cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8380508
title: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 3)

description: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 3) https://sites.google.com/view/icassp2024-spgc-3dcbct/home Please download all files (of all parts, 1-5) into one folder, and then merge them together with: <pre><code class="language-bash">$ zip -s 0 train.zip --out train_unsplit.zip </code></pre> This will create a new zip file, "train_unsplit.zip" that then you can unzip with your favorite tool, e.g. <pre><code class="language-bash">$ unzip train_unsplit.zip</code></pre> The CBCT geometry required to be used image size : [300 300 300] mm<br> image shape : [256 256 256] voxels<br> voxel size : [1.171875 1.171875 1.171875] mm<br> detector shape : [256 256] pixels<br> detector size : [600, 600] mm<br> pixel size : [2.34375, 2.34375] mm<br> distance source origin (axis of rotation, center of image) : 575 mm<br> distance source to detector : 1050 mm We recommend zenodo_get to download the files:<br> https://github.com/dvolgyes/zenodo_get Remember that to be part of the challenge you need to register in the webpage above.
DOI: 10.5281/zenodo.8380507
title: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 3)

description: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 3) https://sites.google.com/view/icassp2024-spgc-3dcbct/home Please download all files (of all parts, 1-5) into one folder, and then merge them together with: <pre><code class="language-bash">$ zip -s 0 train.zip --out train_unsplit.zip </code></pre> This will create a new zip file, "train_unsplit.zip" that then you can unzip with your favorite tool, e.g. <pre><code class="language-bash">$ unzip train_unsplit.zip</code></pre> The CBCT geometry required to be used image size : [300 300 300] mm<br> image shape : [256 256 256] voxels<br> voxel size : [1.171875 1.171875 1.171875] mm<br> detector shape : [256 256] pixels<br> detector size : [600, 600] mm<br> pixel size : [2.34375, 2.34375] mm<br> distance source origin (axis of rotation, center of image) : 575 mm<br> distance source to detector : 1050 mm We recommend zenodo_get to download the files:<br> https://github.com/dvolgyes/zenodo_get Remember that to be part of the challenge you need to register in the webpage above.
DOI: 10.58119/ulg/27vzid/8pgz2h
title: CICDFRA2.DAT

description: :unav
DOI: 10.58119/ulg/27vzid/4aqtjm
title: CICDCAEL.DAT

description: :unav
DOI: 10.58119/ulg/27vzid/g6ok2q
title: CICDIVAT.DAT

description: :unav
DOI: 10.58119/ulg/27vzid/nnrvv8
title: SenMarci.DAT

description: :unav
DOI: 10.6084/m9.figshare.24173738.v1
title: Global polymorphism of <i>Plasmodium falciparum</i> histidine rich proteins 2/3 and impact on malaria rapid diagnostic test detection: a systematic review and meta-analysis

description: This review presents an overview of field findings on sequence variation of <i>Plasmodium falciparum</i> histidine-rich proteins 2/3 (<i>Pf</i>HRP2/3) for which reference types (1–24) have been identified, and its critical impact on <i>Pf</i>HRP2-based rapid diagnostic test (RDT) detection. This systematic review and meta-analysis was registered with PROSPERO, CRD42022316027, and conducted as per the PRISMA guidelines, and the methodological quality of studies was assessed. Of the 2184 records identified, 34 studies were included mostly from Africa (47.1%) and Asia (35.3%). The reference <i>Pf</i>HRP2 types 1, 2, 3, 6, and 7 are invariably found at proportions ≥ 80–100% in all areas with the exception of The Americas where their proportion is very low. The proteins exhibited high diversity of variants/unknown types, especially for types 1, 2, 4, and 7. Eleven major <i>Pf</i>HRP2 epitopes were found at pooled proportion &gt; 90%. The existing models to predict RDT detection are greatly limited by the impact of factors such as low (very low) parasitemia, RDT brand, and <i>Pf</i>HRP3 cross-reactivity. <i>Pf</i>HRP2 length and presence/number of a given reference repeat type/variant did not seem to impact RDT detection. <i>Pf</i>HRP2/3 are highly polymorphic and current findings are insufficient, conflicting and not convincing enough to conclude on the role of <i>Pf</i>HRP2/3 sequence polymorphism in <i>Pf</i>HRP2-based RDT detection.
DOI: 10.6084/m9.figshare.24173738
title: Global polymorphism of <i>Plasmodium falciparum</i> histidine rich proteins 2/3 and impact on malaria rapid diagnostic test detection: a systematic review and meta-analysis

