in situ cryopreservation method where LCOs were frozen on the SMAR-chip, ready for the subsequent drug sensitivity test. As shown in Figure 1, LCOs suspended in Matrigel solution were inoculated into the microwells, followed by cryopreservation of the whole chip, which can be stored in liquid nitrogen for a long time. To perform the drug sensitivity test, the chip was removed from liquid nitrogen and thawed by placing it in a 37 °C incubator. After a short period of culturing, drugs were delivered into the microwells and the responses of LCOs to the drugs were measured. The whole freezing and thawing process eliminates the centrifugation and resuspension steps required in conventional cell freezing methods and injury to the LCOs due to these steps. The SMAR-chip with a 12 × 9 microwell array was fabricated, which was composed of a polycarbonate substrate with the microwells (1 mm in diameter, 200 µ m in depth, and 1.25 mm in pitch) and a layer (~100 µ m thick) of superhydrophobic material on the top surface of the substrate (Figure 2a,b). In order to prevent the paint from entering the microwells, a circular rim was fabricated around each microwell (Figure 2c,d). The contact angle and the SEM images of the superhydrophobic material are shown in Figure 2e,f. Droplet arrays were generated on the SMAR-chip due to the repelling effect of the superhydrophobic layer to the aqueous solution, ensuring the formation of isolated liquid con- The SMAR-chip with a 12 × 9 microwell array was fabricated, which was composed of a polycarbonate substrate with the microwells (1 mm in diameter, 200 µm in depth, and 1.25 mm in pitch) and a layer (~100 µm thick) of superhydrophobic material on the top surface of the substrate (Figure 2a,b). In order to prevent the paint from entering the microwells, a circular rim was fabricated around each microwell (Figure 2c,d). The contact angle and the SEM images of the superhydrophobic material are shown in Figure 2e,f. Droplet arrays were generated on the SMAR-chip due to the repelling effect of the superhydrophobic layer to the aqueous solution, ensuring the formation of isolated liquid conditions in the individual microwells, thus avoiding cross contamination [19]. As shown in Figure 2g, the reagents in the microwells could be changed either as a whole by the submerge-aspirate method or individually by the spot-cover method to ensure unique liquid conditions in each microwell [19]. We cultured 293T cells on the chip and evaluated cell viability using the Calcein AM/PI assay. High survival rates (94 ± 3.9%), comparable to the conventional six-well plate (95 ± 2.7%), were achieved (Figure 2h,i).
Vitrification Is Suitable for LCOs
In order to find the cryopreservation method suitable for organoids, we first compared slow freezing and vitrification on their effect on the phenotype and viability of lung cancer organoids. As a demonstration, a previously established lung cancer organoid line was employed. The LCOs were first frozen in conventional cryovials using both methods, then thawed and analyzed 24 h later. As shown in Figure 3a, spheroid-like morphology similar to the unfrozen organoids was observed in both groups. Tracing of the organoids at different time points (day 3, day 5, day 9 and day 13) demonstrated continuous growth in both groups without significant differences in growth rates (Figure 3a,b). Immunohistochemical staining of Ki67 detected proliferating cells in LCOs of both groups (Figure 3c). In addition, H&E staining revealed that LCOs which underwent the freeze-thaw cycle retained the 3D structure of the original organoid line (solid sphere without lumen, Figure 3c). We also investigated whether the freeze-thaw cycle affected the expression of tumor cell markers. Immunohistochemical staining indicated that LCOs in both groups retained the expression of squamous cell lung cancer markers, including p40, p63, and CK5/6 (Figure 3c). In addition, we measured drug responses of the vitrified and the slow frozen organoids to the chemotherapeutic drugs gemcitabine and cisplatin. LCOs in both groups showed resistance to the two drugs (Figure 3d), consistent with our previous results. These results indicate that cryopreservation had little effect on the phenotype of the LCOs.
Vitrification Is Suitable for LCOs
In order to find the cryopreservation method suitable for organoids, we first compared slow freezing and vitrification on their effect on the phenotype and viability of lung cancer organoids. As a demonstration, a previously established lung cancer organoid line was employed. The LCOs were first frozen in conventional cryovials using both methods, then thawed and analyzed 24 h later. As shown in Figure 3a, spheroid-like morphology similar to the unfrozen organoids was observed in both groups. Tracing of the organoids at different time points (day 3, day 5, day 9 and day 13) demonstrated continuous growth in both groups without significant differences in growth rates (Figure 3a,b). Immunohistochemical staining of Ki67 detected proliferating cells in LCOs of both groups (Figure 3c). In addition, H&E staining revealed that LCOs which underwent the freeze-thaw cycle retained the 3D structure of the original organoid line (solid sphere without lumen, Figure 3c). We also investigated whether the freeze-thaw cycle affected the expression of tumor cell markers. Immunohistochemical staining indicated that LCOs in both groups retained the expression of squamous cell lung cancer markers, including p40, p63, and CK5/6 ( Figure 3c). In addition, we measured drug responses of the vitrified and the slow frozen organoids to the chemotherapeutic drugs gemcitabine and cisplatin. LCOs in both groups showed resistance to the two drugs (Figure 3d), consistent with our previous results. These results indicate that cryopreservation had little effect on the phenotype of the LCOs. Then, we analyzed the viability of the LCOs after the freeze-thaw cycle. Interestingly, the slow freezing group showed excessive cell death in the core region while the vitrified group showed relatively mild cell death (Figure 4a,b), consistent with previous reports, suggesting that the high concentration of CPA in the vitrification method protected the core of organoids from ice injury [15]. We next investigated whether there are differences in the expression of apoptosis genes and oxidative stress-related genes. The Bcl-2 family consists of a number of proteins which play important roles in the regulation of apoptosis, either functioning as promoters (such as Bid, Bax) or inhibitors (such as Bcl-XL, Bcl-2) [24]. Furthermore, the Bax/Bcl-2 ratio was regarded as an indicator of cell susceptibility to apoptosis [25]. As well as the Bcl-2 family, p53 is also known to initiate apoptosis in mammalian cells. RT-qPCR of these genes showed that the levels of apoptosis promoters and indicators (Bid, Bax/Bcl-2, p53) were significantly upregulated, while the anti-apoptosis gene Bcl-XL was downregulated in the slow freezing group (Figure 4c), consistent with increased cell death. Furthermore, the higher expression level of superoxide dismutase Then, we analyzed the viability of the LCOs after the freeze-thaw cycle. Interestingly, the slow freezing group showed excessive cell death in the core region while the vitrified group showed relatively mild cell death (Figure 4a,b), consistent with previous reports, suggesting that the high concentration of CPA in the vitrification method protected the core of organoids from ice injury [15]. We next investigated whether there are differences in the expression of apoptosis genes and oxidative stress-related genes. The Bcl-2 family consists of a number of proteins which play important roles in the regulation of apoptosis, either functioning as promoters (such as Bid, Bax) or inhibitors (such as Bcl-XL, Bcl-2) [24]. Furthermore, the Bax/Bcl-2 ratio was regarded as an indicator of cell susceptibility to apoptosis [25]. As well as the Bcl-2 family, p53 is also known to initiate apoptosis in mammalian cells. RT-qPCR of these genes showed that the levels of apoptosis promoters and indicators (Bid, Bax/Bcl-2, p53) were significantly upregulated, while the anti-apoptosis gene Bcl-XL was downregulated in the slow freezing group (Figure 4c), consistent with increased cell death. Furthermore, the higher expression level of superoxide dismutase 1(SOD1), a stress marker which was reported to be upregulated after the freeze-thaw procedure [26], suggests that cells might suffer more from oxidative stress in the slow freezing group. In addition, the protein levels of Bcl-2 and Bcl-XL were higher in the vitrification group compared to the slow freezing group, as suggested by the peaks of the flow cytometry results (Figure 4d). These results indicate that vitrification caused less injury to the organoids compared to slow freezing.
Micromachines 2021, 12, x FOR PEER REVIEW 8 of 12 1(SOD1), a stress marker which was reported to be upregulated after the freeze-thaw procedure [26], suggests that cells might suffer more from oxidative stress in the slow freezing group. In addition, the protein levels of Bcl-2 and Bcl-XL were higher in the vitrification group compared to the slow freezing group, as suggested by the peaks of the flow cytometry results (Figure 4d). These results indicate that vitrification caused less injury to the organoids compared to slow freezing. Quantification of the live/dead assay (two-tailed Student's t-test, data are presented as mean ± SD, * p < 0.05). (c) RT-qPCR analysis of apoptosis-related genes and oxidative stress-related genes (two-tailed Student's t-test, data are presented as mean ± SD, * p < 0.05, ** p < 0.01). (d) Flow cytometry measurement of the anti-apoptosis genes Bcl-2 and Bcl-XL.
On-Chip Vitrification of LCOs
Then, we demonstrated the feasibility of in situ vitrification of LCOs on the SMARchip. As shown in Figure 5a, organoids suspended in Matrigel were loaded into the microwells and incubated briefly. Then, the equilibration solution was delivered onto the Matrigel droplets. Following 5 min of incubation, the equilibration solution was removed, and the vitrification solution was added. Then, the chip was sealed and placed directly into liquid nitrogen for long-term storage. For thawing, The SMAR-chip was removed from the liquid nitrogen and placed in a 37 °C incubator, followed by delivery of the thawing solution and washing with culture medium. As shown in Figure 5b,c, no significant difference of proliferation capacity was observed between the off-chip and on-chip vitrification groups. Excessive cell death was not found in either groups, as indicated by the live-dead assay (Figure 5d). These results suggest that similar to vitrification in the cryovials, the on-chip vitrification can ensure high cell survival rates after the freeze-thaw procedure. Quantification of the live/dead assay (two-tailed Student's t-test, data are presented as mean ± SD, * p < 0.05). (c) RT-qPCR analysis of apoptosis-related genes and oxidative stress-related genes (two-tailed Student's t-test, data are presented as mean ± SD, * p < 0.05, ** p < 0.01). (d) Flow cytometry measurement of the anti-apoptosis genes Bcl-2 and Bcl-XL.
On-Chip Vitrification of LCOs
Then, we demonstrated the feasibility of in situ vitrification of LCOs on the SMAR-chip. As shown in Figure 5a, organoids suspended in Matrigel were loaded into the microwells and incubated briefly. Then, the equilibration solution was delivered onto the Matrigel droplets. Following 5 min of incubation, the equilibration solution was removed, and the vitrification solution was added. Then, the chip was sealed and placed directly into liquid nitrogen for long-term storage. For thawing, The SMAR-chip was removed from the liquid nitrogen and placed in a 37 • C incubator, followed by delivery of the thawing solution and washing with culture medium. As shown in Figure 5b,c, no significant difference of proliferation capacity was observed between the off-chip and on-chip vitrification groups. Excessive cell death was not found in either groups, as indicated by the live-dead assay (Figure 5d). These results suggest that similar to vitrification in the cryovials, the on-chip vitrification can ensure high cell survival rates after the freeze-thaw procedure. Next, we demonstrated that the responses of the LCOs to anti-cancer drugs were not changed after the on-chip vitrification-thawing cycle. After thawing, the LCOs were cultured for 3 days to recover. Then, the viability of the organoids before drug treatment was measured on the SMAR-chip using the alamarBlue reagent, followed by incubation with the drugs for 72 h. Then, the viability of LCOs post-drug treatment was measured. Organoids were treated with different concentrations of commonly used chemotherapeutic drugs gemcitabine, pemetrexed, or doxorubicin. As shown in Figure 6, both the unfrozen control and the on-chip vitrification LCOs showed resistance to gemcitabine and pemetrexed, while treatment with doxorubicin led to a dose-dependent decrease in viability in a similar manner for the two groups. In addition, because the LCOs harbored the KRAS G12C mutation, the drug AMG510, an inhibitor to KRAS G12C, was also tested. Our results indicated that the LCO was not sensitive to AMG510, echoing the diverse effect of AMG510 on cell lines harboring the mutation. For instance, H358 is sensitive to AMG510 while H2122 is resistant to it, although both cell lines have the KRAS G12C mutation. Overall, these results suggest that the in situ vitrification method enabled readyto-use drug screening of LCOs without compromising the viability or changing the drug responses of the organoids. Next, we demonstrated that the responses of the LCOs to anti-cancer drugs were not changed after the on-chip vitrification-thawing cycle. After thawing, the LCOs were cultured for 3 days to recover. Then, the viability of the organoids before drug treatment was measured on the SMAR-chip using the alamarBlue reagent, followed by incubation with the drugs for 72 h. Then, the viability of LCOs post-drug treatment was measured. Organoids were treated with different concentrations of commonly used chemotherapeutic drugs gemcitabine, pemetrexed, or doxorubicin. As shown in Figure 6, both the unfrozen control and the on-chip vitrification LCOs showed resistance to gemcitabine and pemetrexed, while treatment with doxorubicin led to a dose-dependent decrease in viability in a similar manner for the two groups. In addition, because the LCOs harbored the KRAS G12C mutation, the drug AMG510, an inhibitor to KRAS G12C, was also tested. Our results indicated that the LCO was not sensitive to AMG510, echoing the diverse effect of AMG510 on cell lines harboring the mutation. For instance, H358 is sensitive to AMG510 while H2122 is resistant to it, although both cell lines have the KRAS G12C mutation. Overall, these results suggest that the in situ vitrification method enabled ready-to-use drug screening of LCOs without compromising the viability or changing the drug responses of the organoids.
Discussion
Patient-derived organoids recapitulate the genetic and structural features of parental tumor tissues, represent patient's response to anti-cancer drugs, and are recognized as a promising model to overcome the limitations of cancer cell lines. Due to the limited proliferation capacity and heterogeneity of PDOs, new platforms enabling high-throughput organoid culture and drug sensitivity tests are essential for their future application in anticancer drug development. In our other study, we demonstrated that the SMAR-chip is suitable for lung cancer organoid culture and drug sensitivity tests [22]. In this study, we developed an in situ LCO vitrification method on the SMAR-chip. The whole freeze-thaw procedure can be performed with simple steps, eliminating the centrifugation and resuspension procedures, minimizing freeze injury to the LCOs. More importantly, the cryopreserved chip is ready for the subsequent drug sensitivity test, facilitating future application of PDOs in high-throughput drug screening.
We found that vitrification is better than slow freezing for the cryopreservation of PDOs. The low-concentration CPA used in the slow freezing process (usually 10% DMSO) has difficulty entering the central area of the organoid, which may cause the structure of the organoid to be destroyed due to crystal formation [15]. Previous study has shown that if organoids are cut into small pieces before cryopreservation, cell viability is increased significantly owing to the full penetration of DMSO into cells within the core [27]. The high-concentration CPA used in vitrification ensures rapid penetration into the central area of the organoids, reducing freeze injury to the cells. We observed that the number of dead cells and the expression of apoptosis indicator genes were all significantly decreased in the vitrificated LCOs compared to organoids which underwent slow freezing, consistent with previous reports [15].
Successful vitrification requires high cooling and warming rates to prevent the formation of ice crystals which can cause fatal damage to the cells. Vitrification of cells in microscale fluid volumes has been one approach to increase cooling rates [28,29]. The in situ chip cryopreservation system adopted the SMAR-chip where tiny CPA droplet arrays with a volume of 2 μL were generated, ensuring rapid and uniform temperature change
Discussion
Patient-derived organoids recapitulate the genetic and structural features of parental tumor tissues, represent patient's response to anti-cancer drugs, and are recognized as a promising model to overcome the limitations of cancer cell lines. Due to the limited proliferation capacity and heterogeneity of PDOs, new platforms enabling high-throughput organoid culture and drug sensitivity tests are essential for their future application in anticancer drug development. In our other study, we demonstrated that the SMAR-chip is suitable for lung cancer organoid culture and drug sensitivity tests [22]. In this study, we developed an in situ LCO vitrification method on the SMAR-chip. The whole freezethaw procedure can be performed with simple steps, eliminating the centrifugation and resuspension procedures, minimizing freeze injury to the LCOs. More importantly, the cryopreserved chip is ready for the subsequent drug sensitivity test, facilitating future application of PDOs in high-throughput drug screening.
We found that vitrification is better than slow freezing for the cryopreservation of PDOs. The low-concentration CPA used in the slow freezing process (usually 10% DMSO) has difficulty entering the central area of the organoid, which may cause the structure of the organoid to be destroyed due to crystal formation [15]. Previous study has shown that if organoids are cut into small pieces before cryopreservation, cell viability is increased significantly owing to the full penetration of DMSO into cells within the core [27]. The high-concentration CPA used in vitrification ensures rapid penetration into the central area of the organoids, reducing freeze injury to the cells. We observed that the number of dead cells and the expression of apoptosis indicator genes were all significantly decreased in the vitrificated LCOs compared to organoids which underwent slow freezing, consistent with previous reports [15].
Successful vitrification requires high cooling and warming rates to prevent the formation of ice crystals which can cause fatal damage to the cells. Vitrification of cells in microscale fluid volumes has been one approach to increase cooling rates [28,29]. The in situ chip cryopreservation system adopted the SMAR-chip where tiny CPA droplet arrays with a volume of 2 µL were generated, ensuring rapid and uniform temperature change in the droplet array. Another benefit of rapid cooling is that the concentration of vitrification reagent can be reduced to avoid cell toxicity [30]. In this study, we used commercial vitrification regents which performed well in our system. In the future, the components of the vitrification reagents can be optimized to further reduce cell cytotoxicity.
In our previous study, we fabricated a superhydrophobic layer of poly (propyl methacrylate) on a glass slide, and then transferred the superhydrophobic layer to a PDMS microwell array chip by a polymer transfer process, named "micrografting" [19]. In this study, we adapted a superhydrophobic paint (SHP) composed of the 1H, 1H, 2H, 2H-perfluorooctyltriethoxysilane-coated nanoparticles, which could be coated onto the plastic substrate by simple delivery and drying steps. Compared to the previous method, the new chip is easier to fabricate and more friendly to the end user. We cultured 293T cells and lung cancer organoids on the new chip and observed similar cell viability compared to cells cultured in conventional tissue culture plates. However, the biocompatibility of the chip needs further study. For example, culturing more types of cells and analysis on gene expression are needed.
In summary, we developed an in situ vitrification method on the SMAR-chip for the cryopreservation of patient-derived organoids and demonstrated that lung cancer organoids maintained viability and structural integrity after the freeze-thaw cycle. More importantly, the sensitivity of LCOs to anti-cancer drugs was consistent before and after the on-chip vitrification. Our SMAR-chip-based culture system combined with in situ cryopreservation technology can serve as a convenient tool for PDO-based drug development. In the future, an automated reagent delivery system will be developed to work with the microwell array chip. These technologies will potentially facilitate the application of PDOs in anti-cancer drug development.
Supplementary Materials: The following are available online at https://www.mdpi.com/article/10.3 390/mi12060624/s1, Table S1: Recipe of the lung cancer organoid culture media (LCOM), Table S2: Primer sequences for qPCR analysis of selected genes and control. | 8,524.6 | 2021-05-28T00:00:00.000 | [
"Medicine",
"Engineering"
] |
Single-cell analysis of skeletal muscle macrophages reveals age-associated functional subpopulations
Tissue-resident macrophages represent a group of highly responsive innate immune cells that acquire diverse functions by polarizing toward distinct subpopulations. The subpopulations of macrophages that reside in skeletal muscle (SKM) and their changes during aging are poorly characterized. By single-cell transcriptomic analysis with unsupervised clustering, we found 11 distinct macrophage clusters in male mouse SKM with enriched gene expression programs linked to reparative, proinflammatory, phagocytic, proliferative, and senescence-associated functions. Using a complementary classification, membrane markers LYVE1 and MHCII identified four macrophage subgroups: LYVE1−/MHCIIhi (M1-like, classically activated), LYVE1+/MHCIIlo (M2-like, alternatively activated), and two new subgroups, LYVE1+/MHCIIhi and LYVE1−/MHCIIlo. Notably, one new subgroup, LYVE1+/MHCIIhi, had traits of both M2 and M1 macrophages, while the other new subgroup, LYVE1−/MHCIIlo, displayed strong phagocytic capacity. Flow cytometric analysis validated the presence of the four macrophage subgroups in SKM and found that LYVE1− macrophages were more abundant than LYVE1+ macrophages in old SKM. A striking increase in proinflammatory markers (S100a8 and S100a9 mRNAs) and senescence-related markers (Gpnmb and Spp1 mRNAs) was evident in macrophage clusters from older mice. In sum, we have identified dynamically polarized SKM macrophages and propose that specific macrophage subpopulations contribute to the proinflammatory and senescent traits of old SKM.
Editor's evaluation
In this study, Krasniewski and colleagues describe important findings leveraging single-cell transcriptomics to identify subpopulations of macrophages in the skeletal muscle of aging mice. They present solid evidence for the existence of several new resident subpopulations of skeletal muscle macrophages, spanning a range of polarization states using novel markers. Additionally, they identify a shift in relative abundances of these subpopulations with age, leading to a functional shift in inflammatory marker expression and phagocytic capacity. This work will be useful to researchers in the field of immune aging as a resource.
Introduction
Macrophages are heterogeneous innate immune cells (Shapouri-Moghaddam et al., 2018) that provide the first line of defense against pathogens, but are also deeply involved in inflammation, dead cell removal, wound healing, and tissue remodeling (Mills et al., 2014;Ross et al., 2021;Shapouri-Moghaddam et al., 2018). Macrophages adapt to individual tissues and acquire specific tissue-dependent functions (Wynn et al., 2013). Upon transplantation, tissue-resident macrophages quickly lose their original gene expression patterns and gain host organ markers (Lavin et al., 2014). The tissue environment contributes to determining the tissue-specific protein production by macrophages and thereby establishes tissue-dependent expression patterns and functions (Gautier et al., 2012;Lavin et al., 2014). Hence, the function of macrophages should be studied in the context of their tissue of residence.
Macrophages play diverse functions in tissues by differentiating into specific functional subgroups, a process usually defined as macrophage polarization (Yao et al., 2019). Most macrophages are known to polarize to proinflammatory M1 or anti-inflammatory M2 subgroups (Martinez et al., 2008;Mills et al., 2000;Rath et al., 2014). While such dichotomy largely explains the strikingly different actions of macrophages commonly seen in many tissues, macrophages appear to be more functionally heterogeneous than simply M1 or M2. In this regard, recent flow cytometry and single-cell studies have identified several new macrophage subgroups in arteries, lung interstitium, heart, adipose tissue, and other tissues and organs Dick et al., 2022;Jaitin et al., 2019;Lim et al., 2018;Schyns et al., 2019) with distinct tissue-dependent polarization status. Dissecting polarization in each tissue is thus critical to elucidating shared and tissue-specific macrophage functions.
Skeletal muscle (SKM) contains large numbers of macrophages that play critical roles in injury repair and regeneration (Arnold et al., 2007;Tidball, 2011;Tidball, 2017). Macrophages assume different polarization to play distinct functions at different stages of repair after injury (Scala et al., 2021;Yang and Hu, 2018). In the absence of injury or infection, most macrophages residing in human and mouse SKM were shown to be MRC1 (CD206)+, M2-like macrophages (Cui et al., 2019;Wang et al., 2015). However, the full range of macrophage subgroups and their age-related changes in SKM is poorly understood (Cui and Ferrucci, 2020).
To better understand the complexity of the macrophage polarization status and their changes with aging in mouse SKM, we carried out single-cell transcriptomic analysis. We present evidence that SKM macrophages comprise 11 distinct clusters associated with specific proposed functions. Using a complementary classification based on the presence of membrane markers, SKM macrophages were divided into two large populations based on the presence of LYVE1 and was further classified into four functional subgroups by introducing MHCII as an additional surface marker. We further show that mRNAs that encode proinflammatory proteins and senescence-and aging-related proteins were significantly upregulated in specific macrophage clusters in old SKM. Our findings reveal a dynamic polarization of functional subpopulations of mouse SKM macrophages, including changes toward proinflammatory and senescent phenotypes with aging.
Isolation of macrophages from mouse SKM and single-cell RNA sequencing
To isolate macrophages from SKM, we collected all muscles from hind limbs, including quadriceps, gastrocnemius, tibialis, and soleus, from C57BL/6JN male mice, combined and minced them into small cubes, and isolated mononuclear cells by digesting them with enzymes including collagenase and other proteases (Krasniewski et al., 2022;Liu et al., 2015; Figure 1A). To identify macrophagerich fractions from the mononuclear cell preparation, we carried out flow cytometric analysis based on the presence of CD45, a pan-leukocyte marker, and CD11b, a pan-myeloid lineage marker. As we found previously, CD11b+ cells clearly separated from the rest of the mononuclear cell population (Krasniewski et al., 2022).
For single-cell RNA-sequencing (scRNA-seq) analysis, we collected CD11b+ cells from three young (3 months old [3 m.o.]) and three old (23 m.o.) male mice as biological triplicates by fluorescenceactivated cell sorting (FACS). From each mouse, 5000-10,000 CD11b+ cells were used for single-cell library preparation using the 3' gene expression pipeline from 10× Genomics followed by RNA-seq analysis. We successfully obtained sequences from 2000 to 5000 single cells from each mouse, and a mean of ~80,000 RNA-seq reads per cell corresponding to a median of >2000 genes per cell (Materials and methods; GEO identifier GSE195507). Sequencing analysis showed that >80% of cells expressing Cd11b mRNA were also positive for F4/80 mRNA (Adgre1 mRNA), another common marker for mouse macrophages ( Figure 1B). Those cells expressing both Cd11b mRNA and Adgre1 mRNA were considered SKM macrophages. Very few cells were positive for Ly6g mRNA or Siglecf mRNA (specific markers for neutrophils and eosinophils, respectively; Figure 1-figure supplement 1A), indicating minimal contamination from these cells in our macrophage population.
Identification of 11 macrophage clusters in SKM by unsupervised classification
To gain insight into the subpopulations of SKM macrophages, we pooled scRNA-seq data from young and old mice and performed unsupervised classification. By using FindClusters at a resolution of 0.3, we found 11 clusters (Cl0-10; Figure 1C). Given that we isolated macrophages on three different dates due to technical limitations (lengthy procedure) and mouse availability (Materials and methods), we compared the different datasets to ensure there were no batch effects. Overall, the distribution of macrophages across the 11 clusters was comparable among the biological replicates ( Figure 1figure supplement 1B), and the patterns of transcriptomes were also comparable among the replicates (Figure 1-figure supplement 1C). Those mRNAs that were expressed >1.5-fold higher in a given cluster relative to the other 10 clusters, p<0.05, and were expressed in >25% of macrophages in that cluster are shown in Supplementary file 1. Each cluster showed a distinct gene expression pattern ( Figure 1D).
To investigate the functional features of these clusters, we carried out gene ontology (GO) enrichment analysis using g:Profiler (Materials and methods). Although all clusters shared functional terms general to macrophages, including 'immune system process,' 'defense response,' 'response to stress,' 'cell migration,' and 'cell death,' each cluster also displayed distinct functional associations ( Table 1). The largest cluster, Cl0, showed a more reparative function, with high expression of M2-type genes (Mrc1, Cd163, Lyve1, and Folr2 mRNAs) and reduced proinflammatory function compared to the other clusters ( Figure 1E and Table 1). The second largest cluster, Cl1, showed a similar expression pattern as Cl0 ( Figure 1D), including the expression of M2-type mRNAs (Lyve1 and Folr2 mRNAs), but the expression levels of these mRNAs were lower in Cl1 than in Cl0 (Figure 1-figure supplement 2A, B). This resulted in fewer unique genes in Cl1 when compared to the other 10 clusters (Supplementary file 1). When we excluded Cl0 and compared Cl1 with Cl2-10 (Supplementary file 1, 'Cl1 vs Cl2-10'), Cl1 showed strong enrichment of M2-type mRNAs (Figure 1-figure supplement 2C) and strong association with reparative functions (Table 1). Thus, the two largest clusters, Cl0 and Cl1, account for nearly one-half of total macrophages and displayed M2-like gene expression patterns.
Clusters Cl2-9 showed very low expression of M2 marker genes ( Table 1) and instead displayed more diverse functional associations. Cl2 expressed mRNAs related to inflammation and to the functions of antigen processing and presentation ( Figure 1E and Table 1). The mRNAs present in Cl3 were associated with cellular detoxification, and Cl4 was associated with phagocytosis and expressed elevated MHC class I (MHCI) mRNAs. Cl5 expressed mRNAs strongly associated with the inflammatory response. Cl6 was enriched in mRNAs encoding proteins involved in the response to lipoprotein particles, ATP metabolism, and lipid transport; this cluster also expressed Gpnmb, Spp1, Ctsd, Trem2, and Gdf15 mRNAs, encoding proteins involved in senescence and aging (Henjum et al., 2016;Pazolli et al., 2009;Suda et al., 2021;Suda et al., 2022;Tanaka et al., 2018;Williams et al., 2022), and Fabp5 and Fabp4 mRNAs, encoding proteins implicated in atherosclerosis (Babaev et al., 2011;Furuhashi et al., 2007;Makowski et al., 2001; Figure 1E). The mRNAs expressed in Cl7 were strongly associated with translation and antigen processing and presentation via MHC class II, while those expressed in Cl8 were associated with cell death and phagocytosis, although M2-type markers and MHCII genes were reduced. Of note, S100a8 and S100a9 mRNAs, the most robustly elevated mRNAs in Cl8, encode proinflammatory proteins ( Figure 1E, Supplementary file 1). Cl9 expressed cell cycle-related mRNAs, with elevated Top2a, Mki67, and Cdk1 mRNAs (Supplementary file 1), likely representing a group of reported proliferating macrophages (Wang et al., 2020). The smallest cluster, Cl10 (0.5% of total CD11b+/F4/80+macrophages [ Figure 1C]) was associated with a reparative function, and one-half of Cl10 cells expressed Ly6c1 mRNA (Supplementary file 1). Overall, unsupervised clustering revealed a wide functional heterogeneity of SKM macrophages. GO annotation identified clusters of macrophages expressing mRNAs that were particularly associated with reparative functions (Cl0, Cl1, and Cl10), the promotion of inflammation (Cl2 and Cl5), antigen processing and presentation via MHC class II (Cl2 and Cl7), cellular detoxification (Cl3), phagocytosis (Cl4 and Cl8), lipid homeostasis and cell senescence (Cl6), protein synthesis (Cl7), and proliferation (Cl9).
Identification of M2-like macrophages by membrane marker-based classification
Macrophage membrane markers, including MRC1, CD86, LYVE1, and MHCII, have been successfully used to functionally classify macrophage subgroups (Mantovani et al., 2002;Stein et al., 1992;Dick et al., 2022;Chakarov et al., 2019;Lim et al., 2018). To complement the unsupervised clustering and gain a more comprehensive view of the highly heterogeneous group of SKM macrophages, we further carried out supervised classification with membrane markers.
Initially, we attempted to subgroup SKM macrophages by traditional polarization markers: MRC1, CD86, or CD80. MRC1 is a widely used marker of M2 macrophages, whereas CD80 and CD86 are M1 markers (Mantovani et al., 2002;Stein et al., 1992). However, our scRNA-seq data showed that Mrc1 and Cd86 mRNAs were broadly expressed in ~80% of macrophages, Cd80 mRNA was expressed only in a small population, and most macrophages expressed Mrc1 and Cd86 mRNAs simultaneously ( Figure 2-figure supplement 1A), suggesting they are not ideal to classify SKM macrophages at the transcriptomic level.
Single-cell analysis ( Figure 3B) revealed distinct gene expression patterns across the four supervised subgroups. Those mRNAs that were expressed >1.5-fold higher in a given subgroup relative to the other three subgroups (p<0.01) and were expressed in >25% of macrophages in that subgroup are shown in Supplementary file 3. Functional annotations of the genes showing higher expression in each subgroup revealed that LYVE1+/MHCII lo macrophages (brown box, Figure 3C) expressed higher levels of mRNAs associated with vasculature development and wound healing, similar to the macrophages in Cl0 and Cl1 ( Table 1) and M2 macrophages (Krzyszczyk et al., 2018). LYVE1−/MHCII hi macrophages (blue box, Figure 3C) were associated with antigen processing and presentation, cytokine production, and responses to bacteria and were overall more M1-like (Mills, 2015). LYVE1+/ MHCII hi macrophages (green box, Figure 3C) were a more complex group; GO annotation suggested that they largely shared LYVE1+/MHCII lo (M2-like) functions like vasculature development and wound healing, but also shared LYVE1−/MHCII hi (M1-like) functions such as antigen processing and presentation and cytokine production. Finally, LYVE1−/MHCII lo macrophages (purple box, Figure 3C) were associated with cytotoxicity and phagocytosis. Notably, among the four subgroups, LYVE1+/MHCII hi and LYVE1−/MHCII lo were not previously reported in SKM (Wang et al., 2020), and LYVE1−/MHCII lo macrophages were not reported in any other tissue so far Lim et al., 2018). Thus, in addition to the M2-like (LYVE1+/MHCII lo ) and M1-like (LYVE1−/MHCII hi ) subgroups, supervised classification revealed two new subgroups, LYVE1+/MHCII hi and LYVE1−/MHCII lo , in resting mouse SKM. The supervised classification thus complemented the unsupervised clustering, offering a more comprehensive understanding of the heterogeneity of SKM macrophages.
Confirmation of four SKM macrophage subgroups by flow cytometry
We further analyzed if the macrophage subgroups identified from scRNA-seq could be validated by cell-surface protein markers. As anticipated, flow cytometric analysis using antibodies that recognized LYVE1 and MHCII divided CD45+/CD11b+/F4/80+SKM macrophages from 3 m.o. male mice into four subgroups, LYVE1+/MHCII lo , LYVE1+/MHCII hi , LYVE1−/MHCII hi , and LYVE1−/MHCII lo ( Figure 4A, n=4). Notably, the LYVE1+/MHCII lo , LYVE1−/MHCII hi , and LYVE1−/MHCII lo subgroups showed clear clusters of cells, but LYVE1+/MHCII hi macrophages spread across LYVE1+/MHCII lo and LYVE1−/MHCII hi ( Figure 4A, bottom). The sizes of each subgroup identified by flow cytometry and those identified by single-cell transcriptomics were comparable ( Figures 3A and 4A). While the present study focused on SKM macrophages from male mice, we assessed the overall influence of sex on macrophage polarization in SKM by performing flow cytometric analysis with SKM macrophages from 3 m.o. female mice. As shown, female mice also showed four SKM macrophage subgroups, comparable to male mice (compare Figure 4A with Figure 4-figure supplement 1A; n=4). However, when compared with male SKM macrophages, female SKM LYVE1+/MHCII hi macrophages were ~17% lower, and LYVE1−/ MHCII lo macrophages were ~42% higher (Figure 4-figure supplement 1B). It was recently reported that mouse gender affects macrophage polarization, function, and morphology (Han et al., 2021;Jaillon et al., 2019). The biological significance of the sex-related differences in specific macrophage subgroups in SKM warrants further study.
Macrophage subgroups show distinct phagocytic capacities
To gain insight into the functional differences among the four subgroups, we assessed their phagocytic capacity, a fundamental function of macrophages, using a flow cytometry-based method that measures the uptake of labeled particles (pHrodo Red Escherichia coli Bioparticle assay, Materials and methods). As anticipated, all macrophage subgroups were strongly phagocytic ( Figure 5A), with 97.2% of LYVE1+/MHCII lo , 98.5% of LYVE1+/MHCII hi , 86.4% of LYVE1−/MHCII hi , and 49.6% of LYVE1−/MHCII lo macrophages actively phagocytizing E. coli particles at 37°C; in control incubations, <17.7% macrophages were active at 4°C ( Figure 5A and B, n=3). Significantly, fewer macrophages in the LYVE1−/MHCII lo subgroup were actively phagocytic compared with the other three subgroups ( Figure 5B, p<0.01), but those macrophages that were active showed greater phagocytic capacity than the other three subgroups.
As macrophages showed a range of phagocytic capacities, we divided them into four groups by their geometric mean fluorescence intensity (gMFI): negative (Neg; intensity <10 3 ), low (Lo; 10 3 -10 4 ), medium (Med; 10 4 -10 5 ), and high (Hi;>10 5 ; Figure 5A). The phagocytic capacities of the four macrophage subgroups were similar ( Figure 5C, n=3), and LYVE1+/MHCII lo , LYVE1+/MHCII hi , and LYVE1−/ MHCII hi subgroups showed similar numbers of active macrophages in each of the low-, medium-, and high-capacity groups ( Figure 5D). However, LYVE1−/MHCII lo macrophages showed significantly fewer active macrophages in the Lo group and strikingly more in the Hi capacity group compared to the other three subgroups ( Figure 5D). This finding suggested that the LYVE1−/MHCII lo group comprised two macrophage subpopulations with different phagocytic capacity: a silent group and a highly phagocytic group, each with roughly the same number of macrophages ( Figure 5A, top). We performed efferocytosis assays to further assess the capacity of the macrophage subgroups in phagocytizing apoptotic cells. All four macrophage subgroups showed lower efferocytosis than phagocytosis, but LYVE1−/MHCII lo macrophages again showed relatively greater capacity ( Figure 5-figure supplement 1A, B).
These observations prompted us to further subclassify the LYVE1−/MHCII lo subgroup by unsupervised clustering, which yielded six subclusters (SubCl; Figure 5-figure supplement 2A). GO annotation showed clustering of phagocytosis-related terms only in SubCl0 ( Figure 5-figure supplement 2B). GO annotation suggests that SubCl0 may represent macrophages with higher phagocytic capacity in the LYVE1−/MHCII lo subgroup ( Figure 5A, B and D), although further studies are required for clarification.
Elevated proinflammatory and senescence-related mRNAs in old SKM macrophages
To investigate if there are aging-related changes in SKM macrophages, we further analyzed the genes differentially expressed in macrophages from young and old mouse SKM. The number of live macrophages isolated from SKM was comparable between young and old mice, both in males and females ( Figure 6-figure supplement 1A-D, n=5), and the number of differentially abundant mRNAs was rather small, likely reflecting the lower sensitivity of scRNA-seq analysis. Therefore, we used slightly less strict criteria to find differentially expressed mRNAs: those expressed in >10% of total macrophages in young or old, p<0.01, and fold change >1.3. By these criteria, 41 mRNAs were more abundant, and 47 mRNAs were less abundant in macrophages from old SKM ( Figure 6A). GO annotation suggested that mRNAs encoding proteins involved in chemotaxis of granulocytes (e.g. Cxcl1 and Cxcl2 mRNAs; Girbl et al., 2018) and monocytes (e.g. Ccl2 and Ccl7 mRNAs; Deshmane et al., 2009), and the cellular response to IFN-γ (e.g. Tnf, Cxcl10, and Zfp36 mRNAs) were less abundant in old SKM macrophages ( Figure 6B and C). Some mRNAs encoding M2-like markers (e.g. Lyve1, Folr2, and Mrc1 mRNAs) were also significantly lower in old SKM macrophages ( Figure 6A and C). By contrast, mRNAs encoding proteins related to cellular detoxification (e.g. Gsr, Hp, Prdx1, Prdx5, and Prdx6 mRNAs), inflammation (e.g. S100a8, S100a9, Fabp4, and Il1b mRNAs), senescence (Gpnmb and Spp1 mRNAs), and long-chain fatty acid transporters (Fabp4 and Fabp5 mRNAs; Wang et al., 2018;Babaev et al., 2011;Furuhashi et al., 2007;Pazolli et al., 2009;Suda et al., 2021;Suda et al., 2022) were elevated in old SKM macrophages ( Figure 6B and C; full list in Supplementary file 4).
We next analyzed the relative abundance of macrophage subgroups as a function of age. scRNA-seq indicated that LYVE1+ macrophages decreased, while LYVE1− macrophages increased in old SKM ( Figure 7A). Flow cytometric analysis confirmed this trend, as LYVE1+ macrophages decreased and LYVE1− macrophages increased in old SKM ( Figure 7B -supporting Figure 1A and B, n=4). Thus, both scRNA-seq and flow cytometric analysis confirmed the changes in numbers of LYVE1+ and LYVE1− macrophages in old SKM, consistent with the changes in Lyve1, Folr2, and Mrc1 mRNAs during aging ( Figures 6A, C, 7A and B). All four macrophage subgroups displayed differentially expressed mRNAs. The top 15 elevated and top 10 reduced mRNAs in each subgroup were shown (Figure 7-figure supplement 1C). S100a9 mRNA, encoding a proinflammatory marker, was upregulated in all four subgroups, the senescence-related Gpnmb and Spp1 mRNAs and the fatty acid transporter Fabp5 mRNA were elevated in two MHCII hi subgroups, LYVE1+/MHCII hi and LYVE1−/MHCII hi , while Apoe and Fabp4 mRNAs were only abundant in LYVE1−/MHCII hi macrophages, and Il1b mRNA was elevated only in LYVE1−/MHCII lo macrophages in old SKM (Figure 7-figure supplement 1C).
In unsupervised clustering, Cl0 macrophages, mostly Lyve1+/Folr2+/Mrc1+, were less abundant in old SKM, while macrophages in Cl3, 6, and 8 increased in old SKM ( Figure 7C). Gpnmb, Spp1, and Fabp5 mRNAs were largely concentrated in Cl6, a cluster that was strikingly enriched in old SKM ( Figure 7D), and S100a9 and S100a8 mRNAs were elevated mainly in Cl8 in old SKM ( Figure 7D). Biological replicates of the expression patterns of these genes in young and old SKM (Cl6 and Cl8) are shown (Figure 7-figure supplement 2A,B, respectively).
Overall, gene expression changes suggest that mRNAs related to chemotaxis and responses to pathogens were reduced, but mRNAs encoding proinflammatory, senescence, and cellular detoxification were elevated in macrophages from old SKM. In old SKM macrophages, senescence-related mRNAs were enriched in Cl6 and proinflammatory mRNAs in Cl8.
Discussion
Heterogeneity and functional versatility are critical characteristics of macrophages. Derived from embryonic and/or adult hematopoietic system (Cox et al., 2021), macrophages adapt their gene expression profiles to the tissues in which they reside and play diverse functions by polarizing to different subgroups. In this study, we identified functional subgroups of mouse SKM macrophages by single-cell transcriptomic analysis. Using unbiased clustering, we found 11 clusters, each comprising macrophages associated with reparative, proinflammatory, phagocytic, proliferative, and lipid homeostasis and senescence/aging functions, revealing the striking heterogeneity of SKM macrophages. An alternative classification based on membrane markers further revealed populations that expressed or lacked LYVE1 on their plasma membrane and could be further divided into four subgroups by the levels of cell-surface MHCII proteins. These four subgroups included the well-known M2-like and M1-like macrophages and two additional new subgroups that were confirmed by flow cytometry and immunohistology. Thus, our study has characterized diverse subpopulations of macrophages in resting mouse SKM.
A recent study comprehensively evaluated mouse SKM (Wang et al., 2020) and identified five clusters that largely overlapped with our findings. For example, the 'CD209,' 'CCR2,' and 'proliferating' clusters were very similar to our Cl0, Cl2, and Cl9, respectively ( Figure 1 and Table 1). Moreover, the expression of M2-like markers (e.g. Lyve1, Mrc1, Folr2, and Cd163 mRNAs) suggested that the macrophages in 'unspecified cluster 0' are equivalent to our Cl1 macrophages, which also expressed many M2-like genes, although at lower levels than our Cl0. Excluding Cl0 from the comparison allowed us to identify M2-like features of the Cl1 (Table 1, Supplementary file 1). Furthermore, by analyzing both young and old SKM, we identified important new differences in macrophage clusters, including those associated with senescence and inflammation (Cl6 and Cl8, respectively). Gene expression patterns suggested that clusters 'CD209' and 'CCR2' resembled our LYVE1+/MHCII lo and LYVE1−/MHCII hi subgroups (Figures 3 and 4; Wang et al., 2020). Among the supervised four subgroups, the new LYVE1+/MHCII hi subgroup showed both M1and M2-like gene expression patterns and functional capabilities ( Figure 3C and Figure 4A). We hypothesize that this subgroup may have distinct functions or may have the potential to shift to M2-like LYVE1+/MHCII lo or M1-like LYVE1−/MHCII hi subgroups depending on surrounding conditions. The gene expression heat map showed that LYVE1+/MHCII hi macrophages express features of both LYVE1+/MHCII lo and LYVE1−/MHCII hi , but these patterns are not prominent ( Figure 3B). In flow cytometric analysis, LYVE1+/MHCII hi macrophages spanned two distinct cell clusters, LYVE1+/MHCII lo and LYVE1−/MHCII hi ( Figure 4A), possibly suggesting that LYVE1+/MHCII hi macrophages represent an intermediate stage, even if they stand alone as an independent population ( Figure 4B). The function of LYVE1+/MHCII hi macrophages relative to LYVE1+/MHCII lo and LYVE1 lo /MHCII hi macrophages requires further study.
By contrast, the new LYVE1−/MHCII lo subpopulation, which clearly separated from the other three subgroups by flow cytometric analysis ( Figure 4A), was predicted to have a more distinct 'killing' capacity and may be directly implicated in innate immunity. In phagocytosis assays, the LYVE1−/ MHCII lo subgroup showed fewer active macrophages ( Figure 5A and B), but those that were active had strikingly greater phagocytic capacity compared to the other three subgroups ( Figure 5D). Unbiased further clustering suggested that this specific subgroup consists of strong (SubCl0) and weak (SubCl1-5) phagocytic subclusters ( Figure 5-figure supplement 2), consistent with phagocytosis assays. Importantly, Ly6c mRNA, known to be highly expressed in circulating monocytes (Wolf et al., 2019), was expressed in <3% of LYVE1−/MHCII lo and the other subgroups (not shown), while CD11c, a dendric cell (DC) marker (Singh-Jasuja et al., 2013), and CD49 and CD122, candidate markers for lymphoid lineage natural killer (NK) cells (Nabekura and Lanier, 2016), were not detected in LYVE1−/ MHCII lo or the other subgroups (Supplementary file 3). These data strengthen the view that LYVE1−/ MHCII lo macrophages are distinct from circulating monocytes or DC and NK cells. Additional studies are also needed to characterize the function of LYVE1−/MHCII lo subgroup in SKM.
Our study further revealed aging-related expression changes in macrophages in SKM. Overall, LYVE1+ macrophages were less abundant, and LYVE1− macrophages were more abundant in aged SKM ( Figure 7A and B). Consistent with these observations, S100a8 and S100a9 mRNAs, encoding proinflammatory biomarkers, were significantly elevated in macrophages from aged SKM. Unlike neutrophils, macrophages were reported to express S100A8 and S100A9 at low levels in the absence of stimulation (Hessian et al., 1993;Wang et al., 2018). Often forming heterodimers, S100A8 and S100A9 serve as biomarkers for the diagnosis and therapeutic responses in inflammatory diseases like inflammatory arthritis and inflammatory bowel disease, while blocking their activity resulted in reduced inflammation in mouse models . S100a8 and S100a9 mRNAs were in very low abundance in macrophages from young SKM but were strikingly more abundant in old SKM ( Figures 6C and 7D). The levels of Fabp4, Fabp5, and Il1b mRNAs, encoding additional proinflammatory proteins, were also upregulated in macrophages from old SKM (Figures 6C and 7D). This finding is important because macrophage-derived FABP4 and FABP5 were shown to promote a proinflammatory state in the vasculature during atherosclerosis development (Babaev et al., 2011;Furuhashi et al., 2007;Makowski et al., 2001), in keeping with the proinflammatory status of old SKM. We propose that the expression levels of S100A8 and S100A9 in macrophages can be essential indicators of the inflammatory status of SKM, and possibly other tissues . Several markers of senescence and aging, including Gpnmb and Spp1 mRNAs (Pazolli et al., 2009;Suda et al., 2021;Suda et al., 2022), were also elevated in old SKM macrophages ( Figure 6A-C), suggesting the presence of senescent macrophages. We also found increased expression of mRNAs encoding antioxidant enzymes in old SKM macrophages, possibly reactive to elevated reactive oxygen species (ROS) in aged SKM (Jackson and McArdle, 2011). and Fabp5 mRNAs in old (O) and young (Y) SKM (arrow, Cl6); violin plot representing Gpnmb mRNA (number of macrophages and expression levels) in the different clusters. Bottom, S100a8 and S100a9 mRNAs in O and Y SKM (arrow, Cl8).
The online version of this article includes the following figure supplement(s) for figure 7:
Figure 7 continued
By contrast, several mRNAs encoding neutrophil and monocyte/macrophage chemoattractants (Deshmane et al., 2009;Girbl et al., 2018) were expressed in lower amounts by old SKM macrophages ( Figure 6B and C). In pathological conditions, like injury or infection, neutrophils are the earliest effector cells to infiltrate into the injury site followed by monocytes/macrophages (Forcina et al., 2020). At the same time, it is well known that injury repair and regeneration are slower in old SKM, perhaps due to a delay in leukocyte infiltration at early stages and to reduced CCAAT enhancerbinding protein β function toward regeneration after muscle injury (Blackwell et al., 2015). Thus, the reduced production of chemoattractants in macrophages may contribute to the delayed repair of older SKM.
Finally, unsupervised classification identified specific macrophage clusters significantly affected during SKM aging, particularly Cl6 and Cl8. Gpnmb mRNA, encoding the senescent membrane marker GPNMB (Suda et al., 2021;Suda et al., 2022), was concentrated in Cl6 and was significantly elevated in old SKM macrophages; similarly, senescence-and aging-related Spp1 mRNA and lipid transporter Fabp5 mRNA were highly enriched in Cl6 in old SKM macrophages ( Figures 6A, C and 7D). On the other hand, S100a8 and S100a9 mRNAs were highly concentrated in Cl8 and significantly elevated in the old ( Figures 6A, C and 7D). Thus, unsupervised clustering identified distinct subpopulations specifically altered during aging.
In closing, aging impacts all tissues and organs. Intrinsic and extrinsic factors, including DNA damage, endoplasmic reticulum stress, mitochondrial dysfunction, and a systemic inflammatory environment in aged individuals, inevitably affect the characteristics of macrophages (van Beek et al., 2019). A recent study suggested that macrophages from old SKM contributed to axonal degeneration and demyelination in the neuromuscular junction, and depletion of macrophages led to increased muscle endurance (Yuan et al., 2018). We propose that the age-associated SKM macrophage gene expression patterns identified here represent an important first step toward elucidating how macrophage subpopulations influence the pathophysiology of old SKM.
Materials and methods
Collection of SKMs from young and aged C57BL/6JN mice All mouse work was done under an Animal Study Proposal (ASP #476-LGG-2023) that was reviewed and approved by the Animal Care and Use Committee of the National Institute on Aging (NIA), National Institutes of Health (NIH). Young (Y, 3 m.o.) and aged (O, 22-24 m.o.) male and female inbred C57BL/6JN mice were purchased from the NIA aged rodent colony (https://ros.nia.nih.gov/). The mice were sacrificed, and all hind limb muscles, including quadriceps, hamstring, gastrocnemius, soleus, and tibialis anterior muscles, were harvested. Collected samples were directly used for mononuclear cell isolation or frozen in isopentane chilled by liquid nitrogen and stored at -80°C for immunohistology.
Mononuclear cell isolation from SKM
Tendons, blood vessels, and fat tissues were removed under a dissection microscope. Muscle tissues were finely chopped and minced using dissection scissors to form a slurry. For scRNA-seq analysis, we isolated mononuclear cells with Miltenyi's SKM dissociation kit (#130-098-305) with GentleMACS Octo Dissociator (#130-096-427), as described previously (Krasniewski et al., 2022). For further flow cytometric analysis, we also used an established method (Liu et al., 2015) with slight modifications. Briefly, the muscle slurry was digested with 1000 U/mL Collagenase type II (Gibco, Cat# 17101015) in 10 mL of complete Ham's F-10 medium (Lonza, Cat# BE02-014F) for 70 min with 70 rpm agitation at 37°C. Partially digested muscles were washed in complete Ham's F-10 medium and centrifuged at 400 rcf speed for 5 min, and cell pellet with 8 mL of the remaining suspension (pellet 1) was collected; 42 mL of the supernatant was collected in two tubes (21 mL each) that were filled up to 50 mL with Ham's F-10 media and centrifuged again at 500 rcf for 8 min, and the pellet (pellet 2) was collected. Pellet 1 was subjected to a second round of digestion in 1 mL of 1000 U/mL Collagenase type II and 1 mL of 11 U/mL Dispase II (Thermofisher, Cat# 17105041) along with the 8 mL of the remaining cell suspension, for 20 min with 70 rpm agitation, at 37°C. Digested tissues were aspirated and ejected slowly through 10-mL syringe with 20-gauge needle followed by washing in complete Ham's F-10 media at 400 rcf for 5 min. The supernatant was collected and centrifuged again at 500 rcf for 8 min, and the pellet obtained (pellet 3) was pooled with the pellet 2 above. The suspension of pellets 2+3 was filtered through 40-μm cell strainer (Fisher scientific, Cat # 22363547), followed by final wash in complete Ham's F-10 medium. Cell pellets were resuspended in 1 mL complete Ham's F-10 medium. Cell counting was performed using trypan blue (Invitrogen, Cat# T10282) at a 1:1 ratio in Countess cell counting chamber slides (Invitrogen, Cat# C10228) using Countess II FL Automated Cell Counter (Invitrogen).
Flow cytometric analysis and FACS
Flow cytometric analysis and CD11b+ cell sorting by FACS for scRNA-seq were described in detail in our previous report (Krasniewski et al., 2022).
Macrophage scRNA-seq by 10× Genomics
Macrophages isolated from three 3 m.o. and three 23 m.o. C57BL/6JN male mice (biological triplicates) were stained with CD11b antibody and isolated by FACS analysis. Given that the lengthy collection protocol made it impossible to process all the mice on the same day, we isolated cells in three consecutive weeks: from two young mice (Y1 and Y2) the first week, from two old (O1 and O2) the second week, and from one young mouse (Y3) and one old mouse (O3) the last week. Isolated SKM macrophages were immediately subjected to single-cell library construction without culture to minimize differences related to batch effects. Single-cell libraries were prepared with 10× Genomics Chromium Single Cell 3ʹ Reagent Kits v3 (10× Genomics Cat# PN-1000092) with Chip B (10× Genomics, Cat# PN-1000073) following the manufacturer's protocol. Briefly, 5000-10,000 single macrophages were used for GEM (Gel Bead-in-Emulsion) generation. The cDNAs were then synthesized, and their qualities were assessed on the Agilent Bioanalyzer with High-Sensitivity DNA kit (Agilent Cat# 5067-4626). cDNAs were then used for library preparation and the quality of the final libraries assessed on the Agilent Bioanalyzer with DNA 1000 kit (Agilent, Cat# 5067-1504). The libraries were sequenced with an Illumina NovaSeq 6000 sequencer with a mean depth of ~80,000 (70,876-156,962) RNA-seq reads per cell, corresponding to ~2000 (2027-2256) genes per cell. The numbers of cells from each mouse successfully sequenced and subjected to statistical analysis are as follows: Y1, 3730; Y2, 3325; Y3, 2033 and O1, 3391; O2, 5338; O3, 4097. RNA-seq data were deposited in GEO with identifier GSE195507.
scRNA-seq data analysis scRNA-seq samples were demultiplexed and mapped to the mm10 mouse reference genome using the Cell Ranger software version 3.0.2 (10× Genomics). Further analysis of the matrices of read counts obtained was carried out in R (version 4.1.3) with the Seurat package, version 4.1.0 (Hao et al., 2021), using default parameters in all functions, unless specified otherwise. To exclude empty droplets, poor-quality cells, and potential doublets from downstream analysis, quality control filtering was applied for each sample, which removed cells containing more than 7.5% mitochondrial genes, cells expressing <300 or >7000 transcripts, and below 500 or above 60,000 counts. Genes that were detected in less than 10 cells were eliminated from the analysis. Cells expressing Itgam (Cd11b) and Adgre1 (F4/80) mRNAs, two key macrophage markers, were subjected to further analyses.
Each sample was normalized with the LogNormalize method, and the top 2000 variable genes were selected with the FindVariableFeatures function. The SelectIntegrationFeatures function was applied to find shared variable features across the samples, and the FindIntegrationAnchors function was used to identify inter-sample anchors for integration. Then, the samples were integrated with the IntegrateData function, scaled, and subjected to principal component analysis (PCA).
For supervised cluster analysis, the macrophage dataset was divided into four cell subgroups based on the log-normalized expression values of Lyve1 and H2-Ab1 (MHCII) mRNAs, as follows: LYVE1+/ MHCII lo (Lyve1 >0 and H2-Ab1 <2), LYVE1+/MHCII hi (Lyve1 >0 and H2-Ab1 ≥2), LYVE1−/MHCII hi (Lyve1 ≤0 and H2-Ab1 ≥2), and LYVE1−/MHCII lo (Lyve1 ≤0 and H2-Ab1 <2). For unsupervised cell clustering, a shared nearest neighbor graph was generated with the FindNeighbors function (using the first 30 principal components) and clustered with Louvain algorithm in the FindClusters function with a resolution of 0.3. To visualize and explore cell clusters in a two-dimensional space, the Uniform Manifold Approximation and Projection (UMAP) analysis was performed using the first 30 principal components, as determined by the ElbowPlot method. To identify subpopulations of LYVE1−/MHCII lo cells, the analysis was rerun on the LYVE1−/MHCII lo subgroup, and clusters were visualized with resolution set to 0.3.
Differentially expressed marker genes for each cluster were identified with FindAllMarkers function, and the FindMarkers function was used to find differentially expressed genes across conditions. Those mRNAs that were expressed in at least 25% of cells per cluster were considered for differential gene expression analysis among clusters. mRNAs were defined as differentially expressed if they had an absolute fold change >1.5 and adjusted p-value<0.01. All R processing scripts are included in Supplementary file 6.
Functional annotation of the differentially expressed genes was performed using the web-based tool g:Profiler (Raudvere et al., 2019) (https://biit.cs.ut.ee/gprofiler/gost). The analysis was done with differentially expressed genes in corresponding subpopulations with 'g:SCS threshold' as a 'significance threshold' and 0.05 as the 'user threshold', and functional terms for 'GO biological process' were collected. In addition, we used 14,542 genes detected from young and old macrophages in our scRNA-seq analysis as the background gene set for GO annotation.
RT-qPCR analysis
For RT-qPCR analysis, CD11b+/F4/80+/LYVE1+ and CD11b+/F4/80+/LYVE1− macrophages were isolated by FACS. Sorted LYVE1+ and LYVE1− macrophages were lysed with lysis buffer (RNeasy Mini Kit, Qiagen, Cat# 74104) and stored at -80°C. RNA was then isolated with a QIAcube (Qiagen) instrument following the manufacturer's protocol, using a column for RNase-Free DNase I (Qiagen, Cat# 79254) digestion. The quality of isolated RNAs was assessed on the Agilent TapeStation with RNA Screen Tape (Agilent, Cat# 5067-5576). RT was performed by synthesizing cDNAs from the LYVE1+ and LYVE1− mRNAs with the Superscript III First-Strand Synthesis System (Invitrogen, Cat# 18080051), and qPCR amplification was carried out using ready-to-use Taqman probe/primer sets (Applied Biosystems) to detect expression levels for , and Gapdh (Mm99999915_g1) mRNAs. Two biological replicates (n=2 per replicate) were used for the LYVE1+ and LYVE1− macrophages and assayed in triplicate. The relative RNA levels were calculated after normalizing to Gapdh mRNA using the 2 −ΔΔCt method, and the data were analyzed for significance using Student's t-test.
Phagocytosis assays
Macrophages were isolated from the hind limb muscles of C57BL/6JN male mice as described above. Mononuclear cells from three animals were pooled for each set of experiments, and cells were aliquoted for necessary treatment conditions and technical replicates. Three biological replicates (total nine mice) were analyzed. The phagocytic activity of macrophages was measured by red fluorescence from pHrodo E. coli bioparticles (Invitrogen, Cat# P35361). Briefly, 6×10 6 macrophages were resuspended in 200 μL of Ham's F-10 complete media (Lonza, 12-618 F) containing 10% horse serum (Gibco, 16050114) for each sample. Aliquots of 20 μL of pHrodo E. coli bioparticles, resuspended in live-cell imaging buffer (1 mg/mL, Invitrogen, Cat# A14291DJ) and sonicated for 2 min × 3, with 2 min intervals on ice between each sonication, were added to each cell tube, including appropriate FMO control tubes. Cell suspensions were gently and thoroughly mixed to ensure a homogenous distribution of the E. coli bioparticles. One set of samples was immediately transferred to a CO 2 incubator for 2 hr at 37°C, and another set (negative control) was incubated on ice for 2 hr. After incubation, cells were washed with live cell imaging solution at 400 rcf for 5 min, followed by another wash with PBS. All steps were performed in the dark.
After the phagocytosis assay, cells were stained with viability dye followed by primary antibody staining as described above. Fluorochrome-conjugated antibodies used for staining the cells are as follows: BUV395 Rat anti-mouse CD45, PE-Cyanine7 anti-mouse/human CD11b Antibody, BUV737 Rat anti-mouse F4/80, Brilliant Violet 711 anti-mouse I-A/I-E Antibody, APC Rat anti-mouse LYVE1 Antibody. The cells were acquired on a BD FACSAria Fusion instrument on the same day and analyzed with Flowjo. For all the samples, including controls, CD11b+/F4/80+macrophages were further categorized as high (Hi, >10 5 ), medium (Med, 10 4 -10 5 ), low (Lo, 10 3 -10 4 ), and negative (Neg, <10 3 ) intensity groups based on their ability to engulf labeled bacteria. The relative phagocytosis levels for each group were calculated using gMFI. For statistical analysis, we performed a Shapiro-Wilk test (Mishra et al., 2019) first to assess if our data were normally distributed (GraphPad Prism 8). We found that all data shown in Figure 5B and D, and Figure 4-figure supplement 1B, and Figure 5-figure supplement 1B were normally distributed (not shown). Therefore, we performed parametric tests, one-way ANOVA (Dunnett's multiple comparisons test) for Figure 5D, and two-way ANOVA (Sidak's multiple comparisons test) for Figure 5B and
Efferocytosis assay
To study the engulfment of apoptotic cells by SKM macrophages, hind limb muscles from three male mice were combined as one biological replicate, followed by digestion to generate a mononuclear cell suspension as mentioned above, and pooled for study of phagocytic cells. To generate apoptotic cells, Jurkat T cells, cultured in RPMI 1640 (Thermo Fisher, Cat# 11875-093) with 10% heat-inactivated FBS (Thermo Fisher, Cat# 10438025) at 37°C, 5% CO 2 10 mL were collected from a cell culture flask, washed with PBS, pelleted gently, and resuspended in 1 mL PBS. For labeling Jurkat cells, CFSE (CellTrace CFSE Cell Proliferation Kit, Thermo Fisher, Cat# C34554) was added to cells at final 5 µM concentration and incubated at 37°C for 20 min; 10 mL of RPMI 1640 (10% heat-inactivated FBS) was then added, mixed by vortexing, and further incubated at 37°C for 5 min. After washing, cells were resuspended in 1 mL serum-free RPMI 1640 medium. Apoptosis was induced by treatment with 1 µM staurosporine (Millipore Sigma, Cat# 19-123) for 5 hr at 37°C, 5% CO 2 , followed by washes in RPMI 1640 (10% heat-inactivated FBS) and resuspension in 1 mL RPMI 1640 (10% heat-inactivated FBS) for use in efferocytosis assays. Mononuclear cells from SKM and apoptotic Jurkat T cells were counted and combined at a 1:1 ratio in 2 mL RPMI 1640 (10% heat-inactivated FBS) and incubated for 18 hr at 37°C, 5% CO 2 . Mononuclear cells from SKM without Jurkat cells were used as controls. After incubation for 18 hr, cells were assayed by flow cytometry, as explained above.
• Supplementary file 5. List of antibodies used in this study, including catalog number, company, and dilution used.
• Supplementary file 6. R processing scripts used for data analysis.
Data availability
The single-cell RNA-seq analysis was uploaded to GEO with identifier GSE195507.
The following dataset was generated: | 9,682.4 | 2022-02-23T00:00:00.000 | [
"Biology"
] |
Noise Amplification in Human Tumor Suppression following Gamma Irradiation
The influence of noise on oscillatory motion is a subject of permanent interest, both for fundamental and practical reasons. Cells respond properly to external stimuli by using noisy systems. We have clarified the effect of intrinsic noise on the dynamics in the human cancer cells following gamma irradiation. It is shown that the large amplification and increasing mutual information with delay are due to coherence resonance. Furthermore, frequency domain analysis is used to study the mechanisms.
Mathematical models have achieved oscillatory dynamics by introducing ad hoc time delays to reproduce those that a system incurs when the various molecular components are manufactured [21,22,24,25,28,30,[34][35][36][37][38][39]. Related works have been performed on many fields of research, where delays were found to play a central role. For example, the importance of delay has also recently been recognized in neuronal dynamics [40][41][42][43]. From the mathematical point of view, the difference between single-cell experiments and cell population experiments of simple regulatory networks arises from stochastic events in individual cells that are averaged out in cell population. As the noise intensity of the regulating species increases, the noise intensity of the regulated one also appears to increase. Noise can induce many phenomena in nonlinear dynamical systems, including stochastic resonance, coherence resonance, pattern formation and so on. Lots of original research [44][45][46][47][48][49] and review [50][51][52] articles have been devoted to the stochastic resonance phenomenon. Noise-induced patterns in semiconductor nanostructures have been recently investigated by means of theoretical models [53], where random fluctuations play an essential role. Our presented results are crucially relying on coherence resonance, which has been recently studied for temporal systems [54][55][56][57] and spatially extended systems [58][59][60][61][62][63]. Specifically the relevance of intrinsic noise was elaborated on periodic calcium waves in coupled cells [64] and spatial coherence resonance in excitable biochemical media [65] induced by internal noise. A recent comprehensive review [66] has been done on the stochastic coherence. The large amplification results from the existence of coherence resonance with delay and noise.
In this article, by exploiting a microscopical signal-response model which was proposed in our previous articles [37,38] for studying the dynamical mechanism of the oscillatory behaviors for the activities of p53 and Mdm2 proteins in individual cells, we will explore the mechanism of noise amplification by considering the stochastic events in the cells.
Noise amplification
We introduce the probability Pr(n P ,n M ,t) for the p53 and Mdm2 populations P(t),M(t) ð Þ n P ,n M ð Þ. Then the master equation for Pr(n P ,n M ,t) is given by dPr(n P ,n M ,t) dt~P (n P ,n M )Pr(n P ,n M ,t) where t is added to account for the time delay between the activation of p53 and the induction of Mdm2.
Pr(n P ,n M ,t; m P ,m M ,t{t) is the joint probability distribution of having n P p53 molecules, n M Mdm2 molecules at time t and m P p53 molecules, m M Mdm2 molecules at time t{t. E P and E M are the unitary shift operators, E P Pr(n P ,n M ,t)~Pr(n P z1,n M ,t), E M Pr(n P ,n M ,t)~Pr(n P ,n M z1,t), and S P , a P , c P , m P , S M , a M , m M , K, N and S(t) are the parameters denoting various mechanisms as represented in our previous papers [37,38]. Assume that the time delay t compared with other characteristic times of the system is large, so the processes at time t and t{t are weakly correlated as Pr(n P ,n M ,t; m P ,t{t)~Pr(n P ,n M ,t) Pr(m P ,t{t). Adopting this approximation, we get dPr(n P ,n M ,t) dt~P (n P ,n M )Pr(n P ,n M ,t) The generating function G(s 1 ,s 2 ,t) is defined as G(s 1 ,s 2 ,t)~X We convert the infinite set of ordinary differential equations (3) to a single partial differential equation for G(s 1 ,s 2 ,t), LG The moments of the probability distribution can be found by expanding the generating function near s 1 ,s 2 ð Þ~1,1 ð Þ, LG LG n P ,n M~0 n P n M Pr(n P ,n M ,t)~SP(t)M(t)T, ð8Þ Substituting the expansion into Eq. (5) we obtain where the functions a 1 (t), a 2 (t) and b 12 (t) are Eqs. (6), (7) and (8), respectively. Above is the presentation of the derivation by help of generating functions. In fact, it delivers the same moment equations as the derivation by averaging the master equation. Both approaches run finally into equivalent approximations and problems if decoupling the moments. By the comparison between Eqs. (12) and the corresponding deterministic equations described in our previous papers [37,38], we find that due to the limit cycle of the deterministic description [37,38] changes to a decaying scheme as shown in Fig. 1.
From our numerical results, the reason for the decaying can be considered as dephasing that is mainly caused by differences in the Hill function P N (t{t)= K N zP N (t{t) ð Þbetween the cells. The reason that Hill functions are different is the different states of the different cells at time t{t, i.e., some dephasing happened at time t{t for it to have this impact. The delay further amplifies the differences between cells, causing further dephasing. but if we take two cells with identical state space paths, their Hill functions will also be the same.
This initial difference between the particle numbers of chemical species in different cells, which causes the difference in Hill function at later time, is entirely caused by the intrinsic noise. In fact, any oscillating chemical system, with or without delayed dynamics, will demonstrate dephasing between different realizations, and it isn't an artifact of the delayed dynamics themselves, although this will undoubtedly cause further decorrelation of different realizations at later time, which causes the damped behavior at the population level (which can be thought of as simply taking a large number of realizations of the same stochastic system). Essentially, the value which the cell population converges to is simply approximately the mean of the invariant distribution of the chemical species for one cell, multiplied by the number of cells in the population of interest. This can be shown more rigorously for large populations using the ergodic property of the system. Fig. 2 shows the average power spectrum S P (v) for P(t) time series as a function of frequency v. We also plot the spectrum of the corresponding deterministic model, with delay (e.g., time delay t d~1 00 min in Fig. 2) but without noise, to compare its spectrum with stochastic ones. It can be clearly seen that S P (v) without noise is much smaller than those with noise. Significantly, for the cases with large t (especially, t is larger than the Hopf bifurcation point t c ), there are obvious peaks appearing in S P (v) for P(t) at v=0. This tells us that there is a very large amplification of intrinsic noise due to the resonant effects. This characteristic phenomenon may be termed as coherence resonance with delay and noise, for distinguishing from the '' stochastic resonance'' in common sense.
The peak frequency corresponds to the characteristic frequency of the solution of Eqs. (12), which represents the mean frequency of Fourier transform F P(t) ½ . It is very intriguing that the width of S P (v) represents the dephasing effects, which gives the damping strength on the amplitude of vP(t)w. In order to analyze this resonant oscillation more transparently, we phenomenologically fit S P (v) for the cases with large t (twt c ) shown in Fig. 2
by a formula
where the parameters a, b, V and C are t-dependent. Note that Eq. (14) can be analytically derived with the chemical Langevin equations corresponding to Eqs. (1) under the linearization approximation.
The resultant V and C are shown in the inset picture of Fig. 2. It is obvious that the mean frequency V decreases against t, which is consistent with the conclusion described in our previous article [37]. This is particularly important in biology because in general the low frequency is much more significant than higher frequency in biological systems. C also decreases as t increasing, which means that the oscillation may dominate the evolution of vP(t)w and lasts for rather longer time for very large t. This phenomenon is very intriguing from the biological point of view because it may tell us that the time delay induced by the underlying multistage reactions may weaken the effects of stochasticity and strengthen the oscillation of the relevant molecules.
Mutual information (MI) is meaningful to discuss resonant phenomena [67], so we give the mutual information between the two components p53 and Mdm2 in the nonlinear delayedfeedback network motif. MI is a measure of the amount of information that one random variable interacts with another. It is the reduction in the uncertainty of one random variable due to the MI is zero if and only if the two random variables are strictly independent [69]. Numerically calculating the mutual information between trajectories is in general a formidable task [70], since the joint distribution of continuous variable is smoothly obtained only for large scale stochastic simulation. Intensive work has been done on estimating the mutual information. Khan et al. [71] reviewed three MI estimators: Kernel density estimators, k-nearest neighbor method and Edgeworth expansion. Recently, Suzuki et al. [72] proposed a novel MI estimator called Least-Squares Mutual Information, and discussed the characteristics of the three existing approaches. However, it is accessible here due to the discreteness of the system with the exact delay stochastic simulation algorithm (DSSA) [73]. Information theory [74] provides a natural framework for many problems in biological information processing. The Shannon mutual information has been applied to study the stochastic resonance (SR) [67,75,76], instead of the signal-tonoise ratio (SNR). It can be seen from Fig. 3 that when the DNA is damaged, the phosphorylation of p53 modifies its binding properties to Mdm2, so MI is small; But when the signal is completely resolved, e.g., after t th~1 750 min, MI is large because the amount of p53 is kept low and tightly regulated by the genetic network of Mdm2 and p53 itself. Fig. 4 shows that MI in steady state increases with the increase of time delay due to the coherence resonance.
Fourier analysis
To describe the nonlinear dynamics more clearly, we use frequency domain analysis method to study the mechanisms of the p53 network motif. Our model can be described by a set of chemical Langevin equations corresponding to Eqs. (1), dP(t) dt~S P {a P M(t)P(t)(1{c P S(t)) where g 1 (t) and g 2 (t) are Gaussian white noise, Sg i (t)T~0, Sg i (t)g j (t 0 )T~Sg i g j Td(t{t 0 ), i,j~1,2 f g [77]. In order to analyze our model in the frequency domain, we first replace P(t) and M(t) in Eqs. (18) by where P Ã and M Ã represent the stationary solutions of the deterministic equations of Eqs. (18) with t~0, which satisfy the equations Since we are discussing the solution in the oscillatory scheme, here the signal S(t) is set to be 1. If one hopes to discuss the case of the stationary solution in t??, he can simply set the parameter c P ?0 mathematically, because at t??, the damage can be supposed to be completely resolved as S(t??)~0, i.e., the signal S(t) is first set to 1, later c P is removed because S(t) is becoming 0 if time tends to infinity. Then Eqs. (18) can be rewritten as dp dt~A where and the nonlinear term is kept up to the second order in p(t{t). The Fourier transformations of Eqs. (18) take the form where Since Eqs. (23) are integral equations, they can be solved by interpolation method and truncated at a specific order, the following calculation includes convolutions in the spectral presentation replacing the nonlinear items in the temporal one and truncating them, e.g., we can first solve the linear equation substitute the solutions p(v) and m(v) of Eqs. (25) into Eqs. (24), and then F (v) and G(v) are functions of v. Under the approximations of weak noise and weak negative feedback mechanism, in this paper, the solutions of both p(v) and m(v) are retained up to the second order of g 1 (v) and g 2 (v), because for Gaussian noise, the terms of higher order can be omitted in Ito-Wiener approximation. The validation of such approximations will be discussed with our numerical simulation later. We define and then it can be derived from Eqs. (23) that By defining the intermediate variables, I 4 (v,v 0 )~g 2 (v 0 )g 4 (v 0 )zg 5 (v 0 )zg 2 (v 0 )g 6 (v) ð Þ g 2 (v{v 0 ),ð29dÞ Eqs. (28) can be written as {?
where k,m,n~1,2,3,4 f g . Then the correlation functions of p(v) and m(v) can be expressed as S m (v)~Sm(v)m à (v')T b 1 Sg 2 1 Tzb 2 Sg 1 g 2 Tzb 3 Sg 2 2 T zb 4 Sg 2 1 T 2 zb 5 Sg 2 2 T 2 zb 6 Sg 1 g 2 T 2 zb 7 Sg 2 1 TSg 1 g 2 Tzb 8 Sg 1 g 2 TSg 2 2 T: The parameters a 1 , b 1 , a 2 , b 2 , Á Á Á, a 8 , b 8 represent the contributions of Sg 2 1 T, Sg 1 g 2 T, Á Á Á, Sg 1 g 2 TSg 2 2 T to the correlation functions S p (v) and S m (v), respectively. With the aid of the intermediate variables, those parameters can be expressed as 3,4 (v)zJ 4,3 (v)zL 2,4 (v)zL 4,2 (v)zL 3,4 (v)zL 4,3 (v)Þ, For S p (v), For S m (v), It is worthwhile to mention that a module, which consists of two components, has been discussed recently [78]. They studied a set of coupled Langevin equations for the interacting species. It is very interesting that in the absence of delay and nonlinearity, i.e., a special case of the spectrum as t~0 in Eqs. (55), Eqs. (34) can be reduced as which are consistent with the results presented in the previous paper [78]. Another characteristic feature of Eqs. (34) is that when Sg 1 g 2 T is assumed to be zero, which means that g 1 and g 2 are uncorrelated, both S p (v) and S m (v) can be written as a sum of two contributions which is the so-called spectral addition rule as derived in the previous paper [78]. Even in this case, the coefficients in our results still include the effects coming from the time delay and negative feedback mechanism.
In our numerical calculation, we use the fourth-order stochastic Runge-Kutta method for integrating the chemical Langevin equations (18), and Gaussian integration method to calculate the integrations in Eqs. (34). The numerical results have shown that the correlation functions S p (v) and S m (v) for p(t) and m(t) are precisely consistent between the ones with chemical Langevin equations (18) and the ones with Eqs. (34), which verifies our truncation method in Eqs. (23). The Fourier transforms of p53 and Mdm2 dynamics show that the number of the resonant peaks would increase as time delay increases, which is consistent with the experimental results [12]. The general finding of our analysis is that an increase of delay between activation and induction induces an oscillatory behavior with frequency which corresponds nearly to the delay time. The spectral analysis as well as the mutual information supports this finding. The general finding is in good agreement with our previous work [37].
Bioscience and nanoscience provide pretty examples of nonequilibrium and nonlinear dynamics in which noise can be expected to have unavoidable effects. The methods developed over years to deal with the effects in physical systems will help us to further our understanding of the mechanisms ascribed to nonlinearity and noise.
Methods
The stochastic p53 circuit was characterized by a Monte Carlo method called the exact DSSA. Numerical integration of the equations was carried out using Matlab software. | 3,813.6 | 2011-08-05T00:00:00.000 | [
"Medicine",
"Physics"
] |
Software Engineering Frameworks Used for Serious Games Development in Physical Rehabilitation: Systematic Review
Background: Serious games are a support in the rehabilitation process for treating people with physical disabilities. However, many of these serious games are not adapted to the patient’s needs because they are not developed with a software engineering framework with a set of activities, actions, and tasks that must be executed when creating a software product. Better serious games for rehabilitation will be developed if the patient and therapist requirements are identified, the development is planned
Overview
According to the World Health Organization, over 1 billion people have some form of disability [1], with up to 200 million people having loss or decrease in movement, which limits their ability to perform activities of daily living. To overcome it, they must undergo a rehabilitation program to gradually regain movement and consequently, improve their quality of life.
However, the traditional rehabilitation process is often slow and presents problems such as lack of motivation, boredom, and others; as a result, many patients consider the exercises stressful, and therefore abandon the therapy [2].
To avoid these situations, new ways of conventional therapy support have been used in recent years, such as medicinal treatments, robotics, video games (known as serious games), and others [3], which have contributed to faster rehabilitation when performing exercises in a fun way, allowing the patients to forget their conditions and concentrate on the game.
For this reason, new interaction modes, such as serious games [4], have the potential to provide more attractive, motivating, and enriching experiences for patients who suffer from decreases in movement. Currently, serious game-based physical rehabilitation is an area of research in constant evolution, and therefore, there is the need for developing guidelines adapted from other research fields.
Despite the potential benefits of serious games in physical rehabilitation, many available platforms are inflexible and limited in their scope. Many developments do not follow a process involving a set of activities, actions, or tasks that must be executed when a software product is to be created. As a result, essential elements to the patient's improvement process are ignored within the video game. Some of these elements are motivation, play levels, player commitment, challenges according to the patient's level, clinical evaluation, assessment scales, among others [5,6].
This work aims to describe the software engineering frameworks used in serious games development and their benefits in the physical rehabilitation process.
A Note on Frameworks
The term framework has several meanings depending on the field. For example, it may refer to a model, prescription, guidelines underlying a design and analysis, among others.
The concept of framework is widely used in the field of computer science. However, there is some confusion between the software engineering framework and the application framework. The former provides a skeletal abstraction of a solution to several problems that have some similarities. A software engineering framework will generally outline the steps or phases that must be followed in implementing a solution without getting into the details of what activities are done in each phase [7]. The goal is for developers to use the framework as a guide to creating software systems by applying "building blocks" depending on the problem domain; by contrast, application framework is an integrated set of software artifacts (such as classes, objects, and components) that collaborate to provide a reusable architecture for a family of related applications [8]. They are used to facilitate the development process of applications, reducing time, effort, and costs.
Software engineering framework and application framework should not be confused. The latter is composed of pre-established source codes (eg, data access routines, form validation, templates) that the programmer uses to reduce workload and do not start the project from scratch.
One of the main motivations for applying a software engineering framework in serious game development is to design an efficient and satisfactory system for the patient.
Software Engineering Frameworks and Serious Games
The use of software engineering frameworks for the development of serious games allows the application of a variety of concepts, models, techniques, and artifacts at a high level of abstraction. Being an interdisciplinary field, an orientation on the developed tasks is required. Besides, it is flexible to adapt to changing conditions or personalization according to the final approach of the video game (rehabilitation, education, etc.).
Serious games like other software developments require a "systematic, disciplined, and quantifiable" approach. Every aspect of production, from early stages of system specification to maintenance after its operation, must be established. Below is a set of related activities that lead to the development of a software product [9][10][11][12].
Structural Activities in Software Development
In software engineering, 5 generic structural activities are used during software development [9][10][11][12]: communication, planning, modeling, construction, and deployment. The software process details will be different in each case, but the structural activities are the same. The definitions of the structural activities are presented in Textbox 1.
Benefits of Gamification in Rehabilitation
de Castro-Cros et al [16] analyzed the effects of gamification on the mental imagery brain-computer interface in rehabilitation functional assessments in 10 patients with stroke with hemiparesis in the upper limb and 6 healthy individuals. The authors concluded that user opinions about the game level of entertainment, clarity of rules, narrative, and visual attractiveness were all positive. The patients were consensus about the interest in gamifying stroke rehabilitation sessions. By contrast, Steiner et al [17] performed a scoping review of gamification in the rehabilitation of patients with musculoskeletal disorders of the shoulder. They concluded that gamification is essential in health care to enhance motivation and support therapy in general, especially in chronic diseases and rehabilitation. Other advantages are motivation, avoiding boredom, and distraction from pain and anxiety.
Related Works
A systematic review of literature is a method to identify, evaluate, and interpret all available and relevant research of a particular research question, subject area, or phenomenon of interest. The individual studies that contribute to the systematic review are called primary studies. A systematic review is also considered a form of secondary study [18].
This systematic review includes literature work on developing serious games in physical rehabilitation using a software engineering framework. To identify existing secondary research in the same field, we searched the following electronic databases: IEEE Xplore, ACM Digital Library, Wiley Digital Library, PubMed, ScienceDirect, Taylor & Francis, Mary Ann Liebert, and Springer. Besides, we used Google Scholar as a web source to broaden our results.
The search was realized using the following search string: A1 AND B1 AND (C1 OR C2 OR C3 OR C4 OR C5 OR C6). Textbox 2 shows the terms included in the search string. When this search was performed in the electronic databases, no related secondary studies were identified. Therefore, we sought systematic reviews focused on software engineering frameworks in any field. Table 1 summarizes the secondary studies found.
Mubin et al [19] performed a review on gamification design framework and its application for children with autism. This review aimed to offer gamification solutions for interaction skills. They identified the framework phases in 5 papers and target users/audience/focus. The authors concluded that frameworks have been analyzed from an in-game context but did not emphasize on children with autism. In the literature, studies show that gamification is very effective in the areas of therapy and education for children with autism. The most important contribution of this review is the development of interaction skills. This review identified phases of the development process in some studies (eg, planning, designing). However, it does not explain how users benefit from the process interaction.
Vargas et al [20] developed a systematic mapping study on serious game quality. The aim was to discover the current state of serious games quality initiatives. One of the research questions focused on discovering if quality has been constant throughout the software development cycle or in some stages. The authors showed that 97% of the literature reviewed applied quality in the final phase (product). Only 7.14% focused on quality in the design phase and 1.79% in the requirement phase. This study was included because it identified the phases in which quality was applied: requirement, design, code, and final product.
Tomalá-Gonzáles et al [21] reported on methodologies, game engines currently used in serious games development in various areas (education, cognitive disabilities, and physical rehabilitation), and criteria for game engine selection. From the 27 papers, 8 used a defined methodology such as XP, Cascade, and others, while 3 proposed their own model. The authors concluded that although several software development methodologies can be adapted to serious game development, the best option was the SUM methodology because it is based on Scrum (fast, precise, optimized, and adaptable programming characteristics). However, this review did not make distinctions between framework and methodology. It also did not identify methodology phases nor the benefits of applying a methodology in the learning or rehabilitation process. [20] No a Identifies methodologies and game engines 2020 Review Tomalá-Gonzáles et al [21] a Not available.
Although our work shares similarities with the aforementioned studies, the literature review presented in this paper is different because this review (1) focuses on serious games for physical rehabilitation, (2) identifies the software development stages in each software engineering framework according to the structural activities proposed by Pressman [9], who states that "The software process details will be different in each case, but the structural activities are the same"; (3) identifies contributions of software engineering frameworks to the rehabilitation process; and (4) identifies if the proposed software engineering framework provides objective monitoring of the rehabilitation process.
Research Methodology
The systematic literature review process proposed by Brereton et al [22] was applied for this systematic review. Figure 1 shows the process and steps for each phase. The process consists of 3 main phases: plan review, conduct review, and document review.
The first phase consists of the following steps: (1) describe the main reasons for the literature review, (2) specify a set of research questions, and (3) review the protocol. The second phase comprises 4 steps: (1) identify important research, (2) select primary studies, (3) extract data from primary studies, and (4) synthesize data. Finally, the third phase consists of 3 steps: (1) obtain results, (2) identify the validity threats, and (3) conclusions. Figure 1 shows the literature review process. In the following subsections, we describe the activities carried out in each phase of this systematic literature review.
Research Questions
In this subsection, we present the 9 research questions that guided this study through the investigation to meet the objectives of the systematic review. Table 2 presents these questions.
The research questions can be classified into 4 fields of interest. RQ1 and RQ2 study serious games evaluated in software engineering. These questions identify the number of serious games developed with a software engineering framework and the set of activities, actions, and tasks required.
RQ3 and RQ4 describe framework contributions to the rehabilitation process and implementation of gamification elements. It allows transforming obstacles into positive and fun reinforcements, thereby encouraging patients.
RQ5 and RQ6 are centered on applicability and serious game characteristics for rehabilitation using a software engineering framework. These questions identify relevant data such as target audience, interaction technology for data acquisition, main modalities, among others.
Finally, RQ7, RQ8, and RQ9 studied important aspects to evaluate and provide follow-up of rehabilitation progress depending on the type of exercise.
Question Research question
What framework is used in the development of the serious game? 1 What are the generic structural activities used in frameworks? 2 How the framework contributes to the rehabilitation process? 3 What gamification elements does the framework use? 4 What is the targeted disability contemplated in the frameworks? 5 If the framework includes a case study, which part of the body is rehabilitated? What is the modality of the serious game? Which interaction technology is used?
6 What type of evaluation and number of patients are involved in the clinical trials? 7 Does the framework contemplate a standardized scale to evaluate the patient's rehabilitation progress? 8 Does the framework contemplate adaptability? 9
Search Strategy
The objective of the search strategy was to identify all relevant primary studies. A literature search was conducted to answer the proposed research questions.
The search strategy is an adaptation of Guidelines for Performing Systematic Literature Reviews in Software Engineering [18] and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [23]. Relevant papers were identified by searching in the following databases: PubMed, PEDro (Physiotherapy Evidence Database), IEEE Xplore, ScienceDirect, ACM Digital Library, Mary Ann Liebert, Taylor & Francis Online, Wiley Online Library, and Springer. To build the search string, a list of keywords and their synonyms were identified. Logical operators (AND and OR) and words related to rehabilitation, serious games, and framework were used. The final search strings consisted of the following Boolean expressions: "(A1 AND (B1 OR B2)) AND (C1 OR C2 OR C3) AND D1". The search terms are shown in Textbox 3.
Textbox 3. Search terms for the final search string.
A term
Inclusion Criteria
The systematic review is focused on serious games for physical rehabilitation; clear inclusion criteria were established to determine the eligibility of papers for inclusion in the review.
Only studies with the following criteria were considered eligible for inclusion: serious game papers for physical rehabilitation, papers published in English, and all serious games regardless of the year of development.
Exclusion Criteria
Papers duplicated, papers regarding opinion pieces, existing literature reviews, papers that are not related to rehabilitation using serious games, serious games for educational purposes, and serious games for cognitive rehabilitation were excluded from the study.
Study Selection
First, the search string was used in different databases. Potentially relevant papers were identified after reading the title and abstract. Duplicate papers were removed. Subsequently, an exhaustive verification of compliance with the inclusion and exclusion criteria was carried out to select the papers. Figure 2 shows the item selection process. In the systematic review, 701 papers were included. Table 3 shows the number of documents retrieved from each database.
Extract Data From Primary Studies
After identification, the primary papers were rigorously analyzed in accordance with the following considerations: (1) only the authors of this review can participate in the data collection process; (2) each primary paper should be reviewed with at least two reviewers; (3) each reviewer will collect a set of data from each primary study, then meet with another reviewer to reach an agreement on the data obtained.
Two types of data were extracted for each study: bibliographic (title, author name, country, year, database) and content data, which are used to answer the research questions. Table 4 shows the concentration of the bibliographic data of the primary papers.
Multimedia Appendix 1 shows the percentage of primary studies from each electronic database. IEEE Xplore presented more primary studies than the rest. The following section presents an analysis of the data collected.
RQ1: What Framework Is Used in the Development of the Serious Game?
Only 8 (10%) out of the 83 papers related to physical rehabilitation using a software engineering framework (Multimedia Appendix 2).
In Baranyi et al [24,27], the proposed studies were based on the user-centered design framework. The physiotherapist is important because s/he identifies the needs and limitations of the patients in the rehabilitation process. There are 3 phases: research, design, and evaluation. In research, a physiotherapist conducts brainstorming with the work team and identifies the requirements. Afterward, in the design phase, the team creates mock-ups and a prototype. Finally, the physiotherapist evaluates the application.
Pirovano et al [25] proposed a 4-step procedure to create safe exergames for rehabilitation therapies: exercise definition, virtualization, game design, and secondary goals. In exercise definition, a set of exercises is proposed to cover therapy needs. Each exercise is structured into primary and secondary goals. During virtualization, the team identifies primary goals, and they are implemented into a virtual exercise by defining input (tracking) and output (feedback) requirements through simple graphical elements and specifying interaction mechanisms. Through game design, the virtual exercise is converted into a true exergame. In the last step, there are 2 functionalities. The first is to analyze motion data and identify wrong movements. The second provides feedback to the patients.
In Amengual Alcover et al [26], the serious game development framework follows an iterative process flow structured into 2 dimensions: activities and incremental development. The first dimension is based on 3 approaches: Scrum, the web application development model, and a clinical trial. The activities dimension includes a project initiation activity, an iterative flow composed of 4 basic development activities (planning and control, modeling, construction, and evaluation), and a final clinical study to evaluate the rehabilitation process of the patient through the serious game. Incremental development includes 3 different increments: interaction mechanism, interaction elements, and serious game. In the first increment, an existing device on the market is identified to capture the movements of patients according to their needs. In the second increment, the development team must design the interaction elements that force patients to perform the therapy correctly. The final increment is aimed at designing a serious game that motivates the patient to perform therapy to obtain the best results.
Zain et al [28] proposed a conceptual framework for people with motor impairment, so they can enjoy the experience of playing serious games. The framework's main elements were player skills, challenge, concentration, feedback, immersion, learning opportunities, accessibility, and adaptivity. The proposed framework will help the game designer and developer create a serious game that combines the game's technology with the learning environment. This framework is based on the game flow model. Noveletto et al [29] presented a conceptual model for the design or development of serious games to rehabilitate people with stroke. The framework establishes a relationship between experts and patients to obtain the requirements, considering that the biomedical device and the video game score are used to design serious games.
Afyouni et al [30] proposed a framework consisting of a therapy-driven 3D environment augmented with a natural user interface based on movement. The framework incorporated different adaptation techniques to adjust patient's needs. Patient preferences and limitations were considered key parameters for changing the game, thereby creating personalized games for each patient.
Maggiorini et al [31] presented a framework for serious game development that allows the therapist to remotely control the video game home activities. The objective was to create a more attractive game for the elderly with easily adjustable parameters for therapy adaptability. The framework includes 3 phases of serious game development: requirements definition, empirical validation of requirements list, and design and prototyping.
RQ2: What Are the Generic Structural Activities Used in Frameworks?
The objective of this research question was to identify generic structural activities in primary studies (see the "Background" section). Table 5 summarizes the structural activities and Multimedia Appendix 3 shows the frequency of occurrence of each structural activity in primary studies.
Every study established a communication activity to obtain the requirements. Baranyi et al [24] brainstormed with a physiotherapist to identify relevant problems and needs for patients undergoing rehabilitation. Pirovano et al [25] defined exercises addressing the primary and secondary objectives of rehabilitation. To achieve maximum effectiveness, the exercises are defined in collaboration with therapists. In Amengual Alcover et al [26], the communication began by identifying the context, operational objectives, restrictions, and requirements. Baranyi et al [27] established communication with the therapist to obtain the requirements. Zain et al [28] identified the user abilities, limitations, and behavior, which become requirements for the serious game. Noveletto et al [29] considered experts in the field (health personnel, therapists, etc.) and patients to obtain the requirements. Afyouni et al [30] established the type of game through patient needs, preferences, and limitations, allowing custom game features. Finally, Maggiorini et al [31] analyzed the most diffused issues present in elders' homes (eg, size of rooms, habits) to explore requirements and limitations through an immersive approach.
The planning activity was implemented in Amengual Alcover et al [26]. The goal of this activity was to determine the tasks to perform during the development by identifying the end products and the people who will do the work. The activity includes 3 tasks: planning, scheduling, and tracking.
The modeling activity was performed in several papers. For example, Baranyi et al [24] called it design, elaborating basic models discussed with a therapist. Pirovano et al [25] transformed the exercise requirements into a true exergame by adding all the elements and characteristics of a game and a good game design for the patients. Amengual Alcover et al [26] created models that helped the development team to understand the requirements obtained and the game design. By contrast, Baranyi et al [27] contemplated the use of prototypes to refine user requirements. Finally, Maggiorini et al [31] established a list of technical characteristics (desired) for the prototype creation.
The construction activity was implemented in every study. Developments produce executable software units that will be used by users, through the creation of prototypes to improve the software [24][25][26][27]30,31], or the final product [28,29].
Finally, the user evaluates and provides feedback on the serious game in the deployment stage. In the primary papers, Pirovano et al [25] and Baranyi et al [27], patients were asked to give their opinion to improve the game design and change some aspects of the application.
RQ3: How the Framework Contributes to the Rehabilitation Process?
Baranyi et al [24,27] applied a user-centered design approach to establish constant communication with the physiotherapist who has the experience to identify the needs and limitations of the final user. Serious games are developed with entertainment elements such as levels, rewards, challenges, and adaptability to the patient need, considering special conditions. Pirovano et al [25] proposed the creation of safe exergames, identifying the needs of real exercise besides therapy goals. These needs are incorporated into a video game considering the primary objectives (what a user should do) and secondary objectives (how user actions should be carried out). The former is easily integrated into the gameplay, while the latter aids the patient with corrections or prevention of compensatory movement through analysis of the flow of movement data and wrong movements in real time, thereby providing immediate feedback to patients to correct themselves during the exercise.
Amengual Alcover et al [26] proposed an iterative, prototype-oriented, systematized serious game development process. The proposed process guarantees that products based on this framework are developed and validated by following a coherent and systematic method that leads to high-quality serious games.
For users with motor impairment, Zain et al [28] used flow theory [32] to propose user interface design factors that make their experience enjoyable when playing serious games. This framework includes user interface design factors and aims to establish a conceptual model that can be used by a game designer for efficient game development or an educational practitioner when designing enjoyable serious games for users with motor impairment.
Noveletto et al [29] established a relationship among key stakeholders (experts and patient) and elements (biomedical device and game score) for serious game design. The framework states that a correlation between the game score and clinical tests can aid treatment and evaluation through the biomedical system.
Afyouni et al [30] proposed a framework for video game development with an adaptive and user-centered approach. The framework embeds different adaptation techniques to tailor to patients' needs. The video game adapts to the difficulty level based on the patient's profile and performance in real time. Other aspects such as patient preferences and constraints are considered as key game-changing parameters.
Finally, in Maggiorini et al [31], the framework allowed serious game development with telerehabilitation allowing the therapist to remotely control the video game home activities. It supports parameter adjustments for therapy adaptability. Table 6 summarizes framework contributions. [27], Noveletto et al [29] A physiotherapist establishes communications with patients undergoing rehabilitation to identify the problems and needs.
Communication with health expert
Pirovano et al [25] Exercise can be defined as a sequence of different actions needed to complete it to achieve maximum effectiveness.
Exercise definition
Pirovano et al [25] Provides immediate feedback to the patients for correct exercising.
Analyzes the stream of motion data and identifies in real time wrong movements Baranyi et al [24], Pirovano et al [25], Baranyi et al [27], Noveletto et al [29], Afyouni et al [30], Maggiorini et al [31] Visualize prototypes of serious games from early stages. The therapist or patients identify additional requirements or modify them.
Adaptive approach
Maggiorini et al [31] Therapists can remotely control the video game for home activities and provide adjustable parameters to improve therapy Telerehabilitation
Overview
Gamification allows the transformation of obstacles into positive and fun reinforcement, encouraging users to make the right decisions for their health and well-being [33]. It is essential to keep the patient motivated in physical rehabilitation. For this reason, the software engineering framework is required to use gamification elements. The papers identified the following elements: feedback, motivational factor, adaptability, challenge, levels, immersion, rewards, concentration, and avatar. Table 7 shows the gamification elements in primary studies, and Multimedia Appendix 4 shows the frequency of occurrence of each gamification element.
The gamification elements of primary studies are described below.
Feedback
In Pirovano et al [25], the feedback mechanisms were designed to show the outcome of actions to patients. For instance, whether a target is met or a movement has been successfully performed. Amengual Alcover et al [26] used "mirror feedback," which consists of projecting the user onto the screen and simulating a mirror in such a way that the users can see themselves on the screen at all times. In Baranyi et al [27], the feedback provided was either visual, aural, or haptic. In Zain et al [28], users with motor impairment received feedback on their progress, and when they lose the game, feedback is provided to continue in the right direction. Noveletto et al [29] established that serious same should reward players with feedback on progress. Afyouni et al [30] used a scoring system that was designed to keep track of the number of times the patient successfully passed through the targets. Finally, in Maggiorini et al [31], a skeleton wireframe is drawn in red to provide immediate visual feedback, and an alarm is raised on the screen. Baranyi et al [24] used "goals." The gameplay was based on achieving goals that should act as motivation factors. Pirovano et al [25] established that extrinsic motivational effects can be achieved through careful use of verbal praise, scoring mechanisms, and virtual reward systems. In Amengual Alcover et al [26], the development of new serious games allowed the inclusion of motivational elements to increase engagement. Baranyi et al [27] used rewards in serious games for the user. Finally, Noveletto et al [29] used the "motivational score" to improve attention during rehabilitation sessions. Baranyi et al [24] proposed an adaptive system with the opportunity to adapt the game difficulty. Pirovano et al [25] established that virtual exercises should use dynamic difficulty adaptation, thus further increasing the flexibility of serious games. For Zain et al [28], an adaptive factor was important to design and develop serious games for users with motor impairment because the application, aware of the users' current cognitive load and physical limitations, can change its response, presentation, and interaction flow to improve users' experience and their task performance. In Afyouni et al [30], the framework embeds different adaptation techniques to adapt to the patients' needs. Key game-changing parameters such as patient preferences and constraints are considered. This allows the creation of personalized game features for every patient. Maggiorini et al [31] proposed that remotely controlled serious games may also provide easily tunable parameters to better adapt the game therapy to the actual patient recovery. Baranyi et al [24] proposed the challenge as a "key fact." They considered that the game should not be too easy nor too hard to manage. The game should be sufficiently challenging and match the player's skill level. Zain et al [28] proposed that serious games should also vary the level of difficulty and keep an appropriate pace. Afyouni et al [30] generated therapy-aware navigational movements with multiple levels of difficulty. Baranyi et al [24] stated that the purpose of the serious game developed is to have a rehabilitation system containing different levels that were adapted and created for the individual needs of the patients and to fit their impairments. Amengual Alcover et al [26] considered that serious games must have a definition of different levels in the game. In Baranyi et al [28], when the game is started for the first time, a diagnostic routine is performed; using these data, a baseline for the exercises can be defined by the therapist to get an initial idea about how easy or complex a level might be for a patient. Afyouni et al [30] presented different levels of difficulty based on therapeutic gestures and patient performance.
Immersion
Zain et al [28] considered that immersive games draw players into the game and affect their senses through elements such as audio and narrative.
Reward
Pirovano et al [25] used a scoring system, and at the end of each exergame, a virtual reward is presented to the patients.
Concentration
Zain et al [28] considered that the more concentration a task requires in terms of attention and workload, the more absorbing it will be. The games should grab the player's attention quickly and maintain it throughout the game.
Avatar
Pirovano et al [25] used an avatar for feedback on wrong movements, changing the color of the associated avatar segments. When wrong movements persist for a long time, the game is paused, and a virtual therapist avatar pops up to advise patients.
RQ5: What Is the Targeted Disability Contemplated in the Frameworks?
This specifies whether a study focuses on a particular pathology with loss or decrease in movement. The papers established the following target pathology: 4 defined strokes [24,25,27,29], 2 defined neuromotor disorder [26,30], 1 defined users with motor impairment [28], and 1 defined rehabilitation of the elderly [31]. Stroke is mainly targeted in studies because it is the second cause of death and the third cause of disability worldwide [34]. Multimedia Appendix 5 shows the target disability percentage.
RQ6: If the Framework Includes a Case Study, Which Part of the Body Is Rehabilitated? What Is the Modality of the Serious Game? Which Interaction Technology Is Used?
As Table 8 reports, Baranyi et al [24] presented a prototype that rehabilitates patients with lower limb disabilities with balance and strength exercises using the Wii Fit Balance Board. Pirovano et al [25] developed serious games for upper limb motor rehabilitation therapy using Microsoft Kinect and lower limb with the Wii Fit Balance Board. Amengual Alcover et al [26] also rehabilitated the lower limb by allowing patients to perform repetitions in a video game controlled with Microsoft Kinect, with each repetition varied according to the participant's tolerance and the physiotherapist's recommendations. Baranyi et al [27] performed hand rehabilitation using gesture exercises, touch, and patient movement levels using mobile phone sensors. Zain et al [28] and Noveletto et al [29] did not report any case studies. Afyouni et al [30] developed a serious game for hand rehabilitation using leap motion. Game instructions can be visual (shown on the screen) or voice, depending on the perception capacity of the patient. Finally, Maggiorini et al [31] developed a prototype for rehabilitation using Microsoft Kinect. It only presents the skeleton tracking by a sensor and does not mention whether the video game implements another form of communication with the patient.
RQ7: What Type of Evaluation and Number of Patients Are Involved in the Clinical Trials?
The objective of this research question was to identify clinical validation of the studies and the number of patients involved.
In clinical trials, participants receive specific interventions according to the research plan or protocol created by the researchers to determine the safety and efficacy of the interventions through the measurements of the outcomes [36]. Table 9 shows these data. Amengual Alcover et al [26] conducted a clinical trial and observed a significant difference between before and after scores. They used the Berg Balance Scale and their results showed a significant functional improvement (P=.002) in comparison with assessments before Finally, a significant difference between the pre-and post-assessment scores for the Tinetti Balance Test was observed at the end of the 24-week intervention period. The average score rose from 16 to 21 points on a scale of 28 points. Afyouni et al [30] reported that patients showed improved hand movement using a range of motion. They were able to document 66% of the elements in the video game. No other study reported a clinical trial. An assessment instrument allows to objectively quantify the disability degree of the patient and measure the progress of rehabilitation [37,38]. The evaluation scales in the framework are used to quantify the improvement in rehabilitation depending on the type of exercise applied. During the analysis of primary papers, we identified 3 studies with assessment instruments: Pirovano et al [25], Amengual Alcover et al [26], and Afyouni et al [30].
RQ9: Does the Framework Contemplate Adaptability?
Adaptability is the ability to dynamically adapt difficulty in a video game according to the patient's performance [39]. Five primary studies use this characteristic. In Baranyi et al [24], the physiotherapist designed the level of difficulty of the video game. Pirovano et al [25] established that for every exercise, quality parameters are necessary to define movement properties. This will allow one to determine the challenge degree of the exercises and adapt the difficulty to the patient's needs. Zain et al [28] mentioned that adaptability must consider the following elements: (1) user motivation, (2) experience and abilities, and (3) detection, which identifies necessary changes. Afyouni et al [30] adapted the difficulty level based on the patient's profile and performance in real time. In Maggiorini et al [31] the therapist can remotely adapt the game therapy to the patient's actual recovery. Amengual Alcover et al [26], Baranyi et al [27], and Noveletto et al [29] did not specify how adaptability is incorporated into their game. Multimedia Appendix 6 shows the percentage of frameworks contemplating adaptability.
Threats to Validity of Primary Studies Selected
Although we used search strategies and techniques to systematically find papers by using keywords in the selected databases, these words may vary within papers, so some relevant studies may have been omitted.
Preliminary Findings
We found only few studies that used a systematic process for serious game development. Each framework analyzed in the primary papers highlighted a different feature.
Planning was the structural activity least implemented. This activity is essential because it allows goal definition, objectives, and path to follow in the software development [9,10,40,41].
Regarding applicability, most studies focused on the treatment of stroke sequelae using various modalities such as visual and auditory. The latter should also be implemented to provide feedback on patient performance. Lastly, test cases directly use playable commercial platforms such as Microsoft Kinect and Leap motion as interaction technology.
There were a few clinical trials, and the type of improvement reported varies from one study to another. Amengual Alcover et al [26] used the Berg Balance Scale and Tinetti Balance Test measurements and reported significant functional improvement from previous results. Afyouni et al [30] also reported improvements using range of motion evaluation in hand movement. No other studies used clinical trials to evaluate the framework. Clinical evaluation is essential to objectively validate the patient's rehabilitation progress [36].
Pirovano et al [25], Amengual Alcover et al [26], and Afyouni et al [30] used an evaluation scale to assess the patient's progress. It should also be used as an alternative to adaptability, which is essential for progress and motivation [42]. It is also a technique that can be used to advance game levels [5]. Game levels help engage in the game and could increase treatment compliance.
Each primary study contributes in one or more aspects to the rehabilitation process. Baranyi et al [24,27] applied a user-centered design using which the physiotherapist can personalize individual needs in the serious game. Pirovano et al [25] proposed ease of play and assisted help during the rehabilitation exercise. Amengual Alcover et al [26] developed a framework for motor rehabilitation therapies using a systematized process. Zain et al [28] embraced immersion and fun in the game to maintain flow interest. Noveletto et al [29] used game scores for patient assessment. Afyouni et al [30] developed games with dynamic adaptability that were patient centered. Finally, Maggiorini et al [31] incorporated telerehabilitation and adaptability for the elderly to perform rehabilitation exercises at home (RQ3). Every study applies gamification elements that allow patients to transform rehabilitation obstacles into positive and fun reinforcements. Feedback was the gamification element most applied (7/8, 88%) [25][26][27][28][29][30][31]. Other elements frequently implemented were adaptability [24,25,28,30,31] and motivational factor [24][25][26][27]29] (5/8, 63%) for both; RQ4.
Stroke is the primary pathology on which serious games are focused. This pathology is the third cause of disability worldwide, and a characteristic symptom is the sudden, generally unilateral, loss of muscle strength in the arms, legs, or face (RQ5). Regarding the case studies of limb rehabilitation, 2 studies [24,26] included the lower limb, 1 [25] included lower and upper limbs, 2 [27,30] included hand, 1 [31] full body, and 2 [28,29] did not report case studies. The most used video game modality was visual (6/8, 75%) [24][25][26][27]30,31], followed by auditory (4/8, 50%) [25][26][27]30]. Although each case study used a different motion acquisition technology, every framework allowed a wide variety of the interaction style to obtain the patient's movement and control the serious game (RQ6).
Of the primary papers, 25% (2/8) applied a clinical evaluation to assess patient improvement when the serious game is used [26,30] (RQ7). To objectively evaluate progress and identify abilities and deficits, only 38% (3/8) of the primary studies used an assessment instrument [25,26,30] (RQ8). The assessment used standardized procedures indicating how a patient of any given age and intelligence level would perform. Adjusting the video game difficulty to the patient's rehabilitation needs is essential to avoid frustration or boredom, and 63% (5/8) of the primary studies used adaptability [24,25,28,30,31] (RQ9).
Finally, we recommend that all serious games have to be developed with a framework or methodology. If for some reason this is not possible, they should at least involve the therapist to define requirements. It is also important to include evaluation scales to measure the patient's progress and gamification elements. Besides, the video game development must be an iterative and incremental process based on generic structural activities and the patient should be considered in the validation and feedback phases.
We propose the following recommendations for future studies: • Carry out a study of the papers that propose a methodology for serious game development.
• Study software engineering framework proposals in serious games from other fields, such as education.
• Develop a software engineering framework applying all the structural activities and gamification elements for the creation of serious games for physical rehabilitation. | 9,076.2 | 2020-11-17T00:00:00.000 | [
"Medicine",
"Engineering",
"Computer Science"
] |
Genotyping of hepatitis C virus by nucleotide sequencing: A robust method for a diagnostic laboratory
Graphical abstract
Specifications
Immunology and Microbiology More specific subject area Molecular diagnostics of viruses Method name HCV genotyping Name and reference of original method Other HCV amplification methods exist, but this method has been independently designed, developed and established.
Method details
The HCV genotyping method described here was developed for a diagnostic laboratory workflow, aiming at a simple and straightforward protocol. A requirement for the method was that all genotypes should be amplified using only one primer pair in a single amplification reaction. The method utilizes the detailed and objective information provided by nucleotide sequencing, but requires no specific analysis skills or costly tools to determine the main HCV genotype.
RNA extraction and PCR amplification 1) Extract nucleic acids using the automated NucliSENS easyMAG extraction system (bioMérieux, Marcy-l'Étoile, FR). Use 200 ml of serum and Generic 2.0.1 protocol for extraction, and elute nucleic acids into 25 ml of NucliSens Extraction Buffer (BioMerieux). If PCR amplification is not performed directly after extraction, the nucleic acid preparations can be stored in À70 C. 2) For PCR amplification, use SuperScript III One-Step RT-PCR System with Platinum Taq High Fidelity polymerase (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA), where reverse transcription (RT) and PCR reactions are run in one reaction.
4) Run the reactions in a standard thermal cycler. In our laboratory the DNA Engine Tetrad12 Peltier Thermal Cycler (BioRad, Hercules, CA, USA) was used with the following RT-PCR conditions: cDNA synthesis for 30 min at 55 C, RT-enzyme inactivation for 2 min at 94 C, 40 cycles of 15 s denaturation at 94 C, 30 s annealing at 58 C and 1 min extension at 68 C, followed by a final extension for 5 min at 68 C and cooling to 4 C. 5) The success of amplification can be inspected using gel electrophoresis. In our laboratory 1.8% agarose gels stained with ethidium bromide, or the fast electrophoresis FlashGel System (Lonza, Basel, Switzerland) were used. The expected product length is 374 bp.
Sanger sequencing and sequence analysis
1) The amplification products should be sequenced in both directions using standard Sanger sequencing and the amplification primers described above. Our samples were sequenced at the Institute of Biotechnology, University of Helsinki. 2) Inspect the retrieved chromatograms by using a standard program, for example Chromas (http:// technelysium.com.au/wp/chromas/) or 4peaks (http://nucleobytes.com/4peaks/). Copy the high quality sequence portion with unambiguous individual peaks for analysis. The forward and reverse sequences are analysed separately for each sample without making one consensus sequence.
