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249 results for “3D Structure”
3D structural and probabilistic modeling of geothermal reservoir horizons in the Northern Eifel and its foreland
<p>This repository contains the supplementary data to the submitted publication titled "3D structural and probabilistic modeling of geothermal reservoir horizons in the Northern Eifel and its foreland" which was submitted to the Journal "Geothermal Energy" (https://geothermal-energy-journal.springeropen.com/). </p>
Dataset for "Light and Mass Transport Computations Guide the Fabrication of 3D-Structured TiO2 and Au/TiO2 Aerogel Photocatalysts for Efficient Hydrogen Production in the Gas Phase"
<p>This dataset is related to "Light and Mass Transport Computations Guide the Fabrication of 3D-Structured TiO<sub>2</sub> and Au/TiO<sub>2</sub> Aerogel Photocatalysts for Efficient Hydrogen Production in the Gas Phase" published in <em> Chemistry of Materials</em> <strong>2023</strong> <em>35</em> (10), 3849-3858.</p> <p>Each file contains the dataset for the respective Figure.</p> <p><strong>File 'Figure 1': </strong>Optical Photograph and SEM images of a 3D printed TiO<sub>2</sub> aerogel.</p> <p><strong>File 'Figure 2': </strong>The subdirectory <em>'absorbed'</em> contains data for the calculation of the light absorption of unstructured, sc-structured, and fcc-structured aerogels. A more detailed description is presented in the <em>'readme</em>' file. The subdirectory <em>'flux_time_resolved'</em> contains data for the calculation of the time-resolved flux in a fcc-structured aerogel. A more detailed description is presented in the readme file.</p> <p><strong>File 'Figure 3': </strong>Measured and calculated data of the pressure drop of unstructured, sc-structured, and fcc-structured aerogels. Images of the velocity profile. Images of simulated velocity profiles of an sc-structured aerogel without and with a surrounding wall. The simulations were performed in COMSOL.</p> <p><strong>File 'Figure 4': </strong>Data of the hydrogen evolution experiments.</p> <p><strong>File 'Figure SI1 and Table SI1': </strong>Data of nitrogen physisorption experiments. <em>'Figure_SI1-sample-identification'</em> contains a list to assign the dataset to the respective subfigures in Figure SI1. <em>'Table_SI1-sample-identification' </em>contains a list to assign the dataset to the respective entry in Table SI1.</p> <p><strong>File 'Figure SI2': </strong>Data of the hydrogen evolution experiments with a gas stream containing pure water and a water/methanol mixture, respectively.</p> <p><strong>File 'Figure SI3': </strong>Data of the UV cleaning experiment.</p> <p><strong>File 'Figure SI4': </strong>Chromatograms recorded during hydrogen evolution experiments to discuss the formation of side products.</p> <p><strong>File 'Figure SI5':</strong> Data of two consecutive hydrogen evolution experiments.</p> <p><strong>File 'Figure SI6': </strong>Data of the hydrogen evolution experiments for an fcc-structured and sc-structured TiO<sub>2</sub> aerogel of similar light absorption. Image of a simulated velocity profiles for an unstructured aerogel. The simulation were performed in COMSOL.</p> <p><strong>File 'Figure SI7': </strong>Data of an hydrogen evolution experiments of an fcc-structured TiO<sub>2</sub> aerogel for flow rates in a range of 1.25 to 20 mL min<sup>-1</sup>.</p> <p><strong>File 'Figure SI8': </strong>TEM/STEM images including EDX mapping of an Au/TiO<sub>2</sub> aerogel fragment.</p> <p><strong>File 'Figure SI9': </strong>Data of the hydrogen evolution, the irradiance of the LED, and the amount of water and methanol.</p> <p><strong>File 'Figure SI10': </strong>Attenuated total reflection infrared spectra of TiO<sub>2</sub> nanoparticle powder and aerogel after UV cleaning.</p> <p><strong>File 'Figure SI11': </strong>XRD pattern of TiO<sub>2</sub> nanoparticles and a reference of anatase TiO<sub>2</sub>.</p> <p><strong>File 'Figure SI12': </strong>Data of hydrogen evoltion for TiO<sub>2</sub> nanoparticle powders.</p> <p><strong>File 'Figure SI13': </strong>Transmission and reflectance spectra of a TiO<sub>2</sub> aerogel.</p> <p><strong>File 'Figure SI14': </strong>Calculated transmission and reflectance for an optical thickness and a scattering albedo in a range of 0 to 5 and 0 to 1, respectively. The data was calculated by solving the radiative transfer equation, as implemented in the DISORT algorithm. A more detailed description of the calculation and data processing is provided in the <em>'readme'</em> file. The code of the DISORT algorithm is provided in the <em>'DISORT'</em> subdirectory.</p> <p><strong>File 'Figure SI16': </strong>Data of the derived absorption and scattering coefficient.</p> <p><strong>File 'Figure SI17': </strong>Data of the light absorption and the scattering coefficient. The <em>'readme'</em> file contains a description of the data processing for the light absorption dataset.</p>
Interactive 3D PDF file for the structures 10 hr juvenile of Oikopleura dioica and supplementary movie S1-20 with high resolution
Open the record for dataset details and reuse information.
