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1,600 results for “input”
Input data files for RSS-NET analysis of simulated GWAS summary statistics and B cell regulatory network
<p>Details of these data files are provided in https://suwonglab.github.io/rss-net/wtccc_bcell.</p> <p>Contact:<code> xiangzhu[at]psu.edu </code></p>
Demeter Inputs for Chen et al. 2020
<p>These are the inputs used in Demeter runs for the Chen et al. 2020 submission "Global land use projections for 2015-2100 at 0.05-degree resolution under diverse Shared Socioeconomic Pathways and Representative Concentration Pathways."</p> <p>The input structure is described in detail in:</p> <p>Vernon, C.R., Le Page, Y., Chen, M., Huang, M., Calvin, K.V., Kraucunas, I.P. and Braun, C.J., 2018. Demeter – A Land Use and Land Cover Change Disaggregation Model. <em>Journal of Open Research Software</em>, 6(1), p.15. DOI: <a href="http://doi.org/10.5334/jors.208">http://doi.org/10.5334/jors.208</a></p> <p>Configuration files were created for each run and are contained in the "config_files" directory.</p> <p> </p>
Input data for manuscript "An open-source low-cost sensor for SNR-based GNSS reflectometry: Design and long-term validation towards sea level altimetry"
<p>Input data for Fagundes et al. (2021), "An open-source low-cost sensor for SNR-based GNSS reflectometry: Design and long-term validation towards sea level altimetry", GPS Solutions (in press). <a href="https://www.researchgate.net/publication/341946011">preprint</a></p>
Inputs to calculate the solvation free energies of ECC ions in SPCE water
<p>Scripts and input files for the calculation of the solvation free energies of selected cations with the ECC model. The simulation box contains one cation and 800 water molecules. The ion topologies are from https://bitbucket.org/hseara/ions. Notably, before comparison with experimental values, the electronic solvation free energy contribution must be added to the result [1], as well as the correction due to the use of neutralizing charge density [2].</p> <p>In each folder, ./run.sh creates the folders representing different lambda values in the free energy perturbation approach and performs the respective calculation in each folder. There are a total of 31 windows (11 for electrostatics and 20 for Lennard-Jones). After running the script, the free energy can be extracted by</p> <p>gmx bar -f ?/md.xvg ??/md.xvg -temp 298 -o -b 100</p> <p>The results are reported in DOI: [ADD]</p> <p>[1] DOI: 10.1021/ct9005807</p> <p>[2] DOI: 10.1080/08927022.2015.1121544</p>
Towed chain datasets and input files for simulations used in the manuscript "Increased mixing and turbulence in the wake of offshore wind farm foundations"
<p><strong>Contents</strong></p> <p>1. File S01_S12 Input files for simulations (precursor runs and main runs)</p> <p>2. File S13 Topography file for simulations with monopile</p> <p>2. Data sets ds01 to ds06 (towed chain data collected in May 25, 2015)</p> <p>3. Data sets ds07 to ds14 (towed chain data collected in July 19, 2017)</p> <p>4. Data sets d15 to ds16 (ADCP data collected in May 25, 2015 and July 19, 2017)</p> <p><strong>Introduction </strong></p> <p>This package contains the input parameters used in each of the precursor (S01 - S04) and main runs (S05 - S12) presented in the manuscript “Increased mixing and turbulence in the wake of offshore wind farm foundations”. These input files are found in the PDF file "S01_S12".</p> <p>The main runs, in which the wake of a monopile was simulated (S05, S07, S09, S11), require a topography file, which is a NETCDF-file that has been uploaded separately (S13). All simulations were run using the Parallelized Large-Eddy Simulation Model for atmospheric and oceanic flows (PALM, version 4.0, revision 2504).</p> <p>Further, this package contains the data sets collected using the towed chain in 2015 (ds01-ds06, ds15) and 2017 (ds07-ds14, ds16), which have been uploaded as separate NETCDF-files.</p>
Input parameters, output data, and script to calculate strain and velocity from fault source parameters
<p>This archive contains two data tables, one script, and one dataset to accompany the paper:</p> <p><strong>Strain and velocity across the Great Basin derived from 15-ka fault slip rates: Implications for continuous deformation and seismic hazard in the Walker Lane</strong></p> <p><em>Nadine G. Reitman<sup>1 </sup> and Peter Molnar<sup>1,2</sup></em></p> <p><sup>1</sup>Department of Geological Sciences, University of Colorado Boulder</p> <p><sup>2</sup>Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado Boulder</p> <p> </p> <p>The data tables contain the input source fault parameters (fault strike, dip, rake, length, location, and slip rate) and the contribution to strain calculated for each fault relative to 317 degrees using the associated script. The script uses the methods of Kostrov (1974) and Haines (1982) to calculate strain and velocity across the Great Basin using slip rates reported in the USGS National Seismic Hazard Map (2020 update of the 2014 data, Petersen et al, 2014) and Pérouse & Wernicke (2017). The script is written in Python3 and requires the user to have some knowledge of how to run Python code. The included dataset (hazfaults_clean.p) contains the data to run the script for the USGS fault sources. </p> <p>Please contact nadine.reitman@colorado.edu with questions.</p>
Different enrichment patterns of pedogenic magnetic particles modulated by primary iron-phosphorous input
