cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/zpv2wrxpwf.1
title: Administration of a Male-Specific Depression Screener during Rural Primary Care Clinic Visits to Improve Screening Rates data set

description: This study aimed to assess whether the rates of depression screening in men can be increased by implementing the Male Depression Risk Scale-22 (MDRS-22) within the Integrated Screening Action Model (I-SAM) framework.

Background 
Men are diagnosed with depression at half the rate of women but die from suicide four times more often. Healthcare clinics with as-needed depression screening only, which is not specifically designed for male patients, could be missing depression diagnoses or high risks in males. 

Methods 
MDRS-22 screening was offered to 132 undiagnosed men between the ages of 18 and 60 years who were not on Medicare, during routine visits to a rural primary care site, where screening for depression was not offered to all patients. The researchers compared the depression screening rates from the study period (September 1 to December 31, 2023) with the rates from the previous year during the same period using the site’s Electronic Medical Records.

Results
Fifty of the 132 qualified men were willing to undergo the screening. During the same time frame in the previous year, there were 175 similar qualified males presented for visits with no evidence of any depression screening. Thus, depression screening for qualifying patients compared to the prior year increased from zero to 38%. Six percent of the screened patients were at high and 4% were at extreme risk for depression. 

Conclusion
Implementation of screening with the I-SAM framework increased the rate of depression screening in men and identified individuals with high or extreme risk for depression. The rate of screening for depression can be improved by offering the screenings during typical provider visits. Adhering to screening recommendations for depression can allow patients to have providers specifically assess mental health instead of focusing only on physical complaints. Physician visits that addressed mental health issues increased from 10.7% of visits in 2006-2007 to 15.9% by 2016 and 2018 (Rotenstein et al., 2023), but further improvements may be needed.
DOI: 10.17632/kcgf45y24m
title: Anonymous Transactional Dataset

description: The dataset is comprised of real-world historical sales transactions and product metadata collected from a local Food and Beverage (F&B) Micro-Small-Medium Enterprise (MSME) operating multiple outlets in Indonesia. This data can be used by researchers, data scientists, and industry professionals using various techniques in recommender system and machine learning.
DOI: 10.17632/kcgf45y24m.2
title: Anonymous Transactional Dataset

description: The dataset is comprised of real-world historical sales transactions and product metadata collected from a local Food and Beverage (F&B) Micro-Small-Medium Enterprise (MSME) operating multiple outlets in Indonesia. This data can be used by researchers, data scientists, and industry professionals using various techniques in recommender system and machine learning.
DOI: 10.17632/znhx7sg9pk
title: University of Alberta Biochar-Concrete Beam Test Results

description: This database contains raw data from biochar-concrete beams tested at the University of Alberta in 2025. Specific details regarding the specific dimensions, materials, and test setup/instrumentation is available in the MSc Thesis "Experimental Evaluation of Biochar as Supplementary Cementitious Material in Reinforced Concrete" by Hafiz Asher Muhammad (current access link: https://ualberta.scholaris.ca/items/eccb2570-5776-45c7-b133-06de18676bd2).
DOI: 10.17632/znhx7sg9pk.1
title: University of Alberta Biochar-Concrete Beam Test Results

description: This database contains raw data from biochar-concrete beams tested at the University of Alberta in 2025. Specific details regarding the specific dimensions, materials, and test setup/instrumentation is available in the MSc Thesis "Experimental Evaluation of Biochar as Supplementary Cementitious Material in Reinforced Concrete" by Hafiz Asher Muhammad (current access link: https://ualberta.scholaris.ca/items/eccb2570-5776-45c7-b133-06de18676bd2).
DOI: 10.17632/cyb2xcbcrg
title: Dataset on Gold Prices, Real Interest Rates and Interest Payments

description: This dataset contains monthly macro-financial time series used to analyse the relationship between gold prices, real interest rates, and fiscal conditions. It includes international gold prices, U.S. real long-term interest rates, and interest payments on publicly held federal debt. All variables are constructed at monthly frequency and transformed as described in the accompanying article.
DOI: 10.17632/cyb2xcbcrg.1
title: Dataset on Gold Prices, Real Interest Rates and Interest Payments

