cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30620555
title: Disassembly Use Case for Teaching, Training, and Research Validation in Circular Production Learning Factories: Use case data

description: Circular production, particularly disassembly and remanufacturing, has gained increasing attention in both industry and research. Learning factories, which effectively link research and industry, are also increasingly expanding their scope to include circular production. Disassembly is an essential yet complex process within circular production, characterized by challenges that fundamentally differ from linear systems, such as diverging material flows and uncertain product conditions. However, existing circular production learning factories view disassembly as a supporting step within broader production systems. Dedicated approaches that explicitly focus on teaching and training disassembly are still lacking. At the same time, available disassembly use cases for research validation are often simplified or insufficiently documented, which limits their reproducibility and industrial relevance. To address this gap in a joint environment, this work presents a disassembly use case for circular production learning factories. The design follows the approach for circular economy learning modules by the International Association of Learning Factories and was guided by an industry advisory board. Methods from disassembly research were applied for product and process modeling to ensure compatibility with current research and enable validation. The use case is described across the product, process, and setting dimensions and supported by comprehensive data, including bills of materials, disassembly plans, work instructions, and layout concepts. Its utilization for teaching and training is demonstrated through integration into a circular economy learning module.
DOI: 10.6084/m9.figshare.30620555.v1
title: Disassembly Use Case for Teaching, Training, and Research Validation in Circular Production Learning Factories: Use case data

description: Circular production, particularly disassembly and remanufacturing, has gained increasing attention in both industry and research. Learning factories, which effectively link research and industry, are also increasingly expanding their scope to include circular production. Disassembly is an essential yet complex process within circular production, characterized by challenges that fundamentally differ from linear systems, such as diverging material flows and uncertain product conditions. However, existing circular production learning factories view disassembly as a supporting step within broader production systems. Dedicated approaches that explicitly focus on teaching and training disassembly are still lacking. At the same time, available disassembly use cases for research validation are often simplified or insufficiently documented, which limits their reproducibility and industrial relevance. To address this gap in a joint environment, this work presents a disassembly use case for circular production learning factories. The design follows the approach for circular economy learning modules by the International Association of Learning Factories and was guided by an industry advisory board. Methods from disassembly research were applied for product and process modeling to ensure compatibility with current research and enable validation. The use case is described across the product, process, and setting dimensions and supported by comprehensive data, including bills of materials, disassembly plans, work instructions, and layout concepts. Its utilization for teaching and training is demonstrated through integration into a circular economy learning module.
DOI: 10.5281/zenodo.17610187
title: Dataset for "Rapid generation of transition-state conformer ensembles via constrained distance geometry"

description: Dataset for "Rapid generation of transition-state conformer ensembles via constrained distance geometry"

Stefan P. Schmid, Henrik Seng, Thibault Kläy, Kjell Jorner

2025-11-14, Zürich

Content of this entry

This entry contains the dataset and scripts for reproduction of the results of the paper Rapid generation of transition-state conformer ensembles via constrained distance geometry. The content is divided into multiple folders:- `data` contains all the data generated for the manuscript. A README is provided in this folder for further explanation.- `scripts/conformer_generation` contains all the necessary code to generate conformers using racerTS. A README is provided in this folder for further explanation.- `scripts/plots` contains all the analysis files (plotting scripts) and the plots for the manuscript. A README is provided in this folder for further explanation.- `scripts/workflow` contains all the files to re-run the benchmarking workflow. A README is provided in this folder for further explanation.

Acknowledgements

The authors thank Greg Landrum for fruitful discussions. The authors thank Anna Bischoff for designing the fast logo of racerTS. S.P.S. thanks the Talent Program in Catalysis and Sustainable Chemistry for generous support of this research. This publication was created as part of NCCR Catalysis (grant numbers 180544 and 225147), a National Centre of Competence in Research funded by the Swiss National Science Foundation.
DOI: 10.6084/m9.figshare.30618551
title: <b>Reflections of Cognitive Load in Player Discourse: A Linguistic Profiling of Steam Reviews for RPGs</b>

