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1,880 results for “Dimensionality”
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: </p><p>Data provided is the aligned dataset and reconstruction using a FISTA algorithm. Angles Collected -90 to +45 at 1 degree steps. </p><p><strong>Three-dimensional Nanoscale Metal, Metal Oxide and Semiconductor Frameworks through DNA-programmable Assembly and Templating</strong></p><p>By Aaron Michelson. </p><p> </p>
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> </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>
Dataset used in article "A 2-dimensional guillotine cutting stock problem with variable-sized stock for the honeycomb cardboard industry"
<p>The dataset presented is part of the one used in the article "A 2-dimensional guillotine cutting stock problem with variable-sized stock for the honeycomb cardboard industry" by P. Terán-Viadero, A. Alonso-Ayuso and F. Javier Martín-Campo, published in International Journal of Production Research (2023), doi: <a href="https://doi.org/10.1080/00207543.2023.2279129">10.1080/00207543.2023.2279129</a>. </p><p>In the paper mentioned above, two mathematical optimisation models are proposed for the Cutting Stock Problem in the honeycomb cardboard sector. This problem appears in a Spanish company and the models proposed have been tested with real orders received by the company, achieving a reduction of up to 50% in the leftover generated. </p><p>The dataset presented here includes six of the twenty cases used in the paper (the rest cannot be presented for confidentiality reasons). For each case, the characteristics of the order and the solution obtained by the two models are provided for the different scenarios analysed in the paper.</p><p> </p><p>*Version 1.1 contains the same data but renamed according to the instances name in the final version of the article.<br>*Version 1.2 adds the PDF with the accepted version of the article publised in International Journal of Production Research (2023), doi: <a href="https://doi.org/10.1080/00207543.2023.2279129">10.1080/00207543.2023.2279129</a>. </p>
FIGURE 4 in Ex vivo three-dimensional reconstruction of Acutiramus: a giant pterygotid sea scorpion
FIGURE 4. Acutiramus macrophthalmus showing arrangement of ventral structures. AMNH-FI 2253; specimen from the Silurian (Pridoli), Bertie Group, Waterville, Oneida County, NY (Clarke and Ruedemann, 1912: pl. 71, fig. 6): A. complete specimen; B. close-up of ventral structures; C. interpretive drawing of B. Abbreviation: Ap.II.co, appendage II coxae. Specimens photographed under ethanol.
FIGURE 9. 3D in Ex vivo three-dimensional reconstruction of Acutiramus: a giant pterygotid sea scorpion
FIGURE 9. 3D reconstruction of Acutiramus based on examined specimens in lateral view. A. Reconstruction with chelicerae outstretched. B. Reconstruction with chelicerae rotated. The 3D pdf associated with this reconstruction, figure S1, is available in the online supplement (https://doi.org/10.5531/sd.sp.61).
FIGURE 8. 3D in Ex vivo three-dimensional reconstruction of Acutiramus: a giant pterygotid sea scorpion
FIGURE 8. 3D reconstruction of Acutiramus based on examined specimens in dorsal and ventral view. A, D. Reconstruction with chelicerae outstretched: A. dorsal view; D. ventral view. B, E. Reconstruction with chelicerae rotated: B. dorsal view; E. ventral view. C, F. Close-up of prosomal region in ventral view: C. all prosomal appendages; F. close-up of appendages II–V with appendages VI and metastoma removed. The 3D pdf associated with this reconstruction, figure S1, is available in the online supplement (https:// doi.org/10.5531/sd.sp.61).
