cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/749k3cwbnm
title: Dataset for Autism Diagnosis Based on DSM-5

description: Autism is a neurodevelopmental condition affecting individuals from childhood up to adulthood. Individuals living with Autism are said to be having challenges with cognitive, social, and communication skills. According to the DSM5 criteria, there are 3 levels of Autism: Level 1, Level 2, and Level 3. Knowing the severity level of an individual after diagnosis helps in providing the right therapy for the individual. Most research work has focused on the diagnosis of autism, as in discriminating autistic individuals from non-autistic individuals. Very few works have been done in classifying autism into its severity levels based on the DSM 5 criteria. In this study, we collected datasets from individuals based on the guidelines of the DSM5 criteria using the google forms questionnaire.
DOI: 10.17632/pj9y4h24p2
title: Data for: Visual cues of threat elicit greater steady-state electroencephalographic responses than visual reminders of death

description: EEG data associated with the two experiments described in the paper. Neuroscan raw format (see methods section). The corresponding author can be contacted for other formats (eeglab .set) or questions related to the data (e.g. markers).
DOI: 10.17632/4pkhgx8wcb
title: PAR2 : Parallel Random Walk Particle Tracking Method for solute transport in porous media

description: Computational modeling of solute migration in groundwater systems is a fundamental component in water resources management and risk analysis. Therefore, it is imperative to have fast and reliable computational tools to simulate solute transport in groundwater systems. In this work we present PAR2, a GPU-accelerated solute transport simulator based on the Random Walk Particle Tracking (RWPT) technique, a Lagrangian method particularly suited for parallelization. PAR2 is able to run on any computing platform equipped with an NVIDIA GPU, such as common desktops and High-Performance Computing (HPC) nodes. The program is developed in C++/CUDA. In our illustration, groundwater flow is simulated on a structured grid using MODFLOW, which can be linked to PAR2 using the LMT package. Simulation parameters can be defined through a convenient YAML configuration file. Additionally, we propose an analytical treatment of the dispersion tensor that allows the RWPT to be effectively implemented using GPU parallelization. The speedup gained with the parallelization drastically reduces the total simulation time, allowing the application of computationally expensive algorithms (e.g., Monte-Carlo simulation) on large-scale stochastic hydro-systems.
DOI: 10.6084/m9.figshare.23662662.v1
title: Wearable sensor data during in-lab vs. real-world running

description: This repository contains the data from "Are Gait Patterns during in-Lab Running Representative of Gait Patterns during Real-World Training? An Experimental Study" by Davis et al. 2024. Please cite if you use the data or the code. Davis IV JJ, Meardon SA, Brown AW, Raglin JS, Harezlak J, Gruber AH. Are Gait Patterns during In-Lab Running Representative of Gait Patterns during Real-World Training? An Experimental Study. Sensors. 2024 May 1;24(9):2892. <br>Data processing code are available on GitHub: https://github.com/johnjdavisiv/inlab-vs-realworld
DOI: 10.6084/m9.figshare.3171472.v10
title: EventWiki: A knowledge base of major events

description: <pre>EventWiki is a knowledge base of major events happening throughout mankind history. It contains 21,229 events of 95 types. The details of event entries can be found in our paper submission and documentation file. Data in the knowledge base is mainly harvested from Wikipedia.</pre><pre>As Wikipedia, this resource can be distributed and shared under CC-BY 3.0 license.</pre>
DOI: 10.17632/bjtty5rhcd
title: Data for: A 3-D Structural Model of the Saddle Mountains, Yakima Fold Province Washington, USA: Implications for Late Tertiary Tectonic Evolution of the Columbia River Flood Basalt Province
DOI: 10.17632/rzhpmgkjjx
title: Income inequality-growth_South Africa

description: This study investigates the empirical association between income inequality and economic growth in South Africa from 1989 to 2018.  
The study uses annual time series data from 1989 to 2018. The length of the study is based on the availability of data. We obtain the data from the World Development Indicators (World Bank), 2022, Quantec EasyData, 2022, Penn World 10.0, Chartbook of Economic Inequality by Atkinson et al. (2017) and Standardized World Income Inequality Database (SWIID) 9.2.
DOI: 10.17632/t2cxrczh7h
title: Interpreting the shifts in forest structure, plant community composition, diversity, and functional identity by using remote sensing-derived wildfire severity

