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94 results for “3-D model”

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zenodo48/100

Processing of 3-D Polygon Mesh Model and Radio Propagation Simulations in a Cave: Surface Reconstruction from Point Cloud, Simplification of the Mesh, and Ray Tracing

<p><strong>ABOUT</strong></p><p>This repository includes mesh data from cave geometry scanning and processing, and radio propagation data from ray tracing simulations.</p><p>The geometry data is obtained with laser scanning in a cave in Slovenija. &nbsp;</p><p>The geometry processing includes (i) 3-D shape reconstruction - surface reconstruction from point cloud data and (ii) simplification - reduction of the geometric complexity of the 3-D mesh model. &nbsp;</p><p>The radio propagation data is obtained using CloudRT [1] ray-tracing simulator. &nbsp;</p><p>The obtained propagation-related quantities include information about the propagation mechanism, interactions with the geometry, received power, delay, azimuth and elevation angles of arrival and departure, and path loss.&nbsp;</p><p>&nbsp;</p><p><strong>AUTHORS</strong></p><p>Teodora Kocevska, Andrej Hrovat, Tomaž Javornik</p><p>Department of Communication Systems</p><p>Jožef Stefan Institute, SI-1000 Ljubljana, Slovenia</p><p>teodora.kocevska@ijs.si</p><p>&nbsp;</p><p><strong>GEOMETRY PROCESSING</strong></p><p>The cave segment used for the propagation calculations is selected from a point cloud obtained in a cave in Litia, Slovenia. The point cloud is obtained with 3-D laser scanning of the environment. The selected segment is approx. 58 &nbsp;m long. Several parameter configurations were considered for 3-D shape reconstruction, including Poisson surface reconstruction with octree depths of 8, 10, and 12. Geometries that represent the cave shape and have different levels of complexity were created and studied. In the simplification process, one and two-stage simplification was explored using the Quadric Edge Collapse Decimation approach.&nbsp;</p><p>&nbsp;</p><p><strong>RADIO SETUP</strong></p><p>The transmitter (Tx) is fixed at the entrance of the cave and the receiver (Rx) is moved along the cave in 40 positions with a step of 1 m.</p><p>Omnidirectional antennas at the Tx and Rx sites and vertical polarization are considered. The antenna is mounted 1.5 m above the ground.</p><p>The start frequency is 3.5 GHz, the end frequency is 3.6 GHz and the step is 10 MHz. Direct propagation and first-order reflection are considered. &nbsp;</p><p>The cave geometry is represented by a triangular mesh, and the material of the cave is wet earth. The material electromagnetic properties are selected according to the specifications presented in [2].</p><p>&nbsp;</p><p><strong>FOLDER STRUCTURE</strong></p><p>The folder structure is:</p><p>&nbsp; &nbsp; &nbsp;- Polygon_Mesh_Models</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<i># 3-D environment models with varying </i>levels<i> of geometry complexity</i></p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - Reconstruction_Segmen1_Poisson_Surface_Reconstruction</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - Simplification_Segment1_Quadric_Edge_Collapse_Decimation</p><p>&nbsp; &nbsp; &nbsp;- Propagation_Data</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<i># Propagation quantities of all rays between a transmitter and receiver</i></p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - AllRay_PropData</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - PathLoss</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - readme.txt</p><p>&nbsp; &nbsp; &nbsp;- RayTracing_EnvironmentModel</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;<i> # Final environment model used for ray tracing simulations</i></p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - Cave_MeshModel.json</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - Cave_MeshModel.skb</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - Cave_MeshModel.skp</p><p>&nbsp; &nbsp; &nbsp;- RayTracing_MaterialProperties</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<i># Properties of the materials in the environment</i></p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - materials.json</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - materials.mtl</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; - readme.txt</p><p>&nbsp; &nbsp; &nbsp;- Cave_Length.txt</p><p>&nbsp; &nbsp; &nbsp;<i># Length between selected locations in the environment</i></p><p>&nbsp; &nbsp; &nbsp;- Cave_Segment1_visual.png</p><p>&nbsp; &nbsp;&nbsp;<i> # Visualization of the environment segment used for propagation calculation</i></p><p>&nbsp; &nbsp; &nbsp;- readme.txt</p><p>&nbsp; &nbsp; &nbsp;<i># Overall description&nbsp;</i></p><p><strong>REFERENCES</strong></p><p>[1] D. He, B. Ai, K. Guan, L. Wang, Z. Zhong, and T. Kürner, "The Design and Applications of High-Performance Ray-Tracing Simulation Platform for 5G and Beyond Wireless Communications: A Tutorial," in IEEE Communications Surveys &amp; Tutorials, vol. 21, no. 1, pp. 10-27, First quarter 2019, doi: 10.1109/COMST.2018.2865724.</p><p>[2] R. sector of International Telecommunication Union (ITU-R), "Effects of building materials and structures on radio wave propagation above about 100 MHz," International Telecommunication Union, ITU-R Recommendation P.2040-2, 2021.</p><p>&nbsp;</p><p><strong>ACKNOWLEDGEMENT</strong></p><p>This work was supported by the Slovenian Research Agency under grant <strong>J2-3048</strong>.</p><p>&nbsp;</p>