description: Background: Cognitive load (CL) in digital games is usually measured with lab-based sensors or questionnaires, which are intrusive, costly, and hard to scale. Existing studies rarely examine how players’ own discourse reflects intrinsic, extraneous, and germane load. Methods: We propose the Game-Adaptive Linguistic Profile (G-LP) model, which maps linguistic indicators (e.g., sentence length, entropy, negativity, thematic term density) to the three components of Cognitive Load Theory. Using NLP on 15,000 English Steam reviews from five RPGs (Baldur’s Gate 3, Disco Elysium, Divinity: Original Sin 2, Pathfinder: Wrath of the Righteous, Pillars of Eternity II), we computed game-level CL profiles and compared them via Kruskal–Wallis and Dunn–Bonferroni tests. Results: All three CL profiles differed significantly across games (H_intrinsic = 344.92, H_extraneous = 100.44, H_germane = 186.75, all ps &lt; .001; ε² = .006–.023). Pathfinder and Pillars showed higher intrinsic and extraneous profiles, while Baldur’s Gate 3 exhibited lower intrinsic and extraneous load, consistent with “cognitive load optimization by design.” Pillars had the highest germane profile, whereas Disco Elysium’s unexpectedly neutral germane profile suggests that its philosophical vocabulary is often used in stylistic or memetic ways not fully captured as deep meaning-making. Conclusion: The G-LP model shows that natural language from player reviews can be used to profile intrinsic, extraneous, and germane cognitive load in RPGs. Discourse-based profiling offers a scalable, non-invasive complement to traditional CL measures and provides a new lens for game and UX designers to evaluate and balance “cognitive efficiency” in game experiences.
DOI: 10.6084/m9.figshare.30618551.v1
title: <b>Reflections of Cognitive Load in Player Discourse: A Linguistic Profiling of Steam Reviews for RPGs</b>

description: Background: Cognitive load (CL) in digital games is usually measured with lab-based sensors or questionnaires, which are intrusive, costly, and hard to scale. Existing studies rarely examine how players’ own discourse reflects intrinsic, extraneous, and germane load. Methods: We propose the Game-Adaptive Linguistic Profile (G-LP) model, which maps linguistic indicators (e.g., sentence length, entropy, negativity, thematic term density) to the three components of Cognitive Load Theory. Using NLP on 15,000 English Steam reviews from five RPGs (Baldur’s Gate 3, Disco Elysium, Divinity: Original Sin 2, Pathfinder: Wrath of the Righteous, Pillars of Eternity II), we computed game-level CL profiles and compared them via Kruskal–Wallis and Dunn–Bonferroni tests. Results: All three CL profiles differed significantly across games (H_intrinsic = 344.92, H_extraneous = 100.44, H_germane = 186.75, all ps &lt; .001; ε² = .006–.023). Pathfinder and Pillars showed higher intrinsic and extraneous profiles, while Baldur’s Gate 3 exhibited lower intrinsic and extraneous load, consistent with “cognitive load optimization by design.” Pillars had the highest germane profile, whereas Disco Elysium’s unexpectedly neutral germane profile suggests that its philosophical vocabulary is often used in stylistic or memetic ways not fully captured as deep meaning-making. Conclusion: The G-LP model shows that natural language from player reviews can be used to profile intrinsic, extraneous, and germane cognitive load in RPGs. Discourse-based profiling offers a scalable, non-invasive complement to traditional CL measures and provides a new lens for game and UX designers to evaluate and balance “cognitive efficiency” in game experiences.
DOI: 10.15468/dl.4dewye
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prosopis chilensis",
 "Country is Angola",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024812-250811113504898/datasets/export for details.
DOI: 10.15468/dl.zmsgg2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Enteromius aboinensis)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024815-250811113504898/datasets/export for details.
DOI: 10.17632/55ygh2gr99
title: Validación de instrumento

description: Validación de instrumento
DOI: 10.15468/dl.hx6c7z
title: Occurrence Download

description: A dataset containing 173 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dethawia splendens",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 173 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008015-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/55ygh2gr99.1
title: Validación de instrumento

description: Validación de instrumento
DOI: 10.17632/9y6whkgyf4
title: Multiple Solution Methods of Factoring Trinomials in Undergraduate Mathematics

description: This study explores the impact of the Compare and Discuss Multiple Strategies (CDMS) framework for teaching multiple solution methods for factoring trinomials. Factoring is a foundational skill that serves as a gateway to college-level STEM coursework yet remains a frequent conceptual hurdle for students transitioning to algebraic thinking. Using a mixed-methods pre-post quasi-experimental design, 39 undergraduate students in developmental mathematics participated in a CDMS-based intervention. The research investigated performance changes, method usage patterns, and student experiences.

Results revealed large effect sizes that significantly exceeded typical educational interventions, with substantial improvements across all trinomial types. Method diversity increased, with students shifting from single-method dependency to the flexible use of four distinct approaches, particularly visual strategies like the Box and Tic-Tac-Toe methods. Qualitative findings indicated increased confidence and strategic thinking, with nearly half of participants explicitly valuing the exposure to multiple methods. These findings provide the first empirical evidence for implementing CDMS in college-level developmental mathematics, demonstrating that multiple solution methods can produce meaningful learning gains for students who traditionally struggle with algebraic concepts.
DOI: 10.17632/9y6whkgyf4.1
title: Multiple Solution Methods of Factoring Trinomials in Undergraduate Mathematics

description: This study explores the impact of the Compare and Discuss Multiple Strategies (CDMS) framework for teaching multiple solution methods for factoring trinomials. Factoring is a foundational skill that serves as a gateway to college-level STEM coursework yet remains a frequent conceptual hurdle for students transitioning to algebraic thinking. Using a mixed-methods pre-post quasi-experimental design, 39 undergraduate students in developmental mathematics participated in a CDMS-based intervention. The research investigated performance changes, method usage patterns, and student experiences.