3) Paste the sequences in FASTA or text format to NCBI's Internet based genotyping tool available at: http://www.ncbi.nlm.nih.gov/projects/genotyping [1]. The tool compares the inserted sequence to a HCV sequence database and gives a list of best matches with distinct genotype and subtype information arranged according to scoring points, highest scores indicating the best match. Sequences can also be analysed using the Standard Nucleotide BLAST, available at: https://blast. ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastSearch [2].
Samples
All samples (N = 238) used in the establishment and validation of this method had been previously genotyped at the Helsinki University Hospital Laboratory (HUSLAB), Department of Virology and Immunology, by using the Versant HCV Genotype 2.0 (Siemens Healthcare, Tarrytown, NY, USA) line probe assay (LiPA). Viral loads were quantified for a proportion of samples using the COBAS1 AmpliPrep/COBAS1 TaqMan1 HCV Quantitative Test version 2.0 (Roche Molecular Diagnostics, Pleasanton, CA, USA). After initial analysis the samples had been frozen and stored at À20 C.
Selection of primers
For primer design 5 0 UTR, core/E1 and NS5B regions were selected. For each region 2-4 primer pairs were designed by aligning and comparing reference sequences within the selected regions and by selecting sequences which would share maximal homology between different genotypes. The requirement was that each genotype should be amplified using only one primer pair in a single amplification reaction. For the design process the Basic Local Alignment Search Tool (BLASTN) 2.2.27+ [2] and Primer-BLAST [3] programs were used. The reference sequences were M62321 (genotype 1a), D90208 (1b), D14853 (1c), D00944 (2a), D10988 (2b), D50409 (2c), D17763 (3a), D49374 (3b), Y11604 (4a), Y13184 (5a) and Y12083 (6a). Some primer sequences that had been previously published from our laboratory were utilized as well [4]. All primers (Integrated DNA Technologies, Coralville, IA, USA) were initially tested at annealing temperatures of 50 C and 55 C, after which the temperatures were further adjusted at intervals of 3 C starting from the temperature which produced stronger amplification products for each genotype. All primer sequences and annealing temperatures for each primer pair, as well as success of amplification are presented in Table 1.
PCR optimization
For initial primer testing, a set of eight samples representing all main genotypes and most common subtypes (1a,1b, 2a, 2b, 3a, 4, 5a and 6) was used. Out of all primers, only 5 0 UTR1F and 5 0 UTR1R were able to amplify all samples in our testing set, and were thus selected for further optimization. Reaction conditions were adjusted for the following parameters: annealing temperature, primer concentration, magnesium concentration, amount of template and number of amplification cycles. Using the optimized PCR conditions presented above, a total of 238 serum samples were amplified ( Table 2). Strong amplification products were generally obtained from samples whose viral loads were over 10 000 IU/ml. Distinct but weaker products were obtained from samples whose known viral loads were 1020-9810 IU/ ml. Samples which remained negative in gel had viral loads of 52-2550 IU/ml. Amplification with the established method did not directly correlate with viral load. This may be due to long storage time and multiple freeze-thaw cycles of the samples. The sensitivity of the method was found adequate for genotyping of patient samples, whose viral loads are generally between 10 4 -10 7 IU/mL.
Sequencing
Altogether 201 amplification products were sequenced (Table 2), including nine samples where no amplification product was observed in agarose gel. In total, 197 genotyping results were obtained, including five gel-negative samples. The four samples where no genotyping result was obtained were all gel-negative amplification reactions. The length of the obtained sequences was approximately 300 bp for the majority of samples. The sequence based genotyping results were consistent with LiPA results except for three samples, where a different result at the main genotype level was obtained. For one sample the LiPA method yielded an equivocal result of genotype 2 while sequences in both directions matched genotype 3a. For the second sample both sequences indicated genotype 1b whereas LiPA identified genotype 5a. For the third equivocal sample no amplification product was seen in gel, and only a short reverse sequence indicating genotype 2k was derived, while the LiPA result indicated genotype 1. For two additional samples, two alternative genotypes were reported from LiPA analysis: 2b/1a and 1a/4. The forward and reverse sequences from both of these samples clearly matched genotype 1. Genotypes which were inconsistently amplified are given in brackets. * Primers were tested using two different annealing temperatures which performed equally.
Conclusions 5 0 UTR sequences suit well for main HCV genotype determination and in certain cases for subtype determination as well. However, because of its conserved nature, the 5 0 UTR cannot be applied to reliably distinguish genotype 1 subtypes. The established genotyping method is straightforward and robust, fits well to the diagnostic laboratory workflow, and does not require costly instrumentation or specialized sequence analysis skills. | 1,726.2 | 2018-04-16T00:00:00.000 | [
"Biology"
] |
CELLA : FPGA Based Candidate Execution with Low Latency Approach for Soft MIMO Detector
This paper describes the design and Field Programmable Gate Array (FPGA) based 4 × 4 breadth heuristic Multiple-Input—Multiple-Output (MIMO) decoder using 16 and 64 Quadrature Amplitude Modulation (QAM) schemes. The intention of this work is to observe the performance of Candidate Execution with Low Latency Approach for soft MIMO detector in FPGA (CELLA). The Smart Ordering and Candidate Adding (SOCA), Parallel Candidate Adding (PCA) and Backward Candidate Adding (BCA) give better performance in terms of Bit Error Rate (BER) or chip level service. In order to attain both BER and FPGA level performance in a single system, CELLA is developed in this work. Simulation and experimental results demonstrate the effectiveness of the proposed work under the system 4 × 4 MIMO-OFDM employing 16 QAM and 64 QAM. The proposed experiment is implemented in Xilinx Virtex 5 C5VSX240T. The performance results, in terms of FPGA level 76% slice reduction, 58.76% throughput improvement, 75% power reduction and 87% latency reduction, are achieved. The BER performance is observed and compared with the conventional algorithms. Thus, the proposed work achieves better outcome than the conventional work.
Introduction
In today's data-rich world, MIMO has become an energetic element of wireless communication standard for high data rate communications.MIMO is a method for multiplying the capacity using multiple transmit and for receiving antennas to make use of multipath propagation.The method of incorporating turbo code in MIMO system is labeled as turbo coded MIMO system.Using the sphere decoder, a simple method is used to detect and decode linear space-time mapping with any channel code and it is called "soft" inputs and outputs [1].To simplify the exponentially complex search problem in ML decoders for MIMO systems with greater modulation constellations, sphere decoders are accomplished by realizing near-ML performance with reasonable complexity.Moreover, the lattice decoders can be stretched to care soft decision outputs and, hence, be used in an iterative MIMO receiver.The lattice decoding algorithms have two kinds of application strategies.The first one is called Fincke-Pohst strategy and Schnorr-Euchner strategy.To avoid confusion, the lattice decoder using the Fincke-Pohst strategy is called a Sphere Decoder (SD), and the lattice decoder using the Schnorr-Euchner strategy is called SE.A List Sphere Decoding (LSD) algorithm can be used to effectively find the candidate list.The recognized list type of MIMO decoding algorithms is List Sphere Decoding (LSD) algorithm.The two major problems of the List Sphere Decoder (LSD) are variable complexity and the sequential nature of its tree search.To overcome these issues, a Fixed-complexity Sphere Decoder (FSD) is modified as List FSD (LFSD) [2], which performs iterative detection and decodes in turbo Multiple Input Multiple Output (MIMO) systems.This method obtains a list of candidates for calculating likelihood information about the transmitted bits required by the outer decoder [2].Because of lesser amount of information about expanded candidates, Soft-FSD (SFSD) can be used in turbo-MIMO systems to replace extrinsic soft-information to the outer decoder.It is used to provide the exact performance for the LSD with constant throughput and fixed complexity, by making the algorithm more suitable for hardware implementation [2] [3].The negative aspects of the soft decoder are variable throughput, noise level and the channel conditions.
In [4] FPGA implementation of a new detection algorithm based on SD is introduced for MIMO systems.This paper algorithm overcomes the main drawback of the SD: its variable throughput, depending on the noise level and the channel environments.The performance results of Barbero et al. show that the algorithm is extremely parallelizable and can be completely pipelined.In [5] PCA scheme is used for the soft-output sphere decoder to identify the partial Maximum A Posteriori Estimation (MAP) estimation based on parent nodes in the place of child nodes.It provides low decoding latency and it is suitable for fully pipelined hardware implementation.In order to achieve optimal error rate performance with minimal power consumption, an adaptive switching detection algorithm is designed to incorporate multiple thresholds within the detector, which is implemented in XilinxVirtex-5 simulation hardware [6].
Michael et al. have introduced a low-cost parallel programmable co-processor, which can achieve high throughput in ASIC/FPGA designs [7].In [8] a novel MIMO detection algorithm is introduced which is also called Modified Fixed-Complexity Soft-Output (MFCSO) detection.This MFCSO used achieves better performance in terms of bandwidth and hardware implementation cost.The Maximum Likelihood Detector (MLD), QR decomposition with M-algorithm (QRM) and Fixed-complexity Sphere Decoding (FSD) [9] are used to calculate soft information of each coded bit.This approach can retrieve the coded bits and thus can recalculate the soft information with improved error performance under the system with 4 × 4 MIMO-OFDM employing 16 QAM and 64 QAM.Parallel bidirectional scheme [10] obtains a list of candidates to calculate likelihood information in parallel and each stage corresponds to one direction of the path selection process.Due to its parallel nature, it is well suited for hardware implementation, and it achieves better performance with lower complexity than a LFSD.For the data detection stage based on column-norm categorizing fully parallel GPU and multicore are used in [11].These modules are developed to match the multicore architecture efficiently which has lesser computational time.It supports some of the configurations in the Long Term Evolution (LTE) standard [11].The rest of this paper is organized as follows.Section 2 addresses the system model.Conventional detectors are discussed in Section 3. Proposed work and its module details are discussed in Section 4. The experimental results are presented in Section 5. Finally, the conclusion is presented in Section 6.
System Model
The system model specification is similar to that of Takuma et al. [9].Here, in Low Density Parity Check (LDPC) coded MIMO system, N t represents transmit antennas and N r represents receive antennas (N r ≥ N t ).
These antennas are identically distributed.The binary information (input) is passed through LDPC encoder (by a rate γ c ) and an interleaver.The final results are mapped into symbols.These symbols are demultiplexed into N t sub modules and passed through OFDM section.The vector consisting of the N r receives symbols and is given by, where is the transmit vector with normalized transmit power 2 1 is the vector of independent and identically distributed; complex Additive White Gaussian Noise (AWGN) with variance of σ 2 = N 0 , and H is the N r × N t Rayleigh fading channel matrix, where its element h ij is the complex transfer function from transmitter j to receiver i with . The receiver section consists of MIMO detector, deinterleaver and LDPC decoder.The calculation of A Posteriori Probability (APP) for each of the coded bits b (j,k) is taken in the form of Log Likelihood Ratio (LLR).From [9], the LLR equation is refined as per the proposed system.
( ) , 0 0 min min The list size upsets the complexity of the system, since the computational load increases linearly with the list size.To avoid this issue, the insertion of the list is removed from [9] and it is represented in Equation (2).
Conventional Detectors
The conventional algorithm for visited nodes and the list size are listed in Table 1 and Table 2.The maximum level of complexity is MLD, where visited nodes are 69,904 and the list size is 65,536 in 16 QAM.
The above values are reduced by introducing QRM concept.The visited node is 784 and the list size is 16 in 16 QAM whereas in the 64 QAM, the visited node is 5824 and the list size is 30.After that, LFSD, PCA and BCA combination of QRM-BCA and PCA-BCA visited node and list node are listed for both 16 QAM and 64 QAM.On comparing these concepts, the proposed methodology describes lesser consumption of visited nodes in the order of 34 and there is a decrease in the value of list size in the order of 16 in the 16 QAM.On the other hand, if we are considering 64 QAM case, visited nodes and list size do not give a drastic change like the abovedescribed methodologies.This minimizes the size of Look Up Table (LUT).The decrease in the LUT simultaneously reduces the use of nodes and therefore, the slices are partially used in a considerable percentage.
Table 1.The number of visited nodes and list size.
Proposed Work
SOCA scheme is used to identify the partial MAP using parent nodes [12].Conventional detectors are complex in nature, because it has maximum number of child nodes to identify the partial MAP.In SOCA, PCA [5] and BCA, the maximum number of child and parent nodes are available.In conventional architecture, the activities of child and parent nodes differ from under working node, but the overall architecture is the same as that of the previous work.In Figure 1, PCA, SOCA and CELLA architecture layouts are indicated.In order to reduce the complexity and for further performance in CELLA, a child node and single PE are represented to identify the partial MAP.
Candidate Execution with Low Latency Approach (CELLA)
The counterhypotheses of conventional SOCA, PCA and BCA algorithms are added in parallel with other candidates.From the hardware aspects, Look-Up Table (LUT) is introduced for counterhypotheses, and which is used to reduce the latency [5].The overall resources in SOCA, PCA and BCA slightly differ from one another.Takuma et al. [9] report the visited node and the list size of conventional work, and they are indicated in Table 1 and Table 2.The proposed work is compared with the conventional FPGA family.The major problem of the conventional research (FSD [4], SOCA [12], and PCA [5]) is the performance analysis, which is based on MATLAB Simulink environment model with Xilinx platform.
In order to convert the Simulink to Xilinx, conversion process utilizes more LUT and memory.Due to this complexity, the performance degradation occurs in the conventional architecture in FPGA level.To evade this issue, the conventional architecture is modeled using a VHDL implementation in Xilinx ISE Design Suite 12.1.
The pseudo-code of the CELLA scheme is given in Figure 2 (also refer pseudo-code of the PCA [5] in Figure 1 and pseudo-code of the SOCA [12] in Figure 2).The identification of the partial MAP node is performed in SOCA and PCA.The hardware complexity is slightly reduced in PCA than SOCA.For aggressive low complexity, the proposed concept is introduced.Here, the identification of the partial MAP node takes place within a single PE and MIN Search Unit (MSU).But, PCA and SOCA architectures have same number of extended child nodes with MSUs and parent node.In the proposed system, the identification of partial MAP node is performed by parent node without any additional child node (see Figure 2).This deals with the minimized consumption of the nodes with the above-described elements.It works in a conventional way but with the reduction in the consumption of nodes.This makes the best performance in the usage of nodes and when it is seen microscopically, the motto of the power reduction is achieved at the rate of 141 mw and 40 mw, which correspond to the 64 QAM and 16 QAM, respectively.
Hardware Architecture
Figure 2 shows the top-level architecture of the SOCA, PCA, and the proposed schemes in 4 × 4 16 QAM and 64 QAM systems.It is assumed that the Processing Elements (PEs) have been implemented to compute the required Euclidean Distance (ED) metrics.This experimental case study of the proposed system is carried out using Xilinx Virtex 5 XC5VSX240T.All 4 × 4 architectures are represented in a pipeline manner so that, it takes The clock frequency obtained here is in the range of 150 MHz for two modulation architectures.They turn out with the power reduction in the range of 40 mw and 141 mw in 16 QAM and 64 QAM, respectively.The abovementioned features are extended with the previously proposed metrics, and there is an improved standard in terms of reduction in latency, reduction in usage of slices, and improved data throughput.The most important term is the reduction in the usage of power that makes a standard among all the previous mentioned standards.When the throughput of CELLA is compared, the reduction in latency cycles also makes a greater contribution in the throughput for both 16 QAM and 64 QAM architectures.It is detailed in the FPGA level performance, and that is also independent in the amount of noise level.
Result and Discussion
The performance results are observed in simulation platform via MATLAB environment and FPGA platform via Xilinx ISE Design Suite 12.1.The Bit Error Rate (BER) results of SOCA, PCA, BCA, PCA + BCA, and CELLA are observed.
BER Performance
The BER performance has been obtained by computer simulation using 64-subcarrier OFDM per transmit antenna.Block Rayleigh fading is used for the channel model, where the ordering is required only once at the beginning of each received block.The rate of the LDPC code is chosen as ɣ c =1/2, and the length of the code word is N = 3072 bits with maximum number of sum-product iteration T = 40, and L max = 8.First, Figure 3 compares the BER performance of the SOCA, BCA, PCA, PCA-BCA, and the CELLA using sibling nodes.It is observed from the case of CELLA work, even if the sibling nodes are selected, there is a performance improvement in the proposed work and it is better than other conventional works.The sibling nodes indicate the difference of throughput (E b /N o ) of sibling nodes and the difference between the BER with the proposed and also the conventional algorithms.
FPGA Level Performance
In Table 3, the performance outcomes of the conventional, and the proposed works are compared.The various algorithms are analyzed.In optimized FSD-B algorithm [2], 16 QAM is used to obtain 24,815 slices, 39,800 FFs and 31,759 LUT.The latency and throughput are 78 and 450 Mbps, respectively.Similarly, these results are obtained for algorithms such as K-Best SD [3], PIPSD [13] and FSD 2 [4], and which are implemented in Xilinx platform.The power values are not observed in these methods.Xiang et al. introduced PCA method [5] to attain better results compared to LFSD and SOCA works.The PCA results in 9471 slices, 22,814 FFs, 24,126 LUT, 174 DSP and 70 BRAM with latency cycles of 109 without power calculation.To overcome these problems and to reduce the area, a new method with various modulation levels (16 QAM and 64 QAM) is introduced in The experimental results of the proposed system are implemented in Xilinx Virtex5 XC5VSX240T platform.
The performance analysis at FPGA level attains 76% slice reduction, 58.76% throughput improvement at 20 db, 75% power reduction and 87% latency reduction when compared to the conventional work.The BER performance is also computed for the proposed and conventional algorithms.It minimizes the noise level and improves the performance boost at 20 db/s.
Conclusion
In this work, a candidate execution with low latency approach has been introduced for a turbo coded MIMO system.The proposed system identifies partial MAP nodes during online process and adds counterhypothesis in parallel within the parent candidate, which indicates the use of child nodes.This is not included here to minimize the ED distance metrics.The experimental results of the proposed system are implemented in Xilinx Virtex 5 XC5VSX240T platform.The performance analysis at FPGA level attains 76% slice reduction, 58.76% throughput improvement at 20 db, 75% power reduction and 87% latency reduction when compared to the conventional work.The BER performance is also computed for the proposed and conventional algorithms.It minimizes the noise level and improves the performance boost at 20 db/s.Thus, it proves the execution of the nodes in the confined region compared to other algorithms.Thus, CELLA achieves the best performance than the conventional work.
Figure 1 .
Figure 1.Layout of conventional and proposed detector.only 4 cycles to obtain the entire list for every transmitted vector after a single latency, while the detector receives a throughput of 400 Mbps at a clock frequency of 100 MHz.The functional modules of MSU are comparator and decision logic.The MSU is used to identify the local MAP node and the architecture is made so that, each PE processes 4 nodes sequentially.In PCA, 3 MSUs are employed to deal with the counterhypotheses list, which contains (4 × 3) + (4 × 2) + 4 = 24 nodes.To handle it, 6 numbers of PEs are required, whereas in the proposed scheme, only one MSU and single PE are required to deal with the counterhypotheses list, which contains 4 × 1 + 4 × 1 + 4 = 12 nodes.As a result of hardware elimination (Removal of 4 PEs and MSU) in the proposed work, the performance improvements in terms of throughput give a range of 970 Mbps at 16 QAM and 830 Mbps at 64 QAM.
Figure 2 .
Figure 2. The proposed scheme in the form of algorithm.
Figure 3 .
Figure 3. BER performance using sibling node with the length of code word 3072 rate 1/2 LDPC code with 16-QAM, and 64-QAM in a 4 × 4 MIMO.
Table 2 .
The number of visited nodes and list size with 16-QAM and 64-QAM.
Table 3 .
Performance comparison of conventional and proposed work.They obtain 2215 slices, 4918 FFs, and 4982 LUT with latency of 14 cycles in 16 QAM.Similarly, these results are obtained in 64 QAM.The proposed method achieves the power value of 40 mw, 141 mw in 16 QAM and 64 QAM, respectively.This method is implemented in (FPGA platform) Xilinx Virtex5 XC5VSX240T. | 4,002.6 | 2016-06-02T00:00:00.000 | [
"Computer Science",
"Engineering"
] |
Ethics roundtable debate: should a sedated dying patient be wakened to say goodbye to family?
Intensivists have the potential to maintain vital signs almost indefinitely, but not necessarily the potential to make moribund patients whole. Current ethical and legal mandates push patient autonomy to the forefront of care plans. When patients are incapable of expressing their preferences, surrogates are given proxy. It is unclear how these preferences extend to the very brink of inevitable death. Some say that patients should have the opportunity and authority to direct their death spiral. Others say it would be impossible for them to do so because an inevitable death spiral cannot be effectively palliated. Humane principles dictate they be spared the unrelenting discomfort surrounding death. The present case examines such a patient and the issues surrounding a unique end-of-life decision.
Introduction Brian Woodcock
The ability of modern medicine to maintain the human body by artificial means has progressed dramatically. Even in the face of complete failure of respiratory, cardiac, and renal systems, artificial organ replacements can maintain life to a point beyond that where any feasible recovery is possible. With artificial ventilation, ventricular assist devices, and extracorporeal membrane oxygenation, it can be extremely difficult to die in a medical center with access to these advanced modalities of life support. Problems can arise when the patient reaches a point where technology is maintaining 'life' but there is no way for life to continue without the technology. Withdrawal of this support can raise more difficult questions than during institution of support. The case we are presenting concerns the dilemma of whether a patient would want to awaken before life support is withdrawn and he/she is allowed to die. And in this circumstance, who should make that decision?
The case
A 57-year-old patient suffered intraoperative complications and failed to wean from cardiopulmonary bypass during a coronary artery bypass graft operation. Inotropic drugs and intra-aortic balloon counterpulsation failed to restore an adequate circulation. The patient was transferred to the intensive care unit (ICU) on multiple life support systems, including mechanical ventilation, and left and right ventricular assist devices.
Cardiac transplantation is not possible for this patient for logistical reasons. The biventricular assist devices cannot be continued indefinitely. Placement of a permanent implantable left ventricular assist device is not feasible. The alternative is likely to be withdrawal of support, which will result in rapid death.
In the ICU the patient is heavily sedated with propofol, but otherwise presumably neurologically intact. Would you want Commentary Ethics roundtable debate: should a sedated dying patient be wakened to say goodbye to family?
to wake the patient up first so he could be informed what is happening? Would you give him a chance to say goodbyes to family? Should the intensivist ask the family to decide?
The feelings of the medical team are diverse, opinions vary as to whether an individual would want to wake up before death. Would it be cruel to wake him up, just to tell him that he is going to die? He may have gone into the operation knowing that this was a high-risk procedure but had the reassurance of thinking 'If I wake up, I'll be OK, if I'm going to die, I'll never know about it'. In those circumstances the patient would not be expecting to waken to the certainty of imminent death. An alternative feeling in the medical team was that, given the opportunity, many people would want to know what was happening and possibly complete the process of saying goodbye to loved ones.
Anna Batchelor
The case scenario presented involves three sets of people each with needs and desires: the patient, the relatives, and the carers.
Considering the patient first, he has no choice to make about continuing care as there are no viable options; however, he does have a right to know what is happening and to make a choice about communicating with his family. We are not told what his presurgery views were -would he wish to be able to communicate in this situation or not? Is it possible for this patient to have his pain, distress, and anxiety relieved at the same time as withdrawing sedation to allow a meaningful return of consciousness? The worst endpoint would be a confused, agitated patient in pain failing to effectively communicate.
The relatives are our concern too; they will leave the hospital with memories of their loved one and the quality of care offered them. Some people will be able to communicate effectively their goodbyes and love to the patient, others will find this stressful. We need to know from the family what the patient is likely to have wanted in this situation. Had he already said his goodbyes 'just in case' or had he avoided such discussions? Is he going to be any better prepared for such discussions surrounded by machinery and strangers? Is he someone who liked to be in control of himself and his surroundings and would welcome the opportunity?
The carers have to examine their own reactions and not impose their own views on the family. Nurses particularly being in close contact with the patient may feel strongly that one course of action is preferable.
These matters should be resolved by team discussions involving all the carers, and possibly a minister of religion if that is relevant for the patient. Is it possible to achieve the desired scenario of an awake, communicative, undistressed patient? Would the patient want this? If so, who will care for the patient during this episode.
Discussions with the family should involve a small number of carers all saying the same thing. The relatives must clearly understand that no further active medical treatment is possible and that the patient will die. It is necessary to explore with them the issues raised and find out whether they feel the patient would wish to be awake, and whether they wish this to be attempted. The family should feel that they are involved in the decision-making process and asked for their views but not that they are left to decide; yet again, this is a team decision. Who will be present? Is this an opportunity for the whole family to show they care or an intimate occasion for one or two key people? This in itself can lead to conflict. It should be clearly understood that the patient remains our main focus and it may not be possible to achieve an awake, comfortable patient. We will not allow him to be in pain or distress, and treatment for this along with the presence of an endotracheal tube will limit his ability to communicate.
No spiritual care without consent Leslie Jenal
To wake this patient either to inform him of his impending death or to provide an opportunity for closure violates classic principles of medicine: nonmaleficence, autonomy, and justice [1].
Under the facts of the case, this patient can no longer exercise any meaningful consent as to his treatment because nothing, in fact, can be done for him. Waking the patient to inform him of his prognosis therefore cannot give him autonomy in any meaningful sense. In fact, informing him of his inexorable death is very probably an act of harm if he is likely to suffer from death anxiety. Most people, even those who have had a chance to prepare, suffer from death anxiety, regardless of the depth of their religious faith and belief in an afterlife [2,3]. Justice demands that our patient's needs, and only our patient's needs, inform our actions. In this case, a decision to wake the patient would possibly have more to do with the physician projecting his own need to know the cause of death onto the patient [4,5].
The decision whether to wake this patient for purposes of closure concerns less his medical treatment than his spirituality and, under the facts of this case, can have no bearing on his physical health at all. Spirituality is defined here according to its function as that which brings significance and meaningfulness to a person's life. The principle of autonomy applies because meaningful consent is required for spiritual care as for other types of treatment. The patient cannot consent and probably no surrogate decisionmaker under an advance directive concerning his physical health will have any power over spiritual care decisions. We should not therefore provide spiritual care if we do not have a reasonable belief that the patient would have consented [6].
In this case, the presumption should be that we do not wake the patient because we cannot guess whether he has a spiritual task to complete.
Of course, the patient's family may assist us in determining what the patient would want, but the burden of proof is on the family in this circumstance. The principle of justice demands that we concern ourselves with the patient's needs, and not his family's needs. First-degree relatives who have been in close contact with the patient in recent weeks should be consulted. We must be careful also to recognize that not all families operate like our own families, like other families we have observed, or like the families we would like to have.
Finally, we must consider procedural justice; that is, we must decide with full knowledge of how we, as individuals, make the decisions that we make. Decisions that impact a patient's spirituality require a very acute sense of the boundary between the decision-maker's needs and feelings, and the patient's needs and desires. Good decision-making requires self-reflection, knowing ourselves, and knowing how we make the decisions that we make.
My responsibility is to the patient not the family Farhad Kapadia
This example presents a dilemma one faces frequently in an ICU. A sedated patient on multiple supports has reached the point of no return. The family is informed and enquires whether the patient can be aroused so that they may communicate with the patient.
An encephalopathy is sometimes part of the multisystem involvement. We can inform the family that withdrawing sedation could lead to distress but there is little chance that the patient will be lucid enough to communicate. This invariably leads to a rapid family consensus that no such attempt be made.
Another situation that is more difficult is one in which the patient is likely to be completely lucid off sedation, but there is a glimmer of hope that the illness may not be terminal. As part of the intensive care therapy, sedation is stopped for a few hours of the day and the level of consciousness established. The family invariably communicates with the patient in these brief periods.
The real problem occurs in situations similar to the patient presented. First, it is presumed that the patient has no chance of independent survival. Second, the patient will probably be fully awake and comprehending when sedation is stopped. Finally, the patient was probably not forewarned that such a situation could arise.
In such a situation, to date, I have not agreed to stop sedation. My reasons are as follows. First, my initial responsibility is to the patient and not to the family. Also, I do not know to what sort of distress withdrawal of support will lead. I would not feel confident that I could offer reasonable assurance that there would be minimal pain, minimal gagging, minimal coughing, minimal bucking, and minimal respiratory distress. Finally, even if I could assure an awake and comfortable patient with judicious drug therapy, I would be unwilling to decrease sedation as I have no idea what thoughts would go through the patient's mind. I would worry that these thoughts may lead to severe mental distress and perhaps even to terror of impending death.
I would explain these reasons to the family and inform them that I am unwilling to stop sedation.
There are two settings in which it is conceivable that I would agree to sedative withdrawal for terminal communication. First, if there was some sort of prior documentation stating the patient's desire to communicate with his family terminally, even in the environment of an ICU. Second, if I knew the patient and family before the critical illness, either as their primary care physician or socially, and I really believed that the patient would have desired to communicate terminally with the family. To date, I have not encountered either of these two settings.
First, do no harm
Stephen Streat Does the patient have a 'right' to be awakened? One can only speculate what the potential effects on the patient of such awakening might be, but it is impossible to see this as being anything other than 'very bad news'. I am strongly of the view that simply because the possibility of awakening exists, it does not lead to the concept of a 'right' to experience it. On the contrary, the patient has an overwhelming right to be treated with compassion and dignity, and it is these considerations that lead me to believe that allowing the patient to awaken and be informed of the immediate prognosis is a bad thing.
Possible benefits to the patient such as revising a will are small or absent. What about final farewells to loved ones? Again, I believe that the well-informed patient will have taken this opportunity after presentation of the risks of the planned procedure. I believe that people tend to live their dying much as they have lived their lives. If an opportunity to communicate love and possible farewell was not embraced and fully utilized when it was possible under optimal circumstances, it is unlikely to be taken or be of great benefit under conditions of considerable distress. There is also the possibility that the patient might wish to participate in a religious ceremony, or perhaps receive last rites. I am not strongly persuaded by this view but could entertain the possibility of discussing this aspect with the patient's family with a view to determining the strength and centrality of the patient's religious faith. It should also be mentioned that the patient need not be awake to receive 'last rites' from most, if not all, religions.
The reality is that, after awakening, the patient will probably have some postoperative pain and also experience the discomfort produced by the presence of an endotracheal tube. Communication is imperfect under these circumstances, and this imperfection is often a source of additional distress to intubated patients recovering from critical illness, let alone a patient receiving a hopeless prognosis. Perception of reality may be incomplete, like a bad dream, and the patient may be frightened and unable to respond with lucidity. It is difficult to imagine a patient being grateful for such news, delivered under such circumstances; indeed, I am inclined to view it as cruel.
We do well to realize that in everyday life we make choices based not only on the possibility of benefit, but also on the risk of unacceptably bad consequences -a circumstance that Gillett [7] has eloquently described (in consideration of the possible outcomes of severe brain injury) as "the risk of unacceptable badness". I argue that in this circumstance (with the possible exception of the patient with unusually strong religious faith, who might appreciate a final religious rite), the risk of allowing the patient to awaken is unacceptable in the light of the weak (or absent) arguments for possible benefits that might accrue.
It is my considered opinion that this patient should not be awakened during the dying process.
Leslie Whetstine
This case raises two questions: ought the healthcare team awaken a terminally ill patient before life-sustaining treatment is withdrawn, and who ought to make this decision? All of the discussants agree on the substantive question, that this patient should not be aroused. Some controversy exists however, as to who should be the appropriate decisionmaker. The consensus is that this encumbered patient would probably suffer unmanageable physical and emotional distress upon arousal [8]. The discussants' primary objective is the patient's comfort, and the burdens of arousal appear to outweigh any projected benefit [9].
Kapadia and Streat fear that even if adequate pain management were possible the psychological distress would be inhumane, culminating in a nightmarish altered perception of reality. Streat rejects the notion that simply because arousal may be possible, the patient has a right to it. Jenal argues that this is no longer a medical issue, but a spiritual care decision that should not be imposed upon the patient in the absence of a substantial consent. Jenal correctly points out that the facts of the case leave no autonomy to exercise.
Batchelor, however, suggests that while there may be no available medical options, the patient might have a right to know what is happening and to make choices about familial communication. In an ideal situation Batchelor is most correct, but to respect autonomy in a literal sense would actually require the team to awaken the patient to ask him whether he wanted to be awakened. Clearly this type of reductionism should be avoided.
As a practical matter, Batchelor favors a joint approach to decision-making involving the medical team and family but is clear that the patient's comfort is her primary goal. Thus, if arousal would cause discomfort, it appears she would not comply. Streat does not suggest he would consult with the family, while Kapadia would only awaken the patient if there were advance directives or if he had an ongoing relationship with the patient. Jenal endorses joint decision-making but puts the burden of proof on the family, which seems to be the appropriate standard in this case.
The principles of beneficence and nonmaleficence [10] are clear for this patient. We have an obligation to do well and prevent harm when possible. Given the clinical doubts that arousal could be well palliated, the family must convince the team that the benefits thereof outweigh the detriments. It would seem unlikely that a family would be able to prove such a case. In the event they could prove a convincing case, their decision should be respected since the authority of surrogacy is the established norm, at least in the United States. If not, the physicians are ethically correct to tread the path leading to the greatest patient comfort under the circumstances The outcome of the case
Brian Woodcock
The outcome in this case was that the decision never had to be made. The patient developed signs of a stroke, probably due to embolus from thrombus in his left ventricle. Sedation was discontinued and the patient had severe neurological signs with absent brain stem reflexes. Support was withdrawn and the patient never awoke. | 4,324.6 | 2003-06-09T00:00:00.000 | [
"Medicine",
"Philosophy"
] |
Off-Resonant Absorption Enhancement in Single Nanowires via Graded Dual-Shell Design
Single nanowires (NWs) are of great importance for optoelectronic applications, especially solar cells serving as powering nanoscale devices. However, weak off-resonant absorption can limit its light-harvesting capability. Here, we propose a single NW coated with the graded-index dual shells (DSNW). We demonstrate that, with appropriate thickness and refractive index of the inner shell, the DSNW exhibits significantly enhanced light trapping compared with the bare NW (BNW) and the NW only coated with the outer shell (OSNW) and the inner shell (ISNW), which can be attributed to the optimal off-resonant absorption mode profiles due to the improved coupling between the reemitted light of the transition modes of the leak mode resonances of the Si core and the nanofocusing light from the dual shells with the graded refractive index. We found that the light absorption can be engineered via tuning the thickness and the refractive index of the inner shell, the photocurrent density is significantly enhanced by 134% (56%, 12%) in comparison with that of the BNW (OSNW, ISNW). This work advances our understanding of how to improve off-resonant absorption by applying graded dual-shell design and provides a new choice for designing high-efficiency single NW photovoltaic devices.
Introduction
Single nanowire (NW) solar cells have attracted more and more research interests as nanoelectronic power sources in recent years due to their unique characteristics, such as enhanced light-harvesting capability, efficient carrier collection, ultra-compact volume, large surface area and convenience of integrating with optoelectronic nanosystems [1][2][3][4][5][6][7][8]. Besides its potential applications as power sources for nanoelectronic devices, single NW solar cell is also helpful to understand the mechanism of the self-assembled NW-based solar cells [7][8][9][10][11][12][13][14][15][16]. It is well known that light-harvesting ability is one of the most critical factors for photovoltaic applications, which determines the photoelectric conversion efficiency of a solar cell. Surprisingly, there is a strong interaction of the incident light with a single NW due to the leaky mode resonances (LMRs), which leads to a much higher absorption cross-section than its physical geometry [17][18][19]. However, the light absorption of single NWs is still far from the expectation due to the sharp resonant peak and narrow width, which can only achieve superior light absorption at the peak position. Therefore, various strategies have been implemented to improve the light absorption in the whole solar spectrum range. It was shown that the light absorption could be readily tuned by controlling the size, geometry and orientation of the NWs [20][21][22][23][24][25][26][27][28]. Moreover, our previous studies [29][30][31][32][33] showed that the light absorption could be further improved by introducing a non-absorbing dielectric shell as the antireflection coating, which was experimentally and numerically demonstrated in the recent studies [34][35][36][37][38]. Comparing to the bare NWs (BNWs), semiconductor core-dielectric shell NWs (CSNWs) not only provides the possibility to tune the position of the resonant peak but also enhance the light-harvesting capability at the off-resonant wavelengths by adjusting the thickness and the refractive index of the shell, which is attributed to the high nanofocusing effect [30,38]. However, a further increase of the shell thickness has little contribution to the enhancement of the light absorption of the CSNW structure because the incident light will be mainly concentrated in the dielectric shell. Recently, some new strategies have been employed to improve the light-trapping capability of the CSNW, including the off-axial core-shell design [39] and partially capped design [40]. At the same time, the graded-index concept has been employed to enhance light absorption in the two-dimensional (2D) structures [41][42][43]. However, to the best of our knowledge, the dual shells with the graded refractive index have not been applied to improve the light absorption of single NWs.
In this work, we report a single dual-shell coated NW (DSNW), in which the dual shells have a graded refractive index. We demonstrate that graded dual-shell design can lead to the giant enhancement of off-resonant absorption. The detailed analysis of the absorption mode and photogeneration rate profiles shows that this enhancement results mainly from the optimal off-resonant absorption mode profiles under an improved coupling between the reemitted light of the transition modes of the LMRs of the Si core and the nanofocusing light from the dual shells with the graded refractive index. Simulation results indicate that the photocurrent density is significantly enhanced by 134%, 56% and 12% in comparison with that of the BNW and that of the nanowire only coated with the outer shell (OSNW) and the inner shell (ISNW), respectively.
Model
The cross-sectional schematic diagram of the DSNW is shown in the insets of Figure 1. It should be noted here that the OSNW and the ISNW are also shown for comparison. The geometrical parameters of the DSNW are characterized by the radius r (=100 nm) of the Si core, the thickness t 1 of the outer shell and the thickness t 2 of the inner shell of the DSNW which varies from t 2 = 0 nm (i.e., OSNW) to t 2 = 180 nm (i.e., ISNW), the total shell thickness t = t 1 + t 2 = 180 nm and the total radius R = r + t = 280 nm. Note here that the radius of the Si core is chosen to be 100 nm as a representative nanoscale size and the total shell thickness is chosen to be 180 nm as the DSNW shows the optimal absorption in this study and the OSNW (or ISNW) approaches the optimal absorption at this thickness in our previous study [31][32][33]. The incident light indicated by colorful arrows in the insets of Figure 1 is assumed to be illuminated perpendicularly to the axial from the top, the wavelength range is from 300 to 1100 nm with a step size of 5 nm considering solar radiation and the bandgap of Si. The wavelength-dependent complex refractive index of Si fitted with the experimental data [44] and that of the inner shell, the outer shell and the surrounding medium (air) are set to be 2.5, 1.5 and 1.0, respectively. Note here that for simplicity, we have neglected the wavelength dependence of the refractive indices to neatly determine the impact of their size on the absorption spectra [30,31,45], as discussed later; however, as long as the wavelength dependence is negligible, our results could apply to any other dielectric with similar refractive index, such as SiO 2 , Si 3 N 4 and so forth. The insets are the cross-sectional views of the NW only coated with the outer shell (OSNW) (left), DSNW (middle) and the NW only coated with the outer shell (ISNW) (right), where J ph is the photocurrent density; t 1 , t 2 , t = t 1 + t 2 = 180 nm, r = 100 nm and R = r + t = 280 nm are the outer shell thickness, the inner shell thickness, the total shell thickness, the core radius and the total radius; m 3 , m 2 , m 1 and m 0 are the complex refractive indices of the Si core, the inner shell, the outer shell and air, respectively.
Methods
The light absorption performance of the DSNW was performed by solving the corresponding Maxwell's equations based on 2D finite difference time domain (FDTD) method [46][47][48] by assuming that the length of the NW is far greater than the radius, which can be referred to the work of Kim and co-workers for details [26][27][28]36]. In this simulation, the perfectly matched layers (PML) boundary conditions are used to avoid any non-physical reflection with the boundaries, the total-field scattered-field (TFSF) method was applied to ensure that a single NW interacts with an infinite plane wave. Also, the minimum cell size of the FDTD mesh is set to 1 nm to guarantee the accuracy of the simulation results.
The Absorption Efficiency and Mode Profile
To qualify the light absorption performance of the DSNW, we define the absorption efficiency Q abs of the Si core as [38,[49][50][51]: where C geo is the geometric cross-section (i.e., the projected area of the Si core) and C abs is the absorption cross-section calculated by [38,[49][50][51] C abs = V P abs dV where k 0 is the wave vector in air, ε r is the imaginary part of the relative permittivity, E r is the normalized electric field intensity, V is the volume of the Si core, I 0 is the solar incident light intensity and P abs describes the wavelength-dependent absorption mode profile calculated from Poynting theorem, which can be expressed as [38,[49][50][51]] where ω, c and E 0 is the angular frequency, the speed of light and the electric field intensity of the solar incident light; ε 0 and ε are the permittivities in air and the imaginary part of the permittivity of Si; n and k are the real and imaginary part of the complex refractive index of Si (i.e., m = n + ik, m 2 = ε r = ε r + iε r ); E is the electric field intensity in the Si core, respectively.
The Photogeneration Rate
With the assumption that each photon absorbed inside the Si core has a contribution to the photocurrent, the spatially dependent photogeneration rate G is readily calculated by [52,53] whereh is the reduced Planck's constant and λ is the wavelength of the incident light.
The Photocurrent Density
To evaluate the light-harvesting capability as single NW solar cells, we can calculate the photocurrent density J ph by: where q is the element charge, Γ is the AM1.5G standard solar photon flux density spectrum. It should be noted here that 100% collection efficiency is assumed, which has been widely employed to evaluate the ultimate photocurrent [18,53].
The Photocurrent Enhancement Factor (PEF)
To evaluate the photocurrent enhancement of the DSNW, we calculate the photocurrent enhancement factor (PEF) using the relation: where J ph,DSNW and J ph,rNW are the photocurrent density for the DSNW and the reference NWs (BNW, OSNW and ISNW), respectively. Finally, it is important to stress that the unpolarized illumination (e.g., sunlight) is regarded as the average of transverse electric (TE, electric field normal to the NW axis) and transverse magnetic (TM, magnetic field normal to the NW axis) illumination [22,39,40].
The Absorption Mechanism
To understand the absorption mechanism responsible for the improved light-harvesting performance of the DSNW, we investigate the photocurrent density (J ph ), the absorption efficiency (Q abs ), the absorption mode profile (P abs ) and the photogeneration rate (G), respectively. Note here that r = 100 nm, t = 180 nm, R = r + t = 180 nm, t 2 = 0 → 180 nm, where t = 0, t 2 = 0 and t 2 = 180 nm denote the cases of the BNW, OSNW and ISNW, respectively; m 3 is the complex refractive index of the Si core, m 2 = 2.0, m 1 = 1.5 and m 0 = 1.0, as shown in the insets of Figure 1 To evaluate the light-harvesting performance of the DSNW, we first study the effect of the inner shell thickness on the photocurrent density (J ph ) obtained by Equation (7). In Figure 1, we show t 2 -dependent J ph under normally-incident TE, TM and unpolarized light illumination, respectively. It is observed that J ph increases rapidly first when initially increasing t 2 , reaches a peak at t 2 = 85 nm and then decreases when continuing to increase t 2 . More importantly, J ph of the DSNW is always bigger than that of the OSNW as long as the inner shell is adopted and higher than that of the ISNW in a broad inner thickness range of t 2 > 40 nm. For a direct comparison, we list the J ph values of the considered BNW, OSNW, ISNW and DSNW configurations under TE, TM and unpolarized illumination, as shown in Table 1. The maximum J ph values for TE and TM light are 14.85 and 15.50 mA/cm 2 , respectively. Under unpolarized light illumination (e.g., sunlight), the maximum J ph reaches 15.18 mA/cm 2 , which is 96.6%, 31.2% and 10.2% higher than that of the BNW (7.72 mA/cm 2 ), OSNW (11.57 mA/cm 2 ) and ISNW (13.77 mA/cm 2 ), respectively. It is found that this photocurrent enhancement is mainly ascribed to the improvement of J ph under any polarized situations (especially TM light), indicating the potential of the DSNW in improving the light absorption of single NWs. Table 1. Photocurrent densities (in mA/cm 2 ) of the four typical configurations (in nm) of the bare NW (BNW), OSNW, ISNW and DSNW under TE (Transverse electric field to the nanowire axis), TM (Transverse magnetic field to the nanowire axis) and unpolarized light illumination, where r, t 2 , and t are the core radius, the inner shell thickness and the total shell thickness, respectively. To understand the physical mechanism of the improved photocurrent, we then examine the absorption spectra of the DSNW. In Figure 2a,b, we present 2D maps of λ-dependent Q abs as a function of t 2 under TE and TM light illumination, which is given by Equation (1). It is clear that the dual-shell design can lead to absorption enhancement in the whole spectrum range compared to the OSNW and almost the entire spectrum range (except several narrow peaks) compared to the ISNW under both TE and TM light illumination (especially at the off-resonant wavelengths), as discussed later. Moreover, Q abs can be divided into three regions using two vertical dashed lines by employing the characteristic wavelengths λ c1 (~430 nm) and λ c2 (~525 nm) for both TE and TM lights, as labeled in Figure 2a,b. Firstly, in the wavelength range of λ < λ c1 , Q abs periodically changes with increasing t 2 . Note here that Q abs can be divided into two regions using a horizontal dashed line by employing the characteristic inner shell thickness t 2c (~90 nm) for both TE and TM lights, as labeled in Figure 2a,b. Q abs reaches the maximum absorption near t 2 = 50 nm and t 2 = 130 nm for the first (t 2 < t 2c ) and second (t 2 > t 2c ) period, respectively. In other words, the excellent absorption can be obtained in the inner shell thickness range of 40 < t 2 < 60 nm and 110 < t 2 < 140 nm for two periods, respectively. Secondly, in the wavelength range of λ c1 < λ < λ c2 , Q abs reaches the maximum absorption near t 2 = 50 nm, that is, the superior absorption can be obtained in the inner shell thickness range of 60 < t 2 < 120 nm. Finally, in the wavelength range of λ > λ c2 , Q abs appears to be comparable due to the trade-off between the suppression at the resonant wavelengths and the enhancement at the off-resonant wavelengths, resulting in little contribution to the photocurrent enhancement. Therefore, the photocurrent enhancement of the DSNW with t 2 < 60 nm and t 2 > 120 nm is attributed to the improved absorption in the wavelength range of λ < λ c1 , while that of the DSNW with 60 < t 2 < 120 nm is mainly attributed to the improved absorption in the wavelength range of λ c1 < λ < λ c2 , which is due to the fact that there is a much higher solar radiation in the wavelength range of λ c1 < λ < λ c2 than λ < λ c1 , leading to a more significant contribution to the photocurrent according to Equation (7). To quantitatively characterize the absorption enhancement of the DSNW, we also examine the absorption spectra corresponding to the optimal J ph in Figure 1. In Figure 2c,d, we show λ-dependent Q abs of the DSNW with t 2 = 85 nm for TE and TM light, where the results of the BNW, OSNW and ISNW are also included for comparison. It is shown that Q abs of the DSNW is much higher than that of the BNW and OSNW in the wavelength range of λ < λ c2 and that of the ISNW in the wavelength range of λ < λ c2 (except for several narrow peaks, for example, λ = 470 for TE light) for both TE and TM lights, resulting in a significant photocurrent enhancement. In contrast, although Q abs of the DSNW is weaker at the resonant wavelengths, higher at the off-resonant wavelengths than that of all the other three NW structures in the wavelength range of λ > λ c2 , leading to a similar contribution to the photocurrent, as discussed above. It is worth noting that Q abs can be substantially enhanced at the off-resonant wavelengths over the whole wavelength range for both TE and TM lights, especially for TM light (e.g., near λ = 470 nm), which results in the more prominent photocurrent enhancement for TM than TE light. It should also be noted that the match between the absorption efficiency and the solar spectrum becomes another essential factor in evaluating the photocurrent according to Equation (7). For instance, although Q abs of the DSNW for TE light is much higher than that for TM light in the wavelength range of λ < λ c1 , solar radiation is much lower, which leads to a less photocurrent enhancement, while Q abs for TM light is much higher than that for TE light in the wavelength range of 450 < λ < 650 nm (except the narrow wavelength range of 490 < λ < 505 nm), as shown in the inset of Figure 2d and solar radiation is much higher at the same time, which results in a more significant contribution to the photocurrent.
The Absorption Mode Profile (P abs )
The absorption behavior presented above can be well described by the absorption mode profiles (P abs ) calculated by Equation (3) [22,24,26,50,52]. In Figure 3, we examine the normalized absorption mode profiles inside the Si core corresponding to the wavelengths in Figure 2c,d under TE and TM light illumination (these profiles from left to right columns are related to the evolution of the structure from BNW to OSNW and then to ISNW and finally to DSNW). Figure 3a,c show the off-resonant absorption mode profiles for TE and TM light, while Figure 3b,d show the corresponding resonant absorption mode profiles. Note here that the resonant (or off-resonant) absorption for all the four NW configurations may occur at different wavelengths due to the difference of the thickness and the refractive index of the dielectric shells, that is, t 1 (or t 2 ) or m 1 (or m 2 )-driven shift [30,31], as shown in Figure 2a,b. It is observed that the absorption enhancement is attributed to the excitation of the LMRs, likewise in BNW [17,18], which can capture light by multiple total internal reflections at the Si core/inner shell interface when the wavelength of the incident light matches one of the LMRs supported by the Si core. The LMRs can be noted as TE ml or TM ml , where m and l are the azimuthal mode number and the radial order of the resonances, respectively. Figure 3b,d show that the resonant absorption mode profiles of the DSNW are different from that of the BNW, similar to that of the INSW due to the fact that the LMRs of the Si core occur at the Si core/inner shell interface. Specifically, the modes of the BNW, OSNW, ISNW and DSNW are TE 12 , TE 31 , TE 31 and TE 31 at λ = 495, 470, 470 and 470 nm for TE light and TM 12 , TM 12 , TM 41 and TM 41 at λ = 495, 500, 465 and 470 nm for TM light, respectively. The absorption of the DSNW is indeed enhanced compared to the BNW and OSNW for both TE and TM lights and slightly suppressed for TE light and enhanced for TM light compared to the ISNW. Figure 3a,c show that the off-resonant absorption mode profiles of the DSNW exhibit a transition mode referred to the LMRs, such transition modes are very close to the corresponding LMRs, which is attributed to the fact that the presence of the graded dual shells makes more light couple into the Si core, leading to a more significant absorption enhancement compared to all the other three NWs. The absorption behavior presented above can also be well understood by employing the interference effect of light, which occurs at multiple interfaces due to the difference of the refractive index between Si core/inner shell, inner shell/outer shell and outer shell/air. For weaker LMRs in the wavelength of λ< λ c2 , as shown in Figure 2, the resonant absorption is greatly enhanced due to the constructive interference with the reemitted light of the weaker LMRs of the Si core. However, for stronger LMRs in the wavelength of λ> λ c2 , the resonant absorption is suppressed due to the destructive interference with the reemitted light of the stronger LMRs of the Si core. In contrast, the off-resonant absorption over the whole spectrum is greatly enhanced due to the constructive interference with the reemitted light of the weaker transition modes of the Si core. In a word, the off-resonant (or weaker resonant) absorption is dramatically enhanced owing to an improved coupling between the reemitted light of weaker transition modes (or weaker LMRs) of the Si core and the nanofocusing light from the graded dual shells at the core/inner shell interface [38,39].
The Photogeneration Rate Profile (G)
To further confirm the physical origin discussed above, we show the photogeneration rate (G) obtained Equation (6). In Figure 4, we present the normalized photogeneration rate profiles for TE and TM polarized light, respectively. It is shown in Figure 4a that the absorption of the DSNW for TE light is much stronger than that of the BNW and OSNW and that of almost all the regions of the ISNW [evidently enhanced in the regions labeled by circles (see Figure 4a) and slightly decreased in the region labeled by the square (see Figure 4a)]. It is shown in Figure 4b that the absorption of the DSNW for TM light is also much stronger than that of the BNW and OSNW and that of almost all the regions of the ISNW [evidently enhanced in the regions by labeled by triangles (see Figure 4b)]. These results further reveal that this enhancement arises mainly from the off-resonant absorption enhancement due to the improved coupling between the reemitted light of the weaker transition modes of the LMRs of the Si core and the nanofocusing light from the graded dual shells. More importantly, the photogeneration rate profiles of the DSNW for both TE and TM lights have similar patterns with that of all the other three NWs, again indicating that the absorption enhancement is mainly attributed to the LMRs, likewise in the BNWs. Note that the regions labeled by circles and triangles denote that the absorption of the DSNW is significantly enhanced for TE and TM light and the region labeled by the square denotes that the absorption of the DSNW is slightly decreased for TE light, respectively.
The Optimization of the Light-Harvesting Performance
To evaluate and optimize the light-trapping performance of the DSNW for photovoltaic applications, we now investigate the effect of both the shell thickness and the refractive index on the photocurrent density calculated using Equation (7). Note that except for m 2 , all the other structural details of the DSNW are consistent with that shown in the insets of Figure 1. In Figure 4a, we show 2D J ph as a function of t 2 and m 2 of the DSNW and the optimal t 2 as a function of m 2 . Figure 4a shows J ph sharply increases with increasing t 2 at a fixed m 2 , reaches its maximum and then decreases when continuing to increase t 2 . More importantly, J ph of the DSNW is always much larger than that of the OSNW at any t 2 values and higher than that of the ISNW in a broad inner shell thickness range of t 2 > 40 nm for m 2 < 3.5 and t 2 > 60 nm for 3.5 < m 2 < 4.0. It is observed that the maximum values of J ph can be obtained in the inner shell thickness range of 90 < t 2 < 110 nm for 3.0 < m 2 < 3.5. In Figure 5b, we show m 2 -dependent J ph of the DSNW (corresponding to the optimal t 2 in Figure 5a), together with that of the BNW, OSNW and ISNW for comparison. Also, in Figure 5c, we show the photocurrent enhancement factors (PEFs) defined by Equation (8). It is readily observed that J ph of the DSNW is much larger than all the other three NWs. In particular, the maximum J ph reaches 18.10 mA/cm 2 at t 2 = 100 nm for m 2 = 3.25, which is 134.4%, 56.4% and 12.4% much larger than that of the BNW (7.72 mA/cm 2 ), OSNW (11.57 mA/cm 2 ) and ISNW (16.10 mA/cm 2 ), respectively. Also, J ph versus m 2 of the BNW, OSNW and ISNW are included for comparison. (c) photocurrent enhancement factor (PEF) versus m 2 of the DSNW compared to the BNW, OSNW and ISNW, respectively. Note that the PEF is the photocurrent enhancement factor compared to the reference NWs.
Conclusions
In summary, we proposed a single NW by coating dual dielectric shells. The influence of the thickness and the refractive index of the inner shell of the DSNW on the light absorption for photovoltaic applications are numerically investigated. It is found that the size and material of the inner shell can lead to significantly improved off-resonant absorption. The examination of the spatial profiles of the absorption mode and photogeneration rate reveals that the enhancement effect is the result of the constructive interference under the improved coupling between the reemitted light of the transition modes of the LMRs of the Si core and the nanofocusing light from the graded dual shells. The simulation results show that the photocurrent density can be enhanced by 134.4%, 56.4% and 12.4% in comparison with that of the BNW, OSNW and ISNW, respectively. Therefore, such a dual shell coated structure can be applied to a variety of semiconductors to improve the off-resonant absorption and provides an effective way to achieve high-efficiency single NW solar cells. | 6,209 | 2020-08-11T00:00:00.000 | [
"Physics",
"Engineering"
] |
Energy Dependence of CP-Violation Reach for Monochromatic Neutrino Beam
The ultimate goal for future neutrino facilities is the determination of CP violation in neutrino oscillations. Besides $| U(e3) | \ne 0$, this will require precision experiments with a very intense neutrino source and energy control. With this objective in mind, the creation of monochromatic neutrino beams from the electron capture decay of boosted ions by the SPS of CERN has been proposed. We discuss the capabilities of such a facility as a function of the energy of the boost and the baseline for the detector. We compare the physics potential for two different configurations: I) $\gamma=90$ and $\gamma=195$ (maximum achievable at present SPS) to Frejus; II) $\gamma=195$ and $\gamma=440$ (maximum achievable at upgraded SPS) to Canfranc. We conclude that the SPS upgrade to 1000 GeV is important to reach a better sensitivity to CP violation iff it is accompanied by a longer baseline. In both Setups, the gain in the CP violation sensitivity with a previous knowledge of $| U(e3) |$ is apparent.
Introduction
Neutrinos do have masses and mixings. Present evidence [1,2] from neutrino oscillations is consistently interpreted in terms of two independent mass-differences and mixings: the so-called atmospheric sector (2,3) and the solar sector (1,2). The initial discovery of the zenith effect with atmospheric neutrinos led to the (2,3) sector in neutrino oscillations, later confirmed by long baseline experiments with accelerator neutrinos. The solar neutrino solution to the historical solar neutrino problem led to the (1,2) sector from neutrino oscillations in solar matter, later confirmed by long-baseline vacuum oscillations with reactor neutrinos. Whereas the sign of ∆m 2 12 is thus known, the determination of the sign of ∆m 2 23 needs the incorporation of matter effects and then |U (e3)| = 0. The two mixings angles are large: θ 23 could even be 45 • , whereas θ 12 is large although not maximal.
The third connecting mixing |U (e3)| is bounded as θ 13 ≤ 10 • from the CHOOZ reactor experiment [3]. The angle θ 13 remains thus undetermined. The approved reactor experiments Double CHOOZ [4] and Daya-Bay [5], as well as the second generation of long-baseline superbeam experiments T2K [6] and NOVA [7] will address this point. A number of experimental facilities to significantly improve on present sensitivity and look for CP-violation have been discussed in the literature: neutrino factories (neutrino beams from boosted-muon decays) [8][9][10], superbeams (very intense conventional neutrino beams) [11][12][13][14], improved reactor experiments [15] and β-beams [16]. The original standard scenario for beta beams with low γ = 60/100 and short baseline L = 130 Km from CERN to Frejus with 6 He and 18 N e ions can have a variant by using an electron capture facility for monochromatic neutrino beams [17]. New proposals also include the high Q value 8 Li and 8 Be isotopes in a γ = 100 facility [18]. For the standard beta beam facility, a study of the physics reach as function of the boost and the baseline has been made [19]. In this paper we discuss the physics reach that a high energy facility for EC beams may provide with the expected SPS upgrade at CERN. In Section 2 we discuss the virtues of the suppressed oscillation channel (ν e → ν µ ) in order to have access to the parameters θ 13 and δ. To disentangle the CP-violating phase we emphasize the method of using energy dependence, as obtainable in the EC facility. In Section 3 we present new results on the comparison between (low energies, short baseline) and (high energies, long baseline) configurations for an EC facility with a single ion. Section 4 gives our conclusions.
CP-even and CP-odd terms
The observation of CP violation needs an experiment in which the emergence of another neutrino flavour is detected rather than the deficiency of the original flavour of the neutrinos. At the same time, the interference needed to generate CP-violating observables can be enhanced if both the atmospheric and solar components have a similar magnitude. This can happen in the suppressed ν e → ν µ transition. The appearance probability P (ν e → ν µ ) as a function of the distance between source and detector (L) is given by [20] P (ν e → ν µ ) ≃ s 2 23 sin 2 2θ 13 sin 2 ∆m 2 13 L 4E + c 2 23 sin 2 2θ 12 sin 2 ∆m 2 whereJ ≡ c 13 sin 2θ 12 sin 2θ 23 sin 2θ 13 . The three terms of Eq. (1) correspond, respectively, to contributions from the atmospheric and solar sectors and their interference. As seen, the CP violating contribution has to include all mixings and neutrino mass differences to become observable. The four measured parameters (∆m 2 12 , θ 12 ) and (∆m 2 23 , θ 23 ) have been fixed throughout this paper to their mean values [21]. Neutrino oscillation phenomena are energy dependent (see Fig.1) for a fixed distance between source and detector, and the observation of this energy dependence would disentangle the two important parameters: whereas |U (e3)| gives the strength of the appearance probability, the CP phase δ acts as a phase-shift in the interference pattern. In fact, a general theorem [22] states that, under the assumptions of CPT invariance and absence of absorptive parts, the CP-odd probability is odd in time or, equivalently, odd in L. As vacuum oscillations depend on L/E, this result implies that, for fixed L, the CP-odd probability is odd in E, whereas the CP-even terms are even in E. This is satisfied by Eq. (1), with three contributions, the atmospheric, the solar and their CP-even interference, which are even functions of E, and the CP-odd interference, which is odd in E. These properties suggest the consideration of a facility able to study the detailed energy dependence by means of fine tuning of a boosted monochromatic neutrino beam. In an electron capture facility the neutrino energy is dictated by the chosen boost of the ion source and the neutrino beam luminosity is concentrated at a single known energy which may be chosen at will for the values in which the sensitivity for the (θ 13 , δ) parameters is higher. This is in contrast to beams with a continuous spectrum, where the intensity is shared between sensitive and non sensitive regions. Furthermore, the known definite energy would help in the control of both the systematics and the detector background. In the beams with a continuous spectrum, the neutrino energy has to be reconstructed in the detector. In water-Cerenkov detectors, this reconstruction is made from supposed quasielastic events by measuring both the energy and direction of the charged lepton. This procedure suffers from non-quasielastic background, from kinematic deviations due to the nuclear Fermi momentum and from dynamical suppression due to exclusion effects [23]. The above discussion proves that the study of neutrino oscillations in terms of neutrino energy will be able to separate out the CP phase δ from the mixing parameters. A control of this energy may be obtained from the choice of the boost in the EC facility with a single ion. In order for this concept to become operational, it is necessary to combine it with the recent discovery of nuclei far from the stability line, having super allowed spin-isospin transitions to a giant Gamow-Teller resonance kinematically accessible [24]. Thus the rare-earth nuclei above 146 Gd have a small enough half-life to allow electron capture processes in the decay ring. This is in contrast with the proposal of EC beams with fully stripped long-lived ions [25]. We discuss the option of short-lived ions [17].
Physics reach at different energies and baselines
Electron Capture is the process in which an atomic electron is captured by a proton of the nucleus leading to a nuclear state of the same mass number A, replacing the proton by a neutron, and a neutrino. Its probability amplitude is proportional to the atomic wavefunction at the origin, so that it becomes competitive with the nuclear β + decay at high atomic number Z. Kinematically, it is a two body decay of the atomic ion into a nucleus and the neutrino, so that the neutrino energy is well defined and given by the difference between the initial and final atomic masses minus the excitation energy of the final nuclear state. In general, the high Z nuclear betaplus decay (β + ) and electron-capture (EC) transitions are very "forbidden", i.e., disfavoured, because the energetic window open in these channels does not contain the important Gamow-Teller strength excitation seen in (p,n) reactions. There are a few cases, however, where the Gamow-Teller resonance can be populated having the occasion of a strong "allowed" transition. For the rare-earth nuclei above 146 Gd, the filling of the intruder level h 11/2 for protons opens the possibility of a spinisospin transition to the allowed level h 9/2 for neutrons, leading to a fast decay. Our studies for neutrino beam capabilities have used the 150 Dy ion with half life of 7.2 min, a Branching Ratio to neutrino channels of 64% (fully by EC) and neutrino energy of 1.4 MeV in the C.M. frame, as obtained from its decay to the single giant Gamow-Teller resonance in the daugther 150 T b * .
The parent radioactive ion is accelerated and then accumulated and storaged. A neutrino of energy E 0 in C. M. that emerges from the decay in these conditions will be boosted in energy. This LAB energy is a function of the angle (θ) of neutrino detection and Lorentz gamma (γ) of the ion at the moment of decay and it can be expressed as E = E 0 /[γ(1 − β cos θ)]. The angle θ here expresses the deviation between the actual neutrino detection and the ideal detector position in the prolongation of one of the long straight sections of the decay ring. The neutrinos emerging from a boosted ion beam decaying by EC are concentrated inside a narrow cone around the forward direction. If the ions are kept in the decay ring longer than the half-life, the energy distribution of the Neutrino Flux arriving to the detector in the forward direction, in absence of neutrino oscillations, is given by the Master Formula with a dilation factor γ >> 1. It is remarkable that the result is given only in terms of the branching ratio for electron capture and the neutrino energy and independent of nuclear models. In Eq. (2), N ions is the total number of ions decaying to neutrinos. At the first oscillation maximum, with E/L fixed, Eq. (2) says that lower neutrino energies E 0 in the proper frame give higher neutrino fluxes. The number of events will increase with higher neutrino energies as the cross section increases with energy. To conclude, in the forward direction the neutrino energy is fixed by the boost E = 2γE 0 , with the entire neutrino flux concentrated at this energy. As a result, such a facility will measure the neutrino oscillation parameters as a function of energy by changing the γ's of the decay ring (energy dependent measurement) and there is no need of energy reconstruction in the detector. In this situation, the experiment becomes a counting-rate of events. For the study of the physics reach associated with such a facility, we combine two different energies for the same 150 Dy ion in each of two Setups. In all cases we consider 10 18 decaying ions/year, a water Cerenkov Detector with fiducial mass of 440 Kton and both appearance (ν µ ) and disappearance (ν e ) events. Setup I is associated with a five year run at γ = 90 (close to the minimum energy to avoid atmospheric neutrino background) plus a five year run at γ = 195 (the maximum energy achievable at present SPS), with a baseline L = 130 Km from CERN to Frejus. The results for Setup I are going to be compared with those for Setup II, associated with a five year run at γ = 195 plus a five year run at γ = 440 (the maximum achievable at the upgraded SPS with proton energy of 1000 GeV), with a baseline L = 650 Km from CERN to Canfranc. As explained in Section 2, the virtues of having at least two energies in a given Setup are that the two oscillation parameters θ 13 and δ can be separated out. For the Setup I we generate the statistical distribution of events from assumed values of θ 13 and δ. The corresponding fit with two parameters is shown in Fig. 2 for selected values of θ 13 from 8 o to 1 o and covering a few values of the CP phase δ. As observed, the principle of an energy dependent measurement (illustrated here with two energies) is working to separate out the two parameters. With this configuration, the precision obtainable for the mixing is much better than that for the CP phase. As seen, even mixings of 1 o are still distinguishable. We emphasize that these results are obtained with a two-parameter fit, i.e., assuming that both (θ 13 , δ) are unknown quantities.
At the time of the operation of this proposed Facility, it could happen that the connecting mixing θ 13 is already known from the approved experiments for second generation neutrino oscillations, like Double CHOOZ, Daya-Bay, T2K and NOVA.
To illustrate the gain obtainable in the sensitivity to discover CP violation from the previous knowledge of θ 13 , we have reanalyzed the statistical distribution of events with the assumption of θ 13 already known in advance. In general, the precision to obtain δ is then much better than that of Fig. 2 and the corresponding sensitivity for a CP-violation discovery is discussed later. In the case of Setup II the longer baseline for γ = 195 leads to a value of E/L well inside the second oscillation (see Fig. 1). In that case the associated strip in the (θ 13 , δ) plane has a more pronounced curvature, so that the two parameters can be better disantangled. The statistical distribution generated for some assumed values of (θ 13 , δ) has been fitted and the χ 2 values obtained. The results are given in Fig. 3 for a two-parameter fit. Qualitatively, one notices that the precision reachable for the CP phase is better than that in the case of Setup I. One should emphasize that this improvement in the CP phase determination has been obtained with the neutrino channel only, using two appropriate different energies. One may discuss in this Setup II the sensitivity to discover θ 13 = 0 by giving the χ 2 fit, for each θ 13 , to the value θ 13 = 0. This is given in Fig. 4. Although it is somewhat dependent on the δ-value, we see that values of θ 13 > 1 o are in general distinguishable for zero. The corresponding exclusion plots for CP violation in the two Setups are compared when both θ 13 and δ are unknown. The sensitivity to discover CP violation has been studied by obtaining the χ 2 fit for δ = 0, 180 o if the assumed value is δ. For 99% CL, the sensitivities to see CP violation in both Setups are compared in Fig. 5. In both cases, we assume a two-parameter fit, i.e., θ 13 previously unknown. For Setup I, a non-vanishing CP violation becomes significant for θ 13 > 4 o , with values of the phase δ around 30 o or larger to be distinguished from zero. For Setup II, the sensitivity to CP violation is better and significant even at 1 o in certain cases, depending on the hemisphere for the value of the phase δ. If θ 13 is previously known, the corresponding analysis for the sensitivity to discover CP violation is presented in Figure 6. In this case, the χ 2 fit is made with the single parameter δ. One may notice that the improvement in this sensitivity is impressive, suggesting that going step by step in the determination of the neutrino oscillation parameters by means of several generation experiments is very rewarding. As in Fig. 5, Setup II provides better sensitivity to the discovery of CP violation than Setup I. In the best case, i.e., θ 13 already known at the time of the proposed experiment with Setup II, we give in Fig. 7 the sensitivity to discover CP violation for different χ 2 to be distinguished from δ = 0, 180 o . The result is so good that it enters into the regime of a precision experiment.
Conclusions and Outlook
The simulations of the physics output for an EC neutrino beam at different energies indicate: 1) The principle of energy dependence to separate out the CP-even and CP-odd contributions to the neutrino oscillation probability works.
2) The upgrade to higher energy in the SPS boost (E p = 1000 GeV) helps to have a better sensitivity to CP violation, which is the main objective of the next generation neutrino oscillation experiments, iff accompanied by a longer baseline.
3) The best E/L in order to have a higher sensitivity to the mixing |U (e3)| is not the same than that for the CP phase δ. Like the phase-shifts in interference phenomena, the presence of δ is easier to observe when the energy of the neutrino beams enters into the region of the second oscillation. The mixing is better seen around the first oscillation maximum, instead.
4) The previous knowledge on the connecting mixing θ 13 would greatly improve the sensitivity to CP violation discovery in this facility. This statement is valid in both experimental Setups: I of lower energy, shorter baseline, or II of higher energy, longer baseline. 5) In the best configuration, i.e., with θ 13 known in advance and Setup II, the CP-violation sensitivity is of a few degrees in δ for θ 13 ≥ 1 o .
Besides the feasibility studies for the machine, most important for physics is the study of the optimal configuration by combining low energy with high energy neutrino beams, short baseline with long baseline and/or EC monochromatic neutrinos with 6 He β − antineutrinos.
Among the possible systematics associated with the proposed experiments, one should define a program to determine independently the relevant cross sections of electron and muon neutrinos and antineutrinos with water in the relevant energy region from several hundreds of MeV's to 1 GeV or so.
The result of the synergy of Neutrino Physics with Nuclear Physics (EURISOL) and LHC Physics (SPS upgrade) for the Facility at CERN could be completed with the synergy with Astroparticle Physics for the Detector, which could be common to neutrino oscillation studies with terrestrial beams, atmospheric neutrinos (sensitive to the neutrino mass hierarchy through matter effects [26]), Supernova neutrinos and Proton decay.
The analysis shown in this paper indicates that the proposals discussed here merit R&D studies in the immediate future for all their ingredients: Facility, Detector and Physics. | 4,467.4 | 2007-12-06T00:00:00.000 | [
"Physics"
] |
Web Content Accessibility of Municipal Web Sites in Turkey
The accessibility of the public web sites is crucial for the successfulimplementation of the information society. Therefore, it is essential that all citizens must have equal accessible opportunities to all e-government recourses. This research evaluates the accessibility of each of the 30 metropolitan municipal web sites in Turkey by the disabiledpeople based on the Web Content Accessibility Guidelines (WCAG) 2.0 and employing automated testing tool. It identifies the major problem of accessing the website content to those who have hearing, listening, impairments or other physical disabilities. The Intention of this study is to highlight the ignorance of the government and common people towards people with the disabilities. The Slight concern of the developers during the website development can assist these people in their website usage significantly. The Detailed results are presented after comprehensive evaluation of the metropolitan municipal websites against WCAG 2.0. The analysis of the results reveals a relatively low web accessibility of the municipal web sites and highlights several aspects.
Abstract-The accessibility of the public web sites is crucial for the successfulimplementation of the information society. Therefore, it is essential that all citizens must have equal accessible opportunities to all e-government recourses. This research evaluates the accessibility of each of the 30 metropolitan municipal web sites in Turkey by the disabiledpeople based on the Web Content Accessibility Guidelines (WCAG) 2.0 and employing automated testing tool. It identifies the major problem of accessing the website content to those who have hearing, listening, impairments or other physical disabilities. The Intention of this study is to highlight the ignorance of the government and common people towards people with the disabilities. The Slight concern of the developers during the website development can assist these people in their website usage significantly. The Detailed results are presented after comprehensive evaluation of the metropolitan municipal websites against WCAG 2.0. The analysis of the results reveals a relatively low web accessibility of the municipal web sites and highlights several aspects.
Index Terms-accessibility, WCAG 2.0., metropolitan municipal web sites
I. INTRODUCTION
The use of Information and Communication Technologies for the delivery of the publicservices is becoming more and more popular throughout the world. In the last few years, The Turkish municipalities have made great efforts to harness the implementation and the employment of the information technologies. The municipalities' portals have become a significant source of information for the authorities and citizens, within the scope that denominates e-government.
While the proportion of the people with disabilities (visual impairment, hearing impairment, cognitive disability etc.) in the society has been rapidly increasing due to the demographic trends long documented by many researchers, governmental leaders have paid little attention to their needs when planning and implementing the web projects. Therefore, it is essential that all citizens must have equal accessible opportunities to all e- Manuscript received August 3, 2015; revised November 23, 2015. government recourses. The Web accessibility encompasses all disabilities that affect access to the web, including visual, auditory, physical, speech, cognitive and neurological disabilities. WCAG 2.0 identifies the techniques to create and manage web content (i.e. dynamic and static textual, visual, or audio electronic information) in ways that are more accessible to the people with disabilities-for instance, through assistive technologies like the screen readers. The Websites that are more accessible are also generally more user-friendly to everyone.
Currently, there are a number of guidelines and tools that the web designers and webmasters can use to make their websites accessible to the people with disabilities. Such guidelines include the Web Content Accessibility guidelines (WCAG) developed by the World Wide Web Consortium (W3C), the US government's Section 508 Initiative, Americans with Disabilities Act (ADA), Australians with Disabilities Act and the National Institute on Ageing Guidelines (NIA). The Similar guidelines exist in Canada, UK and Portugal. The most common standards Based website Design and the development are W3C Web Content Accessibility Guidelines 1.0 or 2.0 (WCAG 1.0 or WCAG 2.0). WCAG 2.0 was approved as an ISO/IEC 40500 International accessibility standard in October 2012 [1]. In other words, more countries can formally adopt WCAG 2.0 and many countries are updating their laws to the new version.
An international organization World Wide Web Consortium (W3C) launched the web accessibility initiative (WAI) inorder to improve the web accessibility for the people withdisabilities [2]. For the consortium, web accessibility was defined as "access to the web by everyone, regardless of disability" accessibility means that the people withdisabilities can perceive, understand, navigate, and interactwith the web. In 1999, W3C published the first version ofthe accessibility guidelines (WCAG 1.0) [4]. The secondversion was published in 2008 (WCAG 2.0), and this is thereference recommended for use in the accessibility policies [5]. There are four key principles that underlie WCAG2.0: perceivable, operable, understandable, and robust. "Perceivable" means the web contents and user interface modules which must be offered tothe people as obvious objects. "Operable" refers to the user interface modules and navigationcomponents which should be designed in a way that they work properly. "Understandable" is about the design of a website with a friendly version. "Robust" refers to the capacity ofthe website must be interpreted by a variety type of user agents. Each principle is divided intothe success criteria which offer three conformance levels: A, AA, AAA. Three levels of conformance testing were defined as follows: A (lowest), AA, and AAA (highest).
A considerable number of the users of the web have various types of disabilities such as vision, hearing, motor and cognitive impairments [6]. The Studies show that presently most of the government websites are inaccessible for the impaired users [7]. However, more than one billion people in the world are disabled and this number is increasing day by day as the population increases [8], [9]. Turkey has an estimated population of 77.7 million, out of which about 8.5 million are disabled [10]. Although the access to the information for the people with disabilities was stated as a critical, the web accessibility of both the government level and the local government level is a problem.
The accessibility of these web sites, especially by the people with disabilities, has not been evaluated to date. This has motivated me to assess the accessibility of the metropolitan municipal web sites for the people with disabilities employing the automatic testing tools for checking of target websites. The purpose of this study is limited to the accessibility assessment ofthe metropolitan municipal web sites and to find out whether the web based public services are provided in equitable manner to all the citizens.
The rest of the paper is organized in five sections: In the adopted methodology to make the complete analysis of selected websites of government. Section 4 presents the results and their detailed description. Section 5 presents limitations, future work and concludes the paper with recommendation.
II. PRIOR STUDIES OF THE MUNICIPALITY WEB SITES ACCESSIBILITY
A sample of 30 a preliminary review of the municipality websites in Romania was evaluated in 2010 for conformancewith WCAG 2.0 level A requirements (lowestlevel of conformance) [11]. Pribeanu et al. [12] presented the results of a secondstudy carried on in 2011 based on a largersample of municipalities. The purpose of thiswork is twofold. Firstly, the larger view on the accessibility of this category of the public web sites will be obtained. Secondly, the progress in the web accessibility / the degree to which the web accessibility is maintained in time will be analysed [1 studies have been carried out to evaluate theconformance of Romanian municipal web sites withWCAG 2.0 accessibility guidelines [13]- [15]. [16] presented the results of an evaluation of the level of accessibility of the 100 largest municipalities' websites. The results of this study showed that while a number of cities have accessibility statements, overall compliance with Section 508 is low.
Evans-Cowley
Freire et al. [17] presented a metric based on the approach for evaluating the municipalities Web pages using the automatic accessibility evaluation tools. The Results exhibited that much work should be done to improve the accessibility of the Brazilian municipalities'web sites.
Kumar and Sareen [18] examined the relationship between the income levels of the city and the quality ofthe municipal website.
Youngblood and Mackiewicz [19] employed a heuristics-based content analysis to determine the extent to which municipal government websites comply with the basic usability and accessibility best practices. The Authors applied this technique to 129 official websites for Alabama cities. The other studies have been carried out to evaluate the conformance of the American municipal web sites with the usability and accessibility guidelines [20]. Youngblood and Youngblood [21] found that the portal adoption is associated with each of the demographics above and that accessibility has a weak inverse relationship to the per-capita income.
Miranda et al. [22] evaluated 84 Europeanmunicipal web sites using a model that focusedon four categories of factors: accessibility, speed, navigability and content to access the quality ofweb pages.
Abdelgawad et al. [23] presented a demonstrator simulation model, built employing System Dynamicsmethodology. The model focused on the accessibility of the Norwegian Municipal websites, and was intended to be used as a decision support tool, mainly for the managers responsible for the website development and maintenance.Nietzio et al. [24] evaluated the accessibilityof a group of the Norwegian municipalitiesdesiring to improve the accessibility of theirwebsites. The approach undertaken by themin the eGovMon (eGovernment MonitoringProject) national [23].
Kopackova et al. [25] focused on the accessibility of locale-government web pages in the Czech Republic. The web pages were analysed both from a citizen's point of view (with disadvantage due to the disability or to the technical equipment) and from the point of view of fulltext search engines.
Shi [26] tried to provide an overview of the accessibility of Chinese local government Web sites.
Research results indicated that all the surveyed Chinese e-government Web sites failed one or more W3C's accessibility measures and thus many disabled the Chinese people may have substantial problems to access them.
Sun and Chen [27] tried to find out how accessible they are by means of almost all the examined websites of the provincial and municipal government. To some extent, the accessibility research is a new field in Turkey and there is no accessibility data related to the local public web sites. The Accessibility and usability for the disabled people is the main concern in this area [29]- [33]. According to the auhor's knowledge, there is no one reported who had done such kind of case study of testing a public web site for the accessibility with the disabled users.
III. METHODOLOGY
There are several approaches to the accessibility evaluationand, consequently, many accessibility evaluation methods. Brajnik [34] mentioned the following five categories: Conformancereview, subjective assessment, screening techniques, barrier walkthrough, and user testing.This study is reviewing the metropolitan municipality websites for the accessibility. The sample consists of the first 30 Turkish towns ranked upon the population, according to the 2014 census.
The Conformance review is an analytical method based on the standards and/or the guidelines and includes the computer-aided testing with the accessibility checking tools. As such, it depends on the chosen checklist.After the web accessibility evaluation tools are the software programs or online services that are employed to check your website's accessibility level under the web accessibility guidelines. There is a huge number of the accessibility tools for the commercial purposes or freely available on the web such as Watch Fire Bobby, AChecker, Cynthia Says, EvalAccess, Accessibility Valet Demonstrator (WebThing), AccMonitor Online (HiSoftware), Torquemada (WebxTutti), Wave 3.5 (WebAIM) and Tawdis etc. Some good free web-based website accessibility evaluation tools are linked in [35]- [38]. The whole list of the accessibility evaluation tools is in W3C [39]. These tools are very beneficial for the programmers and designers to determine whether or not their sites follow WCAG. During the design, implementation, and maintenance phases of the web development if these tools are employed carefully, it can assist the targeted users to prevent the accessibility barriers, repair the encountered barriersand improve the overall quality of the web sites [40]. This study will employeTAW automatic evaluation toolwhich is considered as the web accessibility test tool which is capable of providing the complete analysis of the website accessibility and have been the pioneers and are the most well-known, due to their usability, the ease of use and its quick results. TAW is a limited online free service to check the web accessibility against WCAG 1.0 and 2.0 [41]. In this study, the sampled the web pages were evaluated against WCAG 2.0 guidelines (conformance level A).The home page of each one of the websites has been analysed from the accessibility point of view. The home page of a website is the first contact a user has with the website. If the home page displays problems or is not accessible, it would be very difficult that a disabled user can access other pages of the website. Therefore, it is essential to ensure the accessibility of the home page of a website. All the tests of a web page were conducted during the same day in order to avoid alterations in its content. The evaluation was conducted in December 2014-January 2015.
IV. RESULTS
Thirty metropolitan municipalities were evaluated for compliance with the WCAG 2.0 accessibility criteria. Fig. 1 illustrates the overall violation results per guideline for each principle. Due to the lack of space, the author cannot include the whole outcomes of the web accessibility analysis. Therefore, Fig. 3 summarizes the number of the problems detected with the automatic evaluation tools and some information has to be discarded. Unfortunately, the home pages of all the websites have the accessibility issues. The study targeted the metropolitan municipality web sites and revealed several accessibility problems: graphical items that are not accessible to the screen readers, difficult navigation due to the lack of empty links, the lack of text alternatives for the graphical elements, the lack of textual description. In general, the worst results regarding the web accessibility were obtained with the websites of Konya metropolitan municipality, Antalya metropolitan municipality and GaziAntep metropolitan municipality. On the other side, the best results were obtained with the websites of Van metropolitan municipality, Şanlı Urfa Muğla metropolitan municipality. Overall, 3440 WCAG 2 errors were detected on the home pages with a minimum of 4 (one metropolitan municipality) and a maximum of 275 errors (See Fig. 2). A more detailed analysis of results reveals several aspects regarding the conformance to WCAG 2.0 accessibility level A. In Fig. 3 a grouping of web sites following the WCAG 2.0 principle and the error type is presented. In the following section each accessibility principle is analysed and described in depth.
A. Principle 1: Perceivable
The perceivable accessibility principle is the highest violated principle across all metropolitan municipalities. Most errors are related to the first WCAG 2.0principle (perceivable) 52% with a minimum of 1 (one metropolitan municipality) and a maximum of 154 errors. From these, two error types are more frequent: the lack of text alternatives for the nontextcontent (26.62% from total) and the use of labels to modify the presentation (11.71% from total). These two error types account for 38.33% the total number of errors.
The highest violated success criteria in this guideline are the thelack of text alternatives for non-text content. The purpose of alt attribute is to read the text associated with an image that serves the same purpose and conveys the same essential information as the image. It is read out loud by the screen readers for those with visual impairment.
Two home pages had no error. 17 home pages had 1-20 errors. At the other side, 4 web sites with 21-50 errors and 7 web sites with more than 50 errors.
B. Principle 2: Operable
In regard to the operable accessibility principle, this is concerned with ensuring the operability of User interface components and navigation. Other frequent accessibility errors that are relatedto the perception are: consecutive text and image links to the same resource (3.92%), two headers of the same level with no content in between 2.73%, form controls without associated label 2.29% and form controls without label 2.26%.
Regarding the second WCAG 2.0 principle (operable), the total number of errors is 676(19.65% from total). Two error types are more frequent: empty links (18%) and image maps without alternative (1.25%).
The highest violated success criteria in this guideline are the theempty links. This failure condition occurs when a link contains only a non-text content, such as an image, and the non-text content has been implemented in a way that it can be ignored by the assistive technology. Since there is no text content within the link to be used as the name, assistive technology employs a variety of the repair techniques to find some name to use for the link. The Conclusion is that the most accessible link is the one that contains the link text.
Five home pages had no error. 14 home pages had 1-20 errors. At the other side, 7 web sites with 21-50 errors and 4 web sites with more than 50 errors.
C. Principle 3: Understandable
In regard to the understandable principle; this sets guidelines to ensure that information and the operation of user interface are understandable. Regarding the third WCAG 2.0 principle (Understandable), the total number of the errors is 113(3.28% from total). Two error types are more frequent: Labeling of form controls (2.29%) and the declaration of language of the document (0.67%).
The highest violated success criteria in this guideline is the providing labels for form controls, or usage the attribute 'title' to indicate the control functionality.
The second highest neglected criterion is the language of page, where every web page is required to have a correct language declaration, this criterion is very important for screen readers. For example, if German is not indicated for a German-language website, the screen reader will read the site in English.
D. Principle 4: Robust
The robust accessibility principle is the second highest violated principle across all metropolitan municipalities. The last WCAG 2.0 principle (robust) account for a total of 867 errors (25.20%) respectively the web page wellformedness 762 errors are more frequent (22.15%). Two error types are more frequent: Form controls without label (2.29%) and frames without title (0.64%).
The objective of this technique is to avoid the ambiguities in the web pages that often result from the code that does not validate against the formal specifications.
Only one home page had no error. 15 home pages had 1-20 errors. At the other side, 8 web sites with 21-50 errors and 6 web sites with more than 50 errors.
The highest violated success criteria in this guideline are the theuse of labels to modify the presentation. The objective of this technique is to facilitate the interaction of the assistive technology with the content via separating the content's structural encoding logically from the presentational encoding. The Structural encoding is the indication of the elements such as headings, paragraphs, lists, tables, etc., and is done through using the technology features reserved for the purpose.
Sixteen home pages had no error. 8 home pages had 1-20 errors. At the other side, 3 web sites with 21-50 errors and 3 web sites with more than 50 errors.
V. CONCLUSION
This paper endeavors to discover the significance of the website content accessibility focusing the disabled The study further investigates that most of the metropolitan municipality web sites of Turkey are failed to follow W3C WCAG 2.0 guidelines. There are two types of errors that are frequentlyencountered in most web sites: the lack ofalternate text for non-text content and the useof tags purely to create the visual presentations (instead of using CSS). These issues mainly affect the people with visual disabilities. This can cause an accessibility barrier to the screen reader users.This paper is also an eye opening study for all the website developers which will hopefully assist them to identify the key problems of the website accessibility that should be taken into account during development.
Like any other study of this kind, the analysis presented above suffers from number limitations. The first limitation is related to the exclusive reliance of our accessibility analysis on the automated testing results. TheWeb accessibility evaluation tools and expert inspections cannot substitute user testing, because the difficulties of comprehending all the interactions between the web content and the assistive technology. Vigo and Brajnik [42] mentioned the automated accessibility evaluation has several inherent limitations [42], [43].
Hackett and Parmento [44] another limitation is the restriction of our automated accessibility testing on the home page of each tested website. Hackett and Parmantoindicate that home page is not enough when evaluating the web site accessibility.
Moreover, researcher mainly focused on the conformance with WCAG 2.0 without using all features provided by the tool, such as: parsing errors, HTML errors, CSS errors, Browser compatibility, HTML 5 and ARIA usage and broken link errors. Second, the sample size is small since only 30 metropolitan municipal web sites were evaluated. Turkey has 1397 municipalities nevertheless in this study, 30 metropolitan municipal web sites were evaluated. However, some degrees of the representativeness exist since these municipalities have a total population of 58.999.801million people (77%).
Throughout the whole investigation to determine the conformance level of the accessibility, the researcher adopted the TAW evaluation tool which was open source application. However, which is widely used and to ensure the scalability of the result researcher followed W3C Evaluating Accessibility (W3C, 2014). Although the commercial tools (e.g. Bobby) are not freely available and expensive, I will try to apply both the commercial evaluation tools and also open source and commercial assistive Technologies (NVDA, JAWS, etc) them in my next study. In addition to, in order to obtain more conclusive results, I plan to compare the results across countries and across different municipal websites. Finally, another future work I plan to address is to detect the most common problems that recur in the same site and between different sites. And also, I intend to carry on a future evaluation after one year with a larger sample as a second evaluation. In this way I could measure the progress of the web sites already evaluated and better describe the accessibility of the municipal websites. | 5,168.8 | 2016-01-01T00:00:00.000 | [
"Computer Science"
] |
Science as a moral system
Science is a collaborative effort to produce knowledge. Scientists thus must assess what information is trustworthy and who is a competent and honest source and partner. Facing the problem of trust, we can expect scientists to be vigilant. In response to their peers’ vigilance scientists will provide reasons, not only to convince their colleagues to adopt their practices or beliefs, but also to demonstrate that their beliefs and practices are justified. By justifying their beliefs and practices, scientists also justify themselves. Reasons in science thus do not only function as tools of persuasion but also to manage reputation. This analysis strongly suggests that science constitutes a moral system, which has implications for the study and philosophy of science.
Introduction
In 2015 the physics journal Physical Review Letters published, for the first time ever in the history of science, a paper with more than 5,000 authors. The findings reported in the article resulted from the combined efforts of two teams working with the Large Hadron Collider in Geneva. Their goal was to obtain a better estimate of the mass of the Higgs boson that was only discovered a couple of years before. Such instances of "hyperauthorship" (Cronin, 2001) illustrate the increasing importance of large collaborations in science. The complexity of the subject matter and, consequently, the knowledge and technicalities involved in studying it demand ever higher levels of specialization, which no single individual can master. As a result, scientists must put The critical discussion among scientists results in what Longino (2002) describes as "local epistemologies". These epistemologies determine which beliefs and practices scientists within a particular research community find acceptable. Here, I will argue that local epistemologies also function as local moralities. They do not only determine what beliefs and practices are acceptable, but also which individuals are trustworthy partners in the collaborative pursuit of knowledge. Scientists, therefore, do not just provide reasons to convince their peers to accept their practices and beliefs, but also to regard and accept them as trustworthy partners in the production of knowledge. They use reasons as tools for reputation 1 management to convince their peers that they believe and act in justified ways. Science thus functions and can be understood as a moral system. 2 The paper has the following structure. First, I will first briefly discuss the role of trust in science and how this entails the problem of evaluating the trustworthiness of one's peers. Second, as an example of the role of trust in science, I will discuss a historical study by Shapin (1994) of how early modern scientists solved this problem by recruiting the moral code of English gentlemen. Relying on the trustworthiness of English gentlemen to gauge one's reputation, however, is too culturally idiosyncratic to explain the universal role of trust in science. Therefore, thirdly, I introduce cognitive and evolutionary perspectives on communication and cooperation to argue that in science reputation management is handled, at least to a large extent, by the production and evaluation of reasons. From this analysis I infer that science is a moral system recruited for knowledge production. I conclude with a discussion of the implications of this novel perspective for the study and philosophy of science.
Cooperation, communication, and trust
Science is the collaborative effort of producing knowledge. It is therefore slightly weird that traditional approaches in epistemology and philosophy of science have largely overlooked the role of communication and collaboration of science. Instead, they have focused mainly on individual means of acquiring beliefs, namely by relying on our senses and reasoning capacities (Hardwig, 1991). Information that we acquire from others was suspect because people might be wrong or worse, they might even try to deceive us. In recent decades, however, students of science have become increasingly aware of the social dimensions of science. Sociological and ethnological analysis made it blaringly clear that science is not just about accumulating objective data and rigid logical reasoning as some philosophers of science had pretended. Instead, science relies on everyday forms of social interaction and communication involving power struggles, groupishness, competition, emotions, gossip, and argumentation (Feyerabend, 1975;Latour & Woolgar, 1986[1976; Shapin & Schaffer 1985;Ziman, 1968). Epistemologists and philosophers of science have since then integrated these important corrective insights to understand and explain how the social processes of science result in reliable beliefs about the world (Haack, 2003;Kitcher, 1993;Longino, 1990Longino, , 2002. The inherently collaborative and social dimension of science comes in various guises (Haack, 2003;Longino, 2002;Oreskes, 2019). One is the fact, as already mentioned in the introduction, that scientists build on the work of their predecessors and their colleagues. The idea of the scientific genius who, in splendid isolation, labours day and night on experiments and data to attain wonderfully new insights in the structure of the world is a myth. Important figures in the history of science such as Newton, Lavoisier and Darwin could only develop their new theoretical perspectives by relying on the ideas and findings of others, as they fully realized themselves.
Another aspect is the division of cognitive labour (Kitcher, 1993). The world is too complex for one individual to study and understand it in all its aspects. Scientists must specialise in one domain, or a subdomain of that domain, and must leave the other domains to others. Even when investigating a specific research question, scientists rely on one another's skills and expertise to obtain an answer. A third aspect is the organized criticism (Merton, 1973) that we find in peer review, where experts are invited to evaluate the strengths and weaknesses of the articles submitted by their peers. Scientists too are often blind to the errors and omissions in their own research.
By taking a fresh and critical eye, their colleagues can more easily spot and report them, a process that tends to result in more reliable studies (Longino, 2002).
Sciencee is a social enterprise and communication plays a crucial role in its processes. Not only do scientists communicate through institutionalized channels such as books, journal articles, and conference presentations, but also, and more informally and frequently, in discussions and talks that take place in seminars, labs, offices, over the coffee machine, and at conference dinners. Furthermore, as Longino (2002, pp. 99-107) argued, observing and reasoning, of which philosophers traditionally thought of as individual means of acquiring knowledge, are social activities that involve communication as well. Both are processes through which scientists reach a consensus by arguing with one another. Science would simply not be possible without communication and collaboration.
Scientists can rely on one another to collaboratively create reliable representations of the world. However, communication and cooperation also bring certain problems, one of which is that others might deceive or manipulate us (Heintz et al., 2016;Sperber et al., 2010). The question that arises is what information and whom to trust (Mercier, 2020). 3 Scientists too face this problem but given the ubiquity of communication and cooperation in science they seem to have successfully solved it. But how exactly have they done so?
A league of gentlemen
Traditional epistemology has long displayed an "individualistic bias" (Hardwig, 1991, p. 701). The main question to solve was when an individual has knowledge, i.e., justified true belief. To gain knowledge relying on others was not an option. If I do not know someone else's reasons for their belief, then how can I be justified in adopting that belief? How can I tell that the other is not mistaken, or even worse, lying to me? Hardwig criticized this scepticism and argued that trust in others is not only acceptable but necessary to gain knowledge. Scientists constantly rely on another and therefore need to trust their colleagues. He wrote, "belief based on testimony is often epistemically superior to belief based entirely on direct, non-testimonial evidence", when others have "epistemically better" beliefs that oneself (Hardwig, 1991, p. 368). Doing away with trust in knowledge production is not an option because "the alternative to trust is, often, ignorance." (Hardwig, 1991, p. 707) If we want to understand scientific knowledge production, we must investigate the role of trust in science. Since then, philosophers have indeed taken up this important task (e.g., Frost-Arnold 2013;Rolin, 2020;Wilholt, 2013).
One way to study how scientists solve issues of trust is to look at the time and place when modern science emerged, which is, among others, in 17th century England. In The Social History of Truth (Shapin, 1994). Shapin investigates how scientists rely upon and thus trust one another to make their collaborations work. Scientific knowledge requires a group of people who come to an agreement about what is the case, and so decide what counts as truth. Shapin's analysis very much emphasizes the role individual scientists play in the production of knowledge, a role that they tend to render invisible when they report their research to create the impression that science is an entirely objective affair, that does not rely upon the activities and the interactions of people. Indeed, scientists tend to focus merely on content and simply report and justify their methods and beliefs to convince their peers. They do not even tend to mention their own role in the research, let alone of the people they consulted and argued with. It is, therefore, not a surprise that traditional philosophy of science focused almost exclusively on the objectivized aspects of science such as formal methods and theoretical statements. However, by providing such objectivized accounts, both scientists and philosophers deliver a strongly distorted image of how scientists produce knowledge.
To attain a proper understanding of science one must consider the fact that science is a collaborative process that builds on trust. This implies that scientists do not only make a judgment about the reasonableness of the transmitted content, but also about the credibility and honesty of the communicator (see also Hardwig 1991, p. 707). In fact, our assessment of the reliability of these beliefs is entirely intertwined with our evaluation of the trustworthiness of the source. As Shapin writes: "What we call 'social knowledge' and 'natural knowledge' are hybrid identities: what we know of comets, icebergs, and neutrinos irreducibly contains what we know of those people who speak for and about these things, just as what we know about the virtues of people is informed by their speech about things that exist in the world." (Shapin, 1994, p. xxvi) By attributing trust, scientists bring an important moral dimension to the production and distribution of scientific knowledge. According to Shapin, scientists in seventeenth century England handled these moral dimensions by recruiting the moral code of gentlemen. A gentleman-scientist was supposed to be well-mannered, that is, to be honest and sincere, so that his peers could trust his testimony. Consequently, it was important for scientists to maintain their reputation of a gentleman by abiding by those manners. By doing so, they do not only show worthy of respect by their peers, but also that they treat their peers with respect, that is, as gentlemen and thus worthy of our moral considerations (on "the moral significance of manners", see Buss 1999).
Shapin's analysis brings into sharp focus that science is a collaborative project which involves relying on the testimony of others. Hence, scientists need to decide what information they will accept as true, a judgment that they often make based on their assessment of the honesty of the source, which imports a moral dimension into science. This also means that scientists will guard their reputation as a trustworthy source and a reliable collaborator in the production of the collective good called knowledge. However, the English gentlemen code is far from universal, but instead tied to a particular time and space that is not available to scientists anymore. The code relied on a form of trust that suited English gentlemen, but typically excluded other voices such as those of women and other marginalized groups (Baier, 1986). Since such exclusion undermines the diversity required for knowledge production 1 3 (Longino, 2002), the gentleman code is not suitable to solve issues of trust in contemporary science. The question then arises: How do scientists today solve these issues? By relying on recent insights from cognitive and evolutionary psychology, I will argue that scientists commonly rely on social processes involving cooperation and communication that were not alien to English gentlemen either. As such, we will not only be able to develop a more profound understanding of how science functions as a moral system, but also provide an answer to the question why it does.
Trust by vigilance
Shapin acknowledges that science has changed tremendously over the centuries and hence requires different solutions to the problem of trust. In the seventeenth century natural philosophy scientists knew one another personally. In modern science, however, scientists extend their trust to their colleagues not because of their virtuous character but because of their expertise that is guaranteed by institutions. However, Shapin claims, science still fragments into "core-sets", small communities of scientists that collaborate with one another to investigate and solve a particular problem. Members of such core-sets interact with each other like the scientists-gentlemen of the seventeenth century. Nevertheless, within or outside such core-sets, trust continues to play a crucial role in science, even more so than in our daily lives.
Shapin's analysis shows that whatever cultural context scientists find themselves in they must sort out who and what to trust. In this sense, they are no different from other humans. In our everyday affairs we constantly rely on information we acquire from others: we visit our physician to ask about our health, ask people for directions, and learn about places to visit with the children from our friends. Extending trust to people comes natural to us. However, trust is not the same as blind trust (Mercier, 2020). When we trust people, we rely on mechanisms of epistemic vigilance by which we intuitively evaluate both the content and the source of the information (Sperber et al., 2010). We check whether the new information is consistent and coheres with the beliefs they already hold. We also assess whether the source is competent and benevolent. Only when the content and the source tick the right boxes, we will accept the provided information.
Vigilance has the effect of making people honest, which, in turn, explains why our trust is usually not misplaced. People intuitively realize that their audience will critically evaluate the information they provide, and hence adjust the information to the expected standards of their audience (Sperber, 2013). Moreover, since people will not only gauge the reliability of the content, but also of the source, it pays off to provide people with accurate information so that one builds a reputation of a competent and benevolent source (Altay et al., 2020). Because the targeted audience expects the source to have such considerations, they can then expect both the content and the source to be trustworthy. Trust grows in vigilant soil.
The fact that people often have misbeliefs indicates that the processes involved in epistemic vigilance are not entirely fool proof. One can be wrong in one's evaluation and become a victim of deceit. Scientists can commit fraud because their peers expect them to submit to certain norms of scientific conduct (Ritchie, 2020). However, the problem with vigilance is not so much that we are overly trusting, but quite the opposite (Mercier, 2020). We tend to discard useful information more than we accept wrong information. As soon as the new information clashes with our previously held beliefs or when we do not trust a source for whatever reason, we shut our epistemic gates and hence miss out on lots of opportunities to learn important lessons from others. However, the source is not entirely without ammunition as she can crack open the gates by persuading the addressee to accept the information she provides. She can do so by providing reasons (Mercier & Sperber, 2011, 2017.
Reasons
Philosophers and psychologists have since long acknowledged and emphasized the role of reasoning in the production of knowledge, even at the expense of other sources of knowledge such as experience and, especially, communication. Plato, for instance, believed that reasoning enables our mind to escape the vagaries of our lives and attend to the all-important supernatural realm of immutable and perfect forms. Descartes assumed that by thinking clearly and distinctly he could attain unassailable divine truths about the world. More recently, psychologists who work under the banner of dual system theory, have proposed that the reflective or reasoning system corrects for the mistakes of the intuitive system and hence enables us to improve our individual thinking (e.g., Kahneman 2011).
The recently developed interactionist theory by Mercier & Sperber (2011, 2017) challenges this traditional view and argues that reasoning is a social rather than an individual process. 4 The authors start from the observation that if the function of reasoning is to enable us to attain better beliefs on our own, it does not do a very good job. People tend to make systematic reasoning errors such as the confirmation or myside bias. The authors suggest that these errors can be explained if one assumes that our reasoning serves a social function, i.e., to convince others and to justify ourselves which are everyday processes. A shop assistant might try to sell you a sweater by mentioning the quality of the fabric or the low price. When the young dentist accidentally touches the nerve, she might invoke her inexperience to account for her clumsiness. 5 People, however, remain vigilant and are not easily swayed by reasons and this for, well, good reasons. The production of reasons tends to be "biased and lazy" (Mercier & Sperber, 2017, p. 9). Biased, because we will tend to look for arguments that support our case (which explains the confirmation or myside bias); and lazy, because why would one invest time and energy in finding a better argument if a readily available but weaker one suffices. As addressees want to avoid accepting false information or endorsing behaviour that might harm them, however, they will be more critical in evaluating the provided reasons (Sperber et al., 2010). The result of such vigilance is that the producers will have to make an effort and provide reasons that not only reflect one's own point of view, interests and concerns, but also tie into those of their addressees', and hence become less self-serving (Mercier & Sperber, 2017).
Interactive reasoning plays an important role in science as well. As sociological studies of science have pointed out scientific reasoning is not a matter of rigidly applying the rules of logic, but about exchanging arguments and providing justifications and hence is not different from ordinary reasoning. For instance, Ziman (1968, p. 8) notes in his Public knowledge: The social dimension of science that "the reasoning used in scientific papers is not very different from what we should use in an everyday careful discussion of an everyday problem". Scientists try to convince their peers of their views to make them acceptable so that they become part of the consensus. In a similar vein in their famous anthropological study of science Latour andWoolgar (1986 [1976], p. 76) argued that the everyday process of argumentation is key in understanding how scientists create facts: (...) everything taken as self-evident in the laboratory was likely to have been the subject of some dispute in earlier papers. In the intervening period a gradual shift had occurred whereby an argument had been transformed from an issue of hotly contested discussion into a well-known, unremarkable and non contentious fact. Longino (2002) labels this process, by which interactive reasoning changes individual opinion into knowledge as "transformative criticism". Scientists provide arguments and justifications for their hypotheses and practices. The individuals who manage to convince their peers will have their beliefs and practices accepted by their research community as objective knowledge ((in the sense of an intersubjective consensus). These are the beliefs and practices of which the community assumes are the best supported by reasons. Reasons thus also set the standards for what counts as knowledge and proper ways of producing it. They determine what beliefs and practices are acceptable to the community. What these standards are differ from domain per domain, problem per problem, and hence from community to community. For instance, ways of producing knowledge in high energy physics are markedly different from those in molecular biology as their respective subjects require different methods, different technologies and artefacts, different notions of what counts as an observation, etc. (Knorr Cetina, 1999). Hence, scientists working on a particular domain create what Longino calls a "local epistemology": Through their interactions they set the standards for knowledge not for the whole of science, but within their own research community.
In presenting their work scientists will try to convince their peers that their beliefs and practices meet the standards of their community. As such, they will put them, as Sellars (1963, p. 107) famously noted, in the "logical space of reasons". The focus on beliefs and practices, however, blinds the involvement of human individuals. Talmont-Kaminski (2020), for instance, argues that in science vigilance is primarily targeted at the content, not so much at the source of information. However, scientists will not only be concerned about checking the trustworthiness of communicated information and its source, but also to what extent their peers can be relied upon as collaborators. I will argue next that the reasons that determine the fate of scientific beliefs and practices, also regulate the behaviour and interactions of the individuals who bring them about.
Local moralities
Science is the collaborative effort to produce knowledge about the world. As collaborators, scientists thus face the problems that are typical of and common to all forms of cooperation. One crucial problem that any individual must solve is to figure out who is a reliable partner and who is not. If one has several options available, then one enters a biological or cooperative market that consists of all potential cooperative partners. In such a market the individual can shop for trustworthy collaborators (Barclay, 2013;Noë & Hammerstein, 1995). An individual does not care to collaborate with someone who wants to profit from the interaction at one's expense. As such, we can expect any individual to exercise strategic vigilance, that is to look for cues that reliably indicate the trustworthiness of a potential partner (Heintz et al., 2016). One important such cue is an individual's reputation (Raihani, 2021, p. 195). If a person has the reputation of having reliably collaborated in the past, then this might indicate that she will act accordingly in the future. As such she indirectly reaps the benefits of her previous collaborations ("indirect reciprocity", see Alexander 1987). A person's reputation can be gleaned from her track record -how has she behaved so far? -or established by hear-say -what are other people's experiences in collaborating with this person? (Alexander, 1987) In response, an individual will try to make a good reputation for herself by reliably collaborating so that people can see for themselves that she is a reliable partner and that people will say nice things about her (Dores Cruz et al., 2021;Heintz et al., 2016). However, how people interpret your actions and what they will say about behind your back is not entirely under one's control (Origgi, 2018). But one is not entirely at the mercy of others' evaluations and gossip either. One can actively manage one's reputation not just through one's actions but also by providing reasons (Mercier & Sperber, 2017). 6 Reasons plays an important role in reputation management because it enables people to indicate that they are reasonable and hence cooperative community members. People commit themselves to the norms that these reasons imply (Mercier & Sperber, 2017). For instance, when Sara argues that she does not put the heat on anymore because she does not want to support Putin's regime, she thereby commits herself to that standard. To the extent that others find this standard acceptable they will assume that Sara's decision is justified and that she herself acts on good reason. As Mercier & Sperber (2017, p. 186) note "good reasons are seen as justifying not just a thought or an action, but also the thinker of that thought, the agent of that action." In a similar vein, scientists are justified when their beliefs and actions are supported by reasons their peers find acceptable. By providing the right sorts of reasons (e.g., the used method as a reason to justify the data, the data to defend the hypothesis, and so forth) a scientist does not only attempt to justify her beliefs and behaviour, but she is also trying to justify herself. She indicates that she behaves and thinks in ways a member of her research community is expected to behave and think. 7 Hence, the reasons that scientists provide do not only result in local epistemologies, but also local moralities. They determine what a scientist is allowed to say and do if she wants to be known and thus build a reputation as a reasonable and hence cooperative member of her scientific community. If a scientist wants to do or say things that the current set of reasons does not permit, she will try to alter the set by introducing new reasons so that she is justified in her belief or actions after all, just as in any moral system. She thereby does not only put her beliefs and actions in the logical, but also the moral space of reasons.
Although reasons play a crucial role in science -they determine which individuals, actions and beliefs are acceptable -their impact might be mostly indirect. Reasons usually function as post hoc rationalizations, justifying the outcome of processes that crucially do not depend on reasons. The function of reasons is not to accurately describe our mental states or attitudes, but we employ them as social tools to manage our reputation (Bergamaschi Ganapini, 2020; Dennett, 2017;Haidt, 2001;Kurzban, 2010;Mercier & Sperber, 2017). In fact, scientific processes tend to be a lot messier than scientists pretend when they provide reasons (Latour & Woolgar, 1986[1976). As Popper (1972) already realized scientists do not proceed as rationally as we might like to think. They work much more intuitively, based on trial and error. They have hunches about possible solutions and the roads that might lead to them. When they are lucky, their hunches turn out be correct but often scientists end up in dead alleys (Grinnell, 2009, p. 9). But when things go wrong, scientists usually do not give up easily. They provide rationalizations for why the research did not work out the way they assumed thereby displaying a myside bias as any human being (Mercier & Heintz, 2014). They reconsider their position only when their peers make them to through interactive reasoning (Dunbar, 1995;Mercier & Sperber, 2017, p. 318).
Nothing of this messiness ends up in the official reports that we call scientific articles. Take any journal article and you will not read an accurate description of the going-on in the lab, but, as Ziman (1968, p. 34) aptly notes: The work as published is no mere chronicle of the research as it took place; it is a much more contrived document, with its logical teeth brushed and its observational trouser seams sharply creased.
However, reasons do exert an ante hoc effect as scientists will try to conduct their research in such a way that it enables them to justify their newly introduced beliefs, methods, or results and themselves when they present their work. For instance, they will rely on the methods of which they know they are acceptable within their research community. By following those methods, they will later be able to convince their peers of their results and the hypothesis they support. Reasons thus influence the course of science as scientists adjust their views and actions to the normative expectations of their peers. However, when their research does not deliver the expected outcome scientists might manipulate their study to get a result after all. Strategies such as p-hacking, file-drawering and even outright fabricating data become tempting options (Ritchie, 2020). To prevent such misbehaviour an increasing number of scientific journals demand preregistrations. These preregistrations might suggest that reasons directly cause scientists to behave in such and such a way. However, given the function of reasons in general it seems more plausible that preregistrations do not simply provide accurate descriptions of scientists' psychology but constitute commitment devices by which scientists promise to behave in acceptable ways. They are tools for reputation management.
Scientists also adjust to these normative expectations by presenting their work in an impersonal style, giving the impression that their own individual activities and contributions are of no concern (Grinnell, 2009). This move entirely blinds the fact that science depends on individuals seeking to establish a good reputation as a reliable trustworthy partner in the collaborative pursuit of knowledge. However, as Shapin (1994) argued, it is not because the role of the individual and hence the moral character of science is largely blinded or transparent that it does not exist. By relying on cognitive and evolutionary insights about human cooperation and the role of reputation therein I have tried to bring this moral character to light. In the final section I will argue that this has important implications for our understanding and the philosophy of science.
Science and reputation
What follows from the account of science as a moral system is that science should display typical features of such a system and that it can explain why it has such features. One is that scientists do not only evaluate beliefs and practices but also their fellow scientists. This means that when scientists behave improperly such as in the case of fraud their peers will not only reject the beliefs, practices and data that are involved and result from fraud; they will also punish the perpetrator, usually by ostracizing her. A scientist who behaves in ways that are unacceptable to the community is banned from the cooperative market and hence no longer allowed to participate in the production of knowledge.
