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

description: A dataset containing 402 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Conringia austriaca (Jacq.) Sweet"
 ]
}

 The dataset includes 402 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012462-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aia0kl
title: Occurrence Download

description: A dataset containing 180 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Aetomylaeus nichofii (Bloch & Schneider, 1801)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 180 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000598-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ges7m2
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pareiorhaphis mutuca (Oliveira & Oyakawa, 1999)"
 ]
}

 The dataset includes 9 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0343154-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p7feyz
title: Occurrence Download

description: A dataset containing 292 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "TaxonKey is Sarcomphalus amole (Sessé & Moc.) Hauenschild"
 ]
}

 The dataset includes 292 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0233202-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vcny6z
title: Occurrence Download

description: A dataset containing 4875 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "CoordinateUncertaintyInMeters 0.0-10000.0",
 "TaxonKey is Osteopilus septentrionalis (Duméril & Bibron, 1841)",
 "Year 2010-2021"
 ]
}

 The dataset includes 4875 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004785-240130105604617/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.azi6cs
title: Occurrence Download

description: A dataset containing 66 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Ailia coila (Hamilton, 1822)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 66 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000599-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kjdyxr
title: Occurrence Download

description: A dataset containing 358 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Charissa mucidaria (Hübner)"
 ]
}

 The dataset includes 358 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0198842-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w5k5cy
title: Occurrence Download

description: A dataset containing 7759 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lactuca tatarica (L.) C.A.Mey.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7759 records from 182 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004786-240130105604617/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vedntz
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Tylomelania scalariopsis (P.Sarasin & F.Sarasin, 1897)"
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041296-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.58tvcz
title: Occurrence Download

description: A dataset containing 982173 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is RU-BIRDS.RU, Birds observations database from Russia and neighboring regions. Zoological Museum of M.V. Lomonosov Moscow State University."
 ]
}

 The dataset includes 982173 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041283-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x96t5r
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Euastacus dharawalus Morgan, 1997"
 ]
}

 The dataset includes 15 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041298-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qwwdpf
title: Occurrence Download

description: A dataset containing 17736 species occurrences available in GBIF matching the query:
{
 "SpeciesKey" : [
 "is one of (Solidago altissima L.)"
 ]
}

 The dataset includes 17736 records from 346 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041295-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fu5y9e
title: Occurrence Download

description: A dataset containing 70639 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Ireland, United Kingdom of Great Britain and Northern Ireland, Svalbard and Jan Mayen, Norway, Sweden, Finland, Estonia, Latvia, Lithuania, Portugal, Spain, France, Germany, Belgium, Netherlands, Switzerland, Austria, Italy, Greece, Cyprus, Türkiye, Russian Federation, Belarus, Ukraine, Poland, Czechia, Hungary, Slovakia, Romania, Bulgaria, North Macedonia, Albania, Montenegro, Serbia, Kosovo, Bosnia and Herzegovina, Slovenia, Croatia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Catapodium rigidum (L.) C.E.Hubb."
 ]
}

 The dataset includes 70639 records from 1070 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041280-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17250704
title: Extending digital biology: bacterial survival and morphological heterogeneity under antibiotic stress

description: The morphology of bacteria is intimately linked to their biological state: It is modified by antibiotic stress while also serving to survive the antibiotic. As such knowing which morphologies are selected by the surviving cells would help explain how individual cells are able to escape the antibiotic pressure. However associating morphological descriptors with quantitative measurements of cell survival remain elusive. Here we present a workflow to generate morphological signatures for the progeny of individual cells in the presence or absence of antibiotics. The workflow uses stationary microfluidic droplets, to encapsulate and grow bacteria, and confocal microscopy to image the contents of each droplet. Experiments are performed for 168 antibiotic conditions, corresponding to 82,000 droplet images. This massive data set is treated using a custom image analysis pipeline that enables rapid labeling of the morphologies within a subset of the images. The curated images are then used to train a neural network that assigns a positive or negative label, for each of these non-exclusive features, yielding a multidimensional signature of labels within each droplet. The results show the co-existence of different morphologies, even for the progeny of individual cells. The mix of morphologies changes as a function of antibiotic type and concentration, thus providing a way to distinguish antibiotics by their mode of action. By combining these morphological signatures with the digital detection of survival, this workflow can serve to understand the emergence of antibiotic resistance or to identify antimicrobial activity of unknown substances. This dataset contains the SQL database, network weights, and imaging data needed to recreate the interactive web viewer. More details are available at the associated GitHub repository.
DOI: 10.17632/457x9c7rp3.2
title: Fossil diatom microscopy image datasets and annotations for object detection

