cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13140/rg.2.2.10963.64809
title: Rolling-Imax-Processor 0.1.0 https://pypi.org/project/Rolling-Imax-Processor/0.1.0/#description
DOI: 10.15468/dl.aspwc7
title: Occurrence Download

description: A dataset containing 435 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "TaxonKey is Dioscorea grisebachii"
 ]
}

 The dataset includes 435 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002039-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fw547k
title: Occurrence Download

description: A dataset containing 3085 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "TaxonKey is Phylloscopus poliogenys",
 "Year 2024-2025"
 ]
}

 The dataset includes 3085 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002041-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/cwcrcv3jnh.1
title: Quality of Nursing Education in the Philippines: A Meta Analysis of State Universities and Private Colleges, 2021–2025

description: meta analysis paper
DOI: 10.17632/b6t76ccvb5
title: Mass Cytometry Dataset for "Mass cytometry discloses heterogeneity of immune cell proteases"

description: This dataset supports the manuscript “Mass cytometry discloses heterogeneity of immune cell proteases,” accepted in Cell Reports. The research hypothesis driving the study was that innate immune cells, particularly neutrophils and macrophages, exhibit previously unrecognized heterogeneity in their protease activity profiles, and that this heterogeneity can be detected using activity-based TOF probes and mass cytometry.
The dataset consists of raw CyTOF FCS files generated from primary human neutrophils and THP-1 monocytes differentiated into M0, M1, and M2 macrophages. Cells were labeled with either cysteine-reactive or serine-reactive TOF probes designed to detect active proteases within each cell population. Control probe samples lacking the reactive warhead are also included (denoted with “C” in the filenames). Following probe labeling, cells were fixed and stained with a panel of metal-tagged antibodies specific for immune cell proteases to enable simultaneous detection of active enzymes and total protease abundance.
This dataset allows users to examine raw single-cell protease activity signatures across different innate immune cell states. Although gating, normalization, and downstream analyses were performed in Cytobank for the published manuscript, the raw FCS files provided here can be re-gated or re-analyzed using any CyTOF-compatible software. A metal tag map is included to clarify which antibodies and probes correspond to each metal isotope.
All experimental procedures including cell preparation, probe labeling, fixation, metal-antibody staining, and CyTOF acquisition, are described in the STAR Methods of the associated manuscript, enabling full reproducibility. This dataset provides a resource for researchers interested in protease biology, innate immune heterogeneity, activity-based probes, and single-cell mass cytometry.
DOI: 10.17632/b6t76ccvb5.2
title: Mass Cytometry Dataset for "Mass cytometry discloses heterogeneity of immune cell proteases"

description: This dataset supports the manuscript “Mass cytometry discloses heterogeneity of immune cell proteases,” accepted in Cell Reports. The research hypothesis driving the study was that innate immune cells, particularly neutrophils and macrophages, exhibit previously unrecognized heterogeneity in their protease activity profiles, and that this heterogeneity can be detected using activity-based TOF probes and mass cytometry.
The dataset consists of raw CyTOF FCS files generated from primary human neutrophils and THP-1 monocytes differentiated into M0, M1, and M2 macrophages. Cells were labeled with either cysteine-reactive or serine-reactive TOF probes designed to detect active proteases within each cell population. Control probe samples lacking the reactive warhead are also included (denoted with “C” in the filenames). Following probe labeling, cells were fixed and stained with a panel of metal-tagged antibodies specific for immune cell proteases to enable simultaneous detection of active enzymes and total protease abundance.
This dataset allows users to examine raw single-cell protease activity signatures across different innate immune cell states. Although gating, normalization, and downstream analyses were performed in Cytobank for the published manuscript, the raw FCS files provided here can be re-gated or re-analyzed using any CyTOF-compatible software. A metal tag map is included to clarify which antibodies and probes correspond to each metal isotope.
All experimental procedures including cell preparation, probe labeling, fixation, metal-antibody staining, and CyTOF acquisition, are described in the STAR Methods of the associated manuscript, enabling full reproducibility. This dataset provides a resource for researchers interested in protease biology, innate immune heterogeneity, activity-based probes, and single-cell mass cytometry.
DOI: 10.17632/2xgt76z3xk
title: Melanopsin in ocular tissue after corneal abrasion

