robench-2024b
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48 items • Updated
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<|MaskedSetence|> Convolutional neural networks (CNNs) are a class of deep neural networks characterized by a shared-weight architecture of convolution kernels (or filters) that slide along input features and provide translation equivariant features known as feature maps. One of the main advantages of CNNs is that the... | **A**: I used these datasets to characterize and analyze the performance of different CNNs network architectures and GPU accelerators, using a standard, off–the–shelf, deep learning computational library.
Material and methods
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**B**: CNNs have also been used for the detection of lymph node metastases in women with ... | CBA | CBA | CBA | CBA | Selection 1 |
While single jumps across a fitness valley can be regarded as metastable transitions, the limiting jump chain can be related to the concept of adaptive walks or flights. Those are stochastic processes that directly study the motion of the macroscopic population on the trait space, focussing on successful invasions an... | **A**: In adaptive flights, transitions are not just possible between neighbouring traits but from one local fitness maximum to another [23, 24, 22, 30].
**B**: This relates back to the limiting processes derived in this paper, where the population jumps between equilibrium states that are surrounded by valleys of tra... | CAB | CAB | CAB | CAB | Selection 1 |
The subsequent sections of the paper unfold as follows: Section 2: Model formulation- In this section, we meticulously detail the formulation of the model, providing a comprehensive overview of its deterministic aspects. <|MaskedSetence|> <|MaskedSetence|> Section 5: Numerical experiments- this section is dedicated... | **A**: This section serves to summarize key results, implications, and potential avenues for future research.
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**B**: Section 3: Dynamics of the deterministic model- we discuss the reproduction number and stability of the system.
**C**: Section 4: Formulation and description of stochastic COVID-19 model- we explore... | BCA | BCA | BCA | BCA | Selection 3 |
<|MaskedSetence|> Although numerous studies report high heritability for anatomical features such as gray matter density, there are few rs-fMRI studies reporting heritability of rs-fMRI (Glahn et al., 2010; Korgaonkar et al., 2014). <|MaskedSetence|> <|MaskedSetence|> (Korgaonkar et al., 2014) reported HI of 0.41 in... | **A**: (Glahn et al., 2010) reported HI of 0.104 in the left cerebellum, 0.304 in the right cerebellum, 0.331 in the left temporal parietal region, 0.420 in the right temporal parietal region.
**B**: We reported 10 connections that give the highest HI values in all three states in Tables 3, 3 and 3.
**C**: Most of th... | BCA | BCA | ACB | BCA | Selection 2 |
System (50) with its initial and boundary conditions is also interesting from a mathematical viewpoint: it describes a novel sort of taxis cascade, in which tumor cells are chemotactically following ECs, which in turn bias their motion towards gradients of a chemical signal (VEGF) produced by tumor cells and depleted ... | **A**: However, the increasingly fast development of biomedical imaging, computing power, and technology for necessary cell biology experiments will provide a means to assess at least some of the missing quantitative information.
**B**: On the other hand, such multiscale models seem to offer an adequate frame for stud... | ABC | ABC | ABC | BCA | Selection 1 |
Our analyses leverage brain images sourced from academic publications and the open-access website www.brainmuseum.org. The calculated gyral sizes across species are visually represented in Fig. 12 and enumerated in Tables 1, 2, and 3. Note that our data are sample-based. <|MaskedSetence|> The limitations imposed by t... | **A**: Additionally, factors such as image quality and scale bar size could affect the accuracy of measurements.
**B**: Instead, we focus on discerning patterns between gyral size and other factors across multiple species.
**C**: Specifically, when more than one sample is available for the same species, each sample i... | CBA | CBA | CBA | CAB | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> We initially selected random hyperparameter values for the training of each model on a random fold (out of 5555 folds). Subsequently, we repeated the training of each model on all 5555 folds based on the best-performing hyperparameters of the initial random fold.... | **A**: Additionally, 10%percent1010\%10 % of the training partition of each fold was reserved for validation and hyperparameter tuning.
**B**:
In the model training process, we adopted a Stratified 5-Folds cross-validation strategy.
**C**: This method ensures that the test split maintains a balanced representation o... | BCA | BCA | BCA | ACB | Selection 3 |
<|MaskedSetence|> Hodge theory provides a unified framework combining simplicial homology and spectral geometry, offering insights into network topology [9, 10, 11]. <|MaskedSetence|> Hodge decomposition breaks data defined on edges (edge flow) into three orthogonal components: gradient, curl, and harmonic flows, eac... | **A**: The gradient flow, driven by node gradients, represents the network’s gradient-like behavior.
**B**: While the Hodge Laplacian, a generalization of the graph Laplacian, offers insights into the topological features of higher order simplices, the Hodge decomposition allows to establish relationships between simp... | CBA | CBA | CBA | CBA | Selection 1 |
Fig. 4: Interpretability and visualization of FACL. Randomized selections of WSIs from external datasets, DiagSet-A and QHD, are arranged in the first and second rows, respectively. The sequence progresses from left to right, showcasing the complete WSI, followed by its heatmap, a close-up of a local patch, and finally... | **A**: The zoomed-in view of the local patch image indicates our model’s precise identification and representation of cancerous regions.
The validation results for the Gleason scoring task are listed in Table 7.
**B**: Compared to models trained on single-center data, the FACL model exhibited significant improvement... | ABC | ABC | ABC | ACB | Selection 3 |
Beyond, the recent use of SBs has been motivated by an important task in molecular biology: Cells change their molecular profile throughout developmental processes (Schiebinger et al., 2019; Bunne et al., 2022b) or in response to perturbations such as cancer drugs (Lotfollahi et al., 2019; Bunne et al., 2021). <|Maske... | **A**: (2022b) propose a transcriptome profiling approach that preserves cell viability.
**B**: For example, Chen et al.
**C**: As most measurement technologies are destructive assays, i.e., the same cell cannot be observed twice nor fully profiled over time, these methods aim at reconstructing cell dynamics from unp... | CBA | CAB | CBA | CBA | Selection 3 |
<|MaskedSetence|> We do so for a one-dimensional i-state (i.e., the variable capturing the relevant differences among individuals ‘lives’ on the real line), so for an i-state space that comes equipped with an order relation. In fact we shall assume that the presence of ‘larger’ individuals has a negative impact on the... | **A**: In Section 2 we first present the classic PDE formulation of the model.
**B**: Here our aim is to investigate in the context of a toy model the consequences of density dependence that only affects development directly (fertility is affected indirectly, since it depends on the developmental stage of the individu... | CBA | BAC | BAC | BAC | Selection 2 |
8.2 Brain Networks from fMRI Data
Functional MRI is a non invasive technique for collecting data on brain activity that measures the increase in the oxygenation level at some specific brain region, as long as an increase in blood flow occurs, due to some brain activity. The construction of a network from fMRI data r... | **A**: Following Ranciati et al.
**B**: We consider two subjects indexed by 14141414 and 15151515, who have the same psychological traits with no neuropsychiatric diseases and right-handedness.
**C**: A detailed description of the project, scopes, and technical aspects can be found at http://fcon_1000.projects.nitrc.... | CAB | CAB | CAB | BAC | Selection 3 |
Cardiac MRI scans contain high-dimensional spatial and temporal features generated throughout the cardiac cycle. The small number of samples compared to the high-dimensional features poses a challenge for machine learning classifiers. To address this issue, Multilinear Principal Component Analysis (MPCA) [11] utilize... | **A**: We use CM features (i.e., left atrial volume and left ventricular mass) identified in the baseline work by Garg et al. [5] for PAWP prediction.
