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3,688 results for “Computer”
Computation noise promotes zero-shot adaptation to uncertainty during decision-making in artificial neural networks
<p>This dataset contains the behavioral choice data obtained from N = 230 participants that played a two-armed bandit task (139 females, age: 34 +/- 10 years) in partial and complete feedback conditions, as described in (Findling, Skvortsova et al., 2019, Nature Neuroscience, https://doi.org/10.1038/s41593-019-0518-9).</p> <div> <div> <div> <p>The experiment was performed on the Prolific platform (prolific.co) and the research was carried out following the principles and guidelines for experiments including human participants provided in the declaration of Helsinki and approved by the relevant authorities (Inserm Ethical Review Committee, IRB #00003888). All participants provided written informed consent prior to their inclusion.</p> </div> </div> </div>
Data underpinning "Classical Chaos in Quantum Computers"
<div> <div> <div> <div> <p>We provide the data used to produce the figures shown in our publication "Classical Chaos in Quantum Computer" and a Jupyter Notebook to reproduce all figures.</p> <h3>Abstract: </h3> <div> <div> <div> <div> <p>The development of quantum computing hardware is facing the challenge that current-day quantum processors, comprising 50-100 qubits, already operate outside the range of quantum simulation on silicon computers. In this paper, we demonstrate that the simulation of classical limits can be a potent diagnostic tool potentially mitigating this problem. As a testbed for our approach, we consider the transmon qubit processor, a computing platform in which the coupling of large numbers of nonlinear quantum oscillators may trigger destabilizing chaotic resonances. We find that classical and quantum simulations lead to similar stability metrics (classical Lyapunov exponents vs. quantum wave function participation ratios) in systems with O(10) transmons. However, the big advantage of classical simulation is that it can be pushed to large systems comprising up to thousands of qubits. We exhibit the utility of this classical toolbox by simulating all current IBM transmon chips, including the recently announced 433-qubit processor of the Osprey generation, as well as future devices with 1,121 qubits (Condor generation). For realistic system parameters, we find a systematic increase of Lyapunov exponents in system size, suggesting that larger layouts require added efforts in information protection.</p> </div> </div> </div> </div> </div> </div> </div> </div>
The input data of the multi-patch geometries used in: M. Kapl, A. Kosmač, V. Vitrih, Isogeometric collocation for solving the biharmonic equation over planar multi-patch domains, Computer Methods in Applied Mechanics and Engineering 424 (2024) 116882; DOI: 10.1016/j.cma.2024.116882
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Effects of bariatric surgery and dietary interventions for obesity on brain neurotransmitter systems and metabolism: a systematic review of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) studies
<p>Supplementary material for paper:</p> <p><span>Effects of bariatric surgery and dietary interventions for obesity on brain neurotransmitter systems and metabolism: a systematic review of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) studies<em>.<br></em></span>Al-Alsheikh AS<span>, Alabdulkader S, Miras AD, Goldstone AP <br></span><span>Obesity Reviews 24(11): e13620, 2023 </span></p>
Spectral and computational dataset for "Hydrogen-atom-assisted processes on thioacetamide in para-H2 matrix – Formation of thiol tautomers"
<p>TA-pH2_exp.zip: IR spectral data (both blank and 'real' experiments) including difference spectra, lab note files</p> <p>TA-pH2_calc.zip: Gaussian job and output files</p>
Data Repository for Combined Experimental and Computational Study of the Reactivity of the Methanimine Radical Cation (H2CNH·+) and Its Isomer Aminomethylene (HCNH2·+) with Propene (CH3CHCH2)
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Data and Codes for Publication: "Sexually Dimorphic Computational Histopathological Signatures Prognostic of Overall Survival in High-Grade Gliomas via Deep Learning"
