cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.bmmxmz
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Glomera dubia J.J.Sm."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0229978-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xwjm5m
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Seseli diffusum (Roxb. ex Sm.) Santapau & Wagh"
 ]
}

 The dataset includes 30 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126548-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v258ms
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleospora celtidis (Castagne) Sacc., 1883",
 {
 "or" : [
 "Country is United States of America",
 "Country is Canada"
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126549-230530130749713/datasets/export for details.
DOI: 10.15468/dl.m8937s
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Malvastrum grandiflorum Krapov."
 ]
}

 The dataset includes 64 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018720-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rkhkz5
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Glomera ericifolia Ridl."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0229987-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k55d5n
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleospora ellisii Wehm.",
 {
 "not" : {
 "Country" : [
 "is United States of America"
 ]
 }
 },
 {
 "not" : {
 "Country" : [
 "is Canada"
 ]
 }
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126557-230530130749713/datasets/export for details.
DOI: 10.48597/p4qm-tesy
title: Measurement of Aerosol light scattering at Neumayer

description: Measurement of Aerosol light scattering at Neumayer
DOI: 10.15468/dl.rfc85g
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Marrubium propinquum Fisch. & C.A.Mey."
 ]
}

 The dataset includes 53 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019574-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qtsd3j
title: Occurrence Download

description: A dataset containing 264 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleospora helvetica Niessl",
 {
 "or" : [
 "Country is United States of America",
 "Country is Canada"
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 }
 ]
}

 The dataset includes 264 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126560-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s5gugj
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Octarrhena podochiloides (Schltr.) Schuit."
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050086-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11571848
title: Deep transfer learning for detection of breast arterial calcifications on mammograms: a comparative study

description: Introduction Breast arterial calcifications (BAC) are common incidental findings on routine mammograms, whichhave been suggested as a sex-specific biomarker of cardiovascular disease (CVD) risk. Previous work showed the efficacyof a pretrained convolutional network (CNN), VCG16, for automatic BAC detection. In this study, we further testedthe method by a comparative analysis with other ten CNNs.Material and methods Four-view standard mammography exams from 1,493 women were included in this retrospectivestudy and labeled as BAC or non-BAC by experts. The comparative study was conducted using elevenpretrained convolutional networks (CNNs) with varying depths from five architectures including Xception, VGG,ResNetV2, MobileNet, and DenseNet, fine-tuned for the binary BAC classification task. Performance evaluationinvolved area under the receiver operating characteristics curve (AUC-ROC) analysis, F1-score (harmonic mean of precisionand recall), and generalized gradient-weighted class activation mapping (Grad-CAM++) for visual explanations.Results The dataset exhibited a BAC prevalence of 194/1,493 women (13.0%) and 581/5,972 images (9.7%). Amongthe retrained models, VGG, MobileNet, and DenseNet demonstrated the most promising results, achieving AUCROCs> 0.70 in both training and independent testing subsets. In terms of testing F1-score, VGG16 ranked first, higherthan MobileNet (0.51) and VGG19 (0.46). Qualitative analysis showed that the Grad-CAM++ heatmaps generatedby VGG16 consistently outperformed those produced by others, offering a finer-grained and discriminative localizationof calcified regions within images.Conclusion Deep transfer learning showed promise in automated BAC detection on mammograms, where relativelyshallow networks demonstrated superior performances requiring shorter training times and reduced resources.Relevance statement Deep transfer learning is a promising approach to enhance reporting BAC on mammogramsand facilitate developing efficient tools for cardiovascular risk stratification in women, leveraging large-scale mammographicscreening programs.Key points• We tested different pretrained convolutional networks (CNNs) for BAC detection on mammograms.• VGG and MobileNet demonstrated promising performances, outperforming their deeper, more complexcounterparts.• Visual explanations using Grad-CAM++ highlighted VGG16’s superior performance in localizing BAC.
DOI: 10.5281/zenodo.11571849
title: Deep transfer learning for detection of breast arterial calcifications on mammograms: a comparative study