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**B**: To tackle this challenge, we leverage automated landmarks with uncertainty quantification [15] in our pipeline.
**C**: The application of the MPCA method to ... | CBA | BAC | CBA | CBA | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> This yields significantly worse performance −6.9%percent6.9-6.9\%- 6.9 %. We hypothesize that the “true full attention” has low-entropy, making it more challenging to be approximated by low-rank methods [8], and that sparse attention patterns offer better approximations.
Figure 3... | **A**: Both branches bring complementary information (observed decrease of −5.6%percent5.6-5.6\%- 5.6 % and −7.5%percent7.5-7.5\%- 7.5 % in c-index), justifying the need to model both pathway-to-patch and patch-to-pathways interactions.
**B**: We further adapt SurvPath with Nyström attention that enables training on v... | ABC | ABC | ABC | CBA | Selection 2 |
3.6 Non-local feedback to alter system robustness
Another way in which systems can potentially increase their robustness to input noise is through non-local feedback or feedforward loops. <|MaskedSetence|> <|MaskedSetence|> A similar late to early-stage feedback is seen in positive-strand RNA viruses in which newly... | **A**: More generally, positive- and negative-strand RNA viruses have very similar replication structures and an identical feedback mechanism, however are in part distinguished by their feedforward structures [41, 42].
**B**: Hepatitus B, an enveloped DNS virus, recycles new viral DNA that is awaiting repackaging back... | CBA | CBA | BAC | CBA | Selection 2 |
II-E Recurrent Neural Networks (RNN)
Elman networks, more commonly known as vanilla recurrent neural networks (RNN), attempt to introduce the concept of a time-dependent dynamic memory [16]. <|MaskedSetence|> Context-based predictions can be done for four input-output schemes: one-to-one, one-to-many, many-to-one, ... | **A**: One-to-one models are a variation of a classic neural network, one-to-many models are best for image caption generation, many-to-one models are best for sentiment analysis, and many-to-many models are best for translation or video frame captioning.
**B**: The idea is to make predictions about inputs based on co... | BCA | BAC | BAC | BAC | Selection 4 |
<|MaskedSetence|> <|MaskedSetence|> Indeed, as we will show in Section I.3, the quenched regime assumes that, before each topology update, the epidemic has almost reached its equilibrium.
In the annealed regime, the epidemic evolves very slowly compared to the network. The epidemic spreads as on an “average” networ... | **A**: General results for the annealed regime show that the annealed process shares attributes with the static process on the edge-average graph [7, 8, 9].
**B**: Quenched processes are well approximated with processes on static networks and therefore well studied over the last two decades.
**C**:
In the quenched r... | CBA | CBA | CBA | ABC | Selection 3 |
<|MaskedSetence|> <|MaskedSetence|> We explore features of covers arising from networks, and characterise many of the familiar classes in terms of properties of their associated covers. <|MaskedSetence|> Different classes of networks are defined in different ways, and it can be difficult to present a clear hierarchy... | **A**: The class of labellable networks contains many commonly studied classes.
**B**: They have been shown to correspond to a set of covers of finite sets that satisfy a property called “expanding”.
**C**: It is to be hoped that encoding network properties in the properties of sets of sets will enable some new direc... | ABC | ABC | ACB | ABC | Selection 4 |
The ancestral selection graph is an augmented coalescent model for the joint distribution of the gene genealogy and the allelic states of the sample (Krone and Neuhauser, 1997; Neuhauser and Krone, 1997). It includes the usual coalescent rate 1111 per pair of lineages and mutation rate θ/2𝜃2\theta/2italic_θ / 2 per li... | **A**: In this case it is known which lineages are real and which are virtual.
**B**: One of these is real, meaning it is included in the gene genealogy.
**C**: But the allelic states are not known in the construction of the ancestral selection graph.
The conditional ancestral selection graph models gene genealogie... | BAC | BCA | BCA | BCA | Selection 2 |
Firstly, the introduction of annealed disorder in the GLV equations, for any finite correlation time, has exerted a substantial positive influence on the biodiversity of the system. Specifically, when the dynamics of the system converge to the stationary distribution, we observe the quasi-cycles of species populations ... | **A**: We have shown that it not only maintains the core phenomenology described above, but also rectifies any non-physical divergences.
**B**: Again, similar truncated fat-tailed distribution has been recently shown in the chaotic phase [36] and in the strongly interacting limit [5, 41] of the QGLV with immigration.
... | CBA | CBA | CBA | ACB | Selection 3 |
1.5 Structure of the paper
The rest of the paper is structured as follows. In Section 2 we construct a system of MTBDPs that can model the properties and interactions between particles we have discussed so far. <|MaskedSetence|> <|MaskedSetence|> In Section 4 we analyze a special case of an MTBDP system numericall... | **A**: Moreover, this section contains our main theoretical results.
**B**: Finally, in Section 5, we discuss our findings, and compare them to other relevant results from the literature..
**C**: Section 3 is dedicated to their proofs.
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1,667
Table 2: Test set results for different size variations of Prot2Text. <|MaskedSetence|> <|MaskedSetence|> This configuration demonstrates improved performance compared to the smaller model while still maintaining reasonable computational costs. The inference time is in seconds for text generation of each mod... | **A**: Larger models outperform their smaller counterparts across most evaluation metrics, indicating the benefits of employing larger language models in the Prot2Text framework.
**B**: The Prot2TextMEDIUM model, strikes an optimal balance between performance and computational efficiency.
**C**: The inference time he... | ABC | ABC | ABC | BAC | Selection 2 |
From the model-centric perspective, the framework adopted a typical encoder-decoder architecture to extract hierarchical features and integrate them through skip connections. Concretely, SegFormer [48] served as the encoder, while MA-Net [13] was employed as the decoder, utilizing the Mish [34] activation function. The... | **A**: The inference process relied on the sliding window strategy, a highly efficient approach for processing whole-slide images.
**B**: The overall loss function was the combination of binary cross-entropy loss and mean-square error loss.
**C**: Specifically, image intensities were randomized in a cell-wise manner ... | CBA | CBA | ABC | CBA | Selection 4 |
<|MaskedSetence|> For example, a higher-order reduced model is derived using the Haken-Kelso-Bunz (HKB) equation in [36]. <|MaskedSetence|> <|MaskedSetence|> Similarly, there is no restriction to applying our method to questions of coordinated movement, e.g., [25], or studies of coupled population dynamics [39].
O... | **A**: The higher-order terms are the lowest-order Fourier terms of our ℋℋ\mathcal{H}caligraphic_H functions, thus the same questions of existence can be answered with our method and further explored with additional Fourier terms and multi-body interactions.
**B**:
Our method is both a generalization of existing meth... | BCA | BAC | BAC | BAC | Selection 3 |
Recently, the cases of non-Gaussian stable noises acting on QIFs started to attract the attention in mathematical neuroscience. <|MaskedSetence|> In this paper, we explore the possibility of the implementation/generalization of the pseudocumulant approach for/to the populations of QIFs subject to δ𝛿\deltaitalic_δ-cor... | **A**: In Sec. II.4, we derive the governing equation for the dynamics of the characteristic function of the membrane voltage distribution and present the pseudocumulant formalism.