<p>Data supporting this research are available for people who engage in scientific research. Note that the data can not be used for any commercial activities.</p>
Inputs for calculating properties of molecular oxygen
<p>In [Javanainen <em>et al., </em><em>J. Phys. Chem. B</em> 2017, 121, 3, 518–528], we parametrized models for molecular oxygen and benchmarked a number of existing models. Recently, we noticed a mistake in the calculation of heat of vaporization, and thus reparametrized the models [ADD]. The simulation inputs for the performed benchmarks are provided here.</p> <p>The parameters of the new models are provided in the TOP folder. For each model (noQ, QL, QS), the LIQUID folder contains inputs for the simulation of liquid oxygen. The WATER and HEXADECANE folders contain files for the calculation of the energy of solvation into the corresponding phase. The SCRIPTS folder contains scripts for this purpose, and the workflow goes as follows:</p> <ol> <li>./mkdirs (creates directories)</li> <li>./mk_mdp_1 (creates mdp files for the first set of simulations)</li> <li>./mk_md_1 (creates tpr files for the first set of simulations)</li> <li>(run simulations in serial or parallel)</li> <li>repeat 2&3 with "1" replaced by "2" (the second set of simulations)</li> <li>./calc_dgdl_1 & ./calc_dgdl_2 (integrates for the electrostatic and LJ contributions to free energy)</li> </ol> <p> </p>
Input forcing data for CLM4.5 or CLM5 at Soltis Center in Costa Rica
<p>Input forcing data for CLM4.5 or CLM5 at Soltis Center in Costa Rica</p>
Input and Output Data of SGRIST
<p>Three SCM cases as in the manuscript.</p>
Delft3D input and output files
<p>Supplementary data for:</p> <p>Hepkema et al., Oblique sand ridges in confined tidal channels due to Coriolis and frictional torques (submitted to Ocean Dynamics, 2020)</p> <p>Two .mat (matlab) files with the bathymetric output of the D3D runs. One where the Coriolis effect is taken into account and one where it is not.</p> <p>The zip file contains all the necessary inputfiles to rerun the Delft3D model. </p>
Example CCE worldtube input data
<p>This is an example worldtube file for evaluating the installation and functionality of a Cauchy Characteristic extraction scheme for waveform extraction from finite-radius GR simulation. This file was generated by a SpEC run of an equal-mass non-spinning binary black hole simulation by Mark Scheel. The techniques used to simulate the binary black hole system are similar to those used in <a href="https://arxiv.org/pdf/1904.04831.pdf">Boyle et. al. 2019</a>, in particular the GR simulation techniques published in <a href="https://arxiv.org/abs/gr-qc/0512093">Lindblom et. al. 2006</a>. This is a suitable input file for instance, for SpECTRE or SpEC CCE systems.</p>
Replication package for: The Equilibrium Impact of Agricultural Risk on Intermediate Inputs and Aggregate Productivity
<p>The package contains the necessary code and data to reproduce the figures and tables in Donovan (forthcoming), "The Equilibrium Impact of Agricultural Risk on Intermediate Inputs and Aggregate Productivity," Review of Economic Studies. Detailed instructions on accessing the raw data are available in the README file.</p>
Approximate Majority With Catalytic Inputs (video)
Full video presentation of the paper: Approximate Majority With Catalytic Inputs.<br><br>Appears in Session 3 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020<br><a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>
Data from: Assimilating MODIS data-derived minimum input data set and water stress factors into CERES-Maize model improves regional corn yield predictions
Crop growth models and remote sensing are useful tools for predicting crop growth and yield, but each tool has inherent drawbacks when predicting crop growth and yield at a regional scale. To improve the accuracy and precision of regional corn yield predictions, a simple approach for assimilating Moderate Resolution Imaging Spectroradiometer (MODIS) products into a crop growth model was developed, and regional yield prediction performance was evaluated in a major corn-producing state, Illinois, USA. Corn growth and yield were simulated for each grid using the Crop Environment Resource Synthesis (CERES)-Maize model with minimum inputs comprising planting date, fertilizer amount, genetic coefficients, soil, and weather data. Planting date was estimated using a phenology model with a leaf area duration (LAD)-logistic function that describes the seasonal evolution of MODIS-derived leaf area index (LAI). Genetic coefficients of the corn cultivar were determined to be the genetic coefficients of the maturity group [included in Decision Support System for Agrotechnology Transfer (DSSAT) 4.6], which shows the minimum difference between the maximum LAI derived from the LAD-logistic function and that simulated by the CERES-Maize model. In addition, the daily water stress factors were estimated from the ratio between daily leaf area/weight growth rates estimated from the LAD-logistic function and that simulated by the CERES-Maize model under the rain-fed and auto-irrigation conditions. The additional assimilation of MODIS data-derived water stress factors and LAI under the auto-irrigation condition showed the highest prediction accuracy and precision for the yearly corn yield prediction (R2 is 0.78 and the root mean square error is 0.75 t ha-1). The present strategy for assimilating MODIS data into a crop growth model using minimum inputs was successful for predicting regional yields, and it should be examined for spatial portability to diverse agro-climatic and agro-technology regions.