3D Cortical Bone and Trabecular Bone Structure [synthetic data, simple, capsule shell model]
<p>Trabecular bone patterns are mimicked by generating and arranging "capsule shells" in a three-dimensional voxel by following probability distribution. Ground truth (gt) contains 4 labels (Background: 0, Cortical Bone: 11, Trabecular Bone: 21, Cavity: 31).</p>
Supplementary data for article 'Estimating and abstracting the 3D structure of feline bones using neural networks on X-ray (2D) images'
<p>3D DICOM volumes (CT scans) of feline femora, PNGs generated from them as DRRs using MeVisLab, and STLs generated from the DICOM volumes with MIMICS or MeshLab. Software to work with these files can be found at http://doi.org/10.5281/zenodo.3829423</p>
FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure
<p>This upload contains the FISH datasets used in Zou et al. integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure.</p> <p>If you use the datasets, we would be grateful if you cited the following paper:</p> <p>Zou, C., Zhang, Y., Ouyang, Z. (2016) HSA: integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure. Genome Biology, 17: 40.</p>
Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma - Location Data
<p>This dataset is meant to be used with "Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma - Results and Data". It provides spatial output data for 4 different setups (spheroid, traditional, 3d gravity, and traditional floating) of an agent-based model of <i>in vitro </i>tuberculosis infection models. </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>
Crystal structure of natural product Argyrin-D determined by 3D electron diffraction
<p>360° rotation of the Argyrin D model (stick mode with carbon, yellow; nitrogen, blue; oxygen, red; sulfur, gold and hydrogen, white) defined by a 2Fo-Fc map contoured at 1.2 sigma (grey mesh). The model was refined at a resolution of 1.1Å in Phenix using implemented electron scattering factors and restraints to R and Rfree values of 17.3 and 18.6%, respectively.</p>
The dataset for an article - An Evaluation of 3D-Printed Materials' Structural Properties Using Active Infrared Thermography and Deep Neural Networks Trained on the Numerical Data
<p>Dataset used in the research presented in the article:</p> <p>Szymanik, Barbara. 2022. "An Evaluation of 3D-Printed Materials’ Structural Properties Using Active Infrared Thermography and Deep Neural Networks Trained on the Numerical Data" <em>Materials</em> 15, no. 10: 3727. https://doi.org/10.3390/ma15103727</p> <p>The database in the .mat (matlab) format contains arrays of double type related to: A - original thermograms obtained for the plate made with the 3D printing technique Ar - thermograms with ROI included FITorg - approximation of original thermograms ImDiff, ImInt, ImProp - data obtained after subtracting the approximation.</p>
RWQM 3d SHO Structure 2
<p>This is an interactive plot of the second structure for a 3D SHO potential calculated from Real Wave Quantum Mechanics using the matrix method with a radius of 27. It can be downloaded and should run in most browsers.</p> <p>The size of the dots represents the magnitude of the FR at each point. The colour is a cyclic mapping of the phase after removal of the phase alternation which characterizes RWQM fields.</p> <p>This structure corresponds with an n=2, l=1,m=0 orbital. Note that the lobes have opposite phases, and that there is further phase structure within them.</p>
RWQM 3d SHO Structure 8
<p>This is an interactive plot of the 8th structure for a 3D SHO potential calculated from Real Wave Quantum Mechanics using the matrix method with a radius of 27. It can be downloaded and should run in most browsers.</p> <p>The size of the dots represents the magnitude of the FR at each point. The colour is a cyclic mapping of the phase after removal of the phase alternation which characterizes RWQM fields.</p> <p> </p>
RWQM 3d SHO Structure 9
<p>This is an interactive plot of the 9th structure for a 3D SHO potential calculated from Real Wave Quantum Mechanics using the matrix method with a radius of 27. It can be downloaded and should run in most browsers.</p> <p>The size of the dots represents the magnitude of the FR at each point. The colour is a cyclic mapping of the phase after removal of the phase alternation which characterizes RWQM fields.</p> <p> </p>
RWQM 3d SHO Structure 1