In Sec. III, for the case of noninteger α𝛼\alphaitalic_α, we construct a first-order perturbation theory for the effect of noise on the ch... | BCA | BCA | BAC | BCA | Selection 2 |
<|MaskedSetence|> <|MaskedSetence|> Prediction forces a network to learn spatial proximity and not merely image similarity. <|MaskedSetence|> While similar scenes might be proximate in space, similar scenes can also be spatially divergent. For example, the virtual environment we constructed has two different ‘forest... | **A**: Predictive coding network learns spatial proximity not image similarity
In the previous section, we show that a neural network that performs predictive
coding learns an internal representation of its physical environment within its latent space.
**B**: Here, we demonstrate that the prediction task itself is es... | ABC | CAB | ABC | ABC | Selection 1 |
6 Conclusion
Through more careful counting and bounding compared to previous efforts in this area, we showed that rooted balanced species quartets have no anomaly zones. <|MaskedSetence|> The statements of various Propositions also provide a partial ranking of uniformly sampled gene tree topologies, in results some... | **A**: So, it might be expected that anomaly zones for the caterpillar tree are not an important confounding factor, given their remoteness..
**B**: We also showed that if anomaly zones exist, we have shown the respective anomalous gene trees must be balanced quartets.
**C**: (2022) are comparable to each other, i.e.... | BCA | BCA | BCA | ABC | Selection 1 |
In brain science, predictive coding is one of the most influential hypothesis that can implement hierarchical information processing [3, 4]. <|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> Second, this principle shares exactly the same spirit adopted in variational free energy framework [6]. Recently, there ... | **A**: The framework of predictive coding has several benefits for theoretical research.
**B**: First, the framework can be derived from the first principle that the brain is a biological machine of optimizing neural dynamics and synaptic connections to maximize the evidence of its internal model of the outside world ... | ACB | CAB | CAB | CAB | Selection 2 |
<|MaskedSetence|> <|MaskedSetence|> The images were captured using Leica DMi8 microscope (Leica) equipped with 10×/0.32 objective lens. We obtained one whole slide image from each group.
SegmentAnything and post processing. In our research, we utilized the Python API for SegmentAnything and evaluated three pretrai... | **A**: Data acquisition.
**B**: Bright-field images used in this paper were obtained under the protocol described in [5].
**C**: However, we encountered challenges with the SegmentAnything-generated masks, as is shown in FIg.
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<|MaskedSetence|> <|MaskedSetence|> In this model the local updating rule of the connection parameters in BNNs turns out to be a zero-order optimization procedure. More precisely, it is shown in [10] that the expected value of the iterates coincides with a modified gradient descent. However, this holds only on averag... | **A**: In this seminal study, the author proposes a very persuasive stochastic model for brain-supervised learning
which has a thorough biological foundation in terms of spike-timing-dependent plasticity.
We review and discuss this setup in Section 2.
**B**:
The starting point for the present paper is the recent arti... | BAC | BAC | ACB | BAC | Selection 1 |
Our memristor is inspired and supported by a comprehensive theory directly derived from the underlying physical equations of diffusive and electric continuum ion transport. <|MaskedSetence|> The theory exclusively relies on physical parameters, such as channel dimensions and ion concentrations, and enabled streamlined... | **A**: We also assume that the inhomogeneous ionic space charge distribution is constant, while it might well be voltage-dependent.
**B**: We experimentally quantitatively verified the predictions of our theory on multiple occasions, amongst which the specific and surprising prediction that the memory retention time o... | CAB | BAC | BAC | BAC | Selection 4 |
As mentioned previously, between 2015 and 2016, there was a concerning event in Brazil and Colombia associated with the co-infection of two major viral diseases: Zika and HIV/AIDS brasil2016 ; calvet2016 ; villamil2018 . <|MaskedSetence|> This co-infection not only required costly medical resources but also highlighte... | **A**: The following outlines the main assumptions for extracting these parameter values.
.
**B**: However, specific parameter values were derived from available demographic information, previous research on Zika and HIV/AIDS in Colombia and Brazil, and epidemiological assumptions.
**C**: This problem became a compli... | CBA | CBA | BAC | CBA | Selection 1 |
II Spiking Neural Network of The Basal Ganglia
We are concerned in spiking neural networks for the BG. In 2001, based on the functional anatomy proposed by Gurney et al. GPR1 , they developed an artificial neural network for the BG GPR2 . Later, in 2006, based on the anatomical and physiological data, Humphries et al.... | **A**: In some other spiking neural networks for the BG, instead of the Izhikevich neuron model, the adaptive exponential integrate-and-fire model with two dynamic variables AdEx was used for the BG cells for study of signal enhancement by short-term plasticity CN11 and learning stimulus-action association CN20 .
. ... | CBA | CBA | CBA | CBA | Selection 2 |
<|MaskedSetence|> MCR and VIC do not account for instability. For example, after computing MCR for 738 bootstrap iterations, we find that the MCR for the LINC00486 gene has overlap with 0 in 96.2%percent96.296.2\%96.2 % of bootstrapped datasets, meaning MCR would not allow us to distinguish whether LINC00486 is import... | **A**: Such experiments are time consuming and cost tens of thousands of dollars per donor, so narrowing possible future directions to a small set of genes is of the utmost importance.
**B**:
Note that previous methods – even those that account for the Rashomon effect – could not produce this result.
**C**: Our anal... | BAC | BAC | ACB | BAC | Selection 4 |
<|MaskedSetence|> Excitatory and inhibitory connections are denoted by lines with triangles and circles, respectively, and dopamine-modulated cells and connections are represented in blue color. Striatum and STN (subthalamic nucleus), receiving the excitatory cortical input, are two input nuclei to the BG. In the stri... | **A**: The D1 SPNs make direct inhibitory projection to the output nuclei SNr (substantia nigra pars reticulate) through the direct pathway (DP; green color).
**B**: The inhibitory output from the SNr to the thalamus/brainstem is controlled through competition between the DP and IP.
.
**C**: Finally, we give summary ... | CAB | CAB | CAB | CBA | Selection 2 |
Key results are explicit and computationally efficient time-dependent expressions for the expected mean and the expected variance of an additive quantitative trait under exponential selection. They are presented in Section 4, seem to be entirely new, and provide highly accurate approximations to corresponding Wright-... | **A**: This allows us to examine the genomic patterns associated with the early phase of phenotypic adaptation.
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**B**: In Section 5.1 (and Appendix E), we derive explicit, approximate expressions for the evolution of the expected number of segregating sites.
**C**: Interestingly, they even allow the derivation of ... | CBA | CBA | CBA | ACB | Selection 2 |
Acknowledgement
XL, ZKZ, and BH were supported by the NSFC General Program No. <|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> 2022ZD0160703), 111 plan (No. BP0719010), and National Natural Science Foundation of China (No. 62306178).. | **A**: RC-FNRA-IG/22-23/SCI/04, and HKBU CSD Departmental Incentive Scheme.
JCY was supported by the National Key R&D Program of China (No.
**B**: 62376235, Guangdong Basic and Applied Basic Research Foundation Nos.
**C**: 2022A1515011652 and 2024A1515012399, Tencent AI Lab Rhino-Bird Gift Fund, HKBU Faculty Niche Re... | CAB | BCA | BCA | BCA | Selection 4 |
<|MaskedSetence|> <|MaskedSetence|> In case of measuring the accuracy as a function of position on the list, these experiments were repeated 5 times with 5 different random seeds providing in total 150 repetitions. <|MaskedSetence|> This data is wholly characterized by specifying the mean accuracy at that position i... | **A**: In all cases all names and objects/occupations/places were distinct.
