cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/qfotqz
title: Do Augmented Reality Overlays Influence Street-Crossing Decisions for Non-Mobility-Impaired Older and Younger Adults?

description: Older pedestrians represent a particularly vulnerable group of road users. This paper explores how Augmented Reality (AR) can be used to assist older pedestrians in making safe road-crossing decisions. We simulated AR alerts in a large-screen virtual environment and conducted a between-subjects study with older- and younger-adult participants. The experiment had two conditions: Control (no AR) and AR displaying overlays on the roadway indicating the crossability of gaps between two vehicles. We found that participants were more selective in their crossing decisions and took safer gaps in the AR condition than in the Control condition. Older-adult participants also reported reduced mental and physical demand in the AR condition as compared to Control. Our findings show the potential for using AR for improving pedestrian safety. We provide design considerations for such a system, age-related similarities and differences, and avenues for future work in this area.
DOI: 10.7910/dvn/gr54uc
title: PDB - 1QKZ - Crystal Structure of an Fab Fragment in Complex with a Meningococcal Serosubtype Antigen and a Protein G Domain, (310K, 37°C, 100 ns): RMSD, SASA, RMSF, Rg, H-bonds

description: PDB - 1QKZ - Crystal Structure of an Fab Fragment in Complex with a Meningococcal Serosubtype Antigen and a Protein G Domain, (310K, 37°C, 100 ns): RMSD, SASA, RMSF, Rg, H-bonds
DOI: 10.7910/dvn/lk6pzy
title: Replication Data for: Why am I obsessed with viewing Mukbang ASMR? The roles of mediated voyeurism and intertemporal choice

description: Shared dataset
DOI: 10.7910/dvn/v6xmj3
title: GAP Year_Quantitative SRH manuscript

description: This data includes all the variables used for the following manuscript: Knowledge, uptake and patterns of contraception use among in-school adolescents in three South African townships: Baseline findings from the Girls Achieve Power (GAP Year) Trial.
DOI: 10.7910/dvn/8gblzv
title: Replication Data for The Supreme Court, the President, and Congress: Lawmaking in a Separation of Powers System

description: Replication data and accompanying Stata Do File.
DOI: 10.7910/dvn/linpsi
title: Wright Casebook Edited; Docketed Case: 16,888
DOI: 10.7910/dvn/dee36x
title: Replication data for The Effect of Mass Migration on Disease Transmission: Evidence from the Venezuelan Refugee Crisis

description: Since 2014, millions of Venezuelans have fled to neighboring countries. There is only one accessible land crossing along the Brazil-Venezuela border (Pacaraima) and the Brazilian highway system limits migrants to one route through the Amazon for almost 1000km. Using this event as a quasi-random treatment, we find that refugee migration increased malaria incidence in Pacaraima, but this was limited to individuals of Venezuelan nationality. We find no effect on Brazilians in Pacaraima or in other municipalities along the main refugee migration route. We therefore reject the hypothesis that Venezuelan refugees increased the risk of malaria among native residents.
DOI: 10.5281/zenodo.14345392
title: Replication package for the paper: ''Data Privacy in Software Practice: Brazilian Developers' Perspectives"

description: Replication package for the paper: "Data Privacy in Software Practice: Brazilian Developers’ Perspectives" accepted to the Special Issue (Unleashing the Potential of Pervasive and Ubiquitous Computing) of the Journal of Internet Services and Applications.
DOI: 10.5281/zenodo.14345393
title: Replication package for the paper: ''Data Privacy in Software Practice: Brazilian Developers' Perspectives"

description: Replication package for the paper: "Data Privacy in Software Practice: Brazilian Developers’ Perspectives" accepted to the Special Issue (Unleashing the Potential of Pervasive and Ubiquitous Computing) of the Journal of Internet Services and Applications.
DOI: 10.7910/dvn/6frcrm
title: Agroindustrial 4
DOI: 10.7910/dvn/gtpmxl
title: Wright Casebook Edited; Docketed Case: 18180
DOI: 10.15468/dl.n3dfzs
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Herwigia Nielsen, 1972",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((-1.9734 4.2478,-0.0352 5.0957,-0.0352 10.8496,-9.0352 10.8496,-9.0352 4.4397,-8.4168 4.1049,-7.389 3.8664,-5.7288 4.5489,-4.0108 4.7359,-1.9734 4.2478))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009281-250525065834625/datasets/export for details.
DOI: 10.15468/dl.2z2apk
title: Occurrence Download

description: A dataset containing 3285 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "OccurrenceStatus is Present",
 "TaxonKey is Troglodytes musculus J.F.Naumann, 1823"
 ]
}

