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31,887 results for “three”
Data file for: Three-Dimensional Electrical Imaging Across the Cona Woka Rift and Yalaxiangbo Dome in Southern Tibetan Plateau
<p>The magnetotellurics data were used to study the lithospheric electrical structure across the Cona Woka rift and Yalaxiangbo dome in the southern Tibetan plateau, conducted by Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Sciences. The data file of CN6.dat was generated by the Matlab code EM3DVP.</p> <p>You are recommended to refer to the Kelbert et al., 2014 paper: https://doi.org/10.1016/j.cageo.2014.01.010 for a brief understanding of the data file formats.</p> <p> </p>
Lattice studies of the Sp(4) gauge theory with two fundamental and three antisymmetric Dirac fermions—data release
<p>This dataset contains the raw data and metadata used to prepare the publication <a href="https://arxiv.org/abs/2202.05516">Lattice studies of the Sp(4) gauge theory with two fundamental and three antisymmetric Dirac fermions</a>. </p> <p>Included are:</p> <ul> <li>The raw log output from the configuration generation, correlation function calculation, and Dirac eigenvalue computation, as well as metadata describing the ensembles used for the mass spectrum calculation, in `raw_data.zip`. These include all numbers used in the publication (aside from fit parameters) in plaintext form.</li> <li>All numbers included in the above logs, restructured into HDF5 format for convenience, in `data.h5`.</li> <li>The fit parameters used to compute the spectrum, including the thermalisation length, and the plateau start and end points, in `fit_params.zip`.</li> <li>The data underlying tables 2–6 of the publication above, in CSV format.</li> </ul> <p>More details can be found in the file README.md.</p> <p>Version history:</p> <ul> <li>v1.1: Replace out_corr_48x24x24x24b6.5mas-1.01mf-0.71 due to a mistake where the wrong version of the measurement code was used.</li> <li>v1.0: Initial release</li> </ul>
Certain rigid maximally mutable Laurent polynomials in three variables
<p>This dataset contains certain rigid maximally mutable Laurent polynomials (rigid MMLPs) in three variables. Rigid MMLPs are defined in reference [1].</p> <p>The Newton polytopes of these Laurent polynomials are three-dimensional canonical Fano polytopes. That is, they are three-dimensional convex polytopes with vertices that are primitive integer vectors and that contain exactly one lattice point, the origin, in their strict interior. See references [2] and [3].</p> <p>Although the rigid MMLPs specified in this dataset have 3-dimensional canonical Fano Newton polytope, this is by no means an exhaustive list of such Laurent polynomials. The dataset contains examples of rigid MMLPs that correspond under mirror symmetry to three-dimensional Q-Fano varieties of particulaly high estimated codimension: see reference [4].</p> <p>The file "rigid_MMLPs.txt" contains key:value records with keys and values as described below, separated by blank lines. Each key:value record determines a rigid MMLP, and there are 130 records in the file. An example record is:</p> <p>canonical3_id: 231730<br> coefficients: [1,1,1,1,1,1,1,1,1,1]<br> exponents: [[-1,-1,-1],[0,1,0],[0,1,1],[1,0,0],[1,0,1],[1,2,2],[2,1,2],[2,1,3],[3,3,5],[4,2,5]]<br> period: [1,0,0,12,24,0,540,2940,2520,33600,327600,693000,2795100,35315280,129909780,354666312,3816572760,20559258720,59957561664,435508321248,2969362219824]<br> ulid: 01G5CBH3F86NRYF0TJ8MYWM41H</p> <p>The keys and values are as follows, where f denotes the Laurent polynomial defined by the key:value record.</p> <p>canonical3_id: an integer, the ID of the Newton polytope of f in reference [3]<br> coefficients: a string of the form "[c1,c2,...,cN]" where c1, c2, ... are integers. These are the coefficients of f.<br> exponents: a string of the form "[[x1,y1,z1],[x2,y2,z2],...,[xN,yN,zN]]" where x1, y1, z1, ..., xN, yN, zN are integers. These are the exponents of f.<br> period: a string of the form "[d0,d1,...,d20]" where d0, d1, ..., d20 are non-negative integers that give the first 21 terms of the period sequence for f.<br> ulid: a string that uniquely identified this entry in the dataset</p> <p>The sequences defined by the keys "coefficients" and "exponents" are parallel to each other. The period sequence for f is defined, for example, in equations 1.2 and 1.3 of reference [1].</p> <p>References</p> <p>[1] Tom Coates, Alexander M. Kasprzyk, Giuseppe Pitton, and Ketil Tveiten. Maximally mutable Laurent polynomials. Proceedings of the Royal Society A 477, no. 2254:20210584, 2021.</p> <p>[2] Alexander M. Kasprzyk. Canonical toric Fano threefolds. Canadian Journal of Mathematics, 62(6):1293–1309, 2010.</p> <p>[3] Alexander M. Kasprzyk. The classification of toric canonical Fano 3-folds. Zenodo, https://doi.org/10.5281/zenodo.5866330, 2010.</p> <p>[4] Liana Heuberger. Q-Fano threefolds and Laurent inversion. Preprint, arXiv:2202.04184, 2022.</p>