**B**: Consequently, for each position in the list we get 150 binary answers (true/false recall).
**C**:
Technical details
In order to ensure that none of the names or objects biases the results, the names and objects were independently pe... | CAB | CAB | CAB | BCA | Selection 3 |
<|MaskedSetence|> In this setting, taxonomic information is compositional by nature[1, 2], and there exists only limited ways to compute absolute biomass of taxa[3, 4]. <|MaskedSetence|> <|MaskedSetence|> The result is the relative abundance of each bacterial strain identified among bacteria, and separately the rela... | **A**: The most common example of this is the use of 16S rRNA amplicon sequencing to identify the bacteria in a sample paired with ITS rRNA amplicon sequencing to identify the fungi.
**B**: Furthermore, data on two or more kingdoms of taxa (called “transkingdom” data) are often collected with separate methods for each... | CBA | CBA | ACB | CBA | Selection 2 |
The graph depicts the epidemic control time as a function of vaccine allocation time in both country 1 and country 2. In scenarios 1 and 2, illustrated in Fig.4(a) and Fig.4(b), and scenarios 3 and 4, shown in Fig.4(c) and Fig.4(d), respectively, the trend is examined. From the purple line in both Fig.4(a) and Fig.4(b... | **A**:
.
**B**: on the 1168th day for the first scenario without mutual migrations.
**C**: However, if country 1 starts to distribute vaccine resources after the 300th day, the epidemic control time of country 1 would be shortened as expected, whereas the control time in country 2 would be significantly prolonged.... | BCA | BCA | BCA | ABC | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> Edge thickness indicates strength of support for the edge (thick solid: >80% of samples, thin solid: >60%, dashed: >40% support). A: Genes set for the pre-treatment cohort; nodes in pink belong to the Regulation of cell differentiation strength, while the one in yellow to the Reg. ... | **A**:
Figure 6: STRING network of the harmonic persistent homology identified genes.
**B**: apoptotic process.
**C**: The edges indicate both functional and physical association.
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<|MaskedSetence|> More recently, these models have been applied to other types of data. <|MaskedSetence|> Textualized tabular data offers the advantage of being able to handle inputs with different feature sets and is more robust in dealing with missing values. Prior work also investigated the use of LLMs on a variet... | **A**: Recent advancements in large language models (LLMs) have demonstrated remarkable performance in solving language tasks based on human instructions (brown2020language, ; chowdhery2022palm, ; touvron2023llama, ; zhang2022opt, ; vicuna2023, ; alpaca, ).
**B**: For example, LLMs have been used to textualize tabular... | ABC | CAB | ABC | ABC | Selection 4 |
Biological relevance
Enhancers are short, noncoding segments that contribute to regulating gene expression. <|MaskedSetence|> <|MaskedSetence|>
Data
Experimentally validated enhancer-gene pairs were taken from CRISPR interference experiments (Fulco et al. <|MaskedSetence|> (2019) and paired with the main TSS ... | **A**: (2019); Gasperini et al.
**B**: They can be located anywhere from a few thousand to a million bp away from their target gene and work by being brought into physical proximity to the gene’s promoter.
**C**: Their annotation is a highly challenging task that requires detection of long-range interactions.
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2.1 Gene expression data and pre-processing step
The gene expression measure y𝑦yitalic_y are generally of count data type from sequencing reads. Various SVG detection models have been developed to specifically model count data following some mandatory filtering and quality control steps. <|MaskedSetence|> The gene... | **A**: The method sepal[13] uses a slightly different normalization procedure which involves mapping the log-transformed values to the interval [0,1] and using a pseudocount 2.
**B**: Some examples of these models include SPARK-X[18], BOOST-GP[10], SINFONIA[19], and GPcounts[20].
**C**: The data normalization method ... | BCA | ACB | BCA | BCA | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> Models without pre-training (represented by ’w/o pretrain’) perform worst in all tasks. Pre-training strategies without data augmentation (represented by ’w/o img aug’) perform second best, yet they show a significant performance increase compared to models without any pre-training... | **A**: As shown in Figure 2, MolIG, which utilizes both pre-training and data augmentation strategies (represented by the grey bar), performs best among all model architectures.
**B**: Excluding either of these two components can easily lead to a decrease in performance.
Compared to models completely without pre-tra... | CAB | CAB | CAB | CAB | Selection 4 |
<|MaskedSetence|> <|MaskedSetence|> On the other hand, the models which have been pretrained via SSL yield far superior results. In all cases, the models trained with the proposed framework surpass the baseline by 11.68% on average and even outperform it by 21.04% in the case of the PhysioNet22 OOD task. Even more so... | **A**: Additionally, in all cases the baseline models appear to have overfit their training data distribution and fail to maintain their classification ability across distinct datasets.
**B**: Specifically, the downstream models trained on data from PhysioNet2016 and PhysioNet2022 were able to yield better results tha... | BCA | CAB | CAB | CAB | Selection 3 |
Figure 6: Real patient data. Recurrence of the enhancing core overview. a,b Recurrence coverage of selected volume radiotherapy plans. <|MaskedSetence|> Output tumor cell distribution thresholds found through a grid search to match the Standard Plan volumes. <|MaskedSetence|>
It’s important to note that the high ... | **A**: c,d Average Recurrence Coverage and direct patient-by-patient comparisons to the Standard Plan.
**B**: All radiotherapy plans have the same total volume.
**C**: Despite this natural variance, the averages in the Recurrence Coverage column are a reliable predictor of the effectiveness of each planning method, a... | BAC | BAC | BAC | BAC | Selection 2 |
<|MaskedSetence|> On the other hand, the range of [IP3] values corresponds to having
∼similar-to\sim∼100 molecules/μm3𝜇superscript𝑚3\mu m^{3}italic_μ italic_m start_POSTSUPERSCRIPT 3 end_POSTSUPERSCRIPT. Cell sizes vary over various orders of magnitude. The volume of the cells used in the experiments in which the e... | **A**: which the dynamics of the simple model (Eqs. (3)–(4)) is excitable with slope dβ/d𝑑𝛽𝑑d\beta/ditalic_d italic_β / italic_d[IP]3∼1.4{}_{3}]\sim 1.4start_FLOATSUBSCRIPT 3 end_FLOATSUBSCRIPT ] ∼ 1.4.
**B**: Using Poisson statistics
to estimate the ratio between the fluctuations and the mean of this number we co... | ACB | ACB | ACB | ACB | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> Each case with a Dice score of 00 for the corresponding segment was counted as a false positive or a false negative respectively, depending on the ground truth labels. <|MaskedSetence|> The top three values for each metric from each track are marked as gold, silver and bronze cell... | **A**: Group 2 CoW components) for CTA (Top) and MRA (Bottom) tracks.
**B**: Table 6: Detection performance in terms of precision and recall for the R-Pcom, L-Pcom, Acom and 3rd-A2 (i.e.
**C**: Hereby a positive refers to a segment that is present, a negative to a segment that is absent.
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<|MaskedSetence|> GFMDiff and recent SOTA methods show no major difference in stability of atoms, but the performance lead of GFMDiff over the second-best method using the same generative methods in terms of stability of molecules is 2.1%. This indicates that our model is capable of genrating stable molecules. We beli... | **A**:
As it is shown in Table 1, GFMDiff outperforms all baselines and achieves the best performance in stability, validity, and uniqueness times validity.
**B**: The performance lead of GFMDiff over the SOTA method in validity and validity times uniqueness is 1.1% and 1.3%, respectively.
