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852 results for “grain”
Dataset for article " Deformation of polycrystalline MgO up to 8.3 GPa and 1270 K: microstructures, dominant slip-systems, and transition to grain boundary sliding"
<p>This archive countains the dataset used to produce the paper "Deformation of polycrystalline MgO up to 8.3 GPa and 1270 K: microstructures, dominant slip-systems, and transition to grain boundary sliding" in press by Frontiers in Earth Science.</p> <p>(c) Estelle Ledoux, Université de Lille, France, 2020</p>
Coarse-grained molecular dynamics simulations of SARS-CoV-2 envelope protein E in the pentameric form
<p>The trajectories of coarse-grained (CG) molecular dynamics (MD) simulations of<br> 1) unmodified (FeigLab_NMR; FeigLab_PentamerNoPTM_POPC_Martini3b: 5 μs; 5 μs); <br> 2) palmitoylated (FeigLab_PentamerCYSP43; PentamerCYSP44_POPC_Martini3b: 5 μs; 5 μs); <br> SARS-CoV-2 E protein pentamer in a POPC bilayer.</p> <p>The trajectory of CG MD of system containing 2 pentamers in the membrane buckled in a single direction (BuckledMembrane_FeigLab_2xPentamerNoPTM_POPC_Martini3b: 1 μs).</p> <p>FeigLab_Pentamer: https://github.com/feiglab/sars-cov-2-proteins/blob/master/Membrane/E_protein.pdb<br> FeigLab_NMR_Pentamer is assembled based on the transmembrane domain determined by NMR (PDB ID: 7K3G) and FeigLab model for the rest.</p>
Datasets belonging to the paper "Dual phase patterning during a congruent grain boundary phase transition in elemental copper"
<p>This repository contains the raw data of the experimental STEM imaging and the data corresponding to the simulations and theoretical calculations of the paper "Dual phase patterning during a congruent grain boundary phase transition in elemental copper" available under <a href="https://doi.org/10.1038/s41467-022-30922-3">https://doi.org/10.1038/s41467-022-30922-3</a> .</p> <p>See the file README.md for a detailed description.</p>
Dataset for "Universality of grain boundary phases in fcc metals: Case study on high-angle [111] symmetric tilt grain boundaries"
<p>This repository contains the input files, scripts, and raw data of the simulations for the paper "Universality of grain boundary phases in fcc metals: Case study on high-angle [111] symmetric tilt grain boundaries".</p> <p>This data comprises structures of grain boundaries in high-angle [111] symmetric tilt grain boundaries in fcc metals as modeled by various (M)EAM potentials. Investigations include ground state thermodynamic excess properties, excess free energy calculations under stress or strain and with varying temperature, and related molecular dynamics simulations.</p> <p>See README.md for details.</p>
Standardized reference grids for spatial analyses at various grain sizes
<p><strong>Description:</strong><br> These Reference grids have been created for the <a href="https://naturaconnect.eu/">NaturaConnect project</a> and are based on an intersection of the<a href="https://www.eea.europa.eu/data-and-maps/data/eea-coastline-for-analysis-1/gis-data/europe-coastline-shapefile"> European Coastline delineation</a> and the <a href="https://gadm.org/">GADM database</a>.<br> Thee reference grids have been created in a way so that they are fully consistent with the EEA reference grid (https://www.eea.europa.eu/data-and-maps/data/eea-reference-grids-2), meaning that for example two 5km gridded cells fully match a 10km grid cell in width.</p> <p><strong>Filestructure:</strong><br> ReferenceGrid_Europe_{format}_{grain}</p> <ul> <li> format is either "frac" for fractional data (which has been multiplied with 10000 to save in integer format) or binary (0,1).</li> <li> grain is provided as layers in 100m, 1000m, 5000m, 10000m, 50000m spatial resolution. Alternative aggregations can be provided on request.</li> </ul> <p><strong>File format:</strong><br> The layers are gridded geoTiff files and can be loaded in any conventional Graphical Information System (GIS) or specific analytical programming languages (e.g. R or python). In addition external pyramids (.tfw) have been precreated to enable faster rendering.</p> <p><strong>Geographic projection:</strong><br> We use the <a href="https://epsg.io/3035">Lamberts-Equal-Area Projection</a> by default for all layers in NaturaConnect. This is an equal-area (but distorted shape) projection and commonly used by European institution with a focus on the European continent. For global layers the <a href="https://epsg.io/54009">equal-area World Mollweide projection</a> is used.<br> <br> <strong>Sourcecode:</strong><br> The code to reproduce the layers has been made available in the "code" file.<br> </p>
