cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ebqc3q
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((116.914 1.400183, 116.843716 1.394615, 116.775164 1.378048, 116.710032 1.350891, 116.649925 1.313812, 116.596322 1.267725, 116.550544 1.213766, 116.513718 1.153262, 116.48675 1.087704, 116.470303 1.018708, 116.464781 0.947971, 116.470321 0.877235, 116.486784 0.808242, 116.513765 0.742691, 116.5506 0.682196, 116.59638 0.6282450000000001, 116.64998 0.582167, 116.710079 0.545096, 116.775198 0.517945, 116.843734 0.501383, 116.914 0.495816, 116.984266 0.501383, 117.052802 0.517945, 117.117921 0.545096, 117.17802 0.582167, 117.23162 0.6282450000000001, 117.2774 0.682196, 117.314235 0.742691, 117.341216 0.808242, 117.357679 0.877235, 117.363219 0.947971, 117.357697 1.018708, 117.34125 1.087704, 117.314282 1.153262, 117.277456 1.213766, 117.231678 1.267725, 117.178075 1.313812, 117.117968 1.350891, 117.052836 1.378048, 116.984284 1.394615, 116.914 1.400183))"},{"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 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002046-260120142942310/datasets/export for details.
DOI: 10.6084/m9.figshare.31017985
title: Scripts

description: This folder has all the necessary scripts to run the main analyses (supplementary analyses are provided in the supplementary_scripts folder). Goals of each script are in the preface of all scripts. The assumed working directory (stated in all scripts) is the home (i.e. project) folder unless otherwise indicated. Scripts to create/analyze data will follow the steps in their title, with additional separate scripts for plotting the manuscript figures.
DOI: 10.6084/m9.figshare.31017985.v2
title: Scripts

description: This folder has all the necessary scripts to run the main analyses (supplementary analyses are provided in the supplementary_scripts folder). Goals of each script are in the preface of all scripts. The assumed working directory (stated in all scripts) is the home (i.e. project) folder unless otherwise indicated. Scripts to create/analyze data will follow the steps in their title, with additional separate scripts for plotting the manuscript figures.
DOI: 10.6084/m9.figshare.31017985.v3
title: Scripts

description: This folder has all the necessary scripts to run the main analyses (supplementary analyses are provided in the supplementary_scripts folder). Goals of each script are in the preface of all scripts. The assumed working directory (stated in all scripts) is the home (i.e. project) folder unless otherwise indicated. Scripts to create/analyze data will follow the steps in their title, with additional separate scripts for plotting the manuscript figures.
DOI: 10.15468/dl.8926z7
title: Occurrence Download

description: A dataset containing 447 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((118.174 5.706143, 118.10339 5.700573, 118.034523 5.683998, 117.969097 5.656829, 117.908727 5.619735, 117.854901 5.573631, 117.808944 5.519655, 117.771987 5.459139, 117.744939 5.393572, 117.728463 5.324572, 117.72296 5.253837, 117.728563 5.18311, 117.74513 5.114133, 117.77225 5.048601, 117.809253 4.988129, 117.855226 4.934203, 117.909036 4.888149, 117.96936 4.851099, 118.034714 4.823965, 118.103491 4.807413, 118.174 4.80185, 118.244509 4.807413, 118.313286 4.823965, 118.37864 4.851099, 118.438964 4.888149, 118.492774 4.934203, 118.538747 4.988129, 118.57575 5.048601, 118.60287 5.114133, 118.619437 5.18311, 118.62504 5.253837, 118.619537 5.324572, 118.603061 5.393572, 118.576013 5.459139, 118.539056 5.519655, 118.493099 5.573631, 118.439273 5.619735, 118.378903 5.656829, 118.313477 5.683998, 118.24461 5.700573, 118.174 5.706143))"},{"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 447 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002047-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18323965
title: Data_underlying_analyses_and_figures
DOI: 10.5281/zenodo.18323964
title: Data_underlying_analyses_and_figures
DOI: 10.5281/zenodo.18275711
title: Census of Decentralized Autonomous Organizations Across Platforms (2025)

description: This dataset provides a comprehensive, multi-platform overview of Decentralized Autonomous Organizations (DAOs) as of October 2025, covering DAO deployments, proposals, and voting activity across 6 major platforms: Aragon, DAOHaus, DAOstack, Realms, Snapshot and Tally. It is designed to support research in blockchain governance, decentralized finance, and community-driven decision-making.