**C**: A possible explanat... | BAC | ABC | ABC | ABC | Selection 3 |
As the program has been rigorously examined, we anticipate to extend its applications to other functions in Amber software, such as post-processing of the trajectories in MM-PBSA or MM-GBSA. The calculation in dSASA is geometry based, obtaining accurate results with the provided atomic coordinates and radii. Therefore ... | **A**: Moreover, the current algorithm being used for weighted Delaunay Tetrahedrization, gReg3D, is designed to work on a set of random points and the size of the workspace depends on the distribution of points in the workspace.
**B**: As it consumes nearly 70% of wallclock time of our surface area calculation, impro... | CAB | CAB | BAC | CAB | Selection 2 |
<|MaskedSetence|> (2018), we use ROC-AUC as the evaluation metric for classification tasks. <|MaskedSetence|> To ensure fairness, we use Optuna (Akiba et al. 2019) to search 10 learning rates (LRs) for each model. We repeat each task 3 times and report the mean and standard deviation. <|MaskedSetence|> | **A**:
Following the recommendation of Wu et al.
**B**: Due to space limitations, the standard deviations are included in the appendix.
.
**C**: For the regression task qm8, we use MAE, and for other regression tasks, we use RMSE.
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IV-A Impact of Biological Sex on Blood Pressure
To analyze the impact of sex on BP values, we categorized the final pre-processed dataset into females and male groups. Subsequently, we calculated the mean and standard deviation (STD) of SBP and DBP for each group. <|MaskedSetence|> <|MaskedSetence|> <|MaskedSetenc... | **A**: Our findings revealed significant differences in mean BP levels between females and males, as summarized in Table I.
**B**: The difference between the mean SBP and DBP values between the two sex groups are 2.98 and 2.03 mmHg, respectively.
**C**: Fig. 1 illustrates the 95% percentile range contours for males v... | ABC | ABC | ABC | CBA | Selection 3 |
<|MaskedSetence|> Adaptive KFs attempt to estimate their internal parameters from data [brown1985adaptive]. Many extensions of KFs have also been developed to estimate model parameters as observable state variables [sarkka2023bayesian]. The PKF builds on these ideas by adaptively updating both its process uncertainty ... | **A**: Unlike other approaches, the PKF uses analytically tractable internal models to directly compute Bayesian parameter posteriors which results in higher accuracy and more scalability.
**B**:
Comparison to Parameter Estimation Algorithms:
Parameter estimation is an immense topic, so here we focus on parameter es... | BAC | CAB | BAC | BAC | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> Diffusion-like processes can be applied to discrete data
(Avdeyev et al., 2023), but LDMs are preferred for their computational efficiency - this is due to the compaction and smoothness of the latent space (Rombach et al., 2022). Current state-of-the-art models are usually domain-s... | **A**: This technique is widely employed in language modelling, where text is transformed into a continuous format using tools like word2vec or neural network-based embeddings (Dieleman et al., 2022; Li et al., 2022; Han et al., 2022).
**B**:
Latent Diffusion Models (LDMs).
LDMs convert discrete inputs into a contin... | BAC | BAC | CBA | BAC | Selection 1 |
Since we wanted to assess the molecule’s reactivity, we also compute the Gasteiger charges [41] (Figure LABEL:fig:QM9_design(f) for a visual overview). The molecule features an aromatic ring containing a ketone (C=O), which is more electrophilic compared to carbon-carbon or carbon-hydrogen bonds, making it susceptible ... | **A**: Hydrogen bonds are a type of dipole-dipole interaction that occurs when a hydrogen atom, which is bonded to a highly electronegative atom (e.g.: nitrogen, oxygen, or fluorine), interacts with another electronegative atom bearing a lone pair of electrons.
**B**: This can be due to its lone pair of electrons and ... | BCA | BCA | BCA | BCA | Selection 2 |
Motivated by the best results produced in Section 4.1.2, we further proved the effectiveness of the models by using the transductive learning methodology outlined in Yang et al. (2016), where during the training phase the models were given access to the feature vectors of all nodes. While the concept of transductive le... | **A**: (2019) proposed a robust and interpretable end-to-end deep learning model for cytometry data and scRNA-Seq analysis, incorporating elements of self-supervised and semi-supervised learning.
**B**: To achieve this, we conducted five different seed iterations using our models.
**C**: Then we randomly masked the l... | ABC | ACB | ABC | ABC | Selection 3 |
A critical examination of the AT methodology reveals significant shortcomings. Firstly, proponents of AT failed to conduct basic control experiments, a foundational aspect of introducing a new scientific metric. Benchmarking against established indices, particularly in coding and compression algorithms, is crucial to ... | **A**: Previous work on AT
has never included meaningful experimental comparisons of the assembly index with other existing measures on false grounds that their measure is completely different [8] (Figs.
**B**: 1 and 2).
**C**: Yet, we have shown that other algorithms, such as RLE, Huffman coding (the first dictionar... | ABC | ABC | ABC | CBA | Selection 1 |
While the phasor-based HDC algebra developed by McDonald et al. is effective for complex-valued data such as classical analog signals processing, for example,[McDonald_phasor_hdc_ai] it is insufficient for our purposes. <|MaskedSetence|> The Bloch sphere262626A graphical representation of a qubit, where each axis corr... | **A**: This drastically simplifies the problem of analyzing error-tolerance in Projective Cognition prior to measurement.
**B**: provides a convenient representation for this, and is shown in Figure 2.
**C**: With qubits we must additionally account for whatever property (often spin) is to be mapped to measurement ou... | CBA | CBA | BAC | CBA | Selection 2 |
Language-Conformation Pairs: Using Molecule3D Xu et al. <|MaskedSetence|> <|MaskedSetence|> This process resulted in 161K language-conformation pairs.
Conformation-Protein Pairs: By leveraging data from PDBBind Wang et al. <|MaskedSetence|> (2020), we extracted and refined conformation-protein pairs. After filtering... | **A**: (2005) and CrossDocked Francoeur et al.
**B**: (2022) with 37M higher-quality conformations, we matched molecular IDs (CIDs) and InChIs in them with textual descriptions from PubChem.
**C**: (2023), which contains 3.9M ground-state molecular conformations, and the GEOM dataset Axelrod et al.
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We use AiZynthFinder [11] with default parameters to compute the routes of both datasets. A route is considered to be solved if all leaves are purchasable molecules. If more than one route is found for a molecule, the route scored the highest by AiZynthFinder is retained. For solved routes, we compute the depth of the ... | **A**: At a synthesis tree level, this effectively results in the removal of any nodes beyond the intermediate molecule.
**B**: We do the latter by treating the sampled intermediate as an available building block, meaning that we can ignore the synthesis steps needed to create it.
**C**: Since the maximum tree depth ... | CBA | CBA | CBA | BCA | Selection 2 |
Different aspects of cyclically dominant dynamical systems have been studied intensively in the last years Menezes and Barbalho (2023); Park (2022); Szolnoki and Chen (2020); Serrao and Täuber (2021); Avelino et al. <|MaskedSetence|> <|MaskedSetence|> By choosing a similar system, the key question in our present work... | **A**: In this case the average size of domains formed by the members of the loop grows.
**B**: (2018); Roman et al.
**C**: (2016).
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Micro-ultrasound is a newly developed technology that allows visualization of tissue microstructures at much higher resolutions than conventional ultrasound. <|MaskedSetence|> <|MaskedSetence|> This approach has seen some measure of success, but still struggles with a number of issues. For instance, ROI-scale PCa d... | **A**: Typically, deep learning is used during targeted biopsy to classify small regions of interest (ROI) across a needle trace region[2].