Results revealed large effect sizes that significantly exceeded typical educational interventions, with substantial improvements across all trinomial types. Method diversity increased, with students shifting from single-method dependency to the flexible use of four distinct approaches, particularly visual strategies like the Box and Tic-Tac-Toe methods. Qualitative findings indicated increased confidence and strategic thinking, with nearly half of participants explicitly valuing the exposure to multiple methods. These findings provide the first empirical evidence for implementing CDMS in college-level developmental mathematics, demonstrating that multiple solution methods can produce meaningful learning gains for students who traditionally struggle with algebraic concepts.
DOI: 10.17632/m2sx4gsscy
title: Ocean-Bottom Seismic Data

description: Ocean-Bottom Seismic Data
DOI: 10.15468/dl.vxx3zs
title: Occurrence Download

description: A dataset containing 4063 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cyprinus rubrofuscus"
 ]
}

 The dataset includes 4063 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008016-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/m2sx4gsscy.1
title: Ocean-Bottom Seismic Data

description: Ocean-Bottom Seismic Data
DOI: 10.17632/zkgkvb5s4d
title: Does Common Institutional Ownership Matter for Credit Ratings?

description: Using a sample of Chinese A-share non-financial listed firms from 2008 to 2022, we document a significantly positive association between common institutional ownership and corporate credit ratings. Mechanism analyses indicate that this effect operates primarily through reductions in operational risk and improvements in information quality, reflecting the synergistic governance role of common institutional investors. Cross-sectional analyses further show that the positive effect is more pronounced for firms operating in regions with weaker legal environments, lower-quality internal controls, and weaker external monitoring.
DOI: 10.17632/zkgkvb5s4d.1
title: Does Common Institutional Ownership Matter for Credit Ratings?

description: Using a sample of Chinese A-share non-financial listed firms from 2008 to 2022, we document a significantly positive association between common institutional ownership and corporate credit ratings. Mechanism analyses indicate that this effect operates primarily through reductions in operational risk and improvements in information quality, reflecting the synergistic governance role of common institutional investors. Cross-sectional analyses further show that the positive effect is more pronounced for firms operating in regions with weaker legal environments, lower-quality internal controls, and weaker external monitoring.
DOI: 10.17632/4cgthtph6m
title: Supplementary Data for Increasing Incidence of Cutaneous T-Cell Lymphoma Among Children and Young Adults in the United States, 1997–2019: A National Population-Based Study Using the National Childhood Cancer Registry

description: Supplementary Data for Increasing Incidence of Cutaneous T-Cell Lymphoma Among Children and Young Adults in the United States, 1997–2019: A National Population-Based Study Using the National Childhood Cancer Registry in JAAD.
DOI: 10.17632/4cgthtph6m.1
title: Supplementary Data for Increasing Incidence of Cutaneous T-Cell Lymphoma Among Children and Young Adults in the United States, 1997–2019: A National Population-Based Study Using the National Childhood Cancer Registry

description: Supplementary Data for Increasing Incidence of Cutaneous T-Cell Lymphoma Among Children and Young Adults in the United States, 1997–2019: A National Population-Based Study Using the National Childhood Cancer Registry in JAAD.
DOI: 10.17632/r4rv63nfgd
title: Supplement for Reply to Torres et al. Reply to Woodie et al. regarding biologics and tuberculosis risk

description: Supplement for Reply to Torres et al. Reply to Woodie et al. regarding biologics and tuberculosis risk
DOI: 10.17632/r4rv63nfgd.1
title: Supplement for Reply to Torres et al. Reply to Woodie et al. regarding biologics and tuberculosis risk

description: Supplement for Reply to Torres et al. Reply to Woodie et al. regarding biologics and tuberculosis risk
DOI: 10.17632/tbk5zdv863
title: RNA3D-Bench

description: Benchmarking RNA Tertiary Structure Prediction Models and Evaluation Metrics. This package includes RNA structures produced by 14 RNA 3D prediction models.
DOI: 10.17632/tbk5zdv863.1
title: RNA3D-Bench

description: Benchmarking RNA Tertiary Structure Prediction Models and Evaluation Metrics. This package includes RNA structures produced by 14 RNA 3D prediction models.
DOI: 10.17632/k4z6t6nz7g.4
title: From Conflict to Creativity: US-China Trade War and Chinese Corporate Innovation