description: Introduction Breast arterial calcifications (BAC) are common incidental findings on routine mammograms, whichhave been suggested as a sex-specific biomarker of cardiovascular disease (CVD) risk. Previous work showed the efficacyof a pretrained convolutional network (CNN), VCG16, for automatic BAC detection. In this study, we further testedthe method by a comparative analysis with other ten CNNs.Material and methods Four-view standard mammography exams from 1,493 women were included in this retrospectivestudy and labeled as BAC or non-BAC by experts. The comparative study was conducted using elevenpretrained convolutional networks (CNNs) with varying depths from five architectures including Xception, VGG,ResNetV2, MobileNet, and DenseNet, fine-tuned for the binary BAC classification task. Performance evaluationinvolved area under the receiver operating characteristics curve (AUC-ROC) analysis, F1-score (harmonic mean of precisionand recall), and generalized gradient-weighted class activation mapping (Grad-CAM++) for visual explanations.Results The dataset exhibited a BAC prevalence of 194/1,493 women (13.0%) and 581/5,972 images (9.7%). Amongthe retrained models, VGG, MobileNet, and DenseNet demonstrated the most promising results, achieving AUCROCs> 0.70 in both training and independent testing subsets. In terms of testing F1-score, VGG16 ranked first, higherthan MobileNet (0.51) and VGG19 (0.46). Qualitative analysis showed that the Grad-CAM++ heatmaps generatedby VGG16 consistently outperformed those produced by others, offering a finer-grained and discriminative localizationof calcified regions within images.Conclusion Deep transfer learning showed promise in automated BAC detection on mammograms, where relativelyshallow networks demonstrated superior performances requiring shorter training times and reduced resources.Relevance statement Deep transfer learning is a promising approach to enhance reporting BAC on mammogramsand facilitate developing efficient tools for cardiovascular risk stratification in women, leveraging large-scale mammographicscreening programs.Key points• We tested different pretrained convolutional networks (CNNs) for BAC detection on mammograms.• VGG and MobileNet demonstrated promising performances, outperforming their deeper, more complexcounterparts.• Visual explanations using Grad-CAM++ highlighted VGG16’s superior performance in localizing BAC.
DOI: 10.15468/dl.cvty2v
title: Occurrence Download

description: A dataset containing 837143 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Russula Pers."
 ]
}

 The dataset includes 837143 records from 550 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0229965-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e238229
title: A Global Voting Advice Application for the US Election Aimed at Foreign Audiences

description: Billions of people outside of the US hold a vested interest in the outcome of US presidential elections, despite not being allowed to vote. We developed 9 Voting Advice Applications (VAAs) for the 2020 elections and 5 VAAs for the 2024 elections in partnership with leading newspapers across Europe, Asia, and Oceania. Across these two elections, the VAA tools offered 724,294 users from 187 countries an issue-based comparison with Biden and Trump in 2020, and with Trump and Harris in 2024. Users answered demographic questions, the issue statements, and additional attitudinal items. These issue statements covered both domestic topics and topics of the US’ foreign policy. The candidates’ positions were coded using robust primary and secondary sources on 29 (2020) and 62 (2024) issue statements. This deposit includes the candidates’ placement data as well as the user data generated by these VAAs, offering an unprecedented opportunity to analyze global perceptions of US politics and the election’s far-reaching influence on international relations.
description: It is highly advisable to consult the associated publication in Nature Scientific Data for a comprehensive explanation of the data collection procedures, measures, and analytical framework.
DOI: 10.3886/e238229v3
title: A Global Voting Advice Application for the US Election Aimed at Foreign Audiences

description: Billions of people outside of the US hold a vested interest in the outcome of US presidential elections, despite not being allowed to vote. We developed 9 Voting Advice Applications (VAAs) for the 2020 elections and 5 VAAs for the 2024 elections in partnership with leading newspapers across Europe, Asia, and Oceania. Across these two elections, the VAA tools offered 724,294 users from 187 countries an issue-based comparison with Biden and Trump in 2020, and with Trump and Harris in 2024. Users answered demographic questions, the issue statements, and additional attitudinal items. These issue statements covered both domestic topics and topics of the US’ foreign policy. The candidates’ positions were coded using robust primary and secondary sources on 29 (2020) and 62 (2024) issue statements. This deposit includes the candidates’ placement data as well as the user data generated by these VAAs, offering an unprecedented opportunity to analyze global perceptions of US politics and the election’s far-reaching influence on international relations.
description: It is highly advisable to consult the associated publication in Nature Scientific Data for a comprehensive explanation of the data collection procedures, measures, and analytical framework.
DOI: 10.15468/dl.39qpqq
title: Occurrence Download

description: A dataset containing 234 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Germany",
 "OccurrenceStatus is Present",
 "PublishingOrg is one of (28eb1a3f-1c15-4a95-931a-4af90ecb574d, c8d737e0-2ff8-42e8-b8fc-6b805d26fc5f, 2754e9c0-0e43-4f65-968a-6f16b9c378ce)",
 "TaxonKey is Cucujus cinnaberinus",
 "Year 2015-2025"
 ]
}