description: This review presents an overview of field findings on sequence variation of <i>Plasmodium falciparum</i> histidine-rich proteins 2/3 (<i>Pf</i>HRP2/3) for which reference types (1–24) have been identified, and its critical impact on <i>Pf</i>HRP2-based rapid diagnostic test (RDT) detection. This systematic review and meta-analysis was registered with PROSPERO, CRD42022316027, and conducted as per the PRISMA guidelines, and the methodological quality of studies was assessed. Of the 2184 records identified, 34 studies were included mostly from Africa (47.1%) and Asia (35.3%). The reference <i>Pf</i>HRP2 types 1, 2, 3, 6, and 7 are invariably found at proportions ≥ 80–100% in all areas with the exception of The Americas where their proportion is very low. The proteins exhibited high diversity of variants/unknown types, especially for types 1, 2, 4, and 7. Eleven major <i>Pf</i>HRP2 epitopes were found at pooled proportion &gt; 90%. The existing models to predict RDT detection are greatly limited by the impact of factors such as low (very low) parasitemia, RDT brand, and <i>Pf</i>HRP3 cross-reactivity. <i>Pf</i>HRP2 length and presence/number of a given reference repeat type/variant did not seem to impact RDT detection. <i>Pf</i>HRP2/3 are highly polymorphic and current findings are insufficient, conflicting and not convincing enough to conclude on the role of <i>Pf</i>HRP2/3 sequence polymorphism in <i>Pf</i>HRP2-based RDT detection.
DOI: 10.58119/ulg/27vzid/lwonxg
title: CesBGall.DAT

description: :unav
DOI: 10.58119/ulg/27vzid/xuvldg
title: Cic_FD01.dat

description: :unav
DOI: 10.5281/zenodo.8380914
title: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 5)

description: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 5) https://sites.google.com/view/icassp2024-spgc-3dcbct/home Please download all files (of all parts, 1-5) into one folder, and then merge them together with: $ zip -s 0 train.zip --out train_unsplit.zip This will create a new zip file, "train_unsplit.zip" that then you can unzip with your favorite tool, e.g. $ unzip train_unsplit.zip <br> The CBCT geometry required to be used image size : [300 300 300] mm<br> image shape : [256 256 256] voxels<br> voxel size : [1.171875 1.171875 1.171875] mm<br> detector shape : [256 256] pixels<br> detector size : [600, 600] mm<br> pixel size : [2.34375, 2.34375] mm<br> distance source origin (axis of rotation, center of image) : 575 mm<br> distance source to detector : 1050 mm We recommend zenodo_get to download the files:<br> https://github.com/dvolgyes/zenodo_get <br> Remember that to be part of the challenge you need to register in the webpage above.
DOI: 10.5281/zenodo.8380874
title: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 4)

description: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 4) https://sites.google.com/view/icassp2024-spgc-3dcbct/home Please download all files (of all parts, 1-5) into one folder, and then merge them together with: $ zip -s 0 train.zip --out train_unsplit.zip [Click and drag to move] This will create a new zip file, "train_unsplit.zip" that then you can unzip with your favorite tool, e.g. $ unzip train_unsplit.zip [Click and drag to move] <br> The CBCT geometry required to be used image size : [300 300 300] mm<br> image shape : [256 256 256] voxels<br> voxel size : [1.171875 1.171875 1.171875] mm<br> detector shape : [256 256] pixels<br> detector size : [600, 600] mm<br> pixel size : [2.34375, 2.34375] mm<br> distance source origin (axis of rotation, center of image) : 575 mm<br> distance source to detector : 1050 mm We recommend zenodo_get to download the files:<br> https://github.com/dvolgyes/zenodo_get <br> Remember that to be part of the challenge you need to register in the webpage above.
DOI: 10.5281/zenodo.8380913
title: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 5)

description: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 5) https://sites.google.com/view/icassp2024-spgc-3dcbct/home Please download all files (of all parts, 1-5) into one folder, and then merge them together with: $ zip -s 0 train.zip --out train_unsplit.zip This will create a new zip file, "train_unsplit.zip" that then you can unzip with your favorite tool, e.g. $ unzip train_unsplit.zip <br> The CBCT geometry required to be used image size : [300 300 300] mm<br> image shape : [256 256 256] voxels<br> voxel size : [1.171875 1.171875 1.171875] mm<br> detector shape : [256 256] pixels<br> detector size : [600, 600] mm<br> pixel size : [2.34375, 2.34375] mm<br> distance source origin (axis of rotation, center of image) : 575 mm<br> distance source to detector : 1050 mm We recommend zenodo_get to download the files:<br> https://github.com/dvolgyes/zenodo_get <br> Remember that to be part of the challenge you need to register in the webpage above.
DOI: 10.58119/ulg/27vzid/zxpppt
title: Petrone.dat

