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281 results for “Capabilities”
Four Essential Components for FAIR Data: Capability & Category-Specific Requirements
<p>Adapted from Bailo (2019) and Peng (2023), this diagram illustrates FAIR requirements specific to data, metadata, and infrastructure, aligned with the definitions of individual FAIR principles. It highlights the critical role of enterprise capabilities—including processes, systems, standards, tools, and skills—in supporting FAIR data. These four components are essential for systematically enhancing the overall FAIRness of an organization's scientific data collection</p> <p> </p>
Data set supplementing "Benchmarking triage capability of symptom checkers against that of medical laypersons: Survey study"
<p>This is the de-identified data set used to conduct the analyses in the study published as Original Research in the JMIR under the title "Benchmarking triage capability of symptom checkers against that of medical laypersons: Survey study" (https://doi.org/10.2196/24475)</p> <p>The data set contains the assessments of the urgency of symptoms to 45 fictitious clinical case vignettes by 91 US participants, and the participants' age, gender and level of education. Data for the symptom checker apps is needed to fully reproduce our study and can be found in the appendix of the paper "Evaluation of symptom checkers for self diagnosis and triage: audit study" by Semigran et al. (2015) (https://doi.org/10.1136/bmj.h3480).</p>
Thermally switchable, bifunctional, scalable, mid-infrared metasurfaces with VO2 grids capable of versatile polarization manipulation and asymmetric transmission
<p>The data generated by CST Studio Suite that are used to plot a part of the figures, and sample CST scripts. </p> <p>Research supported by Narodowe Centrum Nauki, project no UMO-2020/39/I/ST3/02413. </p>
Dataset of "Capabilities of a novel electrochemical cell for operando XAS and SAXS investigations for PEM fuel cells and water electrolysers"
<p>With this work we present a reversible electrochemical cell and introduce a valuable approach, suitable for being used either for in operando X-Ray Absorption Spectroscopy (XAS) and Small Angle X-Ray Scattering (SAXS). The reversible electrochemical cell was used to depict the time-resolved degradation of a Pt/C catalyst material for Proton Exchange Membrane Fuel Cells (PEMFC). The evolution of the specific electrochemical active surface area (ECSA) was coupled to the evolution of morphological parameters, supported by the analysis of Pt oxidation state. As a result, we obtain a coherent picture in which: the increase of particle (and particle cluster) size is connected to the diminishing of ECSA and to the changes in the fraction of metallic Pt, detailing as the evolution develops in the first 2000 cycles, as previously observed on catalyst model systems. Finally, we introduce some preliminary results underlying the change in Ir oxidation state for a commercial Ir/IrO X catalyst material for PEM water electrolysers and showing as this change is not sufficient to induce any remarkable morphological variations within 500 cycles of accelerated stress tests.</p>
Geo-referencing of journal articles and platform design for spatial query capabilities
<p>We analyzed the corpus of three geoscientific journals to investigate if there are enough locational references in research articles to apply a geographical search method, on the example of New Zealand. We counted place name occurrences that match records from the official Land Information New Zealand (LINZ) gazetteer in the titles, abstracts and full texts of freely available papers of the New Zealand Journal of Geology and Geophysics, the New Zealand Journal of Marine and Freshwater Research, and the Journal of Hydrology, New Zealand, for the years 1958 to 2015. We generated ISO standard compliant metadata records for each article including the spatial references and make them available in a public catalogue service.</p> <ol> <li><em>articles_georef_count_data.xlsx</em>: The counts and evaluation tracking of the place name occurrences in the journal articles.</li> <li><em>summary_final.xlsx</em>: Summary statistics for evaluation based on the counts data.</li> <li><em>article_template.xml</em>: XML template for ISO 19139 compliant metadata record filled for each article.</li> <li><em>full_article.xm</em>l: Exemplary fully filled ISO 19139 compliant metadata record.<br> </li> </ol>
Replication package for "Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation"
