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478 results for “3D data”
General-Relativistic Hydrodynamics Simulation of a Neutron Star — Sub-Solar-Mass Black Hole Merger - 3D Ejecta Data
<p>This dataset contains the 3D output for NSbh_R2 run at refinement level l=1 and simulation time t=7950 (t=39.16 ms).</p> <p>Data: Swami Vivekanandji Chaurasia (Stockholm University), Data release packaging: Ivan Markin (University of Potsdam);</p> <p>Simulations for the project have been performed on the national supercomputer HPE Apollo Hawk at the High Performance Computing (HPC) Center Stuttgart (HLRS) under the grant number GWanalysis/44189, on the GCS Supercomputer SuperMUC NG at the Leibniz Supercomputing Centre (LRZ) [project pn29ba], and on the HPC systems Lise/Emmy of the North German Supercomputing Alliance (HLRN) [project bbp00049] for the final production runs. The particular simulation has been run on HLRN.</p>
Data and statistical analysis scripts for manuscript on pennycress roots & response to nitrate using 3D gel system
<p>Data and statistical analysis scripts for manuscript on pennycress roots & response to nitrate using 3Dgel system</p> <blockquote> <p><strong>A temporal analysis and response to nitrate availability of 3D root system architecture in diverse pennycress (<em>Thlaspi arvense</em> L.) accessions</strong> - [<a href="https://doi.org/10.3389/fpls.2023.1145389">https://doi.org/10.3389/fpls.2023.1145389</a>]</p> </blockquote> <p>The following files contains:</p> <ul> <li><code>gel_data_preprocessing_20221024.R</code> - R statistics script for pre-processing data files from 3Dgel system GIARoots & DynamicRoots raw output</li> <li><code>gel_dataprocessing_20221229.R</code> - R statistics script for data processing of pre-processed 3D gel data</li> <li><code>TaGNS_N_Spring32.zip</code> - CSV data files and R statistics script for Spring32 grown under high, low, trace and zero N treatments.</li> <li><code>TaGNE_N_Accessions.zip</code> - CSV data files and R statistics script for 3 accessions under high and trace N treatments.</li> <li><code>TaGAA_N_Accessions.zip</code> - CSV data files and R statistics script for 24 diverse pennycress lines grown under high N conditions.</li> </ul>
Imaging data from "Live-cell 3D single-molecule tracking reveals modulation of enhancer dynamics by NuRD"
<p>3D 20ms, 3D 500ms and 2D dCas9 raw videos, localisation, tracking and trajectory analysis data</p> <p>From 'Live-cell 3D single-molecule tracking reveals modulation of enhancer dynamics by NuRD" (2021). Biorxiv. https://doi.org/10.1101/2020.04.03.003178</p>
3D video renderings of synchrotron tomography data from the CERIC beamtime proposal 20217193
<p>3D video renderings of corroded roman glass sample from synchrotron X-ray micro Computed Tomography data collected within the CERIC beamtime proposal 20217193.</p> <table> <caption>Uploaded videos</caption> <thead> <tr> <th scope="col">File</th> <th scope="col">Description</th> </tr> </thead> <tbody> <tr> <td>581681_whole_sample.avi</td> <td>Overview of the investigated glass specimen.</td> </tr> <tr> <td>581681_HR_pit.avi</td> <td>High-resolution rendering of glass corrosion pit.</td> </tr> <tr> <td>581681_HR_pit_voids_particles.avi</td> <td>HR video of the corrosion pit highlighting void spaces and secondary corrosion products.</td> </tr> <tr> <td>581681_HR_pit_particles-volume.avi</td> <td>HR video of the corrosion pit highlighting sediment particles and their volume.</td> </tr> </tbody> </table> <p> </p>
Test data for 3D with focal stacking
<p>* the data contains a set of .tiff images of a butterfly wing taken with a Canon</p> <p>* shutter speed: 1/5, ISO: 200</p> <p>* objective Met 20/0.5</p> <p>* speed within stack: 10 um/s, step size: 5 um</p> <p> </p> <p>* Authors: Stefanie Homberger, John Meshreki, Ivo Ihrke, 2023, Universität Siegen / Chair of Computational Sensorics / Communications Engineering</p> <p> </p>
Input and output data from simulations of 2D valves and 3D inflow-outflow model using particle methods
