cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/7z5b522x3f.2
title: Tokopedia E Commerce Review In Indonesia

description: This dataset was obtained through web scraping using Python from customer reviews of a motorcycle oil product on Tokopedia in Indonesia, preserved in their original form, including typos, abbreviations, and informal language, to maintain linguistic authenticity. The research tests the hypothesis that reviews with overly polished language, generic praise lacking product-specific details, and perfect punctuation are more likely to be fake, whereas reviews containing detailed product references, informal expressions, spelling mistakes, and emotional tone are more likely to be genuine. The analysis shows that a small number of reviews appear potentially fake, typically consisting of short, generic praise unrelated to the product, while most reviews seem authentic and contain specific complaints such as unusual smell, abnormal oil thickness, leaking packaging, missing barcodes, and suspicions of counterfeit goods. These findings suggest that the majority of negative feedback likely reflects actual quality issues or the circulation of fake products, and can be used by e-commerce platforms to prioritize relevant reviews and develop linguistic-based fake review detection systems.
DOI: 10.15468/dl.f27pe4
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cephalopoda)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((150 40,160 40,160 50,150 50,150 40))"
 ]
}

 The dataset includes 11 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014088-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/dwky3hnt6j.3
title: Raw data and MATLAB codes for Xu et al., 2025, GRL

description: This dataset includes the raw data, the compilation of published data, and the MATLAB codes of the Monte Carlo model used in Xu et al., 2025, GRL.
DOI: 10.17632/z55db54dj7
title: Supplementary Tables

description: Supplementary TableS1-S5
DOI: 10.17632/z55db54dj7.1
title: Supplementary Tables

description: Supplementary TableS1-S5
DOI: 10.15468/dl.fxe36j
title: Occurrence Download

description: A dataset containing 47 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Solenogastres)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((140 -40,150 -40,150 -30,140 -30,140 -40))"
 ]
}

 The dataset includes 47 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014092-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nkvc9x
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cephalopoda)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((160 40,170 40,170 50,160 50,160 40))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014090-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/rmtxjz6m64
title: The influence of epicardial adipose tissue on cognitive function and survival prognosis in patients with non-valvular atrial fibrillation complicated with ischaemic stroke

description: This dataset includes clinical and experimental data of patients with atrial fibrillation and stroke from March 2018 to May 2025.
DOI: 10.17632/rmtxjz6m64.1
title: The influence of epicardial adipose tissue on cognitive function and survival prognosis in patients with non-valvular atrial fibrillation complicated with ischaemic stroke

description: This dataset includes clinical and experimental data of patients with atrial fibrillation and stroke from March 2018 to May 2025.
DOI: 10.17632/pvsv534ccg
title: Eggplant Leaf Disease Classification Dataset

description: Dataset Overview:
It contains 2991 high-resolution images of eggplant leaves.
Images were collected from the Changao, Paragram, Ashulia, Dhaka, and Narsingdi regions of Bangladesh.
Data was gathered between October 20 and November 2, 2024, over a period of 13 days.
Classes:
Cercospora: 628 images
Curl: 284 images
Flea Beetles: 84 images
Hadda Beetles: 530 images
Healthy: 188 images
LeafhopperJassids: 38 images
Magnesium Deficiency: 50 images
Phomposist Blast: 218 images
TMV (Tobacco Mosaic Virus): 356 images
Tobacco Caterpillar: 452 images
Verticillium Wilt: 163 images
Purpose:
Supports the advancement of automated agricultural disease detection systems.
It aims to assist in the early detection and management of eggplant leaf diseases.
Enables the development of reliable diagnostic tools using machine learning and image processing techniques.
Promotes better crop management, increased yield, and reduced pesticide use, contributing to sustainable agricultural practices.
Serves as a resource for developing and evaluating image-based disease recognition models and deep learning applications in agriculture.
DOI: 10.17632/pvsv534ccg.3
title: Eggplant Leaf Disease Classification Dataset

description: Dataset Overview:
It contains 2991 high-resolution images of eggplant leaves.
Images were collected from the Changao, Paragram, Ashulia, Dhaka, and Narsingdi regions of Bangladesh.
Data was gathered between October 20 and November 2, 2024, over a period of 13 days.
Classes:
Cercospora: 628 images
Curl: 284 images
Flea Beetles: 84 images
Hadda Beetles: 530 images
Healthy: 188 images
LeafhopperJassids: 38 images
Magnesium Deficiency: 50 images
Phomposist Blast: 218 images
TMV (Tobacco Mosaic Virus): 356 images
Tobacco Caterpillar: 452 images
Verticillium Wilt: 163 images
Purpose:
Supports the advancement of automated agricultural disease detection systems.
It aims to assist in the early detection and management of eggplant leaf diseases.
Enables the development of reliable diagnostic tools using machine learning and image processing techniques.
Promotes better crop management, increased yield, and reduced pesticide use, contributing to sustainable agricultural practices.
Serves as a resource for developing and evaluating image-based disease recognition models and deep learning applications in agriculture.
DOI: 10.17632/k635fnzw3s
title: Enhanced Antimicrobial and Wound Healing Properties for Ni-Zn-Co Ferrite Nanoparticles

