cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/syvjrn83bn
title: From Scorpion to Spider: Tracing the Origin of Fear of Spiders and Other Chelicerates through Perceptual Fear Generalization Gradients across Chelicerates

description: Introduction: Previous research has provided evidence, such as higher attentional fixation for scorpions compared to spiders and emotional clustering, that is potentially consistent with fear generalization. However, no prior studies have directly or indirectly tested the existence of fear generalization from scorpions to spiders and other chelicerates. In the current research, we indirectly tested fear generalization by examining the scorpion-driven gradient (the structural signature of fear generalization) across Chelicerates. Our results supported the fact that fear of spiders and other Chelicerates is generalized from scorpions. 

Dataset: The data include fear of Chelicerates and other arthropods, relative and absolute similarity to spiders and scorpions, scorpion fear eliciting body parts, perceived danger, raters evaluations of Chelicerates shared body parts with scorpion, and province of residence.

Complementary analyses: A supplementary methodological manuscript containing confirmatory rank-order consistency analyses that extend the findings reported in the published article: From scorpion to spider: tracing the origin of fear of spiders and other chelicerates through perceptual fear generalization gradients across chelicerates
The preprint provides quantitative support for the individual-level alignment patterns discussed in the original work.
For the primary study findings, please cite the peer-reviewed article: This supplementary manuscript, which details extended rank-order consistency analyses, may be cited for its specific methodological contributions.
DOI: 10.17632/syvjrn83bn.3
title: From Scorpion to Spider: Tracing the Origin of Fear of Spiders and Other Chelicerates through Perceptual Fear Generalization Gradients across Chelicerates

description: Introduction: Previous research has provided evidence, such as higher attentional fixation for scorpions compared to spiders and emotional clustering, that is potentially consistent with fear generalization. However, no prior studies have directly or indirectly tested the existence of fear generalization from scorpions to spiders and other chelicerates. In the current research, we indirectly tested fear generalization by examining the scorpion-driven gradient (the structural signature of fear generalization) across Chelicerates. Our results supported the fact that fear of spiders and other Chelicerates is generalized from scorpions. 

Dataset: The data include fear of Chelicerates and other arthropods, relative and absolute similarity to spiders and scorpions, scorpion fear eliciting body parts, perceived danger, raters evaluations of Chelicerates shared body parts with scorpion, and province of residence.

Complementary analyses: A supplementary methodological manuscript containing confirmatory rank-order consistency analyses that extend the findings reported in the published article: From scorpion to spider: tracing the origin of fear of spiders and other chelicerates through perceptual fear generalization gradients across chelicerates
The preprint provides quantitative support for the individual-level alignment patterns discussed in the original work.
For the primary study findings, please cite the peer-reviewed article: This supplementary manuscript, which details extended rank-order consistency analyses, may be cited for its specific methodological contributions.
DOI: 10.17632/vjxhpfhcfy
title: Replication Folder for "Impact of pension insurance and health insurance on pension savings"

description: This replication folder contains the necessary codes to replicate the quantitative results of the paper.
DOI: 10.17632/vjxhpfhcfy.1
title: Replication Folder for "Impact of pension insurance and health insurance on pension savings"

description: This replication folder contains the necessary codes to replicate the quantitative results of the paper.
DOI: 10.17632/bbbwny8yzt
title: A wire-driven robotic shark with a non-uniform stiffness distribution fish tail

description: This dataset contains the posture data of the fishtail of a wire-driven robotic shark under different structural parameters and kinematic parameters. The data were calculated using the COMSOL Multiphysics simulation platform, revealing the influence of structural parameters and swimming parameters on the fishtail posture. "length" represents the length of the fishtail, and "T" represents the oscillation period of the fishtail.
DOI: 10.5281/zenodo.17627266
title: KP RC Reports b03
DOI: 10.5281/zenodo.17627267
title: KP RC Reports b03
DOI: 10.17632/bbbwny8yzt.1
title: A wire-driven robotic shark with a non-uniform stiffness distribution fish tail