 The dataset includes 3285 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009283-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/x7ydz77c8p.3
title: From borders to boardrooms: Immigrants' impact on productivity

description: This replication package accompanies the paper “From Borders to Boardrooms: Immigrants' Impact on Productivity” ( at Economic Modelling). The original microdata used in the study (Quadros de Pessoal (QP) and SCIE (Sistema de Contas Integradas das Empresas) ) are confidential and cannot be shared publicly.
It contains synthetic and simulated data, along with all Stata code and output files required to reproduce the tables and figures reported in the paper and its Online Appendix.
The repository includes:
• Data folder: Synthetic datasets combining firm-level and worker-level information, and O*NET-based skill variables.
• DoFiles folder: Stata scripts to generate all tables and figures, including a master do-file that automates the full replication.
• Tablesfigs folder: Output tables (text files) and figures (image files) produced by the replication scripts.
All analyses were conducted in Stata/SE 16.1.
DOI: 10.17632/bxmdt72wp2
title: lightbgm_shapley code

description: In this study, we employed a LightGBM-based machine learning framework to analyze the response of soil erosion to extreme precipitation. The workflow consisted of several key steps:
1. Data preparation and splitting: The dataset was read from a CSV file, with the last column defined as the target variable and the remaining columns as predictors. Data were randomly split into training and testing sets (80%–20%) using a fixed random seed to ensure reproducibility.
2. Hyperparameter optimization: To improve model performance, the hyperparameters of the LightGBM model (including num_leaves, learning_rate, feature_fraction, min_child_weight, subsample, and colsample_bytree) were optimized using Hyperopt with a tree-structured Parzen estimator (TPE) algorithm. Five-fold cross-validation was applied on the training set, and the mean RMSE was used as the objective for optimization. A total of 1000 evaluations were performed to identify the best combination of hyperparameters.
3. Model training and evaluation: Using the optimized parameters, the LightGBM model was trained under five-fold cross-validation on the entire dataset to assess predictive performance. The model was evaluated using RMSE, MAE, and R² metrics. Finally, the model was retrained on the full dataset to obtain a final predictive model, and its accuracy was verified on the held-out test set.
4. SHAP-based interpretation: To interpret the contribution of each predictor to soil erosion, we employed the SHAP (SHapley Additive exPlanations) framework. Both global (summary, bar, and beeswarm plots) and local (dependence, waterfall, and force plots) explanations were generated to reveal the relative importance and nonlinear interactions of the driving factors. The mean absolute SHAP values of each predictor were calculated and visualized to quantify their overall contributions.
5.Visualization and reproducibility: All SHAP-based plots and the feature importance table were saved for further analysis. This framework allows flexible adaptation to datasets of different spatial and temporal scales, ensuring robustness and reproducibility.
DOI: 10.15468/dl.ta7sfn
title: Occurrence Download

description: A dataset containing 55525 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-5.60531 35.93282,-4.7086 36.50944,-5.78725 37.58298,-6.74894 36.58253,-5.60531 35.93282))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 55525 records from 142 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020683-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/bxmdt72wp2.1
title: lightbgm_shapley code

