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A: The PCAM dataset was downloaded from the original website (https://github.com/basveeling/pcam). All images have a size of 96 x 96 pixels, in three colorsB: The training set has 262,144 images (80 % of the total), the validation set has 32,768 images (10 %) and the test set also has 32,768 images (10 %). All ...	CAB	ABC	ACB	CAB	Selection 2
A: By definition, an evolutionary stable condition is surrounded by unfit traits, at least within an α𝛼\alphaitalic_α-radiusB: This form of a fitness landscape is referred to as a fitness valley and has been studied in a special case in [8]C: Based on this, we introduce a measure for the stability of a co...	BAC	ABC	CBA	BAC	Selection 2
A: We first compute the virus-free equilibrium and endemic equilibrium after establishing the basic reproductive numberB: Subsequently, we extend our analysis to the stochastic counterpart, determining the basic reproductive number in the stochastic framework. This stochastic reproductive number becomes instrum...	ABC	BAC	BCA	ABC	Selection 3
A: In Wang et al. (2017), persistent homology was shown to outperform topographic power maps. In (Yoo et al., 2017), center persistency was shown to outperform the network-based statistic and element-wise multiple corrections. In Chung et al. (2023b), persistent homology based clustering is shown to outperform k𝑘k...	CBA	ACB	CAB	BAC	Selection 3
A: In this note, we propose a multiscale model for glioma development and spread which interconnects the dynamics of glioma cells, vasculature, and vascular endothelial growth factors. Glioma cells mainly spread according to the anisotropy of brain tissue or moving along the blood vessels therein [17, 38]. In order...	ABC	BCA	ACB	ACB	Selection 1
A: For comparison, two other types of brains are also included. Purple points represent lissencephalic brains, with hemisphere sizes measured as depicted in Fig. 3B: Red points denote quasi-gyrencephalic brains, measured as shown in Fig. 4 and Fig. 5. Data are collected from academic publications and www.brainm...	ABC	CAB	ACB	BCA	Selection 4
A: Often, novel drugs may not demonstrate efficacy in clinical trials despite thorough preclinical safety testingB: Detecting synergistic effects among approved drugs holds clinical significance, as drug repurposing can streamline the expensive and lengthy process of developing new drugsC: In the future, i...	CBA	ACB	ACB	BAC	Selection 4
A: 2F), there is an optimal number of chromosomes for evolving novel traits (FigB: 2B).C: We found that the skewness of the distribution of genotypes coded in each chromosome is essential to determining the probability of evolving new traits. Because skewness peaked with a finite number of chromosomes (Fig	BCA	ABC	CBA	CAB	Selection 1
A: The gradient component sum to zero along any cyclesB: The curl components are zero for edges that are not a 2-simplex boundary and the entries sum to zero around each node. The harmonic component sums to zero around each node, and it also sums to zero along each 2-simplex. We tested the topological equivalen...	BCA	CAB	ABC	ACB	Selection 1
A: preprint arXiv:2210.05819).B: Others are modifications, such as models with varying population sizes [Mohle2002, KajKrone2003, Freund2020] or diploid reproduction [MohleSagitov2003, BirknerLiuSturm2018], using heuristics close to those of [MohleSagitov2001]. Finally some works use different techniques such a...	CAB	ACB	CBA	CBA	Selection 1
A: Noise introduces significant interference into the model, and we aim to ascertain whether attention consistency still holds under noisy conditions. By employing these strategies, we aim to ensure a comprehensive evaluation of our model across different learning scenarios. B: To comprehensively validate the e...	BAC	CBA	ACB	CAB	Selection 2
A: In the experiments, we will demonstrate the importance of taking the alignment of data into consideration by comparing our method to these baselines.B: Solving DSBs is a subject of significant interest in recent years and has flourished in a number of different algorithms (De Bortoli et al., 2021; Chen et a...	BCA	ACB	BCA	CAB	Selection 4
