cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31229329
title: Prevalence of schistosome infection in a region of Madagascar regularly undergoing mass drug administration: a cross-sectional study

description: Schistosomiasis is a parasitic disease primarily controlled by Praziquantel-based Mass Drug Administration (MDA) targeting school-aged children. This study aimed to generate a high-resolution schistosomiasis prevalence map in a region with regular MDA in Madagascar, identify at-risk groups, assess population knowledge, and explore risk factors to support alignment with WHO guidelines. Conducted between July and October 2022 in the District of Vatomandry, Madagascar, this cross-sectional study included participants aged five and older. Point-of-Care Circulating Cathodic Antigen testing determined infection prevalence. A choropleth map was generated to show the geographical distribution of schistosome infection across local communities. Individual risk factors were assessed using hierarchical Poisson regression. The study included 1,215 households (5,200 participants) from 42 communities revealing a high overall prevalence of 59%. Adjusted prevalence ratios (PR) indicated higher infection risks for farmers (PR = 1.17, 95% CI: 1.09–1.25) and older age groups (≥38 years: PR = 1.34, 95% CI: 1.16–1.55; against ≤15 years), while participants with higher education or knowledge about schistosome transmission showed a reduced risk (PR = 0.88, 95% CI: 0.78–0.99). The results show high schistosome prevalence in adults, emphasizing the need to adapt strategies in endemic countries to meet the WHO’s 2030 goal of eliminating schistosomiasis as public health problem.
DOI: 10.6084/m9.figshare.31229329.v1
title: Prevalence of schistosome infection in a region of Madagascar regularly undergoing mass drug administration: a cross-sectional study

description: Schistosomiasis is a parasitic disease primarily controlled by Praziquantel-based Mass Drug Administration (MDA) targeting school-aged children. This study aimed to generate a high-resolution schistosomiasis prevalence map in a region with regular MDA in Madagascar, identify at-risk groups, assess population knowledge, and explore risk factors to support alignment with WHO guidelines. Conducted between July and October 2022 in the District of Vatomandry, Madagascar, this cross-sectional study included participants aged five and older. Point-of-Care Circulating Cathodic Antigen testing determined infection prevalence. A choropleth map was generated to show the geographical distribution of schistosome infection across local communities. Individual risk factors were assessed using hierarchical Poisson regression. The study included 1,215 households (5,200 participants) from 42 communities revealing a high overall prevalence of 59%. Adjusted prevalence ratios (PR) indicated higher infection risks for farmers (PR = 1.17, 95% CI: 1.09–1.25) and older age groups (≥38 years: PR = 1.34, 95% CI: 1.16–1.55; against ≤15 years), while participants with higher education or knowledge about schistosome transmission showed a reduced risk (PR = 0.88, 95% CI: 0.78–0.99). The results show high schistosome prevalence in adults, emphasizing the need to adapt strategies in endemic countries to meet the WHO’s 2030 goal of eliminating schistosomiasis as public health problem.
DOI: 10.15468/dl.xx2gaw
title: Occurrence Download

description: A dataset containing 75634 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((12.569725 0.256058, 14.186564 0.256058, 14.186564 1.789562, 12.569725 1.789562, 12.569725 0.256058))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation, Specimen)"
 ]
}

 The dataset includes 75634 records from 119 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006725-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31229331
title: Reliability analysis of a dynamic system under power trend conditionally proportional hazard model with general family of inverted exponentiated distributions

description: Reliability studies in several engineering domains have recently made extensive use of the general family of inverted exponentiated distributions. Using this family as a baseline model, in this work, we have obtained a number of statistical inferences on the power-trend mechanism-based composite dynamic system. In particular, the maximum likelihood estimates of the unknown parameters and baseline reliability function are computed. The asymptotic and bootstrapped confidence intervals of the baseline reliability function are proposed. A parametric hypothesis test is provided to ascertain, whenever the failed components change the hazard rate function. The Bayes estimates of the unknown model parameters and baseline reliability functions with respect to the squared error and generalized entropy loss functions are obtained. Further, the Metropolis–Hastings algorithm is used to generate Markov chain Monte Carlo samples for the computation of the Bayes estimates. The highest posterior density credible interval of the baseline reliability function is also calculated. For illustration reasons, two real data sets are considered and then analysed. Finally, a simulation study is carried out to examine the behaviour of the proposed estimates.
DOI: 10.6084/m9.figshare.31229331.v1
title: Reliability analysis of a dynamic system under power trend conditionally proportional hazard model with general family of inverted exponentiated distributions

