cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17716244
title: Community knowledge, attitudes, and preferences towards vitamin A supplementation in Kasai Oriental, Democratic Republic of the Congo: a mixed-methods study

description: Vitamin A deficiency remains a critical public health challenge and affects children under five years of age in the Democratic Republic of the Congo. We investigated the community-level knowledge, preferences, and attitudes towards vitamin A supplementation in the Kasaï-Oriental province. The importance of vitamin A supplementation differed among the participants, with some respondents holding health workers responsible for unclear explanations. Regarding the venue of paediatric vitamin A supplementation, the participants either favoured vitamin A supplementation in the health centres or in the households. The majority (95.5%) of respondents had relatively low knowledge scores (≤4). Knowledge was positively associated with the father’s level of education and information from community health workers (adjusted incidence rate ratio [95% confidence interval]=1.35 [1.02–1.78] and 1.56 [1.08–2.23], respectively). Community health workers played a key role in informing the community regarding vitamin A supplementation. Strengthening the competence and interactions of community health workers with community members is key factors for successful vitamin A supplementation delivery
DOI: 10.15468/dl.s9b6xc
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia binata",
 "HasCoordinate is true"
 ]
}

 The dataset includes 119 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014197-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17741982
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model EC-EARTH3, scenario ssp245 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17741983
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model EC-EARTH3, scenario ssp245 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.15468/dl.gu6xf6
title: Occurrence Download

description: A dataset containing 1390 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((2.68053 39.00533,16.73070 39.00533,16.73070 44.63033,2.68053 44.63033,2.68053 39.00533))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Mesophyllum"
 ]
}

 The dataset includes 1390 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014198-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17751689
title: D6.3 GEM-E3 Model Dataset
DOI: 10.5281/zenodo.17751688
title: D6.3 GEM-E3 Model Dataset
DOI: 10.5281/zenodo.17741991
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model EC-EARTH3, scenario ssp370 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17741992
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model EC-EARTH3, scenario ssp370 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742001
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model EC-EARTH3, scenario ssp585 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742002
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model EC-EARTH3, scenario ssp585 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.26301/j7dp-3713
title: Ramesseum

description: Digital cameras are used to capture images in full stereo surround for use in virtual reality systems. These images can cover any field of view, including 360Â° by 180Â° spherical panoramas. Two photographic cylinders are created with identical dimensions, capturing the perspective as seen from each eye position. When these cylinders are mapped to a spherical surface, full stereo in all directions is achieved. This technique allows photographic imaging to create the virtual environment itself. The complete stereo image that is created by this technique can be viewed in any direction that is supported by the virtual reality system design.
description: CAVECam #20 "LuxorThebesRamesseum"
 This CAVEcam was shot in the Ramesseum in Thebes. T See:
 http://www.calit2.net/newsroom/rss.php?id=1862
 http://en.wikipedia.org/wiki/Ramesseum
description: Photogrammetry - Terrestrial, Data Derivatives - 3D photogrammetry
DOI: 10.5281/zenodo.17742011
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario Historical -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742010
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario Historical -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.15532946
title: Replication package for paper: "Evolution of repositories and privacy laws: Commit activities in the GDPR and CCPA era"

description: Dataset on commits (and repositories) on GitHub making reference to data privacy legislation (covering laws: GDPR, CCPA, CPRA, UK DPA). The dataset contains:+ all_commits_info_merged-v2-SHA.csv : commits information as collected from various GitHub REST API calls (all data merged together).+ repos_info_merged_USED-v2_with_loc.csv: repository information with some calculated data.+ top-70-repos-commits-for-manual-check_commits-2coders.xlsx: results of the manual coding of the commits of the 70 most popular repositories in dataset.+ user-rights-ω3.csv: different terms for user rights teriminology in legislation.+ github_commits_analysis_replication.r: main analysis pipeline covering all RQs in the R programming language.

