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Dataset results
453 results for “Dynamic dataset”
Dataset for the paper "Wedge Plasticity and a Minimalist Dynamic Rupture Model for the 2011 Mw 9.1 Tohoku-Oki Earthquake and Tsunami" in Tectonophysics
<p>This dataset contains the Fortran source codes and input files to reproduce the results in the paper "Wedge Plasticity and a Minimalist Dynamic Rupture Model for the 2011 Mw 9.1 Tohoku-Oki Earthquake and Tsunami". Sample Matlab scripts are included to visualize the results. Model results, such as final fault slip, rupture times, stress changes on fault, final surface displacements, and moment density tensors in the wedge associated with inelastic deformation, are also included as ascii files. See readme for more details.</p>
Molecular Dynamics Simulation Dataset for "Hydrophobic Mismatch Drives Self-Organization of Designer Proteins into Synthetic Membranes"
<p>This repository contains molecular dynamics (MD) simulation data from the study on the self-organization of designer proteins in synthetic membranes. The data includes simulations for different single lipid compositions (DOPC, DPPC, DYPC) denoted as [lipid]-PL* where PL stands for the different TMD constructs. Multi component simulation are named accordingly. The repository provides initial (eqi.gro) and final (prod.gro) coordinates for each simulation. The 'cmd' file in each directory outlines the assembly process of each simulation, and the 'mdp' folder contains all input files for the simulations. </p>
Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks: dataset
<p>This repository contains the data accompanying the paper "<em>Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks</em>", by Francesco Regazzoni, Stefano Pagani, Matteo Salvador, Luca Dedè and Alfio Quarteroni.</p> <p>The associated codes are available in the repository <a href="https://github.com/FrancescoRegazzoni/LDNets">https://github.com/FrancescoRegazzoni/LDNets</a></p>
Dataset for "Three-dimensional spin-wave dynamics, localization and interference in a synthetic antiferromagnet"
<p>Data availability for the article titled "Three-dimensional spin-wave dynamics, localization and interference <br>in a synthetic antiferromagnet" by Girardi et al. published in Nature Communications.</p> <p>This data repository contains the following folders and files:<br>• TR Lamni Raw Data - Co: Files with extension .hdf5 are Time-Resolved Soft X-Ray Laminography Raw Data for all projections acquired to obtain the 3D reconstruction for the CoFeB layer. The projections’ data have been organized in sub-folders for the 7 frames acquired during the measurements. For each frame, a final folder “analysis” contains an aligned_projection.mat file with the angles of all measured projections and the sinogram information.<br>• TR Lamni Raw Data - Ni: Files with extension .hdf5 are Time-Resolved Soft X-Ray Laminography Raw Data for all projections acquired to obtain the 3D reconstruction for the NiFe layer. The projections’ data have been organized in sub-folders for the 7 frames acquired during the measurements. For each frame, a final folder “analysis” contains an aligned_projection.mat file with the angles of all measured projections and the sinogram information.