The dataset is structured into three CSV files:





deployments.csv – Contains metadata for each DAO deployment, including a unique identifier (deployment_id), platform name (platform), DAO name (name), number of proposals (proposals_count), number of distinct voters (unique_voters), total votes cast (votes_count), and estimated voting power (estimated_vp).




proposals.csv – Contains detailed information on proposals submitted to each DAO, including a unique proposal ID (proposal_id), associated DAO deployment (deployment_id), creation date (date), number of votes received (votes_count), total voting power used (total_vp), and the platform (platform).




votes.csv – Contains individual vote records, including a unique vote ID (vote_id), associated proposal (proposal_id), corresponding DAO deployment (deployment_id), voter address (voter), timestamp of the vote (date), voting power used (weight), and platform (platform).



Data collection for this release was completed in October 2025. The full data acquisition and processing pipeline typically requires approximately two to three weeks, involving the retrieval, validation, and integration of governance data from each platform’s public APIs and subgraphs.

This dataset is suitable for empirical research on DAO governance dynamics, voting behavior, and multi-platform analysis. Researchers can use this dataset to analyze trends in proposal creation, voter participation, and governance outcomes in decentralized communities.

The code for collecting and formatting the data is in the github repository linked. The instructions of use, requirements, the data loading and some example analyses are in the MSR submission folder of the github repository.

 

Acknowledgements

We would like to acknowledge the use of tools and support provided by DAO Analyzer dataset, GraphiQL, Tally API Reference, and AI-Powered RPC Infrastructure for dApps & Chains | dRPC for data extraction. These resources were indispensable for the successful completion of this project.
DOI: 10.34740/kaggle/dsv/14567816
title: Alibaba (BABA) Stock Market Dataset (2014–2023)
DOI: 10.15468/dl.w3evfp
title: Occurrence Download

description: A dataset listing the 373 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((4.69562 46.73801,4.72189 46.73801,4.72189 46.75113,4.69562 46.75113,4.69562 46.73801))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 373 records were derived from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002030-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vsxd26
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Hong Kong",
 "TaxonKey is Eumenes punctatus"
 ]
}

 The dataset includes 68 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002048-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x74f4b
title: Occurrence Download

description: A dataset containing 13950 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-5000.0",
 "TaxonKey is Podarcis muralis",
 "Year 1970-2000"
 ]
}

 The dataset includes 13950 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002051-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14280845
title: The adding value of non-invasive assessment of stroke volume during cardiopulmonary exercise testing in hypertrophic cardiomyopathy: beyond O2-pulse

description: Abstract 

In hypertrophic cardiomyopathy (HCM), cardiopulmonary exercise testing (CPET) is the gold standard for assessing exercise tolerance, with O2-pulse commonly used as a surrogate for stroke volume (SV). However, as SV reduction can be masked by increased oxygen extraction, direct non-invasive SV measurement is valuable. This study included 102 HCM patients (53±16 years, 78% male) with predominantly non-obstructive phenotype (74%) who underwent CPET with SV measurement using Physioflow® (PF).

Abnormal O2-pulse kinetics were observed in 12 patients, all confirmed by abnormal SV trends with PF. Additionally, PF identified 28 more patients with altered SV kinetics. Abnormal SV trends were associated with higher peak VE/VO2 ratios (42.6 [37.4–47.5] vs. 38.0 [33.6–41.3]) and lower end-tidal CO2 values (31.8±4.9 mmHg vs. 34.3±5.6 mmHg, p<0.05). Patients with greater SV growth in the last 25% of exercise showed improved anaerobic threshold VO2 (49.8±12.3% vs. 43.9±15.2% predicted peak VO2), VO2/work slope (10.2±2.0 vs. 9.3±1.3 mL/min/Watt), and peak PetCO2 (34.5±5.6 mmHg vs. 32.3±5.2), alongside lower VE/VCO2 slope (28.7 [24.9–31.0] vs. 31.3 [27.3–34.2], p<0.05).