A: 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 individual)B: We do so for a one-dimensional i-state (i.e., the variable capturing t...	CBA	ACB	BAC	ABC	Selection 4
A: Specifically, the procedure on the twin lattice was more than five times faster, requiring between 16%percent1616\%16 % and 20%percent2020\%20 % of the time required by the procedure on the model inclusion lattice. Furthermore, the proper implementation of the coherence principle allowed us to fit a much smaller...	CBA	BAC	CBA	BCA	Selection 2
A: However, the current study is limited to single institutional data. In the future, we would like to explore the applicability of the method for multi-institutional data using domain adaptation techniques. B: This paper proposed a tensor learning-based pipeline for PAWP classificationC: We demonstrated th...	BAC	CBA	CBA	CAB	Selection 4
A: Cat refers to concatenation, KP refers to Kronecker product. All omics and multimodal baselines were trained with the Reactome and Hallmark pathway sets. B: Best performance in bold, second best underlinedC: Table 1: Results of SurvPath and baselines in predicting disease-specific patient survival measur...	ACB	CBA	BCA	ABC	Selection 2
A: Most notable is the effect of such systems to smooth and provide an additional degree of control over external noise, consequentially increasing resilience and robustness. The inclusion of feedback and feedforward loops can enhance this effect, providing systems with additional degrees of control and contributi...	CAB	CBA	ACB	BCA	Selection 3
A: Elman networks, more commonly known as vanilla recurrent neural networks (RNN), attempt to introduce the concept of a time-dependent dynamic memory [16]. The idea is to make predictions about inputs based on contextual informationB: Context-based predictions can be done for four input-output schemes: one-to-...	CBA	BCA	ABC	BAC	Selection 3
A: 1). The three regimes correspond to the network topology updates being much faster (annealed regime), comparable (intermediate regime) or much slower (quenched regime) than the spread of the disease. B: The analysis of epidemics on time-variant networks is often under the assumption of timescale separation: ...	CAB	BCA	BCA	ACB	Selection 1
A: We explore features of covers arising from networks, and characterise many of the familiar classes in terms of properties of their associated covers. It is to be hoped that encoding network properties in the properties of sets of sets will enable some new directions to be pursued in studying phylogenetic network...	ABC	ABC	CBA	CAB	Selection 3
A: Suppose we are given a sample from the selected locus at the present time t=0𝑡0t=0italic_t = 0, and that we know the allelic types of the sample but we do not know how the sample was produced. What is the genealogy of the sample? This question was answered by Barton et alB: For samples from a population at ...	CBA	ACB	BCA	ABC	Selection 2
A: MIXALIME also provides machinery to test for the differential allele-specificity between two sample groups (i.eB: control and test)C: We employ Wald or likelihood-ratio test (LRT) to see if there is a difference in parameters estimates between two groups:	BCA	BAC	ABC	BAC	Selection 3
A: fully susceptible (σ⁢(a)=1𝜎𝑎1\sigma(a)=1italic_σ ( italic_a ) = 1)B: If TR=∞subscript𝑇𝑅T_{R}=\inftyitalic_T start_POSTSUBSCRIPT italic_R end_POSTSUBSCRIPT = ∞ a.s., individuals are permanently immune following an infectionC: Depending on the distribution of TRsubscript𝑇𝑅T_{R}italic_T start_POSTSUBS...	CBA	BCA	ACB	BCA	Selection 3
A: In particular, the analytical species abundance distribution derived from the DMFT follows the Gamma distribution, a widely utilized probability distribution in macroecology [32, 1]B: In other words, due to the non-linear nature of the corresponding Fokker-Planck equation and known pathologies in the GLV mod...	BAC	BAC	ACB	CAB	Selection 3
A: Transcription—the synthesis of RNA—is typically modelled as a multistep process in which the gene switches between multiple states before it eventually produces an RNA moleculeB: Depending on the level of details, transitions between gene states may reflect individual biochemical events, such as binding of ...	CBA	ABC	BAC	CAB	Selection 2