FIGURE 7 in Ex vivo three-dimensional reconstruction of Acutiramus: a giant pterygotid sea scorpion
FIGURE 7. Acutiramus macrophthalmus showing ventral morphology. YPM IP 208195 from the Late Silurian (Pridoli), Bertie Group, Fiddlers Green dolomite, Phelps Waterline Member, SW of Spinnersville, Millers Mills Quadrangle, Herkimer County, NY (Briggs and Roach, 2020: figs. 10, 11): A. complete specimen. B. close-up of rectangle in A showing reduced appendage II (white arrow); C. interpretive drawing of close-up in B showing key morphologies and the possible articulation locality for the chelicerae (black arrows). B converted to grayscale. Abbreviation: ELS, epistomal lateral sutures. A, B. Photographs by Jessica Utrup.
FIGURE 5 in Ex vivo three-dimensional reconstruction of Acutiramus: a giant pterygotid sea scorpion
FIGURE 5. Erettopterus bilobus from the Silurian (latest Llandovery and Wenlock) Patrick or Kip Burn formation, Scotland. NHMUK PI In 59343 (Kjellesvig-Waering, 1964: pl. 53, fig. 1): A. complete specimen; B. closeup of rectangle in A showing the purported cheliceral articulation with the epistoma; C. interpretive drawing of B showing the reduction in cheliceral width proximal to the epistoma. Abbreviation: ELS, epistomal lateral sutures. Specimen photographed under ethanol.
Five-dimensional phase space measurement at the Spallation Neutron Source Beam Test Facility
<p>This data set consists of 285,082 two-dimensional images which collectively describe the five-dimensional phase space distribution \(f(x, x', y, y', w)\) of a 2.5 MeV, -25.6 mA H\(^-\) ion beam in the <a href="https://neutrons.ornl.gov/sns">Spallation Neutron Source</a> Beam Test Facility (SNS-BTF). Here, \(x\) and \(y\) are the transverse positions, \(x' = dx/ds\) and \(y' = dy/ds\) are the transverse slopes, \(s\) is the position along the reference trajectory, and \(w\) is the deviation from the kinetic energy of the synchronous particle.</p><p>The measurement plane is located in the medium energy beam transport (MEBT) section of the SNS-BTF, 1.3 meters after a radio-frequency quadrupole (RFQ). The measurement apparatus consists of three transverse slits (one horizontal, two vertical) and a 90-degree dipole bend followed by a fluorescent screen. The horizontal slit selects \(y\); two vertical slits select \(x\) and \(x'\); \(y'\)is a function of \(y\) and the vertical position on the screen, \(w\) is a function of \(x\), \(x'\), and the horizontal position on the screen. Thus, the image on the screen gives the density \(f(y', w)\) within a small three-dimensional region in \(x-x'-y\) space. The five-dimensional density is obtained by scanning the slits in a nested loop.</p><p>The data set consists of 285,082 images (20 GB). Jupyter notebooks are included to interpolate the data on a regular grid in five-dimensional phase space, as well as to generate interactive figures. See 'README.md' for instructions. (The interpolated five-dimensional image is also included in a separate folder.)</p><p>More information can be found in a corresponding publication: https://doi.org/10.1103/PhysRevAccelBeams.26.064202</p>
Deliverable 2.3: Biodiversity impact estimates and documentation for indicators on multi-dimensional biodiversity aspects ready for use in WP3
<p>To quantify human-driven impacts on biodiversity, we used advanced modeling techniques paired with a few key variables such as habitat quality, vegetation structure, climate, and topography to develop an innovative predictive model that estimates both 1) current biodiversity patterns and distributions and 2) a baseline model of biodiversity. By comparing both of these models, we are able to identify regions with significant human-driven reductions in species richness, endemism, and species composition across both of our focus regions, South America and Africa.</p> <p>The files provided in this repository (1 km2 resolution) include:</p> <p>1- Species richness (number of species).</p> <p>2- Endemism (species rarity). For this metric, we used the corrected weight endemism index, which is the inverse of a species’ range size and effectively assigns higher scores to species with more restricted distributions. For this index, we used species ranges found within our study area (of South America and Africa).</p> <p>3- Species composition of vertebrates, invertebrates, and plants (which species occur in a given location). This metric, also known as beta diversity, summarizes which sets of species occur at each location. For this, we used the Sorensen index metric, as it does not depend on species absence data.</p> <p>These results provide a improve in previous deliverable 2.2.</p>
Original data for article "Is Unsupervised Dimensionality Reduction Sufficient to Decode the Complexities of Electrochemical Impedance Spectra?"
