cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18744441
title: Deidentified individual-level viewing datasets (DyspnOthers study)

description: This record contains the deidentified individual-level datasets from the two studies comprised in the DyspnOthers program.The datasets correspond to two complementary population-based studies conducted using a standardised videogram stimulus set in which the same actress and actor portrayed dyspnoea, pain, six canonical emotions, and a neutral state.

 

Two Excel (.xlsx) files are provided, one for each study. Each row corresponds to a “viewing”, defined as a videogram–viewer pair (i.e., one participant’s responses to one videogram). Participants therefore contribute multiple rows. Columns include a deidentified participant identifier, stimulus identifier, descriptive variables, and rating variables.

 

No direct identifiers are included. The datasets are provided in French.

 

These data are not openly available. Access will be granted to researchers submitting a methodologically sound proposal approved by an independent review committee (“learned intermediary”). Data will be shared exclusively for the purpose of achieving the objectives outlined in the approved proposal. A data access agreement must be signed prior to release.
DOI: 10.5281/zenodo.18744440
title: Deidentified individual-level viewing datasets (DyspnOthers study)

description: This record contains the deidentified individual-level datasets from the two studies comprised in the DyspnOthers program.The datasets correspond to two complementary population-based studies conducted using a standardised videogram stimulus set in which the same actress and actor portrayed dyspnoea, pain, six canonical emotions, and a neutral state.

 

Two Excel (.xlsx) files are provided, one for each study. Each row corresponds to a “viewing”, defined as a videogram–viewer pair (i.e., one participant’s responses to one videogram). Participants therefore contribute multiple rows. Columns include a deidentified participant identifier, stimulus identifier, descriptive variables, and rating variables.

 

No direct identifiers are included. The datasets are provided in French.

 

These data are not openly available. Access will be granted to researchers submitting a methodologically sound proposal approved by an independent review committee (“learned intermediary”). Data will be shared exclusively for the purpose of achieving the objectives outlined in the approved proposal. A data access agreement must be signed prior to release.
DOI: 10.15468/dl.ysm34y
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (International Barcode of Life project (iBOL), Diversity of wood-decaying fungi in Zixishan area (Hengduan Mountains), Yunnan Province, China)",
 "TaxonKey is Peniophorella subpraetermissa"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004037-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48580/dgwqk.v3
title: Revealing new species within a species complex of Nemesia Audouin, 1826 (Araneae, Mygalomorphae) trapdoor spiders from Andalusia (Spain)
DOI: 10.5281/zenodo.18681622
title: Datasets and code (Part1) associated with "From video to behaviour: an LSTM-based approach for automated nest behaviour recognition in the wild"

description: This Zenodo record contains the first part off the materials needed to replicate the study “From video to behaviour: an LSTM-based approach for automated nest behaviour in the wild", found here https://www.biorxiv.org/content/10.1101/2025.05.27.656097v5.article-info

This archive represents Part 1 of a two-part material deposited on Zenodo, divided due to file size limitations.

This first part contains:

i) All scripts required for modelling and model evaluation, independent of bird species (present in both parts)ii) A comprehensive README file providing detailed instructions to reproduce all the modelling and analyses presented in the study (present in both parts)iii) The dataset required for automated nest activity recognition in the sociable weaver (Philetairus socius) using LSTMs

iv) The three LSTM-based models corresponding to each behavioural automation task in the the sociable weaver: nest activity, aggression and building detection.
DOI: 10.5281/zenodo.18681623
title: Datasets and code (Part1) associated with "From video to behaviour: an LSTM-based approach for automated nest behaviour recognition in the wild"

description: This Zenodo record contains the first part off the materials needed to replicate the study “From video to behaviour: an LSTM-based approach for automated nest behaviour in the wild", found here https://www.biorxiv.org/content/10.1101/2025.05.27.656097v5.article-info

This archive represents Part 1 of a two-part material deposited on Zenodo, divided due to file size limitations.

This first part contains:

i) All scripts required for modelling and model evaluation, independent of bird species (present in both parts)ii) A comprehensive README file providing detailed instructions to reproduce all the modelling and analyses presented in the study (present in both parts)iii) The dataset required for automated nest activity recognition in the sociable weaver (Philetairus socius) using LSTMs

iv) The three LSTM-based models corresponding to each behavioural automation task in the the sociable weaver: nest activity, aggression and building detection.
DOI: 10.15468/dl.qc6pvd
title: Occurrence Download

description: A dataset containing 5092 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Scutia"
 ]
}

