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2,152 results for “outputs”
Model outputs
<p>Model data for Fig.2-4</p>
Simulation data output used in the plasma nature of lightning channels and the resulting nonlinear resistance
<p>Simulation data shown in "The plasma nature of lightning channels and the resulting nonlinear resistance", a paper submitted for publication in JGR by da Silva et al. [2019].</p> <p>Each folder contains corresponds to a simulation case, as described below. Each file, e.g., s_1.m, corresponds to a different value of current input (all other parameters constant).</p> <p>Use the Matlab script load_and_plot_data.m to load and plot the data. A sample figure output is provided (Sample_Figure_Rss_king_s_3.pdf). The eight panels in the figure show the temporal evolution of all (important) quantities inside the lightning plasma channel, allowing for a detailed inspection of the results shown in da Silva et al. [JGR, 2019].</p> <p>See the file README.txt for further instructions.</p>
Morphodynamic modeling of sediment pulse dynamics: Raw code and output
<p>Fortran source code and raw output files (.csv) for a 1D morphodynamic model simulating sediment pulse evolution.</p> <p>This material is provided as is, with absolutely no warranty expressed or implied. Any use is at your own risk.</p>
LAMMPS output from creep simulation of silica sphere caps with water
<p>Results from creep simulation of silica sphere caps, passivated with hydroxy groups and with water filling the void.</p> <p>38 nanoseconds of data.</p> <p>This description will be updated with a github repo and more information when possible.</p>
LAMMPS output from creep simulation of silica sphere caps, asymmetric system with tdamp=1
<p>Results from creep simulation of silica sphere caps.</p> <p>200 nanoseconds of data.</p> <p>This description will be updated with a github repo and more information when possible.</p>
LAMMPS output from creep simulation of silica sphere caps, symmetric system with tdamp=5
<p>Results from creep simulation of silica sphere caps.</p> <p>200 nanoseconds of data.</p> <p>This description will be updated with a github repo and more information when possible.</p>
LAMMPS output from creep simulation of silica sphere caps
<p>Results from creep simulation of silica sphere caps.</p> <p>1 microsecond of data.</p> <p>This description will be updated with a github repo and more information when possible.</p>
SFRC dataset + target vs output
<p>430 data points</p> <p><strong>meaning of each excel sheet:</strong></p> <p>IN - input variable values for each data point (each data point is one row) </p> <p>TARGET - target variable values for each data point (each data point is one row) </p> <p>VARS - presents the units used for each input (independent) and output/target (dependent) variables</p> <p>TARGET vs OUTPUT - presents the 430 expected (experimental) values and the ones obtained by the proposed ANN</p> <p> </p> <p><strong>Check reference below</strong>:</p> <p><a href="https://www.researchgate.net/publication/335946530_Neural_Nets_-_Steel_Fiber-Reinf_Concrete_-_Shear">https://www.researchgate.net/publication/335946530_Neural_Nets_-_Steel_Fiber-Reinf_Concrete_-_Shear</a></p>
Supporting Model Code and Output for https://doi.org/10.5194/gmd-2019-78, 2019
<p>Model code and timeseries output for Travis et al. 2019 (GMD) https://doi.org/10.5194/gmd-2019-78, 2019.</p> <p> </p>
BCC-GEOS-Chem v1.0 model output (2012-2014)
<p>The file includes the model output of the BCC-GEOS-Chem v1.0.</p>
COSMO-CLM outputs Central Asia Russo et al. 2019
<p>Monthly values of 2-meter temperature (T2M), total precipitation (TOT_PREC) and diurnal temperature range (DTR) derived from the simulations performed with the Regional Climate Model COSMO-CLM (Roeckel et al. 2008) for the CORDEX Central Asia Domain, presented in Russo et al. 2019 ( https://doi.org/10.5194/gmd-2019-22, 2019).</p> <p>The data have a spatial resolution of ~25 km. The data cover the period 1996-2005. For some realization, a file covering the period 2005-2015 is also present. All simulations are initialized on the 01.01.1991. The only exception are 4 simulations used to investigate the model internal variability, whose initial time has been shifted of +1,-1,+3 and -3 with respect to the default initial date.</p>
CCLM outputs Parameters Sensitivity Investigation Central Asia and Europe