opencc-by-4.0Dec 2023View details →
zenodo44/100

MTAB3D: a 3-D velocity model for absolute hypocenter location in southern Iberia and westernmost Mediterranean.

<p>The Trans-Alboran Shear Zone is one of the most seismically active areas in the westernmost Mediterranean, where a wide variety of tectonic domains have developed within the context of oblique convergence between Eurasia and Africa plates. In this region, earthquakes occur close to seismogenic structures, some of them large enough to cause damaging events. In addition, the diversity of tectonic domains implies a lateral variation of seismic wave propagation, which could affect the hypocenter reliability if not addressed during the location procedure. In this work, we present mTAB3D, a new 3D P-wave velocity model that accounts for the lateral heterogeneity of our study area. The new catalogs computed with our model help us to infer possible genetic relations between seismicity and source faults within our study area and can be used as an additional tool when looking into prior seismic sequences.</p>

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

A 3-D model of The Bear Trap: A unique stone structure on the northwest tip of the Nuussuaq Peninsula, Greenland

<p>This dataset consists of five files. The .obj, .jpg., and .mtl files can be used to view a high-resolution 3D mesh model of &lsquo;The Bear Trap&rsquo;, a unique Norse ruin at the western end of the Nuussuaq Peninsula in NW Greenland (also called &lsquo;Bj&oslash;rnef&aelig;lden&rsquo; in Danish, and &lsquo;Putdlagssuaq&rsquo; or &lsquo;The Great Trap&rsquo; Greenlandic Kalaallisut). The .laz file contains the dense cloud. The .avi shows a flyover video of the 3D model. The 3D model was created from 1686 photographs that were processed using Structure from Motion Multiview Stereo photogrammetry software (in this case Agisoft Metashape Pro v1.7; Linux Ubuntu). A 24.3 megapixel Sony a5100 APS-C mirrorless camera fitted with a 24 mm lens was used to acquire ground-level imagery of the structure. The image alignment or bundle adjustment was performed using &lsquo;High&rsquo; accuracy, a key point limit of 60000 and no tie point limit. The sparse point cloud was scaled using three markers with known dimensions that were placed in the area of interest, and which remained stationary throughout the entire photo survey. The dense point cloud was computed using the &lsquo;High&rsquo; setting. The dense point cloud was then used to compute the mesh model using the &lsquo;High&rsquo; setting. Instructions are provided in the readme file that accompanies this dataset.&nbsp;</p> <p>The image survey of the Bear Trap was conducted as part of the Vaigat Iceberg-Microbial Oil Degradation and Archaeological Heritage Investigation (VIMOA) project, which was funded by the Danish Centre for Marine Research and supported by the Arctic Research Centre at Aarhus University, the National Museum of Denmark, the Greenland Institute of Natural Resources, and The Greenland National Museum and Archives in Nuuk. Permits for the survey were obtained in advance from the&nbsp;Greenland National Museum and Archives in Nuuk.&nbsp;Walsh et al. (2020) provides an overview of the archaeological surveys conducted during the VIMOA project and Walsh et al. (submitted) provides further details specific to The Bear Trap and surrounding archaeological contexts.&nbsp;</p> <p>Walsh et al. (2020) The VIMOA project and archaeological heritage in the Nuussuaq Peninsula of north-west Greenland. <em>Antiquity</em> 94:e6 doi:10.15184/aqy.2019.230</p> <p>Walsh, Matthew J., Daniel F. Carlson, Pelle Tejsner, and Steffen Thomsen. The Bear Trap: Reinvestigating a unique stone structure on the northwest tip of the Nuussuaq Peninsula, Greenland. Manuscript submitted to <em>Arctic Anthropology</em></p>