**B**: Moreover, ROI-scale models do not consider the broader contextual information encoded in multiple overlapping patches as clinicians typically do.
.
**C**: As such, this i... | CAB | ABC | CAB | CAB | Selection 4 |
4.2 Plant Winterkill in Northern Latitudes
Plant winterkill impacts the winter annual and perennial ground cover that society uses for recreation and ecosystem services. <|MaskedSetence|> Winter injury to golf course turfgrass has negative ecological impacts when perennial ground cover is absent, and economic losse... | **A**: Winterkill is unpredictable and this has been due largely to the inability to capture microclimate data that characterizes these complex physiological stressors..
**B**: Golf course superintendents in northern latitudes are faced with the problem of winter damage risk every year, and undertake cultural practice... | BCA | BCA | BCA | ABC | Selection 3 |
Overall, the frALBERT-based models have the lowest carbon footprint. <|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> Labrak et al. (2023) reported the overall carbon emissions of their 7 DrBERT-based models, which is 376.45 kg CO2 eq.
. | **A**: (2023) reported that the carbon emissions for pre-training their CamemBERT-bio model is estimated to 0.84 kg CO2 eq.
**B**: Touchent et al.
**C**: These models offer a decrease of carbon emission between 20% and 63% compared to other models, depending on models and corpora.
Note that Carbon tracker does not co... | CBA | CBA | CBA | BAC | Selection 2 |
4.3 Data Visualization
We use the t-distributed Stochastic Neighbour Embedding (t-SNE) algorithm to create 2-dimensional representations of the different embeddings [14]. <|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> On the other hand Morgan Fingerprint daylight are giving different scattered patterns. We ... | **A**: Figure 3 shows the scatter plots produced by t-SNE for various embedding techniques.
**B**: To have a visual inspection and determine whether different embedding strategies are keeping the structure of the data the t-SNE plots are generated.
**C**: The MACCS fingerprint displays some clustering overall, which ... | BAC | BAC | BAC | ACB | Selection 1 |
In other words, the signal may not be able to transfer the desired on/off patterns to the reaction systems at a receiver cell if the waveform of the signal at the receiver is distorted as shown in Fig. 1. <|MaskedSetence|> Specifically, we first introduce indices evaluating signal distortion by the gain and the phase ... | **A**: We then show design conditions for MC channels in which the magnitude of distortion becomes below a specified level based on the indices.
**B**: Finally, the roles of MC channels in nature are discussed from the perspective of signal distortion.
.
**C**: Therefore, to guarantee the quality of the transmitted s... | CAB | CAB | CAB | BAC | Selection 1 |
Three different types of intrinsic rewards have been proposed: prediction-based, count-based, and memory-based intrinsic reward functions. <|MaskedSetence|> The greater the difference from stored memories, the higher the reward[26]. However, memory-based methods have to compare the current state with all previous sta... | **A**: Memory-based intrinsic reward methods involve maintaining a record of previously encountered states in memory, promoting exploration for finding novel states by assessing the novelty of the current state in comparison to stored memories.
**B**: These methods have the advantage of being simple and easy to implem... | ACB | ACB | ACB | CBA | Selection 1 |
<|MaskedSetence|> In the inter-layer connections, the BPT-SAN models the local nonlinearity of dendritic trees by breaking down the standard layer into two stages. In the initial stage, dendritic branches perform a mutually exclusive partition of the input and subsequently execute a weighted summation of the sparsely ... | **A**:
Figure 1:
The schematic diagram of our proposed BPT-SAN, which integrates spiking neurons with rich spatial-temporal dynamics and network topologies featuring biologically-plausible connectivity patterns.
**B**: These two network topologies work synergistically to significantly enhance the information process... | ACB | ACB | ACB | BAC | Selection 3 |
As generative models, Template-free methods opt to generate reactants directly from the given products. In comparison to generating graph structures, SMILES provides a way to represent molecules as strings. <|MaskedSetence|> In particular, Graph2SMILES [29] replaces the Transformer encoder with a graph neural network... | **A**: There are also methods [21, 40] formulates the generation of reactants as a series of graph generation or editing operation and solve it auto-regressively.
**B**: Taking advantage of this, most template-free methods [28, 15, 34, 42, 25] use Transformer models to translate between product SMILES and reactants SM... | BAC | BAC | BCA | BAC | Selection 2 |
Molecular graphs (Shi et al., 2020) and simplified molecular input line entry systems (SMILES) strings (Weininger, 1988) constitute the two primary representations of molecules in deep generative models. <|MaskedSetence|> <|MaskedSetence|> Due to the inability of GANs to calculate rewards for partially generated mo... | **A**: Most prior studies related to generative adversarial networks (GANs) (Yu et al., 2017; Guimaraes et al., 2017; De Cao & Kipf, 2018) typically update the generator by integrating the output probability of the discriminator with the chemical properties of generated molecules as a reward for reinforcement learning ... | BAC | ACB | BAC | BAC | Selection 3 |
Number of Iterations. Table 5 also studies the impact of the number of iterations. For enzyme reaction classification, increasing T𝑇Titalic_T from 1 to 4 leads to better performance (i.e., 84.7%→→\rightarrow→89.6%). <|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> | **A**: This may be because over-clustering finds insufficient and insignificant amino acids, which are harmful to representation learning.
**B**: However, the accuracy drops significantly from 89.6% to 86.3% when T𝑇Titalic_T is set as 5555.
**C**: Similar trends can be observed in the results of other tasks.
Perce... | BAC | BCA | BAC | BAC | Selection 1 |
To address the first point, two possible definitions of the probability of infection will be considered to address the first point: The probability that a given host becomes infected after ingesting a dose with specific infectivities and the average probability of infection for a set of hosts. Previous works have pred... | **A**: However, an explicit link between the slope and the variance of infectivity was again not established.
**B**: Despite the widespread use of this modeling approach, a comprehensive analysis of how the probability of infection varies with infectivity dispersion remains lacking.
For instance, the exact beta-Pois... | BCA | BCA | BCA | CAB | Selection 3 |
Scaffold-Domain Adaptive Molecule Generation.
In the task of scaffold-domain adaptive molecule generation, the baselines are trained on both the entire dataset (††\dagger†) and solely on the source domain (‡‡\ddagger‡), respectively. In contrast, our GADM is trained exclusively over the source domain dataset. After tr... | **A**: In contrast, our proposed GADM, trained solely on the source domain, can generate molecules containing the target scaffolds under the corresponding supervision, achieving at least 95.5% proportion in both new domains.
**B**: Note that the target scaffolds were not seen during training.
.
**C**: The quantitati... | ABC | CAB | CAB | CAB | Selection 4 |
<|MaskedSetence|> The performance across duration shows that using 400ms of data achieves a slightly higher performance than 200ms, despite the fact that other images have started showing by this time. See Appendix A for examples of reconstructions from subject 1. <|MaskedSetence|> <|MaskedSetence|> Using 3 second d... | **A**: To put the performance in context, the reported THINGS-MEG data performance is slightly higher than ours (Benchetrit et al., 2024).
**B**: Although they did not use the provided test set but rather took out parts of the training set as the test set, and thus did not have multiple trials to average during test t... | CAB | CAB | CAB | BCA | Selection 1 |
<|MaskedSetence|> 7) with geographic location, category, and time range specified as ‘Worldwide’, ‘Web Searches’, and ‘Between 9/21/23 and 9/27/23’ (i.e., 3 days before and after the 9/24/23 spike in Fig. 6); we also filtered for ‘health’-related searches.