<br>• Magnetic reconstruction – Ni edge: contains the .mat files of the 3D magnetic reconstruction obtained for Ni-edge for all 7 frames. In each file, the Mx, My and Mz components of the magnetization associated with the 3D reconstruction of the volume of the sample are present. <br>• Magnetic reconstruction – Co edge: contains the .mat files of the 3D magnetic reconstruction obtained for Co-edge for all 7 frames. In each file, the Mx, My and Mz components of the magnetization associated with the 3D reconstruction of the volume of the sample are present. <br>• vtk files: contains the post-processed files for all 7 frames in the .vtk format for the 3D visualization with the Paraview software. In each file, both vectorial and scalar data associated with the 3D reconstruction of the volume of the sample and analyzed in the paper are present.<br>• Mumax3 simulation dispersion relation: contains .ovf files (containing information about the Mx, My, Mz components of the magnetization as a function of the spatial position) obtained from the mumax3 simulation to study the spin wave dispersion relation of the sample investigated. The total simulation runtime is 10 ns, and each .ovf file corresponds to a frame saved every 0.01 ns.<br>• Mumax3 simulation 3D interference: contains the .ovf files (containing information about the Mx, My, Mz components of the magnetization as a function of the spatial position) for the static magnetization and 3 frames used to simulate the 3D interference pattern observed experimentally. </p>
Supporting datasets for the article Using rare event algorithms to understand the statistics and dynamics of extreme heatwave seasons in South Asia
<h3>Supporting datasets for the article<em><strong> Using rare event algorithms to understand the statistics and dynamics of extreme heatwave seasons in South Asia, </strong></em>submitted to <em>Environmental Research: Climate</em></h3> <p> </p> <p>The dataset contains all intermediate data used for the article. The raw outputs of the model may be available upon reasonable request to clement.lpr@gmail.com</p> <p>The climate model Plasim can be downloaded, together with its documentation, from the webpage of the « Theoretische Meteorologie » group at the University of Hamburg: <a href="https://www.mi.uni-hamburg.de/en/arbeitsgruppen/theoretische-meteorologie/modelle/plasim.html">https://www.mi.uni-hamburg.de/en/arbeitsgruppen/theoretische-meteorologie/modelle/plasim.html</a></p> <p>The three jupyter notebooks <a href="../api/records/10888194/draft/files/Figures_article_archive.ipynb/content" target="_blank" rel="noopener noreferrer">Figures_article_archive.ipynb</a>, <a href="../api/records/10888194/draft/files/Zg500_maps_article_archive.ipynb/content" target="_blank" rel="noopener noreferrer">Zg500_maps_article_archive.ipynb</a>, <a href="../api/records/10888194/draft/files/Correlation_maps_3days_ERA5_Plasim_archive.ipynb/content" target="_blank" rel="noopener noreferrer">Correlation_maps_3days_ERA5_Plasim_archive.ipynb</a> contain the analysis and code used to produce the figures in the article.</p> <p><strong><a href="../api/records/10888194/draft/files/pyscripts.tar/content" target="_blank" rel="noopener noreferrer">pyscripts.tar</a> </strong>contains 4 python utilities, <em>data_proceeding_module.py, plot_routines.py, subseasonal_stats_utilities.py, utilities_REA_analysis.py </em>that are imported by the notebooks.</p>
Dataset: Uncovering Obscured Phonon Dynamics from Powder Inelastic Neutron Scattering using Machine Learning
<p>Dataset of simulated and experimental spectra for the manuscript: Uncovering Obscured Phonon Dynamics from Powder Inelastic Neutron Scattering using Machine Learning. </p> <p>The data.zip contains all the simulated spectra and labels.</p> <p>The dataset.zip contains the divided subsets for training, validation and testing purposes, as well as the experimental dataset.</p>
Datasets associated with paper "Five decades of Abramov glacier dynamics reconstructed with multi-sensor optical remote sensing", by Enrico Mattea et al.