opencc-by-4.0Aug 2020View details →
zenodo44/100

Waveform data for centroid moment tensor solutions presented in publication "Bayesian seismic source inversion with a 3-D Earth model of the Japanese islands"

<p>The dataset includes waveform data for&nbsp;centroid moment tensor solutions inferred&nbsp;using Hamiltonian Monte Carlo and a 3-D Earth model in the Japanese islands. The data are provided as&nbsp;Green&#39;s strains at the maximum-likelihood location (indicated in the title of each text file) for all study events&nbsp;inverted at different periods. Inversion period is also indicated in the title. All the data are filtered between 15 s and 80 s. Additionally we provide a Python code to obtain&nbsp;displacement from strains given a moment tensor.</p>

opencc-by-4.0Sep 2022View details →
zenodo44/100

Atmospheric Distribution of HCN from Satellite Observations and 3-D Model Simulations - TOMCAT data

<p>This repository contains the model data from the paper &quot;Atmospheric Distribution of HCN from Satellite<br> Observations and 3-D Model Simulations&quot; submitted to ACP.</p> <p>The files contains the monthly mean hydrogen cyanide (HCN) mixing ratios modelled using the TOMCAT 3-D offline chemical transport model with a horizontal resolution of 2.8&deg; &times; 2.8&deg; with 60 hybrid &sigma;-pressure levels from the surface to ~60 km.</p>

opencc-by-4.0Oct 2022View details →
zenodo44/100

3-D model data used to investigate the role of K-feldspar and quartz in global ice nucleation by mineral dust in mixed-phase clouds

<p>These simulations were run by Chemical Transport Model TM4-ECPL covering the years 2009-01 to 2016-12 and are used for the bellow publication:</p> <p>Chatziparaschos, M., Daskalakis, N., Myriokefalitakis, S., Kalivitis, N., Nenes, A.,<br> Gon&ccedil;alves Ageitos, M., Costa-Sur&oacute;s, M., P&eacute;rez Garc&iacute;a-Pando, C., Zanoli, M., Vrekoussis,<br> M., and Kanakidou, M.: Role of K-feldspar and quartz in global ice nucleation by mineral dust in mixed-phase clouds,<br> Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2022-551, in press 2023.</p> <p>Laboratory: Environmental Chemical Processes Laboratory (EPCL), Department of Chemistry, University of Crete, Heraklion.<br> contact: Kanakidou Maria &lt;mariak@uoc.gr&gt;</p> <p>Model resolution: 2x3<br> Model Levels: 25</p> <p>Data info:</p> <p>DU_m2m(time, lev, lat, lon)<br> short_name :DU_m2m<br> long_name : Dust mode 2 mass accumulation</p> <p>DU_m3m(time, lev, lat, lon)<br> short_name : DU_m3m<br> long_name : Dust mode 3 mass coarse</p> <p>qua2_acc(time, lev, lat, lon)<br> short_name :qua2_acc<br> long_name :Quartz &ndash; accumulation mode</p> <p>qua2_coa(time, lev, lat, lon)<br> short_name :qua2_coa<br> long_name :Quartz &ndash; coarse mode</p> <p>FEL_acc(time, lev, lat, lon)<br> short_name :FEL_acc<br> long_name : K-Feldspar &ndash; accumulation mode</p> <p>FEL_coa(time, lev, lat, lon)<br> short_name :FEL_coa<br> long_name : K-Feldspar &ndash; coarse mode</p> <p>INP_QUA(time, lev, lat, lon)<br> short_name :INP_QUA<br> long_name :Ice Nucleating Particles derived form Quartz</p> <p>INP_FELD(time, lev, lat, lon)<br> short_name :INP_FELD<br> long_name :Ice Nucleating Particles derived form K-Feldpsar</p> <p>&nbsp;</p>

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

SEG/EAGE 3-D Overthrust Models.

