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1,600 results for “input”
Removal of developmentally regulated microexons has a minimal impact on larval zebrafish brain morphology and function - behavior data input files
<p>Unprocessed (tracking) larval zebrafish behavioral data from mutants with microexons removed. All genes are grouped by their beginning letter, and two runs are included for most mutants.</p>
Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands
<p>Field observation data collected from publications, the references from the main text and data sources , grid-level maps showing prediction of global cultivated land NCE(%) and data-driven model codes </p>
Sample of input data for RASflow
<p>Sample input files for the execution of RASflow, a workflow for RASopathy analysis using the Swift parallel scripting system. (https://github.com/mmondelli/rasflow)</p>
Livestock in diverse cropping systems improve weed management and sustain yields whilst reducing inputs
<p>Dataset used for the article: </p> <p>MacLaren, C.; Storkey, J.; Strauss, J.; Swanepoel, P.; and Dehnen-Schmutz, K. (2018). Livestock in diverse cropping systems improve weed management and sustain yields whilst reducing inputs. <em>Journal of Applied Ecology.</em></p> <p> </p>
Input data and scripts for "Spatial conservation prioritization for the East Asian islands: a balanced representation of multi-taxon biogeography in a protected area network"
<p>This release contains the input files 'input_data.zip' for the spatial conservation prioritization analysis by Zonation software, which are conducted in Lehtomäki et al. Input data includes biodiversity features (species distribution maps from vascular plants, mammals, birds, reptiles, amphibians, and freshwater fishes), habitat condition map (human influence index), priority mask information (the categorized protected area distribution) and the Japanese prefecture polygons in GeoTiff format, and the list of species attributes for conservation weighting in CSV format. Note that endangered rare species have been excluded from this dataset, though they were reflected in the output files. The Zonation setting files and R scripts for pre- and post analyses are included in 'japan-zsetup-1.0.zip' and also placed at GitHub : https://github.com/cbig/japan-zsetup</p> <p>The output files (priority score maps and removal curves) from the original Zonation analyses are summarized in 'output_from_original.data.zip'</p>
Input files and data for paper "Modules for Experiments in Stellar Astrophysics (MESA): Pulsating Variable Stars, Rotation, Convective Boundaries, and Energy Conservation"
<p>This entry contains input files to reproduce the results of the paper:</p> <p>Modules for Experiments in Stellar Astrophysics (MESA): Pulsating Variable Stars, Rotation, Convective Boundaries, and Energy Conservation.</p> <p>Each zip archive corresponds to a section of the paper, and includes README files in ASCII format with a description. Raw output data and plotting tools are also provided for some of the results.</p>
Abaqus models and input files for simplified micro models of in-plane loaded masonry walls
<p>The data set contains the Abaqus input files of the numerical analyses presented in two research papers.</p> <p>1) Influence of load history on the force-displacement response of in-plane loaded unreinforced masonry walls, <em>Engineering Structures, </em>2017, <a href="https://www.sciencedirect.com/science/article/pii/S0141029617304248?via%3Dihub">Link</a></p> <p>2) Shear-compression tests of URM walls: Various setups and their influence on experimental results, <em>Engineering Structures</em>, 2017, <a href="https://www.sciencedirect.com/science/article/pii/S0141029617309082?via%3Dihub">Link</a></p>
DustCOMM_v1 Input Dataset
<p>This repository contains the input data for Dust Constraints from joint Observational-Modelling-experiMental analysis – DustCOMM Version 1.</p> <p>The DustCOMM code is publicly available at http://doi.org/10.5281/zenodo.2620556, while the DustCOMM output dataset is similarly available at http://doi.org/10.5281/zenodo.2620475</p> <p>Below, we give a brief description of each file:</p> <p>1. model_dust_concentration -- Simulated 3-D dust concentration (ug/m3) from 6 model simulations. This folder contains both annually-averaged and seasonally-averaged model simulations.<br> 2. model_dust_Vweight -- 3-D model dust vertical weight used in DustCOME. This is calculated from the modeled dust concentration. This folder contains both annually-averaged and seasonally-averaged model simulations.<br> 3. DAOD_clim_reanalysis_all.nc -- Constrained annually-averaged dust aerosol optical depth. See Adebiyi et al. Geoscientific Model Development for details<br> 4. DAOD_seas_reanalysis_all.nc -- Constrained seasonally-averaged dust aerosol optical depth. See Adebiyi et al. Geoscientific Model Development for details<br> 5. DustCOMM_lat.nc -- Latitude array used in DustCOMM. Dimension = 96.<br> 6. DustCOMM_lon.nc -- Longitude array used in DustCOMM. Dimension = 144.<br> 7. DustCOMM_lev.nc -- Altitude (hPa) array used in DustCOMM. Dimension = 48.<br> 8. Globally_averaged_dust_PSD.mat -- Constrained Globally-averaged dust size distribution from Kok et al, Nature Geoscience, 2017.<br> 9. Size_resolved_ext_eff.mat -- Constrained Globally-averaged dust extinction efficiency from Kok et al, Nature Geoscience, 2017.</p> <p>If you have any question, please email the aadebiyi@ucla.edu.</p>
Data from: Grazing-induced patchiness, not grazing intensity, drives plant diversity in European low-input pastures
<p>Vegetation and soil data from:</p> <p>Tonn, Densing, Gabler, Isselstein: Grazing-induced patchiness, not grazing intensity, drives plant diversity in European low-input pastures, Journal of Applied Ecology</p> <p>The first data sheet contains a description of column names and contents, the second data sheet contains the data set itself.</p>
Input template for CASoft
