cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14893797
title: Datasets and models used in the manuscript "On the generalization ability of probabilistic neural networks for hyperspectral remote sensing of absorption properties across optically complex waters"

description: This upload contains all datasets, models and model estimates used in the manuscript "On the generalization ability of probabilistic neural networks for hyperspectral remote sensing of absorption properties across optically complex waters": https://doi.org/10.1016/j.rse.2025.114820 

Upon using this dataset for your work, please acknowledge the dataset curators and authors by citing our article published in Remote Sensing of Environment.
DOI: 10.5281/zenodo.14893798
title: Datasets and models used in the manuscript "On the generalization ability of probabilistic neural networks for hyperspectral remote sensing of absorption properties across optically complex waters"

description: This upload contains all datasets, models and model estimates used in the manuscript "On the generalization ability of probabilistic neural networks for hyperspectral remote sensing of absorption properties across optically complex waters": https://doi.org/10.1016/j.rse.2025.114820 

Upon using this dataset for your work, please acknowledge the dataset curators and authors by citing our article published in Remote Sensing of Environment.
DOI: 10.5281/zenodo.11393594
title: Dataset: an empirical study on architectural smells through a pipeline for continuous technical debt assessment

description: Dataset of the study "An empirical study on architectural smells through a pipeline for continuous technical debt assessment"

Abstract

In recent years, researchers spent an increasing amount of effort investigating technical debt, with quantitative methods, and in particular static analysis, being the most common approach to investigate such a topic.

However, quantitative studies are susceptible, to varying degrees, to external validity threats, which hinder the generalisation of their findings.In response to this concern, researchers strive to expand the scope of their studies by incorporating a larger number of projects into their analyses. This practice is typically executed on a case-by-case basis, necessitating substantial data collection efforts that have to be repeated for each new study.

To address this issue, this paper presents an approach for tackling this problem and enabling researchers to study architectural smells, a well-known indicator of architectural technical debt,  at a large scale. Specifically, we introduce a novel approach to a data collection pipeline that leverages Apache Airflow to continuously generate up-to-date, large-scale datasets with any static analysis tool.

Finally, we use the data collected through the pipeline to study the correlation between architectural smells and logical coupling in order to understand how smells influence maintenance efforts.
DOI: 10.5281/zenodo.11393593
title: Dataset: an empirical study on architectural smells through a pipeline for continuous technical debt assessment

description: Dataset of the study "An empirical study on architectural smells through a pipeline for continuous technical debt assessment"

Abstract

In recent years, researchers spent an increasing amount of effort investigating technical debt, with quantitative methods, and in particular static analysis, being the most common approach to investigate such a topic.

However, quantitative studies are susceptible, to varying degrees, to external validity threats, which hinder the generalisation of their findings.In response to this concern, researchers strive to expand the scope of their studies by incorporating a larger number of projects into their analyses. This practice is typically executed on a case-by-case basis, necessitating substantial data collection efforts that have to be repeated for each new study.

To address this issue, this paper presents an approach for tackling this problem and enabling researchers to study architectural smells, a well-known indicator of architectural technical debt,  at a large scale. Specifically, we introduce a novel approach to a data collection pipeline that leverages Apache Airflow to continuously generate up-to-date, large-scale datasets with any static analysis tool.

Finally, we use the data collected through the pipeline to study the correlation between architectural smells and logical coupling in order to understand how smells influence maintenance efforts.
DOI: 10.5281/zenodo.13827946
title: Dataset: an empirical study on architectural smells through a pipeline for continuous technical debt assessment

description: Dataset of the study "An empirical study on architectural smells through a pipeline for continuous technical debt assessment"

Abstract

In recent years, researchers spent an increasing amount of effort investigating technical debt, with quantitative methods, and in particular static analysis, being the most common approach to investigate such a topic.

However, quantitative studies are susceptible, to varying degrees, to external validity threats, which hinder the generalisation of their findings.In response to this concern, researchers strive to expand the scope of their studies by incorporating a larger number of projects into their analyses. This practice is typically executed on a case-by-case basis, necessitating substantial data collection efforts that have to be repeated for each new study.

To address this issue, this paper presents an approach for tackling this problem and enabling researchers to study architectural smells, a well-known indicator of architectural technical debt,  at a large scale. Specifically, we introduce a novel approach to a data collection pipeline that leverages Apache Airflow to continuously generate up-to-date, large-scale datasets with any static analysis tool.

Finally, we use the data collected through the pipeline to study the correlation between architectural smells and logical coupling in order to understand how smells influence maintenance efforts.
DOI: 10.5281/zenodo.15051564
title: Dataset: an empirical study on architectural smells through a pipeline for continuous technical debt assessment

description: Dataset of the study "An empirical study on architectural smells through a pipeline for continuous technical debt assessment"

Abstract

In recent years, researchers spent an increasing amount of effort investigating technical debt, with quantitative methods, and in particular static analysis, being the most common approach to investigate such a topic.