<p>These are the models available from&nbsp;https://wiki.seg.org/wiki/SEG/EAGE_Salt_and_Overthrust_Models</p> <p>Only uploading here to get a DOI.&nbsp;</p> <p>&nbsp;</p> <p>Copyright notice</p> <p>Copyright 1997 Society of Exploration Geophysicists</p> <p>License</p> <p>This model is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of the license, visit&nbsp;<a href="https://creativecommons.org/licenses/by/4.0">https://creativecommons.org/licenses/by/4.0</a>&nbsp;or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.</p> <p>The license permits any user to freely copy and redistribute the material in any medium or format. Users are free to remix, transform, and build upon the material for any purpose, including commercially. Refer to LICENSE.txt for all terms and conditions, as well as the disclaimer of warranties.</p> <p>Please DO NOT separate the model and data from this license and ALWAYS include the above statement and link with the data.</p> <p>Acknowledgments</p> <p>This model was created by the SEG/EAGE 3-D Modeling committee, co-chaired by Fred Aminzadeh (University of Southern California) and Fabio Rocca (Politecinio di Milano). Chairpersons of the working groups included Kay Wyatt (Phillips Petroleum), Patrick Lailly (IFP), Norm Burkhard (Lawrence Livermore National Laboratory), Tim Kunz (Amoco), Jun Hua Chen (Chevron) and Max Mulder (TNO).</p> <p>Researchers involved in the creation of this model further include Jean Brac, Pierre Duclos, Laurence Nicoletis, Jean-Claude Lecomte and Alain Bamberger (all IFP), as well as Jane Long (Lawrence Livermore National Laboratory).</p> <p>This model was added to the SEG Open Data collection with help from Joseph Dellinger (BP), Ted Bakamjian (SEG), Dieter Werthm&uuml;ller (TU Delft) and Philipp Witte (Georgia Institute of Technology).</p> <p>&nbsp;</p> <p>References</p> <p>Aminzadeh, F., Brac, J., Kunz, T., 1997. SEG/EAGE 3-D Salt and Overthrust Models. SEG/EAGE 3-D Modeling Series, No. 1: Distribution CD of Salt and Overthrust models, SEG book series.</p> <p>Aminzadeh, F., Burkhard, N., Long, J., Kunz, T., Duclos, P., 1996. Three dimensional SEG/EAGE models - An Update. The Leading Edge, Vol. 15, 2.</p> <p>Aminzadeh, F., Burkhard, N., Kunz, T., Nicoletis, L., Rocca, F., 1995. 3-D Modeling Project: 3rd Report. The Leading Edge, Vol. 14, 2.</p> <p>Aminzadeh, F., Burkhard, N., Kunz, T., Nicoletis, L., Rocca, F., 1994. SEG/ EAGE 3-D Modeling Project: 2nd Update. The Leading Edge, Vol. 13, 9.</p> <p>Lecomte, J.-C., Campbell, E., Letouzey, J. 1994. Building the SEG/EAGE Overthrust Velocity Macro Model. EAGE/SEG Summer Workshop - Construction of 3-D Macro Velocity Depth Models. 3D Model Representation and Visualization.</p>

opencc-by-4.0Dec 1996View details →
zenodo40/100

Investigation of the post-2007 methane renewed growth with high-resolution 3-D variational inverse modelling and isotopic constraints - Input data

