cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/b2r7xw6wgm.1
title: AIR_QUALITY_HIGH_ALTITUDE_ROOMS

description: The shared dataset compiles measured air-changes-per-hour values in a high-altitude university in Quito, presented as an alternative mitigation strategy to maintaining 2 m of social distancing in classroom environments. These data enable meaningful comparison with findings from other regions, thereby supporting informed decision-making aimed at reducing infection risk.
DOI: 10.17632/k3f759fb3y
title: It’s a Global Issue: AI, Digital Transformation, and Governance - Mapping the Landscape for the Future of the Higher Education Communities

description: The development of AI, at an above-benchmark pace, has become a worldwide worrying
issue and a central narrative in the tertiary level learning institutions. Digital
transformation, on the other hand, is updating the educational systems, which necessitates
effective governance to steer these improvements. This paper provides an integrated
overview of these three pillars – AI, digital transformation, and governance – and
explores their interplay in reshaping the landscape of higher education. Drawing on key
insights from the EUNIS 2024 conference and recent global studies, the paper examines
AI’s transformative potential in optimizing learning and administration, the role of digital
transformation in enabling scalable and innovative educational services, and the urgent
need for governance frameworks to ensure ethical, equitable, and sustainable practices.
The analysis highlights current gaps, such as the lagging development of regulatory
frameworks amid rapid tech progress, and it sheds light on emerging needs, barriers, and
innovations (including the use of AI and XR in teaching and learning, strategies for digital
readiness, and models for ethical leadership). The argument provided by AI, digital
transformation, and governance is of particular interest, which justifies the need for a
Global Compact on AI in education that would foster international collaboration and
standards. This all-encompassing tracking and mapping of trends, challenges, and
opportunities provides higher education institutions a blueprint for strategic decisionmaking concerning technological integration and guides policymakers in reforming
higher learning education.
DOI: 10.17632/k3f759fb3y.1
title: It’s a Global Issue: AI, Digital Transformation, and Governance - Mapping the Landscape for the Future of the Higher Education Communities

description: The development of AI, at an above-benchmark pace, has become a worldwide worrying
issue and a central narrative in the tertiary level learning institutions. Digital
transformation, on the other hand, is updating the educational systems, which necessitates
effective governance to steer these improvements. This paper provides an integrated
overview of these three pillars – AI, digital transformation, and governance – and
explores their interplay in reshaping the landscape of higher education. Drawing on key
insights from the EUNIS 2024 conference and recent global studies, the paper examines
AI’s transformative potential in optimizing learning and administration, the role of digital
transformation in enabling scalable and innovative educational services, and the urgent
need for governance frameworks to ensure ethical, equitable, and sustainable practices.
The analysis highlights current gaps, such as the lagging development of regulatory
frameworks amid rapid tech progress, and it sheds light on emerging needs, barriers, and
innovations (including the use of AI and XR in teaching and learning, strategies for digital
readiness, and models for ethical leadership). The argument provided by AI, digital
transformation, and governance is of particular interest, which justifies the need for a
Global Compact on AI in education that would foster international collaboration and
standards. This all-encompassing tracking and mapping of trends, challenges, and
opportunities provides higher education institutions a blueprint for strategic decisionmaking concerning technological integration and guides policymakers in reforming
higher learning education.
DOI: 10.17632/fmwvksr66f.1
title: PRJNA1088471 Wastewater Sequences Processed

description: The data come from NCBI BioProject PRJNA1088471, as originally analyzed in Overton et. al (2024). These data are short read sequences from wastewater in Toronto, Ontario. See Overton et. al (2024) for a detailed description of the genomic sequencing process.

Data processing involved alignment of the short reads to the Wuhan-1 reference sequence (NC_045512) with `minimap2` v2.28, identifying the mutations relative to the reference, and recording the number of times a mutation was observed (counts) and the depth of coverage. The frequency is calculated as the counts divided by the coverage. The mutation pre-processing pipeline is available at \url{https://github.com/DASL-Lab/data-treatment-plant}, and heavily relies on the GromStole pipeline (\url{https://github.com/PoonLab/gromstole}).