description: This dataset contains the posture data of the fishtail of a wire-driven robotic shark under different structural parameters and kinematic parameters. The data were calculated using the COMSOL Multiphysics simulation platform, revealing the influence of structural parameters and swimming parameters on the fishtail posture. "length" represents the length of the fishtail, and "T" represents the oscillation period of the fishtail.
DOI: 10.5281/zenodo.18748942
title: espadarana_audax_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18748941
title: espadarana_audax_decontaminated_FSCR.fasta.gz
DOI: 10.17632/gb2dhk8t3m
title: High-Frequency Trading Floor Acoustics

description: High-Frequency Trading Floor Acoustics
DOI: 10.17632/gb2dhk8t3m.1
title: High-Frequency Trading Floor Acoustics

description: High-Frequency Trading Floor Acoustics
DOI: 10.17632/vxjwwdz33m
title: Multi-Model Evaluation of Genotype × Environment Interaction Reveals Adaptive Strategies for Climate-Resilient Wheat Production

description: This dataset contains the raw data for grain yield and related agronomical traits of 12 bread wheat genotypes. The study was conducted across 8 distinct environments (combining 4 years and 2 irrigation regimes: rainfed and supplemental irrigation) in Western Iran. The data was used to perform AMMI, GGE biplot, and multi-trait stability index (MTSI) analyses.
DOI: 10.17632/vxjwwdz33m.1
title: Multi-Model Evaluation of Genotype × Environment Interaction Reveals Adaptive Strategies for Climate-Resilient Wheat Production

description: This dataset contains the raw data for grain yield and related agronomical traits of 12 bread wheat genotypes. The study was conducted across 8 distinct environments (combining 4 years and 2 irrigation regimes: rainfed and supplemental irrigation) in Western Iran. The data was used to perform AMMI, GGE biplot, and multi-trait stability index (MTSI) analyses.
DOI: 10.17632/6wx6zj6h2m
title: DATASET from Transient Ecological Niches for diazotrophs in upwelling bays.

description: Data used to reproduce the analysis and figures of the manuscript submited to JGR Oceans 'Transient Ecological Niches for Diazotrophs in Upwelling Bays'. Code is avaliable at https://github.com/daniel-fernandez-roman/Code-for-figures-of-Transient-Ecological-Niches. Please read the readme_dataREMEDIOS.md file that has all the explanations and description for each file.
DOI: 10.17632/6wx6zj6h2m.1
title: DATASET from Transient Ecological Niches for diazotrophs in upwelling bays.

description: Data used to reproduce the analysis and figures of the manuscript submited to JGR Oceans 'Transient Ecological Niches for Diazotrophs in Upwelling Bays'. Code is avaliable at https://github.com/daniel-fernandez-roman/Code-for-figures-of-Transient-Ecological-Niches. Please read the readme_dataREMEDIOS.md file that has all the explanations and description for each file.
DOI: 10.17632/grf97zfjx7
title: Data Warsiman - Learner Task Performance Across Instructional Cycles

description: Learner task performance was examined to provide an overview of how students engaged with instructional tasks across iterative cycles
DOI: 10.17632/grf97zfjx7.1
title: Data Warsiman - Learner Task Performance Across Instructional Cycles

description: Learner task performance was examined to provide an overview of how students engaged with instructional tasks across iterative cycles
DOI: 10.17632/ypz3sdt473
title: Population size challenge in endemic freshwater species: Field and spatial modelling of the Idle Crayfish

description: The attached document contains the data required to reproduce the results of the study mentioned in the title. These are provided to ensure transparency and facilitate the independent verification of the statistical findings reported in the article.
DOI: 10.15468/dl.eymcas
title: Occurrence Download

description: A dataset listing the 744 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-81.14992 7.81167,-81.16452 7.70947,-81.03103 7.61144,-80.96429 7.4279,-80.99766 7.30901,-80.92884 7.14007,-80.44912 7.16927,-79.99444 7.40078,-79.91101 7.5155,-80.17798 7.90969,-80.42827 8.10158,-80.40324 8.22046,-80.50961 8.24341,-81.02686 8.03275,-81.14992 7.81167))",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset's 744 records were derived from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004334-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/ypz3sdt473.2
title: Population size challenge in endemic freshwater species: Field and spatial modelling of the Idle Crayfish

