Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
328
datasets available to search
ShareScore release 0.9.0
Dataset results
328 results for “Simulation results”
A simple framework for agent-based modeling with extracellular matrix: Simulation results
<h1>Data for "A simple framework for agent-based modeling with extracellular matrix"</h1> <p> </p> <div>Metzcar, J., Duggan, Ben S., Fischer, B., Murphy, M., Heiland, R., Macklin, P. A simple framework for agent-based modeling with extracellular matrix. bioRxiv. doi: 10.1101/2022.11.21.514608</div> <div> </div> <div><a href="https://www.biorxiv.org/content/10.1101/2022.11.21.514608">Link to preprint</a></div> <div> <p>This repository contains the data for each subfigure (and video) in the preprint cited and linked abvoe, as well as the original figures and videos themselves. We have tried to include original model file (<code>PhysiCell_settings.xml</code> or other <code>*.xml</code> file) used to generate each results with each file set as well as the code (see python scripts) to make images and videos that appear in the pre-print - both within the files and base modules and examples in a separate folder.</p> <p>The data can be regenerated using release 2.0, <a href="https://github.com/PhysiCell-Models/collective-invasion/releases/tag/v2.1">2.1</a>, and <a href="https://github.com/PhysiCell-Models/collective-invasion/releases/tag/v2.2.1">2.2.1</a>. Release 2.1 is recommended for reproducing more exactly the results for the fibrosis, invasive carcinoma, and series of leader-follower results as the results archived here were produced using a set of two random number generators (one from PhysiCell and one from BioFVM). 2.2.1, used to produce the invasive cellular front results, consolidates the use of random number generators to just one (the PhysiCell one). As such, in 2.2.1, the random number generator seed may need changed to produce stochastic replicates, even when multithreading.</p> </div> <p> </p> <div>The following file sets are in this download:</div> <ul> <li>Fig2_SM_3_simple_tests.zip <ul> <li>Has results for Figure 2 and SM Figure 3</li> </ul> </li> <li>Fig3_fibrosis.zip <ul> <li>Results from fibrosis simulation (originally Figure 3, now Figure 4)</li> </ul> </li> <li>Fig4_invasive_carcinoma.zip <ul> <li>Results from invasive carcinoma simulation (originally Figure 4, now Figure 5)</li> </ul> </li> <li>Fig5_collective_migration_initial_tests.zip <ul> <li>Results from initial leader follower model development (originally Figure 5, now Figure 6)</li> </ul> </li> <li>Fig6_instant_remodeling.zip <ul> <li>Results from instant remodeling leader follower model scenariods (originally Figure 6, now Figure 7)</li> </ul> </li> <li>Fig7b_leader_follower.zip <ul> <li>Results from leader-follower collective migration scenario (origianlly Figure 7b, now Figure 8b)</li> </ul> </li> <li>images_and_vidoes_for_paper.zip <ul> <li>has all the images, videos, and some figures from the main body of the paper and the supplmental material. Updated in this version.</li> </ul> </li> <li>Invasive_cellular_front.zip <ul> <li>Has results for each ECM scenario: random, parallel, and perpindicular orientations and mixed ECM conditions. New to this data repository.</li> </ul> </li> <li>python_imaging.zip <ul> <li>Base modules and examples for producing images (tested on Python 3.9). Updated in in this verison</li> </ul> </li> <li>SM_Fig_4b_leader_follower_decreased_remodeling.zip</li> <li>stochastic_replicates.zip <ul> <li>Contains stochastic replicates for the collective migration, fibrosis, and invasive carcinoma models and source code for all.</li> </ul> </li> <li>stochastic_replicates_invasive_cellular_front.zip <ul> <li>Contains stochastic replicates for the invasive cellular front scenarios. New to this data repository.</li> </ul> </li> </ul>
Simulation result from Meeting climate target with realistic demand-side policies in the residential sector
<p>Simulation result from EU Implementation of Message-ix Buildings. Result are detailed in the working paper: Meeting climate target with realistic demand-side policies in the residential sector.</p> <p>It contains 3 folders: all scenarios, optimal scenarios detailed in last section of Result and the counterfactual scenario.</p> <p> </p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 9: Operational and damaged scenarios in regular waves
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 9. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
sunflower oil - water emulsion estabilized by BSFLP protein: phase separation simulation results 0.48 h
<p>Animation of the simulation results presented in Figure 7 of Journal of Food Engineering, Volume 387 p. 112331, available at <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jfoodeng.2024.112331" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jfoodeng.2024.112331</a></p> <p>The separation time in the video is dimensionless, and it corresponds to a 0 - 48h period</p>
