cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/mhrywtd7cj
title: Harnessing Artificial Intelligence in Human Resource Management for Sustainable Business Growth

description: Harnessing Artificial Intelligence in Human Resource Management for Sustainable Business Growth Data
DOI: 10.17632/mhrywtd7cj.1
title: Harnessing Artificial Intelligence in Human Resource Management for Sustainable Business Growth

description: Harnessing Artificial Intelligence in Human Resource Management for Sustainable Business Growth Data
DOI: 10.17632/2j3m5skwvz
title: Psychological Richness Data1

description: This is a questionnaire survey data for college students, measuring the following four variables: psychological richness, Cognitive flexibility, innovative self-efficacy, and innovative behavior.
DOI: 10.17632/2j3m5skwvz.1
title: Psychological Richness Data1

description: This is a questionnaire survey data for college students, measuring the following four variables: psychological richness, Cognitive flexibility, innovative self-efficacy, and innovative behavior.
DOI: 10.17632/dtnwcp7rkg
title: Strength testing in the high school-aged baseball athlete: Reliability, percentage ratios, and pain with throwing

description: Data was collected from 34 adolescent male baseball athletes. The purpose was to observe throwing arm strength percentage ratios and throwing with pain during seasonal participation, and reliability of testing for the high school-aged baseball athlete. Data included age, throwing arm strength (measured with an externally fixated digital handheld dynamometer (HHD) in different positions), throwing arm length, Kerlan-Jobe Orthopaedic Clinic (KJOC) shoulder and Elbow Score, and visual analog pain scale.
DOI: 10.17632/dtnwcp7rkg.1
title: Strength testing in the high school-aged baseball athlete: Reliability, percentage ratios, and pain with throwing

description: Data was collected from 34 adolescent male baseball athletes. The purpose was to observe throwing arm strength percentage ratios and throwing with pain during seasonal participation, and reliability of testing for the high school-aged baseball athlete. Data included age, throwing arm strength (measured with an externally fixated digital handheld dynamometer (HHD) in different positions), throwing arm length, Kerlan-Jobe Orthopaedic Clinic (KJOC) shoulder and Elbow Score, and visual analog pain scale.
DOI: 10.17632/y7xfffjh6z.4
title: FER2025: A Deep Learning Approach to Facial Emotion Recognition with Gender Classification Using CNN

description: This dataset was developed for a deep learning project focused on facial emotion recognition with gender classification using Convolutional Neural Networks (CNNs). It comprises a total of 3,176 images and 5,160 annotations, collected exclusively from reputable sources offering copyright-free or royalty-free images, such as Unsplash, iStock, Shutterstock, Getty Images etc. These platforms explicitly permit usage for personal and commercial purposes without requiring attribution.

The dataset includes 12 distinct classes, corresponding to six emotion categories (e.g., happy, sad, angry, fear, surprised, sleepy), each labeled separately for male and female subjects, resulting in a total of 12 unique class labels.

To facilitate effective model training and evaluation, the dataset is organized into three subsets:
Training Set: 70% of the data
Validation Set: 20% of the data
Test Set: 10% of the data

The metadata_FER2025.csv file lists each image of a facial emotion with its name, set type (Train/Valid/Test), Class ID, Class Name, and bounding box details (X, Y, Width, Height). It organizes the dataset for efficient object detection model training.

All annotations were carefully curated to ensure compliance with licensing terms and legal usage rights.
DOI: 10.17632/rwykvcswjd
title: Plume-Lithosphere Interaction and the Role of the Mid-Lithosphere Discontinuity in Craton Delamination

description: The Model_*.prm files in the "Code Files" folder are the input files used in ASPECT 2.5.0 for our model, to simulate the plume upwelling and delamination of the lower lithospheric mantle in cratonic areas, based on the assumptions described in our paper.
The Model_*.mp4 files in the "Videos" folder are videos showing the temporal evolution of the viscosity field for each simulation.
DOI: 10.17632/rwykvcswjd.2
title: Plume-Lithosphere Interaction and the Role of the Mid-Lithosphere Discontinuity in Craton Delamination