Multi-regional Input–output Table for the Global Emerging Economies (EMERGING V2.5)
<p><strong>EMERGING V2.5</strong>: This version removes the 27th sector, totaling 133 sectors, compared to EMERGING1.0. It has been optimized and calibrated to improve the intermediate input matrix (Z matrix), trade volumes (imports and exports), and total output for the electricity, transportation, and energy sectors across 245 economies, with a particular focus on small and medium-sized emerging economies.</p> <p><strong>EMERGING CO<sub>2</sub> Inventory</strong>: CO<sub>2</sub> emissions (Mt CO<sub>2</sub>eq) from fossil fuel combustion and energy consumption at the sectoral level in each region are available from the IEA database and CEADs emission inventory data. The EMERGING CO<sub>2</sub> Inventory includes a total of 7 energy types: 1. Coal; 2. Natural gas; 3. Oil products; 4. Crude, NGL, Ref Feeds.; 5. Other; 6. Oil shale & oil sands; 7. Peat & Peat products.</p> <p><strong>Announcements</strong></p> <p>These data are made freely available to the public and the scientific community in the belief that their wide dissemination will lead to greater understanding and new scientific insights. The availability of these data does not constitute publication of the data. The data providers rely on the ethics and integrity of the user to ensure that they receive fair credit for their work. If the data are obtained for potential use in a publication or presentation, we kindly ask you to cite them properly according to the instructions on the website.</p> <p>Queries about the EMERGING database and further collaboration can be addressed to: huojw20@hotmail.com</p>
China's input-output table
<p>The input-output table is classified into more detailed sectors, which can deeply study the various complex interdependence and main structures between industries and products and reveal the chain reaction between various economic activities in the operation of the national economy, so it is an essential means to analyze the intricate causal relationship and development law of an economic system in the process of operation.</p> <p>This data is based on the input-output table the Chinese Bureau of Statistics released. For the convenience of researchers, it is then organized into a dataset.</p>
DEVOLUTION input files and subclone annotation & single cell data.
<p>Related data files for the paper:</p> <p>"Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma by" by Jenny Karlsson et al.</p> <p>https://www.researchsquare.com/article/rs-2104205/v1</p> <ul> <li>DEVOLUTION input segment files.</li> <li>Subclones obtained from DEVOLUTION.</li> <li>Single cell data for patients and PDX models.</li> <li>A manual of how to create phylogenetic trees based on the data.</li> </ul>
The input files and associated data products for "Modeling High Mass X-ray Binaries to Double Neutron Stars through Common Envelope Evolution"
<p>Simulations were made using the version 12115 of the MESA code together with the x86_64-linux-20190830 MESA SDK. "template.zip" provides the MESA inlist files to reproduce our simulations. "CE_1.zip" provides our simulated results for a grid of binary systems with common envelope ejection efficiencies set to be 1.0. Different folders indicate the binary systems with different initial parameters. Inside each folder information can be found for binary properties in the "history.data" file. Each folder also contains the "result.txt" file with the terminal output of the simulation. "CE_3.zip", "CE_0.3.zip" and "CE_0.1.zip" are the same as "CE_1.zip" but with common envelope ejection efficiencies set to be 3.0, 0.3 and 0.1, respectively.</p>
Data from: Getting to the root of organic inputs in groundwaters: stygofaunal plant consumption in a calcrete aquifer
<p>Groundwater environments interact with and support subterranean biota as well as superficial aquatic and terrestrial ecosystems. However, knowledge of subterranean energy flows remains incomplete. Cross-boundary investigations are needed to better understand the trophic structures of groundwater ecosystems and their reliance on carbon inputs from aboveground. In this study we used carbon and nitrogen stable isotope analyses combined with radiocarbon fingerprints to characterise organic flows in groundwater ecosystems. We coupled these data with DNA metabarcoding of the gut contents of consumers to further elucidate organic matter sources and shifts in diet preferences. Samples were collected from the arid zone Sturt Meadows calcrete aquifer under low rainfall (LR) and high rainfall (HR) conditions. Bayesian modelling of Δ<sup>14</sup>C, δ<sup>13</sup>C and δ<sup>15</sup>N data indicated that primary consumers (copepods) incorporated mainly particulate organic carbon (POC) under LR but during HR shifted to root derived material (either exudates or direct root grazing). By contrast, diets of secondary consumers (amphipods) were dominated by root material under both LR and HR. Our DNA metabarcoding-based results indicate that amphipods relied primarily on root inputs from perennial trees (likely <i>Eucalyptus</i> and <i>Callitris</i>) during the dry season (LR). Under HR, diets of both amphipods and copepods also included organic material derived from a broad range of more shallow rooted shrubs, and ephemeral herbs and grasses. Our findings illustrate the complexity of functional linkages between groundwater biota and terrestrial surficial ecosystems in environments where aboveground productivity, diversity and organic matter flux to groundwater are intimately linked to often episodic rainfall.</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.