After being processed into counts and coverage, the data were filtered to only include mutations that are relevant to analysis. There were many mutations with either consistently low counts (possibly due to sequencing errors) or low coverage. 

We found all mutations that had both a frequency of at least 0.1 and a frequency below 0.9 (with a coverage at least 40) at at least two time points during the study in any location. This ensures that we have all of the mutations that were potentially part of a circulating lineage without relying on lineage definitions.

Overton, Alyssa K., Jennifer J. Knapp, Opeyemi U. Lawal, et al. “Genomic Surveillance of a Canadian Airport Wastewater Samples Allows Early Detection of Emerging SARS-CoV-2 Lineages.” Preprint, April 9, 2024. https://doi.org/10.21203/rs.3.rs-4183960/v1.
DOI: 10.17632/d6hmm7bjnt
title: Repurposing of a DNA segregation machinery into a cytoskeletal system controlling cell shape

description: SOURCE DATA:
 
Data from the manuscript of Springstein et al., "Repurposing of a DNA segregation machinery into a cytoskeletal system controlling cell shape”.

- Alignments/
 - Cyanobacteria_species.aln
 Concatenation of the multiple sequence alignments of the RNA polymerase β and β′ subunit protein sequences from all Cyanobacteria species in the dataset, used to reconstruct a species phylogeny of the Cyanobacteria phylum.

 - ParM_Bacteria.aln
 Multiple sequence alignment of representative ParM proteins identified across all bacterial phyla.

 - ParM_ParR_Cyanobacteria.aln
 Concatenation of the multiple sequence alignments of ParM and ParR protein sequences identified in Cyanobacteria.


- Phylogenies/
 - Cyanobacteria_species.treefile
 Species phylogeny of Cyanobacteria (in Newick format).

 - Cyanobacteria_species.pdf
 Species phylogeny of Cyanobacteria (in pdf format with annotations).

 - ParM_Bacteria.treefile
 Phylogeny of ParM proteins identified across all bacterial phyla (in Newick format).

 - ParM_Bacteria.pdf
 Phylogeny of ParM proteins identified across all bacterial phyla (in pdf format with annotations).

 - ParM_ParR_Cyanobacteria.treefiles
 Phylogeny of the concatenation of ParM and ParR proteins identified in Cyanobacteria (in Newick format).

 - ParM_ParR_Cyanobacteria.pdf
 Phylogeny of the concatenation of ParM and ParR proteins identified in Cyanobacteria (in pdf format with annotations).

- Profiles/
 - RNApolB.hmm
 HMM profile used for the identification of RNA polymerase β proteins in the Cyanobacteria genomes.

 - RNApolBp.hmm
 HMM profile used for the identification of RNA polymerase β′ proteins in the Cyanobacteria genomes.

 - ParM.hmm
 HMM profile used for the identification of ParM proteins in bacterial genomes.

 - ParR.hmm
 HMM profile used for the identification of ParR proteins in bacterial genomes.
DOI: 10.17632/d6hmm7bjnt.1
title: Repurposing of a DNA segregation machinery into a cytoskeletal system controlling cell shape

description: SOURCE DATA:
 
Data from the manuscript of Springstein et al., "Repurposing of a DNA segregation machinery into a cytoskeletal system controlling cell shape”.

- Alignments/
 - Cyanobacteria_species.aln
 Concatenation of the multiple sequence alignments of the RNA polymerase β and β′ subunit protein sequences from all Cyanobacteria species in the dataset, used to reconstruct a species phylogeny of the Cyanobacteria phylum.

 - ParM_Bacteria.aln
 Multiple sequence alignment of representative ParM proteins identified across all bacterial phyla.

 - ParM_ParR_Cyanobacteria.aln
 Concatenation of the multiple sequence alignments of ParM and ParR protein sequences identified in Cyanobacteria.


- Phylogenies/
 - Cyanobacteria_species.treefile
 Species phylogeny of Cyanobacteria (in Newick format).

 - Cyanobacteria_species.pdf
 Species phylogeny of Cyanobacteria (in pdf format with annotations).