description: This dataset primarily consists of scanned images of permanent slides prepared from surface sediments collected across the Southern Ocean for fossil diatom observation. The sampling sites comprise eighteen locations and encompass a wide range of geomorphological settings and depositional systems, making this dataset well-suited for evaluating the performance of object detection models targeting fossil diatoms, as well as for investigating the biogeography of fossil diatoms in paleoenvironmental reconstruction. The dataset is divided into virtual slides, tile images, annotations, and trained models. The virtual slides are high-resolution images obtained by photographing the permanent slides and are provided in NDPI format (the original format of Hamamatsu Photonics K.K.). Each tile image is a JPEG format extracted from the virtual slides, covering a field of view of 552 × 552 μm. YOLO annotations are provided for each tile image and its corresponding folder. These tile images and annotations are specifically designed for detecting Eucampia antarctica (Castracane) Mangin, a diatom species endemic to the Southern Ocean, and are suitable for use as training and testing data in object detection models. The object detection models (YOLOv5x, Ultralytics) trained on a subset of these data are stored under “Trained models.” Note that this dataset includes only selected regions from the areas where tile images were originally captured, due to the storage limitations of the data repository.
DOI: 10.22000/1ffk7e31t4dfmd9y
title: Datasets for plots of "Real-time measurement error mitigation for one-way quantum computation"

description: This dataset accompanies the publication "Real-time measurement error mitigation for one-way quantum computation". It contains results obtained from numerical simulations of a OWQC with projection errors and from execution on IBM quantum hardware. For each dataset we provide a separate readme file explaining format and content.
DOI: 10.17632/y4w9c7c5ct
title: Terrain-Driven Path Tracking: Extraction of the vegetation line and in the Southwest China alpine–gorge region and attribution analysis of its spatial variability

description: data
DOI: 10.17632/y4w9c7c5ct.1
title: Terrain-Driven Path Tracking: Extraction of the vegetation line and in the Southwest China alpine–gorge region and attribution analysis of its spatial variability

description: data
DOI: 10.17632/n3gky25brh.1
title: Inter-eye Molecular Discrepancies in the Corneal Epithelium Point to TFRC in the Keratoconus Severity Signature and Mechanism of Cone Formation

description: This dataset accompanies the manuscript titled 'Inter-eye Molecular Discrepancies in the Corneal Epithelium Point to TFRC in the Keratoconus Severity Signature and Mechanism of Cone Formation’ by Jaskiewicz-Rajewicz et al., submitted to Investigative Ophthalmology & Visual Science (IOVS).

Mendeley Supplementary Table 1. This table presents the results of confocal fluorescence imaging of corneal epithelium (CE) samples, along with associated metadata. The quantitative data derived from these images are summarized in Supplementary Table S11 of the manuscript.
The analysis focused on the expression of the following proteins in CE samples from patients diagnosed with keratoconus (KTCN): TFRC (channel 00, blue), FTL (channel 03, green), FTH1 (channel 01, yellow). Nuclei were counterstained with propidium iodide (PI; channel 02, red). Fluorescence intensities were quantified using Fiji (ImageJ; Schindelin et al., 2012) in defined topographic regions of the CE. Median fluorescence intensities were normalized to the nuclear signal (PI) for accurate comparison.Data are provided for both the more and less affected eyes of seven KTCN patients. Negative controls were included and are available within the dataset. Detailed immunofluorescence staining protocols are described in the Supplementary Methods section of the manuscript.
DOI: 10.17632/wsb6z29vrn
title: Digital Health and Artificial Intelligence in Israel and the Philippines: A Systematic Review and Meta-Analysis of Adoption, Implementation, and Policy Implications

description: Title
Digital Health and Artificial Intelligence in Israel and the Philippines: A Systematic Review and Meta-Analysis of Adoption, Implementation, and Policy Implications