<p>This archive contains Digital Elevation Models and orthoimages produced within the study "Five decades of Abramov glacier dynamics reconstructed with multi-sensor optical remote sensing", published on The Cryosphere by Enrico Mattea et al.</p> <p>Assets include derivative products of SPOT satellite scenes, acquired by CNES’s Spot World Heritage Programme, and of Pléiades <span><span><strong>©</strong></span></span>CNES 2015, 2020, 2022, Distribution AIRBUS DS.</p>
Dataset for "History and dynamics of Fennoscandian Ice Sheet retreat, contemporary ice-dammed lake evolution, and faulting in the Torneträsk area, northwestern Sweden"
<p>This dataset contains the GIS shapefiles and the high resolution map for the manuscript "Ice-dammed lakes and contemporary faulting in the Torneträsk region of northern Sweden are key to understanding regional Fennoscandian Ice Sheet deglaciation patterns and dynamics" in preparation for <em>The Cryosphere</em>. </p>
StateSwitch (dynamic) BIDS dataset
<div> <div>Raw BIDS data for StateSwitch (dynamic)</div> <div> </div> <div>The data are distributed as nested DataLad datasets that are hosted on gin. Please see the repository URL for access.</div> <div> </div> <div> <div> <div>Please cite the following references if you use these data:</div> <br> <div>Kosciessa, J. Q., Lindenberger, U. & Garrett, D. D. Thalamocortical excitability modulation guides human perception under uncertainty. Nat. Commun. 12, 2430 (2021).</div> <div> </div> <div>Kosciessa, J. Q., Mayr, U., Lindenberger, U. & Garrett, D. D. Broadscale dampening of uncertainty adjustment in the aging brain. Nat. Commun. (in press, 2024).</div> <br> <div>A static copy of the data for younger adults is also provided at https://osf.io/mgxqr/.</div> <br> <div>In case of questions, contact kosciessa@mpib-berlin.mpg.de or [MPIB Research Data Management](<rdm@mpib-berlin.mpg.de>).</div> </div> </div> </div>
[Dataset] Intensity and Dimensionality-Dependent Dynamics of Laser-Proton Acceleration in 1D, 2D, and 3D Particle-in-Cell Simulations
<p>The included Jupyter Notebooks (.ipynb) were used to generate figures and make calculations for the work. The resulting image files are saved in Figure_Outputs.tar.gz. The other archives (1D.tar.gz, 2DS.tar.gz, 2DP.tar.gz, 3D.tar.gz, laser_focus.tar.gz, and EField.tar.gz) are compressed directories containing EPOCH PIC simulation outputs for the paper (relevant directories should be extracted to replicate analysis with provided files). </p> <p>Since the last version, a new figure (Figure 6, an ion phase space) has been added. Notebooks for later figures have been renumbered and the figure outputs have been updated. </p>
Neural dynamics model testing dataset
<p>These datasets are used to reproduce the results of the neural dynamics model from the paper https://doi.org/10.1101/725382.</p>
Neural dynamics model training dataset
<p>These datasets are used to reproduce the results of the neural dynamics model from the paper https://doi.org/10.1101/725382.</p>
Dataset from "Monte Carlo-Discrete Dislocation Dynamics: A technique for studying the formation and evolution of dislocation structures"
<p>Raw datasets used in the manuscript:</p> <p>N. Deka and R. B. Sills, Monte Carlo-Discrete Dislocation Dynamics: A technique for studying the formation and evolution of dislocation structures, Modelling and Simulation in Materials Science and Engineering, 2022</p> <p>doi: 10.1088/1361-651X/ac41a2</p> <p>See Readme.txt file for details.</p>
Dataset for Hohls et al "Controlling the error mechanism in a tunable-barrier non-adiabatic charge pump by dynamic gate compensation"
<p>Dataset for Hohls et al "Controlling the error mechanism in a tunable-barrier non-adiabatic charge pump by dynamic gate compensation", <a href="https://arxiv.org/abs/2112.10713">https://arxiv.org/abs/2112.10713</a></p>
Dynamic deformation calculation of articular cartilage and cells using resonance-driven laser scanning microscopy - Osmotic Challenge and Validation Testing Dataset
<p>This archive contains 3-D image stacks obtained over time of articular cartilage undergoing osmotic swelling. These were acquired with a resonance scanning protocol, which allows for fast scanning but with decreased image quality. The Python package, resonant_lsm, was developed to segment and analyze the deformation of cells in such images. The archive also contains validation testing data of this software. Included README files document the archive contents and how to reproduce the analyses. </p>
Molecular Dynamics simulation dataset for : Hypoxia increases the methylated histones to prevent histone clipping and redistribution of heterochromatin during Raf-induced senescence.
