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3,688 results for “Computer”
Computational Sociolinguistics: An Emerging Multidisciplinary Research Area
<p>A TXT consisting in the keywords used for the 62 searches carried out in the Web of Science (WoS) database in order to look for academic publications related to Computational Sociolinguistics.</p> <p> </p> <p>A CSV and a XLSX with the same information: the corpus of unique publications (i.e., 3,454) obtained from the searches conducted in WoS using the queries from the TXT file. They include two additional columns at the end: 'Article Title_clean' and 'Abstract_clean'. They are the normalised titles and abstracts of the publications; they are ready for further analysis on the values of these columns.</p>
Spatiotemporal dataset of dengue influencing factors in Brazil based on geospatial big data cloud computing
<p>We produced a spatiotemporal dataset of dengue influencing factors in Brazil based on geospatial big data cloud computing from 2001-2024.</p> <p>GDP and building surface area are yearly data.</p> <p>PDSI is monthly data.</p>
Supporting data for: "Data-driven discovery of cardiolipin-selective small molecules by computational active learning"
<p>This repository contains supporting data and code for the paper titled "Data-driven discovery of cardiolipin-selective small molecules by computational active learning" by Bernadette Mohr, Kirill Shmilovich, Isabel Kleinwächter, Dirk Schneider, Andrew L.Ferguson, and Tristan Bereau.</p>
Progress Toward SHAPE Constrained Computational Prediction of Tertiary Interactions in RNA Structure
<p>Supplementary repository for the "Progress Toward SHAPE Constrained Computational Prediction of Tertiary Interactions in RNA Structure" article. Contains the simulation on the <em>Didymium iridis</em> lariat-capping ribozyme (DiLCrz, PDB ID: 4P8Z).</p>
Data of "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step."
<p>Data related to<br> ===========<br> title = "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step.",<br> journal = "Computer Methods in Applied Mechanics and Engineering",<br> volume ="390",<br> year = "2022",<br> doi = "https://doi.org/<a href="http://dx.doi.org/10.1016/j.cma.2021.114476">10.1016/j.cma.2021.114476</a> ",<br> pages = "114476 ",<br> author = "Wu, Ling and Noels, Ludovic"</p> <p>We would be grateful if you could cite the paper in the case in which you are using the data</p> <p> </p> <p>The files replace version 1 whose zip was corrupted.</p> <p> </p>
Computational Insights into the Unfolding of a Destabilized Superoxide Dismutase 1 Mutant
<p>This data accompanies the article entitled <em>Computational Insights into the Unfolding of a Destabilized Superoxide Dismutase 1 Mutant</em> and published in Biology.</p> <p>SOD1_WT_I35A_REST2.zip: The zip archive includes REST2 trajectories for the two SOD1 constructs and the two force fields investigated in the paper.</p> <p>The trajectories are saved in the GROMACS XTC file format, separately for each temperature (i=0,...,23). Owing to the considerable trajectory sizes, only protein coordinates are reported, and the output frequency is reduced to 100 ps. The initial geometry (in the Gromos87 GRO format) after a short relaxation is provided for each REST2 simulation (conf_prot.gro). Furthermore, for each REST2 simulation, an xarray (http://xarray.pydata.org) dataset, saved in the netCDF file format, is included and contains the following observables: fraction of native contacts relative to the crystal structure, secondary-structure content (i.e., the fraction of protein residues found in an alpha-helix, beta-sheet, beta-bridge, or a turn), as well as the number of residues with the beta-sheet secondary structure per each beta-strand and beta-sheet of the SOD1 barrel.</p>
Associated code and data for "Multi-level computational modeling of anti-cancer dendritic cell vaccination utilized to select molecular targets for therapy optimization (doi: 10.3389/fcell.2021.74635)"
<p>This deposit contains the data, code, and analysis to reproduce the results in the manuscript - Lai X, Keller C, Santos-Rosales G, Schaft N, Dörrie J, Vera J. Multi-level computational modeling of anti-cancer dendritic cell vaccination utilized to select molecular targets for therapy optimization. Frontiers in Cell and Developmental Biolology. 2022; 9:746359; <a href="https://www.researchgate.net/publication/358461035_Multi-Level_Computational_Modeling_of_Anti-Cancer_Dendritic_Cell_Vaccination_Utilized_to_Select_Molecular_Targets_for_Therapy_Optimization">doi:10.3389/fcell.2021.746359</a>.</p> <p>If you have used the code for your research, please cite the original publication. Thank you very much.</p> <p> </p>
