cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/tpc5czcc99
title: Date for Pennisetum flaccidum Patch Formation Promotes Soil Fine Particle Enrichment and “Fertile Island” Development in Alpine Meadow of Damxung, Tibetan

description: Data Description
Research Hypothesis
This study tested the hypothesis that Pennisetum flaccidum patch formation enhances soil fine particle enrichment and creates "fertile islands" by increasing aboveground biomass and vegetation coverage in the Damxung alpine meadow, Tibet.
Data Overview
The dataset was generated through field sampling and laboratory analysis in October 2024. It includes:
Vegetation Data: Species composition, aboveground biomass (AGB), vegetation coverage (C), and P. flaccidum height across different patch sizes (Small/SP, Medium/MP, Large/LP) and unpatched controls (OP).
Soil Data:
Particle-size distribution (clay, silt, sand fractions)
Physical properties: bulk density (BD), soil water content (SWC)
Chemical properties: pH, electrical conductivity (EC)
Nutrients: total carbon (TC), nitrogen (TN), phosphorus (TP), soil organic carbon (SOC), available nitrogen (AN), available phosphorus (AP)
Structural index: soil monofractal dimension (D)
Sampling Design: Five replicates per patch size and control. Soil samples collected from 0-10 cm, 10-20 cm, and 20-30 cm depths using five-point sampling.
Key Findings
Vegetation: AGB and coverage were significantly higher inside patches (up to 693 g·m⁻² and 96%) versus outside (112 g·m⁻² and 71%).
Soil Texture: Patches had significantly higher clay/silt content and lower sand content. Soil monofractal dimension was significantly higher inside patches.
Fertile Islands: Patches accumulated more SOC, TN, AN, and AP, with reduced bulk density.
Drivers: AGB, coverage, AN, and SWC were identified as primary factors improving soil structure.
Data Interpretation & Usage
The data supports that P. flaccidum patches initiate a plant-soil feedback loop: increased biomass reduces erosion and enriches fine particles, improving soil texture and nutrients. This dataset is valuable for research on grassland ecology, soil erosion control, and alpine ecosystem restoration. It can be used for meta-analyses, model validation, and informing sustainable grassland management strategies.
DOI: 10.17632/tpc5czcc99.1
title: Date for Pennisetum flaccidum Patch Formation Promotes Soil Fine Particle Enrichment and “Fertile Island” Development in Alpine Meadow of Damxung, Tibetan

description: Data Description
Research Hypothesis
This study tested the hypothesis that Pennisetum flaccidum patch formation enhances soil fine particle enrichment and creates "fertile islands" by increasing aboveground biomass and vegetation coverage in the Damxung alpine meadow, Tibet.
Data Overview
The dataset was generated through field sampling and laboratory analysis in October 2024. It includes:
Vegetation Data: Species composition, aboveground biomass (AGB), vegetation coverage (C), and P. flaccidum height across different patch sizes (Small/SP, Medium/MP, Large/LP) and unpatched controls (OP).
Soil Data:
Particle-size distribution (clay, silt, sand fractions)
Physical properties: bulk density (BD), soil water content (SWC)
Chemical properties: pH, electrical conductivity (EC)
Nutrients: total carbon (TC), nitrogen (TN), phosphorus (TP), soil organic carbon (SOC), available nitrogen (AN), available phosphorus (AP)
Structural index: soil monofractal dimension (D)
Sampling Design: Five replicates per patch size and control. Soil samples collected from 0-10 cm, 10-20 cm, and 20-30 cm depths using five-point sampling.
Key Findings
Vegetation: AGB and coverage were significantly higher inside patches (up to 693 g·m⁻² and 96%) versus outside (112 g·m⁻² and 71%).
Soil Texture: Patches had significantly higher clay/silt content and lower sand content. Soil monofractal dimension was significantly higher inside patches.
Fertile Islands: Patches accumulated more SOC, TN, AN, and AP, with reduced bulk density.
Drivers: AGB, coverage, AN, and SWC were identified as primary factors improving soil structure.
Data Interpretation & Usage
The data supports that P. flaccidum patches initiate a plant-soil feedback loop: increased biomass reduces erosion and enriches fine particles, improving soil texture and nutrients. This dataset is valuable for research on grassland ecology, soil erosion control, and alpine ecosystem restoration. It can be used for meta-analyses, model validation, and informing sustainable grassland management strategies.
DOI: 10.5281/zenodo.15838995
title: Raw X-ray diffraction data for crystal structures of human PTP1B variants