description: Reliability studies in several engineering domains have recently made extensive use of the general family of inverted exponentiated distributions. Using this family as a baseline model, in this work, we have obtained a number of statistical inferences on the power-trend mechanism-based composite dynamic system. In particular, the maximum likelihood estimates of the unknown parameters and baseline reliability function are computed. The asymptotic and bootstrapped confidence intervals of the baseline reliability function are proposed. A parametric hypothesis test is provided to ascertain, whenever the failed components change the hazard rate function. The Bayes estimates of the unknown model parameters and baseline reliability functions with respect to the squared error and generalized entropy loss functions are obtained. Further, the Metropolis–Hastings algorithm is used to generate Markov chain Monte Carlo samples for the computation of the Bayes estimates. The highest posterior density credible interval of the baseline reliability function is also calculated. For illustration reasons, two real data sets are considered and then analysed. Finally, a simulation study is carried out to examine the behaviour of the proposed estimates.
DOI: 10.17026/dans-xmt-3zqp
title: Schoolverlatersonderzoek 2016 - SVO 2016

description: &lt;p&gt;Dit bestand is gebaseerd op het Schoolverlatersonderzoek (SVO), kenmerken van schoolverlaters die hun vo- of mbo-diploma hebben behaald of die het onderwijs voortijdig hebben verlaten.&lt;br&gt;Het Schoolverlatersonderzoek (SVO) heeft als doel inzicht te krijgen in de aansluiting van school naar werk of naar vervolgopleiding. CBS doet dit onderzoek in opdracht van het Ministerie van Onderwijs, Cultuur en Wetenschappen (OCW) en werkt daarbij samen met het Researchcentrum voor Onderwijs en Arbeidsmarkt (ROA). Een van de achterliggende redenen voor de uitvoering van dit onderzoek is de wet macrodoelmatigheid mbo. Om het effect van deze wet te kunnen monitoren wil het ministerie van OCW kunnen beschikken over de aansluiting tussen de gevolgde opleiding en de functie die wordt uitgeoefend.&lt;/p&gt;&lt;p&gt;Deze documentatie geeft een beschrijving van de variabelen die zijn opgenomen in dit microdata bestand dat via DANS beschikbaar is gesteld.&lt;br&gt;Dit DANS-Easy SVO 2017 bestand wijkt af van het microdata bestand SVO 2017 dat onder bepaalde voorwaarden voor statistisch en wetenschappelijk onderzoek toegankelijk. Voor nadere informatie microdata@cbs.nl.&lt;/p&gt;
description: CBS provided the .sav version of the data files. DANS provided the .dat, .sps, .dta and .por conversions.
DOI: 10.5281/zenodo.18350398
title: Transnational survey data on European farmers and consumers attitudes towards legumes adoption

description: This dataset contains responses from a consumers’ and farmers’ online survey about legume adoption in Germany, Greece, Italy, The Netherlands, Portugal, Serbia and Spain. Both surveys aimed to explore the enablers and barriers to adopt legumes, as well as the participant’s knowledge about the Ecosystem Services provided by these crops. The dataset includes responses from 600 consumers and 469 farmers, obtained between June and October 2025. In addition to respondents attitudes towards their current and future adoption of legumes in their diets or farms, the dataset contains socio-demographic data and information about the participant’s opinion on the Cultural Ecosystem Services provided by legumes. The variables allows the data to be used for several multivariate analysis about consumers’ and farmers’ current preferences towards legume crops in seven European countries.
DOI: 10.5281/zenodo.18350399
title: Transnational survey data on European farmers and consumers attitudes towards legumes adoption

description: This dataset contains responses from a consumers’ and farmers’ online survey about legume adoption in Germany, Greece, Italy, The Netherlands, Portugal, Serbia and Spain. Both surveys aimed to explore the enablers and barriers to adopt legumes, as well as the participant’s knowledge about the Ecosystem Services provided by these crops. The dataset includes responses from 600 consumers and 469 farmers, obtained between June and October 2025. In addition to respondents attitudes towards their current and future adoption of legumes in their diets or farms, the dataset contains socio-demographic data and information about the participant’s opinion on the Cultural Ecosystem Services provided by legumes. The variables allows the data to be used for several multivariate analysis about consumers’ and farmers’ current preferences towards legume crops in seven European countries.
DOI: 10.15468/dl.s7qs9r
title: Occurrence Download

description: A dataset containing 498763 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Global soil microbiomes: A new frontline of biome-ecology research"
 ]
}