<p>Files are Initial structures of Cathepsin L(CTSL) with histone H3 peptides (naive and K23me3) and their Molecular Dynamics simulation trajectories. AutoDock Vina and Charmm were used in H3 peptide docking. </p> <p>Wild type CTSL was modeled with apo-Cathepsin L C25A mutant(PDB ID : 3K24) using Charmm-GUI. Trimethylated histone H3 peptide was generated with PyMol. H3 peptide Molecular Dynamics simulations were performed with GPU-accelerated OpenMM.</p>
Dataset for analysing spatiotemporal dynamics of large carnivores in Kasungu National Park, Malawi
<p>Effective conservation management requires an understanding of the spatiotemporal dynamics driving large carnivore density and resource partitioning. In African ecosystems, reduced prey populations and the loss of competing guild members, most notably lion (<i>Panthera leo</i>), are expected to increase levels of competition between remaining carnivores. Consequently, intraguild relationships can be altered, potentially increasing the risk of further population decline. Kasungu National Park (KNP), Malawi, is an example of a conservation area that has experienced large-scale reductions in both carnivore and prey populations, leaving a resident large carnivore guild consisting of only leopard (<i>Panthera pardus</i>) and spotted hyaena (<i>Crocuta crocuta</i>). Here we quantify the spatiotemporal dynamics of these two species and their degree of association, using a combination of co-detection modelling, time-to-event analyses, and temporal activity patterns from camera trap data. Detection of leopard and spotted hyaena was significantly associated with the detection of preferred prey and competing carnivores, increasing the likelihood of species interaction. Temporal analyses revealed sex-specific differences in temporal activity, with female leopard activity patterns significantly different to those of spotted hyaena and male conspecifics. Heightened risk of interaction with interspecific competitors and male conspecifics may have resulted in female leopards adopting temporal avoidance strategies to facilitate co-existence. Female leopard behavioural adaptations increased overall activity levels and diurnal activity rates, with potential consequences for overall fitness and exposure to sources of mortality. As both species are currently found at low densities in KNP, increased risk of competitive interactions, that infer a reduction in fitness, could have significant implications for large carnivore demographics. Protection of remaining prey populations is necessary to mitigate interspecific competition and avoid further alterations to the large carnivore guild.</p>
NanoString dataset for study: Dynamic changes in the NK-, Neutrophil-, and B-cell immunophenotypes relevant in high metastatic risk post neoadjuvant chemotherapy–resistant early breast cancers
<p>Pre-processed DSP and mRNA abundance datasets used in this study.</p>
Dataset and code for "Tiltable objective microscope visualizes selectivity for head motion direction and dynamics in zebrafish vestibular system", Nat Commun 13, 7622 (2022). https://doi.org/10.1038/s41467-022-35190-9
<p>Dataset and code for "Tiltable objective microscope visualizes selectivity for head motion direction and dynamics in zebrafish vestibular system", Tanimoto, Watakabe, and Higashijima.</p> <p> </p> <p>The spreadsheet files contain source data for the figures.</p> <p>The file named "register_rotated_images_demo.zip" contains the MATLAB code, example image data, and instruction text data. To use the code, unzip the file and follow the instructions in the "readme.txt" file. The file named "register_rotated_images_demo_output.zip" contains expected output image data.</p> <p> </p>
Dataset for "Attosecond Dynamics of sp-Band Photoexcitation"
<p>Dataset for: </p> <p>"Attosecond Dynamics of sp-Band Photoexcitation</p> <p>Johann Riemensberger, Stefan Neppl, Dionysios Potamianos, Martin Schäffer, Maximilian Schnitzenbaumer, Marcus Ossiander, Christian Schröder, Alexander Guggenmos, Ulf Kleineberg, Dietrich Menzel, Francesco Allegretti, Johannes V. Barth, Reinhard Kienberger, Peter Feulner, Andrei G. Borisov, Pedro M. Echenique, and Andrey K. Kazansky</p> <p>Phys. Rev. Lett. <strong>123</strong>, 176801 – Published 21 October 2019"</p> <p> </p> <p>DOI: https://doi.org/10.1103/PhysRevLett.123.176801</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.