A: Ho et alB: (2018) calculate transition probabilities for the birth/birth-death process—a restricted bivariate case where the death rate of one type vanishes, but rates may be otherwise nonlinear. Xu et alC: (2015) use branching process approximations of birth-death processes and generating-function machi...	CAB	BAC	ABC	BCA	Selection 3
A: Where the similarity represents the highest alignment score between the amino acid sequences of the test and train sets using BLAST identityB: Furthermore, in Figure 2 we report the performance of all Prot2text models with respect to different similarity thresholdsC: We observe that for test proteins wit...	BCA	BAC	BCA	CBA	Selection 2
A: strength [cfB: Fig. 3(b) and discussion after Eq. (31)]C: Note that the saddle point 𝑸∗⁢(𝑫=𝑫¯)superscript𝑸𝑫¯𝑫\boldsymbol{Q}^{*}\left(\boldsymbol{D}=\overline{\boldsymbol{D}}\right)bold_italic_Q start_POSTSUPERSCRIPT ∗ end_POSTSUPERSCRIPT ( bold_italic_D = over¯ start_ARG bold_italic_D end_ARG )	BCA	CBA	ABC	CBA	Selection 3
A: As shown in Figure 7, changes in the shape of the reconstructed volumes indicate a large flexible motion in the continuous conformational space. The corresponding predicted volumes and the distribution of predicted latent z𝑧zitalic_z along the first two principal component axes are similar to that from the lite...	ABC	BAC	CAB	ABC	Selection 3
A: ML, VG, MS, SJR were supported by SNSF grants CRSK-3_190526 and 310030_204938 awarded to SJR. EB: Upschulte and TC: Dickscheid received funding from Priority Program 2041 (SPP 2041) “Computational Connectomics” of the German Research Foundation (DFG), and the Helmholtz Association’s Initiative and Networ...	ACB	BAC	ABC	CBA	Selection 3
A: A careful examination of these explicit terms may be of interest in future work, but we collapse them into single functions and continue these calculations with the aid of a symbolic package up to some chosen order k𝑘kitalic_k: B: Three-body interactions are apparent, as are the existence of interactions be...	ACB	BAC	CAB	ACB	Selection 3
A: 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 characteristic function and derive macroscopic observables: population-mean voltage and firing rateB: In Sec. IV, the theoretical results for macroscopic states of homogene...	CBA	ABC	BCA	BAC	Selection 2
A: Predictive coding can be performed over any sensory modality that has some temporal sequenceB: As natural speech forms a cognitive map, predictive coding may underlie the geometry of human languageC: Intriguingly, large language models train on causal word prediction, a form of predictive coding, build ...	BAC	ABC	ACB	CBA	Selection 2
A: Temporal-spatial convolution is used with spatial modules, made with self and graph attention, to reveal spatial features of brain activityB: The linear layer is used to project the feature dimension.C: Then, the model obtains results by matching test data to templates. (B) Architecture of the EEG encode...	CBA	ACB	BCA	BAC	Selection 3
A: Even with these simplifying assumptions, species tree estimation is confounded by gene tree heterogeneity. Heterogeneity is particular problematic for concatenation-based methods, as the species tree for the entire concatenated sequence can disagree with gene trees for particular loci, Roch and Steel (2015)*B...	BCA	ACB	ABC	CBA	Selection 2
A: In fact, Lawley and Madrid [24] have extended these works to also consider the effect of small noiseB: Relevant to our paper, they argue that the relative benefit of increased numbers of walkers is relatively weak (scaling as 1/log⁡(N)1𝑁1/\log(N)1 / roman_log ( italic_N )), and so it remains unclear if man...	BAC	ACB	ACB	ABC	Selection 4
A: A recent work demonstrated that the weight uncertainty with the form of SaS structure can be also incorporated into the transformer [45]B: In addition, gated recurrent neural networks with multiplicative mechanisms were recently shown to be able to learn to implement linear self-attention [46]C: Further...	CAB	BCA	BAC	ABC	Selection 4
A: Data acquisitionB: 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.C: Bright-field images used in this paper were obtained under the protocol described in [5]	ABC	BAC	CAB	ACB	Selection 4