Air parcel trajectories data generated by MIMICA code and simulation results generated by a trajectory box model
<p>The dataset includes trajectories of air parcels extracted from the large-eddy (cloud-resolving model) simulations of the deep convective clouds from the Amazon based on the soundings retrieved on April 8, 2020, April 23, 2020, and April 27, 2020, over Manaus, Brazil, as well as the results of the chemical box model simulations quantifying the transport of some atmospheric trace gases abundant in the Amazon.</p>
Simulation Results for the Investigation of Back Surface Field layer for High Efficiency Ultrathin In2S3 based CIGS Solar Cell
<p>A comprehensive study of a novel structure for In2S3 based CIGS solar cell has been observed. The effects of the absorber layer and temperature with various back surface field (BSF) layers (SnS/SnTe/MoTe2/GeTe) are analyzed with the SCAPS-1D simulator. Performances of the ultrathin CIGS solar cell enhanced with the proposed structure of ZnO:Al/i-ZnO/In2S3/CIGS/BSF/Mo and efficiency reached over 24% with 1000 nm CIGS absorber layer. The cell with SnS BSF layer has obtained 24.41% efficiency but shows less stability with temperature variation. On the other hand, the cell with MoTe2 BSF shows better stability at a higher temperature and reached an efficiency of 24.14%. Besides, the cell with SnTe BSF also suitable for ultrathin In2S3/CIGS, which results in an efficiency of 23.27%. However, the cell with GeTe BSF can give just over 18% efficiency, but it shows greater stability with temperature changes.</p>
Simulation results for "Modeling the joint effects of vegetation characteristics and soil properties on ecosystem dynamics in a Panama tropical forest"
<p>This dataset is the ELM-FATES simulation outputs for the paper entitled "Modeling the joint effects of vegetation characteristics and soil properties on ecosystem dynamics in a Panama tropical forest". </p>
Sample simulation results for showyourwork
A sample dataset uploaded using showyourwork.
Monte Carlo Simulations results for estimating an offshore structure fatigue life with a Fracture Mechanics based crack growth model, after additional information was considered through Bayesian inference at t=13 years
<p>Monte Carlo Simulations results for estimating an offshore structure fatigue life with a Fracture Mechanics based crack growth model, after additional information was considered through Bayesian inference at t=13 years</p>
Simulation code and results for "Critical behavior and the Kibble-Zurek mechanism in a musical phase transition"
<p>Matlab simulation code and results for "Critical behavior and the Kibble-Zurek mechanism in a musical phase transition."</p> <p>See readme.txt for descriptions of all files.</p>
Simulation Results for "Characteristics of Electron Precipitation Directly Driven by Poloidal ULF waves"
<p>This dataset contains the simulation results and the corresponding code to produce the figures in the manuscript "Characteristics of Electron Precipitation Directly Driven by Poloidal ULF waves". The name of each data file indicates its corresponding figure, and the Matlab code could be used to produce the figures in the manuscript.</p>
MD simulation input files and results for ,,Atomistic MD simulations of n-alkanes in a phospholipid bilayer: CHARMM36 versus Slipids"
<p>Input files and trajectories of n-alkane/lipid systems used in the article: ,,Atomistic MD simulations of n-alkanes in a phospholipid bilayer: CHARMM36 versus Slipids".</p> <p>Equilibrated starting configurations were created using CHARMM36. Otherwise, filenames specifiy the force field used (C36 or SL), Temperature and system composition.</p> <p>.xtc trajectories were created using gmx trjconv with options -pbc nojump -dt 10. run2 equals simulations from 100-200ns, run3 equals 200-300ns. The first 100ns were excluded from the analysis and are not included in this dataset.</p> <p>Exemplary .mdp files have been included for both force-fields. Please refer to the manuscript for the force field sources and additional information.</p>
Earth system model simulation results (1980-2014) for snow analysis
<p>This dataset contains monthly output in 1984-2014 from simulations using E3SM. To extract them, you should first collect the files together and run <code>zip -F sd_simulation_output_sliced.zip --out sd_simulation_output.zip, then unzip sd_simulation_output.zip</code>.</p>
FEG_plus_MC_simulation_results
<p>One file (FEG-sh) contains FEG simulation datasets and figures for this study, that is, BC arriving at YRE. The other contains Monte Carlo simulation results (posterior probability density functions of numerical spread) of the relative source contribution of three major sources (liquid fossil, coal and biomass) for dual carbon isotope samples in this study; there are four seasons for YRE and winter for an urban site.</p>