Dataset for 'Weld map tomography for determining local grain orientations from ultrasound'
<p>This dataset contains data files and Jupyter notebooks used to produce figures in the manuscript 'Weld map tomography for determining local grain orientations from ultrasound'.</p>
Interpolation of the median grain size of the first 2 cm sediment layer in the former saltworks of Salin de Giraud in 2017
<p>Sediment samples were collected in the summer of 2017 over the entire study area at 500 m spacing and in the channels. Grain size analysis of the collected sediment samples was conducted using a Malvern Mastersizer 2000© laser beam grain sizer. The median grain size (d50 in µm) at each sample location was then interpolated over the entire study area. Interpolation was made with the SAGA-GIS software (version 7.9.0). According to the cross-validation error, the best method for the D50mm interpolation was the Modified Quadratic Shepard. The 10-fold validation provided an R² of 0.93, an NMRSE of 24.5, an RMSE of 83.9, an MRE of 7039 with the fit set to “node”, the quadratic neighbours and weighting neighbours set to 50 and the spatial resolution was set to 10 m. The resultant interpolation map was then categorized following the nomenclature of Blott and Pye (2001) provided in the file style_sediment_map.qml.</p>
Data for: Grain structure evolution ahead of the die during friction extrusion of AA2024
<p>Friction extrusion (FE) is a thermo-mechanical process using a rotating die to produce fully consolidated extrudates in different shapes, e.g. wires, rods and tubes. FE utilizes a non-consumable die to plastically deform material and to generate heat by friction due to the relative rotation between the die and feedstock. In this study, the FE process is applied to extrude the Al-Cu alloy AA2024 using a 90 degree scroll-featured die. The grain structure evolution induced by thermo-mechanical processing is analyzed, in particular using the electron backscatter diffraction technique. Introduction of severe plastic deformation and high temperature exposure induced by the die movement in radial and longitudinal directions relative to the materials enable grain refinement induced by dynamic recrystallization. The grain structure formation prior to deformation through the die orifice plays an essential role to obtain fully-recrystallized homogeneous wire.</p>
Data for: Microstructure evolution and texture development during production of homogeneous fine-grained aluminum wire by friction extrusion
<p>This dataset contains the data for paper “Microstructure evolution and texture development during production of homogeneous fine-grained aluminum wire by friction extrusion” published in Materials Characterization.</p> <p>Abstract: This study aims to understand the microstructure evolution and texture development during friction extrusion of aluminium alloys, focusing on AA7075 as exemplary alloy system. Electron backscatter diffraction technique has been employed to obtain crystallographic data from various regions in front of the die and in the wire. It can be deduced that the combination of continuous dynamic recrystallization and geometric dynamic recrystallization mainly govern the formation of a fine-grained structure, however discontinuous dynamic recrystallization may also play a role at high temperature. The global shear deformation during the process was characterized as a simple shear deformation with dominant <span class="math-tex">\(B/\overline{B}\)</span> simple shear texture components. The material flow is mainly driven by the in-plane shear strain and the extrusion-induced shear strain that are determined by die rotational speed and extrusion force, respectively. The in-plane shear strain strongly affects the formation of a homogeneous fine-grained microstructure in the aluminum wire. In this regard, a novel material flow model for friction extrusion has been proposed.</p>
