cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/j4s25jt8v7.2
title: Is Bikeability Cycle Training an Effective Active Travel Behaviour Change Intervention? Confirmatory Evidence from Classroom-Based Surveys of UK Schoolchildren

description: These files relate to the paper of the same title and comprise the following: raw data files downloaded from the JISC survey platform, for each of nine Bikeability training providers who collected data in their local authority areas; a PDF of the survey that participants completed to provide those data; an Excel file containing a cleaned dataset, from which 'Other' responses to the Year Group item have been removed; a PDF of the SPSS output file from the data analysis process; a PowerPoint file that illustrates the geographical spread and diversity of the data location sites; and the summaries of (incomplete) demographic information procured from schools by Bikeability training providers.
DOI: 10.17632/r9fff9zyj4
title: Worldwide Debris-Flow Dataset and Pareto-Poisson Simulation Code

description: S1. A global debris flow dataset, including parameters such as flow discharge, density, velocity, and flow depth, among others.
S2. Pareto-Poisson simulation code for debris flow surges (Matlab version).
DOI: 10.17632/r9fff9zyj4.1
title: Worldwide Debris-Flow Dataset and Pareto-Poisson Simulation Code

description: S1. A global debris flow dataset, including parameters such as flow discharge, density, velocity, and flow depth, among others.
S2. Pareto-Poisson simulation code for debris flow surges (Matlab version).
DOI: 10.17632/7h34j7xmks
title: Industrial Policy and Urban Children’s Human Capital Accumulation: Evidence from China’s “Third Front Construction”

description: This replication package provides all the publicly available data, code, and instructions required to reproduce the main empirical results of the above-mentioned research paper. The package is designed to facilitate transparency and enable independent verification of all statistical findings reported in the study.
DOI: 10.5281/zenodo.17633020
title: Qualitative Insights from Gamification Experts and Digital Strategists on Design, Ethics, and Business Value in the Metaverse
DOI: 10.17632/7h34j7xmks.1
title: Industrial Policy and Urban Children’s Human Capital Accumulation: Evidence from China’s “Third Front Construction”

description: This replication package provides all the publicly available data, code, and instructions required to reproduce the main empirical results of the above-mentioned research paper. The package is designed to facilitate transparency and enable independent verification of all statistical findings reported in the study.
DOI: 10.5281/zenodo.17633019
title: Qualitative Insights from Gamification Experts and Digital Strategists on Design, Ethics, and Business Value in the Metaverse
DOI: 10.17632/y47hfb58yv
title: Harnessing Inactive Molybdenum Species in Ill-Defined Catalyst to Work in Propylene Metathesis by Propane Pretreatment

description: Research and supporting data refers to experimetal and DFT results
DOI: 10.5281/zenodo.17183594
title: On chip digital to analog converters for ultrafast signals using spintronic terahertz emitters

description: Data for THz DAC:

This includes the following folders:-

1) 3_bit_DAC : It contains raw electrical response from 3-bit DAC device and the calculation of its corresponding DNL and INL. It is in the form of a jupyter lab notebook "DNL_INL_analysis_3bit.ipynb" which requires the file "Raw_3bit.csv" and generates a file "DNL_INL_3.csv".

2) 4_bit_DAC : It contains raw electrical response from 4-bit DAC device and the calculation of its corresponding DNL and INL. It is in the form of a jupyter lab notebook "DNL_INL_analysis_4bit.ipynb" which requires the file "Raw_4bit.csv" and generates a file "DNL_INL_4.csv".

3) Preliminary_3_bit_FM : It contains raw data for electrical response from individual Ferromagnetic stripes and corresponding thin film hysteresis from MOKE measurement.

4) Preliminary_4_bit_FMstripes : It contains raw data for electrical response from individual arrays of STE stripes of different widths with error analysis and the hysteresis of STE layer thin film from MOKE measurement.
DOI: 10.5281/zenodo.17183595
title: On chip digital to analog converters for ultrafast signals using spintronic terahertz emitters

description: Data for THz DAC:

This includes the following folders:-

1) 3_bit_DAC : It contains raw electrical response from 3-bit DAC device and the calculation of its corresponding DNL and INL. It is in the form of a jupyter lab notebook "DNL_INL_analysis_3bit.ipynb" which requires the file "Raw_3bit.csv" and generates a file "DNL_INL_3.csv".

