cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/zs3t38sxds
title: Image-PointClouds Multimodal Crack Segmentation Dataset

description: To construct a multimodal dataset of images and point clouds, the Intel RealSense L515 LiDAR camera was used for multi-scene acquisition. The sensor can synchronously capture image and point cloud data. This dataset covers typical crack scenarios under diverse complex backgrounds, including concrete cracks on building surfaces, underground coal mine roadway surrounding rock cracks, and pavement cracks, encompassing variations in material, illumination, surface contamination, and occlusion, while ensuring representative crack orientations and morphologies to reflect the realism of model testing in actual engineering environments.
DOI: 10.17632/zs3t38sxds.1
title: Image-PointClouds Multimodal Crack Segmentation Dataset

description: To construct a multimodal dataset of images and point clouds, the Intel RealSense L515 LiDAR camera was used for multi-scene acquisition. The sensor can synchronously capture image and point cloud data. This dataset covers typical crack scenarios under diverse complex backgrounds, including concrete cracks on building surfaces, underground coal mine roadway surrounding rock cracks, and pavement cracks, encompassing variations in material, illumination, surface contamination, and occlusion, while ensuring representative crack orientations and morphologies to reflect the realism of model testing in actual engineering environments.
DOI: 10.15468/dl.cvgjhb
title: Occurrence Download

description: A dataset containing 363357 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 19.085278",
 "DecimalLatitude is less than or equal to 24.085278",
 "DecimalLongitude is greater than or equal to -160.0",
 "DecimalLongitude is less than or equal to -155.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 363357 records from 211 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065118-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/kkhcvdfxxp
title: Detection algorithm dataset for PWD in complex environments

description: The data used in this study were primarily collected between February and June 2024 through multiple aerial surveys conducted in two cities in northern and southern China, using the DJI Mini 2 drone developed by DJI Innovations, Shenzhen. The drone was flown at relative altitudes ranging from 50 to 120 meters above ground level, following an "S"-shaped flight path to comprehensively cover areas populated with pine trees.Based on the progression of pine wilt disease symptoms, the collected data were categorized into two classes: "early stage" and "late stage." A total of 2,775 images were compiled and divided into training, validation, and test sets in an 8:1:1 ratio. To expand the dataset, a series of augmentation techniques—including flipping, scaling, noise addition, and cropping—were applied, increasing the total number of images to 18,375.Addressing the challenge of reduced detection performance in complex environments, an improved YOLOv5 model was developed to enhance identification accuracy and support large-scale, rapid monitoring. All data and code used in the analysis have been made publicly available through Mendeley Data to ensure experimental reproducibility. While the training and inference data used in the deep learning experiments exceed 80 GB in size, only a portion of the dataset could be uploaded due to storage limitations on Mendeley Data. Researchers interested in replicating this study are welcome to contact me via email, and I will gladly provide access to the full dataset through alternative repositories.
DOI: 10.17632/kkhcvdfxxp.1
title: Detection algorithm dataset for PWD in complex environments

description: The data used in this study were primarily collected between February and June 2024 through multiple aerial surveys conducted in two cities in northern and southern China, using the DJI Mini 2 drone developed by DJI Innovations, Shenzhen. The drone was flown at relative altitudes ranging from 50 to 120 meters above ground level, following an "S"-shaped flight path to comprehensively cover areas populated with pine trees.Based on the progression of pine wilt disease symptoms, the collected data were categorized into two classes: "early stage" and "late stage." A total of 2,775 images were compiled and divided into training, validation, and test sets in an 8:1:1 ratio. To expand the dataset, a series of augmentation techniques—including flipping, scaling, noise addition, and cropping—were applied, increasing the total number of images to 18,375.Addressing the challenge of reduced detection performance in complex environments, an improved YOLOv5 model was developed to enhance identification accuracy and support large-scale, rapid monitoring. All data and code used in the analysis have been made publicly available through Mendeley Data to ensure experimental reproducibility. While the training and inference data used in the deep learning experiments exceed 80 GB in size, only a portion of the dataset could be uploaded due to storage limitations on Mendeley Data. Researchers interested in replicating this study are welcome to contact me via email, and I will gladly provide access to the full dataset through alternative repositories.
DOI: 10.17632/rxg2b32yn7
title: Maternal vitiligo is associated with increased autoimmune and atopic disease in offspring: a nationwide birth cohort study