description: This dataset contains monthly macro-financial time series used to analyse the relationship between gold prices, real interest rates, and fiscal conditions. It includes international gold prices, U.S. real long-term interest rates, and interest payments on publicly held federal debt. All variables are constructed at monthly frequency and transformed as described in the accompanying article.
DOI: 10.17632/crgh2ynmzv.1
title: A Comprehensive Dataset for Context-Aware Security Monitoring for Anomaly Detection

description: This article describes a high-dimensional dataset designed for context-aware security monitoring and anomaly detection in digital transaction systems. The data encompasses 112 features, including transactional metadata, user behavioral patterns, and advanced technical telemetry (IP reputation, VPN detection, device fingerprinting, network security indicators). A unique aspect of this dataset is the integration of Large Language Model (LLM) outputs, providing risk scores and natural language reasoning for contextual security assessment. This dataset is particularly valuable for training machine learning models that require a hybrid approach, combining traditional tabular data with AI-generated contextual insights to identify security threats such as account takeover, suspicious behavioral patterns, and social engineering attacks across multiple digital channels.
DOI: 10.17632/247r7sjsjx
title: Replication data for "Intersecting Inequalities: The Impact of Gender and Income Disparities on Female Educational Access in Asia-Pacific Countries"
DOI: 10.17632/247r7sjsjx.3
title: Replication data for "Intersecting Inequalities: The Impact of Gender and Income Disparities on Female Educational Access in Asia-Pacific Countries"
DOI: 10.17632/rf7rhwsh4v
title: Machine Learning-Based Prediction of Surface Roughness in FFF PLA and Hybrid CNC Machining

description: This dataset supports the study “Machine Learning-Based Prediction of Surface Roughness in FFF PLA and Hybrid CNC Machining” and provides comprehensive experimental, manufacturing, and machine learning data for predicting surface roughness (Ra) in Polylactic Acid (PLA) components produced using fused filament fabrication (FFF) and hybrid additive–subtractive manufacturing.

The study investigates the influence of surface inclination on Ra, an aspect rarely addressed in prior literature, along with the effects of CNC post-processing. A Taguchi L54 design of experiments was implemented across surface inclinations ranging from 10° to 80°, resulting in 54 printed parts. Ten supervised machine learning (ML) algorithms were evaluated, with the Explainable Boosting Machine (EBM) demonstrating the highest predictive performance (R² = 0.983 for AM and R² = 0.616 for hybrid machining). In the AM stage, inclination angle, layer height, nozzle diameter, and extrusion temperature were identified as the dominant parameters, with optimal Ra achieved at a 0.10 mm layer height, 0.25 mm nozzle diameter, and 210 °C extrusion temperature. In hybrid machining, the combination of AM parameters with machining depth of cut and infill density reduced Ra by 85–91%, with a 0.20 mm depth of cut consistently producing low Ra values. Verification experiments confirmed prediction errors within ±2 µm for AM (MAPE = 6.62%) and ±1 µm for hybrid machining (MAPE = 9.17%). Additionally, a preliminary coolant-assisted machining trial demonstrated a further Ra reduction of 15–21%.

The dataset enables full reproducibility of the experimental workflow, including additive manufacturing, hybrid CNC machining, surface roughness measurements, machine learning model development, and validation. It is intended for researchers and practitioners working in additive manufacturing, hybrid manufacturing, surface integrity, and data-driven process optimization.

The dataset is organized into eleven sub-folders containing AM G-codes for 54 printed parts, CNC G-codes for hybrid and validation machining experiments, surface roughness (Ra) measurement reports for AM, hybrid, and wet machining stages, Taguchi L54 design of experiments files, machine learning datasets, Python scripts for ten supervised ML algorithms, and verification datasets for model validation.
DOI: 10.17632/rf7rhwsh4v.2
title: Machine Learning-Based Prediction of Surface Roughness in FFF PLA and Hybrid CNC Machining

description: This dataset supports the study “Machine Learning-Based Prediction of Surface Roughness in FFF PLA and Hybrid CNC Machining” and provides comprehensive experimental, manufacturing, and machine learning data for predicting surface roughness (Ra) in Polylactic Acid (PLA) components produced using fused filament fabrication (FFF) and hybrid additive–subtractive manufacturing.