<p>Input and output data of open-source softwares for computational fluid dynamics simulation involving fluid-structure interaction.</p> <p> </p> <p><strong>Data from two studies</strong></p> <ol> <li>Verifications of the weakly-compressible smoothed particle hydrodynamics (WCSPH) method, open-source code <a href="https://www.sphinxsys.org">SPHinXsys</a>, when applied to the flow of idealized 2D valve models.</li> <li>Validations of inflow-outflow model in moving particle semi-implicit (MPS) method, open-source code <a href="https://github.com/rubensamarojr/polymps/tree/inOutflow">PolyMPS</a>.</li> </ol> <p> </p> <p><strong>Folders and Files</strong></p> <p><strong>valve-2D.zip </strong>is the folder with data from the idealized models of vertical and curved 2D valves:</p> <ul> <li>Vertical valves with parameters provided in <a href="https://doi.org/10.1016/j.jcp.2010.08.005">Gil et al., 2010</a></li> <li>Curved valves with parameters provided in <a href="http://doi.org/10.1007/s00466-013-0890-3">Wick, 2014</a></li> <li>source files (.cpp): input data (physical and numerical parameters) for SPHinXsys</li> <li>text files: SPHinXsys (.dat) and Reference (.tsv) results</li> <li>python files (.py): Generates the graphics</li> </ul> <p> </p> <p><strong>inflow-outflow-3D.zip </strong>is the folder with data from the inflow-outflow model in MPS:</p> <ul> <li>Fluid physical properties of water <ul> <li><span>\(\rho=1000kg/m^3 , \,\, \nu=10^{-6}m/s^{-2}\)</span></li> </ul> </li> <li>Pipes of length <span>\(L=0.15m\)</span>: <ul> <li>circular section of diameter <span>\(D=0.1m\)</span>.</li> <li>square section of sides <span>\(S=0.1m\)</span>.</li> </ul> </li> <li>Constante pressure variation (<span>\(\Delta P = 30 \,\, or \,\, 50 \,\, Pa\)</span>) between inflow and outflow: <ul> <li><span>\(\frac{\partial p}{\partial x} = - \frac{\Delta P}{L}, \\ \Delta P = P_{outflow} - P_{inflow}\)</span></li> </ul> </li> </ul> <ul> <li>Sinusoidal pressure variation (<span>\(\Delta P =700Pa \,\, , \,\, T = 2.0s\)</span>) between inflow and outflow <ul> <li><span>\(\frac{\partial p}{\partial x} = - \frac{\Delta P}{L} \sin \omega t \, \\ \omega = \frac{2\pi}{T} \\ Delta P = P_{outflow} - P_{inflow}\)</span></li> </ul> </li> <li>input data (.json, .grid, .stl): physical properties, numerical parameters and geometries for PolyMPS can be found at <a href="https://github.com/rubensamarojr/polymps/tree/inOutflow/input">https://github.com/rubensamarojr/polymps/tree/inOutflow/input</a></li> <li>text files (.txt): PolyMPS and OpenFOAM results</li> <li>python files (.py): Generates the graphics</li> </ul> <p> </p> <p><strong>References</strong></p> <p><a href="https://doi.org/10.1016/j.jcp.2010.08.005">A. J. Gil. The Immersed Structural Potential Method for haemodynamic applications. J. Comput. Phys., 229 (2010), pp. 8613-8641</a></p> <p><a href="https://doi.org/10.1007/s00466-013-0890-3">T. Wick. Flapping and contact FSI computations with the fluid–solid interface-tracking/interface-capturing technique and mesh adaptivity. Comput Mech 53, 29–43 (2014)</a></p> <p><a href="https://doi.org/10.1016/j.cma.2014.10.040">D. Kamensky, et al. An immersogeometric variational framework for fluid–structure interaction: Application to bioprosthetic heart valves Comput. Methods Appl. Mech. Engrg., 284 (2015), pp. 1005-1053</a></p> <p><a href="https://doi.org/10.1016/j.cma.2015.12.023">C. Kadapa et al. A fictitious domain/distributed Lagrange multiplier based fluid–structure interaction scheme with hierarchical B-Spline grids. Comput. Methods Appl. Mech. Engrg., 301 (2016), pp. 1-27</a></p> <p><a href="https://doi.org/10.1016/j.jcp.2015.10.015">Jie Liu. A second-order changing-connectivity ALE scheme and its application to FSI with large convection of fluids and near contact of structures. J. Comput. Phys., 304 (2016), pp. 308-423</a></p>
3D Printing of Personalised Carvedilol Tablets Using Selective Laser Sintering - Underlying Data