<p>This dataset contains all the input data utilized to perform the inversions in Thanwerdas et al. (2023).</p> <p>First, we store here some data used in the paper but originally generated for other studies. Because these original datasets did not have any DOI, the authors have graciously agreed to store their dataset here. Note that the paper associated to each dataset must be properly referenced if utilized.</p> <ul> <li><strong>Cl Concentrations - Wang et al. (2021).zip:</strong> Original Cl concentrations field from Wang et al. (2021).&nbsp;</li> <li><strong>CH4 Fluxes - Saunois et al. (2020).zip: </strong>Original CH4 fluxes used as prior data for the inversions performed as part of the Global Methane Budget 2000-2017 (Saunois et al., 2020).</li> </ul> <p>Second, we store the processed input data generated for the purpose of our study.</p> <ul> <li><strong>CH4 Fluxes - LMDz9696.zip:</strong> Aggregated CH4 fluxes remapped on LMDz horizontal resolution for the five emission categories used in the paper.</li> <li><strong>d13C Signatures - LMDz9696.zip:</strong> &delta;(13C, CH4) at LMDz horizontal resolution for the five emission categories used in the paper.</li> <li><strong>dD Signatures - LMDz9696.zip:</strong> &delta;(D, CH4) at LMDz horizontal resolution for the five emission categories used in the paper.</li> <li><strong>OH O1D Concentrations - LMDz9696-INCA.zip:</strong> OH and O1D monthly concentrations simulated with LMDz-INCA.</li> <li><strong>Masks regions.zip</strong>: Masks for the regions used for the input data and the analysis.</li> </ul> <p>&nbsp;</p>

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

Paraná Basin 3-D conductivity model

<p>This data product includes Magnetotelluric (MT) and Geomagnetic Deep Sounding (GDS) datasets from the Parna&iacute;ba Basin, which are used for data analysis in ModEM. The 3-D resistivity model (Parana3D_res__NLCG_077.rho) and impedance tensors (Parana3D_fwZ_NLCG_077.dat) were derived by performing forward calculation using the included datasets. This data was analyzed and presented in the paper "Estimating Geomagnetically Induced Currents in Southern Brazil Using a 3-D Earth Resistivity Model." See Espinosa et al., 2023 (<em>Space Weather</em>)</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Oct 2022View details →
zenodo40/100

Coffee3D - 3-D models for coffee trees using multiple-view stereo

<p>This is a set of images, odometry data, and 3-D point clouds for 8 coffee tree specimens. Images were captured by a Logitech C920 camera. Odometry data was produced using monocular visual SLAM by Mur-Artal &amp; Tardos&#39; <a href="https://github.com/raulmur/ORB_SLAM2">ORB-SLAM2 </a>SLAM system under <a href="https://github.com/thsant/3dmcap">3dmcap</a>.</p> <p>Two multiple-view stereo systems were employed in 3-D reconstruction: Furukawa &amp; Ponce <a href="https://www.di.ens.fr/pmvs">PMVS</a> and Sch&ouml;enberger&#39;s <a href="https://colmap.github.io">COLMAP</a>.</p>

opencc-by-nc-sa-4.0Aug 2019View details →
zenodo40/100

Dataset of the cross-correlation functions and 3-D Vs model in the central and western NCC

<p>The file "CCFs_NCC.dat" contains all ZZ components cross-correlation fuctions for all available station pairs.</p> <p>The file "Vs_NCC.dat" contains the 3D crustal and uppermost mantle model of central and western NCC via multimodal dispersion inversion.&nbsp;</p>

opencc-by-4.0Nov 2024View details →
zenodo40/100

3-D T1 relaxation time measurements in an equine model of subtle post-traumatic osteoarthritis using MB-SWIFT

