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478 results for “3D data”
Additional data and models for the article "Role of metasomatism in the development of the East African Rift at the Northern Tanzanian Divergence: Insights from 3D magnetotelluric modelling."
<p>Additional data and models for the article "Role of metasomatism in the development of the East African Rift at the Northern Tanzanian Divergence: Insights from 3D magnetotelluric modelling."</p> <p>This data package includes:</p> <p>1-ModEM rho and dat format files of the final preferred model.</p> <p>2-vtk version of this model</p> <p>3-Scripts to plot the MT models</p> <p>4-Water content models calculated with MATE</p> <p>5-Scripts to plot the water content models</p> <p>6-Parameter files used in water calculation with MATE</p> <p>7- EDI files used in the model.</p>
Data from: facial growth and development trajectories based on 3D images: geometric morphometrics with a deformation perspective
<p>Developmental changes of facial shape are commonly investigated through geometric morphometrics. A limitation with this approach is the inability to investigate patterns of morphological changes at local scale. This could be addressed through quantifying the deformation required to deform one shape to another. This study aimed to investigate changes in mean, rate, and variance of facial shape at local scale using geometric morphometrics through deformation perspective. 2112 Europeans 3 to 40 years-old from the 3D Facial Norms project were included. Shape and rate trajectories from partial least-squares regressions revealed that the developmentally protrusive nasal bridge was due to local expansion in surrounding tissues as opposed to shape changes in nasal bridge per-ser. Local expansion of the supraorbital region, in particular the medial part in males, resulted in the sloping forehead and deep-situated eyes with development. Facial shape variation increased non-linearly with age (p < 0.05), with features having larger rate of change becoming more developmentally diversified. In summary, our deformation perspective facilitates unravelling morphogenetic processes underlying shape changes. Our extended analytical scope inspires novel measures worthy of consideration while establishing facial growth charts. The analytical framework in this study is broadly applicable for analysis of shape changes in general.</p>
Data from: Ultra-uniform, strong and ductile 3D printed titanium alloy through bifunctional alloy design
<p>Coarse columnar grains and heterogeneously distributed phases commonly form in metallic alloys produced by three-dimensional (3D) printing and are often considered undesirable because they can impart non-uniform and inferior mechanical properties. We demonstrate a design strategy to unlock consistent and enhanced properties directly from 3D printing. Using Ti−5Al−5Mo−5V−3Cr as a model alloy, we show that adding molybdenum (Mo) nanoparticles promotes grain refinement during solidification and suppresses the formation of phase heterogeneities during solid-state thermal cycling. The microstructural change due to the bifunctional additive results in uniform mechanical properties and simultaneous enhancement of both strength and ductility. We demonstrate how this alloy can be modified by a single component to address unfavourable microstructures, providing a pathway to achieve desirable mechanical characteristics directly from 3D printing.</p>
Thermal modeling of subduction zones with prescribed and evolving 2D and 3D slab geometries data
<p>Deforming subduction zone finite element model temperature, velocity, surface and flux field data as reported in the work:</p> <p>N. Sime, C. R. Wilson and P. E. van Keken<br> Thermal modeling of subduction zones with prescribed and evolving 2D and 3D slab geometries.</p>
Podcast: Synthetic 3D data and archeology. Régine Hunziker and Andrei Aioanei, Université de Strasbourg
