cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e244138
title: Nutrition, Physical Activity, and Obesity - Behavioral Risk Factor Surveillance System

description: This dataset includes data on adult's diet, physical activity, and weight status from Behavioral Risk Factor Surveillance System. This data is used for DNPAO's Data, Trends, and Maps database, which provides national and state specific data on obesity, nutrition, physical activity, and breastfeeding.
description: (Downloaded 1/7/2026)
DOI: 10.17632/cwry53dm3y
title: A Unified Approach for Quantifying the Redox Molecular Characteristics of Dissolved Black Carbon Coupling FT-ICR-MS and Theoretical Modeling

description: The data in the attachment is the minimal dataset set that supports the core conclusions of the paper in the research paper entitled "A Unified Approach for Quantifying the Redox Molecular Characteristics of Dissolved Black Carbon Coupling FT-ICR-MS and Theoretical Modeling". The journal name is "Geochimica et Cosmochimica Acta".
DOI: 10.17632/cwry53dm3y.1
title: A Unified Approach for Quantifying the Redox Molecular Characteristics of Dissolved Black Carbon Coupling FT-ICR-MS and Theoretical Modeling

description: The data in the attachment is the minimal dataset set that supports the core conclusions of the paper in the research paper entitled "A Unified Approach for Quantifying the Redox Molecular Characteristics of Dissolved Black Carbon Coupling FT-ICR-MS and Theoretical Modeling". The journal name is "Geochimica et Cosmochimica Acta".
DOI: 10.3886/e244138v1
title: Nutrition, Physical Activity, and Obesity - Behavioral Risk Factor Surveillance System

description: This dataset includes data on adult's diet, physical activity, and weight status from Behavioral Risk Factor Surveillance System. This data is used for DNPAO's Data, Trends, and Maps database, which provides national and state specific data on obesity, nutrition, physical activity, and breastfeeding.
description: (Downloaded 1/7/2026)
DOI: 10.17632/4xp62s957c.3
title: Data to Accompany: Space-Time Analysis of Burgeoning US Atrial Septal Defect Rates.

description: R Code and original data files
DOI: 10.17632/pkzh5mwg8b
title: Evaluation Score for Harmonious and Beautiful Island Indicators

description: The dataset records the scores of 13 islands in Zhejiang Province based on the Harmonious and Beautiful Islands evaluation indicators.
DOI: 10.17632/pkzh5mwg8b.1
title: Evaluation Score for Harmonious and Beautiful Island Indicators

description: The dataset records the scores of 13 islands in Zhejiang Province based on the Harmonious and Beautiful Islands evaluation indicators.
DOI: 10.5281/zenodo.18247519
title: Baccharis oxyodonta var. punctulata (DC.) Baker. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.17632/ydx7v73t3k.1
title: Screening Protocol and Study Selection Data for: Artificial Intelligence for Women’s Reproductive Health: A Systematic Review of Global Diagnostic Trends and a Translational Informatics Framework for Low-Resource Settings

description: This repository contains the screening protocol and structured study-selection metadata supporting the systematic review titled Artificial Intelligence for Women’s Reproductive and Hormonal Disorders: A Systematic Review of Global Approaches and a Translational Framework for Low-Resource Settings.

Search and Screening Overview :
A total of 273 records were identified through systematic searches across multiple academic databases. Screening was performed in two stages: (i) title and abstract screening (First Pass), followed by (ii) full-text eligibility assessment (Second Pass). Explicit exclusion rationales were documented at each stage.

Final Inclusion :
Of the 273 screened records, 167 studies met the predefined inclusion criteria and were included in the final qualitative synthesis.

Taxonomy Classification :
Each included study was assigned to a predefined taxonomy category reflecting its primary methodological focus, clinical application, and translational relevance to low-resource healthcare settings.

