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898 results for “three-dimensional”

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zenodo44/100

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)&nbsp;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>&nbsp;&ndash;&nbsp;settings of colour deconvolution in Fiji for double staining.</li> <li>File <em>comments to videos.odt</em>&nbsp;&ndash;&nbsp;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>&nbsp;&ndash;&nbsp;sequence of section with single (a) and double (b) staining for ROI 1 to 3&nbsp;in the main text.</li> <li><strong>S1c Video to S3c Video</strong>: files <em>video_[1,2,3]c.mov</em>&nbsp;&ndash;&nbsp;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>&nbsp;&ndash;&nbsp;an overview video of the reconstruction, double staining.</li> <li><strong>S4 Video</strong>: file <em>video_4.mov</em>&nbsp;&ndash;&nbsp;quality control in virtual reality.</li> <li><strong>S1 Figure</strong>: a supplementary figure&nbsp;<em>fig_S1.tiff</em>&nbsp; and its caption <em>fig_S1_legend.odt</em></li> <li><strong>S2&nbsp;Figure</strong>: a supplementary figure&nbsp;<em>fig_S2.tiff</em>&nbsp; and its caption <em>fig_S2_legend.odt</em></li> </ul> <p>This data corresponds to the&nbsp;publication &quot;Capillary networks and follicular marginal zones in the human spleen. Three-dimensional models based on immunostained serial sections&quot; by B. S. Steiniger, C. Ulrich, M. Berthold, M. Guthe, and O. Lobachev, 2017.</p>

opencc-by-sa-4.0Jul 2017View details →
zenodo44/100

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)&nbsp;as well as raw and processed data to reproduce the results shown in:</p> <p>Maiello, G., Kwon, M. &amp; Bex, P.J. (2018)&nbsp;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>

opencc-by-4.0Dec 2017View details →
zenodo44/100

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-Marz&aacute;n, 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.&nbsp;</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.&nbsp;</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&nbsp;<code>.rec</code> files can be visualized using volume rendering software (e.g. Amira or Avizo), while the&nbsp;<code>.mat</code> files contain structured data for analysis in MATLAB.&nbsp;The supporting code and scripts for this dataset are available on the GitHub repository:&nbsp;<a href="https://github.com/ajinkyakadu/LiquidET_NatComm2024" target="_new" rel="noreferrer">https://github.com/ajinkyakadu/LiquidET_NatComm2024</a>.&nbsp;</p>

opencc-by-4.0May 2024View details →
zenodo44/100

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>

opencc-by-4.0May 2024View details →
zenodo44/100

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.&nbsp;</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&nbsp;the natural neural connectome&nbsp;and artificial silicon-based integrated circuits.&nbsp;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&nbsp; <a href="https://mail.ethz.ch/owa/redir.aspx?C=NzB9-v6wS5uDOPXWL0cW_Vu4ys_MIpbvUqKcmezLt5AHOlhZD1DXCA..&amp;URL=https%3a%2f%2frdcu.be%2fbTudW">https://rdcu.be/bTudW</a></p>

opencc-by-4.0Oct 2019View details →
zenodo44/100

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">&quot;Three-dimensional subnanoscale imaging of unit cell doubling due to octahedraltilting and cation modulation in strained perovskite thin films&quot;</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&#39;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>&nbsp;</p>

opencc-zeroOct 2019View details →
zenodo44/100

Stellar Mass Black Hole Formation and Multimessenger Signals from Three-dimensional Rotating Core-collapse Supernova Simulations

<p>Gravitational waveforms from <a href="https://ui.adsabs.harvard.edu/abs/2021ApJ...914..140P/abstract">Pan et al. (2021) .</a></p> <p>They are the 40 solar mass model from Woosley &amp; Heger 2007 with different<br>initial rotational speeds:</p> <p>Model NR: Omega_0 = 0.0 rad/sec<br>Model SR: Omega_0 = 0.5 rad/sec<br>Model FR: Omega_0 = 1.0 rad/sec</p> <p>/* File content */</p> <p>They are 5 files for each simulation.</p> <p>Files "data_s40_[model]_d3_[Cross/Plus][Equator/Pole].d" are GW strains for different<br>mode of polarization [h_plus or h_cross] and viewing angles [equator or pole].</p> <p>1st column is time [s] in postbounce.&nbsp;<br>2nd column s the GW strain, assuming d=10 kpc.<br>&nbsp;<br>Files "data_s40_[model]_d3_Idotdot.d" are the second time derivative of the<br>quadruple moments.</p> <p>1st: postbounce time [s]&nbsp;<br>2nd: Idd_xx [cgs]<br>3rd: Idd_xy = Idd_yx [cgs]<br>4th: Idd_yy = Idd_yy [cgs]<br>5th: Idd_zx = Idd_zx [cgs]<br>6th: Idd_zy = Idd_zy [cgs]<br>7th: Idd_zz = Idd_zz [cgs]</p> <p>&nbsp;</p>

opencc-by-4.0Sep 2024View details →
zenodo44/100

Insights into non-axisymmetric instabilities in three-dimensional rotating supernova models with neutrino and gravitational-wave signatures