<p><strong>Data</strong></p> <p>The patches and the associated tumor segmentation labels (expert-vetted) from our analysis are available in Patches.pytable file.<br><br><strong>Codes<br><br></strong>The codes for training tumor segmentation models and conducting survival analysis are available in the following files</p> <ul> <li>ResNet-train: Code to train Resnet18 model for Tumor Segmentation</li> <li>Tumor_Segmentation: Code to segment tumor regions from WSI using ResNet18 model</li> <li>ResNet_Cox_train: Code to train ResNet-Cox model in 5 folds cross-validation setting</li> <li>Evaluate_ResNetCox: Code to evaluate ResNet-Cox model</li> </ul>
Multi-Scale Computational Design of Metal-Organic Frameworks for Carbon Capture Using Machine Learning and Multi-Objective Optimization
<p>This repository contains CIF files for metal-organic frameworks and Grand canonical Monte Carlo (GCMC) simulation results for the article <em>Multi-Scale Computational Design of Metal-Organic Frameworks for Carbon Capture Using Machine Learning and Multi-Objective Optimization</em> by Zijun Deng and Lev Sarkisov.</p>
Structural models associated with computational study of PolB2 and Pol V mutasomes
<p>This data set contains several collections of 3D models of protein complexes predicted using AlphaFold-Multimer or AlphaFold3. Detailed information regarding the composition of protein complexes and the confidence scores of models is available in the Model_data.xls file.</p> <div> </div>
FASTQ Data for: A Primordial DNA Store and Compute Engine
<p>Raw FASTQ data generated for the evaluation of the publication "A Primordial DNA Store and Compute Engine" to appear in Nature Nanotechnology.</p> <p> </p> <p>Please contact ajkeung@ncsu.edu regarding queries on the data set.</p>
code for: The cerebellum computes frequency dynamics for motions with numerical precision and cross-individual uniformity
<p>MATLAB codes for data analyses performed in "The cerebellum computes frequency dynamics for motions with numerical precision and cross-individual uniformity".</p>
PyRAMD scheme: a protocol for computing the infrared spectra of polyatomic molecules using ab initio molecular dynamics
<p>Here are illustrative examples of how to compute molecular-dynamics-based vibrational infrared spectra of polyatomic molecules using PyRAMD software.</p> <p>The dataset includes the version of the software used (PyRAMD from https://gitlab.desy.de/denis.tikhonov/pyramd, obtained July 15, 2024) for running molecular dynamics (MD) and various examples of MD simulations that illustrate various analysis issues. The large-time-step correction applicability is shown with methane (CH4) as an example. The applicability of the regularized least-squares spectral analysis is demonstrated in the case of carbon dioxide (CO2). The scale factors for the MD are obtained using water, ammonia, methane, ethane, methylamine, and methanol as the training set of molecules. The scale factors were obtained at the BLYP-D3(BJ)/6-31G, PBE-D3(BJ)/6-31G, and PBEh-3c levels of theory. The whole procedure was demonstrated with protonated methane as a test case.</p>
Test Model for GTT Computational Fluid Dynamics Simulation by TransAT
<p>This archive contains the model and associated code need to run the GTT benchmark test for TransAT.</p>
The impact of exploiting spectro-temporal context in computational speech segregation
<p>The experimental data from the study:</p> <p>https://asa.scitation.org/doi/10.1121/1.5020273</p> <p>Group 1 contains results, masks and audio from the models of the 16 GMM component segregation system<br> Group 2 contains results, masks and audio from the models of the 64 GMM component segregation system</p> <p>There are three folders:</p> <p>Audio:<br> The CLUE sentences that were used for the listener study</p> <p>IBM = Ideal Binary Mask, UP = UnProcessed, EBM = Estimated Binary Mask. </p> <p>The IBM and UP are stored in one of the configuration folders (Front-end), that is:</p> <p>Audio\Group1\Front-end\icra_01_10sec_matched\UP<br> Audio\Group1\Front-end\icra_01_10sec_matched\IBM<br> Audio\Group1\Front-end\icra_01_10sec_matched\EBM</p> <p>Results:<br> The computed metrics for group 1 & 2 as well as Word Recognition Scores (WRSs) from the listener study</p> <p>BinaryMasks:</p> <p>a priori SNR masks, IBMs and EBMs from group 1 and 2.</p> <p><br> Developed with Matlab R2016a.</p>
