cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26636448.v1
title: Additional file 15 of Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway

description: Additional file 15. Subset analysis, by time between chemotherapy start date and sample taken, of the association between chemotherapy and DNA methylation in 525,100 CpG probes in 1,808 breast cancer patients with blood specimens (1,066 treated and 742 not treated with chemotherapy) and 337 breast cancer patients with saliva specimens (207 treated and 130 not treated with chemotherapy). Presented here are associations that reached statistical significance at a Bonferroni threshold p-value (p&lt;9.52e-8) with adjustments for batch, immune cell content (LUMP), cell types (only for blood), year of breast cancer diagnosis, and ethnicity. Standard error = stdev.unscaled * s2.post.
DOI: 10.6084/m9.figshare.26634900.v1
title: Additional file 7 of Transcriptome analysis of the Bactrian camel (Camelus bactrianus) reveals candidate genes affecting milk production traits

description: Additional file 7: Supplementary Table 2. Analysis of reads quality detection.
DOI: 10.6084/m9.figshare.26636130
title: Additional file 1 of Functional responses to deforestation in fish communities inhabiting neotropical streams and rivers

description: Additional file 1: Table S1. Site information with geographical locations, basin and ecosystem membership, the number of detected taxa for each site, sampling date, deforestation percentages and abiotic variables measured at each site.
DOI: 10.26093/cds/vizier.74521523
title: New young stellar cluster towards IRAS 04186+5143

description: VizieR online Data Catalogue associated with article published in journal Monthly Notices of the Royal Astronomical Society with title ' Not a galaxy: IRAS 04186+5143, a new young stellar cluster in the outer Galaxy.' (bibcode: 2015MNRAS.452.1523Y)
DOI: 10.6084/m9.figshare.26634912
title: Additional file 11 of Transcriptome analysis of the Bactrian camel (Camelus bactrianus) reveals candidate genes affecting milk production traits

description: Additional file 11: Supplementary Table 6. Animal QTL database milk traits related to genes.
DOI: 10.6084/m9.figshare.26634918.v1
title: Additional file 13 of Transcriptome analysis of the Bactrian camel (Camelus bactrianus) reveals candidate genes affecting milk production traits

description: Additional file 13: Supplementary Table 8. Functional enrichment analysis (WDL vs WGH).
DOI: 10.3886/e242872
title: Military Health System (MHS) - Vision and Eye Health Surveillance System (VEHSS)

description: The Department of Defense Health Agencys (DHA) Vision Center of Excellence (VCE) analyzed data from the MHS MART database on behalf of the VEHSS project. MHS MART is a data management and reporting system used to support decision-making, health care analysis, and operational reporting. MART integrates various sources within MHS to provide a centralized repository for health care data, facilitating access to information that aids in managing health care services, resources, and performance across MHS.

Data are based on claims and encounter records in the MHS Management Analysis and Reporting Tool (MART) database. The population includes all active-duty and retired military members and their dependents in the MHS. The sample size is approximately 9.08 million persons.

These data are also available in the VEHSS Data Explorer, an interactive data visualization tool reporting prevalence information from more than 10 data sources: https://www.cdc.gov/vision-health-data/index.html
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description: (Downloaded 1/8/2026)
DOI: 10.3886/e242872v1
title: Military Health System (MHS) - Vision and Eye Health Surveillance System (VEHSS)

description: The Department of Defense Health Agencys (DHA) Vision Center of Excellence (VCE) analyzed data from the MHS MART database on behalf of the VEHSS project. MHS MART is a data management and reporting system used to support decision-making, health care analysis, and operational reporting. MART integrates various sources within MHS to provide a centralized repository for health care data, facilitating access to information that aids in managing health care services, resources, and performance across MHS.

Data are based on claims and encounter records in the MHS Management Analysis and Reporting Tool (MART) database. The population includes all active-duty and retired military members and their dependents in the MHS. The sample size is approximately 9.08 million persons.