<p>The uploaded Jupyter notebooks contain original data generation and processing methods used in the article "Is Unsupervised Dimensionality Reduction Sufficient to Decode the Complexities of Electrochemical Impedance Spectra?" by A. Makogon, F. Kanoufi, and V. Shkirskiy</p>
Implications of the three-dimensional chromatin organization for genome evolution in a fungal plant pathogen
<p><span>The spatial organization of eukaryotic genomes is linked to their biological functions, although it is not clear how this impacts the overall evolution of a genome. Here, we uncover the three-dimensional (3D) genome organization of the phytopathogen <em>Verticillium dahliae</em>,<em> </em>known to possess distinct genomic regions, designated adaptive genomic regions (AGRs), enriched in transposable elements and genes that mediate host infection. Short-range DNA interactions form clear topologically associating domains (TADs) with gene-rich boundaries that show reduced levels of gene expression and reduced genomic variation. Intriguingly, TADs are less clearly insulated in AGRs than in the core genome. At a global scale, the genome contains bipartite long-range interactions, particularly enriched for AGRs and more generally containing segmental duplications. Notably, the patterns observed for <em>V. dahliae </em>are also present in other <em>Verticillium</em> species. Thus, our analysis links 3D genome organization to evolutionary features conserved throughout the <em>Verticillium</em> genus.</span></p>
Three-dimensional water exchanges in the shelf circulation system of the Northern South China Sea under climatic modulation from ENSO
<p>Three-dimensional water exchanges in the shelf circulation system of the Northern South China Sea under climatic modulation from ENSO</p>
F I G U R E 1 0 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 1 0 Heatmap of search time for eels within 3 m of the bar rack for 53 attempts by 34 individual eels. Successful passes are shown on the left, and unsuccessful passes on the right. The hydraulic gate is located on the right side. The colours represent the proportion of search time in each zone, averaged over all attempts
F I G U R E 8 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 8 Upper: eel observations along four transects (a–d, with simulated relative water velocities). Observations are coloured by swimming direction. Lower: the density distribution of relative velocities at eel locations for upstream and downstream swimming, with the cross-section relative water velocity distribution in grey., downstream;, upstream;, cross-section
F I G U R E 7 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 7 Vertical and lateral eel distribution in river cross-sections in three parts of the river: the upstream river reach (river), the ponded forebay area (ponded) and the intake channel (channel) (see Figure 2a) for combinations of swimming directions and time of day. The observations are weighted by eel ground velocity and the colours represent scaled density
F I G U R E 5 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 5 Relative depth (a) and width (b) distribution of eels in the upstream river reach. The observations are grouped by eels moving downstream or upstream and by time of day. The observations are weighted by eel ground velocity, and the depth data are from the middle 90% of the river width. Situation:, downstream day;, downstream night;, upstream day;, upstream night
F I G U R E 4 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 4 Detection of eels entering the study area at the Herting hydropower plant grouped by inflow discharge and day/night, displayed as (a) number of eels and (b) eels per hour of current discharge., day;, night
F I G U R E 3 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 3 Schematics of a river cross-section: (a) natural model and (b) rectangular model. Relative depth is defined as zrel ¼ z=d and relative width as Wrel ¼ x=W, where W is the river width and d is the local depth
F I G U R E 1 1 in Three-dimensional migratory behaviour of European silver eels (Anguilla anguilla) approaching a hydropower plant
F I G U R E 1 1 Typical search patterns of eels along the intake screen at the Herting hydropower plant. Top, vertical view; bottom, plan view
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.