The study investigates the influence of surface inclination on Ra, an aspect rarely addressed in prior literature, along with the effects of CNC post-processing. A Taguchi L54 design of experiments was implemented across surface inclinations ranging from 10° to 80°, resulting in 54 printed parts. Ten supervised machine learning (ML) algorithms were evaluated, with the Explainable Boosting Machine (EBM) demonstrating the highest predictive performance (R² = 0.983 for AM and R² = 0.616 for hybrid machining). In the AM stage, inclination angle, layer height, nozzle diameter, and extrusion temperature were identified as the dominant parameters, with optimal Ra achieved at a 0.10 mm layer height, 0.25 mm nozzle diameter, and 210 °C extrusion temperature. In hybrid machining, the combination of AM parameters with machining depth of cut and infill density reduced Ra by 85–91%, with a 0.20 mm depth of cut consistently producing low Ra values. Verification experiments confirmed prediction errors within ±2 µm for AM (MAPE = 6.62%) and ±1 µm for hybrid machining (MAPE = 9.17%). Additionally, a preliminary coolant-assisted machining trial demonstrated a further Ra reduction of 15–21%.

The dataset enables full reproducibility of the experimental workflow, including additive manufacturing, hybrid CNC machining, surface roughness measurements, machine learning model development, and validation. It is intended for researchers and practitioners working in additive manufacturing, hybrid manufacturing, surface integrity, and data-driven process optimization.

The dataset is organized into eleven sub-folders containing AM G-codes for 54 printed parts, CNC G-codes for hybrid and validation machining experiments, surface roughness (Ra) measurement reports for AM, hybrid, and wet machining stages, Taguchi L54 design of experiments files, machine learning datasets, Python scripts for ten supervised ML algorithms, and verification datasets for model validation.
DOI: 10.5281/zenodo.18327646
title: Tulane virus aggregation study data

description: This repository contains Plaque assay data measuring virus infectivity after a 5-hour exposure at 1, 10, and 100 mM CaCl2, along with control samples. Size measurement data at different CaCl2 concentrations and pH values are provided, and zeta potential data measuring the net charge of the virus at different pH values and CaCl2 concentrations.
DOI: 10.5281/zenodo.18327645
title: Tulane virus aggregation study data

description: This repository contains Plaque assay data measuring virus infectivity after a 5-hour exposure at 1, 10, and 100 mM CaCl2, along with control samples. Size measurement data at different CaCl2 concentrations and pH values are provided, and zeta potential data measuring the net charge of the virus at different pH values and CaCl2 concentrations.
DOI: 10.15468/dl.vu5fvb
title: Occurrence Download

description: A dataset containing 5310 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Scandentia"
 ]
}

 The dataset includes 5310 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002652-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xbzkkj
title: Occurrence Download

description: A dataset containing 4621 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Switzerland",
 "GadmGid is CHE.8_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vulpes vulpes"
 ]
}

 The dataset includes 4621 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002653-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kknxga
title: Occurrence Download

description: A dataset containing 974 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Apareiodon affinis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 974 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002654-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18328055
title: MULTIMEDIA VOSITALARI ASOSIDA TALABALARNING KОGNITIV KОMPETENSIYАSINI RIVOJLANTIRISH METODIKASI

description: Ushbu maqolada multimedia vositalari asosida bo‘lajak texnologiya fani o‘qituvchilarining mustaqil fikrlash ko‘nikmalarini rivojlantirish masalasi tahlil qilinadi. Zamonaviy ta’lim jarayonida multimedia texnologiyalaridan samarali foydalanish nafaqat o‘qitish jarayonini interaktivlashtirish, balki talabalarning mustaqil fikrlash qobiliyatlarini shakllantirish va rivojlantirishga ham xizmat qiladi. Tadqiqotda turli xil axborot-kommunikatsiya texnologiyalari (AKT), vizual va audio resurslar, interaktiv dasturlar va onlayn platformalar orqali ta’lim samaradorligini oshirish imkoniyatlari o‘rganiladi. Shuningdek, maqolada mustaqil fikrlashni shakllantirishning pedagogik yondashuvlari, metodikasi va amaliy tajribalari bayon etilgan. Olingan natijalar multimedia vositalari yordamida texnologiya fani o‘qituvchilarining kasbiy kompetensiyasini oshirishda muhim ahamiyatga ega ekanligini ko‘rsatadi.
DOI: 10.5281/zenodo.18328056
title: MULTIMEDIA VOSITALARI ASOSIDA TALABALARNING KОGNITIV KОMPETENSIYАSINI RIVOJLANTIRISH METODIKASI