<p>Prof. Régine Hunziker-Rodewaldt und Andrei Aioanei sprechen über die Bedeutung von komplexen interoperablen Forschungsdaten. Insbesondere 3D-Datensätze werden immer wichtiger. Die beiden Forscher sprechen über Data Science mit 3D, aber auch über die Bedeutung von künstlicher Intelligenz.</p> <p>Prof. Régine Hunziker-Rodewaldt and Andrei Aioanei are speaking about the importance of complex interoperable research data. Especially 3D data sets become more important. Both researches speak about data science with 3D, and also the importance of artificial intelligence.</p> <p>Prof. Régine Hunziker-Rodewaldt e Andrei Aioanei parlano dell'importanza di dati di ricerca complessi e interoperabili. In particolare, i set di dati 3D diventano sempre più importanti. Entrambi i ricercatori parlano della scienza dei dati in 3D e dell'importanza dell'intelligenza artificiale.</p> <p>Prof. Régine Hunziker-Rodewaldt et Andrei Aioanei parlent de l'importance des données de recherche complexes et interopérables. Les ensembles de données en 3D deviennent particulièrement importants. Les deux chercheurs parlent de la science des données en 3D et de l'importance de l'intelligence artificielle.</p>
Data for: Melt electrowriting enabled 3D liquid crystal elastomer structures for cross-scale actuators and temperature field sensors
<p>Liquid crystal elastomers have garnered significant attention due to their remarkable capability to undergo reversible strains and shape transformations under various stimuli. Early studies on LCE primarily focused on limited shape changes of macrostructures or quasi-3D microstructures. However, fabricating complex cross-scale LCE-based 3D structures still remains challenging. Here, we report a compatible method, the Melt-Electrohydrodynamic (Melt-EHD) 3D printing, to create LCE-based microfiber actuators and various 3D actuators across micrometer to centimeter scales, showcasing their actuation to thermal airflow stimulus. By controlling printing parameters, microfiber actuators with different diameters (5 μm~70 μm), and tunable properties including actuation strain (10%~55%), actuation stress (0~0.6 MPa), and large work density (~160J/kg) have been demonstrated. Under dynamic thermal airflow stimulus at 15 Hz, the microfiber actuators lift weights over 3500 times heavier than themselves. These 3D structures were obtained by depositing LCE microfibers along pre-programmed paths, including various gradient-responsive elementary structural units, 1 mm-sized microgripper, and various large area 3D lattice structures. In addition, by integrating a Deep Learning model, we have demonstrated, for the first time, large area (≥ centimeter scale), real-time (24 Hz sampling frequency), high-precision (~95%) LCE grid based spatial temperature field sensors with a spatial resolution of only 4 mm.</p>
Data and code for "Niobium Quantum Interference Microwave Circuits with Monolithic Three-Dimensional (3D) Nanobridge Junctions"
<p>Data and measurements scripts for the paper "Niobium Quantum Interference Microwave Circuits with Monolithic Three-Dimensional (3D) Nanobridge Junctions"</p> <p>The package "stuelab" used in the scripts is also included. <br><br>Funding by the Deutsche Forschungsgemeinschaft (DFG) via Grants No. BO 6068/1-1, No. BO 6068/2-1, and No. KO 1303/13-2, and support from the COST actions NANOCOHYBRI (CA16218) and SUPERQUMAP (CA21144)</p>
Idealized wave data in support of Directional Breaking Kinematics Observations from 3D Stereo Reconstruction of Ocean Waves
<p>You will find the WaveWatchIII data output from idealized solutions of Romero 2019, ST4 and ST6</p> <p>Data are in Netcdf format and include metadata.</p> <p>Each file corresponds to a duration-limited solution with constant wind speed of 13 m/s</p>
MetaVision3D: Automated Framework for the Generation of Spatial Metabolome Atlas in 3D | MALDI Data
<p>This repository contains MALDI data related to the Ma et al. study "<strong>MetaVision3D: Automated Framework for the Generation of Spatial Metabolome Atlas in 3D</strong>". Processed MALDI pixel-by-pixel .csv files for both metabolomics and lipidomics for two Wild-type samples, one 5xFAD sample and one GAA sample. If you use this dataset in your research, please consider citing the above study.</p> <p>The content of the files are:<br>wt.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for wild-type sample.</p> <p>5x.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for 5xFAD sample.</p> <p>gaa.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for GAA sample.</p> <p>wt2.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for wild-type2 sample.</p>