description: Background
Wildfires are increasingly impacting ecosystems worldwide especially in temperate dry habitats, often interplaying with other global changes (e.g., biological invasion). Understanding the ecological consequences of wildfires is crucial for effective conservation and management strategies. The aim of this study is to investigate how the wildfire severity impacts on plant community (both the forest and herbaceous layer) and non-native plant invasion, combining filed observations and remote sensing data.
We conducted an observational study in the Karst forests one year after the large wildfire which affected the area in 2022 through 35 field plots (200 m2 each) distributed among different fire severity classes assessed using the Normalized Burn Ratio (dNBR) calculated from satellite images. In each plot, tree species, diameter, vitality, resprouting capacity and seedling density were measured. As well, herb species richness (taxonomical diversity) was quantified and plant cover visually estimated. Functional diversity was also assessed considering six functional traits retrieved by existing trait database.
Results
Our results highlight the vulnerability of the forest stands to an increase in wildfire severity, resulting in significant mortality and changes in tree community structure. Some tree species (i.e., Quercus pubescens) showed an higher resistance to the fire, while other showed a higher resilience (i.e. recovery after fire through resprouting or seedlings). The transition to a shrub-dominated community (i.e., Cotinus coggygria) where fire severity was the highest underlines the dynamic nature of the post-fire succession. We also detected a significant shift in herbaceous plant community composition, diversity and functional identity with fire severity: high-fire severity areas exhibited higher species richness compared to low-severity or unburned areas. Total non-native plant cover increased with fire severity while native cover remained constant. We also found shifts in species and functional composition, particularly for traits related to germination potential and growth strategy.
Conclusions
This study contributes to the understanding of ecological processes after wildfires in temperate forests, emphasizing the need for conservation strategies aimed at limiting fire damages while increasing prevention.
DOI: 10.6084/m9.figshare.14128502.v1
title: ATX toxins extracellular recordings.xlsx

description: Data concerning nerve activivty under control conditions and after application of sea anemone toxins
DOI: 10.6084/m9.figshare.880644.v1
title: TB - 3 combined datasets (TB MLSMR, CB2 and Kinase)

description: combined dataset from TB paper J Chem Inf Model. 2013 Nov 25;53(11):3054-63. doi: 10.1021/ci400480s. Epub 2013 Oct 30. Fusing Dual-Event Data Sets for Mycobacterium tuberculosis Machine Learning Models and Their Evaluation. Ekins S, Freundlich JS, Reynolds RC. Author information Abstract The search for new tuberculosis treatments continues as we need to find molecules that can act more quickly, be accommodated in multidrug regimens, and overcome ever increasing levels of drug resistance. Multiple large scale phenotypic high-throughput screens against Mycobacterium tuberculosis (Mtb) have generated dose response data, enabling the generation of machine learning models. These models also incorporated cytotoxicity data and were recently validated with a large external data set. A cheminformatics data-fusion approach followed by Bayesian machine learning, Support Vector Machine, or Recursive Partitioning model development (based on publicly available Mtb screening data) was used to compare individual data sets and subsequent combined models. A set of 1924 commercially available molecules with promising antitubercular activity (and lack of relative cytotoxicity to Vero cells) were used to evaluate the predictive nature of the models. We demonstrate that combining three data sets incorporating antitubercular and cytotoxicity data in Vero cells from our previous screens results in external validation receiver operator curve (ROC) of 0.83 (Bayesian or RP Forest). Models that do not have the highest 5-fold cross-validation ROC scores can outperform other models in a test set dependent manner. We demonstrate with predictions for a recently published set of Mtb leads from GlaxoSmithKline that no single machine learning model may be enough to identify compounds of interest. Data set fusion represents a further useful strategy for machine learning construction as illustrated with Mtb. Coverage of chemistry and Mtb target spaces may also be limiting factors for the whole-cell screening data generated to date.
DOI: 10.17632/97p7knbk42
title: Pancreatic Cancer Biomedical Knowledge Graph