These data are also available in the VEHSS Data Explorer, an interactive data visualization tool reporting prevalence information from more than 10 data sources: https://www.cdc.gov/vision-health-data/index.html
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description: (Downloaded 1/8/2026)
DOI: 10.15156/bio/sh0196466.10fu
title: SH0196466.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0196467.10fu
title: SH0196467.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0196468.10fu
title: SH0196468.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.g28jsn
title: Occurrence Download

description: A dataset containing 20641 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Capsicum annuum L."
 ]
}

 The dataset includes 20641 records from 422 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001826-250212154643175/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11160803
title: Quantitatively distinguishing the factors driving runoff and sediment yield variations in karst watersheds

description: Due to the coupled or interconnected relationships among frequent climate extremes, unique geological conditions, discontinuous soil distribution, rugged geomorphology, and highly heterogeneous landscapes in different karst watersheds, few studies were conducted to decouple the relative magnitudes of the of climate, lithology, soil, topography, and landscape on soil erosion in karst regions. The objective of this study was to quantify the relative importance of these influencing factors on runoff and sediment yield in 40 typical karst watersheds in southwest China. To address this issue, the Pearson correlation and random forest were firstly to select the dominant factors influencing runoff and sediment yield. Subsequently, the partial least squares-structural equation model (PLS-SEM) was used to decouple the complex relationships among runoff, sediment yield and their potential influencing factors. Results showed that climate, lithology, soil, topography and landscape could explain 79% of the runoff variation, and only climate factors have significant impact on runoff for heterogeneous karst watersheds (P<0.01, path coefficient (β)=0.589). The explanation of five factors to sediment yield variability is 59%, and the landscape has the greatest impact on sediment yield (P<0.01, β=-0.458). Different from runoff, climatic factors have no significant influence on sediment yield. By elucidating a complex coupled relationship framework, this study can provide a scientific basis for the formulation of soil and water loss program, and the optimization of land resources and ecological environment sustainable development in karst watersheds.
DOI: 10.15468/dl.8hqm3b
title: Occurrence Download

description: A dataset containing 107 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Buccinum striatissimum G.B.Sowerby Iii, 1899",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 107 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001828-250212154643175/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b7uzg5
title: Occurrence Download

description: A dataset containing 203107 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Globularia L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 }
 ]
}

 The dataset includes 203107 records from 887 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001813-250212154643175/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11160802
title: Quantitatively distinguishing the factors driving runoff and sediment yield variations in karst watersheds: relevant data.

description: Due to the coupled or interconnected relationships among frequent climate extremes, unique geological conditions, discontinuous soil distribution, rugged geomorphology, and highly heterogeneous landscapes in different karst watersheds, few studies were conducted to decouple the relative magnitudes of the of climate, lithology, soil, topography, and landscape on soil erosion in karst regions. The objective of this study was to quantify the relative importance of these influencing factors on runoff and sediment yield in 40 typical karst watersheds in southwest China. To address this issue, the Pearson correlation and random forest were firstly to select the dominant factors influencing runoff and sediment yield. Subsequently, the partial least squares-structural equation model (PLS-SEM) was used to decouple the complex relationships among runoff, sediment yield and their potential influencing factors. Results showed that climate, lithology, soil, topography and landscape could explain 79% of the runoff variation, and only climate factors have significant impact on runoff for heterogeneous karst watersheds (P<0.01, path coefficient (β)=0.589). The explanation of five factors to sediment yield variability is 59%, and the landscape has the greatest impact on sediment yield (P<0.01, β=-0.458). Different from runoff, climatic factors have no significant influence on sediment yield. By elucidating a complex coupled relationship framework, this study can provide a scientific basis for the formulation of soil and water loss program, and the optimization of land resources and ecological environment sustainable development in karst watersheds.
DOI: 10.5281/zenodo.11203168
title: Quantitatively distinguishing the factors driving runoff and sediment yield variations in karst watersheds: relevant data.