However, quantitative studies are susceptible, to varying degrees, to external validity threats, which hinder the generalisation of their findings.In response to this concern, researchers strive to expand the scope of their studies by incorporating a larger number of projects into their analyses. This practice is typically executed on a case-by-case basis, necessitating substantial data collection efforts that have to be repeated for each new study.

To address this issue, this paper presents an approach for tackling this problem and enabling researchers to study architectural smells, a well-known indicator of architectural technical debt,  at a large scale. Specifically, we introduce a novel approach to a data collection pipeline that leverages Apache Airflow to continuously generate up-to-date, large-scale datasets with any static analysis tool.

Finally, we use the data collected through the pipeline to study the correlation between architectural smells and logical coupling in order to understand how smells influence maintenance efforts.
DOI: 10.15468/dl.bqumw5
title: Occurrence Download

description: A dataset containing 4778 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Observation",
 "OccurrenceStatus is Present",
 "TaxonKey is Larus marinus Linnaeus, 1758"
 ]
}

 The dataset includes 4778 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017314-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y7k6pf
title: Occurrence Download

description: A dataset containing 1054 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Earthworms and potworms in Dutch soils from the National Biological Soil Monitoring project 1997-2014",
 "Country is Belgium"
 ]
}

 The dataset includes 1054 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017315-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w7scwm
title: Occurrence Download

description: A dataset containing 611 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Saxifraga hostii Tausch"
 ]
}

 The dataset includes 611 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017316-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jh25ke
title: Occurrence Download

description: A dataset containing 2242 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is GalliForm: Galliformes occurrence records from the Indo-Malay and Palaearctic, 1800-2008",
 "Country is Belgium"
 ]
}

 The dataset includes 2242 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017318-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15582784
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250603i Initial

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250603i Initial. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.15582785
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250603i Initial

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250603i Initial. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.34740/kaggle/dsv/12044893
title: OBELiX
DOI: 10.5281/zenodo.15582683
title: Dataset for Energy dissipation on magic angle twisted bilayer graphene

description: Dataset for work: Ollier, A., Kisiel, M., Lu, X. et al. Energy dissipation on magic angle twisted bilayer graphene. Commun Phys 6, 344 (2023). https://doi.org/10.1038/s42005-023-01441-4
DOI: 10.5281/zenodo.15582684
title: Dataset for Energy dissipation on magic angle twisted bilayer graphene

description: Dataset for work: Ollier, A., Kisiel, M., Lu, X. et al. Energy dissipation on magic angle twisted bilayer graphene. Commun Phys 6, 344 (2023). https://doi.org/10.1038/s42005-023-01441-4
DOI: 10.15468/dl.6ffr8e
title: Occurrence Download

description: A dataset containing 60577 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Bacteria exposure experiment North Sea",
 "Country is Belgium"
 ]
}

 The dataset includes 60577 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017309-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17028/rd.lboro.29222198.v1
title: Supplementary information files for "The effect of cysteine oxidation on conformational changes of SARS-CoV-2 spike protein using atomistic simulations"

description: Supplementary information files for article "The effect of cysteine oxidation on conformational changes of SARS-CoV-2 spike protein using atomistic simulations"<br><br><br>The SARS-CoV-2 Spike (S) protein plays a central role in viral entry into host cells, making it a key target for therapeutic interventions. Oxidative stress, often triggered during viral infections, can cause oxidation of cysteine in this protein. Here we investigate the impact of cysteine oxidation, specifically the formation of cysteic acid, on the conformational dynamics of the SARS-CoV-2 S protein using atomistic simulations. In particular, we examine how cysteine oxidation influences the transitions of the S protein’s receptor-binding domain (RBD) between “down” (inaccessible) and “up” (accessible) states, which are critical for host cell receptor engagement. Using solvent-accessible surface area (SASA) analysis, we identify key cysteine residues susceptible to oxidation. The results of targeted molecular dynamics (TMD) and umbrella sampling (US) simulations reveal that oxidation reduces the energy barrier for RBD transitions by approximately 30 kJ mol<sup>−1</sup>, facilitating conformational changes and potentially enhancing viral infectivity. Furthermore, we analyze the interactions between oxidized cysteine residues and glycans, as well as alterations in hydrogen bonds and salt bridges. Our results show that oxidation disrupts normal RBD dynamics, influencing the energy landscape of conformational transitions. Our work provides novel insights into the role of cysteine oxidation in modulating the structural dynamics of the SARS-CoV-2 S protein, highlighting potential targets for antiviral strategies aimed at reducing oxidative stress or modifying post-translational changes. These findings contribute to a deeper understanding of viral infectivity and pathogenesis under oxidative conditions.<br><br>©The Author(s), CC BY-NC-ND 4.0
DOI: 10.17028/rd.lboro.29222198
title: Supplementary information files for "The effect of cysteine oxidation on conformational changes of SARS-CoV-2 spike protein using atomistic simulations"

