cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/rc8vpbfcrc
title: Secretome Mtb infected neutrophil and macrophage

description: Mtb cells was co-cultured with peripheral blood mononuclear cells (PBMC) and polymorphonuclear cells (PMN) in distinct conditions, then secreted proteins in the culture medium were collected and characterized using LC-MS/MS. In brief, heparinized whole blood samples of three healthy donors were provided by Srinagarind Hospital, Khon Kaen, Thailand. After isolation steps, the human leukocyte was divided into two groups: peripheral blood mononuclear cell (PBMC), and polymorphonuclear cell (PMN). PBMCs were treated with 50 nM PMA for 24 h while PMN cells were maintained in RPMI medium at 37oC. The activated PBMCs were then divided into four subgroups: PBMC alone, PBMC co-cultured with PMN after 4 h (PBMC-PMN), PBMC co-cultured Mtb (PBMC-TB), and PBMC co-cultured Mtb then added PMN after 4 h (PBMC-TB-PMN). After a total of 6 h incubation, the protein of culture supernatant was collected and measured in concentration. The protein samples were separated by SDS-PAGE and underwent in-gel digestion. Extracted protein was injected into LC-MS/MS instrument for measurement.
DOI: 10.17632/rc8vpbfcrc.1
title: Secretome Mtb infected neutrophil and macrophage

description: Mtb cells was co-cultured with peripheral blood mononuclear cells (PBMC) and polymorphonuclear cells (PMN) in distinct conditions, then secreted proteins in the culture medium were collected and characterized using LC-MS/MS. In brief, heparinized whole blood samples of three healthy donors were provided by Srinagarind Hospital, Khon Kaen, Thailand. After isolation steps, the human leukocyte was divided into two groups: peripheral blood mononuclear cell (PBMC), and polymorphonuclear cell (PMN). PBMCs were treated with 50 nM PMA for 24 h while PMN cells were maintained in RPMI medium at 37oC. The activated PBMCs were then divided into four subgroups: PBMC alone, PBMC co-cultured with PMN after 4 h (PBMC-PMN), PBMC co-cultured Mtb (PBMC-TB), and PBMC co-cultured Mtb then added PMN after 4 h (PBMC-TB-PMN). After a total of 6 h incubation, the protein of culture supernatant was collected and measured in concentration. The protein samples were separated by SDS-PAGE and underwent in-gel digestion. Extracted protein was injected into LC-MS/MS instrument for measurement.
DOI: 10.15468/dl.btybju
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Strongylopus fasciatus (Smith, 1849)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((31.8862 -21.3285,30.5701 -20.3186,30.5701 -24.0715,35.5909 -24.0715,35.6007 -24.0157,35.6007 -23.8125,35.4969 -23.7035,35.6007 -23.165,35.6007 -22.9702,35.227 -22.2482,34.6862 -21.6944,34.013 -21.3095,33.5 -21.1593,32.9675 -21.1092,32.4352 -21.1612,31.8862 -21.3285))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036319-250525065834625/datasets/export for details.
DOI: 10.17632/n6tgfkwcty
title: The pole of growth-20250611

description: The current folder contains the code and data files that were used for obtaining the results of the paper "The Role of Growth Pole: Pathways of Urban Agglomerations' Integration into the National Value Chain - The Case of Beijing-Tianjin-Hebei Urban Agglomeration", by Na Zhao, Wenshuo Lu, Fulin Wei, Bingwei Cheng.
DOI: 10.17632/n6tgfkwcty.1
title: The pole of growth-20250611

description: The current folder contains the code and data files that were used for obtaining the results of the paper "The Role of Growth Pole: Pathways of Urban Agglomerations' Integration into the National Value Chain - The Case of Beijing-Tianjin-Hebei Urban Agglomeration", by Na Zhao, Wenshuo Lu, Fulin Wei, Bingwei Cheng.
DOI: 10.15468/dl.h8wyg7
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "OccurrenceStatus is Present",
 "TaxonKey is Chondrostoma arcasii (Steindachner, 1866)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036318-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/byyhymtcry
title: A new algorithm for optimization of vehicle energy recovery based on psychology

description: IIDP-LSTM algorithm for energy recovery optimization in electric vehicles.
DOI: 10.17632/byyhymtcry.1
title: A new algorithm for optimization of vehicle energy recovery based on psychology

