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2,113 results for “High resolution”
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>
A High-Resolution Stochastic Modeling Method for Elastic Parameters Based on FDMA
<p>Data used in article ‘A High-Resolution Stochastic Modeling Method for Elastic Parameters Based on FDMA’. Including logging data, seismic P-wave velocity data and data of figures in this article.</p>
HR-GLDD: A globally distributed high resolution landslide dataset
<p> HR-GLDD, a high-resolution (HR) dataset for landslide mapping composed of landslide instances from ten different physiographical regions globally: South and South-East Asia, East Asia, South America, and Central America. The dataset contains five rainfall triggered and five earthquake-triggered multiple landslide events that occurred in varying geomorphological and topographical regions.</p>
Datasets for "High-resolution, basin-scale simulations reveal the impact of intermediate zonal jets on the Atlantic oxygen minimum zones".
<p>This repository contains the 7-year averaged files from runs TATL10 and TATL3 used in the manuscript "High-resolution, basin-scale simulations reveal the impact of intermediate zonal jets on the Atlantic oxygen minimum zones".</p> <p>Additional files include the CARS oxygen climatology and the CMEMS model output used in the study.</p> <p> </p>
Dataset for High-resolution mantle flow models reveal importance of plate boundary geometry and slab pull forces on generating tectonic plate motions
<p>This repository contains the plugin and dataset used to setup models in the manuscript: "High-resolution mantle flow models reveal importance of plate boundary geometry and slab pull forces on generating tectonic plate motions".</p> <p>The material model plugin used in our models is in the "plugins" folder. The "models" folder contains the reference input parameter file described in the paper. All other model configurations shown in the paper can be obtained by modifying this parameter file. The input files used to set up the models are in the respective folder. Additionally, the Jupyter notebook used to compute residuals of our models is provided in the "scripts" folder.</p> <p> </p>
Dataset 2 for the reproduction of figures used in "High-resolution, basin-scale simulations reveal the impact of intermediate zonal jets on the Atlantic oxygen minimum zones""
<p>This is the second dataset with data necessary for the reproduction of the figures used in the manuscript.</p> <p> </p>
High-resolution cone-beam scan of a pomegranate with two dosage levels
<p>We release two tomographic scans of a pomegranate with two levels of radiation dosage for noise-level comparative studies in data analysis, reconstruction or segmentation methods. The dataset collected with higher dosage is referred to as the "<em><strong>good</strong></em>" <strong>dataset</strong>; and the other as the "<em><strong>noisy</strong></em>" <strong>dataset</strong>, as a way to distinguish between the two dosage levels. </p> <p> </p> <p>The dataset are acquired using the custom built and highly flexible CT scanner, FlexRay Lab, developed by XRE NV and located at CWI. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1943-by-1535 pixels, 14-bit, flat detector panel. </p> <p> </p> <p>Both dataset were collected over a 360 degrees in circular and continuous motion with 501 projections distributed evenly over the full circle. The uploaded dataset are not binned or normalized; a single dark and two (pre- and post-) flat fields are included for each scan. Projections for both sets were collected with 100 ms exposure time with the good data projections averaged over 5 takes, and no averaging was made for the noisy data. The tube settings for the good and noisy dataset were 70kV, 45W and 50kV, 20W, respectively. The total scanning time were 7 minutes for the good; 3 minutes for the noisy scan. Each dataset is packaged with the full list of data and scan settings files (in .txt format). These files contain the tube settings, scan geometry and full list of motor settings.</p> <p> </p> <p>These dataset are produced by the Computational Imaging members at Centrum Wiskunde & Informatica (CI-CWI). For any useful Python/MATLAB scripts for FlexRay dataset, we refer the reader to our group's <a href="http://github.com/cicwi">GitHub page</a>.</p> <p> </p> <p>For more information or guidance in using these dataset, please get in touch with </p> <ul> <li>s.b.coban [at] cwi.nl</li> </ul>
Radiographic data of a wooden block with metal markers at the FleX-ray laboratory (high resolution)