description: In this study, we employed a LightGBM-based machine learning framework to analyze the response of soil erosion to extreme precipitation. The workflow consisted of several key steps:
1. Data preparation and splitting: The dataset was read from a CSV file, with the last column defined as the target variable and the remaining columns as predictors. Data were randomly split into training and testing sets (80%–20%) using a fixed random seed to ensure reproducibility.
2. Hyperparameter optimization: To improve model performance, the hyperparameters of the LightGBM model (including num_leaves, learning_rate, feature_fraction, min_child_weight, subsample, and colsample_bytree) were optimized using Hyperopt with a tree-structured Parzen estimator (TPE) algorithm. Five-fold cross-validation was applied on the training set, and the mean RMSE was used as the objective for optimization. A total of 1000 evaluations were performed to identify the best combination of hyperparameters.
3. Model training and evaluation: Using the optimized parameters, the LightGBM model was trained under five-fold cross-validation on the entire dataset to assess predictive performance. The model was evaluated using RMSE, MAE, and R² metrics. Finally, the model was retrained on the full dataset to obtain a final predictive model, and its accuracy was verified on the held-out test set.
4. SHAP-based interpretation: To interpret the contribution of each predictor to soil erosion, we employed the SHAP (SHapley Additive exPlanations) framework. Both global (summary, bar, and beeswarm plots) and local (dependence, waterfall, and force plots) explanations were generated to reveal the relative importance and nonlinear interactions of the driving factors. The mean absolute SHAP values of each predictor were calculated and visualized to quantify their overall contributions.
5.Visualization and reproducibility: All SHAP-based plots and the feature importance table were saved for further analysis. This framework allows flexible adaptation to datasets of different spatial and temporal scales, ensuring robustness and reproducibility.
DOI: 10.17632/nczxvgwycn
title: Quantum-Inspired Attention for Efficient Face Recognition

description: We present a novel quantum-inspired deep learning model for face recognition that draws key ideas from quantum interference yet operates entirely on standard GPUs. By introducing complex-valued attention mechanisms within a lightweight convolutional neural network (CNN), our approach emulates wave-like interference effects using sinusoidal functions in the complex domain. When trained on the large-scale VGGFace2 dataset, our model achieves 92.8% training accuracy and 91.2% validation accuracy, using only around 8.2M parameters which is substantially fewer than many state of the art approaches. These results suggest that “quantum inspired” design can enhance classical deep learning for face recognition without needing specialized quantum hardware.
DOI: 10.17632/nczxvgwycn.1
title: Quantum-Inspired Attention for Efficient Face Recognition

description: We present a novel quantum-inspired deep learning model for face recognition that draws key ideas from quantum interference yet operates entirely on standard GPUs. By introducing complex-valued attention mechanisms within a lightweight convolutional neural network (CNN), our approach emulates wave-like interference effects using sinusoidal functions in the complex domain. When trained on the large-scale VGGFace2 dataset, our model achieves 92.8% training accuracy and 91.2% validation accuracy, using only around 8.2M parameters which is substantially fewer than many state of the art approaches. These results suggest that “quantum inspired” design can enhance classical deep learning for face recognition without needing specialized quantum hardware.
DOI: 10.17632/bys58swpxt
title: Systematic Evaluation of the Spatiotemporal Dynamics of Rural Logistics Capacity and Its Influence on Rural Economic Resilience

description: This dataset supports empirical research on the measurement of rural logistics capacity, its spatio-temporal evolution, and the mechanism of its impact on rural economic resilience. It encompasses a balanced panel dataset covering 31 provinces, municipalities, and autonomous regions of China from 2012 to 2023.
The data originates from the China Statistical Yearbook and official releases by the National Bureau of Statistics. After a rigorous data cleaning process—including the removal of outliers and linear interpolation—the final dataset consists of 368 observations.
The dataset contains a complete panel of independent variables, dependent variables, and control variables. It is suitable for:1.Direct Effect Analysis2.Robustness Checks 3.Heterogeneity Analysis.
The data is provided in Microsoft Excel (.xlsx) format and can be directly used in mainstream statistical analysis software.
DOI: 10.17632/bys58swpxt.1
title: Systematic Evaluation of the Spatiotemporal Dynamics of Rural Logistics Capacity and Its Influence on Rural Economic Resilience

