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3,688 results for “Computer”
Computational modeling of hemoglobin saturation heterogeneity in capillary networks
<p>This repository contains the C++ code based on OpenFOAM used for simulating oxygen transport with moving red blood cells. The OpenFOAM cases used to generate all results in the research article "The heterogeneity of hemoglobin saturation in capillaries and its relation to red blood cell transit time" are included.</p> <p>The archive 'code-axisymmetric.tgz' contains the code for the simulations in axisymmetric domains. This code works with OpenFOAM 2.1.1.</p> <p>The archive 'code-parallel_capillaries.tgz' contains the code for the simulations with parallel capillaries. This code is based on OpenFOAM 2.3.0.</p> <p>The archive 'code-graph.tgz' contains the simulation code for the simulations in reconstructed capillary networks. The postprocessing and plotting script are also in this archive. This code is based on OpenFOAM 2.3.0.</p> <p>The archive 'code-flow_reconstruction.tgz' contains the code for the flow reconstruction algorithm.</p> <p>The remaining archives contain the OpenFOAM cases that were used to run the oxygen transport simulations reported in the research article "The Heterogeneity of Hemoglobin Saturation in Capillary Networks and its Relation to Red Blood Cell Transit Time".</p>
Sets of second degree polynomials used in the problem of 3D neighborhood motion maps computations
<p>The files are Maple source files which contain sets of second degree polynomials used in the problem of computing 3D neighborhood motion maps. The files contain polynomials related to: 6-neighbrhood (see quadrics_N1.mpl); 18-neighbrhood (see quadrics_N2.mpl) and 26-neighbrhood (see quadrics_N3.mpl).</p> <p>The polynomials are related to the paper: Pluta K., Moroz G., Kenmochi Y., Romon P. (2016) Quadric Arrangement in Classifying Rigid Motions of a 3D Digital Image. In: Gerdt V., Koepf W., Seiler W., Vorozhtsov E. (eds) Computer Algebra in Scientific Computing. CASC 2016. Lecture Notes in Computer Science, vol 9890. Springer, doi:10.1007/978-3-319-45641-6_27</p> <p>To refer to a version of the algorithm used to compute the file use DOI:10.5281/zenodo.573013 (https://zenodo.org/badge/latestdoi/53963129).</p>
Global Sensitivity Analysis is Not Always Beneficial for Evolutionary Computation: A Study in Engineering Design
<p>This Zenodo repository contains all the results generated for the book chapter "Global Sensitivity Analysis is Not Always Beneficial for Evolutionary Computation: A Study in Engineering Design".</p>
Curated dataset of 18 computational experiments-(E1-E18)
<h2><strong>Overview</strong></h2> <p>This dataset, <strong>"Multi-Domain Experiment Dataset for Evaluating Reproducibility Tools (E1–E18),"</strong> is curated to facilitate the evaluation and benchmarking of reproducibility frameworks. It provides a structured and diverse collection of scientific experiments, enabling researchers and developers to test and compare different tools designed for computational reproducibility.</p> <h2><strong>Dataset Composition</strong></h2> <p>The dataset consists of 18<strong> experiments (E1–E18)</strong> covering multiple scientific domains, including <strong>computer science, human-computer interaction (HCI), medicine, artificial intelligence, climate change, and economics</strong>. These experiments range from simple computational scripts to complex setups requiring integrated databases, multiple programming languages, and domain-specific computational environments.</p> <h2><strong>Experiment Sources</strong></h2> <p>To ensure a well-balanced dataset, experiments were sourced from <strong>peer-reviewed scientific conferences</strong> and <strong>open-access repositories</strong>:</p> <ul> <li> <p><strong>Computer Science:</strong></p> <ul> <li><strong>Software Engineering:</strong> Experiments from the <strong>IEEE/ACM International Conference on Software Engineering (ICSE 2022)</strong>, a premier venue for software engineering research.</li> <li><strong>Databases:</strong> Selected experiments from the <strong>International Conference on Very Large Databases (VLDB 2021)</strong>, a leading database conference.</li> <li><strong>Human-Computer Interaction (HCI) and User Studies:</strong> <ul> <li>Experiments sourced from the <strong>European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2023)</strong>.</li> <li>These experiments focus on user studies related to software engineering and usability research.</li> </ul> </li> </ul> </li> <li> <p><strong>Interdisciplinary Fields (Collected from Zenodo):</strong></p> <ul> <li><strong>Artificial Intelligence (AI):</strong> Experiments covering machine learning and AI-driven methodologies.</li> <li><strong>Climate Change:</strong> Computational experiments and simulations addressing environmental research.</li> <li><strong>Medicine:</strong> Experiments focusing on medical and healthcare applications.</li> <li><strong>Economics:</strong> Computational economic models and data analysis experiments.</li> </ul> </li> <li> <p><strong>Related Work on Reproducibility Tools:</strong></p> <ul> <li>We included <strong>experiments previously used to evaluate reproducibility tools</strong> and methodologies.