description: Raw data of XPS of Zn0.2Co0.8-xNixFe2O4 (x = 0.2, 0.4, 0.6, and 0.8) nanoparticles , prepared through the sol-gel auto-combustion technique.
DOI: 10.17632/k635fnzw3s.1
title: Enhanced Antimicrobial and Wound Healing Properties for Ni-Zn-Co Ferrite Nanoparticles

description: Raw data of XPS of Zn0.2Co0.8-xNixFe2O4 (x = 0.2, 0.4, 0.6, and 0.8) nanoparticles , prepared through the sol-gel auto-combustion technique.
DOI: 10.15468/dl.yqef2q
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Solenogastres)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((130 -40,140 -40,140 -30,130 -30,130 -40))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014093-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/zcshgj7kyy.2
title: Pb(II) adsorption by KOH-modified rice straw biochar from battery wastewater

description: This data is for FTIR spectroscopy, RSM modelling, the influence of factors on adsorption, isotherm, kinetic and thermodynamic modelling, and all tables and figures. FTIR spectra derived from FTIR-RSB (pristine biochar), KRSB (KOH-modified biochar) and KRSB-Pb (modified biochar after Pb adsorption). The FTIR spectra revealed oxygen-containing functional groups (-OH, -COO⁻, C–O–C) that facilitated complexation and precipitation. Five factors (Dose, initial Pb(II) concentration, contact time, temperature, and pH) were used in RSM modeling and optimisation. The resulting model was adequate with high R2 and low p-value. The adsorption followed dual Langmuir-Temkin isotherm models and pseudo-second-order kinetic model. The Pb(II) adsorption was endothermic with negative gibb's free energy.
DOI: 10.17632/zzvb3bvm7c
title: LaborUnionReporting (LMs forms - US DOL)

description: This repository contains a Stata workflow for processing, cleaning, and merging LM (Labor Management) forms filed by labor unions, specifically LM-2, LM-3, LM-4, and LM-5 forms from the U.S. Department of Labor. Please, cite the following paper if you use this code and/or the cleaned data:
Carlos F. Avenancio-León, Alessio Piccolo, Roberto Pinto, Resilience in collective bargaining, Journal of Financial Economics, Volume 173, 2025.
DOI: 10.17632/zzvb3bvm7c.2
title: LaborUnionReporting (LMs forms - US DOL)

description: This repository contains a Stata workflow for processing, cleaning, and merging LM (Labor Management) forms filed by labor unions, specifically LM-2, LM-3, LM-4, and LM-5 forms from the U.S. Department of Labor. Please, cite the following paper if you use this code and/or the cleaned data:
Carlos F. Avenancio-León, Alessio Piccolo, Roberto Pinto, Resilience in collective bargaining, Journal of Financial Economics, Volume 173, 2025.
DOI: 10.17632/wmfd4p3z32
title: Genuine and Fake Facial Emotion Dataset (GFFD-2025)

description: The Dual-Task Emotion–Authenticity Facial Expression Dataset (GFFD-2025) is a carefully curated collection of facial images created to support research in emotion recognition and authenticity detection. Unlike traditional emotion datasets, it focuses not only on identifying which emotion a person expresses but also on whether the expression is genuine or acted, contributing to studies in artificial intelligence, affective computing, and human–computer interaction.

A total of 2,224 raw facial images were initially collected from voluntary participants. After quality assessment and manual verification, a subset was refined and curated for further research. The dataset repository includes approximately 1,900 raw facial images and around 1,500 cropped and augmented images, representing the cleaned and extended version of the original collection.

The dataset covers seven primary emotions: Angry, Disgust, Fear, Happy, Neutral, Sad, and Surprise; each subdivided into two authenticity categories: Genuine and Fake (Acted). Images were captured under controlled indoor conditions to ensure consistent lighting, neutral backgrounds, and stable face positioning. Genuine expressions were elicited via emotional recall or audiovisual stimuli, while fake expressions were intentionally acted. All data collection sessions were supervised by a certified psychologist to ensure ethical compliance and emotional validity.

Images were reviewed and labeled following micro-expression research principles, considering subtle cues such as eye involvement, facial symmetry, muscle tension, and temporal dynamics to distinguish genuine from acted expressions. Curated images were standardized to 224×224 pixels for compatibility with common deep learning frameworks.