How Creatively Are We Teaching and Assessing Creativity in Computing Education: A Systematic Literature Review
<p>Data from:</p> <p>Wouter Groeneveld, Brett A. Becker, and Joost Vennekens. 2022. How Creatively Are We Teaching and Assessing Creativity in Computing Education: A Systematic Literature Review. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2022),March 3–5, 2022, Providence, RI, USA. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3478431.349936</p> <p><strong>When referring to this dataset, please cite the above article. That contains the DOI of this dataset. Please do not cite this dataset directly without citing the article.</strong></p>
Computational Data supporting "Porous covalent organic nanotubes and their assembly in loops and toroids"
<p>Computational research data supporting the article:<br> Kalipada Koner, Shayan Karak, Sharath Kandambeth, Suvendu Karak, Neethu Thomas, Luigi Leanza, Claudio Perego, Luca Pesce, Riccardo Capelli, Monika Moun, Monika Bhakar, Thalasseril G. Ajithkumar, Giovanni M. Pavan, and Rahul Banerjee, "Porous Covalent Organic Nanotubes and Toroids: A Carbon Nanotube Analogue" </p>
Working memory capacity of crows and monkeys arises from similar neuronal computations
<p>Complex cognition relies on flexible working memory, which is severely limited in its capacity. The neuronal computations underlying these capacity limits have been extensively studied in humans and in monkeys, resulting in competing theoretical models. We probed the working memory capacity of crows (<em>Corvus corone</em>) in a change detection task, developed for monkeys (<em>Macaca mulatta</em>), while we performed extracellular recordings of the prefrontal-like area nidopallium caudolaterale. We found that neuronal encoding and maintenance of information were affected by item load, in a way that is virtually identical to results obtained from monkey prefrontal cortex. Contemporary neurophysiological models of working memory employ divisive normalization as an important mechanism that may result in the capacity limitation. As these models are usually conceptualized and tested in an exclusively mammalian context, it remains unclear if they fully capture a general concept of working memory or if they are restricted to the mammalian neocortex. Here we report that carrion crows and macaque monkeys share divisive normalization as a neuronal computation that is in line with mammalian models. This indicates that computational models of working memory developed in the mammalian cortex can also apply to non-cortical associative brain regions of birds.</p>
Computational results for the publication "Evolution of water structures in metal-organic frameworks for improved atmospheric water harvesting"
<p>This upload contains the computationally obtained atomic coordinates for MOF-303 and MOF-333 at different water loadings.</p>
Data SRL Computational Thinking
<p>Scoping Review of the Literature data (2018-2021) o Computational Thinking. WoS and Scopus databases.</p>
A Dataset for Utility Prediction in Computational Persuasion with Machine Learning Techniques
<p>This dataset contains data for a new benchmark for the prediction of user's utilities with Machine Learning techniques for Computational Persuasion. This work has been accepted at AAAI-22, more information in the relative repository containing the source code: <a href="https://github.com/ivanDonadello/ML-Argument-Based-Computational-Persuasion">https://github.com/ivanDonadello/ML-Argument-Based-Computational-Persuasion</a></p>
Identifying strengths and weaknesses of methods for computational network inference from single cell RNA-seq data
<p>These data files contain single-cell RNA-sequencing expression data (expression_data.zip) and pseudotime files (pseudotime.zip) used to conduct comparisons of network inference methods on six published single-cell RNA-sequencing datasets. The resulting networks generated from the network inference methods are also uploaded here (normalized_inferred_networks.zip and imputed_inferred_networks.zip). Finally, the gold standard networks we used as ground truth to measure accuracy of the inferred networks are uploaded here (gold_standard_datasets.zip).</p>