 - ParM_Bacteria.treefile
 Phylogeny of ParM proteins identified across all bacterial phyla (in Newick format).

 - ParM_Bacteria.pdf
 Phylogeny of ParM proteins identified across all bacterial phyla (in pdf format with annotations).

 - ParM_ParR_Cyanobacteria.treefiles
 Phylogeny of the concatenation of ParM and ParR proteins identified in Cyanobacteria (in Newick format).

 - ParM_ParR_Cyanobacteria.pdf
 Phylogeny of the concatenation of ParM and ParR proteins identified in Cyanobacteria (in pdf format with annotations).

- Profiles/
 - RNApolB.hmm
 HMM profile used for the identification of RNA polymerase β proteins in the Cyanobacteria genomes.

 - RNApolBp.hmm
 HMM profile used for the identification of RNA polymerase β′ proteins in the Cyanobacteria genomes.

 - ParM.hmm
 HMM profile used for the identification of ParM proteins in bacterial genomes.

 - ParR.hmm
 HMM profile used for the identification of ParR proteins in bacterial genomes.
DOI: 10.17632/x3gyskppmp
title: Shape-Dependent Interactions of Gold Nanoparticles with Microalgae: Distinct Cellular and Molecular Responses

description: mRNA-sequencing raw data. 
Method: We collected algae after 72 h exposure to 10 mg/L AuNP and AuNS for RNA-seq to analyze mRNA expression. Chlamydomonas_reinhardtii (Version: CC-503 cw92 mt+). The differentially expressed transcripts and genes were selected with log2 (fold change) ≥ 1 or log2 (fold change) ≤ -1 and p value &lt; 0.05 criteria with the R package edgeR(https://bioconductor.org/packages/edgeR). 
Results: RNA sequencing identified 9 upregulated and 38 downregulated differentially expressed genes (DEGs) in the 10 mg/L AuNP treated cells, impairing photosynthesis and energy storage via the photosystem II subunit S1 (PSBS1)/ early light-inducible protein (ELI3) pathway. In contrast, the AuNS group exhibits 246 upregulated and 145 downregulated DEGs, affecting membrane integrity and nitrogen metabolism through the nitrate reductase (NIT1)/ aminomethyl transferase (AMT1)/ protein kinase domain-containing protein (A0A2K3CRU5) pathway.
DOI: 10.17632/x3gyskppmp.1
title: Shape-Dependent Interactions of Gold Nanoparticles with Microalgae: Distinct Cellular and Molecular Responses

description: mRNA-sequencing raw data. 
Method: We collected algae after 72 h exposure to 10 mg/L AuNP and AuNS for RNA-seq to analyze mRNA expression. Chlamydomonas_reinhardtii (Version: CC-503 cw92 mt+). The differentially expressed transcripts and genes were selected with log2 (fold change) ≥ 1 or log2 (fold change) ≤ -1 and p value &lt; 0.05 criteria with the R package edgeR(https://bioconductor.org/packages/edgeR). 
Results: RNA sequencing identified 9 upregulated and 38 downregulated differentially expressed genes (DEGs) in the 10 mg/L AuNP treated cells, impairing photosynthesis and energy storage via the photosystem II subunit S1 (PSBS1)/ early light-inducible protein (ELI3) pathway. In contrast, the AuNS group exhibits 246 upregulated and 145 downregulated DEGs, affecting membrane integrity and nitrogen metabolism through the nitrate reductase (NIT1)/ aminomethyl transferase (AMT1)/ protein kinase domain-containing protein (A0A2K3CRU5) pathway.
DOI: 10.15468/dl.s3rnzn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyprinion acinaces",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033938-251025141854904/datasets/export for details.
DOI: 10.5281/zenodo.17610032
title: Bridging the Privacy Gap: Developers' Practices and the Missing Role of Privacy Engineers