description: Ushbu maqolada multimedia vositalari asosida bo‘lajak texnologiya fani o‘qituvchilarining mustaqil fikrlash ko‘nikmalarini rivojlantirish masalasi tahlil qilinadi. Zamonaviy ta’lim jarayonida multimedia texnologiyalaridan samarali foydalanish nafaqat o‘qitish jarayonini interaktivlashtirish, balki talabalarning mustaqil fikrlash qobiliyatlarini shakllantirish va rivojlantirishga ham xizmat qiladi. Tadqiqotda turli xil axborot-kommunikatsiya texnologiyalari (AKT), vizual va audio resurslar, interaktiv dasturlar va onlayn platformalar orqali ta’lim samaradorligini oshirish imkoniyatlari o‘rganiladi. Shuningdek, maqolada mustaqil fikrlashni shakllantirishning pedagogik yondashuvlari, metodikasi va amaliy tajribalari bayon etilgan. Olingan natijalar multimedia vositalari yordamida texnologiya fani o‘qituvchilarining kasbiy kompetensiyasini oshirishda muhim ahamiyatga ega ekanligini ko‘rsatadi.
DOI: 10.48331/scielodata.uior8l
title: Dados de replicação para o artigo: Formação de professores que atuam em espaços de privação de liberdade

description: A formação dos professores que atuam em escolas prisionais precisa considerar as especificidades de pessoas privadas de liberdade que vão além dos conteúdos programáticos estabelecidos pelas diretrizes curriculares e é uma forma a auxiliá-las no processo de ressocialização. O objetivo deste estudo foi mapear as evidências científicas sobre os conteúdos abordados no processo de formação de professores para atuarem em escolas prisionais. A pesquisa foi realizada por meio de uma Revisão de Escopo ancorada no referencial do Joanna Briggs Institute (JBI) a partir da questão norteadora “Como se caracterizam os conteúdos abordados no processo de formação de professores que atuam em unidades prisionais?. Não houve recorte temporal e a busca foi realizada em bases de dados selecionadas, além de busca no Google Scholar, durante os meses de junho e agosto de 2023. Os estudos foram selecionados a partir da leitura dos títulos, resumos e texto completo por dois revisores independentes. A amostra final foi de doze estudos publicados entre os anos de 1921 e 2022, dos quais onze foram publicados na língua inglesa e apenas um na língua portuguesa. Os conteúdos abordados no processo de formação foram categorizados nos seguintes núcleos empíricos: Conteúdos sobre Técnicas de Segurança, Conteúdos sobre Processos Pedagógicos e Conteúdos sobre Gestão de Comportamento. Neste sentido conclui-se que os conteúdos são insuficientes para subsidiar os professores a atuarem nas nuances e complexidade do contexto prisional, o que requer adoção de estratégias focadas no desenvolvimento contínuo de currículos de formação abrangentes e específicos ao contexto.
DOI: 10.5281/zenodo.18325238
title: A Practical Guide for Establishing a Technical Debt Management Process

description: The additional material for the paper "Towards Best Practices for Managing Technical Debt in Practice" comprises the following documents:

 

* TDM_Guide.pdf

  Whitepaper for practitioners: Guideline to establish a TDM process

 

* Team_Comparison_adoptedApproaches_challenges.xls

  - Tab: Adopted_Approaches_Overview

  - Tab: Challenges_Overview

  

* Workshop Agendas.pdf

  Example Agendas for KickOff and other workshops

 

* Survey_Overview.xlsx

  - List of all survey questions, type, "mandatory" status, 

    and their relevance/relation to the RQs

* TDMGuide_0_InitialTalk.pdf

Slides for the Inital Talk given to participants at the beginning of the action research to introduce some basic information and terminology

 

 

* Team A/ADOSTDTickets_Template.pdf

  Screenshot of the backlog's TD item template of Team A.

* Team B/JiraTDTickets_Template.pdf

  Screenshot of the backlog's TD item template of Team B.

* Team C/GitHubTDTickets_Template.pdf

  Screenshot of the backlog's TD item template of Team C.

 

 

* Team<A|B|C>/workshop_flipcharts/WS<No.>_<explanation>.jpg

  Anonymized flipchart photos to give an impression of the workshops 

  and workshops' results.

  Translations are directly included in the photos.

 

* Team<A|B|C>/workshop_slides/TDMGuide_<No>_Workshop.pptx

  Anonymized slides of each workshop to give an impression of the workshops 

  and workshops' results.