EXCEED-DMv0.2.8: DFT-computed electronic wave functions for Si and Ge
<p>Wave function coefficients, with and without the all-electron reconstruction, for Si and Ge on a 10x10x10 uniform k mesh. For use with EXCEED-DM to compute Dark Matter induced electronic excitation rates.</p> <p>Note:</p> <p>Compatible with EXCEED-DMv0.2.8</p>
Original datasets for : A computational homogenization framework with enhanced localization criterion for macroscopic cohesive failure in heterogeneous materials
<p>The original datasets from tests in the article: <strong> A computational homogenization framework with enhanced localization criterion for macroscopic cohesive failure in heterogeneous materials</strong>. The results are produced by the in-house fem codes of the Computational Mechanics group, CiTG, TU delft.</p>
Cortical oscillations support sampling-based computations in spiking neural networks
<p>This archive contains the scripts for generating the data and figures and the data of the publication: "Cortical oscillations support sampling-based computations in spiking neural networks".</p> <p>The different parts of the material are grouped into separate archives to enable modular usage and can be individually downloaded as required:</p> <ul> <li>The archive spike-based-tempering_scripts.tgz contains all the scripts to reproduce the simulation data and figures.</li> <li>The file software.img contains the third-party software needed to execute the simulations of the current-based experiments.</li> <li>The archive current-based_experiments_data includes the scripts and the simulation data for the current-based experiments.</li> </ul>
Dataset related to aticle "Additive Fabrication of a Vascular 3D Phantom for Stereotactic Radiosurgery of Arteriovenous Malformations"The database contains 3D models in STL file format of a patient-specific brain arteriovenous malformation phantom reconstructed from computed tomography scans.
<p><em>The database contains 3D models in STL file format of a patient-specific brain arteriovenous malformation phantom reconstructed from computed tomography scans.</em></p>
Reflection Ultrasound Computed Tomography (RUCT) Phantom Data
<p>Test Data for Reflection Ultrasound Computed Tomography (RUCT) Delay and Sum Algorithm</p> <p>This data is shared for "pyruct" package tests. "pyruct" package can be found in "https://github.com/berkanlafci/pyruct"</p> <p>If you use this data in your research, please cite the following paper:</p> <p>B. Lafci, J. Robin, X. L. Deán-Ben and D. Razansky, "Expediting Image Acquisition in Reflection Ultrasound Computed Tomography," in IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, doi: <a href="https://ieeexplore.ieee.org/document/9768674">10.1109/TUFFC.2022.3172713</a>.</p>
Computational synthesis of cortical dendritic morphologies
<p>Neuronal morphologies provide the foundation for the electrical behavior of neurons, the connectomes they form, and the dynamical properties of the brain. Comprehensive neuron models are essential for defining cell types, discerning their functional roles, and investigating brain disease related dendritic alterations. However, a lack of understanding of the principles underlying neuron morphologies has hindered attempts to computationally synthesize morphologies for decades. We introduce a synthesis algorithm based on a topological descriptor of neurons, which enables the rapid digital reconstruction of entire brain regions from few reference cells. This topology-guided synthesis generates dendrites that are statistically similar to biological reconstructions in terms of morpho-electrical and connectivity properties and offers a significant opportunity to investigate the links between neuronal morphology and brain function across different spatio-temporal scales. Synthesized cortical networks based on structurally altered dendrites associated with diverse brain pathologies, revealed principles linking branching properties to the structure of large-scale networks.</p> <p> </p> <p>We provide here the original biological reconstructions, the artificially generated cells and related data (electrical traces, connectivity of artificial networks) that were used for the analysis of the paper "Computational synthesis of cortical dendritic morphologies" to appear in Cell Reports.</p>
ScienceDex guides
Understand access before you commit
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.