description: The Model_*.prm files in the "Code Files" folder are the input files used in ASPECT 2.5.0 for our model, to simulate the plume upwelling and delamination of the lower lithospheric mantle in cratonic areas, based on the assumptions described in our paper.
The Model_*.mp4 files in the "Videos" folder are videos showing the temporal evolution of the viscosity field for each simulation.
DOI: 10.17632/zgrz4f48g3
title: Strategic Decoupling - the Essec experiment 2025

description: Stata database - date for the Essec experiment in Strategic Experiment. Experiment run at the Essec Experimental Lab
DOI: 10.17632/zgrz4f48g3.1
title: Strategic Decoupling - the Essec experiment 2025

description: Stata database - date for the Essec experiment in Strategic Experiment. Experiment run at the Essec Experimental Lab
DOI: 10.17632/zptphkynt6
title: ChemEq25: A Novel Multiclass Dataset for Detecting Chemical Laboratory Apparatus Using Deep Learning Approach

description: The "ChemEq25" dataset comprises 4,599 annotated images of chemical laboratory equipment, collected from three locations: Bangladesh Atomic Energy Chemical Lab, Biochemical Laboratory of United International University, and Chemistry Laboratory of Dhaka Imperial College. Designed for machine learning applications, it supports real-time equipment detection. Images were captured under varying lighting and backgrounds to enhance model robustness. Each item was photographed from multiple angles, auto-oriented, and resized to 640x640 pixels, introducing slight stretching. The dataset includes 25 classes of common lab equipment, divided into training (70%), validation (20%), and test (10%) sets.
DOI: 10.17632/zptphkynt6.4
title: ChemEq25: A Novel Multiclass Dataset for Detecting Chemical Laboratory Apparatus Using Deep Learning Approach

description: The "ChemEq25" dataset comprises 4,599 annotated images of chemical laboratory equipment, collected from three locations: Bangladesh Atomic Energy Chemical Lab, Biochemical Laboratory of United International University, and Chemistry Laboratory of Dhaka Imperial College. Designed for machine learning applications, it supports real-time equipment detection. Images were captured under varying lighting and backgrounds to enhance model robustness. Each item was photographed from multiple angles, auto-oriented, and resized to 640x640 pixels, introducing slight stretching. The dataset includes 25 classes of common lab equipment, divided into training (70%), validation (20%), and test (10%) sets.
DOI: 10.17632/wzygszrwjt.1
title: Bioheat Modeling of Soft Tissues
DOI: 10.17632/d87sgxhsw5
title: Supplemental Figure 1

description: Successful treatment of keratoacanthoma-like atypical squamous proliferations on the lower legs of elderly patients with intralesional triamcinolone suggests a unique reactive pathogenesis and response to therapy that differs from conventional squamous cell carcinoma
DOI: 10.17632/d87sgxhsw5.1
title: Supplemental Figure 1

description: Successful treatment of keratoacanthoma-like atypical squamous proliferations on the lower legs of elderly patients with intralesional triamcinolone suggests a unique reactive pathogenesis and response to therapy that differs from conventional squamous cell carcinoma
DOI: 10.17632/9jy9937xmf
title: Dataset of: Patterns of Needs among Iraqi Families Caring for Children with Autism Spectrum Disorder: A Cross-sectional Study

description: Autism is one of the most common neurodevelopmental conditions worldwide, impacting roughly 1 in 36 children, as per the latest estimates from the Centers for Disease Control and Prevention (CDC). Autism is associated with lifelong challenges, leading to significant social, educational, and psychological impacts for both the children and their families. Yet, In Iraq, there exists a critical lack of research on this condition to the extent that no official estimate of its prevalence has been reported. This gap severely hinders the ability to provide adequate healthcare and support systems for these children and their families.

To address this gap, the International Branch of Tehran University for Medical Sciences and Al-Subtain Academy for Autism and Neurodevelopmental Disorders have conducted nine studies as a part of a research collaboration titled “Epidemiological, Clinical, and Psychosocial Aspects of Iraqi Children with Autism”.