Optimal elevated agrivoltaic system design and key performance indicators across Europe based on three crop light levels
<p>Optimal elevated (stilted) agrivoltaic system design (PV coverage ratio) is given on a European gridded level (25km grid and NUTS3 regions) based on three light levels: shade-loving crops (daily light integral (DLI) of 12 mol/m²day), shade-tolerant crops (DLI of 12 mol/m²day) and shade-intolerant crops (DLI of 25 mol/m²day)</p> <p>Estimations of other performance indicators are given: power capacity (kWp/ha), energy production (MWh/ha), levelized cost of electricity (€/MWh) and land equivalent ratio (LER -).</p> <p>The assumptions and methodology of this dataset can be found in the article "Geospatial assessment of elevated agrivoltaics on arable land in Europe to highlight the implications on design, land use and economic level."</p> <p>Interactive maps can be found on https://iiw.kuleuven.be/apps/agrivoltaics/maps.html</p>
Annotation and Orthofinder results for three Mytilus species genomes.
<p>Annotations and Orthofinder results for three Mytilus species genomes: accessions JAKGDF000000000 (MgalMED), JAKGDG000000000 (MeduEUS), and JAKGDH000000000 (MeduEUN).</p>
Three-dimensional building and mobility infrastructure of the CONUS
<p>Humanity's role in changing the face of the earth is a long-standing concern, as is the human domination of ecosystems. Geologists are debating the introduction of a new geological epoch, the 'anthropocene', as humans are 'overwhelming the great forces of nature'. In this context, the accumulation of artefacts, i.e., human-made physical objects, is a pervasive phenomenon. Variously dubbed 'manufactured capital', 'technomass', 'human-made mass', 'in-use stocks' or 'socioeconomic material stocks', they have become a major focus of sustainability sciences in the last decade. Globally, the mass of socioeconomic material stocks now exceeds 10e14 kg, which is roughly equal to the dry-matter equivalent of all biomass on earth. It is doubling roughly every 20 years, almost perfectly in line with 'real' (i.e. inflation-adjusted) GDP. In terms of mass, buildings and infrastructures (here collectively called 'built structures') represent the overwhelming majority of all socioeconomic material stocks.</p><p>This dataset features intermediate mapping results for estimating material stocks in the CONUS (see related identifiers) on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), Microsoft building footprints, NLCD Impervious data, and crowd-sourced geodata (OSM). These data may also be useful on their own.</p><p><strong>Provided layers @10m resolution</strong><br>- Building height<br>- Building type<br>- Building area<br>- Impervious fraction<br>- street, and rail area<br>- Building and street climate zones<br>- County zones<br>- State masks<br>- EQUI7 correction factors</p><p><strong>Spatial extent</strong><br>This dataset covers the whole CONUS. </p><p><strong>Temporal extent</strong><br>The maps are representative for ca. 2018.</p><p><strong>Data format</strong><br>The data are organized in 100km x 100km tiles (EQUI7 grid), and mosaics are provided.</p><p><strong>Further information</strong><br>For further information, please see the main publication.<br>A web-visualization of the resulting dataset is available <a href="https://ows.geo.hu-berlin.de/webviewer/us-stocks/">here</a>.<br>Visit our <a href="https://boku.ac.at/understanding-the-role-of-material-stock-patterns-for-the-transformation-to-a-sustainable-society-mat-stocks">website</a> to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.</p><p><strong>Publication</strong><br>D. Frantz, F. Schug, D. Wiedenhofer, A. Baumgart, D. Virág, S. Cooper, C. Gómez-Medina, F. Lehmann, T. Udelhoven, S. van der Linden, P. Hostert, and H. Haberl (2023): Unveiling patterns in human dominated landscapes through mapping the mass of US built structures. <i>Nature Communications</i> <strong>14</strong>, 8014. <a href="https://doi.org/10.1038/s41467-023-43755-5">https://doi.org/10.1038/s41467-023-43755-5</a></p><p><strong>Funding</strong><br>This research was primarly funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). </p><p><strong>Acknowledgments</strong><br>We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; USGS for the National Land Cover Database; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on <a href="https://eodc.eu/">EODC</a> - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC, and Wolfgang Wagner for granting access to preprocessed Sentinel-1 data.</p>
Data for "Three-Dimensional Broadband Interferometric Mapping and Polarization (BIMAP-3D) Observations of Lightning Discharge Processes" by Shao et al.
