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2,152 results for “outputs”
RNA Pol III input data and output models
<p>This repository contains the input experimental data used in a tutorial on modeling of RNA Polymerase III and the largest cluster of output models.</p>
Model outputs for "Multi-grid algorithm for passive tracer transport in NEMO ocean circulation model"
<p>Model outputs used to write "Multi-grid algorithm for passive tracer transport in NEMO ocean circulation model" publication.</p>
Outputs of numerical simulation of irregular waves propagating over an idealized shoal under non-breaking conditions
<p>This dataset contains bathymetry files (.txt) and outputs files (.mat) of numerical simulation of irregular waves propagating over an idealized shoal under non-breaking conditions, conducted with SWASH model. The spatial and temporal resolution are 0.5 m and 0.1 s, respectively.</p>
Outputs from policy sprint "How does artificial intelligence contribute to sustainability in Switzerland?"
<p>This dataset contains English-language output from a policy sprint on the question "How does artificial intelligence contribute to sustainability in Switzerland?" by the Swiss organization Expedition Zukunft, documented at https://www.expeditionzukunft.ch/sprint-ki.</p> <p>The information included in this dataset was made publicly available by the organization at https://www.expeditionzukunft.ch/sprint-ki. This dataset is simply a transfer of this information on the output of the policy sprint in tabular form, for ease of consumption and analysis.</p> <p>sprint_outputs.csv contains the raw textual data from the website on the outputs of the policy sprint process.<br>metadata.csv contains an explanation of all columns in sprint_outputs.csv.</p> <p>The dataset accompanies an analysis of the policy sprint published in (preprint) form at <a href="https://doi.org/10.31235/osf.io/xykej">https://doi.org/10.31235/osf.io/xykej</a>.<br>When citing this dataset, please credit the organisation Expedition Zukunft (https://www.expeditionzukunft.ch) as the creators and curators of the original raw data source.</p>
Covsel output summary of 141 native - non-native plant species pairs in Switzerland
<p>The covariates as selected by the covsel R package (Adde et al. 2023) for 141 native - non-native congeneric plant species pairs in Switzerland.</p> <p>Publication of covsel R package:</p> <p>Adde, A., Rey, P.-L., Fopp, F., Petitpierre, B., Schweiger, A. K., Broennimann, O., Lehmann, A., Zimmermann, N. E., Altermatt, F., Pellissier, L., & Guisan, A. (2023). Too many candidates: Embedded covariate selection procedure for species distribution modelling with the covsel R package. Ecological Informatics, 75, 102080. https://doi.org/10.1016/j.ecoinf.2023.102080</p>
Dataset from the outputs of the article "Antarctic sensitivity to oceanic melting parameterizations"
<p>This dataset contains all the netCDF files from the simulations made for the article "Antarctic sensitivity to oceanic melting parameterizations". It also contains a general configuration file with the parameters for launching the simulations.</p> <p>The dataset is divided in three blocks: ISMIP6-ANT-16KM, ISMIP6-ANT-16KM-atmosphere (for the only-atmosphere simulations) and ISMIP6-ANT-16KM-ocean (for the only-ocean simulations). Each block contains three folders for the three different values of the basal melting parameter used in this study, 9620 m/yr, 14500 m/yr and 21000 m/yr and each folder a subset of six subfolders for the experiment projections: ctrlAE (for the control run), expAE02 (CCSM4), expAE03 (HadGEM2-ES), expAE04 (CESM2-WACCM), expAE05 (UKESM1-0-LL) and expAE10 (UKESM1-0-LL with low emissions). </p> <p>Reference: Juarez-Martinez, A., Blasco, J., Robinson, A., Montoya, M., and Alvarez-Solas, J.: Antarctic sensitivity to oceanic melting parameterizations, The Cryosphere, 2024.</p>
Model output data for Xueyi Jing et al., "A Scheme of Sea Surface Upward Longwave Radiation with Sea Spray Layer Effect"
<p>CESM Model output data used in "A Scheme of Sea Surface Upward Longwave Radiation with Sea Spray Layer Effect" .</p> <p> </p> <p>Seasonal files were derived from monthly outputs by CDO. "F2000_f09_CTL*******" are results for control run, "F2000_f09_LW_Test1*******" are results for sensitivity experiment. </p>
The netCDF output data of Parallel Princeton Ocean Model based on OpenACC
<p>This dataset represents the output results from the simulated seamount case, where the outputs vary depending on whether parallel (p) or serial (s) execution is used, as well as the different simulation durations and resolutions applied.</p>
Groundwater model outputs for coastal aquifer system