As a part of this collaboration, we investigated the needs of Iraqi families caring for autistic children. Based on our findings, most parents require assistance in finding information, particularly regarding current or future services for their children. Many parents also needed help in finding reading material about and talking to families with similar children, highlighting the necessity of combating social isolation and providing social support to these families. Across the childcare domain of family needs, respite care was the most requested. We believe that our results offer a significant contribution, as they can be used to make better use of the very limited financial and professional resources that are available to these families.
DOI: 10.17632/9jy9937xmf.1
title: Dataset of: Patterns of Needs among Iraqi Families Caring for Children with Autism Spectrum Disorder: A Cross-sectional Study

description: Autism is one of the most common neurodevelopmental conditions worldwide, impacting roughly 1 in 36 children, as per the latest estimates from the Centers for Disease Control and Prevention (CDC). Autism is associated with lifelong challenges, leading to significant social, educational, and psychological impacts for both the children and their families. Yet, In Iraq, there exists a critical lack of research on this condition to the extent that no official estimate of its prevalence has been reported. This gap severely hinders the ability to provide adequate healthcare and support systems for these children and their families.

To address this gap, the International Branch of Tehran University for Medical Sciences and Al-Subtain Academy for Autism and Neurodevelopmental Disorders have conducted nine studies as a part of a research collaboration titled “Epidemiological, Clinical, and Psychosocial Aspects of Iraqi Children with Autism”.

As a part of this collaboration, we investigated the needs of Iraqi families caring for autistic children. Based on our findings, most parents require assistance in finding information, particularly regarding current or future services for their children. Many parents also needed help in finding reading material about and talking to families with similar children, highlighting the necessity of combating social isolation and providing social support to these families. Across the childcare domain of family needs, respite care was the most requested. We believe that our results offer a significant contribution, as they can be used to make better use of the very limited financial and professional resources that are available to these families.
DOI: 10.17632/2t5wvgmxxr
title: NYC SSO BEAM

description: Biosolids Emissions Assessment Model for NYC Source Separated Organics
DOI: 10.17632/2t5wvgmxxr.1
title: NYC SSO BEAM

description: Biosolids Emissions Assessment Model for NYC Source Separated Organics
DOI: 10.15468/dl.fhmmwn
title: Occurrence Download

description: A dataset containing 2949 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Ischnura denticollis (Burmeister, 1839)"
 ]
}

 The dataset includes 2949 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049681-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hqu3pg
title: Occurrence Download

description: A dataset containing 44 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Strombocarpa tamarugo (Phil.) C.E.Hughes & G.P.Lewis",
 "Country is Chile",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 44 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049682-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/rbwr8td44y
title: Replication codes for “The Art and Science of Monetary and Fiscal Policies in an Emerging Economy”

description: Replication Codes for Sections 6 and 7 in the Study "The Art and Science of Monetary and Fiscal Policies in an Emerging Economy"
DOI: 10.17632/rbwr8td44y.1
title: Replication codes for “The Art and Science of Monetary and Fiscal Policies in an Emerging Economy”

description: Replication Codes for Sections 6 and 7 in the Study "The Art and Science of Monetary and Fiscal Policies in an Emerging Economy"
DOI: 10.17632/bw95h9dt8x
title: metadata dc speed control

description: This dataset contains cleaned metadata extracted from journal articles related to DC motor speed control, collected for a bibliometric and scoping review analysis. The original data was gathered from the Scopus database, using a structured search query based on the PCC (Population–Concept–Context) framework: Population (DC motors), Concept (speed control strategies), and Context (control applications). Only peer-reviewed journal articles in English, published between 2019 and 2024, were included.

After retrieval, metadata such as titles, abstracts, author keywords, sources, and citation data were cleaned using OpenRefine to standardize terms (e.g., unifying “PID” and “Proportional-Integral-Derivative”). The final dataset, comprising 417 articles, was analyzed using VOSviewer for keyword co-occurrence and citation mapping, and Biblioplot for enhanced visual interpretation.

The hypothesis driving this research is that distinct control strategies and optimization methods for DC motor speed control form identifiable research clusters, which can be mapped to reveal trends, gaps, and emerging areas. The findings show four main clusters, corresponding to fuzzy logic methods, PID with metaheuristics, BLDC motor control in renewable/EV applications, and hardware-based implementations.