Similar to Fig. <|MaskedSetence|> <|MaskedSetence|> 7 repres... | **A**: 6, Fig.
**B**: 7 shows a spike on September 25, 2023, for the search terms ‘Dulaglutide’, ‘Ozempic’, ‘Liraglutide’, ‘Trulicity’, and ‘Rybelsus’.
The black dashed line in Fig.
**C**:
To better understand the spike, we queried Google Trends [80]
for the entries on our Medication List (Fig.
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Among the NDC that did have a linked RxCUI but did not have an ATC associated with the RxCUI 13,289 (77.4%) had an RxCUI status of "not current", 1,974 (11.5%) had an RxCUI status of "obsolete", 1,195 (7%) had an RxCUI status of "remapped", and 75 (0.4%) had an RxCUI status of "quantified". 635 "active" RxCUI were unsu... | **A**: The results of this check are shown in Table 2.
**B**: combinations with expectorants) while the correct classification was "R05F" (cough suppressants and expectorants, combinations).
Table 3 shows the concept names for the five most common "active", "alien", or "obsolete" NDC and the five most common "unknow... | CAB | ACB | ACB | ACB | Selection 3 |
Structured approaches sidestep the binning problem by modelling the spectrum as a distribution over chemical formulae, whose masses can be calculated trivially with extremely high precision. Some methods predict the formula distribution directly, using either autoregressive formula generation (Goldman et al., 2023a) o... | **A**: Others rely on recursive fragmentation (Wang et al., 2021; Zhu & Jonas, 2023) or autoregressive generation (Goldman et al., 2024) to model a distribution over fragments, which induces a distribution over formulae.
**B**: While structured MS2C models can generate very high resolution spectra, they tend to be slo... | BAC | ABC | ABC | ABC | Selection 4 |
<|MaskedSetence|> GNNs are capable of learning embeddings for individual nodes and edges as well as complete graphs. <|MaskedSetence|> SMILES) or vectorial representations (e.g. molecular fingerprints), is their capability to learn fine-grained representations that are still explainable in graphical form. In drug syn... | **A**: The main benefit of GNNs over text (e.g.
**B**: They are particularly valuable for assessing the similarity or complementarity of drug properties, an essential factor in predicting drug synergy.
.
**C**: Graph Neural Networks (GNN) specialize in analyzing relational data represented as graphs or networks.
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<|MaskedSetence|> A rule consists of two graph patterns, one to match the input, and the other to specify the output. An application of a rule to a graph which contains a match of the input pattern replaces the matched part by the output pattern. <|MaskedSetence|> Such a model encodes behavior in the usual form of a ... | **A**: This explicit representation of the encoded behavior may be arbitrarily larger than the rule set itself, possibly even infinite.
.
**B**: A collection of such rules then defines a graph transformation model.
**C**:
In graph transformation, the rewriting of one graph into another is specified by the means of... | CBA | CBA | CBA | CBA | Selection 2 |
Given our assumptions about their chemostatting, the concentrations of input species and catalysts can be treated as parameters, rather than variables. <|MaskedSetence|> an intermediate or a product). All reaction rates therefore depend linearly on the concentration of the non-chemostatted species. <|MaskedSetence|>... | **A**: Under such assumptions, the CRNs are linear: the set of complexes contains only the null complex (containing no non-chemostatted species), and singletons (containing a single non-chemostatted species, i.e.
**B**: This graph defines a set of self-avoiding walks (SAWs) from the null state to each product; each SA... | ACB | CAB | ACB | ACB | Selection 3 |
In addition, the rewire-to-same may lead to fragmentation Holme and Newman (2006); Kimura and Hayakawa (2008), which is unrealistic in the information and interconnected age.
Opinion dynamics on dynamical networks are typically based on simulations or numerical solutions Holme and Newman (2006); Horstmeyer and Kuehn ... | **A**: (2012); Du and Wu (2023); Fu and Wang (2008).
**B**: (2010); Wu, Zhou, and Wang (2011); Wu et al.
**C**: (2023); Durrett et al.
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A common method to account for missing data is data-augmented Markov Chain Monte Carlo (MCMC). <|MaskedSetence|> Data-augmented MCMC methods have been applied to network epidemics for a variety of applications \citepbritton2002, groendyke2011, groendyke2012, embar2014, bu2022. However, when large amounts of data are ... | **A**: ABC only yields exact inferences when the summary statistics are Bayes-sufficient and the acceptance threshold is zero; this is rare in practice, as finite-dimensional sufficient summary statistics are available only in the exponential family.
**B**: However, approximate methods are nonetheless useful, as they ... | CAB | ACB | CAB | CAB | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> We also incorporate neurogenesis in the hippocampus, assuming that this newborn neurons could play a role in memory erasure. <|MaskedSetence|> (a) Standard consolidation theory. Initially, the engram is initially present in neocortical areas (red), in a weak form (i.e., not stabil... | **A**: In addition to spike-frequency adaptation and synaptic plasticity, we assumed that the difference of connectivity structure of the neocortex and the hippocampus is playing a role in SCT, in particular the larger size and more sparse structure of the neocortex.
**B**: Using numerical simulations and mathematical... | CAB | BCA | CAB | CAB | Selection 3 |
Yet, a number of these phenomena actually take place in non-flat and so-called curved spaces. Climbing plants for instance may growth on tree trunks or grounds that are not flat surfaces. Vein networks can develop in leaf blades that are markedly curved. Pollen tubes grow on the pin-like structures of papillae that are... | **A**: In both cases, to approximate the formation of a pattern in a curved space, the pattern growth is first evaluated in the 3-D Euclidean ambient space.
**B**: This is different from the approach that we use here which is based on the possibility to follow geodesics in curved spaces to construct forms.
**C**: The... | CAB | BAC | CAB | CAB | Selection 1 |
In ecology, population escape from a long-lived metastable state plays an important role in the long-term stability of populations. Here, even a small population lingering on the brink of extinction can experience a rare fluctuation, securing its survival. On the other hand, a long-lived established population can un... | **A**: (2019).
**B**: (1982); Elowitz et al.
**C**: (2008); Leisner et al.
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In our analysis of veterinary-related risk factors we see that the veterinary practice conducting the test plays a significant role, despite low coverage of the test dataset with veterinary information. <|MaskedSetence|> The variability in testing outcomes by practice is partially correlated to the average size of her... | **A**: We do not see any risk associated with tuberculin batch, though this may be because the test dataset coverage for tuberculin batch information is very low.
**B**: Nonetheless, by showing that the model can identify variability across practices, it does provide a foundation for further interrogation of managemen... | BAC | ABC | ABC | ABC | Selection 3 |
<|MaskedSetence|> <|MaskedSetence|> In older adults, measures of cardio-respiratory activity (e.g. heart rate variability) are known to decline with age [76]. <|MaskedSetence|> Additional video data from older subjects would likely help to improve this, which is discussed further in §C.
. | **A**: We observe a decrease in performance with age, as observed in prior sleep staging work [56, 6].
**B**:
Population performance.
Figure 8 shows the distribution of Cohen’s κ𝜅\kappaitalic_κ values across participants from the OSV dataset plotted against age, sex and Fitzpatrick skin type222Plotted using represen... | BAC | BAC | CBA | BAC | Selection 4 |
<|MaskedSetence|> SELFIES, on performance when predicting binding to the stress response target p53 (SR-p53), a task from the Tox21 data set. <|MaskedSetence|> However, the authors made an initial comparison by training a base model with either SMILES or SELFIES and evaluated both of them for drug-likeness prediction... | **A**: The models trained with SELFIES performed ∼0.004±0.01similar-toabsentplus-or-minus0.0040.01\sim 0.004\pm 0.01∼ 0.004 ± 0.01 better on average.