<p>This dataset contains Key analysis and plotting scripts, data, and sample images.</p> <p>3-D T1 relaxation time measurements in equine model of post-traumatic osteoarthritis using MB-SWIFT</p> <p>Journal of Orthopaedic Research | DOI: 10.1002/jor.25629</p> <p>Swetha Pala (1), Nina H&auml;nninen (1,2), Ali Mohammadi(1), Mohammadhossein Ebrahimi (1,2), Nikae C.R. te Moller(3), Harold Brommer(3), P. Ren&eacute; van Weeren (3), Janne T.A. M&auml;kel&auml; (1), Rami K. Korhonen (1), Isaac O. Afara(1), Juha T&ouml;yr&auml;s (1,4,5), Santtu Mikkonen (1), Mikko J. Nissi (1*), Olli Nyk&auml;nen (1,2)</p> <p>&nbsp;&nbsp; &nbsp;1Department of Applied Physics, University of Eastern Finland&nbsp;<br> &nbsp;&nbsp; &nbsp;2Research Unit of Medical Imaging, Physics and Technology, University of Oulu<br> &nbsp;&nbsp; &nbsp;3Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University<br> &nbsp;&nbsp; &nbsp;4Science Service Center, Kuopio University Hospital, Kuopio, Finland<br> &nbsp;&nbsp; &nbsp;5School of Information Technology and Electrical Engineering, The University of Queensland&nbsp;</p> <p><br> *Corresponding author<br> Mikko J. Nissi<br> Department of Technical Physics<br> University of Eastern Finland, Kuopio Finland<br> POB 1627<br> 70211 Kuopio<br> mikko.nissi@uef.fi<br> +358-50-5955517<br> Running title: &lsquo;3D T1 of mild PTOA using MB-SWIFT&rsquo;</p> <p><br> Keywords: Quantitative MRI, T1 relaxation, equine model,&nbsp;post-traumatic osteoarthritis, proteoglycan content.</p> <p>Included folders and files are:<br> - Article_figures: all figures published in the manuscript (.svg format)<br> - Data: Raw MRI data files per flip angle (phase &amp; magnitude images) from 28 samples and corresponding fitted T1 maps within respective folders. SPSS structured data files used for statistical analysis.<br> - Matlab scripts: Matlab functions used for data processing and T1 computation, aedes plugins, and data analysis with subfolders and files:<br> &nbsp; &nbsp; - aedes_plugins: plugins for aedes (http://aedes.uef.fi) and scripts for calculation of surface visualisations from relaxation time maps and auto-segmented mesh. &nbsp;&nbsp;<br> &nbsp; &nbsp; - Data processing and T1 computation: Scripts for non-linear 3D T1 fitting. &nbsp; &nbsp; &nbsp;<br> &nbsp; &nbsp; - Analysis: Key scripts used for analysis and plotting.</p> <p>- README.txt: this file describing the contents of the dataset.</p> <p><br> See more info in separate readme files included in sub-folders.</p> <p><br> (Swetha Pala, 31&nbsp;May 2023)</p>

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

low Cerro Gordo; StL 2, Cerro Gordo sandstone; StL 3, between Cerro Gordo and Chunchullo; StL 4, Chunchullo sandstone; StL 5, bed set between Chunchullo and Tatacoa; StL 6, Tatacoa sandstone; StL 7, bed set below Cerbatana conglomerate; StL 8, Cerbatana conglomerate; StL 9, Monkey beds; StL 10, bed set above Monkey beds; StL 12, bed set above Fish bed; StL 14, bed set below La Venta red beds; StL 15, La Venta red beds; StL 16, bed set between La Venta red beds and El Cardón red beds; StL 17, El Cardón red beds; StL 18, San Francisco sandstone; StL 19, Polonia red beds; D, reconstruction of the head of Neodolodus colombianus based on the 3D model of the almost complete skull of the specimen VPPLT 1696. Abbreviations: Fm, Formation; St m, Stratigraphic meter. Reconstruction of N. colombianus made by Tatsuya Shimura. in New remains of Neotropical bunodont litopterns and the systematics of Megadolodinae (Mammalia: Litopterna)

low Cerro Gordo; StL 2, Cerro Gordo sandstone; StL 3, between Cerro Gordo and Chunchullo; StL 4, Chunchullo sandstone; StL 5, bed set between Chunchullo and Tatacoa; StL 6, Tatacoa sandstone; StL 7, bed set below Cerbatana conglomerate; StL 8, Cerbatana conglomerate; StL 9, Monkey beds; StL 10, bed set above Monkey beds; StL 12, bed set above Fish bed; StL 14, bed set below La Venta red beds; StL 15, La Venta red beds; StL 16, bed set between La Venta red beds and El Cardón red beds; StL 17, El Cardón red beds; StL 18, San Francisco sandstone; StL 19, Polonia red beds; D, reconstruction of the head of Neodolodus colombianus based on the 3D model of the almost complete skull of the specimen VPPLT 1696. Abbreviations: Fm, Formation; St m, Stratigraphic meter. Reconstruction of N. colombianus made by Tatsuya Shimura.