Computational Logic with Square Rings of Nanomagnets
<p>Open access data set for manuscript " Computational Logic with Square Rings of Nanomagnets" published in Nanotechnology 2018.</p>
Molecular dynamic trajectory for the article "The Binding Mechanism between Inositol Phosphate (InsP) and the Jasmonate Receptor Complex: A Computational Study"
<p>Molecular dynamic trajectory preparation file of Jasmonate receptor complex. We set up six systems. </p> <p>Each system contains PSF file and PDB file.</p>
Backgroun in Computational Tools (Data Science Summer School Goettingen)
<p>Here is a dataset to understand the computational tools background of participants</p>
Supplementary data for "Computational Investigation of RO2 + HO2 and RO2 + RO2 Reactions of Monoterpene Derived First-Generation Peroxy Radicals Leading to Radical Recycling", revised version submitted to J. Phys. Chem. A
<p>log files (Gaussian 09) and out files (Orca 4.0)</p> <p>(Note: Files_final.zip contains all the same log and out files as Files.zip, but also few additional structures added during the revision process, namely two additional RO2 from ocimene ozonolysis, and one additional transition state for a RO2 + HO2 reaction. Please ignore the file Files.zip.)</p>
Time-lapse helical X-ray computed tomography (CT) data of tensile fatigue damage in GFRP
<p>The X-ray CT data here is published with the paper - </p> <p>Wang, Y.; Mikkelsen, L.P.; Pyka, G.; Withers, P.J. Time-Lapse Helical X-ray Computed Tomography (CT) Study of Tensile Fatigue Damage Formation in Composites for Wind Turbine Blades. <em>Materials</em> <strong>2018</strong>, <em>11</em>, 2340.</p> <p>https://doi.org/10.3390/ma11112340</p> <p>More information about the data and the material can be found in the paper above.</p> <p> </p> <p>If using the data here, please cite the above paper.<em> </em></p> <p>Contact details for author: Ying Wang, ying.wang-4@manchester.ac.uk</p>
Dataset: Methods for computing the maximum performance of computational models of fMRI responses.
<p>Accompanying data for the revised version of the manuscript: Methods for computing the maximum performance of computational models of fMRI responses. written by Agustin Lage-Castellanos, Giancarlo Valente, Elia Formisano, Federico De Martino, submitted for publication in Plos Computational Biology, November 2018.</p> <p>The dataset (01.rar) contains the fMRI time series for one subject in Nifti format acquired on an actively shielded MAGNETOM 7T whole body system driven by a Siemens console at Scannexus (<a href="http://www.scannexus.nl)">www.scannexus.nl)</a>. Every folder (24 runs, one folder per run) contains 150 Nifti files, one Nifti file for each fMRI volume. Preprocessing consisted of slice scan-time correction (with sinc interpolation), 3-dimensional motion correction, and temporal high pass filtering (removing drifts of 4 cycles or less per run).</p> <p>The matlab file dmS01_24runs.mat contains a 24-length cell array of fMRI design matrices, one for every run. Every fMRI design matrix is size 150 volumes x 51 covariates. The first 42 columns correspond to the stimuli presented (42 sounds per run). Columns 43, and 44, correspond to the run mean and the linear trend covariates. The rest of the columns correspond to the covariates obtained with GLMdenoise. The matlab variable <em>stimulus</em> of size 24 x 42 contains the index of the sounds presented at every run. A total of 168 sounds were presented, each sound was presented 6 times across the 24 fMRI runs.</p> <p>The file SPMgls0.rar contains the Beta images in Nifti format for every column of the fMRI design matrix, including noise covariates, for every fMRI run. This model was estimated assuming i.i.d fMRI noise (OLS). The codes for computing the noise ceiling are available in the file nccodes.rar, together with a two of examples of their use. SPM is required.</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.