description: Context: Privacy has become a first order concern in software engineering, yet organizations still struggle to translate legal mandates into actionable engineering practices and governance routines. Goal: This study investigates how Brazilian software practitioners perceive, adopt, and operationalize privacy standards and practices, identifying challenges and actionable opportunities to strengthen privacy by design in real projects. Method: We conduct a conceptual replication of prior work on privacy engineering, adapting it to the Brazilian context via a survey (31 practitioners). The instrument maps roles and privacy perceptions and practices (RQ1), the use of standards, frameworks, and techniques (RQ2), and challenges and improvement opportunities (RQ3). Results: Practitioners consistently distinguish privacy from security, but formalization is limited. Although 60.7% report considering privacy across the Software Development Life Cycle (SDLC), half do not use privacy-focused methods and 46.4% are unaware of them. Practices skew toward classic security controls (e.g., access control, 85.7%) rather than dedicated privacy engineering artifacts. The Brazilian General Data Protection Law (LGPD) is the dominant compliance driver (82.1%), with low uptake of ISO 27701/NIST PF. Key barriers include unclear legal guidance (53.6%), insufficient training (42.9%), and late integration of privacy (39.3%). Automation remains incipient (14.3% fully automated Data Subject Rights (DSAR) workflows; 42.9% manual). Organizational support is uneven (39.3% sufficient; 39.3% partial; 21.4% insufficient). Spearman correlations revealed strong relationships (ρ up to 0.63) between experience, training, and integration practices, indicating that professional maturity and capacity building are key enablers of privacy-by-design adoption. Conclusion: Results indicate a persistent gap between awareness and effective governance. We recommend (i) targeted training and curricular inclusion, (ii) clearer role/accountability assignments, and (iii) investment in tooling/automation to operationalize privacy-by-design. These actions can help shift privacy from reactive compliance to a sustained dimension of software quality in Brazilian
DOI: 10.5281/zenodo.17610033
title: Bridging the Privacy Gap: Developers' Practices and the Missing Role of Privacy Engineers

description: Context: Privacy has become a first order concern in software engineering, yet organizations still struggle to translate legal mandates into actionable engineering practices and governance routines. Goal: This study investigates how Brazilian software practitioners perceive, adopt, and operationalize privacy standards and practices, identifying challenges and actionable opportunities to strengthen privacy by design in real projects. Method: We conduct a conceptual replication of prior work on privacy engineering, adapting it to the Brazilian context via a survey (31 practitioners). The instrument maps roles and privacy perceptions and practices (RQ1), the use of standards, frameworks, and techniques (RQ2), and challenges and improvement opportunities (RQ3). Results: Practitioners consistently distinguish privacy from security, but formalization is limited. Although 60.7% report considering privacy across the Software Development Life Cycle (SDLC), half do not use privacy-focused methods and 46.4% are unaware of them. Practices skew toward classic security controls (e.g., access control, 85.7%) rather than dedicated privacy engineering artifacts. The Brazilian General Data Protection Law (LGPD) is the dominant compliance driver (82.1%), with low uptake of ISO 27701/NIST PF. Key barriers include unclear legal guidance (53.6%), insufficient training (42.9%), and late integration of privacy (39.3%). Automation remains incipient (14.3% fully automated Data Subject Rights (DSAR) workflows; 42.9% manual). Organizational support is uneven (39.3% sufficient; 39.3% partial; 21.4% insufficient). Spearman correlations revealed strong relationships (ρ up to 0.63) between experience, training, and integration practices, indicating that professional maturity and capacity building are key enablers of privacy-by-design adoption. Conclusion: Results indicate a persistent gap between awareness and effective governance. We recommend (i) targeted training and curricular inclusion, (ii) clearer role/accountability assignments, and (iii) investment in tooling/automation to operationalize privacy-by-design. These actions can help shift privacy from reactive compliance to a sustained dimension of software quality in Brazilian
DOI: 10.15468/dl.27jn69
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyprinodon diabolis",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033940-251025141854904/datasets/export for details.
DOI: 10.15468/dl.82uwhb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyprinodon eremus",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033941-251025141854904/datasets/export for details.
DOI: 10.15468/dl.nj4kgc
title: Occurrence Download

description: A dataset containing 393 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "DatasetKey is EOD – eBird Observation Dataset",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Hypocnemis subflava, Hypocnemis subflava subflava, Hypocnemis subflava collinsi)"
 ]
}

