cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.fvnzg5
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Guatemala",
 "DatasetKey is Actualización de la base de datos de la Colección nacional mexicana de cultivos microbianos"
 ]
}

 The dataset includes 10 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0339862-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q2qefp
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dendrobium gjellerupii J.J.Sm."
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017217-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bu6b2r
title: Occurrence Download

description: A dataset containing 4440960 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Anas strepera Linnaeus, 1758"
 ]
}

 The dataset includes 4440960 records from 991 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0166096-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.12763/hdrzql
title: Replication data for: A selection process based on the robustness of anti-Listeria monocytogenes activity reveals two strains of Carnobacterium maltaromaticum with biopreservation properties in cheese

description: In this study, the anti-L. monocytogenes EGDelux properties of a collection of 77 C. maltaromaticum strains were investigated by high throughput competition assays under varying conditions of co-culture inoculation level, inoculation delay between C. maltaromaticum and L. monocytogenes, pH, and NaCl, resulting in 1309 different combinations of C. maltaromaticum strains and culture conditions. Deferred growth inhibition assays were followed by halo measurements, and liquid co-cultures were followed by colony counting. Challenge tests in Camembert and Saint-Nectaire cheese were also carried out.
DOI: 10.12763/i5ed78
title: Données de réplication pour : "Solving morphological analogies: from retrieval to generation"

description: This repository contains the models trained for the article "Solving morphological analogies: from retrieval to generation". The data is split in 3 folders: "models", "results", and "logs". The folders "models" and "result", respectively found as "model.zip" and "results.zip", contain the path structure "[model]/[dataset]/[langage]/[random_initialization_id]", where "[dataset]" follows the Siganalogies labels: "2016" for Sigmorphon2016 and JBATS; "2019" for Sigmorphon2019. The data contained is as follows: "models/[...]/model.pkl": PyTorch model file; "models/[...]/summary.csv": file containing the evaluation results and other metadata about the training and the structure of the model, as well as the timestamp at which the model finished training; "models/[...]/version_1.0/": PyTorch-Lightning training logs viewable by Tensorboard; "models/[...]/fails.csv": enumeration of all the test analogies that the model did not manage to predict correctly, in an extensive format (for most purposes, it is not necessary to consult Siganalogies to analyse the results). The two folders cover the following models: "clf": CNN+ANNc for classification; "ret": CNN+ANNr for retrieval; "3cosmul": CNN+3CosMul for retrieval, only contains "summary.csv" and reuses the embedding model of "clf"; "ret-annc": CNN+ANNc for retrieval, only contains "summary.csv" and reuses the embedding model of "clf". The folder "logs" has been unpacked in Dorel, and each file can be found separately. The path structure used follows "ae_annr/[dataset]/[langage]/model[random_initialization_id]-data[random_data_split_id]". The data contained is as follows: "logs/ae_annr/[...]/debug/checkpoints/[...].pkl": PyTorch-Lightning model file; "logs/ae_annr/[...]/summary.csv": file containing the evaluation results and other metadata about the training and the structure of the model, as well as the timestamp at which the model finished training; "logs/ae_annr/[...]/debug/": PyTorch-Lightning training logs viewable by Tensorboard; "logs/ae_annr/[...]/fails.csv": enumeration of all the test analogies that the model did not manage to predict correctly, in an extensive format (for most purposes, it is not necessary to consult Siganalogies to analyse the results). This folder only covers the AE+ANNr model.
DOI: 10.12763/ibe7tc
title: Traduction et validation de l'Échelle de Résilience à la Douleur (Pain Resilience Scale ; Ankawi et al., 2017) : Analyses de données quantitatives recueillies auprès d’adultes français (âgés de 18 ans et plus) souffrant de douleurs chroniques par le biais d’enquêtes en ligne à deux moments (du 28/06/22 au 07/11/22) - Exploration de la validité Interne et de la fiabilité (test-retest)

description: Cette étude a mené une recherche quantitative à travers des questionnaires en ligne à deux moments différents auprès d'adultes français (âgés de 18 ans et plus) souffrant de douleurs chroniques. L'objectif de la recherche était d'explorer la validité interne et la fiabilité de la version française de l'Échelle de Résilience à la Douleur (Pain Resilience Scale ; Ankawi et al., 2017), en se concentrant sur les processus de résilience liés à la douleur chez les individus confrontés à une douleur persistante. La collecte de données, réalisée du 28 juin 2022 au 7 novembre 2022, a inclus des questions démographiques générales, des informations détaillées sur les caractéristiques de la douleur des participants, ainsi que leurs réponses à des mesures de résilience et de vulnérabilité liées à la douleur. L'analyse, basée sur la théorie des tests classiques, a évalué la cohérence interne, la validité convergente et la fiabilité test-retest. De plus, une analyse en théorie de réponse aux items (TRI) a été menée pour chacune des deux dimensions de l'échelle. Cette approche complète offre des perspectives précieuses sur la résilience à la douleur au sein de la population spécifiée.
DOI: 10.12763/mlcfie
title: Siganalogies - morphological analogies from Sigmorphon 2016 and 2019