<p><strong>Summary</strong></p> <p>This submission contains radiographic data containing metal markers of a small wooden block. </p> <p>The data is made available as part of [Bossema et al., 2024].</p> <p><em> </em></p> <p><strong>Apparatus</strong></p> <p>The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].</p> <p><strong>List of Contents</strong></p> <p>The content of the submission is given below. All raw data (i.e. no corrections) is made available in .tif format.</p> <p>The data folder contains:</p> <ul> <li>darkfield image, <em>di000000.tif</em>,</li> <li>flatfield image before acquisition, <em>io000000.tif</em>, and after acquisition, <em>io000001.tif</em>,</li> <li>raw (unprocessed or uncorrected) projections, <em>scan_*.tif</em>,</li> <li><em>data settings XRE.txt</em>, a text file with scanner metadata,</li> <li><em>scan settings.txt</em>, a text file with scanner metadata in more human readable format, and</li> <li><em>data settings XRE.ini</em>, a snapshot text file of basic geometry information at the start of a scan.</li> <li><em>script_executed.txt</em>, the text file containing the list of commands the apparatus has executed.</li> </ul> <p> </p> <p><strong>Additional Links</strong></p> <p>These datasets are produced by the <a>Computational Imaging group</a> at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's <a>GitHub page</a>.</p> <p><em> </em></p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these datasets, please get in touch with </p> <ul> <li>bossema [at] cwi.nl</li> </ul> <p><em> </em></p> <p><strong>Acknowledgments</strong></p> <p>The authors would like to acknowledge the funding from the Netherlands Organisation for Scientific Research (NWO), project numbers 341-60-001, 639.073.506 and 628.007.033 and Netherlands Institute for Conservation, Art and Science (NICAS).</p> <p><strong>References</strong></p> <p>S. B. Coban, F. Lucka, W. J. Palenstijn, D. Van Loo, and K. J. Batenburg, “Explorative imaging and its implementation at the FleX-ray Laboratory,” <em>J. Imaging</em>, vol. 6, no. 18, 2020, doi: 10.3390/jimaging6040018.</p> <p><a href="https://www.nature.com/articles/s41467-024-48102-w">Bossema, F.G., Palenstijn, W.J., Heginbotham, A. <em>et al.</em> Enabling 3D CT-scanning of cultural heritage objects using only in-house 2D X-ray equipment in museums. <em>Nat Commun</em> <strong>15</strong>, 3939 (2024). https://doi.org/10.1038/s41467-024-48102-w</a></p>
Boron elemental and isotopic determination via the BF diatomic molecule using high-resolution continuum source graphite furnace molecular absorption spectrometry
<p>This dataset contains the raw data corresponding to the figures of the publication DOI: 10.1039/d3ja00420a</p>
Data from: Towards high-resolution modeling of small molecule - ion channel interactions
<p>Ion channels are critical drug targets for a range of pathologies, such as epilepsy, pain, itch, autoimmunity, and cardiac arrhythmias. To develop effective and safe therapeutics, it is necessary to design small molecules with high potency and selectivity for specific ion channel subtypes. There has been increasing implementation of structure-guided drug design for the development of small molecules targeting ion channels. We evaluated the performance of two Rosetta ligand docking methods, RosettaLigand and GALigandDock, on structures of known ligand - cation channel complexes. Ligands were docked to voltage-gated sodium (Na<sub>V</sub>), voltage-gated calcium (Ca<sub>V</sub>), and transient receptor potential vanilloid (TRPV) channel families. For each test case, RosettaLigand and GALigandDock methods were able to frequently sample a ligand binding pose within 1-2 Å root mean square deviation (RMSD) relative to the experimental ligand coordinates. However, RosettaLigand and GALigandDock scoring functions cannot consistently identify experimental ligand coordinates as top-scoring models. Our study reveals that the proper scoring criteria for RosettaLigand and GALigandDock modeling of ligand - ion channel complexes should be assessed on a case-by-case basis using sufficient ligand and receptor interface sampling, knowledge about state specific interactions of the ion channel and inherent receptor site flexibility that could influence ligand binding.</p>
High resolution dataset of plastic deformation at cryogenic temperatures in a nickel-based superalloy
<p>A nickel-based superalloy is examined during monotonic deformation at cryogenic temperatures, reaching as low as liquid helium temperature. A detailed multimodal analysis of the microstructure and plasticity is conducted to discern changes in deformation mechanisms and plastic deformation localization under cryogenic conditions. This study employs high-resolution digital image correlation to identify the deformation mechanisms and understand their influence on plastic deformation localization as the temperature varies. At cryogenic temperatures, unusual plastic deformation localization processes are observed, attributed to the competing activation of a range of deformation processes. Furthermore, a mechanism of slip delocalization, i.e., local plastic deformation homogenization through closely spaced slip, is noted at these extreme temperatures. Ultimately, the impact of the microstructure is identified across the temperature range, from room to cryogenic temperatures.</p>