 The dataset includes 5092 records from 126 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004038-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18745011
title: Anisotropic Biot coefficient drives failure in fractured rocks

description: Scripts associated to submitted mansuscript.
DOI: 10.5281/zenodo.18745012
title: Anisotropic Biot coefficient drives failure in fractured rocks

description: Scripts associated to submitted mansuscript.
DOI: 10.5281/zenodo.18745050
title: Improved constraints on Andean Glaciations from the Lake Titicaca continental drilling record

description: Supplementary Data to accompany the manuscript: Improved constraints on Andean Glaciations from the Lake Titicaca continental drilling record
DOI: 10.5281/zenodo.18745051
title: Improved constraints on Andean Glaciations from the Lake Titicaca continental drilling record

description: Supplementary Data to accompany the manuscript: Improved constraints on Andean Glaciations from the Lake Titicaca continental drilling record
DOI: 10.5880/fidgeo.2025.093
title: Datasets of analog modeling results for the V-shaped opening of the South China Sea: 3D DEMs and PIV results

description: This dataset compiles quantitative outputs from eight sandbox experiments conducted under different boundary conditions (differential extension, strong blocks, and a weak zone). It contains 3-D scanning–derived digital elevation models (DEMs) from the final stage of experiments simulating the V-shaped opening of the South China Sea. In addition, it includes particle image velocimetry (PIV) products at four extension states (25 mm, 50 mm, 75 mm, and 100 mm), together with the plotting codes used to generate the figures.
DOI: 10.5281/zenodo.18745086
title: THE IMPORTANCE OF STEAM EDUCATION TECHNOLOGIES IN THE DEVELOPMENT OF PRESCHOOL CHILDREN

description: This article provides a scientific analysis of the role and significance of STEAM (Science, Technology, Engineering, Arts, and Mathematics) educational technologies in the development of preschool children. Based on a literature review, research methodology, analysis, and results, the paper explores the subject in depth, highlighting the contribution of the STEAM approach to children's cognitive, socio-emotional, and physical development. The findings indicate that STEAM education provides children with opportunities to learn through hands-on experiences, increases their engagement, develops problem-solving skills, and fosters essential life skills. The article emphasizes the benefits and potential of implementing STEAM in the preschool education system and offers practical recommendations.
DOI: 10.5281/zenodo.18745087
title: THE IMPORTANCE OF STEAM EDUCATION TECHNOLOGIES IN THE DEVELOPMENT OF PRESCHOOL CHILDREN

description: This article provides a scientific analysis of the role and significance of STEAM (Science, Technology, Engineering, Arts, and Mathematics) educational technologies in the development of preschool children. Based on a literature review, research methodology, analysis, and results, the paper explores the subject in depth, highlighting the contribution of the STEAM approach to children's cognitive, socio-emotional, and physical development. The findings indicate that STEAM education provides children with opportunities to learn through hands-on experiences, increases their engagement, develops problem-solving skills, and fosters essential life skills. The article emphasizes the benefits and potential of implementing STEAM in the preschool education system and offers practical recommendations.
DOI: 10.6084/m9.figshare.31390619
title: Sample dataset

description: Dataset for prediction
DOI: 10.6084/m9.figshare.31390619.v1
title: Sample dataset

description: Dataset for prediction
DOI: 10.7910/dvn/dkpqgs
title: Replication Data for: European Values Survey 1999 analysis

description: Replication for Chapter 3, Figure 3.4. Data is in .csv format. Commands are in Python notebook. For more information on European Values Survey 1999 see: EVS. 2011. European Values Study 1999 Integrated Dataset: ZA3811
Data file Version 3.0.0. Cologne: GESIS Data Archive. https:
//doi.org/10.4232/1.10789.
DOI: 10.15468/dl.pdcy9k
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Scutinanthe"
 ]
}

 The dataset includes 110 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004041-260221153910048/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.31378912
title: Early Prediction of Clinical Outcomes in Unvaccinated COVID-19 Patients Using Integrated Immune Profiling and Machine Learning

description: AI and Machine Learning in Molecular Biomarker Discovery and Mechanisms of Neurodegenerative Disorders
DOI: 10.6084/m9.figshare.31378912.v1
title: AI and Machine Learning in Molecular Biomarker Discovery and Mechanisms of Neurodegenerative Disorders

description: AI and Machine Learning in Molecular Biomarker Discovery and Mechanisms of Neurodegenerative Disorders
DOI: 10.6084/m9.figshare.31378912.v2
title: Early Prediction of Clinical Outcomes in Unvaccinated COVID-19 Patients Using Integrated Immune Profiling and Machine Learning

description: AI and Machine Learning in Molecular Biomarker Discovery and Mechanisms of Neurodegenerative Disorders
DOI: 10.15468/dl.e6mf77
title: Occurrence Download

description: A dataset containing 169335425 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Country is Sweden"
 ]
}

 The dataset includes 169335425 records from 2124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004000-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1397794.10fu
title: SH1397794.10FU

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/sh1397795.10fu
title: SH1397795.10FU

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/sh1397797.10fu
title: SH1397797.10FU

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/sh1397798.10fu
title: SH1397798.10FU

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/sh1397799.10fu
title: SH1397799.10FU

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/sh1397800.10fu
title: SH1397800.10FU

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/sh1397801.10fu
title: SH1397801.10FU

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/sh1397805.10fu
title: SH1397805.10FU

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/sh1397806.10fu
title: SH1397806.10FU

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/sh1397807.10fu
title: SH1397807.10FU

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.