Grain-Scale In-situ Study of Discontinuous Precipitation in Mg-Al
<p>Submitted manuscript and data for paper "Grain-Scale In-situ Study of Discontinuous Precipitation in Mg-Al"</p> <p>Files:</p> <p>Manuscript: insitu_dp_pap.pdf</p> <p>Video: Mg DP.mp4</p> <p>Area 1 image stack: Area_10xxx.tif </p> <p>Area 2 image stack: Aligned 752 of 7520xxx.tif</p> <p>Matlab code: boundarytracker.m, concprof_oblate.m (see code for details)</p> <p>Figures and associated data: *.fig (Matlab figure format), *.txt (ASCII text format)</p> <p> </p>
In-situ Heating-Stage EBSD Validation of Algorithms for Prior-Austenite Grain Reconstruction in Steel
<p>High temperature EBSD and dilatometry data from the manuscript "In-situ Heating-Stage EBSD Validation of Algorithms for Prior-Austenite Grain Reconstruction in Steel". This includes Gifs of the martensitic and bainitic phase transformations, individual frames as Tiff files and as CTF files. It also includes thermocouple read outs from the in-situ crucible and the raw data from the dilatometry experiments.</p>
UBGG-3m: Fine-grained urban blue-green-gray landscape dataset for 36 Chinese cities based on deep learning network
<p>The UBGG dataset provides easily access and leverage to researchers and analysts, which is stored in the following Zenodo repository (<a href="https://doi.org/10.5281/zenodo.8053333">https://doi.org/10.5281/zenodo.8352777</a>). The UBGG dataset consists of two main components:</p> <ul> <li><strong>UBGG-3m: the fine-grained UBGG map product of 36 metropolises in China.</strong> The UBGG-3m dataset captures the intricate urban landscape features with remarkable precision, providing a detailed representation at an impressive 3-meter resolution. Fig. 1 in User Guides shows the classification results for 36 Chinese metropolises. Researchers can delve into the nuances of the UBGG continuum, gaining invaluable insights into the interplay between the blue, green, and gray elements of urban environments in each metropolis.</li> </ul> <ul> <li><strong>UBGGset:</strong> <strong>the large-volume sample dataset to support the UBGG deep learning research.</strong> Complementing the UBGG-3m dataset, UBGGset serves as a large-volume sample dataset specifically tailored to support and foster UBGG research endeavors (Fig. 2). The UBGGset consists of 14,627 sample images (without data augmentation), with dimensions of 256 pixels in length and width, covering an urban area of approximately 2,272 km<sup>2</sup>. The UBGGset was constructed with co-registered pairs of 3 m Planet images and fine-annotated urban landscapes labeled on 1 m Google Earth image. This dataset encompasses 15 typical cities, offering researchers a rich and diverse resource to drive exploration, analysis, and innovation in the field of urban landscape studies.</li> </ul> <p> </p> <p><strong>Citation format for paper and dataset:</strong></p> <p>[1] Zhiyu Xu, Shuqing Zhao. Fine-grained urban blue-green-gray landscape dataset for 36 Chinese cities based on deep learning network. <em>Sci Data</em> 11, 266 (2024). https://doi.org/10.1038/s41597-023-02844-2</p> <p>[2] Zhiyu Xu, Shuqing Zhao, Fine-grained urban landscape mapping reveals broad-scale homogeneity in urban environments,<br>Science Bulletin, (2024). https://doi.org/10.1016/j.scib.2024.03.060</p> <p>[3] Zhiyu Xu, Shuqing Zhao. UBGG-3m: Fine-grained urban blue-green-gray landscape dataset for 36 Chinese cities based on deep learning network (v1.0) [Data set]. (2023). Zenodo. https://doi.org/10.5281/zenodo.8352777</p>
Data for 'Grain boundary segregation and phase separation in ceria-zirconia from atomistic simulation'
<p>Data for the article 'Grain boundary segregation and phase separation in ceria-zirconia from atomistic simulation', including input and output files for simulations, and scripts to perform data analysis and generate figures.</p>
Phenotypic plasticity in response to fine-grained environmental variation in predation.