2) 4_bit_DAC : It contains raw electrical response from 4-bit DAC device and the calculation of its corresponding DNL and INL. It is in the form of a jupyter lab notebook "DNL_INL_analysis_4bit.ipynb" which requires the file "Raw_4bit.csv" and generates a file "DNL_INL_4.csv".

3) Preliminary_3_bit_FM : It contains raw data for electrical response from individual Ferromagnetic stripes and corresponding thin film hysteresis from MOKE measurement.

4) Preliminary_4_bit_FMstripes : It contains raw data for electrical response from individual arrays of STE stripes of different widths with error analysis and the hysteresis of STE layer thin film from MOKE measurement.
DOI: 10.17632/y47hfb58yv.2
title: Harnessing Inactive Molybdenum Species in Ill-Defined Catalyst to Work in Propylene Metathesis by Propane Pretreatment

description: Research and supporting data refers to experimetal and DFT results
DOI: 10.17632/b4ny54tp4y
title: Dataset: Automated Quality Assessment of Online Medical Science Popularization Videos - Dry Eye - TikTok Chinese

description: This repository contains online collected video files for the readers of “Benchmark Evaluation of Video Large Language Models in Quality Assessment of Science Popularization Videos for Dry Eye.”
DOI: 10.17632/b4ny54tp4y.1
title: Dataset: Automated Quality Assessment of Online Medical Science Popularization Videos - Dry Eye - TikTok Chinese

description: This repository contains online collected video files for the readers of “Benchmark Evaluation of Video Large Language Models in Quality Assessment of Science Popularization Videos for Dry Eye.”
DOI: 10.17632/2jmccmzn5b
title: Data from elderly women and photobiomodulation

description: All the complete data used in the study, in editable table format, are available for consultation.
DOI: 10.17632/2jmccmzn5b.1
title: Data from elderly women and photobiomodulation

description: All the complete data used in the study, in editable table format, are available for consultation.
DOI: 10.17632/jsbmtk8hty
title: Comprehensive Dengue Hematology and Clinical Dataset from Bangladesh for Machine Learning and Diagnostic Research

description: Dengue fever is a serious public health issue in Bangladesh. In 2025, more than 83,000 hospitalized dengue cases and over 300 deaths have been reported, with outbreaks worsening in August and expected to peak in November without interventions [1]. This dataset, with demographic and blood test data, supports dengue research, planning and outbreaks prediction. Data were obtained from a total of 1,329 Dengue patients across several medical institutions in Dhaka, Bangladesh, including Shaheed Suhrawardy Medical College and Hospital and Dhaka Medical College Hospital. The data collection period extended from July 2025 to November 2025, during which patient confidentiality was strictly maintained and all ethical guidelines were rigorously followed. For each patient, Biochemical and Hematology profiles were systematically recorded to assess the impact of Dengue on liver function and blood-related parameters. The dataset includes Gender, Age, Dengue NS1 test result, White Blood Cell Count (WBC), Platelet Count (PLT), Red Blood Cell Count (RBC), Hematocrit (HCT), Lymphocyte percentage, Liver function indices (ALT and AST), and Neutrophil percentage. PLT and WBC were converted and presented in thousand units (×10³/µL or K/µL). Percentage based variables such as HCT%, Lymph%, and Neut% were represented in (%) units. The RBC was presented in million units (m/µL). Biochemical markers such as ALT and AST were presented in the standard international unit U/L (Units per Liter). This dataset is important for analyzing Hematological changes in dengue patients. The main goal is to apply Machine Learning to classify patients as dengue positive or negative (Yes/No) using Hematological values. This approach enables early detection and better care.


Information Included in the Dataset 
Demographics:
Gender: Male or Female 
Age: Patient’s Age 
Diagnostic Results: Dengue NS1 (Positive/Negative) - Class label

Hematological Parameters:
1. Platelet Count (PLT) [K/µL] : Helps in blood clotting.
2. White Blood Cell Count (WBC) [K/µL] : Defends the body against infections.
3. Hematocrit (HCT %): Measures red blood cell ratio, useful for detecting blood thickness.
4. Red Blood Cell Count (RBC) [m/µL] : Carries oxygen throughout the body.
5. Lymphocyte Percentage (Lymph %): A type of WBC, important for fighting viral infections.
6. Neutrophil Percentage (Neu %): A type of WBC, mainly fights bacterial infections.
7. Dengue NS1 (Antigen Test) : Detects Dengue Virus antigen in blood.

Biochemical Markers:
Alanine Aminotransferase (ALT) [U/L] and Aspartate Aminotransferase (AST) [U/L] : Liver enzymes, used to assess liver function.