Integrating PF and CPET enhances detection of abnormal SV kinetics, which are linked to reduced functional capacity in HCM patients.
DOI: 10.5281/zenodo.14280844
title: The adding value of non-invasive assessment of stroke volume during cardiopulmonary exercise testing in hypertrophic cardiomyopathy: beyond O2-pulse

description: Abstract 

In hypertrophic cardiomyopathy (HCM), cardiopulmonary exercise testing (CPET) is the gold standard for assessing exercise tolerance, with O2-pulse commonly used as a surrogate for stroke volume (SV). However, as SV reduction can be masked by increased oxygen extraction, direct non-invasive SV measurement is valuable. This study included 102 HCM patients (53±16 years, 78% male) with predominantly non-obstructive phenotype (74%) who underwent CPET with SV measurement using Physioflow® (PF).

Abnormal O2-pulse kinetics were observed in 12 patients, all confirmed by abnormal SV trends with PF. Additionally, PF identified 28 more patients with altered SV kinetics. Abnormal SV trends were associated with higher peak VE/VO2 ratios (42.6 [37.4–47.5] vs. 38.0 [33.6–41.3]) and lower end-tidal CO2 values (31.8±4.9 mmHg vs. 34.3±5.6 mmHg, p<0.05). Patients with greater SV growth in the last 25% of exercise showed improved anaerobic threshold VO2 (49.8±12.3% vs. 43.9±15.2% predicted peak VO2), VO2/work slope (10.2±2.0 vs. 9.3±1.3 mL/min/Watt), and peak PetCO2 (34.5±5.6 mmHg vs. 32.3±5.2), alongside lower VE/VCO2 slope (28.7 [24.9–31.0] vs. 31.3 [27.3–34.2], p<0.05).

Integrating PF and CPET enhances detection of abnormal SV kinetics, which are linked to reduced functional capacity in HCM patients.
DOI: 10.34740/kaggle/dsv/14568199
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.fe956x
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Blysmus rufus"
 ]
}

 The dataset includes 24 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002054-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mukuy4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((101.14 1.407183, 101.069716 1.401615, 101.001164 1.385048, 100.936031 1.357891, 100.875924 1.320812, 100.822321 1.274725, 100.776543 1.220765, 100.739717 1.160262, 100.712749 1.094704, 100.696302 1.025708, 100.69078 0.95497, 100.69632 0.884235, 100.712783 0.815242, 100.739764 0.749691, 100.776599 0.689195, 100.82238 0.6352449999999999, 100.87598 0.589167, 100.936079 0.552096, 101.001198 0.524945, 101.069734 0.508383, 101.14 0.502816, 101.210266 0.508383, 101.278802 0.524945, 101.343921 0.552096, 101.40402 0.589167, 101.45762 0.6352449999999999, 101.503401 0.689195, 101.540236 0.749691, 101.567217 0.815242, 101.58368 0.884235, 101.58922 0.95497, 101.583698 1.025708, 101.567251 1.094704, 101.540283 1.160262, 101.503457 1.220765, 101.457679 1.274725, 101.404076 1.320812, 101.343969 1.357891, 101.278836 1.385048, 101.210284 1.401615, 101.14 1.407183))"},{"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 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002055-260120142942310/datasets/export for details.
DOI: 10.15468/dl.rues87
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((115.657 5.707143, 115.58639 5.701573, 115.517522 5.684998, 115.452097 5.657828, 115.391727 5.620734, 115.3379 5.574631, 115.291943 5.520655, 115.254986 5.460138, 115.227938 5.394572, 115.211462 5.325572, 115.205959 5.254837, 115.211562 5.18411, 115.228129 5.115133, 115.25525 5.049601, 115.292252 4.989129, 115.338225 4.935203, 115.392036 4.889149, 115.45236 4.852099, 115.517714 4.824965, 115.58649 4.808413, 115.657 4.80285, 115.72751 4.808413, 115.796286 4.824965, 115.86164 4.852099, 115.921964 4.889149, 115.975775 4.935203, 116.021748 4.989129, 116.05875 5.049601, 116.085871 5.115133, 116.102438 5.18411, 116.108041 5.254837, 116.102538 5.325572, 116.086062 5.394572, 116.059014 5.460138, 116.022057 5.520655, 115.9761 5.574631, 115.922273 5.620734, 115.861903 5.657828, 115.796478 5.684998, 115.72761 5.701573, 115.657 5.707143))"},{"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 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002056-260120142942310/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.31109464
title: Human annotation files for ISm6APeak