1. In nature, organisms experience environmental variability at coarse-grained (inter-generational) and fine-grained (intra-generational) scales and a common response to environmental variation is phenotypic plasticity. The emphasis of most empirical work on plasticity has been on examining coarse-grained variation with the goal of understanding the costs and benefits of plastic responses in response to a particular environment. 2. In this study, we investigated the effects of fine-grained variation in predation on the inducible defences of larval wood frogs (Rana sylvatica) by widely altering the density and feeding schedule of caged predators (Dytiscusspp.) while holding average predation constant. 3. We found that predator cues induced change in tadpole behaviour, morphology, and mass. Surprisingly, however, temporal variation in predation did not cause the tadpoles to alter their activity (compared to a constant predation treatment) or mass. Temporal variation in predation did alter tadpole tail depth, but only when experiencing our most extreme variation treatment in which the predators were fed once every 8 days. Under these conditions, the predator-induced tadpole tail was less extreme compared to environments containing constant predation. 4. While a number of previous studies have examined behavioural responses of prey to temporal variation in predation risk without holding average predation constant, this appears to be the first test of temporal variation per se. As in previous studies of organism responses to temporal variation in resources, our results suggest that fine-grained environmental variability can affect the expression of phenotypically plastic traits, but our tadpoles appear to be generally unresponsive to this finegrained variation for many of their traits.
Gini index mean score grain size estimates for Murray formation rocks (Gale crater, Mars) from ChemCam LIBS data (sols 766-1804)
<p>This repository includes main research results from the Journal of Geophysical Research: Planets manuscript entitled <em>"Grain Size Variations in the Murray Formation: Stratigraphic Evidence for Changing Depositional Environments in Gale Crater, Mars"</em>. These datasets were also included as Supplementary tables with the manuscript. Please find the plain language summary of the manuscript and the captions for these datasets below:</p> <p><strong><em>Plain language summary:</em></strong> The lowest exposed rocks of the Murray formation in Gale crater, Mars are interpreted as ancient lake deposits based on <em>Curiosity </em>rover data. However, the duration and temporal variability of this ancient lake is still an open question. Here we characterize the vertical distribution of deposits within the entire Murray formation using new grain size information. Characterizing grain size in rocks provides information about the speed of past fluid flows, which is crucial for interpreting depositional environments. However, measuring grain size in images is rarely possible for martian rocks. Thus, we estimate grain sizes with the Gini Index Mean Score (GIMS), a grain-size proxy that uses ChemCam Laser Induced Breakdown Spectroscopy data. GIMS results indicate that the Murray formation is dominated by rocks with mud-sized grains (i.e., mudstones), suggesting mud-sized grain settled in a low energy lake environment. Mud cracks occur in some of the mudstones, indicating drying periods in a lake. Rocks with sand-sized grains (i.e., sandstones) and cross bedding occur at specific intervals, suggesting episodes with stream channels and wind-blown sand dunes. The dominance of lake deposits interspersed with stream deposits suggests that liquid water was present in Gale crater for tens of thousands to millions of years.</p> <p><strong>Table captions:</strong></p> <p><em>Table S3. </em>All Murray formation targets used in the Gini mean index score (GIMS) analysis (sols 766-1804) with summary information, general grain size estimates from MAHLI and RMI images if known, and G<sub>MEAN </sub>values with associated standard deviation errors. For targets with N/A grain sizes, grains could not be resolved in any of the images, or images were not available. Protrusions in the rocks that are not grains are likely diagenetic nodules or concretions. Targets with G<sub>MEAN</sub>=0.07 have transitional GSRs, indicated by GSR1/GSR2. Targets names are merged in the same cell for those analyses that were taken on the same rock exposure. Next to the target names, the symbol * denotes that the ChemCam target was imaged by the MAHLI, the symbol ** denotes that the dust removal tool was used before the MAHLI image was taken, and ~ signifies that a location close to the ChemCam target was imaged by the MAHLI.</p> <p><em>Table S4</em>. The mean, median, minimum and maximum G<sub>MEAN</sub> and the minimum and maximum grain size regime (GSR) for each locality in the Murray formation.</p>