<p>Data set for manuscript of “Three-Dimensional Broadband Interferometric Mapping and Polarization (BIMAP-3D) Observations of Lightning Discharge Processes” by Shao et al. submitted to Journal of Geophysical Research-atmosphere</p>
Statistical analysis for: Mode I fracture of beech-adhesive bondline at three different temperatures
<p>This dataset collects a raw dataset and a processed dataset derived from the raw dataset. There is a document containing the analytical code for statistical analysis of the processed dataset in .Rmd format and .html format. <br> <br> The study examined some aspects of mechanical performance of solid wood composites. We were interested in certain properties of solid wood composites made using different adhesives with different grain orientations at the bondline, then treated at different temperatures prior to testing. </p> <p>Performance was tested by assessing fracture energy and critical fracture energy, lap shear strength, and compression strength of the composites. This document concerns only the fracture properties, which are the focus of the related paper. </p> <p>Notes: </p> <p>* the raw data is provided in this upload, but the processing is not addressed here. <br> * the authors of this document are a subset of the authors of the related paper.<br> * this document and the related data files were uploaded at the time of submission for review. An update providing the doi of the related paper will be provided when it is available.</p>
Capillary networks and follicular marginal zones in the human spleen. Three-dimensional models based on immunostained serial sections - Supplementary videos
<p>We regard ROIs, regions of interest, from a human spleen specimen in single (four ROIs) and double (three ROIs) staining. The ROIs with the same number correspond to each other. Below we map references in manuscript (<strong>bold</strong>) to file names in this repository (<em>italics</em>).</p> <ul> <li>File <em>colour-deconvolution.png</em> – settings of colour deconvolution in Fiji for double staining.</li> <li>File <em>comments to videos.odt</em> – a commentary to S3[c,d] Video.</li> <li><strong>S1a,b Video to S3a,b Video</strong>: files <em>video_[1,2,3][a,b].mov</em> – sequence of section with single (a) and double (b) staining for ROI 1 to 3 in the main text.</li> <li><strong>S1c Video to S3c Video</strong>: files <em>video_[1,2,3]c.mov</em> – video of the reconstruction, single staining, special blood vessels highlighted.</li> <li><strong>S1d Video to S4d Video</strong>: files <em>video_[1,2,3]d.mov</em> – an overview video of the reconstruction, double staining.</li> <li><strong>S4 Video</strong>: file <em>video_4.mov</em> – quality control in virtual reality.</li> <li><strong>S1 Figure</strong>: a supplementary figure <em>fig_S1.tiff</em> and its caption <em>fig_S1_legend.odt</em></li> <li><strong>S2 Figure</strong>: a supplementary figure <em>fig_S2.tiff</em> and its caption <em>fig_S2_legend.odt</em></li> </ul> <p>This data corresponds to the publication "Capillary networks and follicular marginal zones in the human spleen. Three-dimensional models based on immunostained serial sections" by B. S. Steiniger, C. Ulrich, M. Berthold, M. Guthe, and O. Lobachev, 2017.</p>
Data to Three-Dimensional Binocular Eye-Hand Coordination in Normal Vision and with Simulated Visual Impairment
<p>This record contains experimental and analysis scripts (written in Matlab) as well as raw and processed data to reproduce the results shown in:</p> <p>Maiello, G., Kwon, M. & Bex, P.J. (2018) Three-dimensional binocular eye--hand coordination in normal vision and with simulated visual impairment. <em>Experimental Brain Research</em>. https://doi.org/10.1007/s00221-017-5160-8</p>
Three-dimensional Reconstructions and Quantitative Indicators for colloidal particles in Dry and Liquid Conditions in Scanning Transmission Electron Microscope (STEM)
