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78 results for “3D Model Data”
Modeling polar bear (Ursus maritimus) snowdrift den habitat on Alaska’s Beaufort Sea coast using SnowDens-3D and ArcticDEM data
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Data from: Using 3D modeling and printing to study avian cognition from different geometric dimensions
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3D modeling and 4D flow data of total cavopulmonary connection (TCPC) vs. convergent cavopulmonary connection (CCPC)
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Data from: Integrating 3D models with morphometric measurements to improve volumetric estimates in marine mammals
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Input Data for A Fast Surrogate Model for 3D-Earth Glacial Isostatic Adjustment using Tensorflow (v2.8.0) Artificial Neural Networks
<p>Training datasets for the manuscript A Fast Surrogate Model for 3D-Earth Glacial Isostatic Adjustment using Tensorflow (v2.8.0) Artificial Neural Networks. Two separate datasets are contained for training the ANNs: the 3D-spherically-symmetric (SS) rate-of-change of relative sea level (ROCRSL) and the 3D-SS rate of change of radial displacement (ROCRAD) as a function of SS profiles. Two other datasets contain RSL projections from the explicit (i.e. Seakon 3D - Seakon SS + NMSS ) model and the NMSS model, labelled Seakon_plus_NMSS_RSL and NMSS respectively.</p> <p>Filenames denote the structure of the SS profile: </p> <p>???_?.??_??.*.csv = LT_UMV_LMV.*.{csv,nc}<br> </p> <p>LT = elastic lithosphere thickness (km)</p> <p>UMV = upper mantle viscosity (1E21 Pa s)</p> <p>LMV = lower mantle viscosity (1E21 Pa s)</p> <p>i.e. 96_0.5_10.seakon_S40RTS_lr18-SS.rrad.roc.r360x180.P5.density_wSSRRADROC.csv.bz2 has the SS profile</p> <p>96km elastic lithosphere, 0.5E21 Pa s upper mantle viscosity, 10E21 Pa s lower mantle viscosity</p> <p> </p> <p>The columns of the input files are as follows:</p> <p>LT, UMV, LMV, longitude, latitude, time(t=0), ice(t=0), SS_ROC_RSL (t=0), time(t=-1), ice(t=-1), time(t=-2), ice(t=-2), time(t=-3), ice(t=-3), time(t=-4), ice(t=-4), 3D-SS_ROC_RSL(t=0)</p> <p>units for the above are as follows:</p> <p>km, 1E21 Pas, 1E2 Pas, degrees east (0->360), degrees (-180->180), days since 2000, m, mm/year, days since 2000, m, days since 2000, m, days since 2000, m, days since 2000, m, mm/year</p> <p>where 'days since 2000' assumes exactly 365.25 days per year.</p>
3D Model data from the virtual asset marketplace Sketchfab.
<p>3D Model data from the virtual asset marketplace Sketchfab.</p> <p>Publication: <a href="https://www.mdpi.com/0718-1876/17/3/48">https://www.mdpi.com/0718-1876/17/3/48</a></p>
In Situ Volumetric Imaging and Analysis of FRESH 3D Bioprinted Constructs Using Optical Coherence Tomography (Data and 3D models)
<p>These files contain 3D models and reconstructions of the 3D printed models after OCT imaging of the brain stem, circle of willis, kidney, vestibular apparatus, mixing network, and resolution text. These are from the journal article "In Situ Volumetric Imaging and Analysis of FRESH 3D Bioprinted Constructs Using Optical Coherence Tomography" published in <em>Biofabrication </em>(2022).</p>
Rapid T1 quantification from high resolution 3D data with model-based reconstruction
<p>In-vivo datasets used in the work "Rapid T1 quantification from high resolution 3D data with model-based reconstruction" with DOI: 10.1002/mrm.27502<br> </p>
Data of 3D PPMLR-MHD model Simulation for manuscript "Formation and Evolution of Nightside Transpolar arc and Its Relationship with Energetic Plasma in the Magnetotail Lobe"
<p><span>Data of 3D PPMLR-MHD model Simulation for manuscript "Formation and Evolution of Nightside Transpolar arc and Its Relationship with Energetic Plasma in the Magnetotail Lobe"</span></p> <p><span>These data come from a fully run of a 3D MHD Simulation model that is named PPMLR-MHD model (detailed descriptions below).</span></p> <p><span>There are 2 types of data files:</span></p> <p><span>1) X15dXXXX.mat is saved simulation parameters. </span></p> <p><span>2) Xing15XXXX_heatflux.mat is saved heat flux from simulation parameters. </span></p> <p><span>XXXX is the number of files, and files with the same serial number correspond to the same time.</span></p> <p><span> </span></p> <p><span>The first type files of data include the following parameters:</span></p> <p><span>time, x, y, z, logrho, Vx, Vy, Vz, Bx, By, Bz, Pr, Jx, Jy, Jz</span></p> <p><span>Where, time is simulation time, which need to plus the start time to transfer them to universal time: time+16:00.