Researchers and practitioners can use this dataset to explore thematic developments, identify influential works and authors, and inform future studies in intelligent motor control systems.
DOI: 10.17632/bw95h9dt8x.1
title: metadata dc speed control

description: This dataset contains cleaned metadata extracted from journal articles related to DC motor speed control, collected for a bibliometric and scoping review analysis. The original data was gathered from the Scopus database, using a structured search query based on the PCC (Population–Concept–Context) framework: Population (DC motors), Concept (speed control strategies), and Context (control applications). Only peer-reviewed journal articles in English, published between 2019 and 2024, were included.

After retrieval, metadata such as titles, abstracts, author keywords, sources, and citation data were cleaned using OpenRefine to standardize terms (e.g., unifying “PID” and “Proportional-Integral-Derivative”). The final dataset, comprising 417 articles, was analyzed using VOSviewer for keyword co-occurrence and citation mapping, and Biblioplot for enhanced visual interpretation.

The hypothesis driving this research is that distinct control strategies and optimization methods for DC motor speed control form identifiable research clusters, which can be mapped to reveal trends, gaps, and emerging areas. The findings show four main clusters, corresponding to fuzzy logic methods, PID with metaheuristics, BLDC motor control in renewable/EV applications, and hardware-based implementations.

Researchers and practitioners can use this dataset to explore thematic developments, identify influential works and authors, and inform future studies in intelligent motor control systems.
DOI: 10.17632/k84bkv8dkt
title: Cognitive Distortion Dataset for Text Classification in Bahasa Indonesia

description: This dataset is text data related to cognitive distortion sentences that are closely related to thought disorder. This is the first dataset of cognitive distortion sentences in Indonesian. This dataset is a collection of distortion/non-distortion sentences generated from online questionnaire answers. The questions are compiled by experts in this case a psychologist. Annotation is also done by experts to obtain distortion classes. The distribution of existing cognitive distortion classes is adjusted to the theory of Burns, D.D. (1999) in the book "The Feeling Good Handbook". The total generated sentence data is 4662, there are complete sentences and parts of sentences that are distortion parts flanked by the "$" sign, along with labels from two annotators in separate columns. Several distortion classes with a limited number of samples were augmented using the back-translation method. The four augmented classes are "Mental Filter," "All-or-Nothing Thinking," "Magnification or Minimization," and "Emotional Reasoning." Each class was expanded to a total of 200 samples. The back-translation process utilized five languages: Chinese (ZH), English (EN), Javanese (JV), Malay (MS), and Tagalog (TG). In the accompanying CSV file, the "DATA STATUS" column indicates the origin of each sentence. Entries labeled "ORI-RAW" refer to raw data collected directly from questionnaire responses. Entries labeled "DIS-[...]" represent distortion sentences generated through back-translation using the five language codes (ZH, EN, JV, MS, and TG). Apart from Indonesian, an English version is also available.
DOI: 10.17632/k84bkv8dkt.4
title: Cognitive Distortion Dataset for Text Classification in Bahasa Indonesia

description: This dataset is text data related to cognitive distortion sentences that are closely related to thought disorder. This is the first dataset of cognitive distortion sentences in Indonesian. This dataset is a collection of distortion/non-distortion sentences generated from online questionnaire answers. The questions are compiled by experts in this case a psychologist. Annotation is also done by experts to obtain distortion classes. The distribution of existing cognitive distortion classes is adjusted to the theory of Burns, D.D. (1999) in the book "The Feeling Good Handbook". The total generated sentence data is 4662, there are complete sentences and parts of sentences that are distortion parts flanked by the "$" sign, along with labels from two annotators in separate columns. Several distortion classes with a limited number of samples were augmented using the back-translation method. The four augmented classes are "Mental Filter," "All-or-Nothing Thinking," "Magnification or Minimization," and "Emotional Reasoning." Each class was expanded to a total of 200 samples. The back-translation process utilized five languages: Chinese (ZH), English (EN), Javanese (JV), Malay (MS), and Tagalog (TG). In the accompanying CSV file, the "DATA STATUS" column indicates the origin of each sentence. Entries labeled "ORI-RAW" refer to raw data collected directly from questionnaire responses. Entries labeled "DIS-[...]" represent distortion sentences generated through back-translation using the five language codes (ZH, EN, JV, MS, and TG). Apart from Indonesian, an English version is also available.
DOI: 10.17632/jx72cwnprz
title: Environmental Kuznets Curve Applications for Water Pollution in the EU