description: IIDP-LSTM algorithm for energy recovery optimization in electric vehicles.
DOI: 10.15468/dl.azqeqp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Phragmites australis",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036320-250525065834625/datasets/export for details.
DOI: 10.17632/7wjv5xctw7
title: Global Sustainable Development Indicators Dataset: Socio-Economic, Environmental, Financial, and Governance Metrics (2001–2022)

description: This dataset presents a harmonized, high-quality panel of 126 countries spanning the years 2001 to 2022, focused on key indicators relevant to sustainable development, inequality, environmental policy, and inclusive economic growth. Countries were selected based on the availability and continuity of data across the included indicators, ensuring robust coverage for empirical analysis.

The dataset integrates variables from reputable international sources and underwent extensive data preprocessing, including imputation of missing values, standardization, and verification of time consistency. It is optimized for use in econometric modeling, cross-country regressions, panel data analysis, and machine learning applications in the fields of sustainability, development economics, and public policy.

The dataset includes over 50 indicators grouped into thematic domains:
Economic & Development Indicators

Real GDP per capita (GDP_PC_Con), GDP per capita (GDP_PC), GDP Growth (GDPG), Trade Openness (TR), Interest Rate (IR), Inflation (INF, INFG), Unemployment (UE), Financial Deepening (FD), Financial Inclusion (FI), Fintech (FT), Foreign Direct Investment (FDI, FDI Net), Government Subsidies (GS, GS2), Debt Level (DEB), and Debt Servicing (DEBS).

Social and Demographic Indicators

Income Inequality (II), Poverty Headcount Ratio (POV), Poverty Gap (POVG), Life Expectancy (LE), Human Capital Index (HC), Gender Composition (POPF, POPM), Population (POP), Urbanization (URB, URBP), Population Density (POPD), Population Growth (POPG).

Environmental and Sustainability Metrics

Ecological Footprint (EFP, EFPT), Renewable Energy Consumption (REC), Renewable Electricity Output (RELC), Carbon Emissions (COT, CO), Environmental Regulations (ER), Economic Growth Sustainability (EGS), and Green Finance (GF, GF2).

Innovation, Governance & Integration

Governance Indicators (GOV), Green Technology Innovation (GTI), High-Tech Development (HTD), Technology Diffusion (TD), Tourism Activity (TOR), Financial Globalization (FG).

All variables are cleaned, aligned by year and country, and formatted to allow comparative, longitudinal, and multivariate analyses. The dataset supports wide-ranging applications—from sustainability assessments and green finance modeling to inequality diagnostics and global development forecasting.
DOI: 10.17632/7wjv5xctw7.1
title: Global Sustainable Development Indicators Dataset: Socio-Economic, Environmental, Financial, and Governance Metrics (2001–2022)

description: This dataset presents a harmonized, high-quality panel of 126 countries spanning the years 2001 to 2022, focused on key indicators relevant to sustainable development, inequality, environmental policy, and inclusive economic growth. Countries were selected based on the availability and continuity of data across the included indicators, ensuring robust coverage for empirical analysis.

The dataset integrates variables from reputable international sources and underwent extensive data preprocessing, including imputation of missing values, standardization, and verification of time consistency. It is optimized for use in econometric modeling, cross-country regressions, panel data analysis, and machine learning applications in the fields of sustainability, development economics, and public policy.

The dataset includes over 50 indicators grouped into thematic domains:
Economic & Development Indicators

Real GDP per capita (GDP_PC_Con), GDP per capita (GDP_PC), GDP Growth (GDPG), Trade Openness (TR), Interest Rate (IR), Inflation (INF, INFG), Unemployment (UE), Financial Deepening (FD), Financial Inclusion (FI), Fintech (FT), Foreign Direct Investment (FDI, FDI Net), Government Subsidies (GS, GS2), Debt Level (DEB), and Debt Servicing (DEBS).

Social and Demographic Indicators

Income Inequality (II), Poverty Headcount Ratio (POV), Poverty Gap (POVG), Life Expectancy (LE), Human Capital Index (HC), Gender Composition (POPF, POPM), Population (POP), Urbanization (URB, URBP), Population Density (POPD), Population Growth (POPG).

Environmental and Sustainability Metrics

Ecological Footprint (EFP, EFPT), Renewable Energy Consumption (REC), Renewable Electricity Output (RELC), Carbon Emissions (COT, CO), Environmental Regulations (ER), Economic Growth Sustainability (EGS), and Green Finance (GF, GF2).