description: Melanopsin is a non-image forming photoreactive protein that has diverse roles in multiple tissues. This study examines how melanopsin expression changes after corneal abrasion. Corneal abrasion is the most common form of eye injury and can cause severe pain and photoallodynia. Behavior of rats was measured using orbital tightening, a part of the grimace scale. Then melanopsin positive cells in the retina were counted and volume of melanopsin in the iris was calculated at baseline, 24h and 1wk. Finaly the prominence of the pupillary ruff into the pupil was measured. These data indicate that pain behaviors, melanopsin in the iris and prominence of the pupillary ruff all peak at 24h after corneal abrasion.
DOI: 10.17632/2xgt76z3xk.1
title: Melanopsin in ocular tissue after corneal abrasion

description: Melanopsin is a non-image forming photoreactive protein that has diverse roles in multiple tissues. This study examines how melanopsin expression changes after corneal abrasion. Corneal abrasion is the most common form of eye injury and can cause severe pain and photoallodynia. Behavior of rats was measured using orbital tightening, a part of the grimace scale. Then melanopsin positive cells in the retina were counted and volume of melanopsin in the iris was calculated at baseline, 24h and 1wk. Finaly the prominence of the pupillary ruff into the pupil was measured. These data indicate that pain behaviors, melanopsin in the iris and prominence of the pupillary ruff all peak at 24h after corneal abrasion.
DOI: 10.17632/x9v75twt2t
title: Calibrated Simulation of Individual Level Data for the Basic National Pension Scheme (Tier 1) in Ghana for the Periods 2015 to 2024

description: This depository is the result of a calibrated microsimulation that generated the first individual-level dataset for Ghana’s Basic National Pension Scheme (Tier 1) for the period 2015 to 2024. The dataset combines publicly available annual aggregates from the Social Security and National Insurance Trust (SSNIT), National Pensions Regulatory Authority (NPRA) and the Ministry of Labour, Jobs and Employment (MLJE) with demographic, labour and mortality inputs from the Ghana Statistical Service (GSS) and the United Nations World Population Prospects.
Using stratified sampling, membership transition modeling and poststratification calibration, the dataset recreates contributors, retirees and non-members at fine age-sex resolution while exactly reproducing official totals on contributions and benefits/pensions. The resulting microdata support distributional analysis of earnings, contributions, pensions and replacement rates, as well as actuarial projections, policy simulations and research on pension adequacy, coverage expansion and long-term social protection financing in Ghana.
DOI: 10.17632/x9v75twt2t.1
title: Calibrated Simulation of Individual Level Data for the Basic National Pension Scheme (Tier 1) in Ghana for the Periods 2015 to 2024

description: This depository is the result of a calibrated microsimulation that generated the first individual-level dataset for Ghana’s Basic National Pension Scheme (Tier 1) for the period 2015 to 2024. The dataset combines publicly available annual aggregates from the Social Security and National Insurance Trust (SSNIT), National Pensions Regulatory Authority (NPRA) and the Ministry of Labour, Jobs and Employment (MLJE) with demographic, labour and mortality inputs from the Ghana Statistical Service (GSS) and the United Nations World Population Prospects.
Using stratified sampling, membership transition modeling and poststratification calibration, the dataset recreates contributors, retirees and non-members at fine age-sex resolution while exactly reproducing official totals on contributions and benefits/pensions. The resulting microdata support distributional analysis of earnings, contributions, pensions and replacement rates, as well as actuarial projections, policy simulations and research on pension adequacy, coverage expansion and long-term social protection financing in Ghana.
DOI: 10.17632/8btychyrtp
title: Encapsulated Muscle Stem Cell Spheroids Improve Regeneration in VML Mice

description: Raw data from a manuscript currently under review in Frontiers in Pharmacology.
DOI: 10.17632/8btychyrtp.1
title: Encapsulated Muscle Stem Cell Spheroids Improve Regeneration in VML Mice