Simulation Results
<p>Simulation results for the article "A neutral comparison of algorithms to minimize L0 penalties for high-dimensional variable selection" which is to be published by the Biometrical Journal.</p>
Model Simulation Results
<p>mHM model runs</p>
QUEST-MM, QUEST(Subtract), QUEST(Met+Back) and QUEST(Met+MM) quantification results of in-vivo and simulated MRS human and rat brain spectra
<p>QUEST-MM, QUEST(Subtract), QUEST(Met+Back) and QUEST(Met+MM) quantification results of rat and human brain <em>in-vivo</em> and simulated spectra alongside with the metabolite profiles and the simulated 9.4T rat and 4T and 3T human brain spectra.</p> <p>All files can be loaded in jMRUI software version 5 and later.</p>
GITM Electron rocket launch simulation results
<p>Data from GITM simulation of Electron rocket launch "They Go Up So Fast" of March 22 2021. These include data for the simulation with and without rocket exhaust. In each case the following are included:</p> <ul> <li>UAM.in: main GITM input file</li> <li>M2_launch*.dat: rocket trajectory and exhaust flow rate data</li> <li>rec_*_chti_*.dat: range (sr), latitude (lats), longitude (lons), and pierce point (point) data for CHTI ground station slant total electron content (TEC) measurements</li> <li>*_alt_profile_multiple.dat: altitude profiles for CO2, e-, and H2O</li> <li>stec_*_chti.dat: slant total electron content at the CHTI ground station from GITM output</li> <li>tec_data_multiple.dat: vertical TEC from GITM output</li> </ul> <p>Also contains Python post-processing scripts used to produce these data. Note that gitm_append.py and gitm_time.py are from the original open source GITM distribution and not the work of the author.</p>
Properties of whistler waves' ducting in plasmas with systems of small-scale density depletions. Simulation results.
<p><strong>Properties of whistler waves' ducting in plasmas with systems of small-scale density depletions. </strong><strong>Simulation results.</strong></p> <p>The results of numerical FDTD simulations for the paper entitled "Properties of Whistler Waves’ Ducting in Plasmas With Systems of Small-scale Density Depletions" by Zudin I.Yu. et al.</p> <p>All files stored here are vectors or matrices coefficients presented in the text format and space symbol separated. "loadtxt" function from "numpy" library can be used for the data loading by a Python user. Each folder corresponds to a figure with the same number. The data stored in "data.zip" archive сontaining the following folders.</p> <p><strong>Fig2 folder</strong></p> <p>All files are the solutions of the dispersion equations wrote in the paper. Each of file consist in two columns. First column is the density depletion width</p> <p>(in meters), and second column is wavenumber <span class="math-tex">\(p\)</span></p> <ul> <li>"even_0.dat", "even_1.dat" ... are the fist, the second etc. even modes of the plain depletion.</li> <li>"odd_0.dat", "odd_1.dat" ... are the fist, the second etc. odd modes of the plain depletion.</li> <li>"m=0_0.dat", "m=0_1.dat" ... are the fist, the second etc. brunches of the modes of the cylindrical depletion with azimuth number m=0.</li> <li>"m=+1_0.dat", "m=+1_1.dat" ... are the fist, second the etc. modes of the cylindrical depletion with azimuth number m=1.</li> <li> "m=-1_0.dat", "m=-1_1.dat" ... are the fist, second the etc. modes of the cylindrical depletion with azimuth number m=-1.</li> </ul> <p><strong>Fig3 folder</strong></p> <p>All files are the dependences of normalized localization scale <span class="math-tex">\(\delta / d\)</span> from <span class="math-tex">\(d\)</span>. Each of file consist in two columns. The first one is the density depletion width <span class="math-tex">\(d\)</span> (in meters), and the second column is <span class="math-tex">\(p\)</span>.The files is named in such a manner as in Figure2 folder.</p> <p><strong>Fig5 folder</strong></p> <p>"Ex.dat", "Ey.dat" and so on are the amplitudes of electric and magnetic field components presented in Figure #5 of the paper. "Ne.dat" is simulated density profile at z=60 km, as in above the file consists in two columns. The first is the</p> <p>coordinate and the second is the density. "xgrid.dat" and "zgrid.dat" are Cartesian coordinates of the grid's nodes used for field representation. So Ex(x[i],z[j])=Ex[j,i]</p> <ul> <li>units of plasma density is "m(-3)"</li> <li>units of electrical field components is "mkV/m"</li> <li>units of magnetic field components is "pT"</li> <li>units of Cartesian coordinates is "km"</li> </ul> <p>The grid used for the data presentation is less detailed than that used for actual simulation.</p> <p><strong>Fig6 folder</strong></p> <p>The same description as for Fig5 folder.