description: :unav
DOI: 10.5281/zenodo.8380873
title: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 4)

description: Train Dataset for the ICASSP-2024 3D-CBCT challenge (Part 4) https://sites.google.com/view/icassp2024-spgc-3dcbct/home Please download all files (of all parts, 1-5) into one folder, and then merge them together with: $ zip -s 0 train.zip --out train_unsplit.zip [Click and drag to move] This will create a new zip file, "train_unsplit.zip" that then you can unzip with your favorite tool, e.g. $ unzip train_unsplit.zip [Click and drag to move] <br> The CBCT geometry required to be used image size : [300 300 300] mm<br> image shape : [256 256 256] voxels<br> voxel size : [1.171875 1.171875 1.171875] mm<br> detector shape : [256 256] pixels<br> detector size : [600, 600] mm<br> pixel size : [2.34375, 2.34375] mm<br> distance source origin (axis of rotation, center of image) : 575 mm<br> distance source to detector : 1050 mm We recommend zenodo_get to download the files:<br> https://github.com/dvolgyes/zenodo_get <br> Remember that to be part of the challenge you need to register in the webpage above.
DOI: 10.58119/ulg/27vzid/6rikel
title: CICDFRA1.DAT

description: :unav
DOI: 10.58119/ulg/27vzid/digiwd
title: CICDRPOS.DAT

description: :unav
DOI: 10.58119/ulg/27vzid/bh57ac
title: CICDRSEN.DAT

description: :unav
DOI: 10.58119/ulg/27vzid/2kni4n
title: CICDCLUE.DAT

description: :unav
DOI: 10.58119/ulg/27vzid/kyqcuw
title: DAT_french.pdf

description: :unav
DOI: 10.58119/ulg/27vzid/cijcca
title: Cic_FD09.dat

description: :unav
DOI: 10.6084/m9.figshare.23996628.v2
title: Behavioral data

description: Behavioral and fNIRS data
DOI: 10.5281/zenodo.8332447
title: Linear-stability analysis of plane beds under flows with suspended loads

description: The compiled bedform data and the source codes of linear stability analysis used for the paper.
DOI: 10.25794/reference/z/iiguc0
title: Xac-C40
DOI: 10.6084/m9.figshare.23996628
title: Behavioral data

description: Behavioral and fNIRS data
DOI: 10.6084/m9.figshare.24212508
title: <b>Sex-driven neighborhood effects on herbivory in the dioecious Mediterranean palm </b><b><i>Chamaerops humilis</i></b><b> L.</b>

description: Although it is well recognized that the strength of plant-herbivore interactions can vary with plant sex and the distance and density of conspecific neighbors, no study has yet assessed their combined influence. Here, we filled this knowledge gap by focusing on the dioecious palm <i>Chamaerops humilis</i> L., and its two main herbivores, the invasive moth <i>Paysandisia archon</i> Burmeister and the feral goat <i>Capra hircu</i>s L. We evaluated levels and spatial patterns of herbivory, as well as those of plant size and the number of inflorescences in two palm populations in Mallorca (Balearic Islands, Spain). Our spatial point pattern analyses revealed that palms not affected by moth herbivory or goat florivory were spatially aggregated, goats fed more strongly upon inflorescences in palms with more neighbors but they consumed more leaves in isolated palms. Interestingly, we could reveal for the first time that plant sex is a key plant trait modulating neighborhood effects. For instance, whereas aggregated female palms experienced lower intensity of goat florivory than isolated ones, male palms showed the opposite pattern. Palm size and the number of inflorescences also showed sex-related differences, suggesting that sexual dimorphism is a key driver of the observed neighborhood effects on herbivory. Our study highlights the importance of considering relevant plant traits such as sex when investigating plant neighborhood effects, calling for further research to fully understand the dynamics governing plant-herbivore interactions in dioecious systems.
DOI: 10.34740/kaggle/dsv/6563682
title: ImageCategorizerSoftware
DOI: 10.5281/zenodo.7849135
title: Høje-Taastrup - Sankey and indicator data for construction sector

