cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/w95tsbgd6z
title: Replication package for "The Financial Consequences of Undiagnosed Memory Disorders" by Gresenz, Mitchell, Rodriguez, Wang, Turner and van der Klaauw

description: This replication package includes pseudo data and code for "The Financial Consequences of Undiagnosed Memory Disorders" by Carole Roan Gresenz, Jean M. Mitchell, Belicia Rodriguez, Crystal Wang, R. Scott Turner and Wilbert van der Klaauw, forthcoming in the Journal of Financial Economics. Please see README for details. 
Abstract: We examine the effect of undiagnosed memory disorders on credit outcomes using individually-matched nationally representative credit reporting and Medicare data. We find effects of early stage disease, years before diagnosis, on a wide range of financial outcomes, including credit card account payment delinquency and amount of delinquent balance, credit utilization among credit card account holders, mortgage delinquency and delinquent balance amount, and credit scores. Effects are pervasive, affecting seniors in single and coupled households, racial/ethnic minorities and non-minorities, and older adults living in areas with higher and lower education levels. Early stage effects are greater among singles and Black individuals.
DOI: 10.17632/w95tsbgd6z.1
title: Replication package for "The Financial Consequences of Undiagnosed Memory Disorders" by Gresenz, Mitchell, Rodriguez, Wang, Turner and van der Klaauw

description: This replication package includes pseudo data and code for "The Financial Consequences of Undiagnosed Memory Disorders" by Carole Roan Gresenz, Jean M. Mitchell, Belicia Rodriguez, Crystal Wang, R. Scott Turner and Wilbert van der Klaauw, forthcoming in the Journal of Financial Economics. Please see README for details. 
Abstract: We examine the effect of undiagnosed memory disorders on credit outcomes using individually-matched nationally representative credit reporting and Medicare data. We find effects of early stage disease, years before diagnosis, on a wide range of financial outcomes, including credit card account payment delinquency and amount of delinquent balance, credit utilization among credit card account holders, mortgage delinquency and delinquent balance amount, and credit scores. Effects are pervasive, affecting seniors in single and coupled households, racial/ethnic minorities and non-minorities, and older adults living in areas with higher and lower education levels. Early stage effects are greater among singles and Black individuals.
DOI: 10.17632/vt4s83pxx6
title: A Dataset of Aligned RGB and Multispectral UAV Imagery for Semantic Segmentation of Weedy Rice

description: This dataset includes 734 UAV-captured RGB images and their corresponding aligned multispectral (MS) images for the semantic segmentation of weedy rice in cultivated rice fields. The images were collected using a DJI Mavic 3 Multispectral UAV during three cropping seasons in Vietnam’s Mekong Delta. Each sample contains an RGB image, four MS bands (Green, Red, Red Edge, Near-Infrared), a binary mask indicating weedy rice regions, and a visualization overlay. All images were preprocessed (radiometric correction, undistortion, alignment, cropping) and resized to 1280 × 960 pixels. Ground-truth masks were generated using a fine-tuned Segment Anything Model (SAM), followed by manual verification. Spatial metadata and file mappings are included. The dataset supports research in precision agriculture, multi-modal semantic segmentation, and UAV-based crop monitoring.
DOI: 10.17632/vt4s83pxx6.1
title: A Dataset of Aligned RGB and Multispectral UAV Imagery for Semantic Segmentation of Weedy Rice

description: This dataset includes 734 UAV-captured RGB images and their corresponding aligned multispectral (MS) images for the semantic segmentation of weedy rice in cultivated rice fields. The images were collected using a DJI Mavic 3 Multispectral UAV during three cropping seasons in Vietnam’s Mekong Delta. Each sample contains an RGB image, four MS bands (Green, Red, Red Edge, Near-Infrared), a binary mask indicating weedy rice regions, and a visualization overlay. All images were preprocessed (radiometric correction, undistortion, alignment, cropping) and resized to 1280 × 960 pixels. Ground-truth masks were generated using a fine-tuned Segment Anything Model (SAM), followed by manual verification. Spatial metadata and file mappings are included. The dataset supports research in precision agriculture, multi-modal semantic segmentation, and UAV-based crop monitoring.
DOI: 10.6084/m9.figshare.29607851.v2
title: <b>Allocation of responsibility for carbon emission reduction, carbon unlocking pathways and high-quality development of agriculture from the perspective of the Agricultural Industrialization Coalition</b>

