cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18813628
title: Yemeni Proverbs

description: Yemeni Proverbs: A Benchmark Corpus for Figurative and Cultural Language Modeling

This dataset contains 5,252 Yemeni Arabic proverbs paired with their corresponding explanations in Modern Standard Arabic (MSA). The corpus was compiled from four printed proverb anthologies and three publicly accessible digital repositories between January and June 2024.

The dataset was created through manual transcription of printed materials and structured extraction of digital sources. All entries were manually verified to ensure accurate pairing between proverb text and its original explanation. Duplicate and incomplete records were removed during preprocessing.

Each record includes the following fields:





id: Unique integer identifier




proverb: Dialectal Yemeni Arabic proverb (UTF-8 encoded)




explanation: Explanation in Modern Standard Arabic (transcribed from source)




source: Title of the printed anthology or name of the digital repository




city: Geographic origin if explicitly stated in the source (otherwise null)




url: Direct link to online source when applicable (null for printed sources)



The corpus preserves dialectal orthography and does not introduce new explanatory annotations. All explanations were transcribed directly from the original sources.

Geographic metadata is available for approximately 27% of entries. No geographic inference was performed when such information was not explicitly provided in the source materials.

The dataset is intended to support research in:





Figurative language understanding




Dialect-aware Arabic NLP




Culturally grounded language modeling




Evaluation of generative models on non-MSA input




Computational folkloristics



This repository contains:





Yemeni_proverbs.json (primary dataset file, UTF-8 encoded)



The dataset is distributed under the Creative Commons Attribution 4.0 (CC BY 4.0) license.Users are responsible for consulting original publishers for access to full source documents under their respective terms.
DOI: 10.5281/zenodo.18813629
title: Yemeni Proverbs

description: Yemeni Proverbs: A Benchmark Corpus for Figurative and Cultural Language Modeling

This dataset contains 5,252 Yemeni Arabic proverbs paired with their corresponding explanations in Modern Standard Arabic (MSA). The corpus was compiled from four printed proverb anthologies and three publicly accessible digital repositories between January and June 2024.

The dataset was created through manual transcription of printed materials and structured extraction of digital sources. All entries were manually verified to ensure accurate pairing between proverb text and its original explanation. Duplicate and incomplete records were removed during preprocessing.

Each record includes the following fields:





id: Unique integer identifier




proverb: Dialectal Yemeni Arabic proverb (UTF-8 encoded)




explanation: Explanation in Modern Standard Arabic (transcribed from source)




source: Title of the printed anthology or name of the digital repository




city: Geographic origin if explicitly stated in the source (otherwise null)




url: Direct link to online source when applicable (null for printed sources)



The corpus preserves dialectal orthography and does not introduce new explanatory annotations. All explanations were transcribed directly from the original sources.

Geographic metadata is available for approximately 27% of entries. No geographic inference was performed when such information was not explicitly provided in the source materials.

The dataset is intended to support research in:





Figurative language understanding




Dialect-aware Arabic NLP




Culturally grounded language modeling




Evaluation of generative models on non-MSA input




Computational folkloristics



This repository contains:





Yemeni_proverbs.json (primary dataset file, UTF-8 encoded)



The dataset is distributed under the Creative Commons Attribution 4.0 (CC BY 4.0) license.Users are responsible for consulting original publishers for access to full source documents under their respective terms.
DOI: 10.3886/e246561
title: Bayero University, Kano (BUK) 2026/2027 Admission Form is out call 09017730052 To Purchase And Further Registration Guidelines Contact Dr . Sir Martins +2349017730052 or WhatsApp 08169753031

description: Bayero University, Kano (BUK) 2026/2027 Admission Form is out call 09017730052 To Purchase And Further Registration Guidelines Contact Dr . Sir Martins +2349017730052 or WhatsApp 08169753031
DOI: 10.3886/e246561v1
title: Bayero University, Kano (BUK) 2026/2027 Admission Form is out call 09017730052 To Purchase And Further Registration Guidelines Contact Dr . Sir Martins +2349017730052 or WhatsApp 08169753031

description: Bayero University, Kano (BUK) 2026/2027 Admission Form is out call 09017730052 To Purchase And Further Registration Guidelines Contact Dr . Sir Martins +2349017730052 or WhatsApp 08169753031
DOI: 10.15468/dl.fvr2wy
title: Occurrence Download

description: A dataset containing 0 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Mugilogobius tagala"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004260-260226173443078/datasets/export for details.
DOI: 10.15468/dl.cnyks3
title: Occurrence Download

description: A dataset containing 863 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Vipera latastei",
 "Year 2008-2024"
 ]
}