<p>Those are movies of numerical supernova models, which appear&nbsp;in&nbsp;Takiwaki, Kotake, and Foglizzo, (2021), Monthly Notices of the Royal Astronomical Society, Volume 508, Issue 1, pp.966-985</p>

opencc-by-4.0Sep 2021View details →
zenodo44/100

Database of Planar and Three-Dimensional Periodic Orbits and Families Near the Moon

<p>The lunarPOdatabase.zip is the digital database accompanying the paper:<br> <br> C. Franz and R. P. Russell, &ldquo;Database of planar and three-dimensional periodic orbits and families near the Moon,&rdquo; The Journal of the Astronautical Sciences, DOI 10.1007/s40295-022-00361-9 (accepted Nov. 2022).</p> <p>Please see the paper for details, and cite the paper as appropriate. The database is accessible and permanently archived with the following DOI <a href="https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.6411980&amp;data=05%7C01%7C%7C1770e232817c4c99fc1b08dad0a0e3ad%7C31d7e2a5bdd8414e9e97bea998ebdfe1%7C0%7C0%7C638051686701542157%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&amp;sdata=Spb%2FFj5YL8QKaBoojr09MCCIdloAkzLiGKHoUo3uVGE%3D&amp;reserved=0">https://doi.org/10.5281/zenodo.6411980</a>.&nbsp; See accompanying license.txt and gpl-3.0.txt for license information, applying to all files included in the .zip distribution.</p> <p>The database contains over 13 million planar and three-dimensional solutions in the Earth-Moon circular restricted three body problem, grouped into 34,000 family and sub-family clusters. The database exists as human readable text files with periodic orbits organized by clusters and other dynamical characteristics.&nbsp; The database contains the clustered data, a README file describing the output format, an interactive GUI, and a simple MATLAB script as a basic interface with the database. The data are split into five files, one for each of the planar prograde, planar retrograde, axial prograde, axial retrograde, and x-z cases. The results (i.e. initial conditions and relevant dynamical parameters of each converged periodic orbit) are contained in a human-readable text file where each row is a new solution. The data are sorted by cluster and ordered inside the cluster to form a smooth curve. Summary files are included for both the grid search and the clustering for each run. The input parameters to the grid search software are also included with each case for reproducibility. File sizes range from approximately 1.1GB to 2.6GB, with a total uncompressed file size of 5.4GB and a total compressed file size of 1.2GB.</p> <p>It is emphasized that the GUI and other MATLAB interface files are only a preliminary capability to ease interaction with the database.&nbsp; They may not be stable under future releases of MATLAB. On the initial use of the GUI, we recommend to restrict the data to a single value of N (say N=1 or N=16), otherwise the number of solutions may overwhelm the system memory.&nbsp; If a user has difficulties using the GUI, the user is encouraged to use the MATLAB code interfaces or interface with the text files directly. The text files containing the database are the primary product provided here, with the GUI and test scripts provided as a courtesy to help ease the database&#39;s use.</p> <p>Please send questions to <a href="mailto:cfranz21@gmail.com">cfranz21@gmail.com</a> and/or <a href="mailto:ryan.russell@utexas.edu">ryan.russell@utexas.edu</a>.</p>

opengpl-2.0Nov 2022View details →
zenodo44/100

Estimating three-dimensional structures of eddy in the South Indian Ocean from the satellite observations based on the isQG method

<p>Supporting data for Estimating three-dimensional structures of eddy in the South Indian Ocean from the satellite observations based on the isQG method</p> <p>Matlab Codes to reconstruct the subsurface structures (Codes without Figure_*.m) and plot the figures (Figure_*.m) in the manuscript. The file in Netcdf format is our reconstructed 3D density and currents.</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2023View details →
dryad40/100

Data from: Arm waving in stylophoran echinoderms: three-dimensional mobility analysis illuminates cornute locomotion