<p>This repository contains the replication package for the paper "Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation" by Fernando Vallecillos Ruiz, Anastasiia Grishina, Max Hort and Leon Moonen, accepted for publication in ACM Transactions on Software Engineering and Methodology on 2025-10-09.</p> <p>A preprint is deposited on arXiv with DOI: <a href="https://doi.org/10.48550/arXiv.2401.07994">10.48550/arXiv.2401.07994</a>.</p> <p>The replication package is archived on Zenodo with DOI: <a href="https://doi.org/10.5281/zenodo.10500593">10.5281/zenodo.10500593</a>. It is maintained on GitHub at <a href="https://github.com/secureIT-project/RTT_for_APR">https://github.com/secureIT-project/RTT_for_APR</a>.</p> <p>This project builds on code from the <a href="https://github.com/lin-tan/clm/">clm</a> project, which is (c) 2023, The ASSET research group led by Lin Tan, Purdue University, licensed under the BSD 3-Clause License (see jasper/LICENSE.BSD). All modifications and new contributions are (c) 2025 by the authors of this replication package and distributed under the MIT License (see LICENSE.MIT). The data, models and preprint are distributed under the CC BY 4.0 license.</p> <h2>Citation<code> </code></h2> <p>If you build on this data or code, please cite this work by referring to the paper:</p> <div> <pre><code>@article{ruiz2025:rtt, title = {Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation}, author = {Vallecillos Ruiz, Fernando and Anastasiia Grishina and Max Hort and Leon Moonen}, journal = {ACM Transactions on Software Engineering and Methodology (TOSEM)}, year = {2025}, publisher = {{ACM}} }</code></pre> </div> <h2>Organization</h2> <p>The replication package is organized as follows:</p> <ul> <li>clm-apr <ul> <li>plbart: code to generate patches with PLBART models.</li> <li>codet5: code to generate patches with CodeT5 models.</li> <li>transcoder: code to generate patches with the TransCoder model.</li> <li>incoder: code to generate patches with InCoder models.</li> <li>santacoder: code to generate patches with the SantaCoder model.</li> <li>starcoder: code to generate patches with the StarCoderBase model.</li> <li>quixbugs: code to validate patches generated for the QuixBugs benchmark.</li> <li>defects4j: code to validate patches generated for any of the Defects4J benchmarks.</li> <li>humaneval: code to validate patches generated for the HumanEval-Java benchmark.</li> </ul> </li> <li>humaneval-java: the HumanEval-Java benchmark proposed by Jiang et al. 2023</li> <li>jasper: a Java tool to parse Java programs needed to preprocess input.</li> <li>model: folder to download the language models.</li> <li>analysis_wandb: data from WandB and Jupyter notebook to create graphs.</li> <li>tmp_benchmarks: folder for temporary files used in patch validation. The folder may contain pairs of `paralell’ folders src and src_org for each benchmark, used to replace buggy code with candidate patches.</li> </ul> <h2>Replication</h2> <h3>Prerequisites</h3> <ul> <li>Python version: 3.8—3.10.</li> <li><a href="https://git-lfs.com/">Git LFS</a> is required for model downloading.</li> </ul> <h4>Weight and Biases (WandB)</h4> <ol> <li>Create an account on <a href="https://wandb.ai/">Weights and Biases</a></li> <li>Install the <a href="https://docs.wandb.ai/ref/python">Weights and Biases</a> library</li> <li>Run <code>wandb login</code> and follow the instructions</li> </ol> <h4>Set up OpenAI access</h4> <p>OpenAI account is needed with access to <code>gpt-3.5-turbo</code> and <code>gpt-4</code> . The <code>OPENAI_API_KEY</code> environment variable should be set to your OpenAI API access token.</p> <h3>Dependencies</h3> <ul> <li><a href="https://github.com/rjust/defects4j">Defects4J</a> - To generate inputs for the Defects4J datasets or to validate them, you need to have installed <a href="https://github.com/rjust/defects4j">their tool</a>.</li> <li>Java 8</li> <li>Apache Maven</li> </ul> <h3>Setup</h3> <p>We recommend the use of the setup script:</p> <pre><code>setup.sh </code></pre> <p>which performs the following:</p> <ol> <li>Creates a virtual environment for Python and activate it.</li> <li>Install the packages in <code>requirements.txt</code>.</li> <li>Compiles Jasper.</li> <li>Downloads parsers.</li> <li>Check if the Defects4J installation is correct.</li> </ol> <h3>Download models</h3> <p>The following bash script contains the code to download all of the models used:</p> <pre><code>models/download_models.sh </code></pre> <p>We recommend downloading only the models you are going to use due to their size</p> <pre><code>cd models chmod +x download_models.sh ./download_models.sh </code></pre> <p>To run one specific model, for example, PLBART (C#), use the following commands:</p> <pre><code>cd models git lfs install git clone https://huggingface.co/uclanlp/plbart-java-cs git clone https://huggingface.co/uclanlp/plbart-cs-java cd ../.. </code></pre> <h3>Step 1: Preprocessing and Prompting:</h3> <p>Each script in each <code>clm-apr/[model]</code> folder connects one or more models with<br>one dataset. These scripts follow the template: [benchmark]_[model]_[technique].py.