</li> <li>This ensures alignment with prior research and enhances comparability across tools.</li> <li>Among these, two key studies <a href="https://ieeexplore.ieee.org/document/9041769"><strong>SciInc</strong></a> and <strong><a href="https://doi.ieeecomputersociety.org/10.1109/eScience.2017.51">SciUnit</a> </strong>provided three fully documented experiments: <ul> <li><strong>Chicago Food Inspections Evaluation;</strong></li> <li><strong>Variable Infiltration Capacity;</strong></li> <li><strong>Incremental Query Execution.</strong></li> </ul> </li> </ul> </li> </ul> <h2><strong>Methodology for Dataset Curation</strong></h2> <p>To construct this dataset, we employed a structured selection process:</p> <ol> <li> <p><strong>Scientific Conference Selection:</strong></p> <ul> <li>We identified key research areas within <strong>computer science</strong> and selected experiments from <strong>ICSE 2022</strong>, <strong>VLDB 2021</strong>, and <strong>ESEC/FSE 2023</strong> (focusing on user studies in HCI).</li> </ul> </li> <li> <p><strong>Zenodo Repository Search:</strong></p> <ul> <li>Targeted searches were conducted using the keywords <strong>"Medical," "Artificial Intelligence," "Climate Change,"</strong> and <strong>"Economics."</strong></li> <li>We filtered results to include only <strong>software repositories</strong>.</li> <li>From the <strong>top 100</strong> search results in each category, <strong>five experiments were randomly selected per domain</strong>.</li> </ul> </li> <li> <p><strong>Reproducibility Tools & Related Work:</strong></p> <ul> <li>We incorporated experiments <strong>previously used to evaluate existing reproducibility tools</strong>.</li> <li>This selection ensures <strong>comparability and continuity</strong> with past reproducibility studies.</li> </ul> </li> </ol> <p> </p>
Glosario: A multilingual glossary for computing and data science terms.
<p><code>glosario</code> is an open-source glossary of terms used in data science that is available online and also as a library in both <a href="https://github.com/carpentries/glosario-r/">R</a> and <a href="https://github.com/carpentries/glosario-py/">Python</a>. By adding glossary keys to a lesson’s metadata, authors can indicate what the lesson teaches, what learners ought to know before they start, and where they can go to find that knowledge. Authors can also use the library’s functions to insert consistent hyperlinks for terms and definitions in their lessons in any of several languages. The master copy of the glossary lives in the <code>glossary.yml</code> file. </p>
Dataset for paper 'McAN: a novel computational algorithm and platform for constructing and visualizing haplotype networks'
<p>The .zip file includes four datasets for testing the performance of McAN (doi: https://doi.org/10.1093/bib/bbad174).</p>
On the computation of stable coupled state-space models for dynamic substructuring applications
<p>This paper aims at introducing a methodology to compute stable coupled state-space models for dynamic substructuring applications by introducing two novel approaches targeted to accomplish this task: (a) a procedure to impose Newtons's second law without relying on the use of undamped RCMs (residual compensation modes) and (b) a novel approach to impose stability on unstable coupled state-space models. The enforcement of stability is performed by dividing the unstable model into two different models, one composed by the stable poles (stable model) and the other composed by the unstable ones (unstable model). Then, the poles of the unstable state-space model are forced to be stable, leading to the computation of a stabilized state-space model. If this model is composed by real poles, it should be divided into two different ones, one composed by the pairs of complex conjugate poles and the other composed by the real poles. Afterwards, to make sure that the Frequency Response Functions (FRFs) of the stabilized model well match the FRFs of the unstable model, the Least-Squares Frequency Domain (LSFD) method is exploited to update the modal parameters of the stabilized model composed by the pairs of complex conjugate poles. The validity of the proposed methodologies is presented and discussed by exploiting experimental data. Indeed, by exploiting the FRFs of a real system, accurate state-space models respecting Newton's second law are computed. Then, decoupling and coupling operations are performed with the identified state-space models, no matter the models resultant from the decoupling/coupling operations are unstable. Stability is then imposed on the computed unstable coupled model by following the approach proposed in this paper. The methodology proved to work well on these data. Moreover, the paper also shows that the coupled state-space models obtained using this methodology are suitable to be exploited in time-domain analyses and simulations.</p>
Computational linguistics based text emotion analysis using enhanced beetle antenna search with deep learning during COVID-19 pandemic
Open the record for dataset details and reuse information.