Innovation, Governance & Integration

Governance Indicators (GOV), Green Technology Innovation (GTI), High-Tech Development (HTD), Technology Diffusion (TD), Tourism Activity (TOR), Financial Globalization (FG).

All variables are cleaned, aligned by year and country, and formatted to allow comparative, longitudinal, and multivariate analyses. The dataset supports wide-ranging applications—from sustainability assessments and green finance modeling to inequality diagnostics and global development forecasting.
DOI: 10.15468/dl.8tw372
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Plumbago auriculata",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036322-250525065834625/datasets/export for details.
DOI: 10.15468/dl.pgk5ub
title: Occurrence Download

description: A dataset containing 29132 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Onychorhynchus coronatus (Statius Muller, 1776)"
 ]
}

 The dataset includes 29132 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036321-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/mj352nxrx2
title: Climate Tourism Survey

description: This dataset contains responses to a survey examining the effects of climate change on tourists' destination choices and preferences for sustainable tourism in Greece. The survey was conducted between August 1st and August 26th, 2024, with 580 participants recruited via snowball sampling from social media platforms targeting travel groups. Inclusion criteria required participants to be over 18 years of age and either have visited Greece in the past three years or plan to visit within the next three years.
The survey explores various factors influencing tourists’ travel decisions, such as climate change awareness, perceptions of climate risks (e.g., temperature rise, wildfires), and preferences for sustainable practices (e.g., recycling, eco-friendly accommodations). The data also includes demographic information such as age, gender, education, employment status, and household income.
Key findings from the data reveal that traditional factors like cost, safety, and beaches remain dominant in tourists' destination choices, while climate concerns such as temperature rise and wildfires significantly influence destination selection. Notably, there is a growing preference for destinations that prioritize sustainability, although respondents perceive the tourism industry’s response to climate change as insufficient.
This dataset can be used to analyze how climate risk perceptions shape tourist behavior, the role of sustainability in travel decisions, and the potential for climate change to alter tourism patterns in Greece. It also provides insights into demographic variations in climate awareness and sustainable tourism preferences, offering a foundation for targeted communication and policy development to enhance resilience in Greece’s tourism sector.
DOI: 10.15468/dl.hjxwtp
title: Occurrence Download

description: A dataset listing the 334 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((29.47032 -23.53345,29.80445 -23.53345,29.80445 -23.26935,29.47032 -23.26935,29.47032 -23.53345))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset's 334 records were derived from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036301-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/mj352nxrx2.1
title: Climate Tourism Survey

description: This dataset contains responses to a survey examining the effects of climate change on tourists' destination choices and preferences for sustainable tourism in Greece. The survey was conducted between August 1st and August 26th, 2024, with 580 participants recruited via snowball sampling from social media platforms targeting travel groups. Inclusion criteria required participants to be over 18 years of age and either have visited Greece in the past three years or plan to visit within the next three years.
The survey explores various factors influencing tourists’ travel decisions, such as climate change awareness, perceptions of climate risks (e.g., temperature rise, wildfires), and preferences for sustainable practices (e.g., recycling, eco-friendly accommodations). The data also includes demographic information such as age, gender, education, employment status, and household income.
Key findings from the data reveal that traditional factors like cost, safety, and beaches remain dominant in tourists' destination choices, while climate concerns such as temperature rise and wildfires significantly influence destination selection. Notably, there is a growing preference for destinations that prioritize sustainability, although respondents perceive the tourism industry’s response to climate change as insufficient.
This dataset can be used to analyze how climate risk perceptions shape tourist behavior, the role of sustainability in travel decisions, and the potential for climate change to alter tourism patterns in Greece. It also provides insights into demographic variations in climate awareness and sustainable tourism preferences, offering a foundation for targeted communication and policy development to enhance resilience in Greece’s tourism sector.
DOI: 10.34740/kaggle/dsv/12131742
title: Book store management system project report.
DOI: 10.6084/m9.figshare.28052606.v4
title: <b>Supplementary Table S1. </b>Descriptive statistics of mature milk production and longevity traits in Chinese Holstein cattle

description: none
DOI: 10.15468/dl.429skf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Pogonarthria squarrosa",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036323-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.28560650
title: Section_5-1

description: This file contains an overview of participants and the interview guideline for the evaluation from the paper: "A Procedural Framework for Assessing the Desirability of Process Deviations" accepted at the BPM Conference 2025
DOI: 10.15468/dl.98666p
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "StateProvince is RIO DE JANEIRO, RJ"
 ]
}

