cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/dr4386g3cg.1
title: clanorgan_data

description: The data includes 2226 samples, describing their population characteristics, willingness and cognition towards organ donation, as well as cultural features such as ancestral halls and religion in the cities where the samples are located.
DOI: 10.17632/wvyj33kxtk
title: Long-term Electricity Demand Forecasting using THI-ConvNet

description: Electricity load forecasting is critical for ensuring the stability and efficiency of power supply systems, particularly during holidays when demand patterns tend to deviate from normal trends. However, most existing studies focus on short-term forecasts and lack the capability to effectively incorporate the irregularities caused by long-term holidays. To address this gap, we propose a novel deep learning-based forecasting model called the Temporal Holiday-Integrated (THI) model, which is the first to explicitly integrate both short-term and long-term holiday effects into electricity demand prediction. The model is trained using daily data collected from January 1, 2013, to December 31, 2024 (12 years in total), consisting of 61 meteorological variables from the Korea Meteorological Administration, 1 national holiday indicator, and 1 electricity transaction volume column.
DOI: 10.17632/wvyj33kxtk.2
title: Long-term Electricity Demand Forecasting using THI-ConvNet

description: Electricity load forecasting is critical for ensuring the stability and efficiency of power supply systems, particularly during holidays when demand patterns tend to deviate from normal trends. However, most existing studies focus on short-term forecasts and lack the capability to effectively incorporate the irregularities caused by long-term holidays. To address this gap, we propose a novel deep learning-based forecasting model called the Temporal Holiday-Integrated (THI) model, which is the first to explicitly integrate both short-term and long-term holiday effects into electricity demand prediction. The model is trained using daily data collected from January 1, 2013, to December 31, 2024 (12 years in total), consisting of 61 meteorological variables from the Korea Meteorological Administration, 1 national holiday indicator, and 1 electricity transaction volume column.
DOI: 10.17632/bnc9r2vwj9.3
title: Datasets for Analyzing Riverine Bridges: A Hydrological Vulnerability Appraisal

description: The authors present two datasets designed to assess the hydrological vulnerability of riverine bridges under extreme weather conditions. These datasets aim to support infrastructure resilience studies by providing open, reproducible data for researchers and policymakers to enhance the analysis and management of flood-prone bridge systems.
See the latest version: DATASET_FINAL.
DOI: 10.17632/z42m8c43ny
title: Air Quality Monitoring at Universidad Iberoamericana, Mexico City: Ozone and Meteorological Data During the Rainy and Ozone Seasons (Mar–Nov 2024)

description: This dataset provides hourly air quality and meteorological measurements recorded from March 1, 2024, to November 30, 2024, at Universidad Iberoamericana, Mexico City (Geo-location: 19.372292, -99.263679). Each value represents the average of measurements taken within that hour. The data spans the rainy season (approximately May to October) and part of the ozone season (approximately February to May, with overlap into March–April), capturing air pollution and weather patterns in an urban, high-altitude environment.

The dataset includes the following parameters: 

Ozone (O₃) (ppb) – Hourly average ozone concentration. 

Temperature (°C) – Hourly average ambient temperature. 

Relative Humidity (%) – Hourly average humidity. 

Wind Direction (degrees) – Hourly average wind direction (0° = North). 

Wind Speed (m/s) – Hourly average wind speed. 

Air Pressure (hPa) – Hourly average atmospheric pressure. 

Accumulated Precipitation (mm) – Total precipitation accumulated within the hour. 

Solar Radiation (W/m²) – Hourly average solar radiation.

File Format: CSV (comma-separated)
Data Structure: Each row represents an hourly measurement with a timestamp formatted as DD-MM-YY HH:MM (e.g., 01-03-24 14:00), using 24-hour time.

Sensor Details & Data Quality:
Measurements were collected using low-cost air quality sensors deployed at the IBERO campus.

Applications: 
This dataset is suitable for air pollution analysis (e.g., ozone trends during the ozone season), meteorological research (e.g., precipitation and temperature patterns in the rainy season), and environmental modeling in Mexico City.
DOI: 10.17632/h2fwvzw4cb
title: Major and trace elements, along with Sr-Nd-K isotopic data of lavas from the Ryukyu, Mariana, and Manus subduction zones.

description: This dataset include: 
Table S1 Major and trace elements, along with Sr-Nd-K isotopic data of lavas from the Ryukyu, Mariana, and Manus subduction zones. 
Table S2 Endmember compositions used in modeling Sr–K isotopic heterogeneity in the sub-arc mantle.
DOI: 10.17632/z42m8c43ny.3
title: Air Quality Monitoring at Universidad Iberoamericana, Mexico City: Ozone and Meteorological Data During the Rainy and Ozone Seasons (Mar–Nov 2024)

description: This dataset provides hourly air quality and meteorological measurements recorded from March 1, 2024, to November 30, 2024, at Universidad Iberoamericana, Mexico City (Geo-location: 19.372292, -99.263679). Each value represents the average of measurements taken within that hour. The data spans the rainy season (approximately May to October) and part of the ozone season (approximately February to May, with overlap into March–April), capturing air pollution and weather patterns in an urban, high-altitude environment.