  

 

* Team<A|B|C>/evaluations/Meeting_Observations_Researcher<1|2>.xslx

  - Individual observation protocols of each researcher to show the comments of both researchers

  

* Team<A|B|C>/evaluations/Meetings_Overview_combinedObservations_Evaluation_Figures.xlsx

  - Overview of all meetings plus information on length, participants, 

    whether a video exists and was used for evaluation

  - Observation protocols results combined for both researchers 

    (except for comments -> see above for commments)

  - Summation, evaluations, and resulting figures

 

* Team<A|B|C>/evaluations/TD-SAGAT_Survey_and_SurveyResults_Figures.xlsx

  - Survey questions for TD-SAGAT plus results

  - Evaluation plus figures

 

* Team<A|B|C>/evaluations/Workshop_Survey_and_SurveyResults_Figures.xlsx

  - Survey questions for Workshops plus results

  - Evaluation plus figures

 

* Team<A|B|C>/evaluations/Kickoff_Survey_and_SurveyResults.xlsx

  - Survey questions for Kickoff Workshops  plus results

  - Evaluation in Workshop_Survey_and_SurveyResults_Figures.xslx

  

* Team<A|B|C>/evaluations/Backlog_Evaluations_and_Figures.xlsx

  - Last manual backlog evaluation before the visualisations could be used for this evaluation

 

 

* Team<A|B>/visualizations/V<No.>_<explanation>.png

  - Anonymized visualizations of Team A and B. 

  Team C was not able to visualize the results due to technical issues.

  

* Team<A|B>/visualizations/Team<A|B>_readme.txt

  - Text file with short information for each visualization
DOI: 10.5281/zenodo.15476330
title: Data on policy support for electric vehicles

description: This dataset contains detailed, machine-readable data on support policies for electric vehicle adoption from the years 2000-2024 for Germany, Greece, Ireland, and France. It contains information on the following policy instruments:



Subsidies

Tax incentives (rebates, exemptions)

Fee decreases or exemptions

Feebates or bonus/malus schemes

Soft loans

Tenders with additional financial support

Incentives to promote user behavioral change

Technology standards


The work was performed by Silvia Weko, Puru Malhotra, Aksornchan Chaianong, Ioannis Milioritsas, Dogukan Günkördü, Franziska Bold, and Johan Lilliestam, during 2024-2025. The work was led by Silvia Weko and data were cleaned by Puru Malhotra and Silvia Weko. Data were gathered by PM, IM, DG, FB, and SW. AC and JL contributed to the research structure and process. 

The data is published with CC BY-SA 4.0. The dataset should be cited as:

Weko, S., Malhotra, P., Bold, F., Chaianong, A., Günkördü, D., Milioritsas, I., and Lilliestam, J. (2025): Data on policy support for electric vehicles (Version 0, February 2025). Sustainability Transition Policy Group, Friedrich-Alexander-Universität Erlangen-Nürnberg. DOI 10.5281/zenodo.15476330.

The authors would like to thank the German Federal Government, the German State Governments, and the Joint Science Conference (GWK) for their funding and support as part of the NFDI4Energy consortium. The work was funded by the German Research Foundation (DFG) – 501865131 within the German National Research Data Infrastructure (NFDI, www.nfdi.de). Silvia Weko would also like to thank the Office for Equal Opportunities for Women in Science and the Arts at the School of Business, Economics, and Law at FAU Erlangen-Nürnberg.
DOI: 10.15468/dl.2npaxb
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chile",
 "OccurrenceStatus is Present",
 "TaxonKey is Avellanita bustillosii"
 ]
}

 The dataset includes 46 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002659-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25934/pr00012677
title: Phase 3, Randomized, Open Label Trial of Lenalidomide/Dexamethasone With or Without Elotuzumab in Relapsed or Refractory Multiple Myeloma (MM)

description: The purpose of the study is to determine whether the addition of Elotuzumab to Lenalidomide/low-dose Dexamethasone will increase the progression free survival (PFS).
DOI: 10.15468/dl.dsgqj5
title: Occurrence Download

description: A dataset containing 933 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chile",
 "DatasetKey is iNaturalist Research-grade Observations",
 "OccurrenceStatus is Present",
 "TaxonKey is Drimys winteri"
 ]
}

 The dataset includes 933 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002657-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.