Purpose of Data Sharing :
This dataset is shared to promote transparency, reproducibility, and methodological rigor in accordance with PRISMA 2020 guidelines.
DOI: 10.5281/zenodo.18247518
title: Baccharis oxyodonta var. punctulata (DC.) Baker. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.17632/t2fm34x6n4
title: Seismic Bearing Capacity of Footings Adjacent to c-ϕ Soil Slope
DOI: 10.17632/t2fm34x6n4.1
title: Seismic Bearing Capacity of Footings Adjacent to c-ϕ Soil Slope
DOI: 10.25574/30664
title: Chandra X-ray Observatory ObsId 30664

description: X-raying Multiple IMBH Candidates in One Dwarf Galaxy
DOI: 10.17632/9v9rtzch8g
title: Student Awareness, Cognitive Strain, and Emotional Responses to AI Assistance Dataset

description: This dataset examines higher education students’ use of generative AI and its cognitive, emotional, and learning-related effects. Collected through a structured survey, it includes demographic and academic background variables such as gender, field of study, AI usage experience, frequency of use, and average CGPA.

The dataset measures reliance on AI for information seeking, problem solving, and decision-making, along with awareness of skill use, memory recall, and independent thinking. Emotional outcomes such as remorse and regret related to AI over-reliance are captured, as well as perceived benefits including time savings, confidence, learning efficiency, satisfaction, and positive emotional experience. Cognitive strain is assessed through perceived mental effort and reduction of cognitive burden when using AI.

An open-ended section allows participants to share additional reflections on AI use in learning. The dataset supports research on AI assistance, dependence, awareness, and learning outcomes in higher education.
DOI: 10.17632/9v9rtzch8g.1
title: Student Awareness, Cognitive Strain, and Emotional Responses to AI Assistance Dataset

description: This dataset examines higher education students’ use of generative AI and its cognitive, emotional, and learning-related effects. Collected through a structured survey, it includes demographic and academic background variables such as gender, field of study, AI usage experience, frequency of use, and average CGPA.

The dataset measures reliance on AI for information seeking, problem solving, and decision-making, along with awareness of skill use, memory recall, and independent thinking. Emotional outcomes such as remorse and regret related to AI over-reliance are captured, as well as perceived benefits including time savings, confidence, learning efficiency, satisfaction, and positive emotional experience. Cognitive strain is assessed through perceived mental effort and reduction of cognitive burden when using AI.

An open-ended section allows participants to share additional reflections on AI use in learning. The dataset supports research on AI assistance, dependence, awareness, and learning outcomes in higher education.
DOI: 10.15468/dl.djssgs
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"IND.26.17_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009422-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/zcgbnn8zbm
title: MCodeScript

description: MCodeScript, a suite of unsupervised and supervised Marathi-English code-mixed and script-mixed datasets with comments collected from various sources, such as social sites, community groups, and news websites. McodeScript-un is unsupervised gold dataset with 1.3L code-mixed and script-mixed comments. McodeScript-un-annot is transformed version of McodeScript-un by automated procedure. The MCodeScript-MeSent, a transformed MeSent supervised Romanized Marathi dataset into a script-mixed format through our automated process.
DOI: 10.17632/zcgbnn8zbm.2
title: MCodeScript

description: MCodeScript, a suite of unsupervised and supervised Marathi-English code-mixed and script-mixed datasets with comments collected from various sources, such as social sites, community groups, and news websites. McodeScript-un is unsupervised gold dataset with 1.3L code-mixed and script-mixed comments. McodeScript-un-annot is transformed version of McodeScript-un by automated procedure. The MCodeScript-MeSent, a transformed MeSent supervised Romanized Marathi dataset into a script-mixed format through our automated process.
DOI: 10.3886/e240867
title: Arrêts maladie en France (2010–2025) : analyse statistique, économique et juridique