description: This is the replication folder for the paper titled “From Conflict to Creativity: US–China Trade War and Chinese Corporate Innovation”, authored by Jian Du, Xingye Jin, Jing Li, and Xinyi Shen.This version was last updated on January 22, 2026.
DOI: 10.17632/64fhpmsg7w
title: Effectiveness of a 6W Multidimensional Model of Care Trajectories-Based Respiratory Rehabilitation Program in Children with Bronchiolitis Obliterans: A Randomized Controlled Trial

description: This study aims to evaluate the feasibility and preliminary effects of a personalized respiratory rehabilitation program based on the "6W Multidimensional Model" for children with bronchiolitis obliterans (BO). The primary hypothesis is that, compared with usual care, this program can significantly improve intervention adherence among children and their families. The secondary hypotheses are that higher adherence will be accompanied by improvements in pulmonary function, respiratory muscle strength, and exercise tolerance, as well as a reduction in clinical severity, without an increase in adverse reactions.

The dataset contains complete raw data from a controlled trial. The data primarily include: 1) Basic information: anonymized demographic and baseline clinical characteristics of participants; 2) Process and outcome measures: detailed records of session participation data for the intervention group (used to calculate the primary outcome—adherence), as well as raw data from repeated measurements of all participants at three time points—baseline, mid-intervention (4 weeks), and post-intervention (12 weeks)—including pulmonary function, respiratory muscle strength, clinical symptom severity, etc.; and 3) Safety monitoring data: records of all adverse reactions.

Data were collected through clinical assessments, standardized pulmonary function tests, scale-based questionnaires, and research logs. The data files are organized in a "long format" to facilitate repeated measures analysis of variance, testing the "time × group" interaction effect to assess whether the trend of intervention effects over time differs between groups.

The data can be interpreted and used as follows: researchers can first compare adherence between groups to assess feasibility, and then use repeated measures models to analyze secondary outcomes. It is important to note that the correlation between adherence and outcomes cannot be directly equated with causation. This dataset is suitable for validating the implementation effects of complex interventions, exploring determinants of rehabilitation responses, or serving as a resource for methodological comparisons and meta-analyses.
DOI: 10.17632/64fhpmsg7w.1
title: Effectiveness of a 6W Multidimensional Model of Care Trajectories-Based Respiratory Rehabilitation Program in Children with Bronchiolitis Obliterans: A Randomized Controlled Trial

description: This study aims to evaluate the feasibility and preliminary effects of a personalized respiratory rehabilitation program based on the "6W Multidimensional Model" for children with bronchiolitis obliterans (BO). The primary hypothesis is that, compared with usual care, this program can significantly improve intervention adherence among children and their families. The secondary hypotheses are that higher adherence will be accompanied by improvements in pulmonary function, respiratory muscle strength, and exercise tolerance, as well as a reduction in clinical severity, without an increase in adverse reactions.

The dataset contains complete raw data from a controlled trial. The data primarily include: 1) Basic information: anonymized demographic and baseline clinical characteristics of participants; 2) Process and outcome measures: detailed records of session participation data for the intervention group (used to calculate the primary outcome—adherence), as well as raw data from repeated measurements of all participants at three time points—baseline, mid-intervention (4 weeks), and post-intervention (12 weeks)—including pulmonary function, respiratory muscle strength, clinical symptom severity, etc.; and 3) Safety monitoring data: records of all adverse reactions.

Data were collected through clinical assessments, standardized pulmonary function tests, scale-based questionnaires, and research logs. The data files are organized in a "long format" to facilitate repeated measures analysis of variance, testing the "time × group" interaction effect to assess whether the trend of intervention effects over time differs between groups.

The data can be interpreted and used as follows: researchers can first compare adherence between groups to assess feasibility, and then use repeated measures models to analyze secondary outcomes. It is important to note that the correlation between adherence and outcomes cannot be directly equated with causation. This dataset is suitable for validating the implementation effects of complex interventions, exploring determinants of rehabilitation responses, or serving as a resource for methodological comparisons and meta-analyses.
DOI: 10.17632/362x7xbhpy
title: Emotions and Stock Market Primary Dataset

description: This dataset contains primary survey data collected from individual investors in India, examining emotional responses and investment decision-making across different market events.
The supplementary file contains additional tables, robustness checks, and detailed statistical results supporting the analysis of emotional responses and investment decision-making across market events.
DOI: 10.17632/362x7xbhpy.1
title: Emotions and Stock Market Primary Dataset

description: This dataset contains primary survey data collected from individual investors in India, examining emotional responses and investment decision-making across different market events.
The supplementary file contains additional tables, robustness checks, and detailed statistical results supporting the analysis of emotional responses and investment decision-making across market events.