description: The attached document contains the data required to reproduce the results of the study mentioned in the title. These are provided to ensure transparency and facilitate the independent verification of the statistical findings reported in the article.
DOI: 10.17632/nsyp8nnkdj
title: Climate Risk and Intra-Firm Wage Inequality

description: This replication package provides the data, code, and documentation necessary to reproduce the main empirical results of the paper “Climate Risk and Intra-Firm Wage Inequality.”
The paper examines how firm-level climate risk affects the internal distribution of compensation between executives and rank-and-file employees in Chinese A-share listed firms over the period 2010-2022. Using a text-based climate risk index constructed from annual reports, we document that higher climate risk is associated with a wider executive-employee pay gap, driven primarily by wage suppression rather than increases in executive pay. We further explore two mechanisms: (i) an executive leverage channel related to agency costs and managerial bargaining power, and (ii) a climate-induced labor substitution channel via automation and AI adoption.
The replication materials are organized to maximize transparency and facilitate independent verification of all statistical analyses reported in the main text and appendices.
The Data folder contains the fully matched firm-region-industry-year panel dataset used for all empirical analyses in the paper, as well as several auxiliary files that separately document the construction of core explanatory variables, dependent variables, control variables, mechanism variables, and heterogeneity-related variables.
Due to licensing and access restrictions, raw firm-level financial data and certain regional indicators from commercial databases cannot be redistributed. The replication package therefore provides the constructed variables used in the analysis, together with placeholder fields and detailed documentation that enable researchers with access to the original sources to reconstruct the full dataset.
DOI: 10.17632/nsyp8nnkdj.4
title: Climate Risk and Intra-Firm Wage Inequality

description: This replication package provides the data, code, and documentation necessary to reproduce the main empirical results of the paper “Climate Risk and Intra-Firm Wage Inequality.”
The paper examines how firm-level climate risk affects the internal distribution of compensation between executives and rank-and-file employees in Chinese A-share listed firms over the period 2010-2022. Using a text-based climate risk index constructed from annual reports, we document that higher climate risk is associated with a wider executive-employee pay gap, driven primarily by wage suppression rather than increases in executive pay. We further explore two mechanisms: (i) an executive leverage channel related to agency costs and managerial bargaining power, and (ii) a climate-induced labor substitution channel via automation and AI adoption.
The replication materials are organized to maximize transparency and facilitate independent verification of all statistical analyses reported in the main text and appendices.
The Data folder contains the fully matched firm-region-industry-year panel dataset used for all empirical analyses in the paper, as well as several auxiliary files that separately document the construction of core explanatory variables, dependent variables, control variables, mechanism variables, and heterogeneity-related variables.
Due to licensing and access restrictions, raw firm-level financial data and certain regional indicators from commercial databases cannot be redistributed. The replication package therefore provides the constructed variables used in the analysis, together with placeholder fields and detailed documentation that enable researchers with access to the original sources to reconstruct the full dataset.
DOI: 10.17632/hxxy9pby9r
title: Predicting Atomic Structure Coordinates Using Machine Learning Regression Models A Comparative Study of Linear Regression, Random Forest, Decision Tree, and Neural Network Regression for Material Science Applications

description: The rapid digitalization of modern vehicles has led to the generation of high-dimensional sensor data, enabling advanced predictive maintenance and early failure detection strategies. Traditional diagnostic systems often fail to capture complex nonlinear patterns inherent in such data. This study proposes a robust machine learning benchmarking framework for vehicle failure prediction using a dataset containing 171 sensor-based attributes.
Seven supervised learning algorithms are evaluated under a consistent preprocessing and validation strategy: Logistic Regression, Support Vector Machine, k-Nearest Neighbors, Naïve Bayes, Decision Tree, Random Forest, and Neural Network. Performance is assessed using accuracy, precision, recall, F1-score, and Receiver Operating Characteristic–Area Under Curve (ROC–AUC) metrics to ensure robustness in imbalanced classification settings.
Experimental results reveal that ensemble-based methods, particularly Random Forest, significantly outperform linear, probabilistic, and distance-based models, achieving an AUROC of 0.983 on the test set. The findings provide empirical support for ensemble learning as a reliable and scalable solution for real-world vehicle failure diagnostics and predictive maintenance applications.
DOI: 10.15468/dl.nbahqx
title: Occurrence Download