description: Green agriculture is necessary for high-quality agricultural development, emphasizing ecological protection, resource conservation, and product quality for sustainable growth. This study adopts a dynamic deductive approach to investigate the responsibility and pathways for reducing carbon emissions in agriculture. The study assessed the changes in total factor productivity of green agriculture in Chinese provinces using the SBM-GML index model. The study also assessed agricultural modernization, high-quality development, and sectoral coordination through the entropy model and coupled coordination model. Spatial autocorrelation and Markov chain methods were applied to analyze trends. The results of the study elucidated the carbon emission reduction model of “Government &gt; Agricultural Industrialization Entrepreneurs &gt; Farmers”, in which government policies, green technology promotion, and low-carbon practices are key. Pilot policy innovations by agricultural industrialization coalitions have significantly contributed to agricultural development, demonstrating positive effects in terms of coupling coordination, green productivity growth, and modernization. In most regions, technological innovation has mainly contributed to green productivity growth, but the phenomenon of “the strong getting stronger and the weak getting weaker ”persists. The geographical distribution of high-quality agricultural development remains stable, interregional mobility is low, and the spatial lag effect is evident in the stage of regional development. The main objective of this study is to provide policy recommendations for promoting the development of green agriculture and enhancing high-quality development in China.
DOI: 10.15468/dl.a4aee5
title: Occurrence Download

description: A dataset containing 1307 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lygodium microphyllum",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1307 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022849-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.654y6m
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aster novi-belgii",
 "Country is Austria",
 "HasCoordinate is true"
 ]
}

 The dataset includes 43 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022850-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29608901
title: <b>Simulation part of the code: </b><b>Allocation of responsibility for carbon emission reduction, carbon </b><b>unlocking</b><b> pathways and high-quality development of agriculture from the perspective of the Agricultural Industrialization Consortium</b>

description: Green agriculture is necessary for high-quality agricultural development, emphasizing ecological protection, resource conservation, and product quality for sustainable growth. This study adopts a dynamic deductive approach to investigate the responsibility and pathways for reducing carbon emissions in agriculture. The study assessed the changes in total factor productivity of green agriculture in Chinese provinces using the SBM-GML index model. The study also assessed agricultural modernization, high-quality development, and sectoral coordination through the entropy model and coupled coordination model. Spatial autocorrelation and Markov chain methods were applied to analyze trends. The results of the study elucidated the carbon emission reduction model of “Government &gt; Agricultural Industrialization Consortium &gt; Farmers”, in which government policies, green technology promotion, and low-carbon practices are key. The agricultural industrialization consortium policy innovation pilot has significantly contributed to agricultural development, demonstrating positive effects in terms of coupling coordination, green productivity growth, and modernization. In most regions, technological innovation has mainly contributed to green productivity growth, but the phenomenon of “the strong getting stronger, and the weak getting weaker” persists. The geographical distribution of high-quality agricultural development remains stable, interregional mobility is low, and the spatial lag effect is evident in the stage of regional development. The main objective of this study is to provide policy recommendations for promoting the development of green agriculture and enhancing high-quality development in China.
DOI: 10.6084/m9.figshare.29608901.v5
title: <b>Simulation part of the code: </b><b>Allocation of responsibility for carbon emission reduction, carbon </b><b>unlocking</b><b> pathways and high-quality development of agriculture from the perspective of the Agricultural Industrialization Consortium</b>