A: In simple terms, an ANN learns from data by adjusting the weights of the connections between nodes in order to minimize a loss function that measures the difference between the desired output and the actual output of the network. More specifically, the optimization step is performed using the Stochastic Gradien...	ACB	BAC	ABC	BAC	Selection 1
A: The formation of NCNM was formed by a self-assembly of homogeneous nanoparticles with negative surface charge in the desired shallow channel using Laplace pressure to halt the solvent at the base and evaporation of solvent. A close-packed fcc was formed by the growth of the ordered lattice induced by the evapora...	CBA	CAB	ABC	ACB	Selection 2
A: It offers an extensive description of the trade-off between disease control and intervention costs applied in an infectious disease model and can be additive. Based on the considerations mentioned earlier, the following OCP is formulated by a hybrid cost function combining linear and quadratic terms, where the c...	BCA	CAB	ACB	CBA	Selection 4
A: They control voluntary movement and also make a crucial role in cognitive processes (e.g., action selection)B: Dysfunction in the BG is related to movement disorder (e.g., PD) and cognitive disorder.C: The BG exhibit diverse functions for motor and cognition	BCA	ABC	ACB	CBA	Selection 1
A: Therefore, future work should aim to compute and store the Rashomon set of a wider variety of model classes. Future work may investigate incorporating Rashomon sets that may be well-approximated (e.g., GAMs, [10]), but not computed exactly, into the RID approach. Nonetheless, sparse trees are highly flexible, an...	CAB	BAC	ABC	ABC	Selection 1
A: We report our performance against five leading methods [24, 41, 15, 32, 37]B: We detail our experimental methodology in Sec. 5.1 and report quantitative and qualitative evaluations in Sec. 5.2. Ablation studies are presented in Sec. 6. C: Following common practice in the field, we evaluate DREAM with the...	CBA	BCA	BAC	ABC	Selection 2
A: We note that the optogenetic treatment could have benefits in comparison to the traditional deep-brain-stimulation (DBS) treatmentB: The DBS has the following disadvantages OG3 ; OG4 ; (a) it is difficult to accurately determine the target cells, leading to cause many side effects and (b) a process with many...	CAB	CAB	CBA	ABC	Selection 4
A: Bürger and Lynch, 1995; Gomulkiewicz and Holt, 1995; Matuszewski et al., 2015). For models like this, our findings may be of relevance either for the initial response (in case of a sudden shift) or even in the long term (in case of a moving optimum). Below, we briefly review recent treatments focusing on the pol...	CAB	ACB	CBA	BAC	Selection 1
A: In this study, we aim to enhance GNNs to better capture long-range interactionsB: This novel approach reduces interaction distances between nodes to a single hop. Extensive experiments on four long-range graph benchmarks validate our method’s ability to enhance any GNN to capture long-range interactions. **C...	BAC	BCA	ACB	BAC	Selection 3
A: In one set of experiments, in order to study dependence on model size, we take a selection of LLMs from the Pythia family [22]B: We provide full details of the experiments in the Supplementary Information. Throughout the paper we primarily investigate the open source GPT-J model with around 6 billion paramet...	ACB	ACB	BAC	ABC	Selection 3
A: Our analysis has focused only on reconstructing the covariance between the taxa in a set of samplesB: To understand more general relationships, including across kingdoms, other methods should be employed alongside covariance network reconstructionC: In particular, non-negative tensor factorization metho...	CAB	BCA	ABC	BCA	Selection 3
A: The virus is now managed similarly to seasonal influenza, with new vaccine booster shots tailored to target emerging virus variants. B: At present, daily life in most countries has returned to pre-pandemic normsC: The development and widespread use of vaccines and treatments eventually brought an end to ...	CBA	BCA	ACB	ABC	Selection 1