description: This dataset comprises approximately 1 million high-confidence biomedical triples focused on pancreatic cancer, constructed from a curated set of 23 relevant biomedical entities (KRAS, TP53, gemcitabine) and 11 common relation types ( mutated_in, treats, interacts_with). Each triple is embedded in a synthetic, natural language sentence mimicking scientific phrasing and is paired with a simulated attention score ranging from 0.75 to 1.00, reflecting transformer-based model confidence. Heuristic boosting was applied to biologically plausible combinations, resulting in an average attention score near 0.88. This structured resource is ideal for training, validating, or benchmarking biomedical NLP models and knowledge extraction systems within the context of pancreatic cancer.
DOI: 10.17632/m46zzy576w
title: GST Growth rate comparison - India (Maharashtra and Karnataka)

description: Description of the Dataset
The dataset utilized in this analysis focuses on the Goods and Services Tax (GST) growth rates for different regions in India, specifically the national level as well as the states of Maharashtra and Karnataka. This dataset is structured to facilitate a comparative analysis of GST growth over time, providing insights into economic trends and regional performance. Below is a detailed description of the dataset components and their significance:
Dataset Structure
Columns:
Month-Year: This column contains time-series data formatted as "Month-Year" (e.g., "January-2023"), representing specific months within a given year. It serves as the temporal axis for the analysis, allowing for tracking changes in GST growth rates over time.
National Growth Rate (%): This column reflects the percentage growth rate of GST at the national level. It indicates how GST revenue has changed over time, providing a broad view of economic performance across India.
Maharashtra Growth Rate (%): This column presents the GST growth rate specifically for the state of Maharashtra, one of India's largest economies. Analyzing this data helps understand how Maharashtra's economy is performing relative to national trends.
Karnataka Growth Rate (%): Similar to the Maharashtra column, this one details the GST growth rate for Karnataka, another significant state in terms of economic contribution and development.
Purpose of the Dataset
The primary purpose of this dataset is to enable stakeholders—such as policymakers, economists, business analysts, and researchers—to analyze and compare GST growth rates across different regions over time. By visualizing these trends, users can identify patterns, assess regional economic health, and make informed decisions based on historical performance.
Visualization
The accompanying code snippet creates a visual representation of this dataset using a line plot. Key features of the visualization include:
Comparative Analysis: The plot displays three distinct lines representing national, Maharashtra, and Karnataka GST growth rates, allowing for easy comparison between these datasets.
Markers and Colors: Each line is marked with circular markers and colored differently to enhance clarity and facilitate differentiation among the three growth rate trends.
Grid and Labels: The plot includes grid lines for better readability and clearly labeled axes to indicate what each dimension represents (Month-Year on the x-axis and GST Growth Rate (%) on the y-axis).
DOI: 10.17632/2pxf4zdyhr
title: Prolactin EDS-Mogavero et al- raw

description: Study Objectives were: to identify subjects with hyperprolactinemia in a clinical sample of patients; to separate participants with a complaint of significant excessive daytime sleepiness (EDS) from those without; to compare the neurological and sleep conditions found in patients subgrouped by EDS and hyperprolactinemia; to identify patients with hyperprolactinemia and EDS not supported by the presence of any other neurological or sleep disorder, or substance/medication use. A retro-spective chart review of inpatients was carried out in order to identify all patients in whom the prolactin (PRL) serum levels were determined. A total of 130 subjects were retrieved: 55 had in-creased levels of PRL while the remaining 75 participants had normal PRL levels. EDS was reported by 32 (58.2%) participants with increased PRL and 34 (45.3) with normal PRL. EDS was associated with a sleep or neurological condition in all participants with normal PRL (especially obstructive sleep apnea, 79.4%), but not in those with increased PRL, among whom eight had no other neu-rologic or sleep disorder (or drug) potentially causing EDS and, at polysomnography, had time in bed, sleep period time, and total sleep time longer than those with an associated condition. These findings can be considered as a proof of concept supporting the hypothesis of a role of hyperpro-lactinemia in EDS and represent a basis for future controlled studies able to test in a reliable, ob-jective, and methodologically more appropriate way this hypothesis.
DOI: 10.17632/62n6t9vndv
title: Damping identification