</span></p> <p><span> (x,y,z) are the three components of the position of simulation point in GSM coordinates;</span></p> <p><span> logrho is the plasma density at the simulation point;</span></p> <p><span> (Vx, Vy,Vz) are the three components of plasma velocity at the simulation point in GSM coordinates;</span></p> <p><span> (Bx, By,Bz) are the three components of magnetic field at the simulation point in GSM coordinates;</span></p> <p><span> Pr is the plasma dynamic presure at the simulation point;</span></p> <p><span> (Jx, Jy,Jz) are the three components of plasma electric current at the simulation point in GSM coordinates;</span></p> <p><span> </span></p> <p><span>The second type file of data includes the simulated heat flux along the magnetic field lines at the simulation point in GSM coordinates. </span></p> <p><span>PPMLR-MHD model</span></p> <p><span>The PPMLR-MHD model is on the basis of an extension of the piecewise parabolic method (1) with a Lagrangian remap to magnetohydrodynamics (MHD) (2, 3). It is a three-dimensional MHD model, designed specially for the solar wind–magnetosphere–ionosphere system (4-6). The model possesses a high resolution in capturing MHD shocks and discontinuities and a low numerical dissipation in examining possible instabilities inherent in the system (4).</span></p> <p><span>The model uses a Cartesian coordinate system with the Earth’s center at the origin and X, Y, and Z axes pointing towards the Sun, the dawn-dusk direction, and the north, respectively. The size of the numerical box extends from 25 RE to –100 RE along the Sun-Earth line and from –50 RE to 50 RE in Y and Z directions, with 240×240×240 grid points and a minimum grid spacing of 0.2 RE. An inner boundary of radius 3 RE is set for the magnetosphere to avoid the complexities associated with the plasmasphere and large MHD characteristic velocity from the strong magnetic field (6). An electrostatic ionosphere shell with height-integrated conductance is imbedded, allowing an electrostatic coupling process introduced between the ionosphere and the magnetospheric inner boundary. The Earth’s magnetic field is approximated by a dipole field with a dipole moment of 8.06×1022 A/m in magnitude. The model is run to solve the whole system by inputting the real interplanetary conditions for the current event.</span></p>
CT data and 3D models associated with: Palaeoneurology of the Early Cretaceous iguanodont Proa valdearinnoensis and its bearing on the parallel developments of cognitive abilities in theropod and ornithopod dinosaurs
<p><i>Proa valdearinnoensis </i>is a relatively large-headed and stocky iguanodontian dinosaur from the latest Early Cretaceous of Spain. Its braincase is known from three specimens. Similar to that of other dinosaurs, it shows a mosaic ossification pattern in which most of the bones seem to have fused together indistinguishably while a few bones (frontoparietal, basioccipital) might have remained loosely attached. The endocasts of the three specimens are described based on CT data and digital reconstructions. They show unmistakable morphological similarities with the endocast of closely related taxa, such as <i>Sirindhorna khoratensis </i>(which is close in age but from Thailand). This supports a high conservatism of the endocranial cavity. The issue of volumetric correspondence between endocranial cavity and brain in dinosaurs is analysed. Although a brain-to-endocranial cavity (BEC) index of 0.50 has been traditionally used, we employ instead 0.73. This is indeed the mid-value between the situation in adults of <i>Alligator mississippiensis</i> and <i>Gallus gallus</i>, which are members of the extant bracketing taxa of dinosaurs (Crocodilia and Aves). We thence gauge the level of encephalisation of <i>Proa valdearinnoensis</i> by the calculation of the Encephalisation Quotient (EQ), which remains valuable as a metric for assessing the degree of cognitive function in extinct taxa, especially those with fully ossified braincases like dinosaurs and other archosaurs. The EQ obtained for <i>Proa valdearinnoensis</i> (3.611) suggests that this species was significantly more encephalised than most if not all extant non-avian, non-mammalian amniotes. Our work adds to the growing body of data concerning theoretical cognitive capabilities in dinosaurs and supports the idea that increasing encephalisations were fostered not only once in theropods but also in parallel in the shorter-lived lineage of ornithopods. <i>Proa valdearinnoensis</i> was ill-equipped to respond to theropod dinosaurs and possibly lived in groups as a strategy to mitigate the risk of being predated upon. We hypothesize that group-living and protracted caring of juveniles in this and possibly many other iguanodontian ornithopods favoured a degree of encephalisation that was outstanding by reptile standards.</p>
Preliminary DOI/Repository of ALPINE3D and SNOWPACK data of the submitted paper "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model"