<p>This dataset accompanies the research presented in the paper:</p> <div>Esteban, D.A., Wang, D., Kadu, A., Olluyn, N., Iglesias, A.S., Perez, A.G., Casablanca, J.G., Nicolopoulos, S., Liz-Marzán, L.M. and Bals, S., 2023. Liquid phase fast electron tomography unravels the true 3D structure of colloidal assemblies. <em>arXiv preprint arXiv:2311.05309</em>. [<a href="https://arxiv.org/pdf/2311.05309" target="_blank" rel="noopener">link</a>]</div> <p>It provides a comprehensive collection of three-dimensional reconstructions and quantitative descriptors for small colloidal particles. These gold nanoparticles are arranged in tetrahedral and other intricate geometries under both dry and liquid conditions. The dataset contains 3D reconstructions and quantitative indicators such as centroids, volumes, surface areas, solidity measures, and principal axis lengths for assemblies with 4, 5, and 6 particles. </p> <p>The dataset includes: <code>N4_dry_dart.rec</code> and <code>N4_liquid_dart.rec</code> for the 3D reconstructions of an assembly with 4 particles in dry and liquid conditions respectively; <code>N4_quant_descriptors_dry.mat</code> and <code>N4_quant_descriptors_liquid.mat</code> providing quantitative descriptors for these conditions. Similar files are provided for assemblies with 5 and 6 particles, such as <code>N5_dry_dart.rec</code>, <code>N5_liquid_dart.rec</code>, <code>N5_quant_descriptors_dry.mat</code>, <code>N5_quant_descriptors_liquid.mat</code>, and the corresponding files for N6. </p> <p>This dataset can be used to study the structural dynamics of nanoparticle assemblies and studies in colloidal chemistry, materials science, and nanotechnology. The <code>.rec</code> files can be visualized using volume rendering software (e.g. Amira or Avizo), while the <code>.mat</code> files contain structured data for analysis in MATLAB. The supporting code and scripts for this dataset are available on the GitHub repository: <a href="https://github.com/ajinkyakadu/LiquidET_NatComm2024" target="_new" rel="noreferrer">https://github.com/ajinkyakadu/LiquidET_NatComm2024</a>. </p>
Three-Dimensional Characterization of Deformation-induced Damage in Dual Phase Steel using Deep Learning
<p>High performance sheet metals with a multi-phase microstructure suffer from deformation induced damage formation during forming in the constituent phases but importantly also where these intersect. To capture damage in terms of the physical processes in three dimensions (3D) and its stochastic nature during deformation, two challenges remain to be tackled: First, bridging high resolution analysis towards large scales to consider statistical data and, second, characterising in 3D with a resolution appropriate for sub-micron sized voids at a large scale. Here, we present how this can be achieved using panoramic scanning electron microscopy (SEM), metallographic serial sectioning, and deep-learning assisted automatic image analysis. This brings together the 3D evolution of active damage mechanisms with volumetric and environmental information for thousands of individual damage sites. We also assess potential surface preparation artefacts in 2D analyses. Overall, we find that for the material considered here, a dual phase (DP800) steel, martensite cracking is the dominant but not sole origin of deformation induced damage and that for a quantitative comparison of damage density, metallographic preparation can induce additional surface damage density far exceeding what is commonly induced between uniaxial straining steps.</p> <p>https://doi.org/10.1016/j.matdes.2023.112108</p>
Measurement data of a three-phase grid-side converter with a grid-forming synchronverter-based control method with current limitation
<p>The data set was recorded for a publication currently undergoing the submission process. The published data correspond to the data presented in the figures. The first column represents the time vector. All other columns are linked to the corresponding scenario by an identifier in the column name. The column name also contains the name of the recorded signal and the associated unit. The naming convention is <identifier_to_figure>_<recorded_signal>_<unit>.</p>
Symbol Representation of the Three Gluon Form Factor in N=4 Planar Super Yang-Mills Theory
<p>Datasets describing the symbol of the three-gluon form factor in N=4 planar super Yang-Mills theory, generated using the amplitude bootstrap approach. The file "EZ_symb_new_norm" contains the symbol form of this quantity at 1 through 5 loops of precision, while the file "EZ6_symb_new_norm" contains the symbol at 6 loops. The file "EZ_symb_quad_new_norm" contains the symbol at 1 through 6 loops in compressed "quad" form, where the final-entry conditions described in (https://arxiv.org/pdf/2204.11901) are used to dramatically reduce the total number of terms in the symbol. The file "EZ7_symb_quad_new_norm" contains the symbol at 7 loops in the "quad" form. </p> <p>The tag “new_norm” refers to the fact that in the symbols given here, the letters a,b,c are defined by a = sqrt(u/(v*w)), b = sqrt(v/(w*u)), c = sqrt(w/(u*v)), as in arXiv:2405.06107, in order to make all coefficients integers. In contrast, in arXiv:2204.11901, the letters a,b,c were defined by a = u/(v*w), b = v/(w*u), c = w/(u*v).</p> <p>In addition to the funding sources listed, MW was supported by research grant 00025445 from Villum Fonden.</p>