Dr. Fernan Torreno
Famiela Torreno (corresponding author)
torrenofamiela@gmail.com



Abstract 
Background:
Digital health and artificial intelligence (AI) are reshaping health systems worldwide. Israel has emerged as a global leader in digital health innovation, supported by robust infrastructure, national strategy, and AI integration in clinical practice^1,2. By contrast, the Philippines illustrates adoption in a resource-limited context, with advances in telemedicine and AI-supported tuberculosis (TB) screening catalyzed by COVID-19 and donor-supported programs^3,4. Despite distinct trajectories, synthesizing evidence from both nations offers insights into health system readiness, equity, and global policy transfer.
Methods:
We conducted a systematic review and meta-analysis (2000–2025) following PRISMA 2020 guidelines^5. Databases searched included PubMed, Scopus, Web of Science, and regional indices. Eligible studies evaluated digital health or AI interventions in Israel or the Philippines and reported outcomes related to clinical accuracy, access, satisfaction, or system performance. Effect sizes (Standardized Mean Differences [SMD] and Odds Ratios [OR]) were pooled using random-effects models, with subgroup analyses for Israel (high-resource) and the Philippines (LMIC).
Results:
Thirty-two studies met inclusion criteria, of which 12 provided extractable data. In Israel, AI tools demonstrated moderate improvements in diagnostic accuracy (SMD = 0.48, 95% CI: 0.32–0.64), particularly in radiology and oncology^6–8. In the Philippines, telemedicine increased access and satisfaction (OR = 1.55, 95% CI: 1.20–1.98)^9,10, while AI-CAD for TB screening improved case detection yield (OR = 1.62, 95% CI: 1.21–2.14)^11. Subgroup analysis showed comparable pooled benefits in both settings: Israel (SMD = 0.55, 95% CI: 0.38–0.72) vs. Philippines (SMD = 0.48, 95% CI: 0.30–0.66).
Conclusions:
This meta-analysis demonstrates that digital health and AI improve access, diagnostic accuracy, and satisfaction in both high-resource and LMIC settings. Israel illustrates system-level integration, while the Philippines highlights innovation under constraints. Together, they provide transferable lessons for advancing health system resilience and achieving global targets, notably SDG 3 (Good Health) and SDG 9 (Industry, Innovation, and Infrastructure)^12,13.
Keywords: Digital Health, Artificial Intelligence, Israel, Philippines, Systematic Review, Meta-Analysis, Health Policy, Sustainable Development Goals
DOI: 10.17632/wsb6z29vrn.1
title: Digital Health and Artificial Intelligence in Israel and the Philippines: A Systematic Review and Meta-Analysis of Adoption, Implementation, and Policy Implications

description: Title
Digital Health and Artificial Intelligence in Israel and the Philippines: A Systematic Review and Meta-Analysis of Adoption, Implementation, and Policy Implications

Dr. Fernan Torreno
Famiela Torreno (corresponding author)
torrenofamiela@gmail.com