<p>There are 2 zip folders in this repository.</p> <p>"a3d_jgr.zip" contains a folder structure that must be kept as it is in order to run the simulation in the current configuration.<br> The setup contains both input and output data as well as the model configuration as used in the submitted manuscript <br> "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".</p> <p>The zip file contains 3 main folders:</p> <ul> <li>base_setup_files</li> <li>a3d_jgr_alpha1</li> <li> a3d_jgr_alpha3</li> </ul> <p>The "base_setup_files" contains all input files that are necessary to run the reference (R) simulation ("a3d_jgr_alpha1" folder) and the comparison "C" scenario ("a3d_jgr_alpha3") folder. In the a3d_jgr_alpha1 and a3d_jgr_alpha3 folders you find the corresponding outputs as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each a3d_jgr_alphax/setup/io.ini file. The input data is already linked accordingly in each io.ini file.</p> <p>a3d_jgr_alpha1 also contains the detailed snow profiles for each point along the transects.</p> <p>To reproduce the results, download and compile the source code for the adjusted ALPINE3D model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/alpine3d.git under the "alpine3d_mosaic" branch. After installing, you can run the provided model setup uploaded here.</p> <p>_________________________________________________________________________________________________________<br> <br> "SNOWPACK_JGR.zip" contains both input and output data for SNOWPACK as well as the model configuration as used in the submitted manuscript "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".</p> <p>The zip file contains 2 main folders: </p> <ul> <li>SNOWPACK_JGR_ALPHA1</li> <li>SNOWPACK_JGR_ALPHA3</li> </ul> <p>In the SNOWPACK_JGR_ALPHA1 (reference "SP_R" simulation) and SNOWPACK_JGR_ALPHA3 (comparison "SP_C" scenario) folders you find the corresponding inputs, outputs and configuration as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each SNOWPACK_JGR_ALPHA/setup/io.ini file. The input data is already linked accordingly in each io.ini file.</p> <p>To reproduce the results, download and compile the source code for the adjusted SNOWPACK model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/snowpack.git under the "snowpack_mosaic" branch. After installing, you can run the provided model setup uploaded here.</p>
Magnetotelluric data in Subei area, northern Tibet and the 3D isotropic/anisotropic models
<p>This dataset contains four folders. They are ‘aniinv’, ‘isoinv’, ‘sensitivity_test’, ‘syn_mod_test’, respectively. In the ‘aniinv’ folder, there are three sub-folders include ‘azimu_ani_inv’, ‘gener_ani_inv’, ‘verti_ani_inv’, indicating the inversion results for azimuthal, general, and vertical anisotropic inversions, respectively. The ‘isoinv’ folder contains results for isotropic inversion. The ‘sensitivity_test’ folders contains modeified models and their responses for sensitivity tests of anomalies. The ‘syn_mod_test’ folder contains a synthetic model constructed according the final model, the responses of this model, and the recovering for this model. In each folder, there is a ‘readme.txt’ file describing the details of individual files.</p>
Supplemental 3D Model Data - Hapalosiphonacean cyanobacteria (Nostocales) thrived amid emerging embryophytes in a 407-million-year-old landscape
<p>Three-dimensional reconstruction models of cyanobacteria from a 407 million year old fossil from the Lower Devonian Rhynie chert, UK. Thin sections SU.PB. 2023.0.1.2.8 from the Palaeobotany Collection in the Pôle Collections scientifiques et patrimoniales. Bibliothèque de Sorbonne Université, Paris (France).</p> <p>Imaris files (.IMS) can be viewed using the Imaris Viewer software, freely available in both Windows and Mac versions from https://imaris.oxinst.com/imaris-viewer. </p>
Data for: Contributions of deep learning to automated numerical modelling of the interaction of electric fields and cartilage tissue based on 3D images
<p>Replication data for: Contributions of deep learning to automated numerical modelling of the interaction of electric fields and cartilage tissue based on 3D images</p> <p> </p> <p> </p>
Data from: Study on mechanical characteristics of conductors with 3D finite element models
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CT data and 3D models associated with: Palaeoneurology of the Early Cretaceous iguanodont Proa valdearinnoensis and its bearing on the parallel developments of cognitive abilities in theropod and ornithopod dinosaurs
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3D Models from Morales, J. I., et al. (2015). "Measuring Retouch Intensity in Lithic Tools: A New Proposal Using 3D Scan Data." Journal of Archaeological Method and Theory 22(2): 543-558.