description: Raw X-ray diffraction data for crystallographic structures featured in the following preprint:  Perdikari*, Woods*, Ebrahim*, et al. "Structures of human PTP1B variants reveal allosteric sites to target for weight loss therapy" (2024) bioRxiv.

Updated citation:  Perdikari*, Woods*, Ebrahim*, et al. "Structures of human protein tyrosine phosphatase variants reveal targetable allosteric sites" (2025) Journal of Biological Chemistry. 

These data are deposited to the RCSB Protein Data Bank under the following PDB IDs (accession codes): 9CYO for WT, 9CYP for I19V, 9CYQ for Q78R, and 9CYR for D245G.
DOI: 10.5281/zenodo.15838996
title: Raw X-ray diffraction data for crystal structures of human PTP1B variants

description: Raw X-ray diffraction data for crystallographic structures featured in the following preprint:  Perdikari*, Woods*, Ebrahim*, et al. "Structures of human PTP1B variants reveal allosteric sites to target for weight loss therapy" (2024) bioRxiv.

Updated citation:  Perdikari*, Woods*, Ebrahim*, et al. "Structures of human protein tyrosine phosphatase variants reveal targetable allosteric sites" (2025) Journal of Biological Chemistry. 

These data are deposited to the RCSB Protein Data Bank under the following PDB IDs (accession codes): 9CYO for WT, 9CYP for I19V, 9CYQ for Q78R, and 9CYR for D245G.
DOI: 10.17632/n8xwb84yzv
title: Dataset Support Storytelling Marketing for Sustainable Consumer Engagement: A PLS-SEM Study on Brand Trust and Purchase Decision in the Beauty Industry

description: Dataset Support Storytelling Marketing for Sustainable Consumer Engagement: A PLS-SEM Study on Brand Trust and Purchase Decision in the Beauty Industry
DOI: 10.17632/n8xwb84yzv.1
title: Dataset Support Storytelling Marketing for Sustainable Consumer Engagement: A PLS-SEM Study on Brand Trust and Purchase Decision in the Beauty Industry

description: Dataset Support Storytelling Marketing for Sustainable Consumer Engagement: A PLS-SEM Study on Brand Trust and Purchase Decision in the Beauty Industry
DOI: 10.17632/cxwg3t62mz
title: Dataset Support Storytelling Marketing for Sustainable Consumer Engagement: A PLS-SEM Study on Brand Trust and Purchase Decision in the Beauty Industry

description: Dataset Support Storytelling Marketing for Sustainable Consumer Engagement: A PLS-SEM Study on Brand Trust and Purchase Decision in the Beauty Industry
DOI: 10.17632/cxwg3t62mz.1
title: Dataset Support Storytelling Marketing for Sustainable Consumer Engagement: A PLS-SEM Study on Brand Trust and Purchase Decision in the Beauty Industry

description: Dataset Support Storytelling Marketing for Sustainable Consumer Engagement: A PLS-SEM Study on Brand Trust and Purchase Decision in the Beauty Industry
DOI: 10.17632/g53b22v2wp
title: Crowd-Trust-Grid Emergency Decision Dataset

description: The Crowd-Trust-Grid Emergency Decision-Making Dataset is a large-scale partial dataset focused on emergency scenarios in the power grid. This dataset consolidates data fragments from multiple sources, including attributes of 20 experts, sampled public opinion texts from social media platforms, partial evaluation records from experts on a limited set of solutions, and so on.
DOI: 10.17632/g53b22v2wp.1
title: Crowd-Trust-Grid Emergency Decision Dataset

description: The Crowd-Trust-Grid Emergency Decision-Making Dataset is a large-scale partial dataset focused on emergency scenarios in the power grid. This dataset consolidates data fragments from multiple sources, including attributes of 20 experts, sampled public opinion texts from social media platforms, partial evaluation records from experts on a limited set of solutions, and so on.
DOI: 10.15468/dl.26wzfu
title: Occurrence Download

description: A dataset containing 733 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sphaceloma",
 "HasCoordinate is true"
 ]
}

