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5,805 results for “Data model”
Raw data for bodyweights of piglets used to establish the Mainz piglet model of oesophageal strictures
<p>Piglet bodyweight data to reproduce statistical analyses used in our model description</p>
Data_Sheet_2_Management of Hypercholesterolemia Through Dietary ß-glucans–Insights From a Zebrafish Model
<p>Supplementary tables for Management of Hypercholesterolemia Through Dietary ß-glucans–Insights From a Zebrafish Model</p>
Data_Sheet_1_Management of Hypercholesterolemia Through Dietary ß-glucans–Insights From a Zebrafish Model
<p>Supplementary figures for Management of Hypercholesterolemia Through Dietary ß-glucans–Insights From a Zebrafish Model</p>
Unified Model Atmospheric Forecast Model Data for Machine Learning Cloud-Base Height
<p>Unified Model data, in pp format, for machine learning of cloud-base height based on profiles of temperature, humidity, pressure and cloud fraction. The model configuration is Global Atmosphere 6, running with a resolution of N320 (which is coarser than what was running operationally at the time). Each simulation is run for 24 hours, re-initialising every 24 hours. A separate data file is provided every 6 hours. Data points are on a latitude-longitude grid in the horizontal and on a stretched grid in the vertical. See https://gmd.copernicus.org/articles/10/1487/2017/ for details of the model configuration.</p> <p>Data from January 2016 is for training.</p> <p>Data from July 2017 is for development/validation</p> <p>Data from October 2017 is for final testing.</p> <p> </p>
The prediction data analyzed in the article: "An improved regional coupled modeling system for Arctic sea ice simulation and prediction: a case study for 2018"
<p>The outputs of seasonal predictions with the Coupled Arctic Prediction System version 1 analyzed in the article, "An improved regional coupled modeling system for Arctic sea ice simulation and prediction: a case study for 2018", including:</p> <p>Sea ice concentration (SIC)</p> <p>Sea ice thickness (SIT)</p> <p>Sea surface temperature (SST)</p> <p>Ice mass budget diagnostics</p> <p>Accumulated downward shortwave radiation at the surface (ASWDN)</p> <p>Accumulated downward longwave radiation at the surface (ALWDN)</p> <p>Near surface air temperature (T2) </p> <p>Temperature and salinity profile of the upper ocean under sea ice </p>
Models and data in support of "Probing the southern African lithosphere with magnetotellurics" parts I+II
<p>These directories contain the original model and data files for the publications "Probing the southern African lithosphere with magnetotellurics, Part I, model construction" and "Probing the southern African lithosphere with magnetotellurics, Part II, linking electrical conductivity, composition and tectonomagmatic evolution". The two codes used to generate these results are</p> <p>jif3D (Moorkamp et al. 2011) available via subversion at https://svn.code.sf.net/p/jif3d/jif3dsvn/trunk/jif3D and<br> ModEM (Kelbert et al. 2014) (https://sites.google.com/site/modularem/download)</p> <p>All scripts to produce plots are written in Python (Version 3) and require a working Python environment (e.g. Anaconda under Windows https://www.anaconda.com/). Two helper classes are contained in the files mtclass.py (for reading data files) and mtmodel.py (for reading models). These require the packages<br> netcdf4, mtpy, rasterio, matplotlib, numpy, geopandas, cartopy and possibly a few others. If you get error messages related to missing packages, the typical solution is to call "conda install packagename" (Windows) or "pip3 install packagename".</p> <p>We include 3 main Python scripts:</p> <p>PlotHorizontalSlices.py plots horizontal slices through the inversion models similar to Figures 8-11 in part I. However, you get all slices from the surface to the bottom of the model domain. The output is a single PDF called HorSlices.pdf<br> PlotMisfit.py produces 5 different PDF files. Each one shows comparisons between observed and predicted data for all sites used in each inversion.<br> PlotGeoTiff.py produces horizontal slices through the models in GeoTiff format for use in GIS programs or Google Earth. The output files are large (total 1 GB per model), therefore it is currently set to only produce output for one model (jif3D with maximum data). This can be changed by using other filenames (see PlotHorizontalSlices.py).</p> <p>These scripts are also meant as a basis for other scripts for new analyses of these results. All material here is provided under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license (https://creativecommons.org/licenses/by-sa/4.0/).</p> <p> </p> <p> </p> <p>References</p> <p>Moorkamp, M., Heincke, B., Jegen, M., Roberts, A. W., & Hobbs, R. W. (2011). A framework for 3-D joint inversion of MT, gravity and seismic refraction data. Geophysical Journal International, 184(1), 477-493.<br> Kelbert, A., Meqbel, N., Egbert, G. D., & Tandon, K. (2014). ModEM: A modular system for inversion of electromagnetic geophysical data. Computers & Geosciences, 66, 40-53.</p>