description: Maternal vitiligo is associated with increased long-term risks of autoimmune and atopic diseases in offspring, reflecting potential combined genetic and intrauterine immune influences. These findings underscore the importance of maternal immune health during pregnancy and highlight the need for pediatric surveillance.
DOI: 10.17632/rxg2b32yn7.1
title: Maternal vitiligo is associated with increased autoimmune and atopic disease in offspring: a nationwide birth cohort study

description: Maternal vitiligo is associated with increased long-term risks of autoimmune and atopic diseases in offspring, reflecting potential combined genetic and intrauterine immune influences. These findings underscore the importance of maternal immune health during pregnancy and highlight the need for pediatric surveillance.
DOI: 10.17632/h2p8fkbrk4
title: The molecular characteristics of natural organic matter in aquifers of the Hetao Basin, Inner Mongolia, China

description: Physiochemical parameters, optical parameters, and molecular characteristics of DOM and WSOM in the alluvial fan (AF), the transition area (TA), and the flat plain (FP) of the deep aquifers in the Hetao Basin, China and full raw FT-ICR MS data
DOI: 10.17632/h2p8fkbrk4.1
title: The molecular characteristics of natural organic matter in aquifers of the Hetao Basin, Inner Mongolia, China

description: Physiochemical parameters, optical parameters, and molecular characteristics of DOM and WSOM in the alluvial fan (AF), the transition area (TA), and the flat plain (FP) of the deep aquifers in the Hetao Basin, China and full raw FT-ICR MS data
DOI: 10.15468/y8mw2k
title: Notes on the nomenclature and taxonomy of Chiastophyllum and Umbilicus oppositifolius (≡ Cotyledon oppositifolia, ≡ Chiastophyllum oppositifolium) (Crassulaceae subfam. Sempervivoideae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Smith, Gideon F., Monro, Anna M. (2022): Notes on the nomenclature and taxonomy of Chiastophyllum and Umbilicus oppositifolius (≡ Cotyledon oppositifolia, ≡ Chiastophyllum oppositifolium) (Crassulaceae subfam. Sempervivoideae). Phytotaxa 564 (2): 239-247, DOI: 10.11646/phytotaxa.564.2.7AbstractWe show that the genus name Chiastophyllum (Crassulaceae subfam. Sempervivoideae) was validly published in January 1930 by Otto Stapf. This is in contrast to some sources, which indicate the name was merely proposed by Stapf and validated later the same year by Alwin Berger. Stapf based Chiastophyllum on a sectional name published in Umbilicus in 1843 by Carl von Ledebour and, in doing so, published a new combination and a name at new rank. The place of publication and author attribution of Chiastophyllum oppositifolium, the name of the only species included in the genus, as well as of its basionym, Cotyledon oppositifolia, and of Umbilicus oppositifolius, are also clarified. At the rank of genus Chiastophyllum is at present usually treated as a synonym of Umbilicus.
DOI: 10.17632/3yy88gwvbp
title: Fitting parameters of typhoon wind profile models of the lower troposphere (0–2 km) over China

description: This dataset summarizes the statistical values (mean ± std) of the fitted wind profile parameters presented in the manuscript ‘Typhoon Wind Profile Model of the Lower Troposphere (0–2 km) over China’. The data are contained in a PDF file comprising two tables.
DOI: 10.17632/3yy88gwvbp.1
title: Fitting parameters of typhoon wind profile models of the lower troposphere (0–2 km) over China