description: This excel sheet was made by the CityLoops course participants for Høje-Taastrup, Denmark and contains the data needed for the Sankey diagram and indicators for the Sector-wide Circularity Assessment for the Biomass and Construction sectors. "CityLoops - Closing the loop for urban material flows" is a EU Horizon2020 project with 28 partners. <em>(Official project website: https://cityloops.eu/)</em>. CityLoops brings together six ambitious European cities to demonstrate a series of innovative tools and urban planning approaches, aimed at closing the loops of urban material flows and increasing their regenerative capacity. (For detailed information please visit: https://cityloops.metabolismofcities.org/library/1009545/)
DOI: 10.5281/zenodo.7849104
title: Mikkeli - Sankey and indicator data for construction and biomass sectors

description: This excel sheet was made by the CityLoops course participants for Mikkeli, Finland and contains the data needed for the Sankey diagram and indicators for the Sector-wide Circularity Assessment for the Biomass and Construction sectors. "CityLoops - Closing the loop for urban material flows" is a EU Horizon2020 project with 28 partners. <em>(Official project website: https://cityloops.eu/)</em>. CityLoops brings together six ambitious European cities to demonstrate a series of innovative tools and urban planning approaches, aimed at closing the loops of urban material flows and increasing their regenerative capacity. (For detailed information please visit: https://cityloops.metabolismofcities.org/library/997499/)
DOI: 10.5281/zenodo.7849105
title: Mikkeli - Sankey and indicator data for construction and biomass sectors

description: This excel sheet was made by the CityLoops course participants for Mikkeli, Finland and contains the data needed for the Sankey diagram and indicators for the Sector-wide Circularity Assessment for the Biomass and Construction sectors. "CityLoops - Closing the loop for urban material flows" is a EU Horizon2020 project with 28 partners. <em>(Official project website: https://cityloops.eu/)</em>. CityLoops brings together six ambitious European cities to demonstrate a series of innovative tools and urban planning approaches, aimed at closing the loops of urban material flows and increasing their regenerative capacity. (For detailed information please visit: https://cityloops.metabolismofcities.org/library/997499/)
DOI: 10.5281/zenodo.7849134
title: Høje-Taastrup - Sankey and indicator data for construction sector

description: This excel sheet was made by the CityLoops course participants for Høje-Taastrup, Denmark and contains the data needed for the Sankey diagram and indicators for the Sector-wide Circularity Assessment for the Biomass and Construction sectors. "CityLoops - Closing the loop for urban material flows" is a EU Horizon2020 project with 28 partners. <em>(Official project website: https://cityloops.eu/)</em>. CityLoops brings together six ambitious European cities to demonstrate a series of innovative tools and urban planning approaches, aimed at closing the loops of urban material flows and increasing their regenerative capacity. (For detailed information please visit: https://cityloops.metabolismofcities.org/library/1009545/)
DOI: 10.5281/zenodo.7849185
title: Porto - Sankey and indicator data for biomass sector

description: This excel sheet was made by the CityLoops course participants for Bodø, Norway and contains the data needed for the Sankey diagram and indicators for the Sector-wide Circularity Assessment for the Biomass and Construction sectors. "CityLoops - Closing the loop for urban material flows" is a EU Horizon2020 project with 28 partners. <em>(Official project website: https://cityloops.eu/)</em>. CityLoops brings together six ambitious European cities to demonstrate a series of innovative tools and urban planning approaches, aimed at closing the loops of urban material flows and increasing their regenerative capacity. (For detailed information please visit: https://cityloops.metabolismofcities.org/library/997482/)
DOI: 10.5281/zenodo.7849184
title: Porto - Sankey and indicator data for biomass sector

description: This excel sheet was made by the CityLoops course participants for Bodø, Norway and contains the data needed for the Sankey diagram and indicators for the Sector-wide Circularity Assessment for the Biomass and Construction sectors. "CityLoops - Closing the loop for urban material flows" is a EU Horizon2020 project with 28 partners. <em>(Official project website: https://cityloops.eu/)</em>. CityLoops brings together six ambitious European cities to demonstrate a series of innovative tools and urban planning approaches, aimed at closing the loops of urban material flows and increasing their regenerative capacity. (For detailed information please visit: https://cityloops.metabolismofcities.org/library/997482/)
DOI: 10.6084/m9.figshare.24211401
title: stem_fNIRS_HbR.mat

description: HbR data
DOI: 10.6084/m9.figshare.24211401.v2
title: stem_fNIRS_HbR.mat

description: HbR data
DOI: 10.6084/m9.figshare.24211401.v1
title: study3_HbR.mat

description: HbR data
DOI: 10.57745/bh84zt
title: 16S-ITS-23S-DB_GTDB_08-RS214.tar.gz