description: five types of hg38 genomic annotation files
DOI: 10.6084/m9.figshare.31109464.v1
title: Human annotation files for ISm6APeak

description: five types of hg38 genomic annotation files
DOI: 10.15468/dl.295bv9
title: Occurrence Download

description: A dataset containing 6348 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Abrodictyum obscurum, Abrophyllum ornans, Abrotanella forsteroides, Abrotanella scapigera, Acacia acanthoclada acanthoclada, Acacia acuminata, Acacia aemula muricata, Acacia alata, Acacia assimilis atroviridis)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 6348 records from 113 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002057-260120142942310/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.29040476
title: A Systematic Review of Spectroscopic Techniques for Detecting Milk Adulteration

description: Milk adulteration is a crucial worldwide concern that endangers food safety and public health, as it involves the deliberate tampering with milk by adding foreign substances or removing essential nutrients, often to boost profits or hinder microbial growth. Traditional detection methods frequently lack the sensitivity and speed required to identify adulterants within milk’s complex matrix. This systematic review critically examines the application of spectroscopic techniques for detecting milk adulteration, focusing on Nuclear Magnetic Resonance (NMR), Infrared (IR) Spectroscopy, Raman Spectroscopy, Ultraviolet-Visible (UV-Vis) Spectroscopy, Mass Spectrometry, Laser-Based Techniques, Dielectric Spectroscopy, and X-Ray Spectroscopy. Each technique’s principles, advantages, limitations, and specific applications in identifying adulterants, such as water, urea, melamine, added sugars, fats, preservatives, and heavy metals are discussed. The review highlights how these methods offer rapid, non-destructive, and sensitive analysis, enhancing the ability to detect adulterants at molecular levels. Despite advancements, challenges persist, including the complexity and natural variability of milk composition, high costs of advanced equipment, need for specialized expertise, and lack of standardized protocols. Future directions emphasize developing portable and cost-effective spectroscopic devices, integrating artificial intelligence and machine learning for advanced data analysis, and fostering international collaboration to establish standardized methodologies and comprehensive spectral databases. By addressing these challenges, spectroscopic techniques can be more widely implemented, ultimately safeguarding public health, ensuring the integrity of dairy products, and maintaining consumer trust in the global food supply chain.
DOI: 10.6084/m9.figshare.29040476.v1
title: A Systematic Review of Spectroscopic Techniques for Detecting Milk Adulteration

description: Milk adulteration is a crucial worldwide concern that endangers food safety and public health, as it involves the deliberate tampering with milk by adding foreign substances or removing essential nutrients, often to boost profits or hinder microbial growth. Traditional detection methods frequently lack the sensitivity and speed required to identify adulterants within milk’s complex matrix. This systematic review critically examines the application of spectroscopic techniques for detecting milk adulteration, focusing on Nuclear Magnetic Resonance (NMR), Infrared (IR) Spectroscopy, Raman Spectroscopy, Ultraviolet-Visible (UV-Vis) Spectroscopy, Mass Spectrometry, Laser-Based Techniques, Dielectric Spectroscopy, and X-Ray Spectroscopy. Each technique’s principles, advantages, limitations, and specific applications in identifying adulterants, such as water, urea, melamine, added sugars, fats, preservatives, and heavy metals are discussed. The review highlights how these methods offer rapid, non-destructive, and sensitive analysis, enhancing the ability to detect adulterants at molecular levels. Despite advancements, challenges persist, including the complexity and natural variability of milk composition, high costs of advanced equipment, need for specialized expertise, and lack of standardized protocols. Future directions emphasize developing portable and cost-effective spectroscopic devices, integrating artificial intelligence and machine learning for advanced data analysis, and fostering international collaboration to establish standardized methodologies and comprehensive spectral databases. By addressing these challenges, spectroscopic techniques can be more widely implemented, ultimately safeguarding public health, ensuring the integrity of dairy products, and maintaining consumer trust in the global food supply chain.
DOI: 10.15468/dl.u9xqau
title: Occurrence Download

description: A dataset containing 23721 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-0.91685 56.74844,34.9004 56.74844,34.9004 81.9473,-0.91685 81.9473,-0.91685 56.74844))",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Virgularia, Kophobelemnon, Pennatula, Funiculina, Stylatula, Balticina, Ptilella)"
 ]
}

 The dataset includes 23721 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002058-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.