<p>This document compiles the complete set of 3D models and the measurements used for the experimental work of the paper:</p> <p>Morales, J. I., et al. (2015). "Measuring Retouch Intensity in Lithic Tools: A New Proposal Using 3D Scan Data." Journal of Archaeological Method and Theory 22(2): 543-558.<br> <br> It includes 3D scans from both unmodified and modified flakes (X & Xb). All the flakes produced in this experiment were produced by freehand hard hammer percussion and no specific flaking method was followed. Diferents types of tertiary evaporitic flint described in Soto, M., et al. (2017). "The chert abundance ratio (CAR): a new parameter for interpreting Palaeolithic raw material procurement." J. Archaeol Anthropol Sci. (https://doi.org/10.1007/s12520-017-0516-3) were used.</p> <p> </p>
3D-MSNet: A point cloud based deep learning model for untargeted feature detection and quantification in profile LC-HRMS data
<p>Supplementary data of 3D-MSNet</p>
Data from: Ellipsoid segmentation model for analyzing light-attenuated 3D confocal image stacks of fluorescent multi-cellular spheroids
In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more physiologically relevant 3D models, such as spheroid micro-tumor cultures. If suitable fluorescent labels are applied, confocal 3D image stacks can characterize the structure of such volumetric cultures and, for example, cell proliferation. However, several issues hamper accurate analysis. In particular, signal attenuation within the tissue of the spheroids prevents the acquisition of a complete image for spheroids over 100 micrometers in diameter. And quantitative analysis of large 3D image data sets is challenging, creating a need for methods which can be applied to large-scale experiments and account for impeding factors. We present a robust, computationally inexpensive 2.5D method for the segmentation of spheroid cultures and for counting proliferating cells within them. The spheroids are assumed to be approximately ellipsoid in shape. They are identified from information present in the Maximum Intensity Projection (MIP) and the corresponding height view, also known as Z-buffer. It alerts the user when potential bias-introducing factors cannot be compensated for and includes a compensation for signal attenuation.
Functional and ecomorphological evolution of orbit shape in Mesozoic archosaurs is driven by body size and diet: Geometric morphometric data, 3D models (stl files), FEA models (Hypermesh, Abaqus files)
<p class="MsoNormal">The orbit is one of several skull openings in the archosauromorph skull. Intuitively, it could be assumed that orbit shape would closely approximate the shape and size of the eyeball resulting in a predominantly circular morphology. However, a quantification of orbit shape across Archosauromorpha using a geometric morphometric approach demonstrates a large morphological diversity despite the fact that the majority of species retained a circular orbit. This morphological diversity is nearly exclusively driven by large (skull length > 1000 mm) and carnivorous species in all studied archosauromorph groups, but particularly prominently in theropod dinosaurs. While circular orbit shapes are retained in most herbivores and smaller species, as well as in juveniles and early ontogenetic stages, large carnivores adopted elliptical and keyhole-shaped orbits. Biomechanical modeling using finite element analysis reveals that these morphologies are beneficial in mitigating and dissipating feeding-induced stresses without additional reinforcement of the bony structure of the skull.</p>
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.