To enhance dataset diversity and model robustness, images underwent preprocessing and augmentation, including rotation (±30°), width and height shifts (0.2), shear (0.15), zoom (0.2), horizontal flipping, random brightness and contrast adjustments, and normalization to the [0,1] range.

This dataset offers a practical benchmark for research in emotion recognition, authenticity detection, human behavior analysis, multitask learning, and explainable AI, enabling development of models sensitive to subtle psychological authenticity cues.

Data collection and labeling were conducted at Daffodil International University, Dhaka, Bangladesh, under strict ethical guidelines with informed consent from all participants. Sessions were supervised to ensure participant comfort and authenticity.

Supervisor:
Md. Mizanur Rahman
Lecturer, Department of Computer Science and Engineering
Daffodil International University, Dhaka, Bangladesh
Email: mizanurrahman.cse@diu.edu.bd

Data Collectors:
Sarah Tasnim Diya (Email: diya15-5423@diu.edu.bd)
Most. Jannatul Ferdos (Email: ferdos15-5453@diu.edu.bd)
Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.
DOI: 10.17632/wmfd4p3z32.1
title: Genuine and Fake Facial Emotion Dataset (GFFD-2025)

description: The Dual-Task Emotion–Authenticity Facial Expression Dataset (GFFD-2025) is a carefully curated collection of facial images created to support research in emotion recognition and authenticity detection. Unlike traditional emotion datasets, it focuses not only on identifying which emotion a person expresses but also on whether the expression is genuine or acted, contributing to studies in artificial intelligence, affective computing, and human–computer interaction.

A total of 2,224 raw facial images were initially collected from voluntary participants. After quality assessment and manual verification, a subset was refined and curated for further research. The dataset repository includes approximately 1,900 raw facial images and around 1,500 cropped and augmented images, representing the cleaned and extended version of the original collection.

The dataset covers seven primary emotions: Angry, Disgust, Fear, Happy, Neutral, Sad, and Surprise; each subdivided into two authenticity categories: Genuine and Fake (Acted). Images were captured under controlled indoor conditions to ensure consistent lighting, neutral backgrounds, and stable face positioning. Genuine expressions were elicited via emotional recall or audiovisual stimuli, while fake expressions were intentionally acted. All data collection sessions were supervised by a certified psychologist to ensure ethical compliance and emotional validity.

Images were reviewed and labeled following micro-expression research principles, considering subtle cues such as eye involvement, facial symmetry, muscle tension, and temporal dynamics to distinguish genuine from acted expressions. Curated images were standardized to 224×224 pixels for compatibility with common deep learning frameworks.

To enhance dataset diversity and model robustness, images underwent preprocessing and augmentation, including rotation (±30°), width and height shifts (0.2), shear (0.15), zoom (0.2), horizontal flipping, random brightness and contrast adjustments, and normalization to the [0,1] range.

This dataset offers a practical benchmark for research in emotion recognition, authenticity detection, human behavior analysis, multitask learning, and explainable AI, enabling development of models sensitive to subtle psychological authenticity cues.

Data collection and labeling were conducted at Daffodil International University, Dhaka, Bangladesh, under strict ethical guidelines with informed consent from all participants. Sessions were supervised to ensure participant comfort and authenticity.

Supervisor:
Md. Mizanur Rahman
Lecturer, Department of Computer Science and Engineering
Daffodil International University, Dhaka, Bangladesh
Email: mizanurrahman.cse@diu.edu.bd

Data Collectors:
Sarah Tasnim Diya (Email: diya15-5423@diu.edu.bd)
Most. Jannatul Ferdos (Email: ferdos15-5453@diu.edu.bd)
Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.
DOI: 10.17632/8svhn8mt38
title: Metabolomics analysis of dorsal root ganglion in rats of painful diabetic neuropathy

description: DRG samples (n = 5 per group) were analyzed using mass spectrometry in both positive and negative ion modes to identify metabolic alterations. Thirty milligrams of DRG tissue were placed in 2-ml centrifuge tubes for metabolite extraction. A total of 900 μl of extraction solution (methanol: water = 4 : 1) was added to each sample. The DRG tissues were pulverized using a cold tissue grinder for 6 minutes (−10°C, 50 Hz) to ensure thorough homogenization. Following this, the samples underwent low-temperature ultrasonic treatment for 30 minutes (5°C, 40 kHz) to enhance metabolite extraction. The mixtures were left to stand at −20°C for 30 minutes and then centrifuged at 12,000 rpm for 15 minutes at 4°C. The resulting supernatants were transferred into sample vials with insert tubes for further analysis.
Metabolomic profiling was conducted using a Q-Exactive HF mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA), as described in previous methodologies . Initial data-dependent acquisition was performed with a single full-scan at a resolution of 60,000, targeting hydrophilic metabolites with mass-to-charge ratios ranging from 60 to 900. Lipid profiling was subsequently performed within an extended mass-to-charge ratio range of 300 to 1,200. For further structural elucidation, 10 consecutive tandem mass spectrometry scans were conducted in high-energy collision dissociation mode.
Stringent quality control measures were implemented throughout the metabolomic study to ensure the accuracy and reliability of the data generated.
DOI: 10.17632/8svhn8mt38.1
title: Metabolomics analysis of dorsal root ganglion in rats of painful diabetic neuropathy