Data in "Impact of microstructure on solar radiation transfer within sea ice during summer in the Arctic: A model sensitivity study"
<p>The files contain the data of results in the paper "Impact of microstructure on solar radiation transfer within sea ice during summer in the Arctic: A model sensitivity study".</p>
Patient breast MRI images and computational breast phantom data for research in patient-derived realistic breast modelling
<p>The data is comprised of two parts: 1) patient DICOM MRI images and 2) 3D matrix of a computational breast phantom.</p> <ol> <li>The DICOM images are anonymised patient breast MRI images of a female patient diagnosed with invasive ductal carcinoma. The obtaining of the patients’ DICOM images is approved by the Ethics Committee of Medical University of Varna. The acquisition was performed with GE Signa HDxt MRI scanner. The images are from a T1-weigthed Axial multi-phase VIBRANT (3-phase) sequence and with voxel size of 0.7 mm x 0.7 mm x 0.8 mm. Contrast agent is present. The image set can be opened with any standard DICOM reader.</li> <li>The computational breast phantom is derived from the above mentioned dataset. The phantom is in the form of a 3D matrix saved as a MATLAB data file (.mat file). Each voxel has an assigned Hounsfield Unit value depending on its classification: air = 0, adipose tissue = -152, glandular tissue = 42, tumour = 64, skin = 108. The data file can be opened with MATLAB or Octave.</li> </ol>
CONTINUUM HYDROLOGICAL MODEL SAMPLE DATA FOR WRF 24 OCTOBER 2021 (APOLLO MEDICANE CASE)
<p>CONTINUUM HYDROLOGICAL MODEL SAMPLE DATA FOR WRF 24 OCTOBER 2021 (APOLLO MEDICANE CASE). Data are ready for publication on MyDewetra platform</p>
Global Socio-Economic and Environmental data for PyPSA-Earth: An Open Optimisation Model of the Earth Energy System.
<p><strong>PyPSA-Earth </strong>is an open model dataset of the global power system at different network levels that cover our Earth. The African model can be built using the code provided at <a href="https://github.com/pypsa-meets-africa/pypsa-africa">https://github.com/pypsa-meets-africa/pypsa-africa</a>. Other regions follow soon under the same code base.</p> <p>Since the GitHub codebase is not suited for handling large changing files, we provide here separate <strong>data bundles and cutouts</strong> to be downloaded and extracted as noted in the <a href="https://pypsa-meets-africa.readthedocs.io/en/latest/index.html">documentation</a></p> <p>The below-provided<strong> data files </strong>contain various open data for improving energy system modelling decisions. A thorough description with license restrictions will follow soon.</p>
Laboratory evidence supporting a mechanical model describing the dynamic formation of fault damage asymmetry (data)
<p>Data from the paper: Laboratory evidence supporting a mechanical model describing the dynamic formation of fault damage asymmetry</p> <p>This document includes the after-analysis data, where, the variable "Log2by3M" for the relative magnitude of AE events in the catalog, "M" for the coordinates of sensors, "Mechanical" for the raw mechanical loading information before synchronization, "Notch" for the coordinate of the notch on the beam, "QuaLoc" for the source location and time. </p>
Modelling and Enforcing Access Control Requirements for Smart Contracts - Data Set
<p>This data set contains all artifacts for the master thesis of Jan-Philipp Töberg at the Karlsruher Institute of Technology. This includes the Eclipse project for the metamodel and the generator, the extension of the Slither framework and the use case instances employed during the evaluation. Additionally, extensive instructions regarding the installation and usage are provided.</p>
Supplemental Data for "Embryonic Exposure to Tryptophan Yields Bullying Victimization via Reprogramming the Microbiota-Gut-Brain Axis in a Chicken Model"
<p>This is data set associated with an article "Embryonic Exposure to Tryptophan Yields Bullying Victimization via Reprogramming the Microbiota-Gut-Brain Axis in a Chicken Model" by Xiaohong Huang, Jiaying Hu, Haining Peng, and Heng-wei Cheng, including Supplemental Table S1, S2, S3, S4, S5, S6.</p>
Haptic Zoom: An interaction model for desktop haptic devices with limited workspace - Evaluation data
<p>Raw data collected in the evaluation of the new interaction technique for force feedback desktop haptic devices called Haptic Zoom.<br><br></p> <p>Gutiérrez-Fernández, A., Fernández-Llamas, C., Esteban, G. & Conde, Miguel A. (2023). Haptic Zoom: An Interaction Model for Desktop Haptic Devices with Limited Workspace. <em>International Journal of Human–Computer Interaction, 39</em>(4), 851-862. <a href="https://doi.org/10.1080/10447318.2022.2049140">https://doi.org/10.1080/10447318.2022.2049140</a></p>
Source molecular simulation data for calculating energy and friction profiles and permeability coefficients through model lipid membranes