 The dataset includes 863 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004261-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ff8v2b
title: Occurrence Download

description: A dataset containing 93 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Apogon unicolor"
 ]
}

 The dataset includes 93 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004263-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e246562
title: University of Delta, Agbor 2026-2027 POST-UTME FORM/ DIRECT-ENTRY FORM IS OUT CALL 09017730052 TO PURCHASE AND FURTHER REGISTRATION GUIDELINES, Contact School Admin Office (+2349017730052) WhatsApp 08169753031

description: University of Delta, Agbor 2026-2027 POST-UTME FORM/ DIRECT-ENTRY FORM IS OUT CALL 09017730052 TO PURCHASE AND FURTHER REGISTRATION GUIDELINES, Contact School Admin Office (+2349017730052) WhatsApp 08169753031
DOI: 10.3886/e246562v1
title: University of Delta, Agbor 2026-2027 POST-UTME FORM/ DIRECT-ENTRY FORM IS OUT CALL 09017730052 TO PURCHASE AND FURTHER REGISTRATION GUIDELINES, Contact School Admin Office (+2349017730052) WhatsApp 08169753031

description: University of Delta, Agbor 2026-2027 POST-UTME FORM/ DIRECT-ENTRY FORM IS OUT CALL 09017730052 TO PURCHASE AND FURTHER REGISTRATION GUIDELINES, Contact School Admin Office (+2349017730052) WhatsApp 08169753031
DOI: 10.15468/dl.2dg48c
title: Occurrence Download

description: A dataset containing 5 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Thamnaconus septentrionalis"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004264-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mswzzh
title: Occurrence Download

description: A dataset containing 3 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Pictichromis diadema"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004266-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18808457
title: Dataset for "Acurácia e confiabilidade de ferramentas de Inteligência Artificial Generativa na análise estatística de dados epidemiológicos: um estudo metodológico comparativo"

description: Bancos de dados de 5 agravos do SINAN disponíveis no DATASUS, exportados pelos tabwin e utilizado para fazer comparação de desempenho entre dois modelos de IA (ChatGPT e Gemini). Cada banco contém duas variáveis contínuas.
DOI: 10.5281/zenodo.18808456
title: Dataset for "Acurácia e confiabilidade de ferramentas de Inteligência Artificial Generativa na análise estatística de dados epidemiológicos: um estudo metodológico comparativo"

description: Bancos de dados de 5 agravos do SINAN disponíveis no DATASUS, exportados pelos tabwin e utilizado para fazer comparação de desempenho entre dois modelos de IA (ChatGPT e Gemini). Cada banco contém duas variáveis contínuas.
DOI: 10.15468/dl.xg62cp
title: Occurrence Download

description: A dataset containing 0 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Pseudochromis olivaceus"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004267-260226173443078/datasets/export for details.
DOI: 10.5281/zenodo.18814705
title: Daten der Notaufnahmesurveillance

description: Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und das AKTIN-Notaufnahmeregister bei Krankenhausaufnahmen bereitgestellt. Der Datensatz beinhaltet aggregierte Routinedaten aus deutschen Notaufnahmen zur syndromischen Überwachung von akuten Erkrankungen. Dazu zählen grippeähnliche Erkrankungen (ILI), Coronavirus-Erkrankungen (COVID-19), akute respiratorische Erkrankungen (ARE), gastrointestinale Infektionen (GI) und schwere akute respiratorische Infektionen (SARI). Dabei wird der relative Anteil dieser Erkrankungen an der Gesamtzahl der Notaufnahmevorstellungen sowie die berechneten Erwartungswerte und Prädiktionsintervalle ausgewiesen. Die Daten sind nach Notaufnahmetypen und Altersgruppen aggregiert. Damit bietet der Datensatz eine wertvolle Ressource für die Forschung im Bereich der Notfallmedizin und der Überwachung akuter Gesundheitsereignisse in Deutschland.
DOI: 10.5281/zenodo.7189871
title: Daten der Notaufnahmesurveillance