description: clean sequences 16S-ITS-23S from GTDB v214
DOI: 10.5066/p9z3raph
title: Basin Centroid Points for Unregulated Streamgagages in and near West Virginia 1930-2011

description: These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Correlation of flows at pairs of streamgages were evaluated using a Spearman’s rho correlation coefficient to better identify gages that can be used as index gages to estimate daily flow at ungaged stream sites in West Virginia. Correlation maps were developed for each candidate index streamgage using ordinary kriging, and have been compiled as grids. Sets of grids were developed for correlation of daily flows of streamgages on unregulated streams in [...]
DOI: 10.6084/m9.figshare.24212823
title: Religious Leader RA Burnout and Spirituality Dataset

description: Data from research paper on study of burnout in religious leaders at a Christian University, focusing on the role personal accomplishment plays when paired with Awareness of God in the burnout sequence based on data from Resident Assistants.
DOI: 10.6084/m9.figshare.24212823.v1
title: Religious Leader RA Burnout and Spirituality Dataset

description: Data from research paper on study of burnout in religious leaders at a Christian University, focusing on the role personal accomplishment plays when paired with Awareness of God in the burnout sequence based on data from Resident Assistants.
DOI: 10.25794/reference/hkujddj0
title: Xac-JS584
DOI: 10.6084/m9.figshare.24212632.v2
title: Supplementary tables from Phylogeographical evidence for historical long-distance dispersal in the flightless stick insect <i>Ramulus mikado</i>

description: Supplementary tables of “Phylogeographical evidence for historical long-distance dispersal in the flightless stick insect Ramulus mikado”
DOI: 10.5519/qd.zs248n8q
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (28 records)
DOI: 10.5066/p91cg57q
title: Hydrologic Data Sites for Juab County, Utah

description: This map shows the USGS (United States Geologic Survey), NWIS (National Water Inventory System) Hydrologic Data Sites for Juab County, Utah. The scope and purpose of NWIS is defined on the web site: http://water.usgs.gov/public/pubs/FS/FS-027-98/
DOI: 10.25612/837.avlk1gm04gz6
title: Trust for Public Land Parks 2023 City Park Facts

description: Table compiling Trust for Public Land data on park inventories (investment, acreage, amenities) across the 100 most populous cities in the United States.
DOI: 10.5066/p9c7yz9t
title: DS-777 Annual Model-Forecasted Land-Use/Land-Cover Rasters from 2009 to 2050 for the A2 Climate Scenario for the High Plains Aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming

description: These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Estimates of area and aerial extent of land-use categories are an essential component for computing the water budget of the High Plains aquifer. These raster land-use land class data represent yearly simulated future land use for the High Plains from 2009 to 2050 These data were developed using the FOREcasting SCEnarios (FORE-SCE) of future land cover model (Sohl and others, 2007; Sohl and Sayler 2008) for two (A2 and B2) of the four Intergovernmental [...]
DOI: 10.5066/p9ib9w68
title: Specific Water Quality Sites for Uintah County, Utah

description: This map shows specific water-quality items and hydrologic data site information which come from QWDATA (Water Quality) and GWSI (Ground Water Information System). Both QWDATA and GWSI are subsystems of NWIS (National Water Inventory System)of the USGS (United States Geologic Survey). This map is for Uintah County, Utah. The scope and purpose of NWIS is defined on the web site: http://water.usgs.gov/public/pubs/FS/FS-027-98/
DOI: 10.25794/reference/kdmkk7ib
title: Xac-JW160
DOI: 10.5066/p9lejvhx
title: Klamath Basin Restoration Agreement Off-Project Water Program Total Evapotranspiration Map for April to October 2006

description: These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Hydrological Information Products for the Off-Project Water Program of the Klamath Basin Restoration Agreement U.S. Geological Survey Open-File Report 2012-1199 U.S. Department of the Interior By Daniel T. Snyder, John C. Risley, and Jonathan V. Haynes Prepared in cooperation with The Klamath Tribes Access complete report at: https://pubs.usgs.gov/of/2012/1199 Suggested citation: Snyder, D.T., Risley, J.C., and Haynes, J.V., 2012, Hydrological information [...]
DOI: 10.5066/p9zweemb
title: Hydrologic Data Sites for Millard County, Utah

description: This map shows the USGS (United States Geologic Survey), NWIS (National Water Inventory System) Hydrologic Data Sites for Millard County, Utah. The scope and purpose of NWIS is defined on the web site: http://water.usgs.gov/public/pubs/FS/FS-027-98/