The dataset includes the following parameters: 

Ozone (O₃) (ppb) – Hourly average ozone concentration. 

Temperature (°C) – Hourly average ambient temperature. 

Relative Humidity (%) – Hourly average humidity. 

Wind Direction (degrees) – Hourly average wind direction (0° = North). 

Wind Speed (m/s) – Hourly average wind speed. 

Air Pressure (hPa) – Hourly average atmospheric pressure. 

Accumulated Precipitation (mm) – Total precipitation accumulated within the hour. 

Solar Radiation (W/m²) – Hourly average solar radiation.

File Format: CSV (comma-separated)
Data Structure: Each row represents an hourly measurement with a timestamp formatted as DD-MM-YY HH:MM (e.g., 01-03-24 14:00), using 24-hour time.

Sensor Details & Data Quality:
Measurements were collected using low-cost air quality sensors deployed at the IBERO campus.

Applications: 
This dataset is suitable for air pollution analysis (e.g., ozone trends during the ozone season), meteorological research (e.g., precipitation and temperature patterns in the rainy season), and environmental modeling in Mexico City.
DOI: 10.17632/h2fwvzw4cb.1
title: Major and trace elements, along with Sr-Nd-K isotopic data of lavas from the Ryukyu, Mariana, and Manus subduction zones.

description: This dataset include: 
Table S1 Major and trace elements, along with Sr-Nd-K isotopic data of lavas from the Ryukyu, Mariana, and Manus subduction zones. 
Table S2 Endmember compositions used in modeling Sr–K isotopic heterogeneity in the sub-arc mantle.
DOI: 10.17632/r55m6b4mcs
title: Tables and Results of the Neutrosophic Multicriteria FMEA for Environmental Risk Prioritization

description: This dataset contains the tables and results used in the article entitled “Enhancing Environmental Risk Assessment Through a Multicriteria Approach Integrated with Neutrosophic FMEA,” submitted to the journal Gestão & Produção.

The data includes:
- FMEA initial assessment matrices
- Neutrosophic evaluations
- Multicriteria prioritization results (IRAA)
- Risk ranking tables

All tables are compiled in a single Word document and are intended to support the transparency and reproducibility of the study. These data can be used for academic and research purposes and may serve as a basis for comparative analyses in similar industrial contexts.

Corresponding author: Marina Tedesco (UFRGS)
DOI: 10.17632/b8zwgn37kj
title: Improving Feed Efficiency with the EcoFeed® Index Reduces Greenhouse Gas Emissions in Dairy Cattle - Supporting data

description: Supporting information: Improving Feed Efficiency with the EcoFeed® Index Reduces Greenhouse Gas Emissions in Dairy Cattle
DOI: 10.17632/r55m6b4mcs.1
title: Tables and Results of the Neutrosophic Multicriteria FMEA for Environmental Risk Prioritization

description: This dataset contains the tables and results used in the article entitled “Enhancing Environmental Risk Assessment Through a Multicriteria Approach Integrated with Neutrosophic FMEA,” submitted to the journal Gestão & Produção.

The data includes:
- FMEA initial assessment matrices
- Neutrosophic evaluations
- Multicriteria prioritization results (IRAA)
- Risk ranking tables

All tables are compiled in a single Word document and are intended to support the transparency and reproducibility of the study. These data can be used for academic and research purposes and may serve as a basis for comparative analyses in similar industrial contexts.