description: The siganalogies dataset contains morphological analogies built upon Sigmorphon 2016 and Sigmorphon 2019 in PyTorch. An analogical proportion is defined as a 4-ary relation written A:B::C:D and which reads "A is to B as C is to D". In this dataset, we manipulate morphological analogies, i.e., on analogies involving character strings, where the transformations between the objects correspond to morphological transformations of words (e.g., conjugation or declension). In our dataset, A, B, C, and D are words. An example in English would be "dog : dogs :: cat : cats". The dataset contains: (i) a copy of Sigmorphon 2019 and Sigmorphon 2016 extended with Japanese data, (ii) serialized objects, one for each language, containing the indices of the analogies and other relevant data, and (iii) the code necessary to manipulate the dataset and serialized data.
DOI: 10.15468/dl.kutztt
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Atrina chautardi, Pinna chautardi)",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058669-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17034/d10994ca-0344-4b3e-9550-36bf3c115591
title: Dataset for "Polar Discontinuities, Emergent Conductivity, and Critical Twist-Angle-Dependent Behaviour at Wafer-Bonded Ferroelectric Interfaces"

description: Atomic Force Microscopy data associated with the submitted paper: "Polar Discontinuities, Emergent Conductivity, and Critical Twist-Angle-Dependent Behaviour at Wafer-Bonded Ferroelectric Interfaces", Nature Communications.

Abstract for paper: "Probing novel functional properties, arising from twisted interfaces, has traditionally relied on the stacking of exfoliated 2D materials and the spontaneous formation of van der Waals (vdW) bonds. So far, investigations involving more intimate covalent or ionic bonds have not been a major focus. Yet, we show here that an established technique, involving high temperature thermocompressional bonding of bulk single crystalline wafers, works well for creating twisted non-vdW interfaces. We have successfully bonded z-cut lithium niobate single crystals to deliberately create ferroelectric oxide interfaces with strong polar discontinuities and have mapped the associated emergent interfacial conductivity. In some instances, a dramatic change in microstructure occurs, involving local dipolar switching. Such behaviour implies a twist-induced collapse in the capability of the system to effectively screen interfacial bound charge. Importantly, this phenomenon only occurs around specific moiré twist angles which have sparse coincident lattices and associated short-range aperiodicity. In quasicrystals, aperiodicity is known to induce pseudo-bandgaps and we suspect a similar phenomenon here."
DOI: 10.5281/zenodo.17978674
title: Dataset for Systematic Review: Computational Strategies for Depression Detection and Treatment

description: Systematic review metadata and supplementary materials for the study:

Computational Strategies for Depression Detection and Treatment: The Role of Behavioral Activation and Neurobiological Insights – A Systematic Review

This dataset contains structured metadata for the 59 studies included in the PRISMA 2020-compliant systematic review. It supports the analysis of artificial intelligence (AI), machine learning, behavioral activation (BA), physical activity monitoring, and neurobiological mechanisms in depression detection and treatment.

 Contents:- `dataset.csv`: Full bibliographic details (Study ID, first author, year, full title, journal, AI technique, accuracy/outcome metrics, population, DOI/URL) for all 59 included studies, plus 2 more regarding the references of the checklist of CLAIM and IJMI AI/ML reporting guidelines.- `S1_File.docx`: Retrospective review protocol, including PICO framework, search strategy, and inclusion/exclusion criteria.- `S1_Table.pdf`: Complete search strings used across PubMed, Scopus, ACM Digital Library, and Web of Science.- `S2_File.docx`: Completed PRISMA 2020 Checklist.- `README.markdown`: Dataset overview and usage instructions.- `data_availability_statement.md`: Final data availability statement for inclusion in the manuscript.Keywords: depression, artificial intelligence, behavioral activation, machine learning, EEG, neuroimaging, digital mental health, PRISMA-'Appendix_S2_AI_ML_reporting_checklist.docx': Compliance with CLAIM and IJMI AI/ML reporting guidelines
DOI: 10.15468/dl.9uw283
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.3_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.3.6_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058668-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15704069
title: Dataset for Systematic Review: Computational Strategies for Depression Detection and Treatment

description: Systematic review metadata and supplementary materials for the study:

Computational Strategies for Depression Detection and Treatment: The Role of Behavioral Activation and Neurobiological Insights – A Systematic Review

This dataset contains structured metadata for the 59 studies included in the PRISMA 2020-compliant systematic review. It supports the analysis of artificial intelligence (AI), machine learning, behavioral activation (BA), physical activity monitoring, and neurobiological mechanisms in depression detection and treatment.