**B**: They concluded that the difference was not significant (without showing further details).
For RT, given that the model was designed as a decoder that relies on ge... | CBA | CBA | CBA | ACB | Selection 3 |
Each patient’s images were prepared using SPM12 [7]. We coregistered the CT to the CTA, computed affine registration of the CT to MNI space, and applied this to both, reslicing images to 1x1x1 mm resolution. <|MaskedSetence|> In this study, we only run the first two steps of VTrails: (1) digital subtraction image pr... | **A**: The binarised VSP was later converted into the skeleton image (SKEL) using itkBinaryThinningImagheFilter3D in ITK [13].
**B**: Later the DSA image was normalised by its maximum value.
**C**: The prepared images were inputs in VTrails [8, 9].
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In particular there might be other choices of the parameters that give a similar result.
Such a qualitative statement suggests we should be careful whenever we wish to determine parameters from the least squares fit, for any epidemic model. For example, in Figure 1, two SIR least squares fits to NYC Omicron outbreak da... | **A**: These two SIR outbreaks are much more similar to each other than they were to NYC data.
**B**: Figures 5 and 6 are designed to address that question.
.
**C**: It is difficult to use these fits to estimate the correct values of ρ𝜌\rhoitalic_ρ and τ𝜏\tauitalic_τ.
| ACB | ACB | BCA | ACB | Selection 1 |
Recently, a novel approach named the knockoff filter was introduced in [17], designed for FDR control in low-dimensional Gaussian linear models without relying on p-values. Subsequently, the model-X knockoffs framework [18] was proposed to generalize the knockoff filter to general high-dimensional nonlinear models with... | **A**: Incorporating temporal information into the feature selection process has the potential to produce more accurate and interpretable variable selection results.
**B**: Additionally, we examine the robustness of DeepLINK-T to some misspecification of the time series latent factor model; our findings affirm that De... | ABC | ABC | ABC | ACB | Selection 3 |
<|MaskedSetence|> <|MaskedSetence|> These two parameters were calibrated in a pilot study described above using healthy controls. <|MaskedSetence|> As we did not perform a separate calibration and validation study with ME/CFS and Long/COVID patients, we cannot be certain that these threshold parameters are adequatel... | **A**:
We acknowledge that the step counts reported seem unrealistically large.
**B**: The local variance algorithm depends on two related threshold parameters: the length of the sliding window from which local variance is calculated, and a peak threshold value.
**C**: The same threshold parameters were used in this... | ABC | ABC | ABC | ACB | Selection 2 |
<|MaskedSetence|> We therefore hope that our theoretical results will find use in the broader sphere of computation.
The remainder of the paper is organized as follows. In the next subsection, section 1.1, we point out that there are two natural ways to use chemical systems as computational machines and compare/cont... | **A**: There are several bodies of research, outside the world of chemical reactions, on designing efficient hardware and software for analog as well as analog-digital hybrid computing [11, 12, 13, 14].
While we develop our results for a chemistry-based computer, the results apply equally well to any computational syst... | ACB | ACB | ACB | ACB | Selection 3 |
After obtaining the tractography data per subject, a groupwise whole-brain fiber clustering atlas was created using our robust, data-driven fiber clustering pipeline[36, 54, 55], as implemented in the whitematteranalysis (WMA) software (https://github.com/SlicerDMRI/whitematteranalysis). <|MaskedSetence|> The WMA fib... | **A**: Specifically, from each subject’s whole brain tractography, 10,000 streamlines were randomly selected, resulting in approximately 3 million streamlines for clustering.
**B**: We performed co-registration of the two atlases using a tractography-based registration[54] and calculated the mean closest point distanc... | CAB | CAB | CAB | CAB | Selection 2 |
<|MaskedSetence|> We hypothesize that this may allow cells to better sense the electric field – i.e. <|MaskedSetence|> <|MaskedSetence|> If elongated galvanotaxing cells are more accurate when perpendicular to the field, how would this affect a group of cells’ ability to sense an electric field?
This question is par... | **A**: that a cell’s accuracy at sensing the field direction is better if the cell is elongated perpendicular to the field.
**B**: Theoretical studies on chemical gradient sensing have demonstrated that elliptical cells possess higher accuracy in this orientation [12], and preliminary results extending our model of [1... | CAB | CAB | CAB | CBA | Selection 2 |
with R0=10−3,κ=1formulae-sequencesubscript𝑅0superscript103𝜅1R_{0}=10^{-3},\kappa=1italic_R start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT = 10 start_POSTSUPERSCRIPT - 3 end_POSTSUPERSCRIPT , italic_κ = 1/day. Values of λ,Y𝜆𝑌\lambda,Yitalic_λ , italic_Y
displayed along the curves are in units of /day. In panel (a) we set
Y... | **A**: In panel.
**B**: Small values of λ<2Y𝜆2𝑌\lambda<2Yitalic_λ < 2 italic_Y decease ⟨P(T)⟩delimited-⟨⟩𝑃𝑇\langle P(T)\rangle⟨ italic_P ( italic_T ) ⟩ below the baseline, whereas large fluctuations λ>2Y𝜆2𝑌\lambda>2Yitalic_λ > 2 italic_Y increase ⟨P(T)⟩delimited-⟨⟩𝑃𝑇\langle P(T)\rangle⟨ italic_P ( italic_T... | CBA | CBA | BAC | CBA | Selection 4 |
7 Discussion and Final Conclusion
Cell fate switching is a dynamic phenomenon often tied to regulatory network motifs that at the cellular level define the computational machinery of life. Most of these network motifs define molecular switches exhibiting diverse qualitative behaviors such as bistability, catastrophes... | **A**: In fact, higher-order dynamics such as tristability (three stable states/attractors/phenotypes) is now also prominently observed in biological mechanisms.
**B**: Further, the underlying cause of bistable dynamics is attributed to multimeric regulation (higher order Hill coefficient), in contrast to monomeric re... | BAC | BCA | BAC | BAC | Selection 4 |
<|MaskedSetence|> Moreover, as stressed during the paper, the gelatin is a very thin layer. A two-dimensional approach is then required. <|MaskedSetence|> <|MaskedSetence|> Indeed, the estimated parameters helps to quantify membrane permeability inside the Kedem-Katchalsky membrane conditions.
Finally, a more mathem... | **A**: However, this work could be a first step in studying not only basal membrane degradation, but also ECM one.
**B**:
More complex models considering the action of other cells involved in the invasion process, such as fibroblasts [24] could be very interesting to analyse.
**C**: ECM is in fact a thicker layer in... | BAC | BAC | BAC | CAB | Selection 2 |
<|MaskedSetence|> 3 shows list plots of the first 11111111 (top left) and the first 16161616 (top right) coordinates Pnsubscript𝑃𝑛P_{n}italic_P start_POSTSUBSCRIPT italic_n end_POSTSUBSCRIPT of η0(x)subscript𝜂0𝑥\eta_{0}(x)italic_η start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT ( italic_x ) with respect to the Hermite ba... | **A**: The upper segment of Fig.
**B**: For growing N𝑁Nitalic_N the little oscillations of the Hermite components become smaller and smaller and their superposition approaches the predicted wave function.
5 Excited States of the Schematic Hamiltonian.
**C**: The plot in the lower segment of Fig.
| ACB | CBA | ACB | ACB | Selection 1 |
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