description: This dataset summarizes the statistical values (mean ± std) of the fitted wind profile parameters presented in the manuscript ‘Typhoon Wind Profile Model of the Lower Troposphere (0–2 km) over China’. The data are contained in a PDF file comprising two tables.
DOI: 10.15468/k9sw66
title: Phalangipus somnathensis Sureandiran, Karuppasamy & Suyani, 2024 - a junior synonym of Encephaloides armstrongi Wood-Mason in Wood-Mason & Alcock, 1891 (Crustacea, Brachyura, Inachidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Ng, Peter K. L., Patel, Heris, Trivedi, Jigneshkumar (2025): Phalangipus somnathensis Sureandiran, Karuppasamy & Suyani, 2024 - a junior synonym of Encephaloides armstrongi Wood-Mason in Wood-Mason & Alcock, 1891 (Crustacea, Brachyura, Inachidae). Zootaxa 5627 (3): 594-600, DOI: 10.11646/zootaxa.5627.3.13, URL: https://doi.org/10.11646/zootaxa.5627.3.13AbstractThe recently described epialtid majoid crab, Phalangipus somnathensis Sureandiran, Karuppasamy & Suyani, 2024, from off Gujarat in India is here shown to be a junior synonym of the inachid, Encephaloides armstrongi Wood-Mason in Wood-Mason & Alcock, 1891. The holotype male of P. somnathensis does not have a carapace, but the third maxillipeds, thoracic sternum, pleon and first gonopod structure are diagnostic for E. armstrongi. The carapace as described and figured by the authors was actually based on another specimen and was mistakenly associated with the holotype.
DOI: 10.17632/mm6tfm663v
title: Supplementary Data: Regulatory Compliance Mapping for GenAI Security - Requirements, Controls, and Mapping Matrix

description: This dataset accompanies the paper 'Regulatory Compliance Mapping for Generative AI Security: A Cross-Jurisdictional Framework for HIPAA, GDPR, EU AI Act, and Financial Regulations'. It contains: (1) 47 regulatory requirements extracted from HIPAA, GDPR, EU AI Act, and financial regulations; (2) 24 technical controls with coverage and maturity assessments; (3) Control-requirement mapping matrix.
DOI: 10.17632/mm6tfm663v.1
title: Supplementary Data: Regulatory Compliance Mapping for GenAI Security - Requirements, Controls, and Mapping Matrix

description: This dataset accompanies the paper 'Regulatory Compliance Mapping for Generative AI Security: A Cross-Jurisdictional Framework for HIPAA, GDPR, EU AI Act, and Financial Regulations'. It contains: (1) 47 regulatory requirements extracted from HIPAA, GDPR, EU AI Act, and financial regulations; (2) 24 technical controls with coverage and maturity assessments; (3) Control-requirement mapping matrix.
DOI: 10.17632/wn2rv7twh2
title: Female Labour Force Participation

description: Female Labour Force Participation
DOI: 10.17632/wn2rv7twh2.1
title: Female Labour Force Participation

description: Female Labour Force Participation
DOI: 10.15468/uscbz3
title: Novelties in Phyllanthus (Phyllanthaceae) from the Brazilian Cerrado: new records of the rare species P. allemii

description: This dataset contains the digitized treatments in Plazi based on the original journal article Mendes, Jone Clebson Ribeiro, Figueira, Maurício, Schindler, Bianca, Noronha, Sérgio E., Simon, Marcelo Fragomeni, Sales, Margareth Ferreira De, Athiê-Souza, Sarah Maria (2022): Novelties in Phyllanthus (Phyllanthaceae) from the Brazilian Cerrado: new records of the rare species P. allemii. Phytotaxa 538 (2): 149-156, DOI: 10.11646/phytotaxa.538.2.7AbstractPhyllanthus (Phyllanthaceae) is widely distributed within Brazilian phytogeographic domains where 101 species occur, including a number of poorly-known taxa, such as P. allemii, which was until now only known from the type collection. Here we report the rediscovery of P. allemii, which was recently collected during a floristic inventory carried out in the Estação Ecológica Serra Geral do Tocantins, which is located on the border between Bahia and Tocantins states in the Cerrado domain. We provide an updated and detailed morphological description of the species, including plates and field images, as well as a taxonomic key for species of Phyllanthus sect. Phyllanthus subsect. Clausseniani that occur in the Cerrado. We also provide habitat, ecology and distribution data, and, finally, a conservation assessment of this rare species.
DOI: 10.17632/vb2w9h9msp
title: CDAS

description: This repository contains the analysis code for the study “Differential Factor Effects in Comorbid Depressive and Anxiety Symptoms (CDASs): A Machine Learning Approach to Individualized Mental Health Promotion.”