Corresponding author: Marina Tedesco (UFRGS)
DOI: 10.17632/b8zwgn37kj.1
title: Improving Feed Efficiency with the EcoFeed® Index Reduces Greenhouse Gas Emissions in Dairy Cattle - Supporting data

description: Supporting information: Improving Feed Efficiency with the EcoFeed® Index Reduces Greenhouse Gas Emissions in Dairy Cattle
DOI: 10.17632/8784954hgn
title: A One-Health Genomic Analysis of Clinical, Animal and Environmental Enterobac-terales Reveals Cross-Sector Transmission of Antibiotic-Resistance Genes

description: This dataset accompanies a One Health genomics study investigating the multisectoral spread, resistome architecture, and evolutionary dynamics of carbapenemase-producing Enterobacterales (CPE) across clinical, veterinary, and environmental sectors in South Africa. The work involved 1,530 presumptive CRE isolates collected from humans, pigs, abattoir wastewater, and rivers, from which 122 carbapenemase-positive strains were confirmed. Whole-genome sequencing (WGS) using Oxford Nanopore MinIon was performed on 26 representative isolates, providing insights into resistance mechanisms, mobile genetic elements (MGEs), and population structure.

The dataset includes:

Annotated draft genome assemblies for 26 CPE isolates

Antibiotic resistance gene (ARG) profiles across 11 antimicrobial classes

IncL/M and IncX3 plasmid maps showing bla_OXA-48, bla_NDM, bla_VIM contexts

Maximum-likelihood phylogenies for Klebsiella pneumoniae, Proteus mirabilis, Serratia marcescens, and Providencia rettgeri

Multiplex PCR results confirming carbapenemase gene presence

Metadata including isolate ID, sample type, sector source, resistance profiles, and ARG counts

WGS data were processed using state-of-the-art tools including SPAdes for de novo assembly, Prokka for annotation, ResFinder/CARD for ARG detection, PlasmidFinder and MOB-suite for plasmid typing and reconstruction, and ISFinder/IntegronFinder for MGE mapping. Phylogenomic inference was performed with RAxML on core genome alignments produced via Roary.

The dataset underscores the ecological complexity of carbapenem resistance dissemination, the evolutionary convergence of ARGs across hosts and environments, and the urgent need for integrated surveillance. It enables comparative genomics, resistance tracking, plasmid evolution research, and development of diagnostic targets or control strategies.
DOI: 10.17632/8784954hgn.1
title: A One-Health Genomic Analysis of Clinical, Animal and Environmental Enterobac-terales Reveals Cross-Sector Transmission of Antibiotic-Resistance Genes

description: This dataset accompanies a One Health genomics study investigating the multisectoral spread, resistome architecture, and evolutionary dynamics of carbapenemase-producing Enterobacterales (CPE) across clinical, veterinary, and environmental sectors in South Africa. The work involved 1,530 presumptive CRE isolates collected from humans, pigs, abattoir wastewater, and rivers, from which 122 carbapenemase-positive strains were confirmed. Whole-genome sequencing (WGS) using Oxford Nanopore MinIon was performed on 26 representative isolates, providing insights into resistance mechanisms, mobile genetic elements (MGEs), and population structure.

The dataset includes:

Annotated draft genome assemblies for 26 CPE isolates

Antibiotic resistance gene (ARG) profiles across 11 antimicrobial classes

IncL/M and IncX3 plasmid maps showing bla_OXA-48, bla_NDM, bla_VIM contexts

Maximum-likelihood phylogenies for Klebsiella pneumoniae, Proteus mirabilis, Serratia marcescens, and Providencia rettgeri

Multiplex PCR results confirming carbapenemase gene presence

Metadata including isolate ID, sample type, sector source, resistance profiles, and ARG counts

WGS data were processed using state-of-the-art tools including SPAdes for de novo assembly, Prokka for annotation, ResFinder/CARD for ARG detection, PlasmidFinder and MOB-suite for plasmid typing and reconstruction, and ISFinder/IntegronFinder for MGE mapping. Phylogenomic inference was performed with RAxML on core genome alignments produced via Roary.

The dataset underscores the ecological complexity of carbapenem resistance dissemination, the evolutionary convergence of ARGs across hosts and environments, and the urgent need for integrated surveillance. It enables comparative genomics, resistance tracking, plasmid evolution research, and development of diagnostic targets or control strategies.
DOI: 10.17632/v58pb4dhkc
title: Metabolic shifts in murine inner ears mimicking erythrocytes and plasma reveal diagnostics and early predictors for age-related hearing loss