Because violating one community's normative expectations can bring high personal costs, most scientists will tend to believe and behave in acceptable ways to procure their reputation as a reliable collaborator (Blais, 1987). However, psychologists theorize that humans are probably not Machiavellian strategists who calculate their reputational score and only do good when they know people are watching -although people do behave better when being watched (Baumard et al., 2013;Heintz et al., 2016;Sperber & Baumard, 2012). As such calculations would probably miss opportunities to promote our reputation, most humans are disposed to act pro-socially, so that will tend to act in ways that further collaboration. Hence, they demonstrate that they are reliable collaborators without necessarily being consciously aware of the reputational gains their behaviour imports (Heintz et al., 2016). In the same vein we can expect scientists to adopt a pro-social stance and do what they are expected to do to advance the collaborative production of knowledge (Frost-Arnold, 2013;Rolin, 2020). 8 Despite the alarms raised about the decay of science, most of the scientific production of science will live up to scientific standards because overall scientists will tend to behave in ways that they can justify. This does not mean that no scientist will be tempted to cheat or that certain conditions such as high publication pressure might lead more individuals to risk reputation damage and break the rules. Or, that the standards are always what they should be (Ritchie, 2020). Therefore, efforts to raise the standards of science under the banner of open science including the preregistrations should be welcomed. But overall, we can expect most scientists to be honest without much need for external measures. Their prosocial nature will direct them to acceptable beliefs and behaviour.
Practically, the tendency of scientists to conform to the prevailing norms might bring good news for science. Its standards are upheld because scientists desire to be and to be known as reliable collaborators in the production of knowledge. At least, we must take these considerations into account when calculating the costs and benefits of measures to improve science. If a large majority of science is already prone to behaving well, then most scientists might not need extra policing so that the costs of the measurements might be outweighed by their benefits. However, scientists' desire to conform may also have negative effects. When a scientific community gets stuck by continuing practices and endorsing beliefs that are unjustifiable when evaluated from outside the community, many members of that community will still tend to bring their individual beliefs and behaviour in line with the available reasons, rather than challenge them. It takes courage to dare to question the status quo and endeavour to alter the standards of the community as in any moral system (Pennock, 2019). As one does not behave or believe as expected, one risks being ostracized by the community. The conservative streak in science is understandable as most alterations of standards do not result in improvements. Think, for instance, of purveyors of pseudoscience who continue the question the standards by which they are excluded. However, at times, 8 The position I am arguing for here might cover the middle ground between the "reliance of self interest" account and the "moral trust" account discussed by Frost-Arnold (2013). In the former account scientists trust their colleagues because they know that their colleagues know that they risk punishment if they would violate other people' trust. This position is defended by Blais (1987). Frost-Arnold argues for the latter view and holds that scientists trust their colleagues because they expect them to be morally motivated. My take suggests that people are indeed sincerely morally motivated because such motivations direct them towards cooperative behavior that results in a high reputational pay-off, thereby making future cooperation with others more likely. Nonetheless, reputational concerns and the fear of exclusion will play a role as well. (for a discussion of the role of moral and reputional motivations in cooperation, see Sperber & Baumard 2012) some of the changes bold individuals suggest are worth the risk as they eventually make it to the consensus and bestow the individual or individuals who introduced it with a reputation beyond the grave.
Cognitively, we can predict that the processes by which scientists defend and adjust their beliefs and practices depend on the same mental mechanisms and processes by which people adjust their beliefs and behaviour to the normative expectations of their social surroundings in general. For instance, we can expect moral emotions such as guilt, shame, and anger by which we commonly regulate one's own and others' behaviour to affect scientists' behaviour as well. We can also hypothesize that the way in which scientists invoke reasons in support of their beliefs and practices is similar to how we use reasons to justify ourselves in our everyday lives and manage our reputation. Conceptual change, which is an important phenomenon in the development of science (Kuhn, 1962;Thagard, 2012), can then be understood not just as a process by which individuals adjust their beliefs with the intention of making them more accurate, but also by which they bring them in line with the normative expectations of their relevant peers. This could mean that conceptual change is difficult to realize in the minds of students not only because scientific concepts are highly counterintuitive (Shtulman, 2017) but also because students are expected to bring their beliefs in line with the normative expectations of a group whom they do not care about. As they do not run a serious risk of reputation damage (and can even gain a reputation bonus with the people they do want to associate with), they feel no urge to adjust their beliefs. These predictions are admittedly speculative. However, I hope to have shown that thinking about science as a moral system enables us to develop novel hypotheses about the cognitive processes underlying science that warrant and might inspire further empirical investigation.
History, sociology, and philosophy of science
Historians, sociologists, and philosophers of science have studied the moral dimensions of science at length. However, by introducing cognitive and evolutionary insights on human cooperation, thinking about science as a moral system does not only establish and confirm that science is a moral system, but it also delivers us insights in the cognitive and communicative processes that give rise to it. Furthermore, it explains why science has important moral dimensions in the first place. The reason is that scientific knowledge production recruits cognitive and communicative processes that are geared at cooperation involving the identification of trustworthy sources and partners, the production and evaluation of reasons, and reputation management. As such, the conception of science as a moral system provides a framework theory that helps to make sense of the historical, sociological, and philosophical studies.
Let us first return to Shapin's historical and sociological account of the role of trust in science. According to Shapin the natural philosophers at the start of modern science settled the problem of trust by attributing to one another the essential character of a gentleman. If one had such a character, then one was supposed to be honest. By attributing and essentializing such a trait, however, they were not providing an accurate description of the character that was peculiar to each member of their com-1 3 Page 13 of 18 454 Synthese (2022) 200:454 munity. Instead, they were merely vaguely labelling their expectation that any of their colleagues would submit to the normative expectations of their peers and thus be honest to maintain their reputation as a member of the community. Their membership however crucially depended not on having an essential trait but on their disposition to act and think in ways that their community of natural philosophers found acceptable. And even gentlemen had to rely on reasons to justify their beliefs, methods and findings and demonstrate their reasonableness and trustworthiness. Hence, we can understand Shapin's analysis as a particular historical case-study of a solution to a problem that is common to all scientific endeavours as they are instances of human cooperation.
An example of a sociological analysis that focuses on the moral dimensions of science is Robert Merton's theory about scientific norms (Merton, 1973). According to Merton, science is characterized by four such norms, i.e., universalism (everyone can contribute to the production of knowledge based on objective criteria), communism (scientific knowledge is a common good contributed by and accessible to all scientists), disinterestedness (scientist should not pursue a personal agenda but should aim to contribute to the production of knowledge), and organized scepticism (scientists look critically at their own and one another's work, see the discussion above). Merton's account was more about the moral dimension of science as an institution and less about the behaviour of individual scientists. Nevertheless, it recognizes that science comes with a normative framework that regulates the beliefs and practices of scientists. Thinking about science as a moral system explains why. If scientists do not behave and think according to these norms, they do not act and think in justifiable and hence acceptable ways and they will no longer reliable cooperative partners in the production of knowledge. The account sketched above thus makes more precise the cognitive and communicative processes by which scientists conform to such institutional norms.
The account of science as a moral system also sheds light on recent philosophy of science approaches based on virtue epistemology. Virtue epistemology builds on the idea that knowing depends not solely on the content of knowledge but on the proper disposition of the knower. Philosophers of science emphasize that science involves a particular mindset, a set of virtues, or a scientific attitude, by which scientists strive to live up to the values that are deemed central to the scientific enterprise of knowledge production (McIntyre, 2019; Pennock, 2019). The focus thereby shifts from scientific beliefs and practices to the individual scientist. Instead of asking what conditions belief and practices must meet, the question becomes what the mindset, virtues of attitude the scientist must adopt. Such a "philosophy of the scientist", as Pennock (2019, p. 11) puts it, brings attention to the important role scientists as individuals play in science which accords with the account that I presented above. The scientific mindset or attitude comes about as reputational concerns motivate scientists to bring their beliefs and behaviour in line with the normative expectations of their community. Scientists who are disposed to behave and think according to those expectations are virtuous. Scientists bring attention to this alignment by providing the sorts of reasons of which they think will indicate that they are justified in believing what they believe and doing what they do. In sum, that students of science have been able to analyse and describe science in moral terms such as norms and virtues suggests and can be explained from the fact that science constitutes a moral system.
Scientists anonymous?
A possible objection to the account of science as a moral system and the role of reputation therein is that science's organized scepticism comes largely in the form of anonymous peer review. Since the authors are unknown to the referees (and sometimes also to the handling editor), the referees cannot evaluate them as individuals. This seems to contradict one of the central ideas of this paper namely that scientists do not only evaluate the products of science but also their producers. However, peer review could be interpreted as an institutional recognition of the fact that in evaluating beliefs and practices we also evaluate the people who are responsible for them. In fact, it is a specific and unique cultural construct that prohibits people from doing so. As such, the institution of peer review might be quite counterintuitive. The reason is that we want to hold people accountable for what they say and do. If that is not possible because people are anonymous, we intuitively realize that people are more tempted to misbehave. And we are not wrong. Think, for instance, of the cruel reports that some referees dare to write. We also see this concern about anonymity in the controversy surrounding the Journal of Controversial Ideas that allows authors to publish their theories anonymously. The establishment of the journal itself constitutes a recognition of the fact that we do not only evaluate beliefs but also their producers. If an author proposes an idea the community finds unacceptable, this might have dire consequences for the author's reputation and career. However, the journal's critics have argued that such anonymity gives anyone the opportunity to publish immoral or pseudoscientific ideas because they cannot be held individually responsible (e.g., see Stokes 2021). The way that peer review is now usually organized might be an attempt to strike a balance between anonymity and accountability. By anonymizing the authors during the review process the referees are forced to focus on the reported beliefs and practices without evaluating the individual scientist. However, when the work is published the anonymity is lifted, not only so that scientists can reap reputational benefits from their work but also that they can be held responsible for their beliefs and behaviour. Such accountability thus discourages scientists to misbelieve and misbehave and motivates them to bring their beliefs and behaviour in line with the normative expectations of their peers.
Conclusion
I have here only scratched the surface regarding the implications of thinking of science as a moral system. However, the sketch above points in the direction of a novel approach to science. Science does not build solely on our capacities to develop knowledge about the world. It also recruits our capacities for creating and altering moral systems that enable and regulate cooperation and to which individuals adapt because of reputational concerns. In our collaborative efforts, truth is only one of our concerns; it is only instrumental for making cooperation successful. However, with science, humans have developed a peculiar and historically rare moral system that puts the production of knowledge as its main target (Pennock, 2019). I do not thereby wish to imply a sceptical view on science in which scientists' pursuit of reputation undermines their pursuit of truth. This conclusion does not follow. My account only brings to the fore that for individuals who wish to participate in the collaborative production of knowledge reputation is a valuable good. If a scientist wants to pursue truth, then she better believes and acts in justifiable ways, which she demonstrates by providing reasons which she shops for in the available pool of reasons. Otherwise, she runs the risk of becoming ostracized and excommunicated and, consequently, she will have to resign her pursuit of the truth. A conclusion that does follow is that we can better understand how science works by studying it as a moral system; and, vice versa, we can understand moral systems better by the study of science. | 10,439.8 | 2022-11-01T00:00:00.000 | [
"Philosophy"
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BMC Medical Informatics and Decision Making
Background: Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts.
Background
Collaboration among investigators and research groups in the biomedical field has become increasingly crucial to achieving success in the understanding of complex diseases such as cancer and heart disease [1]. As a result, many networks and consortia have been established to promote collaboration and data sharing. Networking of investigators and searching for potential collaborators in a specific research domain will be especially important in the genomics era, which provides an opportunity to apply basic research to the promotion of human health and disease prevention. The HuGENet initiative to develop a "network of investigator networks" in human genome epidemiology [2] illustrates the efforts of a diverse, global research community that is committed to accelerating the development and synthesis of knowledge on genetic variation and human diseases [3]. As more researchers recognize the importance of establishing networks to enhance efficiency and reduce redundancy in scientific research, major challenges include identifying investigators with particular interests and acquiring contact information for building new networks and updating this information for existing networks.
PubMed [4], offering access to the MEDLINE database of citations and abstracts of biomedical research articles, provides one of the most valuable information resources for tracking the progress of biomedical research through the published literature; it can also be used to find collaborators and investigators by authorship. Citation analyses that address the structure of scientific collaboration networks have been done many times [5][6][7][8]. Our approach shows how information contained in PubMed abstracts and author affiliation strings can be used to extend existing networks even further by identifying more investigators who may be new collaborators. In this paper, we present a novel PubMed-based approach to building a dynamic investigator network with detailed investigator profiles that include institutional affiliation, country of origin, email address, and publication history. We illustrate our concept using a prototypical web-based system for building an investigator network.
Data sources
We used 20,000 randomly selected PubMed abstracts from articles published between 2001 and 2005 (PubMed data) to determine the extent of affiliation data in PubMed. We used a continuously updated literature database of studies relevant to human genome epidemiology (HuGE Pub Lit [9]) to create a prototype web-based system for building an investigator network. As of October 19, 2006, the HuGE Pub Lit database contained 23,876 PubMed abstracts of gene-disease association studies (HuGE PubMed data).
The National Center for Biotechnical Information Entrez Programming Utilities (NCBI E-utility) [10] was used to retrieve full PubMed records containing title, authors, abstract, and affiliations based on PubMed Unique Identifier (PMID). We took advantage of the fact that most PubMed abstracts are indexed with National Library of Medicine medical subject headings (MeSH) terms by NCBI staff. We used a standard vocabulary, Unified Medical Language System (UMLS) metathesaurus (version 2006AB) [11], to index PubMed abstracts by converting MeSH terms to UMLS concept unique identifiers (CUIs). To enrich the capacity of UMLS to handle gene information, we incorporated Entrez gene records into the UMLS metathesaurus, substituting Entrez gene IDs for the UMLS CUIs. Gene symbols were indexed manually using these Entrez gene IDs [12]. The MeSH hierarchy tree [13] was used to provide "children" concepts for query terms.
Affiliation parsing
PubMed affiliation string format While building the affiliation parsing tool, we found that over 80% of the affiliation strings in PubMed articles adhered to the following format:
Country name lookup list
We created a country lookup table containing country names and their synonyms based on International Organization for Standardization 3166 country codes [14] and UMLS. The UMLS metathesaurus lists numerous synonyms for country names, for example, United States, US, U.S.A., etc. Using this table, country names could be assigned to 86% of the affiliation strings. The remaining affiliation strings could not be parsed for one or more of the following reasons: 1) a noncountry geographic location, such as a city or state, was provided instead of a country name; 2) the affiliation was written in a language other than English; or 3) the affiliation was provided in an unconventional format. To handle the first two scenarios, we created a custom country name list by manually inspecting these affiliation strings and adding the geographic locations as synonyms for countries. For example, if "Beijing" was in an affiliation string without country information, we added "Beijing" to the lookup table as a synonym for China in the custom country name list. We used a second-run parsing algorithm if the affiliation was provided in unconventional format.
Email address parsing pattern A regular expression pattern was used to find and parse the email address in the affiliation string (see detail in the appendix file)
Institution key work list
To capture this information, including some in languages other than English, we created an institution key word list (Table 1).
Detailed affiliation parsing algorithm can be found in the appendix file.
Web-based demonstration version of the system implementing the methodology
We generated a relational database that linked PubMed abstract content, detailed investigator profiles, and indexed UMLS/Entrez gene concepts. Because PubMed abstracts provide an affiliation only for the first author, the parsed affiliation information was linked to the first author of the corresponding publication abstract. A diagram of the database schema is shown in Figure 1.
Java J2EE 1.4 [15] was used to build the web-based system combined with the open-source frameworks Hibernate [16] and Struts [17]. The Microsoft SQL server was used as the back-end database.
Performance Evaluation
Two test sets were used to assess the accuracy of the parsing application. We extracted all 311 records (HuGE PubMed test data) added to HuGE Pub Lit between October 20, 2006, and November 3, 2006, and randomly selected 311 articles (PubMed test data) that had been added to the PubMed database during the same period By using preterm birth as a test case, we tested the system's ability to dynamically create domain-specific investigator networks. After consulting with an expert in the domain of preterm birth, the following query was used to search the database: "prematurity or infant, premature or infant, low birth weight or labor, premature." We compared the members of the dynamic investigator network built by using our system with the membership of an existing network, the International PREterm BIrth Collaborative (PREBIC), which includes a subgroup for study of genetic factors in preterm birth [18].
To further evaluate the performance of the methodology, we invited domain experts in the fields of human genome epidemiology of preterm birth, Chlamydia infection and HIV infection to participate in the tests. The experts performed the search using the Investigator Browser by choosing their own search terms. Each expert reviewed the list of investigators generated by the Investigator Browser and labeled the ones they had collaborated with or recognized as investigators in their field; they also provided us with investigator names that they expected to find but that Relational database schema were not on the list. We used this information to estimate sensitivity of the methodology.
Extent of affiliation information in general PubMed abstracts and HuGE PubMed abstracts
In our sample of general PubMed abstracts, 87% had affiliation strings; those lacking them were mostly nonresearch publications such as biographies, comments, or letters. In all, 98.6% of HuGE PubMed abstracts contained affiliation strings. Email information was available in about 40% of both general PubMed records and HuGE PubMed records. In both datasets, affiliation profiles could be constructed for about 20% of all authors ( Table 2).
Performance Evaluation
Our parsing tool was able to obtain all email addresses in the valid format by using regular expression pattern matching (see Methods). Performance of affiliation parsing is given in Table 3.
Comparing the list of investigators generated by the methodology with information provided by domain experts showed that our approach could identify about 70% -85% of investigators in three different research areas with the selection of the first or last authors only while over 90% of investigators were identified if all authorship was considered (Table 4).
By using a domain-specific query (see Methods) and the web-based prototype system, we dynamically built an investigator network for the HuGE field focused on genetic factors in preterm birth. The HuGE Pub Lit database contained 122 relevant abstracts, from which we identified 548 investigators (authors), including 178 who were represented as either first or last authors. Detailed profiles for each investigator included the number of publications in PubMed, number of publications in HuGE Pub Lit, and number of HuGE publications as the first or last author. Of the 10 genetics investigators within the PREBIC network, 9 were included in the list of investigators returned by web-based network building system. One investigator was missed because he had not yet published any articles that were included in HuGE Pub Lit.
Web-based demonstration version of the system
With this system, we were able to retrieve articles using a query for a specific domain of interest identified by indexed UMLS terms, all possible children terms, and text word searching of title and abstract to generate a dynamic, user-defined network with a list of authors and detailed author profiles. This approach allows users to construct domain-specific investigator networks ( Figure 1); browse investigators and corresponding investigator profiles (Figure 2); and stratify the investigators by country ( Figure 3) and institution (Figure 4). * %: the number of the investigators in the methodology-generated list/the number of investigators experts identified. § F/L:First/Last Authors option in Investigator Browser; All: All Authors option in Investigator Browser.
Discussion
Investigator networking and collaboration is common practice in modern scientific research, aided by the emergence of new technology, especially the Internet. Collaboration can greatly enhance research by increasing the volume of high-quality data available to investigators and accelerating progress toward research goals [19,20]. The HuGENet movement [2] has made great efforts to promote global collaboration among investigators conducting population-based research in genetic epidemiology.
Recently, HuGENet launched an initiative to establish a "network of networks" across the field by registering existing networks, teams, and investigators to share data, develop standards, facilitate the confirmation of research findings, and reduce duplication of effort [1,21]. Domainspecific investigator networks created by our prototype system could be instrumental in identifying additional investigators to recruit to these networks.
Citation analysis of the published literature is a reliable method for describing scientific collaboration networks by identifying and connecting authors that have made contributions in the same research field [7]. MEDLINE is the largest component of PubMed, the freely accessible online database of biomedical journal citations and abstracts created by the U.S. National Library of Medicine (NLM). With the assistance of information technology, PubMed allows for quick elucidation of comprehensive investigator networks. In addition to abstract content and author names, PubMed provides limited affiliation information (including country, institution, and contact infor-
Figure 2
Results of Investigator Browser search for HIV investigator network in human genome epidemiology.
mation), which has practical value for network building. The ability to search MeSH-indexed abstracts allows domain-specific investigator networks to be generated dynamically. Quick and up-to-date answers to the "3W" questions (Who, Where, and What) can be obtained without soliciting investigators.
Affiliation strings in PubMed records have been used to analyze the geographic distribution of published studies [22,23]. However, the heterogeneity of country names has required time-consuming manual extraction procedures that precluded the generation of large datasets. We successfully developed and implemented an automated approach that uses the UMLS to accurately and robustly parse the affiliation string. Our affiliation parsing strategy demonstrates the capacity to extract investigator profile information efficiently from PubMed records.
Although our approach provides a new way to explore and build investigator networks from PubMed, it has many limitations. First, PubMed records identify authors only by last name and first initial, which can create some ambiguity in investigator networks generated by our system. However, this may not be a consideration in the future, because PubMed recently started to provide full names in XML format. Second, because PubMed provides affiliation information only for the first author, detailed investigator profiles can be generated only for investigators with publications in which they are first author. Third, indexing of institutions could not be completely Investigator Browser showing an investigator detail profile in HIV investigator network in human genome epidemiology Figure 3 Investigator Browser showing an investigator detail profile in HIV investigator network in human genome epidemiology.
automated because of inconsistency in the institution names provided by authors, a problem that could be addressed by establishing an international registry of research institutions. Finally, PubMed does not include all biomedical journals, especially those published in other countries. Adapting the current system for other data sources such as EMBASE [24] could result in more comprehensive, dynamically created investigator networks.
Conclusion
The new approach presented in this paper uses information available in PubMed abstracts as an efficient way to identify potential collaborators in a particular research domain. We demonstrated this approach in the field of human genome epidemiology, but it could be applied to any field represented in PubMed to track investigators and dynamically create domain-specific investigator networks.
design, provided advice on the project and revised the draft manuscript. MJK oversaw the project and revised the draft manuscript. All authors read and approved the final document. | 3,180.8 | 2007-01-01T00:00:00.000 | [
"Computer Science"
] |
Anemarrhena asphodeloides Non-Steroidal Saponin Components Alter the Pharmacokinetic Profile of Its Steroidal Saponins in Rat
A rapid, selective and sensitive UPLC-MS/MS assay was established to determine the plasma concentrations of four steroidal saponins. Sprague-Dawley rats were allocated to four groups which were orally administered Anemarrhena asphodeloides extracts (ASE), ASE combined with macromolecular fraction (ASE-MF), ASE combined with small molecule fraction (ASE-SF) and ASE combined with small molecule and macromolecular fraction (ASE-SF-MF) containing approximately the same dose of ASE. At different time points, the concentration of timosaponin BII, anemarsaponin BIII, timosaponin AIII and timosaponin E1 in rat plasma were determined and main pharmacokinetic parameters including Cmax, Tmax, T1/2, AUC were calculated using the DAS 3.2 software package. The statistical analysis was performed using the Student’s t-test with p < 0.05 as the level of significance. MF had no effect on the pharmacokinetic behaviors and parameters of four steroidal saponins. It was found that Cmax and AUC of four steroidal saponins in group ASE-SF and ASE-SF-MF, were significantly increased compared with those in group ASE. These results indicate that SF in A. asphodeloides extracts could increase the absorption and improve the bioavailability of the steroidal saponins.
Several analytical methods are reported for the determination of steroidal saponins in A. asphodeloides, including thin-layer chromatography (TLC), gas chromatography (GC) and high-performance liquid chromatography (HPLC) with different detectors [19][20][21]. However, these methods have some limitations including long analysis times and/or low sensitivity and thus are not suitable for the determination of steroidal saponins in biological fluids after administration of A. asphodeloides extract. In this study, we hypothesized that the non-steroidal saponin ingredients in A. asphodeloides might influence the pharmacokinetics of the active components in the steroidal saponin fraction of A. asphodeloides. Therefore, a rapid, sensitive and selective LC-MS/MS method was developed to determine simultaneously four steroidal saponin components in rat plasma and applied to demonstrate the pharmacokinetic influences after comparing the pharmacokinetics of compounds 1-4 in the steroidal saponins fraction from A. asphodeloides when combined with different non-steroidal saponin fractions. The results are expected to be very helpful for evaluating the effect of non-steroidal saponin ingredients and guiding changes to the dosage form in clinical applications of this herb.
Optimization of Mass Spectrometry Conditions
In order to optimize the MS conditions, both positive and negative scan modes were evaluated and the negative mode was selected due to its higher sensitivity, as thee response observed in the negative ionization mode was higher than that in positive ionization mode. MRM mode was used to monitor both quasimolecular and fragment ions, which made the method more specific. ESI source temperature, capillary and cone voltage, flow rate of desolvation gas and cone gas were optimized to obtain the best signal-to-noise ratio of protonated molecules of the four analytes.
Optimization of Chromatography Conditions
To achieve a better peak shape and a shorter running time for simultaneous analysis of the four steroidal saponin compounds, optimization of the mobile phase was conducted. It was recommended that the analysis of furostanol saponins such as timosaponin BII by HPLC-MS be performed using aqueous acetonitrile as mobile phase but not methanol due to the interconversion of the C-22 hydroxy and C-22 methoxy forms [22], hence acetonitrile was chosen as the organic phase. Moreover, the use of 0.1% formic acid in the water phase could improve the ionization efficiency of the analytes and decrease the response intensity of the endogenous matrix, so acetonitrile-0.1% formic acid with gradient elution was applied and selected as the mobile phase with the most favorable retention time and low background noise. Under the developed chromatographic conditions for simultaneous determination of the four compounds, all analytes were eluted rapidly within 4.2 min.
Optimization of Extraction Conditions
In order to obtain a higher recovery of the analytes and IS and no endogenous interference, three types of reagents (n-butanol, acetonitrile, and ethyl acetate) were tried for precipitation of protein in rat plasma. It was demonstrated that acetonitrile produced the best extraction efficiency for all the analytes and IS.
Specificity
All the analytes and internal standard could be detected on MRM spectrograms without any significant interference ( Figure 2).
No endogenous peaks and carryover were observed in the representative chromatograph of blank plasma sample at the retention times of the analytes and IS.
Linearity and Lower Limits of Quantification (LLOQ)
The calibration curves of four compounds exhibited good linearity with correlation coefficients (R 2 ) within the range from 0.9919 to 0.9983. The LLOQS were suitable for quantitative detection of compounds in the pharmacokinetic studies. Linear ranges, LLOQs, LLODs and correlation coefficients are shown in Table 1.
Precision and Accuracy
The results of the intra-and inter-day precision and accuracy of all the analytes in three QC samples are summarized in Table 2. The intra-and inter-day precisions ranged 4.5%-11.6% and 6.9%-11.2%, respectively. The accuracy derived from QC samples was between 92.7%-106.8% for each QC level of the four analytes. The results indicated that the precision and accuracy values were within the acceptable range.
Extraction Recovery and Matrix Effect
The mean recoveries of all analytes at different concentrations are shown in Table 3. The mean recovery of the analytes was within 73.9%-89.3%. The extraction recovery of the IS was 78.2% ± 9.3%. The matrix effect of blank plasma of all analytes was found to be within the acceptable range; all values were more than 80.7% (Table 3). The matrix effect of IS was 85.4% ± 6.2%. Thus it was indicated that the plasma matrix effect was negligible for the assay.
Stability
Stability of the four analytes during the sample storing and processing procedures was fully evaluated by analysis of QC samples. The results are shown in Table 4. The results demonstrated that these analytes in rat plasma were all stable for the auto-sampler for 24 h (4 °C), at −80 °C for 1 month and freeze-thaw cycles with accuracy in range from 83.3% to 103.2%. Table 4. Stability for four analytes in rat plasma (n = 6).
Pharmacokinetics Study
The developed and validated method was applied to the pharmacokinetic evaluation of the four steroidal saponins 1-4 after oral administration of administration of different fractions to rats (Figure 3). The assay was proved to be sensitive enough for the determination of these analytes in rat plasma. Table 5. Table 5. Pharmacokinetics parameters of four steroidal saponins after an oral administration (n = 6).
Comparison of the Pharmacokinetic Profile of the Four Steroidal Saponins 1-4 in the Group ASE and Group ASE-SF
As shown in Figure 3 and Table 5, the pharmacokinetics parameters of the four steroidal saponins show significant differences in Cmax .There were no significant differences in Tmax for the four steroidal saponins 1-4 in the ASE and ASE-SF groups. The T1/2 value of timosaponin AIII was significantly increased. Although the T1/2 of timosaponin BII, anemarsaponin BIII and timosaponin E1 in the ASE group showed no obvious difference in comparison with those in the ASE-SF group, their T1/2 values were prolonged. It could be inferred that SF could increase the maximum plasma concentration and extend the elimination time of the four steroidal saponins in rat plasma compared with ASE alone. The AUC of the four steroidal saponins were significantly larger in the ASE-SF group than in the ASE group, which showed that SF may increase the bioavailability of the four steroidal saponins.
Comparison of the Pharmacokinetic Profiles of the Four Steroidal Saponins 1-4 in the Group ASE and Group ASE-MF
As shown in Table 5, there are no significant differences among all the groups in Cmax, Tmax, T1/2 and AUC, indicating that MF have no influences on absorption, elimination and bioavailability of four steroidal saponins in rat plasma.
Comparison of Pharmacokinetic Profile of Four Steroidal Saponins 1-4 in Group ASE and Group ASE-SF-MF
Cmax, T1/2 and AUC of the four steroidal saponins, the major active components of A. asphodeloides increased significantly in the ASE-SF-MF group. There was no significant difference in Tmax for the four steroidal saponins 1-4. The result indicated that SF and MF administered simultaneously with ASE could increase the absorption and improve the bioavailability of four steroidal saponins in rat plasma.
Double Peak Phenomenon
The plasma concentration-time curves of timosaponin BII, anemarsaponin BIII and timosaponin E1 after oral administration showed a double peak, which was also reported in [23][24][25]. It is well known that drug absorption is a very complex process that manifests itself through potential interaction with a host of physicochemical and physiological variables. Some factors that may affect the absorption process include presystemic metabolism/efflux, "absorption window" along the gastrointestinal tract, enterohepatic recirculation, variable gastric emptying and drug-drug interactions [26,27]. Therefore, atypical drug absorption profiles such as double-peaks and absorption window-type absorption profiles are often encountered [27].
Timosaponin AIII is the derivative of timosaponin BII, so they share similar steroid cores. In comparison with timosaponin AIII timosaponin BII only contains an extra sugar moiety in addition to a shared disaccharide moiety, however, their pharmacokinetic parameters are remarkably different. Most obviously, the concentration-time curves of timosaponin AIII after oral administration showed a single peak. There is no scientific report about the aglycone of timosaponin BII. As we know, the aglycone of timosaponin AIII is sarsasapogenin. It is a report of a single plasma concentration peak of sarsasapogenin, which is consistent with the pharmacokinetic behavior of its glycoside (timosaponin AIII). It may be inferred that this sugar is responsible for the different pharmacokinetics [28,29].
Influence of SF and MF on the Pharmacokinetic Profile of Steroidal Saponins
Chinese traditional medicine extracts are an effective aggregation of multiple components, and the pharmacokinetics of a single ingredient cannot represent the pharmacokinetics of the whole herbal medicine. The results of this study implied that SF could increase the absorption and improve the bioavailability of four steroidal saponins from Anemarrhena asphodeloides and MF did not significantly improve the bioavailability. However, compared to the ASE-SF group, the values of AUC of ASE-SF-MF increased, so it is unclear if MF can be removed from the clinical medicine so as to alleviate the oral medication burden of patients. However, all these hypotheses need further demonstration.
Mass Spectrometric Conditions
Mass spectrometry analysis was performed using a Xevo TM triple quadrupole mass spectrometer (Waters Crop., Milford, CT, USA) equipped with an electrospray ionization source (ESI). The ESI source was set in negative ionization mode. The parameters in the source were set as follows: capillary voltage 3.0 kV; source temperature 150 °C; desolvation temperature 550 °C; cone gas flow 50 L/h; desolvation gas flow 1000 L/h. Analytes were performed by using multiple-reaction monitoring (MRM) mode. The cone voltage and collision energy were optimized for each analyte and selected values are given in Table 6. All data collected in centroid mode were acquired using Masslynx4.1 software (Waters Crop, Version 4.1, 2010) and post-acquisition quantitative analysis was performed using the TargetLynx program (Waters Crop, 2010).
Preparation of Administered Samples
The dried A. asphodeloides were chopped into slices before using. The A. asphodeloides was immersed in water (1:10, w/v) and extracted twice by refluxing for 2 h. After filtration, the supernatant was condensed to a certain volume under reduced pressure, and 95% ethanol was added to the water extract filtrates until the concentration of ethanol was 80%. The precipitate was filtered as the macromolecular fraction (MF), the ethanol supernatant was concentrated under reduced pressure to a certain volume under vacuum and then purified by gradient elution with water, 40% ethanol and 70% ethanol from an AB-8 MARO porous resin column and then the water-eluted fraction was combined with the 40% ethanol-eluted fraction as the small molecule fraction (SF) and the 70% ethanol eluted fraction was the A. asphodeloides saponins extract (ASE). All of the residues were lyophilized and the resulting dry powder was stored at 4 °C before usage. The contents of four steroidal saponins in ASE dry powder were measured quantitatively by the external standard method using the same chromatography conditions as described above. The contents of timosaponin BII, anemarsaponin BIII, timosaponin AIII and timosaponin E1 in ASE were 429.12, 89.81, 59.13 and 41.25 mg/g, respectively.
Preparation of Standard Solution and Quality Control (QC) Samples
Stock solutions were separately prepared by dissolving the four accurately weighed standard reference compounds in a mixture of 50% acetonitrile. Then, the four stock solutions were mixed and diluted with 50% acetonitrile to prepare a final mixed standard solution containing 650.00 ng/mL of timosaponin BII, 620.00 ng/mL of anemarsaponin BIII, 485.00 ng/mL of timosaponin AIII, 530.00 ng/mL of timosaponin E1. A series of working solutions were freshly prepared by diluting mixed standard solution with 50% acetonitrile to the appropriate concentration. The internal standard solution of ginsenoside Re was prepared to the concentration of 920 ng/mL in 50% acetonitrile. For the validation of the method, three concentrations of standard solution containing timosaponin BII (5.20, 52.00 and 520 ng/mL), anemarsaponin BIII (4.96, 49.60 and 496.00 ng/mL), timosaponin AIII (3.88, 38.8 and 388 ng/mL), timosaponin E1 (4.24, 42.40 and 424.00 ng/mL) were used for preparing the QC plasma samples.
Preparation of Plasma Samples
Frozen plasma samples were unfrozen at room temperature and treated as follows: to each 200 µL plasma sample, 20 µL of IS (920 ng/mL ginsenoside Re) working solution and 600 µL of acetonitrile were added. After vortexing for 2 min and centrifugation at 13,000 rpm at 4 °C for 10 min the supernatant was transferred into a new tube and evaporated to dryness in a rotary evaporator at 39 °C and the residue was reconstituted in 100 µL of 0.1% formic acid-acetonitrile (50:50, v/v), vortexed for 2 min and centrifuged at 13,000 rpm at 4 °C for 10 min. The supernatant was transferred to an autosampler vial and an aliquot of 2 μL was injected onto the UPLC-MS/MS system for analysis.
Assay Specificity
The specificity of the method was evaluated by comparing the chromatograms of six different batches of blank plasma samples, plasma samples spiked with the timosaponin BII, anemarsaponin BIII, timosaponin AIII, timosaponin E1 and IS, and plasma samples obtained from rats administered ASE.
Linearity and lower limits of quantification (LLOQ)
The calibration curves were determined by plotting the peak area ratio (Y) of analytes to IS versus the nominal concentration (x) of analytes with weighted (1/x 2 ) least square linear regression. The lower limit of quantitation (LLOQ) of the assay was defined as the lowest concentration on the standard curve that can be quantitated with accuracy within 20% bias of the nominal concentration and RSD.
Precision and accuracy
The intra-day and inter-day precision and accuracy were determined by quantifying three concentration levels of QC samples (six samples for each concentration level) on the same day and on three consecutive validation days, respectively. The precision was expressed as the relative standard deviation (RSD), and the accuracy by (mean measured concentration/spiked concentration) × 100%.
Recovery and matrix effect
The extraction recoveries of analytes at three QC levels were determined by comparing the peak area of each analyte extracted from plasma samples with that of post-extraction spiked plasma blank. The matrix effect was evaluated by comparing the peak areas of the analytes obtained from six plasma samples with the analytes spiked after extraction, at three concentration levels, to those from the neat standard solutions at the same concentrations. The extraction recovery and matrix effect of IS were also evaluated using the same procedure.
Stability
The stability experiments were measured by analyzing replicates (n = 6) of three QC samples during the sample storing and processing procedures. For all stability experiments, freshly prepared stability testing QC samples were evaluated by using freshly prepared standard curve for the measurement. The post-preparation stability was tested by determined of the extracted QC samples stored in the auto-sampler (4 °C) for 24 h. The freeze and thaw stability were determined after three freeze-thaw cycles (−80 °C to room temperature). Long-term stability in rat plasma stored at −80 °C was studied for a period of one month.
Pharmacokinetic Study
Male Sprague-Dawley rats (250-280 g) were obtained from the Shanghai Slac Laboratory Animal Co., Ltd. (Shanghai, China). All animals were kept in an environmentally controlled breeding room (temperature: 20-25 °C, humidity: 55%-65%) for 1 week before the experiments started. Animal welfare and experimental procedures were strictly in accordance with the ethical norms of the Nanjing University of Chinese Medicine. All rats were fasted for 12 h with free access to water prior to the experiments, twenty-four rats were divided into four groups and then were given a single dose of ASE, ASE-SF, AS-MF, AS-M-SF. A 40 mg/mL ASE (the amount of MF, SF added to group AS-MF, ASE-SF, AS-M-SF were based on the proportion extracted from A. asphodeloides) aqueous solution in each group was administered orally at a dose of 400 mg/kg, which contained 171.61, 35.92, 23.62, 16.53 mg/kg of timosaponin BII, anemarsaponin BIII, timosaponin AIII, timosaponin E1, respectively.
About 400 μL blood samples were collected from venipuncture before intragastric gavage and at 0.083, 0.25, 0.5, 1, 1.5, 2, 4, 6, 8, 10, 12, 24 h after a single oral administration. The blood samples were immediately transferred to heparinized tubes and centrifuged at 3000 rpm for 10 min, and the supernatant was transferred into 2.0 mL Eppendorf tubes and stored at −80 °C prior to analysis. Blank plasma was obtained from the rat without oral administration and was used to investigate the assay development and validation
Statistical Analysis
To calculate the pharmacokinetic parameters of analytes in different group, concentrations-time dada were analyzed by DAS 3.2 software (Mathematical Pharmacology Professional Committee of China, Shanghai, China, 2011). Data were measured as the mean ± standard deviation (S.D.) with triplicate measurements. The identification of significances between different groups was executed with Student's t-test. A p value < 0.05 was considered statistically significant.
Conclusions
In this paper, a rapid, selective and specific LC-MS/MS method for the simultaneous analysis of four components of A. asphodeloides in rat plasma in a simple 4.2 min chromatographic run was developed for the first time. The results obtained from this study implied that after combination with different fractions extracted from A. asphodeloides extract, the pharmacokinetic behaviors of the four steroidal saponins showed differences their pure forms or from other extracts. The SF had a significant influence on the pharmacokinetic parameters of the steroidal saponins and the bioavailability and absorption rate were the major parameters which were mainly influenced. But for MF, there was no impact on the pharmacokinetic parameters of the four steroidal saponins. The obtained knowledge might contribute to the safety of clinical therapy and provide valuable information for the pharmacokinetic investigation of TCMs. | 4,306.4 | 2015-06-26T00:00:00.000 | [
"Chemistry",
"Biology"
] |
Openness in Education: Claims, Concepts, and Perspectives for Higher Education
Characteristics of openness can be found in many respects throughout the history of education. From Comenius’ call for pedagogical reform to postmodern educational theory, requirements of access, social justice, creativity, knowledge sharing, innovation, and capacity building have been emphasized in various ways. The chapter provides an outline of different understandings and notions of openness in educational contexts as well a discussion of their relevance for openness towards academic knowledge cultures and different forms of knowledge. Finally, the contribution highlights organizational, methodological, and critical perspectives as three aspects which appear to be undervalued in current debates about openness in higher education.
Introduction
Since about 15 years, we find a variety of initiatives dealing with open education (OE), open educational resources (OER), and Creative Commons (CC) licenses. Almost 10 years ago, in 2008 Stephen Downes and George Siemens led a course called Connectivism and Connective Knowledge at the University of Manitoba (Canada) which inspired Dave Cormier to coin the term 'MOOC' as an acronym for a Massive Open Online Course. Apart from a small number of students learning in class, over 2200 online students from the general public and various backgrounds took part in this course. Today, we find a wide range of OE and OER initiatives as well as diverse kinds of MOOCs all over the world. Consistently, the activities are aiming at opening up education in one way or another by the use of digital media technologies. However, these initiatives as well as related discourses and practices, are predominantly linked to general policy statements, claims of educational policies aiming at basic, vocational or higher education, and institutional strategies on global, international or regional levels. So far, these themes and developments have been taken up rather reluctantly in mainstream educational theory and philosophy. innovation, as well as further related notions. Most commonly, recent debates about education for all, enabling universal education, or free educational infrastructures can be characterized by a kind of historical amnesia -calls for education for all are anything but new, they can be traced back at least to the work of Johann Amos Comenius (1592-1670) and social and religious learning with the Pauline epistles. Characteristics of openness and motives of opening up education can be found in many respects throughout the history of education. From Plato's elitist concept of education for a ruling class of philosophers to the strategic efforts of the UNESCO and other institutions to improve the quality of education, the relation of private and public issues and its relevance for educational processes have been highlighted repeatedly.
As to higher education, respective discourses are oscillating between political calls for employability and economization, industrial hopes for funding for digitization strategies and implementation of new learning technologies, management objectives of marketization and efforts to profit financially. The commercialization of academic institutions generally follows socio-political commitments to enable access to higher education more widely. On one hand, educational policies aim at opening new latitudes and flexibilities for students and teachers. On the other, educators make significant pedagogical efforts toward expanding scopes of action learners and educational institutions involve themselves co-create institutional conditions for all involved. Public aspirations tend to lean toward free culture, educational commons, and democratization through openness and media.
At the Crossroads of Openness and Education
Characteristics and motives of openness can be found in many respects in the context of education. Throughout history of education, we can find implicit dimensions of openness. For example, there are many reasons to assume that children educated themselves largely through varying degrees of free play, exploration, sharing and exchange for thousands of years. Even though historic conditions, cultural constraints and media constellations are to be considered when reflecting such forms of openness avant la lettre, they remind us of always changing modes and scopes of learning and knowledge acquisition. Although children's play for its own sake might seem a prototypical example for openness in education at first sight, dynamic interrelationships of dimensions of opening and closure are essential for a differentiated understanding of the various aspects of free play, open education, and its conditions and constraints. Moreover, dynamics and interdependencies of opening and closure are generally underestimated in discourses about openness in education, culture, and society. extends to openness to criticism, intellectuality, freedom of expression, reasonable and sober-minded acting, bureaucratization of society as well as Eurocentric thinking and European colonialism.
From a systematic perspective, openness in education refers to all levels of education as well as formal, informal and non-formal contexts. This counts for both, opening up educational processes and institutions as well as opening up minds, bodies, hearts, or communicative dynamics through education.
As to OER and higher education, the "definition of 'open' is constantly evolving and varies according to context e.g. sharing software source code, re-(using) content and open access to publications" (Yuan et al. 2008, p. 2 Nyquist (1972) and Nyberg (2010Nyberg ( [1975), or in terms of current basic research, for example, with reference to Peters (2010) or Deimann and Peters (2016). Another possibility for opening up debates and encouraging an open approach to openness in education might start by asking for synonyms of "open" and "education" or closely related terms. Table 1 shows a series of basic meanings and synonyms in the form of a matrix. Of course, other terms than those offered in table 1 could be used, too, such as "uncovered," "unprotected," "free from concealment," or "not restricted to members of a particular group" for "open," and "schooling," "instructional principles," "learning to learn," "distribution of content," "transmission of knowledge," "pedagogical interaction," "touching events," or "biographical upheavals" for "education." Thus, understandings and conceptions of "open education" can be conceptualized in the fields of such a matrix. Then again, existing notions of "open education" or "openness in education" can be positioned tentatively in one or more of the fields. Obviously, further enhancements of (re-)thinking openness in education can be considered beyond complementing further meanings in an OE-Matrix as exemplified in table 1. One way of moving beyond the addition of other basic meanings can be realized by introducing a third dimension in order to reflect on (a) temporal or spatial dynamics, (b) informational, socio-cultural, relational or emotional ecologies, or (c) on definitional and metaphorical uses of key concepts including related goals and politics of concepts (Begriffspolitik). In addition, contexts of use, language games, alternative approaches, and discursive relationships can be opened up for debate according to problem descriptions being in negotiation.
Although, often there are various limitations to negotiate meta-reflexive considerations in academic or pedagogical contexts, it is not least the metareflexive leeway which indicates the quality of dynamics and interdependencies of opening and closure. Correspondingly, modes self-reflection on the level of individuals, groups, institutions and organizations can act as important Generally speaking, openness in education can be regarded as an operative fiction and also as an "educationalization formula" (Pädagogisierungsformel) (cf. Veith 2003, pp. 183-201) that has been and can be interpreted in many ways.
Veith (2003) provides a useful historical overview of reproduction problems and educationalization formulas. Although it has been developed for issues of education in the German-speaking area, it can be helpful to focus on guiding differences and formulas of relevance for education both in history and today in a wider sense, too. He analyses tensions between normative aspects of legitimation and educational discourses regarding conceptual clarifications of the core areas and responsibilities of the discipline, and the increasingly multifaceted societal demands of providing various kinds of education.
However, his approach can be further differentiated in a number of ways, for example, with regard to educational formulas in different countries and world regions, transnational and global contexts of education, and not least recent OE developments and contemporary claims for open education, opening up education, and openness in education. Although 'openness' suggests a static understanding of the concepts, in large parts of respective discourses processes and dynamics are being emphasized rather than results.
Today, we are facing contrasting and competing relevance formulas for education rather than one formula, among them all kinds of competencies and literacies up to the "literacification of everything" (Hug 2012, p. 118), dealing with complexities, inclusion, and openness as a sufficiently shimmering concept that is applicable in multiple ways in pedagogical, academic, political, medial, and economic discourses. Openness in education includes patterns of thinking and speaking of education as upbringing, learning to learn, training, output, or relation. Needless to say that these and similar thinking patterns imply various options for conceptualizations. If we take education, for example, as relation and not as output 1 we can describe various qualities of educational relations and also a number of basic understandings of 'relation' or 'relational'. From a metatheoretical perspective, the term 'relational' can be used in everyday language in the sense of both 'connected' or 'bonded' or associated domains of reference like kinship. It can be used in more specific or theoretically informed ways by referring, for example, to • conventional Venn-diagrams, • relational realism in relational sociology (sensu Charles Tilly and Pierpaolo Donati), • ecological systems theory or human ecology theory (sensu Urie Bronfenbrenner) complementing the meta-model with respect to exo-Seminar.net -International journal of media, technology and lifelong learning Vol. 13 -Issue 2 -2017 77 and chrono-levels, • actors who are relationally positioned within a field (sensu Pierre Bourdieu) and the modes in which respective positions are determining his or her situated viewpoint of activities in and towards certain fields, • the notational distinction between monadic versus relational predicates (sensu Charles S. Peirce), • relational logics of development (Richter 2014) as a methodological basis for clarifications of the concept of transformatory education (transformatorischer Bildungsbegriff) • theory of radical relationism as outlined by Peter Krieg (2005, p. 137-163).
These and other notions of 'relational' offer points of references for relationoriented conceptualizations of education and for corresponding understandings of openness in education. Accordingly, openness as educationalization formula can take many forms ranging from ideological claims to moral imperatives, and context-related norms. All of them are to be distinguished from more or less differentiated descriptions and analyses of OE practices, initiatives and conceptualizations of openness.
OER and the Case of MOOCs: Reflections and Critical Considerations
Openness can also be characterized as a meta-principle that has been relevant in many ways for educational and academic practices throughout history. In their book on The Virtues of Openness, Peters and Roberts (2012) ). Hypes and more quiet practices of "going aMOOC" can take many forms ranging from rather non-massive open online courses ("OOCs") with less than 30 participants to extraordinarily numbers which can go beyond 150,000 students registering for a single MOOC. In detail, further distinctions can be drawn along business models, licensing models, forms of dealing with content, tasks and networking, relations of individuals and groups, roles of students, teachers and tutors, understandings of learning and pedagogy, gender differences, and other distinguishing characteristics. In their review of literature on MOOCs published from 2008-2012, Liyanagunawardena et al. (2013) come to the conclusion that "[m]any articles published to date have discussed empirical evidence from case studies, the influence on higher education structure, or educational theory relating to MOOCs" and that there are "further interesting research avenues such as cultural tensions within courses and the ethical aspects of using data generated by MOOC participants still to be explored" (ibd.). In another systematic review the authors state in a sobered manner: "A rich, original idea that started strongly, with high expectations based on the innovative potential of openness, has, over the years, gradually becoming a mechanical formula with little genuine creativity but more focused on reaching global audiences rather than delivery through traditional academic institutions." (Chiappe-Laverde et al. 2015, p. 14) On the whole, skeptical assessments clearly predominate in analytic, reflective or evaluative literature. There are also critical voices from within. For example, in an interview with Chris Parr (2013), Stephen Downes argues: "Moocs as they were originally conceived…were the locus of learning activities and interaction, but as deployed by commercial providers they resemble television shows or digital textbooks with -at best -an online quiz component." (Downes in Parr, 2013) There are also voices claiming "that Open Education provides a road to deeply modernize education to the challenges of tomorrow, to support complex skills and to adapt education better to the demands of a knowledge society" (Meiszner & Squires 2013, p. 17). However, addressing MOOCs and uses of OER in terms of empowerment of students and faculty, better learning outcomes, or making use of course material anytime, at one's own pace and anywhere generally remains problematic. This can easily be illustrated with reference to critical issues and paradoxical aspects.
A critical scrutiny of the literature suggests that terms like «openness» and «freedom» are under-theorized (cf. Knox, 2013), and pay little respect to well established philosophical and historical evidence of its vagueness and implicit political agendas (cf. Hug 2014), as well as its hidden assumptions about selfmotivation and expectations on media technologies (cf. Missomelius, 2014). Facing these MOOCs one also can detect a number of paradoxes and ambivalences regarding claims of freedom and exclusive demands for stable and advanced technologies, providing opportunities that attract the well informed and already privileged users while weakening the financial foundation for public education. A different kind of paradoxes relate to how ideology states "sharing practices" and still promotes "branding" and marketing of prestigious institutions with rigorous copyright policies. Technologies are, similarly, most often proprietary and its proponents avoid Free/Libre Open Source Software, and -last the discrepancy between the huge exposure to learning analytics and big data analysis, while, in theory, advocating data privacy and autonomy.
Ignoring such paradoxes and ambivalences will not lead to improvements of the quality of education. As far as MOOCs and OER can be characterized as modes of opening up educational opportunities and disengaging them from institutional ties, the public-private nexus has to be (re-)considered explicitly in view of developments of new institutional features and widespread forms of the incorporation of profit-oriented structures especially in higher education.
Perspectives for Higher Education -All Open?
At times, it is stated that openness and knowledge sharing have always been at the heart of higher education and academic knowledge cultures. Then again, there are initiatives like the "science shop" (Wetenschapswinkel, Wissenschaftsladen) at least since the 1970s and more recently initiatives like the Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities (2003) which remind us of the unequal distribution of scientific knowledge as well as its benefits and risks, social accountability (Sozialpflichtigkeit) of academic knowledge, and fair access to resources and results of academic knowledge production generally. Today, open access initiatives are widespread and important but often fall short in terms of conceptual, social, and organizational aspects -at the same time ignoring former lessons learned in the context of opening up systems of scientific knowledge production (cf. for example, Leydesdorff & Besselaar, 1987).
Indeed, even connections to traditional distinctions like doxa, epistêmê, technê, phronêsis, gnosis, or sophia (cf. Glasersfeld 1997, p. 198) remain implicit or even forgotten all too often. Although in the field of theory of knowledge, there are research activities going on regarding implicit dimensions 3 their relevance remains widely undervalued in contexts of higher education.
These understandings and other distinctions regarding the assumed location of knowledge, for example, in minds or heads, bodies, objects to be treated, societies, social structures or networks, in the "cloud" or Vanishing into Things (Allen 2015), are of significant importance for concrete meanings of openness in higher education and strategies of opening up academic knowledge. Distinguishing degrees of openness along the lines of access and availability, accreditation and forms of licensing, dimensions of information technology or computational thinking, and corresponding pedagogical framings and scopes for action are too narrowly considered. Beyond that, concepts and practices of opening up are always relevant in terms of knowledge cultures and knowledge politics as well as medial constellations and understandings of education, too. Besides, there is the ongoing struggle for clarification of various forms of knowledge -like experience-oriented everyday knowledge, common sense forms of knowing as well as knowing in arts and academic contexts, scientific knowledge or mythical knowledge -, not to forget about efforts to point out respective conceptual distinctions, transitions, and similarities.
In view of these complexities in flux, taking 'openness' as an absolute value or a value in itself appears to be problematic. Unintended side-effects are rather likely if claims for openness are too simply conceived and if corresponding educational practices build upon such claims. Opening up academic knowledge cultures without considering some strands of the complex interplay of understandings, organizational dynamics and practices at least in part could resemble a blind flight in foggy sky or end up in openness towards everything. 4 Moreover, we should always be aware of socio-cultural and media dynamics of opening and closure (cf. Rußmann et al., 2012, Dobusch, 2017 as well as dynamics of co-evolution of media and culture, knowledge and space, and "knowledge scapes" (Matthiessen, 2007) as related to knowledge milieus. With this in mind, I want to highlight three aspects which appear to be undervalued in current debates about openness in higher education.
(1) From an organizational perspective there are issues of openness towards structural changes. Universitas est semper reformanda -throughout history, we find an ongoing transformation of academic cultures and scientific systems including outsourcing of technical universities in the 19th century, nonuniversity research, and the invention of universities of applied sciences. Today, media are often described as means of empowerment, participation and digital inclusion while being used as instruments of "Wikiwashing" (Fuster Morell 2011), non-transparent data collection, surveillance, governance and control. Whitchurch (2008) -following Homi Bhaba's cultural concept of an "intermediary space" -uses the term 'Third Space' with reference to new roles between administration (in a narrow sense) and academic research and teaching. Corresponding activities are related to fields like quality management, controlling of educational "outputs", innovation management, e-learning "implementation" units, public relations offices, research management, library services, staff development, etc.
These fields have been established and continuously expanded in many universities all over the world, whereas many research departments and academic units have been struggling with substantial cutbacks. While Zellweger Moser and Bachmann (2010) are describing this development in uncritical ways, Baecker (2010) pleads in favor of balancing dynamics of research, teaching and administration. However assignment of responsibilities and competencies is being done, for example, in the context of innovation management within universities, mostly the respective activities show characteristics of re-acting or re-structuring and hardly characteristics of redesigning, re-framing, or-generating according to possible modes of coping with change (cf. Peschl & Fundneider 2008). It must remain an open question at this point, how and to what extent the ongoing activities in academic "Third Spaces" are complicating, obstructing, supporting or opening up perspectives for which areas of academic research and higher education.
(2) As far as methodological perspectives are concerned, wide parts of academic research are dealing with standardized methodologies. Especially in empirical research, communicative stabilization of research topics, objects and methods is crucial in order to enable traceability, validity, reliability, replicability, transparency, reflection of limitations and well reasoned arguments concerning Openness towards innovative solutions and research-based learning and education in a globalized world require not only multi-perspective views, wellreasoned applications of methods and thoughtful thinking but also abilities to become sensitive towards styles, languages and cultures of knowledge and science (cf. Thiel & Rost 2001, Hess 2012 and to call into question basic assumptions. In contrast to prevalent versions of monological research, and in contrast to much less common versions of dialogical research, options for polylogical research have been widely ignored so far. Polylogical research as outlined by Wimmer (2001) allows for extensive reciprocal influences of various positions and promotes situations in which all basic concepts, assumptions, starting points and methods are debatable (cf. Wimmer, 2001).
(3) As to critical perspectives openness towards critical thinking is widely recognized as an indispensable prerequisite to foster good scientific practice. Even though today often other forms of thinking -such as design thinking, computational thinking, complexity thinking, or emotional thinking -are being emphasized, critical thinking remains a general requirement in the sense of both a teaching and researching principle and a remedy against opportunistic or dogmatic thinking. On closer examination, it quickly becomes clear that there are varying preferences for this cross sectional subject among them logical reasoning as well as skeptical, multi-perspective, science-oriented, independent, systematic, methodical, critical of society, networked, systemic, self-reflective, and meta-cognitive thinking. By and large, on a paradigmatic level we can distinguish between four approaches: • neo-Marxist philosophy, critical theory, criticism of ideologies • phenomenological critique • praxis-oriented and activist movements • postmodern, post-structuralist and post-colonial thinking.
If we take conceptual, discursive and performative aspects of critical activities into consideration we frequently are facing paradogmatic tendencies or paradoxical aspects, too. For example, it is sometimes the case that those who like to express themselves as particularly "critical", "transparent" and "democratically oriented" are concerned with the covert enforcement of antidemocratic interests. Dynamics of opening and closure play an important role in the context of critical thinking, too, not least in the sense of problematic turning-points or tilt-effects when, for example, • criticism of ideology is turning into an ideological endeavor • critique of culture industry comes as part of arts and entertainment industry • re-governementalization takes place in the name of de-governmentalization • postmodern easiness is tipping in a cynical smile, laugh, or laughter • post-colonial activities are changing to a colonialist undertaking.
While critical thinking may end up in the prohibition of criticism of the other, a deeper understanding of open mindedness and openness in higher education aims at overcoming and avoiding pitfalls of arbitrary positings (Setzungen) and epistemological foundationalism based on, for example, empiricism, rationalism or transcendentalism. From a meta-theoretical perspective it is important to be aware of epistemological and methodological research contexts as well as researcher-generated contexts, too. A non-foundationalist approach as outlined by Heyting (2001) and Goor et al. (2004) appears to be useful here. Such an undogmatic approach takes account of the undecidable character of many questions, and it helps countering premature, oversimplified "solutions" or arbitrary strategies by means of a threefold contextualization of specific problems and topics: reflection on the meaning context, personal context and discourse context (cf. Goor et al. 2004, p. 176, 182 ff).
Against this background, openness in education means being in search of ways between Scylla of epistemological foundationalism and Charybdis of arbitrary positings (Setzungen).Thus, openness as related to critique and critical thinking means opening up towards reflective forms of meta-critique (Latour 2004;Hoy 2004). This claim for meta-critical, polylogical and context-sensitive perspectives should not be mixed up with a claim for 'anything goes': "openness to possibilities is not the same as saying 'anything goes' because possibilities are always limited and situated. Furthermore, openness is the opposite of saying 'nothing matters' because possibilities are considered open only insofar as they are found to be worth pursuing." (Hoy 2004, p. 232)
Conclusions
This essay has discussed different understandings of openness in educational contexts and their relevance for openness towards academic knowledge cultures and different forms of knowledge. It was shown that superficial understandings of 'openness' and 'education' in widespread discourses and practices related to OE, OER and MOOCs are problematic, in particular if more effort is put into marketing of learning opportunities, doubtful learning analytics, and politics of simplistic concepts than into clarification of concepts and methodologies, solid normative reasoning, and context-sensitive argumentation. Perspectives for openness in higher education turn out to be dead ends if they are based on confusions of learning, training and education, and everyday theories of pedagogical concepts, instable platforms, and priorities of fast-paced economization. Fruitful and future-oriented perspectives for openness in higher education are necessarily linked to an understanding of higher education through participation in academic research as well as theoretical and methodological deliberation. Furthermore, this study has found that generally organizational, methodological, and critical aspects are underestimated in OE and OER contexts. As to organizational perspectives, structural changes in the sense of excessive strengthening of activities in academic "Third Spaces" prove to be ambivalent. Far more importantly, dynamics of openness and closure are related to the ongoing reorganization of academic tribes, territories and disciplines beyond epistemological essentialism (cf. Trowler et al., 2012;Müller ,2014), too. This is about nothing less than considering both The Structure of Scientific Revolutions (Kuhn, 1962) and the Revolution of Scientific Structures (Müller, 2016), and re-thinking critical thinking with an emphasis on meta-critical, polylogical and context-sensitive perspectives.
In other words: If we take seriously that all knowledge is contextually bound, then context-sensitive concepts and practices open to the future are vital. If we frame OE and OER in contexts of medialization and digitization, interdependencies between human agency and the ongoing work of algorithms are to be considered explicitly. If we consider higher education as both a public and a private good for many and not just for elites, polylogical approaches are needed in order to enable critical mediation between individual and cultural memories as well as bet-ween contemporary societal challenges and "pure" research meant to be purpose-free. | 5,838 | 2017-10-17T00:00:00.000 | [
"Education",
"Philosophy"
] |
Dracula’s ménagerie: A multispecies occupancy analysis of lynx, wildcat, and wolf in the Romanian Carpathians
Abstract The recovery of terrestrial carnivores in Europe is a conservation success story. Initiatives focused on restoring top predators require information on how resident species may interact with the re‐introduced species as their interactions have the potential to alter food webs, yet such data are scarce for Europe. In this study, we assessed patterns of occupancy and interactions between three carnivore species in the Romanian Carpathians. Romania houses one of the few intact carnivore guilds in Europe, making it an ideal system to assess intraguild interactions and serve as a guide for reintroductions elsewhere. We used camera trap data from two seasons in Transylvanian forests to assess occupancy and co‐occurrence of carnivores using multispecies occupancy models. Mean occupancy in the study area was highest for lynx (Ψwinter = 0.76 95% CI: 0.42–0.92; Ψautumn = 0.71 CI: 0.38–0.84) and wolf (Ψwinter = 0.60 CI: 0.34–0.78; Ψautumn = 0.81 CI: 0.25–0.95) and lowest for wildcat (Ψwinter = 0.40 CI: 0.19–0.63; Ψautumn = 0.52 CI: 0.17–0.78) We found that marginal occupancy predictors for carnivores varied between seasons. We also found differences in predictors of co‐occurrence between seasons for both lynx‐wolf and wildcat‐wolf co‐occurrence. For both seasons, we found that conditional occupancy probabilities of all three species were higher when another species was present. Our results indicate that while there are seasonal differences in predictors of occupancy and co‐occurrence of the three species, co‐occurrence in our study area is high. Terrestrial carnivore recovery efforts are ongoing worldwide. Insights into interspecific relations between carnivore species are critical when considering the depauperate communities they are introduced in. Our work showcases that apex carnivore coexistence is possible, but dependent on protection afforded to forest habitats and their prey base.
| INTRODUC TI ON
Terrestrial carnivores are some of the most imperiled species today due to their large home range requirements, high metabolic demands, sensitivity to habitat fragmentation, and persecution by humans (Crooks, 2002;Palomares & Caro, 1999;Ripple et al., 2014;Woodroffe & Ginsberg, 1998). Carnivores can also be important top-down regulators in ecological communities (Beschta & Ripple, 2009;Ripple & Beschta, 2006;Ripple & Beschta, 2012). The loss of key carnivore species can have devastating ecosystem effects (Effiom et al., 2013;Ripple et al., 2014) and changes in abundance or occurrence of carnivores can trigger trophic cascades (Ripple & Beschta, 2012). As such, the recovery of apex predators as a conservation tool to restore ecosystem functions (termed trophic rewilding) has become increasingly popular (Jørgensen, 2015;Seddon et al., 2014). Trophic rewilding is an ecological restoration strategy used to promote self-regulating ecosystems (Svenning et al., 2016).
Rewilding efforts in the context of apex predators requires not only an understanding of their ecological interactions within the carnivore guild but also the broader context of these interactions including sources of anthropogenic impacts. Many apex predators readily reestablish in human-dominated landscapes and exhibit potential coexistence with humans (Chapron et al., 2014;Lamb et al., 2020). Although the effects of apex predator recovery in natural landscapes are relatively well understood, there are significant knowledge gaps regarding the effects of their recovery in shaping species interactions (both intraguild and across trophic levels) in human-dominated landscapes (Dorresteijn et al., 2015;Kuijper et al., 2016). Interactions between carnivores are complex in nature and are integral to shaping the ecology and structure of wildlife communities. Therefore, examining such interactions in landscapes that harbor viable carnivore populations may provide important insights into the effects of carnivore recovery on the mesocarnivore communities that often dominate landscapes where apex predators have been eliminated.
Grey wolf (Canis lupus) and Eurasian lynx (Lynx lynx) are top predators in many temperate ecosystems in Europe and Asia, but their co-occurrence has been severely limited by extirpation of one species (most often wolf). This is particularly the case for most of Western and Central Europe due to a long history of human habitation and persecution of carnivore species. Both wolves and Eurasian lynx are recovering in Europe's landscapes (Chapron et al., 2014;Kaczensky et al., 2013) either through natural range expansion (wolf) or reintroductions and population augmentation (lynx). The European wildcat (Felis silvestris) is a mesocarnivore that was once common in Europe and has also been extirpated and currently at the core of reintroduction programs in some European Union states. In this context, the Romanian Carpathians represent one of the few natural areas in Europe that still harbor intact viable populations of all three species and serve as a stronghold for carnivore populations in Europe, despite anthropogenic influences common (hunting, forestry, farming, and livestock production) (Popescu et al., 2016;Salvatori et al., 2002).
While no work has been conducted on understanding the spatial relations and interactions between these three species simultaneously, research exists on pairwise interactions between species, particularly for lynx and wolf. Lynx and wolf are sympatric across most of their range and there is some diet overlap between them.
Research addressing coexistence between these species differ in their findings, but recent studies looking at spatial interactions between these species in Europe found that these two apex predators coexist and competition between them is low Wikenros et al., 2010). In Poland, lynx and wolf territories overlap and researchers concluded that the co-occurrence of these two species was facilitated by heterogeneous habitat and specialization on different prey . These predictors, habitat heterogeneity and diet, are also explaining competitive interactions between canids and felids in North America, with a lack of interference competition in heterogeneous habitat . Therefore, we expect to observe similar co-existence (high co-occurrence) and little evidence of interference competition (neutral or positive conditional occupancy values) between lynx and wolf in our study area.
Additionally, we expect to observe differences in co-occurrence based on seasonal changes in these species' behaviors. For example, the daily movement distances of male lynx are greater during the mating season (January-March) and for female lynx are greater during periods of extensive kitten care (May-August) (Jedrzejewski et al., 2002), which could cause increased interactions with wolves as lynx cover a larger geographic area during these periods. Research on wildcats is scarce, but a study conducted in the Jura Mountains of central Europe found no evidence of avoidance between lynx and wildcat (Hercé, 2011). No published research examines interactions between wildcats and wolf. Given the size difference between wolf and wildcats and their different diets, it is likely that the relationship between wildcats and wolf will be similar to that of wildcats and lynx.
In this study, we aimed to address these knowledge gaps by studying the intraguild interactions of two apex carnivores, the Eurasian lynx and the grey wolf, and a mesocarnivore, the wildcat in the Romanian Carpathians using multispecies occupancy models (Rota et al., 2016). Unlike traditional occupancy modeling, multispecies occupancy models allow for the estimation of K E Y W O R D S carnivores, coexistence, human-dominated, interactions, landscapes, multispecies occupancy
T A X O N O M Y C L A S S I F I C A T I O N
Conservation ecology; Population ecology; Spatial ecology; Trophic interactions co-occurrence probabilities for more than two species and do not assume asymmetric interactions (i.e., dominant and subordinate species). This is useful for estimating co-occurrence probabilities between species for which there is not a priori knowledge about interspecific relationships or for which there is not an obvious dominant or subordinate species. Multispecies occupancy models also allow for the estimation of marginal occupancy (occupancy of a single species irrelative of other species) and conditional occupancy (occupancy of a single species based on the presence or absence of another species) probabilities in relation to variables of interest (e.g., altitude). This approach has been used effectively to assess habitat use, interspecific interactions of carnivores in a variety of landscapes (Dechner et al., 2018;Lombardi et al., 2020;Van der Weyde et al., 2018). Previous research on lynx-wolf and lynx-wildcat interactions suggests a high capacity for coexistence, low interspecific competition, and little to no intraguild killing.
However, this research is limited and there has been no work on wolf-wildcat dynamics or interactions of lynx, wildcat, and wolf in the same region. Additionally, none of the published literature in Europe has been conducted in an area with a fully intact carnivore guild, whereas the Romanian Carpathians have viable, reproducing populations of many large carnivores and meso-carnivores that have not been extirpated (see study area). This information is crucial to understanding the effects of apex predators on mesocarnivores and the carnivore guild. By using a multispecies occupancy approach, we can analyze complex intraguild interactions and better understand competition and coexistence patterns. Results can elucidate variables and thresholds important for occurrence and coexistence of elusive species and help inform management or reintroduction efforts. Our specific objectives were as follows: (1) evaluate seasonal predictors for occupancy of each species, (2) characterize the spatial relationships (co-occurrence) of each species in winter and autumn, and (3) identify predictors that facilitate co-occurrence. Specifically, we analyzed the effects of potentially dominant apex carnivores on the occupancy and detection of a mesocarnivore to understand potential impacts reintroductions of apex predators may have on smaller carnivores. We also evaluated seasonal changes is marginal and co-occurrence probabilities to better understand how species persist and interact under different environmental conditions.
| Study area
The study area is situated in the Southern Carpathians, Romania, covering 1200 km 2 in the eastern part of the Făgăraș Mountains, Piatra Craiului, and parts of Leaota Mountains (Figure 1). The altitude of the study area ranges from 600 to 2400 m; forests cover most of the area (62%), along with a mosaic of urban-rural landscape and agriculture with significant areas of natural vegetation (22%), and alpine grasslands and subalpine shrubs (16%) (Iosif et al., 2022).
| Camera trapping and environmental variables
We divided the study area into a grid of 2.7 × 2.7 km cells ( Figure 1) and removed cells with more than ⅔ of their area exceeding 1800 m altitude and cells more than ½ of their area covered by urban landscape features. From the remaining cells, we sampled every other cell, when it was not possible to reach a selected cell, we used an adjacent cell. Each sampled cell contained a trap station, randomly located within the cell. We conducted two seasons of monitoring: (1) December 17th, 2018, to March 31st, 2019 (winter) and (2) October 9th, 2019, to January 15th, 2020 (autumn). We installed 64 camera trap stations during winter, and 76 during autumn, with high spatial overlap between seasons ( Figure 1). Each trap station had two opposite cameras installed at a height of 40 to 60 cm positioned toward animal paths. We used two camera models per trap station, a CuddeBack C1 Model 1279 with white flash for highquality color pictures in night conditions, and a Bushnell Trophy infrared camera. Camera traps were installed on animal trails along mountain ridges, mid-slopes, upper valleys, and bottom of slopes to detect carnivores at various altitudes/habitats. Camera traps were installed 1-2 weeks prior to the start of monitoring to account for additional anthropogenic disturbance from the camera installation process. We checked camera trap stations every two weeks to replace batteries and SD cards.
At each camera trap location, we recorded the presence or absences of anthropogenic disturbance (i.e., logging or settlements) as a binary variable for species detection and occurrence. We also recorded altitude (m) via GPS and extracted distance to stream (m), distance to settlement (m), and distance to roads (m) from the camera trap location using Geographic Information Systems (ArcGIS 10.7, ESRI, Redlands CA). Within a 500-meter buffer around each camera trap location (Lombardi et al., 2020), we calculated the density of local roads (km/km 2 ), the proportion of forested area and a terrain ruggedness index (TRI) (Riley et al., 1999). Full covariate descriptions and summaries are available in Table 1.
| Occupancy modeling
We implemented a multispecies occupancy model of two or more interacting species (Rota et al., 2016) in program R 3.5.1 (R Core Team, 2021) via package unmarked (Fiske & Chandler, 2011) to explore how environmental and anthropogenic variables affect the marginal occupancy (occupancy without accounting for interactions with other species), co-occurrence (overlap in marginal occupancy between species), and conditional occupancy (effects of each species presence on other species detection and occupancy) of lynx, wildcat, and wolf in the Romanian Carpathians. Unlike traditional cooccurrence models, multispecies occupancy models do not require a priori assumptions of asymmetric interactions; therefore, species were not considered dominant or subordinate to one another (Rota et al., 2016). Data from the two seasons were analyzed separately, and sessions were divided into 14-day sampling occasions, with the winter and autumn seasons having eight and seven sampling occasions respectively. Camera trap photos were cataloged by FCC staff and volunteers, and the date, time, location, and species identification were recorded for each animal detection (Iosif et al., 2022).
Covariates were checked for correlation using Pearson's correlation tests and Pearson's chi-squared test (for numerical and factors respectively), those with high correlations r > .7 were not included in the same models for the same parameter. We first explored combinations of five detection covariates for species-specific detection probabilities (Table 1) by comparing models with the same marginal occupancy parameterization for each species. Detection covariates were kept the same for all three species as we did not have a biological reason to vary them between species. We also included the latent presence/absence of every other species as species-specific detection covariates (e.g., lynx detection predicted by the presence/ absence of wildcat and wolf). Although multispecies occupancy models do not assume asymmetric interactions between species, we wanted to explore the possibility that dominant species could exist in our system and affect the presence of other species. Therefore, we also included species-specific detections of lynx as a function of the latent presence/absence of potentially dominant wolf, and wildcat as a function of lynx and wolf. From these models, we determined a best model for each season based on Akaike information criterion (AIC), using R package MuMIn (Bartoń, 2020). We included the top detection covariates in the models exploring marginal occupancy and co-occurrence. We then ran a series of models to assess the marginal occupancy of our three species using environmental and anthropogenic variables ( Table 1) that were determined a priori and we hypothesized it would affect the marginal occupancy of each species. The candidate set of marginal occupancy models was similar for both seasons, models were only removed if variation in covariates was not great enough to allow estimation (i.e., models produced NAs or unreasonable estimates and standard errors). We compared the marginal occupancy models for each season using AIC to identify the best covariates explaining occupancy of each individual species. Using the top covariates from the marginal occupancy analysis, we ran a series of additional candidate models that reflected a priori hypotheses regarding pairwise co-occurrence between lynx and wildcat, lynx and wolf, and wildcat and wolf, and compared the models using AIC and biological relevance (Table S1). Due to data limitations (small sample size), we did not implement a three-species co-occurrence parameterization.
| Marginal occupancy
Mean occupancy for both seasons was highest for lynx (winter However, in autumn, marginal occupancy of wolf decreased with terrain ruggedness (Figure 2f), and lynx occupancy increased with forest cover (Figure 2b) while wildcat occupancy decreased with forest cover (Figure 2d).
| Co-occurrence
We also found differences in predictors of co-occurrence between seasons for both lynx-wolf and wildcat-wolf co-occupancies.
In winter, lynx-wolf and wildcat-wolf co-occurrence were predicted by forest cover (Figure 3b,c), but in autumn, co-occurrence for both pairs were predicted by terrain ruggedness (Figure 3e,f).
Lynx-wildcat co-occurrence was predicted by terrain ruggedness
for both winter and autumn seasons and was positively associated with terrain ruggedness in both winter and autumn (Figure 3a,d), but in autumn, the relationship was less linear (Figure 3d). In contrast, both lynx-wolf and wildcat-wolf co-occurrence were negatively associated with terrain ruggedness in autumn (Figure 3e,f). In winter, wildcat-wolf co-occurrence was negatively associated with forest cover while lynx-wolf co-occurrence was positively associated with forest cover, but only at >75% forest cover (Figure 3e,f).
| Conditional occupancy
In the winter season, we found that occupancy probabilities of all three species were higher when another species was present, regardless of the species (Figure 4). However, the occupancy probability of wildcat, decreased with increasing forest cover when either lynx or wolf were present (Figure 4), potentially a signal for mesopredator exclusion by apex predators in area of higher suitability. Similarly, in autumn, all species tended to co-occur, but this relationship was dependent on terrain ruggedness. Occupancy probabilities for both felids, lynx and wildcat, increased with terrain ruggedness when the other felid species was present and decreased when the other species was absent ( Figure 5). We observed the inverse relationship for both felids when considering the presence/absences of wolf, such that occupancy probabilities for lynx and wildcat decreased with increased terrain ruggedness when wolf were present and showed a positive relationship with terrain ruggedness when wolf were absent ( Figure 5). The presence of lynx and wildcat appeared to have no effect on wolf occupancy.
| Detection probabilities
For both seasons, the models that included that latent presence/absence of a potentially dominant species as a detection covariate performed significantly better than those that did not (∆AIC > 5). The top models for each season did not vary in their detection covariates; both models included distance to stream and the latent presence/absence of all species as species-specific detection covariates.
For both seasons, lynx, wildcat, and wolf detections were positively associated with the presence of the other two species (Table S1).
| DISCUSS ION
The results from our multispecies occupancy model of lynx, wildcat, and wolves in the Romanian Carpathians indicate that while there are seasonal differences in predictors of occupancy and co-occurrence of the three species, co-occurrence of the three species in our study area is high during both seasons. We identified useful predictors of marginal occupancy for each species; in winter were local road density (lynx and wolf) and altitude (wildcat). While in autumn, the best predictors of marginal occupancy were, forest cover (lynx and wildcat) and terrain ruggedness (wolf). We found that co-occurrence was influenced by environmental variables, forest cover, and terrain roughness, for both winter and autumn. Overall in this heavily forested landscape results from our study indicate that these species coexist but shift patterns of habitat use and co-occurrence seasonally.
| Determinants of occupancy
In winter, local road density was the most important predictor of occupancy for wolf, with higher road density associated with a lower probability of wolf occupancy (Figure 2e). Higher local road density in our study area is associated with higher human disturbance (e.g., limited logging) and habitat fragmentation; this corroborates findings from Jedrzejewski et al. (2004) forests. In our study area, the proportion of forest was not an important predictor of wolf occupancy in either season, even though multiple studies have found it to be an important habitat characteristic for wolf (Jedrzejewski et al., 2004;Zlatanova & Popova, 2013) This may be due to the characteristics of our study area which is heavily forested (mean proportion forest =0.78 and 0.75 for winter and autumn monitoring sessions, respectively); thus, forest cover is not a limitation to wolf occurrence. In autumn, terrain ruggedness was the most important predictor of wolf occupancy; when terrain ruggedness index was >200 (moderately to highly rugged areas) the probability of wolf occupancy declined steeply ( Figure 2f). This can be explained by the fact that wolf's main prey source in Romania, wild boar (Sin et al., 2019), was documented to prefer less fragmented areas with large beech forest stands in autumn and early winter (Fonseca, 2008). Additionally, red and roe deer, which are also important prey for wolves, are known to move corridors and for hunting and movement within their home range (Bailey, 1993;Bragin, 1986;Gordon & Stewart, 2007;Kerley et al., 2002;Matyushkin, 1977;Rabinowitz et al., 1987). Our results suggest that, in winter, Eurasian lynx are more likely to occupy areas with higher densities of local logging roads; these roads, which in our area are mostly unpaved, dirt roads, may provide easier access to resources within lynx home ranges due to decreased complexity of terrain and decreased snow depth/harder snowpack from vehicle travel. We did not observe this relationship with wildcat, however.
Rather, there was a negative relationship between density of local roads and wildcat occupancy in autumn (Figure 2d), which could be an artifact of body size; most documented examples of felids utilizing roads for movement within their home ranges was with larger bodied species (>11 kg). We also did not observe this relationship in winter; however, this is likely an outcome of the importance of altitude for wildcat occupancy, which has a negative relationship ( Figure 2c). Higher altitudes are associated with greater snow depth, and while lynx are well adapted to move in deep snow and altitude was not important for lynx occupancy, wildcats have physical limitations that make travel through deep snow more difficult. A study in Switzerland had similar findings whereby wildcats moved to areas free of snow in winter and spring and moved back to high elevations in summer (Mermod & Liberek, 2002). Similarly, in North America, the relationship between Canadian lynx (Lynx canadensis) and bobcat (Lynx rufus) is mediated by snowpack, with the distribution of the less snow-adapted, the bobcat, being limited by snow depth at the northern edge of its range (Morin et al., 2020;Reed et al., 2017). Our results for marginal occupancy of lynx, wildcats, and wolf provide insights into both habitat selection and spatial relations for these elusive carnivores in Romania. Our results suggest lynx may use roads for movement, a practice common for other felids of similar body size, but not described in this species. Additionally, we provide further support for previous findings on habitat selection and occupancy for these three European terrestrial predators.
| Determinants of co-occurrence
In winter and autumn, co-occurrence for lynx and wolf was high indicating that both species have similar habitat requirements. In winter, we found an effect of forest cover on the co-occurrence of lynx and wolf; co-occurrence increased with proportion of forest cover >0.75. prey of lynx and wolf. Roe deer abundance is also lower in areas with high forest cover (Melis et al., 2009). Higher lynx-wolf co-occurrence in areas expected to have lower roe deer abundance indicates that lynx and wolf are likely partitioning prey resources which would reduce competition. In our study area, wolf also prey on wild boar and red deer (Sin et al., 2019). In autumn, terrain ruggedness was a negative predictor of co-occurrence for lynx and wolf, such that predicted co-occurrence was ~0 for the highest values of terrain ruggedness.
This relationship is driven by the negative relationship between marginal occupancy for wolf and terrain ruggedness, which is related to prey movements and availability as explained above (Fonseca, 2008;Sin et al., 2019) (Figure 2c). Because marginal occupancy for wolf is ~0 at high terrain ruggedness, co-occurrence for lynx and wolf is low as well. Additionally, co-occurrence between wolf and wildcat decreased with terrain ruggedness in autumn (Figure 3f) due to the low marginal occupancy for wolf at high terrain ruggedness. In winter however, co-occurrence of wolf and wildcat was predicted by proportion of forest such that increasing forest cover resulted in lower co-occurrence (Figure 3c). In both seasons, the co-occurrence of lynx and wildcat increased with terrain ruggedness, but the relationship was stronger in winter (Figure 3a,d). This relationship also provides further evidence that the negative relationship observed for lynx and wolf co-occurrence and terrain ruggedness was driven by wolf marginal occupancy.
| Management and conservation implications
The positive effect of wolf and lynx presences on detection of one another, high levels of co-occurrence in winter, and high levels of conditional occupancy in both seasons (higher occupancy probability when other species is present), for lynx and wolf provide little evidence of interference competition between these apex predators. This suggest that carnivore species may aggregate in certain habitats during winter, potentially driven by prey availability. This corroborates findings from other studies assessing interactions between co-occurring felids and canids that overlap in resource use. not affect the introduction efforts given that prey base can support both species, and releases occur in highly forested but less topographically fragmented areas. Additionally, our findings also suggest that apex predators have little negative effects on the mesocarnivore, wildcat. This information is useful for management given that wolves are recolonizing their former range in Europe (Chapron et al., 2014). Our findings suggest that wolf would not have negative impacts on wildcat given enough suitable habitat is available. In summary, studying intraguild interactions in an intact system has enabled us to observe and quantify intraspecific interactions among carnivores where they have co-existed and co-evolved for centuries. This provides insight into their potential long-term dynamics for areas where they are recovering naturally or recovering through rewilding efforts. While our study did not include the summer season, our results from two separate and partially overlapping autumn and winter seasons suggest that competition between lynx, wildcat, and wolf is low. However, additional information on the richness and abundance of the prey base, and the spatial and temporal relations between predators and their prey can augment these findings and provide additional management insights in the context of rewilding.
ACK N OWLED G M ENTS
We thank Piatra Craiului National Park Administration and the Hunting Associations Bârsa, Jderul, and GTS Muntenia, for permissions to undertake fieldwork. We thank Liviu Ungureanu, Călin Șerban, and rangers of the Foundation Conservation Carpathia for help with camera deployment and checking. We thank Ken Kellner for continued support with R code for the multispecies occupancy Travel for MD to Romania was provided by the Ohio University College of Arts and Sciences. | 6,006 | 2022-02-09T00:00:00.000 | [
"Environmental Science",
"Biology"
] |
Modeling size controlled nanoparticle precipitation with the co-solvency method by spinodal decomposition
The co-solvency method is a method for the size controlled preparation of nanoparticles like polymersomes, where a poor co-solvent is mixed into a homogeneous copolymer solution to trigger precipitation of the polymer. The size of the resulting particles is determined by the rate of co-solvent addition. We use the Cahn–Hilliard equation with a Flory–Huggins free energy model to describe the precipitation of a polymer under changing solvent quality by applying a time dependent Flory–Huggins interaction parameter. The analysis focuses on the characteristic size R of polymer aggregates that form during the initial spinodal decomposition stage, and especially on how R depends on the rate s of solvent quality change. Both numerical results and a perturbation analysis predict a power law dependence R B s (cid:2) 16 , which is in agreement with power laws for the final particle sizes that have been reported from experiments and molecular dynamics simulations. Hence, our model results suggest that the nanoparticle size in size-controlled precipitation is essentially determined during the spinodal decomposition stage.
Introduction
Because of their great potential in nano-and biotechnology, polymeric nanoparticles such as polymersomes have attracted growing interest during the last decades. 1,2One possible application can be found in the field of drug delivery, where they serve as transport vehicles for medication. 3A crucial property of such transport vehicles is their size, as it does not only determine their loading capacity, but also the composition of their protein corona in blood, which affects the retention times in the circulatory system. 4Furthermore, the nanoparticle size plays a critical role in passive targeting of tumors, which is based on the enhanced permeability and retention effect. 5 method to prepare polymersomes of a particular size is the co-solvency method or flash nanoprecipitation: a poor co-solvent is mixed into an initially homogeneous solution of a good solvent and a block copolymer to induce particle formation via selfassembly of the polymer. 6,7The co-solvency method can be implemented in different ways.A straightforward approach is to add co-solvent by drop injection to a polymer solution.In this method the size of the produced nanoparticles depends on the rate of co-solvent addition. 8Thiermann et al. fed the co-solvent and the copolymer solution into continuous flow multilamination micro mixers and observed that the size of the synthesized particles decreases with an increasing flow rate, which connects nanoparticle size to an easily adjustable parameter of the experimental setup. 9The micro mixer approach has several advantages as it yields narrower size distributions and can be done without additional steps like membrane extrusion to achieve acceptably low polydispersities.
A superficial comparison between the two realizations of the co-solvency method suggests that the size of the produced nanoparticles depends on a completely different quantity in both cases: the rate of co-solvent addition on the one hand and the flow rate on the other.However, due to the special design of multilamination micro mixers, an increase in flow rate decreases the mixing time of liquids that are fed into its inputs. 10Changing the flow rate indirectly changes the mixing rate.Hence, in both cases particle sizes are found to depend on the mixing rates of the co-solvent and the copolymer solution.
To gain a deeper understanding of the size controlled preparation of polymeric nanoparticles with the co-solvency method, one must analyze how different rates of co-solvent addition affect the particle formation and how the particle size depends on the rate of co-solvent addition.In this article we consider the earliest stage of particle formation, the spinodal decomposition of an oversaturated polymer solution.We present a simple phase field model that can be used to determine the size of aggregates in that stage.The model is an extension of the popular Cahn-Hilliard model for the dynamics of phase separation, where we represent the effect of mixing solvent and co-solvent in an effective manner by using time dependent interaction parameters.Using numerical simulations of an idealized mixing process, we show that the model can reproduce the dependence of particle size on mixing speed observed experimentally.
Our article is organized as follows: we present the model in Section 2 and describe the simulation method in Section 3. In Section 4, we explain the evaluation method, show our simulation results, compare them to a perturbation theory, and discuss scaling laws both have in common.These scaling laws are then compared to experimentally observed power laws in Section 5. We summarize and conclude in Section 6.
Theoretical model
Experimentally, three different components are involved in the co-solvency method of nanoparticle synthesis: a polymer, a good solvent and a poor or selective co-solvent.The precipitation of the polymer is triggered and influenced by the continuous addition of co-solvent into the polymer solution -i.e., by solvent mixing.We assume that solvent mixing is fast on the time scales of the polymer phase separation and that the main effect of solvent mixing is a change of 'mean solvent quality' from 'good' to 'poor'.Thus, we incorporate solvent mixing by only taking into account the change in solvent quality: the three component system from the experiment is modeled by a two component system containing a polymer and only one solvent, which changes its quality over time.More specifically, at any given time we describe the momentary solvent mixture by one single effective solvent with an associated interaction parameter w at a polymer-solvent contact.The addition of co-solvent into the solvent mixture is modeled by a temporal increase of w.
Close to a homogeneous ground state isothermal phase separation of incompressible binary mixtures in a fixed volume can be modeled by the Cahn-Hilliard equation.It describes the local evolution of a globally conserved dimensionless composition field u, for example the volume fraction of one component.The Cahn-Hilliard equation is a special case of the generalized diffusion equation @u @t ¼ Àr Á ÀvzMðuÞ Á r dF du z represents the scale of the mobility and M(u) describes its dependence on the composition.v is the volume of a polymer or solvent segment.Here we will use the ''degenerate mobility'' M(u) = uÁ(1 À u), which is suitable for the description of composition currents in incompressible mixtures. 12,13dF/du is the functional derivative of the free energy functional and can be interpreted as a chemical potential.With the free energy functional F proposed by Cahn and Hilliard, 11 (d is the spatial dimension) one obtains Here, f (u) is the free energy per segment in a homogeneous system, 1 2 l(ru) 2 represents surface contributions, and l is the gradient energy parameter.Insertion of eqn (3) into eqn (1) yields the Cahn-Hilliard equation In this article we specifically consider polymeric systems.Hence we choose z = D/k B T and l = R g 2 Ák B T with the segment diffusion coefficient D = D p N, the Boltzmann factor 1/k B T and the radius of gyration R g .D p is the diffusion coefficient of a polymer chain composed of N segments.The expression for l is an approximation to the gradient energy parameter for a binary homopolymer solvent mixture, which holds in the weak segregation limit where concentration gradients are weak. 14We also use which is free energy per segment from the Flory-Huggins solution theory, 15,16 where w is the Flory-Huggins interaction parameter mentioned earlier.
To describe phase separation during solvent mixing, we assume that w in eqn (5) explicitly depends on time, i.e. w = w(t), and increases from w(0) = w 0 to w max .We choose w 0 to be the spinodal interaction parameter, which is the value of w where a homogeneous system becomes unstable.It depends on the mean polymer volume fraction in the system, as well as N and is defined by the condition @ 2 f @u 2 u; t ¼ 0 ð Þ¼0, which yields w max 4 w 0 is a constant and we consider a situation where w(t) grows linearly as with t max = (w max À w 0 )/s.In the following, all lengths will be given in units of , and all energies in units of k B T(R d g /v).Eqn (4) can then be rewritten as and the derivative of the free energy becomes In experiments, polymersomes are typically formed from amphiphilic diblock copolymers and stabilized by the hydrophilic block.The model presented in this article neither incorporates the stabilization effects from copolymers nor is it able to describe an internal structure of polymer aggregates, because eqn ( 5) is restricted to homopolymers.Thus, the equilibrium state will always correspond to macroscopic phase separation.However, simulations of more detailed models have shown that nanoparticle self-assembly is initially dominated by the formation of unstructured droplets, and that the number of droplets after the initial stage largely determines the final number and size of particles. 17The system defined by eqn (5) represents the simplest model system that reproduces this early stage of particle assembly.
In this article we restrict our investigations to the very early stages of phase separation, where the first patterns in the concentration profile form and where the gradients in the composition field are still small, which motivates the application of eqn (4) with our choice of l.In the context of different possible mechanisms that lead to the formation of structured copolymernanoparticles, 17,18 we focus on the spinodal decomposition before the first micelles appear.In these very early stages, the self-assembly should be driven mainly by the energetically unfavorable interaction between the co-solvent and the co-solventphobic block of the polymer, which leads to typical 'Cahn-Hilliard-type' spinodal decomposition patterns in the concentration profiles. 19The solvent-philic block of the polymer, which is often incompatible with the other one, is mainly responsible for internal structure formation in aggregates once they have formed.So if the internal structuring does not significantly change the size of an aggregate, the substitution of the copolymer by a homopolymer of its hydrophobic block might still yield approximate results for its size.We shall see below that eqn ( 5) is indeed sufficient to describe the relation between particle sizes and mixing rates in the early stages of mixing.
A very recent publication also shows that it is possible to produce homopolymer particles stabilized by surface charges. 20esides an experimental part it also contains molecular dynamics simulations, where solvent mixing is modeled by a time dependent strength of the repulsive force.They observe very similar scaling laws as we do.Another work from the same group applied time dependent repulsive forces to dissipative particle dynamics simulations for copolymers. 21Although they only slightly touched the issue of particle size dependence on mixing time their curves look also similar to ours and the ones from. 20Thus, the model presented in this article reproduces important features observed in much more complex particle models.Its simple structure allows a perturbation treatment and we will see that typical scaling laws observed in our simulations, the molecular dynamics simulations and the experiments are already inherent in the perturbation theory, which might pave the way for semi analytical approaches.In addition, the phase field model allows to study slow mixing processes with characteristic mixing times in the range of milliseconds or more, whereas molecular dynamics simulations are limited to microseconds. 20here also exists a pinning effect of structures, 22 which is caused by viscoelasticity in systems with asymmetric molecular dynamics, i.e. polymer solutions.It might also affect particle sizes and there are models that incorporate this effect. 23However, the present model does not, because pinning did not occur in the experiments 9 we aim to describe.
Since we focus on situations where the particle formation is a thermodynamically driven process (initiated by spinodal decomposition), which does not involve a thermally activated crossing of free energy barriers as in nucleation theory, we do not include thermal noise in our theoretical model, eqn (1).This corresponds to the limit v -0 in eqn ( 1) and (2) (thermal noise would scale with ) and is also motivated by the fact that the relative thermal fluctuations are generally small in polymeric systems.
For simplicity, we call the first aggregates of well-defined shape that emerge during spinodal decomposition 'particles'.How we exactly define these particles and how we determine their size is described in the discussion in Section 4.
Simulation method
Eqn ( 7)-( 9) with M(u) = u(1 À u) constitute the model equations.The applied scheme is very similar to the one used by Zhu et al., 24 which is a first order time accurate pseudo spectral method, and any Fourier transform was calculated by the FFTW library. 25The domains are boxes [0, L b ) d  R 0 + with d = 2, 3 and periodic boundary conditions.As initial conditions we use uniformly distributed random perturbations in the interval [ À u À 0.001, À u + 0.001] generated by the Mersenne twister. 26All numerical results are averages over 5 simulation runs with different initial perturbations and we performed simulations in both 2 and 3 dimensions to check the influence of dimensionality.As it will turn out, the particular dimension plays only a minor role, which allows investigations of main dependencies in 2D to speed up computation times.
The adjustable physical parameters in the model are N, s, w max and À u.The slope s in eqn (7) parameterizes the rate of solvent quality change.It is varied to investigate the effect of different solvent mixing rates on phase separation, while the three remaining parameters are kept constant.In this article, we will mostly study a model with parameters set to À u = 0.1, N = 14, and w max = 2. Simulations for more realistic parameters are shown in Section 5.In 2D we used 400 Â 400 grid points with a lattice constant 0.25, and set the time step to 0.005.
Using that lattice constant assures that the spatial resolution does not limit the smallest particles we encounter in our simulations (which is the particle size at w max ).For constant interaction this problem could also be approached by a rescaling of the spatial coordinate that involves the quench depth Dw. 27 However, this might introduce numerical artifacts that lead to unphysical pinning close to the spinodal.Even though these artifacts can be avoided by proper normalization, 28,29 we did not scale the spatial coordinate by Dw because in our case it depends on time, meaning the system size would exhibit a temporal change if we kept our lattice size and number of grid points constant as is customary in simulations.We should also note that we did not encounter any pinning artifact in our simulations either.In 3D we used 64 Â 64 Â 64 grid points and a lattice constant of 1.
This journal is © The Royal Society of Chemistry 2016
Qualitative characterization of the demixing process
In all simulation runs the phase separation proceeds in a similar manner as in the case of constant interaction parameters w.In the first stage, termed spinodal decomposition, a bicontinuous pattern emerges in the concentration profiles and initially grows and coarsens on a relatively fast time scale, until droplets with well-defined interfaces have formed (see examples in Fig. 2).In the second stage, called Ostwald ripening, the droplet pattern coarsens on a very slow time scale.As stated at the end of Section 2, we focus on the spinodal decomposition stage.This restriction requires us to identify the crossover time between spinodal decomposition and Ostwald ripening.To this end, we use a procedure proposed by Sofonea and Mecke, which is based on Minkowski measures. 30Minkowski measures are a complete set of additive motion-invariant measures for unions of convex sets.Each measure assigns one real number to any polymer volume fraction profile depending on its morphology.Since the morphology of concentration profiles during phase separation depends on time, the Minkowski measures also do.One of these measures, from here on denoted by C, is the total boundary length of the union over all subsets in [0, L b ) d where the polymer volume fraction u exceeds a predefined threshold u th .During spinodal decomposition, polymer aggregates form on a fast time scale leading to a rapid temporal increase of C and during Ostwald ripening, polymer aggregates merge on a large time scale leading to a slow decrease of C.These two characteristic regimes can be seen in Fig. 1, which shows C as a function of time for two examples discussed below.The regimes are separated by a maximum of C and the corresponding time is called the transition time t tr . 30Therefore, spinodal decomposition dominates for t o t tr and Ostwald ripening for t 4 t tr .The remaining Minkowski measures yield equivalent estimates for the transition time. 30To calculate the Minkowski measures we use the algorithm proposed by Mantz et al. 31 In the following, we first discuss exemplarily the effect of a time dependent interaction parameter on spinodal decomposition by comparing the results from s = 5 Â 10 À5 and s = 5 Â 10 À3 .Fig. 1 shows the corresponding time series of C. The transition time obviously depends on s.Hence, spinodal decomposition happens faster for large values of s.Fig. 2 illustrates how different values of s affect the morphology of the polymer volume fraction profiles during spinodal decomposition.The upper panel (Fig. 2(a), (c) and (e)) and the lower panel (Fig. 2(b), (d) and (f)) show temporal evolutions of the same initial polymer volume fraction profile for different growth rates s.At t = 10 the volume fraction profiles look very similar (Fig. 2(a) and (b)).At t = 200, however, they deviate significantly from each other (Fig. 2(c) and (d)) and at the end of the spinodal decomposition there are significantly smaller droplets for the larger quench rate (Fig. 2(e) and (f)).Hence, we see that the time dependence in the interaction parameter does not only affect transition times but also the length scales of structures during spinodal decomposition.We can rationalize this observation as follows: with incasing w, one reaches deeper into the miscibility gap and the characteristic wavelength of the most unstable mode decreases.If w(t) increases very slowly, the initially unstable modes have time to grow and dominate also the later stages of demixing.If w(t) increases more rapidly, modes with smaller wavelengths take over and determine the final structure.Indeed, Fig. 2 demonstrates that the characteristic length scale of patterns in the initial stage of demixing (Fig. 2(c) and (d)) is larger than the characteristic length scale of the final droplet pattern (Fig. 2(e) and (f)).We will analyze this effect at a more quantitative level further below in Section 4.3.
In general, bicontinuous patterns are favored for a larger range of composition variables À u in 3D than in 2D, but for our set of parameters we observed droplets in both dimensions.
Definition of particles and quantitative determination of particle size
To examine the length scales in the volume fraction profiles more quantitatively, we evaluate the normalized radially averaged structure factor 24 Sðk; tÞ ¼ S c ðk; tÞ where S c is the absolute value from the radial average of are usually used to quantify a characteristic inverse length scale.We define the polymer aggregates at transition time as 'particles' and estimate their radius with and where k max (t tr ) := arg max k S(k,t tr ) and g := 1/4.We use two estimators since both k 1 and k max are reasonable choices to quantify a characteristic inverse length scale and we want to assess the difference between the two.The particle radius is thus taken to be one fourth of the characteristic wave length 2p/k 1 (t tr ) or 2p/k max (t tr ), respectively.
In addition, we used a standard image labeling algorithm to determine the total particle number n p and for each particle we calculate its sphere equivalent radius by with V and A being the volume or the area of particle i.As a measure for the mean particle size we use the mean radius It should be emphasized that we have to restrict to the very early stages of particle formation, where no sharp interfaces are present, if we use the Cahn-Hilliard equation.So actually we are interested in structures as they appear for example at t = 200 in Fig. 2(d) but since it is hard to define a clear measurement specification in the early stages we pick the particles at transition time as representatives because the structures from earlier times seem to imprint onto them.
Dependence of particle size and transition time on solvent mixing rate
Fig. 3 shows the simulation results for R, l 1 , l max and the transition time t tr as a function of the mixing rate s.l 1 , l max , and R take slightly different values but the progression of their data This journal is © The Royal Society Chemistry 2016 points is the same.All simulation results decrease monotonically in s and show the same asymptotic behavior for large s.
We begin with discussing the asymptotic behavior.Since eqn (7) indicates that the value of the time dependent interaction parameter in the limit of infinitely fast solvent mixing is given by the asymptotes are expected to correspond to the simulation results for an instantaneous quench with constant interaction parameter w max .To check this assumption the corresponding results are represented by the dashed horizontal lines in Fig. 3.
The data points clearly converge to these lines, hence the asymptotes are consistent with the expectations.In our set of eqn ( 7)-( 9), a constant interaction parameter is achieved by substituting eqn (7) by w(t) = w max .Next we define an asymptotic regime and discuss which values of s belong to that regime.The growth of w(t) is cut off when t becomes greater than t max .We call the asymptotic regime the values of s for which the choice of the cutoff affects the simulation results at the transition time.This is clearly the case if t tr exceeds t max .Hence the condition defines the asymptotic regime.The function t max (s) is represented by the dash-dotted line in Fig. 3(d) and (h).It crosses the simulation results for t tr at s E 2 Â 10 À4 -5 Â 10 À4 in both 2D and 3D.The complement of the asymptotic regime is called non-asymptotic regime.The numerical results for particle size in Fig. 3 show a remarkable similarity to the behavior of structure sizes that occur during continuous cooling of an alloy, which was investigated with a perturbation theory long time ago, including a typical scaling law with an exponent À1/6. 32This similarity does not come as a surprise due to the formal relation of the underlying models.We are going to verify the scaling laws in a semi analytical manner and check if the actual values of the data points agree with this theory and not only their qualitative progression.To this end, we first expand eqn (8) in u about the homogeneous ground state with a mean polymer volume fraction % u.After a Fourier transformation in space, we obtain the ordinary differential equations @c m @t ðtÞ ¼ aðk; tÞ Á c mðtÞ; (15) where c m ~are the Fourier coefficients of the perturbation (u( r,t) À % u), and a(k,t) is given by aðk; tÞ
:
Inserting eqn ( 7) and ( 9) into a(k,t) gives We use k* to estimate the particle radius within the linearized theory.The corresponding estimator is which is defined analogously to eqn (11) and (12).The comparison between the numerical results and l* is depicted in Fig. 4. The data points are identical to the data points in Fig. 3(a)-(c) but they are plotted in a different representation, namely versus Dw* := k* 2 instead of s.In this representation, l* becomes which is shown as a straight line in Fig. 4(a).The data points in the asymptotic regime in Fig. 3 collapse onto a single accumulation point at Dw à ¼ lim t tr has a lower bound greater than zero (cf.Fig. 3(d) and (h)).Fig. 4 shows that the prediction for the particle size from the linearized theory, l*, approximates the numerical results with a relative deviation of less than 20%.Regarding our interpretation of l*, l max should be the best approximation and it can be seen from Fig. 4(b) that its deviation is even less than 10%.Hence, we conclude that the perturbation theory yields a good approximation to the numerical results at transition time.The scaling l* p Dw* À0.5 also reminds of the relation between particle size and quench depth for constant interaction parameters, 33,34 which gives Dw* the interpretation of an effective constant quench depth.
To establish a relation between k* and s we plot t tr against Dw* in Fig. 5 and observe that t tr p Dw* À2 , which is also reminiscent of a scaling behavior for constant quench depths.The proportionality can be used to formulate approximate scaling laws for the non-asymptotic regime in Fig. 3. Inserting t tr p Dw* À2 = k* À4 into the case for t tr o t max from eqn (16) yields for t tr o t max .Employing the proportionality (18) into eqn (16) and combining it with definition of l* leads to l* p s À 1 6 (19) for t tr o t max or s o max{s: t tr o t max }.The solid lines in Fig. 3(a)-(c) and (e)-(g) are regression lines to the corresponding data points.Their equations are shown in the diagrams and their exponents deviate about 10% and less from À1/6.Hence, the semi analytical approach verifies the predictions from the perturbation theory.The deviation of the exponents in Fig. 3(d) and (h) from À2/3 in eqn ( 18) is 3.5% and less.Therefore, the scaling behavior of the numerical data in the non-asymptotic regime comes very close to the predicted scaling behavior from eqn (18) and (19).These two equations are independent from % u and N. The parameter w max affects t max and thus the extent of the non-asymptotic regime, but not the simulation results within that regime.Since the only independent parameters in the model other than s are % u, N, w max , the scaling laws in the non-asymptotic regime seem to be an universal feature -at least provided that different choices of % u and N do not destroy the analogy between linearly time dependent and constant interaction parameters.Even though they are not shown in the current publication we performed simulation runs for different parameters and the scaling laws were always observed with the same exponents within an error of 20% and less.Fig. 4 implies that even the actual values of the particles sizes correspond to the perturbation theory.
Reference to experiments
From a practical point of view, the most relevant part in Section 4 is the scaling law l* p s À 1 6 .Batch experiments with drop injection of selective solvent 8 report that the mean vesicle or micelle radius depends on the rate of co-solvent addition according to a power law with an exponent of approximately À0.13.The drop-wise co-solvent addition at a constant rate could imply the applicability of a linear time dependence of the interaction parameter allowing a direct comparison between À0.13 and À1/6, which is a good agreement.In experiments where nanoparticles are produced continuously inside micro mixers 9 it was also observed that the mean particle radius depends on the flow rate according to a power law with an exponent of À0.11, À0.13, or À0.17 depending on the mixer.For a comparison with the micro mixer approach, however, s has to be translated into a flow rate n.Usually, the mixing time (corresponding to t max in our model) is inversely proportional to the Reynolds number and thus, to n. 10 So linear interpolations of the temporal co-solvent volume fraction evolutions in such a mixer show slopes proportional to n.This leads to scaling laws l* p n À 1 6 , which is also in good agreement with the experiments.
To make a more quantitative comparison we calculate mixing times t for different flow rates in the Cater Pillar Micro Mixer with an analytical approach 35 and assume s = (w max À w 0 )t 0 /t, with the time scale t 0 = R g 2 /D defined in the beginning.This leads to where R g 2 and D have SI units and n is given in ml min À1 like in the experiments.The polymer PB 130 PEO 66 possesses a molar mass of M E 10 kg mol À1 . 9Unfortunately, the density for the copolymer was not measured but the homopolymer densities are r PB = 0.96 kg l À1 and r PEO = 1.2 kg l À1 , so we estimated the copolymer density by their mean value, r E 1.08 kg l À1 .The polymer content in the dilute solution was about c = 4 (g polymer) (l solvent) À1 .Basic algebra leads to a mean polymer volume fraction of % u = a/(1 + a) with a = c/r.Using the values above we have % u = 0.004.Both the molar mass and the density of THF is comparable to the molar mass and the density of the monomers PB and PEO, resulting in similar molar volumes.Thus we estimated N = 190 and set D to the diffusion coefficient of THF in water, which is about 10 À9 m 2 s À1 .We substituted the PEO part by PB and estimated R g of the resulting homopolymer from its molar mass M by a relation 36 which is valid for PB in THF and gives R g E 10 nm.
Simulations were performed with % u = 0.004, N = 190 and w max = 16.It should be noted that we Taylor expanded ln(u) in eqn (9) up to 10th order around % u/10 to avoid numerical difficulties caused by large N. Using R g and D as mentioned above we converted R to the nanometer scale and calculated flow rates with eqn (20).The results are shown in Fig. 6.The open symbols are data from the experiments for symmetric flow conditions and the black dots represent our simulation results.CPMM, SIMM, SFIMM denote specific types of micro mixers and A and B refer to different end groups attached to the polymer.The SFIMM and SIMM [37][38][39] are pictured for the sake of completeness -strictly speaking n is the corresponding flow rate in the CPMM.It can be seen that the model is able to reproduce both the scaling law and typical length and time scales of the experiments but it predicts roughly two times smaller particles.This could either be due to the rather rough approximations for D and R g , the application of an implicit solvent model, 40 or the restriction to homopolymers.The final particle size is also influenced by 'technical' issues like the choice of u th , so strict quantitative comparisons should be taken with care.It also should be emphasized that Fig. 6 shows simulation results for homopolymers and experimental data for copolymers, i.e. components of very different composition.
Comparing the experimental data for PB 130 PEO 66 -H (sample A) and PB 130 PEO 66 -CO-CH 2 -CH 2 -COOH (sample B) in the CPMM it can be seen that the composition of the polymer chain significantly shifts the data.
Summary and outlook
We have described nanoparticle precipitation by spinodal decomposition.
The simulations reproduce power laws as well as typical length scales for the size of vesicles and micelles from experiments. 8,9hese scaling laws are also in par with analytical investigations of spinodal decomposition during continuous cooling 32 and our results also agree with more complex particle models for homopolymer precipitation, 20 where similar exponents were observed (EÀ0.17).Thus, the main result of the present article is that the thermodynamic notion of spinodal decomposition is a promising frame to study size controlled flash nanoprecipitation.
Compared to particle models, field theories and especially phase field models require less computation time and grant access to time scales corresponding to mixing times in experiments.Computation time also benefits from the fact that the scaling laws can be investigated in 2D, since 2D and 3D simulations show the same behavior, which allows relatively efficient explorations of parameter spaces.Due to their simple structure even an analytical treatment in the frame of a perturbation theory might be possible.
Scaling laws l p a À 1 6 were also found in a recent publication, which considered the structuring of polymer solutions in the spinodal area upon solvent evaporation, 41 where l is a typical structure size and a a constant evaporation rate.The authors added a as a source term in a Cahn-Hilliard-Cook equation.Within a typical ''Flory-Huggins''-phase diagram with axes % u and w, they advance into the spinodal area in the % u-direction, while we move in the w-direction.The fact that both processes yield the same scaling behavior suggests that the scaling should just depend on the distance to the spinodal line independent of the direction in the % u-w-plane.As far as the comparison between homopolymers and copolymers in Fig. 6 is concerned, a possible interpretation of the similar particle size behavior could be that the co-solvent addition controls the size of the vesicles mainly by determining the size of their micellar predecessors (cf.mechanisms I and II 17,18 ) and that 'population balance effects' like flow induced collision-coagulation and break-up of aggregates in the micro channels might play a minor role, if any.Thus we have also identified one possible mechanism that determines the nanoparticle size in micromixers.
The similar behavior of homopolymer and copolymer particle size might also imply that the principal effect behind size controlled nanoparticle precipitation could be independent of the actual polymer architecture.
In the future, we plan to couple solvent mixing to more sophisticated free energy models, 19,42 which are able to describe copolymers and the vesicle formation process, in order to capture the nanoparticle self-assembly also in the later stages of the aggregation process.Furthermore, it would be interesting to compare simulations for three component systems to our effective two component system and to analyze explicitly how the phase separation process depends on the time-dependent solvent composition.In our study, we have focused on liquid-liquid phase separation, where crystallization and solidification effects can be neglected.Recent experiments on semi-crystalline copolymers 43 have shown that the effect of solvent exchange (in this case, solvent evaporation) on the dynamics is very different if demixing interferes with solidification.For example, the characteristic length scales of the resulting structures no longer depend on the solvent evaporation rate, and the experiments can be described within a model based on homogeneous nucleation theory.In the future, it will also be interesting to consider the competition of liquid-liquid phase separation and solidification in more detail.
Fig. 1
Fig. 1 Time series of the Minkowski measure C (see text) for slopes s = 5 Â 10 À5 (a) and s = 5 Â 10 À3 (b).The time when C reaches its maximum is defined as the transition time.The threshold value u th is set to 0.3.The insets show a magnification of the regions in the dashed rectangles.
Fig. 2
Fig. 2 Spatial distribution of polymer volume fraction u(x,y,t) (color coded) in the domain [0, L b ) 2 at different times t (t = 10, t = 200, and t = t tr ) during spinodal decomposition for s = 5 Â 10 À5 (upper panel: (a), (c), (e)) and s = 5 Â 10 À3 (lower panel: (b), (d), (f)).The transition time t tr depends on s and marks the time at which the behavior crosses over from spinodal decomposition to Ostwald ripening.The color coding is different for every snapshot and chosen such that the smallest value is blue and the largest dark red.