Supplementary data to "Three scenarios for coal power in Vietnam"
<p>This dataset includes the history of coal power generation in Vietnam, listing generation units capacity, creation date, and current status up to March 2019.</p> <p>It defines three scenarios for the future. “Blazing up” corresponds to the power development plan 7 revised and updated as of March 2019. “Closed window” tells what we think would happen under pure market forces. “Coal peak” tells what could happen if the State continues to steer the electricity system into the energy transition, decisively and without imposing high costs to stakeholders.</p> <p>Corresponds to Table 2 and 3 in the manuscript.</p> <p>#VIETSE</p>
Nanolaminography dataset: Three-dimensional imaging of integrated circuits with a macro to nanoscale zoom
<p>Here we present a ptychographic X-ray laminography (PyXL) dataset. It is a new approach for nano-imaging that combines a coherent diffractive imaging technique called ptychography with laminography, which is a generalization of tomography. This allows achieving sub-20 nm resolution over large sample volumes. </p> <p>Non-destructive three-dimensional imaging over large volumes with nano-scale resolution is a challenge faced in many fields, perhaps most acutely in mapping the natural neural connectome and artificial silicon-based integrated circuits. For the latter, such inspection is of interest for quality control and security acquiring particular importance due to the delocalized nature of the chain connecting chip design, manufacture and use. A hierarchy of probes are used to image at length scales from that of the entire chip (millimeters) to those of individual features (nanometers) of the underlying transistors, starting with optical microscopy and finishing with transmission electron microscopy on thin slices prepared using a focused ion beam. What has been missing until now is a single technique yielding a three-dimensional image of the entire chip volume with zooming capability to produce high-resolution images of arbitrarily chosen sub-regions, including virtual delayering.</p> <p>The related publication can be accessed via ShareIt <a href="https://mail.ethz.ch/owa/redir.aspx?C=NzB9-v6wS5uDOPXWL0cW_Vu4ys_MIpbvUqKcmezLt5AHOlhZD1DXCA..&URL=https%3a%2f%2frdcu.be%2fbTudW">https://rdcu.be/bTudW</a></p>
Generation of synthetic, realistic vehicular traces for three access highways of Quito using SUMO
<p>These files present the maps of three access highways of Quito simulated in SUMO. The contributions are.</p> <ul> <li>Careful validation of the imported maps from OpenStreetMaps (imported in July 2019) including time intervals in traffic lights, location of traffic lights, suppression on non-existing junctions, edges, etc.</li> <li>Simulation of realistic number of vehicles for each road considerings the statistics from traffic authority of Quito</li> <li>Configuration of the 5 generation tools provided in the SUMO package. We used all the meaningful configuration for each tool to obtain synthetic realistic vehicular traces</li> </ul>
Three-dimensional subnanoscale imaging of unit cell doubling due to octahedral tilting and cation modulation in strained perovskite thin films
<p>Transmission electron microscopy data used in the journal publication <a href="https://doi.org/10.1103/PhysRevMaterials.3.063605">"Three-dimensional subnanoscale imaging of unit cell doubling due to octahedraltilting and cation modulation in strained perovskite thin films"</a></p> <p><strong>Data files</strong></p> <p>There are two data types:</p> <ul> <li>Scanning TEM (STEM) diffraction patterns acquired with a Medipix3 detector (Merlin): m004_LSMO_LFO_STO_medipix.hdf5 <ul> <li>Acquired on a probe corrected Jeol ARM200CF</li> <li>Acceleration voltage: 200 kV</li> <li>Convergence semi-angle: 20.4 mrad (calibrated using the SrTiO<sub>3</sub> substrate HOLZ ring)</li> <li>Detector calibration: 1.357 mrad per pixel (calibrated using the SrTiO<sub>3</sub> substrate HOLZ ring)</li> </ul> </li> <li>Atomic resolution STEM data, both annular dark field (ADF) and annular bright field (ABF), which were acquired simultaneously: s007_ADF.hdf5, s007_ABF.hdf5</li> </ul> <p>The data can be loaded in python using h5py.