<p>The locomotion strategies of fossil invertebrates are typically interpreted on the basis of morphological descriptions. However, it has been shown that homologous structures with disparate morphologies in extant invertebrates do not necessarily correlate with differences in their locomotory capability. Here, we present a new methodology for analysing locomotion in fossil invertebrates with a rigid skeleton through an investigation of a cornute stylophoran, an extinct fossil echinoderm with enigmatic morphology that has made its mode of locomotion difficult to reconstruct. We determined the range of motion of a stylophoran arm based on digitized three-dimensional morphology of an early Ordovician form, <i>Phyllocystis crassimarginata</i>. Our analysis showed that efficient arm-forward epifaunal locomotion based on dorsoventral movements, as previously hypothesized for cornute stylophorans, was not possible for this taxon; locomotion driven primarily by lateral movement of the proximal aulacophore was more likely. 3D digital modelling provides an objective and rigorous methodology for illuminating the movement capabilities and locomotion strategies of fossil invertebrates.</p>

opencc-zeroMay 2020View details →
zenodo40/100

SWASH Model Files from Modeled Three-Dimensional Currents and Eddies on an Alongshore-Variable Barred Beach

<p>This archive contains SWASH model input, MATLAB processing scripts, and the model output used to produce the figures in&nbsp;&ldquo;Modeled Three-Dimensional Currents and Eddies on an A longshore-Variable Barred Beach.&quot;</p> <p>Support was provided by the Washington Royalty Research Fund, the National Science Foundation, the Office of Naval Research, a National Defense Science and Engineering Graduate Fellowship, a Vannevar Bush Faculty Fellowship, the United States Army Corps of Engineers, the United States Coastal Research Program, Sea Grant, and the WHOI Investment in Science Fund.</p> <p>&nbsp;</p> <p>The model inputs, scripts, and data&nbsp;are contained in three&nbsp;zip files:&nbsp;</p> <ul> <li>model_input.zip: input files for all simulations presented in this paper</li> <li>model_output_processing.zip: MATLAB model output processing&nbsp;scripts.</li> <li>model_data.zip: model output used to produce the&nbsp;figures</li> </ul> <p>&nbsp;</p> <p>SWASH is an open source code and can be&nbsp;download at <a href="http://swash.sourceforge.net/home.htm">http://swash.sourceforge.net/home.htm</a>. Please contact C.M. Baker at cmbaker9@uw.edu with questions.&nbsp;</p>

opencc-by-4.0Oct 2020View details →
zenodo40/100

Unique dynamics and exocytosis properties of GABAergic synaptic vesicles revealed by three-dimensional single vesicle tracking

<p>This data set includes x, y, and z trajectories of all GABAergic synaptic vesicles&nbsp;that we used for the study. These GABAergic synaptic vesicles in inhibitory presynaptic terminals of living primary hippocampal neurons&nbsp;were&nbsp;labeled by single quantum dots (QDs) conjugated with anti-VGAT antibody under electrical stimulation, and were tracked three-dimensionally by using a dual-focus imaging in real-time.&nbsp;Each trajectory data indicates x, y, and z positions (nanometer-scale) over time from the start of imaging to the moment of vesicle fusion. The electrical stimulation to the neurons was applied for 120 s, starting from 20 s.</p>

opencc-by-4.0Jan 2021View details →
zenodo40/100

Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - methods

<p>We reconstruct the 3D shape of microvasculature in human bone marrow specimen.</p> <ul> <li>&nbsp;Files &quot;2016-07-01_Methodenvideo_....mp4&quot; detail on the novel embedding process of our specimen. The video details on material preparation, special embedding device and devised procedure, the sectioning and further processes. For convinience, a high-resolution ....FullHD.mp4 and low-resolution .....SD.mp4 versions are provided.</li> <li>Files &quot;2016-07-27 Manual Quality Control - ...mp4&quot; details on the computer-based verification of final mesh and initial (registered) image stack. We can observe some blind ends or interrruptions in the reconstruction,&nbsp;this tools allows us to evaluate the suspective areas. There is&nbsp;a FullHD encode, and a&nbsp;SD version.</li> </ul>

opencc-by-4.0Jul 2016View details →
zenodo40/100

Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - final data

<p>These are the meshes used to render the videos in 10.5281/zenodo.57834 and 10.5281/zenodo.57754</p> <p>The file names are:</p> <p>R[n]_[kind].ply</p> <p>where</p> <p>n is the ROI number, 1-4<br> kind is the diameter mesh or the overview mesh.</p> <p>The diameter meshes have additionally removed inner components and also other small non-connected components, as described in the paper.</p>