Fig. 3
Fig. 3 Particle size (a-c) and transition time with t max (d) vs. solvent mixing rate s in double logarithmic representation for 2D.Error bars in (b-d) indicate the standard deviation over 5 simulation runs.In (a) the error bars indicate the mean standard deviation of droplet radii within a specific simulation run to indicate polydispersity.The statistical variance of R is similar to l 1 and l max and is not shown.The dashed horizontal lines give simulation results for w(t) = w max and the grey solid lines are regression lines (discussed in Section 4.3).(e-h) Show the same as (a-d) but for 3 dimensions.
Fig. 4
Fig. 4 (a) Characteristic particle size vs. parameter Dw*.The symbols correspond to simulation data shown in Fig. 3(a)-(c), the line represents the prediction of the linear approximation l*.(b) Relative deviation between simulation data and l*.The data for 3D is not shown but looks very similar.
Fig. 5
Fig. 5 Transition times t tr from Fig. 3(d) plotted vs. Dw*.The solid line is a regression line.The simulation results for 3D show a very similar scaling. | 8,537.2 | 2016-08-24T00:00:00.000 | [
"Materials Science"
] |
Development of a Piezoelectric Vacuum Sensing Component for a Wide Pressure Range
In this study, we develop a clamped–clamped beam-type piezoelectric vacuum pressure sensing element. The clamped–clamped piezoelectric beam is composed of a PZT layer and a copper substrate. A pair of electrodes is set near each end. An input voltage is applied to a pair of electrodes to vibrate the piezoelectric beam, and the output voltage is measured at the other pair. Because the viscous forces on the piezoelectric beam vary at different air pressures, the vibration of the beam depends on the vacuum pressure. The developed pressure sensor can sense a wide range of pressure, from 6.5 × 10−6 to 760 Torr. The experimental results showed that the output voltage is inversely proportional to the gas damping ratio, and thus, the vacuum pressure was estimated from the output voltage.
Introduction
Recently, vacuum technology has occupied a key position in diverse fields of advanced science and technology such as surface science, thin film technology, space science, high-energy particle accelerators, microelectronics, and materials science. In addition, vacuum technology has an increasingly wide range of industrial production applications such as product packaging, vacuum casting, vacuum drying, chemical vapor deposition, evaporation, sputtering and dry etching. The vacuum pressure ranges from atmospheric pressure (760 Torr) to ultra-high vacuum pressure (10 −13 Torr). For example, evaporation [1] must be conducted in vacuum pressures from 10 −7 to 10 −5 Torr to increase the evaporation rate and to maintain the purity and density of the film. Sputtering [2] must be conducted in vacuum pressure less than 10 −2 Torr to have deposited thin films which are uniformly distributed on the substrate. The low pressure environment leads to reduction in the frequency of collision of ions with gas molecules, thus increasing the mean free path of the particles. In reactive ion etching [3], the etching operation is carried out at vacuum pressures below 10 −2 Torr to increase directional etching. The low pressure environment leads to reduce the probability of collision of ions and neutral particles. In the electron cyclotron resonance plasma process [4], the operating pressure is controlled at below 10 −4 Torr to achieve high density and uniformity. High density plasma [5] is operated in vacuum pressures from 10 −6 to 10 −2 Torr, which improves the etching rate and enhances the etching direction.
Vacuum covers a wide range of pressures. The mean free path of residual gas molecules is an important parameter that defines the vacuum state, which indicates the average distance travelled by molecules between collisions with each other. In initial stages of evacuation, i.e., at low vacuum, the motion of gas is similar to gas flow. In high vacuum, i.e., as the vacuum pressure is lowered below 10 −3 Torr, the mean free path of residual gas molecules increases, and the motion of gas gradually becomes a molecular motion. For convenience, when discussing vacuum technology, we use different gas motions to distinguish between different vacuum states.
To achieve the vacuum condition, a mechanical pump is initially used to exhaust the gas at atmospheric pressure. This initial state of gas flow is called viscous flow [6] or continuous flow. In this state, the features of gas flow are the mutual collisions between each gas molecule, movement of each gas molecule limited by surrounding molecules, friction between the gas molecules, direction of gas flow, and gas molecules moving in the same direction. As the vacuum system continues the pumping action, the gas pressure continues to decline and the gas flow state becomes transition flow [7]. This gas flow state is very complicated which part of the gas flow maintains the viscous flow state but part of them converts into the molecular flow state. When the gas pressure of the vacuum system is reduced to a certain level, the gas flow state reaches the molecular flow range [8]. In this state, gas molecules have free random motion. The collisions are elastic and consistent with the conservation of kinetic energy and momentum conservation law. The probability of a gas molecule colliding with the chamber wall is greater than the probability of it colliding with another gas molecule. Regardless of how low the pressure is, the flow state maintains molecular flow once the flow conditions in the vacuum system reach the molecular flow range.
According to the operating principle, the vacuum gauges can be distinguished as absolute vacuum gauges and relative vacuum gauges. The operating principle of an absolute vacuum gauge involves the direct measurement of the forces on the unit area. The measurement principle of a relative vacuum gauge involves the use of the relationship between gas pressure and certain physical quantities. For example, the pressure can be obtained by thermal conduction [9][10][11][12][13][14]. Moreover, the pressure also can be measured by gas-molecule ionization technology indirectly [15][16][17].
The abovementioned gauges include the diaphragm gauge [18][19][20][21][22], thermal conductivity vacuum gauge, ion vacuum gauge, and viscosity vacuum gauge [23]. The operating principle of the diaphragm gauge involves the measurement of the capacitance change caused by deformation of a film surface by pressure. The pressure value can be estimated based on the capacitance change. The operating principle of the thermal conductivity vacuum gauge involves the use of heat transfer from the objects heated by gas collision. Heat conduction is proportional to the frequency of gas molecule collisions with the objects. Therefore, the vacuum pressure is proportional to the heat conduction, enabling the estimation of pressure. The operating principle of the ion vacuum gauge involves the measurement of the number of molecules in the vacuum system to determine the pressure. The operating principle of the viscosity vacuum gauge involves the use of the viscosity characteristics of residual gas in the vacuum system to determine the pressure. The spinning rotor viscosity vacuum gauge [24,25] can be used to measure vacuum pressure ranges between 10 −1 and 10 −7 Torr. Gas viscosity caused by gas resistance is proportional to the degree of vacuum.
Based on existing literature, there are just few vacuum gauges that can measure the entire pressure range from 10 −7 to 10 −2 Torr. Current spinning rotor viscosity vacuum gauges can measure vacuum pressure ranges of 10 −7 -10 −1 Torr. Due to the presence of several components such as the ball and control coil, spinning rotor viscosity vacuum gauges increases the volume, weight, and complexity of the system, thus limiting their applications. Mortet et al. [26] used a commercially available piezoelectric bimorph cantilever as pressure sensor which detected the change in the resonance frequencies due to the drag force of the surrounding gas. Sumali et al. [25] used a bulk piezoelectric transducer shook the whole chip on which an atomic force microscope probe mounted. A laser Doppler vibrometer (LDV) with a microscope measured the velocities at a point on the chip, and 42 points along the edges and tip of the cantilever. They stressed that the air damping is proportional to pressure in the rarefied regime. Wang et al. [27] developed a micro-cantilever beam deflected using electrostatic force. They measured the capacitance between two electrodes which were mounted around the proof mass of the trapezoidal micro-cantilever beam and a sensing electrode was placed on top of the proof mass with the deflection electrode mounted beneath to determine the free decay rate of the sensing beam with respect to deflection force and vacuum pressure. However, those devices still need additional actuators to drive the element and outside sensing devices to convert deflection of beams to electrical signals. Outside sensing devices make the measurement system complex.
In this study, we designed a self-actuated and self-sensing piezoelectric pressure sensor. The piezoelectric sensors are in the form of clamped-clamped beams. The sensor was designed using two piezoelectric elements: for self-actuating and self-sensing. Applying voltage to the PZT self-actuating element causes deformation of the clamped-clamped beams. At the other end of the beam, the PZT self-sensing element produces a voltage caused by the bending of the beam. Under different vacuum pressure values, the gas viscosity and the damping ratio of devices are different. This causes different swing amplitudes and resonant frequencies of the device and results to different output voltages and resonant frequencies from the sensing element. Thus, the vacuum pressure can be calibrated. The advantages of developed vacuum sensor are self-actuating and self-sensing without additional actuators and outside sensing elements. The wide range vacuum pressure from 6.5 × 10 −6 to 760 Torr can be directly derived from piezoelectric output. Fabrication of developed vacuum sensors was easy because of simple structure.
This study has three specific goals. First, a piezoelectric pressure sensing element was developed that can be used to measure a wide range of vacuum pressure from 6.5 × 10 −6 to 760 Torr. Second, the size of sensing element was 20 mm length, 5 mm width and 200 µm thick. Compared to commercial pressure sensors, the piezoelectric pressure sensors have the following advantages such as small size, low weight and simple instrumentation. Finally, the sensing elements were used to measure the pressure in nitrogen and argon to study the relationship between vacuum pressures and damping ratios of different gases.
Principle of Operation
This study proposes the clamped-clamped beam-type piezoelectric vacuum pressure sensing element, a self-actuating and self-sensing microresonator, to detect the damping ratio of the gas, thus enabling the calculation of the pressure of vacuum system. The schematic diagram of the vacuum pressure sensing element is shown in Figure 1. The sensing element comprises a PZT layer, a substrate, and two pairs of electrodes. The electrodes are placed near both ends for piezoelectric actuation and sensing. When the sinusoidal voltage signal is applied to a pair of electrodes, due to the inverse piezoelectric effect, the clamped-clamped beam vibrates and resonates. Simultaneously, the other pair of electrodes captures the vibration energy and converts it to electric energy using the positive piezoelectric effect. Finally, we measured the output voltages which varied under different gases viscosity and vacuum pressures.
Choice of Component Materials
The piezoelectric sensor consists of a piezoelectric layer and a substrate. We choose PZT-5A as the piezoelectric layer and copper as the substrate. PZT-5A has a high piezoelectric constant and electromechanical coupling constant, and the energy consumption is small for conversion between mechanical energy and electrical energy. Copper has a low Young's modulus and high electrical conductivity and can reduce the operating frequency. On the other hand, it can facilitate current conduction.
Component Size Design
The Euler-Bernoulli beam theory is the basis of assumptions to establish the mathematical model and is used to determine the size of the vacuum pressure sensing element. The force conservative equation is given as follows: where YI is the bending stiffness of the composite beam, indicating the resistance of the bending moment; w(x,t) is the cantilever deflection function, which is the neutral axis of the lateral displacement of each section (y-direction is positive); csI is the equivalent damping term due to the viscosity of the combination cross section, where cs is the strain damping coefficient and I is the second moment of inertia for the combination of the cross section between the piezoelectric layer and substrate; ca is the air damping coefficient; m is the mass per unit length; and α is the piezoelectric coupling term. vin (t) and vout (t) are the input and output voltages, respectively. This cantilever piezoelectric sensing element contains two pairs of electrodes. The position of the input electrode ranges from x = 0 to x = x1, and that of the output electrode ranges from x = x2 to x = L. Only the electric field is generated in the electrode coverage. We assume that the operation of the piezoelectric sensor considers only the influence of resonance frequency (first mode). Therefore, the ratio of the output voltage to the input voltage from the mathematical model can be written as follows [28]: where ω is the first resonance frequency of the cantilever, τc is the time constant of the output circuit, λ1 is the integrating factor, and ξ is the damping term in the modal coordinate functions. This damping term can be shown as Equation (3), and it combines the effect of air damping and structural damping: To reduce the sensor size in practical applications, the cantilever length and breadth are set as 20 and 5 mm, respectively, and the piezoelectric sheet thickness is set as 200 μm.
Electrode Design of Sensor
The two pairs of electrodes are distributed on the upper and lower surfaces of the piezoelectric material layer, which are placed on both ends of the cantilever. One pair of electrodes is placed beside the fixed boundary in the cantilever as an actuator to drive the cantilever and generate resonance. The other pair of electrodes is placed on the other side of the fixed boundary as a sensor to acquire the vibration energy and convert voltage signals, as shown in Figure 2. The electrode size is determined by the force conservative equation, thus leading to two designs. First, when the input electrode is close to the fixed end and has a length of 4.4 mm, the actuator can generate maximum power. Second, when the output electrode is close to the fixed end and has a shorter length, a larger open circuit output voltage is obtained. In our previous study, output voltages as high as twice the input voltages have been reported [29]. To obtain maximum power, we determine the length of the input and output electrodes to be 4.4 mm. The width and thickness of the electrodes were 5 mm and 10 μm, respectively. The upper electrode is fabricated using screen-printed silver.
Design and Production of Fixtures
To allow the sensor to maintain the same boundary conditions during each measurement, we designed a fixture that can keep the cantilever beam fixed at both ends. The fixture contains two parts: upper cover and base. The upper cover has two holes for electrical wires. The clamped-clamped piezoelectric beam is placed in a trench in the base. Four M2 screws were used to fix the upper cover and the base which is shown in Figure 3. The fixture is made by transparent acrylic material which has advantages such as low density, high mechanical strength, good tensile and impact resistance, high transparency, low cost, and ease of machining.
Laboratory Equipment and Experimental Setup
The vacuum system consists of a stainless steel vacuum chamber, a mechanical pump, a turbo molecular pump, a gas flow controller and reference vacuum gauges. A mechanical pump (DOU 16B Balzers, Albuquerque, NM, USA) was first used to exhaust the gas at atmospheric pressure to achieve vacuum condition. When pressure was down to 10 −2 Torr, a turbomolecular pump (Turbo VAC 450, Leybold, Cologne, Germany) was then used to obtain high vacuum (10 −2 to 6.5 × 10 −6 Torr). However, it might take more than 24 h to achieve 1 × 10 −6 Torr using our pumping system. To reach certain pressure accurately, a gas flow controller was used to flow certain amount of nitrogen or argon into chamber. Two reference vacuum gauges, Pirani gauge and cold cathode gauge, were used. Pirani gauge is able to measure the pressure between 760 to 10 −3 Torr and cold cathode gauge is capable to measure the pressure between 10 −2 to 10 −9 Torr.
The experimental setup is shown in Figure 4. The clamped-clamped piezoelectric pressure sensor was fixed by the fixture and was placed in the vacuum chamber. Electrical feedthroughs were used to transfer electrical signals through the vacuum system wall. A sine wave was generated by a function generator (33220A, Agilent, Santa Rosa, CA 95403-1738, USA) and amplified by a power amplifier (PZD700, TREK, Lockport, NY, USA) to excite the piezoelectric beam at first resonance frequency. At the mean time, a spectrum analyzer (Agilent 35670A) was used to measure the frequency response of input and output voltages.
Frequency Response under Different Pressures
Frequency response functions were obtained by the following steps. The spectrum analyzer generated a swept-sine signal to drive a pair of electrodes through an amplifier. In the meantime, the other pair of electrodes generated electric output. Both the swept-sine signal and the output voltage were fed back to the spectrum analyzer to calculate the frequency response function. To maximum sensor output, the piezoelectric beams were excited at the first resonance frequencies under different pressures condition in the following experiments. The data from measured frequency response functions were processed to extract damping ratios using half power method. Figure 5 shows the frequency response functions of a clamped-clamped piezoelectric beam under different pressures when the residue gas in the vacuum chamber is nitrogen. The clamped-clamped piezoelectric beams have maximum output and input ratio when the beams were excited at resonance frequencies. The resonance frequencies of the piezoelectric beam under the vacuum pressures at 5 × 10 −6 , 7.5 × 10 −4 , 1 and 75 Torr were 3100, 3067, 3038 and 3030 Hz, respectively. When the pressures in the vacuum chamber decreased, the resonance frequencies and the resonance amplitudes of beam decreased because the damping coefficient of gas increased. The difference of first resonance frequencies of the vacuum sensor between 75 torr and 5 × 10 −6 torr was just 2.25% (70 Hz) because of tiny damping variation. The resonance amplitude, output and input voltage ratio, were 0.0063, 0.0059, 0.0052 and 0.0032, respectively, when the pressures were 5 × 10 −6 , 7.5 × 10 −4 , 1 and 75 Torr. Figure 6 showed the resonance amplitudes (Vout/Vin) versus the vacuum pressures in the chambers when the residue gas is nitrogen. Each operating frequency corresponding to the maximum amplitude values is applied in different vacuum pressure. In the experimental results, each pressure value corresponds to a piezoelectric output ratio. The vacuum pressure from 6.5 × 10 −6 to 760 Torr can be directly derived from piezoelectric output ratio. Note that each experiments corresponding to different pressures were repeated 10 times. Finally, the average values of output voltage were reported. The data have been plotted on a log-log plot to show the extreme range of both the measured maximum amplitude and imposed air pressure. All the experimental results appear to have the same general trend, showing decreasing damping values with decreasing pressure. Clearly these experimental results 75 Torr 1 Torr 7.5E-4 Torr 5.0E-5 Torr support both the rarefied and the viscous theories. The pressure in the vacuum region is divided into three ranges for further analysis. Vacuum pressure below 10 −3 Torr belonging to molecular flow is known as high vacuum; vacuum pressure in the range 10 −3 -1 Torr belonging to transition flow is known as medium vacuum; vacuum pressure greater than 1 Torr belonging to viscous flow is known as low vacuum. We use the linear regression method to deal with the results of each segment to obtain the best linear data. After processing, each line segment will be discussed. Pandey et al. [29] reported a paper to discuss effect of pressure on fluid damping in MEMS torsional resonators with flow ranging from continuum to molecular regime. Their results also indicated that the quality factors of devices varied in different flow regions. pressure curve in the viscous flow region is greater than that in the transition flow region, while the slope in the transition flow region is greater than that in the molecular flow region. From this result, we infer that the gas viscosity force of viscous flow is greater than the other two flows. Also, the force due to change in gas viscosity for viscous flow is more obvious than that for transition flow and molecular flow. Therefore, the change in the piezoelectric output ratio is the most obvious in viscous flow. However, fitting in three regions may not be the best solution. It also looked that the data in the molecular flow and transition flow region could be fitted with one straight line instead of two. The slopes of the voltage vs. pressure from 5 × 10 −6 to 1 torr is y = −0.00022x + 0.0053 and R² = 0.924. The slopes of the voltage vs. pressure from 1 to 750 torr is y = −0.0007x + 0.0054 and R² = 0.971.
Relationship between Pressure and Damping Ratio
The data from measured frequency response functions in the previous experiments were processed to extract damping ratios using half power method. After processing, we obtain the damping ratio corresponding to the respective pressure. Figure 7 showed that the damping ratios versus the vacuum pressures in the chamber when the residue gas is nitrogen. The slopes of the damping ratios vs. pressure in the viscous flow region is y = 0.0009x + 0.0206 and R² = 0.957. The slopes of the damping ratios vs. pressure in the transition flow region is y = 0.0018x + 0.0226 and R² = 0.8574. The slopes of the damping ratios vs. pressure in the molecular flow region is y = 0.0042x + 0.0225 and R² = 0.9592. However, fitting in three regions may not be the best solution. It also looked that the data in the molecular flow and transition flow region could be fitted with one straight line instead of two. The slopes of the voltage vs. pressure from 5 × 10 −6 to 1 torr is y = 0.0013x + 0.0216 and R² = 0.916. The measured damping ratio is the sum of structural damping and gas damping. Experimental results showed that the greater the quantity of residual gas in the vacuum chamber, the larger is the damping effect for the sensing element caused by the residual gas. Greater pressure indicates a larger number of gas molecules in the vacuum chamber. Therefore, there is a greater probability of collisions between gas molecules and piezoelectric beam; this situation increases the gas damping effect for the sensing element when the pressure increases. When the residual gas in the vacuum chamber was rarer, small damping effects for the sensing element were obtained experimentally. Figure 8 shows the resonance amplitudes (Vout/Vin) versus the vacuum pressures in the chambers when the residue gases are nitrogen and argon. However, the resonance amplitudes of the sensing element in the argon were just performed in the vacuum pressure from 6.5 × 10 −6 to 1 Torr due to the limitation of the gas flow controller. We find that the output result has similar trends for both nitrogen and argon in the vacuum pressure from 6.5 × 10 −6 to 1 Torr. The output value changes marginally. Under the same pressure, the output value of nitrogen is larger than that of argon. We can conclude that the vibration of the cantilever beam affected by the viscous force caused by argon is larger than that caused by nitrogen. The mass of argon (39.948 amu) is larger than that of nitrogen (28 amu). The resistance force of the molecular collision of argon is larger than that of nitrogen. Each experimental corresponding to different pressures under Nitrogen and Argon was repeated 10 times and the average values of output voltage were reported. Experimental results were consistent if that boundary condition remained the same. Pressure measurement was taken after observing the steady state condition to prevent measurement errors. However, the duration of steady state condition varies for the flow in the continuous region to the flow in the molecular region. One of the samples was leaved in the vacuum chamber for 3 months and there were no significant difference even the sample was driven for a long time. However, there still need further research to study the consistency and stability of the system. There also still need further research to study the different gases to verify the consistency and stability of the system.
Conclusions
In this study, we developed a clamped-clamped beam-type piezoelectric vacuum pressure sensor. The sensor was designed using two piezoelectric elements: for actuating and sensing. Applying voltage to the PZT actuating element causes deformation of the cantilever. At the other end of the beam, the PZT sensing element produces a voltage caused by the bending of the beam. The piezoelectric pressure sensing element was developed that can be used to measure a wide range of vacuum pressure from 5 × 10 −6 to 760 Torr. From low to high vacuum, the output and input voltage ratio (Vout/Vin) gradually increased with decrease in pressure. The relationship between vacuum pressure and damping ratio was obtained for pressure from 5 × 10 −6 to 760 Torr. In high vacuum, the damping ratio is less than that in low vacuum. Finally, the sensing elements were used to measure the pressure in nitrogen and argon to study the relationship between vacuum pressures and damping ratios of different gases. Comparison of the output voltage ratios in argon and nitrogen showed that the damping ratios follow the same trend as the vacuum pressure. The damping ratio of argon is greater than that of nitrogen because the mass of argon is larger. | 5,804.4 | 2014-11-01T00:00:00.000 | [
"Engineering",
"Physics"
] |
GM ethical decision making in practice
Celia Dean-Drummond’s case for wisdom as an approach to ethical decision making and her doubts about case-oriented methodology are critiqued with reference to the SRT Project’s Engineering Genesis study. Its approach is explored in practical decisions on various real life examples of genetic modification in crops and animals. It involved both intrinsic and consequential approaches, and identified key value positions behind different policies and stakeholders. The paper also clarifies the relationship between reactive (cost-benefit) and precautionary risk assessment, explaining their strengths and limitations, and the role of underlying values in both forms of risk decision making. Resale or republication not permitted without written consent of the publisher
The Society, Religion and Technology Project (SRT) of the Church of Scotland has for a decade sought to offer more nuanced and in depth insights into the GM debate than much of the polarised and confrontational portrayals in the political and media arenas.Its Engineering Genesis study (Bruce & Bruce 1998) was a landmark in bringing together the differing perspectives from experts in a wide variety of disciplines in extended discussion over 5 years.
The plural nature of this an enquiry implied a bottom-up, case-oriented approach.It applied a set of standard ethical questions to eleven case studies.These were then examined in more depth in the light of the different professional insights and value perspectives of members of the group.The study was careful to take into account both intrinsic and consequential ethical issues, and value-based and instrumental rationalities.It was critical of an implicit orthodoxy of consequentialism in Government, academia and industry which was apt to dismiss principled ethical concerns, or even to regard them as irrational.For example, the ethical method taken by the Nuffield study evidently found it difficult to take intrinsic concerns seriously (Nuffield Council on Bioethics 1999).
The long timescale allowed a thorough exposure of different technologies to the varying perspectives and experiences represented by the group.It also helped build trust and mutual listening, which greatly added to the quality of the critical discourse.In so doing we encountered many of the difficulties of public decisionmaking on biotechnology in a context of considerable differences in knowledge, opinions, interests and underlying values.
In her paper Celia Deane-Drummond (2002, this ESEP Theme Section) addresses the role of wisdom in relation to ethical issues of genetic modification and risk.She offers many useful insights into the theological background of the nature of wisdom and especially its exposition in the natural law tradition of Thomas Aquinas.She suggests this as a more convincing grounding for virtue ethics than some contemporary approaches, and discusses some important and helpful criteria.Her focus on the agent before the issue is refreshing in its challenge to policy makers to examine their own attitudes.Perhaps the most telling critique of genetic modification has been not so much of the technology itself, as the unspoken values, tacit visions and vested interests of the principal actors in its development, which lost sight of the values of the wider public (Bruce & Bruce 1998: 178-186, ESRC Global Environmental Change Programme 1999).
ABSTRACT: Celia Dean-Drummond's case for wisdom as an approach to ethical decision making and her doubts about case-oriented methodology are critiqued with reference to the SRT Project's Engineering Genesis study.Its approach is explored in practical decisions on various real life examples of genetic modification in crops and animals.It involved both intrinsic and consequential approaches, and identified key value positions behind different policies and stakeholders.The paper also clarifies the relationship between reactive (cost-benefit) and precautionary risk assessment, explaining their strengths and limitations, and the role of underlying values in both forms of risk decision making.
Resale or republication not permitted without written consent of the publisher
Deane-Drummond is critical of approaches based on particular cases, seeing these as tending to assume a consequentialist approach to ethics.She regards these as unhelpful, given the uncertainties involved in the issues.SRT's case-oriented study would, however, challenge this assertion by its use of intrinsic methods, and also questions whether wisdom as such comes close enough to practical decision making about particular GM issues.
EVALUATING GM CROP DECISIONS
Would such wisdom have made any difference if it had been applied in the mid-1990s when seminal decisions about GM crops and products were being made in the UK? Experience of the real world of policy making in both public and private sectors suggests that other factors usually frustrate and override ethical good intentions.In reality the virtuous agent may be constrained by a company's ethos, Government policy, or the mandate given to a particular regulatory or advisory body.Wisdom at a corporate level is framed according to the dominant values of the corporation.Thus in the view of the UK Government of the early 1990s, GM crops were good for growth and competitivity and needed to be promoted.Regulations should be relaxed.Doubts and opposition were largely dismissed (House of Lords 1993).The brief given by the Ministry of Agriculture to the original advisory committee on GM food ethics explicitly excluded the examination of underlying issues of genetic modification of crop applications, which were presumed to raise no issues worthy of consideration.The regulatory bodies on GM releases and novel foods were obliged to evaluate risks primarily on an evidential basis which marginalised other ethical considerations.Scientific rationality elevated the notion of the 'substantial equivalence' of GM and non-GM products in chemical terms out of its proper scientific context into a philosophical dogma.If chemical equivalence was established, ethical concerns were of no consequence.
Decisions at a company level reveal strikingly different values applied to wisdom.Zeneca consulted about how to market their tomato paste in the mid-1990s, the first main GM food product in the United Kingdom.It was given what would now be seen as wise advice to label the tins as containing a GM component, in view of possible public sensitivities, even though the prevailing regulations did not oblige it to do so.The company took this advice and the labelled GM paste sold fairly well.Zeneca urged Monsanto to do the same when the US corporation planned to import GM soya into Britain.This did not fit Monsanto's approach, which saw the market for the product as the farmer, not the consumer.Since the product had passed the regulatory requirements, people would buy whatever they were given.What was good enough for mid-western USA was good enough for Europe.It did not occur to their view of the world that the general public might object to having no choice over a product which carried perceived risks and no tangible consumer benefits.
DOES WISDOM BRING US CLOSE ENOUGH TO THE ISSUES?
Monsanto's action has now become a byword in corporate folly.The Government's neglect of warnings to take account of public values over genetic modification is similarly seen as an archetypal failure of wise governance of science (House of Lords 2000).Yet government ministers, regulators and corporate executives no doubt thought their actions wise.Wisdom can be conceived in many different terms depending on the societal context and ethical values of the particular actor.In complex public policy situations such as these, the question behind wisdom is 'Wise, in which (or whose) terms?'Of itself, it is doubtful whether wisdom would have been close enough to the issues for real environmental or biotechnological decision making.This suggests that to be useful in practical decision making over biotechnology, wisdom needs considerable unpacking.It needs to be considered in terms of various underlying values which inform what each stakeholder regards wisdom to be.
This leads to much the same set of questions faced by the Engineering Genesis study, in selecting among ethical and social values.A Christian understanding of the issues would require a full orbed consideration of all relevant criteria, above and beyond those of a dominant elite who makes the decisions.Wisdom is just one factor amongst others.It could be used to assess the decision of Monsanto to begin their promotion of GM products with agronomic traits which offered no tangible benefits to consumers, and to apply these to commodity crops used so widely in food processing that GM-derived ingredients would be present in a wide variety of foodstuffs.In a market known to be sensitive to the idea of GM food, wisdom would have held back on these applications, and focused on easily segregated products with nutritional or health advantages which consumers could choose or avoid.Wisdom would have been less useful in evaluating Zeneca's decision to develop a GM tomato paste.It did not serve any very useful purpose other than reducing cost and possibly improving flavour, but neither did it raise serious problems.Wisdom may perhaps be better as a mode of critique than as a positive evaluation of innovation.
Faced with the sorts of mind sets, policies and power interests described above, one suspects the application of wisdom would not have made much difference, because one was not dealing with wise agents.SRT's case-oriented evaluation found that wider value perspectives were often marginalised by certain dominant modes of thinking, social contexts and vested interests.Its cross-disciplinary stakeholder approach also offers a potential model for enabling different groups to listen to viewpoints they had previously dismissed.
RISK, COST-BENEFIT AND PRECAUTION
Deane-Drummond ( 2002) makes a strong critique of risk-benefit approaches to decision making, on the grounds of the uncertainties involved, because the risks are usually unknown or unquantified and also because precaution needs disentangling from costbenefit approaches.This critique goes too far.Certain aspects of genetic modification are indeed subject to unknowns, by the nature of a new technology.Other areas of biotechnology such as pesticide risk have, however, been the subject of extensive risk assessment over several decades, and have amassed a very large body of data.These represent, respectively, the difference between precautionary principle and reactive or calculative models of risk regulation, which are bound in a complex relationship (Bruce et al. 1996).
In the case of pesticide use, the risks are relatively well understood and quantified, so that meaningful assessments and comparisons can be made.One is still faced with a value judgement about what constitutes acceptable risk.Suppose a calculations shows a particular risk to be 1 in 10 000, what does this mean?The mere number does not tell us whether a risk of this magnitude is acceptable or not.To do so requires an ethical judgement, which must take into account much wider issues than the calculated magnitude and frequency of risk.In cases where the data are reliable enough, once such an ethical judgement has been made, a calculation of like risks is a valid way of assessment.
The precautionary principle comes into play where reliable data are insufficient or do not exist, and is thus a quite different mode of risk assessment.It is not quantitative, and draws upon a much wider set of ethical values, against which to assess the seriousness of the hazard, were it to be real (Bruce & Bruce 1998:198-201, Chevassus-au-Louis 2000).Confusion often arises in the circumstances in which one may switch from one approach to the other.Sometimes a new risk emerges which requires precaution to be taken in a previously well established risk.Thus, in the area of organ transplantation a new hazard was identified of retro-virus transmission from pigs if animal organs were to be used.A moratorium was called by the Government.Unless and until data become available to clarify this risk, precaution is the appropriate course.
On the other hand, precaution was the initial regulatory approach to genetic modification research in the 1970s.Eventually, it was felt that sufficient data had been obtained to establish criteria for different levels of hazard and measures for appropriate containment or release.The mistake made in the 1990s UK evaluation of GM crops was to assume that substantial equivalence constituted closure for GM food risks, and that it was the only question which needed to be answered.As far as it goes, there is some logic in the notion that, if there is no scientifically detectable difference between a crop derived from genetic modification and one that is not, then their risks are equivalent.But in this case, wider value concerns surrounding the risk were sidelined by decision makers.They also presumed that all the necessary risks had been taken into account.A precautionary approach ought to have been maintained over emerging biodiversity concerns, for example.
Political pressures to defend its case on various agricultural trade issues from hostile US criticism led the European Commission to present the precautionary principle as a temporary expedient to be used in the course of a quantified cost-benefit risk assessment (European Commission 2000).It did not provide criteria against which to decide that grounds existed to apply precaution.It also presumed that the uncertainties would eventually be resolvable, which is not always the case.Where they cannot be, precaution is still needed.
The current evaluation of field scale GM crop trials in the UK provides a good example of this.Some are looking to these to supply a science-based closure on the risks.It seems likely that the trials will not provide closure, because, by the very nature of the question, it would take much longer to establish the basic ecological and soil characterisations to make long-term comparisons.They will probably provide some indications but much residual uncertainty.Ethical and value aspects will play a large part in assessing whether the results are acceptable to allow commercial crops to be sown, or to continue the de facto moratorium while further trials are conducted, or to abandon the idea of growing GM crops in the UK.
The first option would judge that the evidence obtained to date had not shown a likelihood of an obvious and serious risk to health or ecology, and would point to the fact that large numbers of crops were being grown and consumed in some other parts of the world with no apparent serious ill-effects.The second would judge that the risks had not so far been clarified enough to warrant proceeding, but that the trials themselves did not pose an unacceptable risk.The third position would judge unusually that no prospect existed of ever resolving the uncertainties, or that the indications already showed risks that were deemed unacceptable.A crucial factor in such assessments is the constructions put and value judgements made concerning the notion of genetic 'contamination'.For some the mere fact of unintended gene flow constitutes grounds to stop the technology.For others, it would only represent a limit if it led to some significant ecological or social damage (Bruce & Eldridge 2000).A 4th conclusion is that the basic idea of genetic modification was flawed in the first place, or that the goals intended were not worth having, or that better ways existed to achieve them.This may be related to inherent objections or to risk or to social factors.
The above examples are given to illustrate the complexity of the relationships between evidence based and precautionary judgements of biotechnology risk.They both have their place, and both involve decisions based on ethical values.As with the case of the other GM crops decisions discussed earlier, wisdom is indeed a prerequisite for such decisions, but it is the beginning of the story, not the end. | 3,470.6 | 2002-09-01T00:00:00.000 | [
"Environmental Science",
"Philosophy"
] |
Maximum Power Transfer versus Efficiency in Mid-Range Wireless Power Transfer Systems
The condition for maximum power transfer of 2-coi ls wireless power transfer (WPT) system is derived fro m circuit analysis and discussed together with the respective WPT system efficiency (η). In the sequence, it is shown that a 4-coils WPT system (which can be divided in source, two communi cation and load circuits) without power losses at the two communication circuits (ideal 4-coils WPT system) presents, from maximum power transfer and efficiency point of view, a performance similar to those of a 2-coils WPT system. The exception is the influ ence of coupling coefficient (k): in 2-coils system η increases as k approaches one, while in ideal 4-coils WPT system η increases as k between the two communication coils approaches zero. In addition, r ealistic 4-coils WPT systems (with power losses at the two communica tion circuits) are also analyzed showing, for instance, that η presents a maximum as a function of k of the communication coils. In order to validate the presented theory, 4 coils were built, and a set up to perform 2coils and 4-coils WPT systems has been carried out. Practical results show good agreement with the developed theo ry.
Fig. 1 shows the equivalent circuit of a 2-coils WPT system.Considering both circuits tuned at the same resonance angular frequency ( = = ), it can be written and where, M12 is the mutual inductance, R1 the total transmitting circuit resistance (including the internal resistances of the source and those of the involved capacitance (C1) and inductance (L1)), and R2 the total receiving circuit resistance (the sum of internal resistances of the involved capacitance (C2) and inductance (L2) -r2-with the load resistance (RL)).
Electric power is calculated multiplying the resistance by the square of the current amplitude so that using (1) and (2) it can be written = and where, P1 and P2 are the electric power dissipated at R1 and R2, respectively.
Taking the derivative of (4) with respect to M12 and making the result equal to zero, after manipulation, yields = This is the MPT condition for a 2-coils WPT system.(That ( 5) is a condition of maximum can be demonstrated making the second derivative of (4) with respect to M12 equal to zero.)Moreover, using 3) and ( 4) it leads to = = .(6) as classical MPT theorem teaches.
For comparison purposes it is interesting to compute the relative power transferred to R2 dividing (4) by ( 6) which gives Dividing the power transferred to R2 (P2) by the total power (P1+P2), the transmission efficiency (%) can be calculate yielding Note that, as also the classical MPT theorem teaches, using ( 5) in (8) gives % =1/2.
B. 4-Coils Circuit
Figure 2 shows the equivalent circuit of a 4-coils WPT system.
where; M12, M23 and M34 are the mutual inductances, and R1, R2, R3 and R4 the total individual circuits resistances.Note that R4 is, in fact, the sum of internal resistances of the involved capacitance (C4) and inductance (L4) -r4 -with the load resistance (RL).
Taking the derivative of (18), also using 2-coils WPT system as a guide, with respect to k23 (M23 would be more general [8] but in 4-coils WPT system L2 and L3 appears in M12 and M34 and in (18) they had been simplified) and making the result equal to zero yields This is the MPT condition for 4-coils WPT system without power losses at the communication circuits.Note that using (19) in ( 17) and ( 18) gives as classical MPT theorem teaches.
The system efficiency (%), also with R2=R3=0, can be defined as Observe that, in case of R2=R3=0, (23) and ( 24) become ( 21) and ( 22), respectively.Moreover, it can be seen that ( 23) and ( 24), due to their format, present a maximum.Thus, taking the derivative of them with respect to k23 (as mentioned before, M23 would be more general [7] but in 4-coils WPT system L2 and L3 appears also in M12 and M34) and making the results equal to zero yields Observe that (25) and (26) show that the points of maximum of (23) and ( 24) are not coincident.In addition, note that in case of R2=R3=0 (25) becomes (19), and (26) does not present a meaning anymore, i.e., η does not have (in sense of derivative zero) a point of maximum.Finally, substituting (25) in ( 23) and ( 26) in (24) it can be seen that the maximum in (23) and ( 24) is always, as expected, less than one.
III. EXPERIMENTAL VALIDATION For practical evaluation of the analysis presented in the previous section, a set of 4 coils, with equal dimensions and shape, was constructed.The coils are circular with diameter of 150 mm and 20 mm of length, wound with 22 turns of enameled copper 19 AWG wire in a single layer way.The coils selfinductances have a similar measured value of 127 µH in the range of 10 to 800 kHz.All measurements of inductances, capacitances, resistances, and resonance frequencies were obtained using an Agilent precision vector impedance analyzer (4294A).
Since the presented analysis has a strong dependence on the coupling coefficient k, at first, considering coaxial coils, the practical behavior of k in function of distance was determined.For this, 102 it has been used a Tektronix signal generator CFG253 to excite one coil, as primary, at a low frequency of 10 kHz, to reduce the influence of the coils´ stray capacitances.Using an Agilent digital oscilloscope MSO6034, the voltages were measured in the primary (v1) and in the open terminals of the secondary coil (v2), while the distance between the coils was varied.Since the current in secondary coil is zero, v1 = .: :; ⁄ and v2 = .: :; ⁄ .As the inductances are equal (L1=L2=L), then 1 = / , after little manipulation it gives 1 = ⁄ .Fig. 3 shows the measured coupling coefficient in a range of 2 to 32 cm (the distances are considered between the closer first turns).To achieve the same resonant frequency at four coils, precision capacitors of 560 pF were used.In fact, in a set of 20 capacitors, 4 were selected by measuring their capacitances (all around 575 pF).It is important to note that even using precision capacitors, each capacitor was chosen specifically for each coil´s inductance, since the inductances also have small variations.In this way, it was possible to select the resonant frequency of 589 kHz with a precision of 100 Hz for the 4 coils.After tuning, the total internal series resistances RS of the LC circuit, at the resonant frequency of 589 kHz, were measured, resulting in similar values of 3.3 Ω.
To measure the relative power transfer and efficiency, it is necessary to know the currents in coil 1 and in the load.In this way, a shunt resistor (R0) of 10 Ω was used in series with coil 1 in all the measurements (the measured resistance value was 9.85 Ω at 589 kHz).Three different loads (Rl) values were used 10, 50, and 100 Ω (exact values of 9.85, 49.7 and 100.24Ω).All resistor presented measured stray inductances of 40 nH at 589 kHz.
A voltage signal (vG) of 7.7 VRMS with 589 kHz was applied on coil 1.To confirm that the resonant frequency has not been changed by external influences of the setup, such as cable capacitances and others, the resonant frequency was confirmed by measuring a minimum voltage point over the RLC 105 Fig. 7. Relative power (P2/P2MAX) as function of distance between coils (for 2-coils set).Dots are measured values for loads of 10, 50, and 100 Ω (R2 total of 13.15, 53, and 103.54 Ω, respectively).Solid curves are calculated using (7).
However, the resistances R2 and R3 are not external resistors, so P2 and P3 could not be measured directly.Thus, considering that all the power, delivered by the generator PG, is dissipated by ohmic losses, the efficiency can be alternatively calculated by PL/PG, where PG = vG⋅i1.Theoretical values are calculated using (23) and (24).
Several different coils arrangements can be conducted with 4-coils WPT systems.Here two approaches are presented.First, it was imposed the same distance between adjacent coils in a range of 2 to 32 cm between them, yielding k12 = k23 = k34.The results for the efficiency and relative power transferred for a load of 100 Ω are given in Fig. 8. Maximum power was measured at distance of 3 cm, whereas the calculated distance is 5 cm.
It can be noted that for distances smaller than approximately 5 cm the inter-couplings between non-adjacent coils (k13, k14, and k24 different from zero) introduce errors, so that theoretical and practical results are not equal to each other.This is in agreement with the theory presented since the influence of non-adjacent coils (k13, k14, k24) are not considered in the derived equations.
IV. CONCLUSION
The MPT conditions of 2-coils and 4-coils WPT system have been derived from circuit analysis and discussed together with the respective system power transfer efficiency, demonstrating that 4-coils system with R2=R3=0 presents, from maximum power transfer and efficiency point of view, a performance similar to those of a 2-coils system.The exception is the influence of coupling coefficient: in 2-coils system η increases as k12 approaches one, while in 4-coils system η increases as k23 approaches zero.Obviously, the condition R2=R3=0 is not attainable in common practical circuits, being used in this work only as a theoretical guide to allow the comparison between 2-coils and 4coils WPT.
In fact, usually a 4-coils WPT system presents power losses at R2 and R3.For this condition, it has been also demonstrated that 4-coils WPT system has, as expected, its ability to transfer power to the load and its efficiency reduced as power losses at R2 and R3 increase.Here it is important to emphasize that, from efficiency point of view, a 2-coils or a 4-coils WPT system with R2=R3=0 are different from a 4-coils WPT system with power losses at R2 and R3 since the later presents a maximum efficiency as a function of k23.
Note that in a series circuit classical MPT theorem teaches that if RSOURCE=RLOAD, power transferred to the load is maximum and is ½, and that, keeping RSOURCE constant, η increases as RLOAD increases.
So that, for a given source (RSOURCE constant), the circuit designer makes RLOAD> RSOURCE if his or her
Fig. 3 .
Fig. 3. Measured coupling coefficient (k) as function of distance between two adjacent coaxial coils.Four coils with same features: 150 mm of diameter, 20 mm of length, 22 turns of copper wire with diameter 0.9 mm. | 2,466.8 | 2015-06-01T00:00:00.000 | [
"Engineering",
"Physics"
] |
Combined leaching of Carlin-type gold deposit in Guizhou by potassium chlorate and bleaching powder
Cyanidation has been considered an effective process for extracting gold from gold-bearing ores for over 100 years. However, this process also has several disadvantages including it being toxic, inefficient, and unsuitable for leaching gold from carbonaceous gold ores containing organic and inorganic carbons. Moreover, it is not feasible for the extraction of gold from refractory gold ores , which are increasingly being used.Therefore, there is an urgent need to find an environmentally friendly and efficient leaching method to improve the extraction rate of gold from refractory gold ores. This study discusses using potassium chlorate and bleaching powder for combined leaching of refractory gold ore. Compared with other leaching methods, this method does not require the pre-oxidizing of the refractory gold ore. Moreover, the optimal reaction temperature required for the reaction is lower, thus achieving efficient and environmentally friendly leaching of refractory gold ore. To improve on the method, we used response surface methodology (RSM). RSM can quickly determine the quadratic function connection between the response value and each component and optimize the experimental settings to precisely forecast the experimental findings, saving a significant amount of time and money.This study presents a response surface approach based on a thermodynamic analysis of gold-bearing mineral oxidation to analyze the primary composite design experiment. The response surface model uses four components and three levels of potassium chlorate concentration, bleaching powder addition, reaction temperature, and reaction pH. The model gives 0.16 mol l−1 potassium chlorate, 37.5 g bleaching powder, 25 °C reaction temperature, and reaction pH of 13 as the optimal conditions for leaching gold using potassium chlorate and bleaching powder. Under these conditions, the gold leaching rate can reach 90.84%. In addition, the following parameters influence combined gold leaching in decreasing order: bleaching powder dose, reaction temperature, potassium chlorate concentration, and reaction pH.The results show that potassium chlorate and bleaching powder combined is advantageous for leaching of Carlin-type gold ore in Guizhou. It provides a high leaching rate. There is no need for pre-oxidation of gold ore. It is a simple inexpensive process that can be operated at a low optimum reaction temperature. Thus, it is a feasible method in industrial applications and provides a new way for gold leaching.
Introduction
Gold, a rare and valuable metal, is a reserve, investment and significant material in the jewelry, electronics, and aerospace industries, among other disciplines [1][2][3]. As the world's gold mines continue to be exploited [4,5], easy-to-separate gold resources are being depleted, and massive amounts of refractory gold are becoming essential raw materials for the gold manufacturing sector [6,7].
Owing to its high selectivity for gold and silver over other metals and its relatively low cost, cyanidation has been considered an effective process for extracting gold from gold-bearing ores for over 100 years [8][9][10][11]. Currently, many gold mines use cyanidation for gold extraction.
The main reagents used in the test were potassium chlorate, bleaching powder, hydrochloric acid, nitric acid, sodium chloride, sodium fluoride, anhydrous ethanol, tartaric acid, and thiourea (all reagents are analytical grade).
Experimental materials
The gold ore used in this experiment was obtained from Zijin Mining, Guizhou Province, China. It is a dark gray, thick block broken by a jaw crusher, ground in a conical ball mill, sieved to a 74 μm fraction, accounting for 92%, mixed, and then bagged for later usage using the grid sampling method. Table 1 lists the major chemical composition of the ores.
Experimental method
The ore powder was broken, ball-milled, sieved, dried, and blended ahead of time, and 50 g was inserted into a 500 ml beaker. The prepared leaching agent was introduced into a thermostatic water bath and agitated at 400 rpm. The pulp was filtered using medium-speed qualitative filter paper after leaching, and the filter cake was weighed after drying. The mineral gold concentration, before and after leaching, was evaluated using foam plastic enrichment flame atomic absorption spectrometry [29,30]. The leaching rate was estimated, and the gold recovery was calculated using equation 1 as follows: where M i , M 0 , W i , and W 0 are the mass of the leached sample at a specific time interval (g), mass of the raw sample (g), concentration of gold in the leached sample at specific time intervals (g/t), and concentration of gold in the raw sample (g/t), respectively.
Thermodynamic analysis of gold-bearing mineral oxidation
The main gold-bearing minerals in refractory gold ores in Guizhou are pyrite and arsenopyrite. Fine gold particles are primarily encapsulated in pyrite and arsenopyrite, and a small amount is encapsulated in other metal sulfides. Therefore, maximizing the dissociation of the above metal sulfides and destroying the encapsulated gold carrier is the key to improving the gold leaching rate. Table 2 lists the standard redox potential of metal sulfides common in ores. In the table, the redox potential of metal sulfides and the difficulty of oxidation gradually increase from left to right.
The redox potential reflects the macroscopic redox properties of all substances in an aqueous solution. The higher the redox potential, the stronger is the oxidation. Conversely, the lower the redox potential, the stronger is the reducibility. Positive and negative potentials indicate that the solution shows a specific oxidation and reduction, respectively.
As shown in figure 1, the redox potential of Fe 3+ /Fe 2+ is higher than that of other metal sulfides, except Ag 2 S, and the redox potential of Cl 2 /Cl − is significantly higher than that of metal sulfides, indicating that both can oxidize and decompose such base metal sulfides.
Thermodynamic analysis of S-H 2 O system
When the leaching process is carried out under acidic conditions, the element is precipitated to form a film of sulfur, which hinders the oxidation of pyrite and arsenopyrite by the solution, as shown in figure 2. When pH > 7, the stable area of elemental sulfur is very small. The sulfur element in the system mainly exists in the form of S 2 -, HS-, HS − , or SO 4 2− in the solution. Therefore, under alkaline conditions, the S element in pyrite and arsenopyrite will eventually be converted into SO 4 2− .
E-pH diagram of FeS 2 -H 2 O system
To further explore the oxidative decomposition process of the main gold-bearing minerals (gold minerals pyrite and arsenopyrite) in gold deposits, E-pH diagrams of the FeS 2 -H 2 O and FeAsS-H 2 O system at 298.15 K were drawn, and the E-pH diagram of the FeS 2 -H 2 O system is shown in figure 3.
As shown in figure 3, the redox potential of FeS 2 is higher, and the oxidative decomposition of FeS occurs prior to FeS 2 . Therefore, increasing the potential or pH of the solution can cause the Fe in FeS 2 to enter the solution in the form of Fe 2+ and Fe 3+ . S is leached in the form of S 2− , HS − or SO 4 2− . In an alkaline solution, using oxygen as an oxidant to oxidize pyrite, the following reaction occurs: According to the thermodynamic data, Gibbs free energy of the reaction (Δ r G θ ) is −1582.44 kJ mol −1 , indicating that the reaction has a strong tendency and can proceed spontaneously.
E-pH diagram of FeAsS-H 2 O system
It can be seen from figure 4 that at higher oxidation potentials, As mainly exists in the form of HAsO 4 2− and AsO 4 3− in the solution, sulfur mainly exists in the form of SO 4 2− , and Fe mainly exists in the form of goethite. In an alkaline solution, arsenic pyrite is oxidized using oxygen. The reaction is as follows: The thermodynamic data show that Δ r G θ is −1258.57 kJ mol −1 indicating that the reaction can be carried out spontaneously. The gold-coated arsenopyrite will be converted into ionic AsO 4 3− and SO 4 2− , and because of the formation of colloidal Fe(OH) 3 , some gold will be adsorbed by Fe(OH) 3 , resulting in a decrease in gold leaching rate.
Thermodynamic analysis of Au-H 2 O system
The chemical properties of gold are relatively stable, and leaching generally requires both oxidants and leaching agents to play a role. If the oxidant has a stronger oxidizing property, the formed gold complex will be more stable, and the leaching of gold will be easier. Similar to other amphoteric hydroxides, gold hydroxide also has amphoteric properties; however, the compound is more acidic. Au(OH) 3 (also known as H 3 AuO 3 ) is dissolved in a strong alkaline solution to form H 2 AuO 3 − , which can also be further dissolved to form HAuO 3 2− . Under alkaline conditions, the following reactions occur in the Au-H 2 O system: It can be seen from figure 5 that Au (OH) 3 , as an amphoteric hydroxide, can dissolve Au by thermodynamic analysis to ensure sufficient oxidation potential and an alkaline environment. Under the condition of sufficient alkalinity and potential, Au(OH) 3 will exist in the solution as H 2 AuO 3 − and HAuO 3 2− to achieve gold leaching. Figure 6 shows a simple E-pH diagram of the Cl-H 2 O system. As shown in the figure, under acidic conditions, the dissolved chlorine gas may undergo a disproportionation reaction to form HClO, which is unstable and decomposes into O 2 . When Cl 2 is introduced into the solution in a strong alkali medium, the following reaction occurs: As shown in figure 6, the solution is mainly in the form of ClO − , and the ClO − potential is higher than O 2 . Therefore, hypochlorite oxidation is greater than that of oxygen, and ClO − can oxidize many substances that O 2 cannot. Hence, ClO − is more easily oxidized than O 2 to decompose the gold-bearing mineral.
Thermodynamic analysis of Au-Cl-H 2 O system
Chlorination of aqueous solutions is carried out under acidic conditions, and gold is stable in the form of AuCl 4 − .
However, AuCl 4 − is reduced by water owing to the increase in solution pH and the decrease in oxidation potential, forming Au(OH) 3 and AuO 2 precipitates; as the pH increases, the dissolved chlorine is converted into hypochlorous acid. If the pH continues to increase, hypochlorous acid continues to be converted into hypochlorous acid ions, and hypochlorous acid has a strong oxidizing property. If the pH continues to increase further, Au(OH) 3
Thermodynamic analysis of potassium chlorate dissolving gold
The following calculation is performed using the Nernst equation to obtain the theoretical dosage for the effective leaching of gold in the gold ore. The reaction equation of potassium chlorate dissolving gold is The Nernst equation is: The gold grade of the gold ore used in this experiment was 15.03 g /T . It is assumed that 50 g of gold ore is leached in a 400 ml aqueous solution system, and the gold content in the solution system is 9.5 × 10 -6 mol l −1 . It is also assumed that all Au in the system is converted to H 2 AuO 3 − , that is, [H 2 AuO 3 − ] = 9.5 × 10 −6 mol l −1 . The ion activity coefficient is 1, and the ion concentration is used instead of the ion activity. When the pH of the gold leaching system is 8 and the concentration of potassium chlorate is 0.01 mol L −1 , E >0, which proves that the gold leaching reaction of potassium chlorate can proceed in the positive direction.
Thermodynamic analysis of bleaching powder dissolving gold
To obtain the theoretical dosage for the effective leaching of gold in the gold ore, the following calculation is performed using the Nernst equation: The reaction equation of bleaching powder dissolving gold is The gold grade of the gold ore used in this experiment is 15.03 g t −1 . It is assumed that 50 g of gold ore is leached in a 400 ml aqueous solution system, and the gold content in the solution system is 9.5 × 10 −6 mol l −1 . Assuming that all Au in the system is converted to H 2 AuO 3 − , that is, [H 2 AuO 3 − ] = 9.5 × 10 −6 mol l −1 , the ion activity coefficient is taken as 1, and the ion concentration is used to replace the ion activity. When pH = 12 and the amount of bleaching powder is 1 g, the standard electrode potential E 0 > 0, it is proved that the gold leaching reaction of bleaching powder can proceed positively.
Results and discussion
4.1. Response surface methodology experiment on combined leaching of refractory gold ore from Guizhou by potassium chlorate and bleaching powder 4.1.1. Response surface test design According to previous single-factor test results, the zero level was selected as the maximum value of the singlefactor test. The change interval selects the part with a noticeable change that is symmetrically distributed on both sides of the single factor maximum. The effects of potassium chlorate concentration, bleaching powder addition, leaching temperature, leaching pH, and the significance of each factor on the gold leaching rate were studied. The RSM was used to design the interaction experiment, and the BBD design module was used to conduct the central composite design experiment with four factors and three levels. According to the BBD composite test design principle, the zero level should be the maximum value of a single-factor test. The center point and level of the response surface test factors were reasonably selected. In the variation interval of each factor in the experiment, the authors selected the part with a noticeable change, and the maximum value of a single factor was symmetrically distributed on both sides. The base change steps in the single-factor test are listed in table 3.
Response surface test results
The experimental factors and level values in table 3 were input into Design Expert v8.0.6.1, and the experiment was carried out according to the experimental scheme generated by the software. There were 29 groups of points in the experimental scheme. The experimental scheme and results are listed in table 4. The test data in table 4 were fitted using a multivariate quadratic equation. The fitted regression equation is given by equation (22).
The variance analysis data of the regression model of the gold leaching rate (Y) in table 5 can be obtained using Design Expert v8.0.6.1 software for variance analysis.
The P-value is usually used to represent the significance of the model in the variance analysis; when P < 0.05, the model is significant, and when P < 0.001, the model is highly significant. As can be seen from table 5, the regression model P < 0.0001 indicates that the regression model reached a highly significant level. Variance R 2 = 0.9856, indicating that the model can explain 98.56% of the change in the response value. The model has a good degree of fitting [31]. Figure 8 exhibits the comparison result between the actual value and the predicted value. The closer the distance between the point in the graph and the slash, the closer is the actual value and the predicted value. The higher the fitting degree of the equation because the points in figure 8 are concentrated near the slash, it shows that the model fits well and has little difference from the actual conditions. Figure 9 shows the relationship between the residual and the number of experiments. It can be seen from the figure that the experimental points are randomly distributed at both ends of the residual zero-point line, indicating that the residual distribution is uniform and the residual is small. In addition, it can be seen from figure 9 that the range of residuals is −3-3 under the condition of 1-29 experiments, indicating that the experimental fitting degree is good and can well represent the gold leaching model.
Three-dimensional response surface plots can better demonstrate the influence of the interaction between different factors (potassium chlorate concentration, bleaching powder addition, reaction temperature, and reaction pH) on the gold leaching rate, as shown in figures 10-14. If the curvature of the response surface is high, the interaction between the two factors significantly affects the gold leaching rate. In contrast, the low curvature of the response surface indicates that the interaction between the two factors has little effect on the gold leaching rate [32,33].
The interaction between potassium chlorate concentration (X1) and bleaching powder addition (X2) is shown in figure 10. As the concentration of potassium chlorate gradually increased from 0.1 mol l −1 to 0.2 mol l −1 , the gold leaching rate increased rapidly with the increase of bleaching powder addition. The effect of bleaching powder addition on the gold leaching rate is greater than that of potassium chlorate concentration. In the contour map, the contour density along the direction of the bleaching powder addition (X2) is substantially higher than that along the direction of the potassium chlorate concentration (X1), indicating that the influence of bleaching powder addition on the gold leaching rate is more significant than that of the potassium chlorate concentration. Figure 11 shows that when the reaction temperature increases from 20°C to 30°C, the gold leaching rate increases significantly with the addition of bleaching powder. The effect of bleaching powder addition on the gold leaching rate is greater than that of the reaction temperature. The contour density along the direction of the bleaching powder addition (X2) is larger than that along the direction of the reaction temperature (X3) in the contour map, showing that the influence of bleaching powder addition on the gold leaching rate is more substantial than that of the reaction temperature.
As shown in figure 12, the interaction between the quantity of bleaching powder added (X2) and the reaction pH (X4) increases the gold leaching rate as the reaction pH rises from 12 to 14 as the amount of bleaching powder supplied rises. The effect of bleaching powder addition on the gold leaching rate is more significant than that of the reaction pH. The contour density along the route of bleaching powder addition (X2) is larger than that along the direction of reaction pH (X4) in the contour map, showing that the influence of bleaching powder addition on the gold leaching rate is more substantial than that of the reaction pH.
The relationship between potassium chlorate concentration (X1) and reaction temperature (X3) can be seen in figure 13. As the concentration of potassium chlorate gradually increases from 0.1 mol l −1 to 0.2 mol l −1 , the gold leaching rate increases significantly with the increase in reaction temperature. Therefore, the influence of the reaction temperature on the gold leaching rate is larger than that of the potassium chlorate concentration. In addition, the contour density along the direction of the reaction temperature (X3) is greater than that along the direction of the potassium chlorate concentration (X1) in the contour map, indicating that the influence of the reaction temperature on the gold leaching rate is more important than that of the potassium chlorate concentration.
The relationship between potassium chlorate concentration (X1) and reaction pH (X4) can be seen in figure 14. As the reaction pH gradually climbs from 12 to 14, the gold leaching rate increases significantly with the rise in potassium chlorate concentration. The influence of potassium chlorate concentration on the gold leaching rate is larger than that of the reaction pH. The contour density on the contour map is significantly larger along the direction of potassium chlorate concentration (X1) than along the direction of the reaction pH (X4), showing that the influence of potassium chlorate concentration on the gold leaching rate is substantially more significant than that of the reaction pH.
In summary, the significant factors affecting the gold leaching rate are X2, X3, X1, and X4, in descending order, and the interactions between factors X2 and X3 are more significant compared to other interactions.
The experiment was optimized using a numerical module. For the combined leaching of potassium chlorate and bleaching powder, the following conditions are optimal: potassium chlorate concentration of 0.16 mol l −1 , bleaching powder addition of 37.5 g, reaction temperature of 25°C, and reaction pH of 13. It is predicted that, under these conditions, the primary leaching rate of gold can reach 74.91%.
Confirmatory experiment
The mixture was leached for 4 h at 50 g ore powder, an 8:1 liquid-solid ratio, a stirring rate of 400 rpm, a reaction temperature of 25°C, a potassium chlorate concentration of 0.16 mol l −1 , a bleach amount of 37.5 g, and a pH of 13. The slag was then subjected to secondary leaching under identical conditions. Three parallel experiments were performed under the above conditions to verify the stability and repeatability of the optimal conditions. The results are listed in table 6. It can be seen from table 6 that the average leaching rate of gold in the three parallel samples under the optimal conditions is 74.39%. The highest secondary leaching rate of slag after washing is 84.20%, and the average total leaching rate is 90.84%. The average difference between the predicted value of the primary leaching rate and the experimental value is 0.52%, which verifies the model's reliability.
XRD analysis of ore samples before and after leaching
XRD spectroscopy experiments were carried out on raw ore and leaching residue under better process conditions. The experimental results are shown in figure 11. XRD patterns of ore and leaching residue, where figure 11(a) is ore and figure 11(b) is leaching residue. Figure 11(b) is the optimal leaching condition of 4.2 leaching.
The diffraction peaks in the slag-scanning pattern after leaching primarily included SiO 2 , Ca(CO 3 ), CaMg(CO 3 ) 2 , and Fe(OH) 3 phases, as shown in figure 15. Compared to the XRD pattern of the raw ore powder, the diffraction peak of FeAsS in the raw ore disappears. Instead a new Fe(OH) 3 diffraction peak is formed. After oxidation, arsenopyrite in the raw ore has a good dissociation action and interacts with potassium chlorate to generate Fe(OH) 3 under alkaline conditions. Because silica and dolomite are insoluble in water and stable in nature, they are not engaged in the gold-leaching process and have diffraction peaks before and after. Under optimal leaching conditions, the combination of potassium chlorate and bleaching powder has better leaching ability for Guizhou Carlin-type gold mine, and the encapsulation of gold by arsenopyrite is opened. The ideal gold leaching rate is obtained through XRD analysis of ore samples before and after leaching. (2) Through thermodynamic analysis of leaching of gold by potassium chlorate and bleach powder, and calculating the results by using Nerst equation, the standard electrode potential E 0 in the reaction equation of gold dissolution is greater than zero, which proves the feasibility of gold leaching with potassium chlorate and bleaching powder.
Conclusion
(3) The response surface model is significant and fits well. The addition of bleaching powder, reaction temperature, potassium chlorate concentration, and pH influence the leaching rate in descending order. The relationship between the amount of bleaching powder and the reaction temperature significantly influences the response value. The optimal conditions for model optimization are obtained as 0.16 mol l −1 potassium chlorate concentration, 37.5 g bleaching powder addition, 25°C reaction temperature, and pH of 13. Under these conditions, the primary leaching rate of gold is 74.54%, the secondary leaching rate of slag after washing is 84.20%, and the average total leaching rate is 90.84%.
(4) The advantages of potassium chlorate and bleaching powder combined with the leaching of Carlin-type gold ore in Guizhou are a high leaching rate, no need for pre-oxidation of gold ore, low cost, low optimum reaction temperature, and simple process, making this a feasible method in industrial applications and providing a new way for gold leaching. | 5,591.6 | 2022-11-29T00:00:00.000 | [
"Materials Science"
] |
As featured in: fl by using
Identi fi cation of new redox compounds is essential for the design of new improved redox- fl ow batteries. Phenazines are a new class of organic compounds that have been recently used in electrochemical energy storage applications. By applying high-throughput density functional theory calculations, we investigated the redox-potentials of 200 phenazine derivatives in non-aqueous media containing various electron-donating or -withdrawing groups at di ff erent positions. We identi fi ed promising candidates for both the negative and positive sides of organic-based fl ow batteries. By adding an appropriate number of functional groups at the speci fi c targeted positions, the redox potentials can be modi fi ed up to (cid:1) 0.65 V (for the electron-donating amino groups) and to +2.25 V (for the electron-withdrawing cyano groups) compared to the parent phenazine. The analysis of the results revealed the e ff ect of both the functional groups and their position on the redox potential. By strategically partially functionalizing with EDGs at the appropriate positions, a redox potential equal to or even more negative than that of full functionalization can be obtained. To further accelerate the design of new improved batteries, a computational approach was used in order to assess their structural stability. The results show that the proposed compounds are predicted to have similar stabilities to other organic molecules that are used in redox- fl ow batteries.
Introduction
Climate change and rising global energy demands have prompted an urgent search for new renewable energy solutions. While great technological advances in accessing sustainable forms of energy such as wind and solar power have been made, the storage of these energies for on-demand usage and transport remains a major challenge. 1,2 Electrical energy storage and conversion is vital to a clean, sustainable, and secure energy future. Rechargeable batteries, based mainly on lithium, have attracted great attention due to their high energy density for portable (electronics), mobile (electrical vehicles), and stationary (micro-grids) applications. 3 Despite their high energy densities, lithium-ion batteries exhibit several limitations, such as the use of critical elements and associated safety issues that eventually might cause a battery explosion. Therefore, new and improved technologies for energy storage are urgently required to make a more efficient use of our nite supply of fossil fuels, and to enable the effective and safe use of renewable energy sources. In this scenario, Redox-Flow Batteries (RFBs) are considered an interesting alternative energy storage technology, which can exhibit high potential, high efficiency, room temperature operation, and long charge/discharge cycle life. 4,5 The main advantage of the RFBs is that power is independent of the energy density, thus allowing for independent power and energy sizing, which can be tailored according to each desired application. 6 The energy density of RFBs depends on the concentration (solubility) of the active species in the electrolytes, the number of electrons involved in the redox reaction and the operation voltage, given by the potential difference between the redox reaction at the catholyte and anolyte (E f nCV). Therefore, species with high solubilities and highly separated redox potentials are required in order to maximize the energy density of RFBs. Currently, most of the RFB systems are based on dissolved metallic redox species including vanadium, iron and chromium, with the aqueous all-vanadium technology (VRFB) being the one employed in most commercial available RFBs. 7 However, the main disadvantages of VRFBs are associated with the toxicity, high cost and scarcity of vanadium salts. 5 During the last few years there has been a boom in the eld of organic redox ow batteries triggered by the research on abundant, environment friendly and cheaper redox active organic materials as substitutes of vanadium compounds. 8,9 Moreover, non-aqueous solvents are also being investigated due to their wider electrochemical window enabling larger cell voltage that might boost the energy density of RFBs. 10 Many different molecules and specially those based on quinones, 11,12 viologens, 13 nitroxides 14 and methoxybenzenes, 15,16 have been proposed and investigated in both aqueous and non-aqueous organic redox ow batteries. Among all candidates, the quinoyl family has been the most widely investigated due to their structural diversity and broad tunability, permitting the engineering of solubility, redox potential, kinetics, and stability. 12,[17][18][19] As an inspiring example, Yang et al. exploited the tunable redox potential of the quinoyl family to develop the rst all-quinone aqueous RFB in which active species in both catholyte and anolyte were quinones having different functionalities. 20 Recently, our group reported the rst example of a membrane-free battery, in which the same molecule, p-benzoquinone, was used as the active material in both immiscible electrolytes. 21 In that work, we took advantage of the different redox mechanisms undergone by quinones in electrolytes with different nature; in protic electrolytes the reduction proceeds via a 2e À /2H + proton-coupled electron transfer (PCET) mechanism in one single step whereas in aprotic electrolytes quinones are reduced in successive oneelectron steps (ET) to form the radical anion and dianion. 22 Computational modeling has been proved to be a useful tool to explain the electrochemical properties of redox-active materials and also predict new molecules with improved properties. High-throughput computational screening offers the possibility of exploring thousands of molecules for desirable properties without the need for experimental trial and error. [23][24][25] The computational results can provide key insights into structureactivity properties that may be used in the design and tuning of new molecules for electrochemical energy storage. The majority of theoretical studies have been conducted on the quinone family (benzoquinone, naphthoquinone, and anthraquinone) whose redox potential and solvation free energies strongly depend on the chemical nature of electron donating groups (EDGs) and electron withdrawing groups (EWGs) attached to the basic quinoyl skeleton. 24,26,27 Though solubilities higher than 2 M have been reported, the reversible capacities achieved in those reports are still substantially lower than their theoretical values. Moreover, parasitic side reactions in quinoid-based compounds and relatively high redox potentials in most anolyte materials are still an issue in the development of organic redox ow batteries. [28][29][30] Therefore, there is still a need for discovering new redox-active molecules to fulll the exigent requirements of redox ow batteries, and computational chemistry can undoubtedly accelerate this task.
Phenazines comprise a large group of redox-active nitrogencontaining heterocyclic anthracene skeletons, sharing similar chemical, electrochemical and physical properties to those of the quinone family. They are structural analogues to anthraquinones and their reduction mechanism also depends on the media, occurring either via a 2-electron reduction (ET) in two steps in aprotic solvents, or via a 2e À /2H + proton-coupled electron transfer (PCET) mechanism in a single step in protic media. [31][32][33] Moreover, similar to quinones, some properties of phenazines such as their redox potential strongly depend on the nature of functional groups in the molecular structure. 34 However, there are only a few examples where phenazine compounds have been used for redox ow batteries. [35][36][37] In the rst example, a bipolar redox active molecule containing phenazine and TEMPO moieties acting as anolyte and catholyte redox centers, respectively, was synthesized and employed in a symmetric RFB. 35 Following a similar strategy to the quinone family, 24,38 Hollas et al. performed a virtual screening on several phenazine derivatives with hydroxo, carboxylate and sulfonate groups in aqueous solutions and modied the molecular structure of the pristine phenazine with hydroxo and sulfonate groups to increase the solubility and tune the redox potential. 36 In a similar fashion, Wang et al. characterized phenazines containing amino and hydroxo groups in aqueous RFBs with experimental and computational techniques. 37 They also performed a systematic computational investigation of various multi-hydroxyl substituted phenazines and showed how the redox potentials depend on the number and position of the hydroxo groups. However, a systematic computational screening of phenazine derivatives with functional groups of different nature is still highly needed, considering that more than 100 different phenazine structural derivatives have been identied in nature, and over 6000 compounds that contain phenazine as a central unit have been synthesized. 39,40 Here, we provide a systematic computational study to ll the existing gap in knowledge on how the relevant electrochemical properties of phenazines change by systematic insertion of different functional groups (FGs). The main objective is to determine the effects of the: (i) addition of FGs with different electronic behaviors, (ii) position of the FG, and (iii) degree of functionalization (i.e. single versus multiple FGs), on the redox potentials of phenazine-derivatives. To achieve this, we analyzed $200 phenazine compounds containing 22 FGs with different electronic behaviors like electron donating groups (EDGs) and electron withdrawing groups (EWGs). As a result, new insights into the phenazine structure-activity relationships in non-aqueous electrolytes are disclosed for the rst time. Additionally, we performed a theoretical assessment of their stability based on structural criteria and we determined how the different FGs affect this stability. This computational-experimental research aims to contribute to the rational design of appropriate redox molecules and to accelerate the development of phenazine compounds as high performing anolytes for RFBs.
Experimental details
Phenazine (98% purity) was purchased from Sigma Aldrich and used as received. The redox behavior of phenazine was determined by cyclic voltammetry (CV) of 5 mM of phenazine in 1,2dimethoxyethane (DME) with 0.5 M TBAPF 6 as the supporting salt. CV was carried out at room temperature in a threeelectrode cell using 3 mm diameter glassy carbon and a Pt wire as working and counter electrodes, respectively. A silver wire in a frit tube lled with electrolyte solution was used as the pseudo-reference electrode. Ferrocene was used as an internal standard for electrochemical measurements. CV at different scan rates was conducted in a Biologic VMP multichannel potentiostat inside a glove box (O 2 < 0.1 ppm, H 2 # 0.1 ppm).
Computational details
Calculation of the redox potential. As depicted in Scheme 1, the reduction mechanism of phenazines in aprotic solvents involves two successive one-electron reduction steps to form rst the radical anion and the dianion in the second step. Using DFT and the standard thermodynamics relations, the redox potentials were obtained by calculating the Gibbs free energy for all the compounds involved in the reduction reaction. The geometries of the neutral compounds were pre-optimized using Avogadro soware 41 and the MMFF94/MMF94s force elds, 42,43 which show good accuracy with organic molecules. Subsequently, geometric optimizations were performed for the neutral and reduced forms of the phenazine compounds in the gas phase using the B3LYP functional [44][45][46] in combination with the 6-31+G(d,p) basis set. 47 Finally, the structures were conrmed to be minima on the potential energy surface by conducting a subsequent harmonic frequency analysis, where all frequencies were calculated to be real. Thermal contributions to the Gibbs free energies were computed within the idealgas, harmonic oscillator approximation assuming conditions of T ¼ 298 K and P ¼ 1 bar. Solvation effects associated with DME as the solvent were accounted by using the SMD 48,49 continuum solvation model and performing single-point M06-2X 50 energy calculations. The nal composite free energies of species i in solution (G 0 (i,sol) ) were calculated according to eqn (1) by adding the free energy contributions calculated at the B3LYP level (G 0 therm(i,gas) ) to single-point M06-2X energies (E M06-2X (i,sol) ).
All DFT calculations were performed with the Gaussian 16 soware package. 51 An example of an input le with DME as the solvent for the SMD calculation is given in section A of the ESI, † since the DME solvent needs to be dened explicitly via its descriptors.
The reduction potentials of the functionalized compounds (RPZ) were calculated using the isodesmic reaction: [PZ] À + [RPZ] / [PZ] + [RPZ] À , relative to the corresponding values for the reference species, the parent phenazine (PZ). The following equation was used: is the experimentally measured reduction potential of the reference compound, the parent phenazine, DG (rxn,sol) is the free energy change of the isodesmic reaction, F is the Faraday constant and n is the number of electrons involved in the reduction process. By using this approach, the systematic error in the electronic structure calculations is cancelled and the obtained DFT reduction potentials are more accurate. This approximation has been used successfully previously to calculate the reduction potentials of organic molecules in both aqueous and non-aqueous solvents. 26,[52][53][54] Estimation of stability-performance. From the computational perspective, predicting the stability and performance of a molecule for use in battery applications is challenging because of the many possible decomposition reactions and products. In this work, structural properties are used as indicators to assess their stability and performance.
Two properties that can be related to the structural stability are (i) the reorganization energy (l) and (ii) the root-meansquare deviation (RMSD) between the optimized coordinates of the neutral and reduced state of the phenazine species. The reorganization energy (l) of a molecule during the reduction and oxidation process was computed from the geometries of the neutral and anionic states using the Vertical Electron Affinity (VEA), the Vertical Detachment Energy (VDE) and the Adiabatic Electron Affinity (AEA) energies. The total reorganization energy (l tot ) is dened as the sum of the reorganization energy during oxidation (l ox ) and reduction (l red ).
Results and discussion
Accuracy of the computational approach The reduction potentials of the phenazine derivatives were calculated according to eqn (1) and (2) using DFT, the standard thermodynamic relations and the reference value for the parent phenazine. The redox potential of the parent phenazine was determined experimentally by cyclic voltammetry as presented in Fig. S1 in the ESI. † In order to assess the accuracy of the proposed computational approach, the redox potentials calculated by this methodology were benchmarked against reported experimental values for several triuoro-methylated derivatives of phenazine. 34 Table 1 shows that the calculated values for these phenazine derivatives are in very good agreement with the experimental redox potentials, thus validating the choice of the density-functional and basis set.
Inuence of the dielectric constant on the redox potential
Initially, the effect of the dielectric constant (3 r ) of the solvent on the redox potential of the parent phenazine was investigated.
Several solvents with values of the dielectric constant ranging from 2 up to 109 were selected for the calculations. Fig. 1 shows that the change in the redox potential of the parent phenazine is very pronounced among solvents with low values (3 r < 20), where the potential increases rapidly from À2.3 V in 1,4-dioxane (3 r ¼ 2.20) to À1.6 V in 1,2-dichloroethane (3 r ¼ 10.12). For solvents with higher values of the dielectric constant, the potential increases very slowly reaching a plateau at À1.4 V. A similar trend is expected for the other phenazine derivatives.
Inuence of the incorporated functional group on the redox potential
One of the main objectives of this study is to understand the effect of the chemical nature of the functional groups (FGs) and their position on the redox potential of phenazines. Due to the symmetry of the phenazine molecule (see Fig. 2A), there are only two possible positions to introduce those substituents: the R1position, adjacent to nitrogen and the R2-position. As depicted in Fig. 2A, the R4, R6, and R9 positions are equivalent to R1, while R3, R7 and R8 are equivalent to R2.
The calculated values of the rst reduction potential of the phenazine derivatives aer incorporating one functional group either in R1 or R2 positions are presented in Fig. 2B and C, respectively. Fig. 2 suggests that EDGs, such as -OH and -NH 2 , shi the redox potential (E 0 1 ) to lower values, whereas functionalization with EWGs, such as -NO 2 and -CN, lead to higher E 0 1 values. For example, compared to the parent molecule, the -N(CH 3 ) 2 group shis the E 0 1 by À107 and À239 mV when incorporated in R1 and R2 positions, respectively. In contrast, the incorporation of the -NO 2 group shis the E 0 1 by +386 and +454 mV at the R1 and R2 positions, respectively. Therefore, it is clearly shown in Fig. 2 that the electronic behavior of the FGs plays a key role in the redox potential of phenazine derivatives. For compounds negatively charged, such as the anion or dianion of a reduced molecule, the presence of FGs with electron withdrawing behavior tends to stabilize the effect of the negative charge on the whole molecule. Consequently, the Gibbs free energy of the reaction of phenazines with EWGs present more positive values resulting in the redox potential shiing towards more positive values than for the parent phenazine. In contrast, the presence of EDGs tends to destabilize the reduced phenazine, shiing the potential towards more negative values. These results are in good agreement with the trends observed in both computational and experimental studies reported for quinones and other heteroatom-doped organic redox compounds with 5-and 6-membered rings. 26,27,34,[55][56][57] Inuence of the position of added functional groups on the redox potential Fig. 3. In these cases, the hydrogen atoms from the FGs are in proximity to the nitrogen atom of the phenazine when the FG is attached to the R1 position, and intramolecular interactions are present. The main geometric characteristics of the above mentioned examples are shown in Fig. S2 in the ESI. † In the cases of -NH 2 , -OH, -SH, -COOH and -CONH 2 , the interactions are attributed to weak hydrogen bonds between the proton and the nitrogen atom based on the analysis of the main geometrical features (see Fig. S2 in the ESI †). In the reduced form, the negative charge stabilizes even more the hydrogenbond, therefore the RPs for the FGs at R1 are shied to more positive values compared to those for R2.
FGs as shown in
It is also observed that in the case of EWGs (green bars in Fig. 3), there is not a clear trend with the position of the FG and the DE 0 1 (R2,R1) seem to have a random distribution with negative and positive values. However, most of the derivatives with EDGs (blue bars in Fig. 3) show E 0 1 shied to more negative values when the FG is incorporated in the R2 position. The best examples are the -N(CH 3 ) 2 and -OH groups, where the R2-derivatives have a more negative potential by À132 and À122 mV respectively, compared to the R1-derivatives. Although there is only one exception, we can conclude that functionalization with EDGs in the R2 position is highly desirable to design new anolytes for RFBs, where more negative potentials are required. It is important to remark that this unique trend of phenazines is revealed for the rst time in organic redox molecules. Compared to their quinone analogues, anthraquinones showed the opposite effect, i.e. functionalization of the 9,10-AQ with EDGs always produced positive values for the DE 0 1 (R2,R1). 24
Effect of multiple substitutions
In a more detailed computational study we investigated the effect of adding more than one FG on the redox potential of phenazine. Amino (-NH 2 ) and cyano (-CN) groups were selected as two representative examples of EDGs and EWGs, respectively. Two, three, four and eight amino or cyano FGs were introduced on different positions and the redox potentials were calculated. Although the synthesis of phenazines with eight FGs is a challenging task, 58 we computationally explored these fully substituted derivatives to identify the upper and lower limits for the redox potential. All possible combinations were investigated, although only the redox potential of the derivative showing the largest shi in E 0 1 is shown for each group in Fig. 4. A more extended table with all the results is reported in the ESI (see Table S2 †). Fig. 4 shows that aer the insertion of the second amino group, the redox potential (E 0 1 ) decreases from À1.92 V to À2.09 V. This represents a redox potential shi of À0.17 V with respect to the addition of only one amino group. As mentioned in the previous section, the insertion of the rst amino group induces the same redox potential shi of À0.17 V compared to the parent phenazine. For the successive addition of the third and fourth amino functionality, the redox potential shi is reduced to À0.11 V and À0.14 V for the tri-amino-phenazine and tetra-amino-phenazine (TAPZ) respectively, while between four and eight groups the potential changes only by À0.05 V. Thus, the lowest limit of the redox potential aer functionalization with eight amino groups is calculated to be À2.39 V for the octa-amino-phenazine (OAPZ). The marginal difference of the potentials between TAPZ and OAPZ suggests that full functionalization with amino groups is not necessary to achieve the most negative potential. By strategically functionalizing at the appropriate positions with EDGs, a derivative with four amino groups is able to achieve an almost equally negative potential as a derivative with eight groups. This is a unique property of phenazines that has not been shown to exist for quinones. This effect is not dependent on the EDG, since the same trend is computed for functionalization with hydroxo groups (see Table S2 in the ESI †). Regarding the functionalization with EWGs, Fig. 4 shows that the effect of increasing the degree of functionalization is clearly more pronounced with cyano groups. It can be observed that the consecutive addition of one cyano group shis the potential by an almost constant value of +0.35 V per group up to four substitutions. With eight cyano groups the redox potential can reach a value as high as +0.51 V for the octa-cyano-phenazine (OCPZ), which represents an increment of +1.23 V with respect to the phenazine with four cyano groups. This effect is also not dependent on the EWG, since the same trend is observed for functionalization with nitro groups (see Table S2 in the ESI †). Interestingly, this huge shi of redox potential towards more positive values might pave the way towards the design of phenazine derivatives to be used not only as anolytes but also as catholytes in RFBs.
Comparison of phenazines with other common anolytes and catholytes
Fig . 5 presents the redox potentials of the most promising phenazines computed in this work in comparison with those of other redox-active candidates reported for non-aqueous RFBs. 34,59,60 Since not all reported molecules were tested on the same electrolyte, for a fair comparison, the rst redox potentials of all compounds were recalculated in the same DME media and plotted together with the best phenazine candidates obtained in this work. Fig. 5 shows that the redox potential of TAPZ is 140 mV more negative than that of N-methylphthalimide (MePht), having one of the most negative redox potentials reported so far. 60 This evidences the potential of phenazine derivatives, in particular amino-phenazines, as anolytes for non-aqueous RFBs. Fig. 5 shows that the high theoretical voltage calculated in DME for a battery using 9-FLuoroenone (FL) as the anolyte and N,N-dimethyl-phenazine (DMPZ) as the catholyte 59 (its rst oxidation peak at 1.82 V) might be further increased by 330 mV until 2.15 V, if the FL anolyte is substituted by the TAPZ reported here. In such an example, the voltage for the battery is associated with the rst-redox peak of the DMPZ catholyte at a positive potential. 59 Interestingly, due to the huge effect of the functional groups on the redox potential of the phenazine family, it was possible to envisage the rst theoretical example of the allphenazine battery having a meritorious 2.83 V by combining the phenazine functionalized with four amino groups (TAPZ) as the anolyte with the phenazine functionalized with cyano groups (OCPZ) as the catholyte.
Stability-performance prediction
The long-term performance of a RFB depends on the stability of the redox organic molecules used as the anolyte and catholyte.
Stability is a multifaceted issue that can be further categorized into: (i) chemical stability, which is associated with the decomposition of the redox molecule upon reaction with its reduced/oxidized species or solvent molecules, (ii) electrochemical stability, which is related to the decomposition reactions at very negative/positive potentials and (iii) structural stability, which is associated with the geometric strain between the oxidized and the reduced form of the redox molecule. From the computational perspective, predicting the chemical stability of a molecule is challenging because of the many possible decomposition reactions and products. When the kinetic aspects are taken into account on top of thermodynamics, this task becomes even more cumbersome because the reaction barriers for the decomposition reactions need to be calculated. While the degradation mechanisms can be calculated by applying heuristically aided quantum chemistry approaches to modeling complex chemical reactions, 63 this is out of the scope of the current work. However, a preliminary assessment of their structural stability can be performed based on the structural differences between the neutral and reduced forms of the phenazine compounds, as it was reported previously in the case of methoxy-benzene catholytes. 64 Fig . 6 shows the reorganization energy (l) of a molecule during the reduction and oxidation process computed using the geometries of the neutral and anionic states using the Vertical Electron Affinity (VEA), the Vertical Detachment Energy (VDE) and the Adiabatic Electron Affinity (AEA) energies. The total reorganization energy (l tot ) is dened as the sum of the reorganization energy during oxidation (l ox ) and reduction (l red ) as presented on the right side of Fig. 6. The results for all compounds with one functional group at the R1 and R2 position are shown in Fig. S3 and S4 in the ESI. † Based on the calculations, phenazine and its amino-and cyano-derivatives have lower (oxidation and total) reorganization energies than commonly reported anolytes such as the FL, MePht or DMAQ. The lower reorganization energies suggest that the anionic molecular species aer the VEA is closer to the minimum energy of the reduced state, thus it can reach the reduced state faster. The second structural stability criterion is associated with the geometric changes upon reduction. Molecules with larger geometric distortions aer the reduction are more prone to decomposition reactions. 65 The root-mean-square deviation (RMSD) between the optimized coordinates of the neutral and reduced state can also serve as an indicator for the geometric distortion, thus large RMSD values are not desired. The computed RMSD values (see Table S1, Fig. S5 and S6 in the ESI †) suggest that the majority of the phenazine compounds have values in the same range as the FL and MePht compounds as can be seen in the ESI (Table S1 †). While the parent phenazine and the cyano-derivatives show lower RMSD values, the corresponding values for the amino-derivatives are slightly higher. However, the values remain small, and do not exceed 0.05Å. Summarizing, all the above results suggest that the structural stability of the amino-and cyano-phenazine compounds from this work is predicted to be similar to that of the FL and MePht and better than that of the DMAQ.
Conclusions
With the use of DFT calculations, the redox potentials of $200 phenazine-derivatives were computed and structure-property relationships were revealed. Aer analysis of the results, the main conclusions are drawn: (1) The use of EDGs shis the potential toward negatives values, whereas the use of EWGs increases the potential toward positive values.
(2) The calculations have identied an unprecedented effect of the position (R1 versus R2) of functional groups on the redox potential. Functionalization with EDGs in the R2 position shis the potential to more negative values compared to the R1 position. This is a highly desirable property for the newly designed anolytes for RFBs, where more negative potentials are required. Surprisingly, this is a unique feature exhibited by phenazines that has never been observed in the quinone family.
(3) The shi in the redox potential of phenazines functionalized with the electron withdrawing cyano groups was found to be proportional to the number of cyano groups. Therefore, the functionalization with EWGs has an additive effect on the reduction potential of phenazine derivatives. In contrast, the amino groups do not show such a pronounced additive effect. It was observed that by functionalization at the appropriate positions with four groups, a potential equal to or even more negative than that of the full functionalization was obtained.
(4) Phenazines can be a promising substitute for anthraquinones in RFBs, due to their higher ability of modifying the redox potential. The changes in their redox potential are signicantly higher than in their anthraquinone analogues aer the introduction of multiple functional groups. For example, introduction of four cyano groups in the phenazine increases the potential by 1.3 V, whereas in the anthraquinones by $0.5 V. 27 (5) Based on the reorganization energies and the RMSD values between the geometries of oxidized and reduced states of the phenazines, the new derivatives are predicted to have similar or even improved structural stabilities than the commonly reported anolytes.
(6) The rst theoretical example of an all-phenazine battery having a meritorious voltage of 2.83 V was envisaged by combining the TAPZ and OCPZ as the anolyte and catholyte, respectively.
Conflicts of interest
There are no conicts to declare. | 6,759.2 | 0001-01-01T00:00:00.000 | [
"Chemistry"
] |
Goethite and Hematite Nanoparticles Show Promising Anti-Toxoplasma Properties
Toxoplasma gondii is an intracellular parasitic protozoan with a high infection rate in mammals, including humans, and birds. There is no effective vaccine, and treatment relies on antiparasitic drugs. However, existing antiprotozoal drugs have strong side effects and other problems; therefore, new treatment approaches are needed. Metal nanoparticles have attracted increased interest in the biomedical community in recent years because of their extremely high surface area to volume ratio and their unique reactivity that could be exploited for medicinal purposes. Previously, we confirmed the anti-Toxoplasma effects of gold, silver, and platinum nanoparticles, in a growth inhibition test. Here, we asked whether the anti-Toxoplasma effect could be confirmed with less expensive metal nanoparticles, specifically iron oxide nanoparticles (goethite and hematite). To improve the selective action of the nanoparticles, we modified the surface with l-tryptophan as our previous findings showed that the bio-modification of nanoparticles enhances their selectivity against T. gondii. Fourier-Transform Infrared Spectroscopy (FTIR) analysis confirmed the successful coating of the iron oxide nanoparticles with l-tryptophan. Subsequently, cytotoxicity and growth inhibition assays were performed. L-tryptophan-modified nanoparticles showed superior anti-Toxoplasma action compared to their naked nanoparticle counterparts. L-tryptophan enhanced the selective toxicity of the iron oxide nanoparticles toward T. gondii. The bio-modified nanoparticles did not exhibit detectable host cell toxicity in the effective anti-Toxoplasma doses. To elucidate whether reactive oxygen species contribute to the anti-Toxoplasma action of the bio-modified nanoparticles, we added Trolox antioxidant to the assay medium and found that Trolox appreciably reduced the nanoparticle-induced growth inhibition.
Introduction
T. gondii is a protozoan parasite that infects most birds and mammals and causes the zoonotic disease toxoplasmosis.In the life cycle of Toxoplasma, oocysts expelled from the terminal host cat by feces or other means enter the bodies of mammals and birds, where they transform into tachyzoites [1].T. gondii infects more than one-third of all humans and is asymptomatic in healthy individuals but causes severe symptoms in the immunocompromised [2][3][4].In addition, if a pregnant woman is infected with T. gondii, it can cause in utero infection, resulting in miscarriage or birth defects [5][6][7].It is also the second leading cause of death from food poisoning [8], resulting in many economic and human losses worldwide.There is no effective vaccine against T. gondii, and the treatment of infections caused by this protozoan is dependent on antiparasitic drugs.Pyrimethamine, one of the drugs used to treat toxoplasmosis, is also known to have side effects [9].Therefore, a new approach to treatment is required.
We have focused on metal nanoparticles (NPs), which have attracted increased interest in the biomedical community [10], and have analyzed their antiparasitic effects against T. gondii.Metal nanoparticles have been the subject of various biological studies due to their characteristics.Examples include drug carriers for drug transport due to their easy surface modification and targeting specific molecules in cells due to their high light scattering and absorption efficiency.Experiments using metal nanoparticles as a therapeutic agent for parasitic infections have also been conducted for other parasites as well, indicating the potential of metal nanoparticles [11].Metal NPs exhibit different properties than their bulk counterparts due to their large surface area relative to their volume [12]; therefore, they are thought to stimulate the generation of reactive oxygen species in cells and exhibit parasitic activity [13][14][15].The small size of NPs also allows them to penetrate cell membranes, making them highly reactive.Metal NPs are already being used for biomedical applications [16][17][18].
Although it has been shown that gold, silver, and platinum metal NPs exhibit antiparasitic activity [19][20][21][22], these are precious metals and are expensive.In this study, we focused on iron, an inexpensive metal, and asked whether iron oxide NPs exhibit antiparasitic activity against T. gondii.Iron oxide nanoparticles have a variety of medical applications, including MRI and cancer therapy [23].It has also been reported to have no significant side effects under certain conditions [24], leading to this verification as a candidate for an anti-Toxoplasma drug.We examined three relatively stable iron oxides: goethite, hematite, and magnetite.Previous studies have also shown that the L-tryptophan coating of metal NPs increases their anti-Toxoplasma effect [25,26].Since Toxoplasma has a tryptophan requirement [27][28][29][30], we also investigated whether the l-tryptophan modification of iron oxide NPs enhances the anti-Toxoplasmic effect.
Parasites
We used T. gondii RH strain 2F in this study.The parasite was maintained by repeated passages in monolayers of Vero cells (American Type Culture Collection, Manassas, VA, USA) cultured in Dulbecco's Modified Eagle's medium (DMEM; Nacalai Tesque, Kyoto, Japan) supplemented with 5% (v/v) fetal bovine serum (FBS) and penicillin and streptomycin (100 U/mL; Thermo Fisher Scientific Inc, Waltham, MA, USA).Host cells infected with T. gondii tachyzoites were passed through a 27 G needle to lyse them.The cell lysates were then filtered through a 5 µm filter to obtain a tachyzoite suspension free of host cell debris.The suspension was centrifuged (400× g, 10 min, 23 • C), and the supernatant was removed and suspended in fresh culture medium.Then, the parasite density was measured by using a hemocytometer and adjusted for in vitro experimental infection analyses.
Cytotoxicity of Metal NPs in Mammalian Cells
By using previously reported methods [16], we maintained HFF cells in DMEM supplemented with 5% (v/v) FCS and penicillin and streptomycin (100 U/mL).Cells were grown to confluence at 37 • C in a 5% CO 2 atmosphere.All experiments were performed in 96-well plates (Nunc) unless otherwise stated.At confluence, cells were trypsinized and resuspended to the desired cell density.The cells were seeded onto plates at a density of 1.0 × 10 4 cells/well and incubated for 48 h followed by treatment with various concentrations (between 0.01 and 100 µg/mL) of the NPs (goethite NPs, hematite NPs, and magnetite NPs).Culture medium lacking the test compounds was added to the control well, and the medium-only well was used to correct for any background signal.The treated cells were incubated for 48 h before being subjected to the cell viability assay.
Cell viability was determined using the CellTiter 96 ® AQueous One Solution Cell Proliferation Assay kit (Promega, Madison, WI, USA).Briefly, the well plate and its contents were equilibrated to room temperature.Then, 100 µL of the CellTiter 96 ® AQueous One reagent was added to each well.The contents were briefly mixed on an orbital shaker and then incubated at 37 • C in a 5% CO 2 atmosphere for 1-4 h.The absorbance signal was recorded at 490 nm using a microplate reader (GloMax Navigator 96; Promega).The assay was repeated three times in triplicate.The results are presented as the mean ± standard error of the mean (SEM; n = 3) of three independent experiments.
In Vitro Growth Inhibition Assessment by Use of Luciferase Reporter Assays
The number of T. gondii tachyzoites was determined by using a luminescence-based assay of β-galactosidase (β-gal) activity expressed by the parasite strain RH-2F, as described previously [16].To obtain a purified parasite suspension for the assays, infected cells were syringe-released, and the lysates were filtered to remove cell debris.
The growth inhibition assays and in vitro invasion assays were performed as described elsewhere [26].For the growth inhibition assay, purified parasite (1 × 10 4 ) suspension was added to growing monolayers and invasion was allowed to occur for 1 h.Then, fresh medium containing the NPs (reconstituted in culture medium) was added.The monolayers were then incubated for 48 h.The mock-treated (treated with NP vehicle only; in this case, culture medium) cells served as a positive control, whereas the medium-only well was used to correct for any background signal.After the 48 h incubation at 37 • C in a 5% CO 2 atmosphere, the viability of the RH-2F parasite strain was determined by measuring the galactosidase expression in a Beta-Glo ® Luminescent Assay kit (Promega, Madison, WI, USA).The assay was performed in triplicate and repeated three times.All experiments were performed in 96-well optical bottom plates (Nunc; Fisher Scientific, Pittsburgh, PA, USA) unless otherwise stated.
Tryptophan-Coated Iron Oxide Nanoparticles
Tryptophan was purchased from Sigma-Aldrich (St. Louis, MO, USA).Using previously reported methods [26], powdered tryptophan was added to DMSO and stirred for 10 min, then goethite and hematite were added, and the mixture was stirred for another 10 min.Then, with the support of the ARIM Support Office of Chitose University of Science and Technology, the coating was assessed by the use of FTIR spectroscopy to confirm that it was successful.We determined the concentration of the bio-modified TiO 2 NPs by the use of a gravimetric method.
Optimal Nanoparticle Concentration Assessment
First, to test the growth inhibition of Toxoplasma at NP concentrations that would not significantly affect host cell viability, toxicity tests were conducted on host cells in the absence of Toxoplasma using various iron oxide NPs (Figure 1).We found that the survival rate exceeded 80% at concentrations of 10 µg/mL or less for goethite, hematite, and magnetite, respectively.Therefore, we used concentrations of ≤10 µg/mL in subsequent experiments.
Concentration-Dependent Growth Inhibition by Iron Oxide Nanoparticles
Based on the results obtained from the cytotoxicity test, we conducted a growth inhibition test at NP concentrations that caused ≤20% toxicity.The relative numbers of Toxoplasma were significantly reduced at concentrations of ≥10 µg/mL for goethite and ≥1.0 µg/mL for hematite (Figure 2).These results suggest that iron oxide NPs of goethite and hematite may have growth inhibitory effects on Toxoplasma.
Surface Modification of Iron Oxide Nanoparticles with Tryptophan
Previous studies have shown that tryptophan coating on gold, silver, and platinum nanoparticles increases their growth inhibitory effect on Toxoplasma [31].Therefore, we
Concentration-Dependent Growth Inhibition by Iron Oxide Nanoparticles
Based on the results obtained from the cytotoxicity test, we conducted a growth inhibition test at NP concentrations that caused ≤20% toxicity.The relative numbers of Toxoplasma were significantly reduced at concentrations of ≥10 µg/mL for goethite and ≥1.0 µg/mL for hematite (Figure 2).These results suggest that iron oxide NPs of goethite and hematite may have growth inhibitory effects on Toxoplasma.
Concentration-Dependent Growth Inhibition by Iron Oxide Nanoparticles
Based on the results obtained from the cytotoxicity test, we conducted a growth inhibition test at NP concentrations that caused ≤20% toxicity.The relative numbers of Toxoplasma were significantly reduced at concentrations of ≥10 µg/mL for goethite and ≥1.0 µg/mL for hematite (Figure 2).These results suggest that iron oxide NPs of goethite and hematite may have growth inhibitory effects on Toxoplasma.
Surface Modification of Iron Oxide Nanoparticles with Tryptophan
Previous studies have shown that tryptophan coating on gold, silver, and platinum nanoparticles increases their growth inhibitory effect on Toxoplasma [31].Therefore, we
Surface Modification of Iron Oxide Nanoparticles with Tryptophan
Previous studies have shown that tryptophan coating on gold, silver, and platinum nanoparticles increases their growth inhibitory effect on Toxoplasma [31].Therefore, we applied tryptophan coating to goethite and hematite.FTIR spectroscopic analysis showed that tryptophan-coated goethite and hematite peaked in the same wave number range as tryptophan (Figure 3).This suggests that the iron oxide NPs were coated with tryptophan, albeit in small amounts.
Pharmaceutics 2024, 16, x FOR PEER REVIEW 5 of 10 applied tryptophan coating to goethite and hematite.FTIR spectroscopic analysis showed that tryptophan-coated goethite and hematite peaked in the same wave number range as tryptophan (Figure 3).This suggests that the iron oxide NPs were coated with tryptophan, albeit in small amounts.
Host Cytotoxicity Testing of Tryptophan-Coated Iron Oxide Nanoparticles
Before testing the inhibitory effect of the tryptophan-coated iron oxide NPs on Toxoplasma growth, we tested their toxicity in host cells.Strong toxicity (approximately 90% reduction in cell viability) was observed at a concentration of 50 µg/mL for tryptophancoated goethite, whereas concentrations up to 2.0 µg/mL of tryptophan-coated hematite resulted in a 20% reduction in cell viability (Figure 4).Based on these results, growth inhibition studies were conducted at concentrations below 25 µg/mL for tryptophan-coated goethite and 2.0 µg/mL for tryptophan-coated hematite.
Host Cytotoxicity Testing of Tryptophan-Coated Iron Oxide Nanoparticles
Before testing the inhibitory effect of the tryptophan-coated iron oxide NPs on Toxoplasma growth, we tested their toxicity in host cells.Strong toxicity (approximately 90% reduction in cell viability) was observed at a concentration of 50 µg/mL for tryptophancoated goethite, whereas concentrations up to 2.0 µg/mL of tryptophan-coated hematite resulted in a 20% reduction in cell viability (Figure 4).Based on these results, growth inhibition studies were conducted at concentrations below 25 µg/mL for tryptophan-coated goethite and 2.0 µg/mL for tryptophan-coated hematite.
Pharmaceutics 2024, 16, x FOR PEER REVIEW 5 of 10 applied tryptophan coating to goethite and hematite.FTIR spectroscopic analysis showed that tryptophan-coated goethite and hematite peaked in the same wave number range as tryptophan (Figure 3).This suggests that the iron oxide NPs were coated with tryptophan, albeit in small amounts.
Host Cytotoxicity Testing of Tryptophan-Coated Iron Oxide Nanoparticles
Before testing the inhibitory effect of the tryptophan-coated iron oxide NPs on Toxoplasma growth, we tested their toxicity in host cells.Strong toxicity (approximately 90% reduction in cell viability) was observed at a concentration of 50 µg/mL for tryptophancoated goethite, whereas concentrations up to 2.0 µg/mL of tryptophan-coated hematite resulted in a 20% reduction in cell viability (Figure 4).Based on these results, growth inhibition studies were conducted at concentrations below 25 µg/mL for tryptophan-coated goethite and 2.0 µg/mL for tryptophan-coated hematite.
Tryptophan-Coated Iron Oxide Nanoparticles Increase the Growth Inhibitory Effect of the Nanoparticles on Toxoplasma
To investigate the effect of the tryptophan coating on the growth inhibitory effect of iron oxide nanoparticles, we performed the growth inhibition test using tryptophancoated nanoparticles at various concentrations less than 50 µg/mL.The relative number of Toxoplasma was significantly reduced at a concentration ≥ 12.5 µg/mL of tryptophancoated goethite NPs.For hematite NPs, the relative number of Toxoplasma was significantly reduced at concentrations ≥ 1.0 µg/mL (Figure 5A,B).
Tryptophan-Coated Iron Oxide Nanoparticles Increase the Growth Inhibitory Effect of the Nanoparticles on Toxoplasma
To investigate the effect of the tryptophan coating on the growth inhibitory effect of iron oxide nanoparticles, we performed the growth inhibition test using tryptophancoated nanoparticles at various concentrations less than 50 µg/mL.The relative number of Toxoplasma was significantly reduced at a concentration ≥ 12.5 µg/mL of tryptophancoated goethite NPs.For hematite NPs, the relative number of Toxoplasma was significantly reduced at concentrations ≥ 1.0 µg/mL (Figure 5A,B).
In addition, a significant difference in the relative number of Toxoplasma was observed for both types of tryptophan-coated iron oxide NPs compared to the same concentration without coating.These results suggest that the tryptophan coating of iron oxide NPs may increase their growth inhibitory effect on Toxoplasma.
The Growth Inhibitory Effect of Iron Oxide Nanoparticles May Be Due to the Generation of Reactive Oxygen Species
Prior studies have suggested that the mechanism by which gold, silver, and platinum NPs inhibit growth involves the generation of reactive oxygen species (ROS) [32].To test whether the same mechanism of action is true for iron oxide NPs, we examined the role of ROS by adding the antioxidant Trolox [33,34] to the Toxoplasma growth inhibition assay medium.
Trolox attenuated the growth inhibition induced by tryptophan-coated goethite and hematite (Figure 6A,B).There was no significant difference in the non-tryptophan-coated goethite and hematite to the Trolox group, which may be because the lower concentrations of goethite and hematite did not show growth inhibition effects.These results suggest that ROS may be involved in the growth-inhibiting action of tryptophan-coated iron oxide NPs against Toxoplasma.In addition, a significant difference in the relative number of Toxoplasma was observed for both types of tryptophan-coated iron oxide NPs compared to the same concentration without coating.These results suggest that the tryptophan coating of iron oxide NPs may increase their growth inhibitory effect on Toxoplasma.
The Growth Inhibitory Effect of Iron Oxide Nanoparticles May Be Due to the Generation of Reactive Oxygen Species
Prior studies have suggested that the mechanism by which gold, silver, and platinum NPs inhibit growth involves the generation of reactive oxygen species (ROS) [32].To test whether the same mechanism of action is true for iron oxide NPs, we examined the role of ROS by adding the antioxidant Trolox [33,34] to the Toxoplasma growth inhibition assay medium.
Trolox attenuated the growth inhibition induced by tryptophan-coated goethite and hematite (Figure 6A,B).There was no significant difference in the non-tryptophan-coated goethite and hematite to the Trolox group, which may be because the lower concentrations of goethite and hematite did not show growth inhibition effects.These results suggest that ROS may be involved in the growth-inhibiting action of tryptophan-coated iron oxide NPs against Toxoplasma.
Discussion
Metal nanoparticles are known to have antimicrobial effects [19][20][21][22], and this study tested whether they could be applied to Toxoplasma.Although previous studies have shown that gold, silver, and platinum NPs exhibit anti-Toxoplasma effects [16], these are expensive metals, and therefore their extensive use, including in livestock, is financially probative necessitating the use of NPs of less expensive metals.Here, we confirmed the anti-Toxoplasmic effect and the lack of host cytotoxicity of NPs of iron oxide.
Since damage to host cells by iron oxide NPs (goethite, hematite, and magnetite) could cause strong side effects, we first examined their effect on host cell viability.Cell survival rates in the presence of each iron oxide nanoparticle exceeded 80% at concentrations of >10 µg/mL.Based on these results, we performed a growth inhibition test at concentrations of >10 µg/mL.
To determine the effect of iron oxide nanoparticles on Toxoplasma growth, we analyzed the relative survival of Toxoplasma after 48 h of incubation with iron oxide NPs in HFFs infected with Toxoplasma.We found that the relative number of Toxoplasma was significantly reduced at concentrations of ≥10 µg/mL for goethite and ≥1.0 µg/mL for hematite.The EC50 could not be calculated because the relative counts were not less than 50% at the concentrations used in this study.These results confirm the growth inhibitory effect of goethite and hematite NPs on Toxoplasma.Our results thus confirmed previous studies [16] demonstrating that metal NPs other than those bearing precious metals have anti-Toxoplasma effects.Considering the widespread use of anti-Toxoplasma drugs in humans and livestock, it is significant that an anti-Toxoplasma effect was observed in such a relatively inexpensive metal.
Tryptophan coating on gold, silver, and platinum nanoparticles has been shown to increase their growth inhibitory effect on Toxoplasma [31].Therefore, we thought that tryptophan coating on iron oxide nanoparticles would increase the growth inhibitory effect.We coated iron oxide NPs with tryptophan, and a solution of tryptophan dissolved in DMSO was analyzed by FTIR spectroscopy with the support of the ARIM Support Office of the Chitose University of Science and Technology.The results showed that tryptophancoated goethite and hematite showed peaks at 2500-3500 cm −1 , which is the specific wavenumber range of tryptophan.This result means that a small amount of tryptophan coated
Discussion
Metal nanoparticles are known to have antimicrobial effects [19][20][21][22], and this study tested whether they could be applied to Toxoplasma.Although previous studies have shown that gold, silver, and platinum NPs exhibit anti-Toxoplasma effects [16], these are expensive metals, and therefore their extensive use, including in livestock, is financially probative necessitating the use of NPs of less expensive metals.Here, we confirmed the anti-Toxoplasmic effect and the lack of host cytotoxicity of NPs of iron oxide.
Since damage to host cells by iron oxide NPs (goethite, hematite, and magnetite) could cause strong side effects, we first examined their effect on host cell viability.Cell survival rates in the presence of each iron oxide nanoparticle exceeded 80% at concentrations of >10 µg/mL.Based on these results, we performed a growth inhibition test at concentrations of >10 µg/mL.
To determine the effect of iron oxide nanoparticles on Toxoplasma growth, we analyzed the relative survival of Toxoplasma after 48 h of incubation with iron oxide NPs in HFFs infected with Toxoplasma.We found that the relative number of Toxoplasma was significantly reduced at concentrations of ≥10 µg/mL for goethite and ≥1.0 µg/mL for hematite.The EC 50 could not be calculated because the relative counts were not less than 50% at the concentrations used in this study.These results confirm the growth inhibitory effect of goethite and hematite NPs on Toxoplasma.Our results thus confirmed previous studies [16] demonstrating that metal NPs other than those bearing precious metals have anti-Toxoplasma effects.Considering the widespread use of anti-Toxoplasma drugs in humans and livestock, it is significant that an anti-Toxoplasma effect was observed in such a relatively inexpensive metal.
Tryptophan coating on gold, silver, and platinum nanoparticles has been shown to increase their growth inhibitory effect on Toxoplasma [31].Therefore, we thought that tryptophan coating on iron oxide nanoparticles would increase the growth inhibitory effect.We coated iron oxide NPs with tryptophan, and a solution of tryptophan dissolved in DMSO was analyzed by FTIR spectroscopy with the support of the ARIM Support Office of the Chitose University of Science and Technology.The results showed that tryptophancoated goethite and hematite showed peaks at 2500-3500 cm −1 , which is the specific wavenumber range of tryptophan.This result means that a small amount of tryptophan coated the surface of the goethite and hematite NPs.The tryptophan-coated iron oxide NPs were used for cytotoxicity testing, and all but 50 µg/mL of tryptophan-coated goethite resulted in survival rates exceeding 80%.To our knowledge, no previous studies have reported increased toxicity with tryptophan coating [26].Therefore, the reason for the very strong toxicity at 50 µg/mL of goethite in this study is not clear and is a subject for future investigation.
The growth inhibition effect of tryptophan-coated iron oxide NPs was verified, and significant growth inhibition was shown for both goethite and hematite.A comparison of the same concentration of NPs with and without the amino acid coating showed that the l-tryptophan-coated iron oxide NPs exhibited a significant growth inhibitory effect.As reported elsewhere [16], the tryptophan requirement of Toxoplasma may contribute to its increased sensitivity to the amino acid-coated NPs.Coating the nanoparticles with l-tryptophan might have led to an increased local concentration in the Toxoplasma as the parasite sought to acquire this nutrient from its host.However, it is not clear from the results of this study whether the iron oxide nanoparticles penetrate the parasite, and further analysis is needed to determine the mechanism by which the growth inhibitory effect of Toxoplasma was enhanced.
Prior studies have suggested that the mechanism of action of gold, silver, and platinum NPs involves decreasing the mitochondrial membrane potential by generating ROS [32].We confirmed the effect of adding Trolox, an antioxidant, on the relative viability of Toxoplasma in the presence of the NPs.The attenuation of growth inhibition by the addition of Trolox was confirmed in both tryptophan-coated goethite and hematite.There was no significant difference in the non-tryptophan-coated goethite and hematite compared to the Trolox group, which may be because the lower concentrations of goethite and hematite did not show growth inhibition effects.These results suggest that ROS may be involved in the growth-inhibiting action of tryptophan-coated iron oxide NPs against Toxoplasma, consistent with previous reports on gold, silver, platinum, and titanium dioxide [2,16].Previous studies have reported that ROS reduces the membrane potential of Toxoplasma, thereby decreasing the production of ATP and causing a growth-inhibitory effect, and it is possible that a similar mechanism of action caused the growth-inhibitory effect [8].The fact that the addition of Trolox did not result in 100% relative parasite survival suggests that factors other than ROS development may be involved in the growth inhibition effect, which needs to be verified in the future.