description: This dataset supports empirical research on the measurement of rural logistics capacity, its spatio-temporal evolution, and the mechanism of its impact on rural economic resilience. It encompasses a balanced panel dataset covering 31 provinces, municipalities, and autonomous regions of China from 2012 to 2023.
The data originates from the China Statistical Yearbook and official releases by the National Bureau of Statistics. After a rigorous data cleaning process—including the removal of outliers and linear interpolation—the final dataset consists of 368 observations.
The dataset contains a complete panel of independent variables, dependent variables, and control variables. It is suitable for:1.Direct Effect Analysis2.Robustness Checks 3.Heterogeneity Analysis.
The data is provided in Microsoft Excel (.xlsx) format and can be directly used in mainstream statistical analysis software.
DOI: 10.17035/cardiff.31075399
title: Fabrication and characterisation of optical float-zone (100) β-Ga₂O₃ Schottky diodes – Data

description: This dataset supports the manuscript titled <i>“</i>Fabrication and characterisation of optical float-zone (100) β-Ga₂O₃ Schottky diodes <i>”. </i>To assess the suitability of (100) OFZ Ga₂O₃ substrates for deep UV photodetection and power rectifiers, we rapidly fabricated vertical Schottky diodes using simple steps to produce deep UV photodetectors and Schottky Barrier Diodes (SBDs). Here, we present results solely from the SBD power diodes, and our study aims to analyse the quality of SBDs made with two different contact sizes (50 µm and 100 µm) and three distinct shapes (circular, square, and squircle) to relate material quality and device processing to device performance. The key figures of merit—Schottky barrier height (ϕ<sub>B</sub>), threshold voltage (VTH), specific on-resistance (R<sub>ON</sub>), reverse breakdown voltage (V<sub>BD</sub>), reverse leakage current density (J<sub>O</sub>), and maximum electric field (E<sub>max</sub>)—are estimated, and their qualities evaluated, with plausible reasons for device failures discussed.<br>The dataset includes:Linear and log plots of forward J-V Characteristics of the fabricated devicesRoom temperature and temperature dependetnt reverse J-V characteristics of a diodeJ<sub>0</sub> and V<sub>BD</sub> as a function of temperature in the reverse bias; the behaviour of V<sub>TH</sub> and Φ<sub>B</sub> as a function of temperature in the forward bias; J<sub>0</sub> and η as a function of temperature in the forward bias for a diode with a dimension of 50 µm.C-V plots of the fabricated devicesScanning electron microscopy images of devices before and after breakdown
DOI: 10.17035/cardiff.31075399.v1
title: Fabrication and characterisation of optical float-zone (100) β-Ga₂O₃ Schottky diodes – Data

description: This dataset supports the manuscript titled <i>“</i>Fabrication and characterisation of optical float-zone (100) β-Ga₂O₃ Schottky diodes <i>”. </i>To assess the suitability of (100) OFZ Ga₂O₃ substrates for deep UV photodetection and power rectifiers, we rapidly fabricated vertical Schottky diodes using simple steps to produce deep UV photodetectors and Schottky Barrier Diodes (SBDs). Here, we present results solely from the SBD power diodes, and our study aims to analyse the quality of SBDs made with two different contact sizes (50 µm and 100 µm) and three distinct shapes (circular, square, and squircle) to relate material quality and device processing to device performance. The key figures of merit—Schottky barrier height (ϕ<sub>B</sub>), threshold voltage (VTH), specific on-resistance (R<sub>ON</sub>), reverse breakdown voltage (V<sub>BD</sub>), reverse leakage current density (J<sub>O</sub>), and maximum electric field (E<sub>max</sub>)—are estimated, and their qualities evaluated, with plausible reasons for device failures discussed.<br>The dataset includes:Linear and log plots of forward J-V Characteristics of the fabricated devicesRoom temperature and temperature dependetnt reverse J-V characteristics of a diodeJ<sub>0</sub> and V<sub>BD</sub> as a function of temperature in the reverse bias; the behaviour of V<sub>TH</sub> and Φ<sub>B</sub> as a function of temperature in the forward bias; J<sub>0</sub> and η as a function of temperature in the forward bias for a diode with a dimension of 50 µm.C-V plots of the fabricated devicesScanning electron microscopy images of devices before and after breakdown
DOI: 10.17632/v42xbd9wh3
title: Personal exposure to nitrogen-containing organic compounds (NOCs) in household PM2.5 and PM0.25, urinary inflammatory biomarkers, and targeted/untargeted metabolomics data from rural Chinese homemakers using solid fuels versus clean energy