Data Description:
The data are derived from the Psychology and Behavior Investigation of Chinese Residents (PBICR) 2021, including 2,951 Chinese youth aged 19–35 years. The dataset integrates multidimensional variables covering demographic, psychological, family, social, behavioral, physiological and environmental factors (59 independent variables). The dependent variable represents four mental health categories:
• 0 = No symptoms
• 1 = Depressive symptoms only
• 2 = Anxiety only
• 3 = Comorbid Depressive and Anxiety (CDAS)
For the final analysis, categories 1 and 2 were excluded to construct a binary classification (0 = asymptomatic, 1 = CDAS) focusing on identifying individuals with comorbid risks.

Analytic Framework:
All analyses were conducted in Python (version 3.8.8). The pipeline includes:
1. Data preprocessing – handling missing values, encoding categorical variables, and standardizing continuous ones.
2. Feature selection – combining LASSO and Boruta to select predictive factors.
3. Model training and evaluation – Random Forest (RF), XGBoost, LightGBM, CatBoost, Support Vector Machine (SVM), and Multilayer Perceptron (MLP) were trained under stratified cross-validation.
4. Model interpretation – SHAP (Shapley Additive exPlanations) was used to quantify feature importance and visualize group-specific factor effects.
5. Bidirectional hierarchical Clustering Analysis (HCA) – reveal underlying risk subtypes and characteristic combination patterns.
6. Decision Curve Analysis (DCA) – to evaluate clinical utility across risk thresholds.

Key Findings:
Random Forest demonstrated optimal performance (AUC = 0.905, PR-AUC = 0.703). SHAP analysis revealed that stress and swimming were core risk factors for comorbid symptoms. Neglecting or normalizing negative emotions, obesity-related dietary behaviors, and sports equipment usage were positively correlated with comorbid symptoms. Family health, social support, self-efficacy, and healthcare exerted protective effects. SHAP waterfall plots and SHAP bidirectional hierarchical clustering dendrogram provided individualized predictive explanations, while decision curve analysis confirmed the model's clinical net benefit within the threshold range of 0.02–0.67.

How to Use:
All code files can be executed sequentially. Each script is annotated for reproducibility. Researchers can apply for access via the official PBICR data portal.
DOI: 10.17632/vb2w9h9msp.2
title: CDAS

description: This repository contains the analysis code for the study “Differential Factor Effects in Comorbid Depressive and Anxiety Symptoms (CDASs): A Machine Learning Approach to Individualized Mental Health Promotion.”

Data Description:
The data are derived from the Psychology and Behavior Investigation of Chinese Residents (PBICR) 2021, including 2,951 Chinese youth aged 19–35 years. The dataset integrates multidimensional variables covering demographic, psychological, family, social, behavioral, physiological and environmental factors (59 independent variables). The dependent variable represents four mental health categories:
• 0 = No symptoms
• 1 = Depressive symptoms only
• 2 = Anxiety only
• 3 = Comorbid Depressive and Anxiety (CDAS)
For the final analysis, categories 1 and 2 were excluded to construct a binary classification (0 = asymptomatic, 1 = CDAS) focusing on identifying individuals with comorbid risks.

Analytic Framework:
All analyses were conducted in Python (version 3.8.8). The pipeline includes:
1. Data preprocessing – handling missing values, encoding categorical variables, and standardizing continuous ones.
2. Feature selection – combining LASSO and Boruta to select predictive factors.
3. Model training and evaluation – Random Forest (RF), XGBoost, LightGBM, CatBoost, Support Vector Machine (SVM), and Multilayer Perceptron (MLP) were trained under stratified cross-validation.
4. Model interpretation – SHAP (Shapley Additive exPlanations) was used to quantify feature importance and visualize group-specific factor effects.
5. Bidirectional hierarchical Clustering Analysis (HCA) – reveal underlying risk subtypes and characteristic combination patterns.
6. Decision Curve Analysis (DCA) – to evaluate clinical utility across risk thresholds.