description: Due to the coupled or interconnected relationships among frequent climate extremes, unique geological conditions, discontinuous soil distribution, rugged geomorphology, and highly heterogeneous landscapes in different karst watersheds, few studies were conducted to decouple the relative magnitudes of the of climate, lithology, soil, topography, and landscape on soil erosion in karst regions. The objective of this study was to quantify the relative importance of these influencing factors on runoff and sediment yield in 40 typical karst watersheds in southwest China. To address this issue, the Pearson correlation and random forest were firstly to select the dominant factors influencing runoff and sediment yield. Subsequently, the partial least squares-structural equation model (PLS-SEM) was used to decouple the complex relationships among runoff, sediment yield and their potential influencing factors. Results showed that climate, lithology, soil, topography and landscape could explain 79% of the runoff variation, and only climate factors have significant impact on runoff for heterogeneous karst watersheds (P<0.01, path coefficient (β)=0.589). The explanation of five factors to sediment yield variability is 59%, and the landscape has the greatest impact on sediment yield (P<0.01, β=-0.458). Different from runoff, climatic factors have no significant influence on sediment yield. By elucidating a complex coupled relationship framework, this study can provide a scientific basis for the formulation of soil and water loss program, and the optimization of land resources and ecological environment sustainable development in karst watersheds.
DOI: 10.15468/dl.b3w5gn
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Solanum stenotomum Juz. & Bukasov"
 ]
}

 The dataset includes 23 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001829-250212154643175/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/10740663
title: Full TMDB Movies Dataset 2024 (1M Movies)
DOI: 10.15468/dl.cptqbc
title: Occurrence Download

description: A dataset containing 185292 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "TaxonKey is Mammalia",
 "Year 2020-2025"
 ]
}

 The dataset includes 185292 records from 114 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001822-250212154643175/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14864858
title: Sediment connectivity in different karst watersheds

description: As a key parameter reflecting the hydrological and soil erosion processes, sediment connectivity is influenced by climate, lithology, soil, topography, and landscape. However, there are few studies on decoupling these factors on sediment connectivity. Therefore, the objective this study was to quantify the relative importance of driving factors on sediment connectivity by partial least squares-structural equation model in 40 karst watersheds. Results showed that the connectivity index (IC) ranged from -0.46 to 1.73 for different watersheds. The 92% of the IC variation can be explained by climate, lithology, soil, topography and landscape. Topographic have the most significant positive influence on IC (P < 0.01, path coefficient (β) = 0.708), while landscape had a significant negative effect on IC (P < 0.05, β= -0.249). By clarifying the coupling relationship framework among the variables, the results provide valuable information for formulating soil and water conservation strategies in karst watersheds.
DOI: 10.5281/zenodo.14864859
title: Sediment connectivity in different karst watersheds

description: As a key parameter reflecting the hydrological and soil erosion processes, sediment connectivity is influenced by climate, lithology, soil, topography, and landscape. However, there are few studies on decoupling these factors on sediment connectivity. Therefore, the objective this study was to quantify the relative importance of driving factors on sediment connectivity by partial least squares-structural equation model in 40 karst watersheds. Results showed that the connectivity index (IC) ranged from -0.46 to 1.73 for different watersheds. The 92% of the IC variation can be explained by climate, lithology, soil, topography and landscape. Topographic have the most significant positive influence on IC (P < 0.01, path coefficient (β) = 0.708), while landscape had a significant negative effect on IC (P < 0.05, β= -0.249). By clarifying the coupling relationship framework among the variables, the results provide valuable information for formulating soil and water conservation strategies in karst watersheds.
DOI: 10.6084/m9.figshare.28408484
title: Encuestas de motivación y utilidad para el aprendizaje basado en retos reales. Tabla 5 - Comparación del estadístico X2 de Pearson en la encuesta para profesores de los centros educativos