<p>This file may be used for using CA Software</p>
Input files to test the DiSCount installation - Masteling et al
<p>Input images to test the installation of DiSCount.</p>
"Laser wakefield accelerator driven by the super-Gaussian laser beam in the focus" - Input files for the PIC simulations in the EPOCH Code
<p>These are particle-in-cell simulation set-ups for the EPOCH code. The simulations show the super-Gaussian beam diffraction in free space and in plasma (LWFA acceleration).</p> <p>Coresponding publication is currently reviewed.</p>
Low-Input Estimation of Site-Specific Lime Demand - Table S1
<p>Overview of combined observations for soil apparent electrical conductivity (via EM38 MK1 (Geonics, Canada) in vertical mode), soil humidity, ex situ determined topsoil pH (pHREF), in situ determined topsoil pH (pHFE), modified in situ determined topsoil pH (pHFEM2) and the respective estimated lime demands based on ECa and pH (pHREF, pHFE, pHFEM2) values.</p>
Input data for article "Large eddy simulation of the optimal street-tree layout for pedestrian-level aerosol particle concentrations"
<p>Input dataset used when performing LES simulations for journal article "Large eddy simulation of the optimal street-tree layout for pedestrian-level aerosol particle concentrations" (Karttunen et al., in preparation). The dataset was used with the PALM model system revision 3698 and most likely it won't work on older or newer versions.</p> <p>Instructions for use:<br> A precursor run must be run first. Output data (BINOUT) of it should be linked into a BININ directory of the actual scenario runs. You'll most likely have to tweak the CPU grid settings in ENVPAR and PARIN files in order to fit them to your computational resources. For more information on usage please refer to the PALM model documentation available online in <a href="https://palm.muk.uni-hannover.de/trac/wiki/doc">https://palm.muk.uni-hannover.de/trac/wiki/doc</a>.</p>
Artifact of An LLM-based Readability Measurement for Unit Tests' Context-aware Inputs
<div> <p><strong>Artifact of An LLM-based Readability Measurement for Unit Tests' Context-aware Inputs</strong></p> <p> </p> <p>A README.md file can be found in the base folder after unzipping the artifact.</p> <p> </p> </div>
Input files for MD simulations of VP40 matrix protein dimer-dimer structure for WT, G198R, and G201R
<p>For AA simulations, the inp files need to have the path for the toppar folder and the corresponding pdb/psf files need to be renamed.</p>
Example inlists and GYRE input files for the paper "Tidal Spin-up of Subdwarf B Stars" by Ma & Fuller 2024
<p>These folders contain the files for the stellar models and oscillation solution setups for the paper "Tidal Spin-up of Subdwarf B Stars" by Ma & Fuller 2024</p> <p>For any questions, please contact Linhao Ma: linhaoma@princeton.edu (before June 2028), lma.astrophys@gmail.com (after)</p> <p>Explanations of folders:</p> <p>MESA/: files to reproduce MESA stellar evolution models<br>MESA/MESA_working_directory_r12778/: the working directory for MESA version r12778, which is used in the paper<br>MESA/1.2SDB_9.85e-04: the inlist and model files to create the canonical sdB model (0.47 solar-masses, 0.001 hydrogen mass left in the envelope)<br>MESA/2.7SDB_1.00e-03: the inlist and model files to create the low-mass sdB model (0.37 solar-masses, 0.001 hydrogen mass left in the envelope)<br>MESA/1.2SDB_3.14e-03: the inlist and model files to create a canonical sdB model with 0.003 hydrogen mass left in the envelope (for discussions in Section 5.1)<br>MESA/1.2SDB_5.04e-03: the inlist and model files to create a canonical sdB model with 0.005 hydrogen mass left in the envelope (for discussions in Section 5.1)</p> <p>GYRE/gyre.in: example GYRE input files to solve for oscillation modes. The GYRE version used is GYRE 6.0.1. Note that some of the flags will change if you use newer versions of GYRE.</p> <p>Explanations of inlist and model files:<br>MESA/MESA_working_directory_r12778/inlist: the general inlist file. You should change extra_star_job_inlist1_name and extra_controls_inlist1_name to the name of the inlist files of a certain evolutionary phase, which are:<br>inlist_project_TRGB: the phase from zero-age main-sequence (ZAMS) to the tip of the red giant branch (TRGB)<br>inlist_project_MT: the phase of the mass loss to strip the stellar envelope, until core helium burning starts<br> *NOTE: for canonical (1.2SDB) models, this file has only been tested for MESA r12778, other versions of MESA may fail to run a model due to numerical difficulties when treating the off-center Helium flash.<br>inlist_project_sdB: the phase of sdB core helium burning<br>inlist_project_WD: in MESA/1.2SDB_9.85e-04/, this is the phase after the sdB until it evolves to a carbon-oxygen white dwarf (for discussions in Section 5.4)<br> You should first run inlist_project_TRGB, then inlist_project_MT, then inlist_project_sdB. They will automatically generate model files that can be used in the next phase of the evolution.<br>sdB: the zero-age sdB model (which should be generated after the mass loss phase), in case you only want to run the sdB helium burning phase</p>
Sequential migrations of diverse fish community provide seasonally prolonged and stable nutrient inputs to a river
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Acrolein solution and gas phase configurations and OpenMM inputs
<p>Dataset for acrolein solution phase and gas phase spectrum calculations with the ESPF-DRF method. Included in the dataset are:</p> <ul> <li>OpenMM input files for generating configurations together with the trajectory file.</li> <li>The extracted configurations for gas and aqueous solution simulations.</li> <li>QM/MM ESPF-DRF data and input files for PyESPF + PySCF for several different water models.</li> </ul>
Online repository input data collection framework
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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.