description: Data used for the paper preparation
DOI: 10.17632/9fkgx5c5yb
title: data for APA onset time and magnitude based on different level of expertise and temporal pressure

description: SPSS file for onset time and magnitude of Anticipatory postural adjustment level of expertise consist of skilled and novice player temporal pressure consist of low and high stimulus speed
DOI: 10.17632/mtd59df24s
title: Datset for "Social Media Use, Self-Efficacy, Perceived Threat and Preventive Behavior in Pakistan in Times of COVID-19: Results of a Cross-Sectional Study in Pakistan"

description: We aimed to determine whether there is a relationship between social media use, preventive behavior, the perceived threat of coronavirus, self-efficacy, and socio-demographic characteristics. We used the online sampling technique to interview 310 respondents across Pakistan for a cross-sectional survey. The paper from this data titled "Social Media Use, Self-Efficacy, Perceived Threat and Preventive Behavior in Pakistan in Times of COVID-19: Results of a Cross-Sectional Study in Pakistan" is currently under consideration for publication in Frontiers in Psychology.
DOI: 10.17632/2nhm7vpx7y
title: Supplemental Material - Efficacy and Tolerability of Low-Dose Versus High-Dose Doxycycline in the Management of Lymphocytic Scarring Alopecias

description: Supplemental tables for the publication entitled, "Efficacy and Tolerability of Low-Dose Versus High-Dose Doxycycline in the Management of Lymphocytic Scarring Alopecias." These supplemental tables include a breakdown of adjunctive treatments, associations between doxycycline dose and clinical outcomes for the FFA/LPP cohort alone, and associations between doxycycline dose and patient/provider evaluations and change in trichoscopic measures.
DOI: 10.17632/59mryz4czw
title: A single-cell transcriptome atlas of adult male and female human hookworm Ancylostoma ceylanicum - Supplementary Table S1

description: Supplementary Table S1: Functional annotations, cluster marker statistics and gene expression values per cluster for every A. ceylanicum protein coding gene.
DOI: 10.17632/k4ndccmy5b
title: Longitudinal Examination of Exercise Addiction

description: There are few cases of exercise addiction reported in the literature. However, this subject receives substantial attention in the field of sports and exercise psychology. Recent research suggests that the risk for exercise addiction (REA) is largely predicted by passion, which is associated with the motivation of the individual. The objective of this 12-week longitudinal study was to examine the temporal changes in these variables in women and men (N=149) who started a new sport activity. Latent growth modeling showed that REA and passion were high at baseline and showed a slight increase over the 12 weeks. Motivational factors predicted passion, whereas REA was predicted by gender, team sport participation, exercise intensity, and identified motivation. These findings show that the development of passion and REA over time, both partially mediated by motivation, manifest independent patterns. Consequently, despite the reported relationship between the two, they appear to be independent constructs.
DOI: 10.17632/k5g548t5x6
title: Supplemental Material: Effectiveness and tolerability of ritlecitinib in children with alopecia areata: A case series

description: Supplementary table 1. Characteristics of alopecia areata patients treated with ritlecitinib
Supplementary figures (a, b, c). Clinical images of patients treated with ritlecitinib (figures a, b, and c correspond to patients 1, 2, and 9, respectively).
DOI: 10.17632/txjp3zjwjj
title: Expectations, structural breaks and the recent surge in inflation - replication files

description: These files are to replicate the results in "Expectations, structural breaks and the recent surge in inflation"
DOI: 10.6084/m9.figshare.25378828.v1
title: Tooth Isotope Data from the Netherlands

description: Human tooth (dentin and enamel) samples from the Netherlands.Strontium, oxygen, carbon and nitrogen isotope data.
DOI: 10.6084/m9.figshare.28887671.v1
title: RAGE rs184003 rs2070600 genotyping.xlsx

description: The database contains genotyping data for 2 SNPs in the RAGE gene (rs2070600 G/A and rs184003 G/T) in 336 patients with acute coronary syndrome (ACS) in their medical history: 175 &lt; 50 years old, 161 ≥ 50 years old, and 160 control subjects matched for ethnicity, age, and sex, using the restriction fragment length polymorphism method.
DOI: 10.17632/s3wcyw3r64
title: Data of characteristics related to morphology, components and wettablity of the epidermis of a butterfly species （2）