Abstract 
Background:
Digital health and artificial intelligence (AI) are reshaping health systems worldwide. Israel has emerged as a global leader in digital health innovation, supported by robust infrastructure, national strategy, and AI integration in clinical practice^1,2. By contrast, the Philippines illustrates adoption in a resource-limited context, with advances in telemedicine and AI-supported tuberculosis (TB) screening catalyzed by COVID-19 and donor-supported programs^3,4. Despite distinct trajectories, synthesizing evidence from both nations offers insights into health system readiness, equity, and global policy transfer.
Methods:
We conducted a systematic review and meta-analysis (2000–2025) following PRISMA 2020 guidelines^5. Databases searched included PubMed, Scopus, Web of Science, and regional indices. Eligible studies evaluated digital health or AI interventions in Israel or the Philippines and reported outcomes related to clinical accuracy, access, satisfaction, or system performance. Effect sizes (Standardized Mean Differences [SMD] and Odds Ratios [OR]) were pooled using random-effects models, with subgroup analyses for Israel (high-resource) and the Philippines (LMIC).
Results:
Thirty-two studies met inclusion criteria, of which 12 provided extractable data. In Israel, AI tools demonstrated moderate improvements in diagnostic accuracy (SMD = 0.48, 95% CI: 0.32–0.64), particularly in radiology and oncology^6–8. In the Philippines, telemedicine increased access and satisfaction (OR = 1.55, 95% CI: 1.20–1.98)^9,10, while AI-CAD for TB screening improved case detection yield (OR = 1.62, 95% CI: 1.21–2.14)^11. Subgroup analysis showed comparable pooled benefits in both settings: Israel (SMD = 0.55, 95% CI: 0.38–0.72) vs. Philippines (SMD = 0.48, 95% CI: 0.30–0.66).
Conclusions:
This meta-analysis demonstrates that digital health and AI improve access, diagnostic accuracy, and satisfaction in both high-resource and LMIC settings. Israel illustrates system-level integration, while the Philippines highlights innovation under constraints. Together, they provide transferable lessons for advancing health system resilience and achieving global targets, notably SDG 3 (Good Health) and SDG 9 (Industry, Innovation, and Infrastructure)^12,13.
Keywords: Digital Health, Artificial Intelligence, Israel, Philippines, Systematic Review, Meta-Analysis, Health Policy, Sustainable Development Goals
DOI: 10.17632/vyy8vhcrgr
title: Disruptiveness and Resilience in a Global Timber Trade Network: Modeling Underload Cascading Failures and Structural Vulnerability Reserch Database

description: Disruptiveness and Resilience in a Global Timber Trade Network: Modeling Underload Cascading Failures and Structural Vulnerability
The data of this paper is derived from the United Nations database, covering the original global timber trade data from 2004 to 2023. After data preprocessing, it serves as the data foundation for the research.
The uploaded files are all the processed data files.
DOI: 10.17632/vyy8vhcrgr.1
title: Disruptiveness and Resilience in a Global Timber Trade Network: Modeling Underload Cascading Failures and Structural Vulnerability Reserch Database

description: Disruptiveness and Resilience in a Global Timber Trade Network: Modeling Underload Cascading Failures and Structural Vulnerability
The data of this paper is derived from the United Nations database, covering the original global timber trade data from 2004 to 2023. After data preprocessing, it serves as the data foundation for the research.
The uploaded files are all the processed data files.
DOI: 10.7929/issda/onerie
title: NCPP National Workplace Survey, 2009

description: NCPP (National Centre for Partnership and Performance), in collaboration with the ESRI and Amarach Research, conducted a large-scale survey of the perspectives and experiences of more than 5,000 employees in the private and public sectors. This is the second major national workplace survey to be conducted in Ireland, enabling researchers to track the changes in the attitudes and experieces of employees over a period of intense change in this country. In addition to the employee survey, a complementary report on employers' views was also undertaken.
DOI: 10.7929/issda/vcnsoz
title: NCPP National Workplace Survey, 2003

description: NCPP (National Centre for Partnership and Performance) commissioned the Economic and Social Research Institute to carry out this survey among over 5,000 employees. The employee survey provides the first, large, nationally representative study of Irish employees specifically devoted to exploring worker experiences and attitudes and fills a long-existing gap in our understanding of the Irish workplace, its management and of employees' approach to and experience of change.