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2,019 results for “boundary”
Dataset for "Effect of the atomic structure of complexions on the active disconnection mode during shear-coupled grain boundary motion"
<p>This repository contains the data of the simulations and theoretical<br>calculations of the paper "Effect of the atomic structure of complexions on the active disconnection mode during shear-coupled grain boundary motion".</p>
EU field boundaries
<p><em>A vector dataset of Field Boundaries, automatically delineated from Sentinel-2 satellite imagery from May-June 2022.</em></p> <p>Automatic field delineation refers to the process of automatically tracing the boundaries of agricultural parcels from satellite or aerial imagery. We consider an agricultural parcel as a spatially homogeneous land unit used for agricultural purposes, where a single crop is grown. The result of the FD is a set of closed vector polygons marking the extent of each agricultural parcel. Such polygons are the input to a multitude of applications, ranging from the management of agricultural resources, such as the Area Monitoring for the Common Agricultural Policy, to precision farming, to the estimation of damages to crop yield due to natural (e.g. drought, floods), and human-made disasters (e.g. war). Automatic estimation of parcels with high fidelity in a timely manner allows therefore to characterize the changes of agricultural landscapes due to anthropogenic activities, agricultural practices, and climate change consequences.</p> <p><strong>Additional links</strong></p> <ul> <li>Automatic Field Delineation <a href="https://medium.com/sentinel-hub/automatic-field-delineation-new-release-1c2938399f0">Blog post</a></li> <li>Dataset description on <a href="https://github.com/fiboa/data-survey/blob/main/data/Planet.md">Fiboa</a></li> </ul>
Phase Field Simulation of Morphotropic phase boundary of relaxor ferroelectrics
<p>Phase-field simulation of a mixed system of Tetragonal and Rhombohedral phases representing the morphotropic phase boundary of relaxor ferroelectrics</p>
Supplemental data from: "From lake to river: Documenting an environmental transition across the Jura/Knockfarril Hill members boundary in the Glen Torridon region of Gale crater (Mars)."
<p>This document, uploaded on the FAIR repository Zenodo, contains large data tables pertaining to the Supplementary Online Material of the above-mentioned article.</p> <p>These tables contain the complete list of individual MAHLI and ChemCam targets investigated, detailed laminae measurements and complete ChemCam compositional data.</p>
Datasets for the paper "Microstates and defects of incoherent Σ3 [111] twin boundaries in aluminum"
<p>This repository contains the raw data of the experimental EBSD analysis and the STEM imaging of the grain boundary microstates of ORI and ORII of the paper "Microstates and defects of incoherent Σ3 [111] twin boundaries in aluminum". Simulation data is also provided.</p> <p>See the file README.md for a detailed description.</p>
Geographical and geological GIS boundaries of the Tibetan Plateau and adjacent mountain regions
<p><strong>Introduction</strong></p> <p>Geographical scale, in terms of spatial extent, provide a basis for other branches of science. This dataset contains newly proposed geographical and geological GIS boundaries for the <strong>Pan-Tibetan Highlands </strong>(new proposed name for the High Mountain Asia), based on geological and geomorphological features. This region comprises the <strong>Tibetan Plateau</strong> and three adjacent mountain regions: the <strong>Himalaya</strong>, <strong>Hengduan Mountains</strong> and <strong>Mountains of Central Asia</strong>, and boundaries are also given for each subregion individually. The dataset will benefit quantitative spatial analysis by providing a well-defined geographical scale for other branches of research, aiding cross-disciplinary comparisons and synthesis, as well as reproducibility of research results.</p> <p>The dataset comprises three subsets, and we provide three data formats (.shp, .geojson and .kmz) for each of them. Shapefile format (.shp) was generated in ArcGIS Pro, and the other two were converted from shapefile, the conversion steps refer to 'Data processing' section below. The following is a description of the three subsets:</p> <p>(1) The GIS boundaries we newly defined of the Pan-Tibetan Highlands and its four constituent sub-regions, i.e. the Tibetan Plateau, Himalaya, Hengduan Mountains and the Mountains of Central Asia. All files are placed in the "Pan-Tibetan Highlands (Liu et al._2022)" folder.