<br>The scripts first create an <code>[model]_input.json</code> file with the preprocessed<br>input. Then generate outputs based on that file with one or more models.<br>For example:</p> <pre><code>cd clm-apr/plbart python quixbugs_plbart_round.py # Generates input for QuixBugs and generate patches using Java<->C# RTT. python quixbugs_plbart_round_nl.py # Generates input for QuixBugs and generate patches using Java<->NL RTT. </code></pre> <p>Optionally, use argument <code>--device_map cpu</code> if you wish to run the script on<br>CPU, for example:</p> <pre><code>python quixbugs_plbart_round.py --device_map cpu </code></pre> <p>Otherwise, the script will be run on all available CUDA GPU’s.</p> <p>We have commented the generation of inputs in the scripts. Users are free to<br>uncomment this method and try for themselves. It is easily recognizable by<br>their name template <code>[model]_[benchmark]_input()</code>. In the previous case:</p> <pre><code>quixbugs_plbart_input() </code></pre> <h3>Step 2 and 3: Round Trip Translation and Postprocessing</h3> <p>These steps are also included in the [benchmark]_[model]_[technique].py<br>script mentioned above. They are modularized in the method recognizable by<br>their name template [model]_[benchmark]_output().<br>For example:</p> <pre><code>quixbugs_incoder_output() </code></pre> <p>This method:</p> <ol> <li>Reads the input json file.</li> <li>Generates outputs through the LLM.</li> <li>Postprocess the output (extract the patch, clean up extra token, etc.).</li> <li>Creates [model]_output_[technique]_[extra].json.</li> </ol> <p>The last 3 steps are repeated according to the number of runs set to performed<br>(10 in our experiments). Each run will produce a different file with the seed<br>used in its generation. For example, <code>quixbugs\_plbart\_round.py</code> and<br><code>quixbugs\_plbart\_round_nl.py</code> scripts create:</p> <pre><code>clm-apr/quixbugs/plbart_results/run_0/plbart_java_cs_java_output_round_csharp_batch.json clm-apr/quixbugs/plbart_results/run_0/plbart_java_nl_java_output_round_nl_batch.json </code></pre> <h3>Step 4: Evaluation of RTT Results:</h3> <p>The last step evaluates the generated outputs against the test-suites of each<br>benchmark. This script reads the previous outputs files and generates a new one<br>with the results of the test for one model. Furthermore, it connects with the<br><em>WandB</em> tool to calculate metrics and send them to analyze.</p> <p>Following the previous examples, to validate the results previously obtained,<br>we execute the following:</p> <pre><code>cd clm-apr/quixbugs python validate_quixbugs_parallel.py </code></pre> <p>Given the included JSON, this script would create:</p> <pre><code>clm-apr/quixbugs/plbart_results/run_0/plbart_java_cs_java_validate_round_csharp_batch.json </code></pre> <p>We have disabled <em>WandB</em> in the script to allow users to try the script first.<br>However, it can be easily activated by changing the parameter <code>mode="disabled"</code><br>to <code>mode="online"</code>.<br>We have set the variable <code>total_runs = 1</code>, as well as <code>input_file</code> and <code>output_file</code><br>to the results included. They should be modified accordingly to validate more runs<br>or to validate other files/models.</p> <h3>Included Results</h3> <p>We include two CSV files obtained through WandB.</p> <pre><code>'data_cleaned_grouped.csv': Aggregated metrics of the 25 outputs for all runs. 'full_data_all_runs.csv': All metrics for all outputs on all runs. </code></pre> <h2>Changelog</h2> <ul> <li>v1.0 - updates corresponding to the accepted version of the manuscript in TOSEM</li> <li>v0.1 - initial replication package corresponding to v1 of arXiv deposit: includes raw data, code, and example outputs.</li> </ul> <h2>References</h2> <p>Jiang, N.; Liu, K.; Lutellier, T.; and Tan, L. 2023. Impact of Code Language<br>Models on Automated Program Repair. In 45th International Conference on<br>Software Engineering (ICSE), 1430–1442. IEEE. ISBN 978-1-66545-701-9.</p> <div> </div>
Fig. 1 in Evidence of Stress Recovery in Free-Living Ciliate Colpoda cucullus: The Repair Capability of Resting Cysts to Damage Caused by Gamma Irradiation
Fig. 1. Excystment assay of Colpoda wet cysts (A) and dry cysts (B). 'Non-irradiated' indicates non-irradiated cysts; 'irradiated' indicates cysts irradiated at 4000 Gy, and 'irradiated-incubated' indicates cysts irradiated at 4000 Gy and incubated for 12 hours before the induction of excystment. Time indicates the number of hours after the induction of excystment. Columns and attached bars correspond to the means and standard errors, respectively, of six measurements. Asterisks and double asterisks represent significant differences at p <0.05 and p <0.01 (Mann-Whitney U test), respectively.