 The dataset includes 498763 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006795-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17286566
title: Dataset for Biomass-derived Diformylxylose as a Renewable Solvent for Biocatalysis Applications

description: The Zenodo repository contains the complete CSV datasets underlying all main-text and Supporting Information figures and tables of the manuscript, including raw and processed GC/LC peak data, calibration data, and calculated conversions (with means and standard deviations) for a broad set of biocatalytic reactions across enzymes, substrates, solvent systems, temperatures, and concentrations. Data cover substrate scope studies, solvent and substrate-load effects, time courses, comparative enzyme performance, and additional enzyme classes (ADHs, KREDs, IREDs, transaminases, and CalB), alongside molecular dynamics–derived structural metrics and energy calculations. Conversions were calculated using substrate depletion or response-factor–corrected product/substrate quantification based on external calibrations, with all experiments performed in at least duplicate (often triplicate), and raw GC/LC calibration files are provided to ensure full transparency and reproducibility.
DOI: 10.5281/zenodo.17286567
title: Dataset for Biomass-derived Diformylxylose as a Renewable Solvent for Biocatalysis Applications

description: The Zenodo repository contains the complete CSV datasets underlying all main-text and Supporting Information figures and tables of the manuscript, including raw and processed GC/LC peak data, calibration data, and calculated conversions (with means and standard deviations) for a broad set of biocatalytic reactions across enzymes, substrates, solvent systems, temperatures, and concentrations. Data cover substrate scope studies, solvent and substrate-load effects, time courses, comparative enzyme performance, and additional enzyme classes (ADHs, KREDs, IREDs, transaminases, and CalB), alongside molecular dynamics–derived structural metrics and energy calculations. Conversions were calculated using substrate depletion or response-factor–corrected product/substrate quantification based on external calibrations, with all experiments performed in at least duplicate (often triplicate), and raw GC/LC calibration files are provided to ensure full transparency and reproducibility.
DOI: 10.15468/dl.wkqrcw
title: Occurrence Download

description: A dataset containing 159 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Epimedium pubescens"
 ]
}

 The dataset includes 159 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006800-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18455854
title: StopUP. WP1. Pollution risk characterization. Task1.4. Monitoring concepts and data acquisition for and from case studies: catchment characterization

description: The dataset includes information obtained by the monitoring of case studies of the project StoUP. The dataset includes data concerning catchment characteristics of the urban area as drainage capacity of the soil and land use (roads, roofs, gardens, industry, etc.): the land use and land type characterization is obtained by exploiting aerial pictures, satellite images and LIDAR information, aimed to derive classification criteria (e.g. impact categories related to land use with low, medium and high intensity).
DOI: 10.5281/zenodo.18455855
title: StopUP. WP1. Pollution risk characterization. Task1.4. Monitoring concepts and data acquisition for and from case studies: catchment characterization

description: The dataset includes information obtained by the monitoring of case studies of the project StoUP. The dataset includes data concerning catchment characteristics of the urban area as drainage capacity of the soil and land use (roads, roofs, gardens, industry, etc.): the land use and land type characterization is obtained by exploiting aerial pictures, satellite images and LIDAR information, aimed to derive classification criteria (e.g. impact categories related to land use with low, medium and high intensity).
DOI: 10.5281/zenodo.18455856
title: pollimyrus_nigripinnis_spades_01.fasta.gz
DOI: 10.5281/zenodo.18455857
title: pollimyrus_nigripinnis_spades_01.fasta.gz
DOI: 10.3886/e244706
title: Model Inputs: Midwest Climate Change Vulnerability Assessment for the U.S. Fish and Wildlife Service

description: 'This data release contains the climate change model inputs and Soil and Water Assessment Tool (SWAT) model outputs from 360 HUC-8 watersheds in the Midwest United States (Illinois, Indiana, Iowa, Michigan, Minnesota, Ohio, and Wisconsin), that were generated using the HAWQS (Hydrologic and Water Quality System) platform (https://hawqs.tamu.edu). The summarized data for a watershed-based climate change vulnerability assessment for U.S. Fish and Wildlife Service is also provided, along with the R code used to summarize the raw outputs. Watershed-based Midwest Climate Change Vulnerability Assessment Tool: https://rconnect.usgs.gov/CC_Vulnerabi [sic]. Related External Resource: https://rconnect.usgs.gov/CC_Vulnerability/ (Watershed-based Midwest Climate Change Vulnerability Assessment Tool ).‘
description: (Downloaded 2026-01-26)
DOI: 10.3886/e244706v1
title: Model Inputs: Midwest Climate Change Vulnerability Assessment for the U.S. Fish and Wildlife Service