description: This repository includes:
- Raw and processed personal exposure concentrations of nitrogen-containing organic compounds (NOCs) in PM2.5 and PM0.25 samples
- Urinary inflammatory biomarker measurements (8-OHdG, VEGF, IL-8, CRP)
- Targeted amino acid metabolites data
- Non-targeted metabolomics data (GC-MS)
DOI: 10.17632/v42xbd9wh3.1
title: Personal exposure to nitrogen-containing organic compounds (NOCs) in household PM2.5 and PM0.25, urinary inflammatory biomarkers, and targeted/untargeted metabolomics data from rural Chinese homemakers using solid fuels versus clean energy

description: This repository includes:
- Raw and processed personal exposure concentrations of nitrogen-containing organic compounds (NOCs) in PM2.5 and PM0.25 samples
- Urinary inflammatory biomarker measurements (8-OHdG, VEGF, IL-8, CRP)
- Targeted amino acid metabolites data
- Non-targeted metabolomics data (GC-MS)
DOI: 10.17632/b9bjrwn2m9
title: Data for "Coupling Relationship and Threshold Calculation Between Forest Degradation/Improvement and Carbon-Water Use Efficiencies"

description: Data for "Coupling Relationship and Threshold Calculation Between Forest Degradation/Improvement and Carbon-Water Use Efficiencies"
DOI: 10.17632/b9bjrwn2m9.1
title: Data for "Coupling Relationship and Threshold Calculation Between Forest Degradation/Improvement and Carbon-Water Use Efficiencies"

description: Data for "Coupling Relationship and Threshold Calculation Between Forest Degradation/Improvement and Carbon-Water Use Efficiencies"
DOI: 10.17632/vjpn5m3rjw
title: Establishing a Demographic Health Surveillance System in Tsakare Community, Mt. Darwin District, Zimbabwe, 2024 Baseline Study - Dataset
DOI: 10.17632/vjpn5m3rjw.1
title: Establishing a Demographic Health Surveillance System in Tsakare Community, Mt. Darwin District, Zimbabwe, 2024 Baseline Study - Dataset
DOI: 10.5518/1637
title: Dataset for 'Influence of limestone addition in the engineering and durability performance of Portland-blast furnace slag blended concretes'
DOI: 10.14284/411
title: Global Compositae Database. Accessed at https://www.compositae.org/gcd on yyyy-mm-dd

description: The Compositae is one of the largest plant families in the world. The Global Compositae Database is built on the Global Compositae Checklist which has been moved to the Aphia platform of the World Register of Marine Species. An international network of taxonomic experts will assess, edit and update the taxonomic information for this important family.
description: Datasets for the Compositae from across the world were integrated in the Global Compositae Checklist between 2006 and 2011 using purpose designed Checklist Integration software (C-INT, Landcare Research, New Zealand). Names were matched using a set of rules and a consensus name was generated with all original data sources linked to that name. The consensus name was a summary of all information from multiple data providers that were in agreement on any given field. Entries were complete to differing levels depending on the data contributed (e.g. only some data sources had type information). Broad distribution data was included, using the TDWG Geographic Standard although, as this is derived from the data contributed, the distribution is not necessarily comprehensive. Taxonomic concepts were also derived from the data sources, using a system of prioritised ranking where local datasets have more weight that global. The most recent version of this Checklist forms the starting point for the Global Compositae Database.
DOI: 10.17632/rgypd4sjy7
title: HPLC-HRMS and Interpretable Machine Learning Decipher Serum Lipidomic Signatures in NSCLC

description: RAW data
DOI: 10.17632/rgypd4sjy7.1
title: HPLC-HRMS and Interpretable Machine Learning Decipher Serum Lipidomic Signatures in NSCLC

description: RAW data