description: A comprehensive investigation was conducted to characterize the epidermal features of third-to-fifth instar Papilio polytes larvae, with systematic analysis encompassing three types of critical features: ultrastructural, chemical composition, and surface wettability. Morphometric evaluation was performed through high-resolution scanning electron microscopy (SEM) to quantify ultrastructural details of the larval epidermis. Compositional profiling was achieved using Fourier-transform infrared (FTIR) spectroscopy in the mid-infrared range (4000-400 cm⁻¹), enabling precise identification of chemical functional groups. Hydrophobic properties were quantitatively assessed through contact angle measurements employing the sessile drop method.
DOI: 10.17632/thnzm3yk23
title: Dataset of Jordanian University Students’ Psychological Health Impacted by Using E-learning Tools during COVID-19

description: COVID-19 has affected different sectors in society, and education is not an exception. Schools and higher education institutions were among the most affected. In Jordan, the government imposed an emergency state through taking strict measures to prevent further spread of the virus. These measures included closing borders, suspending schools and universities, halting flights, banning gatherings, quarantine, and others. Students’ shifting to the e-learning model led to the prolonged use of digital e-learning tools including smartphones, laptops, and i-pad tablets, which ultimately affected their mental health and their psychological well-being. This dataset focuses on the impact of the excessive use of COVID-19’s e-learning digital tools on university students’ psychological and mental health. The dataset further investigates whether there is a correlation between the students’ prolonged use of e-learning digital tools, imposed by the COVID-19 crisis, and the psychosomatic symptoms and disorders. A Likert-type questionnaire was administered in Arabic, being the official language in Jordan. This dataset contains two main sections; the first section is demographic information, and the second section reports on the psychosomatic impact of COVID-19’s e-learning digital tools on university students’ well-being. A total of 775 responses were received, and the data were analyzed according to Likert’s five-point scale, where frequencies and percentages were calculated. The demographic information part aimed to gather information about gender, level/year (first/freshman, second/ sophomore, third/junior, fourth/senior, or other), age (18-24, 25-30, or 30+), cumulative average/GPA ( +90 / 3.5+, 80-89 / 3.0-3.49, 70-79 / 2.5-2.99, 60-69 / 2.0-2.49, Below 60 / Below 2.0 or other). The second section consisted of five main constructs. The first construct is concerned with the use of digital tools (mobile phone, laptop, i-pad) before and after COVID-19. This construct identifies the type of digital tools used, length of use before and after COVID-19, and whether their excessive use for academic purposes led to distraction. The second construct seeks to compare the students’ sleeping habits before and after COVID-19, and if their frequent use of e-learning tools interfered with their bedtime and wake-up. The third construct aims to elicit responses on the students’ social behaviour and the extent to which the closures, lockdowns, and curfews, in addition to their prolonged use of e-learning tools, have impacted their everyday life routines. The fourth construct focused on the psychological state of students after having undergone unfavourable conditions during the COVID-19 crisis. This was reflected in cases of stress, frustration, tension, and depression. The last construct seeks to probe into the consequences of the above factors, i.e. social and psychological, on the students’ academic performance and achievements.
DOI: 10.17632/tszrbdcn4k
title: Replication data for project "Develop STEAM education projects for Vietnamese preschool children based on local cultural aspect"

description: This dataset surveyed 754 preschool teachers across ten cities and provinces in Vietnam from 8 Apr 2022 to 15 May 2022. The surveys included eight demographic questions and 56 measurement items on four, five, and six Likert scales. The dataset includes seven main sections: (i) Demographics; (ii) Teachers' knowhow about STEAM education; (iii) Teachers' competencies; (iv) Conditions to implement STEAM projects; (v) School policies; (vi) Local culture factors integrated with STEAM projects; and (vii) Teachers' willingness to implement STEAM education. This data set primarily clarified the relationship between willingness to implement STEAM education activities for preschool children and the following factors: self-knowledge; own proficiency level; operating conditions; level of support for implementing STEAM education projects; and ability to integrate local cultural factors.