description: This study utilized C57BL/6J mice as an animal model to systematically investigate the metabolic changes in the peripheral circulatory system and inner ear tissues at different age stages (1, 2, 10, and 16 months), and their association with age-related hearing loss (ARHL). The experimental design employed a multi-omics combined analysis approach.
Sample Collection and Processing:
Subjects: A total of 80 C57BL/6J mice were divided into four groups based on age (1, 2, 10, and 16 months), with 20 mice per group.
Sample Types: Peripheral blood (isolating red blood cells and plasma) and inner ear tissues were collected.
Analytical Platforms and Methods:
1、Ultra-High-Performance Liquid Chromatography-Mass Spectrometry (UHPLC-MS): Non-targeted metabolomic analysis was conducted using a high-resolution mass spectrometry platform.
2、Stable Isotope Tracing: 13C6-glucose was used for metabolic flux analysis to track dynamic changes in key metabolic pathways, including glycolysis and the tricarboxylic acid cycle.
3、Targeted Metabolomics: Absolute quantification of amino acids was performed.
Raw Data Files: Red blood cell metabolomics mzXML files (n=80); plasma metabolomics mzXML files (n=80); inner ear metabolomics mzXML files (n=56).
DOI: 10.17632/5kgjnhzsmd
title: AI-Assisted Syllabification and Tone Annotation Datasets for South-South Nigerian Languages

description: This dataset includes lexical, syllabic, and tonal data from 25 South-South Nigerian languages. To achieve the data, phonotactic rules and tone patterns were semantically interpreted by GPT-4 to build syllabification and tone-labelling engines. The process followed a human-in-the-loop framework ensuring accurate rule execution across languages.

Contents:
1) Language_Profile_Wordlist.xlsx: Original language profile/template and wordlists
2) Language_Profile_Wordlist_Updated.xlsx: Updated (corrected/edited) profile/template and wordlists 
3) wordlist.xlsx: Swadesh lexical list (108 English words) used as the primary input for documenting the 25 languages.
4) syllabified_output_result.zip: Syllabified outputs (without corrected/edited profile and wordlists) annotated without human-in-the-loop validation labels across 25 languages.
5) syllabified_output_result_with_HILV.zip: Syllabified outputs (without corrected/edited profile and wordlists) annotated with human-in-the-loop validation labels across 25 languages.
6) syllabified_output_result_updated.zip: Updated syllabified outputs (with corrected/edited profile and wordlists) per language.
7) structure_transformed_updated.zip: Syllabified outputs further transformed into syllable structure representations (e.g., V-CV, N-CVV) with a transformed syllable structure column (N_CV Structure) 
8) tone_labelling_output_result.zip: Wordlists with auto-generated tone labels without human-in-the-loop validation.
9) tone_labelling_output_result_updated.zip: Wordlists with auto-generated tone labels with human-in-the-loop validation (edited/corrected tone labels).

Applications:
1) Phonological typology: Contents 3, 4, 5, 6, and contents 7, 8, provide syllabified and tone-annotated wordlists across 25 Nigerian languages, enabling comparative analysis of phonotactic constraints, syllable structures (e.g., CV, CVV, N-CVC), and tonal systems. 
2) Cross-linguistic NLP development: By offering consistent syllabification and tone annotations, the dataset would facilitate the design and evaluation of NLP tools that can generalize across typologically diverse languages. Use cases include multilingual grapheme-to-phoneme converters, syllable-aware machine translation models, and pronunciation-aware text-to-speech systems.
3) Low-resource language modeling: The dataset could serve as a valuable resource for training and evaluating AI models in low-resource settings. 
4) Tonal morphology and suprasegmental analysis: The tone-labelled column in the dataset allow for the study of tonal morphology, such as tone sandhi, tone disambiguation, and morphotonemic alternation. 

Format:
All files are provided in .xlsx and .zip formats for ease of integration into language modeling pipelines.
DOI: 10.17632/v58pb4dhkc.1
title: Metabolic shifts in murine inner ears mimicking erythrocytes and plasma reveal diagnostics and early predictors for age-related hearing loss

description: This study utilized C57BL/6J mice as an animal model to systematically investigate the metabolic changes in the peripheral circulatory system and inner ear tissues at different age stages (1, 2, 10, and 16 months), and their association with age-related hearing loss (ARHL). The experimental design employed a multi-omics combined analysis approach.
Sample Collection and Processing:
Subjects: A total of 80 C57BL/6J mice were divided into four groups based on age (1, 2, 10, and 16 months), with 20 mice per group.
Sample Types: Peripheral blood (isolating red blood cells and plasma) and inner ear tissues were collected.
Analytical Platforms and Methods:
1、Ultra-High-Performance Liquid Chromatography-Mass Spectrometry (UHPLC-MS): Non-targeted metabolomic analysis was conducted using a high-resolution mass spectrometry platform.
2、Stable Isotope Tracing: 13C6-glucose was used for metabolic flux analysis to track dynamic changes in key metabolic pathways, including glycolysis and the tricarboxylic acid cycle.
3、Targeted Metabolomics: Absolute quantification of amino acids was performed.
Raw Data Files: Red blood cell metabolomics mzXML files (n=80); plasma metabolomics mzXML files (n=80); inner ear metabolomics mzXML files (n=56).
DOI: 10.17632/5kgjnhzsmd.1
title: AI-Assisted Syllabification and Tone Annotation Datasets for South-South Nigerian Languages