description: A dataset containing 651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anadia bogotensis",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 651 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004344-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hxxy9pby9r.1
title: Predicting Atomic Structure Coordinates Using Machine Learning Regression Models A Comparative Study of Linear Regression, Random Forest, Decision Tree, and Neural Network Regression for Material Science Applications

description: The rapid digitalization of modern vehicles has led to the generation of high-dimensional sensor data, enabling advanced predictive maintenance and early failure detection strategies. Traditional diagnostic systems often fail to capture complex nonlinear patterns inherent in such data. This study proposes a robust machine learning benchmarking framework for vehicle failure prediction using a dataset containing 171 sensor-based attributes.
Seven supervised learning algorithms are evaluated under a consistent preprocessing and validation strategy: Logistic Regression, Support Vector Machine, k-Nearest Neighbors, Naïve Bayes, Decision Tree, Random Forest, and Neural Network. Performance is assessed using accuracy, precision, recall, F1-score, and Receiver Operating Characteristic–Area Under Curve (ROC–AUC) metrics to ensure robustness in imbalanced classification settings.
Experimental results reveal that ensemble-based methods, particularly Random Forest, significantly outperform linear, probabilistic, and distance-based models, achieving an AUROC of 0.983 on the test set. The findings provide empirical support for ensemble learning as a reliable and scalable solution for real-world vehicle failure diagnostics and predictive maintenance applications.
DOI: 10.5281/zenodo.18685459
title: Spiral Graph Tracings DR01

description: This dataset is bundled as a TGZ file that contains two file types. One type is the deprojected tracing images of 6171 spiral galaxies in FITS format. The other file type is a CSV file containing the deprojection parameters associated with the tracing images. The galaxies are from Hart et al. (2017; https://doi.org/10.1093/mnras/stx2137) and account for the first dataset obtained by the Spiral Graph citizen science project.
DOI: 10.5281/zenodo.18685458
title: Spiral Graph Tracings DR01

description: This dataset is bundled as a TGZ file that contains two file types. One type is the deprojected tracing images of 6171 spiral galaxies in FITS format. The other file type is a CSV file containing the deprojection parameters associated with the tracing images. The galaxies are from Hart et al. (2017; https://doi.org/10.1093/mnras/stx2137) and account for the first dataset obtained by the Spiral Graph citizen science project.
DOI: 10.17632/nyxfxrfc7b.2
title: Thermal Conductivity of Fe3C

description: Data for manuscript on thermal conductivity measurements of Fe3C.
DOI: 10.17632/2dyfdwpphd
title: Decreased energy acquisition, not the energetic costs of an immune response, can explain increased host activity and metabolic rate following infection

description: These Excel files contain the raw data from two experiments investigating the effect of a bacterial infection on the behaviour and metabolic rate of Nannoperca vittata, a threatened freshwater fish from south-western Australia.

In experiment 1 there were two treatments: exposed to bacterial infection (Exposed) or not exposed (Control). Measurements of standard metabolic rate (SMR) , activity (TL) and boldness (ET) were taken three times before exposure (weeks 1-3) and three times after exposure (weeks 6-8).