Phlorest phylogeny derived from Robinson and Holton 2012 'Internal Classification of the Alor-Pantar Language Family Using Computational Methods Applied to the Lexicon'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Robinson, L. C., & Holton, G. (2012). Internal Classification of the Alor-Pantar Language Family Using Computational Methods Applied to the Lexicon. Language Dynamics and Change, 2(2), 123-149. doi:10.1163/22105832-20120201</p> </blockquote>
Simulation data for paper "Evaluation of Fendiline Treatment in VP40 System with Nucleation-Elongation Process: A Computational Model of Ebola Virus Matrix Protein Assembly"
<p>This is the original simulation data sets for paper "Evaluation of Fendiline Treatment in VP40 System with Nucleation-Elongation Process: A Computational Model of Ebola Virus Matrix Protein Assembly".</p>
Dataset for the publication titlted "A computational mechanics model for producing molecular assembly using molecularly woven pantographs" in the journal Cell Reports Physical Science, authored by Byeonghwa Goh and Joonmyung Choi.
<p>Dataset for the publication titlted "A computational mechanics model for producing molecular assembly using molecularly woven pantographs" in the journal Cell Reports Physical Science, authored by Byeonghwa Goh and Joonmyung Choi.</p>
Dataset for "Mo-Si alloys studied by atomistic computer simulations using a novel machine-learning interatomic potential: Thermodynamics and interface phenomena"
<p>This dataset was used to fit a general purpose machine-learning interatomic potential for Mo-Si alloys based on the Atomic Cluster Expansion (ACE) formalism. It supports the paper "Mo-Si alloys studied by atomistic computer simulations using a novel machine-learning interatomic potential: Thermodynamics and interface phenomena".</p>
Public data for nonlinear optical computational histology
<p>Experimental datasets for training and testing nonlinear optical computational histology (NOCH), which include label-free nonlinear optical data: stimulated Raman scattering (SRS) images of human brain tumors and multiphoton (MP) images of human ovarian cancers, and the corresponding H&E slices. The <a href="https://github.com/shenblin/NOCH">contrastive deep learning framework</a> can generate diagnostic quality H&E slides comparable to conventional histopathology. </p> <p>If you find this work useful in your research, please consider citing the paper:</p> <p><a href="https://doi.org/10.1002/advs.202308630">B. Shen, Z. Li, Y. Pan, Y. Guo, Z. Yin, R. Hu, J. Qu, L. Liu, Noninvasive Nonlinear Optical Computational Histology. Adv. Sci. 2023, 2308630.</a></p>
Hydrophobically gated memristive nanopores for neuromorphic computing
<p>The file named "experimental.zip" has the .abf files of the different electrophysiology experiments realized on the engineered FraC.</p><p>The file named "model_pore.zip" has the initial condition, the LAMMPS file to run the RMD simulations as well as the files required to compute the free energy, P1 and P2.</p><p>The file named "frac_md.zip" has the files to run the FraC simulations, as well as the files necessary to compute the free energy, P1 and P2.</p><p> </p>
Supplementary data for "Structural, biochemical, and computational characterization of sulfonamides as bimetallic peptidase inhibitors"
<p>Supplementary data for "Structural, biochemical, and computational characterization of sulfonamides as bimetallic peptidase inhibitors"</p> <p>Coordinates, schemes, NCI density visualization in VMD, and PyMOL sessions for the Figures in the publication are provided.</p>
Iterative evaluation of mobile computer-assisted digital chest x-ray screening for TB improves efficiency, yield, and outcomes in Nigeria