Conclusions
Our data show that iron oxide NPs inhibit the growth of Toxoplasma tachyzoites in vitro.Goethite and hematite show promising anti-Toxoplasma properties.Furthermore, the coating of goethite and hematite with l-tryptophan enhances their anti-Toxoplasma action without a corresponding increase in host cell toxicity.Collectively, our findings support the potential of nanoparticles as novel treatment agents for toxoplasmosis.In addition, ROS may be involved in this growth inhibitory effect.The demonstration of the anti-toxoplasmic effect of iron oxide, a relatively inexpensive metal, in this study is very important for the future use of anti-toxoplasmic drugs in a wide range of human and animal species.Future research will aim to further strengthen the growth-inhibitory effect of iron oxide nanoparticles by elucidating the more detailed mechanism of action and clarifying what points affect the growth-inhibitory effect.
Figure 1 .
Figure 1.In the absence of T. gondii infection, host monolayers were treated with NPs at the effective anti-T.gondii concentration, and cell viability was determined after a 48 h incubation.HFF was seeded at a desired density of 4.0 × 10 4 cells/well.The experiment was conducted three times independently in triplicate.The data shown are the means ± standard deviation (SD).
Figure 2 .
Figure 2. Relative number of Toxoplasma parasites after 48 h of infection of HFFs with Toxoplasma and addition of iron oxide nanoparticles (goethite, hematite, and magnetite).Figures are triplicates and averages of three independent runs.Data are means ± standard deviation (SD).Experiments were performed in triplicate and repeated three times independently; ns, not significant at p > 0.05; *, significant at p < 0.05.
Figure 1 .
Figure 1.In the absence of T. gondii infection, host monolayers were treated with NPs at the effective anti-T.gondii concentration, and cell viability was determined after a 48 h incubation.HFF was seeded at a desired density of 4.0 × 10 4 cells/well.The experiment was conducted three times independently in triplicate.The data shown are the means ± standard deviation (SD).
Figure 1 .
Figure 1.In the absence of T. gondii infection, host monolayers were treated with NPs at the effective anti-T.gondii concentration, and cell viability was determined after a 48 h incubation.HFF was seeded at a desired density of 4.0 × 10 4 cells/well.The experiment was conducted three times independently in triplicate.The data shown are the means ± standard deviation (SD).
Figure 2 .
Figure 2. Relative number of Toxoplasma parasites after 48 h of infection of HFFs with Toxoplasma and addition of iron oxide nanoparticles (goethite, hematite, and magnetite).Figures are triplicates and averages of three independent runs.Data are means ± standard deviation (SD).Experiments were performed in triplicate and repeated three times independently; ns, not significant at p > 0.05; *, significant at p < 0.05.
Figure 2 .
Figure 2. Relative number of Toxoplasma parasites after 48 h of infection of HFFs with Toxoplasma and addition of iron oxide nanoparticles (goethite, hematite, and magnetite).Figures are triplicates and averages of three independent runs.Data are means ± standard deviation (SD).Experiments were performed in triplicate and repeated three times independently; ns, not significant at p > 0.05; *, significant at p < 0.05.
Figure 3 .
Figure 3. Tryptophan-coated and uncoated iron oxide nanoparticles (goethite and hematite), as well as tryptophan and DMSO, were analyzed by FTIR spectroscopy.The vertical axis shows absorbance, and the horizontal axis shows wavenumber (cm −1 ).
Figure 4 .
Figure 4.The cytotoxicity testing of tryptophan-coated iron oxide nanoparticles (goethite and hematite).The maximum concentration was adjusted for both goethite and hematite, and three concentrations were prepared by two-fold dilution.Data are means ± standard deviation (SD).
Figure 3 .
Figure 3. Tryptophan-coated and uncoated iron oxide nanoparticles (goethite and hematite), as well as tryptophan and DMSO, were analyzed by FTIR spectroscopy.The vertical axis shows absorbance, and the horizontal axis shows wavenumber (cm −1 ).
Figure 3 .
Figure 3. Tryptophan-coated and uncoated iron oxide nanoparticles (goethite and hematite), as well as tryptophan and DMSO, were analyzed by FTIR spectroscopy.The vertical axis shows absorbance, and the horizontal axis shows wavenumber (cm −1 ).
Figure 4 .
Figure 4.The cytotoxicity testing of tryptophan-coated iron oxide nanoparticles (goethite and hematite).The maximum concentration was adjusted for both goethite and hematite, and three concentrations were prepared by two-fold dilution.Data are means ± standard deviation (SD).
Figure 4 .
Figure 4.The cytotoxicity testing of tryptophan-coated iron oxide nanoparticles (goethite and hematite).The maximum concentration was adjusted for both goethite and hematite, and three concentrations were prepared by two-fold dilution.Data are means ± standard deviation (SD).
Figure 5 .
Figure 5. Toxoplasma growth inhibition using tryptophan-coated iron oxide nanoparticles.Tryptophan-coated iron oxide nanoparticles were added to Toxoplasma-infected cells, and the relative number of Toxoplasma was calculated after 48 h of incubation.(A) Results for tryptophan-coated goethite; (B) results for tryptophan-coated hematite.Data are means ± standard deviation (SD).Experiments were performed in triplicate and repeated three times independently; significant at p < 0.05.
Figure 5 .
Figure 5. Toxoplasma growth inhibition using tryptophan-coated iron oxide nanoparticles.Tryptophancoated iron oxide nanoparticles were added to Toxoplasma-infected cells, and the relative number of Toxoplasma was calculated after 48 h of incubation.(A) Results for tryptophan-coated goethite; (B) results for tryptophan-coated hematite.Data are means ± standard deviation (SD).Experiments were performed in triplicate and repeated three times independently; *, significant at p < 0.05.
Figure 6 .
Figure 6.The effect of the antioxidant Trolox on the anti-Toxoplasma effect of iron oxide nanoparticles.Trolox was added after the addition of iron oxide nanoparticles, and the relative survival of Toxoplasma after incubation was calculated.The results of (A) goethite and (B) hematite are shown.Data are means ± standard deviation (SD).Experiments were performed in triplicate and repeated three times independently; ns, not significant at p > 0.05; *, significant at p < 0.05.
Figure 6 .
Figure 6.The effect of the antioxidant Trolox on the anti-Toxoplasma effect of iron oxide nanoparticles.Trolox was added after the addition of iron oxide nanoparticles, and the relative survival of Toxoplasma after incubation was calculated.The results of (A) goethite and (B) hematite are shown.Data are means ± standard deviation (SD).Experiments were performed in triplicate and repeated three times independently; ns, not significant at p > 0.05; *, significant at p < 0.05. | 6,749.4 | 2024-03-01T00:00:00.000 | [
"Medicine",
"Materials Science",
"Environmental Science"
] |
A New Method Used for Traveling salesman problem Based on Discrete Artificial Bee Colony Algorithm
We propose a new method based on discrete Artificial Bee Colony algorithm (DABC) for traveling salesman problem. We redefine the searching strategy and transforming mechanism of leading bees, following bees and scout bees according to discrete variables. The transition of swarm role is based on ratios factor of definition. Leading bees use 2-Opt operator and learning operator to accelerate the convergence speed and to search the neighborhood. The searching of following bees introduces tabu table to improve the local refinement ability of the algorithm. Scouts bees define an exclusive operation to maintain the diversity of population, so it is better to balance the exploration and exploitation ability of the algorithm. Finally, the experimental results show that the new algorithm can find relatively satisfactory solution in a short time, and improve the efficiency of solving the traveling salesman problem.
Introduction
Traveling salesman problem (it is abbreviated in TSP) [1] is an important combinational optimization problem in the area of mathematics. It belongs to Non-Deterministic Polynomial (NP) problem [2]. Although there are some precise algorithms which can be used to solve the problem, the principle of precise algorithms is complex, and it can produce "combination explosion problem" along with the increase number of city, therefore, the domestic and foreign scholars have been trying to seek a highly efficient and stable algorithm for solving this complex problem.
Artificial bees colony algorithm (ABC) [3] is one of heuristic search algorithms based on swarm intelligence, which was proposed by Karaboga et al. [4] in 2005. ABC algorithm [5] is based on the self-organization of the swarm simulation model with the advantages of less setting parameters, strong robustness, it has received extensive attention of scholars both at home and abroad, and been applied in many fields.
Nowadays, many researchers have studied the new algorithm about Artificial bees colony for TSP. Sharma P et al. [6] showed that bees speculative modified over time and based on the best solution found by the bee itself and the swarms of bees were dynamically divided into smaller groups and search process was performed by an independent smaller group of bees. Hong-Tao et al. [7] proposed a discrete artificial bee colony algorithm. And he introduced a tabu list and a repulsion operator.
The above methods almost are used for solving continuous domain optimization problems. However, ABC algorithm is relatively few used in the aspect of discrete domain application. To improve the performance of TSP solution, we propose improved discrete Artificial Bee Colony algorithm through redefining leading bees, following bees and scouts which better coordinates and balances the exploration and mining process of ABC algorithm. To facilitate the description, this paper also gives some definitions. We present a new discrete Artificial Bee Colony algorithm for traveling salesman problem. This new scheme takes balance of space exploration and the local refinement into consideration. Finally, we conduct some experiments to verify its performance. The results show that the new algorithm has a good effect on solving TSP question.
Artificial Bees Colony Algorithm and Discretization
Optimization process of artificial colony algorithm simulates the behavior of bees searching a high quality nectar source. It divides artificial bee colony into leading bees, following bees and scouts according to their division of labor. They change roles based on certain conditions. Each bee is a possible solution of corresponding problem, profitability ratios of nectar source represents the quality of the solution. Each leading bee is corresponding to a certain nectar source, and in the process of iteration it starts to search among its neighborhood. After searching, leading bees would share the searched information with the following bee. Following bees choose nectar source according to certain probability, and they keep on searching in their neighborhood. If leading bees within a given number of searching don't accept better nectar source, they will give up this nectar source and leading bees would be transformed into scouts to randomly search feasible new nectar source.
ABC algorithm is an intelligent optimization algorithm, and exploration and production is two main factors, which decides to the performance of swarm intelligence optimization; the better exploring ability and the stronger searching ability for individual in globally searching unknown area. What this amounts is to, global optimization capability is stronger, the exploiting ability is better. The ability of individual searching optimal solution in local area is stronger, ability of local refinement in better. Therefor, to ensure the solution quality of ABC algorithm, it needs to coordinate and balance the exploration and mining process, which is a core problem in intelligent algorithm. When solving the problem of continuous variables, ABC algorithm lacks consideration of the exploration and exploitation ability. That is difficult to guarantee solving speed and quality of algorithm. Here are four definitions for discretization ABC.
Profitability ratio i r : the ratio between searched nectar source nectar amounts of each bee i fit and nectar source nectar amounts of optimum individual in swam best fit . For TSP, the relation of i fit and objective function )
Discrete Artificial Bee Colony algorithm for TSP
According to the above definitions, we divide artificial bee colony into leading bees, following bees and scouts according to their division of labor. They change roles based on certain conditions. Each bee is a possible solution of corresponding problem, profitability ratios of nectar source represents the quality of the solution. We redefine the three bees.
Improved Leading Bees
The leading bees in the discrete ABC algorithm have the same function as ABC algorithm. It searches an optimal nectar source in the neighborhood of each nectar source. But it is a discrete variable problem for solving TSP, generation mechanism of neighborhood solution needs to be redefined. So the detailed processes of improved leading bees are as follows. Firstly, this paper adopts 2-opt neighborhood structure to search neighborhood of each nectar source at the beginning of optimization. When operating 2-opt neighborhood, secondly it Figure 1(b).
Figure 1. 2-opt neighborhood operation
Comparing i X with i X , the real operation of 2-opt is that it inverts the second city of first side as the the first city of second side.
Improved Following Bees
The following bees in the discrete ABC algorithm have the same function as ABC algorithm. It calculates the probability based on the roulette method and formula (2) to choose one nectar source and it starts to conduct local searching.
SN is the total number of nectar source. The improved following bees in the discrete ABC algorithm introduce Tabu table searching information of bees nearest nectar source. For example, the nearest neighborhood solution i X of nectar source i X in example 2 is obtained by converting city 2 and city 4. If we again make 2-opt transformation for side (2,5) and side (1,4) in this two cities respectively, and it will get neighborhood solution i X which is meaningless. In order to avoid the bees repeated searching within the same neighborhood and improve the production ability of algorithm, for Tabu table i tabu in example 2, it just needs to record (2,4) two points, namely record the second city of first side and first cit of second side.
Improved Scouts
The scouts are transformed by leading bees and have the responsible for finding the individual with possibility falling into a local optimum and updating it. That can reduce the probability of precocity. Leading bees are transformed into scouts, which satisfies the following conditions: it does not obtain better nectar source within the setting searching number. As we all know, there are three questions among scouts shift mechanism and searching behavior in ABC algorithm.
a. The changing role of scouts depends on the given searching number. This parameter is different for solving different practical problems and difficult to set. Also setting unsuitable parameters will affect the ability of algorithm to jump out of local optimal.
b. Scouts are transformed only after individual changing into precocity and it explores new nectar sources, which leads to slow speed to find the global optimal solution. c. Scouts randomly search new nectar sources in ABC algorithm without considering In order to solve the above shortcomings, this paper defines the profitability ratios, leading bees are transformed into scouts based on the index. The advantage of this definition, on the one hand, is that the index is more likely to be set when solving different problems. On the other hand, swarm role and search mechanism relies on the dynamic changing of searching number. At the optimizing initial stage, the profitability ratios is relatively poor, leading bees immediately turn into scouts. And it operates exclusive operation based on roulette method, so that it can find better nectar sources in global scope. In the late optimization, the profitability ratios are all good, leading bees no longer turn into scouts. The search mechanism is transformed from 2-opt to learning operation based on roulette method. Namely, we should adequately consider the individual species diversity at the initial stage to improve exploring ability of ABC algorithm. At the end of optimization, population information sharing should be taken into account to improve the production ability and optimization speed of ABC algorithm.
The detailed process of the proposed ABC algorithm is as follows: a.
Step 1. Initializing the swarm. Randomly initializing nectar sources, namely randomly generating population initial solution, and calculating profitability ratios of each nectar source by formula (1). b.
Step 2. The searching stage of leading bees. Calculating profitability ratios. If profitability ratios are greater than or equal to the setting value r, then leading bees execute 2opt operation, search new nectar sources and get candidate neighborhood solution i X .
Otherwise, leading bees adopt roulette method based on probability calculated by formula (2) Step 3. The searching stage of following bees. Following bees adopt roulette method based on probability calculated by formula (2) Step 4. The searching stage of scouts. Calculating profitability ratios. If profitability ratios are greater than or equal to the setting value r. r is a setting value. Then it gives up the nectar source i X whose profitability ratios is less than r. It adopts roulette method based on probability calculated by formula (2)
The Effect of Profitability Ratios Setting Value on DABC
The setting value r of profitability ratios is the main parameter in Discrete ABC algorithm(DABC). We make simulation experiments to analyze the effect of r on performances of algorithm solution under the MATLAB platform. We adopt different r to conduct experiments under the other same parameters conditions. Setting maximum iterations From Table 1 we can know that when r gradually reduces about solution time, the average running time is little-changed. When r=0.7, 0.8, 0.9, average running time is relatively short. And r=0.8, average running time is 9.0341 which is the shortest time. But as a whole, the average running time of algorithm has a little change. This is mainly because whatever value r is, the sum of leading bees, following bees and scouts remains unchanged in the iteration process of algorithm. In current iteration, leading bees have been transformed into scouts, they no longer perform operations of leading bees in the next iteration. Also search strategy and complexity of swam has little difference at different stage based on profitability ratios. When r gradually reduces about solution quality, the solution performance gets good and then gradually becomes worse . When r=1, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0, average value of DABC is greater than 3.5×10 -4 . The worst values are all greater than 3.6×10 -4 . However, when r=0.7, 0.8, 0.9, average value is less than 3.5×10 -4 . The worst values are all less than 3.6×10 -4 . When r=0.8, average value is 3.43×10 -4 , worst value is 3.49×10 -4 . Best value is 3.34×10 -4 . The standard deviation is 3.58×10 -2 just over the standard deviation (3.50×10 -2 ) when r=0.7. Therefore, r=0.8 is the best value for DABC.
The Experiment of Algorithms Performance Comparison
In order to further verify the feasibility and effectiveness of this paper's method, we choose multiple instances in international universal test library for testing, and use testing results to make a comparison to Resource Recovery Solutions Artificial Bees Colony (RRSABC) [8], Ant Colony Optimization [9] (ACO) and ABC.
In Table 2.
From Table 2, RRSABC algorithm gets the known optimal solutions in Berlin52, Oliver30 and Eil51. But iteration number of DABC has reduced by 98percent. What's more, steps of DABC are not complicated. The average value has increased by 0.5% (Not exceed 0.5%). Compared with ACO algorithm, the best value and average value is relatively small, and for Bays29, Oliver30 and Dantzig42, the standard deviation is smaller. For the five instances, the running time of DABC has saved by 98.2%, 98.3%, 98.66%, 98.96 and 98.98% respectively. ABC algorithm also can obtain the results closely to known optimal solutions for all instances. For Oliver30 and Bays29, DABC algorithm gets the same results as known optimal solutions. For Dantzig42, calculation result of DABC algorithm has decreased by 19.8% compared with ABC algorithm. Figure 2 The average value of DABC algorithm is relatively small compared with ABC algorithm for Oliver30, Dantzig42 and Bays29. ABC algorithm is mainly based on the ACO algorithm and has combined with other operations. When the number of population in ABC is equal to that in ACO, the running time in ABC is closely to that of ACO at least. Nevertheless, the running time in ACO is relatively long. Therefor, DABC algorithm has the better solution performance in terms of solution time and solution quality compared with ACO, ABC and RRSABC algorithm.
Conclusion
This paper proposes a new discrete artificial colony algorithm for solving TSP question. It extends continuous artificial swarm optimization algorithm to discrete domain. The new algorithm makes transition for colony characters and search mechanism based on income ratios index of defination. It defines rejection operator to keep the diversity of population, and it introduces Tabu table and defines the learning operator to improve the local refinement ability of the algorithm and the optimal speed. Therefore, the new scheme can better coordinate space exploration and the local refinement ability of ABC algorithm at the same time. What's more, it accelerates convergence speed of the algorithm. The experimental results show that the algorithm can find relatively satisfactory solution in a short time and improve the efficiency of solving the TSP. In the future, we would find more effective ABC algorithms to improve optimum searching method. | 3,385.2 | 2016-03-01T00:00:00.000 | [
"Computer Science"
] |
Synthesis, structures and magnetic properties of [(η9-C9H9)Ln(η8-C8H8)] super sandwich complexes
Sandwich complexes are an indispensable part of organometallic chemistry, which is becoming increasingly important in the field of lanthanide-based single molecule magnets. Herein, a fundamental class of pure sandwich complexes, [(η9-C9H9)Ln(η8-C8H8)] (Ln=Nd, Sm, Dy, Er), is reported. These neutral and sandwiched lanthanide compounds exclusively contain fully π-coordinated coplanar eight and nine membered CH rings. The magnetic properties of these compounds are investigated, leading to the observation of slow relaxation of the magnetization, including open hysteresis loops up to 10 K for the Er(III) analogue. Fast relaxation of the magnetization is likewise observed near zero field, a highly important characteristic for quantum information processing schemes. Our synthetic strategy is straightforward and utilizes the reaction of [(η8-C8H8)LnI(thf)n] complexes with [K(C9H9)]. Although all compounds are fully characterized, structural details of the title compounds can also be deduced by Raman spectroscopy only.
A popular model for the SMM behavior of mononuclear lanthanide complexes focuses on the stabilization of the corresponding lanthanide ions m J ground state by tuning the local electron density around the lanthanide ion generated by the ligand sphere 27 . Two prominent examples proving this concept are dysprosium and erbium. For example, the highest m J state (±15/2) for dysprosium(III) has an oblate shape, thus an axial ligand field enhances the anisotropic properties of dysprosium containing complexes 35 . Recently, significant advances were reported by using homo-and heteroleptic cyclopentadienyl based dysprosium(III) metallocene cations, which exhibit a highly axial ligand field, enabling record high anisotropy barriers [32][33][34] . On the other hand the highest m J state of erbium(III) is prolate shaped, therefore, an equatorial ligand field is beneficial in this case. This can be achieved by introducing one or two η 8 -C 8 H 8 ligands, which exert a strong equatorial ligand field, into the coordination sphere of erbium ions 27,28,[35][36][37] . These two examples highlight that the local symmetry generated around the central lanthanide ion, determined by the ligand field and the rigidity of the complex, plays a crucial role in the design of SMMs 23,24,[38][39][40][41][42] . A review published recently pointed out that other, uncommon ligand systems, such as the cyclononatetraenyl anion may shed light on interesting properties in terms of SMM behavior and fundamental magneto-structural correlations 23 .
Herein, we present a long sought for class of sandwich complexes [(η 9 -C 9 H 9 )Ln(η 8 -C 8 H 8 )], which exclusively contain fully π-coordinated eight and nine-membered rings. Synthesizing these compounds was already attempted by Streitwieser et al. 43 in 1973, shortly after the first successful synthesis of KC 9 H 9 was reported by Katz and coworkers 43,44 . Their strategy was based on a onepot reaction between LnCl 3 (Ln=Ce(III), Pr(III), Nd(III), Sm (III)), K 2 C 8 H 8 , and KC 9 H 9 . However, they could only isolate complexes of the type [(η 8 -C 8 H 8 )LnCl(thf) 2 ] thereby highlighting, that the C 9 H 9anion does not form sandwich complexes analogous to C 8 H 8 2-. After a 45 years quest for [(η 9 -C 9 H 9 )Ln(η 8 -C 8 H 8 )], we now report a synthetic protocol based on two distinct steps.
Results
Synthesis and crystallographic characterization of [(η 9 -C 9 H 9 ) Ln(η 8 -C 8 H 8 )]. First, we synthesized the starting material KC 9 H 9 following the procedure of Katz et al. 44 The 1 H-NMR spectrum shows only one sharp resonance at δ 7.05 ppm, which is attributed to the nine ring protons and consistent with the regular 1all-cis-configuration being present in solution. Additionally, the molecular structure of the dimethoxyethane solvate [(η 9 -C 9 H 9 )K (DME) 2 ] (1) was established by X-ray diffraction experiments. A flat and aromatic nine-membered carbon ring is observed with C-C bond lengths ranging from 1.389(3) Å to 1.394(3) Å, which is in the expected region for aromatic sp 2 -hybridized carbon atoms (Fig. 2). Only the perfectly nonagonal all cis-isomer was found in the solid state and no positional disorder, indicating the presence of the cis,cis,cis,trans-cyclononatetraenyl isomer, was observed. This is in contrast to very recent findings from Nocton et al. 11 , who also reported on the solid-state structure of [(η 9 -C 9 H 9 )K(OEt 2 )]. They obtained KC 9 H 9 from diethyl ether as a mixture of cis-and trans-isomers of the C 9 H 9ring and discussed the influence of the isomer on its subsequent reactivity. The potassium ion is centered below the ring and shows a complete η 9 -coordination with K-C bond distances ranging from 3.085 (2)-3.154(2) Å.
Single crystals of the heteroleptic sandwich complexes [(η 8 -C 8 H 8 )Ln(η 9 -C 9 H 9 )] (Ln=Nd (3a), Sm (3b), Dy, (3c), Er (3d)) were obtained from toluene. The solid-state structures of 3c and 3d show a disorder of the eight and the nine-membered rings (see Supplementary Information for details). Especially the molecular solid-state structure of 3d exhibits a complicated disorder with split positions of the Er(III) ion, showing slight indications of ring slipping and tilting in both ligands. The Er-C distances in the eight-membered ring vary between 2.406(11) Å and 2.670(10) Å with 5 carbon atoms closer located to the Er(III) ion than the others. Similarly, the Er-C distances in the nine-membered ring vary between 2.468(12) Å and 2.733(10) Å with four carbon atoms in closer proximity to the Er(III) ion (see Supplementary Table 10 for detailed bond lengths). However, this might also be caused by the unusual split Er(III) positions and thus, do not reflect the actual binding mode of the two aromatic moieties. We, therefore, performed a DFT geometry optimization and found the energetic minimum for 3d to be a perfect sandwich-type configured [(η 9 -C 9 H 9 )Er(η 8 -C 8 H 8 )] molecule (see Fig. 5). As a result, we propose 3d to comprise two fully π-coordinated and ARTICLE coplanar aromatic ligands, although the solid-state structure does not undoubtedly proof this assumption. On the other hand, 3a and 3b did not show this type of disorder. Their solid-structures exhibit perfect sandwich-type configuration with both rings bound to the central lanthanide ion in a coplanar fashion (Fig. 5).
Only the structural parameters of 3a are discussed here in detail (Ln-Cg distances for 3a-d are given in Table 1). In compound 3a, the neodymium atom is centered between both rings with Nd-C bond lengths of 2.613(8)-2.653(8) Å to the eight-membered ring and Nd-C bond lengths of 2.845(6)-2.915 (7) Å to the nine-membered ring. The distances of the Nd atom to the ring centroids (Cg) are Nd-Cg(8) 1.8925(3) Å and Nd-Cg (9) 2.0441(3) Å. The Cg(8)-Nd-Cg(9) angle accounts for 176. 47 (1)°and underpins an almost ideal coplanar arrangement. Interestingly, the η 8 -C 8 H 8 unit is, albeit the lower ring diameter, significantly closer to the neodymium ion than the η 9 -C 9 H 9 unit. This is probably caused by the higher negative charge of η 8 -C 8 H 8 compared to η 9 -C 9 H 9 , leading to a stronger electrostatic attraction.
Raman-spectroscopic analysis. We further investigated the bonding situation and ligand aromaticity using Raman spectroscopy and vibrational analysis. Fourier transform Raman (FT-Raman) spectra of 3a-3d were recorded powdered samples (Fig. 6). The band assignments were validated by quantum chemical calculations. The Raman spectra can be divided in two sections: (i) above 300 cm -1 the spectra of all molecules are almost identical as the signals are solely attributable to both sandwich ligands. Vibrational coupling to the lanthanide cations is not expected due to the orthogonality of the in-plane vibrations of the ligands with respect to that of the lanthanide-ring centroid 46 . Therefore, the signals at 3042 (η 8 -C 8 H 8 ) and 3006 cm -1 (η 9 -C 9 H 9 ) are attributed to the fully symmetric C-H-valence motions, those at 1495 (η 8 -C 8 H 8 ) and 1517 cm -1 (η 9 -C 9 H 9 ) to the antisymmetric C-C-stretching vibrations of the ligands. A third group of bands belongs to the (local) symmetric ring breathing modes at 749 cm -1 (ν sym (η 8 -C 8 H 8 )) and at 681 cm -1 (ν sym (η 9 -C 9 H 9 )). Analyzing these modes is an unambiguous proof of the ring size and the bond strength within these aromatic ligand systems. According to normal coordinate analyses on C 5 H 5 -, C 6 H 6 and C 7 H 7 + 47 the stretching force constant values of the C-H and C-C bonds are each of comparable size. Assuming, this is furthermore true for larger aromatic C n H n monocyclic ligand systems, the approximate wavenumber of the fully symmetric ring breathing mode is easily calculated using a mathematical expression deduced in the Supplemental Information (see Supplementary Equation 1). This formula nicely reproduces the observed ring breathing mode energies of the two ligands (ν(C 8 H 8 2 -) = 754 cm -1 (calc. 761 cm -1 ) and ν(C 9 H 9 -) = 680 cm -1 (calc. 680 cm -1 )) and therefore, confirms the comparable bonding situation in these ligand systems with those of aromatic ligands like C 5 H 5 -, C 6 H 6 and C 7 H 7 + (see SI for details). (ii) At vibrational energies lower than 300 cm -1 lanthanide-ring centroid stretching modes are expected in the Raman spectra of [(η 9 -C 9 H 9 )Ln(η 8 Table 4b in the SI). However, 3a-d are rare cases in modern organometallic chemistry, in which the coordination mode of the ligands can be determined by Raman spectroscopy as sole method.
Magnetic properties of [(η 9 -C 9 H 9 )Er(η 8 -C 8 H 8 )] (3d). Although the single-crystal X-ray structures of 3c and 3d show some disorder, we conclude an almost coplanar η 9 -C 9 H 9 and η 8 -C 8 H 8 arrangement of the ligands as observed in 3a and 3b, based on the Raman-spectroscopic analysis. This arrangement is known to exert an equatorial ligand field, which drastically stabilizes prolate shaped m J states of lanthanide ions. The prime example for this family of trivalent lanthanide ions in terms of single molecule magnetic behavior is without doubt erbium (vide supra), where the equatorial ligand field exerted by a η 8 -C 8 H 8 ligand, can yield SMMs with not just large energy barriers to the relaxation of the magnetization, but also leading to open hysteresis loops at temperatures as high as 10 K 26,27,36,48 . We, therefore, carried out detailed magnetic studies on compound 3d, to test whether the asymmetric η 8 -C 8 H 8 /η 9 -C 9 H 9 ligand field enhances the magnetic anisotropy of the sandwiched erbium ion. The rationale is two-fold: (i) as mentioned above η8-C 8 H 8 ligands exert a strong equatorial ligand field, resulting in erbium compounds showing slow relaxation of the magnetization; and (ii) the introduction of a larger cyclic ring as η 9 -C 9 H 9 could allow a closer Er-C contact, which could increase the equatorial ligand field, therefore enhancing the anisotropic characteristics of 3d. DC magnetic susceptibility studies of 3d were conducted in an applied field of H dc = 1 kOe. At room temperature the χ M T (T) (χ M is the molar magnetic susceptibility) value is 11.25 cm 3 K mol -1 , in agreement with the expected value for an isolated Er (III) ion (c.f. 11.48 cm 3 K mol -1 for J = 15/2, g J = 6/5). The moment decreases smoothly upon cooling, until ca. 6 K, where it sharply decreases to 7.13 cm 3 K mol -1 at 2 K (see Supplementary Fig. 11). The abrupt drop in χ M T(T) indicates magnetic blocking, Raman emission/a.u. where pinning of the magnetic moment in the immobilized crystalline material occurs. The dynamic behavior of 3d was probed via magnetic susceptibility AC studies under zero applied DC field. A single peak is observed in the temperature and frequency dependent out-of-phase magnetic susceptibility, i.e. χ M "(T) and χ M "(ν), respectively. This result is in agreement with the dynamic studies for [(η 8 -C 8 H 8 ) 2 Er] -28 , while they differ from the asymmetric [(η 5 -C 5 H 5 )Er(η 8 -C 8 H 8 )] counterparts 24 , where two maxima were observed. The χ M "(T, ν) reveals a temperature dependent maximum at temperatures between 16-26 K, whilst below 15 K the maximum in χ M "(ν) remains practically constant (Fig. 7a). Between 18 and 26 K, the Arrhenius analysis of τ at different temperatures show a relaxation dominated thermally activated Orbach process, whereas below 9 K temperature independent processes dominate. The curvature between 10 and 15 K suggests that other relaxations pathways, such as Raman, are also active. The distribution of the relaxation parameter (α) likewise indicates a narrow distribution of relaxation times between 20 K and 26 K (α ≤ 0.18(1)), while for temperatures below 15 K the parameter is greater (α ≥ 0.18(1)). The energy barrier U eff of 251(1) cm -1 and τ 0 = 1.3(2) × 10 -10 s (Fig. 7b) are very similar to the ones observed for homoleptic and heteroleptic erbium complexes 24,27,28,36 . The plateau at temperatures between 2 and 5 K marks the quantum tunneling of the magnetization regime, with a τ QTM = 0.18(1) s. Application of an optimal field of 2 kG (at which relaxation is slower), efficiently suppressed QTM, leading to an almost purely temperature dependent relaxation (green symbols in Fig. 7b and SI (see Supplementary Fig. 14)), with a slightly enhanced U eff = 261(1) cm -1 .
An open magnetic hysteresis is the ultimate proof of the strong anisotropic behavior in SMMs and their bistable magnetic behavior. Extrapolation of the Arrhenius data to low temperature indicates that the observation of magnetic hysteresis below 12 K is feasible, where the relaxation time is 100 s. To confirm the SMM behavior and the slow relaxation observed through AC studies, magnetization hysteresis loops were collected between 1.8-10 K. Figure 7c shows butterfly-like hysteresis loops between 2 and 10 K and a field ranging from ±2 T, leading to a blocking temperature (T B ) of 10 K. Note that, albeit the energy barrier being rather large, the hysteresis loops are practically close at zero field, strongly indicating that QTM is rather efficient, as commonly observed in lanthanide-based SMMs.
To gain deeper insight into the relaxation mechanism and the anisotropic magnetic properties of 3d, CASSCF/SO-RASSI/ SINGLE_ANISO calculations were performed [49][50][51][52][53][54] . Due to the highly disordered character of the crystal structure of 3d, CASSCF calculation were carried out employing an optimized crystal structure (see SI for details). The electronic calculation predicts a highly axial ground state with g z = 17.95 and g x,y ≈ 10 -5 . As observed in Fig. 7d, the anisotropy axis is perpendicular to the η 8 -C 8 H 8 and η 9 -C 9 H 9 planes. Employing the ligand field parameters from electronic calculations, we find that the ground, first and second excited states are almost colinear and highly pure c Hysteresis measurements for 3d between ±2 T and from 1.8 K to 10 K employing a field sweep rate of 700 G/s; d optimized structure of 3d and direction of the principal magnetic anisotropy axis obtained from CASSCF calculations (green arrow). e ab initio calculated electronic states of the J = 15/2 manifold of the 4 I term of 3d and the most probable relaxation pathway for the magnetization represented by the red arrows, involving spin phonon excitation to the first and second doublets. The thick black lines represent the Kramers doublet states as function of their magnetic moments m J = ±15/2 and ±13/2 and ±1/2 states, respectively. The relative energies for the first and second excited state are 140 and 268 cm -1 . The succeeding excited states are highly pure and huddled over 330-490 cm -1 . As it can be observed in Fig. 7e, ab-initio results reproduce rather well the χ M T(T) and M(H) (see Supplementary Fig. 11) with only small differences. The discrepancies might arise by structural distortions not reflected in the geometry optimization. Using the average matrix elements of magnetic moment between the electronic states, it is predicted that the most efficient magnetic relaxation pathway is to occur via thermally assisted QTM through the second excited state at 268 cm -1 . As observed, this state is very close to the U eff obtained from dynamic studies (cf.~260 cm −1 (Fig. 7e)). Interestingly, the energy barrier is also very similar to the antisymmetric vibration of the C 8 /C 9 rings observed in the Raman spectrum (240 cm -1 ). As molecular vibrations have been predicted to facilitate spin-phonon coupling, these could be relevant for the relaxation in 3d 33 . Note that the strongly equatorial ligand field exerted by the η 8 -C 8 H 8 and η 9 -C 9 H 9 ligands is optimal at stabilizing the largest m J state for Er(III), characterized by a prolate electron density, as demonstrated by the magnetic studies and supported by CASSCF calculations. In contrast, for the Dy(III) ions an axial ligand field is more suitable to stabilize the largest m J = 15/2 state, thus the anisotropic magnetic properties in [(η 9 -C 9 H 9 )Dy(η 8 -C 8 H 8 )] are expectedly worse, as confirmed by AC tests and other reports 27,55 .
Discussion
By synthesizing [(η 9 -C 9 H 9 )Ln(η 8 -C 8 H 8 )] (Ln=Nd, Sm, Dy, Er), we unveiled a fundamental class of pure sandwich complexes. The title compounds represent a long sought asymmetric organometallic motif, leading to the observation of hysteresis loops up to 10 K. In addition, we observe fast quantum tunneling of the magnetization near zero field, which opens the possibility of nuclear spin read-out with the 167 Er(III) analog of [(η 9 -C 9 H 9 )Er (η 8 -C 8 H 8 )] 56 . Our results clearly highlight the significance of not just a long desired and extremely elusive organometallic complex class, but are also of relevance to future quantum spintronic applications.
Methods
Synthetic methods. Experiments were carried out under a dry, oxygen-free argon atmosphere using Schlenk-line and glovebox techniques. All solvents and reagents were rigorously dried and deoxygenated before use. All compounds were characterized by single-crystal X-ray diffraction studies. Further details are available in the Supplementary Information (see section Supplementary Methods).
Data availability
All data is available from the authors on reasonable request. The X-ray crystallographic coordinates for structures reported in this study have been deposited at the Cambridge Crystallographic Data Centre (CCDC), under deposition numbers 1894445-1894450. These data can be obtained free of charge from The Cambridge Crystallographic Data Centre via www.ccdc.cam.ac.uk/data_request/cif. | 4,463.2 | 2019-07-17T00:00:00.000 | [
"Chemistry"
] |
In Vivo Recognition of Vascular Structures by Near-Infrared Transillumination
: Transillumination is a very well-known non-invasive optical technique that relies on the use of non-ionizing radiation to obtain information about the internal morphology of biological tissues. In a previous work, we implemented a laser-based illuminator operating at a wavelength of 850 nm, combined with a CMOS digital camera and narrow-band optical detection that showed great potential for in vivo imaging. A great advantage is the use of low-cost semiconductor lasers, driven by a very low current (about 11 mA, spatially distributed as a 6-by-6 matrix covering a 25 cm 2 area). Thanks to the strong absorption of hemoglobin at this wavelength, we have collected raw data of vascular structures that have been further processed to achieve images with much better quality. In particular, here we show that a higher contrast can be attained by the expansion of gray level histograms to exploit the full range, 0–255. This elaboration can be, for instance, exploited for the recognition of vascular structures with better resolution. Examples are reported relative to hand dorsal vein patterns and live chick embryos’ blood vessels. Analyses can be successfully performed without applying any thermal or mechanical stress to the human tissue under test and without damaging or puncturing any parts of the eggshell.
Introduction
Optical transillumination is a non-invasive method for imaging that allows the investigation of the internal structure of thin portions of biological tissues [1][2][3][4]. It relies on the use of non-ionizing radiation, resulting, thus, in a totally safe diagnostic tool. The transillumination analysis consists of illuminating the sample with a light source and collecting the radiation that is transmitted through the tissue under test. The propagation of the photons is conditioned by absorption, scattering, and reflection effects taking place inside the tissue: hence, the acquired images carry important information about the morphology and the health condition of the sample. In biological tissues, absorption effects are mainly due to water; macromolecules, such as proteins and lipids; and pigments, such as hemoglobin [5,6]. In particular, in the wavelength range from 600 to 1200 nm (the so-called "diagnostic and therapeutic window") the absorption of water is much lower than that of oxygenated and deoxygenated hemoglobin. The choice of light sources emitting in this spectral region produces results that are particularly interesting when studying highly perfused tissues. As it concerns scattering, only a small amount of light is redirected but this phenomenon still prevents the formation of high-definition images comparable with the results from more complex diagnostic techniques that make use of ionizing radiations. Nevertheless, transillumination can be exploited as a first approach to perform preliminary analysis, in place of more complex and invasive tests [7,8]. Hence, it is applied for the investigation of hydroceles, hydrocephalus, caries, malignant lumps, and blood vessel patterns. Commercial medical devices are available: they are based on light-emitting diodes (LEDs) emitting visible light and they can be used only in a darkened environment [9,10]. Transillumination is also exploited for photoplethysmography (PPG), a non-invasive optical method that allows reconstruction of a signal related to the change of blood volumes inside the blood vessels of the tissue under test. The PPG signal obtained with pulse oximetry looks similar to the arterial pressure wave, but its waveform appears distorted. This happens because the PPG analysis is carried out by applying the sensor typically to a fingertip or to an earlobe that is subjected to mechanical pressure. This stress activates alpha adrenergic receptors which affect the arteries and veins vasoconstriction (narrowing the blood vessels).
To solve this issue and in view of the technological advancement done in the past years in the fabrication of light sources and detectors operating in the wavelength range 800-1000 nm, in previous work we proposed and demonstrated a portable vertical cavity surface emitting laser (VCSEL)-based instrumental setup for morpho-functional imaging of in vivo biological tissues [11,12]. We employed the optoelectronic system to acquire pictures and videos of human hands and chick embryos inside eggshells and to extract vital sign information. In this manuscript, we show how the raw images can be further processed (by expansion and equalization of the gray level histograms) in order to obtain better quality images with higher contrast, for a more precise identification of blood vessel patterns.
Materials and Methods
The optoelectronic transillumination system for in vivo imaging featured an illuminator composed of 36 VCSELs arranged in a 6-by-6 matrix covering an area of 25 cm 2 . Their pumping current was driven by a custom-designed circuit. A digital CMOS camera was employed for image acquisition (Figure 1). In particular, the employed VCSELs (OPV 332, OPTEK Technology, TTElectronics, Woking, UK) were characterized by a nominal peak emission wavelength of 850 nm, particularly interesting for our purpose as it falls within the diagnostic and therapeutic window. Each VCSEL had a small divergence angle of 4°, was driven by a direct current (DC) of 11 mA, and emitted an optical power of about 6 mW. The acquisition system was positioned at a distance of 50 cm from the biological tissue under examination and obtained images that can be processed and subsequently archived. It consisted of a CMOS camera (GS3-U3-41C6NIR-C, CMOS sensor 1″, 2048 × 2048 pixels, Point Grey Research Inc., Richmond, BC, Canada), a long-wavelength-pass optical filter with 780 nm cut-on wavelength (MidOpt LP780, Midwest Optical Systems, Inc., Palatine, IL, USA), and a 10-nmbandpass optical filter centered at 850 nm (FBH850-10, Thorlabs Inc., Newton, NJ, USA). The use of the filter was fundamental for the collection of the NIR photons scattered from the biological tissue and the rejection of ambient light, thus allowing the system to perform the measurements in standard daylight conditions. The camera was USB 3.0 interfaced to a laptop using dedicated software (FlyCapture2, Point Grey Research Inc.). The acquired images were then processed with MATLAB.
Results and Discussion
To demonstrate the performance of the system, raw images were acquired first by transilluminating the upper limbs of human volunteers at rest. During the procedure, the subjects were seated in a comfortable position and the biological tissues were not subjected to any kind of thermal stress or mechanical constriction. Before the test, the volunteers provided their agreement to take part in the study and to publish their images. Grayscale pictures were acquired in standard ambient light conditions using exposure times of the order of hundreds of ms and allowed the visualization of vascular structure that appears darker because light is strongly absorbed by the hemoglobin present in the blood flowing in the vessels.
In particular, Figure 2 shows the data related to the transilluminated hand of a male darkskinned volunteer. Figure 2a reports the raw image: morphological details are visible but with lower contrast with respect to pictures acquired on subjects with white skin [11,12], because of the high pigmentation of the epidermis. Hence, with the aim of obtaining higher contrast, the image was further processed using MATLAB software. The original picture was cropped (Figure 2b) to eliminate un-significant borders and the histogram relative to the density distribution function of the gray levels was calculated (Figure 2c). Figure 2c shows that the gray levels of the image pixels are concentrated only in a limited range of the histogram because of the low contrast. The cropped picture was processed by contrast adjustment, a procedure that remaps image intensity values to cover the entire range of gray level 0-255 maintaining the shape of the distribution of the original image, as visible from the histogram of Figure 2e. The modified image (Figure 2d) has a higher definition and tiny details of the venous tree are now recognizable.
Since the setup is portable, it was employed also to carry out in field monitoring of the growth of chicken embryos inside the eggshell. Figure 3a-c reports the original picture of the fecundated egg at day 20 of incubation, a cropped area of the image, and its histogram, respectively. The pixel distribution shows that only a limited range of gray levels is present in the selected area. For this reason, the blood vessels inside the eggshell are barely recognizable and the image looks very dark. Figure 3d, with its histogram (Figure 3e), reports the processed image by contrast enhancement. In this case, a further elaboration step was computed, i.e., histogram equalization (Figure 3g). While the expansion is limited to stretching the histogram without changing its shape, the purpose of the equalization is to change it in such a way to obtain a distribution of constant density. In the final picture (Figure 3f), the blood vessels are finally recognizable without uncertainty. The white small dots are due to the local egg-shell porosity.
Conclusions
We employed our house-built near-infrared transillumination setup to acquire functional images of in vivo biological tissues and we processed the acquired data to obtain better quality and higher contrast pictures. First, the image processing sequence was tested on a male dark-skinned volunteer. In subjects with high pigmentation of the skin, it is more difficult to clearly distinguish the dorsal vein tree because of partial absorption of the light from the epidermis. By processing the original image, it was possible to obtain a better contrasted picture and to visualize, also, tiny details of the vessel pattern. Moreover, the setup, which is portable, was used also to perform in field monitoring of fecundated chicken eggs. Pictures of the eggs containing embryos were collected and processed by contrast enhancement and further histogram equalization. Elaborated images were of better quality and allowed for more precise recognition of the blood vessels. Future works could focus on a more sophisticated image processing to use this transillumination system for biometric recognition and validation [13]. | 2,244.2 | 2019-11-15T00:00:00.000 | [
"Physics"
] |
Prediction of Hormone-Binding Proteins Based on K-mer Feature Representation and Naive Bayes
Hormone binding protein (HBP) is a soluble carrier protein that interacts selectively with different types of hormones and has various effects on the body’s life activities. HBPs play an important role in the growth process of organisms, but their specific role is still unclear. Therefore, correctly identifying HBPs is the first step towards understanding and studying their biological function. However, due to their high cost and long experimental period, it is difficult for traditional biochemical experiments to correctly identify HBPs from an increasing number of proteins, so the real characterization of HBPs has become a challenging task for researchers. To measure the effectiveness of HBPs, an accurate and reliable prediction model for their identification is desirable. In this paper, we construct the prediction model HBP_NB. First, HBPs data were collected from the UniProt database, and a dataset was established. Then, based on the established high-quality dataset, the k-mer (K = 3) feature representation method was used to extract features. Second, the feature selection algorithm was used to reduce the dimensionality of the extracted features and select the appropriate optimal feature set. Finally, the selected features are input into Naive Bayes to construct the prediction model, and the model is evaluated by using 10-fold cross-validation. The final results were 95.45% accuracy, 94.17% sensitivity and 96.73% specificity. These results indicate that our model is feasible and effective.
INTRODUCTION
With the rapid development of society, people have higher and higher requirements for medical and health care (Lin, 2020). Therefore, it is urgent to learn more about the structure and function of proteins in order to explain more of the meaning of life and promote the development of biomedicine and other fields (Wang et al., 2020a;Qu et al., 2021). However, there is a difficulty in the current research, that is, how to use its sequence information to predict proteins effectively. Although effective prediction of protein sequences can be made using physical, chemical and biological experiments, these methods are costly and time consuming.
Hormone binding proteins (HBPs) are carrier proteins that bind specifically to targeted hormones and were first identified in the plasma of pregnant mice, rabbits and humans (Mortezaeefar et al., 2019;Niu et al., 2021a). They are involved in hormonal regulation in living organisms. HBPs not only regulate the amount of hormones reaching the target cell to produce the desired effect but also regulate non-protein-binding or free-circulating active steroid hormones, which are thought to be the main gatekeepers of steroid effects. Sexual HBPs, mainly produced in the liver, combine with sexual steroid hormones to regulate their bioavailability. The incorrect expression of HBPs, however, can cause various diseases (Tan et al., 2019).
Therefore, understanding the function and regulatory mechanism of HBPs has become very important. Accurately identifying HBPs is the first step in studying their function. Traditional HBPs identification methods involve wet biochemical experiments, such as immunoprecipitation, chromatography, or cross-linking (Sohm et al., 1998;Zhang and Marchant, 1999;Einarsdóttir et al., 2014;Cheng et al., 2016;Fang et al., 2019). These experimental methods are time-consuming and expensive, and with the discovery of a large number of protein sequences, it is difficult to determine HBPs through biochemical experiments. Therefore, it is necessary to establish an effective recognition model to identify HBPs (Akbar et al., 2020). The description of the characteristics of the protein sequence method contains a lot of information, such as the chemical and physical properties of amino acids, sequence characteristics, feature extraction algorithm for classification algorithm which has great impact on the design and the classification of results. Generally, prediction techniques based on machine learning consist of three steps: feature extraction, construction of predictors, and performance evaluation (Liu, 2017;Wang et al., 2018;Zhang et al., 2019). In 2018, Tang et al. (Hua et al., 2018). developed a method based on support vector machines to identify HBPs, which uses the optimal characteristic coding protein obtained by using the optimized dipeptide composition. Subsequently, Basith et al. developed the computational predictor iGHBP, which combined the dipeptide composition and the value of the amino acid index to obtain the optimal selection and predict the construction model (Basith et al., 2018). In this paper, we constructed a prediction model, HBP_NB, to correctly identify HBPs. First, the k-mer (Liu et al., 2008;Christopher et al., 2013;Liu et al., 2015a;Manavalan et al., 2019) method was used to obtain the frequency characteristics of protein sequences, and then the F-score value method was used to select the feature subset. Finally, input the obtained features into Naive Bayes (Gong and Tian, 2010;He et al., 2010;Gumus et al., 2014;Hu et al., 2020;Hu et al., 2021a;Hu et al., 2021b) to construct the prediction model.
Main Process of the Article
Machine learning frameworks have been used to identify multiple protein types, such as DNA binding proteins (Zeng et al., 2015;Qu et al., 2017;Shen and Zou, 2020), RNA binding proteins (Xiao et al., 2017;Lei et al., 2021), lncRNA interacting proteins Liu, 2020), and drug targets (Yan et al., 2016;Wang et al., 2020b;Wang et al., 2020c). Since the recognition of protein sequences includes two important steps sequence feature extraction and classifier selection the effective combination of feature extraction algorithms and classifiers has also been extensively studied . In this paper, we propose a predictive model for identifying hormone-binding proteins based on Naïve Bayes.
HBPs prediction analysis was carried out through the following five steps: 1) HBPs and non-HBPs were searched and downloaded from UniProt, and the similarity threshold of protein sequences was set by the CD-HIT program to construct a high-quality dataset ; 2) feature extraction of protein sequences was performed using the k-mer feature coding method; 3) the extracted features were selected to improve the accuracy of classification; 4) different classification methods were used to classify and predict the selected feature subset and select the best classification methods; and 5) Performance evaluation. Figure 1 shows the structural framework for identifying HBPs in this paper. This section will introduce dataset establishment, feature selection methods and classification methods in detail.
Dataset
It is necessary to collect sufficient correlation function data as the basis of statistical model prediction. Therefore, it is first necessary to construct an objective dataset to ensure the effectiveness and robustness of the model. Therefore, we adopt the benchmark dataset constructed by Tang et al. (Tang et al., 2018). To build this dataset, follow these steps. The first step was to search and collect HBPs from UniProt (Bairoch et al., 2009;Schneider, 2012) and to generate the original HBPs dataset by selecting the hormone binding keywords in the molecular function items of the gene body (Ashburner et al., 2000). Consequently, 357 HBPs with manual annotation and review were selected. In the second step, to avoid the high similarity of protein sequences affecting the results, we used the CD-HIT (Li and Godzik, 2006;Fu et al., 2012) program to set the truncation threshold to 0.6 to remove highly similar HBPs sequences. In the third step, when the protein sequence in the dataset contains unknown residues (such as "X," "Z," and "B"), it will affect the model prediction results, so protein sequences containing unknown residues need to be excluded. After the above steps, a total of 122 HBPs were obtained, which were regarded as positive data. As a control, 121 non-HBPs were randomly selected from UniProt as negative data using a similar selection strategy. The data of the model can be freely download from https://github.com/GUOYUXINXIN/-. The benchmark dataset can be expressed as: Among them, subset D p contains 122 HBPs, and subset D n contains 121 non-HBPs.
Feature Extraction
Protein sequence is a string generated by the permutation and combination of 20 English letters with different lengths. Currently, general machine learning algorithms can only deal with feature vectors, so when machine learning methods are used, protein sequences need to be transformed into numerical vectors representing the characteristics of protein sequences. As the first step in building a biological sequence analysis model, feature extraction is an important part of correctly predicting protein sequences, an efficient feature extraction method can obtain a Frontiers in Genetics | www.frontiersin.org November 2021 | Volume 12 | Article 797641 high performance classification model. The extracted features should not only retain the protein sequence information to the maximum extent, but also have a greater correlation with protein classification. Given a protein sequence, express it as: where Pstands for protein sequence, R i represents theithamino acid residue of proteinP(i 1, 2, /, L).
K-Mer
K-mer (Liu et al., 2015b;Niu et al., 2021b) is the most basic method of expressing protein sequences as digital vectors (Liu et al., 2016), in which k-mer frequency coding refers to the occurrence frequency of all possible nucleotide sequences with k length in a given sequence (Liu et al., 2015c;Bin et al., 2017). The k-mer feature extraction algorithm is used to convert the protein sequence into a vector with a fixed length, which is used as the input vector of the machine learning classifier. For example, setting k to 2 produces a 400-dimensional vector (AA, AC, AD, /, AY, YA, YC, /, YY).
To avoid the problem of overfitting, we generally setk < 4 because whenk > 4 , more dimensions will be generated, resulting in dimension disaster . Therefore, we set k to 3 so that the input protein sequence could be converted into a vector with 8,000 dimensions of fixed length.
Distance-Based Residual
DR (Liu et al., 2014) is a feature expression method based on protein sequences that uses the distance between residue pairs to represent the feature vector of the protein. The feature vector is expressed by calculating the number of occurrences of residual pairs within a certain distance threshold. The feature vector dimension obtained by the DR feature extraction method is 20 + 20 × 20 × d MAX dimensions, where in 20 in 20 + 20 × 20 × d MAX represents the types of amino acids that make up the protein; d MAX is a distance threshold that can be set manually, which represents the maximum distance between pairs of amino acid residues.
Profile-Based Cross-Covariance
Since machine learning-based technologies such as random forest (RF) and logistic regression (LR) require the input of fixed-length vectors as input vectors for training, it is necessary to convert protein sequences of different lengths into fixed length vectors as input vector machine learning. Because each residue in a protein has many physical and chemical properties, protein sequences can be regarded as time series with similar properties. Therefore, CC-PSSM (Dong et al., 2009) is used in this article to convert protein sequences of different lengths into fixed length vectors. PSSM algorithm is a common algorithm in the field of bioinformatics, known as the "positionspecific scoring matrix," which can store the evolutionary information of protein sequences so that it can be used for protein prediction. It is a matrix that calculates the percentage of different residues at each position in a multi sequence alignment, the matrix size is L × 20 (L for protein sequence length). Among them, CC is a measure of correlation between FIGURE 1 | Structure flow chart. The first step is to search and download HBPs and non-HBPs from the protein resource database and then use CD-HIT to perform protein de-redundancy operations. The threshold is set to 60%. Finally, protein sequences containing unknown residues are removed to generate the final protein dataset. The second step is to extract features of the protein, and the third step is to use different classification methods to classify the selected features.
Frontiers in Genetics | www.frontiersin.org November 2021 | Volume 12 | Article 797641 two different properties of amino acid residues and can be calculated using the following equation: (3) wherei1, i2represents amino acids, and S i1 , S i2 represents the average score of i1, i2along the protein sequence. LAG is the maximum lag, lag is an integer value from 1 to LAG, and the total number of CC variables is 380 × LAG. In this paper, we set the value ofLAG to 2 to obtain a 720(380 × 2)-dimensional vector.
Feature Selection
When the feature size is large, there may be irrelevant features or inter-dependence between features, which will easily affect the accuracy of the prediction results. In particular, the more feature dimensions, the more likely it is to lead to "dimension disaster," model complexity and model generalization ability decline. Therefore, removing irrelevant or redundant features through feature selection can improve the accuracy of classification performance and reduce the running time of the model (Polat and Güneş, 2009;Quan et al., 2016;Zou et al., 2016;Guohua and Jincheng, 2018;Wei et al., 2018;Riaz and Li, 2019;He et al., 2020). In this paper, the F-score value is used to select the optimal feature (Chen and Lin, 2008;Cheng et al., 2019;Wei et al., 2019), which is a method to measure the distinguishing ability of features between the two categories, and the most effective feature selection can be achieved through this method. Therefore, we can use (Eq. 4) to describe the contribution of each feature and perform feature selection: whereF(i) is the score of theith feature of the F-score. Generally, the larger the value of F(i) is, the stronger the ability to recognize samples.s 2 w (i) is the intragroup variance, ands 2 b (i) is the intergroup variance. Their calculation formula is as follows: wheress b (i)is the sum of squares between groups; ss w (i)is the sum of squares within the group; Kis the total number of classes; andNis the total number of samples.
Classifier
In this paper, Naive Bayes, Random forests, logistic regression, linear discriminant and other classification algorithms are used to predict HBPs.
Naïve Bayes
The Naive Bayes method is a classification method based on Bayes' theorem and the assumption of the independence of characteristic conditions. It is characterized by combining prior probability and posterior probability and a very widely used algorithm. The main idea of the naive Bayes classifier is to solve the posterior probability P(Y|X) through joint probability modeling and use Bayes' theorem. Then, the category corresponding to the largest posterior probability is used as the predicted category. Suppose there is a sample dataset D {d 1 , d 2 , /, d n }, the feature dataset corresponding to the sample dataset is X {x 1 , x 2 , /, x d }, features are independent and random, and the class variable is Y {y 1 , y 2 , /y m }.
According to the Naive Bayes algorithm, the posterior probability of the sample belonging to categoryycan be expressed as: WhereP(Y)is the prior probability, Naive Bayes is based on the independence of each feature. In the case of a given category, Eq. 6 can be further expressed as the following equation: The posterior probability can be calculated from the above two Eqs 6, 7: Since the magnitude of P(X)is fixed, when comparing the posterior probability, only the molecular part of the above equation can be compared. Therefore, a naive Bayesian calculation of sample data belonging to category y i can be obtained:
Random Forests
RF is a flexible, easy-to-use machine learning algorithm that contains multiple decision trees. It is an optimized version of bagging Zeng et al., 2020). The idea of bagging is to vote on the results of multiple weak classifiers to combine them into a strong classifier, thereby improving the prediction accuracy of the model. In the training phase, RF uses the bootstrap sampling method to collect multiple different subsets from the input training dataset and then uses the different collected subsets to train the internal decision tree. Then, in the prediction phase, RF votes for the prediction results of multiple internal decision trees and then outputs the prediction results. Its advantages are as follows: 1) it can process high-dimensional data without feature selection; 2) accuracy can be maintained even if many of the features are missing; and 3) it has a fast training speed (Jiao et al., 2021).
Logistic Regression
As a classification model, LR can deal with the 0/1 classification problem because of the nonlinear factor introduced by the Frontiers in Genetics | www.frontiersin.org November 2021 | Volume 12 | Article 797641 sigmoid function. The image of the logical function is an S-shaped curve with values between (0, 1). The farther away from 0 a function is, the closer to 0 or 1 the value of the function will be. Therefore, this feature can be used to solve the problem of binary classification. The function formula is as follows: Among them, z θ T x n i 0 θ i x i θ 0 x 0 + θ 1 x 1 + θ 2 x 2 + /+ θ n x n ; therefore, the predictive function of logistic regression can be expressed as:
Linear Discriminant Analysis
LDA is a classical linear learning method, also known as "Fisher" discriminant analysis in dichotomies. Unlike the perception machine, the principle of LDA is dimension reduction. In other words, given a set of training samples, the article tries to sample projections to a straight line, keeping the points with the same classification as close as possible and the classification of different points as far apart as possible, i.e., maximizing and minimizing the variance between variance. LDA can, therefore, make use of sample points in the projection line (or projection location) to determine the type of sample.
Performance Evaluation
In this article, we use the specificity (SP), sensitivity (SN), accuracy (ACC) (Yang et al., 2021) and Matthews correlation coefficient (MCC) to evaluate our proposed method (Snow et al., 2005;Cheng et al., 2018), which can be expressed as: 1. Accuracy: ACC represents the probability that all positive and negative samples will be correctly predicted.
ACC
TP + TN TP + TN + FN + FP (12) 2. Sensitivity: SN represents the probability that the actual hormone-binding protein is predicted to be a hormone-binding protein.
3. Specificity: SP represents the probability that a nonhormone-binding protein is predicted to be a non-hormonebinding protein. 6. F1-Score: The F1 score is balanced by taking into account both accuracy and recall, so that both are maximized at the same time.
Where, the recall rate is: recell TP TP+FN 7. The ROC curve: Receiver operating characteristic curve (the area under the curve is AUROC), X-axis is false positive rate (FPR), Y-axis is true positive rate (TPR): 8. PRC: PRC takes precision rate as Y-axis and recall rate as X-axis.
Where TPrefers to the model correctly predicting positive category samples; FPrefers to the model incorrectly predicting negative category samples as positive category; TN refers to the model correctly predicting negative category samples; and FNrefers to the model incorrectly predicting positive category samples as negative category (Ding et al., 2020a;Ding et al., 2020b).
In machine learning, a test set is needed to test the model and describe its generalization ability. However, in practical applications, due to the limited number of datasets, cross validation is used as a test method. There are three types of cross validation: K-fold cross validation, fold cross validation and independent data verification. In this article, we use K-fold cross-validation to test the constructed model. K-fold cross-validation divides the training data into K parts, of which (K-1) pieces of data are used to train the model, and the remaining 1 piece of data is used to evaluate the quality of the model. This process is cycled K times, and the K evaluation results obtained are combined, such as averaging or voting. The flow chart of K-fold cross verification is shown in Figure 2.
RESULTS AND DISCUSSION
In machine learning, the predicted results of the model can be tested through cross-validation. In this article, we use 10-fold cross-validation to evaluate the built model.
Performance Comparison of Different Feature Expression Methods
According to the feature extraction part, protein sequences are transformed into feature vectors of different sizes through different feature extraction methods. Therefore, in this study we tested the performance of three feature extraction methods: k-mer (K 2), k-mer (K 3), DR and CC-PSSM.
Frontiers in Genetics | www.frontiersin.org November 2021 | Volume 12 | Article 797641 First, use the F-score feature selection method to reduce the dimensionality of the feature vectors obtained by different feature extraction methods to 250 dimensions, then use the selected best feature vector as the input vector of the naive Bayes algorithm and perform 10-fold cross-validation, and finally draw forecast results. The prediction results are shown in Table 1 (the maximum value is in bold). As shown in Table 1, the k-mer (k 3) feature extraction algorithm used in this model performs best in all indicators, among which the values of ACC, MCC,SP and SN are,respectively,95.45,91.36,96.73,and 94.17%. These results prove the validity of our model.
Comparison With Other Classifiers
To show the superiority of naive Bayes in HBPs recognition, we can compare the HBPs recognition performance of different classification algorithms based on the same feature subset (i.e. 250 optimal features). In this paper, we used the constructed HBP_NB model to perform performance comparison with RF, LDA, Logistic regression and other models under the condition of 10-fold cross-validation, and the comparison results are shown as follows. Figures 3, 4 respectively show the boxplot diagram of different models, ROC and PRC curves schematic diagram. These results show that our model has good classification ability. Therefore, we construct the final model based on naive Bayes. Where, the line in the middle of the box in the boxplot is the median of the data, representing the average level of the sample data; The top of the box represents the upper quartile and the bottom quartile represents the lower quartile, which means the box contains 50% of the data, so the width of the box reflects, to some extent, how much the data fluctuates; at the same time, the lines above and below the box represent the maximum and minimum values of data. The ROC curve is a curve that evaluates the effect of binary model on positive FIGURE 2 | K-fold cross-validation diagram. Divide the data into K parts, where k-1 parts are used as the training dataset, and the remaining part is used as the test set. The mean value of the results of the k groups is calculated as the performance index of the current k-fold cross-validation evaluation model. Frontiers in Genetics | www.frontiersin.org November 2021 | Volume 12 | Article 797641 7 category prediction. X-axis is false positive rate (FPR), Y-axis is true positive rate (TPR), which indicates that the optimal classifier with the best performance is located in the upper left corner of the image (coordinate 0,1), and the area under its ROC curve is AUROC, with an area value between 0,1. PRC takes presion rate as Y-axis and recall rate as X-axis, and lines are drawn according to changes in the value of probability threshold. The ideal model would be at the point (1,1). The model with excellent performance is as close to this point as possible.
Performance Comparison With the Existing Optimal Algorithm
This section compares the model constructed in the article with other existing methods, in which the results of HBPred (Hua et al., 2018) and iGHBP (Basith et al., 2018) are directly obtained from the literature. The comparison results are shown in Table 3 (the maximum value is in bold). As seen from Table 3, the HBP_NB model constructed in this paper has the best performance in all indicators, among which ACC, SP and SN have reached maximum values of 95.45, 96.73 and 94.17%, respectively. The effect is significantly better than that of the other two methods, which also proves the effectiveness of the HBP_NB model constructed in this paper.
CONCLUSION
As a carrier protein related to the regulation of hormones in the circulatory system, HBPs can cause various diseases when they are abnormally expressed. Therefore, it is very important to understand their function and regulatory mechanism, and the correct identification of HBPs is the first step in understanding their biological process and is necessary to further study their function. There is growing evidence that it is crucial to develop an efficient computational model to identify hormone-binding proteins. In this study, we used a reliable predictive model for HBP_NB to identify HBPs. First, the model uses the k-mer feature extraction method to extract the features of HBPs. Then, to remove redundancy and noise and improve the accuracy of model prediction, the F-score value is used to sort the features and select the optimal features. Secondly, the reduced feature set is input into naive Bayes classifier and the 10-fold cross validation is used to judge the quality of the prediction model. Finally, the accuracy, sensitivity and specificity of the HBP_NB model reached 95.45, 94.17 and 96.73%, respectively, in 10-fold cross validation. The feasibility and validity of our model are illustrated.
However, there is room for improvement in our current approach. Since the data set selected in this experiment is small, we will collect more data for model training and independent test set experiments in the future to improve the model's robustness and generalization ability. At the same time, we will further learn more effective feature representation methods and classification algorithms to gain an in-depth understanding of machine learning and establish a more stable model. In addition, we also hope that our work can help scholars to study hormone binding proteins, to promote research on hormone-binding protein drugs.
DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors. | 5,930.4 | 2021-11-23T00:00:00.000 | [
"Biology",
"Computer Science"
] |
Concepts for 3 D Printing-Based Self-Replicating Robot Command and Coordination Techniques
Self-replicating robots represent a new area for prospective advancement in robotics. A self-replicating robot can identify when additional robots are needed to solve a problem or meet user needs, and create them in response to this identified need. This allows robotic systems to respond to changing (or non-predicted) mission needs. Being able to modify the physical system component provides an additional tool for optimizing robotic system performance. This paper begins the process of developing a command and coordination system that makes decisions with the consideration of replication, repair, and retooling capabilities. A high-level algorithm is proposed and qualitatively assessed.
Introduction
The concept of self-replicating robots has been around for some time-dating back to the 1940s and earlier [1].With the advent of 3D printing technology, the development of self-replicating robots seems more feasible to implement than it was previously.This opens the door to research and development opportunities in this area of robotics.
Ellery [2] proposed the use of self-replicating robots for planetary exploration (in particular, focusing on the moon).A major benefit of having robots that are able to make more robots on their own is that the survivability of the multi-robot system increases dramatically.A single surviving robot that can self-replicate could repopulate an entire 'colony' of robots with sufficient resources and time.This would give the robots an opportunity to take more risks in trying to accomplish an objective.While suggesting solutions to numerous hardware and logistical issues, Ellery's work didn't consider the autonomy of the robotic system.Autonomy is, of course, a key consideration for maximizing the functionality (or allowing functionality in a communications limited/denied environment) of this type of robotic system.
This paper advances previous work by presenting the conceptual framework and an overarching architecture for a self-replication robot system.It also discusses the operation of such a system, by describing an autonomous command and coordination approach.To understand how to efficiently utilize a self-replicating robot system, it is important to analyze the overall concept and command strategies involved.These are discussed in subsequent sections.Then, a prospective command algorithm is proposed and qualitatively evaluated, based on selected metrics and using case studies, to ascertain its prospective efficacy.
Background
This section presents prior work in a number of areas that are relevant to the challenge of the development of a command system for a self-replicating robot.First, an overview of prior work on self-replication and its prospective benefits, is presented.Then, prior work on soft robotics, distributed robot system coordination, swarm intelligence, and automated manufacturing, is discussed.
Self-Replication
Von Neumann is seen by many as the father of self-replicating machines.In the 1940s, he investigated the logical foundations of self-replication [1].In the 1950s, he proposed a self-replicating structure [3] and this work was presented in Scientific American [4], bringing it into the public consciousness.After von Neumann's death [3], Burks completed his design for a 29-state automaton and published it in 1966 [5].More recently, the technology to actually perform self-replication has become feasible.Beuchat and Haenni [3], for example, created a hardware implementation of cellular automaton and published the results of its analysis in 2000.
As a stepping stone to self-replication, self-configuration and self-reconfiguration were pursued.Von Neumann proposed a self-assembler (that used a cache of spare parts) [1].Whitesides and Grzybowski [6] demonstrated the similarity of natural and mechanized self-assembly.Butler, Murata, and Rus [7] advanced mechanized self-assembly by developing algorithms for a generic self-reconfiguring robot to divide and reform into different configurations.Sahin, et al. [8] demonstrated how self-assembly and disassembly can be used to allow a swarm of robots to collaborate, in one instance, while retaining the capability to perform tasks independently and in smaller groups, in other instances.Butler, Murata, and Rus [7] presented algorithms for this purpose.
Evolutionary self-assembly was proposed by Jakobsen and Tannum [9], building on the self-improvement concept (for replication) proposed by Koza and Rice [10] in 1995.Cooperation [11] and colonies [12] of self-assembling robots have also been proposed.
In [13], Pfeifer, Lungarella, and Lida augment the self-replication concept by presenting a discussion of how robots will eventually be able to exhibit certain desirable properties of biological organisms, such as adaptivity, robustness, versatility, and agility.In [14], Lee, Moses, and Chirikjian follow a von Neumann-inspired framework and, in this context, define the degree of self-replication and task complexity.Self-replication is presented in terms of an equation that compares the complexity among subsystems and overall system complexity.Mathematically, this can be presented as: where C min is the module under test with the least complexity and C max is the module with the most complexity.C total and C avg present the sum and mathematical mean, respectively.Entropy (based on Sanderson's model [15]) is used as a measure of task complexity.
In addition to logical and theoretical works, a number of efforts have been made to create hardware systems.Suthakorn, Kwon, and Chirikjian [16], for example, demonstrated the operations of a semi-autonomous robot made from LEGO Mindstorm kit parts, that performs supervised replication.In [16], they built upon previous work (in [17]), where a concept and initial remote-controlled replication was presented.In [18], machine vision and other capabilities are added to the system, to facilitate autonomous operations.Similarly, Zykov, et al. [19] demonstrated real-world replication using modular robots based on specially-produced cubes.These robots collect cubes from feeder troughs and use them to produce equivalent copies.Even more flexible is the work presented in [20], where an algorithm for duplicating shapes using 'smart sand' replicates the shape of presented 3D objects.This work's efficacy was demonstrated via hundreds of simulated test runs.
More practically, the RepRap 3D printer [21] has been used as a template for the creation of numerous consumer-grade 3D printers, based-in part-on the use of parts printed on another 3D printer.Once a user has a working RepRap printer, he or she can produce many of the mechanical parts required to make another RepRap printer for his or her own use or for use by another person.Unlike the systems proposed herein, which use autonomous replication, RepRap construction requires significant human involvement.
Robot 3D Printing and the Use of In-Situ Resources
Creating robots with 3D printing is well established.Numerous robots and robot parts have been created using 3D printing.The MU-L8 robot [22], for example, utilized 3D printed limbs to emulate human movements and play robot soccer.For more distant applications, the use of in-situ resources is necessary to prolong mission duration and, potentially, facilitates having a greater ability to take risks.Examples of in-situ resources being used for 3D printing include the use of basalt printing of structures for Martian exploration [23].The use of a D-shape printer for building infrastructure out of regolith on the Earth's moon [24], and the use of a collection of simple self-replicating robots to exploit lunar material and energy resources [25], have also been previously considered.
Soft Robots
Soft Robotics refers to robotic devices that are fabricated from soft, flexible, materials, instead of the hard plastics and metals traditionally used in robotics [26,27].An overview of how they have been designed, fabricated, and controlled is presented in [28].An overall theme is that they tend to trade precision and deterministic control for bioinspired compliance and physical robustness [29].
Hiller and Lipson [29] demonstrated the automatic design of freeform soft robots for forward locomotion, using soft volumetrically expanding actuator materials.A robot was automatically fabricated and assembled.Performance demonstrated an error of approximately 15%.
In [26], "smart materials" (materials which change their physical properties in response to external stimuli) were demonstrated and used to create a tentacle-like active structure, employed for movement.
In [30], Bartlett et al. employed multi-material 3D printing to manufacture a combustion powered robot whose body transitions from a rigid core to a soft exterior.The robot is powered by the combustion of butane and oxygen, and can perform untethered jumping.
Multi-Robot Coordination
The study of multi-robot coordinated systems, according to Yan, Jouandeau, and Cherif [31], has recently increased "significantly in size and importance".They attribute this to the resolution of many previously vexing issues in single robot systems, as well as to specific multi-robot system needs.A number of key decisions define the coordination of a multi-robot system [31].These include decisions related to the use of static or dynamic coordination, explicit or implicit communications, cooperative or competitive approaches, and centralized or decentralized decision-making.Task and motion planning, and resource conflict resolution techniques, also need to be identified.
Several examples of coordination approaches exist.Nieto-Granda, Rogers, and Christensen [32], for example, compared three exploring and mapping strategies: the reserves, divide and conquer, and buddy system approaches.Under the reserves approach, extra robots wait in the starting area until they are needed and are then given tasks.Under the divide and conquer approach, robots travel in as large of a group as possible and split in half when new navigation goals are uncovered.Finally, with the buddy system approach, robots travel in teams of two, until new navigation goals are detected.Similar to the divide and conquer approach, the team will then split, following both paths.
Portugal and Rocha [33] compared two techniques for the multi-robot system patrolling of a given area.The first technique seeks to optimize local gain (using a Greedy Bayesian Strategy).The other technique seeks to reduce interference and foster scalability (using a State Exchange Bayesian Strategy).They found that both approaches sufficiently solve the problem; however, the state exchange strategy outperformed the greedy strategy.
A wide number of examples of multi-robot coordination use exists.Liu, et al. [34], for example, presented a control system for a collection of life science laboratory mobile robots.Pennisi, et al. [35] presented the use of multi-robot surveillance (for indoor public places) using a distributed sensor network that combines RFID tags, mobile robots, and RGBD cameras.Starke, et al. [36] demonstrated close-proximity multi-robot operations for a welding automation application.
To meet the challenges presented by distributed systems, a variety of approaches have been suggested.Caliskanelli, Broecker, and Tuyls [37] presented a swarm-inspired method (based on the pheromone signaling behavior of honey bees), called BeePCo, to maximize the total area covered by a robot network in an environment.Swarm control styles are discussed in greater detail in the subsequent subsection.Straub [38] proposed a boundary node-based Blackboard Architecture approach for limiting the data replication traffic, to facilitate local robot decision-making.Jullian, et al. [39] proposed an information theoretic approach that iteratively estimates the environment state using a sequential Bayesian filter and a gradient of mutual information for the purposes of distributed control.Jin, XingJie, and ZengRong [40] explored the use of robot coordinated adaptive tracking.They presented a control algorithm with the distinctive feature that only a subset of followers need to access the position information of a dynamic leader in the task space, reducing communications and other resource needs.
Swarm Robotic Control
With swarm robotic control, simplistic local rules are used to create complex behaviors [41].The approach is patterned on insect colonies where groups of insects perform behaviors that are too complicated to be coordinated by any one insect's capabilities [41].Sahin [42] proffers that swarm robotics involves the use of a "large number of relatively simple physically embodied agents", from which a "desired collective behavior emerges from the local interactions among agents and between the agents and the environment".Practically, this means that members of the robotic system can have simplistic command software and reduced processing capabilities, but still produce a complex outcome.Several efforts to classify swarm robotic systems have been conducted.Abukhalil, Patil, and Sobh [43] define four high-level categories for robotic systems: swarm, self-replicating, self-reconfigurable, and modular.Significant overlap between these categories exists.Groβ, Dorigo, and Yamakita [12], for example, combine self-assembly/reconfiguration and swarm control (this approach is also discussed by Barca and Sekercioglu [44]).
Brambilla, et al. [45] take an alternate approach in (like Abukhalil, et al.) categorizing prior articles on swarm intelligence.Unlike Abukhalil, Ptali, and Sobh's approach, Brambilla, et al. classify systems into the categories of method-based and collective behavior-based.The method-based category is further divided into two sub-categories (design and analysis methods), that are further divided into five sub-categories (behavior-based, automatic design, microscopic, macroscopic, and real-robot analysis).Collective behaviors are divided into four sub-categories (spatially-organizing, navigation, collective decision-making, and other), which are further divided into ten sub-categories.
Swarm control has been demonstrated for a variety of applications, including robotic self-assembly [12], dynamic cleaning [46], exploration and mapping [47], foraging [48], object movement and interaction [47], and coordinating cooperation [47,49].Systems implementing swarm approaches, according to Sahin [42], have benefitted from system robustness, flexibility, and scalability benefits, provided by the approach.Barca and Sekercioglu [44] also identify a number of application-specific benefits.
Manufacturing Automation
Manufacturing automation uses electrical-, mechanical-, and computer-based solutions to operate and control a production process [50].It is becoming more popular as markets drive rapid product enhancements and the customization of products requires the use of flexible automation infrastructures [51].To this end, Saliba, Zammit, and Azzopardi [52] discuss a strategy and propose a set of practical guidelines for reconfigurable manufacturing automation.
For a machine to be self-replicating, it must be able to automatically manufacture a replica of itself.Collaborative robots that are used in manufacturing plants are becoming more flexible and efficient [53].Robots are now considered, by some, as an integral part of industries, due to their role in improving accuracy, repeatability reliability, preciseness, and efficiency [50].
The software that manages the automation process, referred to as manufacturing automation software projects (MASP), includes information regarding applied automation hardware and is becoming more complex.In [54], an approach for model driven development of automation software, based on the Systems Modeling Language, is discussed.In addition, Vyatkin [55] provides an overview of state-of-the-art software engineering for industrial automation.
The increasing capabilities (hardware and software) created for manufacturing automation make a significant contribution to work on self-replicating robotics.The automation of the replication process is a necessity for robots to be truly self-replicating.
Capability Requirements
In the design and development of a multi-robot system, identifying the requirements is a key initial task.A self-replicating multi-robot system must have certain capabilities to be successful.This section outlines these requirements.Relevant capabilities include the ability to: move, communicate, process data, sense the environment, and make more robots.Each will now be discussed.
Mobility
How robotic mobility is achieved has a bearing on robot replication decision-making and the required supplies.Robot mobility is necessary because making robots requires resources, and mobility is one portion of solving the challenge of obtaining resources.
One option for mobility, perhaps an obvious choice, is the use of wheels.Depending on the quality, wheels are generally reliable and able to support a substantial amount of weight.However, in the absence of appropriate mechanisms, the wheel utility can be easily impaired by unfavorable terrain.Another option is the use of robotic legs.The number of legs and the way in which they are configured on the robot would determine its mobility capabilities.Advanced options include hover, jet propulsion, subterranean digging, and gliding.
Communication
The coordination of a multi-robot system is heavily dependent on the ability of robots to communicate.Communicating can be accomplished with various techniques and technologies.For instance, installing a radio on each robot would enable them to communicate at a distance, as well as removing the necessity for a line of sight between them (although obstacles and environmental factors could interfere with the signal).Another possibility is using a coded visual system, such as blinking LED lights, to relay a message.A more range restrictive approach would be physically attached wires that temporarily connect robots.
Processing
Each robot needs a computer processing unit.Fabricating such a device in a factory setting with exact materials, machinery, and a relatively controlled environment, is well understood.For self-replicating robots, especially those designed to forage for resources, fabrication is complicated due to the possible lack of the availability of suitable materials, as well as the need for specialized fabrication equipment and suitable conditions.Currently, processor fabrication requires large, heavy, and expensive production equipment, which makes it impractical for in-situ use.In the longer term, with suitable resources available in-situ, the development of a processor fabrication capability may be possible.In the short term, however, processor availability becomes a limiting factor, that may be the primary determination of how many robots can be produced within a given environment and its available resources, if computer processing units cannot be fabricated locally.
Sensors
Sensing various aspects of the environment is important for performing mission tasks, gathering resources, and navigating the terrain.These can include visual, audio, touch, and magnetic sensors that aid in detecting various aspects of the environment.Robots may need to relay sensor readings to others, without sensing capabilities, for some applications.
Replication
The capability to perform replication activities is a core functionality of a self-replicating robot system.The replication process can be performed in a single step or consist of multiple stages of construction, such as the fabrication of parts and their subsequent assembly.
The selection of a replication mechanism must consider the need to duplicate itself during the robot production process.Thus, using sophisticated replication equipment would necessitate the ability to make a copy of the sophisticated equipment.
One promising solution is the use of 3D printing, with an emphasis on printer designs that are simple, yet very capable.For example, currently-available RepRap 3D printers can print parts to make another RepRap printer [21].However, the assembly of the robot does not need to be performed solely by the printer.In the case of RepRap reproduction, it's achieved through human involvement.
To perform robotic replication, a printing unit could be teemed with robotic arms (either on a single robot, or from a second cooperating robot).These arms could be used to assemble printed, stored, or otherwise obtained parts into their needed configuration.Some sort of assembly capability is critical for allowing robots to print similarly sized robots.If the printing robot cannot produce and connect multiple small parts (or expand the printing area in some way), a subsequent generation of robots would be constrained to be smaller than the originals, so that they could be printed in the printing area.
Techniques for robotic assembly are well understood.Robotic assembly has been used for applications ranging from small parts [56] to buildings [57].Techniques for both independent and cooperative robotic assembly techniques have been previously proposed [58,59].
In addition to printing and assembly capabilities, a capability for milling [60] may also be needed.Milling capabilities may be required to work with metals and other materials that cannot be 3-D printed, or for rectifying issues detected with a printed object or component.However, milling capabilities will not be required in many cases, as robots can be made with printable materials (plus stock components).
Design Considerations
This section examines system design considerations.First, robot replication design choices are considered.Then, the use of homogenous versus heterogeneous robots is discussed.Third, design considerations based on concepts found in nature are outlined.
Robot Replication
The difference between self-replicating multi-robot system approaches are now considered.The first approach is that of a centralized control node.Second, a peer to peer approach is discussed.These approaches can be implemented for either replication or communication, or perhaps both.
Centralized
With the centralized approach, a special robot or stationary hub is setup such that it acts as the replication center.Having a central node dedicated to the replication process has benefits and drawbacks.One benefit to this approach is that the regular robots that are made by the central node wouldn't have to have the replication equipment installed, such that the additional materials that would not be needed for this could be used for other purposes.It would also mean that all of the replication-related materials collected would end up in the same place, such that the replication process wouldn't get bottlenecked by poor resource exchange between robots (although this could be remedied by proper implementation of cooperation in non-centralized models).A drawback to this approach is that robots must bring all replication resources to the central node, which becomes problematic for resources that are located far away.This centralized approach also introduces the question as to whether this central node can be made in-situ, or must be specially fabricated and installed in the desired location.If it cannot be made by the multi-robot system, or if an existing central node cannot craft a copy of itself, then this creates a central point of failure.Even if it can copy itself, it would be a single point of failure until the copy was made.
Decentralized
An alternative approach is where all robots can carry out the replication process.A benefit to this approach is that, if one robot survives, and has replication resources available, it can make more robots.This notion leads to the increased survivability of the multi-robot system.It also allows the multi-robot system to split up, and have less dependency on a central hub.One potential drawback, depending on implementation, is that a central hub can be highly versatile in transforming raw materials into usable replication resources.Lacking the ability to use a wide array of raw materials would cause problems in certain environments.
Homogeneous vs. Heterogeneous
If all the robots in a system are the same, it is considered a homogeneous system.Having multiple types of specialized robots makes the system heterogeneous [31].Deciding whether to have different autonomous robots with unique designs to fulfill various requirements includes the consideration of many factors.
Material Usage
Using the minimum amount of materials required to produce a functional robot-meeting relevant quality standards-is desirable, in the context of producing a single robot, as it allows the greatest number of robots possible to be constructed, given the available level of in-situ and stored materials.However, while reducing material consumption in robot production is desirable, having plenty of stock (beyond known and projected requirement levels) is also desirable.This excess stock facilitates system resiliency.In particular, it increases the options that the robot system has in regards to new construction and/or repairs, especially during periods where resource collection is scarce (if resources are prone to periods of scarcity and abundance).
Tailoring robots to special roles can ensure that each robot is designed to include only the necessary functionality, thus saving potentially valuable resources.Another consideration is the design's material requirements versus what is available and abundant.Choosing a design that utilizes locally abundant resources would be ideal, to maximize the number of robots that can be produced.
Manufacturing Efficiency
The decision-making process may also need to consider which robot designs are most efficient.For instance, if the equipment that builds robots is tailor-made for efficiently producing a specific design, then deviating from that would come at a cost.Alternatively, a specialized design may also require certain less-abundant resources or a long duration to build.
Specialization Factors
Having specialized designs may affect how the tasks are allocated amongst the robots, such that the capabilities of each robot would need to be accurately considered in this decision-making process.These specialized designs could arise from evolvable hardware, which makes use of evolutionary computation methods to develop a variety of technologies that enable the automatic design, adaptation, and reconfiguration of electrical and mechanical hardware systems, in ways that outperform conventional techniques [61].However, a potential disadvantage to this is that producing a robot for a specific task which isn't carried out frequently may render it unhelpful after that task is completed.
Hybrid
It may be possible to combine some of the advantages of specialization and interchangeability.For instance, if robots are comprised of a base unit and interchangeable add-ons that can be removed and added, this could effectively make a robust system of highly adaptable robots.
Parallels with Biological Organisms
It is beneficial to consider design concepts based on nature.The field of bionics, for example, seeks to do this by designing technology that mimics features of biological structures [13].For instance, the presence of skin on a hand affects the gripping of objects [13], and an analog may be needed for robotic gripping applications.Jiang, et al. [62] designed an antenna radar cross-section that was inspired by studying insect tentacles.In terms of future applications, Dickinson [63] speculates that, as mechanical capabilities increase and are able to implement such designs, engineers may adopt more and more design concepts from nature.
Biological organisms also provide a model for replication, reproducing in many ways and adapting to their environment through the process of natural selection [64].Similarly, robots could build other robots that are better suited to the environment or to objective-related needs.For robots, the 'mating' process may be replaced with an automatic analysis of needs, and may only involve one parent.
The behavior of certain species of organisms can also provide design inspiration for robots.For instance, certain social animals, such as ants and birds, exhibit intelligent collective behavior.Observations of these animals provided inspiration for swarm intelligence [45], which was discussed in Section 2.5.
Organic materials can also be used as part of a robot's electronic system.For instance, organic semiconductors such as Organic Thin Film Transistors (OTFT) may be able to be used as printable low-cost materials for a wide variety of applications [65].This may make producing robots from in-situ resources easier to accomplish, and increase possible fabrication options so that specific resource scarcity may become less burdensome.Furthermore, it may be possible to grow the organic compounds necessary to craft organic electronics.
However, while biology provides many insights, certain design considerations cannot be directly inferred by studying organic life.For instance, robots do not share certain constraints that animals have, such as the need to maintain a running metabolism.Certain technological solutions may also be superior to natural counterparts.Pfeifer et al. [13], for example, suggested that this was the case for the wheel.
Task Allocation
Task allocation is critical to the operations of a multi-robot system.Determining which robot does what part of what task can become complicated, as tasks become more complex.This is a field that is reasonably well-explored by the scientific community, known as absent consideration of replication.This section provides an overview of this challenge and the prior work used to solve it.
Scheme
Gerkey, et al. [66] provides three criteria that can be used to characterize multi-robot task allocation problems: Single-task robots (ST) vs. multi-task robots (MT):
•
ST means that each robot is capable of executing, at most, one task at a time.
•
MT means that some robots can execute multiple tasks simultaneously.
Single-robot tasks (SR) vs. multi-robot tasks (MR): • SR means that each task requires exactly one robot to achieve it.
•
MR means that some tasks can require multiple robots.
Instantaneous assignment (IA) vs. time-extended assignment (TA): • IA means that the available information concerning the robots, the tasks, and the environment, only permits an instantaneous allocation of tasks to robots, with no planning for future allocations.
•
TA means that more information is available, such as the set of all tasks that will need to be assigned, or a model of how tasks are expected to arrive over time.
It is difficult to definitively categorize a self-replicating multi-robot system based on these criteria.There are benefits and drawbacks to each prospective approach.To simplify the allocation problem, having single task robots is preferable; however, multi-task robots are more capable.This is also similar for the question of designing specialized robots or interchangeable robots, as perhaps some could be designed to be capable of performing multiple tasks concurrently.It is also important to consider how complex disjoint tasks can be, such that robots could be assigned to scan the surrounding environment with visual sensors, while performing an analysis of the soil (assuming that specific visual sensor used for scanning wasn't needed for that).This could warrant having multiple separate task allocation systems, such that one would determine where to scan (i.e., the robots may need to watch a specific area), while another task allocation system could determine movement and environmental interaction.
The category of single robot tasks versus multiple robot tasks will typically lean towards the multiple robot tasks when dealing with self-replicating robots.For most applications, this depends on how the tasks are defined, such that if a task is as broad as 'gather resources to make more robots,' it is very likely that there will be multiple robots tasked with this at one time (the criteria is that some tasks involve multiple robots, not necessarily all of them).
The use of instantaneous assignment versus time-extended assignment is also implementation dependent, but choices will likely fall under the time-extended assignment category, to some degree.This is due to a certain number of future objectives and information being known, or predicted, at the time of assignment.
Centralized vs. Decentralized
With the centralized approach, each robot connects to a central robot that allocates the tasks to all the robots in the system.Each robot sends all the information they have to the central robot, which in turn evaluates this information and sends the appropriate commands to the other robots in the system, which execute their assigned tasks [67].The advantages of this approach include the reduction of the duplication of effort, resources, and savings of cost and time [68].Centralized systems suffer from a lack of redundancy, such that if the central robot fails, the whole system fails.Scalability is also restricted because of the reliance on the central robot, creating a bottleneck for communications and task allocation computation.In addition, centralized approaches generally have a higher communication overhead [69], although this is dependent on the implementation and the size of the system.
In the decentralized system type, each robot communicates relevant information to the other robots [68].This allows administrative tasks to be dispersed among members of the system.The main advantage of the decentralized approach is redundancy.For instance, if one of the robots fails, the other robots can still work on their own and/or cooperatively with other robots in the system [67].This approach also allows for a greater scalability, as adding additional robots does not necessarily overload the central communications, processing, and other capabilities of the system.A disadvantage to this approach is that the robots that make decisions may not receive all of the information gathered by the system, and thus, sub-optimal solutions may be produced.However, this could potentially be overcome by increasing the amount of shared information, and along with this, the level of communications required.Thus, a tradeoff between the communication overhead and solution quality exists [69].
The decision of which system type to use may follow the choice of centralized or decentralized replication.This is because, with centralized replication, the system is already impacted by the reliance of the system on a central hub, providing less incentive to use distributed task allocation.
Optimization vs. Market-Based
Optimization focuses on solving a certain problem, with the aim of finding the best solution for the problem, out of a set of available solutions, given certain decision-making metrics.Optimization techniques are used to maximize the 'profit' (maximization problem) or mitigate the 'loss' (minimization problem) of a prospective solution [70].The set of available solutions is restricted by a set of constraints, and the optimum solution is chosen within these constrained solutions, based on certain criteria.These criteria define the objective function, which is a mathematical expression combining variables in order to describe the goal of the system [71].
Alternatively, market-based approaches use the concept of utility functions, which can represent the ability of the agents to measure interest in specific tasks for trading.In these systems, the utility functions show how the robot's skills can match the task's requirements [70].
Either approach could feasibly be used for decision-making for a self-replicating robot system.For instance, optimization techniques have been demonstrated to be effective in allocating resources for automated manufacturing [72].
Decision to Replicate
The decision of when a self-replicating robot system should replicate is affected by several factors.These factors include the available resources, replication equipment, current objectives, and robot capacity.These factors are depicted in Figure 1 and are discussed in the following subsections.The decision of which system type to use may follow the choice of centralized or decentralized replication.This is because, with centralized replication, the system is already impacted by the reliance of the system on a central hub, providing less incentive to use distributed task allocation.
Optimization vs. Market-Based
Optimization focuses on solving a certain problem, with the aim of finding the best solution for the problem, out of a set of available solutions, given certain decision-making metrics.Optimization techniques are used to maximize the 'profit' (maximization problem) or mitigate the 'loss' (minimization problem) of a prospective solution [70].The set of available solutions is restricted by a set of constraints, and the optimum solution is chosen within these constrained solutions, based on certain criteria.These criteria define the objective function, which is a mathematical expression combining variables in order to describe the goal of the system [71].
Alternatively, market-based approaches use the concept of utility functions, which can represent the ability of the agents to measure interest in specific tasks for trading.In these systems, the utility functions show how the robot's skills can match the task's requirements [70].
Either approach could feasibly be used for decision-making for a self-replicating robot system.For instance, optimization techniques have been demonstrated to be effective in allocating resources for automated manufacturing [72].
Decision to Replicate
The decision of when a self-replicating robot system should replicate is affected by several factors.These factors include the available resources, replication equipment, current objectives, and robot capacity.These factors are depicted in Figure 1 and are discussed in the following subsections.
Available Resources
Resource availability is critical to the decision to build a robot.Multiple factors, as shown in Figure 2, contribute to the resource availability characterization that is supplied to the decision-making algorithm.A requirement for fabricating a new robot is to have (or project having) the materials that are needed to build it.Another factor to consider is the quality/purity of the resources.Poor quality resources could impact the quality of the finished product, which (ideally) should be considered when deciding whether to move forward with the replication process.
Available Resources
Resource availability is critical to the decision to build a robot.Multiple factors, as shown in Figure 2, contribute to the resource availability characterization that is supplied to the decision-making algorithm.A requirement for fabricating a new robot is to have (or project having) the materials that are needed to build it.Another factor to consider is the quality/purity of the resources.Poor quality resources could impact the quality of the finished product, which (ideally) should be considered when deciding whether to move forward with the replication process.The acquisition of resources occurs through foraging.Robot foraging is broadly defined as robots searching for and collecting objects, and subsequently bringing them to a collection point [73].Baldassano and Leonard [74] described measures of performance that can be used to allocate tasks for this purpose.Fibla and Bernardet [75] designed a strategy for robot foraging, based on the behavior of rodents.Cai [76] developed a learning algorithm to handle foraging tasks in completely unknown environments.
Resources can be divided into three categories: collected, located but not collected, and predicted to be in the environment but not located.Collected resources, as the name suggests, are resources that have been collected and stored by the robot system.However, a consideration in this category is the proximity of storage relative to where they would need to be used.The second category, resources that are located but not collected, encompasses resources that have been identified, with some degree of accuracy, to be present in specific locations in the environment.The degree of accuracy of this identification can significantly impact the level of reliance that is appropriate for resources in this category.The last category is resources that are predicted to be in the environment, but have not been located yet.This category's importance will vary in inverse proportion to how much of the environment is currently explored.For instance, at the early stages of exploration, the system may predict that there will be a certain amount of a certain material available, but as soon as the exploration effort progresses, the predicted resources will be transformed into located resources.As exploration is conducted, the resource prediction accuracy may also increase.
The process of predicting the resources available in a given environment may require prior knowledge of certain environmental traits, including geological and other information.To this end, Popa, Screenath, and Lewis [77] discussed algorithms for sampling an environment using mobile robots.Alternatively, certain environments can be continuously monitored by robots.Dunabin and Marques [78] detail the ways in which this has been done in the past, with one example being the monitoring of lakes for specific ecological changes.
Recognizing resources in a given environment can be accomplished in many ways.For example, reflection seismology (similar in concept to radar) has been used to discover oil and natural gas [79].Magnetic surveys can used to detect ore deposits [80].The visual recognition of surface resources can be accomplished by processing images using trained deep convolutional neural networks [81].The foregoing techniques could identify many of the resources required for robot replication.Additional techniques may be needed for robots with additional resource identification needs.
Once the resources are identified, the robots must be able to autonomously collect them.A number of prior experiments and applications demonstrate relevant capabilities.For example, Green and Vogt [82] proposed a multi-robot system that could cooperatively and autonomously mine ore using rock drills.Similarly, Shaffer and Stentz [83] tested a robotic system for coal mining that could autonomously navigate and reposition itself underground using a laser range finder.Hecker, Carmichael, and Moses [84] described a resource cluster prediction algorithm, inspired by ant foraging behavior, that exploited the natural clustering of resources to efficiently direct robots to find and collect them.Dunker et al. [85] demonstrated a proof of concept for utilizing teams of robots that could automatically gather regolith on the surface of the Moon with an actuated scoop.It would then The acquisition of resources occurs through foraging.Robot foraging is broadly defined as robots searching for and collecting objects, and subsequently bringing them to a collection point [73].Baldassano and Leonard [74] described measures of performance that can be used to allocate tasks for this purpose.Fibla and Bernardet [75] designed a strategy for robot foraging, based on the behavior of rodents.Cai [76] developed a learning algorithm to handle foraging tasks in completely unknown environments.
Resources can be divided into three categories: collected, located but not collected, and predicted to be in the environment but not located.Collected resources, as the name suggests, are resources that have been collected and stored by the robot system.However, a consideration in this category is the proximity of storage relative to where they would need to be used.The second category, resources that are located but not collected, encompasses resources that have been identified, with some degree of accuracy, to be present in specific locations in the environment.The degree of accuracy of this identification can significantly impact the level of reliance that is appropriate for resources in this category.The last category is resources that are predicted to be in the environment, but have not been located yet.This category's importance will vary in inverse proportion to how much of the environment is currently explored.For instance, at the early stages of exploration, the system may predict that there will be a certain amount of a certain material available, but as soon as the exploration effort progresses, the predicted resources will be transformed into located resources.As exploration is conducted, the resource prediction accuracy may also increase.
The process of predicting the resources available in a given environment may require prior knowledge of certain environmental traits, including geological and other information.To this end, Popa, Screenath, and Lewis [77] discussed algorithms for sampling an environment using mobile robots.Alternatively, certain environments can be continuously monitored by robots.Dunabin and Marques [78] detail the ways in which this has been done in the past, with one example being the monitoring of lakes for specific ecological changes.
Recognizing resources in a given environment can be accomplished in many ways.For example, reflection seismology (similar in concept to radar) has been used to discover oil and natural gas [79].Magnetic surveys can used to detect ore deposits [80].The visual recognition of surface resources can be accomplished by processing images using trained deep convolutional neural networks [81].The foregoing techniques could identify many of the resources required for robot replication.Additional techniques may be needed for robots with additional resource identification needs.
Once the resources are identified, the robots must be able to autonomously collect them.A number of prior experiments and applications demonstrate relevant capabilities.For example, Green and Vogt [82] proposed a multi-robot system that could cooperatively and autonomously mine ore using rock drills.Similarly, Shaffer and Stentz [83] tested a robotic system for coal mining that could autonomously navigate and reposition itself underground using a laser range finder.Hecker, Carmichael, and Moses [84] described a resource cluster prediction algorithm, inspired by ant foraging behavior, that exploited the natural clustering of resources to efficiently direct robots to find and collect them.Dunker et al. [85] demonstrated a proof of concept for utilizing teams of robots that could automatically gather regolith on the surface of the Moon with an actuated scoop.It would then bring the collected materials to a central processing station.Each of the foregoing would be a capability that could be integrated into the self-replication robots' design to provide basic functionality.As with resource identification, the resource collection capabilities of a robot (both in terms of physical collection hardware and commanding software) may need to be augmented to support mission-specific collection requirements.
Replication Equipment
The replication equipment present needs to have the capability to produce the needed design, otherwise the process cannot move forward.There will typically be a probability of success associated with the equipment's capability to perform a given printing task.If this is known, it can be factored into the decision-making process.This chance of success can be calculated, based on a few factors, such as damage to the equipment and the limitations of equipment in pristine condition.Damage can be identified by measuring the results of production and comparing it to the expected results [86].Even if the equipment can build the design, it may have known limitations or the potential to encounter errors.Issues can include the equipment jamming, printed parts not fitting together properly, and adverse environmental conditions.
Objectives
The current mission objectives, as shown in Figure 3, are relevant to the decision to build a new robot (or not).These objectives would determine the necessity for fabricating a new robot, and what design it would have.This information would drive the need (if required) for increasing the quantity of robots, or optimizing a design for a specific capability.
bring the collected materials to a central processing station.Each of the foregoing would be a capability that could be integrated into the self-replication robots' design to provide basic functionality.As with resource identification, the resource collection capabilities of a robot (both in terms of physical collection hardware and commanding software) may need to be augmented to support mission-specific collection requirements.
Replication Equipment
The replication equipment present needs to have the capability to produce the needed design, otherwise the process cannot move forward.There will typically be a probability of success associated with the equipment's capability to perform a given printing task.If this is known, it can be factored into the decision-making process.This chance of success can be calculated, based on a few factors, such as damage to the equipment and the limitations of equipment in pristine condition.Damage can be identified by measuring the results of production and comparing it to the expected results [86].Even if the equipment can build the design, it may have known limitations or the potential to encounter errors.Issues can include the equipment jamming, printed parts not fitting together properly, and adverse environmental conditions.
Objectives
The current mission objectives, as shown in Figure 3, are relevant to the decision to build a new robot (or not).These objectives would determine the necessity for fabricating a new robot, and what design it would have.This information would drive the need (if required) for increasing the quantity of robots, or optimizing a design for a specific capability.
An increase in the quantity of robots may be needed for certain exploration efforts, or to support planned future robot fabrication predictions.An alternative consideration is that a design may be needed for a specific task that has a necessary benefit, such as reaching and collecting a resource that is out of reach of the current robots in the system (see the discussion of homogeneous vs heterogeneous selection, above for more on special designs).
Capacity
Depending on user choices or implementation and design constraints, it may be that the robot system is capped at having a certain maximum number of robots.The system capacity factor, depicted in Figure 4, characterizes the ability of the system to support more robots, to inform the build-or-not decision-making process.One example of a restriction would be having centralized command and communications, such that the number of robots that the central robot can command or communicate with is limited.Another restriction would be if robots needed a certain resource to continue functioning over time, such as energy or replacement parts.Finally, the number of robots that a system can have may also be restricted by the space available in the operating environment.Small spaces would obviously necessitate a fewer number of robots for optimal performance.This notion of an optimal number of robots as opposed to a maximum may even be a more general consideration.An increase in the quantity of robots may be needed for certain exploration efforts, or to support planned future robot fabrication predictions.An alternative consideration is that a design may be needed for a specific task that has a necessary benefit, such as reaching and collecting a resource that is out of reach of the current robots in the system (see the discussion of homogeneous vs heterogeneous selection, above for more on special designs).
Capacity
Depending on user choices or implementation and design constraints, it may be that the robot system is capped at having a certain maximum number of robots.The system capacity factor, depicted in Figure 4, characterizes the ability of the system to support more robots, to inform the build-or-not decision-making process.One example of a restriction would be having centralized command and communications, such that the number of robots that the central robot can command or communicate with is limited.Another restriction would be if robots needed a certain resource to continue functioning over time, such as energy or replacement parts.Finally, the number of robots that a system can have may also be restricted by the space available in the operating environment.Small spaces would obviously necessitate a fewer number of robots for optimal performance.This notion of an optimal number of robots as opposed to a maximum may even be a more general consideration.
System Operations
The operations of the system are now considered, holistically.Figure 5 depicts the general decision-making process undertaken by each robot in the system.This diagram assumes a limited set of objectives, including repair robot, build robot, idle, gather resources, explore, and other missionrelated objectives.
One point of interest is the flow of locating resources, to collecting resources, to having them available to use as materials (for new robots or for repairs to existing ones).The 'explore' objective locates resources and contributes to the terrain map.Located resources can subsequently be gathered by a robot that is pursuing the 'gather resources' objective.Gathering resources contributes to the available resources, which may then be used to build or repair robots.These different steps can be performed by the same robot or performed by different robots, depending on the circumstances.Communication amongst robots in the system updates these databases to reflect changes in resource status.This is important because this data affects the decision-making process, such as whether the system carries out a task or not.It also lets a robot know which tasks it has been allocated, based on the task allocation scheme.An example would be communicating that resources from the available resource pool are no longer available, as they were used to construct or repair a robot.
System Operations
The operations of the system are now considered, holistically.Figure 5 depicts the general decision-making process undertaken by each robot in the system.This diagram assumes a limited set of objectives, including repair robot, build robot, idle, gather resources, explore, and other mission-related objectives.
System Operations
The operations of the system are now considered, holistically.Figure 5 depicts the general decision-making process undertaken by each robot in the system.This diagram assumes a limited set of objectives, including repair robot, build robot, idle, gather resources, explore, and other missionrelated objectives.
One point of interest is the flow of locating resources, to collecting resources, to having them available to use as materials (for new robots or for repairs to existing ones).The 'explore' objective locates resources and contributes to the terrain map.Located resources can subsequently be gathered by a robot that is pursuing the 'gather resources' objective.Gathering resources contributes to the available resources, which may then be used to build or repair robots.These different steps can be performed by the same robot or performed by different robots, depending on the circumstances.Communication amongst robots in the system updates these databases to reflect changes in resource status.This is important because this data affects the decision-making process, such as whether the system carries out a task or not.It also lets a robot know which tasks it has been allocated, based on the task allocation scheme.An example would be communicating that resources from the available resource pool are no longer available, as they were used to construct or repair a robot.One point of interest is the flow of locating resources, to collecting resources, to having them available to use as materials (for new robots or for repairs to existing ones).The 'explore' objective locates resources and contributes to the terrain map.Located resources can subsequently be gathered by a robot that is pursuing the 'gather resources' objective.Gathering resources contributes to the available resources, which may then be used to build or repair robots.These different steps can Example 1: A self-replicating robot system could be used for planetary exploration.This would be especially useful due to the high cost of bringing materials to those sites.This example works with the proposed approach, due to having the overall mission objectives of exploring and resource gathering.Exploring the planet would provide a non-competitive resource source for the robots, such that they could use whatever they find without competition, promoting scalability.Printing robots could also achieve a faster exploration rate, compared to a fixed number of robots, as well as providing the opportunity to take more risks when exploring.Security wouldn't be a concern due to the non-contention environment of the robot system.The efficiency of the system would depend on the planet being explored and the resources available.The teamwork of the robots should be satisfactory.
Example 2: A second considered use for the system is for military purposes.A key benefit of this application is that lost robots could be replenished (by robots constructing more robots).This works with the proposed approach because materials may be easy to find in combat zones, and the need to explore is usually present, for intelligence gathering and other purposes.The security of this use is very low due to the entire purpose of this system being to engage in combat missions.This may necessitate more thought being devoted to system security.The efficiency of the system depends on the combat environment and the capabilities of individual robots.
Example 3: Self-replicating nano-robots that can repair larger structures are now considered.This application fits the proposed approach due to the need for exploration and resource gathering for repair materials.The scalability is quite high due to the low amount of material needed to build a small robot.System security needs of this use are low, due to the difficulty (for an attacker) in keeping track of all the nano-bots and their ability to cause harm to individuals.The efficiency of the system and cooperation is satisfactory, due to the robots' ability to work well as a team, as well as alone.
Example 4: Self-replicating visual sensor robots could be tasked with surveying an environment.The proposed approach would perform well, due to the already existent exploration component task.It would also be scalable, because having redundant environmental sensors is a reasonably smart practice to ensure up-time.System security wouldn't be a typical issue, unless it was used for intelligence purposes.The efficiency of gathering resources would be lackluster, due to the presumed low mobility of the robots in this example.System teamwork would be satisfactory (across the board), providing constant performance across varying circumstances.
Example 5: The proposed approach's efficacy for the application of self-replicating satellites that use orbital debris to construct more satellites is considered.The proposed approach may not perform well due to the limited mobility of most satellites, as well as the availability of materials.It would likely not be scalable due to possible distance, line of sight, and communication obstructions.It would present a security risk due to high value asset proximity operations and the high surveillance capability of that vantage point.The performance would generally be satisfactory (as long as it has suitable equipment for dealing with the difficult conditions in space).Craft cooperation would largely be limited to communications and not proximal teamwork, for this application.
Example 6: A system of self-replicating robots tasked with collecting garbage is feasible to implement with the proposed approach.The collected garbage may even be able to be used as material for the robots to replicate with, which would promote scalability.The exploration usefulness, for this example, may be hampered in favor of locating and collecting garbage in a predetermined area.Cooperation, however, would be needed for efficiency and support, for when multiple robots are needed to collect a heavy or otherwise difficult to remove piece of garbage.
Example 7: The use of self-replicating transportation vehicles for commercial use is now evaluated.This example would work well with the proposed approach due to operating in already mapped terrain, such that the transportation would be across frequently visited paths.It would be scalable enough to provide suitable transportation to passengers.The utility of replication capabilities, on a distributed basis, is questionable.Its cooperative teamwork would depend on implementation and design.
Example 8: Robots that collect energy may be implemented as self-replicating, to increase the amount of energy gathered.While the proposed approach is feasible for this example, it would lack the necessity to explore the environment and foraging requirements for replication.Cooperation may be hampered by the lack of exploration goals and perhaps even result in robots in competition for resources, such that proximity operations would become inefficient.
Example 9: Finally, the proposed approach's utility for self-replicating and reconfiguring modular robots that bond together to form shapes is considered.The amount that this use would benefit from the proposed approach is possibly limited by the specific area of application.However, this application would be very scalable and highly cooperative, with an emphasis on proximity operations.In contrast, the performance of this example when the robots are distributed would be poor, due to their modular nature.
The ability of the robot system to switch capabilities (and thus missions), by printing new robots, is also of interest due to the dynamic nature of many prospective operation environments.This can lead to a drastic shift of purpose, such that vastly different missions can be carried out with the same robot system, after it undergoes a design configuration change.
Conclusions and Future Work
The concepts, design, and coordination of self-replicating robot systems have been discussed in this paper and a high-level algorithm was proposed and qualitatively assessed.The increasing capabilities of 3D printers are opening the door to feasible 3D printing-based self-replicating robots.This work stems from the general notion of a need for a machine that can assemble anything, like a universal constructor.
There is a need for software that can command these robots, despite their potential for differing designs and capabilities.An interface could be used to determine hardware capabilities, which would then be communicated to the general behavioral command program (the algorithm that was presented herein).
The benefits of a self-replicating robot system stem from being able to replenish lost robots and the capability to create new ones.However, there are issues that arise during the development of these machines, such as the ethical, environmental, and societal ramifications.These issues may need to be adequately addressed before such robot systems become available, and future work plans to discuss this.
Figure 1 .
Figure 1.Key decision-making factors for the new robot construction decision.
Figure 1 .
Figure 1.Key decision-making factors for the new robot construction decision.
Figure 4 .
Figure 4. Example constraints on the maximum number of robots needed.
Figure 4 .
Figure 4. Example constraints on the maximum number of robots needed.
Figure 4 .
Figure 4. Example constraints on the maximum number of robots needed. | 13,036.8 | 2017-04-06T00:00:00.000 | [
"Computer Science",
"Engineering"
] |
Quantification of Protein Glycosylation Using Nanopores
Although nanopores can be used for single-molecule sequencing of nucleic acids using low-cost portable devices, the characterization of proteins and their modifications has yet to be established. Here, we show that hydrophilic or glycosylated peptides translocate too quickly across FraC nanopores to be recognized. However, high ionic strengths (i.e., 3 M LiCl) and low pH (i.e., pH 3) together with using a nanopore with a phenylalanine at its constriction allows the recognition of hydrophilic peptides, and to distinguish between mono- and diglycosylated peptides. Using these conditions, we devise a nanopore method to detect, characterize, and quantify post-translational modifications in generic proteins, which is one of the pressing challenges in proteomic analysis.
FraC monomer expression and purification
Plasmid containing the FraC gene was transformed into BL21(DE3) cells using electroporation.
The transformed cells were grown overnight at 37 ºC on LB agar plates supplemented with 1% glucose and 100 µg/ml ampicillin. On the next day, the colonies were pooled together and resuspended and grown in 200 mL 2YT medium at 37 ºC until the OD600 reached a value of 0.6-0.8. At this point, the expression was induced by the addition of 0.5 mM IPTG and the culture was incubated overnight at 25 ºC. Afterwards, the cells were pelleted by centrifugation at 4000 rpm for 15 minutes and the cell pellets were stored at -80 ºC for at least 30 minutes.