description: Cette étude analyse l’évolution des arrêts maladie en France entre 2010 et 2025 à partir des données INSEE, CNAM, DARES, Cour des comptes, Sénat et OCDE. Elle examine les tendances statistiques, les causes structurelles de la hausse, les dérives possibles du système d’indemnisation et l’impact économique global sur le modèle social français. Le rapport propose également quinze recommandations concrètes pour améliorer l’équité du dispositif, réduire les abus, moderniser les contrôles et renforcer la prévention.
description: Aucun poids statistique utilisé.
description: Response Rates: Non applicable (étude basée sur des données administratives et publiques).
description: Presence of Common Scales: Aucun équilibrage ou pondération appliqué.
description: Aucun échantillonnage : analyse exhaustive de sources nationales (INSEE, CNAM, DARES, Sénat, Cour des comptes, OCDE).
description: Smallest Geographic Unit: France (niveau national).
description: record abstracts
DOI: 10.17632/t38bht87kf
title: Determinants of HIV, Hepatitis B, and Hepatitis C Infections Among Preoperative Patients

description: Data from a retrospective cross-sectional study carried out in the departments of Surgery and Gynecology of a tertiary care hospital in Bukavu, in eastern DRC. They include data from routine minimum preoperative assessments of our hospital. In addition, they contain socio-demographic parameters, data related to the surgical procedure, serological results (HIV, HBV, HCV), and any risk factors for acquiring these infections.
DOI: 10.17632/t38bht87kf.1
title: Determinants of HIV, Hepatitis B, and Hepatitis C Infections Among Preoperative Patients

description: Data from a retrospective cross-sectional study carried out in the departments of Surgery and Gynecology of a tertiary care hospital in Bukavu, in eastern DRC. They include data from routine minimum preoperative assessments of our hospital. In addition, they contain socio-demographic parameters, data related to the surgical procedure, serological results (HIV, HBV, HCV), and any risk factors for acquiring these infections.
DOI: 10.17632/vmzrd2rjgj.1
title: GitHub Copilot in Computing Education: A Field Study Dataset

description: Description
This dataset was generated from a field study conducted to evaluate the integration of the AI pair programmer, GitHub Copilot, into project-based computer science and software engineering curriculums. The primary aim was to assess how undergraduate students perceive and utilize AI-assisted coding tools during a realistic development task, and to measure the tool's impact on their productivity, learning, and final project quality.
Methodology
Participants: 114 senior undergraduate students from Software Engineering and Computer Science programs in Three Universities in Kurdistan Region of Iraq.
Task: Participants were tasked with building a static personal portfolio website using HTML, CSS, and JavaScript.
Intervention: GitHub Copilot was used as the primary AI-assisted coding tool within the Visual Studio Code IDE.
Design: The study followed a structured, project-based learning protocol. Students participated in a guided competition to complete the task, adhering to a predefined set of functional and non-functional requirements.
Data Collection: Three streams of data were collected:
Perceptual Survey: A post-task survey using a 5-point Likert scale measured five constructs adapted from the Technology Acceptance Model (TAM).
Objective Performance Metrics: Actual project completion time (in hours) and a final project score assessed via a detailed rubric.
Qualitative Feedback: An open-ended question prompted students to describe a critical engagement with an incorrect or suboptimal AI suggestion.

Dataset Description

Column Name; Description; Data Type Allowed Values / Range
No: Unique participant identifier Integer 1-114
Gender: Participant gender String (Nominal) m (Male), f (Female)
Perceived Ease of Use: TAM construct: Ease of using GitHub Copilot Ordinal (Integer) 1 (Strongly Disagree) - 5 (Strongly Agree)
Perceived Code Quality: TAM construct: Belief that Copilot improved output code quality Ordinal (Integer) 1-5
Perceived Time Efficiency: TAM construct: Belief that Copilot saved time Ordinal (Integer) 1-5
Support in Learning Construct: Belief that Copilot aided in learning new concepts Ordinal (Integer) 1-5
Willingness to Recommend: TAM construct: Intention to adopt/recommend the tool Ordinal (Integer) 1-5
Actual Completion time Total project duration in hours: Continuous (Float) 8-15 hours
Final Project Score-Functionality: Rubric sub-score for functional requirements. Continuous (Float) 0-10
Final Project Score-Readability: Rubric sub-score for code structure & readability. Continuous (Float) 0-10
Final Project Score-UI: Rubric sub-score for design & user interface. Continuous (Float) 0-10
Final Project Score-Responsiveness: Rubric sub-score for responsive design. Continuous (Float) 0-10
Final Project Score-Total Overall project score (average of sub-scores): Continuous (Float) 0-10
Critical Engagement: Qualitative response describing a critical interaction with Copilot String (Text) Free-text response
DOI: 10.17632/xzwp62vny3
title: To Flee or Wait and See? Response of Incubating White-browed Scrubwrens to Information about Danger