 Contents:- `dataset.csv`: Full bibliographic details (Study ID, first author, year, full title, journal, AI technique, accuracy/outcome metrics, population, DOI/URL) for all 59 included studies, plus 2 more regarding the references of the checklist of CLAIM and IJMI AI/ML reporting guidelines.- `S1_File.docx`: Retrospective review protocol, including PICO framework, search strategy, and inclusion/exclusion criteria.- `S1_Table.pdf`: Complete search strings used across PubMed, Scopus, ACM Digital Library, and Web of Science.- `S2_File.docx`: Completed PRISMA 2020 Checklist.- `README.markdown`: Dataset overview and usage instructions.- `data_availability_statement.md`: Final data availability statement for inclusion in the manuscript.Keywords: depression, artificial intelligence, behavioral activation, machine learning, EEG, neuroimaging, digital mental health, PRISMA-'Appendix_S2_AI_ML_reporting_checklist.docx': Compliance with CLAIM and IJMI AI/ML reporting guidelines
DOI: 10.15468/dl.ta3jza
title: Occurrence Download

description: A dataset containing 23129 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "Geometry POLYGON((-6.25617 41.0851,27.48128 41.0851,27.48128 72.26782,-6.25617 72.26782,-6.25617 41.0851))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cicerbita alpina"
 ]
}

 The dataset includes 23129 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058670-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kzgx3p
title: Occurrence Download

description: A dataset containing 277 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-1000000.0",
 "Geometry POLYGON((-6.25617 41.0851,27.48128 41.0851,27.48128 72.26782,-6.25617 72.26782,-6.25617 41.0851))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Crepis conyzifolia"
 ]
}

 The dataset includes 277 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058671-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17949339
title: Specificity towards primary and secondary hydroxyls of monosaccharides as acceptor substrates in transphosphatidylation catalysed by Streptomyces sp. phospholipase D

description: NMR raw data for publication
DOI: 10.5281/zenodo.17949338
title: Specificity towards primary and secondary hydroxyls of monosaccharides as acceptor substrates in transphosphatidylation catalysed by Streptomyces sp. phospholipase D

description: NMR raw data for publication
DOI: 10.6084/m9.figshare.30903884
title: Supplementary Methods and Figure Legends

description: Extracellular vesicles (EVs) contain RNA, protein, lipids, and other molecules from their parental cell type, which led to the hypothesis that urine-derived stem cell EVs (USC-EVS) could have potent regenerative effects in the setting of acute kidney injury (AKI). We tested this hypothesis in two different in vitro AKI models and an in vivo AKI model. To test USC-EVs ability to recover human kidney cells from nephrotoxicity, HK-2 human proximal tubular epithelial cell line and human kidney organoids derived from induced pluripotent stem cells were treated with 5 μM cisplatin for 48 h followed by 10 μg USC-EVs for 48 h. We next also tested USC-EVs in the unilateral nephrectomy followed by ischemia reperfusion model (UNIRI) AKI model to explore systemic effects in animals. USC-EV treatment of human kidney cells resulted in increased cellular proliferation (p ≤ 0.0001), decreased cytotoxicity (p &lt; 0.0001), and lowered oxidative stress (p ≤ 0.01) as compared to cisplatin alone groups. In mouse models, we found improved pathology as well as reduced kidney injury marker KIM-1 expression in the USC-EV treated group as compared to the UNIRI alone group. Analysis of USC-EV miRNA-targeting pathways associated with epithelial cell proliferation, migration, and positive regulation of MAPK signaling pathway. As predicted by this analysis, we found increased phosphorylation of the MAPK downstream target ERK1/2 in USC-EV-treated HK-2 cells. This study suggests that much of the reported benefit of USCs is due to their EVs and supports further development of USC-EVs as a potential next-generation therapeutic for AKI.
DOI: 10.6084/m9.figshare.30903884.v1
title: Supplementary Methods and Figure Legends