Application Case 3: Data sets consisting of 3D scans, 3D model and the derived metadata, from two different software programs
<p>In this repository we provide 3D scan projects and the 3D models processed from them with their metadata using the example of a wood sample. The metadata was generated using our metadata generation script, which is described in the referenced publication.</p> <p>The 3D scan projects were created in different software (atos v6.2, atos 2016 and zeiss 2023). For each there is a scan project, a 3D model and the generated metadata with and without uri in this repository.</p> <p>The publication in which this application case is included: Homburg, T., Cramer, A., Raddatz, L. <em>et al.</em> Metadata schema and ontology for capturing and processing of 3D cultural heritage objects. <em>Herit Sci</em> <strong>9</strong>, 91 (2021). <a href="https://doi.org/10.1186/s40494-021-00561-w">https://doi.org/10.1186/s40494-021-00561-w</a></p> <p>Python scripts for exporting metadata can be found here: <a href="https://github.com/i3mainz/3dcap-md-gen/tree/0.1.3">GitHub - i3mainz/3dcap-md-gen</a></p>
Data for preprint: "Non-Telecentric 2P microscopy for 3D random access mesoscale imaging "
<p>Numerical data used in latest version of preprint: "Non-Telecentric 2P microscopy for 3D random access mesoscale imaging ", https://www.researchsquare.com/article/rs-121292/v1</p>
Source data for "Non-Telecentric two-photon microscopy for 3D random access mesoscale 2 imaging"
<p>Source data used in a manuscript "Non-Telecentric two-photon microscopy for 3D random access mesoscale 2 imaging"</p> <p> </p> <p> </p> <p> </p>
3D Point Cloud Data for LiDAR-based Mobile Robot
<p>LiDAR point cloud data serves as an machine vision alternative other than image. Its advantages when compared to image and video includes depth estimation and distance measurement. Low-density LiDAR point cloud data can be used to achieve navigation, obstacle detection and obstacle avoidance for mobile robots. autonomous vehicle and drones. In this metadata, we scanned over 1400 objects and classified it into 6 groups of object namely, human, cars, motorcyclist, signboard, road divider and others.</p>
Pultruded carbon fiber profiles - 3D x-ray tomography data-sets for two different pultruded profiles
<p>3D X-ray scan on Zeiss Xradia 520</p> <table> <tbody> <tr> <td> <table> <tbody> <tr> <td> </td> <td>A1</td> <td>A2</td> <td>A2S</td> <td>B1</td> <td>B1S</td> <td>B2</td> <td>B3</td> </tr> <tr> <td>Scanning Voxel size [μm]</td> <td>1.9767</td> <td>1.97</td> <td>1.9731</td> <td>1.9751</td> <td>1.9753</td> <td>1.9771</td> <td>1.9752</td> </tr> <tr> <td>FoV: (x; y; z) [mm]</td> <td>2.0x2.0</td> <td>2.0x2.0</td> <td>2.0x2.0</td> <td>2.0x2.0</td> <td>2.0x2.0</td> <td>2.0x2.0</td> <td>2.0x2.0</td> </tr> <tr> <td>Accelerating Voltage [kV]</td> <td>30</td> <td>30</td> <td>30</td> <td>30</td> <td>30</td> <td>30</td> <td>30</td> </tr> <tr> <td>Power [W]</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> </tr> <tr> <td>Filter</td> <td>Air</td> <td>LE1</td> <td>LE1</td> <td>LE1</td> <td>LE1</td> <td>Air</td> <td>LE1</td> </tr> <tr> <td>Optical magnification</td> <td>4x</td> <td>4x</td> <td>4x</td> <td>4x</td> <td>4x</td> <td>4x</td> <td>4x</td> </tr> <tr> <td>Detector to sample distance [mm]</td> <td>25.5</td> <td>25.52</td> <td>26.82</td> <td>25.4</td> <td>26.75</td> <td>25.5</td> <td>25.8</td> </tr> <tr> <td>Source to sample distance [mm] </td> <td>10.6</td> <td>10.61</td> <td>11.11</td> <td>10.5</td> <td>11.1</td> <td>10.6</td> <td>10.7</td> </tr> <tr> <td>Exposure time [s]</td> <td>15</td> <td>18</td> <td>20</td> <td>18</td> <td>18</td> <td>15</td> <td>18</td> </tr> <tr> <td>No. of projections</td> <td>5201</td> <td>5201</td> <td>5201</td> <td>5201</td> <td>5201</td> <td>5201</td> <td>5201</td> </tr> <tr> <td>Rotation</td> <td>360</td> <td>360</td> <td>360</td> <td>360</td> <td>360</td> <td>360</td> <td>360</td> </tr> <tr> <td>Binning</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> </tr> <tr> <td>Total scanning time [h]</td> <td>26</td> <td>33</td> <td>33</td> <td>32</td> <td>32</td> <td>26</td> <td>29</td> </tr> <tr> <td>File-size [GB]</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> <td>2</td> </tr> </tbody> </table> </td> </tr> </tbody> </table>