Supplementary data to "High-Resolution Raman Imaging of >300 Patient-Derived Cells from Nine Different Leukemia Subtypes: A Global Clustering Approach"
<p>Compressed ".feather" files including the entire dataset of 319 Raman maps of the same number of cells from 19 patients affected by nine distinct leukemia subtypes.<br>Raw data have been pre-processed as follows using custom software (LabVIEW, National Instruments Corp., TX): a) cosmic rays removal by singular value decomposition (SVD); b) camera offset subtraction; c) CCD response correction (intensity and etaloning) using a tungsten halogen light with known emission (Avalight-HAL, Avantes BV, NL)); d) wavenumber calibration using the zero-wavenumber laser line, toluene and argon-mercury emission (CAL-2000, Ocean Optics, Germany); e) denoising by SVD.<br>More details in the open access published article and supplementary material (10.1021/acs.analchem.4c00787).</p>
High-resolution topography data and fault trace along the Elashan fault
<p> High-resolution digital elevation models (DEM) topography data extracted from the uncrewed aerial vehicle (UAV) of a DJI (Dajiang Innovations Science and Technology Co., Ltd.) Phantom 4 RTK, and GF-7 satellite stereo imagery. The trace of the Elashan fault is interpreted based on these high-resolution topography data.</p>
Synthetic Emission Line Catalog and High-Resolution SEDs for SPHEREx Galaxy Simulations
<p><strong>Overview:</strong></p> <p>This repository contains the synthetic galaxy models derived from multi-wavelength photometry in the COSMOS field (166k galaxies over 1.27 sq. deg., 18 < i < 25) and from the GAMA survey (44k galaxies over 217 sq. deg., i < 18). These encompass a representative sample of galaxies SPHEREx will observe, and should be applicable for other surveys as well.</p> <ul> <li>Synthetic emission line strengths in the rest-frame optical/near-infrared (H-alpha, H-beta, Paschen-alpha, [OIII], [OII], [NII], [SII])</li> <li>High-resolution SEDs (0.1 - 8 micron), which are produced by 1) fitting a library of 160 galaxy templates to multi-band photometry and 2) inserting emission lines with strengths predicted by an empirical model that depends on galaxy type, redshift and stellar mass.</li> </ul> <p>These products were made using the modeling framework <strong>C</strong>onditional <strong>LI</strong>ne <strong>P</strong>ainting on <strong>S</strong>ynthetic <strong>S</strong>pectra (<em>CLIPonSS</em>), the details of which are summarized in Feder+2023b (<a href="https://arxiv.org/abs/2312.04636">arXiv link here</a>). The synthetic emission line catalog is validated against a variety of LF measurements, line ratio trends and direct line comparisons. </p> <p><strong>Data description:</strong></p> <p><em><strong>High-resolution SEDs</strong></em>: The SEDs are stored in .FITS files, for which each galaxy SED has its own Header Data Unit (HDU). This format was chosen due to the fact that the wavelength sampling for the 160 galaxy empirical and model-based templates varies, i.e., we do not perform any interpolation onto a homogenized wavelength grid. In cases where emission lines are added but the continuum template resolution is coarse, the resolution is increased in the vicinity of the emission line(s) to adequately sample the line profiles. Each galaxy's HDU is indexed by its Farmer ID (for COSMOS) or alternatively its uberID (GAMA). The COSMOS SEDs are split into three files for relative ease of access, while the GAMA sources are all in one file.</p> <p><em><strong>Emission line catalogs:</strong></em> The emission line catalogs are stored in .csv format with the following information:</p> <p>Tractor_ID (or uberID) [integer]: Unique identifier for each source</p> <p>RA/DEC [float, in degrees]: Celestial coordinates</p> <p>imag [AB]: i-band magnitude</p> <p>mass_best [float]: log-stellar masses estimated through SED fitting process</p> <p>ebv [float]: Galaxy intrinsic dust extinction (ranging from ebv=0 to 1)</p> <p>redshift [float]: Best-fit redshift from COSMOS2020 (GAMA) catalogs</p> <p>bfit_tid [integer]: Best fit template ID from library of templates</p> <p>dustlaw [integer]: Best fit dust law (1=Prevot, 2=Calzetti, 3=Seaton, 4=Allen, 5=Fitzpatrick)</p> <p>L_{line} [float, erg s-1]: Line luminosities from empirical model</p> <p>F_{line} [float, erg cm-2 s-1]: Line fluxes from empirical model</p> <p>ew_ha [float, Angstrom]: Equivalent width of H-alpha from empirical model</p> <p><strong><em>Fitting templates: </em></strong>We include the 31 model-based templates and 129 empirical templates from Brown+2014. In the Brown templates we have removed any relevant lines that were directly measured in the initial spectra, however we do not fit for/remove PAH features. These can serve as the basis for other empirically based galaxy simulations with different emission line prescriptions.</p> <p>Any questions regarding the use of these data products or related issues can be directed to Richard Feder (link to <a href="https://richardfeder.github.io/">personal website</a>). </p> <p> </p>