</p> <p>(2) We also provide GIS boundaries that were applied by other studies (cited in Fig. 3 of our work) in the folder "Tibetan Plateau and adjacent mountains (Others’ definitions)". If these data is used, please cite the relevent paper accrodingly. In addition, it is worthy to note that the GIS boundaries of Hengduan Mountains (Li et al. 1987a) and Mountains of Central Asia (Foggin et al. 2021) were newly generated in our study using Georeferencing toolbox in ArcGIS Pro.</p> <p>(3) Geological assemblages and characters of the Pan-Tibetan Highlands, including Cratons and micro-continental blocks (Fig. S1), plus sutures, faults and thrusts (Fig. 4), are placed in the "Pan-Tibetan Highlands (geological files)" folder.</p> <p>Note: <strong>High Mountain Asia</strong>: The name ‘High Mountain Asia’ is the only direct synonym of Pan-Tibetan Highlands, but this term is both grammatically awkward and somewhat misleading, and hence the term ‘Pan-Tibetan Highlands’ is here proposed to replace it. <strong>Third Pole</strong>: The first use of the term ‘Third Pole’ was in reference to the Himalaya by Kurz & Montandon (1933), but the usage was subsequently broadened to the Tibetan Plateau or the whole of the Pan-Tibetan Highlands. The mainstream scientific literature refer the ‘Third Pole’ to the region encompassing the Tibetan Plateau, Himalaya, Hengduan Mountains, Karakoram, Hindu Kush and Pamir. This definition was surpported by geological strcture (Main Pamir Thrust) in the western part, and generally overlaps with the ‘Tibetan Plateau’ <em>sensu lato</em> defined by some previous studies, but is more specific.</p> <p>More discussion and reference about names please refer to the paper. The figures (Figs. 3, 4, S1) mentioned above were attached in the end of this document.</p> <p> </p> <p><strong>Data processing</strong></p> <p>We provide three data formats. Conversion of shapefile data to kmz format was done in ArcGIS Pro. We used the <em>Layer to KML</em> tool in Conversion Toolbox to convert the shapefile to kmz format. Conversion of shapefile data to geojson format was done in R. We read the data using the <em>shapefile</em> function of the raster package, and wrote it as a geojson file using the <em>geojson_write</em> function in the geojsonio package.</p> <p> </p> <p><strong>Version</strong></p> <p>Version 2022.1.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>This study was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDB31010000), the National Natural Science Foundation of China (41971071), the Key Research Program of Frontier Sciences, CAS (ZDBS-LY-7001). We are grateful to our coauthors insightful discussion and comments. We also want to thank professors Jed Kaplan, Yin An, Dai Erfu, Zhang Guoqing, Peter Cawood, Tobias Bolch and Marc Foggin for suggestions and providing GIS files.</p> <p> </p> <p><strong>Citation</strong></p> <p>Liu, J., Milne, R. I., Zhu, G. F., Spicer, R. A., Wambulwa, M. C., Wu, Z. Y., Li, D. Z. (2022). Name and scale matters: Clarifying the geography of Tibetan Plateau and adjacent mountain regions. Global and Planetary Change, In revision</p> <p> </p> <p>Jie Liu & Guangfu Zhu. (2022). Geographical and geological GIS boundaries of the Tibetan Plateau and adjacent mountain regions (Version 2022.1). https://doi.org/10.5281/zenodo.6432940</p> <p> </p> <p><strong>Contacts</strong></p> <p>Dr. Jie LIU: E-mail: <a>liujie@mail.kib.ac.cn</a>;</p> <p>Mr. Guangfu ZHU: <a>zhuguangfu@mail.kib.ac.cn</a></p> <p>Institution: Kunming Institute of Botany, Chinese Academy of Sciences</p> <p>Address: 132# Lanhei Road, Heilongtan, Kunming 650201, Yunnan, China</p> <p> </p> <p><strong>Copyright</strong></p> <p>This dataset is available under the Attribution-ShareAlike 4.0 International (<a href="https://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA 4.0</a>).</p>
Supplement photos for paper: New genus Navipelta (Peltaspermales, Pteridospermae) from Permian-Triassic boundary of Moscow sineclise
<p>Additional images of ovuliferous organs <em>Navipelta </em>from the terrestrial deposits of the Nedubrovo locality (village of Nedubrovo, Vologda Region, Russia), belonging to the base of Vetlugian Group (Upper Permian–Lower Triassic)</p>
Data for manuscript "Creating boundaries along a synthetic frequency dimension" in Nature Communications
<p>Data for manuscript "Creating boundaries along a synthetic frequency dimension"</p> <p>https://www.nature.com/articles/s41467-022-31140-7</p> <p>https://arxiv.org/abs/2203.11296</p>