Data from: Passive sampling of environmental DNA in aquatic environments using 3D-printed hydroxyapatite samplers
<p>The study of environmental DNA released by aquatic organisms in their habitat offers a fast, non-invasive and sensitive approach to monitor their presence. Common eDNA sampling methods such as water filtration and DNA precipitation are time consuming, require difficult-to-handle equipment and partially integrate eDNA signals. To overcome these limitations, we created the first proof of concept of a passive, 3D-printed and easy-to-use eDNA sampler. We designed the samplers from hydroxyapatite (HAp samplers), a natural mineral with a high DNA adsorption capacity. The porous structure and shape of the samplers were designed to optimise DNA adsorption and facilitate their handling in the laboratory and in the field. Here we show that HAp samplers can efficiently collect genomic DNA in controlled set-ups, but can also collect animal eDNA under controlled and natural conditions with yields similar to conventional methods. However, we also observed large variations in the amount of DNA collected even under controlled conditions. A better understanding of the DNA-hydroxyapatite interactions on the surface of the samplers is now necessary to optimise the eDNA adsorption and to allow the development of a reliable, easy-to-use and reusable eDNA sampling tool.</p>
Research data supporting "Tunable microgel-templated porogel (MTP) bioink for 3D bioprinting applications"
<p>Raw research data supporting Ouyang L. et al., 2022, Advanced Healthcare Materials</p> <p><a href="https://doi.org/10.1002/adhm.202200027">https://doi.org/10.1002/adhm.202200027</a></p>
CAD file and chromatographic data for determination of diclofenac in wastewater using a 3D printed immunosorbent device
<p>CAD file of the 3D-printed device (in FreeCAD) and chromatographic data for determination of diclofenac in wastewater associated to Fig. S5 (in CSV) of the paper "A 3D printed spinning cup-shaped device for immunoaffinity solid-phase<br> extraction of diclofenac in wastewaters" published in Microchimica Acta 2022 (DOI:10.1007/s00604-022-05267-9.)</p>
Density driven flow in porous media by 3D print_measured data
<p>Density-driven convection in porous media constructed with 3D printed porous blocks were performed. This dataset is the measured total dissolved MEG and flux across the top interface.</p>
Accurate lattice parameters from 3D electron diffraction data I: Optical distortions
<p>3D ED data were measured with an FEI Tecnai G2 20 transmission electron microscope equipped with an Olympus SIS Veleta camera (CCD, 14 bit, 2048 x 2048 px) and a NanoMEGAS Digistar precession unit.</p> <p>Supporting information for article submitted to a scientific journal. Examples 1 and 2 including manuals and command files for optical distortions refinement in 3D ED data using PETS2 software.</p> <p>Manuals for the examples are available as the supporting information of the submitted article.</p>
Raw data files for "3D vs. turbostratic: controlling metal-organic framework dimensionality via N-heterocyclic carbene chemistry" manuscript
<p>Raw data files for a manuscript "3D vs. turbostratic: controlling metal-organic framework dimensionality via N-heterocyclic carbene chemistry" published in Chemical Science. <a href="https://doi.org/10.1039/D2SC01041K">https://doi.org/10.1039/D2SC01041K</a></p> <p>The files are organized by manuscript figure names and are in a simple text or CSV format. The headers contain the necessary information such as column designations, units, etc.</p> <p> </p> <p> </p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.