<p>Wellness on Wheels (WoW) is a model of mobile systematic tuberculosis (TB) screening of high-risk populations combining digital chest radiography with computer-aided automated detection (CAD) and chronic cough screening to identify presumptive TB clients in communities, health facilities, and prisons in Nigeria. The model evolves to address technical, political, and sustainability challenges.</p> <p>Screening methods were iteratively refined to balance TB yield and feasibility across heterogeneous populations. Performance metrics were compared over time. Screening volumes, risk mix, number needed to screen (NNS), number needed to test (NNT), sample loss, TB treatment initiation and outcomes. Efforts to mitigate losses along the diagnostic cascade were tracked. Participants with high likelihood on CAD4TB (≥80) who tested negative on a single spot GeneXpert were followed-up to assess TB status at six months.</p> <p>An experimental calibration method achieved a viable CAD threshold for testing. High-risk groups and key stakeholders were engaged. Operations evolved in real-time to fix problems. Incremental improvements in mean client volumes (128 to 140/day), target group inclusion (92% to 93%), on-site testing (84% to 86%), TB treatment initiation (87% to 91%), and TB treatment success (71% to 85%). Attention to those as highest risk boosted efficiency (the NNT declined from 8.2 ± SD8.2 to 7.6 ± SD7.7). Clinical diagnosis was added after follow-up among those with ≥ 80 CAD scores initially spot-sputum negative found 11 additional TB cases (6.3%) after 121 person-years of follow-up.</p> <p>Iterative adaptation in response to performance metrics foster feasible, acceptable, and efficient TB case-finding in Nigeria. High CAD scores can identify subclinical TB and those at risk of progression to bacteriologically-confirmed TB disease in the near term.</p> <p>Policy makers, donors, and community advocates are hesitant to invest in the steep infrastructure costs for mobile digital chest x-ray and GeneXpert MTB/RIF (dCXR/GXP) laboratories without a better understanding of how to maximize and sustain their impact. It is rarely possible to conduct the months of local CAD calibration recommended by experts via costly universal testing with a reference standard.4,9 Stakeholder needs and resource limitations require a more rapid and cost-conscious means of setting a sustainable algorithm. Viable, field-robust methodologies are needed, and optimization strategies informed by routine field findings were lacking. A precise assessment of the contribution of routine mobile TB screening has been challenging because few authors fully disaggregate losses along the diagnostic cascade or track TB treatment outcomes. Publication bias has limited access to results of active case finding pilots with suboptimal risk group targeting, community engagement, yield, or treatment outcomes.10–14 Evaluations (and scrutiny) of routine data are needed that make the demands, constraints, costs and choices facing implementers more explicit.</p>
Data associated with the study titled "The role of micro-environments on computed vibrationally-resolved emission spectra: The case of oxazines."
<p>This repository contains data associated with the study titled "The role of micro-environments on computed vibrationally-resolved emission spectra: The case of oxazines."</p> <p>Folder Structure:<br>========== /CV/ ==========<br>/CV-bare/: Coordinates of the ground state (GS) and excited state (ES) for CV+ dye.</p> <p>========== /DR/ ==========<br>/DR-bare/DR-most-stable/: Coordinates of the ground state (GS) and excited state (ES) for the most stable conformer of DR+ dye.</p> <p>========== /NB/ ==========<br>/NB-bare/NB-most-stable/: Coordinates of the ground state (GS) and excited state (ES) for the most stable conformer of NB+ dye.<br>/NB-bare/NB-other-conformers/: Coordinates of the ground state (GS) and excited state (ES) for other conformers responsible for over 90% of the total Boltzmann weighted population of NB+ dye.</p> <p>========== /Ox1/ ==========<br>/Ox1-bare/Ox1-most-stable/: Coordinates of the ground state (GS) and excited state (ES) for the most stable conformer of Ox1+ dye.<br>/Ox1-bare/Ox1-other-conformers/: Coordinates of the ground state (GS) and excited state (ES) for other conformers responsible for over 90% of the total Boltzmann weighted population of Ox1+ dye.</p> <p>========== /Ox4/ ==========<br>/Ox4-bare/Ox4-most-stable/: Coordinates of the ground state (GS) and excited state (ES) for the most stable conformer of Ox4+ dye.<br>/Ox4-bare/Ox4-other-conformers/: Coordinates of the ground state (GS) and excited state (ES) for other conformers responsible for over 90% of the total Boltzmann weighted population of Ox4+ dye.<br>/Ox4-bare/Ox4-PCM/: Coordinates of the ground state (GS) and excited state (ES) for the most stable conformer of Ox4+ dye in the Polarizable Continuum Model (PCM).