</p> <p><strong>Fig7 folder</strong></p> <p>"subdecameter.Sz.dat", "subdecameter.Sx.dat", "subhectometer.Sz.dat", and "subhectometer.Sz.dat" are the Pointing vector projections calculated in the cases of subdecameter and subhectometer depletions. "xgrid.dat", "zgrid.dat" are the coordinates of the grid's nodes. "subdecameter.Ne.dat" and "subhectometer.Ne.dat" is is simulated density profiles of systems of subdecameter and subhectometer depletions. The files ogranized in such mannar as in Figure5 folder. The grid used for the data presentation is less detailed than that used for actual simulation.</p> <ul> <li>units of plasma density is "m(-3)"</li> <li>units of energy flux is "mkW/m(2)"</li> <li>units of Cartesian coordinates is "km"</li> </ul> <p><strong>Fig8 folder</strong></p> <p>"subdecameter.Sz.dat", "subdecameter.Sz.dat" are the Pointing vector projections calculated in the cases of subdecameter and subhectometer depletions. "subhectometer.Ex.dat", and "subhectometer.Ex.dat" are the amplitudes of the electric field component. "xgrid.dat", "zgrid.dat" are the coordinates of the grid's nodes. "subdecameter.Ne.dat" and "subhectometer.Ne.dat" is is simulated density profiles of systems of subdecameter and subhectometer depletions. The files organized in such manner as in Figure5 folder. The grid used for the data presentation is less detailed than that used for actual simulation.</p> <ul> <li>units of electrical field components is "mkV/m"</li> <li>units of plasma density is "m(-3)"</li> <li>units of energy flux is "mkW/m(-2)"</li> <li>units of Cartesian coordinates is "km"</li> </ul> <p><strong>Fig9 folder</strong></p> <p>"subhectometer.Ex.dat", "subhectometer.Ex.dat" etc. are the profiles along <span class="math-tex">\(x\)</span> of the components of the electric field and the plasma density. The files organized in such a manner. First column is coordinates values, the second one is the field component or density value.</p> <ul> <li>units of plasma density is "m(-3)"</li> <li>units of electrical field components is "mkV/m"</li> <li>units of Cartesian coordinates is "km"</li> </ul> <p><strong>Fig10 folder</strong></p> <p>"subhectometer.Ex.dat", "subhectometer.Ex.dat" are the 2d-spectrums of the <span class="math-tex">\(E_x\)</span> complex amplitude in the cases of subhectometer and subdecameter depletions. "kx_grid.dat" and "kz_grid.dat" are the Cartesian coordinates of the grid's nodes used for spectrums representation.</p> <ul> <li>units of electrical field components is "mkV/m km(2)"</li> <li>units of Cartesian coordinates is "km(-1)"</li> </ul> <p><strong>Fig11 folders</strong></p> <p>"subhectometer.Ex.dat", "subhectometer.Ex.dat", and "smoothed.Ex.dat" are the 1d spectrums presented on the Figure #11 the cases of subhectometer, subdecameter and smoothed depletions.</p> <ul> <li>units of electrical field components is "mkV/m km"</li> <li>units of Cartesian coordinates is "km(-1)"</li> </ul> <p><strong>Fig12 folders</strong></p> <p>"subhectometer.Ex.dat", "subhectometer.Ex.dat", and "smoothed.Ex.dat" are the 1d spectrums presented on the Figure #12 the cases of subhectometer, subdecameter and smoothed depletions.</p> <ul> <li>units of electrical field components is "mkV/m km"</li> <li>units of Cartesian coordinates is "km(-1)"</li> </ul> <p> </p>
HeatResilientCity II - work package 2.3: Interactions between buildings and open space adaptation measures – Results of building performance simulations
<p>This repository contains the <strong>results of the building performance simulations</strong> carried out in the working package 2.3: Interactions between buildings and open space adaptation measures of the project <a href="http://heatresilientcity.de/">HeatResilientCity II</a>. The buildings under consideration are a multi-residential so-called „Gründerzeithaus“ (GZH) and a large-panel construction (LPC) building. The results were extracted for two rooms of each building on the top floor/attic and follow a consistent name convention. Each file contains hourly resolved values for the outdoor air temperature, the indoor air temperature, the indoor operative temperature and the relative humidity indoor and outdoor. Further information can be found in the README of this repository.</p> <p>In addition to the “plain” simulation results, some <strong>heat-indicator variables</strong> were calculated and listed in <em>Calculate_Indicators_Dresden.txt </em>and<em> Calculate_Indicators_Erfurt.txt</em>. The calculated quantities include temperature weighted exceedance hours for the limits of 25, 26 and 27 °C, the maximum operative temperature occurring during the simulation and the operative indoor temperature and outdoor air temperatures at 4 am and 6 pm on the last day of the heat period/simulation.</p> <p>The used <strong>input data</strong> and <strong>building models</strong> can be found in the related identifiers.</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.