<p>Model outputs for 9 predevelopment coastal groundwater models, and one development scenario for each of these models. This data has been used to generate results for a manuscript which has been submitted for publication.</p>
MicroHH LES output for 08 August 2017 over the Southern Great Plains
<p>Data for paper: Improving the Estimate of Higher Order Moments from Lidar Observations Near the Top of the Convective Boundary Layer</p> <div><a href="https://doi.org/10.5194/egusphere-2024-868" target="_blank" rel="noopener">doi: 10.5194/egusphere-2024-868</a></div>
CESM2 model output from Eisenman & Armour (2024): Part 3
<p>Description of data: See README.txt</p> <p>Citation for data: I. Eisenman and K. Armour (2024). The radiative feedback continuum from Snowball Earth to an ice-free hothouse. Nature Communications, https://doi.org/10.1038/s41467-024-50406-w</p> <p>See also https://eisenman-group.github.io for links to other fields from these simulations.</p>
CESM2 model output from Eisenman & Armour (2024): Part 2
<p>Description of data: See README.txt</p> <p>Citation for data: I. Eisenman and K. Armour (2024). The radiative feedback continuum from Snowball Earth to an ice-free hothouse. Nature Communications, https://doi.org/10.1038/s41467-024-50406-w</p> <p>See also https://eisenman-group.github.io for links to other fields from these simulations.</p>
CESM2 model output from Eisenman & Armour (2024): Part 1
<p>Description of data: See README.txt</p> <p>Citation for data: I. Eisenman and K. Armour (2024). The radiative feedback continuum from Snowball Earth to an ice-free hothouse. Nature Communications, https://doi.org/10.1038/s41467-024-50406-w</p> <p>See also https://eisenman-group.github.io for links to other fields from these simulations.</p>
Experimental online quantum dots charge autotuning using neural networks - Output data
<p>Outputs of the model training and the online autotuning experiments presented in the paper: "Experimental online quantum dots charge autotuning using neural networks".</p> <p>Each folder in the zipped files represent a run that includes:</p> <ul> <li>log file</li> <li>plots / images</li> <li>run settings</li> <li>performance results</li> <li>pytorch model parameters</li> </ul> <p>See README.txt for more information about the file strucutre.</p>
Interactive Outputs for "Automated Mixture Analysis via Structural Evaluation"
<p>HTML files with interactive outputs related to the mixture assignments discussed in the paper "Automated Mixture Analysis via Structural Evaluation."</p>
UltraHD CityCLIM example binary output files for one timestep
<p>These files are example numerical output from the UltraHD Large Eddy simulation model in binary format. The UltraHD Large Eddy simulation model was operational from beginning of June 2023 till October 2024 for three different city regions (Luxemburg, Karlsruhe and Valencia). These example outputs consist of arrays with 500x500 float32 values for the following parameters: 2m temperature (t2m), 2m dewpoint (dewpoint), skin temperature (tsk), windspeeds (u10m, v10m), vertical velocity (w), orografic height (hgt), liquid water path (lwp), surface pressure (psfc). Some of these files are used within the CityCLIM cloud environment for numerical analysis within the identification services. The data is from the run from the 19th of July 2024 for forecast minute 2220.</p> <p> </p>
Post-processed SAM (System for Atmospheric Modeling) simulation output for "Tipping to an Aggregated State by Mesoscale Convective Systems"
<p>Statistics output files for all variables, for a select number of SAM (System for Atmospheric Modeling v. 6.11) simulation runs used in the study "Tipping to an Aggregated State by Mesoscale Convective Systems". The following simulations are included: DIU, OCEAN, DIU2OCEAN branch A1, DIU2OCEAN branch A2.</p>
ERGA post assembly QC test output files
Open the record for dataset details and reuse information.
Model outputs used in "Regional cooling potential from expansion of perennial grasses in Europe"
<p>This dataset accompanies a scientific publication: Xia Zhang, Bo Huang, Nariê Rinke Dias de Souza, Xiangping Hu, and Francesco Cherubini. 2024. Regional cooling potential from expansion of perennial grasses in Europe. Communications Earth & Environment <strong>5</strong>, 772 (2024). https://doi.org/10.1038/s43247-024-01923-5</p>
Data output from Projecting future climate change impacts on the distribution of pelagic squid in the Southern Ocean
<p>Data output from Projecting future climate change impacts on the distribution of pelagic squid in the Southern Ocean:<br>Rasters, R models and scripts</p>
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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.