description: Green agriculture is necessary for high-quality agricultural development, emphasizing ecological protection, resource conservation, and product quality for sustainable growth. This study adopts a dynamic deductive approach to investigate the responsibility and pathways for reducing carbon emissions in agriculture. The study assessed the changes in total factor productivity of green agriculture in Chinese provinces using the SBM-GML index model. The study also assessed agricultural modernization, high-quality development, and sectoral coordination through the entropy model and coupled coordination model. Spatial autocorrelation and Markov chain methods were applied to analyze trends. The results of the study elucidated the carbon emission reduction model of “Government &gt; Agricultural Industrialization Consortium &gt; Farmers”, in which government policies, green technology promotion, and low-carbon practices are key. The agricultural industrialization consortium policy innovation pilot has significantly contributed to agricultural development, demonstrating positive effects in terms of coupling coordination, green productivity growth, and modernization. In most regions, technological innovation has mainly contributed to green productivity growth, but the phenomenon of “the strong getting stronger, and the weak getting weaker” persists. The geographical distribution of high-quality agricultural development remains stable, interregional mobility is low, and the spatial lag effect is evident in the stage of regional development. The main objective of this study is to provide policy recommendations for promoting the development of green agriculture and enhancing high-quality development in China.
DOI: 10.6084/m9.figshare.29608901.v4
title: <b>Simulation part of the code: </b><b>Allocation of responsibility for carbon emission reduction, carbon </b><b>unlocking</b><b> pathways and high-quality development of agriculture from the perspective of the Agricultural Industrialization Coalition</b>

description: Green agriculture is necessary for high-quality agricultural development, emphasizing ecological protection, resource conservation, and product quality for sustainable growth. This study adopts a dynamic deductive approach to investigate the responsibility and pathways for reducing carbon emissions in agriculture. The study assessed the changes in total factor productivity of green agriculture in Chinese provinces using the SBM-GML index model. The study also assessed agricultural modernization, high-quality development, and sectoral coordination through the entropy model and coupled coordination model. Spatial autocorrelation and Markov chain methods were applied to analyze trends. The results of the study elucidated the carbon emission reduction model of “Government &gt; Agricultural Industrialization Entrepreneurs &gt; Farmers”, in which government policies, green technology promotion, and low-carbon practices are key. Pilot policy innovations by agricultural industrialization coalitions have significantly contributed to agricultural development, demonstrating positive effects in terms of coupling coordination, green productivity growth, and modernization. In most regions, technological innovation has mainly contributed to green productivity growth, but the phenomenon of “the strong getting stronger and the weak getting weaker ”persists. The geographical distribution of high-quality agricultural development remains stable, interregional mobility is low, and the spatial lag effect is evident in the stage of regional development. The main objective of this study is to provide policy recommendations for promoting the development of green agriculture and enhancing high-quality development in China.
DOI: 10.15468/dl.k93dsq
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lithobates catesbeianus",
 "Country is Ecuador",
 "HasCoordinate is true"
 ]
}

 The dataset includes 133 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022851-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6s9mkd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Phaethornis longirostris)",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022853-250717081556266/datasets/export for details.
DOI: 10.15468/dl.rnfcxp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Phaethornis longirostris)",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022854-250717081556266/datasets/export for details.
DOI: 10.15468/dl.vsvd4n
title: Occurrence Download

description: A dataset containing 142 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Scirpus atrovirens, Holoschoenus atrovirens, Scirpus atrovirens angustispicatus, Scirpus atrovirens atrovirens, Scirpus atrovirens cephalanthus, Scirpus atrovirens prolifer, Scirpus atrovirens proliferus, Scirpus atrovirens sychnocephalus, Scirpus atrovirens viviparus, Scirpus atrovirens atrovirens)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Continent is Europe",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 142 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022855-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vc7ggz
title: Occurrence Download

description: A dataset containing 3298 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lithobates catesbeianus",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3298 records from 80 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022857-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yhqc5e
title: Occurrence Download

description: A dataset containing 2369 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dioscorea polygonoides"
 ]
}

 The dataset includes 2369 records from 182 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022856-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bhs4pz
title: Occurrence Download

description: A dataset containing 452 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arabidopsis neglecta"
 ]
}

 The dataset includes 452 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022860-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16185786
title: Mind the Gap! The Overlooked Ethical Dimensions of GenAI in Software Modeling Education

description: This dataset supports the methodology and findings presented in the paper "Mind the Gap! The Overlooked Ethical Dimensions of GenAI in Software Modeling Education". It contains all materials used during the systematic literature review and snowballing process.