opencc-zeroAug 2023View details →
zenodo36/100

Supplementary Material for "Time-domain modelling of 3-D Earth's and planetary electromagnetic induction effect in ground and satellite observations"

<p>1. Magnetic field residuals from Observatory and Swarm data. Details about data origin and pre-processing are given in the main paper.</p> <p>2. Time series of external Spherical Harmonic coefficients estimated from observatory and satellite data as described in the main paper.</p>

opencc-by-4.0Sep 2020View details →
zenodo36/100

3-D geological and petrophysical models with synthetic geophysics based on data from the Hamersley region (Western Australia)

<p>3-D geological and petrophysical models with synthetic geophysics based on data from the Hamersley region (Western Australia)</p> <p>M. Jessell<sup>1,2</sup>, J. Giraud<sup>1,2</sup>, M. Lindsay<sup>1,2&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; </sup></p> <p><sup>1</sup>Centre for Exploration Targeting (School of Earth Sciences), University of Western Australia, 35 Stirling Highway, 6009 Crawley, Australia</p> <p><sup>2</sup>Mineral Exploration Cooperative Research Centre, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Australia</p> <p>Contact author: Jeremie Giraud (jeremie.giraud@uwa.edu.au)</p> <p>Companion dataset to the paper:</p> <p>Structural, petrophysical and geological constraints in potential field inversion using the Tomofast-x open-source code, J. Giraud, V. Ogarko, R. Martin, M. Lindsay, M. Jessell, Geoscientific Model Development Discussions.</p> <p>This dataset contains models and data shown in the paper, in both 2D and 3D:</p> <p>1. Geological model</p> <ul> <li>Reference lithology voxet:</li> </ul> <p>The reference geological model was obtained using public data from the Geological Survey of Western Australia and modified subsequently (stretched vertically and flattened at surface level) for the purpose of this study.</p> <ul> <li>Probability voxet<br> The lithology probability voxet was derived using Monte Carlo simulations for uncertainty estimation as mentioned in the paper.</li> </ul> <p>2. True and inverted models for density and magnetic susceptibility</p> <p>Derivation is detailed in the paper; it uses fictitious density and magnetic susceptibility values.</p> <p>3. Bouguer and total magnetic field anomaly</p> <p>Calculation is detailed in the paper.</p> <p>The authors are supported, in part, by Loop &ndash; Enabling Stochastic 3D Geological Modelling (LP170100985) and the Mineral Exploration Cooperative Research Centre (MinEx CRC) whose activities are funded by the Australian Government&#39;s Cooperative Research Centre Program. This is MinEx CRC Document 2021/3. Mark Lindsay acknowledges funding from the ARC and DECRA DE190100431.</p> <p>It is a companion dataset to:&nbsp;<br> Vitaliy Ogarko, Jeremie Giraud, &amp; Roland. (2021, February 5). Tomofast-x v1.0 source code (Version 1.0). Zenodo. <a href="http://doi.org/10.5281/zenodo.4452620">http://doi.org/10.5281/zenodo.4452620</a></p>

opencc-by-4.0Jan 2021View details →
zenodo36/100

Crustal thicknesses, Moho depths and 3-D density anomaly model for GJI paper: Crustal structure of onshore-offshore Atlantic Canada and environs from constrained 3-D gravity inversion using variable mesh depths by J. Kim Welford

<p>The files are provided as ascii text files in terms of both latitudes/longitudes and eastings/northings. For the 3-D density anomaly model, it is provided with columns of x, y, z, and absolute density. The conversions from latitudes/longitudes to eastings/northings for all of the models and maps in this work are computed with ellipsoid WGS-84 and UTM zone 19 using Generic Mapping Tools.</p>

opencc-by-4.0Nov 2023View details →
zenodo36/100

Supplemental data files for: Evidence for the superposition of tectonic systems in the northern Songliao Block, NE China, revealed by a 3-D electrical resistivity model