 The dataset includes 733 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000336-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/5tt5bp4skx
title: News Coverage of the Access Hollywood Tape in 2016, 2020, and 2024
DOI: 10.17632/5tt5bp4skx.1
title: News Coverage of the Access Hollywood Tape in 2016, 2020, and 2024
DOI: 10.17632/yc7tvmmr73
title: Arce-Gallego et al; Combination therapy overcomes secondary PARPi resistance in ATM-deficient prostate cancer. DOI: 10.1038/s41698-025-01179-y

description: Data from publication DOI: 10.1038/s41698-025-01179-y
Targeted NGS (DNA) and RNAseq data (expression levels and DGEA) included in this manuscript
DOI: 10.17632/yc7tvmmr73.1
title: Arce-Gallego et al; Combination therapy overcomes secondary PARPi resistance in ATM-deficient prostate cancer. DOI: 10.1038/s41698-025-01179-y

description: Data from publication DOI: 10.1038/s41698-025-01179-y
Targeted NGS (DNA) and RNAseq data (expression levels and DGEA) included in this manuscript
DOI: 10.17632/shr3wzpvbk
title: Multi-dimensional evaluation of the similarity between infant formulas and human milk based on macronutrients, fatty acid composition and positional distribution, and sn-2 palmitoyl triacylglycerols

description: The development of infant formulas is focused on simulating the nutritional structure of human milk, aiming to narrow the gap with breastfeeding. To evaluate infant formulas’ similarity to human milk, the nutrient composition and energy supply, fatty acids, sn-2 fatty acids, and sn-2 palmitoyl triacylglycerols (OPO/OPL) in 12 commercial infant formulas samples and human milk samples from Hainan Island, China, were determined in this study. Similarity evaluations between infant formulas and human milk were conducted from multiple dimensions using the optimal distance method and multivariate statistical analysis. It is hoped that this can provide data references for future in-depth studies on the humanization of infant formulas, contributing to the development of high-quality products that are more similar to the nutritional structure of human milk. The data submitted here are the specific scores for each individual evaluation indicator of different brands of infant formula milk powder at various levels, calculated using the optimal value distance method.
DOI: 10.17632/shr3wzpvbk.2
title: Multi-dimensional evaluation of the similarity between infant formulas and human milk based on macronutrients, fatty acid composition and positional distribution, and sn-2 palmitoyl triacylglycerols

description: The development of infant formulas is focused on simulating the nutritional structure of human milk, aiming to narrow the gap with breastfeeding. To evaluate infant formulas’ similarity to human milk, the nutrient composition and energy supply, fatty acids, sn-2 fatty acids, and sn-2 palmitoyl triacylglycerols (OPO/OPL) in 12 commercial infant formulas samples and human milk samples from Hainan Island, China, were determined in this study. Similarity evaluations between infant formulas and human milk were conducted from multiple dimensions using the optimal distance method and multivariate statistical analysis. It is hoped that this can provide data references for future in-depth studies on the humanization of infant formulas, contributing to the development of high-quality products that are more similar to the nutritional structure of human milk. The data submitted here are the specific scores for each individual evaluation indicator of different brands of infant formula milk powder at various levels, calculated using the optimal value distance method.
DOI: 10.17632/vzfyk22fhn.2
title: Student Performance Dataset in AI course

description: This dataset contains student performance records from an Artificial Intelligence (AI) course conducted at Universiti Teknologi Malaysia (UTM). The data includes various academic performance metrics and demographic details of students enrolled in the course. This dataset is valuable for educational data mining, machine learning applications, and predictive analytics in AI education. This dataset can be used for AI-driven analysis of student performance, predicting academic success, and understanding factors that influence learning outcomes
DOI: 10.17632/pyxbw4h2w4
title: Dataset_TerapiaOcupacional_CentrosMayores_Madrid

description: Este conjunto de datos contiene las respuestas anonimizadas de un estudio observacional transversal cuyo objetivo fue analizar las ratios profesionales y las funciones del personal de terapia ocupacional en centros de atención a personas mayores de la Comunidad de Madrid (España).