Dataset Overview 
Dataset type: Primary data 
File Type: CSV
Total Records (Rows): 1,329 (each representing an individual patient case) 
Number of Variables (Columns): 12 (Demographic, Diagnostic, Hematological and Biochemical Features)

Reference:
[1] DGHS Dengue Dashboard- https://dashboard.dghs.gov.bd/pages/heoc_dengue_v1.php
DOI: 10.17632/jsbmtk8hty.4
title: Comprehensive Dengue Hematology and Clinical Dataset from Bangladesh for Machine Learning and Diagnostic Research

description: Dengue fever is a serious public health issue in Bangladesh. In 2025, more than 83,000 hospitalized dengue cases and over 300 deaths have been reported, with outbreaks worsening in August and expected to peak in November without interventions [1]. This dataset, with demographic and blood test data, supports dengue research, planning and outbreaks prediction. Data were obtained from a total of 1,329 Dengue patients across several medical institutions in Dhaka, Bangladesh, including Shaheed Suhrawardy Medical College and Hospital and Dhaka Medical College Hospital. The data collection period extended from July 2025 to November 2025, during which patient confidentiality was strictly maintained and all ethical guidelines were rigorously followed. For each patient, Biochemical and Hematology profiles were systematically recorded to assess the impact of Dengue on liver function and blood-related parameters. The dataset includes Gender, Age, Dengue NS1 test result, White Blood Cell Count (WBC), Platelet Count (PLT), Red Blood Cell Count (RBC), Hematocrit (HCT), Lymphocyte percentage, Liver function indices (ALT and AST), and Neutrophil percentage. PLT and WBC were converted and presented in thousand units (×10³/µL or K/µL). Percentage based variables such as HCT%, Lymph%, and Neut% were represented in (%) units. The RBC was presented in million units (m/µL). Biochemical markers such as ALT and AST were presented in the standard international unit U/L (Units per Liter). This dataset is important for analyzing Hematological changes in dengue patients. The main goal is to apply Machine Learning to classify patients as dengue positive or negative (Yes/No) using Hematological values. This approach enables early detection and better care.


Information Included in the Dataset 
Demographics:
Gender: Male or Female 
Age: Patient’s Age 
Diagnostic Results: Dengue NS1 (Positive/Negative) - Class label

Hematological Parameters:
1. Platelet Count (PLT) [K/µL] : Helps in blood clotting.
2. White Blood Cell Count (WBC) [K/µL] : Defends the body against infections.
3. Hematocrit (HCT %): Measures red blood cell ratio, useful for detecting blood thickness.
4. Red Blood Cell Count (RBC) [m/µL] : Carries oxygen throughout the body.
5. Lymphocyte Percentage (Lymph %): A type of WBC, important for fighting viral infections.
6. Neutrophil Percentage (Neu %): A type of WBC, mainly fights bacterial infections.
7. Dengue NS1 (Antigen Test) : Detects Dengue Virus antigen in blood.

Biochemical Markers:
Alanine Aminotransferase (ALT) [U/L] and Aspartate Aminotransferase (AST) [U/L] : Liver enzymes, used to assess liver function.

Dataset Overview 
Dataset type: Primary data 
File Type: CSV
Total Records (Rows): 1,329 (each representing an individual patient case) 
Number of Variables (Columns): 12 (Demographic, Diagnostic, Hematological and Biochemical Features)

Reference:
[1] DGHS Dengue Dashboard- https://dashboard.dghs.gov.bd/pages/heoc_dengue_v1.php
DOI: 10.15468/dl.88gwvd
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salmacisia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 50 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039418-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/8t76fsrj3m
title: Data Thesis

description: Data thesis
DOI: 10.17632/8t76fsrj3m.1
title: Data Thesis

description: Data thesis
DOI: 10.17605/osf.io/9k5z3
title: The Effects of a Learned Helplessness Task on Anhedonia, Intolerance of Uncertainty, and Physiological Stress Markers

description: This OSF project contains the anonymized dataset and supporting materials for the manuscript titled 
“The Effects of a Learned Helplessness Task on Anhedonia, Intolerance of Uncertainty, and Physiological Stress Markers.” 
The dataset includes pre–post measures of anhedonia (DARS), intolerance of uncertainty (IU), 
and physiological stress markers (heart rate, systolic/diastolic blood pressure, and GSR).
DOI: 10.17632/kytv77kfsr
title: Supplementary material - When Consistency Signals Distinctiveness: How Univalent Reviews Elevate Perceived Uniqueness and Purchase of Plant-Based Meat Alternatives