<br>/Ox4-betaine/: Coordinates of the ground state (GS) and excited state (ES) for a betaine molecule aggregated to Ox4+ dye at different positions.<br>/Ox4-water-gasphase/: Coordinates of the ground state (GS) and excited state (ES) for a water molecule aggregated to Ox4+ dye at different positions as well as two water mocules aggregated to Ox4+ at postion 1.<br>/Ox4-water-PCM/: Coordinates of the ground state (GS) and excited state (ES) for a water molecule aggregated to Ox4+ dye at different positions in PCM.</p> <p>========== /Ox170/ ==========<br>/Ox170-bare/Ox170-most-stable/: Coordinates of the ground state (GS) and excited state (ES) for the most stable conformer of Ox170+ dye.<br>/Ox170-bare/Ox170-other-conformers/: Coordinates of the ground state (GS) and excited state (ES) for other conformers responsible for over 90% of the total Boltzmann weighted population of Ox170+ dye.<br>/Ox170-bare/Ox170-PCM/: Coordinates of the ground state (GS) and excited state (ES) for the most stable conformer of Ox170+ dye in the Polarizable Continuum Model (PCM).<br>/Ox170-betaine/: Coordinates of the ground state (GS) and excited state (ES) for a betaine molecule aggregated to Ox170+ dye at different positions.<br>/Ox170-water-gasphase/: Coordinates of the ground state (GS) and excited state (ES) for a water molecule aggregated to Ox170+ dye at different positions as well as two water mocules aggregated to Ox170+ at postion 1.<br>/Ox170-water-PCM/: Coordinates of the ground state (GS) and excited state (ES) for a water molecule aggregated to Ox170+ dye at different positions in PCM.</p> <p><br>Notes:<br>For any inquiries or clarifications, please contact the creators.</p>
Profiling of pancreatic adenocarcinoma using artificial intelligence-based integration of multi-omic and computational pathology features - Validation Data Sets
<p>Two public validation cohorts were utilized in the MT-Pilot study, the Cancer Genome Atlas (TCGA) and cohort-1 Johns Hopkins University (JHU). These datasets included DNA, RNA, clinical data, and tissue protein analytes analyzed for survival outcome prediction using AI/Machine Learning modeling. </p>
Input parameters and output trajectory files for manuscript "Inhibitory Activity of Flavonoid Scaffolds on SARS-CoV-2 3CLPro: Insights from the Computational and Experimental Investigations"
<p>Input parameters used for molecular dynamics simulations on GROMACS 2022 software and the output trajectory files for calculating binding free energy, in the manuscript with the title: "Inhibitory Activity of Flavonoid Scaffolds on SARS-CoV-2 3CL<sup>Pro</sup>: Insights from the Computational and Experimental Investigations"</p>
Rapid divergent evolution of internal female genitalia and the coevolution of male genital morphology revealed by micro-computed tomography
<p>Animal genitalia are thought to evolve rapidly and divergently in response to sexual selection. Studies of genital evolution have focused largely on male genitalia, with our understanding of female genital evolution relatively limited. The paucity of work on female genital morphology is likely due to problems faced in quantifying shape variation, due to their composition and accessibility. Here we use a combination of micro-computed tomography, landmark-free shape quantification, and phylogenetic analysis to quantify the rate of female genital shape evolution among 29 species of Antichiropus millipedes, and the coevolution of male genitalia. We found significant variation in female and male genital shape among species. While male genital shape showed significant phylogenetic signal, female genital shape did not. Male genital shape was found to be evolving 1.2 times faster than female genital shape. Female and male genital shapes exhibited strongly correlated evolution, indicating that genital shape changes in one sex are associated with corresponding changes in the genital shape of the other sex. This study adds novel insight into our growing understanding of how female genitalia can evolve rapidly and divergently and highlights the advantages of three-dimensional techniques and multivariate analyses in studies of female genital evolution.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.