 The dataset includes 393 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033943-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e155161v91
title: Advance Layoff Notice Data from the WARN Act

description: We collect novel and timely data from advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act. The act requires larger employers to notify affected workers at least 60 days before a potential mass layoff. We assemble WARN data from across the United States, and for many large states our data begin in the 1990s. We aggregate these data into an unbalanced, monthly panel of the state-level number of workers affected by WARN notices, and we update this panel twice a month. We also aggregate this panel to a national-level indicator of job loss (the "WARN factor") using a dynamic factor model.<br>

<b><br>Data Collection</b><br>We update the data twice a month by collecting WARN
notices from state websites. For many states, we have extended our historical
data by using digital archives of the internet and contacting state
officials.<br> <br><b>Citation</b><br>To learn more about
the data and the dynamic factor model, see:<br>Krolikowski, Pawel M. and Kurt G. Lunsford. 2022. “Advance Layoff Notices and Aggregate Job Loss.” Federal Reserve Bank of Cleveland, Working Paper no. 20-03R. https://doi.org/10.26509/frbc-wp-202003R.<br>Krolikowski, Pawel M., and Kurt G. Lunsford. 2024 “Advance Layoff Notices and Aggregate Job Loss.” Journal of Applied Econometrics. https://doi.org/10.1002/jae.3032.<b><br><br></b><b>File Description</b><br>The file labelled WARNFiles_YYYYMMDD.zip in the
main directory contains our most recent data. All data included in this zip
file were collected as of the date listed in the file name. Previous
vintages of our data appear in the `Archived_Vintages’ folder, with the same
naming convention.<br>
<br>The zip files contain three files:<br>
<br>


1. 
README.txt

<br>2. 
WARNData_NSA_YYYYMMDD.csv


 
 This .csv contains the number of workers affected by
 WARN notices by state and month. These data are not seasonally adjusted.
 These data are the input into the dynamic factor model.
 


3. 
WARNFactors_YYYYMMDD.csv


 
 This .csv contains the output of the dynamic factor
 model. The output is labeled as follows:
 
 WARN Factor: the estimates of the factor from the
 dynamic factor model.
 MSE: the estimated mean squared errors
 of the WARN factor.
 WARN_hat: the number of workers affected by
 WARN notices as implied by the WARN factor.
 WARN_sum: the sum of the number of
 workers affected by WARN notices from several states that form a
 balanced panel beginning in January 2006. These states can change every
 update.<b>Disclaimer</b><br>These data are
updated by the authors and are not an official product of the Federal Reserve Bank of Cleveland.<br>
description: Smallest Geographic Unit: State
DOI: 10.6084/m9.figshare.30625085
title: <b>Validación de contenido de un cuestionario sobre herramientas de LM para análisis y diagnóstico en la industria</b>

description: En este repositorio se presentan dos archivos:El formato de evaluación para cada uno de los expertos y debe usarse word para abrirlo.Un archivo de Excel con los cálculos realizados.
DOI: 10.6084/m9.figshare.30625085.v1
title: <b>Validación de contenido de un cuestionario sobre herramientas de LM para análisis y diagnóstico en la industria</b>

description: En este repositorio se presentan dos archivos:El formato de evaluación para cada uno de los expertos y debe usarse word para abrirlo.Un archivo de Excel con los cálculos realizados.
DOI: 10.15468/dl.vey35m
title: Occurrence Download

description: A dataset containing 10437 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Material citation, Specimen, Occurrence evidence)",
 "Geometry POLYGON((-88.071 41.05,-86.236 41.05,-86.236 42.176,-88.071 42.176,-88.071 41.05))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mollusca"
 ]
}

 The dataset includes 10437 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033945-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e8vu9t
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is New Zealand",
 "TaxonKey is Crassula multicava multicava"
 ]
}

 The dataset includes 8 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033946-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.25umbz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyprinodon macularius",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033947-251025141854904/datasets/export for details.