<p>Energy files from GROMACS molecular dynamics simulations with enhanced free energy sampling contain time-dependent evolution of the free energy profiles and friction profiles (and other energies and simulation properties) that were used for calculating permeability coefficients in the publication https://www.biorxiv.org/content/10.1101/2021.07.16.452599v1</p> <p>Simulation system contains a lipid POPC or DPPC bilayer with a varying amount of cholesterol (specified as mol% in the file name). Hydrophobic level of the permeating particle is specified as "level-I", "level-II" etc. When unspecified in the file name, the particle is hydrophobic level "III". Lipids D-C14-PC denote PC lipids with both tails monounsaturated of length 14 carbon atoms. DOPC is equivalent to D-C18-PC. (Detailed description in the publication)</p> <p>Adaptive Weighted Histogram (AWH) method was used to sample the free energy profile of translocating small molecule through the lipid bilayer.</p> <p>GROMACS tool `gmx awh` reads the files and provides the described profiles.</p> <p>Files were generated by GROMACS `mdrun` simulation engine version 2019.3.</p> <p> </p> <p>Coarse-grained MARTINI 3.0 model was used for modeling the biomolecular interactions.</p> <p>Scripts to perform the simulations and the files with initial configurations and simulation settings are stored in a public GitHub repository depozited on Zenodo.org: <a href="https://doi.org/10.5281/zenodo.5082249">https://doi.org/10.5281/zenodo.5082249</a>.</p> <p> </p> <p>Abraham, M. J. et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2, 19–25 (2015).</p> <p>Lindahl, V., Lidmar, J. & Hess, B. Accelerated weight histogram method for exploring free energy landscapes. J. Chem. Phys. 141, 044110 (2014).</p> <p>Souza, P. C. T. et al. Martini 3: a general purpose force field for coarse-grained molecular dynamics. Nat. Methods 18, 382–388 (2021).</p> <p>Melcr, J. Git repository with analysis scripts for MD simulations of permeability through lipid membranes. (2021) doi:<a href="https://doi.org/10.5281/zenodo.5082249">https://doi.org/10.5281/zenodo.5082249</a>.</p>
HARMONIE-AROME model data (cy40REF and cy40NEW) and observations for December 2018
<p>File kmds_202812 contains the observations at weather stations (following international code) that are used for Figs. 19 and 20 in: Model development in practice: a comprehensive update to the boundary layer schemes in HARMONIE-AROME cycle 40, Wim C. de Rooy et al. 2022, Geosc. Mod. Dev.</p> <p>Similarly, files vlfd* contain the model data (cy40REF and cy40NEW in the file name refer to the corresponding model version) used for Figs 19 and 20, where the relevant parameters are:<br> FI 0: Geopotential station height<br> NN 0: Total cloud cover<br> DD 0: Wind direction (°)<br> FF 0: Wind speed<br> TT 0: 2-Meter Temperature<br> RH 0: 2-Meter Relative Humidity<br> PS 0: Mean Sea Level Pressure<br> PE 15: Total precipitation?<br> QQ 0: 2-m Specific Humidity<br> VI 0: Visibility<br> N75 0: Cloud cover below 7500 m<br> CH 0: Cloud base height<br> LC 0: Low cloud cover</p>
Processed FDG-PET data from: A computational model of neurodegeneration in Alzheimer's disease
<p>Disruption of mental functions in Alzheimer's disease (AD) and related disorders is accompanied by selective degeneration of brain regions. These regions comprise large-scale ensembles of cells organized into systems for mental functioning, however the relationship between clinical symptoms of dementia, patterns of neurodegeneration, and functional systems is not clear. We developed a model of the association between dementia symptoms and degenerative brain anatomy using F18-fluorodeoxyglucose (FDG) PET and dimensionality reduction techniques patients with AD. This data and code package contains preprocessed FDG-PET images from 423 subjects across the Alzheimer's disease spectrum and the MATLAB code to produce eigenbrains from this data.</p>
An empirical model of the dayside Martian ionosphere based on the radio occultation data from MGS, MEX, and MAVEN
<p>This empirical model is developed from the radio occultation data to reconstruct the dayside Martian ionosphere. The observations include the measurements from MGS, MEX, and MAVEN. Based on PCA and optimized regression, this model well reproduces the peak electron density and altitude in observations.</p>
Raw data to "Opioid sequestration by intravenous lipid emulsion – comparison of lipophilicity in a cell-free system and cellular model"
<p>Data that resulted from the conduction of the in vitro part of the project: Intravenous lipid emulsions as a treatment in acute opioid poisoning - pharmacokinetic and pharmacodynamic evaluation in the rabbit model. It served as raw data for the publication Opioid sequestration by intravenous lipid emulsion – comparison of lipophilicity in a cell-free system and cellular model (draft title). </p>
The model data of Potential Impact of Spring Thermal Forcing over the Tibetan Plateau on the Following Winter El Niño–Southern Oscillation
<p>This is the model data of "Potential Impact of Spring Thermal Forcing over the Tibetan Plateau on the Following Winter El Niño–Southern Oscillation". The data includes the last 20 years data of control run (CTRL), the 20 years data of TP–T experiment, and the wave activity flux difference between ensemble means of TP–T and CTRL. 2D is two dimensions. 3D is three dimensions.</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.