In experiment two there were four treatments: no lipopolysaccharide (LPS) injection and normal food supply (UNF); no LPS injection and food-deprived (UFD); LPS injection and normal food supply (INF); and LPS injection and food-deprived (IFD). Measurements of standard metabolic rate (SMR) , activity (TL) and boldness (ET) were taken three times before exposure (weeks 1-3) and three times after exposure (weeks 5-7).
DOI: 10.17632/2dyfdwpphd.1
title: Decreased energy acquisition, not the energetic costs of an immune response, can explain increased host activity and metabolic rate following infection

description: These Excel files contain the raw data from two experiments investigating the effect of a bacterial infection on the behaviour and metabolic rate of Nannoperca vittata, a threatened freshwater fish from south-western Australia.

In experiment 1 there were two treatments: exposed to bacterial infection (Exposed) or not exposed (Control). Measurements of standard metabolic rate (SMR) , activity (TL) and boldness (ET) were taken three times before exposure (weeks 1-3) and three times after exposure (weeks 6-8).

In experiment two there were four treatments: no lipopolysaccharide (LPS) injection and normal food supply (UNF); no LPS injection and food-deprived (UFD); LPS injection and normal food supply (INF); and LPS injection and food-deprived (IFD). Measurements of standard metabolic rate (SMR) , activity (TL) and boldness (ET) were taken three times before exposure (weeks 1-3) and three times after exposure (weeks 5-7).
DOI: 10.17632/c5mk3gc473.1
title: From Stream to Purchase: Exploring Parasocial Interaction and Social Presence as Mediators of Impulsive Purchase in TikTok Live Commerce

description: This dataset contains primary survey data investigating the drivers of impulsive purchase behavior in TikTok Live Commerce in Indonesia. Data were collected from 415 respondents using a structured questionnaire with a five-point Likert scale (1 = strongly disagree to 5 = strongly agree). The variables include Social Attraction, FOMO, Narrative Involvement, Telepresence, Parasocial Interaction, Social Presence, and Impulsive Purchase. All data have been anonymized and are provided to support transparency, replicability, and further quantitative analysis in the field of digital consumer behavior.
DOI: 10.17632/d4bv52fgmd
title: Datasets for Carbon Pricing and Energy Markets in Sustainable Production (2003-2025)

description: Dataset Title: Energy, Carbon, and Financial Market Data for Cleaner Production Research (2003-2025)

Description: This dataset supports the reproducibility of experiments in the paper titled Carbon Price Forecasting for Sustainable Industrial Transitions: A Multi-Source Heterogeneous Data Framework Based on ALA-LSTM-Transformer and Dual Interpretability. It includes time-series data on weather, energy prices, carbon emissions allowances, futures, and stock indices related to sustainable energy and carbon trading in Shanghai and EU markets.

Files:
- shanghai_history_daily.csv: Daily weather data for Shanghai (date, weather, high, low).
- 电力价格宏观EDB.xlsx: Shanghai Power closing prices (2003-2025, daily, source: Shanghai Stock Exchange via Miaoxiang Choice).
- 期货结算价(连续)_欧盟排放配额(EUA).xlsx: EU EUA futures settlement prices and volumes (2005-2025, daily, source: Wind).
- 碳价格与配额.xlsx: Shanghai carbon prices and allowances (2013-2025, daily).
- 焦煤期货历史数据.csv: Coking coal futures data (2013-2025, daily: close, open, high, low, volume, change%).
- 燃料油期货历史数据 (2).csv: Fuel oil futures data (2010-2025, daily: close, open, high, low, volume, change%).
- 天然气期货历史数据 (2).csv: Natural gas futures data (2012-2025, daily: close, open, high, low, volume, change%).
- 沪深300指数历史数据.csv: CSI 300 Index data (2010-2025, daily: close, open, high, low, volume, change%).

Sources: Public financial databases (Wind, Choice, stock exchanges). No sensitive or proprietary data.
Usage: Load with pandas (Python) or Excel for analysis. Units and formats as in files.

Carbon Price and Carbon Quota: Derived from the National Carbon Market Information Network and SEEE (Shanghai Environment and Energy Exchange).
Electricity Price: Sourced from Wind financial database.
Coking Coal, Natural Gas, and Fuel Oil: Obtained from Choice Financial Terminal.
CSI 300 and EUA Price: Compiled from Investing.com historical data.