GOIMAI DataSet-Phase-I of high-resolution macroscopic images for the identification of wood species
<p>GOIMAI Phase I is a wood species dataset obtained through magnifying lenses. The inputs needed in our laboratory were a mid-range mobile phone (e.g. Samsung Galaxy S7), a magnifying lens with a universal clamp attached to the lens of the mobile phone (in our case with 24x magnifier) and the wood sample itself.</p> <p>GO IMAI project - Identificación de madera por dispositivo móvil. <br>Convocatoria EI-Agri Programa Nacional de Desarrollo Rural 2014-2020 por el Ministerio de Agricultura, Pesca y Alimentación y el Fondo Europeo Agrícola de Desarrollo Rural (FEADER).</p>
Ship Plume Dispersion in Marseille Port: A High-Resolution CFD Visualization
<p><strong><u>Description</u></strong></p> <p>This video visualizes the results of a high-resolution Computational Fluid Dynamics (CFD) model applied to study ship plume dispersion in the passenger port of Marseille, France. The video focuses on a scenario where a small cruise/pleasure ship docked at the port turns on its main engines in preparation for departure, considering seaborn prevailing wind conditions.</p> <p>The visualization concentrates on two areas. The first is the area around La Major Cathedral, which is close to the waterfront. The second is a street canyon approximately 650 meters downwind of the ship's location. Due to the local urban layout, the plume becomes entrapped within this distant street canyon. Here, the spatial distribution of pollutants can vary even between neighboring floors of a single building. Finally, a rendered video of the plume dispersion is presented, where the urban landscape is visualized to make the dispersion more comprehensible for non-technical and non-scientific audiences.</p> <p>This video was previously published on YouTube at the following link: <a href="https://www.youtube.com/watch?v=HwLFTj1D4LU&ab_channel=SCIPPERProject" target="_blank" rel="noopener">YouTube</a>. </p> <p>All data used to create this video were made available through the EU Horizon 2020 project <a href="https://www.scipper-project.eu/">SCIPPER</a>.</p> <p>The SCIPPER project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement <a href="https://doi.org/10.3030/814893">Nr. 814893</a>. </p>
High-resolution figures of Amaral et al. 2024
<p>High-resolution figures of Amaral et al. 2024 "Expanding the Mesozoic record of early brachyceran fly larvae, including new larval forms with chimera-type morphologies" in Insects (MDPI).</p>
A regional high-resolution (1/12 degree) coupled ocean-ecosystem model (INCOIS-BIO-ROMS) output for Indian Ocean
<p>The dataset contains sea-surface temperature, sea-surface salinity, sea-surface dissolved inorganic carbon, sea-surface total alkalinity, sea-surface pH, and sea-surface partial pressure of CO2 for the Indian Ocean region. The data is available from 1980 to 2019 on a monthly time scale. Each of these data has a spatial resolution of 1/12º.</p>
Considerations for high-resolution regional meteorological wind modelling over complex terrain: a typhoon case study for assessing forestry damage (data)
<p>This is the experiment data.</p> <p>The Weather Research and Forecasting (WRF) model is a popular and easily used as a numerical weather prediction (NWP) model, but configuring WRF to produce accurate results can be time-consuming. This is especially so when simulating extreme events, over complex terrain, or at high resolutions. In this study, a strong wind event from Tropical Cyclone (TC) Thad in year 1981 was simulated at 200 m resolution over an experiment forest in a mountainous region of Hokkaido island, Japan. The simulation configuration is challenging, in order to cover a larger area to produce a TC with appropriate track and intensity, and at the same time to resolve the smallest domain of sub-km grid spacing with computational stability. A mixed nesting method was applied with two-way nesting up for the first three domains, followed a separate simulation over the smallest domain. The mixed method could produce 10 min wind speed distributions similar to that of the full simulation with two-way nesting of all four domains, if a 30-minute boundary update interval was used for the separate simulation. Mixed nesting improves the efficiency of the simulation process, since the larger phenomenon scale and smaller human impact scale can be tuned separately. </p>
Data for: Influence of Anomalous Ocean Heat Transport on the Extratropical Atmospheric Circulation in a High-Resolution Slab-Ocean Coupled Model
<p>This dataset, provided in NetCDF format, supports the research presented in the paper titled "Influence of Anomalous Ocean Heat Transport on the Extratropical Atmospheric Circulation in a High-Resolution Slab-Ocean Coupled Model." Please contact Dr. Sun (ltsun@rams.colostate.edu) if you have any questions.</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.