<p><strong>Underlying μCT Data for "<em>3D Printing of Personalised Carvedilol Tablets Using Selective Laser Sintering</em>"</strong></p> <p>by <em>Atabak Ghanizadeh Tabriz, Quentin Gonot-Munck, Arnaud Baudoux, Vivek Garg, Richard Farnish, Orestis L. Katsamenis, Ho-Wah Hui, Nathan Boersen, Sandra Roberts, John Jones, and Dennis Douroumis</em></p> <p><em>published in MDPI pharmaceutics<br> In section: Physical Pharmacy and Formulation, Recent Non-oral Dosage Form Development: Focus on 3D-Printed Formulations</em></p> <p><em>The micro- and macro-porosities of representative 3D-printed tablets at 25%, 40%, and 55% laser intensities was measured. SLS-printed components were also characterised by means of X-ray microfocus computed tomography (μCT). Imaging was performed at the University of Southampton’s μ-VIS X-ray Imaging Centre (www.muvis.org) using a customised μCT scanner optimised for 3D X-ray histology (www.xrayhistology.org). The system, which is based on Nikon’s XTH225ST system (Nikon Metrology UK Ltd.)</em></p> <p> </p> <p><strong>Data index</strong></p> <ul> <li>20230206_XRH_3299_OLK_PHAR08603-DOSF_40.zip <ul> <li>Dataset (including ORS Dragonfly analysis file) of object printed at 40% laser power<br> 10 µm voxel size isotropic</li> </ul> </li> <li>20230206_XRH_3299_OLK_PHAR08616-DOSF.zip <ul> <li>Dataset (including ORS Dragonfly analysis file) of object printed at 55% laser power<br> 10 µm voxel size isotropic</li> </ul> </li> <li>20230206_XRH_3299_OLK_PHAR08616-DOSF_25.zip <ul> <li>Dataset (including ORS Dragonfly analysis file) of object printed at 25% laser power<br> 10 µm voxel size isotropic</li> </ul> </li> <li>SLS-3DP_OLK-CorrectRes.xlsx <ul> <li>Analysis results & graphs</li> </ul> </li> </ul> <p><em>X-ray CT analysis conducted using Dragonfly software (v. 2022.1.0.1231; Object Research Systems (ORS) Inc, Montreal, Canada, 2020; software available at http://www.theobjects.com/dragonfly</em></p>
Supplementary data to 'The origin and differentiation of CO2-rich primary melts in Ocean Island volcanoes: Integrating 3D X-ray tomography with chemical microanalysis of olivine-hosted melt inclusions from Pico (Azores).'
<p>Supplementary data to:</p><blockquote><p>The origin and differentiation of CO2-rich primary melts in Ocean Island volcanoes: Integrating 3D X-ray tomography with chemical microanalysis of olivine-hosted melt inclusions from Pico (Azores).</p></blockquote>
Data from: Long-term monitoring of <em>Ziphius cavirostris</em> behavior using 3D tracking from fixed hydrophone arrays off Southern California
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Area and Timing data and R script for: 3D scanning as a tool to measure growth rates of live coral microfragments used for coral reef restoration
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Data from: 3D morphology of an outer-hair-cell hair bundle increases its displacement and dynamic range
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Correlative 3D SBFSEM data from: Intermittent bulk release of human cytomegalovirus
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Data from: The effect of external flow on 3D orientation of a microscopic sessile suspension feeder, Vorticella convallaria
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Supplementary data for: Nowcasting 3D cloud fields using forward warping optical flow
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Data from: 3D printed digital pneumatic logic for the control of soft robotic actuators
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Scan files, 3D reconstructions, data spreadsheet and supplementary files for Heterochrony and parallel evolution of echinoderm, hemichordate and cephalochordate internal bars
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Detecting anomalies in melt-extruded 3D printed parts using in situ data
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Data and code from: 3D-SOCS: synchronized video capture for posture estimation
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Supporting data: 3D projection electrophoresis for single-cell immunoblotting (Part 3)
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Supporting data: 3D projection electrophoresis for single-cell immunoblotting (Part 1)
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ScienceDex guides
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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.