</p> <p>For the Medipix3 data:</p> <pre><code class="language-python">import h5py f = h5py.File('m004_LSMO_LFO_STO_medipix.hdf5', mode='r') data = f['fpd_expt/fpd_data/data'] data_subset = data[0:16, 0:16, :, :]</code></pre> <p>For the STEM-ADF or STEM-ABF data:</p> <pre><code class="language-python">import h5py f = h5py.File('s007_ADF.hdf5', mode='r') data = f['Experiments/__unnamed__/data']</code></pre> <p>Exploring the Medipix3 dataset lazily, i.e. without loading the whole dataset into memory at the same time. Using pixStem:</p> <pre><code class="language-python">import pixstem.api as ps s = ps.load_ps_signal("003_stripe1.hdf5", lazy=True) s.plot()</code></pre> <p>Loading the STEM-ADF or STEM-ABF data using HyperSpy, which automatically loads the probe scaling:</p> <pre><code class="language-python">import hyperspy.api as hs s = hs.load("s007_ADF.hdf5") s.plot()</code></pre> <p><br> <strong>Processing files</strong></p> <p>All the TEM data has been processed using python scripts, which is named based on the type of processing:</p> <ul> <li>d00N_...: Medipix3 data processing</li> <li>a00N_...: Atomic resolution STEM-ADF and STEM-ABF processing using Atomap</li> </ul> <p>The scripts generate intermediate files, which are saved in folders with the same prefix as the scripts. So the d001_... script makes a folder named d001_... . These intermediate files are included here as zip-files, since Zenodo doesn't support folder structures.</p> <p>The python libraries required to run the scripts are listed in requirements.txt. Newer versions of the libraries will most likely also work.</p> <p>To setup the python environment with the required libraries, and run all the scripts:</p> <pre><code class="language-bash">pip3 install -r requirements.txt python3 run_all_scripts.py</code></pre> <p> </p>
Homology modelling, molecular docking and molecular dynamics simulations of wild type and mutant human CYP2J2 with three polyunsaturated fatty acids
<p>This is the "parent" repository for the Data Note : "­Molecular dynamics simulations of the interaction of wild type and mutant human CYP2J2 with polyunsaturated fatty acids" by Abelak, Bishop-Bailey and Nobeli.</p> <p>It contains a document (<strong>Abelak_etal_Methods.pdf</strong>) describing the methods used to produce the data here and the data in all repositories supplementing it.</p> <p>It also contains a shell script (<strong>create_sim4_repeats.sh</strong>) that is typical of those used to set up the molecular dynamics simulations in the repositories supplementing this one.</p> <p>Finally, it contains the results of the homology modelling and docking simulations that formed the starting points for the molecular dynamics simulations in this study.</p> <p>Description of files in this dataset:</p> <p><strong>C2J2_min3_mod_noH.pdb</strong> : Homology model of the wild type CYP2J2 built from an alignment of templates with PDB ids: 1SUO, 2P85, 3EBS and 1Z10.</p> <p><strong>docking_wild_type_C2J2.zip</strong> : Nine docked poses of arachidonic acid docked to the homology model of the wild type CYP2J2.</p> <p>Details of how this data was produced is available in the Abelak_etal_Methods.docx document.</p>
Data from "Predicting Global Ground Geoelectric Field With Coupled Geospace and Three‐Dimensional Geomagnetic Induction Models"
<p>Data presented in http://dx.doi.org/10.1029/2018SW001859 excluding the first and last hours which were determined to contain partially unphysical results and probably should not be used.</p> <p>Each file contains the external ground magnetic field components calculated on 5x5 degree geographic grid and the results of induction modeling using 1d and 3d ground conductivity models: total ground magnetic field components, horizontal ground electric field components. Times are given in UTC.</p> <p>To reproduce Figure 8 in above reference use:</p> <p> </p> <p>import numpy<br> import matplotlib.pyplot<br> data = numpy.load('2006-12-14T22:58:00.npz') # or 2006-12-14T22_58_00.npz<br> matplotlib.pyplot.colorbar(<br> matplotlib.pyplot.imshow(<br> data['B_3D_north'],<br> cmap = matplotlib.pyplot.get_cmap('bwr'),<br> vmin = -800, vmax = 800,<br> extent = (-180, 180, -90, 90)<br> ),<br> format = '%.0f', fraction = 0.02, pad = 0.03<br> )<br> matplotlib.pyplot.show()</p> <p> </p> <p>and substitute B_3D_east, E_3D_north, etc. for the different panels.</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.