Key Findings:
Random Forest demonstrated optimal performance (AUC = 0.905, PR-AUC = 0.703). SHAP analysis revealed that stress and swimming were core risk factors for comorbid symptoms. Neglecting or normalizing negative emotions, obesity-related dietary behaviors, and sports equipment usage were positively correlated with comorbid symptoms. Family health, social support, self-efficacy, and healthcare exerted protective effects. SHAP waterfall plots and SHAP bidirectional hierarchical clustering dendrogram provided individualized predictive explanations, while decision curve analysis confirmed the model's clinical net benefit within the threshold range of 0.02–0.67.

How to Use:
All code files can be executed sequentially. Each script is annotated for reproducibility. Researchers can apply for access via the official PBICR data portal.
DOI: 10.17632/j53z3y7bx8
title: Benchmark dataset for safety assessment under blast loading

description: This dataset provides a benchmark comprising 50 curated assessment tasks designed to evaluate the performance of large language model (LLM)-based multi-agent frameworks. Each item represents an independent task with both simple and complex task descriptions, along with corresponding ground-truth references.
DOI: 10.15468/np9x7x
title: Integrative taxonomy supports two new species of Macrobiotus (Tardigrada: Eutardigrada: Macrobiotidae) allowing further discussion on the genus phylogeny

description: This dataset contains the digitized treatments in Plazi based on the original journal article Stec, Daniel (2024): Integrative taxonomy supports two new species of Macrobiotus (Tardigrada: Eutardigrada: Macrobiotidae) allowing further discussion on the genus phylogeny. European Journal of Taxonomy 930: 79-123, DOI: 10.5852/ejt.2024.930.2481, URL: https://europeanjournaloftaxonomy.eu/index.php/ejt/article/download/2481/11065Abstract. In this study, I describe two new species of Macrobiotus based on morphological data collected through light and scanning electron microscopy. Both species are accompanied by DNA sequences from four commonly used molecular markers (18S rDNA, 28S rDNA, ITS-2, and COI). Macrobiotus ovovittatus sp. nov. was discovered in Greenland and can be distinguished from similar taxa of Macrobiotus by its continuous, solid, and clearly wrinkled egg surface, adorned with sparse, very small and irregularly spaced pores. Additionally, the terminal discs of egg processes are covered in multiple light-refracting dots, resembling crocheted napkins. Macrobiotus mileri sp. nov. was found in Israel and is characterized by unique pore arrangements in its body cuticle, expressed in two distinct animal forms: (i) forma porata with large pores arranged in five distinct patches and (ii) forma aporata with single, almost undetectable pores. It also features weakly defined convex terminal discs with smooth edges. Furthermore, the phylogenetic analyses conducted in this study offer the most updated phylogeny of superclade I within the family Macrobiotidae. This facilitates additional discussion concerning the interrelationships among species within the genus Macrobiotus and the circumscription of species groups within it.
DOI: 10.17632/j53z3y7bx8.1
title: Benchmark dataset for safety assessment under blast loading

description: This dataset provides a benchmark comprising 50 curated assessment tasks designed to evaluate the performance of large language model (LLM)-based multi-agent frameworks. Each item represents an independent task with both simple and complex task descriptions, along with corresponding ground-truth references.
DOI: 10.17632/wv77vss33h
title: Replication Folder for "Sectoral Bubbles and Contagion Dynamics in China’s Stock Market"

description: This dataset and code serve as the empirical data for all tables and figures including in "Sectoral Bubbles and Contagion Dynamics in China’s Stock Market". The readers can read the file of "readme" before running all codes.
DOI: 10.17632/wv77vss33h.1
title: Replication Folder for "Sectoral Bubbles and Contagion Dynamics in China’s Stock Market"

description: This dataset and code serve as the empirical data for all tables and figures including in "Sectoral Bubbles and Contagion Dynamics in China’s Stock Market". The readers can read the file of "readme" before running all codes.
DOI: 10.17632/x49b2h4v5h.1
title: Mobile Measurements next to Biosolid Processing Plants

description: Raw data from work: Nucleation Mode Particle Emissions from Biosolid Processing Plants