description: 'This data release contains the climate change model inputs and Soil and Water Assessment Tool (SWAT) model outputs from 360 HUC-8 watersheds in the Midwest United States (Illinois, Indiana, Iowa, Michigan, Minnesota, Ohio, and Wisconsin), that were generated using the HAWQS (Hydrologic and Water Quality System) platform (https://hawqs.tamu.edu). The summarized data for a watershed-based climate change vulnerability assessment for U.S. Fish and Wildlife Service is also provided, along with the R code used to summarize the raw outputs. Watershed-based Midwest Climate Change Vulnerability Assessment Tool: https://rconnect.usgs.gov/CC_Vulnerabi [sic]. Related External Resource: https://rconnect.usgs.gov/CC_Vulnerability/ (Watershed-based Midwest Climate Change Vulnerability Assessment Tool ).‘
description: (Downloaded 2026-01-26)
DOI: 10.5281/zenodo.18456048
title: Results of 2DCA methods on synthetic data

description: barberpole_data.npz containes the results of velocity estimation methods (2DCA, 2DCC, with contouring, maxtracking and three-point time-delay estimation) on synthetic data generated by the blobmodel python package. 

plot_barberpole_data_from_file.py is a simple Python file that reads the barberpole_data.npz results and makes a plot similar to the one of our manuscript.

synthetic_blob_2dca.nc xarray dataset containing the underlying synthetic data of Fig. 3 in our manuscript.
DOI: 10.5281/zenodo.18456047
title: Results of 2DCA methods on synthetic data

description: barberpole_data.npz containes the results of velocity estimation methods (2DCA, 2DCC, with contouring, maxtracking and three-point time-delay estimation) on synthetic data generated by the blobmodel python package. 

plot_barberpole_data_from_file.py is a simple Python file that reads the barberpole_data.npz results and makes a plot similar to the one of our manuscript.

synthetic_blob_2dca.nc xarray dataset containing the underlying synthetic data of Fig. 3 in our manuscript.
DOI: 10.5281/zenodo.18455917
title: lavatera_stenopetala_spades_01.fasta.gz
DOI: 10.5281/zenodo.18455918
title: lavatera_stenopetala_spades_01.fasta.gz
DOI: 10.57932/9d344c70-2f09-4fff-a2d9-ce72f5cf1757
title: Air temperature, humidity and pressure measured over coastal Namibia from 2018 to 2019

description: Surface observations are conducted at the Henties Bay Aerosol Observatory (HBAO; http://www.hbao.cnrs.fr/), a recent regional station in the Global Atmosphere Watch (GAW) programme of the World Meteorological Organization (WMO). The research centre is located on the Sam Nujoma Marine and Coastal Resources Research Centre (SANUMARC) of the University of Namibia in Henties Bay (22∘ S, 14∘05′ E), Namibia (Fig. 1). Henties Bay is a small town in an arid environment with no vegetation, no industrial activity and very little traffic. Energy usage is predominantly a mix of electricity and gas, with some solid fuel combustion (wood) due to low availability. The monitoring site, situated on the university campus, is located on the coast approximately 100 m from the shoreline. To the east are the Namibian gravel plains, 3 km to the south of the campus is the town of Henties Bay and to the north is the Omaruru riverbed (river mouth approximately 100 m from SANUMARC). The population of Henties Bay ranges between 4600 and 6000 inhabitants, according to the Namibia Population and Housing Census Main Report (available at http://cms.my.na/assets/documents/p19dmn58guram30ttun89rdrp1.pdf.
A Vaisala WXT530 sensor measured the air temperature, relative humidity and pressure from January 2018. Measurements were acquired as 5-min averages. The curation of the meteorological observations was rather simple as sensors are robust and did not suffer the conditions of the site that complicated data curation for other instruments in the marine coastal environment.
DOI: 10.15468/dl.a525s2
title: Occurrence Download

description: A dataset containing 395 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rehmannia glutinosa",
 "Year 2005-2026"
 ]
}

 The dataset includes 395 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006806-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jbejvr
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((43.29329 -24.41169,51.76322 -24.41169,51.76322 -18.47241,43.29329 -18.47241,43.29329 -24.41169))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Salix madagascariensis"
 ]
}

 The dataset includes 9 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006805-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18422600
title: IoMB: Isle of May Birds
DOI: 10.5281/zenodo.18422599
title: IoMB: Isle of May Birds
DOI: 10.6084/m9.figshare.31220881
title: Metabolic profile of feces from mice colonized with human gut microbiota

description: Metabolic profile of feces from mice colonized with human gut microbiota
DOI: 10.6084/m9.figshare.31220881.v1
title: Metabolic profile of feces from mice colonized with human gut microbiota

description: Metabolic profile of feces from mice colonized with human gut microbiota
DOI: 10.15468/dl.tj4jax
title: Occurrence Download

description: A dataset containing 82170 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Atlas of Amphibians and Reptiles of Portugal"
 ]
}

 The dataset includes 82170 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006801-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b8xp2w
title: Occurrence Download

description: A dataset containing 2628483 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Merluccius",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2628483 records from 265 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006781-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.