description: DRG samples (n = 5 per group) were analyzed using mass spectrometry in both positive and negative ion modes to identify metabolic alterations. Thirty milligrams of DRG tissue were placed in 2-ml centrifuge tubes for metabolite extraction. A total of 900 μl of extraction solution (methanol: water = 4 : 1) was added to each sample. The DRG tissues were pulverized using a cold tissue grinder for 6 minutes (−10°C, 50 Hz) to ensure thorough homogenization. Following this, the samples underwent low-temperature ultrasonic treatment for 30 minutes (5°C, 40 kHz) to enhance metabolite extraction. The mixtures were left to stand at −20°C for 30 minutes and then centrifuged at 12,000 rpm for 15 minutes at 4°C. The resulting supernatants were transferred into sample vials with insert tubes for further analysis.
Metabolomic profiling was conducted using a Q-Exactive HF mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA), as described in previous methodologies . Initial data-dependent acquisition was performed with a single full-scan at a resolution of 60,000, targeting hydrophilic metabolites with mass-to-charge ratios ranging from 60 to 900. Lipid profiling was subsequently performed within an extended mass-to-charge ratio range of 300 to 1,200. For further structural elucidation, 10 consecutive tandem mass spectrometry scans were conducted in high-energy collision dissociation mode.
Stringent quality control measures were implemented throughout the metabolomic study to ensure the accuracy and reliability of the data generated.
DOI: 10.17632/jrzs2zwd76.1
title: Enzyme Kinetics Reveal Biochar-Driven Improvements in Soil Multifunctionality in Arid Soils: Insights from Pot Experiments and Meta-Analysis (Meta-analysis Research Data)

description: The search focused on pot experiments examining biochar’s impact on the chemical and biological properties of grey desert and aeolian sandy soils.
DOI: 10.15468/dl.3nvu4j
title: Occurrence Download

description: A dataset containing 86 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Fremontodendron mexicanum)",
 "StateProvince is one of (California, Mexico Northwest)",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 86 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014094-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6096/msec.laos.4
title: Raingauge network data, Houay Pano, Laos

description: <b>If using this dataset, please cite Ribolzi et al., 2017 <a href="https://doi.org/10.1038/s41598-017-04385-2" target="_blank">https://doi.org/10.1038/s41598-017-04385-2</a></b><br>
Daily rainfall (mm) data from the Houay Pano catchment manual rain gauges network (Laos)
DOI: 10.15468/dl.t9xdct
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Solenogastres)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((120 -40,130 -40,130 -30,120 -30,120 -40))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014095-251009101135966/datasets/export for details.
DOI: 10.60525/04teye511/3meujd/c1tytn
title: ecim_sensor_sambat_2025-2.csv

description: :unav
DOI: 10.25976/3dtf-pf61
title: WaterWealth Chilliwack Climate Monitoring - temperature loggers

description: "Our goal is to identify tributaries to the Chilliwack River that have natural advantages against climate change for salmonid spawning and rearing. 

Pearson Ecological helped produce the initial stream list and has provided advice along the way. Emil Anderson Contracting, Valley Tank and Container, Gerry Enns Contracting have provided material and labour support. People of the River Referrals Office helped ensure that the work is carried out in a manner respectful of its place on Ts'elxwéyeqw Tribe territory. "
description: HOBO Pendant MX2201 temperature loggers are used to record water temperature at hourly intervals. Loggers are placed inside ~10 cm x 20 cm x 20 cm hollow concrete blocks. Frequency of data download varies with site accessibility and volunteer availability.
description: Data is offloaded from loggers using Onset HOBOmobile (older data) and HOBOconnect app.
DOI: 10.60525/04teye511/3meujd
title: Conjunto de datos: ECIM CTD SAMBAT 2025

description: Este conjunto de datos contiene registros de sensores CTD de la estación ECIM, utilizados para caracterizar parámetros físico-químicos en la columna de agua, incluyendo presión, temperatura, salinidad, oxígeno disuelto, pH, turbidez y fluorescencia.
DOI: 10.15468/dl.pgvkmw
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Draba athoa)"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014096-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nt9xwg
title: Occurrence Download

description: A dataset containing 1143 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Albizia glaberrima)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1143 records from 102 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014097-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.