description: Purpose of the dataset

This dataset is intended to be used to utilize information provided in the paper: Environmental Kuznets Curve Applications for Water Pollution in the EU. This research investigates the effects of economic activity from five economic sectors on biological oxygen demand (BOD) - a common form of water pollution. 

Contents

This repository contains panel data, regression code, and figures related to the analysis of sectoral GDP and Biological Oxygen Demand (BOD) across 18 EU countries (2000–2021). The data files included are in CSV format, while the code is in .rmd format.

Data sources
BOD data (EEA, 2024). BOD is measured in milligrams of O2 per litre. 
GDP data (Eurostat, 2025), with the unit of measurement being the current price in millions of euros. 
Freshwater withdrawal rates (UN Water).
Environmental flow requirements Food and Agricultural Organization of the United Nations (FAO). Units are in terms of 10*9 m3/year. 
Dam Capacity (Aquastat) measured as Total Dam Capacity in km*3.
Freshwater resources (World Bank) in billion cubic meters.
Primary Education rates (World Bank) as a percentage of primary school age children.
Environmental taxes (OECD) measured in millions of U.S. dollars. 
Employment (Eurostat) (thousands of people).
Total population (World Bank) is a measure of the number of inhabitants per country.
Energy balances (Eurostat) measured in thousand tons of oil equivalent.
Fossil fuel emissions (Eurostat) measured in thousand tonnes.
Primary energy consumption (Our World in Data) is measured in terawatt-hours. 
Emissions allude (EEA) measured in thousand tonnes.

README availability
A detailed README.txt is included that explains how to use the files.
DOI: 10.17632/jx72cwnprz.1
title: Environmental Kuznets Curve Applications for Water Pollution in the EU

description: Purpose of the dataset

This dataset is intended to be used to utilize information provided in the paper: Environmental Kuznets Curve Applications for Water Pollution in the EU. This research investigates the effects of economic activity from five economic sectors on biological oxygen demand (BOD) - a common form of water pollution. 

Contents

This repository contains panel data, regression code, and figures related to the analysis of sectoral GDP and Biological Oxygen Demand (BOD) across 18 EU countries (2000–2021). The data files included are in CSV format, while the code is in .rmd format.

Data sources
BOD data (EEA, 2024). BOD is measured in milligrams of O2 per litre. 
GDP data (Eurostat, 2025), with the unit of measurement being the current price in millions of euros. 
Freshwater withdrawal rates (UN Water).
Environmental flow requirements Food and Agricultural Organization of the United Nations (FAO). Units are in terms of 10*9 m3/year. 
Dam Capacity (Aquastat) measured as Total Dam Capacity in km*3.
Freshwater resources (World Bank) in billion cubic meters.
Primary Education rates (World Bank) as a percentage of primary school age children.
Environmental taxes (OECD) measured in millions of U.S. dollars. 
Employment (Eurostat) (thousands of people).
Total population (World Bank) is a measure of the number of inhabitants per country.
Energy balances (Eurostat) measured in thousand tons of oil equivalent.
Fossil fuel emissions (Eurostat) measured in thousand tonnes.
Primary energy consumption (Our World in Data) is measured in terawatt-hours. 
Emissions allude (EEA) measured in thousand tonnes.

README availability
A detailed README.txt is included that explains how to use the files.
DOI: 10.17632/4t5vy62fm6
title: HFCHEBY2D13

description: A Fortran90 source code of Function HFCHEBY2D13 to calculate values of Ambartsumian-Chandrasekhar H-function for isotropic scattering with 13-digit accuracy for a given set of values for the single scattering albedo and the angular parameter mu. The formula implemented is based on numerical fittings by a bivariate Chebyshev polynomial to the values of this function calculated with 15-digit accuracy.