A: Since each p𝑝pitalic_p-dimensional simplex corresponds to a collection of (p+1)𝑝1(p+1)( italic_p + 1 ) data points222Recall that points are 00-dimensional simplices, edges are 1111-dimensional, etc., we can assign weights to the datapoints themselves by considering for each node in the Vietoris-Rips complex, t...	CAB	BCA	CAB	ABC	Selection 4
A: In iopart.cls, to make any line start at the left margin of the page, add \fl at start of the line (to indicate full left).B: The iopart.cls class file automatically does this and indents each line of a displayC: The normal style for aligning displayed equations in our published journal articles is to a...	ACB	BAC	CBA	ACB	Selection 3
A: As evidenced in FigB: However, the pre-trained LMs are not inherently trained on data specific to the target environmental ecosystems, which often results in a failure to effectively capture feature dependencies within the descriptionsC: 3 (b), the input features from samples in different seasons tend t...	CAB	CAB	BAC	ACB	Selection 3
A: Nucleotide Transformer introduced the first large-scale transformer-based DNA LMs. All NT models share the same architecture, but differ in their number of training genomes and model parametersB: A second generation of multispecies models released later (NT-V2) extended the input length to 12,282 bp. The NT ...	ABC	ABC	ACB	BAC	Selection 3
A: However, from a statistical perspective, concerns arise regarding the potential for false discoveries of genes that lack genuine spatial variability. This concern becomes more pronounced when a large number of genes are simultaneously tested across most frameworks. If the false discovery rate or type 1 error is ...	BAC	BCA	BCA	CBA	Selection 4
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 architecturesB: Models without pre-training (represented by ’w/o pretrain’) perform worst in all tasks. Pre-training strategies without data augmentation...	ACB	BCA	CAB	ABC	Selection 2
A: During the downstream task, the classification head is attached to the pretrained encoder and its weights are fine-tuned on the dataset of said task in a fully-supervised manner. The architecture of the ”downstream model” is used as a baseline in all of our experiments, where all of its layer weights are adjuste...	CBA	ACB	BAC	ABC	Selection 1
A: Our main analysis encompasses two distinct definitions of tumor recurrence: a broad definition including edema, enhancing core, and necrotic core, and a more specific definition aligned with current RANO guidelines focusing only on the enhancing coreB: Furthermore, we conduct a patient-specific comparison wi...	BCA	CAB	ACB	CAB	Selection 3
A: Figure 2: Time course of C𝐶Citalic_C derived by solving Eqs. (3)–(4) for the same parameter values as in Fig. 1B: In (a) and (b) we show the time evolution for two initial conditions to illustrate that the only fixed point of the system is stable but excitableC: In (c) there is a stable limit cycle.	ABC	BAC	BCA	BAC	Selection 1
A: The top three values for each metric and each track are marked as gold, silver and bronze cells in decreasing order. A ‘*’ behind the team name means that the segmentation predictions have been converted from the multiclass submissions and inserted here. If a team only submitted to one of the tracks the columns ...	CAB	BAC	BAC	ACB	Selection 1
A: Building upon DDPMs, MoFusion (Dabral et al. 2023) employs U-Net (Ronneberger, Fischer, and Brox 2015) as the backbone for the denosing kernel in motion sequence synthesis. Apart from applications on continuous data, many research efforts are devoted to discete data generationB: EDP-GNN (Niu et al. 2020) int...	ABC	ACB	BAC	BCA	Selection 4
A: In this diagram, every point is represented by a cell enclosed by the red solid lines and dashed curves, then the surface area can be calculated with such information.B: The purpose of this step is to obtain the dual complex 𝒞𝒞\mathcal{C}caligraphic_C and the conjugated Laguerre diagramC: As shown in F...	BAC	BCA	CBA	BAC	Selection 3
A: 2021) and ChemBERTa-2 (Ahmad et al. 2022). B: Additionally, in our experiments, we tested two types of M-Encoder: CHEM-BERT (Kim et alC: Since any molecular pretraining model can serve as the M-Encoder in our method, in this section we mainly describe the Transformer encoder block (TEB), the fundamental ...	ACB	CBA	BCA	ACB	Selection 2