In order to perform also the initial data collection, the GitHub REST API can be used, collecting data using time intervals, for instance:https://api.github.com/search/commits?q=%22GDPR%22+committer-date:2018-05-25..2018-05-30&sort=committer-date&order=asc&per_page=100&page=1

This dataset accompanies the following publication, so please cite it accordingly:

Georgia M. Kapitsaki, Maria Papoutsoglou, Evolution of repositories and privacy laws: commit activities in the GDPR and CCPA era, accepted for publication at Elsevier Journal of Systems & Software, 2025.
DOI: 10.5281/zenodo.15532947
title: Replication package for paper: "Evolution of repositories and privacy laws: Commit activities in the GDPR and CCPA era"

description: Dataset on commits (and repositories) on GitHub making reference to data privacy legislation (covering laws: GDPR, CCPA, CPRA, UK DPA). The dataset contains:+ all_commits_info_merged-v2-SHA.csv : commits information as collected from various GitHub REST API calls (all data merged together).+ repos_info_merged_USED-v2_with_loc.csv: repository information with some calculated data.+ top-70-repos-commits-for-manual-check_commits-2coders.xlsx: results of the manual coding of the commits of the 70 most popular repositories in dataset.+ user-rights-ω3.csv: different terms for user rights teriminology in legislation.+ github_commits_analysis_replication.r: main analysis pipeline covering all RQs in the R programming language.

In order to perform also the initial data collection, the GitHub REST API can be used, collecting data using time intervals, for instance:https://api.github.com/search/commits?q=%22GDPR%22+committer-date:2018-05-25..2018-05-30&sort=committer-date&order=asc&per_page=100&page=1

This dataset accompanies the following publication, so please cite it accordingly:

Georgia M. Kapitsaki, Maria Papoutsoglou, Evolution of repositories and privacy laws: commit activities in the GDPR and CCPA era, accepted for publication at Elsevier Journal of Systems & Software, 2025.
DOI: 10.5281/zenodo.17742023
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario ssp126 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742022
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario ssp126 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742029
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario ssp245 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742028
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario ssp245 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742038
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario ssp370 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742039
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario ssp370 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742047
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario ssp585 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742048
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, Global model MPI-ESM1-2-HR, scenario ssp585 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.15468/dl.zeeqej
title: Occurrence Download

description: A dataset containing 3056 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia brachybotrya",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3056 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014200-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17742061
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level sfc, Global model CanESM5, scenario Historical -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742060
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level sfc, Global model CanESM5, scenario Historical -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.15468/dl.b99mz5
title: Occurrence Download

description: A dataset containing 23703 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "DatasetKey is EOD – eBird Observation Dataset",
 "Month is October",
 "StateProvince is New Brunswick",
 "Year 2024-2024"
 ]
}

 The dataset includes 23703 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014201-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17742084
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level sfc, Global model CanESM5, scenario ssp126 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742085
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level sfc, Global model CanESM5, scenario ssp126 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742104
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level sfc, Global model CanESM5, scenario ssp245 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17742105
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level sfc, Global model CanESM5, scenario ssp245 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.18150/bnllfn
title: Ashwagandha: optimizing the extraction and electrospun nanofiber production

description: Dissolution.xlsx - data represent the percentage of withanoside IV released. Columns indicate the systems tested, rows the corresponding time points. Data are presented as µg. Dissolution studies of electrospun nanofibers were performed using an Agilent 708-DS dissolution apparatus. A standard basket method was used at 37 ± 0.5 °C with a stirring speed of 50 rpm. Nanofibers were placed in 300 mL of artificial saliva solution at pH 6.8 (potassium chloride (1.20 g), sodium chloride (0.85 g), di-potassium hydrogen orthophosphate (0.35 g), magnesium chloride (0.05 g), calcium chloride (0.20 g), xylitol (20.0 g) and water up to 1 L; pH was adjusted to 6.8 by 1 M HCl). The liquid samples were collected at specified time intervals, and an equal volume of temperature-equilibrated media was replaced. The samples were filtered through a 0.45 μm nylon membrane filter. The content was determined using the HPLC method (https://www.mdpi.com/1999-4923/17/1/61).
DOI: 10.5281/zenodo.17742124
title: DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level sfc, Global model CanESM5, scenario ssp370 -  The Metropolitan City of Turin (CMTo, Italy)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.