description: Raw data from a manuscript currently under review in Frontiers in Pharmacology.
DOI: 10.17632/38z4hmj488
title: Autism_Awareness_PSA_Reception_Data_2025
DOI: 10.17632/38z4hmj488.1
title: Autism_Awareness_PSA_Reception_Data_2025
DOI: 10.17632/8w59jvtjfm
title: Coastal shelterbelt forests SOC stability

description: The indicators of organic carbon stability for different types of coastal shelterbelt forests, including carbon dioxide release rate, molecular stability (r1620/(2850 + 2920)), and thermal stability (TG-T50 and DSC-T50)
DOI: 10.17632/8w59jvtjfm.1
title: Coastal shelterbelt forests SOC stability

description: The indicators of organic carbon stability for different types of coastal shelterbelt forests, including carbon dioxide release rate, molecular stability (r1620/(2850 + 2920)), and thermal stability (TG-T50 and DSC-T50)
DOI: 10.17632/s88zf59nm9
title: ESOGU-EVRP-PD-TW DATASET

description: ESOGU-CEVRPTW is generated for Eskisehir Osmangazi University (ESOGU) Meselik Campus. The ESOGU-CEVRPTW comprises 118 customers, ten charging stations, and a single depot. The dataset contains 21 different instances for the Capacitated Electric Vehicle Routing Problem with Time Windows. The proposed dataset also includes information about EVs and charging stations. The dataset consists of test problem groups of 7 different sizes with 5, 10, 20, 40, 60, 80, 100 customers. Each test problem group contains instances from the random (R), clustered (C), and random-clustered (RC) customer distribution. Each group includes three different types of time windows: wide, medium, and narrow. All instances in the dataset are txt files.
DOI: 10.17632/s88zf59nm9.1
title: ESOGU-EVRP-PD-TW DATASET

description: ESOGU-CEVRPTW is generated for Eskisehir Osmangazi University (ESOGU) Meselik Campus. The ESOGU-CEVRPTW comprises 118 customers, ten charging stations, and a single depot. The dataset contains 21 different instances for the Capacitated Electric Vehicle Routing Problem with Time Windows. The proposed dataset also includes information about EVs and charging stations. The dataset consists of test problem groups of 7 different sizes with 5, 10, 20, 40, 60, 80, 100 customers. Each test problem group contains instances from the random (R), clustered (C), and random-clustered (RC) customer distribution. Each group includes three different types of time windows: wide, medium, and narrow. All instances in the dataset are txt files.
DOI: 10.17632/csz5dzp7nx
title: ASQ-PHI: An Adversarial Synthetic Benchmark for Clinical De-Identification and Search Utility

description: Hospitals are beginning to deploy HIPAA-compliant Business Associate Agreement (BAA) large language models (LLMs). In the public setting, LLMs with fixed training cutoffs are routinely augmented with tools such as web search, deep research, and Model Context Protocol (MCP) servers so they can reach up-to-date knowledge. BAA LLMs, by contrast, almost never expose live web search or external tools, even though clinicians expect LLMs to surface current guidelines, drug safety updates, and literature. The constraint is that any query leaving a BAA-protected LLM for an external service must be free of Protected Health Information (PHI). We refer to this boundary as the safe handoff: the moment when a clinician’s PHI-containing query, generated inside a HIPAA-compliant BAA LLM, must be transformed into a HIPAA Safe Harbor–compliant version before being sent to non-BAA tools such as web search APIs, external evidence services, or MCP servers. Existing de-identification datasets are built from long electronic health record narratives rather than the short, compressed search queries clinicians type into LLM chat interfaces, so they do not allow de-identification performance to be tested at this safe handoff. ASQ-PHI (Adversarial Synthetic Queries for Protected Health Information de-identification) is constructed to supply this missing data: a benchmark of 1,051 fully synthetic clinical search queries with ground-truth PHI annotations for stress-testing HIPAA-compliant de-identification software. All queries were generated using Azure OpenAI GPT-4o. No real patient data were used.