<p>Data files for a 3-D electrical resistivity model in the northern Songliao Block, NE China,&nbsp;including the MT data observed there&nbsp; (note the data format is for 3-D inversion using ModEM), and&nbsp;the&nbsp;preferred&nbsp;resistivity&nbsp;model.</p> <p>The software EMdesk from Jilin Kingti Geoexploration Tech, Ltd (Changchun, China) can be&nbsp;used for data analysis and modeling (http://www.kingti.net).</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Dataset files for 'Tan et al., Hydraulic Fracturing Induced Seismicity in the Changning Shale Gas Field: Evidence From 3-D Seismic Velocity Structure and Pore Pressure Field Models'

<p>These files are the data&nbsp;and result files&nbsp;for the manuscript entitled<strong> &#39;Hydraulic Fracturing Induced Seismicity in the Changning Shale Gas Field: Evidence From 3-D Seismic Velocity Structure and Pore Pressure Field Models&#39;</strong> by Tan et al., including</p> <p>catalog.dat : the seismic phase catalog used in seismic tomography</p> <p>station.dat : the&nbsp;station&nbsp;coordinates of the local seismic network</p> <p>relocation.dat : the&nbsp;earthquake relocations obtained by double-difference seismic tomography</p> <p>1-D Vs.xlsx : the 1-D Vs model in the shale gas field</p> <p>3-D Vp.dat: the 3-D Vp&nbsp;model obtained by DD seismic tomography</p> <p>3-D Vs.dat: the 3-D Vs&nbsp;model obtained by DD seismic tomography</p> <p>3-D VpVs.sgy: the 3-D Vp/Vs model obtained by DD&nbsp;seismic tomography (3-5 km)</p> <p>3-D pressure.sgy: the 3-D pore pressure field model obtained by focal mechanism tomography (3-5 km)</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Dataset files for 'Tan et al., Hydraulic Fracturing Induced Seismicity in the Changning Shale Gas Field: Evidence From 3-D Seismic Velocity Structure and Pore Pressure Field Models'

<p>These files are the data&nbsp;and result files&nbsp;for the manuscript entitled<strong>&nbsp;&#39;Hydraulic Fracturing Induced Seismicity in the Changning Shale Gas Field: Evidence From 3-D Seismic Velocity Structure and Pore Pressure Field Models&#39;</strong>&nbsp;by Tan et al., including</p> <p><strong>station.dat</strong> : the&nbsp;station&nbsp;coordinates of the local seismic network (including the station ID, longitude, latitude, elevation(negative)/depth(positive), X, Y)</p> <p><strong>catalog.dat</strong> : the seismic phase catalog used in double-difference (DD) seismic tomography</p> <p><strong>relocation.dat </strong>: the&nbsp;earthquake relocations obtained by DD tomography</p> <p><strong>1-D Vs.xlsx</strong> : the 1-D Vs model in the shale gas field</p> <p><strong>3-D Vp.dat</strong>: the 3-D Vp&nbsp;model obtained by DD tomography</p> <p><strong>3-D Vs.dat</strong>: the 3-D Vs&nbsp;model obtained by DD tomography</p> <p><strong>3-D VpVs.sgy</strong>: the 3-D Vp/Vs model (interpolated, within 3-5 km)</p> <p><strong>3-D pressure.sgy</strong>: the 3-D pore pressure field model (interpolated, within 3-5 km)</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Output files of the 3-D thermal modeling in the Alaska subduction zonne

<p>Data products (&mu;&#39;=0.01275) for &lsquo;Temperature distribution for interplate seismic events in the Alaska subduction zone based on 3-D thermal modeling&rsquo; by Kaya Iwamoto, Nobuaki Suenaga and Shoichi Yoshioka.</p>

opencc-by-4.0Jan 2022View details →

ScienceDex guides

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

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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