description: Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und das AKTIN-Notaufnahmeregister bei Krankenhausaufnahmen bereitgestellt. Der Datensatz beinhaltet aggregierte Routinedaten aus deutschen Notaufnahmen zur syndromischen Überwachung von akuten Erkrankungen. Dazu zählen grippeähnliche Erkrankungen (ILI), Coronavirus-Erkrankungen (COVID-19), akute respiratorische Erkrankungen (ARE), gastrointestinale Infektionen (GI) und schwere akute respiratorische Infektionen (SARI). Dabei wird der relative Anteil dieser Erkrankungen an der Gesamtzahl der Notaufnahmevorstellungen sowie die berechneten Erwartungswerte und Prädiktionsintervalle ausgewiesen. Die Daten sind nach Notaufnahmetypen und Altersgruppen aggregiert. Damit bietet der Datensatz eine wertvolle Ressource für die Forschung im Bereich der Notfallmedizin und der Überwachung akuter Gesundheitsereignisse in Deutschland.
DOI: 10.15468/dl.qbzgqn
title: Occurrence Download

description: A dataset containing 0 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Pseudochromis springeri"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004269-260226173443078/datasets/export for details.
DOI: 10.15468/dl.4z88yh
title: Occurrence Download

description: A dataset containing 2694469 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Données de l'inventaire forestier national de l'IGN-Relevés floristiques du protocole de l'Inventaire National Forestier de l'IGN",
 {
 "or" : [
 "Geometry POLYGON((-16.95376 38.72183,21.95376 38.72183,21.95376 54.27817,-16.95376 54.27817,-16.95376 38.72183))",
 "Geometry POLYGON((2.99706 47.04739,2.99219 46.72586,3.36407 46.06492,3.52159 46.05193,3.29099 47.03603,2.99706 47.04739))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2694469 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004265-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34804/supra.20211007403
title: A New Fluorometric Method for the Detection of the Neurotransmitter Acetylcholine in Water Using a Dansylcholine Complex with p-Sulfonated Calix[8]arene - Journal of Inclusion Phenomena and Macrocyclic Chemistry

description: A new method for the fluorometric detection of the neurotransmitter acetylcholine (ACh) in water is presented. Use of the fluorescence of dansylcholine (DANCh) bound to p-sulfonated calix[8]arene affords a new fluorometric method for the detection of ACh (>10-4 M) inaqueous solution (pH = 6.9). The fluorescence intensity of DANCh in aqueous solution was enhanced 1.8 fold after the complexation with p-sulfonated calix[8]arene. The addition of ACh to the aqueous solution of the DANCh-calix[8]arene complex significantly decreased the fluorescence intensity, which results from the replacement of DANCh in the complex with ACh. The effects of other synaptic neurotransmitters on the fluorescence of the DANCh complex were examined for dopamine, histamine, ATP, GABA, glycine, l-glutamic acid, and l-aspartic acid. Among the neurotransmitters studied, ACh was most effective in changing the fluorescence of the DANCh complex. Possible application of the DANCh complex dye for the detection of ACh in biological systems is discussed.
DOI: 10.21227/g4bg-3y74
title: "Training Dataset for Small-Signal Modelling of Power Systems"

description: "This dataset presents a collection of structured training data designed for fine-tuning Tool-Augmented Large Language Models (TA-LLMs) in the power and energy domain. Specifically, it focuses on the small-signal modeling and simulation of AC-DC hybrid power electronic-defined power systems. The dataset for LLMs' training addresses challenges of the inefficiency of manual Grid Code Compliance assessments for Inverter-Based Resources (IBRs) and the scarcity of realistic network parameters due to confidentiality concerns. Organized in a hierarchical structure, the data covers fundamental mathematical control blocks, complex apparatuses such as synchronous generators and inverter-based resources, and multi-node AC-DC network topologies. The synthesis of this dataset utilizes a closed-loop framework that integrates physics-informed templates generated from online LLMs with an automated generation pipeline. All data entries are formatted in the standardized Alpaca-style JSONL structure, ensuring high machine-readability and compatibility with modern instruction-tuning workflows. To ensure technical rigor, the dataset's accuracy is evaluated through time-domain and power-flow simulations compared with public models. This article provides detailed documentation on data sources, formatting conventions, and usage instructions to facilitate the development of AI-driven digital twins and automated simulation tools in power systems."
DOI: 10.15468/dl.bwwsb8
title: Occurrence Download