Los datos fueron recogidos mediante un cuestionario estructurado en línea, elaborado a partir de guías profesionales internacionales (WFOT, AOTA) y de la normativa laboral española aplicable. El archivo incluye variables relacionadas con el tipo de centro (residencia, centro de día o centro combinado), el modelo de gestión (público, privado o mixto), los años de experiencia profesional, las ratios profesional-usuario, la presencia de puestos uniprofesionales y la realización de tareas no propias del ámbito competencial de la terapia ocupacional.

El propósito de este conjunto de datos es describir la organización real de las plantillas de terapia ocupacional y documentar posibles discrepancias con los estándares profesionales recomendados. Todos los registros están completamente anonimizados y corresponden a profesionales, no a personas usuarias.

Este dataset permite realizar análisis secundarios sobre planificación de recursos humanos, delimitación de roles profesionales, estructuras organizativas en cuidados de larga duración y comparaciones con modelos internacionales.
DOI: 10.15468/dl.8rc8re
title: Occurrence Download

description: A dataset containing 4174 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Country is Germany",
 "DecimalLongitude is greater than or equal to 7.20947384794932",
 "DecimalLongitude is less than 7.21253340113371",
 "DecimalLatitude is greater than or equal to 47.27011",
 "DecimalLatitude is less than or equal to 55.05864"
 ]
}

 The dataset includes 4174 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000337-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/pyxbw4h2w4.1
title: Dataset_TerapiaOcupacional_CentrosMayores_Madrid

description: Este conjunto de datos contiene las respuestas anonimizadas de un estudio observacional transversal cuyo objetivo fue analizar las ratios profesionales y las funciones del personal de terapia ocupacional en centros de atención a personas mayores de la Comunidad de Madrid (España).

Los datos fueron recogidos mediante un cuestionario estructurado en línea, elaborado a partir de guías profesionales internacionales (WFOT, AOTA) y de la normativa laboral española aplicable. El archivo incluye variables relacionadas con el tipo de centro (residencia, centro de día o centro combinado), el modelo de gestión (público, privado o mixto), los años de experiencia profesional, las ratios profesional-usuario, la presencia de puestos uniprofesionales y la realización de tareas no propias del ámbito competencial de la terapia ocupacional.

El propósito de este conjunto de datos es describir la organización real de las plantillas de terapia ocupacional y documentar posibles discrepancias con los estándares profesionales recomendados. Todos los registros están completamente anonimizados y corresponden a profesionales, no a personas usuarias.

Este dataset permite realizar análisis secundarios sobre planificación de recursos humanos, delimitación de roles profesionales, estructuras organizativas en cuidados de larga duración y comparaciones con modelos internacionales.
DOI: 10.17632/ygvdf54s6t
title: A UK dataset of 262 adjectives for cognitive-emotional tasks rated by young adults (Aged 18-24)

description: This dataset comprises of 262 adjectives describing personality characteristics, rated by young adults (aged 18-24) based on three key factors: valence (the perceived positivity or negativity of a word), imageability (how easily one can create a mental image of the word), and frequency (how commonly the word is encountered in everyday language). The word list is designed to support the development and validation of experimental tasks in cognitive and emotional research relevant to younger populations. 

Word stimuli used in modern experimental tasks, such as those used in the Emotional Test Battery (ETB), are outdated, having been developed from a study conducted in 1968 with older adults. To address this gap, the present dataset was co-produced with a Young Person’s Advisory Group, adapting and a wordlist published by Raslescu et al. in 2022 to be more relevant to younger populations. The advisory group reviewed the list to remove outdated, ambiguous, or unfamiliar adjectives, and contributed suggestions for replacements, including additional terms relevant to irritability and contemporary emotional language. 

To characterise the updated word list, an online survey was conducted with over 600 participants aged 18–24. Participants were divided into three groups of approximately 200 individuals, each rating all 262 adjectives on one of the three dimensions (valence, imageability, or frequency). Demographic data, along with measures of depressive symptoms and state anxiety, were also collected. 