Data set: Variations in water economy traits in two Sphagnum species across their distribution boundaries
<p><em>Sphagnum</em> trait data collected (2016-2017) across a climatic gradient in Sweden. Trait data for both shoot and canopy traits. Data for <em>Sphagnum cuspidatum</em> and <em>Sphagnum lindbergii</em>. Also contains data on species occurrence records in Sweden and output from speceis distribution modelling. See published paper for more information.</p> <p>Files contain (i) processed data ("calculated_trait_data...cvs"), (ii) raw data ("Campbell_etal_clim_traits_...cvs"), (iii) their readme files, and (iv) R-scripts to run the analyses. Note that you need the files in the zip-file to run the analyses in the R-script. The zip-file contains all raw data (climate, traits, species occurences), MaxEnt output, and raster files from photogrammetry.</p> <p>More info in paper: <a href="https://doi.org/10.1002/ajb2.16347" target="_blank" rel="noopener">https://doi.org/10.1002/ajb2.16347</a></p>
Dataset for "A simple and accurate method to determine fluid-crystal phase boundaries from direct coexistence simulations"
<p>This is a dataset for the article "A simple and accurate method to determine fluid-crystal phase boundaries from direct coexistence simulations", available at https://arxiv.org/abs/2403.10891 (Full citation data will be added upon final publication of the article.)</p> <p>This package provides figure data and representative configuration files associated with the systems studied in the article above. Additionally, for the hard sphere system, this package includes direct coexistence data for all reported system sizes and crystal orientations.</p> <p> </p> <p> </p>
Aeroacoustic investigations of streamwise vortex generators for boundary layer separation control.
<p>This project contains the data obtained as a result of the Preludium Grant no 2022/45/N/ST8/01425 of the Polish National Science Centre fundings. Within the "Aeroacoustic investigations of streamwise vortex generators for boundary layer separation control" project, two main research tasks were defined:<br> 1. Implementation of porous FW-H analogy into the developed aeroacoustic code.<br> 2. Validation of the porous FW-H analogy implementation against analytical solutions for elementary sources.</p> <p>The resutls from these tasks are uploaded here. The details of the data are included in the EOP_medata_2.docx document uploaded. </p>
Data for: Nonlinear dynamics of the near-shore boundary layer of a large lake (Lake Geneva)
<p>We examined near-shore and pelagic current variability in Lake Geneva, a large and deep lake in western Europe, using observations from several measurement locations and a three dimensional numerical model, based on the period 2014–2016. The data include measurements from Acoustic Doppler Current Profiler (ADCP) campaigns and vertical temperature profiles along with the corresponding modelling results. The model used in this study is based on the MIT General Circulation Model (MITgcm, <a href="http://mitgcm.org/">http://mitgcm.org/</a>, <a href="https://doi.org/10.1029/96JC02775">https://doi.org/10.1029/96JC02775</a>).</p>
Supplementary Dataset: chapter 9 of "Chemostratigraphy Across Major Chronological Boundaries"
<p>This dataset belongs to the book chapter (ch 9): "Chemostratigraphy across the Permian-Triassic Boundary: The Effect of Sampling Strategies on Carbonate-carbon Isotope Stratigraphic Markers" written by: Schobben, M., Heuer, F., Tietje, M., Ghaderi, A., Korn, D., Korte, C., Wignall, P.B., as part of the book: "Chemostratigraphy Across Major Chronological Boundaries", published by the American Geophysical Union and Wiley, The book is edited by Sial, A.N., Gaucher, C., Ramkumar, M., Ferreira, V.P. and is due to appear in Januari 2019. The dataset is the bulk carbonate carbon and oxygen isotope data used in the aforementioned chapter. The x and y column refer to coordinates on the drilled surface of the polished rock slabs.</p>
Detecting edge effects of geese grazing at the boundary of woodland and grassland