<p>Monthly values of 2-meter temperature (T2M), total precipitation (TOT_PREC) and total cloud cover (CLCT) derived from the simulations performed with the Regional Climate Model COSMO-CLM (Roeckel et al. 2008) for the CORDEX Central Asia and Europe Domains, used for the paper "Exploring the Parameters Space of the Regional Climate Model COSMO-CLM 5.0 for the CORDEX Central Asia Domain" by RUSSO et al. (geoscientific model development), submitted for the first time on the 31st of October 2019.</p> <p>The data have a spatial resolution of ~25 km. The data cover mainly the year 2000. These are the sensitivity simulations, initialized on the 01.01.2000 using a restart file derived from the reference simulations for the two domains (ncep022_test_belprat1 and europe_test_belprat1) also provided here. For some realization, a file covering the period 1996-2005 is also present. These data are used to assess the model internal variability over the considered period.</p>
A Weighting Function Model for Unsteady Open Channel Friction: Raw code and output
<p>Matlab source code and Raw Origin Lab file (.opj) for a weighting function model simulating unsteady open channel friction slopes. This material is provided as is. Methods (formulas) and Figures are explained further in the related article "A Weighting Function Model for Unsteady Open Channel Friction" by Junwei Zhou; Weimin Bao; Geoffrey R. Tick; Qing Cao; and Fanghong Ye.</p>
PACMAN-P Model Outputs for TRAPPIST-1b and e
Open the record for dataset details and reuse information.
Example Analysis Output of Vizgen Mouse Brain Data
<div> <p>This is an example analysis output data from Vizgen Mouse Brain Data Analysis</p> <p> </p> </div>
Example Analysis Output of Stereo-seq Mouse Brain Data
<p>This is an example analysis output data from Stereo-seq Mouse Brain Data Analysis</p>
Example Analysis Output of Xenium Mouse Brain Data
<p>This is an example analysis output data from Xenium Mouse Brain Data Analysis</p>
binary_c output files to reproduce "Massive runaway and walkaway stars"
<p>Raw binary_c output for the paper "<a href="https://ui.adsabs.harvard.edu/abs/2019A%26A...624A..66R/abstract">Massive runaway and walkaway stars: A study of the kinematical imprints of the physical processes governing the evolution and explosion of their binary progenitors</a>" by Renzo et al. <br><br>The tarball is ~21GB zipped, and unzips to >250Gb file with all the parameter variations.<br><br></p>
Raw Data and Full Ensemble Output (1880-2020) for "A NASA GISTEMPv4 Observational Uncertainty Ensemble"
<p>Contains the Raw and Final data for "A NASA GISTEMPv4 Observational Uncertainty Ensemble" as accepted at JGR:Atmospheres (August 2024). </p> <p><code>FinalEnsembleOutput/</code> Contains the official GISTEMPv4 uncertainty ensemble from 1880-2020 with anomalies relative to a 1951-1980 climatology. The ensemble is organized into three subdirectories</p> <p><code>FinalEnsembleOutput/FullEnsemble</code> Contains a netCDF file [lon,lat,month] for each of the 200 members on a 2x2 grid.</p> <p><code>FinalEnsembleOutput/GriddedSummary</code> Contains netCDF files [lon,lat,month] of statistics summarizing the 200-member ensemble. The statistics contained are the ensemble mean, ensemble sd, quantiles, and sample size (can be less than 200 due to differences in the homogenization in data-sparse regions). The quantiles provided are (0.025, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 0.975).</p> <p><code>FinalEnsembleOutput/KeySeries</code> Contains 200-member ensembles of key, large scale time series at monthly resolution. Global, hemispheric, and zonal mean series are provided each for land, ocean, and combined (land and ocean) mean temeperature. <strong>Use this data when working with these series rather than calculating yourself from the full ensemble as the method for creating these series incoproates unertainty due to regions without coverage.</strong></p> <p><code>Raw/</code> Contains the raw, source data for the GISTEMP ensemble. This directory is not very large, but contains ~50k files as the GHCN product is distributed as an individual text file for every station in the record.</p> <p>Intermediate data products from the analysis can be found here: <a href="https://doi.org/10.5281/zenodo.13344579" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13344579</a></p>
STIM model output for "Aurorally-driven Supersonic Gravity Waves in Saturn's Atmosphere"
<p>Saturn Thermosphere-Ionosphere Model (STIM) output corresponding to the figures shown in the paper "Aurorally-driven Supersonic Gravity Waves in Saturn's Atmosphere".</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.