description: Extracellular vesicles (EVs) contain RNA, protein, lipids, and other molecules from their parental cell type, which led to the hypothesis that urine-derived stem cell EVs (USC-EVS) could have potent regenerative effects in the setting of acute kidney injury (AKI). We tested this hypothesis in two different in vitro AKI models and an in vivo AKI model. To test USC-EVs ability to recover human kidney cells from nephrotoxicity, HK-2 human proximal tubular epithelial cell line and human kidney organoids derived from induced pluripotent stem cells were treated with 5 μM cisplatin for 48 h followed by 10 μg USC-EVs for 48 h. We next also tested USC-EVs in the unilateral nephrectomy followed by ischemia reperfusion model (UNIRI) AKI model to explore systemic effects in animals. USC-EV treatment of human kidney cells resulted in increased cellular proliferation (p ≤ 0.0001), decreased cytotoxicity (p &lt; 0.0001), and lowered oxidative stress (p ≤ 0.01) as compared to cisplatin alone groups. In mouse models, we found improved pathology as well as reduced kidney injury marker KIM-1 expression in the USC-EV treated group as compared to the UNIRI alone group. Analysis of USC-EV miRNA-targeting pathways associated with epithelial cell proliferation, migration, and positive regulation of MAPK signaling pathway. As predicted by this analysis, we found increased phosphorylation of the MAPK downstream target ERK1/2 in USC-EV-treated HK-2 cells. This study suggests that much of the reported benefit of USCs is due to their EVs and supports further development of USC-EVs as a potential next-generation therapeutic for AKI.
DOI: 10.5281/zenodo.17945086
title: Climate TRACE Emissions Inventory

description: Climate TRACE is a non-profit coalition of organizations building a timely, open, and accessible inventory of exactly where greenhouse gas emissions are coming from. Climate TRACE estimates greenhouse gas (GHG) and air pollutant emissions for over 2.7 million sources (from over 744 million assets), and every single country globally.

Each download package includes CSVs of:



Annual country-level emissions by sub-sector and by gas beginning in 2015

Monthly source-level emissions by sub-sector and gas beginning in 2021 and confidence

Emissions source ownership where and when available.


All Climate TRACE data are free and publicly available under a CC-BY 4.0 license to enable action and accountability at the massive scale necessary for global progress. Beginning in March 2025, Climate TRACE is releasing updated data with a 60-day lag during the final week of each month. All previous versions of the Climate TRACE asset- and country-level database will be uploaded to this page.

With the addition of October 2025 data, the Climate TRACE database is now updated to version 5.2.0.

Version 5.1.0 (released November 25, 2025) will be available here. Note: V5.0.0 release launched at COP30 and now includes data on potential options for reducing emissions at every asset in the Climate TRACE database.

V5.1.0 includes new modeling of cropland fires, additional sources and updated emissions factors across multiple mining subsectors, updated estimates for solid waste disposal using more detailed input data, updated non-GHG emissions in petrochemical steam cracking, updated SO₂ and PM2.5 emissions globally, and updated GHG emissions in North America and Europe in the oil and gas transport and production sectors.

A detailed description of data updates is available in our changelog here.

We recommend getting familiar with how Climate TRACE data are created and structured by reviewing our FAQs, resources, and guidance:



The Climate TRACE FAQs page is an especially useful resource to quickly learn how we develop the emissions inventory, what data are contained in the inventory, details on units of measurement and coverage, and much more.

The Sectors page summarizes methodological details on dozens of sub-sectors. The data are licensed under the Creative Commons Attribution 4.0 International License; more details can be found on our terms of use page.

Detailed guidance on the data schema, licensing, and citations can be found in the data guide, as well as in the “detailed-data-schema” in the download packages.


If you have any questions, please reach out to us via our contact page.
DOI: 10.15468/dl.xaebrw
title: Occurrence Download

description: A dataset containing 1255 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "Geometry POLYGON((-6.25617 41.0851,27.48128 41.0851,27.48128 72.26782,-6.25617 72.26782,-6.25617 41.0851))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Crepis conyzifolia"
 ]
}

 The dataset includes 1255 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058673-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/uy1vks
title: PAN-00182727 - three-ribbed La Tène bracelet

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00182727&lt;/p&gt;
description: Modified: 2025-11-17T10:27:42+01:00
DOI: 10.15468/dl.pcb368
title: Occurrence Download

description: A dataset containing 19108 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 15.0",
 "DecimalLatitude is less than or equal to 20.0",
 "DecimalLongitude is greater than or equal to -110.0",
 "DecimalLongitude is less than or equal to -105.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 19108 records from 135 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058674-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.