<p>The presence of geese on different areas of lawn was estimated by the length of droppings on the lawn. Geese defecate frequently and seemingly indiscriminately. Counting dropping is a well-known method for estimating their density on areas of land (Owen, 1971). However, we found it difficult to distinguish individual defecation events as the dropping tend to break apart as they are released. Therefore, we measured the total length of dropping in an area. Geese dropping are more or less cylindrical and we consider a measure related to the volume of droppings is more reliable than a count of their number.</p> <p>Observations were conducted in July 2014 and March and April 2015 at Meise Botanic Garden, Meise, Belgium. Rectangular plots were laid out perpendicular to a woodland-lawn boundary on sections of a Botanic Garden frequently used by geese. These plots are detailed in file DroppingsPlots.csv. The sites for these plots were chosen because they were well separated from each other; were away from other trees and faced different directions. The plots were marked out using bamboo canes and a tape measure. Then either 20 or 30 randomly chosen 1 m<sup>2</sup> square quadrats were surveyed within the rectangular plot. The cumulative length of dropping in a quadrat was measured to the nearest centimeter with a ruler.</p> <p>The results are found in file DroppingsMeasurements.csv.</p> <p>The columns of this file are as follows</p> <p>Plot - The identifying number given to the plot</p> <p>X - The distance parallel to the woodland-lawn boundary</p> <p>Y - The distance from the woodland-lawn boundary</p> <p>Length - The total length in centimeters of the dropping found in a 1m<sup>2</sup> quadrat</p> <p>Prunella - coverage of <em>Prunella vulgaris</em> L. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Renoncule - coverage of <em>Ranunculus</em> sp. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Bellis - coverage of <em>Bellis perennis</em> L. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Lotus - coverage of <em>Lotus</em> sp. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Glechoma - coverage of <em>Glechoma hederacea</em> L. in the 1m<sup>2</sup> quadrat on the DAFOR Scale (dominant 5, abundant 4, frequent 3, occasional 2, rare 1, absent 0)</p> <p>Four species of geese are present in the Botanic Garden and may have contributed droppings to the observations. These species are <em>Alopochen aegyptiaca</em> (L. 1766) (Egyptian geese), <em>Branta canadensis</em> (L. 1758) (Canada geese), <em>Anser anser</em> (L. 1758) (greylag geese) and <em>Branta leucopsis</em> (Bechstein, 1803) (barnacle geese).</p>
Photometric stereo data of non-crimp fabric boundaries
<p><strong>DATA DESCRIPTION</strong></p> <p>This data set was acquired in the context of EU project ZAero. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 721362. Project duration: 2016/10/01 - 2019/09/30. This data set contains a set of 68 HDF5 files from two different example surface patches of NCF carbon fiber fabrics.</p> <p>For more information about the HDF5 format, please visit the HDF5 Group website:<br> https://www.hdfgroup.org/solutions/hdf5/</p> <p>Each file contains data from a photometric stereo vision system [1]. The data set is intended for evaluation of methods for carbon fiber fabric edge detection [2].</p> <p>Each file contains a single 3-dimensional (W x H x L) array 'raw' with:<br> H...height of the images<br> W...width of the images<br> L...number of images with different light sources (L = 8)</p> <p>An example for loading and visualizing the data in Python comes with this data set:<br> readDataExample.py</p> <p><br> <strong>REFERENCES</strong></p> <p>[1]<br> @inproceedings{Palfinger2011, <br> author = {Palfinger, Werner and Thumfart, Stefan and Eitzinger, Christian},<br> title = {Photometric stereo on carbon fiber surfaces},<br> booktitle = {35th Workshop of the Austrian Association for Pattern Recognition},<br> year = {2011}<br> }</p> <p>[2]<br> @inproceedings{Zambal2019,<br> author = {Zambal, Sebastian and Heindl, Christoph and Eitzinger, Christian}<br> title = {Probabilistic Modelling combined with a CNN for boundary detection of carbon fiber fabrics},<br> booktitle = {IEEE International Conference on Industrial Informatics (INDIN)}<br> year = {2019}<br> }</p> <p> </p> <p> </p>
Unstable Ion Composition Boundary Layer Crossings
<p>A list of unstable ion composition boundary layer crossings by the MAVEN spacecraft, separated into three categories. "Snowplow" events have discrete parcels of low energy escaping heavy ion plasma interspersed with more energetic magnetosheath plasma. "Plume" events have higher energy escaping heavy ions with a beam-like distribution, interspersed with magnetosheath plasma. "Unclassified" events do not neatly fit in either of these categories. </p>
Data for the paper "Construction of an invertible mapping to boundary conforming coordinates for arbitrarily shaped toroidal domains."