<p>This is an interactive plot of the 1st structure for a 3D SHO potential calculated from Real Wave Quantum Mechanics using the matrix method with a radius of 27. It can be downloaded and should run in most browsers.</p> <p>The size of the dots represents the magnitude of the FR at each point. The colour is a cyclic mapping of the phase after removal of the phase alternation which characterizes RWQM fields.</p> <p>This structure corresponds with an n=1, l=0 orbital. Note that there is phase variation within the structure.</p>
RWQM 3d SHO Structure 10
<p>This is an interactive plot of the 10th structure for a 3D SHO potential calculated from Real Wave Quantum Mechanics using the matrix method with a radius of 27. It can be downloaded and should run in most browsers.</p> <p>The size of the dots represents the magnitude of the FR at each point. The colour is a cyclic mapping of the phase after removal of the phase alternation which characterizes RWQM fields.</p> <p><br> </p>
RWQM 3d SHO Structure 7
<p>This is an interactive plot of the 7th structure for a 3D SHO potential calculated from Real Wave Quantum Mechanics using the matrix method with a radius of 27. It can be downloaded and should run in most browsers.</p> <p>The size of the dots represents the magnitude of the FR at each point. The colour is a cyclic mapping of the phase after removal of the phase alternation which characterizes RWQM fields.</p> <p><br> </p>
RWQM 3d SHO Structure 4
<p>This is an interactive plot of the 4th structure for a 3D SHO potential calculated from Real Wave Quantum Mechanics using the matrix method with a radius of 27. It can be downloaded and should run in most browsers.</p> <p>The size of the dots represents the magnitude of the FR at each point. The colour is a cyclic mapping of the phase after removal of the phase alternation which characterizes RWQM fields.</p> <p> </p>
RWQM 3d SHO Structure 5
<p>This is an interactive plot of the 5th structure for a 3D SHO potential calculated from Real Wave Quantum Mechanics using the matrix method with a radius of 27. It can be downloaded and should run in most browsers.</p> <p>The size of the dots represents the magnitude of the FR at each point. The colour is a cyclic mapping of the phase after removal of the phase alternation which characterizes RWQM fields.</p> <p><br> </p>
Experimental data linked to publication "Process optimization and study of the co-sintering behaviour of Cu-Ni multi-material 3D structures fabricated by spark plasma sintering (SPS)"
<p>Those are all the experimental data used to produce the plots in the article</p>
High-resolution 3D forest structure explains ecomorphological trait variation in assemblages of saproxylic beetles
<p>Climate, topography, and the 3D structure of forests are major drivers affecting local species communities. However, little is known about how the specific functional traits of saproxylic (wood-living) beetles, involved in the recycling of wood, might be affected by those environmental characteristics.</p> <p>Here we combine ecological and morphological traits available for saproxylic beetles and airborne laser scanning (ALS) data in Bayesian trait-based joint species distribution models to study how traits drive the distributions of more than 230 species in temperate forests of Europe.</p> <p>We found that elevation (as a proxy for temperature and precipitation) and the proportion of conifers played important roles in species occurrences while variables related to habitat heterogeneity and forest complexity were less relevant. Further, we showed that local communities were shaped by environmental variation primarily through their ecological traits whereas morphological traits were involved only marginally. As predicted, ecological traits influenced species' responses to forest structure, and to other environmental variation, with canopy niche, wood decay niche, and host preference as the most important ecological traits. Conversely, no links between morphological traits and environmental characteristics were observed. Both models, however, revealed strong phylogenetic signal in species' response to environmental characteristics.</p> <p>These findings imply that alterations of climate and tree species composition have the potential to alter saproxylic beetle communities in temperate forests. Additionally, ecological traits help explain species' responses to environmental characteristics and thus should prove useful in predicting their responses to future change. It remains challenging, however, to link simple morphological traits to species' complex ecological niches.</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.