Included files:





Individual .bib files from each digital library (ACM DL, Science Direct, IEEE Explorer, Scopus, SpringerLink and Web of Science) used in the initial search phase.




A merged .bib file after removing duplicates across databases.




An Excel spreadsheet documenting the exclusion process, including reasons for exclusion at each stage of screening, as well as the outcome of the backward snowballing procedure.



This dataset ensures full transparency and reproducibility of the review process and may serve as a resource for future research on the intersection of generative AI, ethics, and software modeling education.
DOI: 10.5281/zenodo.16185787
title: Mind the Gap! The Overlooked Ethical Dimensions of GenAI in Software Modeling Education

description: This dataset supports the methodology and findings presented in the paper "Mind the Gap! The Overlooked Ethical Dimensions of GenAI in Software Modeling Education". It contains all materials used during the systematic literature review and snowballing process.

Included files:





Individual .bib files from each digital library (ACM DL, Science Direct, IEEE Explorer, Scopus, SpringerLink and Web of Science) used in the initial search phase.




A merged .bib file after removing duplicates across databases.




An Excel spreadsheet documenting the exclusion process, including reasons for exclusion at each stage of screening, as well as the outcome of the backward snowballing procedure.



This dataset ensures full transparency and reproducibility of the review process and may serve as a resource for future research on the intersection of generative AI, ethics, and software modeling education.
DOI: 10.15468/dl.ym5g6s
title: Occurrence Download

description: A dataset containing 1827 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Valvata macrostoma"
 ]
}

 The dataset includes 1827 records from 93 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022861-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13012/b2idb-7439710_v1
title: Data for: Probabilistic global maps of crop-specific areas from 1961 to 2014

description: Agriculture has substantial socioeconomic and environmental impacts that vary between crops. However, information on how the spatial distribution of specific crops has changed over time across the globe is relatively sparse. We introduce the Probabilistic Cropland Allocation Model (PCAM), a novel algorithm to estimate where specific crops have likely been grown over time. Specifically, PCAM downscales annual and national-scale data on the crop-specific area harvested of 17 major crops to a global 0.5-degree grid from 1961-2014. 

The resulting database presented here provides annual global gridded likelihood estimates of crop-specific areas. Both mean and standard deviations of grid cell fractions are available for each of the 17 crops. Each netCDF file contains an individual year of data with an additional variable ("crs") that defines the coordinate reference system used. Our results provide new insights into the likely changes in the spatial distribution of major crops over the past half-century. For additional information, please see the related paper by Jackson et al. (2019) in Environmental Research Letters (https://doi.org/10.1088/1748-9326/ab3b93).
DOI: 10.15468/dl.yte255
title: Occurrence Download

description: A dataset containing 853 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Iran (Islamic Republic of)",
 "OccurrenceStatus is Present",
 "TaxonKey is Bombus"
 ]
}

 The dataset includes 853 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022862-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.59nhyr
title: Occurrence Download

description: A dataset containing 89 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Syzygium cumini",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 89 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022858-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16269942
title: Data set (moldex3D simulations) of the results of the research titled Application of New Conformal Cooling Layouts to the Green Injection Molding of Complex Slender Polymeric Parts with High Dimensional Specifications

description: This dataset comprises the results obtained from simulations performed with Moldex3D software for the research titled "Application of New Conformal Cooling Layouts to the Green Injection Molding of Complex Slender Polymeric Parts with High Dimensional Specifications."

The main objective of these simulations was to evaluate and demonstrate the effectiveness of a new green conformal cooling system, specifically designed to optimize the injection molding process of complex slender polymeric parts, improving dimensional quality and sustainability.