For protein purification, cell pellets of 100 ml culture were resuspended in 20 ml lysis buffer,
Single-channel recordings
Two fluidic compartments are separated by a polytetrafluoroethylene (Teflon) film (Goodfellow Cambridge Ltd) with a thickness of 25 µm, containing an aperture of approximately 100 µm in diameter. First, 10 µl of a 5% hexadecane solution in pentane is applied to the aperture and the pentane is left to evaporate shortly. Afterwards, both compartments are filled with 400 µl buffer and 10 µl of a 10 mg/ml DPHPC solution in pentane is added on top of the buffer solution.
The chamber is left to evaporate the pentane and an Ag/AgCl electrode is placed in each compartment as to make contact with the buffer solution. Planar lipid bilayers were formed by repeatedly lowering and raising the buffer solution until a stable lipid bilayer was formed. FraC nanopores were added to the cis-compartment and the lipid bilayer was reformed until a single channel was present. Presence of a single channel and its orientation were confirmed by the IV characteristics of the pore. A two-minute blank was recorded and afterwards substrate was added to the cis-compartment.
Data acquisition
The ionic current was recorded using a Digidata 1440A (Molecular Devices) connected to an Axopatch 200B amplifier (Molecular Devices). All data is recorded with a sampling frequency of 50 kHz and with a Bessel filter of 10 kHz. The data is then digitally filtered using a 5 kHz Gaussian low-pass filter prior to the event detection.
Event detection
First, using Clampfit software, the full-point histogram of the ionic current trace was taken in order to determine the open pore current (Io) and the open pore noise ( 0 ). A Gaussian around the open pore current was fitted to determine the peak centre (Io) and standard deviation ( 0 ).
Then, events were detected using a threshold search with a threshold of 5* 0 and with a minimum duration of 50 µs. The excluded current percent (Iex%) was calculated using % = ( ∆ 0 ) * 100%, where ΔIB (=IO -IB) is the magnitude of the current blockade.
Glycopeptide dwell time analysis
After event detection, the average dwell time of the peptides was estimated for each salt concentration in triplicates. First, the Iex% range was determined for each peptide cluster: 71 to 78% for 9mer_2Glc, 62 to 68% for 9mer_1Glc and 56 to 61% for 9mer_unmod. A log-normal distribution was fitted through the dwell time histogram to obtain the mean dwell time of each peptide cluster. The standard deviation is calculated between the three individual measurements in different nanopores.
Reaction mixtures (total 5.4 mL) consisted of 0.5 mM 9mer peptide (~2.5 mg) (from 10 mM DMSO stock to keep DMSO content low) and 2.5 mM UDP-Glc in the reaction buffer (50 mM HEPES, 100 mM NaCl, 10% glycerol, pH 7.5). Reactions were initiated by the addition of 10 µM ApNGT 2 and incubated at room temperature overnight. The glycosylation of ANVTLNTTG was pushed over the next five days by addition of total extra 7.3 mg of UDP-Glc and 10 µM of ApNGT until ~90% conversion to the di-glycosylated product was reached. To prepare the samples for LCMS analysis, an aliquot of the reaction mixture was diluted 10-fold and analyzed with RP-LCMS (1 µL injection, Acquity UPLC HSS T3 column (Waters, 2.1×150 mm, 1.8 µm) in combination with eluents A (0.1% formic acid in H2O) and B (0.1% formic acid in acetonitrile), 20 min run (flow rate 0.3 mL/min) with a linear gradient from 5% to 95% of B in 13 min with subsequent increase to 95% B for 3min and return to 5% B). Before anion exchange purification, reaction mixtures were filtered through a 0.2 µm filter. The resulting peptides were separated from the ApNGT, UDP and UDP-Glc by strong anion exchange on FPLC ÄKTA system (GE Healthcare). For this, 1 mL of the reaction mixture (~ 0.2 mM peptide concentration) was applied on a Q FF column (5 mL, GE Healthcare) with a flow rate of 1.5 mL/min. The column was eluted with the linear gradient from 0 to 60% Buffer B (0.9 M NH4HCO3) in ten column volumes, with subsequent increase to 100% in four CV. Elution was monitored with UV (214 nmpeptide and 280 nm -UDP, UDP-Glc). The fractions containing glycosylated peptides (first 5-6 min of the elution) were pooled and freeze-dried. Dried samples were reconstituted in DMSO to prepare stocks for the nanopore analysis.
Rhamnosylation and purification of the 11mer_Pa peptide
To prepare rhamnosylated 11mer-L-Pro-D-Pro_Pa, 2.7 mM 11mer_Pa (1 mg), 6.1 mM TDP-Rha (1.2 mg) and 41 µM EarP were incubated at room temperature for two days in the reaction buffer (20 mM Tris, 100 mM NaCl, pH 8). The reaction was pushed to full conversion over the next three days by addition of total extra 1 mg of TDP-Rha and 24 µM of EarP until ~90% conversion was reached. Subsequently, the reaction mixture was diluted to a 0.5 mM concentration of Rha-11mer, applied to an Amicon spin filter (MWCO 10 kDa, 15 mL,Millipore) and centrifuged at 5000 x g to remove the enzyme. The resulting solution was further purified from TDP and TDP-Rha by strong anion exchange on FPLC (ÄKTA system, GE Healthcare).
For this, 0.25 mL of the reaction mixture was applied on Q FF column (5 mL, GE Healthcare) with flow rate 1 mL/min in five column volumes (CV). The column was eluted with the linear gradient from 0 to 10% Buffer B (1M NH4HCO3) in two CV with subsequent increase to 100% in four CV. Elution was monitored with UV (214 nmpeptide and 280 nm -TDP, TDP-Rha).
The fractions containing rhamnosylated 11mer_Pa peptide were pooled and freeze-dried.
Residual buffer salts were removed by desalting with PD-10 desalting columns (GE Healthcare). Desalted fractions of Rha-11mer were freeze-dried and aqueous stock of 0.5 mM was prepared for the nanopore studies.
Quantification of rhamnosylation on peptides using the nanopore
After event detection, the Iex% spectra of the three measurements were first realigned to correct for small shifts in the baseline. After baseline correction, a Gaussian mixture model was used to detect the event clusters. We found that the clusters are best detected in the Iex% vs event noise (ISD) spectrum, where ISD is the fluctuation of the ionic current during the event. From the fitting of the Gaussian mixture model, the location and distribution of the event clusters in the Iex% vs ISD spectrum was obtained. For each detected event cluster, the center (µ1) and the spread (σ1) in Iex% and the center (µ2) and spread (σ2) in ISD was determined. Then, for each event cluster the events that satisfy both (µ1-σ1) > Iex% > (µ1+σ1) and (µ2-σ2) > ISD > (µ2+σ2) were counted to obtain the number of events belonging to the rhamnosylated peptide (nRha) and the unmodified peptide (nunmod). In addition, the events that satisfy the same equation in the blank measurement were subtracted to reduce the effect of intrinsic current blockages. The percentage of rhamnosylation in the sample is estimated as: nRha/(nRha+nunmod)*100%. These values are then used in equation 2 to calculate the RDF. Finally, the conversion is calculated using: The standard deviation is calculated between the three individual measurements in different nanopores.
Rhamnosylation and purification of EF-P
To prepare rhamnosylated EF-P, 12 μM of EF-P (after His6-SUMO-tag cleavage, as described in 3 ) was incubated with 2 μM of EarP-His6-SUMO and 100 μM TDP-Rha in the reaction buffer (20 mM Tris, 500 mM NaCl, pH 8) overnight at room temperature. The next day, Ni-affinity chromatography was used to isolate Rha-EFP. Briefly, the reaction mixture was incubated with Ni-NTA resins for 1.5 h at 4 ºC with gentle shaking. The resulting suspension was allowed to pass through the gravity column and the flow-through was collected. Next, the resin was washed once with lysis buffer (20 mM Tris, 500 mM NaCl, pH 8), followed by washing buffer 1 in two steps (20 mM Tris, 500 mM NaCl, 15 mM imidazole, pH 8), and washing buffer 2 in two steps (20 mM Tris, 500 mM NaCl, 30 mM imidazole, pH 8). This was followed by elution with elution buffer (20 mM Tris, 500 mM NaCl, 400 mM imidazole, pH 8). Analysis of the purification fractions with SDS-PAGE ( Figure S7) indicated that Rha-EFP was present in the flow-through, lysis buffer wash, and washing buffer (1 and 2) fractions. To prepare the Rha-EF-P sample for the nanopore analysis, fractions containing the protein were pooled, diafiltrated, and concentrated with Amicon spin filter to 6.5 mg/mL (0. 3 mL total). The purity of the sample was confirmed with intact protein MS analysis ( Figure S8).
Lys-C digestion of EF-P and rhamnosylated EF-P
200 ng of protein was dissolved in 180 µl buffer containing 100 mM Tris, buffered to pH 8.0.
Then we add 4 µg of Lys-C, yielding a 1:50 enzyme : protein mass ratio and the sample is subsequently incubated overnight at 37 ºC. On the next day, an Amicon filter with a molecular weight cut-off of 3000 Da was used, to eliminate the protease and any undigested protein from the sample. The sample is stored at -20 ºC until use. Figure S4: Initial screening of other FraC mutants for glycopeptide detection. Ionic current traces (left) and event characteristics (right) of measurements in FraC mutants with single glycopeptides. Top panel: 30 µM of 9mer_2Glc added to a FraC D10R nanopore, measured at +100 mV applied voltage. Middle panel: 10 µM of 9mer_2Glc added to a FraC G13H nanopore, measured at +50 mV applied voltage. Bottom panel: 7.5 µM of 9mer_2Glc added to a FraC G13W nanopore, measured at -70 mV applied voltage.
20mdv048-YAK-EFP_XT_00001_MHp__200608123306 #1 RT: 1. The -10lgP score relates to the probability of detection and the peak area (Area EF-P) relates to the concentration of the peptides in the sample. The second column shows the peptide numbers according to Table 2. The -10lgP score relates to the probability of detection and the peak area (Area Rham EF-P) relates to the concentration of the peptides in the sample. The second column shows the peptide numbers according to Table 2. | 2,689.4 | 2022-06-29T00:00:00.000 | [
"Biology"
] |
A comparison of male and female headed house holding of orphans and vulnerable children in Nigeria
1 Association for Reproductive and Family Health,-Lopin 1 Project, Plot 815A, Ibadan Army Officers Mess Road, Ibadan, Oyo State, Nigeria. 2 United States Agency for International Development (USAID), Plot 1075, Diplomatic drive, Central Business District, Garki, Abuja, Federal Capital Territory, Nigeria. 3 Department of Epidemiology and Medical Statistics, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
INTRODUCTION
A household is one or more individual(s) occupying the same room(s) in a house or building such that all members eat from the same source. It could also be made up of one or more families, extended in their relationship (Lawson, 2014). However, the household is regarded as the fundamental social and economic unit of society. The head of household is defined as "the one who manages the income earned and expenses incurred *Corresponding author. E-mail<EMAIL_ADDRESS>Tel: +234-803-395-1181.
Author(s) agree that this article remain permanently open access under the terms of the Creative Commons Attribution License 4.0 International License by the household, and is recognized by other members of the household as the head (UNHS, 09/10). This household head could either be a male or a female.
Historically, household headship in many African countries including Nigeria is synonymous with the primary provider of economic needs of the household members and males are culturally and socially enjoined to hold this position right from the day of marriage, when a family starts. It is a major responsibility of the household head to provide direction and access to social and basic services such as food, health, education, potable water, protection, psychosocial support, good hygiene and sanitation for members of his or her households (Appleton, 1996). This is more so in many societies in Nigeria where patriarchy is the cultural norm, and so headship of the household is usually related with men (Bammeke, 2010). Although in recent times, it is being encapsulated that women are recognized as potential household heads but in reality men are most often ascribed the headship position because of the patriarchal view that men should provide for the family while women nurture it (Illo, 1989).
However, it appears there is indeed a paradigm shift in headship of households in many regions of the world where household heads were known to be typically men have witnessed a rising proportion of households headed by females. For example, 13% of households in the Near East/North Africa, 16% in Asia, 22% in sub-Saharan Africa, and 24% in Latin America have females as head of households. In fact the proportion of female headed households (FHH) was more than one-third in countries such as Ghana, Haiti and Zimbabwe (Bongaarts, 2001) and between 15 and 27% in Nigeria, Kenya, Uganda and Chad (World Bank, 2015;ICRW, 1988). Studies have shown that the nature of poverty in sub-Saharan countries in Africa could be responsible for the observed situations that female headed households tend to be poorer and less equipped to cater for children in their households. But, it has been perceived that with the nature of poverty experienced in the sub-Saharan countries, female headed households tend to be poorer and less prepared to care for children in their households (Milazzo and van de Walle, 2015). But this observation is not limited to developing countries as globally femaleheaded households are well known as poorer of the poor (Kennedy and Haddad, 1994).
In spite of the inadequacies of females to cater for a household as the head, there has been a continual upsurge in the number of female headed households. A key population of interest in this study is the households of orphans and vulnerable children (OVC). In most cases these children are made orphans by HIV/AIDS or other events that make the female the surviving parent and so forced to assume the burden of headship of their households. And so, the welfare of the surviving children becomes that of the surviving wives who unfortunately might not have been prepared for their sudden headship role of their households. It is therefore not surprising to find these female households to perform poorly on the living standard indicators such as per capita expenditures (purchasing power), poverty incidence and caloric intake. Also, when assets, capacity to borrow and labor resources are considered, FHHs are more vulnerable to the shocks that lead to declines in living standards in the long term (Ha, 2002).
Regrettably, the incidence of OVC has been on the increase globally and Nigeria shares a high burden of this special population. The Federal Ministry of Women Affairs and Social Development puts the number of OVC in Nigeria as 17.5 million (FMWASD, 2014). Studies have shown that female-headed households are naturally more mature households with older adults and less young children, hence, they have smaller household size. A global report showed that the OVC population has been fuelled by the epidemic of HIV/AIDS contributing about 16.6 million of the OVC who lost either one or both parents (majority of whom are in the African continent) (Asia, 2011). In fact, the death of prime-age-adults due to HIV/AIDS has orphaned millions of children, jeopardizing their well-being and compromising their opportunities (Guarcello et al., 2004. Thus, households with orphans and vulnerable children often suffer from inadequate care with a sizeable majority being cared for by not too well prepared mothers and end up with extended family members (UNICEF, 2006). A study in Malawi showed that OVC prefer to live in households headed by their grandparents. In some countries in sub-Saharan Africa, 40-60% of orphans live in grandmother-headed households (UNICEF, 2006).
Unfortunately, there is a dearth of strategic information on the caregivers of households of OVC with respect to the heads of these households in Nigeria. The Federal Ministry of Women and Social Development in Nigeria in partnership with foreign partners like the United State Government through PEPFAR and the USAID have been in the vanguard of care for the OVC. Recently, a project entitled Local Partners for Orphans and Vulnerable Children in Nigeria (LOPIN) was sponsored by USAID to mitigate the impact of HIV/AIDS on families infected and affected in selected states and LGAs with high burden of HIV/AIDS in Nigeria. The strategy adopted is to link the families of OVC to appropriate educational, nutritional, protective and health services while empowering the households to enable them provide for their households on a sustainable manner. The Association for Reproductive and Family Health (ARFH), an indigenous local non-governmental organization (NGO) with headquarters located in Ibadan, South West Nigeria, started the implementation of this project in 13 LGAs located in Akwa Ibom, Lagos and Rivers states of Nigeria in 2015. In a baseline survey, the heads or caregivers of the OVC households were identified and their personal social demographic characteristics and other health characteristics of the households and OVC were documented.
Aims
This paper focuses on the characteristics of the gender of the heads of the OVC households and the wellbeing of their OVC. It also compares the advantages and disadvantages of female and male headed households as it affects the welfare of the OVC households.
METHODOLOGY
This is a descriptive cross sectional survey of OVC households conducted in 13 Local Government Areas (LGAs) in Nigeria; 5 each in Akwa Ibom and Lagos States and 3 others in Rivers State. The LGAs in Akwa Ibom State were: Ikot Ekpene, Okobo, Oron, Uruan and Uyo; Lagos State: Agege, Ajeromi, Badagry, Ojo and Kosofe while those in Rivers State were: Port Harcourt, Eleme, and Obio/Akpor. The LGAs were purposively selected as they were part of the 32 PEPFAR/USAID priority LGAs with high burdens of HIV and OVC in Nigeria (PEPFAR, 2012). The National Vulnerable Assessment Questionnaire was used to identify the vulnerable households (Federal Ministry of Women Affairs and Social Development, Nigeria, 2009;Bamgboye et al., 2017).The survey was carried out between May and July 2016, by the Association of Reproductive and Family Health (ARFH), the implementing partner of LOPIN Region 1 project.
Data collection
A structured questionnaire adapted from MEASURE Evaluation OVC tool kit was used to obtain information on the demographic characteristics of the caregivers or heads of the enrolled vulnerable households, their household socio economic characteristics, including household income, membership of savings groups and access to obtaining loans by personal interview (MEASURE Evaluation, 2014). There was also an enquiry about their income generating activities and potential interests of the OVC caregivers hitherto limited by funds. These caregivers were also asked about the constraints or obstacles to doing business as well as their general perceptions of their economic situations. Ethical consideration was adhered to by obtaining an informed consent from each respondent.
Derived variables
Some of the variables analyzed were derived from questions asked during the survey. These variables were Paid Employment, Food security, Household economy, Psycho social support, Adequacy of Shelter.
Paid employment: This variable was derived from: "Are you paid in cash or kind for this work or are you not paid at all?" If payment was in cash only or cash and kind, it is recoded as 1 (Having a source of income); but if the response was either "in kind only or not paid at all", it was re-coded as 0 (No source of income).
Household economy was derived by generating a new variable from the question: "Was your household able to pay for food-related expenses, school-related expenses?" If response was Yes, it was re-coded as 1 interpreted as "good economy" and recoded as "poor economy" if response was No or 2.
Food security was derived from three questions: "In the past 4 weeks, was there ever no food of any kind to eat in your household? ""In the past 4 weeks, did you or any household member go to sleep at night hungry because there was not enough food?" "In the past 4 weeks, did you or any member of your household go a whole day and night without eating anything because there was not enough food?" If each of the 3 responses was "Yes" coded as"1", it gave a maximum score of 3. Everyone with a score ≥1 was coded as "food insecure" otherwise as "food secure" with a score of 0.
Psychosocial support: This variable was generated from responses to the following questions: "Is child happy and content with a generally positive mood and hopeful outlook and "Is child cooperative?" coded as 1 if "Yes" and "0" if No and "Does child enjoy participating in activities with adults and other children?" also coded as 1 if "Yes" and 0 if "No". The maximum score from these two questions was 2 and so scores <2 were re-coded as "Need psychosocial support" and 2 recoded as "Do not need psychosocial support".
Adequacy of shelter was derived from responses to the following question "Do you think child has stable shelter that is adequate, safe, dry and secure?" There are four options to this question and options 1 and 2 are recoded as "1" that is Adequate shelter while options 3 and 4 are recoded as "0" interpreted and categorized as "Inadequate shelter".
Descriptive statistics such as means, medians and standard deviations were used to summarize quantitative variables while categorical variables were summarized with proportions and percentages. The wealth index was calculated using standard methods as described in our previous publications (Fagbamigbe et al., 2015). The Student-T-test and X 2 -test were used to determine statistical significant differences between two mean values and associations between any two categorical variables respectively. The logistic regression model was used to obtain the odds of females as OVC Household Heads (HH) given a particular variable, after adjusting for some important social and demographic variables. The results were presented in appropriate tables. The statistical analysis was carried out using SPSS version 21 (IBM SPSS, 2017).
RESULTS
We examined a total of 3,706 households from the three states in which ARFH-LOPIN 1 PROJECT was implemented. The distributions of the number of households by state are Lagos State-1,299, Rivers State-912 and Akwa Ibom State-1,495. Table 1 shows the socio-demographic characteristics of the heads of these households categorized by their sex. There was a female preponderance of the households" heads as males constituted only 44%. The mean age of all the household heads was 45.1 years with a standard deviation of 14.7 years, higher among males (46.8 years, SD=14.5) than females (43.7 years, SD=14.6 years), p<0.01. The age distribution of these households" heads is also shown in panel 1 of Table 1.The average age of the household heads was different for different states, being statistically significantly higher in Akwa Ibom (48.0years, SD= 15.7) than in Lagos (43.0 years) and Rivers (43.1 years) States. Table 3 shows the distribution of OVC by demographic and access variables to basic social services in each state. Table 4 shows the odds of a household head are 14 times more likely to be male if age 25-34 years relative to being less than 25 years. However, these likelihoods decreased with increase in age to about 2 times in older age groups. The result in Table 4 also shows that relative to those who are married female HHs are more likely to be unmarried. In fact they are either never married, widowed, divorced or separated.
The male HHs are more than 3 times not likely to have access to health care than female HHs. Children under male HHs are 25% more likely to need psychosocial support than their female headed households counterparts. In comparison with Akwa Ibom State, males are about 80% less likely to be HHs heads in Lagos and Rivers States. There was indeed an almost 4 times likelihood of a HH to undergo quranic education than female HH. Male HHs are almost 2 times more likely to complete secondary school than female HHs.
DISCUSSION
The preponderance of households of orphans and vulnerable children headed by females found in these selected LGAs is not surprising. In fact it is in consonance with the Nigerian demographic data that suggest a higher survival rate among females than males (National Bureau of Statistics, 2016). Headship of households normally reverts to females as a result of either the death of the husband or divorce which is not uncommon in the Nigerian society. Besides this, traditionally, in most marital relationships, wives are generally younger than their husbands in Nigeria. Therefore this phenomenon can explain why the females heading households in this study were younger than their male counterparts.
Another finding is the similarity in the age distribution of the house hold heads in Lagos and Rivers States and this can be attributed to the high level of urban settlements in both states characterized with a high level of commercial life. However, Akwa Ibom State is more of a traditional settlement experiencing less pollution and exposure to hazards thereby providing a good explanation for the higher survival of people living in these communities. This study also observed that about 2 in every 3 female household heads were either widowed or divorced, a finding which corroborates the report that female household heads are more of the divorced and widowed population (Oginni et al., 2013;Milkalitsa, 2015). The high mortality rate among males has been identified as a factor attributed to the continual rise in females becoming household heads in developing countries of the world (Motts, 1994;Banerjee and Roy, 2015;Kousar et al., 2017). According to some reported studies, singlehood, separation/divorce and widowhood have been attributed to the shift in responsibilities to care for children which opens women and the wards to vulnerability (Chant, 2003;Opara, 2016). The fact that the husbands in most traditional Nigerian society are the primary bread winners could also be attributed to high poverty levels among widows and single mothers who were definitely not prepared for such responsibilities as heading households and whose productive resources could be under the control of male relatives due to the patriarchal systems in Nigeria. However, our finding that the females heading households are more likely to be unmarried corroborated findings from other studies (Habib, 2010). The finding in this study that female headed households were more likely to be food secured than their male counterparts seems to support the general notion that when women have active role in decision making in the household (either as heads of households or as co-decision-makers with their husbands), the nutritional status of their children improves. But it contradicts the report of a study by Ponle that femaleheaded households were mostly affected by food poverty with a higher incidence of malnutrition (Lawson, 2014;Milkalitsa, 2015;Tibesigwa and Visser, 2015;Mengesha GS 2017 ). Anecdotal reports also observed that women in Nigeria and indeed other African countries would always do things within their powers to ensure there is always food on the table for the family. In fact a recent study reported that the proportion with food poverty was higher in female headed households than male-headed households (Lawson, 2014;Anyanwu, 2010;Tibesigwa and Visser, 2015). A similar study reported females are not known to fully and properly support their families and ensure the wellbeing of their children (Jackson, 1996;Liu et al., 2017)). This same study concluded that female headed household is a proxy for women"s poverty. And the hypothesis that female headed households are always associated with poverty that ranks among the poorest of the poor in the world cannot be easily controverted (Zarhan, 2011;Chant, 1997).
This notion of poverty about women may not be out of place if one considers the basic culture of Nigerians and indeed most African countries that places the responsibility of household finances in the hands of husbands. Therefore, the head of household is generally regarded as the key economic provider of a household. It has been reported that in the African perspective a man is usually recognized as the breadwinner of the household and as such its head (Hedman et al., 1996;Liu et al., 2017;Montoya and Teixeira 2017)). And no matter the economic status of the spouse, the man is the recognized head of the household Dar , 2018). In the recent past, traditional Nigerian society considers the woman as part of the household property to be protected and provided for by the man-the husband, who is the head of the household (Eboiyehi, 2013).Therefore the concept of females heading households could be new in Nigeria. But recent studies have documented that females now head households in the absence of males in a patriarchal culture such as the case in Nigeria (Habib, 2010;Hamid, 1992;Opara, 2016;Morakinyo et al., 2015). However, National Bureau of Statistics had reported as high as 16.5% of the households in Nigeria, are headed by women -(NBS, 2009). The impact of HIV/AIDs might have reduced the number of males and this must have increased the number of female headed households.
The observed lower proportions of OVC currently enrolled in school and also attending school regularly in female headed households compared with those in male headed households is a phenomenon generally associated with womanhood. In the Nigerian culture, there is a general tendency for females to be more lenient with children who choose not to go to school than males. And in this peculiar case of OVC, the female head of households might also send the children on hawking some goods items thereby making them another source of income generation (Guarcello et al., 2004;Shahbazi et al., 2015). And as reportedly previously, this may partly explain why OVC is generally limited in the pursuant of formal education (Bammeke, 2010). Another major finding in this survey is that a higher proportion of OVC in male headed households had access to health care and needed psychosocial support than female headed households. This has been reported in a previous study that found a higher mortality among members living in female headed households than males" (Doctor, 2011;Gupta et al., 2015;Khalid and Martin 2017).
Conclusion
Households headed by females appear to be on the increase in Nigeria. The education of the girl child is strongly recommended to prepare them for responsibilities other than house wives. The condition of orphans make them vulnerable with female caregivers who themselves are symbols of poverty. The high poverty level in Nigeria demands that a special attention should be paid to the care of orphans and vulnerable children (OVC) if they are to live a meaningful life. The OVC households deserve such services as health, education, nutrition and economic strengthening. This study also found that households headed by males are more likely to withstand the shocks attributed to vulnerable households. The program should hence focus more on gender norm to improve the potential leadership roles of females in any household. | 4,786.6 | 2020-07-31T00:00:00.000 | [
"Economics"
] |
3D assisted face recognition via progressive pose estimation
Most existing pose-independent Face Recognition (FR) techniques take advantage of 3D model to guarantee the naturalness while normalizing or simulating pose variations. Two nontrivial problems to be tackled are accurate measurement of pose parameters and computational efficiency. In this paper, we introduce an effective and efficient approach to estimate human head pose, which fundamentally ameliorates the performance of 3D aided FR systems. The proposed method works in a progressive way: firstly, a random forest (RF) is constructed utilizing synthesized images derived from 3D models; secondly, the classification result obtained by applying well-trained RF on a probe image is considered as the preliminary pose estimation; finally, this initial pose is transferred to shape-based 3D morphable model (3DMM) aiming at definitive pose normalization. Using such a method, similarity scores between frontal view gallery set and pose-normalized probe set can be computed to predict the identity. Experimental results achieved on the UHDB dataset outperform the ones so far reported. Additionally, it is much less time-consuming than prevailing 3DMM based approaches.
INTRODUCTION
In the light of tremendous progress that has been made in traditional FR where pose variations are strictly prohibited or controlled, it is natural to extend the research interest to unconstrained environment. Compared with conventional 2D techniques [1,2,3], 3D methods, which could account for pose variations, show complete dominance using comprehensive facial information [4,5]. However, the expensive cost in acquisition, registration and calculation of 3D data makes it difficult to be widely used in FR systems.
As a trade-off between 2D and 3D techniques, 2D/3D asymmetric FR has recently become an attractive topic. The main motivation of this scenario is to integrate superiorities of both 2D and 3D based methods and avoid their drawbacks, such as unilateral enrollment of 3D data in gallery with 2D texture images in probe. In this way more robustness could be gained by applying 3D models on 2D image analysis, meanwhile acquisition of 3D data is not required in verification stage so as to largely reduce the computational cost.
To deal with such an issue, a few attempts have been made [6]. Blanz and Vetter [7] build a statistical model by a set of training data and densely fit it to a given facial image for matching, but it generally requires a long convergence process. Riccio and Dugelay [8] established a correspondence between the 3D gallery face and the 2D probe using geometric invariants on the face; Toderici et al. [9] also located some pre-defined key landmarks (eye corners and nose tip) on the facial images in different poses, and then roughly align them to a frontal 3D model for matching. Nevertheless, they both assumed that accurate localization in multi-view facial images was fulfilled, which turns out to be another tough topic. Zhang et al. proposed an asymmetric 3D-2D FR approach [10] which performs a 2D-2D matching by synthesizing 2D images from 3D models towards the same pose as probe samples, where a preprocessing pipeline for illumination normalization and pose correction as well as Oriented Gradient Maps (OGMs) based facial representation [11] are adopted. This approach was further compared and associated with work of Zhao et al. [12] as a benchmarking asymmetric 3D-2D FR system on the UHDB face database [13]. Unfortunately they both suffer from high computational cost owing to considerable complexity of pose synthesis and their pose estimation processes still lack satisfactory accuracy.
In this work, we are especially concerned with an efficient pose-independent face recognition approach. It deals with accurate pose reconstruction by introducing a progressive pose estimation processing while greatly improving computational efficiency. Experiments carried out on the UHDB dataset demonstrate our prominence compared with prevailing techniques. Fig. 1 shows an illustrative overview of the proposed method, in which we organize our system and the remainder as well by concatenating three main parts: random forest based pose estimation (Section 2), 3D morphable model based pose normalization (Section 3) and LBPbased matching (Section 4). Finally the experimental results and conclusions are presented in Section 5 and Section 6 respectively.
RANDOM FOREST BASED POSE ESTIMATION
As a strong classifier in machine learning, Random Forest (RF) inherits and enhances the classification capacity of a single decision tree while overcoming its inconvenience of over-fitting, therefore it is commonly used in applications towards pose estimation and feature point extraction [14,15].
In our preprocessing stage, 3D models in the gallery set are firstly rotated to specific poses and then projected onto 2D plane to obtain a multi-pose 2D face database with accurate ground truth of pose value. As shown in Fig. 2, these images are regarded as training data of RF after a rough delighting processing. Moreover, aiming at decreasing the impact of over-fitting, only a randomly selected subset of images will be adopted for each tree, and it is thus sufficient to present the proceeding of a single tree's training.
Instead of directly utilizing the grayscale value of a randomly selected region as feature value in previous work [14], which leads to heavy computational cost and potential error, we extract LBP (Local Binary Patterns) features of each image to construct an SVM (Support Vector Machine) based classifier for each split node. The detailed algorithm is presented in Algorithm 1. Algorithm 1. The outline of our RF training 1. Select a subset of images at random as training data for a new tree , each image is associated with its pose vector = , , where the three subscripts stand for Euler angles representing conditions of 3D space rotation. 2. Judge whether current node is a leaf node or a split one.
If any of these conditions is satisfied: 1) maximum depth of tree is reached, 2) remaining images are less than preselected threshold, we define this node a leaf node and jump to step 5; or we go to step 3.
3. Divide images into two classes. Histograms of LBP features for each image in current node are calculated as features to be classified by SVM. Certain binary tests in the form of (1) ωℎ − <0 (1) would be carried out by training certain SVMs. Note that ℎ is the LBP histogram of image , ω and are trained weight parameter and bias offset of each SVM obtained by randomly labeling images. The final SVM coefficients are chosen by minimizing the corresponding differential entropy: and stand for quantity weight of the left and right image subset compared with their parent node, and represent the covariance matrix of the left and right subset. These SVM coefficients are stored in this node as attributes. 4. Perform steps 2, 3 iteratively until a leaf node is found. 5. Record the leaf node by storing the mean vector of all pose vectors arrived as an annotated attribute and the trace of covariance matrix. 6. Perform steps 2 to 5 iteratively until all nodes of tree are traversed. After training a certain number of trees, a random forest is constructed which actually performs a projection from continuous pose variations onto discrete pose candidates in order to transform the estimation problem to a classification problem. Upon largely enhancing classification performance by gathering considerable SVM classifiers, RF is capable to tackle this problem.
When an unseen image enters, we simply release it to our well-trained RF and cluster all pose candidates obtained after discarding ones which are not informative, i.e. owning a too large trace.
3DMM BASED POSE NORMALIZATION
Despite of RF's powerful classification capacity, it is still greatly restricted when it comes to a situation requesting high accuracy because of the intrinsic errors caused by training data's diversity and cluster effect. Another formidable tool is subsequently introduced to perfect our system.
Widely employed in 3D recovery and synthesis, 3D morphable model has always been a significant parametric modeling technique. Assuming that human face could be represented by linearly combining a train of 'prototype' face models, 3DMM offers a 3D face generation processing: = ̅ + ∑ , = + ∑ (3) where and are generated shape and texture of a new face; ̅ and are mean shape and texture of existing face models; and are eigenvectors of all models after PCA transformations; and stand for respective weights of eigenvector of shape and texture.
To date, 3DMM based FR methods could be categorized into three classes by model's usage rules: 1. Pose fitting [7,16]: The most simple and primary method directly comparing shape and texture parameters between gallery and probe images obtained by fitting 3D models to both of them; 2. Pose synthesis [17,18]: Estimate the pose value of probe image by the aim of generating photo-realistic images with similar pose by fitting 3D models to gallery images, and pose-invariant matching is hence achieved; 3. Pose normalization [19,20]: Instead of rotating frontal gallery image to a specified pose, both gallery and probe images are normalized to frontal pose and then regular face recognition could be performed. The categorization could be intuitively illustrated and compared in Fig. 2. For pose fitting methods, despite of their simplicity and intuition, the performance depends largely on their fitting accuracy. Pose synthesis methods are easier to implement and could avoid texture missing; however they require high computational cost since all gallery images are processed for each probe image. Compared with them, pose normalization tends to be more appropriate for its merits of quickness and accuracy. Nevertheless, most existing methods still adopt the same framework which aims at searching for parameters and simultaneously or iteratively by minimizing the pixel-wise difference between the raw input image and the recovered image. Although they may finally acquire an accurate fitting result, they suffer from embarrassing computational cost and pose initialization for optimization procedure still remains a challenge.
Starting from these problems, we propose a novel 3DMM based framework by introducing a reasonable pose initialization and avoiding pixel-wise comparison in order to gain a quite considerable acceleration while preserving the performance. We utilize 100 3D models in USF face dataset [21] as 'prototype' models and assume that 18 feature points are manually labeled as prior knowledge for both USF models and all images in gallery and probe. Their positions are depicted in Fig. 3. For clarity purposes, the proceeding of proposed technique is shown in Algorithm 2.
Note that refers to scale parameter; stands for orthogonal projection; indicates 3D space rotation formed by three Euler angles , , ; and are feature points of input image. Particularly, we avail ourselves of the pose values estimated by RF in Sec. 3 for initialization so that the optimization procedure develops in a relatively correct range. Furthermore, a variance-normalized constraint weighted by a pre-defined value ω is added to avoid abnormal shape parameters. 3. Synthesize normalized face shape. Since all parameters are recovered, we can synthesize the normalized face shape of an image by simply generalizing the shape parameters to whole point clouds: = + ∑ (5) The proposed method benefits from RF based pose estimation and much less computational cost. Notwithstanding the imperfect shape recovery accuracy shown in Fig. 4, we truly realize an effective and speedy pose normalization approach which inspires a novel pose-invariant FR system.
LBP-BASED MATCHING
Once the frontal shape model of an input face image is reconstructed, texture values could be mapped to new model by respecting the correspondence between 2D and 3D. After that, we could carry out another projection of this textured 3D model from 3D space onto 2D plane in order to gain a frontal-view 2D face image, several examples are depicted in Fig. 4. Manifold matching methods could afterwards be available for classical face recognition. In this work we calculate the chi-square distance between LBP features [22] of gallery and probe images to evaluate the recognition rate.
EXPERIMENTAL RESULTS
The proposed method aims at achieving a 2D/3D asymmetric face recognition, and the dataset applied for evaluating its performance should hence satisfy two conditions: 1) 3D models are provided in the gallery set, 2) 2D images with pose variations are included in the probe set. In respect of the fact that most existing public face datasets, such as FRGC and CMU-PIE, could hardly meet these requirements all at once, a novel dataset is adopted in our work which is offered by University of Houston, known as the UHDB face dataset.
The UHDB contains 23 3D meshes and their corresponding textures of 23 subjects in the gallery set and 1692 2D textures in the probe set. 6 illumination conditions and 12 pose conditions are covered in the probe set, considering that only pose impact is handled in our work, we merely take into account all pose conditions under neutral lighting, including 23*12 = 276 images. Several examples of one subject and their recovery results are illustrated in Fig. 4. We can infer from the figure that our method is capable to successfully recover the shape information of given image and re-map the texture onto frontal face shape to obtain a pose-normalized image. Although identity inference based on shape fitting lacks accuracy and there might occur texture missing for large pose variations (as shown in last column of Fig. 4), we could still perceive that a high-quality pose normalization is achieved and FR based on pose-normalized image is feasible.
As shown in Table. 1, the proposed method is compared with two previous work on UHDB [12]. Furthermore, another comparison experiment without RF based pose estimation is carried out as well for validating the efficiency of progressive pose estimation for pose-invariant face recognition. In the meanwhile, their computation complexities are also comparatively measured and analyzed through the average processing time for each image.
It is clear to find out that our method outperforms the state-of-the-art 2D/3D FR approaches which report the performance on this dataset and is much more computationally efficient. In addition, it is worth mentioning that RF based pose estimation helps improve the performance of the proposed method and slightly shorten the processing time. Table 1. Verification result and average processing time
CONCLUSIONS
In this work, a novel 2D/3D asymmetric FR system is proposed which takes advantage of random forest based pose estimation as a preprocessing pipeline to improve the poseinvariant FR performance while limiting the use of 3D data so that a low computational cost is obtained. Compared with existing 2D/3D asymmetric methods, the proposed approach is much faster and less dependent of 3D model fitting accuracy. Furthermore, the experimental results on the UHDB prove the predominant verification power and computational efficiency of our method under unconstraint environment.
ACKNOWLEDGEMENT
This work was in part supported by the French Research Agency, Agence Nationale de Recherche (ANR), through the Biofence project, under the grant ANR-13-INSE-0004-02.
Method
Rank-1 RR Processing Time LIRIS [12] 0.802 61.2s UR2D [12] 0.852 -Proposed method without RF 0.862 12.5s Proposed method 0.888 10.8s Fig. 4. Examples in UHDB. First row is raw image; second and third rows illustrate respectively the recovered face shape with and without estimated pose; last row shows the textured image after pose normalization. In particular, first column is gallery and others are probes. | 3,497.2 | 2014-10-01T00:00:00.000 | [
"Computer Science"
] |
Turning the Tide Against Regulatory T Cells
Regulatory T (Treg) cells play crucial roles in health and disease through their immunosuppressive properties against various immune cells. In this review we will focus on the inhibitory role of Treg cells in anti-tumor immunity. We outline how Treg cells restrict T cell function based on our understanding of T cell biology, and how we can shift the equilibrium against regulatory T cells. To date, numerous strategies have been proposed to limit the suppressive effects of Treg cells, including Treg cell neutralization, destabilizing Treg cells and rendering T cells resistant to Treg cells. Here, we focus on key mechanisms which render T cells resistant to the suppressive effects of Treg cells. Lastly, we also examine current limitations and caveats of overcoming the inhibitory activity of Treg cells, and briefly discuss the potential to target Treg cell resistance in the context of anti-tumor immunity.
INTRODUCTION-REGULATORY T CELL IN CANCER Challenges in Immune-Oncology-Immunosuppressive Cells
The concept of utilizing the T cells, to recognize and eliminate cancer cells has contributed to the advancement of immunotherapy against multiple malignancies. Recent advances in checkpoint inhibitors (in particular CTLA-4 and PD-1 inhibitors) and cell-based therapy such as Chimeric Antigen Receptor (CAR)-T cell therapy demonstrate promising clinical responses in various cancer types in a subset of patients. However, despite the attempts to modulate anti-tumor T cell responses, a proportion of patients still do not respond to these immune therapies (1)(2)(3). The mechanisms of resistance against immune therapy is currently a key area of investigation. Some of these mechanisms include the presence of immunoregulatory cells in the tumor microenvironment such as tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs) and regulatory T (Treg) cells which could play an important role in restricting T cell immunity (4)(5)(6). Thus, overcoming the effects of these immunosuppressive cells remain a challenge for those seeking to enhance anti-tumor immune response.
Evidence for a Role for Regulatory T Cells in Anti-tumor Immunity
Treg cells are one of the integral components of the adaptive immune system that contribute to maintaining tolerance to self-antigens and preventing autoimmune diseases (7,8). It is postulated that these cells have an important role in regulating immune surveillance and promoting tumor progression. However, their precise role in regulating anti-tumor immunity and the mechanism of how Treg cells could suppress T cells in tumor is still unclear (9). Early studies used CD4 + CD25 + markers to identify Treg cells with the caveat that activated helper T cells would also express these markers (10). Woo et al. (11) provided evidence for the presence of regulatory T in patients with early-stage non-small cell lung cancer and late-stage ovarian cancer. Numerous other manuscripts have also noted the presence of potential CD4 + CD25 + Treg cells in multiple types of cancer including melanoma, pancreatic cancer and breast cancer (12)(13)(14).
In 2003, studies reported that the transcription factor FoxP3 was critical for Treg development (15)(16)(17), Subsequently, Curiel et al. (18) examined CD4 + CD25 + FoxP3 + cells and found that increased infiltration of Treg cells correlated with disease progression in ovarian carcinoma, and infiltration of these cells in each stage of cancer served as a good metric for survival prediction. Similarly, studies demonstrated that the presence of Treg cells in breast cancer correlated with reduced overall survival (19,20). In contrast, several reports suggested that infiltration of Treg cells can be a favorable prognostic factor (21)(22)(23)(24). Such discrepancies may result from the inability to precisely identify regulatory T cells within the heterogenous pool of FoxP3 + expressing CD4 + T cells (25). Alternatively, considering high infiltration of Treg cells also correlate with high infiltration of CD8 + T cells in a specific tumor subtypes (24), regulatory T cells may be recruited in response to an inflamed tumor microenvironment. Part of the controversy could also be due to the finding that FoxP3 can be transiently upregulated in activated human T cells, and is therefore not an exclusive marker for Treg cells (25,26). The expression level of other markers such as CD45RA (27) and Treg-specific DNA demethylation status within the FoxP3 locus can increase the accuracy of identifying functionally active Treg cells (28,29). However, it is not always possible to perform these in depth analysis. Studies have also utilized ex vivo Treg suppression assays to demonstrate the presence of regulatory T cells within tumor tissue (18,30,31).
In mice, the role of Treg cells in regulating anti-tumor immunity has been investigated through ablation of Treg cells (using FoxP3 DTR mice or antibodies targeting receptors highly expressed on Treg cells, such as CD25, GITR, and folate receptor 4) in transplantable tumor models (32-35). In these models, depletion of regulatory T cells in conjunction with modulation of T cell immunity improves anti-tumor immunity. In contrast, co-adoptive transfer of CD8 + T cells with Treg cells prevented effective adoptive cell therapy against B16-F10 melanoma (36). In summary, although the presence of Treg cells in tumors cannot be used as an accurate prognostic factor, the literature suggests that Treg cells are a potent regulator of anti-tumor immunity.
Immune Therapy and Treg Cells
One potential mechanism that may reduce the efficacy of cancer immunotherapy is suppression mediated by the Treg cell population. In addition, the therapeutic modalities such as anti-PD-1 may potentially alter Treg cell function and/or frequency, either directly or indirectly by changing the immune microenvironment (37-39). Thus, the potential effect of Treg cells on tumor-specific T cells should not be neglected even in therapeutic arena.
One of the most predominantly utilized checkpoint inhibitors in clinical and translational studies involve therapeutic blockade of PD-1 (nivolumab and pembrolizumab) or PDL-1 (atezolizumab and duravalumab) (40). There is a limited number of clinical studies thoroughly documenting changes in the quantity and quality of Treg cells in response to these PD-1/PD-L1 inhibitors. To date, studies either report an increase or no change in the frequency of Treg cells in response to nivolumab or pembrolizumab (39, 41). It is also important to note that PD-1 and PD-L1 can be expressed by Treg cells, thus direct modulation of Treg cell function should not be excluded as a possibility (31, [42][43][44]. A few reports demonstrate that PD-1 blockade attenuates Treg cell suppression in vitro, based on the effect of PD-1 inhibitor on T cell proliferation in the presence of Treg cells (39,45,46). However, the effect of these inhibitors on Treg cells have not been clearly discriminated against its effect on T cells. A few reports including a study conducted by Toor et al. (47,48) suggest that PD-1 blockade does not modulate Treg cell phenotype or function, but instead targets activated T cells. A murine study conducted by Chen et al. (49) demonstrates that PD-1 has no influence over the development and suppressive effects of thymically-derived Treg cells, however PD-1 appears to be crucial for differentiation of naïve CD4 + T cells into iTregs. Similarly, PD-L1 blockade can interfere with the induction and maintenance of iTreg cells in mice (50).
Collectively, the precise effect of PD-1 blockade on Treg cells is poorly understood. Nevertheless, PD-1 inhibition synergizes with therapeutic strategies which reduce the quantity of Treg cells in mice (35,51,52), suggesting that enhanced anti-tumor immunity in response to PD-1 blockade may still be limited by Treg cells. Extensive studies have been performed evaluating the clinical potential of interfering with immune checkpoint receptors beyond PD-1, including CTLA-4, LAG-3, and TIM-3. However, the effect of each checkpoint inhibitors on Treg cells is also poorly understood and are beyond the scope of this review.
Adoptive cell therapies using TCR transduced T cells, CAR-T cells and Tumor-infiltrating Lymphocytes (TIL) are capable of directly recognizing and targeting tumor cells (3,53). However, whether or not these T cell products are susceptible to regulation by Treg cells in humans is yet to be elucidated. In a few cases, the frequency of lymphocytes resembling Treg cells increases with adoptive T cell therapy (37,38,54). In the context of TIL therapy, Yao et al. (37) has demonstrated that the quantity of Treg cells reconstituted after non-myeloablative chemotherapy, which correlates with the number of administered doses of IL-2, is associated with patient responsiveness to TIL therapy. Supportive of this finding, administration of high-dose IL-2 (often utilized in conjunction with TIL therapy) can result in expansion of immunosuppressive ICOS + Treg cells, which may be predictive of clinical outcomes in patients with metastatic melanoma (55). Baba et al. (56) utilized a murine model of fibrosarcoma to suggest that rapid reconstitution of Treg cells post-lymphodepletion suppress anti-tumor immunity, and targeting these regulatory T cells using neutralizing antibodies significantly reduced tumor growth. In the context of CAR-T cell therapy, the effect of the treatment on Treg cells may vary. For instance, clinical infusion of EGFRvIII-directed CAR-T cells for the treatment of glioblastoma resulted in influx of CD4 + CD25 + FoxP3 + cells in the tumor (38), whereas CD19targeted CAR-T cells against B-cell lymphoma and leukemia did not increase the frequency of Treg cells (57). Lymphodepletion, known to transiently reduce the frequency of Treg cells, improves persistence of CAR-T cells as well as therapeutic outcome (58), however the direct effect of Treg cells on CAR-T cells is unknown. In summary, the role of regulatory T cells in the context of adoptive T cell therapy is currently unknown, however the literature suggests that Treg cells may limit the outcome of these therapeutic modalities.
Mechanisms of Treg Suppression
The general mechanisms of T cell suppression by Treg cells, mostly evaluated through in vitro experiments, suggest that Treg cells may exploit diverse contact-dependent and cytokinemediated mechanisms to limit T cell function (59,60). One of the proposed mechanisms involve the ability of Treg cells to downregulate CD80/86 expression on dendritic cells (61)(62)(63). (73). Through in vitro experiments, Deaglio et al. (73) suggested that CD39 and CD73 (ectonucleotidases used for hydrolysis of phosphate residues) expression by Treg cells can induce hydrolysis of extracellular ATP to adenosine, which triggers A2A receptor on T cells and elevates intra-cellular cAMP for T cell inhibition. However, most of these proposed mechanisms have not been explored in vivo.
Treg cells may also attenuate the T cell response via the production of chemokines and inhibitory cytokines. Treg cells can secrete TGF-β, IL-10, and IL-35 in a context-dependent manner, and reduce effector T cell function (74)(75)(76)(77). For example, TGF-β can be a potent regulator of CTL function in vitro and in vivo (76,78,79), and reduce anti-tumor immunity in a transplantable tumor model (76,79,80). Although the secretion of TGF-β by Treg cells appears to be an important mechanism of suppression, an in vitro study conducted by Piccirillo et al. (81) also suggests that blockade of TGF-β produced by regulatory T cells do not reduce the suppressive effects of Treg cells. The role of IL-10 on T cells is unclear due to evidence of IL-10 serving as either stimulatory or inhibitory cytokine in a context-dependent manner, however evidence suggests that IL-10 plays an important role in Treg cell-mediated suppression of T cells (82,83). For instance, Chaudhry et al. (82) suggests that IL-10 signaling acts on Treg cells to attenuate pathogenic T h 17 response, however, the molecular mechanism of T cell suppression is still unclear.
Similarly, the precise mechanism of T cell inhibition by IL-35 is also unclear, but studies suggest that IL-35 restricts T cell proliferation and induces "infectious tolerance" by inducing Treg cells from naïve CD4 + T cells (84,85). Lastly, in conjunction with previously described cytokine-driven suppressive mechanisms, it has been recently demonstrated in EAE and islet allograft models that secretion of the chemokines CCL3 and CCL4 by Treg cells plays an important role in the recruitment of effector T cells to close proximity of Treg cells where they become susceptible to suppression (86).
Lastly, in vitro Treg suppression assays suggest that Treg cells compete with other T cells for IL-2, and that the decreased availability of IL-2 reduces T cell proliferation and function (87)(88)(89). In this particular system, Treg cells constitutively express a high level of high-affinity IL-2 receptors whereas stimulated naïve T cells do not express high-affinity IL-2 receptors at an earlier time point; this may further contribute to preferential acquisition of IL-2 by Treg cells. Furthermore, IL-2 provides STAT5 signaling in Treg cells that is necessary to further enhance their immunosuppressive function (90,91). This particular mechanism of suppression can also be observed in vivo. A study conducted by Chinen et al. (91) suggest that the ability of Treg cells to capture and compete for IL-2 is critical for controlling CD8 + T cell expansion and function. The general consensus for those investigating Treg cell-mediated suppression of T cells is that each suppressive mechanism likely acts in a contextdependent manner and more than one mechanism could be employed simultaneously to inhibit T cell function (7,59). Thus, the ability of Treg cells to compete for IL-2 likely works in tandem with other suppressive mechanisms to regulate T cell immunity.
It remains unclear which of the previously described mechanisms are relevant for regulatory T cells residing in the tumor. Treg cells found in the tumor often display a distinct phenotype in comparison to those circulating the periphery, which is exemplified through their unique transcriptional signatures and the expression of markers including PD-1 (31, 43,44,92,93). In the context of head and neck squamous cell carcinoma, tumor-infiltrating CD4 + CD25 hi Foxp3 + T cells produce a higher level of TGF-β and reduced T cell proliferation more effectively than Treg cells from the periphery in Treg suppression assays (30, 94). These correlative studies suggest that intra-tumoral Treg cells display highly immunosuppressive phenotype in vitro, suggesting that they may regulate antitumor immunity. However, it is still unclear precisely "when, " "where" and "how" these distinct Treg cells exert their suppressive effect in cancer biology. Most in vivo and in vitro experiments performed to elucidate the cellular and molecular mechanism of T cell suppression by Treg cells in mice were performed using Treg cells from secondary lymphoid organs such as spleen and lymph nodes, and therefore may not fully recapitulate the interaction between intra-tumoral Treg cells and T cells. Nevertheless, evidence acquired from studies using non-tumor derived Treg cells may provide insights in understanding how intra-tumoral Treg cells could potentially limit anti-tumor T cells.
Potential Strategies to Interfere With Immune Suppression by Regulatory T Cells
Acknowledging the significance of Treg cells and their potential role in inhibiting anti-tumor immunity, multiple strategies have been proposed to deplete Treg cells in vivo. However, one major challenge associated with Treg cell depletion is the lack of a Treg cell-specific marker. Most surface molecules expressed on Treg cells are also present on activated T cells, although the level of expression may be different. Similarly, FoxP3 is expressed by both activated T cells and Treg cells in humans (25,26). Despite such challenges, several potential strategies have been proposed to reduce the suppressive effects of Treg cells (Figure 1). First, several non-specific anti-cancer drugs have been shown to reduce Treg cell activities. Low-dose cyclophosphamide (CTX), a common chemotherapeutic agent known to target rapidly dividing cells, significantly reduced Treg cells owing to their higher rate of proliferation, leading to enhanced anti-tumor immunity (95)(96)(97)(98). In these studies, investigators have noted that CTX reduced the levels of intra-tumoral Treg cells while maintaining or elevating the level of CD8 + T cells in the tumor (96,97). In contrast, several studies have reported contradicting data where CTX either increased the level of Treg cells or did not enhance anti-tumor immunity (99,100). Additional studies showed that treatment with CTX was further improved in its selectivity and efficacy through combination therapy with OX40 agonist or anti-PD-1, demonstrating increased intra-tumoral Teff/Treg cell ratio and subsequent regression of B16 and TC-1 tumors (101,102). Several other FDA-approved anti-cancer agents including tyrosine kinase inhibitors sunitinib, sorafenib, and imatinib also reduced the levels of intra-tumoral Treg cells (101,(103)(104)(105).
While specific targeting of tumor-infiltrating Treg cells can be challenging, several agents including daclizumab (CD25 blocking antibody), denileukin diftitox (Ontak, IL-2-diphtheria toxin conjugate protein), and several other antibodies have been proposed to target Treg cells and enhance anti-tumor immunity (106, 107) (Figure 1). First, the use of CD25 to target and deplete Treg cells has resulted in improved anti-tumor immunity in some cases (108,109). However, this strategy has raised a number of concerns based on inconsistent in vivo responses and lack of specificity. Similar to the effects of anti-CD25 in mice (clone PC-61), the use of denileukin diftitox for depleting Treg cells and eliciting a stronger anti-tumor immune response remains controversial, due to varying clinical responses (110,111). For instance, treatment of patients with renal cell carcinoma using denileukin diftitox effectively relieved inhibition by Treg cells to promote anti-tumor immunity, but the opposite trend was observed in patients with metastatic melanoma (110,111). Tumor heterogeneity, the existence of CD25 − Treg cells and CD25 expression on other immune cells, such as T cells, B cells, and NK cells (112,113), may explain seemingly opposite outcomes in this particular approach. However, recent studies have further modified and improved strategies targeting CD25 and suggest that it may still be a viable option to restrict Treg cell activities. Arce Vargas et al. (35) demonstrated that Fc-optimized antibodies against CD25 could effectively reduce the frequency of intra-tumoral Treg cells and improve tumor control. Furthermore, CD25targeted near-infrared photoimmunotherapy (NIR-PIT) has been developed in a murine model. By conjugating anti-CD25 with a photoactivatable silica-phthalocyanine dye sensitive to nearinfrared light, and localizing near-infrared irradiation specifically on tumors, NIR-PIT achieved reduction of intra-tumoral Treg cells (114).
Beyond CD25 as a target molecule, regulatory T cells constitutively express receptors such as GITR, CTLA-4, and folate receptor 4. In the tumor microenvironment, Treg cells further upregulate a large number of receptors including ICOS, OX40, GITR, TIGIT, PD-1, and CTLA-4 (31, 115). Antibodies targeting some of these receptors expressed by Treg cells such as GITR and folate receptor 4 reduce the amount of Treg cells and enhance anti-tumor immunity in mice (32,33,116). Similarly, checkpoint inhibitors designed to block inhibitory signals on T cells may also play an important role in regulating Treg cell activities. With Treg cells expressing a high level of CTLA-4 (27), administration of an anti-CTLA-4 antibody has resulted in a major reduction in the frequency of intratumoral CTLA-4 + FoxP3 + Treg cells which was dependent on Fcγ receptor-expressing cells in the tumor microenvironment (117)(118)(119)(120)(121). This is consistent with the correlation of decreased frequency of tumor-infiltrating Treg cells with the usage of ipilimumab in patients with bladder cancer and advanced melanoma (122)(123)(124). Lastly, a study conducted by Sugiyama et al. (125) demonstrated that a high proportion of Treg cells express CCR4 in tumor-infiltrating lymphocytes (TILs) acquired from melanoma patients. CCR4 expression was specific to CD4 + CD45RA − FoxP3 hi Treg cells, a terminally differentiated and highly suppressive subset of Treg cells that preferentially accumulates within tumors, whereas CCR4 is not expressed on CD4 + CD45RA + FoxP3 lo naïve T cells. In agreement with these findings, administration of anti-CCR4 (Mogamulizumab) in patients with Adult T-Cell Leukemia-Lymphoma (expressing NY-ESO-1) resulted in reduction in CD4 + CD45RA − FoxP3 hi Treg cells and enhanced NY-ESO-1-specific CD8 + T cell response (125). Although anti-CCR4 antibodies target a specific subset of Treg cells that are highly abundant within tumors, this particular strategy does not selectively deplete intra-tumoral Treg cells since a large proportion of Treg cells in peripheral blood are CD4 + CD45RA − CCR4 + FoxP3 + Treg cells (8,27,125).
Interestingly, studies published within the last few years suggest that promoting the conversion of Treg cells into immune-stimulatory cells could be an alternative approach to enhancing anti-tumor immunity (Figure 1). FoxP3 + regulatory T cells are comprised of heterogenous sub-populations of cells some of which display functional plasticity. Depending on the environmental cues, these Treg cells remain uncommitted and become susceptible to being re-programmed to FoxP3 − helper T cells or FoxP3 + cells which display properties of a helper T cell (126)(127)(128)(129). Similarly, there are heterogenous populations of highly suppressive Treg cells in the tumor microenvironment. Although the composition and function of these tumor-infiltrating Treg cells is still a topic of debate, evidence suggest that both thymically-derived natural Treg cells, characterized by high expression of neuropilin-1, and induced Treg cells play important role in regulating antitumor immunity (130). Peripherally-derived regulatory T cells, which display greater plasticity, can be targeted to enhance anti-tumor immunity (130,131). Furthermore, despite the initial assumption that thymically derived Treg cells undergo a strict lineage commitment, Overacre-Delgoffe et al. (132) demonstrated that targeting neuropilin-1 on Treg cells induces IFNγ production and "functional fragility" which can in turn enhance anti-tumor immunity. A recent approach of converting Treg cells into immune-stimulatory cells in the context of tumor immunity involve epigenetic modification of intratumoral Treg cells to disrupt their lineage and functional stability. For example, Wang et al. (133) have demonstrated that the histone H3K27 methyltransferase enhancer of zeste homolog 2 (EZH2) activities are increased in tumor-infiltrating Treg cells in both murine and human cancers, and molecular targeting of EZH2 promoted conversion of Treg cells into IFNγ producing cells that were capable of remodeling the tumor microenvironment and enhancing anti-tumor immunity. Several other epigenetic modifiers such as Bromodomain and Extra-Terminal (BET) family proteins and histone acetyltransferase Ep300 can also be targeted to disrupt Treg cell function and improve anti-tumor immune response (134,135). However, these epigenetic modifiers possess other biological functions, and molecular targeting of these proteins could potentially induce off-target effects.
Despite these alternative approaches to Treg cell blocking or depletion strategies, limitations still exist, including the lack of a Treg cell-specific biomarker and potential induction of autoimmunity as a consequence of systemic Treg cell depletion (136,137). Lastly, depletion of Treg cells can be followed by their rapid reconstitution, often resulting in a higher frequency in comparison to the level of Treg cells prior to depletion (138,139). Alternatively, another approach to enhance antitumor immunity would be to modify tumor-specific T cells to be resistant to the suppressive effects of Treg cells. This approach may be relevant when adoptive T cell therapies are used including TCR transduction with tumor specific TCR or CAR-T cells.
REPORTED CASES OF TREG RESISTANCE
Since the early 2000s, evidence suggests that there are a variety of molecular pathways and cellular mechanisms which render T cells resistant to the suppressive effects of Treg cells. Numerous surface receptors, intracellular signaling molecules and cytokines have been implicated in T cell resistance to Treg cells (Figure 2).
E3 Ubiquitin Ligase Cbl-b
The inhibition of E3 ubiquitin ligase Cbl-b has shown promising results based on the ability of T cells to resist the suppressive effects of Treg cells both in vitro and in vivo (140,141). Through
expressed on Treg cells can be used to reduce the frequency of regulatory T cells and enhance anti-tumor immunity. (2) Regulatory T cells can convert into T cell stimulatory cells in response to inhibition of EZH2 epigenetic modifier or NRP-1-targeting antibody. Treg cells treated with these agents upregulate IFNγ and enhance anti-tumor immunity (132, 133). (3) T cells can be rendered resistant to the suppressive effects of Treg cells. Intracellular molecules which govern T cell activation (such as Cbl-b and TRAF-6), co-stimulatory receptors (such as TLRs and GITR) and various T cell stimulatory cytokines reduce the ability of Treg cells to suppress T cells.
ubiquitination (and in many cases, subsequent ubiquitinmediated degradation) or phosphorylation of proteins involved in the TCR signaling pathway, Cbl-b serves as a negative regulator of antigen-induced T cell activation (142). Several molecular targets have been identified, including PKCθ, Nedd4, PLC-γ1, Vav1, LAT, and p85, along with several other TCR signaling molecules that play an important role in T cell activation (143)(144)(145)(146)(147). Consequently, through the regulation of these molecules, Cbl-b can control a diverse repertoire of intracellular mechanisms associated with the early phase of T cell activation, such as calcium influx, cytoskeletal rearrangement, immune synapse formation, cytokine secretion as well as proliferation (148,149). Amongst several signaling pathways downstream of TCR activation, reports highlight the role of PI3K/Akt signaling pathway in T cell resistance to Treg cellmediated suppression (150,151). Interestingly, it has become evident that that PI3K and Cbl-b are indirectly regulated by each other to control T proliferation (Figure 3). Fang et al. (143) has suggested that Cbl-b regulates the PI3K signaling pathway by binding and ubiquitinating a PI3K regulatory subunit p85. However, a study conducted by Guo et al. (146) offers an alternative explanation where Cbl-b does not directly inhibit PI3K, but instead inhibits the Nedd4-mediated ubiquitination of PTEN, a negative regulator of PI3K activity. Adding to the complexity of the interaction between PI3K/Akt pathway and Cbl-b, Akt also negatively regulates Cbl-b protein level through inactivation of GSK-3, a protein kinase which enhances Cblb activity by catalyzing the phosphorylation at Ser476 and Ser480 (152).
In addition to the ability of Cbl-b to regulate molecular pathways associated with TCR signaling, evidence suggests Cbl-b is intertwined with multiple T cell inhibitory signaling pathways. Early studies demonstrated that Cbl-b can be re-expressed in response to CTLA-4 signaling, and CTLA-4 deficient T cells display reduced Cbl-b expression (153). Recent studies suggest that T cells deficient in Cbl-b are less susceptible to PD-1 inhibitory signaling in vitro (154,155). These findings are consistent with a study suggesting that SHP-1, which plays an important role in downstream PD-1 and CTLA-4 signaling pathway, controls Cbl-b activity through direct phosphorylation (156). Furthermore, a study conducted by Mercadante and Lorenz (157) utilizes an in vitro Treg suppression assay and homeostatic in vivo Treg suppression assay to demonstrate that SHP-1 deficient T cells are less responsive to the suppressive effects of Treg cells. These studies suggest that Cbl-b is linked with key negative regulatory pathways in T cells. Lastly, Cblb is also intertwined with TGF-β receptor signaling. Gruber et al. (158) demonstrated that Cbl-b directly ubiquitinates and subsequently downregulates SMAD7, an attenuator of TGF-β receptor signaling. Consistent with this finding, CD4 + T cells FIGURE 3 | Potential mechanisms of T cell resistance to Treg cells. Regulatory T cells utilize multiple inhibitory mechanisms to limit T cell activation and proliferation, such as downregulation of CD80/86 on DCs, secretion of TGF-β, and consumption of IL-2. Reports suggest amplified PI3K signaling, through TCR, co-stimulatory and cytokine receptors, may render T cells resistant to these effects of Treg cells. In contrast, Cbl-b plays an important role in regulating diverse arms of the TCR signaling pathways and promoting T cell inhibition. Cbl-b deficient T cells are refractory to Treg cell-mediated suppression, but the mechanism of Treg cell resistance remains yet to be elucidated. deficient in Cbl-b display reduced sensitivity to TGF-β mediated inhibition (140,141,158,159). The multi-faceted role of Cblb in regulating TCR signaling pathways as well the inhibitory signaling pathway enables Cbl-b deficient T cells to acquire TCR sensitivity, CD28-independent stimulation, increased cytokine production, and context-dependent TGF-β insensitivity (141,160), all of which potentially contribute to T cell resistance to Treg cell-mediated suppression (Figure 3).
Cbl-b deficient CD4 + and CD8 + T cells resist Treg cellmediated suppression in an in vitro Treg suppression assay, where naïve Cbl-b −/− T cells stimulated with anti-CD3 and irradiated APCs are capable of overcoming the suppressive effects of splenic Treg cells (140,161). However, (1) the ability of Cblb −/− T cells to resist potentially "activated" Treg cells (such as those found in tumors) has not been explored, and (2) in vitro Treg suppression assay cannot recapitulate the complex interaction between T cells and Treg cells in vivo (60), especially since the Cbl-b −/− mice do not have the same phenotype as Treg deficient mice (17,(162)(163)(164). Despite these limitations, many of the in vitro observations have been consistent with in vivo T cells deficient in Cbl-b have also been studied in the context of enhancing tumor immune surveillance and antitumor immunity. Cbl-b deficiency augments anti-tumor T cell responses in both genetically engineered and transplanted tumor models (161,(166)(167)(168). Loeser et al. (161) and Chiang et al. (166) provide evidence showing a greater infiltration of CD8 + T cells using TC-1 and EL4/EG7 transplantable tumors in Cbl-b deficient mice. In both circumstances, CD4 + effector T cell infiltration did not increase. Interestingly, despite the increased infiltration of Treg cells in the tumors from Cbl-b deficient mice, T cells were able to either reject or attenuate tumor growth. A similar observation has been made when Cbl-b deficient mice were crossed with ataxia telangiectasia mutated (ATM) deficient mice, which attenuated the spontaneous development of lymphoid tumors and increased overall survival, demonstrating a robust anti-tumor immunity against genetically engineered tumor model (166). Although further investigation is required to understand how Cbl-b deficient T cells enhance anti-tumor immunity, one of the proposed mechanisms include insensitivity to TGF-β receptor signaling. Gruber et al. (158) suggested that Cbl-b deficiency promotes spontaneous rejection of TC-1 tumors, whereas Cblb −/− mice crossed with CD4 Cre -SMAD7 fl/fl mice abrogates anti-tumor immunity, thus highlighting the importance of Cblb deficient T cells in anti-tumor immunity and the ability of these T cells to potentially overcome TGF-β receptor signaling. Lastly, in all of the previously described studies, whether Cblb deficient T cells resist the suppressive effects of Treg cells to enhance anti-tumor immunity has not been shown in vivo.
TLR-MyD88-TRAF6 Axis
Evidence suggests that TLR signaling also play an important role in T cell resistance to Treg cells. Pasare and Medzhitov (169) suggested that TLR4 and TLR9-mediated stimulation of DCs and the subsequent increase in IL-6 production by DCs render T cells resistant to the effects of Treg cells. However, this particular study presumed that TLR signaling was restricted to DCs. TLRs can be expressed by effector T cells and Treg cells, and play an important role in their cellular activation and survival (170,171). Although our understanding of TLR signaling pathways in T cells is rather limited, TLRs expressed on T cells likely function similar to co-stimulatory receptors which trigger the downstream MyD88 signaling pathway as well as the PI3K/Akt signaling pathway (172). TLR signaling in T cells may also play an important role in rendering T cells refractory to Treg cell-mediated suppression. For example, TLR9 stimulation of murine T cells enhances the PI3K/Akt signaling pathway and MyD88-dependent IL-2 production; TLR9 signaling also renders T cells resistant to the suppressive effects of Treg cells (173,174). Downstream of TLRs, MyD88 interacts with IRAK1 and IRAK4, modulating the activities of an E3 ubiquitin ligase TRAF6 which may contribute to NFκB signaling (175). However, the role of TRAF6 in T cells is far more complex and contradictory, which is exemplified through a study suggesting that TRAF6 also serves as a negative regulator of T cell function (176). In this study, T cells deficient in TRAF6 display enhanced T cell activation, CD28-indpendent stimulation and resistance to Treg cell-mediated suppression (176). Although TLR signaling can promote T cell resistance to Treg cells, the precise molecular mechanism remains yet to be elucidated. It is worth noting that TLR stimulation of T cells increases cytokine production (173,177), thus future studies should delineate the effect of TLR-MyD88 signaling vs. subsequently induced cytokines in generating resistance to Treg cells. Lastly, it is also crucial to evaluate the effect of TLR signaling on regulatory T cells which also express TLRs (170). The role of TLR signaling on Treg cell function requires further investigation and clarification since it can both abrogate and enhance Treg cell functions (170,(177)(178)(179). A recent study suggested that TLR signaling on regulatory T cells induces PI3K/Akt/mTORC1 signaling which subsequently increases glycolysis and GLUT1 expression, which in turn interferes with FoxP3 expression and the suppressive ability of Treg cells (180). However, increased Treg cell function observed in several studies could also occur indirectly as a result of enhanced T cell stimulation and IL-2 secretion, which can subsequently promote Treg cell function.
Although TLR agonists can improve anti-tumor immune responses by enhancing T cell function and/or stimulating APC maturation, they may also act on other immune cells and cancer cells to impact anti-tumor immunity (181,182). Therefore, it would be difficult to specifically target TLRs to promote resistance to Treg cells.
TNF Family Members
TNF family members such as GITR, OX40, and 4-1BB on T cells can also be targeted to induce T cell resistance to Treg cells (183)(184)(185)(186)(187)(188). Evidence suggests that amplification of GITR signaling through the use of agonistic antibody, DTA-1, enhances T cell stimulation in the presence of Treg cells both in vitro and in vivo (184,189,190). However, GITR is also highly expressed on Treg cells and studies suggests that a GITR agonist attenuates Treg cell stability (191,192). In contrast, in vivo administration of nondepleting Fc-GITR-L induces context-dependent modulation of Treg cell activities (193). Further work is required to precisely understand the effect of GITR signaling on Treg cells. Although the role of GITR agonist in the interaction between T cell and Treg cell is unclear in vivo, Stephens et al. (184) suggested that GITR signaling directly acts on T cells to resist the suppressive effects of Treg cells in vitro. Lastly, a GITR agonist antibody (DTA-1) has demonstrated its potential in enhancing CD8 + T cell response and reducing intra-tumoral Treg cell activities using transplantable tumor models including the B16 melanoma model (190,192,194). In summary, administration of TNF-family receptor agonists such as those targeting GITR promote T cell response in the presence of Treg cells and contribute to enhanced anti-tumor immunity. However, the mechanism behind how TNF family receptor signaling renders T cells refractory to Treg cell-mediated suppression is poorly understood.
Cytokine Networks
Most intracellular molecules and surface receptor targets which render T cells resistant to inhibition by Treg cells often promote the secretion of a high quantity of T cell stimulatory cytokines. This is demonstrated by the early study conducted by Pasare and Medzhitov (169), which showed that LPS stimulation of DCs leads to increased IL-6 which plays an important role in T cell resistance to regulatory T cells (169,195). Similarly, inhibition of Cbl-b or activation of GITR signaling increases IL-2 production by T cells both in vitro and in vivo (167,168,183). Increased cytokine production is often perceived as an indicator of Treg resistance. However, evidence suggests that various cytokines themselves can directly drive T cell resistance to Treg cells (195)(196)(197)(198)(199). This raises a question-to what extent do cytokines play a role in Treg resistance? Both T cells and Treg cells are susceptible to cytokine receptor-mediated signaling, and therefore the effect of cytokines in both cell compartment must be considered.
Soluble mediators such as cytokines can modulate a powerful receptor-mediated T cell signaling required for cellular proliferation, survival, and resistance to Treg cell-mediated suppression. Cytokines including interferons (IFNγ and IFNα), those binding to receptors that include the common γ-chain (IL-2, IL-4, IL-7, IL-15, IL-21, and TSLP), gp130 receptor cytokines (IL-6) and IL-1 receptor cytokines (IL-1β and IL-18) employ diverse combinations of intracellular signaling pathways such as the JAK/STAT signaling pathways to promote T cell differentiation and effector functions (200)(201)(202). Many studies have also highlighted the role of T cell stimulatory cytokines, in particular IL-1β, IL-2, IL-4, IL-6, IL-7, IL-15, and IL-21, as central drivers of T cell stimulation in the presence of Treg cells (87,(195)(196)(197)(198)(203)(204)(205). Some of these T cell stimulatory cytokines may induce T cell proliferation and survival in the presence of Treg cells by common mechanisms, because their receptors share overlapping downstream signaling pathways, but the mechanism by which each of these cytokines support T cell proliferation in the co-cultures has not been fully clarified.
One of the first cytokines reported to enhance T cell proliferation in the presence of Treg cells in vitro is IL-2 (199). Upon high-affinity quaternary IL-2-IL2R complex formation, tyrosine kinases JAK1, and JAK3 also initiate a STAT1, STAT3, and STAT5-dependent response, along with the induction of the PI3K signaling pathway (201,202). Although IL-2 serves as a potent inducer of T cell proliferation in Treg suppression assays, there is no strong evidence suggesting that the signaling pathways downstream of IL-2 directly attenuates the inhibitory signals induced by Treg cells. Instead, excess IL-2 could enable T cells to overcome Treg cell-mediated cytokine deprivation (87,199), which, despite being somewhat controversial, may be an important suppressive mechanism utilized by Treg cells (89,91). Lastly, many T cell stimulatory cytokines including IL-2, IL-7, and IL-15 play an important role in enhancing anti-tumor immunity (206)(207)(208), but whether or not these cytokines render T cells resistant to the suppressive effects of Treg cells in the context of anti-tumor immunity is unclear.
When evaluating the role of cytokines in rendering T cells resistant to Treg cells, the effect of cytokine signaling must also be evaluated on Treg cells. Under a circumstance where T cell stimulatory cytokine destabilizes Treg cell function, it becomes challenging to determine whether T cell resistance to Treg cells play an important role in the observed T cell proliferation in the presence of Treg cells. Although poorly understood, Treg cells display phenotypic and functional plasticity in response to certain cytokines; T cell stimulatory cytokines may mediate the downregulation of FoxP3 or conversion of Treg cells into conventional T cells (209,210). This is exemplified through a study which demonstrates the ability of IL-4 to convert FoxP3 + cells into effector CD4 + T cells, thereby undermining oral tolerance (211). PI3K signaling pathway is regulated by PTEN expression in Treg cells to prevent loss of Treg cell stability (212,213), however, IL-4 may disrupt this process by enhancing PI3K signaling. Several other cytokines including IL-21 also antagonize Treg cell proliferation and reduce the frequency of Treg cells (214). However, a study conducted by Attridge et al. (215) suggest that IL-21 may act on T cells to limit IL-2 production which subsequently impairs Treg cell homeostasis. Furthermore, a recent study conducted by Overacre-Delgoffe et al. (132) suggests that attenuating Nrp-1 signaling on intra-tumoral Treg cells induces increased secretion of IFNγ by the Treg cells, and IFNγ subsequently acts on nearby regulatory T cells to "destabilize" their suppressive phenotype. In contrast to the previously discussed examples which destabilize FoxP3 expression in Treg cells, a few cytokines binding to receptors that include the common γ-chain can enhance Treg cell proliferation and function. For instance, adding IL-2 enhances T cell proliferation, despite also stimulating Treg cells (87,199).
Another possibility to be considered in cytokine-induced T cell resistance to Treg cells in vitro is proliferation and expansion of T cell quantity as the mechanism of Treg cell resistance, which should be distinguished from the ability to negate immunosuppressive signals. Especially in a murine in vitro system where Treg cell proliferation is limited, the capacity of T cells to proliferate may be independent of their ability to negate immunosuppressive signals by Treg cells. In other words, these T cells stimulated with cytokines may be equally susceptible to Treg cell-mediated suppression, but by increasing proliferation and quantity of T cells, the suppressive effect of Treg cells may become less apparent.
Observations From Current Clinical Studies
One of the primary objectives of cancer immune therapy is to modulate anti-tumor T cell properties to reduce the tumor burden. However, the presence of immunoregulatory cells such as Treg cells are likely to interfere with the anti-tumor T cell response (9,60,216). Thus, overcoming the suppressive effects of Treg cells to potentially enhance anti-tumor T cell response in patients is a strategy currently under investigation. Many of the current clinical studies involve targeting surface receptors on Treg cells such as CD25, CTLA-4, and CCR4 (110,124,217).
However, clinical studies have not focused on rendering T cells resistant to the suppressive effects of Treg cells. Interestingly, some of the existing treatment methods may already foster T cells resistant to Treg cells. For instance, high dose IL-2 is part of the protocol for adoptive TIL therapy against metastatic melanoma, despite actively expanding immunosuppressive ICOS + Treg cells (55,(218)(219)(220)(221), supporting the possibility that high-dose IL-2 is successful because it may render TIL resistant to Treg cell suppression. Therefore, the dosage of systemic IL-2 administration in these studies may play an important role in promoting the T cell response against the tumor, since low dose IL-2 has been used to preferentially expand Treg cells to attenuate the progression of human autoimmune diseases (222,223). To avoid IL-2mediated expansion of immunosuppressive Treg cells, a preclinical study conducted by Charych et al. (224) suggested that NKTR-214, a biologic drug containing an IL-2 core conjugated to 6 releasable polyethylene glycol chains, can be utilized to preferentially induce IL-2 signaling on T cells while reducing the expansion of Treg cells. In this study, the ability of NKTR-214 to preferentially bind to IL-2Rβ over IL-2Rα induces a greater CD8 + T cell to Treg cell ratio, greater exposure to IL-2 in the tumor and a more robust anti-tumor immunity in comparison to aldesleukin. This particular approach is currently in clinical trials. Several other therapeutic strategies involving modified IL-2 biologics also suggest similarly promising results in their ability to preferentially enhance T cells over Treg cells (225,226).
CONCLUDING REMARKS
Regulatory T cells can be potent regulators of anti-tumor immunity, and numerous strategies have been proposed to reverse the suppressive effects of Treg cells. One promising approach involves rendering T cells resistant to the suppressive effects of Treg cells. Resistance to Treg cells can be achieved through modulation of intracellular molecules, co-stimulatory surface receptors or cytokines, all of which may act through partially redundant or overlapping mechanisms. Concepts discussed in this review primarily focus on strategies to manipulate the balance between T cells and Treg cells. However, future studies should validate these concepts in the context of anti-tumor immunity and focus on recapitulating many of these observations using primary human T cells.
AUTHOR CONTRIBUTIONS
All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication. | 9,676.8 | 2019-04-16T00:00:00.000 | [
"Biology"
] |
Quantitative evaluation of 3D dosimetry for stereotactic volumetric‐modulated arc delivery using COMPASS
The purpose of this study was to evaluate quantitatively the patient‐specific 3D dosimetry tool COMPASS with 2D array MatriXX detector for stereotactic volumetric‐modulated arc delivery. Twenty‐five patients CT images and RT structures from different sites (brain, head & neck, thorax, abdomen, and spine) were taken from CyberKnife Multiplan planning system for this study. All these patients underwent radical stereotactic treatment in CyberKnife. For each patient, linac based volumetric‐modulated arc therapy (VMAT) stereotactic plans were generated in Monaco TPS v3.1 using Elekta Beam Modulator MLC. Dose prescription was in the range of 5–20 Gy per fraction. Target prescription and critical organ constraints were tried to match the delivered treatment plans. Each plan quality was analyzed using conformity index (CI), conformity number (CN), gradient Index (GI), target coverage (TC), and dose to 95% of volume (D95). Monaco Monte Carlo (MC)‐calculated treatment plan delivery accuracy was quantitatively evaluated with COMPASS‐calculated (CCA) dose and COMPASS indirectly measured (CME) dose based on dose‐volume histogram metrics. In order to ascertain the potential of COMPASS 3D dosimetry for stereotactic plan delivery, 2D fluence verification was performed with MatriXX using MultiCube phantom. Routine quality assurance of absolute point dose verification was performed to check the overall delivery accuracy. Quantitative analyses of dose delivery verification were compared with pass and fail criteria of 3 mm and 3% distance to agreement and dose differences. Gamma passing rate was compared with 2D fluence verification from MatriXX with MultiCube. Comparison of COMPASS reconstructed dose from measured fluence and COMPASS computed dose has shown a very good agreement with TPS calculated dose. Each plan was evaluated based on dose volume parameters for target volumes such as dose at 95% of volume (D95) and average dose. For critical organs dose at 20% of volume (D20), dose at 50% of volume (D50), and maximum point doses were evaluated. Comparison was carried out using gamma analysis with passing criteria of 3 mm and 3%. Mean deviation of 1.9%±1% was observed for dose at 95% of volume (D95) of target volumes, whereas much less difference was noticed for critical organs. However, significant dose difference was noticed in two cases due to the smaller tumor size. Evaluation of this study revealed that the COMPASS 3D dosimetry is efficient and easy to use for patient‐specific QA of VMAT stereotactic delivery. 3D dosimetric QA with COMPASS provides additional degrees of freedom to check the high‐dose modulated stereotactic delivery with very high precision on patient CT images. PACS numbers: 87.55.Qr, 87.56.Fc
Notice
This User's Guide is an integral part of OmniPro I'mRT System and should always be kept at hand. Observance of the manual instructions is required for proper performance and correct operation of OmniPro I'mRT System.
OmniPro I'mRT System and its accessories must not be used for any other purpose than described in the accompanying documentation (intended use). Violation will result in loss of warranty.
IBA Dosimetry does not accept liability for injury to personnel or damage to equipment that may result from misuse of this equipment, failure to observe the hazard notices contained in this manual, or failure to observe local health and safety regulations.
IBA Dosimetry shall under no c i r c u ms t a n c e s b e l i a b l e fo r i n c i d e n t a l o r coincidental damage arising from use of the equipment described in this document.
No part of the accompanying documentation may be translated or reproduced without written permission of IBA Dosimetry, unless reproduction is carried out for the sole purpose to be used by several people in the same department.
The user must treat the accompanying documentation like any other copyrighted material. Especially, if part of the accompanying documentation is provided in electronic form, these files shall not be modified in any way. IBA Dosimetry and its suppliers retain title and all ownership rights to the accompanying documentation (either in electronic or printed form).
Table of ContentsIntroduction
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | iii | I'MRT MatriXX consists of a 1020 vented ion chambers array detector, arranged in 32 × 32 grid. When irradiated, the air in the chambers is ionized. The released charge is separated by means of an electrical field between the bottom and the top electrodes. The current, which is proportional to the dose rate, is measured and digitalized by a non-multiplexed 1020 channels current sensitive analog to digital converter.
The measured data are transmitted t o a P C v i a a s t a n d a r d E t h e r n e t interface, available on most PCs.
MatriXX Evolution
MatriXX Evolution is an optimized 2D digital verification system for rotational therapy techniques. It operates with the OmniPro I'mRT software for complete plan verification and QA of ImRT, IGRT, and rotational treatments.
I'mRT Phantom
The I'mRT Phantom resembles the human body in shape and radiation properties. The cube, which can be used separately, resembles the human head.
After CT scanning of the phantom, a treatment plan is calculated, and the dose distribution data is imported into OmniPro I'mRT software. The I'mRT Phantom is then treated according to this plan, and the dose distribution or the absolute dose in singular points is measured, using films and ionization chambers respectively. The OmniPro I'mRT s o f t w a r e w i l l c o m p a r e t h e measurement values with the calculated dose distributions.
Safety information, technical information, and instruction for use for I'mRT Phantom are found in I'mRT Phantom User's Guide. OmniPro I'mRT System User's Guide contains health and safety information, installation, setup, and measurement instructions, and descriptions of the OmniPro I'mRT software functions for visualization, analysis, handling, and storing of measurement data.
I'mRT MatriXX and MatriXX Evolution
OmniPro I'mRT System User's Guide contains product information, health and safety information, instructions for installation, and instructions for setup and preparation of measurements for MatriXX.
Other Devices Supported by OmniPro I'mRT
OmniPro I'mRT S y s t e m U s e r ' s G u i d e c o n t a i n s i n s t a l l a t i o n , s e t u p , a n d measurement instructions, related to OmniPro I'mRT software. For general information, refer to the product specific manuals (see References).
DATA EVALUATION RESPONSIBILITY
The person managing the OmniPro I'mRT s y s t e m b e a r s t h e f u l l responsibility for critically evaluating every measurement result and/or manipulated measurements, before using data for verifying or modifying treatment plans, or using data for adjusting, checking, or servicing a radiation device.
GENERAL RESPONSIBILITY
OmniPro I'mRT i s i n t e n d e d t o b e u s e d b y t h e p h y s i c i s t o r e n g i n e e r responsible for the quality control of radiation therapy equipment and of treatment delivery.
The user of OmniPro I'mRT must have experience in radiation physics and radiotherapy, and must be familiar with the terminology used in the area of dosimetry.
WARNING FILM MEASUREMENT: SENSITIVITY MAY VARY FROM FILM TO FILM
The sensitivity of radiographic films is strongly dependent on parameters like type, age, batch, or storage conditions. Perform a film calibration when using films where one or more of the above parameters differ from the film used for the current film calibration.
WARNING FILM MEASUREMENT: OD VALUES OUTSIDE FILM SCANNER CALIBRATION RANGE
If a film is calibrated or measured outside the film scanner calibration range, the measurement values may not be correct. Never calibrate or measure a film outside the OD range for which the film scanner has been calibrated.
WARNING FILM MEASUREMENT: DOSE OUTSIDE THE FILM CALIBRATION RANGE
If a film is measured outside the film calibration range, the measurement values may not be correct. Never measure a film outside the dose range for which the film has been calibrated.
WARNING FILM MEASUREMENT: FILM BECOMES SATURATED
Depending on the choice of film, the saturation dose of the film may be lower than the maximum dose to be verified. Scale down the treatment plan or select an appropriate film.
WARNING FILM MEASUREMENT: MARKERS ON FILM
Markers for identification, orientation, or positioning may overlap or interfere with optical density, due to radiation. Mark your films outside the region where you want to determine the dose.
WARNING FILM MEASUREMENT: FILM AND FILM-ENVELOPE PRODUCE AN OFFSET
When inserting films in a body phantom, other film planes or slices are shifted, due to the thickness of the films and their envelopes.
When defining the offset information in the film setup, take into account the additional offset produced by the other films.
WARNING I'MRT QA/BIS MEASUREMENT: I'MRT QA/BIS CORRECTION IMAGE
The specification of the correction image file and the CCD area are mandatory. If you specify an incorrect or non-existing file and/or path, the measured image will not be corrected. If you specify an incorrect CCD area, the measured image will be incorrect. It will be very noisy and shifted, and may not appear fully on the screen.
WARNING I'MRT MATRIXX MEASUREMENT: I'MRT MATRIXX UNIFORMITY CORRECTION MATRIX
The application of the Uniformity Correction Matrix is mandatory. If the Uniformity Correction Matrix is not activated, the measured image will not be corrected.
WARNING SYMMETRY/FLATNESS: PARAMETERS MEASURED UNDER NON-REFERENCE CONDITIONS
Dosimetry protocols define the reference conditions for the determination of symmetry or flatness. Definition of water as medium, a certain depth, and a certain field is required, and also the type of detector to be used may be specified.
If measuring under different conditions (e.g. when using I'mRT QA/BIS in air), these parameters may differ from those measured under reference conditions.
WARNING ASCII EXPORT: LIMITED NUMBER OF DATA ROWS AND/OR COLUMNS
Some Windows applications support fewer rows and/or columns than the number of columns exported by OmniPro I'mRT (e .g . M icro s o ft EX C EL supports 256 × 65536).
If importing OmniPro I'mRT ASCII data to those applications, rows and/or columns exceeding the limit will not be imported.
If necessary, reduce the number of data by selecting a small region of interest.
WARNING TWAIN SCANNERS: 8-BIT GREYSCALE NOT SUFFICIENT
Using an 8 bit grey-scale scanner will give insufficient dose resolution, which will result in incorrect interpretation of data.
16 bit grey-scale is required.
WARNING DOSE EXPOSURE CHECKING: DOUBLE EXPOSURE
Double exposure will result in incorrect plan verification. When checking dose exposure for parts of a field or treatment, use a new film for each irradiation.
WARNING I'MRT MATRIXX: CALCULATION GRID
For correct comparison of treatment planning system (TPS) data and MatriXX data, the TPS grid resolution must be adapted to the MatriXX grid resolution. ■ have knowledge about safety procedures to be observed when working with radiation sources such as Cobalt-60 machines or linear accelerators.
■ are aware of safety precautions required to avoid possible injury when using electrical/electronic equipment.
Before using I'mRT MatriXX or MatriXX Evolution for measurements, the operator must verify the general functionality, safety, and duly condition of the device and the dosimetry system. The device must not be used if any blemish is noticed, and the manufacturer should be notified.
ACCESSORIES AND SPARE PARTS
No other accessories and spare parts than those provided or approved by the manufacturer must be used, otherwise operator safety, specified measuring accuracy, and interference free operation cannot be guaranteed. Violation of this prescription will result in loss of warranty. IBA Dosimetry cannot be held liable for any damages resulting from the use of accessories or consumables that are not provided or approved by the manufacturer.
Environmental Requirements
MatriXX are sensitive measuring systems and must be stored and used in a clean, dry, preferably air-conditioned area, at room temperature. Protect them from mechanical and thermal stress, and unnecessary moisture. Avoid exposure to solvents and aggressive vapors.
IMPORTANT NOTICE THE DEVICE MUST NOT BE USED UNLESS IT IS COMPLETELY DRY
If moisture has developed as a result of temperature changes, I'mRT MatriXX or MatriXX Evolution must not be used unless it has been completely dried.
Storage
When the system is not in use, unplug the power supply from the mains connector.
Store MatriXX in a radiation protected area. Do not place the system near equipment generating a strong magnetic field.
WARNING DO NOT STORE THE MATRIXX ADJACENT TO OR STACKED WITH OTHER EQUIPMENT
MatriXX should not be stored adjacent to, or stacked with other equipment. If adjacent or stacked storing is necessary, the device should be observed to verify normal operation in the configuration in which it will be used.
CAUTION DO NOT STORE THE DEVICE IN THE ACCELERATOR ROOM
Due to the sensitivity of the electronics against radiation, never store MatriXX in the accelerator room. This would considerably shorten their lifetime. Move the device into the accelerator room only if you intend to make measurements.
Handling
Handle MatriXX with careavoid impact, excessive weight on the surface, and strong vibrations. Maximum load of build-up is 25 g/cm 2 .
Never irradiate other parts than the marked sensor area.
Do not handle the devices with wet hands.
If a handling incident occurs, always perform a check before using the device again. If the device has been covered with water, un-power the device, and wait approx. 1 minute before touching it.
Electrical Installations
The electrical installations in the rooms where I'mRT MatriXX or MatriXX Evolution with c o n n e c t e d e q u i p m e n t i s u s e d m ust comply with IEC recommendations. Always use a power cord with a grounding pin.
Rating Label
The power entry module of the device contains the rating label below:
HAZARDOUS VOLTAGE
Pay attention to the voltage ratings on the rating label. This determines the safety hazards for the power supply. Do not open covers.
WARNING EMC PRECAUTIONS
MatriXX need special precautions regarding EMC and must be installed and put into service according to the EMC information provided in this manual.
RF COMMUNICATION EQUIPMENT
Portable and mobile RF communication equipment can affect the performance of MatriXX.
Guidance and Manufacturers Declaration -Electromagnetic Emissions
MatriXX are intended for use in the electromagnetic environment specified below.
The customer or the user of I'mRT MatriXX or MatriXX Evolution should assure that it is used in such an environment.
Not applicable
MatriXX use RF energy only for their internal function. Therefore, its RF emissions are very low, and are not likely to cause any interference in nearby electronic equipment.
MatriXX are suitable for use in all establishments other than domestic and those directly connected to the public low-voltage supply network that supply buildings used for domestic purposes.
Guidance and manufacturer's declarationelectromagnetic immunity
The I'mRT MatriXX is intended for use in the electromagnetic environment specified below.
The customer or the user of the I'mRT MatriXX should assure that it is used in such an environment. 800 MHz to 2,5 GHz:
Immunity
where P is the maximum output power rating of the transmitter in watts (W) according to the transmitter manufacturer and d is the recommended separation distance in meters (m). Field strengths from fixed RF transmitters, as determined by an electromagnetic site survey a, should be less than the compliance level in each frequency range b.
Interference may occur in the vicinity of equipment marked with the following symbol: NOTE 1 At 80 MHz and 800 MHz, the higher frequency range applies. NOTE 2 These guidelines may not apply in all situations. Electromagnetic propagation is affected by absorption and reflection from structures, objects and people.
Field strengths from fixed transmitters, such as base stations for radio (cellular or cordless) telephones and land mobile radios, amateur radio, AM and FM radio broadcast and TV broadcast cannot be predicted theoretically with accuracy. To assess the electromagnetic environment due to fixed RF transmitters, an electromagnetic site survey should be considered. If the measured field strength in the location in which MatriXX are used exceeds the applicable RF compliance level above, MatriXX should be observed to verify normal operation. If abnormal performance is observed, additional measures may be necessary, such as reorienting or relocating the MatriXX devices. In the frequency range 150 kHz to 80 MHz, field strengths should be less than 3 V/m. For calculating the dose for verification plans in the TPS a CT scan of the MatriXX is necessary. The verification plan will be calculated on the MatriXX CTs. The T P S p l a n e w h e r e t h e e f fe c t i ve p o i n t o f measurement of the chamber row is located will be exported. A calculated TPS dose plane and a 2D measurement at the same position are available for verification in the OmniPro I'mRT software.
During the CT scan the position of MatriXX at the linear accelerator should be exactly like during the subsequent measurement of the verification plans. In order to be able to measure the scattering, MatriXX is positioned either in the MULTICube or on a 5 cm thick layer of water equivalent material (RW3plates). Also, as build-up material a 5 cm thick layer of RW3-plates is positioned on the MatriXX measurement area. In this way the scattering resembles that of the human body.
If the gantry holder is used the same build-up and backscatter should be mounted for the verification measurement as used in the CT.
To use the CT data in the TPS system, the origin has to be precisely defined. MatriXX is positioned in such a way in the CT scanner that the central point of the measurement level is positioned exactly at the CT central axis. Thus point zero of the measurement system always coincides with point zero of the CT data set (DICOM origin). In the plan system the isocentre can be positioned precisely in the DICOM origin.
DIFFERENT CT SCANS FOR DIFFERENT MATRIXX'S
For every MatriXX a CT is necessary. Otherwise deviations in dose calculation and measurements are possible. Ensure that the correct CT scan is used. The calibration of the MatriXX should be c a r r i e d o u t d i r e c t l y a f t e r t h e calibration of the linac. MatriXX has built-in pressure and temperature sensors. Therefore the input of pressure and temperature is not necessary during the calibration, nor during the subsequent measurements.
The measurement setup follows directly from the verification measurements and therefore directly from the setup during the CT scan.
The precise thickness of the water-equivalent layer over the MatriXX measurement level is known and therefore also the exact number of monitor units required for a certain dose (for more details please see chapter 7.4.4.1 Creating a kUser Factor).
Realization of the Measurement
The MatriXX setup is exactly like the setup used for the CT scan.
For the exact orientation of the measurement system, the gantry and collimator angles of the linear accelerator must be set at precisely 0°. The vertical orientation of MatriXX is carried out with assistance from the laser and the sideways positioned markers on MatriXX that indicate the exact position of the measurement level (for more details please see chapter 7 Setup of MatriXX).
After connecting the MatriXX with the computer, setting the measuring parameters in the software and measuring the background the first measurement can be started. Either all fields of the treatment plan can be irradiated in a queue as one measurement or one field after each other in single measurements to verify each single field. The raw data should be collected beforehand as copy in a separate order.
Analysis
The most common method to analyze the pre-treatment verification is using the Gamma Index Method.
Installation of SCSI Adapter and Scanner Drivers
The plug-and-play function recognizes the SCSI adapter, and starts the Add New Hardware wizard.
Select Search for the best driver for your device.
Find the Adaptec SCSI adapter in the list of installed hardware.
Restart the computer.
Select Settings/ControlPanel/System/Hardware/Device manager -SCSI adapters from the Windows Start menu. Check that the Adaptec adapter is present. If there is a yellow exclamation mark on the icon, there is a problem with the drivers. Select Properties and change driver.
Insert the Vidar Drivers and Toolkit Installation CD, and install the STI drivers and the Vidar Toolkit. (The CD is supplied with the scanner.) The STI driver and Vidar Toolkit for Windows® 2000 and XP are also available at the Vidar Systems' website: www.filmdigitizer.com/html/drivers.html.
The plug-and-play function recognizes the VXR scanner, and tries to install a driver for that device. It is found on the Vidar installation CD.
Step through the pages in the Found New Hardware w i z a r d , s e l e c t i n g t h e d e f a u l t alternatives. Finally, select Finish.
USB
The computer must have a USB 2.0 port. A USB 2.0 peripheral connected to a 1.1 port will not recognize the Vidar scanner.
A USB 2.0 adapter can be installed. The Adaptec™Model USB2Connect, part number AUA-2000 is recommended.
The scanner must be connected to the computer with a USB 2.0 cable. .NET Framework 2.0 must be installed (Internet Explorer 5.01 or higher is required for installation).
The validation of the software is done with the US versions of the operating systems. Troubleshooting or support in case of problems related to local language operating systems is therefore very limited.
SOFTWARE CONTROLLING MATRIXX
The software controlling the MatriXX is included as a part of Windows application softwares developed by IBA Dosimetry, and can be directly accessed from the application's main window. The latest type of computer is always recommended, especially if you are going to use large data sets or work with film scanners.
OmniPro I'mRT Installation Utility
The OmniPro I'mRT CD-ROM contains a setup utility that will install the necessary files and create a program group and icons.
START BY INSTALLING THE SCANNER
If you have a film scanner, the scanner must be installed prior to the installation of I'mRT software, otherwise the vscsi32.dll file might be overwritten.
LOG IN AS ADMINISTRATOR
When installing, log in as Administrator. Otherwise the installation will fail.
Follow these steps to install the software: Insert the CD-ROM in the CD-drive.
INSTALLED FILES
During the installation of this software some important files are placed in the same directory as the application. Since the application needs these files to be able to run properly, please do not move the OmniPro I'mRT application from the original directory.
Select Install OmniPro I'mRT. The Installation wizard starts. Follow the instructions on the screen.
WINDOWS VISTA
A message "An unidentified program wants access to your computer" might appear. The program is setup.exe. Select Allow to continue.
Follow the instructions on the screen:
Installation
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 39 | During installation of the software, an empty data base is created in a user definable folder, and a connection to this data source is established.
The database can be installed either locally on a computer, or in a network.
READ AND WRITE ACCESS
All users must have full read and write access to the OmniPro I'mRT folder where the equipment database is located, to be able to run OmniPro I'mRT.
If OmniPro I'mRT s h a l l b e i n s t a l l e d o n mo r e t h a n o n e c o mp u t e r , i t i s recommended to make the database available for all installations: Choose a directory that is shared via network.
Map this directory on each computer to a drive letter.
DRIVE LETTER
The drive letter must be the same for all users on an individual computer.
DESTINATION DIRECTORY
If an installation in a network is planned, the destination directory must be mapped to a driver letter. This driver letter must be the same for all users.
Select the shared drive letter as database folder. Follow the instructions on the screen.
Repeat the installation and select the shared driver letter on all computers.
SHARED DATABASE LOCATION
When installing OmniPro I'mRT o n s e ve ra l co mp u t e rs , s e le ct th e s a me shared database location as for the first installation. The installation program will detect that the database already exists, and will connect to it (instead of copying an empty database to the folder).
NO ACCESS TO THE NETWORK
Sometimes the administrator on the computer does not have access to the network. If that is the case, consult the chapter Troubleshooting.
SOFTWARE VERSION EARLIER THAN 1.4
If an earlier version than version 1.4 is used (e.g. if not all users in a network have yet been upgraded), the equipment database created in version 1.7 will not be accessible.
Test of the Installation
A test is available to ensure that the OmniPro I'mRT software has been installed correctly. Use the example file, delivered with the software, to check the installation:
WINDOWS VISTA
To be able to run OmniPro I'mRT correctly, and to create the computer ID, the program must be started with Run as Administrator the first time, even if you are logged in as administrator.
Right click the OmniPro I'mRT icon, and select Run as Administrator.
Select Accept when the message "An unidentified program wants access to your computer" appears.
Double-click the OmniPro I'mRT icon on the desktop, or go to the Windows Start menu. Select Program-IBA Dosimetry-OmniPro-IMRT. The program will start.
Select the menu command File:Open Workspace. A standard Open dialog opens.
Browse for an *.opw file. (It should be stored in the DATA folder). Open the sample file.
The Workspace opens. Depending on the type of data loaded, it will be displayed in either Plan Verification 2D or 3D mode.
Registration of the Software
After installation the software works for a limited time (30 days). Thereafter it will run only if it has been registered.
LOG IN AS ADMINISTRATOR
You must be logged in as Administrator when entering the license number and the license key.
When you start the program after installation, the About OmniPro I'mRT dialog will open.
Register the software at IBA Dosimetry in the following way: 8. Note the License Number and the Computer ID for each installation.
9. Contact IBA Dosimetry for registration via the Radiotherapy/Support section of the homepage www.iba-dosimetry.com.
Registration may also be made by e-mail or fax.
The following information must be included: ■ Name and address (do not forget email address). ■ Product serial number ■ Computer ID For more information check the Registration Form sent to you together with the installation CD.
After a few days a license key will be sent to you.
Open the About box (found under Help), and enter the License Key. From the list of installed programs, select OmniPro I'mRT a n d c l i c k Add/Remove. The Installation wizard starts. Follow the given instructions.
Alternative procedure:
Insert the OmniPro I'mRT CD-ROM.
Select Install OmniPro I'mRT.
The installation program presents three alternatives. Select Remove.
All OmniPro I'mRT files, except for the calibration files, setup and equipment information, and measured data, will be removed.
Reinstallation of OmniPro I'mRT
IMPORTANT NOTICE
LOG IN AS ADMINISTRATOR
You must be logged in as Administrator to reinstall the program.
It may be necessary to perform a reinstallation of the software, e.g. when installing a new option.
Insert the OmniPro I'mRT CD-ROM.
Select Install OmniPro I'mRT. The installation program will present three alternatives. Select Modify. The installation starts.
During the installation, enter the new license number from the License Document.
DO NOT SELECT REPAIR
Do not select Repair to install new options, since OmniPro I'mRT will be reinstalled using the same settings as during the previous setup.
MOVING THE SOFTWARE TO ANOTHER COMPUTER
If it becomes necessary to move the software to another computer, e.g. after a computer crash, a new registration is necessary. Follow the instructions for a normal registration.
Computer settings for MatriXX
MatriXX can be connected directly to a PC, or to a local network (LAN), via an Ethernet cable.
Several devices can be connected to a network.
Administrator status is required to perform connections.
MATRIXX
In the instructions for connection to a PC or a local network ( The new firmware version will be installed.
Select Yes when you are prompted to restart the device.
RESTART
Manual restart of the device is necessary. Turn power off and on to restart the device.
Main Toolbar
The tool buttons provide shortcuts to common menu commands, such as "selection of the data set to be displayed": Displays dataset 1 in all panes.
Displays dataset 2 in all panes.
Displays two 2D data sets for comparison.
Displays two 3D data sets for comparison.
To get a brief description of the command, move the mouse over the tool button until a tool tip is displayed, or look at the information text in the status bar. Depending on the data displayed, some commands in the toolbar may not be available (dimmed).
To view/hide the toolbar, select Workspace:Toolbar.
Refer to the OmniPro I'mRT on-line help for detailed descriptions of all buttons.
The I'mRT QA/BIS toolbar contains status indicators, selection buttons for the measurement mode, start button, and a button for background definition.
6.1.6. I'mRT MatriXX Toolbar When I'mRT MatriXX is selected as the measurement device, the OmniPro I'mRT MatriXX toolbar will be expanded.
The I'mRT MatriXX toolbar contains status indicators, selection buttons for the measurement mode, start button, and a button for background definition.
Status Bar
The status bar, at the bottom of the main window, displays information about current actions, and provides brief help texts for menu and toolbar commands. To display or hide the status bar, select Workspace:Statusbar.
Panes
Four different panes are used to display the data. The type of data displayed depends on what kind of data is selected (one data set or two data sets for comparison).
The following general commands are used to select the view:
Toolbar icons
Shows the data as isodose contours.
Shows the data as a two-dimensional array.
Shows the data as a three-dimensional array.
Pane icons
Maximizes a single pane to full window display.
Restores a maximized window to the previous window size.
Resets all panes to default sizes. Array Pane: Shows the data as a 2D array.
Isodose or 3D-Pane: Shows the data either as Isodose contours or in a 3D view.
Profile Panes: Shows profiles along the main axes. The profile offset to the origin can be defined when selecting the View:Profile Cursor inside the Array Pane.
See also 9.4 Analyzing one single data set.
Panes during Plan Verification
When Plan Verification 2D or 3D is selected, two panes are used to display the two single data sets. The other two panes are used for comparison.
Data Set 1 (or 2) Pane: Displays the data set 1 (or 2) as a 2D array, an Isodose contour, or in a 3D View.
Comparison Pane: Displays isodoses or profiles of both data sets in the same window.
Result Pane: Displays the result of a mathematical comparison between the two data sets. Possible operations are, for example, Difference, Gamma method, or DTA method.
In the Comparison Pane you can either compare isodoses or profiles: Shows the isodose levels of both data sets in one single pane. Isodose levels can be defined when selecting View:Isodose Levels inside the data set 1 and 2 panes. For example, click in data set 1 pane, select View:Isodose, and then View:Isodose Levels. (Or right click in the isodose pane and select Isodose Levels Set 1 (or 2)).
Shows one profile of each data set along one of the main axes. The offset to the origin can be defined when selecting View:Profile Cursor inside the Array Pane of each data set. To switch over to the other axis, right click in the pane and select the other axis.
File type Description
*.opw OmniPro I'mRT workspace file. The workspace file does not contain any 2D dose distribution data itself, but rather information about where data that belong together are saved. It can contain the link to two data set files (*.opd) and one result file (with the name workspace name_res.opd). Additionally it can contain Absolute Dose verification data and comments. If you want to add the data to the open data set, check Append to current data set. Use the Field list dialog to select data from the data set. To select all data in the Field list, press <Ctrl + A>.
Configuration of OmniPro I'mRT Software
The OmniPro I'mRT system needs to have information about the equipment that is used with the system, such as the clinic, scanners, detectors, film type and the radiation device. Normally this is done directly after you have installed OmniPro I'mRT. Prior to measurements it is then quite easy to select the used equipment from a drop down list. (It is possible to add, modify, or remove equipment at any time.) Choose the category of equipment that you want to configure from the Equipment menu:
Clinic:
Enter administrative data about your clinic. This information will be stored together with the measurements.
Radiation Devices: Specify the accelerators including energies, wedges, etc.
MatriXX Evolution: Define the MatriXX Evolution .
Film: Define the type of films you are going to use.
Film Scanner: Define the settings for the film scanner to be used with OmniPro I'mRT.
Body Phantom: Define the body phantom.
Detectors: Not applicable in this SW version.
See the on-line help for detailed descriptions for the configurations.
Specify Units and Parameters
There are a number of items, related to parameter calculation and the user interface, which can be defined according to your preferences. This is done in the Options dialog. Open the dialog by selecting the menu command Tools:Options. The parameters will be displayed in the profile view: The calculation methods are described in 14 Algorithms.
User-defined Protocols
To define a customized protocol, options for calculation methods for field width, penumbra, flatness, symmetry, and deviation, are available.
INTENSITY MODULATED FIELDS
The FermiFit algorithm is not intended to be used on intensity modulated fields.
When a parameter in one of the pre-defined protocols is changed, the protocol name will be cleared. Thus the user-defined protocol will not have a name assigned to it. ■ Define the size and location of the region of interest (ROI).
Search distance: This is the search range for the Gamma algorithm. It should always be larger or equal to the criterion of acceptance. Normally it is sufficient to set the value exactly the same as Delta Distance.
However, if you also like to have values larger than 1, regarding the local aberration with the Gamma method, you must search also beyond this limit. Thus you will see if the gamma value is not correct (Gamma > 1), and the size of deviation as well (e.g. Gamma = 1.5).
Relevant Signal: Defines a threshold value to take underground signals (non irradiated areas) out of statistics.
Invalid Result:
Value assigned to all pixels that are below the threshold value. If you assign i.e. -1 for these pixels they will be displayed in the histogram later on but will not be taken into account.
Refer to the OmniPro I'mRT online help for further description. ■ Define the output resolution for Copy/Paste to an external application.
Refer to the OmniPro I'mRT online help for further description.
Setting up I'mRT MatriXX
The diagram below shows the general placement of the MatriXX, the power supply, the PC, and the connections between them.
For measurements the MatriXX is placed under the gantry head, either on the treatment couch or on a lifting table, as shown in the figure below, or mounted on the gantry. It is connected to the PC in the control room via an Ethernet cable, or via an existing LAN network. 2. The lasers in conjunction with the side cross makers of the MULTICube or on the I'mRT MatriXX can be used to position the device in the center of the beam.
3. Align I'mRT MatriXX, using a spirit level placed on the detector area.
4. At the accelerator, set the field size 20 × 20 cm, and turn on the light field.
5. Use the adjustment capabilities of the treatment couch, or the lifting table, to position I'mRT MatriXX so that the crosshairs at the sensor area and the light field crosshairs are superimposed.
USE THE SIDE MARKERS FOR POSITIONING
Due to the higher uncertainty when positioning the device in the light field (diffuse penumbras and cross-hair width), for precise positioning it is advisable to refer to the side markers which are engraved in the housing.
6. Ensure that the cables to the PC or the network are properly connected.
7. Plug the power cord into a mains power outlet, and switch on the MatriXX. Verify that only the green LED is illuminated.
Allow an appropriate warm-up time, and pre-irradiate the device during the warm-up (See 7.3.2 Pre-irradiation and Warm-up). Table) so that the crosshairs at the sensor area of the MatriXX and the light field crosshairs are superimposed.
USE THE SIDE MARKERS FOR POSITIONING
Due to the higher uncertainty when positioning the device in the light field (diffuse penumbras and cross-hair width), for precise positioning it is advisable to refer to the side markers which are engraved in the housing.
6. Ensure that the cables to the PC or the network are properly connected.
7. Plug the power cord into a mains power outlet, and switch on the MatriXX. Verify that only the green LED is illuminated.
ALL ACCESSORIES MUST BE LOCKED TO THE SUPPORT FRAME
The total weight of the support frame with the MatriXX with 50 mm build up, backscatter holder with 100 mm backscatter plates, and the gantry holder, is 37.9 -39.6 kg (depending on the type of gantry holder).
Ensure that all knobs and safety clamps are firmly tightened before starting the measurement. Check: Try to pull the MatriXX out of the holder. It must not be possible to move it.
MATRIXX MUST STAY CLEAR OF SURROUNDING EQUIPMENT
Ensure that the mounted MatriXX stays clear of the patient couch or other equipment, when the gantry is rotated.
CAUTION ENTER GANTRY ADAPTER INFORMATION TO THE LINAC SOFTWARE
Ensure that the gantry adapter is accepted as an accessory by the Linac software; otherwise interlocks may occur.