A: Of course, this qualitative understanding is no substitute for the detailed analysis obtained by solving the replicator equation and, in particular, cannot predict the existence of an all-cooperators regime. B: Direct application of the variance decomposition formula Weiss_2005 shows that a non-degenerate d...	CAB	CAB	CBA	ACB	Selection 3
A: In exploring the influence of racial and ethnic groups on BP values, we categorized the final pre-processed dataset based on the racial/ethnic groups listed in Table IIB: Importantly, race and ethnicity are compound factors, impacted by biology (genetic factors that impact BP from a physiological or anatomi...	BAC	BCA	ACB	ABC	Selection 4
A: The effects of repressing the clock can be seen in Figure (4A) which shows the dynamics of the core circadian oscillator gene BMAL1. The failure of BMAL1 to oscillate indicates the repression of the circadian clock. Figure (4B) shows the filter output for BMAL1. B: In order to demonstrate the scalability of...	CAB	CBA	CBA	CBA	Selection 1
A: We propose Absorb-Escape, a generalisable post-training algorithm for refining the quality of generated discrete sequencesB: We show that Absorb-Escape further increases the performance of DiscDiff by 4% in long DNA generationC: In addition, Absorb-Escape allows control over the property of generated sa...	ACB	CAB	ABC	BAC	Selection 3
A: FM-indexes over minimizer digests are known to be usually significantly faster than indexes over the original datasets, both because some characters are not represented in the digests and because we use a backward step for each minimizer rather than for each character, incurring fewer cache missesB: If we ar...	ABC	BAC	CBA	ABC	Selection 2
A: We base our kernels on the vLLM implementation ([51]).B: Fused kernels enable complex operations, such as Rotary Embedding ([50]) which would otherwise be executed sequentially, to be combined into a single kernel than can be executed in parallel on a GPUC: To optimize the forward pass, we implement fus...	CBA	BCA	BCA	ACB	Selection 1
A: This feature denotes the level of light scatter at a 90-degree angle in relation to the laser beamB: Side Scatter (SSC)-Cell’s granularityC: SSC reflects the internal complexity or granularity of the cell, encompassing features like the presence of granules, nuclei, or other organelles. A high importance...	BAC	ABC	ACB	CAB	Selection 1
A: The natural deathB: both phases of the pandemicC: The recovery periods σ−1superscript𝜎1\sigma^{-1}italic_σ start_POSTSUPERSCRIPT - 1 end_POSTSUPERSCRIPT and γ−1superscript𝛾1\gamma^{-1}italic_γ start_POSTSUPERSCRIPT - 1 end_POSTSUPERSCRIPT are taken to be 21⁢days21days21\,{\rm days}21 roman_days	CBA	BAC	CAB	BCA	Selection 3
A: Parameter reallocation within the network also plays an important role in memory conservationB: This step involves redistributing parameters by expanding channel width in critical modules while reducing it in less important onesC: This strategy allows for more efficient learning of representations in hig...	CAB	BCA	ABC	CAB	Selection 3
A: Any approximation to 𝐊𝐊\mathbf{K}bold_K that accounts for identical repetitions, including all known lossless statistical compression algorithms, can achieve equivalent or superior results, as demonstrated in the Supplementary Information and [4]B: This alignment with ‘Template Program A’ effectively high...	CAB	ABC	CBA	BAC	Selection 2
A: This tactic for Cognitive Security against readout requires alteration, albeit strategically minimal alteration. And as seen with the similarities between SMON/SION and MOA/IOA, there is a meaningful analogy between AA and defensive measures against RA, and between RA and defensive measures against AA. If no rea...	CAB	BAC	BCA	BCA	Selection 2
A: These metrics are evaluated both within a batch of 64 samples and across the entire test set, following the methodology outlined in Liu et al. (2023b). As presented in Table 1, MolBind’s performance surpasses that of MolCA by a large margin. Overall, MolBind significantly outperforms prior work on two molecule-l...	CAB	ACB	BAC	BAC	Selection 1