description: A dataset containing 0 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Pseudochromis dixurus"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004272-260226173443078/datasets/export for details.
DOI: 10.5281/zenodo.18814617
title: Cytokine expression dataset from extracellular vesicle and soluble fractions of adipose-derived mesenchymal stem cells in discogenic pain cell model

description: Dataset supporting the article DOI:10.1016/J.SPINEE.2022.01.012
DOI: 10.5281/zenodo.18814616
title: Cytokine expression dataset from extracellular vesicle and soluble fractions of adipose-derived mesenchymal stem cells in discogenic pain cell model

description: Dataset supporting the article DOI:10.1016/J.SPINEE.2022.01.012
DOI: 10.5281/zenodo.17908767
title: Supplementary material and datasets of the paper 'Trade induced extinction risk footprints by European financial institutions'

description: This repository hosts the datasets generated during the elaboration of the research article 'Trade induced extinction risk footprints by European financial institutions'. It also includes the environmental pressure to IUCN threat correspondence matrix as well as a document where the scientific justification for each pressure-threat link is further explained. These files are sufficient to reproduce the results presented in the research article.

The title of the files are self-explanatory. We provide here a brief description of the variables contained in them where necessary.

Sup_Mat_World_biodiversity_footprint.xlsx:



country

fdom: Species extinction-risk footprint generated and consumed domestically

fexp: Species extinction-risk footprint generated domestically but exported

fimp: Species extinction-risk footprint imported

nfp: fdom + fimp

type: Whether the country is Importer, Exporter or Domestic consumer


Sup_Mat_Sectoral_economic_output_decrease.xlsx:



iso: 3-character iso country code, e.g. PER, USA, BRA.

country

NACE: Nace economic sector classificaiton code

dx: Output after shock - Initial output

x: Initial output

df: New final demand based on footprint reduction - Initial final demand

f: Initial final demand

abvarx: Variation rate of output in absolute terms

abvarf: Variation rate of final demand in absolute terms

eu: 2-character iso country code of european countries


Sup_Mat_National_Financial_Assets_exposure.xlsx:



country

exposure: percentage of national financial assets linked to economic sectors with highest biodiversity footprints


Sup_Mat_Interest_Burden_increase.xlsx:



country: 2-character iso country code

sector: Nace economic sector classificaiton code

abvarx: Variation rate of output in absolute terms

turnover: Amount of turnover/output per sector in thousands of dollars

I83_WM: Other financial expenses as percentage of turnover

I10_WM: Interest payments as percentage of turnover

I1_WM: Turnover (percentage)

ipt0: Initial Interest Burden ratio

ipt1: Interest Burden ratio after shock

vaript: Variation rate of Interest Burden ratio

di: (ipt1 - ipt0) * turnover

i: ipt0 * turnover
DOI: 10.15468/dl.ke8t23
title: Occurrence Download

description: A dataset containing 0 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Pseudochromis sankeyi"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004273-260226173443078/datasets/export for details.
DOI: 10.5281/zenodo.16732268
title: Radially anisotropic shear-wave velocity model and associated datasets for the central-southern segment of the Tanlu Fault Zone

description:  

Data description

This dataset consists of four parts:





TL_RA_Vs_Model.zip – Shear-wave velocity and radial anisotropy model obtained by Bayesian joint inversion of receiver functions together with Rayleigh- and Love-wave dispersion. The model spans longitudes 115°E–122°E and latitudes 30°N–38°N on a 0.25° grid. Vertically it extends from 0 to 80 km at 1 km intervals. Results shallower than 45 km are considered the most reliable. See the included README for details.




RF.zip – Q-component receiver-function waveforms from 214 stations, provided in SAC format.




Dispersion.zip – Interstation Rayleigh- and Love-wave dispersion measurements among 328 stations. In each dispersion file, column 1 is period, column 2 is phase velocity, and column 4 is a binary flag (0 = unusable, 1 = usable).


Tanlu_CFs.tar.gz - This folder contains stacked ambient-noise cross-correlation functions computed between 328 seismic stations in the central-southern segment of the Tanlu Fault Zone and its surrounding region. The subfolder T-T includes stacked cross-correlations for the transverse (T) component, and the subfolder Z-Z includes stacked cross-correlations for the vertical (Z) component.