<p>Data and scripts for the paper "Construction of an invertible mapping to boundary conforming coordinates for arbitrarily shaped toroidal domains."</p> <p>Presented at the "JOINT VARENNA - LAUSANNE INTERNATIONAL WORKSHOP: THEORY OF FUSION PLASMAS, 2024" and published in PPCF.</p>
Atmospheric sounding of the boundary layer over alpine glaciers using fixed-wing UAVs
<p>Additional code and data for the paper by Groos et al. entitled "Atmospheric sounding of the boundary layer over alpine glaciers using fixed-wing UAVs"</p> <p>Correspondence: Alexander R. Groos (alexander.groos@fau.de)</p> <p><br>The repository contains:<br>(1) The raw data (log files) for each UAV-based atmospheric sounding<br>(2) The postprocessed and reformatted data for each sounding and vertical profile<br>(3) The commented R-Scripts for data processing, analysis and visualisation<br>(4) A subset of the meteorological data from the nearby weather stations</p> <p><br>Description of sub-folders:</p> <p>-aws_data<br>-- aws_fisistock.txt # meteorological data from AWS Fisistock for the period of the campaign<br>-- aws_gandegg.txt # meteorological data from AWS Gandegg for the period of the campaign<br>-- aws_sackhorn.txt # meteorological data from AWS Sackhorn for the period of the campaign</p> <p>- processed_data<br>-- kanderfirn_2021-06-16_10:45_p1_pprz.tab # meteorological data for first profile/descent at about <br>-- kanderfirn_2021-06-16_10:45_p2_fr.tab # flight recorder data for second profile/descent at about 10:45 CEST<br>-- kanderfirn_2021-06-16_10:45_p2_pprz.tab # meteorological data for second profile/descent at about 10:45 CEST<br>-- kanderfirn_2021-06-16_10:45_pprz.tab # meteorological data for the entire sounding (first and second profile/descent) at about 10:45 CEST<br>-- .<br>-- .<br>-- .<br>-- kanderfirn_2021-06-16_16:50_p1_pprz.tab # meteorological data for first profile/descent at about 16:50 CEST<br>-- kanderfirn_2021-06-16_16:50_p2_fr.tab # flight recorder data for second profile/descent at about 16:50 CEST<br>-- kanderfirn_2021-06-16_16:50_p2_pprz.tab # meteorological data for second profile/descent at about 16:50 CEST<br>-- kanderfirn_2021-06-16_16:50_pprz.tab # meteorological data for the entire sounding (first and second profile/descent) at about 16:50 CEST<br>-- kanderfirn_soundings_2021-06-16.csv # summary table of vertical profiles (1 m height intervals): one column for each profile/descent and variable<br>-- kanderfirn_turbulence_2021-06-16.csv # summary table of vertical turbulence profiles (1 m height intervals): one column for each profile/descent</p> <p>- raw_data<br>-- fr_kanderfirn_2021-06-16_10:45.LOG # flight recorder data from the sounding at about 10:45 CEST (binary file)<br>-- .<br>-- .<br>-- .<br>-- fr_kanderfirn_2021-06-16_16:50.LOG # flight recorder data from the sounding at about 16:50 CEST (binary file)<br>-- pprz_kanderfirn_2021-06-16_10:45.LOG # meteorological data from the sounding at about 10:45 CEST (human readable text file)<br>-- .<br>-- .<br>-- .<br>-- pprz_kanderfirn_2021-06-16_16:50.LOG # meteorological data data from the sounding at about 16:50 CEST (human readable text file)</p> <p>- R_scripts<br>-- figures.R # Script to create Figures 5, 6, 8, 9, 10, 11, 12<br>-- lapse_rate.R # Script to calculate lapse rates and surface-based inversions (includes code for Figures 7 and B1)<br>-- postprocessing.R # Script to reformat preprocessed and preselected pprz-files<br>-- turbulence.R # Script for the calculation of the turbulence proxy from the recorded roll rate</p>
Development and analysis of entropy stable no-slip wall boundary conditions for the Eulerian model for viscous and heat conducting compressible flows
<p>The database used in the submission of "Development and analysis of entropy stable no-slip wall boundary conditions implementation of the Eulerian model for viscous and heat conducting compressible flows."</p> <p>Abstract: Nonlinear entropy stability analysis is used to derive entropy stable no-slip wall boundary conditions for the Eulerian model proposed by Svärd ( <em>Physica A: Statistical Mechanics and its Applications, 2018 </em>). and its spatial discretization based on entropy stable collocated discontinuous Galerkin operators with the summation-by-parts property for unstructured grids. A set of viscous test cases of increasing complexity are simulated using both the Eulerian and the classic compressible Navier–Stokes models. The numerical results obtained with the two models are compared, and differences and similarities are then highlighted.</p>
Measurement and prediction of bottom boundary layer hydrodynamics under modulated oscillatory flows
<p>Experimental and numerical model data pertaining to the manuscript "Measurement and prediction of bottom boundary layer<br> hydrodynamics under modulated oscillatory flows" accepted for publication in Coastal Engineering (<a href="https://doi.org/10.1016/j.coastaleng.2021.103954">https://doi.org/10.1016/j.coastaleng.2021.103954</a>)</p> <p>Please read the README.txt file for more information.</p>
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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.