Research hypothesis:
Current de-identification systems fail at the safe handoff from LLMs running inside HIPAA BAAs to external tools in two ways:

1) Leaking PHI

2) Over-redacting non-identifying clinical information reducing query utility.

What the data shows:
The dataset contains 832 PHI-positive queries (79.2 percent) and 219 hard negatives (20.8 percent), totaling 2,973 tagged PHI elements across 13 HIPAA Safe Harbor types. Most common: GEOGRAPHIC_LOCATION (27.8 percent), NAME (27.4 percent), DATE (27.1 percent). Hard negatives mimic PHI-containing text but contain no identifiers, enabling over-redaction measurement.

Notable findings:
Baseline validation using Amazon Comprehend Medical (DetectPHI) revealed severe recall-utility tradeoffs, as shown in validation_results.

How the data was generated:
Queries were generated using GPT-4o. A system prompt specified natural clinical questions containing 0 to 5 HIPAA identifiers. Output format: "===QUERY===" followed by "===PHI_TAGS===" with JSON {"identifier_type": "TYPE", "value": "..."}. Complete code in code/data_generation_pipeline.ipynb.

The dataset serves developers building HIPAA-compliant LLM infrastructure, privacy researchers benchmarking algorithms, and compliance teams evaluating vendor claims.
DOI: 10.17632/csz5dzp7nx.1
title: ASQ-PHI: An Adversarial Synthetic Benchmark for Clinical De-Identification and Search Utility

description: Hospitals are beginning to deploy HIPAA-compliant Business Associate Agreement (BAA) large language models (LLMs). In the public setting, LLMs with fixed training cutoffs are routinely augmented with tools such as web search, deep research, and Model Context Protocol (MCP) servers so they can reach up-to-date knowledge. BAA LLMs, by contrast, almost never expose live web search or external tools, even though clinicians expect LLMs to surface current guidelines, drug safety updates, and literature. The constraint is that any query leaving a BAA-protected LLM for an external service must be free of Protected Health Information (PHI). We refer to this boundary as the safe handoff: the moment when a clinician’s PHI-containing query, generated inside a HIPAA-compliant BAA LLM, must be transformed into a HIPAA Safe Harbor–compliant version before being sent to non-BAA tools such as web search APIs, external evidence services, or MCP servers. Existing de-identification datasets are built from long electronic health record narratives rather than the short, compressed search queries clinicians type into LLM chat interfaces, so they do not allow de-identification performance to be tested at this safe handoff. ASQ-PHI (Adversarial Synthetic Queries for Protected Health Information de-identification) is constructed to supply this missing data: a benchmark of 1,051 fully synthetic clinical search queries with ground-truth PHI annotations for stress-testing HIPAA-compliant de-identification software. All queries were generated using Azure OpenAI GPT-4o. No real patient data were used.

Research hypothesis:
Current de-identification systems fail at the safe handoff from LLMs running inside HIPAA BAAs to external tools in two ways:

1) Leaking PHI

2) Over-redacting non-identifying clinical information reducing query utility.

What the data shows:
The dataset contains 832 PHI-positive queries (79.2 percent) and 219 hard negatives (20.8 percent), totaling 2,973 tagged PHI elements across 13 HIPAA Safe Harbor types. Most common: GEOGRAPHIC_LOCATION (27.8 percent), NAME (27.4 percent), DATE (27.1 percent). Hard negatives mimic PHI-containing text but contain no identifiers, enabling over-redaction measurement.

Notable findings:
Baseline validation using Amazon Comprehend Medical (DetectPHI) revealed severe recall-utility tradeoffs, as shown in validation_results.

How the data was generated:
Queries were generated using GPT-4o. A system prompt specified natural clinical questions containing 0 to 5 HIPAA identifiers. Output format: "===QUERY===" followed by "===PHI_TAGS===" with JSON {"identifier_type": "TYPE", "value": "..."}. Complete code in code/data_generation_pipeline.ipynb.