IODP Expedition 362 Bulk and grain density (MAD)
<p>Moisture and density (MAD) data were acquired on ~10 mL sediment or rock samples by measuring three out of four material parameters: wet (saturated) mass, wet volume, dry mass, and/or dry volume after 24 h drying in a convection oven at 105 degrees C. From the moisture and volume measurements, the following phase relationships are calculated: wet and dry water content, wet bulk density, dry bulk density, grain density, porosity, and void ratio. The combination of measurements is defined by the submethod chosen: A, B, C, or D. Wet (A, B, or C) and dry (A, B, C, or D) mass is determined using motion-compensated balances. Wet volume is determined either by helium pycnometry (A) or by the sample's geometric dimensions using calipers (A or D). Dry volume (C or D) is measured by helium pycnometry. Submethods A and B are not recommended by IODP. Submethod C is suitable for saturated materials such as fine-grained sediments. Submethod D is suitable for unsaturated porous material such as certain limestones and basalts.</p>
Coarse-grained Near-global Aqua-planet Simulation with Computed Dynamical Tendencies
<p>This dataset includes the coarse-grained 3D state of the near-global CRM simulations (NG-Aqua). The simulation is run at a 4km resolution using the System for Atmospheric Modeling (SAM)</p> <p>A dataset derived from the same simulation is included at the <a href="https://dx.doi.org/10.5281/zenodo.1226370">10.5281/zenodo.1226370</a>. This current posting supplements this dataset with the dynamical tendencies for total water and liquid-ice potential temperature, respectively given by FQT and FSLI. These are computed by initializing SAM run at a 160km resolution with the coarse-grained fields from NG-Aqua; evolving the state forward for 10 30 second time steps; saving the output; and finally computing the difference with the initial condition.</p> <p>This netCDF dataset is split into several part files for more robust uploading/downloading. To download this data, download each "part" file, and combine them with the "cat" linux command:</p> <pre><code>cat noBlur.nc.part?? > noBlur.nc</code></pre> <p>If using this with the uwnet code repository, you should then move this file to "data/processed/training/noBlur.nc", creating that folder if necessary.</p>
Input Files for Peptide Translocation Across Phospholipid Membranes Using Various Collective Variables and Martini Coarse-Grained Simulations
<p>Input files for publication: Ivo Kabelka, Radim Brožek, and Robert Vácha: Selecting Collective Variables and Free Energy Methods for Peptide Translocation Across Membranes, Journal of Chemical Information and Modeling, submitted</p>
IODP Expedition 368X Bulk and grain density (MAD)
<p>Moisture and density (MAD) data were acquired on ~10 mL sediment or rock samples by measuring three out of four material parameters: wet (saturated) mass, wet volume, dry mass, and/or dry volume after 24 h drying in a convection oven at 105 degrees C. From the moisture and volume measurements, the following phase relationships are calculated: wet and dry water content, wet bulk density, dry bulk density, grain density, porosity, and void ratio. The combination of measurements is defined by the submethod chosen: A, B, C, or D. Wet (A, B, or C) and dry (A, B, C, or D) mass is determined using motion-compensated balances. Wet volume is determined either by helium pycnometry (A) or by the sample's geometric dimensions using calipers (A or D). Dry volume (C or D) is measured by helium pycnometry. Submethods A and B are not recommended by IODP. Submethod C is suitable for saturated materials such as fine-grained sediments. Submethod D is suitable for unsaturated porous material such as certain limestones and basalts.</p>
Data from "Multi-wavelength continuum sizes of protoplanetary discs: scaling relations and implications for grain growth and radial drift"
<p>Table 1, Table 2, and Table 3 from Tazzari et al., 2021, "Multi-wavelength continuum sizes of protoplanetary discs: scaling relations and implications for grain growth and radial drift", Monthly Notices of the Royal Astronomical Society, arXiv:2010.02249</p> <p>Both tables are available in IPAC format, which is in human- and machine-readable:</p> <pre><code class="language-python">from astropy.io import ascii tb = ascii.read('Table1.txt', format='ipac')</code></pre> <p>Table comments (stored at the beginning of the ASCII file as lines starting with "/") can be read as:</p> <pre><code class="language-python">tb.meta['comments'] </code></pre>
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.