 The dataset includes 234 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018717-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xuqk62
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cordylus warreni",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 75 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018719-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zf3vtx
title: Occurrence Download

description: A dataset containing 2661 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tityus pachyurus",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2661 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009746-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17171065
title: Erfassung seltener Brutvögel im Rammert und angrenzenden Streuobstgebieten mittels PAM und Revierkartierung (2025)
DOI: 10.5281/zenodo.17171064
title: Erfassung seltener Brutvögel im Rammert und angrenzenden Streuobstgebieten mittels PAM und Revierkartierung (2025)
DOI: 10.15468/dl.xs2fpb
title: Occurrence Download

description: A dataset containing 120592 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "GadmGid is one of (PRT.2.1_1, PRT.2.12_1)",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 120592 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009670-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18770733
title: Data and analysis code for: "Beyond True/False in Generative AI: Toward Contextual Agreement States for Reliable Statements"

description: Data and Code Repository

Study: Beyond True/False in Generative AI: Toward Contextual Agreement States for Reliable StatementsAuthors: Heimo Müller, Markus Plass, Andreas HolzingerAffiliations: Machine Learning and Information Science Group, Medical University of Graz, Austria; Human Machine Mind Cooperation, Graz, Austria; Human-Centered AI Lab, BOKU University Vienna, AustriaEthics approval: EK-Number 34-527 ex 21/22, Medical University of GrazFunding: Austrian Science Fund (FWF), Project "Explainable AI", Grant P-32554
DOI: 10.5281/zenodo.18768827
title: Integrated Salivary Proteomic and Metabolomic Analyses Reveal Molecular Characterization and Novel Biomarker Panels of Chronic Obstructive Pulmonary Disease

description: Abstract

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection.
DOI: 10.5281/zenodo.18768828
title: Integrated Salivary Proteomic and Metabolomic Analyses Reveal Molecular Characterization and Novel Biomarker Panels of Chronic Obstructive Pulmonary Disease

description: Abstract

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection.
DOI: 10.5281/zenodo.18770732
title: Data and analysis code for: "Beyond True/False in Generative AI: Toward Contextual Agreement States for Reliable Statements"

description: Data and Code Repository

Study: Beyond True/False in Generative AI: Toward Contextual Agreement States for Reliable StatementsAuthors: Heimo Müller, Markus Plass, Andreas HolzingerAffiliations: Machine Learning and Information Science Group, Medical University of Graz, Austria; Human Machine Mind Cooperation, Graz, Austria; Human-Centered AI Lab, BOKU University Vienna, AustriaEthics approval: EK-Number 34-527 ex 21/22, Medical University of GrazFunding: Austrian Science Fund (FWF), Project "Explainable AI", Grant P-32554
DOI: 10.5281/zenodo.18770774
title: FEATURES OF ARTISTIC PSYCHOLOGISM AND POETICS IN V.M. GARSHIN'S WAR STORIES

description: The article analyzes the poetics of V.M. Garshin’s war stories within the context of the historical perception of the Russo-Turkish War (1877–1878). Primary focus is placed on the subjectivization of the narrative, naturalism, and the transformation of the "little man" image during wartime. The author explores Garshin’s rejection of traditional heroic pathos in favor of an existential understanding of the value of human life.
DOI: 10.5281/zenodo.18770773
title: FEATURES OF ARTISTIC PSYCHOLOGISM AND POETICS IN V.M. GARSHIN'S WAR STORIES

description: The article analyzes the poetics of V.M. Garshin’s war stories within the context of the historical perception of the Russo-Turkish War (1877–1878). Primary focus is placed on the subjectivization of the narrative, naturalism, and the transformation of the "little man" image during wartime. The author explores Garshin’s rejection of traditional heroic pathos in favor of an existential understanding of the value of human life.
DOI: 10.6084/m9.figshare.29390189
title: Supplementary files (database and ROSES form) to <i>What happens after oil and gas decommissioning? A global systematic review of marine environmental effects</i>

description: These are the supplementary files to the systematic review by Lemasson & Knight entitled "<b>What happens after oil and gas decommissioning? A global systematic review of marine environmental effects</b>" accepted for publication in <i>Ecological Applications. </i>It contains the database will all coded evidence (scientific literature) on the environmental effects of decommissioned oil and gas platforms, as well as the ROSES form (RepOrting standards for Systematic Evidence Syntheses).
DOI: 10.6084/m9.figshare.29390189.v1
title: Supplementary files (database and ROSES form) to <i>What happens after oil and gas decommissioning? A global systematic review of marine environmental effects</i>

description: These are the supplementary files to the systematic review by Lemasson & Knight entitled "<b>What happens after oil and gas decommissioning? A global systematic review of marine environmental effects</b>" accepted for publication in <i>Ecological Applications. </i>It contains the database will all coded evidence (scientific literature) on the environmental effects of decommissioned oil and gas platforms, as well as the ROSES form (RepOrting standards for Systematic Evidence Syntheses).
DOI: 10.15468/dl.8urky4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Campoplex capitator",
 "BasisOfRecord is Human Observation",
 "Year is greater than or equal to 1990",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009748-260221153910048/datasets/export for details.