description: This dataset is used for the research paper entitled "When Consistency Signals Distinctiveness: How Univalent Reviews Elevate Perceived Uniqueness and Purchase of Plant-Based Meat Alternatives"
DOI: 10.15468/dl.8asuka
title: Occurrence Download

description: A dataset containing 3713 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (iNaturalist Research-grade Observations)",
 "Geometry POLYGON(( -105.601802164238 35.5325227840993 , -105.2372292897 35.5325227840993 , -105.2372292897 36.1779250141282 , -105.601802164238 36.1779250141282 , -105.601802164238 35.5325227840993 ))",
 "Year is greater than or equal to 2016"
 ]
}

 The dataset includes 3713 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039420-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/kytv77kfsr.1
title: Supplementary material - When Consistency Signals Distinctiveness: How Univalent Reviews Elevate Perceived Uniqueness and Purchase of Plant-Based Meat Alternatives

description: This dataset is used for the research paper entitled "When Consistency Signals Distinctiveness: How Univalent Reviews Elevate Perceived Uniqueness and Purchase of Plant-Based Meat Alternatives"
DOI: 10.17632/88cf83p264
title: Iron and zinc isotope fractionation during sulfide-silicate melt immiscibility: insights from clinopyroxene megacrysts

description: This dataset includes major and trace element compositions of clinopyroxene megacrysts, and iron and zinc isotope compositions of clinopyroxene megacrysts, sulfide inclusions, and host basalts in eastern China. To understand how iron (Fe) and zinc (Zn) isotopes behave during sulfide-silicate melt immiscibility, we analyzed clinopyroxene megacrysts and their encapsulated sulfide inclusions from Cenozoic basalts in eastern continental China. These megacrysts, known to have co-precipitated with garnet alongside immiscible segregation of sulfide melts from basaltic magmas, show increasing δ56Fe (from 0.06‰ to 0.22‰) with decreasing Mg# in response to high-pressure magma differentiation. Sulfide inclusions have markedly lighter Fe isotopes (δ56Fe from –0.38‰ to 0.13‰), resulting in large and variable Fe isotope fractionation between clinopyroxene and sulfide (∆56FeClinopyroxene-Sulfide = 0.04‰-0.55‰). In contrast, Zn isotope fractionation is more uniform (∆66ZnClinopyroxene-Sulfide = ~0.18‰) between clinopyroxene (δ66Zn = 0.39 ± 0.05‰) and sulfide (δ66Zn = 0.21 ± 0.05‰).
We attribute the variable Fe isotope fractionation to the compositional variations of sulfide melts. Early-stage Cu-rich sulfides with more chalcopyrite (Cu1+Fe3+S2) component have heavy Fe isotope compositions (δ56Fe ≈ 0.07‰) and a limited isotope fractionation with co-crystallizing clinopyroxene (∆56FeClinopyroxene-Sulfide ≈ 0.10‰). In contrast, late-stage Cu-poor sulfides are isotopically light (δ56Fe ≈ –0.38‰), resulting in a greater ∆56FeClinopyroxene-Sulfide of ~0.55‰. Quantitative modeling shows that while sulfides host isotopically light Fe and Zn, their segregation is volumetrically minor. As a result, fractional crystallization of silicate minerals (e.g., clinopyroxene and garnet), instead of the segregation of immiscible sulfides, dominates Fe-Zn isotope evolution during basaltic magma differentiation. This finding requires revision of models that invoke extensive sulfide segregation to explain heavy Fe isotope signatures in evolved magmas.
DOI: 10.17632/88cf83p264.1
title: Iron and zinc isotope fractionation during sulfide-silicate melt immiscibility: insights from clinopyroxene megacrysts