The dataset serves developers building HIPAA-compliant LLM infrastructure, privacy researchers benchmarking algorithms, and compliance teams evaluating vendor claims.
DOI: 10.6084/m9.figshare.30674894
title: Evolution of the retrograde response to mitochondrial dysfunction in budding yeasts

description: We investigated the function and evolution of the retrograde (Rtg) mitonuclear signalling pathway by searching for the orthologs of relevant proteins encoded in the genomes of supphylum Saccharomycotina within the phylum Ascomycota. We also identified targets of the retrograde regulation in Candida albicans using EMSA. This dataset contains code and results of the evolutionary analyses as well as the supplementary figures.
DOI: 10.6084/m9.figshare.30674894.v2
title: Evolution of the retrograde response to mitochondrial dysfunction in budding yeasts

description: We investigated the function and evolution of the retrograde (Rtg) mitonuclear signalling pathway by searching for the orthologs of relevant proteins encoded in the genomes of supphylum Saccharomycotina within the phylum Ascomycota. We also identified targets of the retrograde regulation in Candida albicans using EMSA. This dataset contains code and results of the evolutionary analyses as well as the supplementary figures.
DOI: 10.6084/m9.figshare.30674894.v1
title: Evolution of the retrograde response to mitochondrial dysfunction in budding yeasts

description: We investigated the function and evolution of the retrograde (Rtg) mitonuclear signalling pathway by searching for the orthologs of relevant proteins encoded in the genomes of supphylum Saccharomycotina within the phylum Ascomycota. We also identified targets of the retrograde regulation in Candida albicans using EMSA. This dataset contains code and results of the evolutionary analyses as well as the supplementary figures.
DOI: 10.17632/xv8j4sbfwt
title: Valuing and enhancing the visibility of research by teacher educators in Uruguay

description: This dataset compiles official documents, institutional reports, academic analyses, policy proposals, and resolutions pertaining to the research function within the Council of Teacher Education (Consejo de Formación en Educación - CFE) in Uruguay. The documents span from 2008 to 2024, a period characterized by significant transformations and debates regarding the role and status of research in teacher education.
The collection provides insights into the institutional efforts, challenges, and diverse perspectives surrounding the promotion, structuring, funding, and evaluation of research conducted by teacher educators in Uruguay. It includes:
• Legal and policy frameworks: Key legislation (e.g., Law N° 19.889, General Law of Education N° 18.437) and institutional development plans (Administración Nacional de Educación Pública - ANEP and CFE) that outline strategic directions for research in teacher education.
• Curriculum and programmatic documents: Curricular plans (e.g., Plan 2008, Plan 2019, Plan 2023), regulations for practical training, and details on academic workloads, illustrating how research is (or is not) integrated into teacher education programs.
• Research support mechanisms: Documents related to the creation and operation of research support programs such as PRADINE (Program for the Support of Research Development in Education) and CFE Investiga, calls for research grants, sabbatical leave regulations, and funding for academic events.
• Postgraduate education: Proposals and regulations for master's degrees, diplomas, and other postgraduate programs, highlighting the role of research in advanced teacher education.
• Institutional structures and governance: Resolutions and reports concerning the Academic Secretariat for Research and Postgraduate Studies (SAAIP), the impact of the Hourly Performance Units (Unidades Horarias de Desempeño - UHDD) on research time, and debates around the Teacher Civil Servant Statute (Estatuto del Funcionario Docente) and its implications for academic careers and research.
• Perspectives from academic and union collectives: Analyses, critiques, and proposals from teacher educator groups such as ALICIA Network (Red ALICIA), the CFE's Technical Teacher Assembly (Asamblea Técnico Docente - ATD), and the Teachers' Union (Sindicato de Docentes de Formación en Educación - SIDFE), reflecting their views on the state of research and the conditions for its development. This dataset is a valuable resource for researchers, policymakers, educators, and students interested in understanding the evolution of research policy in teacher education in Uruguay, the challenges of fostering a research culture within teacher training institutions, and the ongoing debate about the university status of teacher education in the country. The documents offer a multifaceted view of how the research function has been conceptualized, promoted, and contested by various stakeholders within the Uruguayan education system.