For each adjective and rating type, a range of descriptive statistics were computed, including mean, standard deviation, standard error, number of ratings, median, minimum, maximum, range, skewness, and kurtosis. These results were combined into a single dataset [Dataset Positive and Negative Personality Descriptor Words (18–24)] which includes measures of self-referential valence, imageability, subjective frequency, and word length. 

Only fully anonymised data are provided; all pseudonymous variables were removed by the research team prior to sharing. Supplementary materials are currently being prepared for release, including raw datasets, figures, R code, and demographic summaries.
DOI: 10.17632/ygvdf54s6t.2
title: A UK dataset of 262 adjectives for cognitive-emotional tasks rated by young adults (Aged 18-24)

description: This dataset comprises of 262 adjectives describing personality characteristics, rated by young adults (aged 18-24) based on three key factors: valence (the perceived positivity or negativity of a word), imageability (how easily one can create a mental image of the word), and frequency (how commonly the word is encountered in everyday language). The word list is designed to support the development and validation of experimental tasks in cognitive and emotional research relevant to younger populations. 

Word stimuli used in modern experimental tasks, such as those used in the Emotional Test Battery (ETB), are outdated, having been developed from a study conducted in 1968 with older adults. To address this gap, the present dataset was co-produced with a Young Person’s Advisory Group, adapting and a wordlist published by Raslescu et al. in 2022 to be more relevant to younger populations. The advisory group reviewed the list to remove outdated, ambiguous, or unfamiliar adjectives, and contributed suggestions for replacements, including additional terms relevant to irritability and contemporary emotional language. 

To characterise the updated word list, an online survey was conducted with over 600 participants aged 18–24. Participants were divided into three groups of approximately 200 individuals, each rating all 262 adjectives on one of the three dimensions (valence, imageability, or frequency). Demographic data, along with measures of depressive symptoms and state anxiety, were also collected. 

For each adjective and rating type, a range of descriptive statistics were computed, including mean, standard deviation, standard error, number of ratings, median, minimum, maximum, range, skewness, and kurtosis. These results were combined into a single dataset [Dataset Positive and Negative Personality Descriptor Words (18–24)] which includes measures of self-referential valence, imageability, subjective frequency, and word length. 

Only fully anonymised data are provided; all pseudonymous variables were removed by the research team prior to sharing. Supplementary materials are currently being prepared for release, including raw datasets, figures, R code, and demographic summaries.
DOI: 10.17632/pkbxp5tm8w
title: JANC: A cost-effective, differentiable compressible reacting flow solver featured with JAX-based adaptive mesh refinement

description: The compressible reacting flow numerical solver is an essential tool in the study of combustion, energy disciplines, as well as in the design of industrial power and propulsion devices. We have established the first JAX-based (a Python library developed by Google for accelerator-oriented array computation and high-performance numerical computing) block-structured adaptive mesh refinement (AMR) framework, called JAX-AMR, and then developed a fully-differentiable solver for compressible reacting flows, named JANC. JANC is implemented in Python and features automatic differentiation capabilities, enabling an efficient integration of the solver with machine learning. Furthermore, benefited by multiple acceleration features such as accelerated linear algebra (XLA)-powered Just-In-Time (JIT) compilation, GPU/TPU computing, parallel computing, and AMR, the computational efficiency of JANC has been significantly improved. In a comparative test of a two-dimensional detonation tube case, the computational cost of the JANC core solver, running on a single A100 GPU, was reduced to 1% of that of OpenFOAM, which was parallelized across 384 CPU cores. When the AMR method is enabled for both solvers, JANC’s computational cost can be reduced to 1-2% of that of OpenFOAM. The core solver of JANC has also been tested for parallel computation on a 4-card A100 setup, demonstrating its convenient and efficient parallel computing capability. JANC also shows strong compatibility with machine learning by combining adjoint optimization to make the whole dynamic trajectory efficiently differentiable. JANC provides a new generation of high-performance, cost-effective, and high-precision solver framework for large-scale numerical simulations of compressible reacting flows and related machine learning research.