description: Comparación del estadístico X2 de Pearson de la encuesta para el profesorado universitario vinculada al estudio "Implementación del aprendizaje basado en retos reales en la docéncia universitária" - "Encuestas de motivación y utilidad para el aprendizaje basado en retos reales"El objetivo del estudio fue crear, validar y demostrar la fiabilidad de encuestas que valorasen la motivación, la percepción del aprendizaje y de la utilidad de la metodología del aprendizaje basado en retos reales (ABRR) tras su la aplicación en el grado universitario de Ciencias de la Actividad Física y el Deporte. Los retos reales los propusieron centros educativos y fueron resueltos e implementados por estudiantes universitarios. La validación la realizaron doce expertos y para establecer su fiabilidad se realizaron test-retests a los estudiantes universitarios y al profesorado de los centros educativos aplicando la comparación estadística χ2 de Pearson por preguntas y temas. Los resultados de la validación fueron tres encuestas: para los estudiantes universitarios (18 preguntas), para el profesorado de escuelas e institutos (28 preguntas) y para su alumnado (16 preguntas). Todas fueron conformadas por preguntas tipo likert y abiertas. Los resultados del χ2 mostraron buena fiabilidad (p ≥ 0,05). El estudio demostró su validez con relación al contenido y estructura, así como buena fiabilidad para analizar la motivación, la percepción del aprendizaje y la utilidad del ABRR desde la perspectiva de los estudiantes universitarios, los docentes de los centros educativos y su alumnado. Puesto que mostraron rigurosidad suficiente, permitían obtener datos de los diferentes agentes implicados en el proceso y la posibilidad utilizarlas para analizar otras materias en que se aplicara esta metodología u otras metodologías activas.
DOI: 10.6084/m9.figshare.28408484.v1
title: Encuestas de motivación y utilidad para el aprendizaje basado en retos reales. Tabla 5 - Comparación del estadístico X2 de Pearson en la encuesta para profesores de los centros educativos

description: Comparación del estadístico X2 de Pearson de la encuesta para el profesorado universitario vinculada al estudio "Implementación del aprendizaje basado en retos reales en la docéncia universitária" - "Encuestas de motivación y utilidad para el aprendizaje basado en retos reales"El objetivo del estudio fue crear, validar y demostrar la fiabilidad de encuestas que valorasen la motivación, la percepción del aprendizaje y de la utilidad de la metodología del aprendizaje basado en retos reales (ABRR) tras su la aplicación en el grado universitario de Ciencias de la Actividad Física y el Deporte. Los retos reales los propusieron centros educativos y fueron resueltos e implementados por estudiantes universitarios. La validación la realizaron doce expertos y para establecer su fiabilidad se realizaron test-retests a los estudiantes universitarios y al profesorado de los centros educativos aplicando la comparación estadística χ2 de Pearson por preguntas y temas. Los resultados de la validación fueron tres encuestas: para los estudiantes universitarios (18 preguntas), para el profesorado de escuelas e institutos (28 preguntas) y para su alumnado (16 preguntas). Todas fueron conformadas por preguntas tipo likert y abiertas. Los resultados del χ2 mostraron buena fiabilidad (p ≥ 0,05). El estudio demostró su validez con relación al contenido y estructura, así como buena fiabilidad para analizar la motivación, la percepción del aprendizaje y la utilidad del ABRR desde la perspectiva de los estudiantes universitarios, los docentes de los centros educativos y su alumnado. Puesto que mostraron rigurosidad suficiente, permitían obtener datos de los diferentes agentes implicados en el proceso y la posibilidad utilizarlas para analizar otras materias en que se aplicara esta metodología u otras metodologías activas.
DOI: 10.15468/dl.seeaz2
title: Occurrence Download

description: A dataset containing 275 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Fratercula cirrhata (Pallas, 1769)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 275 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001830-250212154643175/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bf996v
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Alca cirrhata Pallas, 1769",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001831-250212154643175/datasets/export for details.
DOI: 10.5281/zenodo.14860368
title: Consumer-Grade EEG and Eye-Tracking Dataset

description: Dataset containing EEG and eye-tracking data of 113 participants, recorded with consumer-grade hardware.