To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing?
<p>Datasets created and used in the paper "To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing?"</p> <p>https://arxiv.org/pdf/2109.13445.pdf</p>
Disseminating metaproteomic informatics capabilities and knowledge using the Galaxy-P framework
<p>Data for the "<strong>Disseminating metaproteomic informatics capabilities and knowledge using the Galaxy-P framework</strong>" paper and training.</p>
Maintenance of a narrow hybrid zone between native and introduced red foxes (Vulpes vulpes) despite conspecificity and high dispersal capabilities
<p>Human-facilitated introductions of nonnative populations can lead to secondary contact between previously allopatric lineages, resulting in either homogenization of the lineages or stable hybrid zones that are maintained by pre-zygotic (e.g., behavioral) or post-zygotic (e.g., reduced hybrid fitness) reproductive barriers. We investigated patterns of gene flow between the native Sacramento Valley red fox (<em>Vulpes vulpes patwin</em>) and an introduced conspecific population of captive-bred (fur-farm) origin in California's Central Valley. Considering their recent divergence (i.e., ~50 kya), we hypothesized that pre-zygotic mechanisms primarily impede gene flow, rather than post-zygotic barriers. Additionally, some genes originating in nonnative foxes may confer higher fitness in the currently human-dominated landscape resulting in selective introgression into the native population. Genetic analysis of 682 red foxes (255 native, 427 nonnative) at both mitochondrial (cytB + Dloop) and nuclear loci (~19,000 SNPs) revealed significantly narrower cline widths than expected under a simulated model of unrestricted gene flow, consistent with the existence of pre- or post-zygotic reproductive barriers. We identified several loci with reduced introgression linked to behavioral divergence in captive bred foxes, which supports pre-zygotic mechanisms as a putative driver of the narrow hybrid zone. Additionally, several loci with elevated gene flow from the nonnative into the native population, were near genes associated with adaptation to human dominated landscapes. Overall, this study contributes to our understanding of hybrid zone dynamics in vertebrates, particularly in the context of species introductions and landscape changes, underscoring the importance of considering multiple mechanisms that may be at play in maintaining lineages at both the species and subspecies level.</p>
CausalBench A Comprehensive Benchmark for Evaluating Causal Reasoning Capabilities of Large Language Models
<p>CausalBench is a comprehensive benchmark dataset designed to evaluate the causal reasoning capabilities of large language models. The primary uses of this dataset include, but are not limited to:</p> <p>- Testing the performance of large language models on causal reasoning tasks</p> <p>- Serving as a benchmark dataset for causal reasoning research</p> <p>- Improving and developing new causal reasoning algorithms and models</p>
Tadpoles rely on mechanosensory stimuli for communication when visual capabilities are poor
<p>The ways in which animals sense the world changes throughout development. For example, young of many species have limited visual capabilities, but still make social decisions, likely based on information gathered through other sensory modalities. Poison frog tadpoles display complex social behaviors that have been suggested to rely on vision despite a century of research indicating tadpoles have poorly-developed visual systems relative to adults. Alternatively, other sensory modalities, such as the lateral line system, are functional at hatching in frogs and may guide social decisions while other sensory systems mature. Here, we examined development of the mechanosensory lateral line and visual systems in tadpoles of the mimic poison frog (<em>Ranitomeya imitator)</em> that use vibrational begging displays to stimulate egg feeding from their mothers. <em>We found that tadpoles hatch with a fully developed lateral line system. While begging behavior increases with development, ablating the lateral line system inhibited begging in pre-metamorphic tadpoles, but not in metamorphic tadpoles.</em> We also found that the increase in begging and decrease in reliance on the lateral line co-occurs with increased retinal neural activity and gene expression associated with eye development. Using the neural tracer neurobiotin, we found that axonal innervations from the eye to the brain proliferate during metamorphosis, with little retinotectal connections in recently-hatched tadpoles. We then tested visual function in a phototaxis assay and found tadpoles prefer darker environments. The strength of this preference increased with developmental stage, but eyes were not required for this behavior, possibly indicating a role for the pineal gland. Together, these data suggest that tadpoles rely on different sensory modalities for social interactions across development and that the development of sensory systems in socially complex poison frog tadpoles is similar to that of other frog species.</p>