description: This dataset includes lexical, syllabic, and tonal data from 25 South-South Nigerian languages. To achieve the data, phonotactic rules and tone patterns were semantically interpreted by GPT-4 to build syllabification and tone-labelling engines. The process followed a human-in-the-loop framework ensuring accurate rule execution across languages.

Contents:
1) Language_Profile_Wordlist.xlsx: Original language profile/template and wordlists
2) Language_Profile_Wordlist_Updated.xlsx: Updated (corrected/edited) profile/template and wordlists 
3) wordlist.xlsx: Swadesh lexical list (108 English words) used as the primary input for documenting the 25 languages.
4) syllabified_output_result.zip: Syllabified outputs (without corrected/edited profile and wordlists) annotated without human-in-the-loop validation labels across 25 languages.
5) syllabified_output_result_with_HILV.zip: Syllabified outputs (without corrected/edited profile and wordlists) annotated with human-in-the-loop validation labels across 25 languages.
6) syllabified_output_result_updated.zip: Updated syllabified outputs (with corrected/edited profile and wordlists) per language.
7) structure_transformed_updated.zip: Syllabified outputs further transformed into syllable structure representations (e.g., V-CV, N-CVV) with a transformed syllable structure column (N_CV Structure) 
8) tone_labelling_output_result.zip: Wordlists with auto-generated tone labels without human-in-the-loop validation.
9) tone_labelling_output_result_updated.zip: Wordlists with auto-generated tone labels with human-in-the-loop validation (edited/corrected tone labels).

Applications:
1) Phonological typology: Contents 3, 4, 5, 6, and contents 7, 8, provide syllabified and tone-annotated wordlists across 25 Nigerian languages, enabling comparative analysis of phonotactic constraints, syllable structures (e.g., CV, CVV, N-CVC), and tonal systems. 
2) Cross-linguistic NLP development: By offering consistent syllabification and tone annotations, the dataset would facilitate the design and evaluation of NLP tools that can generalize across typologically diverse languages. Use cases include multilingual grapheme-to-phoneme converters, syllable-aware machine translation models, and pronunciation-aware text-to-speech systems.
3) Low-resource language modeling: The dataset could serve as a valuable resource for training and evaluating AI models in low-resource settings. 
4) Tonal morphology and suprasegmental analysis: The tone-labelled column in the dataset allow for the study of tonal morphology, such as tone sandhi, tone disambiguation, and morphotonemic alternation. 

Format:
All files are provided in .xlsx and .zip formats for ease of integration into language modeling pipelines.
DOI: 10.15468/dl.ktswzh
title: Occurrence Download

description: A dataset containing 475 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Inventario de la fauna arrecifal asociada al ecosistema de Pocillopora en el Pacífico Tropical Mexicano",
 "Geometry POLYGON((-100.16080 16.71020,-99.53408 16.71020,-99.53408 16.96078,-100.16080 16.96078,-100.16080 16.71020))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 475 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067958-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2ckvcp2rh7
title: Data for "Sb(V) incorporation into stable residual fractions during schwertmannite transformation: Contrasting solid-phase partitioning mechanism with As(V)"

description: Raw data for all figures in the manuscript as "Sb(V) incorporation into stable residual fractions during schwertmannite transformation: Contrasting solid-phase partitioning mechanism with As(V)"
DOI: 10.17632/2ckvcp2rh7.1
title: Data for "Sb(V) incorporation into stable residual fractions during schwertmannite transformation: Contrasting solid-phase partitioning mechanism with As(V)"

description: Raw data for all figures in the manuscript as "Sb(V) incorporation into stable residual fractions during schwertmannite transformation: Contrasting solid-phase partitioning mechanism with As(V)"
DOI: 10.17632/ykzdzxxf2j
title: Bachelor students data (6 semester GPA, gender, high school, and town)

description: This dataset contains 16,787 bachelor students from an anonymous Indonesian university's higher education system. The dataset includes time-series academic performance data over six semesters. Each student's record also contain textual attributes such as gender, city of origin, and high school name. University name, student name, student's origin town name, or student's high school origin name are kept anonymous to protect their privacy.