description: The raw data for the study "To Flee or Wait and See? Response of Incubating White-browed Scrubwrens to Information about Danger"
DOI: 10.17632/xzwp62vny3.1
title: To Flee or Wait and See? Response of Incubating White-browed Scrubwrens to Information about Danger

description: The raw data for the study "To Flee or Wait and See? Response of Incubating White-browed Scrubwrens to Information about Danger"
DOI: 10.57903/uj/fp9qm7
title: Neutralising External and Internal Barriers in the Digital Inclusion Process for Seniors - Finding Ways to Effectively Shape Digital and Media Competences among Older People - data for the article
title: angielski

description: Statements of 72 participants of the e-learning course entitled. ‘How to teach older people to use new technologies?’
The course was part of the REMEDIS (Rethinking Media Literacy and Digital Skills in Europe) project


Data collection method:


MS Forms tool was used to collect online responses
Participants answered open-ended questions that were an integral part of the course
The key activation task was: ‘Please prepare arguments that should motivate older people to enter the digital world. Organise the arguments according to external and internal barriers. Remember that the arguments should be addressed directly to older people.’


Data analysis structure:


Data were imported into MAXQDA Analytics Pro
Qualitative analysis with open coding was used
Statements were divided into two main groups:

concerning external barriers
concerning internal barriers




The analysis process involved three parallel activities:


Data reduction
Data representation
Drawing and verifying conclusions


Coding structure:


In the first phase, 12 working categories were identified classifying arguments according to the type of barrier being overcome (e.g. lack of support, lack of knowledge, financial barriers, biological barriers)
In the second phase, statements were divided according to the type of action proposed into 3 categories
The broadest category was further divided into 3 subcategories


Data verification:


Researcher triangulation was used - categories were checked by someone not involved in the analysis and coding process
The aim was to ensure the relevance and reliability of the research results
DOI: 10.5281/zenodo.18247492
title: Baccharis organensis Baker. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.5281/zenodo.18247493
title: Baccharis organensis Baker. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.5281/zenodo.18247522
title: MATRITSANING XOS SON VA XOS VEKTORINI TOPISH METODLARI VA ALGORITMLARI

description: Ushbu maqolada matritsaning xos son va xos vektor tushunchalari, ularni aniqlashning nazariy asoslari hamda amaliy hisoblash metodlari keng yoritilgan. Xos sonlarni topishning klassik determinantga asoslangan usullari bilan bir qatorda, katta o‘lchamli matritsalar uchun samarali bo‘lgan iteratsion algoritmlar, jumladan daraja usuli va QR-algoritmning mohiyati tahlil qilingan. Shuningdek, xos sonlarning karraligi, spektral radius, diagonalizatsiya shakli kabi tushunchalar orqali mavzuning chuqur matematik mazmuni ochib berilgan. Maqolada xos son va xos vektorlarning differensial tenglamalar, dinamik tizimlar, mexanik modellar, iqtisodiy tahlil hamda sun’iy intellekt sohalaridagi amaliy qo‘llanilishiga alohida e’tibor qaratilgan. Tadqiqot natijalari chiziqli algebra fanini o‘rganayotgan talabalar va amaliy masalalar bilan shug‘ullanuvchi mutaxassislar uchun foydali bo‘lishi mumkin.
DOI: 10.5281/zenodo.18247523
title: MATRITSANING XOS SON VA XOS VEKTORINI TOPISH METODLARI VA ALGORITMLARI