START WITH THE BACKSCATTER HOLDER AND PLATES
If backscatter plates are going to be used, start by mounting the backscatter holder and plates.
Mounting the Backscatter Holder and Plates
Backscatter plates can be mounted from 10 to 100 mm, in steps of 1, 2, 5, and 10 mm.
The delivered backscatter plates are made of water equivalent polystyrene, RW3.
BACKSCATTER HOLDER
The plates must be positioned and locked in the backscatter holder. . Lock the backscatter holder with the four knobs (b). These knobs will also lock the MatriXX to the frame.
CAUTION ENSURE THAT ALL KNOBS AND SAFETY CLAMPS ARE PROPERLY TIGHTENED.
The design of the holder is based on friction, therefore proper tightening of the screws is essential.
Mounting the MatriXX in the Support Frame
When inserting the MatriXX into the support frame, ensure that it will be positioned tightly to the wall of the frame. The openings in the frame allow the markings for laser adjustment to remain visible (c).
1. Move the MatriXX cautiously to the opposite wall of the frame, by turning the two knobs (d) on the side of the frame. Do not tighten the knobs.
Setup of MatriXX for measurements
| 76 | P-07-002-510-001 06 OmniPro-ImRT System User's Guide 2. Use the four knobs (b) in the bottom of the frame to lift the MatriXX to the upper surface of the frame, so that the distance to the isocenter will be correct (100 or 76.2 cm). These knobs will also lock the MatriXX to the frame.
SURFACE OF THE DETECTOR AREA
The surface of the detector area is positioned 3 mm below the MatriXX housing surface. The water equivalent thickness is 3.2 mm.
CAUTION LOCK THE MATRIXX TO THE FRAME
Ensure that the MatriXX is locked with the four knobs in the bottom of the frame. The two knobs on the side of the frame will not lock the MatriXX. Check: Try to pull the MatriXX out of the holder. It must not be possible to move it.
Buildup Plates
Build up can be mounted up to 5 cm, in steps of 1 mm.
The delivered build up plates are made of water equivalent polystyrene, RW3.
The water equivalent depth of the MatriXX housing is 3.2 mm.
Remove the safety clamps (a).
Tip! Turn the clamps 180° and put them on the knob again, to keep them readily at hand. (a)
Setup of MatriXX for measurements
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 77 | 2. Position the plates on the MatriXX surface, in the frame. Lock the plates from above with the four clamps on the side of the frame (b).
CAUTION ENSURE THAT ALL CLAMPS (A) AND (B) ARE TIGHTENED
All clamps must be tightened, otherwise the plates may slide out. Table IMPORTANT NOTICE
BACKSCATTER PLATES AND BUILD-UP PLATES
If backscatter plates and build up plates are going to be used, adjust the XY table after the backscatter holder and the build up plates have been mounted and locked.
MATRIXX MOUNTED ON THE GANTRY
If the MatriXX is going to be mounted on the gantry, adjust the XY-table after the complete equipment, the gantry adapter included, has been mounted on the gantry (see 7.1.1. 3
.5 Mounting of the Gantry Adapters).
XY
Setting up MatriXX Evolution
The diagram below shows the general placement of MatriXX Evolution , the power supply, the PC, and the connections between them.
It is connected to the PC in the control room via an Ethernet cable, or via an existing LAN network.
MatriXX
Evolution can be positioned on the treatment couch, or mounted in a MULTICube.
Setup with MULTICube
In the MULTICube the device can be positioned in steps of 5 cm vertically, thus raising the measurement plane up to 20 cm above the plane of the couch.
MatriXX
Evolution may also be positioned in a vertical position.
CAUTION SUPPORT THE ELECTRONICS PART OF THE MATRIXX
When backscatter plates are used, the center of mass is on the electronics side of the detector bed. Support the electronics part of the device to eliminate the risk that the MatriXX will tip over. (Sufficient build-up will offset the weight of the electronics and shielding).
If the MULTICube is not used place at least 5 cm solid water as backscatter and build-up material underneath and on top of the MatriXX.
Setup with Gantry Holder
For details about head mounting and alignment, see 7. Ensure that the cables to the PC or the network are properly connected.
Plug the power cord into a mains power outlet, and switch on the device. Verify that only the green LED is illuminated.
Pre-irradiation
Like other ion chambers, the MatriXX device needs a certain dose of preirradiation before the chamber signal reaches a stable value. Final profile
Examples of pre-irradiation profiles
Pre-irradiation can be performed during the warm-up phase.
Pre-irradiation has to be repeated every time the device is switched on.
Warm-up Time
For relative dosimetry, the stability of the MatriXX will be sufficient after 15 minutes' warm-up.
For absorbed dose measurements, the stability will be sufficient after 1 hour's warm-up.
Gantry Angle Sensor (available with MatriXX Evolution )
The Gantry Angle Sensor is an additional tool for the MatriXX E v o l u ti o n . Its purpose is online detection of the gantry angle while irradiating for treatment verification.
For the Gantry Angle Sensor, the use of MatriXX Evolution is mandatory, since only the MatriXX Evolution is intended to be used in rotational applications.
The sensor is equipped with 4 LEDs to facilitate alignment of the sensor in a vertical plane; a precondition for correct measurements (see 7. 3 The sensor shall be fixed on the gantry (e.g. using powerstrips or similar adhesive tapeobserve the instructions of use!). In order to provide correct results, the sensor must be aligned in a vertical plane within ± 5°.
MatriXX Evolution service port
Gantry angle sensor
2. Connect the sensor to the service port of the MatriXX Evolution .
3. Power on the MatriXX Evolution .
4. At the sensor, remove the tilt in direction Y.
6. Remove the tilt in direction X.
How to remove the tilt in each direction: 1. Turn the gantry to 0°, loosen the screw for Y direction and align the sensor until no LED for this direction lightens up. Fasten this screw. Repeat this procedure after turning the gantry to 90° for X direction.
2. The LEDs on the sensor will light up if the tilt is not within the permitted range (± 5°) in the respective direction. If no LEDs lighten up anymore, the sensor tilt is within the tolerance for both directions. The sensor can then be calibrated.
3. The correct alignment is checked in the software during calibration of the sensor (see 7. 3
MPORTANT NOTICE DISTANCE BETWEEN MATRIXX EVOLUTION AND GANTRY ANGLE SENSOR
Make sure the distance between MatriXX Evolution and Gantry Angle Sensor is such that the length of the cable (3 m) is sufficient even when turning the gantry.
GANTRY ANGLE AND ROTATIONAL DIRECTION
The gantry angle and the rotational direction of the sensor are defined in IEC 61217.
SENSOR READOUT
The sensor readout can be affected by outside influences (vibration, etc.).
Calibration of the Sensor
When the sensor is connected to the MatriXX Evolution , and the OmniPro I'mRT software is started, the software automatically detects the sensor. If a measurement is started without an existing sensor calibration, a warning message appears.
CALIBRATION OF SENSOR
The sensor calibration must be repeated every time that the MatriXX Evolution is switched on.
1. When the sensor is aligned, go to Measure/Calibrate Angle Sensor.
The Gantry Angle Calibration window opens.
The checkmark for Angle sensor is mounted on the collimator will for now only serve as information for the user. In later versions of the software there will be the possibility to mount the angle sensor at the collimator, and an algorithm will calculate the angle also when the collimator rotates.
Descriptions of the steps through the calibration process are displayed in the Gantry Angle Calibration window.
2. The first step after fixation of the sensor on the gantry is to move the gantry in an upright position (gantry head up) and press the Start button. The tilt of the sensor and the gantry angle will be displayed.
The tolerance to pass the calibration is ± 5°. If the tilt is within this range, a green checkmark is displayed. 3. Accumulate the corrected images to an integral.
4. Perform the QA in integral of set 4.
After performing a measurement with the gantry angle sensor, the angle will be stored. It is displayed in the dataset pane for each measurement.
The angle will also be displayed in the field list, for each measurement done with the sensor. For the automatically calculated integral no angle will be displayed.
Setup of MatriXX for measurements
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 93 | The header information of a measurement done with the gantry angle sensor will contain the gantry angle value.
Function Check
To check the function of the sensor, measure two single shots and compare the measured gantry angle with the expected value.
CHECK FUNCTIONALITY
It is recommended to check the functionality of the sensor once a year.
Gantry Angle Correction
The MatriXX Evolution has a small angular dependence which can be corrected by a calculated matrix. These values are stored in look up tables and can be applied to already measured data dependent from the angle.
LUT CORRECTION
The values in the look up tables are only valid for the combination of MatriXX Evolution with MULTICube. If the MatriXX Evolution is not used with a MULTICube you can create and use your own angular correction tables (please see below).
IMPORTANT NOTICE
APPLYING ANGULAR CORRECTIONS Applying angular corrections to measurements is only possible if they were done with the gantry angle sensor.
Settings for Angular Correction
For applying a correction matrix to measurements go to Edit/Apply gantry angle correction.
Linac: In the drop down menu the given correction files are listed. Given by default is a matrix for 6 MV and a beam quality index of 0.666, and a matrix for 18 MV and a beam quality index of 0.783. These are common values for the beam quality index and representative for the 6 MV and 18 MV.
Energy: Select Set User-Defined to enable the fields for editing MV and Beam Quality Index values. Enter energy and a beam quality index.
The Beam Quality Index is specified by the tissue phantom ratio TPR20/10. If this value is not available, it can be obtained from the percentage depth dose curve for the given energy: where PDD 20/10 is the ratio of the percent depth dose at 20 cm and 10 cm depths for a field size of 10 cm × 10 cm defined at the phantoms surface with an SDD of 100 cm.
It is possible to select a customized beam quality index by ticking the box Select Beam Quality Index. Enter energy and a beam quality index. The software creates via linear interpolation the matrix for the given beam quality index and calculates the angular correction for the measured data. The entered energy is only a header information and does not influence the calculation.
Check the box Copy the original images if the original measurements shall be kept. In the field list the originals will be corrected, and a copy of the originals will be created. The integral is still the integration of the originals, even if the originals were replaced by the corrected data.
Setup of MatriXX for measurements
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 95 | In the field LUTs it is possible to delete and export existing look up tables for correction of gantry angles, or to import new tables.
PATH TO ORIGINAL CSV FILES
If the LUTs were deleted by mistake, the original csv-files are stored under the path: C:\ProgramFiles IBADosimetry OmniPro-ImRT\ SampleData \ AngularCorrection.
To customize existing correction tables, export the LUT by pressing Export.
Save the csv-file under an individual name and open it with e.g. Microsoft Office Excel. To do this, in the Windows settings the decimal point must be "." and the list separator must be ",". Only csv-files can be imported.
In a similar way it is possible to customize the values as required (also without the MULTICube).
Setup of MatriXX for measurements
| 96 | P-07-002-510-001 06 OmniPro-ImRT System User's Guide Create a customized angular correction factor tables It is possible to create a customized set of correction factor tables from MatriXX measurement and reference dose distributions. By doing so, it is possible to adjust the angular correction of MatriXX measurement to individual reference, e.g. heterogeneous or homogeneous TPS dose distributions or film measurements.
For the measurement of angular correction factors it is recommended to use a set of static fields with incident angles between 0° and 180° with an angular resolution of at least 10° for each photon beam energy (OmniPro ImRT 1.7 assumes symmetry between the angle range [0° -180°] and [180° -360°] so for example the correction factor for gantry angle 90° is used for gantry angle 270° as well). Correction factor tables are stored in a simple "comma separated value" (csv) file with following format:
MULTIPLE CORRECTION TABLES
One csv file can contain multiple correction tables, e.g. correction factor tables for different linacs or different beam energies.
Save the customized correction factor table and import the LUT by pressing Import under Edit/Apply gantry angle correction.
Correction of Measurements 1. Copy all data which shall be angular corrected to a field list, or choose the last done measurement.
2. Go to Edit/Apply gantry angle correction and select one of the listed correction files, and enter/mark the relevant options.
3. Press OK to apply the correction matrix to all measurements in the field list.
Example:
Below is an example of a measurement with 10 × 10 cm field size at a gantry angle of 90° and measured with 6 MV photons: In Dataset 1 is the original measurement is displayed. Dataset 2 displays the corrected measurement, for which a beam quality index of 0.67 was used.
Setup of MatriXX for measurements
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 97 | When using the plan verification 2D tool and comparing the profiles, the result of the correction is displayed: The difference between the original and corrected data is displayed. The absolute measured values for 90° are approx. 4% lower than they shall be (red line). The corrected data (green line) adjust the measured points upwards by 4%. N DW (60Co) • K uni ij is measured and calculated at the production site.
The k User factor can be created by the user (see Create the k User factor).
K off i,j can be created by the user (see User-defined off-axis calibration).
k pT is measured and calculated by the MatriXX system. The pressure factor can be corrected with the offset obtained when comparing the p value as measured by the system and by a reference meter (see 7.4.4.2 User-defined offset for the k pT factor).
Uniformity Correction Matrix for MatriXX
IMPORTANT NOTICE
UNIFORMITY CORRECTION MATRIX
The uniformity correction matrix is stored in the device itself, and shall be applied in all measurements.
WARNING UNIFORMITY CORRECTION MATRIXX FOR MATRIXX
The application of the Uniformity Correction Matrix file is mandatory. If the checkbox Activate device-internal calibration data is unmarked, the measurement will be performed without correction.
The uniformity correction matrix is individual for each MatriXX device, and will be used to remove inhomogeneities from the measured image. Data are stored in the device.
Add Correction Factors
A correction factor for the detector (k User ), and of the measured pressure and temperature (k pT ), can be added by the user.
The k User factor will be specific for the selected Linac, energy type, and energy value. Several factors, for different Linacs and energies, can be created. The new factor is persistent between sessions, and will be used until another factor is created.
If the Active checkbox in the Correction/Calibration dialog is not marked, the factor will be set as 1.
Dose Mode
1. Select Dose and enter the reference value. The value will be displayed as mGy, cGy, or Gy, depending on the settings in Options.
Click
Next to open the next wizard window.
3. Click the Measure button to start the measurement. The beam shall be turned on after the measurement has been started. Ensure that the beam time is long enough to cover the entire measuring time.
4. When the defined measurement time has elapsed, turn off the beam, and click the Stop button to stop the measurement.
Setup of MatriXX for measurements
| 104 | P-07-002-510-001 06 OmniPro-ImRT System User's Guide The system will calculate k User , using the entered reference value and the average of the values of four central MatriXX chambers. The new factor will be displayed in the k User field.
Click
Save As to open the dialog Save Calibration Factor.
6. Enter a unique name. Optionally a comment in the Comment field can be added, and the number of monitor units can be edited. Click OK to save data and close the dialog. To overwrite the value for a previously calculated factor, select the name and click OK.
The new factor is persistent between sessions, and will be used until another factor is created.
If the Active checkbox in the Correction/Calibration dialog is not marked, the factor will be set as 1.
Selecting the K user Factor for a Measurement
Open the Correction/Calibration dialog from the MatriXX toolbar.
Expand the drop-down list in Select factor, and select a factor.
If the selected factor does not fit with the currently selected measurement parameters, a warning will be displayed in the MatriXX toolbar: To view data for the selected factor, click Details. The following information is displayed: The difference between the value measured by the device and the entered reference value is displayed in the User-defined Pressure Offset field, in the Correction/Calibration dialog.
The defined offset is persistent between sessions, and will be used in all measurements until another offset is defined.
Setup of MatriXX for measurements
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 107 | If the Active checkbox in the Correction/Calibration dialog is not marked, the correction will not be used.
User-defined Off-axis Calibration
A user-defined calibration can be applied, to compensate for deviations that occur after the I'mRT MatriXX or MatriXX Evolution have been in use for some time. The calibration shall be applied as an add-on calibration.
The user calibration makes use of only three full-field measurements in order to calculate user calibration factors for 1020 pixels. Therefore inaccuracies and noise during the user calibration measurement will propagate from one pixel to the other over the full active area of the pixel array, adding a small amount of noise to the calibration data. Therefore it is recommended applying the user calibration only in cases where pixel deviations from uniformity are well above 1%.
The user calibration procedure has been proven to work well for typical cases of miscalibrated pixels, e.g. single or few pixels randomly distributed in the pixel array with arbitrary amount of miscalibration, or Gaussian noise on the entire active area. There might be rare cases however, when the user calibration leads to unsatisfying results. This can happen when miscalibrated pixels are unfavorably distributed in the pixel array, and one miscalibrated pixel is mapped to another one during the user calibration measurement (e.g. many adjacent miscalibrated pixels in one pixel column). In these cases we recommend to recalibrate the device in the factory.
It is recommended to use the gantry holder for the calibration. The recommended measurement time for each step in the calibration procedure is 100 MU. The recommended field size is 28 × 28 cm. All channels have to be covered, but the electronics must not be in the beam.
DEVICE-INTERNAL CALIBRATION DATA MUST BE ACTIVATED
Ensure that the check-box Activate device-internal calibration data is marked, before performing the measurements for the K off i,j factor.
A series of dialogs will guide you through the procedure.
First measurement
Position the MatriXX centered under the accelerator with an angle of 0 degrees. Select the number of monitor units that will be used for all measurements within the calibration process. Press the Measurement button to start the measurement first, and then turn on the beam.
Second measurement
Turn the MatriXX 90 degrees clockwise, and make a measurement with the same number of monitor units, and in the same way as described in First measurement.
Third measurement
Shift the MatriXX exactly one row of detectors in the right hand direction (looking at the gantry from the front), and repeat the measurement as in First and Second measurement.
ADDITIONAL MARKERS
On both sides of the MatriXX there are two smaller additional markers for aligning the MatriXX after shifting one pixel row to the right site.
Click Finish, and save the calibration in Save MatriXX User Calibration.
Click View to open the calibration file. Verify the result.
Apply the User-defined Calibration
Click the Correction button in the toolbar. Mark Activate device-internal calibration data and Activate user calibration matrix.
DEVICE-INTERNAL CALIBRATION DATA MUST BE ACTIVATED
Ensure that the check-box A ctivate device-internal calibration data is marked, when applying the K off i,j factor.
Click OK.
MatriXX Setup Tab
Open the MatriXX Setup tab.
Define how the device is mounted in Mounting. The options Table mounted and Head mounted are available.
Define the position in relation to the accelerator in Position.
Device data are found in the Device section in the dialog.
Single Shot Mode
In this mode, one single image is composed of a set of single frames (each one measured with the selected measuring time). The composed image contains the average of the selected number of samples.
If background compensation is activated, the background is subtracted from each individual frame.
Movie Mode
In this mode, a given number of movie pictures (single shots, as described above) are acquired. Each picture, as well as one integrated image, are saved.
NUMBER OF MOVIE IMAGES
If the No. of Movie Images is set to "0" the movie will not stop until the Stop Movie button is pressed. Firmware version 1.34 is required to use this option. Therefore please refer to chapter 5.
On-line Mode
In this mode, single shots, as described above, are measured continuously and displayed on-line. Only the last five images are saved.
3. Select scaling mode in the Mode drop down list: Relative to Maximum: All data is normalized to the maximum value which in turn is set to 100%.
RELATIVE TO MAXIMUM
It is not recommended to use Relative to Maximum during acquisition, as the original scaling cannot be retrieved later. It also may give the wrong impression that it looks like dose is building up without any beam present since the background will be scaled.
Relative to CAX: All data is normalized to the central axis value (4 central pixels) which set to 100%.
RELATIVE TO CAX
It is not recommended to use Relative to CAX during acquisition, as the original scaling cannot be retrieved later. I t also may give the wrong impression that it looks like dose is building up without any beam present since the background will be scaled.
SAMPLING TIME
The sampling time must be entered in multiples of 10.
Single Snap:
The measurement time is the product of the sampling time and the number of samples. The relative scaling is given by total integral, divided by the number of samples.
The dose is divided by the number of samples.
ABSORBED DOSE VALUE
Provided that No. of samples is set to 1, the absorbed dose value is not affected by renormalization, and always represents the total accumulated dose.
NUMBER OF SAMPLES
It is not recommended to set the no. of samples other than 1.
Movie mode:
The measurement time is the product of the sampling time and the number of samples. The relative scaling for single frames is given by total integral, divided by the number of samples.
The total movie time is the product of the measurement time and the number of movie images.
Setup of MatriXX for measurements
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 113 | An example of the relation between the measurement time and the total movie time.
SAMPLING TIME ≤40 MS
If the sampling time is ≤40 ms, the allowed number of images is limited, due to firmware limitations and limitations that might occur in the local network.
The movie acquisition can be stopped manually, without data loss.
At the end of a movie acquisition an integral frame is produced, containing the sum of all required frames. The relative scaling of this integral frame is divided by the number of frames in the movies (regardless if the movie has been aborted manually or completed).
The dose is divided by the number of samples.
ABSORBED DOSE VALUE
Provided that No. of samples is set to 1, the absorbed dose value is not affected by renormalization, and always represents the total accumulated dose.
NUMBER OF SAMPLES
It is not recommended to set the no. of samples other than 1.
TOTAL MOVIE TIME
In Movie Measurement mode (i.e. when checking dynamic or step and shoot fields), the total movie time must be longer than it takes to perform the treatment. Always add some margin for the startup of the accelerator. To remove all deactivations, click Activate All.
Select an algorithm (or
The four corner pixels are by default deactivated.
ADJACENT CHANNELS
Two perpendicular adjacent channels must not be selected.
View Deactivated Channels
Deactivated channels can be viewed in the info parameters for a MatriXX measurement.
Select Parameters in the View menu. Select the MatriXX Meas. tab.
When moving the mouse cursor to the Channel button, a tooltip will display how many channels that are deactivated. Click the button to view the deactivated channels.
If no channels are deactivated, the Channel button will be disabled. If the maximum signal is much higher than 100%, decrease the sampling time.
If the maximum signal is much less than 100%, increase the sampling time.
10. Repeat the measurement to check if the signal level is now about 100%.
TURN OFF THE ACCELERATOR
During background definition the accelerator must be turned off.
The background procedure performs a measurement of the signal level on a "dark" image. The defined value will be subtracted from all calculations and presentations.
Click the toolbar button Background. The measurement starts.
The button remains dimmed until the measurement is completed.
Background is always measured with one sample, for 20 seconds. To adapt the background level to the level of measured signals, the values are rescaled with the factor sampling time/background sampling time.
THE BACKGROUND VALUE IS VALID DURING ONE SESSION
The background value can be used for all subsequent measurements during a session. If the device or the software is turned off, a new background value must be defined before the next measurement. Select the radiation device, the wedge, the applicator, and the energy to be used.
Enter the SDD, and the gantry and collimator angle values.
Specify the field size used as reference field for the selected energy at SAD in inline and crossline.
Administration Tab
Select the Administration tab.
Since the information on this tab is already defined in the Clinic setup dialog, you only have to check if the information is correct.
If the information is correct, click OK. Depending on the measurement situation, different measurement modes are available for best results:
Single Shot Mode
In this mode, one single image is composed of a set of single frames (each one measured with the selected measuring time). The composed image contains the average of the selected number of samples.
If background compensation is activated, the background is subtracted from each individual frame.
Movie Mode
In this mode, a given number of movie pictures (single shots, as described above) are acquired. Each picture, as well as one integrated image, are saved.
NUMBER OF MOVIE IMAGES
If the No. of Movie Images is set to "0" the movie will not stop until the Stop Movie button is pressed.
If background compensation is activated, the background is subtracted from each individual frame.
If no interpolation is selected, the measured data is displayed on-line.
Use this measurement mode e.g. to analyze dynamic wedges, or MLC fields.
LOW COMPUTER PERFORMANCE
If the computer performance is low, display of movie data may be delayed.
SHORT SAMPLE TIMES
For low sample time values (<500 ms), an accumulated background rounding error of values may occur.
On-line Mode
In this mode, single shots, as described above, are measured continuously and displayed on-line. Only the last five images are saved.
If background compensation is activated, the background is subtracted from each individual frame.
Use this measurement mode e.g. to trim the field parameters of the accelerator. By looking at the inline and crossline profiles, it is easy to check symmetry and flatness parameters in both orientations simultaneously.
Single Shot Mode Measurements
Click the toolbar button Measure.
After measurement is completed the resulting image is displayed.
On-line Mode Measurements
Click the toolbar button Start On-line.
The images are displayed during the measurement.
When the treatment is completed, click S t o p O n -line t o s t o p t h e measurement.
Only the last five images are saved. To check these images open the Field list dialog by selecting View:Field list.
Movie Mode Measurements
Click the toolbar button Start Movie. Start the treatment as planned.
When the pre-defined time has elapsed, the measurement stops. If you want to stop the measurement before the total time has elapsed, use the Stop Movie button. The current image will be finished before the measurement stops.
When the measurement is completed the resulting image is displayed. If the Stop Movie button was used to stop the measurement, the images that were measured until the stop will be calculated and stored, and an integral image is calculated and stored.
To check single movie pictures, or to run the movie, open the Field list dialog by selecting View:Field list.
Manually Start and Stop Measurements using Movie Mode
If the No. of Movie Images in the Parameters is set to "0" the movie starts by clicking the Start Movie button. The software measures as long as the Stop Movie button is clicked.
Setup Measurement Parameters
Using the MULTICube please make sure to measure a correction factor for this constellation. Therefore please refer to 7.4.4 Add Correction Factor. For rotational measurements use the "Dose Mode" for measuring this factor.
For general software settings please refer to the chapter 7.4.5 Measurement Setup.
TAKE TREATMENT COUCH IN TPS INTO ACCOUNT
For a precise verification please make sure that the TPS takes the treatment couch into account for calculation the plans.
MatriXX
Evolution used together with the Gantry Angle Sensor (Gantry Angle Sensor), is required for the measurements.
The analysis can be made in OmniPro I'mRT, after import of DQA files from TomoTherapy (7.6.2.6 Export of DQA files to OmniPro I'mRT), or in TomoTherapy, after export of a MatriXX TIFF file from OmniPro I'mRT (7.6.2.5 Export of TIFF files to TomoTherapy).
EXPORT OF MATRIXX TIFF FILES RECOMMENDED
Export of a MatriXX TIFF file, to be analyzed in TomoTherapy, is recommended as a better alternative.
CT Scan of the MatriXX CT Setup and Configuration Use the same configuration for the MatriXX as the one that will be used in TomoTherapy.
The physical limitations of the TomoTherapy couch (i.e. it is impossible to raise the couch above a certain point) must be taken into consideration. The plan that will be administered must allow that the plane of the MatriXX will be within the physical limitations of the couch, once the plan is superimposed on the MatriXX.
As a general rule, 5 cm additional backscatter material will be sufficient for most plans, but not for all. If in doubt, choose using more backscatter material rather than less. 10 cm or more can be regarded as sufficient.
Using the MULTICube phantom in its full or "light" configuration will eliminate this problem for virtually all plans.
DIFFERENT CT SCANS FOR DIFFERENT MATRIXX'S
For every MatriXX a CT is necessary. Otherwise deviations in dose calculation and measurements are possible. Ensure that the correct CT scan is used.
Slice Width
The slice width is important, because the exported TomoTherapy DQA (Delivery Quality Assurance) files derive their resolution in the x-direction (parallel to the couch in the DQA) from it.
If the analysis is going to be made in OmniPro I'mRT, use 2 mm slice width, or less. A better resolution improves the landmark selection on the further procedure.
BANDING IN THE GAMMA ANALYSIS
If 3 mm slice width is used, it will work for analysis in OmniPro I'mRT, but the resolution of the DQA export will be non-isotropic, and "banding" will appear in the gamma analysis: 7.6.1.
Alignment
Align the MatriXX to the laser cross-hairs meticulously, to avoid obtaining skewed slices.
If a MULTICube phantom is not used, it is recommended that a couple of markers are placed right on the cross-hairs on the MatriXX housing. Thus the center of the device will easily be identified on the CT images.
If a MULTICube is used, it is not necessary to use markers, since the engraved crosshairs of the cube will be visible in the CT images.
Setup of MatriXX for measurements
| 124 | P-07-002-510-001 06 OmniPro-ImRT System User's Guide CT DICOM Export Set TomoTherapy requires phantom CT sets to be named _phantom. In the phantom list in TomoTherapy, the name of the phantom will be the Patient ID that was assigned at the CT, not the patient name. The _phantom will not be displayed in the phantom list.
Thus the Patient ID at the CT should be e.g. MatriXX, and the patient name at the CT must be _phantom.
Pre-irradiation of the MatriXX
The MatriXX requires pre-irradiation prior to use. The most convenient way to do it is to use a C-Arm Linac, if available (I'mRT MatriXX -Setting up for Measurements / Pre-irradiation). Perform the pre-irradiation, un-plug the MatriXX, and move it to the TomoTherapy.
Pre-irradiation can also be performed in the TomoTherapy, either by using a static field, or a "cylindrical" helical plan from TomoTherapy. With these assumed values the pre-irradiation dose (D) will be 99 cGy, and the couch velocity (V) will be 0.144 cm/sec.
Pre-irradiation dose for a typical TomoTherapy dose rate:
In the
THE TOMO THERAPY MVCT CANNOT BE USED FOR PRE-IRRADIATION
The TomoTherapy MVCT cannot be used for pre-irradiation, since it does not deliver the sufficient quantity of MUs. The energy is only 3 MV.
USE ONLINE MODE IN OMNIPRO I'MRT
For pre-irradiation use the Online Mode in the OmniPro I'mRT software for better observing.
Background Subtraction and Energy Calibration
After pre-irradiation, the next step would normally be to do the background subtraction and to obtain the k User factor for energy calibration (see 7. 4
.4 Add correction factors).
The need for these procedures depends on which export method that will be used.
TOMO THERAPY DICOM PLANAR EXPORT METHOD TO BE RELEASED
This export method is not yet released at the time of publishing this manual.
The k user factor must be obtained in order to get the same information as with a C-arm Linac. A cylindrical plan to be delivered helically must be created. A known dose will be administered to the four central chambers of the MatriXX.
TIFF Export from OmniPro I'mRT
The k user factor must be obtained in order to get the correct dose information.
Creation of the Plan
Export the MatriXX CT images to the TomoTherapy planning station, and then select the plan that will administered to the MatriXX.
When the dose distribution is superimposed on the MatriXX phantom in the TomoTherapy, it is usually considered necessary that the distribution over the phantom is such that it includes the PTV, and other information, e.g. spine. To facilitate this, take into account the fact that the effective point of measurement, P eff , of the MatriXX is at a depth of 3 mm.
The air gaps of the ion chambers will be visible in the CT images rendered by the planning system. Thus it is possible to position the desired planar dose distribution at the MatriXX P eff , which is just slightly beneath the top electrodes of the chambers.
MVCT
Align the MatriXX 1. Align the MatriXX with the TomoTherapy lasers. There are two sets of lasers: red and green. The green laser defines the virtual isocenter in TomoTherapy, 70 cm offset from the real isocenter. The red lasers can be viewed and moved manually from the virtual isocenter, to match the patient/phantom fiducially. Usually it is suitable to align the MatriXX to the red patient laser/coordinate system.
2. Select the center axes of the device in order to define the origin of the phantom. This is done by moving the red laser around in the planning station. The BBs or the MULTICube c r o s s -hairs are useful in this procedure.
IMPORTANT NOTICE ALIGNMENT
Do not align the red laser to the center of the chamber air cavities in the coronal plane. The P eff is on the top electrode.
MVCT AREA
It is not necessary to do an MVCT of the entire active area of the MatriXX. A few centimeters on either side of the transverse zero slice is sufficient to get the BBs in the MVCT and to make the center of the device visible.
4. Align the CT and MVCT images, using the TomoTherapy checkerboard. 2. Define the registration points in the TIFF image, by using the "General Coronal" procedure in TomoTherapy.
ONLY TWO REGISTRATION POINTS IN THE TIFF IMAGE
Since there are only two registration points in the TIFF image, the "Coronal plus 4 lasers" procedure cannot be used.
3. Select the plane that shall be exported. A plane that is near the center of the ion chamber air cavities shall be selected.
AIR CAVITIES MAY NOT BE VISIBLE
If a plane at the top electrode is selected, the air cavities will not be visible.
4. Two registration points will be requested by TomoTherapy. Use the hash marks. Mark the points on the dose plane, corresponding to the hash marks. The hash marks correspond to the chambers on the MatriXX diagonal to the blank spots on the top right corner and the bottom left corner of the device.
ENSURE THAT THE CORRECT SPOTS ARE MARKED
The MatriXX may be displayed sideways in the DQA workspace. Ensure that the correct spots are marked.
Setup of MatriXX for measurements
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 129 | 7.6.2.6. Export of DQA Files to OmniPro I'mRT Creation of the DQA Export If the analysis will be made in OmniPro I'mRT, prepare the DQA export from TomoTherapy as follows: Use the "Text DQA Header and Image Files" for export to OmniPro I'mRT. These files are created by TomoTherapy for export.
CUBIC DICOM EXPORT
The cubic DICOM export method is not recommended.
Select a random film in the TomoTherapy film panel, and mock register it. The film can be of any size. This action will enable the dose plane export button.
7.6.2.7. Import of DQA Files to OmniPro I'mRT Select File/TomoTherapy/Import ASCII File i n t h e O m n i P r o I ' m R T software.
SAVING DQA FILES
It is not recommended to save the DQA files in sub-folders, since certain sub-folder names or characters will disrupt the function. Copy the files to the desktop, and work from there.
The imported file will look similar to the example below: Take notes of the isodose lines and the coordinates corresponding to the import. The position to the import relative to measured data is arbitrary, since there is no coordinate system in the DQA export file. Data must be registered manually, using the Turn Array, Flip Horizontal, and Move data functions. Turn the array 90degrees clockwise, select Flip Horizontal, and use the Move Data f u n c t i o n t o r e g i s t e r t h e i m a g e s m a n u a l l y . T h e s e functions can be pre-defined in Macros, under the Edit menu.
Setup of MatriXX for measurements
| 130 | P-07-002-510-001 06 OmniPro-ImRT System User's Guide The following macro is recommended: ■ Turn array 90 degrees in the positive X direction ■ Flip horizontal ■ Convert grid to 0.762 cm -optional ■ Convert grid to 1 mm in order to frequency match the data with the interpolated MatriXX data -optional
CHANGE THE STEP SIZE
It is recommended to change the step size to 1 cm, instead of 1mm, for the initial alignment.
Use the isodose lines to align data, and then use the profiles for fine-tuning. If appropriate isodose lines are picked, it will be possible to hone in on the ideal registration point without the use of profiles. 2. Use a marker in the I'mRT Phantom origin that can be clearly seen on the CT image, and that can be used for later positioning of the I'mRT Phantom, e.g. a small piece of metal, or a characteristic structure of the phantom.
3. Set the isocenter in such a way that it will be easy to position the I'mRT Phantom under the gantry.
4. Note down the distance from the phantom origin to the isocenter, and the distance from the phantom origin to the origin for the dose calculation (in case the origin for dose calculation is not at isocenter position). 2. Tip! One possibility is to align the I'mRT Phantom in such a way that the I'mRT Phantom is parallel to the couch and the lasers (room coordinate system), and the phantom origin is in isocenter position.
3. Move the treatment couch by the distance between marker and isocenter (as noted when calculating the dose plan). ■ It must be possible to mark the films. The distance between the film marking and the phantom origin must be known.
Insert an ionization chamber into
■ The composition of the material shall be water or tissue equivalent.
The picture above shows the default orientation of the I'mRT Phantom. If you look in the direction towards the gantry, the origin marker for each film slice is on the right side of the center. If the phantom is rotated, you have to adapt the marker position in the equipment setup.
HEAD AND NECK TREATMENT
If you want to verify a head and neck treatment, perform a CT-scan and calculate the treatment plan for the cube only.
An example of a dose plan calculated for a patient:
The marker in the origin of the I'mRT Phantom coordinate system is clearly visible. Note that this marker can be in any CT-slice, as long as the distance to the isocenter and to the origin for dose calculation is known.
WARNING FILM GETS SATURATED
Depending on the choice of film, the saturation dose of the film may be lower than the maximum dose to be verified. Scale down the treatment plan or select an appropriate film.
. I'mRT Phantom Setup
Tip! To avoid mixing up the films, mark each film in a corner far outside the beam.
MARKERS ON FILM
Markers for identification, orientation, or positioning may overlap or interfere with optical density, due to radiation. Mark your films outside the region where you want to determine the dose.
1. Mount the films into the phantom.
2. Mark the films (for later alignment and positioning).
IMPORTANT NOTICE ALIGNMENT
The film may be misaligned either in its envelope, or tilted inside the phantom. To correct this misalignment after scanning, use two markers, or a line (e.g. the border of the phantom), to align the film to the body phantom coordinate system. The alignment markers must be parallel to the main axes of the phantom coordinate system.
ABSOLUTE POSITION
It is important to know the absolute position of the film with respect to the phantom origin. Mark the film, at a precisely defined position in relation to the phantom origin. The absolute position of this marker is entered in the Body Phantom setup dialog in Equipment.
Position the I'mRT
Phantom onto the treatment couch, and align it according to the treatment plan.
Tip! One possibility is to align the I'mRT Phantom in such a way that the I'mRT Phantom is parallel to the couch and the lasers (room coordinate system), and the phantom origin is in isocenter position. Then move the treatment couch by the distance between marker and isocenter (as noted when calculating the dose plan).
Measurement
Perform the treatment according to the treatment plan.
VERIFYING ONE PART OF THE TREATMENT ONLY
If you want to verify only one part of the treatment (e.g. one field), insert new films for this field, take them out after irradiation and insert new films for the next field. Remember to mark the films.
I'MRT QA/BIS CORRECTION IMAGE
The specification of the correction image file and the CCD area are mandatory. If you specify an incorrect or non-existing file and/or path, the measured image will not be corrected. If you specify an incorrect CCD area, the measured image will be incorrect. It will be very noisy and shifted, and may not appear fully on the screen. Before performing an I'mRT QA/BIS measurement, the Correction image file, found on the installation disk delivered with the I'mRT QA/BIS, must be copied to your computer.
The Correction image is individual for each I'mRT QA/BIS and will be used to remove inhomogeneities of the scintillator from the measured image. Before performing any analysis tasks the Correction image must be applied to the measured image.
FRAME GRABBER BOARD
The Frame grabber board must be installed in the computer that will be used for the measurements. Refer to the I'mRT QA/BIS Manual for further instructions.
WARNING I'MRT QA/BIS CORRECTION IMAGE
The specification of the correction image file and the CCD area are mandatory. If you specify an incorrect or non-existing file and/or path, the measured image will not be corrected. If you specify an incorrect CCD area, the measured image will be shifted and may not appear fully on the screen.
LIGHT FIELD MEASUREMENT
If you want to measure the light field (for comparison of light field with radiation field), insert the light field scintillator instead.
Measurement scintillator
The white side shall be located downwards; th e b l a ck s id e s h a ll b e located towards the radiation source.
Light field scintillator
The label I'mRT QA/BIS Light S/N xxx shall be located downwards.
6. Connect the data cable to the frame grabber board in the PC.
7. Plug the power cord of the power supply into a mains power outlet. Verify that the green and yellow LEDs ("Power" and "Image on Demand") are illuminated.
8. Continue by defining the I'mRT QA/BIS parameters.
Define the image device position in relation to the accelerator, in
Position.
The icon shows the relationship between the IEC and the I'mRT QA coordinate systems. 2. Specify information about the scaling mode to be used, in Mode.
Setup of MatriXX for measurements
3. In the Timing section, enter the sampling time (i.e. the integration time for one measurement) to be used, and the number of samples and movie images to be used.
TOTAL MOVIE TIME
In Movie Measurement mode (i.e. when checking dynamic or step and shoot fields), the total movie time must be longer than it takes to perform the treatment. Always add some margin for the startup of the accelerator.
An example of the relation between the measurement time and the total movie time.
The measurement time is the product of sampling time and the number of samples. The total movie time is the product of measurement time and the number of movie images.
Correction:
The path for the Correction Image and the CCD Region will be displayed as previously defined.
Date/Time: The date and time for the measurement will be automatically entered.
BIS 710
If BIS 710 is selected, the Meas. tab will be displayed as below.
Enter data in Scaling and Timing as in the I'mRT QA Meas. tab.
SAMPLING TIME
The minimum sampling time is 240 ms.
IMPORTANT NOTICE AMPLIFICATION
The Amplification option is not available for BIS 710.
I'mRT QA/BIS 710 Field Tab
1. Click the Field tab. The options available in this dialog are dependent upon the specifications setup in the Radiation Device Setup dialog.
Setup of MatriXX for measurements
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 141 | 2. Select the radiation device, the wedge, the applicator, and the energy to be used.
Enter the SSD and the gantry and the collimator angle values.
4. Specify the field size used as reference field for the selected energy at SAD in inline and crossline.
I'mRT QA/BIS 710 Administration Tab
Click the Administration tab.
Since the information on this tab is already defined in the Clinic setup dialog, you only have to check if the information is correct.
If the information is correct, click OK.
TURN OFF THE ACCELERATOR
During background definition the accelerator must be turned off.
The background procedure performs a measurement of the signal level on a "dark" image. The defined value will be subtracted from all calculations and presentations.
1. Ensure that the measurement scintillator is inserted. No light may enter the image device! 2. Click the toolbar button Background. The measurement starts.
The button remains dimmed until the measurement is completed.
SAMPLING TIME AND NUMBER OF SAMPLES
Background becomes invalid if the sampling time is changed, or if the number of samples used for background compensation is less than the number of samples used for the measurement.
Measurement
When I'mRT QA/BIS has been selected as measurement equipment, the toolbar and menu options will be expanded. If background compensation is activated, the background is subtracted from each individual frame.
Movie Mode
In this mode, a given number of movie pictures (single shots, as described above) are acquired. Each picture, as well as one integrated image, are saved. To ensure acquisition without gaps, the measured data is not displayed on-line.
If background compensation is activated, the background is subtracted from each individual frame.
Use this measurement mode e.g. to analyze dynamic wedges, or MLC fields.
On-line Mode
In this mode, single shots, as described above, are measured continuously and displayed on-line. Only the last five images are saved.
If background compensation is activated, the background is subtracted from each individual frame.
Use this measurement mode e.g. to trim the field parameters of the accelerator. By looking at the inline and crossline profiles, it is easy to check symmetry and flatness parameters in both orientations simultaneously.
Single Shot Mode
Click the toolbar button Measure.
After measurement is completed, the resulting image is displayed.
On-line Mode
Click the toolbar button Start On-line.
The images are displayed during the measurement.
When the treatment is finished, press Stop On-line t o s t o p t h e measurement.
The images are not saved.
Movie Mode
Click the toolbar button Start Movie. Start the treatment as planned.
When the pre-defined time has elapsed, the measurement stops. If you want to stop the measurement before the total time has elapsed, use the Stop Movie button After measurement is completed, the resulting image is displayed.
FILM OFFSET
Film and film-envelope produce an offset. When inserting films in a body phantom, other film planes or slices are shifted, due to the thickness of the films and their envelopes. When defining the offset information in the film setup, take into account the additional offset produced by the other films.
6. Edit the field information under the Field tab.
Click OK.
It is possible to save the measurement setup. Data for the selected scanner will be displayed in the Info Panel.
The resolution and bit depth options available for the connected scanner type are displayed.
3. Define Resolution, Bit depth, and Number of films.
RESOLUTION
In most cases the lowest resolution is sufficient, and should be used to minimize the amount of data.
Options for Vidar Scanners:
Use feeder: Option for Vidar scanners with multi film feeder. Mark the checkbox, and enter the number of films to be scanned, if you want to scan more than one film.
Autodetect film width:
Option for all Vidar scanners. If this option is selected, the scanner will detect the width of the inserted film before it starts to scan, and will stop the scanning process when the last line is reached.
AUTODETECT FILM WIDTH
The displayed progress bar will not be accurate if Autodetect film width is selected, since the height of the film cannot be estimated before the start of the scan.
AUTODETECT FILM WIDTH
Do not select Autodetect film width if part of the film is not irradiated.
The selection is persistent between sessions.
If the Autodetect film width option is not selected, the entire scan area will be scanned.
Eject film after scanning: If selected, the film will be ejected after the scan.
If not selected, the film will be automatically re-positioned for scanning.
Eject: Click to eject the film.
Light calibration:
Option for all Vidar scanners. Click this option to perform a light calibration. It takes 1 -2 minutes to perform the calibration. A progress bar is displayed.
Option for LumiScan Scanners:
Use film present sensor: Mark the checkbox to activate the function that handles information from the scanner's film detector.
FILM PRESENCE DETECTOR
If the scanner model used does not have a film presence detector, the I'mRT film present sensor will not receive the information that the film is inserted, and the message Film Not Inserted will appear. This applies for a few LumiScan scanner models. If this happens, uncheck the Use film present sensor checkbox.
7. Apply the scanner artifacts correction to that film using for the scanner and film calibration.
IMPORTANT NOTICE
Apply the calculated correction matrix always before performing the scanner/film calibration.
8. Perform the calibration as described in 7.9.5 Scanner Calibration and 7.9.6 Film Calibration.
ALWAYS USE THE CALCULATED CORRECTION FOR THE CALIBRATION FILM
Apply the calculated correction matrix always to the films used for the calibration procedure. The steps should be the follows: -Scan film.
-Correct the film with the correction matrix.
-Calibrate the film.
9. For applying the correction matrix open an image (or scan a film), and select it in the Film List by checkmarking. 10. Click Apply correction. The background data will be subtracted from the image. The name of the image will appear in green in the Film List.
11. Save the corrected image.
CAUTION DO NOT APPLY CORRECTION TO A SAVED FILE
The information that the image is corrected is not saved. To prevent that an image will be corrected more than once, do not apply this function to a saved file. 2. Insert the calibration film in the film magazine of the scanner. Orient the film so that the step with the lowest density is scanned first.
Setup of MatriXX for measurements
3. Select the Scan t a b , a n d p r e p a r e t h e s c a n i n t h e Task Panel (see 7.9.3.3 Prepare Scanning).
Define Resolution (the lowest resolution is sufficient for calibration) and
Bit depth. The default value for Number of films is 1.
Select scanner options. Click
Scan to perform the scanning.
OLDER TYPES OF VIDAR SCANNERS
For older types of Vidar scanners it is important that the film guides are closed as much as possible in order to avoid ambient light disturbing the calibration process. If the step film is narrower than the film guide opening, it needs to be attached to a larger sheet of film, or similar, which is not transparent to the light from the scanner. The scanned (Vidar and LumiScan scanners) or imported (external scanner) image will be displayed in the Display Panel.
SCANNER ARTIFACTS CORRECTION
If a correction for scanner artifacts will be appliedthis needs to be done before the calibration. Therefore please refer to chapter 7.9.4 S c a n n e r Artifacts Correction.
Select New calibration in the Task Panel:
Current date is automatically displayed in Calibration Info.
2. Enter the serial number of the step film, and the name of the operator.
Option: Enter additional information in the Comments field.
Define the step film properties in Options:
4. Enter the side length of the square to be used for ADC mean value calculation, in Measure area square side. 8. Position the cursor in the area with the lowest OD value in the step film image. Ensure that the cursor is positioned at half the step length from the border to next step (i.e. if the step length is 10 mm, position the cursor 5 mm below the border).
Setup of MatriXX for measurements
9. Select Load steps. All steps are automatically entered in the ADC column in the Calibration Data table.
If the step length in the step film varies, enter one step at a time. Position the cursor in a field, and select Add new step. Repeat for each step. Hold the <Shift> key to display the measuring area. It is strongly recommended to calibrate both the scanner and the film.
Save Calibration Data
Data is automatically saved in the OmniPro I'mRT main application when the dialog is closed. It is also possible to save data to the main application manually, by clicking the Send button in the Film List.
Load Template
The Load template function is similar to the Load steps function.
APPLY SIMILAR CONDITIONS
The calibration films, on which the template is applied, must be scanned under approximately the same conditions (orientation and size), otherwise the values will be read from the wrong positions. 11. Define the step film properties in Options i n t h e Task Panel (7.9.5.3 Calibration Procedure).
12. Right-click in the image, and select Show cursor in the context menu.
13. Position the cursor in the area with the lowest OD value in the step film image. The cursor must be positioned at half the step length form the border to the next step.
14. Click Load steps. All steps are automatically entered in the Calibration Data 19. Calibration data is automatically saved in the OmniPro I'mRT database when the Film Control Panel is closed. Data can also be saved by clicking the Send button in the Film List.
Scanner Calibration Workflow, External Scanners
Below is a summary of the workflow for external scanner calibration. For details, please refer to 7.9.5.2 Prepare Calibration and 7.9.5.3 Calibration Procedure.
1. Scan the calibration film according to the instructions for the external scanner 2. Save the image in .tif format.
3. Open the file in the Film Control Panel. The scanned image will be displayed in the Display Panel.
Select New calibration.
5. The current date is automatically displayed in Calibration Info. Enter the serial number of the scanner and the step film, and the name of the operator. Option: Enter additional comments in the Comments field. 11. Enter the density values, delivered with the step film, in the OD column in Calibration data.
12. Option: Click Find maximum to find the point with the highest ADC value. Enter the value with Add new step.
13. Option: Save the calibration te mp la te in th e Film Control Panel b y clicking Save template.
14. Option: Save calibration data in the Film Control Panel by clicking Save calibration (7.9.5.5 Save Calibration data).
15. Calibration data is automatically saved in the OmniPro I'mRT database when the Film Control Panel is closed. Data can also be saved by clicking the Send button in the Film List.
Setup of MatriXX for measurements
| 160 | P-07-002-510-001 06 OmniPro-ImRT System User's Guide 7.9.6. Film Calibration Film calibration defines the conversion factor between the Optical Density (OD) and absorbed dose. The calibration is dependent upon the type of film in use and how it was developed. The calibration is stored with the selected film type in the measurement setup. It is required that each film type has an individual calibration. For greater accuracy every film batch should be calibrated individually.
SENSITIVITY MAY VARY FROM FILM TO FILM
The sensitivity of radiographic films is strongly dependent on parameters like type, age, batch, or storage conditions. Perform a film calibration when using films where one or more of the above parameters differ from the film used for the current film calibration.
To perform the calibration, you can choose to use multiple films exposed to various dose levels or a single film exposed to multiple various dose levels, covering the range of interest (e.g. 0.0 to 3 Gy). 7.9.6.1.
Fog Determination
For fog determination, you can choose to scan an unexposed film, or use an unexposed part of a film with multiple exposed dose levels. Enter the dose value 0 to the corresponding optical density in the calibration table.
WARNING OD VALUES OUTSIDE FILM SCANNER CALIBRATION RANGE
If a film is calibrated or measured outside the film scanner calibration range, the measurement values can be incorrect. Never calibrate or measure a film outside the OD range for which the film scanner has been calibrated.
WARNING OD VALUES OUTSIDE FILM SCANNER CALIBRATION RANGE
If a film is measured outside the film calibration range, the measurement values can be incorrect. Never measure a film outside the dose range for which the film has been calibrated.
Mark the points on the scanned film, where you know the dose. The points will be added in the film calibration table with the optical density value. 7.9.6.3. Prepare Calibration 1. Place a single or multiple exposed developed film into the film magazine of the scanner.
2. Open the Scan tab in the Film Control Panel.
3. Define Resolution (the lowest resolution is sufficient), Bit depth, and Number of films, and select scanner options (see 7.9.3.3 Prepare Scanning).
Click
Scan to perform the scanning.
SCANNER ARTIFACTS CORRECTION
If a correction for scanner artifacts will be appliedthis needs to be done before the calibration. Therefore please refer to chapter 7.9.4 S c a n n e r Artifacts Correction.
1. Open the Calibration tab. The scanned image will be displayed in the Display Panel.
Select New calibration in the Task Panel:
3. Select Film in the Task Panel.
The current date will be displayed automatically.
4. Enter the film type, the batch ID, and the name of the operator. The points can be deleted or modified. Select Delete step or Modify step.
11. Data will also be graphically displayed in Calibration Graph. Doubleclick in the graph to enlarge the view. Double-click again to restore the original scale.
12. Option: Save calibration data in the Film Control Panel by clicking Save calibration. See 7.9.6.8 Save Film Calibration Data.
13. Calibration data is automatically saved in the OmniPro I'mRT database when the Film Control Panel is closed. Data can also be saved by clicking the Send button in the Film List. Select Overwrite in the dialog to save the calibration for the current film.
14. Select Print calibration to print the calibration table and graph.
MEASUREMENT POINTS
For a valid calibration you need at least three measurement points.
RECALIBRATION
Recalibration on a regular basis is recommended, due to variation in film quality, and especially due to variation when developing the film.
PREVIOUSLY SAVED FILMS
Recalibration will not change the measurement values on previously scanned and saved films. 7.9.6.5.
Film Calibration Templates
A film calibration can be saved as a template. The positions of the calibration points and the entered OD values are saved in the template, and will be used when the template is loaded for a new calibration.
.1. Save Template
Define the calibration points, and enter the corresponding OD values. Click Save template to save the calibration template as a .tem file.
Load Template
The Load template function is similar to the Load steps function.
APPLY SIMILAR CONDITIONS
The calibration films, on which the template is applied, must be scanned under approximately the same conditions (orientation and size), otherwise the values will be read from the wrong positions.
Open (or scan) the calibration film. Adjust it in the same way as the film in the calibration template that is going to be used.
Click Load Template, and select a template file (.tem).
When the template file is loaded, the position and dose value for each point is loaded, and the OD value is read from the image. A new calibration table is created.
Film Calibration Workflow, Vidar and LumiScan Scanners
Below is summary of the workflow for film calibration, with Vidar or LumiScan scanners. 5. Insert an unexposed film into the scanner, to make the fog determination (7.9.6.1 Fog Determination).
6. Select the Scan tab, and click the Scan button to perform the scanning.
7. Insert a single or multiple exposed developed film into the scanner (7.9.6.4 C a l i b r a t i o n P rocedure a n d 7.9.6.2 Optical Density to Dose Determination).
8. Click the Scan button to perform the scanning. The scanned images will be displayed in the Display Panel and in the Film List.
9. Select the Calibration tab, and expand Film in the Task Panel.
Select New calibration. For recalibration select Edit calibration.
11. The current date is automatically displayed in Calibration Info. Enter the serial number of the step film, and the name of the operator. Option: Enter additional comments in the Comments field.
12. Select the image of the unexposed film. Right-click in the image, and select Show cursor in the context menu.
13. Position the cursor at the point where you want to define the fog value (no dose).
Setup of MatriXX for measurements
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 165 | 14. Option: If a calibration template will be used, click Load template, and continue by saving the calibration data.
15. If no calibration template is used: Select the image of the exposed film. 21. Calibration data is automatically saved in the OmniPro I'mRT database when the Film Control Panel is closed. Data can also be saved by clicking the Send button in the Film List.
Select
Overwrite in the dialog to save the calibration for the current film. 7.9.6.7.
Film Calibration Workflow, External Scanners
Below is a summary of the workflow for film calibration, with an external scanner.
2. Save the image as a .tif file.
3. Scan a single or multiple exposed developed film into the scanner 12. Option: If a calibration template (7.9.6.5 Film Calibration Templates) will be used, click Load template, and continue by saving the calibration data.
13. Select the image of the exposed film.
14. Position the cursor at the point where you want to define the dose, and click Add new step.
15. Repeat for each point. 19. Calibration data is automatically saved in the OmniPro I'mRT database when the Film Control Panel is closed. Data can also be saved by clicking the Send button in the Film List (7.9.6.8 Save Film Calibration Data).
Select
Overwrite in the dialog to save the calibration is the current film.
Save Calibration Data in the Film Control Panel
Click Save calibration to save data in the Film Control Panel. The data will not be saved in the OmniPro I'mRT database. Data is saved as a .cal file.
Save calibration data in the OmniPro I'mRT database
Data is automatically saved in the database of the main application when the Film Control Panel is closed.
SAVE ADC TO DOSE IN THE FILM CONTROL PANEL
ADC to dose calibration must be saved in the Film Control Panel (Save calibration), and loaded (Load calibration) before use.
It is also possible to save data by sending it to the I'mRT Workspace: 1. Select the calibration image and click Send i n t h e Film List. The Importing data… dialog opens.
Apply Current Calibration to All Films in the Film List
The current calibration can be applied simultaneously to all films, calibrated as well as un-calibrated, that are displayed in the Film List.
CHECK LOADED CALIBRATION
When the Film Control Panel is opened, the calibrations for the selected scanner and film will be displayed in the Task Panel. Ensure that the correct calibration is loaded before applying it to the film.
1. Load the calibration that shall be used.
2. Click the button Apply the current scanner and film calibration to all films in the list in the Task Panel: The current calibration data will be applied, and displayed in the Info Panel.
RISK OF UNPREDICTABLE RESULTS
Applying a different calibration table on an already calibrated film can produce unpredicted results. 7.9.6.11.
Replace Calibration Data in a Calibrated Film
The calibration data embedded in a film can be replaced with the current calibration. Select the Calibration tab.
Select the film to which the current calibration data shall be applied, by marking the checkbox in the Film List. Click the Scanner or/and the Film Calibration button in the Info Panel. The embedded calibration data is displayed. Click the button Apply selected global calibration.
The current calibration data will be applied, and displayed in the Info Panel.
RISK OF UNPREDICTABLE RESULTS
Applying a different calibration table on an already calibrated film can produce unpredicted results.
Display and Modification of Images
To modify an image, and to change the display, select the Registration tab. 7.9.7.1.
Phantom Orientation
Expand Orientation in the Task Panel.
Film orientation: The orientation is displayed relative to the phantom, as defined in Equipment:Body Phantom Setup.
Phantom position (Rotation angle):
Select the rotation angle. The IEC coordinate system is used.
CAUTION CHANGE THE POSITION OF THE MARKER IF THE P H ANTOM IS ROTATED
The default orientation of the body phantom is as shown in the screen-shot above. If the phantom is rotated, the position of the marker should also be changed.
Distance from phantom origin to film markers: Define the offsets for origin and alignment points (the distance from the phantom origin to these markers). If the offsets are defined in Equipment:Body Phantom Setup, they will be displayed as read-only. The modification can be applied simultaneously on all films in the film list. Mark all checkboxes, and apply the modification. The Restore/Undo/Redo commands will be applied on the currently displayed film.
Crop
Select Crop. A square appears in the image. Define the cropping area by dragging the corners of the square. Select Apply.
To return to a previously cropped area, select Undo Crop.
To return to the original image, select Restore Original Film.
The modification can be applied simultaneously on all films in the film list. Mark all checkboxes, and apply the modification. The Restore/Undo/Redo commands will be applied on the currently displayed film.
Dose Unit:
The selected unit will be applied in all views and files.
Extract Channel: Select channel for import of RGB files.
Film Label: Define a name that will be used as film label in the Film List.
The default label is Film.
Length Unit: The selected unit will be applied in all views and files.
Measure Area Square Side: Define the area used for ADC mean value calculation (average value area).
MEASURE AREA IN CALIBRATIONS
The measure area used in calibrations is defined in the Options box in the Task Panel in the Calibration tab:
CORRUPT FILES
There are file types that are not secured via a check sum. If such a file has been corrupt by editing and manipulating the file, it will in most cases not be possible to import or open the file. However, in a few cases it may be possible to import or open a file that contains incorrect information. Never manipulate or edit files in a way not intended by the manufacturer! Always check the consistency of data!
LARGE FILES
Depending of the RAM capacity of the computer used, it may be impossible, or take very long time, to import very large files.
DICOM CONFORMANCE
OmniPro I'mRT is a co mmo n p la t fo r m fo r d ig i ta l , fi l m, a n d EP ID IMR T verification. To support these functions some of the radiotherapy objects (RT Plan, RT Image, and RT Dose), and the CR Image modality defined by the DICOM standard are supported for import. Please refer to the DICOM Conformance Statement [2] for details. See References. The document is available on the OmniPro I'mRT installation disk.
IMPORT OF DATA IN GRAPHIC FORMAT
Import of graphic files is restricted to 16 bit grey scale images, and any attempt to open an image with another bit depth will result in an error.
Since the files do not contain any calibration information, the current scanner and film calibration will be applied.
ORIENTATION OF ISOCENTER
The transformation of the coordinate system where the dose is stored to the gantry coordinate system is not possible from the dose information. Therefore a movement of the orientation might be done manually.
Import of Dose Planes and Dose Cubes
Select the menu command File:Import Data to import dose planes or dose cubes in the following formats:
Dose Planes
Dose plane is calculated 2D data. Select the menu command File:Import Data:TPS Dose Planes, or click the button in the toolbar.
Dose cubes
Dose cube is calculated 3D data. Select the menu command File:Import Data:TPS Dose Cube.
A window for TPS data import will open. In the left panel patient and data information, embedded in the imported image, will be displayed.
The panel to the right contains three tabs, Imported Data, Data Transformation, and Options, containing the functions and information needed for import and data transformation.
DICOM Import
Select the DICOM RTDOSE tab. The Import dose distributions in DICOM RTDOSE format dialog opens.
Data Import
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 179 | The orientation of the imported slice will be visualized in the coordinate system in the upper right corner of the dialog. The orientation of the coordinate system will be changed corresponding to the attributes from the imported DICOM data. It is not possible to import dose planes with different orientation at the same time.
The images will be displayed in the Image Preview box, with the original TPS orientation.
The images can be imported from file, via DICOMDIR, o r v i a T C P / I P (StorageSCP Service).
Select the Options tab and define the TCP parameters, and the logging directory (optional): Port number: 0 -65535.
Application Entity: Application entity title.
SPACES IN TITLE
Do not use spaces in the application entity title.
8.1.1.1. Import from a Local Data Source Select the Imported Data tab.
Click File to import files from your local data source.
A standard Open dialog opens. Browse for and select the required file. Click Open.
The file will be imported and displayed.
To continue, see 8. The StorageSCPService is a Windows service, which collects DICOM data via TCP/IP and saves it on the disk. The service is started at system start, so files can be collected even if the OmniPro I'mRT software is not running.
The TCP settings are changed in the Options dialog.
The collected data is displayed in the Collect list. Only RT Dose data is displayed.
Select the data to import. If Preview is selected, the data is displayed in the image list.
The imported data is automatically removed from the list. 3. Click Add, and select the requested CMS files.
Data Import
| 182 | P-07-002-510-001 06 OmniPro-ImRT System User's Guide The images will be displayed in the Image Preview box, with the original TPS orientation.
The orientation of the imported slice will be visualized in the coordinate system in the upper right corner of the dialog.
4. Select the Data Transformation t a b . C l i c k Change a n d e n t e r t h e distance from TPS origin to phantom origin. The changed data is reflected in Extensions.
Different offsets can be named and selected in Select previous or store existing offset. The selection of offsets will be persistent.
RTOG Import
Binary and ASCII RTOG files can be imported.
FILE NAMING
The directory file must end with zeros. The number of zeros determine the format of image files reference by their image number in the reference file. E.g. directory file name: aapm0000. If an image number in this is 12, the corresponding image file name has to be 'aapm0012'.
Select the Imported Data tab.
Click Directory File. A standard Open dialog opens.
The orientation of the imported slice will be visualized in the coordinate system in the upper right corner of the dialog.
Browse for, and select the directory file. All dose distributions in the file are displayed. Select a dose distribution in the list view.
The images will be displayed in the Image Preview box, with the original TPS orientation.
Select the Data Transformation tab. Click Change and enter the distance from TPS origin to phantom origin. The changed data is reflected in Extensions.
Different offsets can be named and selected in Select previous or store existing offset. The selection of offsets will be persistent. Select the Imported Data tab.
Click Add, and select the requested CadPlan files. Click Open.
Select the Options t a b . D e fi n e a c o o r d i n a t e s y s t e m fo r t h e T P S , a n d (optional) name the labels of the axes.
Click Change and enter the distance from TPS origin to phantom origin. The changed data is reflected in Extensions.
Different offsets can be named and selected in Select previous or store existing offset. The selection of offsets will be persistent. Enter the dose at 100%.
To continue, see 8.1.6 Send to I'mRT Workspace.
Select the Imported Data tab.
The icon in the upper right corner displays the TPS coordinate system.
Click File, and select the requested files. The images will be displayed in the Image Preview box, with the original TPS orientation.
Select the Data Transformation tab. Click Change and enter the distance from TPS origin to phantom origin.
The changed data is reflected in Extensions.
Different offsets can be named and selected in Select previous or store existing offset. The selection of offsets will be persistent. Choose if data shall be saved as Data set 1 or Data set 2.
Define the normalization value.
Tip! By default the Normalization is selected in such a way that 1 Gy becomes 100% in the OmniPro I'mRT main program. This means that the values displayed in OmniPro I'mRT can be interpreted as cGy (or rad). Film data may also be imported with a rescaling factor of 1 Gy = 100%. By this, the planned data and measured data can be compared without further rescaling.
Click OK. The imported data is displayed in the OmniPro I'mRT Workspace. A window for TPS fluence map import will open. In the left panel patient and data information, embedded in the imported image, will be displayed.
The panel to the right contains three tabs, Imported Data, Fluence Planes, and Options, containing the functions and information needed for import and data transformation. Select the Fluence Planes tab to edit SSD (Source to Surface Distance) and Depth (build-up).
Distance, i.e. the distance from the source to the fluence plane, will be calculated automatically.
If required, enter the value for the collimator Rotation and the Gantry angle.
IMAGE ROTATION
The imported fluence will be rotated in the same direction as the collimator is rotated (according to the definition in IEC 61217). The image will therefore appear to be rotated in the direction opposite to the specified angle. The definition of the direction of angles in I'mRT is in the other direction. Therefore the angle displayed in the Field tab and Modification tabs of the Parameter window will have the opposite sign. Select the compensator type. The selection is persistent between sessions.
Define the TCP port, and the logging directory (optional): Port number: 0 -65535.
Application Entity: Application entity title. These files shall be in the same folder or in a folder below the DICOMDIR file. Filenames must be 8 characters without extension.
Click the DICOMDIR… button.
Select the folder where the DICOMDIR file is. A list of data is displayed.
Only RTPlan data is displayed.
Select the data to import and click OK. The images are displayed in the image list.
To continue, see 8.2.5 Enter location.
TCP/IP Import (StorageSCP Service)
The StorageSCPService is a Windows service, which collects DICOM data via TCP/IP and saves it on the disk. The service is started at system start, so files can be collected even if the OmniPro I'mRT software is not running.
The TCP settings are changed in the Options tab.
Data Import
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 191 | The collected data is displayed in the Collect list in the Imported data tab. Only RT Plan with Compensator data is displayed.
Select the data to import. If Preview is selected the data is displayed in the image list.
The imported data is automatically removed from the list .
To continue, see 8.2.5 Enter location.
KonRad Fluence Import
Select the KonRad button. The Import fluence distributions in KonRad format dialog opens.
Click Add and select the requested files. The imported fluence map data is displayed.
TCP/IP Import (StorageSCP Service)
The StorageSCPService is a Windows service, which collects DICOM data via TCP/IP and saves it on the disk. The service is started at system start, so files can be collected even if the OmniPro I'mRT software is not running.
The TCP settings are changed in Options tab.
The collected data is displayed in the Collect list in the Import Data tab.
Only RT Image data is displayed.
Select the data to import. If Preview is selected, the data is displayed in the image list.
The imported data is automatically removed from the list.
To continue, see 8.2.5 Enter location.
Enter Location
Select the Image Planes tab to enter SSD and Depth (build-up).
Distance, i.e. the distance from the source to the fluence plane, will be calculated automatically.
If required, enter the value for the collimator Rotation and the Gantry angle.
IMAGE ROTATION
The imported fluence will be rotated in the same direction as the collimator is rotated (according to the definition in IEC 61217). The image will therefore appear to be rotated in the direction opposite to the specified angle. The definition of the direction of angles in I'mRT is in the other direction. Therefore the angle displayed in the Field tab and Modification tabs of the Parameter window will have the opposite sign.
To continue, see 8.1.6 Send to I'mRT Workspace. The coordinate system used is fixed to the collimator, with the x-direction in leaf movement direction (a row in the file is parallel to the x-axis), and the y-direction perpendicular to the leafs (a column in the file is parallel to the yaxis). The first row gives the x-coordinate of each column running from -x to +x. The first column gives the y-coordinate of each row running from -y to +y. The isocenter is at position (x = 0, y = 0). X Collimator (leaf movement direction) and Y Collimator (perpendicular to the leaves) are mapped one-to-one to X IEC and Y IEC .
IMPORTANT NOTICE COORDINATES
If the file is viewed without using the coordinates given in the first row and column, you have to keep in mind the following fact: the y-coordinates are increasing with increasing row number, with the consequence that the rows have to be mirrored to get the correct coordinate system layout (x pointing to the right, y pointing upward).
Error Messages
Error messages are displayed as follows: 1st row: Name and path of the erroneous file.
2nd row: The number of the line where the error occurred, and the error number.
3rd row and forward: Descriptive text.
The following error messages may occur during the import of BrainLAB files: Error # Text Description / Possible cause 1 Unexpected symbol: "symbol 1" Expected: "symbol 2" The format of the file is not correct as symbol 1 was found, whereas symbol 2 was expected in the given line.
"Token" expected
The format of the file is not correct as the Token was expected but not found in the given line.
Error when reading Object
A general error occurred when reading the named Object. Either the error cannot be specified in more detail, or the error is displayed in addition to a previous error.
8
"Type" not supported The file has a valid format, but contains objects that are not supported by the import component. Direction and length unit of horizontal values inside the plane. The direction must be the first direction of the plane type defined in the header.
FLUENCE MAP IS SET TO ABSOLUTE DOSE
The length unit must equal the one defined in the header.
Optional. If set, the next line below must also be entered. Positions in the first direction All positions in the first direction in the defined length unit.
Optional. If not set, the "Spacing" value from the header is used, and the data is centered horizontally. n: Numbers separated by the Separator defined in the header, where n must be the number of columns as defined above. Positions in the second direction + data values The first value in each row is the position in the second direction in the defined length unit.
The subsequent numbers are the data values in the unit defined in the header.
1 Number (optional), followed by n numbers, separated by the Separator defined in the header each.
n must be the number of columns as defined above.
*)
*) The line above is repeated x times, where x must be the number of rows as defined in the header. The user interfaces of the ASCII and the BrainLAB Import look exactly the same. They only differ in the header information that is displayed.
Identifier
File Name and Path display the file name and folder location of the files selected for import.
In the pane to the right of the File Selection pane, header information on the selected file is displayed. If more than one file is selected, the pane displays the text Multiple Selection. If a file that has not the appropriate format is selected, the text File has an invalid format is displayed.
The preview of the selected file can be switched on or off, by marking or unmarking the Preview checkbox. The loading time of large files can be reduced by switching the preview off.
The preview pane displays a preview image of the currently selected file and the coordinate axes. If the Preview checkbox is unchecked, or more than one file or a file containing more than one plane is selected, the preview pane is empty.
Select import as a 3d cube or as single planes with the radio-buttons Import as Cube and Import as Planes.
This image shows the target coordinate system in OmniPro I'mRT, which is always according to IEC-61217.
The Add File(s) button opens a standard Open dialog.
The Remove button removes the selected files from the list. The format of the file is not correct, as symbol 1 was found whereas symbol 2 was expected in the given line.
"Token" expected
The format of the file is not correct as the Token was expected but not found in the given line.
Macros
Several operations for data modification can be combined in a macro. The macro may be applied to one field or to a whole field list.
The parameters displayed below can be combined in a macro. To display the flatness marker, select the right-click command Show markers. Two horizontal lines are displayed at the chosen dose levels.
Function
To display symmetry and flatness values, select the right-click command Profile analysis.
PARAMETERS MEASURED UNDER NON-REFERENCE CONDITIONS
Dosimetry protocols define the reference conditions for the determination of symmetry or flatness. Definition of water as medium, a certain depth, and a certain field is required, and also the type of detector to be used may be specified. If measuring under different conditions (e.g. when using I'mRT QA/BIS in air), these parameters may differ from those measured under reference conditions.
To edit or change the protocol for penumbra and field width parameterization, select Tools:Options and choose the 1D-Options tab in the dialog.
To edit or change the protocol for flatness or symmetry parameterization, select the Tools:Options command and choose the 1D-Options tab in the dialog.
Build a 3D Cube
Film data is 2D data. If this 2D data shall be compared with calculated 3D Dose distributions the measured 2D data must first be converted into 3D data.
To create a 3D cube of measured or imported data you need several images of the same measuring type with different offset values. These images then are "piled on each other" to build the 3D cube.
SINGLE 2D SET
It is also possible to convert just one single 2D set (e.g. one film) into 3D dose format. Select the order of calculation (dataset 1 vs. dataset 2, or vice versa).
DISSIMILAR RESOLUTIONS
When the two datasets have dissimilar resolutions, the results may also be slightly dissimilar.
Use the Export Results command to export the Result data as an opd file (OmniPro I'mRT data).
COMPARING HIGH AND LOW RESOLUTION DATA
When comparing two matrices with different resolution, the high resolution data (this is typically the scanned film data) should be in data set 2, the lower resolution data (typically the imported data from treatment planning system) in data set 1. This speeds up the calculation and prevents interference-like patterns in the gamma matrix.
GAMMA CALCLULATION
To evaluate the result of a gamma calculation, the palette should be switched to Gamma. (Use the right-click command Change Palette). The palette range should be 0% to 125% (set the range in the Palette Range dialog). The color turns to red at the selected upper threshold value. 100% is equal to the gamma value 1.
The delta dose and delta distance values are displayed in the caption of the result view. 9.5.6.1.
Practical usage of the Gamma Method
The most common method to verify calculations vs. measurements is the Gamma method. Therefore a workflow for using the Gamma method in a correct way is described: 1.) Import the plan, perform the measurements.
Data Analysis
| 246 | P-07-002-510-001 06 OmniPro-ImRT System User's Guide The screenshot shows the measured field in data set 1 and the imported dose plane in data set 2.
2.) Convert the grid of the imported TPS dose plane to the resolution of the MatriXX. With this step it is simulated what the MatriXX should "see". This step is required as the MatriXX has a resolution of 7.62 mm while TPS calculates with a resolution of 1 mm (in this case).
If the used linac has an even number of leaf pairs, the use of the centre adaption Align edges (2 centre lines) is recommended. For an odd number the Centre A daption " A l i g n c e n t r e ( o n e c e n t r e l i n e ) " i s r e c o m me n d e d . Centre Adaption is required especially when the grid resolution is reduced. Please check the effect on a square field (plan import). A shift of the field can be seen for grid conversion to lower resolution with no centre alignment.
3.) Convert the grid of the TPS data and the measurements to a higher resolution (1mm for example).
Data Analysis
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 247 | The reason for the convert grid to a higher resolution is the discrete Gamma calculation in OP I'mRT (the number of measurement points are evaluated).
Please use the settings like in the screenshot above.
The reason for this normalization step is the fact that OmniPro I'mRT is using the normalization v a l u e t o c a l c u l a t e t h e Δ G a m m a v a l u e .
5.) Analyzing
For analyzing the profile cursor as well as the histogram is available. Please refer to chapter 9.4.2 Profile and 9.5.4 Histogram.
OPEN TWO DATA SET FILES
To perform the operations described below, it is necessary to open two data set files. Normally this will be the measured data in one data set, and an imported dose cube from TPS in the other data set.
2D DATA SET AND 3D CUBE
It is not possible to compare a 2D data set with a 3D dose cube. The 2D data must first be converted to a 3D cube. See 9.4.3 Build a 3D cube.
Click the toolbar button to switch to 3D Plan verification view. 9.6.1. Difference to 2D In Plan 3D Verification you can perform the same operations as in 2D. The difference is that you can choose which plane to view, and that it is possible to move through the different planes, step by step.
To select a plane with another orientation, click XY, XZ, or YZ.
To select a plane with another offset, drag the slider.
If you want to synchronize the views, click . The profile cursors, the plane orientation, and the offset of the selected plane will be synchronized. P-07-002-510-001 06 | 267 | 2. After selecting a patient, step through the buttons in the iViewGT Browser to make your selection of images.
Patients: Activates a search for the Search for patients dialog.
Treatments: Shows the active treatments associated with a patient.
Fields: Shows the fields belonging to a treatment.
Images: Shows the images belonging to a field. Observe that an image can consist of several frames.
The image pixels are renormalized before they are saved in the database. The scaling factor is displayed in the column Pixel factor.
Example:
If 100 image frames were integrated at acquisition time during delivery of an I'mRT segment, a typical maximum brightness in this raw accumulated image might be 2 500 000 pixel units. Before saving into the database, the pixel values are renormalized in this accumulated image to give maximum brightness of, typically, 40 000, so all pixel values would be multiplied by 0.016. This is the value of the pixel factor.
COMPOSED IMAGE
In the case of a composed image, the pixel factor is not available until the user wants to visualize this image.
A checkbox is placed in the table associated to the images. This checkbox is used for marking images to be composed or to be sent to the I'mRT application.
View selected images: Click this button to display the selected images in the pane beside the button. To remove an image, right-click in it and select Remove image i n t h e c o n t e x t m e n u t h a t a p p e a r s . T h e corresponding checkbox will become unmarked. You can also remove an image by unmarking the corresponding checkbox.
You can add images from other patients, treatments, and fields, and send them simultaneously.
If an image is composed of several frames, an arrow (expand/collapse) button will be shown at the left side of the image. Each individual frame can be previewed. If you click on a frame in the preview window, the frame will be displayed in the right side of the browser (image holder). If you left click with the mouse on any image in the image holder, a new image dialog will be displayed. The left mouse button gives you a zoom function.
. Compose Images
Compose images: This button allows you to compose images. All images with a marked checkbox will be composed to a single image.
In image composition, a max internal scale factor is used. Observe that an image does not hold an absolute dose.
During image composition, all images/frames are calculated with a renormalization factor and scaled relative to each other.
Send Images to the Main Application
Send: All images with a marked checkbox will be transferred to the OmniPro I'mRT application for further analysis. It is possible to select images from different treatments, fields, or patients, and send them simultaneously. If an image consists of frames, a dialog will be shown, asking if the frames shall be transferred to the I'mRT application.
The image data is normalized before it is sent to the main application. The pixel value, read from the image, is divided with pixel factor, resulting in a 32 bit pixel value. A median filter is applied so that the bad pixels are not taken into account for the calculation of the maximum value. Thus they have no influence on the rescaling factor, but they are not removed from the image.
Set origin:
If the origin of the image was not set in the database, the Set origin dialog will open when you click the Send button. This dialog gives you the option to set the origin in the centre of the image, before it is sent.
Close and Log Out
Close: The iViewGT Browser dialog will be closed, but the username and password are remembered for the next dialog usage.
Logout: The iViewGT Browser dialog will be closed and you will be logged out. You need to enter the username and password the next time you open the dialog.
CORRECT ELEKTA IVIEWGT SOFTWARE VERSION
You must ensure that you use the correct version of Elekta's iViewGT software. The version must contain an image renormalization factor.
CONNECT TO THE CORRECT DATABASE
You must ensure that you connect to the correct database. It is possible to set up/configure multiple ODBC drivers.
VERIFY PATIENT SELECTION iViewGT Browser
OmniPro-ImRT System User's Guide P-07-002-510-001 06 | 269 | You must ensure that you select the correct patient, treatment, fields, and images. The current selection is displayed in the upper part of the iViewGT Browser dialog.
DOSIMETRY LIMITATIONS
You must be aware of the dosimetry limitations of the image information given from the iViewGT.
CORRECT IMAGE TYPE
For I'mRT verifications you must ensure that you are using the correct image 12.1.1.2. Moving the Database
REINSTALLATION REQUIRED
Change of the location of the database requires reinstallation of the program. The existing database can be copied over the newly created database after installation, or copied there before installation (will not be overwritten).
To move the database to another location (after the initial installation), follow the steps below:
Cleaning
To clean the housing of the device, use a soft, dry duster, moistened with a cleaning agent. Do not use organic solvents.
Use dry compressed air to clean the connectors on the rear side of the device, and the cable connectors.
Repair
Extremely low-current devices, like ion chamber detectors, require special knowledge and tools. Do not try to repair MatriXX yourself, but return it to IBA Dosimetry.
Recalibration
MatriXX needs recalibration, please return it to IBA Dosimetry. Cross-over cable not used for direct connection to the computer.
Use cross-over cable.
Adapter is used for connection. Do not use adapters (e.g. USB-Ethernet converter) for connection.
Ethernet cable / pins are broken or defect.
Network socket is defect.
Network (cable) defect or is not compatible with CAT-6.
Ethernet port blocked by other application
Check if the Ethernet port is available.
Recommended cable length exceeded.
Use an Ethernet minihub and ping the device.
The Ethernet port can be deactivated if a battery-powered laptop is used.
Check power administration.
Firewall is active and blocks communication.
Deactivate the firewall.
Device cannot be found by the computer / is not communicating The laptop has a WiFi interface. Verify that the wireless internet connection is turned off. Impossible to install / modify / set up the device on the computer.
Operator does not have administrator rights.
Log-on with administrator rights before the program is started.
XX Setup tool not accepted by the local network Network firewall settings.
Add the XX Setup tool to the list of applications that are allowed access to the network. Problems with the isscript-file installation.
Right click the isscript.msi from the OmniPro I'mRT installation disk, and select Install. A wizard will guide you through the installation.
The administrator on the local computer has no access to the network location where the database shall be located.
Log in as local administrator, and install the program and the database locally on the computer.
Log in as user with network access.
Create a folder on the network. Map the folder to a driver letter (same letter for all users) Move the database to the new location.
Configure the ODBC data source, see 12. Measured film data are 2D distributions, 3D dose cubes are 3D data. 2D Data must be converted to a 3D cube first.
Select the film data.
Set the Offset for each film.
The result of a gamma-calculation shows an interference pattern Data with high resolution (typically filmdata) in Dataset 1, data with low resolution (typically planned data) in Dataset 2.
Open the low resolution data in Dataset 1, and the high resolution data in Dataset 2.
or Use data with similar resolution.
Lost "old" data set? If a new measurement /import is performed while another data set is already open, the "old" data set disappears from the pane.
All fields are found in the in the Field list. No data is lost.
Open the Field list dialog.
Select requested field from the list. This field is displayed in the data set pane(s).
If saving the data set the new data will be saved as new fields in the same field list as the old ones. Max quotient in dose between two points on equal distance from central axis, within flattened area defined as in item The profiles are internally and individually normalized to 100%. The fit works on left and right penumbra zones (e.g. 10% -90% area). The width shall be equal on both sides.
14. x: x-distance between C1 and C2 (equals x-distance between C3 and C4) x1: x-distance between C1 and Si (equals x-distance between C3 and Si) x2: x-distance between Si and C2 (equals x-distance between Si and C4) y: y-distance between C1 and C3 (equals y-distance between C2 and C4) y1: y-distance between C1 and Si (equals y-distance between C2 and Si) y2: y-distance between Si and C3 (equals y-distance between Si and C4) The interpolation is done in three steps:
Applicator
Extended collimator used for electron fields, also called Cone or Tube.
Array
Presents the Data set pane in a 2D array view.
ASCII American Standard Code for Information
Interchange; a code for information exchange between computers made by different companies.
Background
The signal of a measurement device without any beam.
BIS
Beam Imaging System. IBA Dosimetry provides three beam imaging systems: I'mRT QA, BIS 710, and MatriXX.
BIS2G
A 2D detector array by IBA Dosimetry, sold until 2nd quarter 2003 under the product name BIS2G. The new product name is I'mRT QA.
Its predecessor was the BIS 710.
In this manual the term I'mRT QA/BIS is used in information that applies to both I'mRT QA and BIS 710.
BIS 710
A 2D detector array by IBA Dosimetry.
In this manual the term I'mRT QA/BIS is used in information that applies to both I'mRT QA and BIS 710. DTA Distance To Agreement. The DTA is the distance between a dose point in the calculated distribution and the nearest point containing the same dose value in the measured distribution.
dpi Dots per Inch. A unit used to describe the resolution of scanners.
Field
Radiation Field. One single dose distribution. One or more fields can be saved in one Data set.
Film calibration
With the help of a number of films, irradiated with known doses, the optical density can be calibrated to dose.
Fixture
Attachment in-between the BIS and the treatment head, allowing the servo to rotate with the gantry.
Fog
The optical density of an unexposed but developed film.
Frame grabber
A PCI card mounted in the computer: It acts as an interface between the BIS and the OmniPro I'mRT software.
FW
Field Width.
Head mounted
Fixed to the gantry (head).
I'mRT QA
A 2D detector array by IBA Dosimetry, sold until 2nd quarter 2003 under the product name BIS2G. The new product name is I'mRT QA.
In this manual the term I'mRT QA/BIS is used in information that applies to both I'mRT QA and BIS 710.
I'mRT MatriXX
A 2D detector array by IBA Dosimetry.
Isocenter
Rotation centre for the gantry.
Isodose
Points with the same dose value.
MatriXX Evolution
A 2D detector array by IBA Dosimetry, especially intended for rotational techniques.
MeV
MegaelectronVolt, a unit used for the nominal or real energy of a beam consisting of charged particles (electrons, protons).
Complaint Reports
This section contains three copies of Complaint Report, OmniPro I'mRT, and three copies of Complaint Report, MatriXX.
Always keep one copy of the form. If needed, make more photocopies of the form. If there is no form, make a written report describing the fault with as much detail as possible. Please always include your name, address, email, phone, and the license number (found in the About box of OmniPro I'mRT).
The user shall report all complaints about the system to any representative of IBA Dosimetry, or directly to: | 33,710.6 | 2014-01-07T00:00:00.000 | [
"Medicine",
"Physics"
] |
Infrared Perfect Ultra-narrow Band Absorber as Plasmonic Sensor
We propose and numerically investigate a novel perfect ultra-narrow band absorber based on a metal-dielectric-metal-dielectric-metal periodic structure working at near-infrared region, which consists of a dielectric layer sandwiched by a metallic nanobar array and a thin gold film over a dielectric layer supported by a metallic film. The absorption efficiency and ultra-narrow band of the absorber are about 98 % and 0.5 nm, respectively. The high absorption is contributed to localized surface plasmon resonance, which can be influenced by the structure parameters and the refractive index of dielectric layer. Importantly, the ultra-narrow band absorber shows an excellent sensing performance with a high sensitivity of 2400 nm/RIU and an ultra-high figure of merit of 4800. The FOM of refractive index sensor is significantly improved, compared with any previously reported plasmonic sensor. The influences of structure parameters on the sensing performance are also investigated, which will have a great guiding role to design high-performance refractive index sensors. The designed structure has huge potential in sensing application.
Background
In recent years, plasmonic metamaterials have attracted increasing interest owing to their potential applications in high sensitive photodetection [1], hot electron collection [2,3], and biosensing [4][5][6][7][8]. Perfect narrow band absorber based on plasmonic metamaterial is a rapidly developing area of research owing to their various applications in energy harvesting [9][10][11][12][13][14] and thermal emitters [15][16][17][18]. The localized surface plasmon resonance (LSPR) is attributed to collective behavior of electrons as the incident wave interacts with metallic nanostructures. Due to the excellent characters of LSPR in confining light at the nanoslit and transforming it into thermal energy, metallic metamaterials possess a great advantage to design absorber. So far, various perfect absorbers have been designed and demonstrated over different frequency ranges. Landy designed and demonstrated the first perfect metamaterial absorber consisting of two electric ring resonators [19]. Tao proposed and experimentally demonstrated a terahertz metamaterial absorber working over a wide range of angles of incidence, which consists of two metallic layers separated by a dielectric layer [20]. A perfect absorber is designed by Hedayati in the visible region by a combination of a metal film with suitable metal-dielectric nanocomposites [21].
When the plasmonic metamaterial structures are surrounded by gas and liquid, a spectral shift of the resonance wavelength can be occurred due to the change of refractive index of environment. Thus, in practical application, narrow band absorbers are often used as biosensor, owing to the narrower band to improve the sensing performance. In designing sensors, the wavelength sensitivity (S) and the FOM are generally used for evaluating their performance, where the sensitivity and figure of merit are defined as S = Δλ/Δn, FOM = S/ FWHM respectively. The Δλ is the resonance wavelength change of reflectance spectrum, which results from the refractive index change of surrounding environment, and FWHM is the full width at half maximum of the reflectance spectrum. As we all know, the higher FOM of refractive index sensor means the bio-sensor with better performance of molecule detection. Thus, it is very meaningful to design an ultra-high FOM refractive index sensor with a simple structure. Unfortunately, the previously reported plasmonic sensors based on metamaterial structure generally have a relatively low FOM <600 [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39], which will severely limit their further development and application. Shen designed a gold mushroom array structure with a narrow FWHM of 10 nm and a high FOM of 108 [22]. Liu designed a crossshape patch array structure with FWHM of 12 nm and S of 538 nm/RIU [23]. Lin proposed and analyzed based on bowtie nanoantenna arrays (BNAs) with a FOM of 254 [24]. Lu proposed a nanolit microcavity-based structure and demonstrated a narrower FWHM of 8 nm and a FOM of 25 [25]. Li designed and investigated a plasmonic sensor with a FOM of 120 based triple-band metamaterial [26]. Recently, Srekanth proposed a plasmonic refractive index sensor based on a hyperbolic metamaterial with a FOM of 590 [27]. So, the plasmonic sensors based on metamaterial structure in most previous studies are either complicated or have lower FOM.
In this paper, we demonstrate a novel and easily fabricated plasmonic ultra-narrow band absorber based on a two-dimensional metal-dielectric-metal-dielectric-metal (MDMDM) periodic structure, consisting of gold nanobar array and a gold thin film separated by a dielectric layer operating at the near-infrared region. As a plasmonic refractive index sensor, the structure has a high wavelength sensitivity of 2400 nm/RIU as well as an ultra-narrow absorption bandwidth (FWHM) of 0.5 nm. Thus, the FOM of the proposed plasmonic sensor can reach 4800. As far as we know, this is the highest FOM compared with previously reported plasmonic refractive index sensor [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. In order to evaluate the sensing performance of the plasmonic structure, we also investigate the sensitivity of the plasmonic sensor dependence on different structure parameters. By adjusting the structure parameters, the optimized absorption peak or FWHM can be achieved. Moreover, compared with previously reported plasmonic sensor, the metamaterial is simple in structure and easy to manufacture. Importantly, owing to the ultra-high FOM, the LSPR-based sensor possesses huge potential in biomedical and chemical fields. Figure 1a illustrates the designed geometry of the metamaterial structure, which consists of gold nanobar periodic array on a thin gold film separated by a dielectric layer. The cross section of the designed structure parameters are shown in Fig. 1b. The gap d between two nanobars in one unit cell is d = 20 nm. And other structure parameters include top layer nanobar width w 1 = w 2 = w, nanobar thickness t 1 , dielectric layer thickness t 2 , gold film thickness t 3 , and period p. In the infrared region, permittivity of gold can be reasonably characterized by the Drude model. The refractive index of the MgF 2 layer is set as 1.37. The proposed structure is investigated by changing the surrounding refractive index and measuring the absorption spectra.
Methods
To investigate the sensing performance of the designed structure, we apply two-dimensional finite-difference timedomain (FDTD) simulation in calculations. In our simulation, we set period boundary conditions in the x direction. The optimized geometric parameters of the sensor are set as follows: w = 360 nm, t 1 = 20 nm, t 2 = 10 nm, t 3 = 25 nm, t 4 = 170 nm, t 5 = 100 nm, and p = 2400 nm. A plane wave is normally incident onto the sensor along the -z direction, with its electric field E along the x direction. Because the thickness t 5 of the gold film is thick enough to forbid the transmission of the incident light (T = 0), the absorption could be simplified to be A = 1 − R.
Results and Discussion
The characteristics of the simulated absorption and reflection spectra of the designed structure are very important to evaluate the sensor performance. The absorption spectra at normal incidence for different polarization configurations are studied and shown in Fig. 2a. It is easy to observe that there exists an absorption peak for the TM polarization and no absorption occurs for the TE polarization. This feature can be well explained by the asymmetrical structure of the metamaterial. As shown in Fig. 2a, for TM polarization configuration, when the refractive index of the sensing material is 1.02, the resonance absorption peak of the structure is found at 2449.87 nm with FWHM of 0.5 nm, which is much narrower than previously reported plasmonic refractive index sensor [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. The magnetic field H and electric field E distributions at resonance are calculated Fig. 2b, c, respectively. Figure 2b illustrates that the magnetic field mainly locates in the dielectric spacer among two gold nanobars and the thin gold film, which indicates the coupling effect of the nanostructures caused by LSPR. To better interpret the physical mechanism of the plasmonic absorber, the absorption spectrum is compared between the designed structure and metallic grating structure (see insert of Fig. 2d) in Fig. 2d. The absorption peak of the designed structure is obviously higher than that of the metallic grating structure. The magnetic field H and electric field E distributions of the metallic grating structure are The magnetic field distribution and c the electric field distribution at the resonant wavelength of the structure. d The comparison chart of absorption spectrum between the designed structure and metallic grating structure. e The magnetic field distribution and f the electric field distribution at the resonant wavelength of the metallic grating structure. g Simulated absorbance spectra when the damping constant of the gold film is two and three times that of bulk gold presented in Fig. 2e, f, respectively. As shown in Fig. 2e, the magnetic field is concentrated in the surface of the gold nanobars. Then, compared with the magnetic field of the designed structure coupled into the dielectric layer in Fig. 2b, the metallic grating structure will theoretically have a poor performance in absorbing ability, which is consistent with the calculated results in Fig. 2d. Therefore, we attribute the ultra-narrow band absorption to the excitation of LSPR between each element in the designed structure. In addition, due to the grain boundary effects and the surface scattering in real thin films, the damping constant of the gold film is likely higher than that of bulk gold [23,40]. To take this effect into consideration, we also calculate the absorption spectra for damping constant of two and three times that of bulk gold. As shown in Fig. 2g, absorbance peaks with different amplitude and FWHM are observed. The material loss would deteriorate the performance of the designed narrowband absorber [23,40]. The coupling behavior in the metamaterial structure also can result in the enhancement of electric field intensity. Figure 2c shows that nearly all the electric field is confined to the nanoslits between gold nanobars and the thin gold film and the electric field intensity in extremely tiny volume is about 11 times larger than the incident waves, which have great potential applications in hot electron generation and biosensor.
As shown in Fig. 3, the influences of materials in dielectric layer on the reflection spectrum are investigated. Figure 3a shows that, when the refractive index of dielectric is increased from 1.1 to 1.8, the resonant wavelength of reflection spectrum redshifts slightly. We provide a comparative analysis of the reflection spectrum using three common dielectric materials (MgF 2 , SiO 2 , Al 2 O 3 ) as shown in Fig. 3b. The plasmonic sensor using MgF 2 can achieve the better sensing performance than sensors used SiO 2 and Al 2 O 3 , due to the narrower FWHM and lower reflectivity dip. Figure 3c shows a blueshift of resonant wavelength with the thickness t 2 of the dielectric spacer increased. At the same time, the reflection dip and FWHM decrease with decreasing the thickness t 2 shown in Fig. 3d. This feature can be explained that the LSPR is enhanced with the decrease of distance between gold nanobars and gold film. The dielectric spacer with a thickness about 10 nm can be manufactured with standard fabrication techniques [41]. The FWHM and reflectivity dip of the reflection curve depend strongly on the coupling strength between the nanobars and the gold film. Thus, the sensing performances are different with various dielectric materials and thickness of dielectric spacer. Fig. 3 a, b The dependence of reflective spectra of the designed structure on the index of dielectric. c The resonance wavelength as a function of dielectric spacer thickness t 2 . d Reflectivity of the resonance dip and FWHM as functions of dielectric spacer thickness t 2 Figure 4 shows influence of structure parameters on the reflectance spectrum of the proposed metamaterial structure. According to Fig. 4a, when the nanobar thickness t 1 varies from 10 to 30 nm, the resonant wavelength blueshifts obviously. The resonant wavelength of reflectance spectrum redshifts slightly as the nanobar width w increases from 340 to 370 nm depicted in Fig. 4b. Figure 4c presents a blueshift of resonant wavelength with the distance between two nanobars d increased from 15 to 50 nm. Figure 5 presents the effects of structure parameters on the reflectivity dip and FWHM. Figure 5a shows that the reflectivity of the resonance dip decreases first and then increases obviously with the increase of the thickness of gold nanobar, and the value of FWHM remains at a certain level first and then decreases as the thickness t 1 increases from 10 to 30 nm. As shown in Fig. 5b, when the nanobar width w is 363 nm, the reflectivity dip is minimum, and the minimum value of FWHM can reach up to 0.36 nm when the nanobar width w is 348 nm, which is far narrower than any previously reported plasmonic sensor. In Fig. 5c, it is easy to observe that the reflectivity is strongly dependent on the distance between two nanobars and the reflectivity of the resonance dip increases obviously when the distance d changes from 15 to 50 nm. This characteristic can be attributed to the reduction of coupling effect between two nanobars with the increase of d and then the absorption is weakened. FWHM changes slightly when the distance d increases. In practical application, it is generally known that lower reflectivity and narrower FWHM of reflection spectrum is required to enhance the performance of refractive index sensor. From Fig. 5, the optimal value of FWHM and reflectivity cannot be simultaneously obtained. However, in our design, the FWHM changes slightly and the reflectivity of the resonance dip remains low in a wide range, which is favorable to practical application owing to its outstanding robustness.
As shown in Fig. 2b, the high absorption is caused by the magnetic resonance resulting from LSPR. The equivalent LC circuit model can be used to explain the characteristics of the reflection resonant dip in this work [42][43][44][45][46]. Here, the mutual inductance L m of the gold nanobars and gold film can be represented by L m = 0.5 μ 0 wt 2 , where μ 0 is the permeability of surrounding environment [44][45][46]. Owing to the contribution of the drifting electrons to the inductance, the kinetic inductance L e is given by L e ¼ w= , where γ is a factor considering the effective cross-sectional area of the gold nanobars, ε 0 is the dielectric permittivity of surrounding environment and ω p is the plasma frequency of the gold [44][45][46]. On the other hand, the gap capacitance C g ¼ πε 0 = ln d=t 1 ð Þ is used to represent the capacitance between the two nanobars. The parallelplate capacitor C m between the upper gold nanobars and the gold film is expressed as C m = c 1 ε 2 ε 0 w/t 2 , where c 1 is a numerical factor accounting for the non-uniform charge distribution at the metal surfaces and ε 2 is the dielectric permittivity of dielectric spacer. According to the equivalent circuit model in Fig. 6, the total impedance is expressed as [44][45][46] Then, the resonance wavelength can be obtained by zeroing the impedance. From the magnetic field distribution shown in Fig. 2b, the coupling between the two gold nanobars is much weaker than that between gold nanobars and the gold film, due to the large gap between the nanobars. When C g is less than 5 % of C m , the effect of C g can be neglected. Then, the resonance wavelength of the structure can be obtained by [45] where L m ¼ 0:5 μ 0 wt 2 ; L e ¼ w= γε 0 t 1 ω 2 p and C m = c 1 ε 2 ε 0 w/t 2 . The relationship between resonance wavelength Fig. 4 The reflectance spectrum as a function of top layer nanobar a thickness t 1 , b width w, and c the distance between two top layer nanoribbons d, respectively. The refractive index of the surrounding environment is set as 1.02 and structural parameters (nanobar width w, nanobar thickness t 1 , dielectric spacer thickness t 2 ) can be predicted approximately by Eq. (2). In the LC model, obviously, the resonance wavelength λ r increases with increasing the w and ε 2 . The larger t 2 will cause smaller values for L e C m , while the other term L m C m is independent on the t 2 . Similarly, larger t 1 will lead to smaller L e C m and the other term L m C m is also independent on the t 1 . Thus, the resonance wavelength λ r decreases with increasing the thickness t 1 and t 2 . These predicted resonance wavelengths are in good agreement with the simulated results on the influence of n dielectric , t 2 , w, and t 1 shown in Figs. 3a, c and 4a, b. The d can only influence the value of C g ¼ πε 0 = ln d=t 1 ð Þ . Owing to the weakness of C g , the effect of d on resonance wavelength λ r may be extremely slight, which matches the simulated results shown in Fig. 4d quite well.
As is well known, the resonant wavelength of plasmonic nanostructures is dependent on the refractive index of the surrounding dielectric environment, a property that has been widely utilized for sensing applications. According to Eq. (2), the term L m C m will increase with increasing the dielectric permittivity ε 0 of surrounding environment and L m C m is independent on the ε 0 . Therefore, the resonance of reflection redshifts as the refractive index of surrounding environment increases in the LC model. Then, the sensing characteristics of the designed metamaterial structure are investigated in Fig. 7. According to Fig. 7a, b, the resonance of reflection redshifts as the refractive index of surrounding environment increases. Particularly, in Fig. 7c, the blue to green curves present resonant wavelength of 2449.8 to 2450.1 nm when the surrounding refractive index changes from 1.0200 to 1.0201 with a step of 0.0001. It is easy to observe that this plasmonic sensor can detect a very small change of refractive index of surrounding environment. As shown in Fig. 7d, the sensitivity (S) of the sensor is 2400 nm/RIU, while FWHMs can be narrower than 0.5 nm. Therefore, the FOM of the plasmonic sensor can reach 4800, which is improved remarkably compared to any previously reported plasmonic metamaterial structure [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37].
Moreover, the intensity change of reflected wave at a special wavelength can be detected in application and a relative intensity change dI/dn at the wavelength can be obtained owing to a refractive index change of surrounding environment. Then, the corresponding figure of merit is defined as FOM* = max |(dI/dn)/I|, which can be used for evaluating the ability of detecting the light intensity change of reflected wave, and I is the intensity of reflected wave at the fixed wavelength. Then, in order to more clearly describe the sensing performances of the designed metamaterial structure, we calculated the FOM and FOM* from the reflectance spectra, as shown in Fig. 8. Figure 8a shows increase of FOM varying with the thickness t 1 from 345 to 370 nm and a maximum of FOM* = 1.24 × 10 5 at t 1 = 23 nm. In Fig. 8b, with increasing the w, the FOM decreases obviously and has a maximum value 6666.67, which is greater than FOM of any previously reported plasmonic refractive index sensor [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. As shown in Fig. 8c, the FOM and FOM* increase first and then decrease as the d changes from 15 to 45 nm. These studies of this ultra-high FOM sensor will have a great guiding role to design high-performance sensors.
Conclusions
In this paper, using finite-difference time-domain (FDTD) simulation, we propose and numerically investigate a novel ultra-narrow bandwidth plasmonic absorber based on a MDMDM periodic structure at near-infrared wavelengths. The metamaterial absorber shows an ultranarrow absorption bandwidth (FWHM) of 0.5 nm with absorption peaks over 98 % at normal incidence. The high absorption is ascribed to the coupling effect between gold nanobars and the gold film resulting from the excitation of LSPR. Importantly, this plasmonic structure presents excellent sensing performance with a high wavelength sensitivity of 2400 nm/RIU and an ultra-high FOM of 4800. To the best of our knowledge, this is the highest value of FOM compared with any reported plasmonic sensor to date. Then, we investigate the influence of the structure parameters on the performance of the plasmonic sensor. Moreover, the designed structure also can show the strong electric field confinement and enhancement in a nanogap region. Due to the ultra-high FOM and the high sensitivity, our metamaterial structure achieves a promising way to realize ultra-high resolution refractive index sensor based on LSPR, which has great potential in biomedical and chemical applications. | 4,848.2 | 2016-11-02T00:00:00.000 | [
"Engineering",
"Materials Science",
"Physics"
] |
5-Acetyl-4-(4-methoxyphenyl)-6-methyl-3,4-dihydropyrimidine-2(1H)-thione
In the title molecule, C14H16N2O2S, the heterocyclic ring adopts an envelope conformation with the plane through the five coplanar atoms making a dihedral angle of 88.99 (4)° with the benzene ring, which adopts an axial orientation. The thionyl, acetyl and methyl groups all have equatorial orientations. Intermolecular N—H⋯S, N—H⋯O, C—H⋯O and C—H⋯S hydrogen bonds are found in the crystal structure.
In the title molecule, C 14 H 16 N 2 O 2 S, the heterocyclic ring adopts an envelope conformation with the plane through the five coplanar atoms making a dihedral angle of 88.99 (4) with the benzene ring, which adopts an axial orientation. The thionyl, acetyl and methyl groups all have equatorial orientations. Intermolecular N-HÁ Á ÁS, N-HÁ Á ÁO, C-HÁ Á ÁO and C-HÁ Á ÁS hydrogen bonds are found in the crystal structure.
S1. Comment
As part of our investigations of dihydropyrimidine derivatives to compare their biological activity, we have undertaken the X-ray crystal structure analysis of the title compound. The crystal structures of three very closely related compounds have recently been reported [Anuradha et al., (2008[Anuradha et al., ( , 2009Chitra et al., (2009]; these studies have also reported their chemical and biological applications. In the title molecule, C 14 H 16 N 2 O 2 S, (Fig. 1), the heterocyclic ring adopts an envelope conformation with the plane through the five coplanar atoms (N1,C2,N3,C5,C6) making a dihedral angle of 88.99 (4)° with the benzene ring, which adopts an axial orientation. The thionyl, acetyl and methyl groups all have equatorial orientations. Intermolecular N1- 1 + y, z) and C61-H61B···S2(2 -x, 1 -y, 1 -z) hydrogen bonds are found in the crystal structure.
S2. Experimental
A solution of acetylacetone (1.001 g, 0.01 mol), 4-methoxybenzaldehyde (1.202 g, 0.01 mol) and thiourea (1.14 g, 0.015 mol) was heated under reflux in the presence of calcium fluoride (0.078 g, 0.001 mol) for 3 h (monitored by TLC). After completion of the reaction, the reaction mixture was cooled to room temperature and poured into crushed ice. The crude product containing also the catalyst was collected by filtration on a Buchner funnel. The mixture of the product and the catalyst was digested in methanol (40 ml). The undissolved catalyst was removed by filtration. The crude product was obtained by evaporation of the methanol and further purified by recrystallization from hot ethanol to afford the pure title compound. Yield 90% (1.2 g).
S3. Refinement
The two N-bound H atoms were located in a difference Fourier map and refined freely; N1-H1 = 0.87 (2) Å and N3-H3 = 0.85 (2) Å. The remaining H atoms were positioned geometrically and allowed to ride on their parent atoms, with C -H = 0.95 -1.00 Å ; U iso (H) = kU eq (C), where k = 1.5 for methyl and 1.2 for all other H atoms.
Special details
Geometry. Bond distances, angles etc. have been calculated using the rounded fractional coordinates. All su's are estimated from the variances of the (full) variance-covariance matrix. The cell e.s.d.'s are taken into account in the estimation of distances, angles and torsion angles Refinement. Refinement of F 2 against ALL reflections. The weighted R-factor wR and goodness of fit S are based on F 2 , conventional R-factors R are based on F, with F set to zero for negative F 2 . The threshold expression of F 2 > 2σ(F 2 ) is used only for calculating R-factors(gt) etc. and is not relevant to the choice of reflections for refinement. R-factors based on F 2 are statistically about twice as large as those based on F, and R-factors based on ALL data will be even larger. | 851.2 | 2009-11-07T00:00:00.000 | [
"Chemistry"
] |
Development and Characterization of Eudragit-RL-100-Based Aceclofenac Sustained-Release Matrix Pellets Prepared via Extrusion/Spheronization
Aceclofenac (AC) is a nonsteroidal anti-inflammatory drug used in the treatment of chronic pain in conditions such as rheumatoid arthritis, with frequent administration during the day. The formulation of sustained release matrix pellets can provide a promising alternative dosage form that controls the release of the drug, with less blood fluctuation and side effects—especially those related to the gastric system. The extrusion/spheronization technique was used to formulate AC matrix pellets. The response surface methodology (version 17.2.02.; Statgraphics Centurion) was used to study the impacts of Eudragit RL 100 and PVP K90 binder solution concentrations on the pellets’ wet mass peak torque, pellet size, and the release of the drug. Statistically, a significant synergistic effect of PVP K90 concentration on the peak torque and pellet size was observed (p = 0.0156 and 0.031, respectively), while Eudragit RL 100 showed significant antagonistic effects (p = 0.042 and 0.013, respectively). The peak torque decreased from 0.513 ± 0.022 to 0.41 ± 0.021 when increasing the Eudragit RL 100 from 0 to 20%, and the pellet size decreased from 0.914 ± 0.047 to 0.789 ± 0.074 nm. The tested independent factors did not significantly affect the drug release in the acidic medium within 2 h, but these pellet formulae maintained the drug release at less than 10% in the acidic medium (pH 1.2), which may decrease gastric irritation side effects. In contrast, a highly significant synergistic effect of Eudragit and highly antagonistic effect of the PVP solution on drug release in the alkaline-pH medium were observed (p = 0.002 and 0.007, respectively). The optimized pellet formula derived from the statistical program, composed of 3.21% Eudragit and 5% PVP solution, showed peak torque of 0.861 ± 0.056 Nm and pellet size of 1090 ± 85 µm, and resulted in a significant retardation effect on the release after 8 h compared to the untreated drug.
Introduction
Aceclofenac (AC) is a non-steroidal anti-inflammatory drug (NSAID), and it is prescribed and recommended in the treatment of osteoarthritis and rheumatoid arthritis to relieve pain. Moreover, AC has the ability to reduce morning stiffness and improve spine movement in a comparable manner to indomethacin and tenoxicam. It acts by blocking the effects of natural substances called cyclooxygenase (COX) enzymes, which act as the key step in the formation of prostaglandin 2, which plays a critical role in inflammation [1,2]. AC is used to relieve chronic pain, and this requires frequent administration of the drug for a long time. A dosage regimen of 100 mg twice daily for up to 6 months is recommended for the treatment of a patient with osteoarthritis of the knee [3]. The most common adverse effects of AC are related to the GI systems, as with other NSAIDs, including diarrhea, flatulence, gastritis, constipation, vomiting, and ulcerative stomatitis, with a frequency rate of <5%. Dyspepsia and abdominal pain can also occur, but at a higher rate than 5% [4]. Several clinical trials have shown similar GI event rates after the administration of AC and other NSAIDs: 8-28% after AC, and 15-36% after other NSAIDs, including indomethacin, diclofenac, piroxicam, ketoprofen, tenoxicam, and naproxen [5][6][7][8]. From a pharmacokinetic point of view, AC bioavailability is low, with an elimination half-life of 4 h [2].
Sustained-release formulation provides several advantages over conventional oral dosage forms; it is formulated to stabilize the drug concentration in the blood and decrease its fluctuation. Moreover, it is formulated to minimize the side effects of the drug. In some cases, continuous and prolonged release of the drug will be effective in achieving a certain therapeutic effect, due to its short half-life and low bioavailability. This is the main target in the treatment of chronic diseases such as osteoarthritis or rheumatoid arthritis. Different research articles have formulated AC as a sustained-release dosage form. The formulation of AC sustained-release matrix tablets with different grades of hydroxypropyl methylcellulose (HPMC)-with or without PVP K30-has been carried out by Ankita et al. [9]; all formulations successfully sustained the release for up to 24 h [9]. Polymer-based sustained release of microspheres was prepared using rosin polymer, with polyvinyl alcohol as an emulsifying agent [10]; only 55% of the drug was released over 24 h, due to the hydrophobic nature of the polymer [10]. Ghosh et al. [11] formulated AC SR matrix tablets using different grades of HPMC, ethylcellulose, and guar gum; it was found that HPMC K4 provides a reliable sustained effect, with good stability compared to freshly prepared tablets [11].
Multiparticulate oral solid dosage forms or pellets are spherical in shape, with sizes ranging from 500 to 1500 µm. Pellet formulations have attracted researchers' attention, since they provide several advantages over conventional solid dosage forms. The large surface area of the pellets is considered to be a major advantage of this formulation. Once administered, the pellets will be distributed over the gastrointestinal tract (GIT), with a low risk of gastric irritation. Pellets can be produced using different techniques, including the powder-layering technique [12], solution-/suspension-layering technique [13], extrusion/spheronization technique [14,15], balling/spherical agglomeration [16], spraycongealing/drying [16], cryopelletization [16], and melt spheronization [16].