description: This dataset includes major and trace element compositions of clinopyroxene megacrysts, and iron and zinc isotope compositions of clinopyroxene megacrysts, sulfide inclusions, and host basalts in eastern China. To understand how iron (Fe) and zinc (Zn) isotopes behave during sulfide-silicate melt immiscibility, we analyzed clinopyroxene megacrysts and their encapsulated sulfide inclusions from Cenozoic basalts in eastern continental China. These megacrysts, known to have co-precipitated with garnet alongside immiscible segregation of sulfide melts from basaltic magmas, show increasing δ56Fe (from 0.06‰ to 0.22‰) with decreasing Mg# in response to high-pressure magma differentiation. Sulfide inclusions have markedly lighter Fe isotopes (δ56Fe from –0.38‰ to 0.13‰), resulting in large and variable Fe isotope fractionation between clinopyroxene and sulfide (∆56FeClinopyroxene-Sulfide = 0.04‰-0.55‰). In contrast, Zn isotope fractionation is more uniform (∆66ZnClinopyroxene-Sulfide = ~0.18‰) between clinopyroxene (δ66Zn = 0.39 ± 0.05‰) and sulfide (δ66Zn = 0.21 ± 0.05‰).
We attribute the variable Fe isotope fractionation to the compositional variations of sulfide melts. Early-stage Cu-rich sulfides with more chalcopyrite (Cu1+Fe3+S2) component have heavy Fe isotope compositions (δ56Fe ≈ 0.07‰) and a limited isotope fractionation with co-crystallizing clinopyroxene (∆56FeClinopyroxene-Sulfide ≈ 0.10‰). In contrast, late-stage Cu-poor sulfides are isotopically light (δ56Fe ≈ –0.38‰), resulting in a greater ∆56FeClinopyroxene-Sulfide of ~0.55‰. Quantitative modeling shows that while sulfides host isotopically light Fe and Zn, their segregation is volumetrically minor. As a result, fractional crystallization of silicate minerals (e.g., clinopyroxene and garnet), instead of the segregation of immiscible sulfides, dominates Fe-Zn isotope evolution during basaltic magma differentiation. This finding requires revision of models that invoke extensive sulfide segregation to explain heavy Fe isotope signatures in evolved magmas.
DOI: 10.17632/wfbnhy5gvw
title: DKS Datasets and Source Codes

description: 1. Five shells for running DKS on five standard real-world datasets: 
 shell-citeseer.py, shell-cornell.py, shell-wisconsin.py, shell-toy.py, and shell-video.py.
2. Four source codes, including DKS code, contaminated graph generation code, incomplete graph generation code, and query generation code.
3. Five standard real-world datasets from various domains:
(1) "CiteSeer" is a standard citation network dataset, where nodes represent documents, edges represent citation links, and keywords are the bag-of-words representation of papers. 
(2) "Cornell" and "Wisconsin" are two subdatasets of a webpage dataset collected from computer science departments of various universities, where nodes denote web pages, edges denote hyperlinks between nodes, and keywords are the bag-of-words representation of web pages. 
(3) "Toy" and "Video" are co-purchase networks. Their nodes denote the products, and the keywords are features of the product. An edge is built if two products are purchased by one customer.
4. Three extended datasets:
(1) "Pubmed" is another standard citation network dataset, where nodes represent documents, edges represent citation links, and keywords are the bag-of-words representation of papers.
(2) "Chameleon" and "Squirrel" are very dense heterogeneous knowledge-graph style datasets. In both Chameleon and Squirrel, nodes represent Wikipedia entries, edges represent links between entries, and keywords are descriptive terms for the entries.
DOI: 10.17632/wfbnhy5gvw.2
title: DKS Datasets and Source Codes

description: 1. Five shells for running DKS on five standard real-world datasets: 
 shell-citeseer.py, shell-cornell.py, shell-wisconsin.py, shell-toy.py, and shell-video.py.
2. Four source codes, including DKS code, contaminated graph generation code, incomplete graph generation code, and query generation code.
3. Five standard real-world datasets from various domains:
(1) "CiteSeer" is a standard citation network dataset, where nodes represent documents, edges represent citation links, and keywords are the bag-of-words representation of papers. 
(2) "Cornell" and "Wisconsin" are two subdatasets of a webpage dataset collected from computer science departments of various universities, where nodes denote web pages, edges denote hyperlinks between nodes, and keywords are the bag-of-words representation of web pages. 
(3) "Toy" and "Video" are co-purchase networks. Their nodes denote the products, and the keywords are features of the product. An edge is built if two products are purchased by one customer.
4. Three extended datasets:
(1) "Pubmed" is another standard citation network dataset, where nodes represent documents, edges represent citation links, and keywords are the bag-of-words representation of papers.
(2) "Chameleon" and "Squirrel" are very dense heterogeneous knowledge-graph style datasets. In both Chameleon and Squirrel, nodes represent Wikipedia entries, edges represent links between entries, and keywords are descriptive terms for the entries.
DOI: 10.15468/dl.y6ydys
title: Occurrence Download

description: A dataset containing 162579 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Myocastor coypus"
 ]
}

 The dataset includes 162579 records from 2054 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039387-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.