opencc-by-4.0Jul 2016View details →
zenodo40/100

Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - difference between meshes

<p>The difference between the overview mesh and mesh used for SDF for all ROI.</p> <p>Black is no difference, i.e. baseline, objects removed for SDF processing are red.</p>

opencc-by-4.0Oct 2016View details →
zenodo40/100

Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - diameters

<p>We reconstruct blood vessels in human bone marrow specimen. These videos show the diameters of blood vessels.</p> <p>Red is under 12 µm, green is over 30 µm, in-between is the gradient from red to green. The coloring is based on the SDF computation and the accompanying MeshLab Quality Mapper file.</p>

opencc-by-4.0Jul 2016View details →
zenodo40/100

Three-dimensional GNSS Time Series Data for Terrestrial Water Storage Changes Inversion in Yunnan, China

<p>The dataset includes three-dimensional GNSS time series data featured in the publication "Using the global navigation satellite system and precipitation data to establish the propagation characteristics of meteorological and hydrological drought in Yunnan, China", published in 'Water Resources Research'.</p> <p>Reference:<br>Zhu, H., Chen, K., Hu, S., Liu, J.,Shi, H., Wei, G., et al. (2023). Using the global navigation satellite system and precipitation data to establish the propagation characteristics of meteorological and hydrological drought in Yunnan, China. Water Resources Research, 59, e2022WR033126. https:// doi.org/10.1029/2022WR033126</p> <p><br>The sitelist file lists basic information about all the utilized stations, including their names and geographic coordinates.&nbsp;<br>The Time.mat file contains the time vectors of the data employed.&nbsp;<br>The Filter_time_series_N/E/U.mat files showcase the filtered time series, which have been processed using Independent Component Analysis (ICA) for the inversion of terrestrial water storage in Yunnan, after removing the effects of outliers, steps, and non-tidal atmospheric/oceanic loading.</p>

opencc-by-4.0Mar 2023View details →
zenodo40/100

Tomography Data for: Three-dimensional Nanoscale Metal, Metal Oxide and Semiconductor Frameworks through DNA-programmable Assembly and Templating

<p>This is data collected at the 3-ID Hard X-ray Nanoprobe beamline. This repository supports the following research article:&nbsp;</p><p>Data provided is the aligned dataset and reconstruction using a FISTA algorithm. Angles Collected &nbsp;-90 to +45 at 1 degree steps.&nbsp;</p><p><strong>Three-dimensional Nanoscale Metal, Metal Oxide and Semiconductor Frameworks through DNA-programmable Assembly and Templating</strong></p><p>By Aaron Michelson.&nbsp;</p><p>&nbsp;</p>

opencc-by-4.0Nov 2023View details →
zenodo40/100

A Stereo Camera Simulator for Large-Eddy Simulations of Continental Shallow Cumulus clouds based on three-dimensional Path-Tracing

<p>Dataset to produce the results of the publication: "A Stereo Camera Simulator for Large-Eddy Simulations of Continental Shallow Cumulus clouds based on three-dimensional Path-Tracing"</p><p>The dataset contains:</p><ul><li>Large-Eddy Simulation (LES) model configuration files</li><li>Selected output data of the LES experiments</li><li>Data and analysis scripts for the figures</li><li>The rendered camera images</li><li>The cloud field, cloud hulls, and reconstructed hulls</li><li>A frozen version of the open-source Blender code (version 2.90) as used in this study</li></ul><p>For the latest version of Blender, please visit:</p><p><a href="https://chat.openai.com/c/www.blender.org">www.blender.org</a></p><p>It is important to note that the method was specifically tested only on version 2.90.</p><p>&nbsp;</p><p>This research is supported by the German Research Foundation (DFG) under project number 430226822 (https://gepris.dfg.de/gepris/projekt/430226822). This research was supported by the U.S. Department of Energy's Atmospheric System Research, an Office of Science Biological and Environmental Research program, under grant DE-SC0022126. This work used resources of the Deutsches Klimarechenzentrum (DKRZ) granted by its Scientific Steering Committee (WLA) under project ID bb1086. The Gauss Centre for Supercomputing e.V. (https://www.gauss-centre.eu/) is acknowledged for providing computing time on the Gauss Centre for Supercomputing (GCS) supercomputer JUWELS at the Jülich Supercomputing Centre (JSC) under projects VIRTUALLAB and RCONGM.</p>

opencc-by-4.0May 2023View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record