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11,982 results for “africa”
ERA5-Land selected indicators daily aggregates for Africa, 1976
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1976.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for Africa, 1977
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1977.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for Africa, 1979
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1979.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for Africa, 1978
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1978.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for Africa, 1974
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1974.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for Africa, 1970
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1970.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p> </p>
ERA5-Land selected indicators daily aggregates for Africa, 1973
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1973.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for Africa, 1971
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1971.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for Africa, 1972
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1972.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
Continuous phylogeography analysis of Rift Valley fever virus (RVFV) in Africa and the Arabian Peninsula
<p>Spatiotemporal-explicit Bayesian phylogenetic trees and MCMC log files for Rift Valley fever virus large, medium and non-structural genetic sequences generated by BEAST v1.10</p> <ol> <li>Log files (logs.zip)</li> <li>Tree files (trees.zip)</li> </ol>
Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa: collation and synthesis of survey data 2010-2023
<p>This dataset contains surveillance study estimates for population size, HIV prevalence, and ART coverage among female sex workers (FSW), men who have sex with men (MSM), people who inject drugs (PWID), and transgender men and women (TGM/W) from 2010-2023. It was created to support the UNAIDS Estimates Key Population Workbook for use by HIV estimates teams in sub-Saharan Africa. Key population surveillance reports, including Ministry of Health-led biobehavioural surveys, mapping studies, and academic studies were used to populate the database.</p> <p>The dataset was populated using existing key population size estimate databases including:</p> <ul> <li>UNAIDS Key Population Atlas</li> <li>US Centers for Disease Control and Prevention surveillance database</li> <li>Global Fund against HIV/AIDS, TB, and Malaria surveillance database</li> <li>Global.HIV database</li> <li>Systematic review databases among MSM (<a href="https://pubmed.ncbi.nlm.nih.gov/31601542/" target="_blank" rel="noopener">Stannah et al, 2019</a> and <a href="https://pubmed.ncbi.nlm.nih.gov/37453439/" target="_blank" rel="noopener">Stannah et al., 2023</a>) and PWID (<a href="https://pubmed.ncbi.nlm.nih.gov/36996857/" target="_blank" rel="noopener">Degenhardt et al., 2023</a>)</li> </ul> <p><br>and was additionally supplemented by a literature review of peer-reviewed and grey literature sources.</p> <p>The data can be <a href="https://shiny.dide.ic.ac.uk/kp-data/" target="_blank" rel="noopener">explored in this web application</a> and the <a href="https://www.medrxiv.org/content/10.1101/2022.07.27.22278071v3" target="_blank" rel="noopener">accompanying manuscript can be found here</a></p>
Appendix S3 from: Droissart V, Dauby G, Hardy OJ, Deblauwe V, Harris DJ, Janssens S, Mackinder BA, Blach-Overgaard A, Sonké B, Sosef MSM, Stévart T, Svenning J-C, Wieringa JJ, Couvreur TLP (2018) Beyond trees: biogeographical regionalization of tropical Africa. Journal of Biogeography. DOI:10.1111/jbi.13190
<p>This dataset corresponds to GIS file that were generated in the study published by Droissart, Dauby et al. in <em>Journal of Biogeography</em>:</p> <p>Droissart V, Dauby G, Hardy OJ, Deblauwe V, Harris DJ, Janssens S, Mackinder BA, Blach-Overgaard A, Sonké B, Sosef MSM, Stévart T, Svenning J-C, Wieringa JJ, Couvreur TLP (2018) Beyond trees: biogeographical regionalization of tropical Africa. <em>Journal of Biogeography. </em>DOI:10.1111/jbi.13190</p> <p><em>Please cite the aforementioned article and the dataset herein, when using of any of these files in this dataset.</em></p> <p> </p> <p>The GIS file is referred in the paper as <strong>Appendix S3</strong> and correspond to the map presented in Figure 1. Each polygons of the shapefile correspond to the main floristic bioregions and transition zones of tropical Africa delimited using bipartite network clustering analysis of 24,719 plant species.</p> <p>The coordinate system of the ESRI shapefile is GCS_WGS_1984. Field descriptions for the associate table are:</p> <ul> <li><strong>bionames</strong>: name of the bioregions as given in Table S1.1.</li> <li><strong>bioreg_ID</strong>: identifier of the bioregions as given in Table S1.1 and Fig. 1. T= Transition zones</li> <li><strong>cluster_ID</strong>: identifier of clusters delimited using bipartite network clustering on the 24,719 plant species of the RAINBIO database, as given in Table S1.1 and Fig. S2.1.</li> </ul>
Regional climate simulations of surface precipitation and temperature for West Africa using COSMO-CLM based on MPI-LR (ECHAM6) and RCP4.5
<p>Regional climate model COSMO-CLM (CCLM) simulations with a horizontal resolution of 0.11° (approx. 12 km) for sub-Saharan West Africa under current and future climate conditions. The CCLM is driven by initial and lateral boundary conditions from the MPI-LR (ECHAM6), based on the emission scenario RCP4.5. The downscaled MPI-LR (ECHAM6) data for surface precipitation (P) and surface temperature (Tmin, Tmax) are provided for the baseline period (1981-2010) and two future time slices, i.e. the 2021–2050 and the 2071–2100 period. </p> <p> </p>
Regional model results (combined) for the six transition potentials (one for Africa, Australia, Asia, Europe, North America, and South America)
<p>Results for the six regional models showing areas of high potential to transition from tree cover to tree cover loss to areas of low potential to transition.</p>
Geographic variation of tree height of Pinus pinaster Aiton gathered from common gardens in Europe and North-Africa
<p>This dataset collects individual georeferenced tree height data from <em>Pinus pinaster</em> Aiton planted in common gardens in France, Morocco and Spain, between years 1966 and 1992. The experimental design varies depending on the common garden, from a randomized complete to incomplete block design, RCB or RIB, respectively. The final dimension of the dataset is 123,801 individual tree height data measurements <em> </em>with 14 common gardens and 182 different genetic units. The data can be used to assess genetic variation and phenotypic plasticity with further applications in biogeography and forest management. </p>
National Checklists 2017: Africa Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>List of species from the continent of Africa inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2017: South Africa Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from South Africa collected using effechecka and geonames polygons
National Checklists 2019: Africa Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>List of species from the continent of Africa inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2019: South Africa Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from South Africa collected using effechecka and geonames polygons
National Checklists 2019: Africa Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>List of species from the continent of Africa inferred from individual country lists that were derived from effechecka and modified geonames polygons
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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.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.