A: 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 tree. Since the maximum tree depth allowed by AiZynthFinder’s default parameters is 7, we assign a depth of 10 for molecules where a route is not found. B:...	ACB	CAB	ABC	ABC	Selection 2
A: The three panels summarize the system behavior for α=0.8,0.4𝛼0.80.4\alpha=0.8,0.4italic_α = 0.8 , 0.4, and 0.2, where the inner invasion in odd-labeled loop is strong, intermediate or weakB: Our first results, shown in Fig. 3, were obtained when the interaction between the triplets are strongC: Evidentl...	BCA	BAC	BCA	ACB	Selection 2
A: We compare several transformer architectures on the task of cancer detection on a single ROIB: We choose a modified ResNet18 [9] as our ROI-scale baseline, with only one sequence of convolutions and batch normalization in each residual block. This reduction in the number of parameters mitigates overfitting a...	BCA	CAB	ACB	CBA	Selection 3
A: One response was removed because the person stated in the open ended comments that they did not use the tool, but filled out the survey anyway. User responses indicated that the dashboard were visually appealing (>89% appealing or very appealing) sufficiently easy to navigate (>82% responded easy or very easy), ...	BCA	ABC	CBA	BAC	Selection 3
A: These MLMs are available in the HuggingFace transformers library Wolf et al. (2020). However, it can be noted that some level of adaptation was needed at the tokenization step to use some of the models within NLstruct, especially for frALBERT and FlauBERT models555The source code is available here: https://gitla...	BAC	ABC	CBA	CAB	Selection 3
A: The proposed method has a wide variety of potential applications, including drug discovery, and molecular designB: By creating low-dimensional embeddings and using them to find molecules with related qualities, the approach makes it possible to construct unique compounds with certain properties. Overall, thi...	BCA	ABC	CBA	ACB	Selection 4
A: Specifically, we first introduce indices evaluating signal distortion by the gain and the phase delay characteristics and derive these characteristics of MC channels based on the diffusion equation and the rate equationB: We then show design conditions for MC channels in which the magnitude of distortion bec...	CBA	BAC	BCA	CAB	Selection 3
A: The prediction-based method, a learning-based approach, employs a deep neural network to extract meaningful features from past statesB: It leverages the neural network’s ability to automatically learn and remember states without requiring manually designed storage solutions and also promotes more efficient e...	ACB	CAB	ABC	BAC	Selection 3
A: 2023b; Zhang et al. 2022b)B: Recently, a growing body of literature has explored the integration of SNNs with DRL (Zhang et al. 2022a; Wang et alC: Several methods convert a trained DQN into a SNN version (Patel et al. 2019; Tan, Patel, and Kozma 2021) or directly train a deep spiking Q-network (Liu et a...	BAC	BCA	CAB	ACB	Selection 1
A: We remove the data augmentation during the second training stage, which means training solely using the DFS order that can generate canonical SMILESB: Data AugmentationC: Table 6 demonstrates a significant decline in model performance across all metrics. This clearly demonstrates that our data augmentat...	BCA	BAC	ACB	ACB	Selection 2
A: For flow-based models, despite exhibiting high uniqueness and novelty, their validity was lower, specifically less than 89.03%percent89.0389.03\%89.03 %, which significantly trails behind InstGAN. InstGAN demonstrated comparable performance to SOTA diffusion models GDSS and D2L-OMP. All models, including pretrai...	CBA	CAB	CAB	BCA	Selection 4
A: It may be that one or a few self-supervised tasks are insufficient to learn effective representations, as mentioned in [22]B: To further showcase the effectiveness of our method, we compare our algorithm with some recent protein pretraining language models on fold classification [68, 20, 37, 85, 94], which ...	BCA	BCA	BAC	ABC	Selection 3
A: Advancing in these two directions constitutes the central motivation of the present work.B: The systematic investigation of whether each type of heterogeneity enhances or diminishes the probability of infection has not been systematically undertaken in previous studiesC: Furthermore, a link between hete...	BAC	BAC	BCA	CAB	Selection 4