Coating of the pellets with polymer film has been employed by several researchers to control the release of drugs. Budesonide SR coated pellets with Eudragit were prepared by Raval et al. [17]; the results showed the efficacy of Eudragit S100 not only in sustaining the release of the drug, but also in decreasing the intensity of gastric irritation by preventing the release in the first 2 h [17]. Coated pellets containing salbutamol were prepared using a combination of different Eudragit types (RSOP and L100); the resultant pellets provide a good sustained release over 8 h [18]. There are few studies concerning the use of Eudragit as a matrix former in matrix pellets. For example, É. Bölcskei et al. [19] prepared immediaterelease matrix pellets containing diclofenac sodium, based on Eudragit NE 30D as a binder and matrix former, via extrusion/spheronization procedures; they studied the critical material and process parameters that control pellet attributes and drug dissolution by means of a factorial design. Furthermore, Amin et al. [20] prepared SR matrix pellets containing lornoxicam via extrusion/spheronization, using a 3 2 full factorial design to study the effects of Eudragit RLPO and Eudragit RSPO on drug release rates.
Technically, coating is a complex and time-consuming process. It requires the preparation of some organic solvents, and these solvents may present some health hazards. Moreover, the release of a drug from coated dosage forms mainly depends on the thickness of the coating, which plays a crucial role in controlling the release. Therefore, matrix pellets provide several advantages over coated pellets, such as eliminating the use of explosive solvents, as well as simplifying the process. Extrusion/spheronization procedures are currently among the methods utilized to manufacture pharmaceutical pellets. The characteristics and properties of the manufactured pellet formulations can be manipulated by controlling both materials' composition and extrusion/spheronization conditions. It is worth mentioning that the formulation of AC sustained-release matrix pellets has not been discussed in the literature. In our study, sustained-release matrix pellets containing AC were manufactured without the use of coating procedures. The formulation of AC SR matrix may might provide several advantages over the use of coating procedures for SR purposes, as mentioned previously, in addition to controlling the drug release from the formulated pellets by controlling pellet wet mass properties. Formulations of AC as SR matrix pellets are expected to be able to provide and maintain therapeutically effective plasma concentrations for a period longer than the untreated drug after oral administration. In this current study, Eudragit RL 100 was used as a polymer and PVP K90 as a mass-forming agent to sustain the release of AC. A 3 2 full factorial design was used to determine the effects of different concentrations of Eudragit RL100 (X1) and PVP K90 (X2) on different response parameters, including mean line torque (Y1), pellet size (Y2), % drug released after 2 h (Y3), and % drug released after 8 h (Y4).
Experimental Design
The influences of two independent factors (Eudragit RL 100 (X1) and PVP binder solution (X2)) on the characteristics of AC SR matrix pellets using the 3 2 full factorial design were evaluated. Statistical analysis was conducted using Statgraphics software (version 17.2.02.; Statgraphics Centurion). Statistical models (individual, interactive, and quadratic effects) were analyzed in order to assess the impacts of the tested independent variables on the characteristics of the pellets (responses), viz., wet mass peak torque (Nm, Y1), pellet size (µm, Y2), AC release at pH 1.2 after 2 h (Y3), and AC release at pH 7.4 after 8 h (Y4). Table 1 illustrates the levels of the tested independent variables.
Assessment of Pellet Wet Mass (Mixer Torque Rheometry (MTR))
The wet masses of the tested pellet formulae were measured via MTR using an MTR-3 mixer torque rheometer (Caleva, Dorset, UK), prior to extrusion/spheronization, in order to calculate the PVP solution volume (binder ratio) needed for maximum wet mass peak torque. The measurement was carried out in a stainless steel vessel (135 mL capacity) with two knife-edge mixing blades attached, which was adjusted at a speed of 50 rpm. Twenty grams of the excipients' powders were mixed using a Turbula mixer (Erweka type S27; Apparatebau, Germany) for 10 min, and then added to the MTR vessel. Aqueous PVP binder solutions were prepared by dissolving the required amount of PVP in distilled water. Thereafter, 5 mL of binder liquid (PVP solution) was added to the vessel over 5 intervals for wet massing. Each wet massing measuring cycle involved 60 s for mixing and 20 s for data logging (gathering). During the wet massing procedures, the consistency of pellet wet mass (represented by the mean line torque; Nm) was computed [21]. Moreover, the binder ratio (mL of PVP binder solution required for 1 g of powder to attain wet mass peak torque) was determined. The acquisition and curation of the obtained data were achieved using a data acquisition system and software package.
Extrusion/Spheronization Procedures
AC sustained-release matrix pellets containing 15% drug were produced via the extrusion/spheronization method. Aqueous PVP solution (containing different polymer concentrations: 1, 3, and 5%) was utilized as a binder. The ratio of binder PVP solution to powder required for powder wet massing was calculated from the maximum wet mass torque value acquisition based on MTR studies (Table 3). Table 1 displays the compositions of different AC matrix pellet formulations. Powdered excipients (Avicel ® PH101, Eudragit RL 100, and the AC) were blended for 10 min in a Turbula mixer and then added to the MTR vessel. The required volume of the PVP solution was added, and the powder was wetted with the binder solution for 10 min. The obtained wet mass was then subjected to extrusion through a screen pore size of 1 mm Ø (Mini Screw Extruder, Model MSE1014; Caleva, Dorset, UK) at an extrusion speed of 100 rpm [22]. Consequently, the produced rod-shaped extrudates were spheronized for 5-7 min at a speed of 700 rpm using a rotating plate of even cross-hatch geometry (Spheronizer Model 120; Caleva, Dorset, UK). The resulting spheroids were finally dried for 5 h at 60-70 • C in a hot oven.
Drug Content
AC content in the prepared pellets was calculated in triplicate by using UV spectrophotometry. The pellet formula was crushed, 50 mg of which was placed in 250 mL of phosphate buffer (pH 7.4), sonicated for 15 min, and filtered through a 0.45 µm filter (Sartorius, Göttingen, Germany) [23] AC content was measured spectrophotometrically at 276 nm using a calibration curve in phosphate buffer, pH 7.4, in a concentration range of 5-30 µg/mL (UV-2800 spectrophotometer Labomed Inc., Los Angeles, CA, USA).
Particle Size
The sizes of the manufactured AC SR matrix pellets were measured via laser diffractometer (Mastersizer Scirocco 2000; Malvern Instruments, Grovewood Road, UK). Approximately 500 mg of the manufactured pellet formulation was added to the sample micro feeder and measured five times. The average volume-weighted mean size was determined [24].
In Vitro Release
The USP dissolution basket method (apparatus I) was used to study the in vitro release of AC from the SR matrix pellet formulas using a dissolution tester (LOGAN Instrument Corp., Somerset, NJ, USA). Drug-loaded pellets equivalent to 100 mg of AC were weighed accurately and added to the dissolution flask. The drug release experiment was carried out in triplicate, and the amount of AC released at predetermined time intervals was measured spectrophotometrically at 276 nm up to 8 h, using calibration curves in both 0.1 N HCl (pH 1.2) and phosphate buffer (pH 7.4). For the in vitro release dissolution studies over a pH range relevant to GIT conditions, 750 mL of 0.1 N HCl (pH 1.2) was added to each of the flasks and equilibrated to 37 ± 0.5 • C. Aliquot samples were withdrawn at time intervals for 2 h, and then the pH was changed to 7.4 by adding 250 mL of 0.2 M trisodium phosphate, and the release experiment was continued for a further 6 h. To determine the sustaining behavior of the optimized formula, the release of untreated AC was also performed under the same experimental conditions as all formulations.
Effect of Independent Factors on Wet Mass
The statistical effects of Eudragit RL 100 (X1) and PVP K90 solution (X2) on the peak torque values of the AC pellets' wet mass are illustrated in Table 2, as well as the Pareto chart in Figure 1. The ANOVA results depicted in Table 2 indicate that Eudragit exerted a significant antagonistic effect on wet mass peak torque (p = 0.042), while PVP solution showed significant synergistic action on pellets' wet mass peak torque (p = 0.016). Only the individual effects of Eudragit and PVP exhibited significant effects on wet mass, while other interactive quadratic effects were found to be insignificant, as displayed in the response surface plot (Figure 2a). It is worth mentioning that the binder ratio (mL of PVP solution required for wet mass peak torque) varied according to the composition of the pellet formula. The binder ratios of the tested wet masses ranged from 0.667 to 0.933 mL/g, as shown in Table 3. As shown in Table 2 and Figure 3, pellet formulae AC2 and AC5 (composed of 10% and 0% Eudragit, respectively, and 5% PVP binder solution) exhibited the greatest peak torque values (0.81 ± 0.047 and 0.789 ± 0.071 Nm, respectively) amongst the tested wet masses. On the other hand, AC3 pellet wet mass showed the lowest peak torque value amongst the formulations. Increasing the concentration of the binder solution (PVP K90) resulted in an increase in the mean line torque of the wet mass. This could be due to the increased cohesiveness of the powder mass and the mean torque line upon increasing the PVP concentration [25]. Additionally, Alshora et al. [15] indicated that increasing the concentration of PVP K30 as a binder resulted in an increase in the wet mass peak torque values of flurbiprofen pellets. Moreover, the level of Eudragit L 100 polymer in the pellet wet mass resulted in a reduction in the peak torque of the wet mass.
Mahrous [25] found that the extent of peak torque for the Eudragit ® systems was lower than that obtained with Avicel ® alone, using water as the wet-massing liquid; he attributed this finding to the better interaction of Avicel with the binder via hydrogen bonding.
Drug Content
The AC content in pellet formulae was measured, and the obtained data revealed that drug content ranged from 13.71 ± 0.62 mg (91.4%) to 15.81 ± 0.57 mg (105.40%) of the theoretical content (15 mg), signifying homogeneous drug distribution in the prepared SR matrix pellets (Table 3).
Effect on Pellet Size
The effects of the independent factors (Eudragit and PVP solution) on the size of the sustained-release AC pellets showed the dependence of the pellets' sizes on the pellet excipients. Eudragit exerted significant antagonism on the pellet size (p = 0.031), while the PVP had a synergistic effect on the tested response (p = 0.013), as shown in the Pareto chart ( Figure 2b) and Table 2. In addition, no statistical significance was observed regarding the interactive and quadratic effects of the excipients on pellet size (p < 0.05). The response surface plot in Figure 2b reveals that the particle size of the AC pellets was noticeably increased when increasing the concentrations of PVP binder solution, and decreased when increasing the level of Eudragit in the pellet formulation. The smallest pellet size (789 ± 74 µm) was noted in AC3, in which a low concentration of PVP and high concentration of Eudragit were used. In contrast, the largest pellet size (1230 ± 87 µm) was detected in AC2, which contained a moderate concentration of Eudragit and a high concentration of PVP (Figure 3). The direct relationship between wet mass peak torque and pellet size is consistent with the results obtained by Mahrous et al. [24], who showed that minimizing wet mass mean line torque can cause a noticeable decrease in pellet size. A low pellet wet mass consistency enables easy extrusion of pellets and yields small pellets with smoother surfaces. A similar finding was obtained by Ibrahim and Mahrous [22].
Effect on In Vitro Release
The dissolution studies of the AC pellets were performed in 0.1 N HCl for the first 2 h, then shifted to an alkaline pH of 7.4. The dissolution profile (Figure 4) showed that less than 10% of the drug was released within the first 2 h from all formulations. This behavior could be due to the presence of Eudragit, which starts to be ionized at alkaline pH-at which time the release of the drug started to increase [26]-in addition to the acidic nature of AC, which slows its release at low pH values [26]. The Pareto chart (Figure 1c) showed that neither Eudragit nor PVP K90 had a significant effect on the release in the first 2 h. Although it was insignificant (p > 0.05) (Table 1), the response surface (Figure 2c) showed that at the lowest concentration of Eudragit RL100 and PVP K90 (AC1), the release was highest (9.1%) compared with AC6 (containing the highest concentrations of PVP K90 and Eudragit RL 100), which reduced the release to 6.22% (Table 3).
By rendering the pH more alkaline, the release of AC sped up, due to the ionization of Eudragit at alkaline pH. At this stage, the Pareto chart ( Figure 1d) and the response surface ( Figure 2d) showed significant antagonistic effects of Eudragit RL100 (p = 0.002) and PVP K90 (p = 0.007) ( Table 1) on the release. This indicates that increasing the Eudragit concentration to the intermediate point resulted in enhancing AC release from the pellets at low PVP solution concentrations. Formulations (AC1, AC7, AC8) containing 1 and 3% PVP K90 and 0, 10, and 0% Eudragit, respectively, showed the highest release rates amongst the tested formulae (100.00 ± 5.51, 92.78 ± 6.52, and 98.7 ± 4.87, respectively). However, at high Eudragit concentrations (20%), the drug exhibited slow release rates, as was the case for pellet formulae AC3, AC6, and AC9, which contained 20% Eudragit and 1, 5, and 3% PVPB, respectively. The wet mass peak values of these formulations were low, with small particle sizes, as shown in Table 3. At the lowest Eudragit RL 100 concentration, and with increasing the concentration of the binder solution, increasing the mean torque line from 0.513 (AC1) to 0.789 Nm (AC5) dramatically increased the pellets' size, from 9.14 to 1.187 µm, respectively (Table 3). This increase in the pellet size significantly reduced the release after 8 h, from 100 to 78.52%. A similar finding was obtained by Ibrahim et al. [27], who revealed an inverse relationship between the peak torque values of pellet wet mass and indomethacin release rate from pellet formulations. Moreover, Ibrahim et al. [21] indicated that at a low pellet wet mass, the peak torque was associated with small pellet size and, hence, a rapid drug release rate.
As indicated by the release data, AC showed a biphasic release from the SR matrix pellets. Therefore, the release kinetics of AC from the tested matrix pellet formulae were studied for the two release periods (0-2 h at pH 1.2, and 2-8 h at pH 7.4) using different release kinetics models ( Table 4). The release kinetics were determined by the highest correlation coefficient. The results showed that the release of AC from pellets in the first period (acidic pH) followed the zero-order kinetics for formulae F2, F3, F6, and F9 (r 2 = 0.979), while formulae F1, F4, F5, F7, and F8 followed the Higuchi model, with a correlation coefficient value of 0.998 (Table 4). When the release data were analyzed by calculating the n value for the Korsmeyer-Peppas equation, the n values ranged from 0.539-0.704, indicating anomalous non-Fickian anomalous release [28]. With respect to AC release at alkaline pH (second phase), the drug followed "zero-order" release kinetics, with a correlation coefficient value 0.975-0.989, which is the highest value compared with other models. The n values for all formulations were more than 0.89, supporting super case II transport, where the release is controlled by both diffusion and relaxation of the polymer chain. The super case II relaxational release designates the drug transport process concomitant with stresses and state transition in hydrophilic glassy polymers, and it mainly symbolizes polymeric chain erosion, as in the case of Eudragit RL 100 [28].
Optimization of AC Sustained-Release Matrix Pellet Formulation
Optimization of AC pellet formulae was established based on the following desirability features: maximum peak torque, maximum pellet size, less than 10% release in the first 2 h (in acidic medium), and minimal release rate after 8 h. A checkpoint of Eudragit RL 100 (X1) = 3.21% and PVP K 90 solution (X2) = 5% was recommended by the statistical program using multiple-response optimization, as shown in Figure 5. The optimized pellet formula was prepared based on the composition suggested by the statistical software, and 0.8 mL of 5% PVP solution/g solid was used as the binder ratio, as obtained from the MTR measurement. The observed values for the attributes (responses) of the sustained-release optimized pellet formula were matched to the predicted responses, and the results revealed a good correlation with the software model's predicted response values ( Figure 6). The optimized pellet formula showed a peak torque of 0.861 ± 0.06 Nm (observed) compared to the predicted value (0.81 Nm), and the observed pellet size was 1090 ± 85 µm, which was narrowly interrelated with the predicted value (1220 µm). In addition, the percentages of drug release in the acidic pH in the first 2 h, and after a further 6 h (at pH 7.4), were 8.97 ± 0.74% and 80.41 ± 4.84%, respectively, showing high correlation with the predicted values (7.32% and 77.74%, respectively).
Conclusions
Formulations of AC sustained-release matrix pellets successfully controlled the release of the drug, with a minimal amount of drug released in the gastric system, eliminating the GI irritant side effects of the drug. In addition, the results showed controlled in vitro release of AC from the investigated SR pellets. The results show that Eudragit RL 100 exerts significant antagonistic effects on both peak torque and pellet size, while PVP K90 solution exerts significant synergistic effects on them. Moreover, it was noted that increasing the concentration of PVP binder solution significantly retarded the release of the drug after 8 h at alkaline pH. | 5,475.4 | 2021-11-01T00:00:00.000 | [
"Materials Science"
] |
Nonindependent Session Recommendation Based on Ordinary Differential Equation
the original
Introduction
e traditional recommendation algorithms are based on the fact that all items that interact with the user are independent of each other. ese methods ignore the continuity of information about the user's behavioral sequence and increasingly fail to meet the individual needs of the user. For example, in the Item-based recommendation algorithms [1][2][3], more attention is paid to the similarity between items, and the similarity calculation is used to infer the user's preference.
e User-based recommendation algorithms [4][5][6] are similar to the Item-based recommendation. e difference is that the similarity between the preferences for different users is calculated. Although there are many hybrid recommendation methods [7][8][9] to compensate for the incompleteness of the above two methods, personalized recommendations are still not implemented. However, in recent years, due to the increasing amount of data, the limitations of traditional algorithms have become more and more visible, and Neural Networks have once again been pushed highly to the research. Network structures such as Long Short-Term Memory (LSTM) [10][11][12], Gated Recurrent Unit (GRU) [13,14], and Recurrent Neural Networks (RNNs) [15] have been widely used in user behavior serialization modeling problems and personalized recommendation [15,16]. e environment of the recommendation system is more complex and varied than expected. e user's behavior sequences are often indefinite, and the internal correlation between each sequence is very close, so Graph Neural Networks (GNN) [17,18] are introduced into the recommendation system. We use a graph-structured model to capture the transformation of items and generate accurate item embedding vectors accordingly. is is clearly different from traditional methods, because we are not building a single item embedding. With this in mind, more and more people are beginning to use the graph network to implement the method of session recommendation.
In recent years, more and more researchers have focused on recommendation methods based on user sessions. In most session-based recommendation studies, a unified definition of a session is a sequence of records of a temporal relationship that can be used to track a user's browsing, clicking, or purchasing behavior. Compared to other methods of directly modeling the relationship between users and items, the session-based approach can bring more implicit feedback.
In recent years, more and more researchers have focused on recommendation methods based on user sessions. In most session-based recommendation studies, a unified definition of a session is a sequence of records of a temporal relationship that can be used to track a user's browsing, clicking, or purchasing behavior. Compared to other methods of directly modeling the relationship between users and items, the session-based approach can bring more implicit feedback. But these studies are based on the fact that user behaviors are independent of each other, but it is not the case in real life.
In our research, we still use the idea of GNNs to model sessions, and Gated Graph Neural Networks (GGNNs) [19,20] capture the complex transitions between items within the session. However, since the discretization of such data has been often undefined, leading to the direct use of neural networks to learn such data, there may be problems of data loss or inaccurate inconsistencies in certain time intervals. At this time, we introduce Ordinary Differential Equations (ODE) [21][22][23] to make up for this shortcoming.
We will present our model in this article: Sess-ODEnet. It uses Neural Differential Equations to propose another novel idea for session recommendation. e original intent of this approach was to model the user's nonindependent intent. In other words, we can get the potential trajectory at any point in time by solving the Ordinary Differential Equations [24], which allows us to make forward or backward predictions at any point in time.
e contributions of this work are as follows:
Related Work
A reexamination of the user's behavioral sequence becomes very important. More and more researchers agree to use the form of conversation to represent the sequence of user behavior, so there are more and more researches based on user sessions.
For the user, the relationship between the items inside each session is more closely compared to other items, so session-based recommendations are very significant. For the first time, Hidasi et al. [25] applied RNNs to session recommendation, treating a series of click behaviors occurring in a session as a sequence, and completing item-based sequence modeling to predict user preferences. Jannach and Ludewig [26] combined RNNs with kNN in 2017 and applied it to session recommendations, recognizing user behavior by RNNs, taking into account the mixture of simultaneous signals and sequence patterns.
Li et al. [27] studied a hybrid encoder (NARM), which has an attention mechanism to model the user's sequential behavior, capture the user's main purpose of the current session, and then combine it into a unified session representation. NARM's consideration of the primary purpose of the user's current action distinguishes it from previous sequence modeling methods.
However, the user's behavior sequences do not always have the same lengths. For these variable-length sequences, there are also many studies on their processing. According to the idea of word2vec, Barkan and Koenigstein [28] proposed a method of Item2vec. In item2vec, the item in the session is equivalent to the word in word2vec. If it appears in the same collection (sequence purchased or clicked by the same user), the item is considered a positive example. Although this method processes the indefinite length sequence by embedding and then calculates the probability of the prediction by calculating the similarity of the embedded vector. Grbovic and Cheng [29] proposed a "list embedding" method that provides a new perspective for item embedding. e internal relationship between these listings that the user clicks is mined by the context of the user's click sequence.
ese proposed embedded-based methods focus on sequences of variable length but inevitably make the elements inside the session more sequential [30][31][32][33]. We need to consider the intimacy of all the items inside the session, not the items that are next to each other. Ideally, we can keep the intimacy of the items inside the session and prevent them from relying too much on timing and spatial location. In fact, the Graph Neural Network can do this.
Graph Neural Networks are further used to recommend modeling system scenarios [34,35]. Wu et al. [36] proposed SR-GNN in 2018 to model the session sequence of graph structure data to extract the embedded vector of the item using GNNs. e advantage of this is that the model does not rely on the user's relevant representation at this time, using the embedded layer of the session for the recommendation. It is different from the classic embedding method. It not only solves the problem of embedding unequal sequences but also gives different representations for the embedding of each item.
Description of Nonindependent Identically Distributed Intention Problems
In this section, we will primarily describe the intelligibility of the problem we are trying to solve, which will not contain more algorithmic details. We also give descriptive meanings to the symbols that appear in our work.
Problem Description.
e data in the recommendation system appears as multi-source heterogeneous data. In this case, the analysis and prediction of user behavior through traditional independent and identical distribution assumptions will bring specific problems. erefore, the processing of such multi-source heterogeneous data is a fundamental problem that the recommendation system cannot avoid. It requires us to design the model, and it needs to be more specific to the actual problem and the characteristics and complexity of the actual data.
Let us consider the state of user behavior in real life. For example, a user has purchased K identical items in a year. In the previous recommendation algorithms, they considered the user's K-time behavior as independent and identical distribution. However, it is easy to imagine that he might have purchased the item for different reasons at different points in time. We refer to this behavior as "nonindependent identical distribution intent." Compared to Independent and identically distributed situations, the above user behavior is more common in real life.
is kind of thinking is straightforward to be recognized. We cannot get specific factors that affect user behavior, but we can mine such a layer of information from user behavior data. One idea is that we can use the context information of the user's click action to determine if the same action is due to the same situation.
From the perspective of continuous-time and space, we looked for another analysis method for the user's nonindependent behavior. e problem we are trying to solve is how to model such intentions. We try to achieve this by using Neural Ordinary Differential Equations [37]. In its forward propagation process, the original discrete states inside the network are connected by time t, presenting a continuous spatial state. However, how do we get the potential preferences of segmented users? Reverse-mode automatic differentiation [38] can solve this problem. It helps us solve the adjoint states at different times.
at is, we assume that user behavior is different between different points in time.
is means that we can "split" the user state in the continuous latent space.
Definition of Symbols.
We describe the key representations used by the model and show them in Table 1 for quick access.
Sess-ODEnet: Use ODE Solver to Make Session Recommendation
In this section, we will introduce our model in detail. Our work can be divided into two parts. First, we can get a neural network that can be solved and then use ODE to solve the neural network to get the predicted results.
Recognition Network and Ordinary Differential Equation
Solver. According to the description in Neural Ordinary Differential Equations [21], we need to define a recognition network. It can be arbitrary. We first considered the importance of user sessions. In the actual application scenario, long-term, orderly history may not be relevant to the user. User behavior may occur when an action occurs to an irregular point in time. erefore, the internal continuity of the conversation and the irregular time points are the focus of our research.
Session
Graph. In our model, we still use the definition of the session graph in [36]. Each session graph appears as a graph structure derived from the user's click sequence. e session graph is defined as G � (V, E). In the session graph, each node represents an item v s,i ∈ V, and the user clicks on the item in the session as the edge of the graph, denoted as We assign a normalized weight to each edge, which is calculated as the number of occurrences of that edge divided by the degree of the starting node of that edge. is is to avoid duplicate items in the user's session. We embed each item in a unified embedding space. e node vector v ∈ R d represents the potential vector of the item learned through the Graph Neural Networks, where d is the dimension. us, each session s can be represented as an embedded vector S consisting of the node vectors used in the session graph.
GGNNs as Recognition Network. Because Ordinary
Differential Equation solver is suitable for any form of a neural network, we use Gated Graph Neural Networks (GGNNs) to learn session graphs. It is to allow information to propagate in space to model the complex relationships between items. e gated graph neural network embeds each session graph into the graph, at which point each node contains context information. e GGNNs can be represented by the following equation: (1) Among them, S (1) v represents the initial state of the D dimension of the node v. x T v represents node feature. A is an adjoint matrix that includes in-and out-degrees, and a (t) v represents a 2-dimensional vector of the result of the interaction between nodes and adjacent nodes. Since the adjoint matrix A contains both in-degree and out-degree, the result of the calculation is similar to that of a cyclic neural network; that is, it contains bidirectional information v indicates the newly generated information, and S (t) v indicates the node status of the final update.
It shows that we take advantage of the gated graph neural network, which is its "forgetting" and "update" mechanisms. It essentially acts as an attention mechanism, which allows us to consider the user's long-term and short-term preferences better because information with too small weight will be filtered out. Finally, we can get the final representation of the individual node vectors in the graph.
ODEsessSolver.
We will detail the ordinary differential equation solver, and its forward and backward propagation processes, which are the core of Neural Ordinary Differential Equations.
Forward Propagation on the Graph.
In GGNNs, the activation values of all layers need to be preserved after forwarding propagation, because these activation values are used to make backpropagation gradients on the computational path. However, it takes up an ample memory space, which makes the training process of the network limited. erefore, we use GGNNs to parameterize the derivative of the hidden state, rather than directly parameterizing the hidden state as usual. It brings two benefits: (1) the level and parameters of continuity are implemented within the graph network; (2) the continuous graph network space eliminates the need for hierarchical propagation gradients and parameter updates.
In order to make the network hierarchy continuous, it is required that the error between hidden layers should be close to infinity within a network. When our GGNNs are added to a hidden layer that approaches infinity, the network can be considered to be contiguous. We represent this continuous transformation as an Ordinary Differential Equation: where g denotes the Gated Neural Network layer, t changes from the initial to the end. e change in S(t) represents the forward propagation result. At this point, we can see that we only need to find the solution of the equation, which is equivalent to completing the forward propagation. Formally, we need to transform the above formula to find the solution we need. Given the initial state S(t ini ) and the Gated Graph Neural Networks, the hidden state S(t ter ) of the end time is solved: Note that both S(t ini )and t ter t ini g(S(t), t, θ)dt can be solved by ODEsessSolver. At this point, we solved the termination state S(t ter ), which is equivalent to the completion of the forward propagation. is method has a high degree of maturity and recognition in the field of mathematics, we only need to regard it as a "black box solver." We gave pseudocode for forwarding propagation shown in Table 2. As you can see, we can define a neural" network and an ordinary differential equation solver. e solution results can be obtained by "feeding" the initial state, the final state, and the neural network to the solver.
Among them, gatedNet is defined as a Gated Graph Neural Network, S and t, respectively, represent state and time, and West Tower is a learnable parameter of the model.
Reverse-Mode Automatic Differentiation on the Graph.
To make the GGNNs' network hierarchy continuous, the challenge is how to make the gradient pass through ODE-sessSolver. If the gradient is reversed back along the calculation path of forwarding propagation, it is very intuitive. However, the memory usage will be extensive, and the numerical error cannot be controlled. As stated, we treated the forwardpropagating ODEsessSolver as a "black box operation," and the gradient does not need to be passed in at all, just bypassing it. We learned in the previous section that it uses GGNNs to parameterize the derivative of the hidden state, where the derivative of the parameterized hidden state is similar to
Symbol
Meaning G � (V, E) Session graph. V denotes a node in the graph, and E denotes an edge between the nodes S e embedding vector of the session graph g A single layer representation of a gated graph neural networks t, θ ey represent each moment in the graph and the current gradient a(t) Adjoint. It represents the dependence of the descending gradient on the hidden state at each time point Terminal state of time t ODEsessSolver Ordinary differential equation solver I t It represents the sampled output at any time t obtained by the ODE solver q(·) It represents the posterior probability of the sampled output. Specifically, it represents the probability of the item to be recommended constructing the hierarchy and parameters of continuity, rather than discrete levels. So the parameter is also a continuous space; we do not need to layer the gradient and update the parameters. It should be noted that ODE does not store any intermediate results during forwarding propagation, so it only needs to approximate the memory cost of the constant level.
In this way, taking the initial state S(t ini ) and the terminating state S(t ter ) as an example, we can give the loss function of the backpropagation: It should be noted that the input to the loss function is the result of ODEsessSolver. It can be concluded from the above equation that the optimization problem is a gradient optimization problem that is converted to θ.
We use the adjoint sensitivity method [39] to calculate the inverse gradient. is method calculates the gradient by solving the second augmented Ordinary Differential Equation backward. is method is linear with the size of the problem, has low memory costs, and can explicitly control numerical errors. In this method, the dependence of the descending gradient on the hidden state S(t) at each time point is defined as an adjoint a(t) and has a(t) � zL/zS(t). On every instant, there are Among them, the accompanying amount of the initial time point t ini can be directly solved by the ordinary differential equation. For [t 1 , . . . , t n ], it can be calculated backward from its final value. For parameter θ, its gradient depends on the current hidden state S(t) and the accompanying amount a(t): Among them, a(t) T (zg/zS) and a(t) T (zg/zθ) are vector-Jacobian products [40]. ey can all be evaluated by the automatic differentiation method [41][42][43]. e integrals forms of S, a, and zL/zθ are solved by ODE. In the solution process, the original state, the accompanying state, and other partial derivatives of the nodes in the layer at each moment are connected into a single vector. Note that when Loss relies on the intermediate state, we use the reverse-mode automatic differentiation [37,38,42] to decompose the derivative into a series of solutions according to the time interval between each successive output pair. e method of reverse automatic differentiation is different from the backward propagation method of the neural networks. It means that we can get his termination state at any time through the user's initial state [44,45].
Session Recommendation Using ODEsessSolver.
In the previous section, we have already mentioned that our goal is to find a way to model conversations differently from traditional sequential learning ideas. Since the user's behavior exhibits a continuous state or time-series data with different frequencies, durations, and starting points, we may have the same behavior at different points in time for different reasons. For example, we went to the pharmacy twice to buy painkillers, but one was because of a headache, and the other was because of a toothache. It makes it easy to tell from the context of the user's behavior that these are two different situations. At present, the application of modeling of this idea is not enough. Such irregular time-series data can be divided into discrete steps of weeks, days, or even hours by parallel sessions.
In Section 4.1, we have included some details of the gated graph neural network and the ordinary differential equation solver. To achieve nonindependent and identically distributed session prediction, they are critical tools. In this section, we use the above ideas and tools to implement recommendation-based dependent sequence prediction. We presented model diagrams (Figure 1) to understand the recommendation process better.
Give the observed time T � t ini , t 1 , . . . , t n , an initial state S(t ini ). Again, ODEsessSolver is used to calculate the potential state S � S t ini , S t 1 , . . . , S t n representing each time point, while generating the sampled output I t � I t ini , I t 1 , . . . , I t n for each potential state in any time. Our model can be defined as follows: S t 1 , S t 2 , . . . , S t n � ODEsessSolver S t 1 , g, θ g , t ini , t 1 , . . . , t n , where each layer of the Gated Graph Neural Network takes the corresponding S at the current time point and outputs the gradient zS(t)/zt � g(S(t), θ g ). After the GGNNs consume the data in an orderly manner, the posterior probability of each sample is output, that is, the probability of the item we use for prediction: For GGNNs, each of its graph network layers g is timeinvariant and given any potential state, S t ; its anti-pattern derivative trajectory should be unique. At any time, we can make any session prediction forward or backward. For example, if the initial session state S t ini is the current input session, its potential trajectory to the termination state S t ter should be unique. Extrapolation from this termination state allows for the prediction of potential states in future time. Mathematical Problems in Engineering 5 at is, by solving the termination state S t ter , we can predict the potential behavior of the user for a certain period time from this point in the future.
According to the results of the ordinary differential equation solver, we used softmax to get the results of multi-classification. In fact, we only need to get the first few items of the forecast.
We gave a diagram ( Figure 2) containing this example to feel the process visually:
Experimental Settings.
Our experiment was to verify the correctness of the idea of applying Neural Ordinary Differential Equations to conversational recommendations. In the context of session-based sequence learning, we chose Gated Graph Neural Networks as the recognition network and explored the user's preferred sessions using the Latent Neural Ordinary Differential Equations Model proposed in [21]. We used a learning rate of 0.005 in training and used the Adam optimizer for optimization learning. To alleviate the overfitting, we use the L2 loss function and take advantage of the early-stop training method. Ten epochs without improvement mean that training saturation stops training. Our experiments were implemented on Windows 10, Python 3.6, and pytorch 1.0 frameworks and accelerated using TITAN XP GPUs.
Experimental Datasets.
We tested for four real datasets, including two large datasets in the form of conversations (Yoochoose (http://2015.recsyschallenge.com/challege.html) 1/64 and Diginetica (http://cikm2016.cs.iupui.edu/cikmcup)), a dataset containing the user's music playback history (separated by timestamp) (Last.fm (https://grouplens. org/datasets/hetrec-2011/) And a user behavior data set Retailrocket (https://www.kaggle.com/retailrocket/ecomm erce-dataset) (Users' clickstream data). e Yoochoose dataset is from RecSys Challenge 2015, which contains user clickstreams on e-commerce sites within 6 months. e Diginetica dataset is from the CIKM Cup 2016, which uses only its transaction data. After removing sessions of length 1 and too few occurrences, we can get the data shown in Table 3. ese two datasets are classic datasets based on session recommendations. ese two datasets are commonly used for session-based recommendations. We used a data preprocessing method similar to [36] because this processing method allows us to get a clearer input.
Last.fm is a dataset about music recommendations. e data includes a list of the most popular artists, as well as the number of plays and tags for songs. Retailrocket dataset is the behavioral data of a real e-commerce website user. It includes, a slightly shorter period of time than Yoochoose, only 4.5 months of website visitor behavior data. In the dataset, there are three types of user behaviors: browsing, adding to shopping cart, and transaction. We used Table 4 to show the specific data of these two data sets.
ese two datasets are commonly used in recommendation systems based on user behavior analysis. ey are characterized by easy access to user behavior in the form of sequences. (RNNs). It models the session by using a deep-loop neural network consisting of GRU cells. NARM: the Neural Attentive Recommendation Machine. Based on the cyclic neural network, the attention mechanism is added. Based on the analysis of the sequential behavior of the cyclic neural network, the main behavior of the user is more closely concerned. SR-GNN: this model was proposed by ShuWu et al. in January 2019 to aggregate separated session sequences into graph structure data. rough the Graph Neural Networks, the global session preference and local preference are comprehensively considered.
Metrics.
We use the two evaluation indicators commonly used in the recommendation system, namely, the recall rate and the average reciprocal ranking, to qualitatively evaluate the experiment.
Recall@S: it is a very important one of the recommended system evaluation indicators and is used to measure the recall rate of the first S items in all test instances in the recommendation list. Recall@20: It represents the proportion of correctly recommended items in the top 20 items. Recall@50: It represents the proportion of correctly recommended items in the top 50 items. Mean Reciprocal Rank: it measures the ranking of the predicted positions of the real target items in all test cases and counts them down and averages them as to accuracy. MRR@20: it represents the average of the peer-level levels of the correctly recommended items in the top 20 items.
Results.
We tested on four data sets. To train the model's ability to predict the data at irregular time points, we randomly selected the time points for extraction in each trajectory. At the same time, each time of new input is connected to the next predicted time difference to improve further the ability of the Gated Graph Neural Network to observe irregularities. We showed the experimental results in Table 5.
Gated graph neural networks
S(t ter )
ODEsessSolver Terminal state Initial state Figure 2: e process of processing the data by the model. It depicts the flow from the initial state to the termination state. For the input, we nonlinearly transform the input through gated graph neural networks (GGNNs) to get (g). ODEsessSolver integrates the neural network g and adds the initial state value to get the final prediction. Our model gives a new definition of the specific potential state of a user session over a continuous period of time. In our baseline algorithm, NARM and SR-GNN are the models based on the session recommendation proposed in the past two years. When the model predicts user behavior, the results they get should be very similar, because these models are all proposed on independent and identically distributed assumptions. Nevertheless, our model is more focused on the different companion states that users present in different periods. ese adjoint states indicate that although the user has generated the same behavior at different points in time (e.g., clicks, purchases), it may be for different reasons. e ability to model user sessions in complex spaces is enhanced. Most of the recommended algorithms use RNNs or GRU to model user sequences. However, in a complex recommendation system, although the user's action behavior exhibits a sequence state, the inside is still closely related in the form of a graph network. In our model, the Gated Graph Neural Network combined with the Ordinary Differential Equation preserves the ability of the network to model complex data, enabling it to propagate in a contiguous space. e model has a lower complexity in the solution process. When we use ordinary differential equations to solve the problem, we usually do not need to solve the complete form of the solution of the equation, as long as the obtained solution is gradually close to the optimal value. e Ordinary Differential Equation Solver eliminates the need for hierarchical propagation gradients and parameter updates by parameterizing the derivative of the network's hidden state [39]. We can get the desired result by solving the network once, without the need for a gradient-like approach. erefore, our model usually has a constant storage cost for ordinary differential equations.
Conclusion
We must realize that session recommendation plays a vital role in the user's implicit preference mining, but it cannot be considered as an independent and identical distribution. We propose a recommendation model based on Neural ODE: Sess-ODEnet. e model combines differential equations with gated graph neural networks to model complex sessions. e model derives the representation vector of each embedded item by representing the session as the structure of the conversation graph and then through the Graph Neural Network. On this basis, the ODE solver is used to predict and recommend nonindependent intentions at any point in time. Not only that, Neural ODE is different from traditional neural network training methods, which makes our models have not only low memory usage but complicated search time as well.
However, the focus on this work is still to regard the user session as a continuous state in time. In the future, we hope to apply this model to the sequence of behaviors lacking time steps and to model the nonindependent intentions of users at higher levels, with recommendations [14].
Data Availability
e illustrative example data used to support the findings of this study are included within the article.
Conflicts of Interest
e authors declare no conflicts of interest. | 6,885.2 | 2020-02-10T00:00:00.000 | [
"Computer Science"
] |
The Toxicity of Eichhornia crassipes Fractionated Extracts against Aphis craccivora and Its Safety in Albino Rats
Eichhornia crassipes were evaluated in order to investigate the insecticidal activity towards Aphis craccivora adults. The LC50 values were promising and reflected the bio-efficacy of the tested extracts (39 and 42 mg/L), respectively, and reduced the fecundity markedly. Using GC/MS analysis, the major components were n-hexadecanoic, linolenic, hexadecenoic, myristic, stearic acids, linolelaidic acid, methyl ester and some terpenoids, alkaloids, and hydrocarbons. A safety assessment of non-target organisms is essential for the development of new pesticides. In order to guide the rational use of the most potential insecticidal extracts AcF and EtF, the effect of these extracts on body weight, hematological indices, biochemical indicators, and histopathology of some relevant organs of albino rats (as a model for mammals) was investigated. The research outcomes revealed that the LC50 of AcF and EtF extracts had gradually raised body weight for 14 days (p > 0.05). Similarly, there were no remarkable alternations in the complete blood count (CBC); only a slight decrease in the monocytes count (612 ± 159.80 × 103 µL) in the EtF-treated group. There was a notable increase in alanine transferase (ALT) activity (36.73 ± 1.44 IU/L) in the AcF-treated group. No destructive changes were noted with the remaining biochemical parameters. Cholesterol and triglycerides non-significantly increased in the EtF group, whereas, cholesterol levels decreased significantly in the AcF group. In addition, histopathological examination reflected minor changes in AcF and EtF groups in the form of mild inflammation in the lungs and mild vacuolar degeneration in the kidneys, while no lesions were detected in the heart and liver in the same groups. Thus, the present research suggested that AcF and EtF extracts of E. crassipes are safe green insecticides for insect control strategies.
Introduction
Aphis craccivora Koch. (the bean aphid) (Hemiptera: Aphididae) is considered one of the most deleterious insects globally [1]. The bean aphid infests many parts of the bean plant (leaves, stems, twigs, pods, and flowers) [2]. In addition, these insect species cause serious economic losses in the yields (up to 100%) of a wide range of family Leguminosae [3].
Insecticidal Activity of AcF and EtF Extracts against Aphis craccivora
The insecticidal activity of acetone and ethanol fractionated extracts were tested against Aphis craccivora adults using different concentrations for each.
The toxicological activity of AcF extract was tested at different concentrations (60,50,40,30, and 20 mg/L). The mortality percentages increased gradually according to concentration and time gradients as follows: 47 Figure 2.
Efficacy of AcF and EtF Extracts against Aphis craccivora
The results of the bioassay of acetone and ethanol fraction extracts of E. crassipes extract against aphid adults indicated that acetone fraction extract (AcF) was more effective against A. craccivora during the experiment (24, 48, and 72 h) with the lowest LC50 values as 64, 52, and 39 mg/L, respectively. Conversely, ethanol fraction extract (EtF) had higher LC50 values of 140, 86, and 42 mg/L ( Table 2). The insecticidal effect of EtF extract reflected that the percentage of mortality was directly proportioned with concentration and time. After 24 h, mortality was 36.8%, 31.58%, 23.7%, 13.16%, and 5.3% for concentrations 100, 50, 40, 30, and 20 mg/L, respectively compared with zero percent in the control. There was a gradual increase in mortality after 48 h (52.78%, 47.22%, 44.44%, 22.22%, and 13.9%) for previously mentioned concentrations, respectively. In addition, after 72 h, the mortality percentage reached the maximum, especially with the higher concentrations (100, 50, and 40 mg/L) as 77.78%, 63.9%, and 55.56% and 44.44% and 30.56% with 30 and 20 mg/L as presented in Figure 2.
Efficacy of AcF and EtF Extracts against Aphis craccivora
The results of the bioassay of acetone and ethanol fraction extracts of E. crassipes extract against aphid adults indicated that acetone fraction extract (AcF) was more effective against A. craccivora during the experiment (24, 48, and 72 h) with the lowest LC50 values as 64, 52, and 39 mg/L, respectively. Conversely, ethanol fraction extract (EtF) had higher LC50 values of 140, 86, and 42 mg/L ( Table 2).
Efficacy of AcF and EtF Extracts against Aphis craccivora
The results of the bioassay of acetone and ethanol fraction extracts of E. crassipes extract against aphid adults indicated that acetone fraction extract (AcF) was more effective against A. craccivora during the experiment (24, 48,
Effect of AcF and EtF Extracts on the Number of Offspring of Aphis craccivora
AcF extract reduced the fecundity of aphid adults more than EtF extract ( Figure 3). AcF recorded the highest effect at 60 mg/L (number of offspring was 8) and 11,13,19, and 42 offspring for 50, 40, 30, and 20 mg/L, respectively, compared with 92 offspring in the
Effect of AcF and EtF Extracts on the Number of Offspring of Aphis craccivora
AcF extract reduced the fecundity of aphid adults more than EtF extract ( Figure 3). AcF recorded the highest effect at 60 mg/L (number of offspring was 8) and 11,13,19, and 42 offspring for 50, 40, 30, and 20 mg/L, respectively, compared with 92 offspring in the control (Figure 3a). On the other hand, EtF extract at the highest concentration (100 mg/L) reduced the fecundity to 5 offspring then 7, 8, 17, and 25 offspring for 50, 40, 30, and 20 mg/L, respectively, compared with 95 offspring in the control (Figure 3b).
Effects of Exposure to LC 50 of AcF and EtF Extracts of E. crassipes on Body Weight
Overall body weight increased with time in all groups, but there was no difference between the control and treatment groups (AcF and EtF) at any time point (14 days) (p > 0.05) ( Figure 4). On day 1, weights were recorded as 120, 121.67 ± 1.67, and 125 g, respectively. On day 7, weights were 131.67 ± 1.67, 133.33 ± 1.67, and 135 ± 2.89 g, respectively. Whereas, on day 14, weights elevated to 143.33 ± 1.67, 143.33 ± 1.67, and 145 ± 2.89 g, respectively (p < 0.05).
Effect of LC50 of AcF and EtF Extracts on Differential WBC Count
After 14 days of treatment with the most potent insecticidal extracts (AcF and EtF), there was a non-significant (p > 0.05) effect on the values of WBC, lymphocytes, monocytes, neutrophils, eosinophils, and segmented cells with AcF-treated samples compared to the control (Table 3). Conversely, EtF-treated samples reflected a significant reduction only in the monocytes (612 ± 159.80 × 10 3 /µL) compared with the control (1006 ± 255.60 × 10 3 /µL) (p < 0.05) (Tables 3 and 4).
Effect of LC50 of AcF and EtF Extracts on RBC Count and Indices
Treated groups (with the LC50 concentration of AcF and EtF extracts) reflected nonsignificant (p > 0.05) alternations in total red blood cell count (RBC), hemoglobin, After 14 days of treatment with the most potent insecticidal extracts (AcF and EtF), there was a non-significant (p > 0.05) effect on the values of WBC, lymphocytes, monocytes, neutrophils, eosinophils, and segmented cells with AcF-treated samples compared to the control (Table 3). Conversely, EtF-treated samples reflected a significant reduction only in the monocytes (612 ± 159.80 × 10 3 /µL) compared with the control (1006 ± 255.60 × 10 3 /µL) (p < 0.05) (Tables 3 and 4). The results of the liver function (acid phosphatase, alkaline phosphatase, and alanine transaminase activities) and kidneys function (urea and creatinine) showed that no considerable significance was detected in the activity of acid phosphatase (ACP) with AcF and EtF extracts (3.18 ± 0.52 and 2.65 ± 0.56 U/L, respectively) when compared with the control (2.25 ± 0.29 U/L) (p > 0.05). Similarly, the activity of alkaline phosphatase (ALP) had no notable alternations compared with the control (342.67 ± 4.63, 329 ± 2.08, and 329.33 ± 2.40 IU/L, respectively) (p > 0.05). Whereas, a significant elevation (p < 0.05) was detected in alanine transaminase (ALT) activity in the group treated with AcF as 36.73 ± 1.44 IU/L compared with the control at 25.04 ± 1.99 IU/L ( Table 5). Urea concentration showed a non-significant effect (p > 0.05) in groups treated with AcF and EtF (33.4 ± 1.07 and 34.10 ± 1.31 g/dL), respectively, compared with the control (30.9 ± 0.53). Probably, creatinine had non-significant changes in AcF and EtF groups (29.05 ± 0.52 and 28.67 ± 1.91 mg/dL), respectively, compared with the control (27.37 ± 0.40 mg/dL) (p > 0.05) ( Table 5).
Effect of LC 50 of AcF and EtF Extracts on Total Cholesterol and Triglycerides
The quantitative analysis of total cholesterol showed a significant decrease with the AcF-treated group (67.33 ± 3.84 mg/dL) (p < 0.05) while a significant elevation was seen with the EtF group (100.67 ± 12.67 mg/dL) when compared with the control (76 ± 3.06 mg/dL). Whereas, the triglycerides content was 77.33 ± 9.94 mg/dL in the control and had minor changes after exposure to AcF (65.67 ± 5.49 mg/dL). Similarly, the EtF treated group reflected a significant elevation in triglycerides (134.67 ± 41.91 mg/dL) (p < 0.05) ( Figure 5).
Histopathological Findings and Lesion Scoring
Heart from the control group showed normal myocardial muscles bundles with normal striations and normal nucleation with no histopathological alterations ( Figure 6a); heart from the AcF and EtF groups revealed normal histology as the control group (Figure 6b,c). Lungs from the control group revealed normal bronchiole, alveoli, and interstitial tissues with no signs of inflammation (Figure 6d), while lungs from the AcF and EtF groups showed slight inflammatory signs in the form of a mildly congested blood vessel with thick muscle wall and slight peri-bronchial and interstitial tissue mononuclear cells infiltrations (Figure 6e,f). Liver from all experimental groups reported normal hepatic parenchyma with organized hepatic cords, normal blood sinusoids, and central vein (Figure 6g), and portal (Figure 6h,i). Kidneys from the control animals showed normal renal glomeruli, renal tubules, and interstitial tissues with no signs of degeneration (Figure 6j), while kidneys from the AcF and EtF groups showed vacuolar degeneration in some renal tubules (Figure 6k,l). Moreover, all the recorded lesions in the heart, lungs, liver, and kidneys were scored, as shown in Table 6.
Histopathological Findings and Lesion Scoring
Heart from the control group showed normal myocardial muscles bundles with normal striations and normal nucleation with no histopathological alterations ( Figure 6a); heart from the AcF and EtF groups revealed normal histology as the control group ( Figure 6b,c). Lungs from the control group revealed normal bronchiole, alveoli, and interstitial tissues with no signs of inflammation (Figure 6d), while lungs from the AcF and EtF groups showed slight inflammatory signs in the form of a mildly congested blood vessel with thick muscle wall and slight peri-bronchial and interstitial tissue mononuclear cells infiltrations (Figure 6e,f). Liver from all experimental groups reported normal hepatic parenchyma with organized hepatic cords, normal blood sinusoids, and central vein ( Figure 6g), and portal tract (Figure 6h,i). Kidneys from the control animals showed normal renal glomeruli, renal tubules, and interstitial tissues with no signs of degeneration (Figure 6j), while kidneys from the AcF and EtF groups showed vacuolar degeneration in some renal tubules (Figure 6k,l). Moreover, all the recorded lesions in the heart, lungs, liver, and kidneys were scored, as shown in Table 6.
Recently, various plant materials are being used as pesticides (insecticides). Mackled et al. [39] found that the essential oils of Mentha piperita, Pinus roxburghii, and Rosa spp. were highly effective against some stored product pests. Moreover, the results of Zhou et al. [40] revealed that plant derivatives of Dracocephalum integrifolium had a potential value against Aphis pomi. Extracts and fractions of Trillium govanianum indicate a promising insecticidal activity towards Plutella xylostella and Aphis craccivora larvae [41]. According to our data, the toxicity of AcF and EtF at different concentrations (60,50,40,30, and 20 mg/L) AcF, and (100, 50, 40, 30, and 20 mg/L) for EtF for 24, 48, and 72 h, reflected that the lowest LC 50 value (39 mg/L) was for AcF after 72 h, and 42 mg/L for EtF. These results showed that the AcF extract is more potent than EtF extract, which is in an agreement with Abdelkhalek et al. [13], who found that the acetone fraction of water hyacinth was the most effective against Agrotis ipsilon. Similarly, Jayanthi et al. [20] found that water hyacinth extracts have insecticidal activity against Culex quinquefasciatus and the mortality increased by increasing the concentrations. Conversely, Reddy et al. [42] illustrated that parthenium hysterophorus extract was less toxic to A. craccivora due to its LC 50 value (947.87 mg/L) compared with parthenin insecticide, which had an LC 50 value (839 mg/L). Furthermore, there was a reduction in the number of aphid progeny in samples treated with both tested extracts (AcF and EtF). These results are in an agreement with Thakshila et al. [43], who stated that the aqueous solution of Calotropis gigantea and Croton laccifera leaf extracts decreased the fecundity of A. craccivora significantly. Moreover, Soliman et al. [44] evaluated that the extracts of Nerium oleander and Yucca glauca (with different solvents) reduced the number of aphid's offspring remarkably.
According to Komalamisra et al. [45], if the LC 50 value was less than 50 mg/L, the plant extract was considered a promising insecticide, while the extracts with LC 50 values ranged between 100-500 mg/L were to have moderate insecticidal potency. Moreover, the presence of some fatty acids in the insecticidal formulation improves its toxicological efficacy against targeted pests. Such fatty acids are environmentally safe for vertebrates, have low persistence, and do not have resistance build-up in pests [46]. For example, Yousef et al. [47] investigated the toxicological potency of linoleic acid against different larval instars of Spodoptera littoralis and it showed a highly significant insecticidal effect with LC 50 values of 4.7 and 9.11 g/100 mL for 2nd and 4th larval instars, respectively. In addition, Mostafa et al. [48] found the effectiveness of three fatty acids (stearic, oleic, and linoleic acids) against the 4th larval instar of Earias insulana. Their results revealed that the stearic acid had the highest effect, followed by oleic and linoleic acids, and all of them had deleterious effects on the biological and biochemical parameters.
However, these criteria are dependent on the duration of exposure to the plant material and the susceptibility of the insect stage, which may change the values of LC 50 of examined phytochemicals [49]. Thus, the presence of fatty acids (n-hexadecanoic acid, linolenic acid, hexadecanoic acid), phytol, and hexahydrofarnesyl acetone in AcF and EtF extracts-and according to the revealed results-makes them very promising to complete for further insecticidal formulations and field application as green insecticidal agents.
In order to confirm the eligibility of a pesticide and its introduction to the field application, the pesticide must go through a series of animal studies to determine the hazardous effects that may be expected after acute and chronic exposure [50]. Furthermore, it is mandatory to follow sets of international guidelines and maintain the national legislation [51]. The safety evaluation of the most toxic plant extracts of E. crassipes (acetone (AcF) and ethanol fractions (EtF) was conducted by using the lethal median concentration (LC 50 ), which kills 50% of the insect population in albino rats as a mammalian model (non-target organism). There was no mortality observed in animals treated with the LC 50 (240 and 370 mg/L for AcF and EtF, respectively), indicating the safety of the used extract. These results agree with Huma et al. [52] and Lalitha et al. [16], who found that the ethyl acetate and methanolic extracts of water hyacinth are safe with doses of 500-2000 mg/Kg body weight, which is greater than the doses used in the current research.
As body weight is considered one of the animal health indicators, our findings reflected a normal gradual increase in body weight, which indicated the safety of used extracts. These outcomes were in concurrence with that shown in some studies [53,54].
The analysis of hematological and biochemical indices indicated crucial illustrations of the changes in the physiology of the blood due to diseases or xenobiotics exposure in animal models [55]. The results showed total WBC count, lymphocyte, neutrophils, eosinophils, segmented cells, RBC count, hemoglobin, hematocrit, MCV, MCH, MCHC, and platelet counts of treated animals with AcF and EtF of water hyacinth did not reveal any remarkable alternations compared to the control group. This is in agreement with Mirza and Panchal [53], who investigated non-significant increases with most of the hematological parameters when treated with vanillic acid, and even the significant increases and reductions were in the normal range. However, our data indicated a significant decrease in monocytes numbers with the EtF extract-treated group; it cannot be considered a sign of inflammation because of their number in the reference range. Moreover, our results had a disagreement with Akintimehin et al. [56], who found that the ethanol leaf extract of Justicia carnea caused an increase in RBC, PVC, hemoglobin, and platelet and a significant decrease in WBC, lymphocytes, and granulocytes levels. Another controversial study indicated that a highly significant decrease in WBC, lymphocytes, and monocytes percentages occurred when animals were treated with leaves extract of Eruca sativa and indicated that the leaves extract had some adverse effects on the blood indices [57]. Therefore, the hematological indices indicated the safety of E. crassipes AcF and EtF extracts.
Among the biochemical indices evaluated in the current study were ACP, ALP, ALT, urea, creatinine, total cholesterol, and triglycerides. ACP is located in the cellular lysosome and catalyzes the peroxidation of the lysosomal membrane. Furthermore, the elevation in ACP activity in the liver may be an indicator of lysosomal membrane damage and enzymes liberation [58]. The resulting data indicated no significant changes in ACP activity. This is in disagreement with the results of Sharma et al. [58]. ALP is an enzymatic marker for the destruction of the plasma membrane and is used for testing its integrity [59]. The outcomes cleared a non-remarkable modification in the activity of ALP are consistent with Ahmad et al. [54]. Moreover, Nwosu et al. [60] had an opposite reflection as they showed that the activity of ALP was reduced in treated rats with the botanical extract. ALT is a critical marker for detecting the organ's disruption, particularly liver and kidney. It is frequently produced in the serum when the hepatic membrane is damaged as a result of chemical exposure [61]. The presented outcomes showed a remarkable rising in the activity of ALT in animals treated with AcF compared with the control group. Nevertheless, this rising is considered to be within the normal ALT range of up to 45 IU/L as reported by Derbalah et al. [62]. This shows an agreement with other studies [54,63].
Blood urea and serum creatinine are critical indicators utilized for diagnosing kidney implementation [64]. Urea is the main nitrogen-containing protein breakdown metabolic byproduct [65]. Furthermore, creatinine is also the muscles' metabolic byproduct. Therefore, their accumulation in blood with high levels indicates physiological implementations and kidney injury [66]. Our results revealed normal concentrations of both urea and creatinine. These findings disagree with Kanu et al. [67], who found that levels of urea and creatinine were elevated significantly throughout the exposure period to chemically synthesized pesticides reflecting its deleterious effects on the renal functions. Moreover, the data are in concordance with Thangavelu et al. [68], who showed that the Acacia catechu seed extract was non-toxic to kidney.
Highly accumulative levels of lipids are one of the most crucial factors in cardiovascular disorders [69]. The most serious lipids associated with these cases are total cholesterol and triglycerides [70]. In the current study, the treatment with AcF extract reflected a significant depletion in cholesterol and a non-significant reduction in triglycerides. Whereas, EtF-treated groups had a non-remarkable elevation in both cholesterol and triglycerides levels since the elevated concentrations of triglycerides are associated with a high risk of heart and blood vessels diseases. Thus, there was no cholesterol accumulation in the blood vessels of treated animals, and the levels of triglycerides were still in the normal range, so no cardiovascular dysfunction occurred. This shows an agreement with the results obtained by Arwora et al. [69] and Hadi et al. [57].
Histopathological examination of treated groups' liver showed normal hepatic architecture without any alternations, even in the number of Kupffer cells (which activated and increased to eliminate the xenobiotics from hepatic cells). This supports the obtained biochemical results of ACP, ALP, and ALT. There was no damage observed in heart histology in AcF and EtF treated groups compared to the control group. However, the lungs had a mild inflammatory effect in groups treated with AcF and EtF extracts, the inflammation in pulmonary tissues did not indicate the toxicity of the extracts but may be a result of the existence of some active phytochemicals in the extracts. In addition, the rats did not have any respiratory discomfort during the experimental period. Kidneys tissues reflected a slight vacuolar degeneration; such few changes in the histology of AcF and EtF groups may be due to the daily intake of tested extracts [56]. Moreover, the urea and creatinine results supported normal kidney functionality. Our data were in conformity with many studies [56,60,71]. Conversely, our results disagreed with Ugagu et al. [72] and Maxwell et al. [73].
According to the aforementioned results and illustrations about the chemical composition of tested extracts, toxicological activities against Aphis craccivora, and the activities of hematological, biochemical parameters, and histopathological examination of different experimental animal groups, the use of AcF and EtF extracts of E. crassipes is considered safe as insecticidal agents in integrated pest management programs until further safety investigations are conducted.
Conclusions and Future Perspectives
Based on the obtained data, acetone and ethanol fractions of E. crassipes and their main elaborated components, n-hexadecanoic, linolenic, hexadecenoic, myristic, stearic acids, and linolelaidic acid, methyl ester and some terpenoids, alkaloids, and hydrocarbons displayed an insecticidal potency against A. craccivora adults and had a significant effect on aphids fecundity. The exposure of albino rats to the most potent insecticidal water hyacinth extracts (AcF and EtF) revealed normal changes in body weight, hematopoietic system, liver and kidney functions, cholesterol, and triglycerides levels. In addition, the histopathological examination showed mild effects on lungs and kidneys, which rank the extracts in the safe range for mammals. Therefore, this research study recommended that the AcF and EtF extract of water hyacinth should be considered as environmentally green insecticides and can be involved in integrated pest management programs. Furthermore, there is a need for further experiments on a field scale, some beneficial insects, and female rats' hormones and the histopathological alterations of their reproductive system to detect more safety investigations.
Plant Sample and Extraction
The plants of E. crassipes (fresh and mature) were collected from Zhanjiang city, Guangdong province, China. The plant identification was carried out at the Botany laboratory, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China. Then, plants were thoroughly rinsed using distilled water and then dried at room tem-perature~26 • C. Thereafter, an electrical blender was used for grinding the dried plants. The preparation and modifications of fractionated extracts (acetone and ethanol fractions) were prepared according to our previously published work [13]. LC 50 concentrations of AcF and EtF (240 and 370 mg/L, respectively) extracts were used in this study. The LC 50 concentrations used in the current research were determined according to the previous bioassay test for Agrotis ipsilon [13]. Since it is stronger than Aphis craccivora, we used their LC 50 to be more accurate in the safety assessment tests.
Gas Chromatography-Mass Spectrometry (GC-MS) Analysis
The chemical composition of samples was performed using a Trace GC1310-ISQ mass spectrometer (Thermo Scientific, Austin, TX, USA) with a direct capillary column TG-5MS (30 m × 0.25 mm × 0.25 µm film thickness). The column oven temperature was initially held at 50 • C and then increased by 5 • C/min to 230 • C held for 2 min and increased to the final temperature of 290 • C by 30 • C min and held for 2 min. The injector and MS transfer line temperatures were kept at 250 and 260 • C, respectively; helium was used as a carrier gas at a constant flow rate of 1 mL/min. The solvent delay was 3 min and diluted samples of 1 µL were injected automatically using an Autosampler AS1300 coupled with GC in the split mode. EI mass spectra were collected at 70 eV ionization voltages over the range of m/z 40-1000 in full scan mode. The ion source temperature was set at 200 • C. The components were identified by comparison of their retention times and mass spectra with those of WILEY 09 and NIST 11 mass spectral databases.
Aphis craccivora Rearing
Parthenogenetic aphids were reared on previously planted broad beans plants (Vicia faba L.) on clay soil in plastic pots (7 cm diameter and 10 cm depth) under controlled laboratory conditions with a temperature of 22 ± 2 • C, relative humidity 75%, and photoperiod of 16:8 (Light: Dark) according to Soliman et al. [44] The newly ecdyced adults were selected for the experiments.
Efficacy/Bioassay of AcF and EtF Extracts of E. crassipes against A. craccivora
Five concentrations of each extract were prepared as 60, 50, 40, 30, and 20 mg/L for AcF and 100, 50, 40, 30, and 20 mg/L for EtF. Distilled water was used for the control groups. The insecticidal evaluation of the extracts was done using the leaf-dipping technique. Groups of ten wingless aphids were placed in Petri-dishes (9 cm diameter and 1.5 cm depth) having broad bean leaves dipped in the desired concentration for 10 s. Then, all dishes were placed in an adjusted plant growth room at 22 ± 2 • C, 75% RH, and 16:8 L:D. Five replicates were prepared for each concentration (one dish for each replicate) and each replicate had ten individuals. Accordingly, each concentration has 50 aphids. After 24, 48, and 72 h the mortality of aphid was determined by gently probing using a fine-haired brush [44]. Numbers of aphid progeny (offspring) were also assessed in order to determine the effects of tested concentrations on the fecundity of aphids. Aphids were counted by a magnifying glass.
The bioassay against A. craccivora was conducted at low doses and safety assessment experiments were done at higher doses (240 and 370 mg/L) based on our previous research [13].
Animals
This research included 15 female albino rats weighing 125-135 g. They were randomly categorized into three groups with five animals in each. Group 1: was treated with the LC 50 AcF extract (240 mg/L). Group 2: was treated with the LC 50 of EtF extract (370 mg/L), and Group 3 was the control group with only distilled water. Rats were housed under the optimum climatic conditions (relative humidity 25-75%, temperature 25 ± 5 • C, and photoperiod 12/12 light and dark cycles for 14 days). They were given the required doses (1 mL/mg) of body weight orally by gavage according to the LC 50 of the insecticidal extracts of E. crassipes. All experimental procedures were approved and performed by the Research Ethics Committee (REC) for Animal Subject Research affiliated with Ain Shams University, Egypt (Ethics approval number: 1,8467, 2015), according to the World Health Organization (WHO) guidelines for animal care [51].
Body Weight and Blood Sampling
The body weight of each animal was recorded weekly during the three weeks experimental period. At the end of the experiment (14th day), rats had the last dose and starved overnight. Ultimately, they were sacrificed by cervical dislocation and the blood samples were collected through the orbital plexus into test tubes, some of them with EDTA as an anticoagulant for hematological parameters determination. The remaining tubes were without anticoagulant for the biochemical analysis.
Hematological and Biochemical Indices Determination
Hematological parameters of collected blood samples were analyzed using an automated hematology analyzer ABX Micros 60 (HORIBA Ltd., Montpellier, France). The blood indices were performed and included the total count of white blood cells (WBC), lymphocytes, monocytes, neutrophils, eosinophils, segmented cells, total red blood cell count (RBC), hemoglobin, hematocrit, mean cell hemoglobin (MCH), mean corpuscular cell volume (MCV), MCH concentration (MCHC), and platelets count.
Biochemical indices for liver and kidney function, such as acid phosphatase (ACP), alkaline phosphatase (ALP), alanine transaminase (ALT), urea, creatinine, total cholesterol, and triglycerides were determined using the serum of collected samples. They measured according to the protocols provided in the used commercial laboratory kits, BIODIAGNOS-TIC (BIODIAGNOSTIC, Giza, Egypt) for ACP, ALP, ALT, urea, and creatinine. Cholesterol and triglycerides levels were measured with the SPINREACT kit (Ctra. Santa Coloma, 7 E-17176 SANT ESTEVE DE BAS (Barcelona, Spain).
Histopathological Examination
By the end of the experiment (14th day), the heart, lungs, liver, and kidneys were collected from different experimental groups and routinely processed. The paraffin-embedded blocks were sectioned at a 5-micron thickness and stained with Hematoxylin and Eosin [74] for histopathological examination by a light microscope (Olympus BX50, Tokyo, Japan).
Statistical Analysis
The mortality percentages were corrected in regard to the control using Abbott's formula [76]. The values of lethal concentrations (LC 50 ) and slope were calculated according to Finney [77], using probit analysis software. All provided data were expressed as mean ± standard error (SE) of the mean. Differences between the experimental groups were obtained by one-way ANOVA followed by Tukey's test through the SPSS software version 22.0 (SPSS, Inc., Chicago, IL, USA) which was used for data analysis. Significant results were observed at a p < 0.05 level. | 6,858.6 | 2022-05-01T00:00:00.000 | [
"Environmental Science",
"Biology"
] |
The Role of the N-Terminal Domains of Bacterial Initiator DnaA in the Assembly and Regulation of the Bacterial Replication Initiation Complex
The primary role of the bacterial protein DnaA is to initiate chromosomal replication. The DnaA protein binds to DNA at the origin of chromosomal replication (oriC) and assembles into a filament that unwinds double-stranded DNA. Through interaction with various other proteins, DnaA also controls the frequency and/or timing of chromosomal replication at the initiation step. Escherichia coli DnaA also recruits DnaB helicase, which is present in unwound single-stranded DNA and in turn recruits other protein machinery for replication. Additionally, DnaA regulates the expression of certain genes in E. coli and a few other species. Acting as a multifunctional factor, DnaA is composed of four domains that have distinct, mutually dependent roles. For example, C-terminal domain IV interacts with double-stranded DnaA boxes. Domain III drives ATP-dependent oligomerization, allowing the protein to form a filament that unwinds DNA and subsequently binds to and stabilizes single-stranded DNA in the initial replication bubble; this domain also interacts with multiple proteins that control oligomerization. Domain II constitutes a flexible linker between C-terminal domains III–IV and N-terminal domain I, which mediates intermolecular interactions between DnaA and binds to other proteins that affect DnaA activity and/or formation of the initiation complex. Of these four domains, the role of the N-terminus (domains I–II) in the assembly of the initiation complex is the least understood and appears to be the most species-dependent region of the protein. Thus, in this review, we focus on the function of the N-terminus of DnaA in orisome formation and the regulation of its activity in the initiation complex in different bacteria.
Introduction
Chromosomal replication is a key step in cell cycle progression in all organisms of the three domains of life: Bacteria, Archaea, and Eukaryota. This process begins by the assembly of a multiprotein complex at a predefined locus (multiple loci in Archaea and Eukaryota) on a chromosome, which is called the origin(s) of chromosomal replication (ori, in bacteria called oriC) [1,2]. The main roles of these nucleoprotein initiation complexes are to recognize the ori site, to distort the double helix, and to provide a platform for the assembly of the multiprotein replication machinery, termed the replisome, that will synthesize the nascent chromosome [3,4]. Chromosomal replication is highly regulated, mainly at the first step (initiation), to ensure that DNA replication does not begin under conditions that prevent the cell from completing the process, thus preventing the cell from dividing and producing a viable offspring cell [5,6].
The general mechanism of replication initiation is similar in all organisms. However, the number of initiation complexes per chromosome, initiation complex composition, protein-protein and protein-DNA interactions between initiation complex components, and check-point steps vary among organisms, with greater differences occurring among more unrelated taxonomic groups [3,4]. It is assumed that the molecular mechanism of replication initiation and its control are simplest in bacteria and most complex in Eukaryota. Indeed, the composition of the initiation complex in bacteria is less intricate than in organisms from the other two domains of life [1]. Nonetheless, the bacterial initiator protein DnaA is highly specialized, such that it can perform the functions of distinct subunits of Archaeal and Eukaryotic initiation complexes. For example, all initiators, including bacterial DnaA, Archaeal Orc1/Cdc6, or Eukaryotic Orc1-Orc6 origin recognition complex (ORC), recognize ori sites. However, in contrast to the last two, which are unable to melt DNA, only DnaA unwinds DNA and recruits other replisome proteins, especially the replicative helicase DnaB, to the newly formed single-stranded replication eye [7,8]. The DnaA protein and oriC are also the main factors controlling the assembly of the initiation complex or are subjected to control mechanisms that restrict the number of replications to one per cell cycle [6,9,10]. It is noteworthy that in some species, e.g., Escherichia coli or Bacillus subtilis, DnaA also serves as a transcription factor [11,12]. Thus, DnaA is a multifunctional protein, which is reflected by its complex structure and structure-function related activities.
Bacterial DnaA-General Overview of the Structure and Function
To form a bacterial initiation complex, often called an orisome, DnaA binds to DNA at oriC and employs protein-protein interactions between protomers to assemble into a helical filament that is capable of opening double-stranded DNA (dsDNA) at the DNA unwinding element (DUE) [13]. DnaA is encoded by the dnaA gene, which is found in nearly all bacterial species. Exceptions include a few endosymbiotic bacteria, such as Azolla filiculoides, Blochmannia floridanus, and Wigglesworthia glossinidia, which lack a functional dnaA gene. In these bacteria, the initiator protein and mechanisms of initiation of chromosomal replication remain unidentified [14][15][16]. The DnaA proteins in bacteria characterized thus far vary in molecular weight between 47 kDa and 73 kDa (399-amino acid Aquifex aeolicus DnaA and 656-amino acid Streptomyces coelicolor DnaA, respectively). DnaA is composed of four structural and functional domains ( Figure 1). The C-terminal domain IV encompasses approx. 120 amino acids (~13 kDa) and, together with domain III (approx. 230 amino acids,~25 kDa), constitutes the most conserved part of DnaA with regard to structure and function. Domain II, which links domain III and domain I, is the most diverse domain between species with respect to sequence and length, varying between approx. 20 amino acids (~2 kDa) in Helicobacter pylori and approx. 250 amino acids (~28 kDa) in S. coelicolor. However, it should be noted that some DnaA proteins, such as the A. aeolicus initiator protein, appear to lack domain II ( Figure 2) [17]. N-terminal domain I is composed of approx. 75-110 amino acids (~8-12 kD) (74 amino acids in A. aeolicus DnaA, 90 amino acids in E. coli DnaA, 108 amino acids in Mycobacterium tuberculosis DnaA), and in contrast to a well-conserved secondary structure, its sequence is poorly conserved among unrelated bacterial species.
Domain IV is responsible for DNA binding via a helix-turn-helix motif ( Figure 1). The domain recognizes 9-mer, non-palindromic DNA sequences called DnaA boxes that are clustered at oriC (E. coli consensus sequence: 5 -TTATNCACA-3 ). Domain III belongs to the ATPases Associated with diverse cellular Activities (AAA+) class of proteins; upon interaction with adenosine triphosphate (ATP), but not adenosine diphosphate (ADP), domain III changes conformation to enable the protein to properly oligomerize into a filament. The structure of such a filament bound to dsDNA and the means by which DnaA melts oriC is not fully understood. Nonetheless, the interaction between DnaA monomers within the filament introduce a conformational change in the bound DNA to melt its double-stranded structure at the DUE [18][19][20]. Subsequently, multiple domain III's of the filament bind to and stabilize single-stranded DNA (ssDNA) via initiator-specific motifs (ISMs) [18,[21][22][23][24]. E. coli DnaA domain III, together with domain I, recruits DnaB helicase to an open complex and helps position the helicase onto the ssDNA [25,26]; however, DnaA interactions with DnaB helicase and helicase loaders vary among species [27][28][29][30]. It should be noted that filamentation is mediated by domain III and controlled by other proteins that interact directly with this domain, such as a complex of the beta subunit of the DNA polymerase III (β-clamp) and the protein homologous to DnaA (Hda) (β-clamp-Hda-complex) in E. coli and possibly in Caulobacter crescentus or the sporulation initiation inhibitor protein Soj and the initiation-control protein YabA in B. subtilis [31][32][33][34][35]. Interestingly, as shown for E. coli DnaA, domains III and IV are sufficient in vitro for opening the oriC region; i.e., proteins that lack domains I and II unwind oriC in vitro in a manner similar to that of the full-length protein [36]. However, N-terminally truncated DnaA does not support DNA replication in vitro and is not viable in vivo, which indicates that the N-terminal part of E. coli DnaA is required to maintain its function in bacterial cells. Indeed, it has been shown that DnaA domain I, similar to domain III, mediates interactions between DnaA monomers and interacts with other proteins, including the helicase DnaB (see below).
Although the N-terminal domain is crucial for DnaA activity in vivo, its role in orisome formation is the least understood of the four domains. The reason for that is, in part, related to the lack of structure of full-length DnaA. The structure of the N-terminal portion of DnaA [37,38], which consists of a largely unstructured domain II and independently solved structures of domains III-IV [13,17,22], does not allow us to predict how the N-terminal domain is positioned within the orisome and how domain I is oriented with regard to the C-terminal domains III and IV. Due to the flexible domain II, DnaA domain I appears to be structurally detached from domains III-IV; however, it does affect DnaA activity in the orisome. Moreover, domain I is sensitive to regulation by cellular proteins ( Figure 1B) that appear to coordinate DnaA activity with the bacterial growth phase or cell cycle, stress, or unknown stimuli. Domain I possibly controls the transition from the initiation phase to the elongation phase in E. coli through mutually exclusive interactions with regulatory proteins and DnaB. Altogether, the findings indicate that domain I is important for the activity of DnaA at the orisome. domain III and controlled by other proteins that interact directly with this domain, such as a complex of the beta subunit of the DNA polymerase III (β-clamp) and the protein homologous to DnaA (Hda) (β-clamp-Hda-complex) in E. coli and possibly in Caulobacter crescentus or the sporulation initiation inhibitor protein Soj and the initiation-control protein YabA in B. subtilis [31][32][33][34][35]. Interestingly, as shown for E. coli DnaA, domains III and IV are sufficient in vitro for opening the oriC region; i.e., proteins that lack domains I and II unwind oriC in vitro in a manner similar to that of the full-length protein [36]. However, N-terminally truncated DnaA does not support DNA replication in vitro and is not viable in vivo, which indicates that the N-terminal part of E. coli DnaA is required to maintain its function in bacterial cells. Indeed, it has been shown that DnaA domain I, similar to domain III, mediates interactions between DnaA monomers and interacts with other proteins, including the helicase DnaB (see below).
Although the N-terminal domain is crucial for DnaA activity in vivo, its role in orisome formation is the least understood of the four domains. The reason for that is, in part, related to the lack of structure of full-length DnaA. The structure of the N-terminal portion of DnaA [37,38], which consists of a largely unstructured domain II and independently solved structures of domains III-IV [13,17,22], does not allow us to predict how the N-terminal domain is positioned within the orisome and how domain I is oriented with regard to the C-terminal domains III and IV. Due to the flexible domain II, DnaA domain I appears to be structurally detached from domains III-IV; however, it does affect DnaA activity in the orisome. Moreover, domain I is sensitive to regulation by cellular proteins ( Figure 1B) that appear to coordinate DnaA activity with the bacterial growth phase or cell cycle, stress, or unknown stimuli. Domain I possibly controls the transition from the initiation phase to the elongation phase in E. coli through mutually exclusive interactions with regulatory proteins and DnaB. Altogether, the findings indicate that domain I is important for the activity of DnaA at the orisome. [39]. Secondary elements of domains I-II are marked in green (α-helices) and brown (β-strands). Dark green and dark brown correspond to experimentally resolved structures of H. pylori (pdb 2WP0), E. coli (pdb 2E0G), B. subtilis (pdb 4TPS), and M. genitalium (pdb 2JMP) DnaAs; light green and light brown correspond to predicted secondary structures of C. crescentus, M. tuberculosis, and A. aeolicus DnaAs. The coloured fonts indicate conserved residues in domain I (violet, red, and pink from highest to lowest conservation, respectively); non-conserved residues are shown in black. Conserved residues involved in domain I dimerization (E. coli W6 (Trp6)), DnaB binding (E. coli E21 (Glu21), and F46 (Phe46)) are marked by a pink pentagon, red triangle, and violet peen, respectively; these symbols correspond to Figure 1. [39]. Secondary elements of domains I-II are marked in green (α-helices) and brown (β-strands). Dark green and dark brown correspond to experimentally resolved structures of H. pylori (pdb 2WP0), E. coli (pdb 2E0G), B. subtilis (pdb 4TPS), and M. genitalium (pdb 2JMP) DnaAs; light green and light brown correspond to predicted secondary structures of C. crescentus, M. tuberculosis, and A. aeolicus DnaAs. The coloured fonts indicate conserved residues in domain I (violet, red, and pink from highest to lowest conservation, respectively); non-conserved residues are shown in black. Conserved residues involved in domain I dimerization (E. coli W6 (Trp6)), DnaB binding (E. coli E21 (Glu21), and F46 (Phe46)) are marked by a pink pentagon, red triangle, and violet peen, respectively; these symbols correspond to Figure 1.
Structures of Bacterial DnaA Domains I and II
The structures of E. coli, B. subtilis, H. pylori, and Mycoplasma genitalium DnaA domain I have been solved; for the last, however, no functional analyses have been performed to date. Despite high sequence diversity (Figure 2), domain I is structurally conserved and consists of α-helices and β-strands ( Figure 3). E. coli domain I is composed of 3 α-helices and 3 β-strands in the order of α1-α2-β1-β2-α3-β3 [37,38]. H. pylori DnaA is missing one β-strand between α1 and α2 [40], and B. subtilis DnaA contains an extra α4 helix between α3 and β3 [41]; M. genitalium contains two additional α-helices in the order of α1-α2-β1-β2-α3-α-β3-α [38] (Figure 3). Structurally, the α-helices and β-strands form distinct surfaces; an exception is for M. genitalium, in which the β-strands are packed between helices α1-α2 and α3-α4 at one site and α5 at the other. The β-strands comprise a β-sheet; however, the functional roles of the individual β-strands and entire β-sheet in domain I are unknown. The α helices are involved in different protein-protein interactions, and α1 of E. coli DnaA, together with a loop between β1-β2, forms a hydrophobic patch that engages in intermolecular interactions between the N-termini of DnaA monomers [37,42,43]. Nonetheless, this hydrophobic patch is not conserved among all DnaAs; for example, it is not present in H. pylori DnaA, and the N-terminus of this DnaA does not dimerize [40]. The α2 and α3 helices of E. coli, H. pylori, and B. subtilis DnaAs interact with other proteins (the DnaA initiator-associating factor DiaA and DnaB [37,44], the Helicobacter orisome binding protein A (HobA) [40], and the sporulation inhibitor of replication SirA [41], respectively), and despite a lack of sequence conservation, they are proposed to form structurally conserved protein-protein interaction surfaces utilized by regulatory proteins to control DnaA activity (see below) [41,44].
Structures of Bacterial DnaA Domains I and II
The structures of E. coli, B. subtilis, H. pylori, and Mycoplasma genitalium DnaA domain I have been solved; for the last, however, no functional analyses have been performed to date. Despite high sequence diversity (Figure 2), domain I is structurally conserved and consists of α-helices and βstrands ( Figure 3). E. coli domain I is composed of 3 α-helices and 3 β-strands in the order of α1-α2-β1-β2-α3-β3 [37,38]. H. pylori DnaA is missing one β-strand between α1 and α2 [40], and B. subtilis DnaA contains an extra α4 helix between α3 and β3 [41]; M. genitalium contains two additional αhelices in the order of α1-α2-β1-β2-α3-α-β3-α [38] (Figure 3). Structurally, the α-helices and β-strands form distinct surfaces; an exception is for M. genitalium, in which the β-strands are packed between helices α1-α2 and α3-α4 at one site and α5 at the other. The β-strands comprise a β-sheet; however, the functional roles of the individual β-strands and entire β-sheet in domain I are unknown. The α helices are involved in different protein-protein interactions, and α1 of E. coli DnaA, together with a loop between β1-β2, forms a hydrophobic patch that engages in intermolecular interactions between the N-termini of DnaA monomers [37,42,43]. Nonetheless, this hydrophobic patch is not conserved among all DnaAs; for example, it is not present in H. pylori DnaA, and the N-terminus of this DnaA does not dimerize [40]. The α2 and α3 helices of E. coli, H. pylori, and B. subtilis DnaAs interact with other proteins (the DnaA initiator-associating factor DiaA and DnaB [37,44], the Helicobacter orisome binding protein A (HobA) [40], and the sporulation inhibitor of replication SirA [41], respectively), and despite a lack of sequence conservation, they are proposed to form structurally conserved protein-protein interaction surfaces utilized by regulatory proteins to control DnaA activity (see below) [41,44]. It has been reported that the structure of DnaA domain I is similar to the K homology domain (KH domain) [37,40]. KH domains interact with RNA and ssDNA nucleic acids, and affinity toward ssDNA or RNA is increased by the presence of multiple KH domains [45]. Additionally, the It has been reported that the structure of DnaA domain I is similar to the K homology domain (KH domain) [37,40]. KH domains interact with RNA and ssDNA nucleic acids, and affinity toward ssDNA or RNA is increased by the presence of multiple KH domains [45]. Additionally, the N-terminus of E. coli DnaA weakly interacts with ssDNA [37], though DnaA lacking domain I is able to unwind DNA and stabilize ssDNA via the ISM motif located in domain III [21,36,46]. Therefore, it remains unknown whether the KH motif plays any role in ssDNA binding upon unwinding of DNA by DnaA.
Domain II is unstructured and the most variable in sequence ( Figure 2). Accordingly, there is little information about the possible motifs in regions that function in overall DnaA structure or function, especially within the context of mutual interdependence between domain I and domains III-IV.
Escherichia Coli DnaA Domain I
E. coli is a gram-negative, non-sporulating, facultatively anaerobic bacterium. Although E. coli constitutes a natural microflora in the lower intestine of warm-blooded organisms, including humans, some strains are pathogenic. This bacterium can survive and multiply outside of its host despite a decline in growth over time. The genomes of natural isolates of E. coli range from 4.5 to 6.0 Mb and encode approx. 4200-6500 genes. The bacterium has been used as a model organism for studying bacterial processes, including chromosomal replication and the cell cycle. Therefore, E. coli DnaA is one of the best characterized initiator proteins, especially within the context of structure-function relationships. In fact, studies on E. coli DnaA pioneered work on other initiators, including those in Archaea and Eukaryota. The resolved structure of E. coli DnaA domain I (1-86 aa) complements comprehensive biochemical data collected to date. It has been shown that domain I is engaged in numerous protein-protein interactions that include other DnaA monomers, as well as proteins that regulate DnaA activity at the orisome (DiaA, the histone-like protein HU, the ribosomal protein L2, the DNA-binding proteins from starved cells Dps, cryptic prophage protein YfdR, the β-clamp-Hda complex). Domain I of E. coli DnaA also participates in recruiting the replisome protein DnaB helicase; thus, it is important for the transition between the initiation and DNA synthesis (elongation) phases of replication.
The amino acids important for domain I head-to-head dimerization have been mapped to a patch formed by helix α1 and the loop between β1 and β2 (Figures 2 and 3; amino acids leucine 5 (Leu5), tryptophan 6 (Trp6), glutamine 8 (Gln8), cysteine 9 (Cys9), Leu10, and Leu33) [37,42,43,47,48]. Regardless, how these interactions impact the structure and function of the entire DnaA protein, especially within the context of the assembled orisome, is still not fully understood. It has been suggested that N-terminal domains of E. coli DnaA, possibly due to dimerization of domain I, mediate long-distance interactions between DnaA monomers (Figure 1), similar to S. coelicolor (see below), and that this interaction facilitates or stabilizes DnaA binding to distantly located DnaA binding sites [49,50]. Dimerization might also be important to facilitate cooperativity of DnaA binding to closely spaced DnaA boxes, particularly for those with low affinity [49,51,52]. Indeed, domain I promotes DnaA oligomerization at oriC, possibly by bringing DnaA monomers into a closer contact so they can make a filament via domain III ( Figure 1) [42,43]. The N-terminal domain is also required for DnaB loading [43]; DnaA defective in dimerisation via domain I (e.g., DnaA lacking the N-terminal domain or DnaA mutated at the amino acid Trp6, which is critical for domain I dimerization), is not able to load DnaB onto an open complex despite the fact that it can unwind DNA and bind to DnaB via a second interaction surface located at domain III [36,43,53]. It was suggested that dimerized domain I of DnaA oligomers at oriC provides an array of sites that, together with domain III, stably bind to DnaB and help load helicase onto ssDNA (Figure 1) [23,37]. Indeed, DnaB interacts with DnaA domain I via the amino acids glutamic acid 21 (Glu21) and phenylalanine 46 (Phe46), which are located on helix α2 and α3, respectively, i.e., at the region opposite from the α1 dimerization surface (Figures 3 and 4) [36,37,53]. Such localization of surface interaction allows domain I to simultaneously dimerize and interact with DnaB.
As they are also engaged in interactions with DiaA and Hda regulatory proteins, DnaA helices α2 and α3 exposed to protein surfaces appear to be a hot spot for protein-protein interactions. DiaA is found in many bacterial species [54,55]. Although E. coli DiaA is not essential in vivo, it stimulates chromosomal replication, controls synchrony of initiation events, and ensures that the process is coordinated with the cell cycle [56]. Upon orisome formation, the DiaA tetramer simultaneously binds to multiple DnaA molecules and stimulates the assembly of DnaA onto oriC, which in turn facilitates the unwinding of the oriC duplex DNA [55]. In particular, amino acids Glu21 and Trp25 on α2 and asparagine 44 (Asn44), Phe46, and Trp50 on α3 are important for DiaA binding (Figure 4) [31,44,55]. Moreover, it has been shown that DiaA and DnaB compete for binding to DnaA and that DiaA bound to DnaA inhibits the DnaA-DnaB interaction and DnaB loading onto DnaA multimers at oriC [44]. These results demonstrate that DiaA controls DnaB loading [44,57]. The possible mechanism that regulates DiaA binding to DnaA is not known; however, it has been suggested that unknown cellular factors control DnaA-DiaA interactions [44]. coordinated with the cell cycle [56]. Upon orisome formation, the DiaA tetramer simultaneously binds to multiple DnaA molecules and stimulates the assembly of DnaA onto oriC, which in turn facilitates the unwinding of the oriC duplex DNA [55]. In particular, amino acids Glu21 and Trp25 on α2 and asparagine 44 (Asn44), Phe46, and Trp50 on α3 are important for DiaA binding (Figure 4) [31,44,55]. Moreover, it has been shown that DiaA and DnaB compete for binding to DnaA and that DiaA bound to DnaA inhibits the DnaA-DnaB interaction and DnaB loading onto DnaA multimers at oriC [44]. These results demonstrate that DiaA controls DnaB loading [44,57]. The possible mechanism that regulates DiaA binding to DnaA is not known; however, it has been suggested that unknown cellular factors control DnaA-DiaA interactions [44]. Hda plays a pivotal role in regulating DnaA activity via a mechanism called RIDA (regulatory inactivation of DnaA). Hda consists of an N-terminal β-clamp-binding consensus sequence and the AAA+ domain, which shares homology with DnaA domain III. Hda-ADP in a complex with a βclamp of DNA polymerase III interacts with DnaA domains I, III, and IV shortly after initiation [31,58], and inter-AAA+ interactions between domain III of E. coli DnaA and Hda stimulate the hydrolysis of ATP bound to DnaA [31,59]. DnaA-ADP is not able to properly oligomerize and unwind DNA; thus, it is inactive for initiation until it becomes reactivated into DnaA-ATP, which occurs either by DnaA de novo synthesis or by the interaction of DnaA-ADP with DnaA-reactivating sequences (DARS) or phospholipids (see below) [6,60,61]. Interactions between domains I and IV with Hda likely stabilize the complex and promote interactions between the AAA+ domains. In particular, DnaA mutated at Asn44 or lysine 54 (Lys54) located on helix α3 is insensitive to RIDA in vitro and in vivo [31]. Interestingly, E. coli domain I has also been proposed to participate in the transition of DnaA-ADP into DnaA-ATP, which is able to initiate replication [62]. Such an exchange of nucleotides, called rejuvenation, is promoted by the interaction between DnaA domain III and Hda plays a pivotal role in regulating DnaA activity via a mechanism called RIDA (regulatory inactivation of DnaA). Hda consists of an N-terminal β-clamp-binding consensus sequence and the AAA+ domain, which shares homology with DnaA domain III. Hda-ADP in a complex with a β-clamp of DNA polymerase III interacts with DnaA domains I, III, and IV shortly after initiation [31,58], and inter-AAA+ interactions between domain III of E. coli DnaA and Hda stimulate the hydrolysis of ATP bound to DnaA [31,59]. DnaA-ADP is not able to properly oligomerize and unwind DNA; thus, it is inactive for initiation until it becomes reactivated into DnaA-ATP, which occurs either by DnaA de novo synthesis or by the interaction of DnaA-ADP with DnaA-reactivating sequences (DARS) or phospholipids (see below) [6,60,61]. Interactions between domains I and IV with Hda likely stabilize the complex and promote interactions between the AAA+ domains. In particular, DnaA mutated at Asn44 or lysine 54 (Lys54) located on helix α3 is insensitive to RIDA in vitro and in vivo [31]. Interestingly, E. coli domain I has also been proposed to participate in the transition of DnaA-ADP into DnaA-ATP, which is able to initiate replication [62]. Such an exchange of nucleotides, called rejuvenation, is promoted by the interaction between DnaA domain III and acidic phospholipids in the cell membrane [61]. However, it has recently been demonstrated that this process strongly depends on DnaA protein membrane occupancy, which affects the functional state of DnaA [62,63]. It was proposed that domain I is particularly important for rejuvenation associated with DnaA density-driven, cooperative oligomerization [62].
The molecular mechanisms of DnaA domain I interactions with HU, Dps, L2, and YfdR, and their roles in the initiation of chromosomal replication are much less understood than those described above. The HU protein is a DNA-binding protein that functions in compaction of the bacterial chromosome (by inducing DNA bends) and regulates DNA-related processes, including replication and transcription [64]. HU is composed of two subunits, α and β, that can form homo-and heterodimers. HU is known to stimulate in vitro DNA unwinding by DnaA, though the mechanism remains obscure [7,65]. Recently, it was shown that HU directly interacts with DnaA and that this interaction stabilizes DnaA oligomers assembled at oriC [66]. In particular, DnaA domain I preferentially binds to the α subunit of HU, either as an α2 or αβ dimer. In vitro, the α2 homodimer stimulates DNA replication more efficiently than αβ or β2. In vivo, the composition of the subunits in a dimer changes with the growth phase: the α2 dimer predominates during early log-phase growth but decreases to only approx. 5% of HU in the stationary phase [67]. Moreover, inactivation of the α but not the β subunit perturbs coordination between the initiation of DNA replication and the cell cycle. These findings suggest that HU facilitates initiation of chromosomal replication in E. coli during logarithmic growth.
In contrast to HU, proteins Dps, L2, and YfdR inhibit initiation [68][69][70]. Dps is synthesized upon exposure to environmental stress (e.g., oxidation, starvation) and protects DNA from oxidative stress via three intrinsic activities: DNA binding, iron sequestration, and ferroxidase enzymatic activity [71]. In vitro, Dps weakly inhibits DnaA-dependent replication of plasmids; however, the protein significantly (but not completely) inhibits chromosomal replication in vivo [68]. Interestingly, Dps synthesis is especially induced in oxygen-stressed cells during the logarithmic phase of growth. Under these conditions, Dps might be especially important for protecting replicating DNA and for inhibiting new rounds of DNA synthesis. However, it has been suggested that incomplete inhibition of replication initiation might allow for the synthesis of nascent DNA with mutations and, as a consequence, an increase in genetic variation within a population in response to oxidative stress [68].
L2 is a ribosomal protein that has recently been shown to interact with the N-terminus of DnaA [70]. In vitro, L2 and its truncated form, which lacks 59 N-terminal amino acids, destabilizes DnaA oligomers at oriC and thus inhibits DnaA-dependent DUE unwinding. Thus, L2 interferes with prepriming complex formation because it precludes DnaB loading, which is required for further replisome assembly. It has been suggested that L2 coordinates replication with transcription under specific, yet unknown, conditions. YfdR, a protein encoded by a set of genes of the cryptic phage CPS-53, binds to domain I of E. coli DnaA in a Phe46-dependent manner [69]. Consistently, YfdR inhibits the binding of other Phe46-dependent proteins, DiaA and DnaB, to DnaA. YfdR also reduces the initiation of plasmid replication in vitro. Although the exact role of the YfdR protein is still not clarified, it has been suggested that the protein may regulate replication under specific stress conditions because the cryptic phage CPS-53 is involved in response to oxidative and acid stresses.
Bacillus Subtilis DnaA Domain I
B. subtilis is a gram-positive soil bacterium that sporulates under suboptimal growth conditions [72,73]. The genomes of natural isolates of B. subtilis range from 4.0 to 4.3 Mb and encode approx. 4000-4500 genes. Many B. subtilis cellular processes, including chromosomal replication, adjust to environmental conditions to promote vegetative growth, sporulation, or spore germination. Accordingly, a master Spo0A regulator, which is responsible for entry into sporulation, directly controls the activity of oriC [74,75] and indirectly regulates DnaA (see below). B. subtilis oriC is bipartite, i.e., it contains two clusters of DnaA boxes separated by a dnaA gene; both clusters are required for the initiation of chromosomal replication in vivo [76,77]. In vitro, DnaA binds to both sub-regions, acting as a bridge and looping out the dnaA gene [78]. B. subtilis DnaA-ATP has been shown to interact with oriC in a manner characteristic of AAA+ proteins; upon orisome assembly, DnaA-ATP forms a helix-like structure that unwinds DNA and binds to ssDNA [33,46]. Domain III of B. subtilis DnaA has a predominant role in DnaA filament assembly and is thus a target for binding numerous regulatory proteins, such as Soj, YabA, and the primosomal protein DnaD, none of which is found in E. coli [33,34,79]. In fact, B. subtilis DnaA domain III is the best characterized domain of the entire DnaA protein, whereas the roles of the other domains in the formation and activity of the initiation complex are much less understood. Knowledge of the role of the B. subtilis N-terminal domains (1-86 aa domain I, 87-111 aa domain II) in orisome assembly is particularly scarce. It is known that the N-terminal domains are not required for filament formation and ssDNA binding by B. subtilis DnaA in vitro [46], though it remains unclear whether B. subtilis DnaA domain I dimerizes. Most residues involved in the dimerization of E. coli DnaA domain I are conserved in B. subtilis DnaA (Figures 2 and 3), and 22 amino acids of the N-terminus of the latter can functionally replace the 20 N-terminal residues of the former (i.e., helix α1) [48]. Such a hybrid protein complements the temperature-sensitive (Ts) growth phenotype of the dnaA46 mutant strain WM2063, though E. coli DnaA lacking 23 N-terminal amino acids is unable to complement this Ts strain. This suggests that the interaction between molecules of B. subtilis DnaA via domain I may occur and play a role in formation of the DnaA-oriC complex. This hypothesis is supported by the fact that SirA, which interacts with domain I of B. subtilis DnaA, displaces the initiator protein from oriC when incubated with the DnaA-oriC complex [80]. In vivo, SirA is produced under Spo0A∼P regulation and inhibits new rounds of replication prior to sporulation [80,81]. SirA forms a heterodimer with domain I of DnaA via interaction with initiator protein α2 and α3 helices. In addition, certain amino acids in domain I (Trp27, Asn47, Phe49, and alanine 50 (Ala50)) were shown to be especially important for interaction with SirA [41,82] (Figure 4). It is noteworthy that SirA also interacts with domain III [83] and, together with domain III-binding Soj and oriC-interacting Spo0A, controls B. subtilis chromosomal replication and coordinates replication during the transition from a vegetative to dormant state [74,83,84].
Unlike in E. coli, B. subtilis DnaA domain I appears to play no role in helicase recruitment into an open complex. Thus far, no interactions between B. subtilis DnaA domain I and helicase DnaC or helicase loading proteins (a loader-DnaI, a co-loader-DnaB, and an assisting protein-DnaD; please note the differences in helicase-related nomenclature; DnaD interacts with domain III of DnaA) have been reported [29,85]. Moreover, B. subtilis helicase is loaded onto ssDNA via a "ring-making" mechanism, which is different from the "ring-breaking" mechanism in E. coli [86,87]. Thus, distinct protein-protein interactions might be involved in helicase assembly into an open complex.
Helicobacter Pylori DnaA Domain I
H. pylori is a gram-negative pathogenic bacterium that resides in the human stomach, a relatively stable, albeit hostile, ecological niche [88,89]. The genomes of natural isolates of H. pylori range from 1.5 to 1.7 Mb and encode approx. 1400-1800 genes, with only a few regulatory proteins controlling cellular processes [90,91]. H. pylori oriC resembles B. subtilis oriC, i.e., it is bipartite and consists of two clusters of DnaA boxes, oriC1 and oriC2, separated by a dnaA gene [92]. The structure of H. pylori oriC and DnaA-DNA interactions have recently been well characterized [92][93][94][95], but there are limited biochemical data for H. pylori DnaA, particularly concerning domain III. For instance, it is not known whether H. pylori is regulated by ATP binding and hydrolysis, and no protein homologous to Hda has been found in H. pylori. Moreover, no proteins interacting with domain III of H. pylori DnaA have been identified thus far. As domain III is highly homologous among species, it likely forms a filament that is typical of DnaA. The N-terminus of H. pylori DnaA has been relatively well characterized. It comprises 110 amino acids (1-90 amino acids domain I, 91-110 amino acids domain II) and does not self-associate [40], possibly due to structural obstacles that may preclude dimerization. These obstacles include a shorter helix α1, a lack of conserved Trp6, and a positively charged (non-hydrophobic) area of interaction. H. pylori DnaA domain I interacts with HobA, a protein essential for H. pylori survival. To date, HobA is the only known protein that interacts with DnaA, and it influences DnaA assembly at oriC [96,97]. Indeed, HobA binding to DnaA stimulates DnaA oligomerization at oriC1 [54]. Despite low sequence homology, HobA is a structural and functional homologue of E. coli DiaA [54,98]. Similar to DiaA and SirA, HobA interacts with DnaA helices α2 and α3 [40], and residues tyrosine 29 (Tyr29), Asn28, and Gln32 on α2, and Lys61, valine 53 (Val53), Gln52, Asn51, Thr56, and Ala60 on α3 have been shown to be involved in interactions with HobA ( Figure 4). However, DiaA and HobA cannot substitute for each other in vitro or in vivo because DiaA-E. coli DnaA and HobA-H. pylori DnaA interaction surfaces co-evolved [54]. Despite the high functional homology between DiaA and HobA, the dynamics of HobA/DiaA-stimulated oligomerization differ. HobA enhances and accelerates H. pylori DnaA binding to oriC, whereas DiaA increases but decelerates E. coli DnaA binding to oriC. Interestingly, the kinetics of responses involving domains III-IV do not depend on the stimulating protein (DiaA or HobA). In a hybrid system in which E. coli domain I was fused to domains II-IV of H. pylori DnaA (Ec I Hp II-IV DnaA), DiaA stimulated Ec I Hp II-IV DnaA in a manner similar to that of HobA stimulation of H. pylori DnaA, though with a sensitivity characteristic of DiaA [54]. This suggests that HobA or DiaA binding to cognate DnaA stimulates subsequent interaction, possibly between domain III, and that an induced response depends on domain III, the activity of which apparently differs slightly between these species.
It is not known whether the N-terminus of H. pylori DnaA or any domain of the DnaA protein participates in helicase loading onto an open complex because no DnaA-DnaB interactions, either between isolated proteins or within an orisome, have been shown thus far. Glu21, which is important for interactions of E. coli DnaA with E. coli DnaB, is present in H. pylori (Glu 25), but Phe46 is missing. It should be noted that H. pylori DnaB helicase is atypical, and unlike bacterial hexameric helicases, it forms a dodecamer that dissociates into hexamers upon interaction with DnaG primase [99,100]. Regardless, the mechanism for DnaB loading onto an open complex is still unknown.
Streptomyces Coelicolor DnaA Domain I
S. coelicolor is a gram-positive soil bacterium. It possesses a large, 9 Mb chromosome encoding approx. 8300 genes, which is almost twice as large as the E. coli or B. subtilis chromosome. S. coelicolor grows as substrate mycelia, which differentiate into an aerial mycelium and spores upon nutrient depletion. The key elements of the initiation of S. coelicolor chromosomal replication, DnaA and oriC, have been identified, and their interactions have been characterized [101][102][103][104][105][106]. S. coelicolor oriC contains two clusters of DnaA boxes separated by a short spacer DNA [103]; in total, there are 19 DnaA boxes spread over nearly 1000 bp. The DnaA-DNA complexes formed on both sides of the DNA spacer interact with each other to form a hairpin-like structure [106]. Although this resembles DnaA binding to bipartite origins in B. subtilis and H. pylori, the number of distinct nucleoprotein complexes is higher in S. coelicolor (up to 4 complexes per hairpin) than in the other two bacteria (1 complex per loop), as visualized by electron microscopy [78,92,106]. S. coelicolor DnaA is one of the largest known DnaA proteins (656 amino acids) due to the presence of a long domain II, which comprises an additional stretch (approx. 150 amino acids) of predominantly acidic amino acids. Such an exceptionally large domain II should enable DnaA dimers or oligomers to interact with distantly located DnaA boxes to establish a functional nucleoprotein complex. Domain I of the S. coelicolor DnaA protein dimerises [106], and together with domain III it participates in DnaA oligomerization [105,106]. It is possible that domain I mediates interactions between DnaA bound to distal DnaA boxes, whereas domain III mediates interactions between closely spaced boxes [106]. In addition, DnaA lacking domain I aggregates strongly upon DNA binding; thus, domain I should support the correct DnaA structure upon orisome formation [106]. Nonetheless, there is no detailed information concerning possible interaction surfaces or amino acids that participate in domain I intermolecular interactions, and there are no known proteins that interact with S. coelicolor DnaA. Thus, further studies are required to gain insight into protein-protein interactions that lead to assembly or regulation of a functional S. coelicolor orisome.
DnaA Domain II
Domain II was initially regarded as only a flexible linker that joins domain I with domains III-IV. However, it has been suggested that "nonessential" regions of domain II may be transiently involved in DnaB recruitment, and this domain, similar to DiaA, is presumably required to promote optimal helicase loading [107]. Moreover, domain II can be extended, and it tolerates the insertion of structured fragments. This was shown in E. coli, whereby green fluorescent protein (GFP) of 238 amino acids was inserted into domain II or into the C-terminal region of domain I (right after β3), without the loss of DnaA functionality in vivo [108,109]. In fact, it was the only location of GFP in DnaA that was tolerated by the E. coli protein. In addition, comprehensive deletion analysis within domain II of E. coli DnaA showed that at least 21-27 residues are required to sustain the correct conformation of the entire protein, possibly because they properly align domain I with domains III-IV [110]. Furthermore, deletions shortening E. coli domain II resulted in an under-initiation phenotype [107,111], which raises the question of how domain I and domains III-IV are aligned in proteins that have almost no existing domain II. Because domain I plays an important role in the cooperative binding of DnaA molecules at oriC, it is tempting to speculate that the length of domain II is adjusted according to the spacing between DnaA boxes. Regarding this hypothesis, the S. coelicolor DnaA protein can bind to widely spaced DnaA boxes due to the presence of a long domain II, whereas the H. pylori DnaA protein, with a relatively short domain II, binds to closely spaced H. pylori DnaA boxes [3]. It should reminded here, that the N-terminal domain I of H. pylori DnaA does not dimerise (Section 3.4, see also below), however, the direct interactions between the N-terminal domains of DnaA might be substituted by not-direct, HobA mediated, tetramerisation of DnaA [40,112].
Conclusions and Perspectives
The N-terminal domains of bacterial DnaAs are essential for full protein activity upon initiation of chromosomal replication, ensuring cooperativity of the protein in DNA binding and correct spatial assembly at oriC. This, in turn, is required for proper control of orisome activity with respect to further replisome assembly (e.g., DnaB loading) and the transition from the initiation to the DNA synthesis step. The N-terminal domains are also engaged in coordinating chromosomal replication with the cell cycle (e.g., sporulation) and other cellular processes (e.g., transcription) or environmental conditions (e.g., oxidative stress).
It should be noted that the N-terminal domains exhibit the least conserved sequence (Figure 2), and accordingly, it has been shown that the N-termini of DnaA from various species have different activities or interactions (Figure 1). The N-terminal domains likely evolved to meet the requirements of species that reflect differences in the structures of oriCs, the mechanisms of replisome assembly and the strategies of regulating DnaA activity. However, there are relatively few experimental data that assert the general features of the N-terminal domains with respect to the structure-function relationship of orisomes in different species. Nonetheless, dimerization and interaction with other proteins are the most conservative features of domain I. Domain II serves as a linker that coordinates the function of largely independent domains I, III, and IV.
It was experimentally shown that domain I in E. coli and S. coelicolor DnaAs dimerize. Helix α1 is crucial for dimerization in E. coli, but amino acids and interaction surfaces involved in S. coelicolor DnaA dimerization are unknown. In contrast, H. pylori DnaA domain I was shown not to interact, and there are no data regarding the dimerization of B. subtilis DnaA domain I. It was proposed that domain I dimerization and a sufficiently long, flexible domain II help to establish long-distance interactions. Thus, it was suggested that for some orisomes, domain I dimerization is not important when DnaA boxes are closely spaced at oriC, such as for H. pylori oriC [93,95,113]. However, H. pylori DnaA participates in long-distance interactions between DnaA-oriC1 and DnaA-oriC2 subcomplexes [92], raising the question of which domain (or domains) mediates the interactions between subcomplexes in H. pylori, B. subtilis, and other bipartite orisomes (e.g., mollicutes or Epsilonproteobacteria) [9,85,114].
Interaction of DnaA domain I with other proteins (E. coli DiaA, H. pylori HobA, and B. subtilis SirA) is mediated by helices α2 and α3, which likely comprise a common interface for protein-protein interactions (Figure 4). Interactions with DiaA and HobA are species specific, i.e., one protein cannot be substituted with another for interaction with DnaA in other species. Although it is not known whether SirA-DnaA interaction is also species specific, the amino acid sequence within the B. subtilis DnaA α2-α3 interface is quite different from that of E. coli and H. pylori DnaAs (Figure 4). In the structure-function relationship, it appears that proteins that bind multiple DnaA molecules, such as DiaA or HobA, stimulate DnaA oligomerization, whereas proteins that bind only a single DnaA protomer, such as SirA, destabilize DnaA oligomers. Multimerization of domain I might be important for cooperative binding of DnaA with DnaA boxes or for assembly of the multi-protomer interface for protein-protein interactions. When this interaction interface is released by DiaA/HobA, it can be further utilized by other proteins, such as when it is used by E. coli DnaB. However, proteins such as SirA might destabilize dimerization or the multi-protomer interface and thus preclude cooperative DNA binding or inhibit the loading of other proteins. It would be interesting to analyse how SirA affects oligomerization of hybrid DnaAs (E. coli (Bs I Ec II-IV DnaA) or H. pylori (Bs I Hp II-IV DnaA)), in which domain I is swapped for B. subtilis domain I. Such proteins should be able to interact with SirA, and this interaction could possibly destabilize orisomes formed by chimeric DnaAs.
Interaction between DnaA domain I and the helicase has only been demonstrated for E. coli. However, the interaction between DnaA domain III and helicase loader/loader assisting proteins appears to be more common in bacteria (DnaC binds to A. aeolicus DnaA [27], and DnaD interacts with B. subtilis DnaA [34,79]). It is reasonable to assume that by participating in helicase loading and activation, DnaA might be a key factor controlling the transition from initiation to elongation. More studies are required to reveal whether the binding between helicase and domain I of DnaA depends on the helicase loading mechanism (ring-making in E. coli vs. ring-breaking in B. subtilis), the loading proteins (E. coli DnaC, B. subtilis DnaI, or recently discovered DciA [30]), the oriC structure (E. coli mono-vs. B. subtilis bipartite), or other species-specific factors.
As mentioned above, domain I has various activities and has a different number and variety of interacting partners. The fact that there is a large discrepancy between the known activities exhibited by E. coli DnaA and initiators from other species is especially puzzling. Within this context, the N-terminus of E. coli DnaA appears to be an omnipotent domain. However, within the context of environmental challenges, physiology, and genetics, E. coli is not that different from other species, particularly B. subtilis or S. coelicolor. This makes it difficult to justify such an increase or decrease in the properties or interaction partners (seven, one, and zero DnaA interacting partners have been discovered thus far in E. coli, B. subtilis, and S. coelicolor, respectively- Figure 1). Nonetheless, these species have different life cycles. Thus, for example, because E. coli is unable to sporulate, it may require additional or different regulatory proteins to control chromosomal replication, whereas B. subtilis and S. coelicolor enter a dormant state under similar unfavourable conditions. Indeed, the initiation of B. subtilis chromosomal replication is controlled by Spo0A, SojA, and SirA, which are proteins associated with sporulation cycle control. Nonetheless, information is likely missing for many proteins that can interact with the N-terminal domain of DnaAs from other species, which, in turn, may regulate the initiation of chromosomal replication. For example, no interacting partners are known for C. crescentus, S. coelicolor, and M. tuberculosis DnaAs. It should be noted that in some bacteria, the number of proteins that regulate replication might be very low. For example, in H. pylori, a bacterium known for an overall limited number of regulatory proteins (compare approx. 30 proteins involved in signal transduction in H. pylori with approx. 300 and 1000 proteins in E. coli/B. subtilis and S. coelicolor, respectively [115]), the number of DnaA-interacting proteins might not be much higher than has been identified thus far. However, it is also possible that alternative pathways have been developed to control DnaA activity in B. subtilis, S coelicolor, H. pylori, and other bacteria. For example, it appears that B. subtilis DnaA is controlled primarily at domain III, whereas C. crescentus DnaA is primarily controlled at the levels of expression and proteolysis [116].
Functional and structural studies on E. coli DnaA-DiaA and H. pylori DnaA-HobA heterocomplexes have revealed relatively high specificity of interactions between initiation proteins [54]. This finding opens new possibilities for selective pathogen eradication by targeting essential protein-protein interactions involved in the initiation of chromosomal replication. Indeed, replication proteins are increasingly being considered as drug targets [117,118], among which species-specific domain I interactions appear promising. Thus, further studies will be important to increase our knowledge about the role of the N-terminus in controlling the initiation of bacterial chromosomal replication. | 11,198.6 | 2017-05-01T00:00:00.000 | [
"Biology",
"Chemistry"
] |