description: Ushbu maqolada matritsaning xos son va xos vektor tushunchalari, ularni aniqlashning nazariy asoslari hamda amaliy hisoblash metodlari keng yoritilgan. Xos sonlarni topishning klassik determinantga asoslangan usullari bilan bir qatorda, katta o‘lchamli matritsalar uchun samarali bo‘lgan iteratsion algoritmlar, jumladan daraja usuli va QR-algoritmning mohiyati tahlil qilingan. Shuningdek, xos sonlarning karraligi, spektral radius, diagonalizatsiya shakli kabi tushunchalar orqali mavzuning chuqur matematik mazmuni ochib berilgan. Maqolada xos son va xos vektorlarning differensial tenglamalar, dinamik tizimlar, mexanik modellar, iqtisodiy tahlil hamda sun’iy intellekt sohalaridagi amaliy qo‘llanilishiga alohida e’tibor qaratilgan. Tadqiqot natijalari chiziqli algebra fanini o‘rganayotgan talabalar va amaliy masalalar bilan shug‘ullanuvchi mutaxassislar uchun foydali bo‘lishi mumkin.
DOI: 10.15468/dl.9pjt34
title: Occurrence Download

description: A dataset containing 479 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Abramis brama",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1935",
 "Year is less than or equal to 1939"
 ]
}

 The dataset includes 479 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009423-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/nshmrbbzmb
title: Feature-Level Reconstructed Dataset for Detection of Obfuscated Malicious JavaScript Code

description: This dataset provides feature-level representations extracted from JavaScript files for the purpose of replicating an existing static machine learning-based
malware detection methodology. The dataset was reconstructed following the experimental specifications of the referenced base research paper "Detection of Obfuscated Malicious JavaScript Code, Author et Ammar Alazab, Ansam Khraisat, Moutaz Alazab and Sarabjot Singh, 2022".

Raw JavaScript samples are not included. The dataset is intended solely for baseline implementation, reproducibility, and academic validation of existing
approaches, and does not claim novelty.
DOI: 10.17632/nshmrbbzmb.1
title: Feature-Level Reconstructed Dataset for Detection of Obfuscated Malicious JavaScript Code

description: This dataset provides feature-level representations extracted from JavaScript files for the purpose of replicating an existing static machine learning-based
malware detection methodology. The dataset was reconstructed following the experimental specifications of the referenced base research paper "Detection of Obfuscated Malicious JavaScript Code, Author et Ammar Alazab, Ansam Khraisat, Moutaz Alazab and Sarabjot Singh, 2022".

Raw JavaScript samples are not included. The dataset is intended solely for baseline implementation, reproducibility, and academic validation of existing
approaches, and does not claim novelty.
DOI: 10.17632/9s44yykz6x
title: Data_Entrepreneurship Learning Model

description: This file contains qualitative research data derived from in-depth interviews with eighteen former Indonesian migrant workers who have successfully transitioned into independent entrepreneurs after returning home. The data represent firsthand narratives that capture the participants’ lived experiences before migration, during employment abroad, and throughout the process of establishing small businesses in their local contexts.

The interviews explore how entrepreneurial intentions were formed prior to departure, how overseas work was consciously used as a learning space, and how skills, knowledge, and discipline were gradually accumulated beyond financial savings. Participants describe migration not merely as a means of earning income, but as an intentional investment period for acquiring technical competence, market awareness, and managerial insight that could later be applied in self-employment.

The data also highlight the central role of family relationships in shaping entrepreneurial outcomes. Informants explain how trust, role-sharing, and negotiated agreements within the household influenced savings management, risk-taking decisions, and business continuity. Family members frequently acted as partners, caretakers, or informal managers rather than passive recipients of remittances.

In addition, the interviews reveal iterative and context-based learning processes. Participants relied heavily on trial-and-error experimentation, peer networks among fellow former migrant workers, and informal knowledge sources such as community groups and digital platforms. Access to capital emerged as a hybrid strategy, combining personal savings, soft family loans, social networks, and non-financial resources such as land, labor, and trust.

Overall, this qualitative interview dataset provides rich empirical material for analyzing migrant entrepreneurship, experiential learning, family-based economic strategies, and alternative pathways to business formation. It is intended for academic analysis, thematic coding, and theory development, offering grounded insights into entrepreneurship as a survival-oriented and socially embedded process rather than a purely individual or opportunity-driven choice.