A: Target novelty (N): The percentage of novel molecules among all the desired valid molecules, the novel molecule is different from training samples;B: 3C: Target validity (V): The percentage of valid molecules among all the desired molecules, which is measured by RDkit (Landrum et al., 2016) and widely us...	CBA	ABC	CAB	ABC	Selection 3
A: Each training image is shown 4 times, and each test image is shown 80 times. We took the average of all trials for each image to form the final dataset. B: Each trial in the data is from -0.2 seconds to 0.8 seconds relative to the onset of the stimulusC: The training images and test images are presented ...	ABC	CAB	BAC	ABC	Selection 2
A: Our drug-ASE matrix analysis (FigB: 6) to data from Google Trends (Fig. 7), we found that the ASEs mentioned most frequently over time are nausea, pain, vomiting, and constipation.C: 4) highlights numerous prevalent ASEs based exclusively on social media reports. Additionally, comparing mentions of ASEs ...	BCA	ACB	ABC	BCA	Selection 2
A: Our approach retrieves drug information using a set of free-to-use application program interfaces (APIs) provided by NLM via representational state transfer (REST) to access the RxNorm and RxTerms datasets: the RxNorm and RxTerms [9], and RxClass [10] APIsB: To avoid sending potentially thousands of request...	BAC	BAC	BCA	ABC	Selection 4
A: This modification removes sampling error in the fragment generation process, creating an artificially easier learning problem that should result in better performance. We emphasize that ICEBERG-ADV is only suitable for benchmarking: in most realistic C2MS problems ground truth spectra are not available at infere...	CAB	CBA	BAC	ACB	Selection 2
A: In addition, we do not cover web-based tools, software and libraries that implement prediction methods (see e.g. [8] for a review). B: We limit our focus to new methods that have been tested against large benchmark datasets on pre-clinical synergy and dose response data, in particular leaving out drug-drug i...	BCA	ACB	BCA	CAB	Selection 4
A: The complexity K⁢(S)𝐾𝑆K(S)italic_K ( italic_S ) measures the number of distinct transformations, including their execution conditions, allowed by the graph transformation modelB: Such a complexity measure is useful for study and evaluation of empirically inferred input transition systems. In the case of ch...	ACB	BCA	BCA	ABC	Selection 1
A: These works hypothesise a minimal thermodynamic cost or entropy production per product made, which is related to the information accurately transferred from template to products [2, 31, 32]B: However, entropy production in stochastic thermodynamics is related to the relative rate of forwards and backwards tr...	ACB	CAB	BCA	BAC	Selection 3
A: In addition to clustering, the software includes a feature for outlier detection to identify residues that deviate significantly from the expected torsion angle distributionsB: The software employs a distance-based approach to identify outliers, where residues that fall beyond a certain threshold euclidean ...	ABC	BCA	ABC	ACB	Selection 4
A: (2012). And individuals can be prone to stay away from those with similar opinions corresponding to out-group bias Kimura and Hayakawa (2008). Thus social relationships are under social biases.B: (2012); Fu et alC: Individuals can voluntarily stay away from those who do not adopt their opinions correspon...	BCA	CAB	CBA	BCA	Selection 3
A: However, though ABC can potentially be expanded to high-dimensional applications, it is usually only practical to apply ABC when the parameter space is relatively low-dimensional. We propose to focus on inferences for the contagion parameters while considering the true network as a nuisance parameter that is mar...	ACB	BAC	CBA	ABC	Selection 3
A: Here, we focused on the widespread standard consolidation theoryB: However, there exist other models and questions around systems memory consolidation conceptsC: For instance, the multiple trace theory suggests that some of the hippocampus patterns are conserved in the long term. This theory follows obs...	BAC	BAC	ABC	BCA	Selection 3

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