Piezo1 ion channels are capable of conformational signaling
<p>Piezo1 is a mechanically activated ion channel that senses forces with short latency and high sensitivity. Piezos undergo large conformational changes, induce far-reaching deformation onto the membrane, and modulate the function of two-pore potassium (K<sub>2P</sub>) channels. Taken together, this led us to hypothesize that Piezos may be able to signal their conformational state to other nearby proteins. Here, we use chemical control to acutely restrict Piezo1 conformational flexibility and show that Piezo1 conformational changes, but not ion permeation through it, are required for modulating the K<sub>2P</sub> channel TREK1. Super-resolution imaging and stochastic simulations further reveal that both channels do not co-localize, which implies that modulation is not mediated through direct binding interactions; however, at high Piezo1 densities, most TREK1 channels are within the predicted Piezo1 membrane footprint, suggesting the footprint may underlie conformational signaling. We speculate that physiological roles originally attributed to Piezo1 ionotropic function could, alternatively, involve conformational signaling.</p>
Figure 2 in Diversity and enzymatic capabilities of fungi associated with the digestive tract of larval stages of a shredder insect in Cerrado and Amazon Forest, Brazil
Figure 2. Percentage of fungal isolates from the DT of Triplectides (Trichoptera: Leptoceridae) in Cerrado (A) and Amazon Forest (B) biomes producers and non-producers of xylanase (Xyl) and cellulase (CMCase).
Fig. 1 in Assessing the flight capabilities of fed and starved Allograpta obliqua (Diptera: Syrphidae), a natural enemy of Asian citrus psyllid, with computerized flight mills
Fig. 1. Mean flight parameters measured for starved and fed Allograpta obliqua attached to flight mills for 24 h. Error bars indicate ± SEMs; asterisks indicate a significant (P <0.05) difference between feeding treatments.
Fig. 2 in Assessing the flight capabilities of fed and starved Allograpta obliqua (Diptera: Syrphidae), a natural enemy of Asian citrus psyllid, with computerized flight mills
Fig. 2. Mean flight parameters measured for male and female Allograpta obliqua attached to flight mills for 24 h. Error bars indicate ± SEMs; asterisks indicate a significant P <0.05) difference between sex.
Fig. 2 in Predation capability of Hippodamia convergens (Coleoptera: Coccinellidae) and Chrysoperla carnea (Neuroptera: Chrysopidae) feeding of Melanaphis sacchari (Hemiptera: Aphididae)
Fig. 2. Average of consumption rate (in %) of aphids by larvae and adults of Hippodamia convergens when allowed to freely forage 100 aphids for a period of 30 or 60 min. Larvae had a higher consumption rate, compared to adults, only for the 30-min period (t = −2.99; P = 0.0400).
Fig. 1 in Predation capability of Hippodamia convergens (Coleoptera: Coccinellidae) and Chrysoperla carnea (Neuroptera: Chrysopidae) feeding of Melanaphis sacchari (Hemiptera: Aphididae)
Fig. 1. Average consumption rate by adult males and females of the convergent ladybeetle (Hippodamia convergens) when allowed to freely forage for 24 h at different prey densities (4, 8, 16, 32, 64, or 128 aphids). The only statistical difference was found at density of 64 aphids (t = 3.625; P = 0.0222).
Fig. 5 in The effect of larval diet on the flight capability of the adult moth Athetis lepigone (Möschler) (Lepidoptera: Noctuidae)
Fig. 5. Flight distance (A) and max speed (B) of 3 to 4 d old Athetis lepigone moths with different host plants.
Fig. 4 in The effect of larval diet on the flight capability of the adult moth Athetis lepigone (Möschler) (Lepidoptera: Noctuidae)
Fig. 4. Frequency distribution of flight distance (A) and duration (B) of Athetis lepigone moths. The arrow shown in (B) shows the threshold flight time of 44.7 min that differentiates the short and long flight populations.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.