description: Supplementary information files for article "The effect of cysteine oxidation on conformational changes of SARS-CoV-2 spike protein using atomistic simulations"<br><br><br>The SARS-CoV-2 Spike (S) protein plays a central role in viral entry into host cells, making it a key target for therapeutic interventions. Oxidative stress, often triggered during viral infections, can cause oxidation of cysteine in this protein. Here we investigate the impact of cysteine oxidation, specifically the formation of cysteic acid, on the conformational dynamics of the SARS-CoV-2 S protein using atomistic simulations. In particular, we examine how cysteine oxidation influences the transitions of the S protein’s receptor-binding domain (RBD) between “down” (inaccessible) and “up” (accessible) states, which are critical for host cell receptor engagement. Using solvent-accessible surface area (SASA) analysis, we identify key cysteine residues susceptible to oxidation. The results of targeted molecular dynamics (TMD) and umbrella sampling (US) simulations reveal that oxidation reduces the energy barrier for RBD transitions by approximately 30 kJ mol<sup>−1</sup>, facilitating conformational changes and potentially enhancing viral infectivity. Furthermore, we analyze the interactions between oxidized cysteine residues and glycans, as well as alterations in hydrogen bonds and salt bridges. Our results show that oxidation disrupts normal RBD dynamics, influencing the energy landscape of conformational transitions. Our work provides novel insights into the role of cysteine oxidation in modulating the structural dynamics of the SARS-CoV-2 S protein, highlighting potential targets for antiviral strategies aimed at reducing oxidative stress or modifying post-translational changes. These findings contribute to a deeper understanding of viral infectivity and pathogenesis under oxidative conditions.<br><br>©The Author(s), CC BY-NC-ND 4.0
DOI: 10.15468/dl.g2tqnp
title: Occurrence Download

description: A dataset containing 1054 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Global soil microbiomes: A new frontline of biome-ecology research",
 "Country is Belgium"
 ]
}

 The dataset includes 1054 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017320-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.udznak
title: Occurrence Download

description: A dataset containing 43622 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Nocardioides Prauser, 1976"
 ]
}

 The dataset includes 43622 records from 475 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017319-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mga72x
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 (Myrmotherula axillaris (Vieillot, 1817))",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016435-250525065834625/datasets/export for details.
DOI: 10.15468/dl.jspfey
title: Occurrence Download

description: A dataset containing 13661 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Dominican Republic",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 13661 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016436-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/yq8zxg
title: A08_17377.jpg

description: Link to OCHRE database: &lt;a href = 'http://pi.lib.uchicago.edu/1001/org/ochre/50aa685f-e73b-059a-5b73-0e7aececec32'&gt;http://pi.lib.uchicago.edu/1001/org/ochre/50aa685f-e73b-059a-5b73-0e7aececec32
DOI: 10.7910/dvn/g6n5w7
title: Replication Data for: The Realignment of Tolerance in the United States

description: 2 Stata do files
3 data sets (GSS and 2 CA studies)
DOI: 10.7910/dvn/gtsewp
title: Smart Subsidies for Catchment Conservation in Malawi

description: This dataset includes a baseline and endline survey from a cluster-randomized sample of households within villages covering the five uppermost Extension Planning Areas (EPAs) in the Shire River Basin in southern Malawi, spanning the districts of Balaka, Machinga, and Zomba. These EPAs were identified by the Malawian Department of Land Resources Conservation (DLRC) as the key riparian areas to the Shire River. Additionally, it includes registration and monitoring data from two years of the experimental intervention, with the intervention consisting of varying incentive structures and visual monitoring of land management practices. Finally, the data include an accounting of what, if anything, recipients purchased with the voucher they received. In sum, these data include detailed assessments of farm and household characteristics; detailed crop-level measurements of inputs and production for all plots (baseline and endline surveys) or the main plot (intervention registrations; summaries at plot-level for all other plots); assessments of access to services, coupons, and markets; an economic experiment designed to assess marginal willingness-to-accept a conservation agriculture (CA) incentive (baseline), and the perceived risks associated with CA (year 2 intervention and endline).
description: Household- and Community-level Surveys
description: STATA , 12
description: <b>Acknowledgements</b>
This work is part of the project entitled "Agglomeration Payments for Catchment Conservation in Malawi – NE/L001624/1," which was partly funded with support from the Ecosystem Services for Poverty Alleviation (ESPA) program. The ESPA program is funded by the Department for International Development (DFID), the Economic and Social Research Council (ESRC), and the Natural Environment Research Council (NERC). This work was further supported through a grant from the Feed the Future Innovation Lab for Collaborative Research on Assets and Market Access, funded by the United States Agency for International Development (USAID). Additional support was provided by the CGIAR Research Program on Policies, Institutions, and Markets (PIM).
DOI: 10.7910/dvn/gxmoxs
title: Replication Data for: A NOTE ON THE USE OF PARTIAL CORRELATION COEFFICIENTS IN META-ANALYSES

description: The files in this collection will allow one to reproduce the results in the paper, "A NOTE ON THE USE OF PARTIAL CORRELATION COEFFICIENTS IN META-ANALYSES." The README file provides more details.