 The dataset includes 14 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036324-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rvmt7u
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "OccurrenceStatus is Present",
 "TaxonKey is Chondrostoma lemmingii (Steindachner, 1866)"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036325-250525065834625/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.26300143.v8
title: <b>Supplementary Table S2.</b> significant KEGG pathways and GO terms in candidate gene enrichment in WssGWAS for colostrum quality (Brix, %) in parity 1-3 Chinese Holstein cows

description: none
DOI: 10.15468/dl.hkefeq
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Strongylopus fasciatus (Smith, 1849)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((27.1586 -33.5889,28.2048 -32.9007,25.5395 -32.9007,25.5395 -34.1098,25.6468 -34.1222,25.7787 -34.0734,25.7098 -33.9109,25.8639 -33.797,26.4806 -33.8473,27.1586 -33.5889))"
 ]
}

 The dataset includes 42 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036326-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rrrg4t
title: Occurrence Download

description: A dataset containing 180 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cebus aequatorialis J.A.Allen, 1914"
 ]
}

 The dataset includes 180 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036328-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ucxbv2
title: Occurrence Download

description: A dataset containing 7069 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Carcharias taurus Rafinesque, 1810"
 ]
}

 The dataset includes 7069 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036329-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15640890
title: Aligning foundation models on encoded synthetic omic data for patient stratification

description: The use of real world health data for Foundation Model training often comes with concerns due to the potential sharing of sensitive information. Synthetic data may prove to be one of the best assets to limit such concerns. In this manuscript, we introduce a new paradigm of training Foundation Models - generate synthetic data, encode it with a compression method and frequency-based mapping, and use these encoded data to align a Foundation Model. We demonstrate our pipeline on the task of colorectal cancer patient stratification into consensus molecular subtypes (CMS) using a decoder-only model. Evaluation of the aligned model on real data results in a balanced accuracy and F1 score of approximately 91%, competitive with baselines established by prior work leveraging real data as well as with models trained directly on synthetic data.

This repository contains the data used in the experiments and the results of LLM-finetuning in json form. The numbered folders in data.zip correspond to the seed that was used for generating the synthetic data.
DOI: 10.5281/zenodo.15641421
title: Aligning foundation models on encoded synthetic omic data for patient stratification

description: The use of real world health data for Foundation Model training often comes with concerns due to the potential sharing of sensitive information. Synthetic data may prove to be one of the best assets to limit such concerns. In this manuscript, we introduce a new paradigm of training Foundation Models - generate synthetic data, encode it with a compression method and frequency-based mapping, and use these encoded data to align a Foundation Model. We demonstrate our pipeline on the task of colorectal cancer patient stratification into consensus molecular subtypes (CMS) using a decoder-only model. Evaluation of the aligned model on real data results in a balanced accuracy and F1 score of approximately 91%, competitive with baselines established by prior work leveraging real data as well as with models trained directly on synthetic data.

This repository contains the data used in the experiments and the results of LLM-finetuning in json form. The numbered folders in data.zip correspond to the seed that was used for generating the synthetic data.
DOI: 10.15468/dl.3tmkxp
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "StateProvince is RIO DE JANEIRO, RJ"
 ]
}

 The dataset includes 14 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036330-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/b6r79w7z86
title: Phytopythium niubeiliangense sp. nov., a novel species of Phytopythium from warm-temperate forest of China

description: The Oomycetes are well-known for many important pathogenic species, such as Phytophthora and Pythium species. In this study, two isolates, including a non-papillate, homothallic Phytophthora strain and another papillate, asexual Phytopythium strain, collected from subtropical island of Japan and warm-temperate forest of China respectively, were described. The two strains could not be completely assigned to any existing taxon and were characterized through morphological studies and multi-gene phylogenetic analyses. Additionally, the mitochondrial genome of the new Phytophthora strain was sequenced and annotated, revealing a distinct gene arrangement when compared with related Phytophthora species. Therefore, based on the unique morphological characteristics and taxonomic status, the two strains were described here as two new species formally designated as Phytophthora umbellatus sp. nov. and Phytopythium niubeiliangense sp. nov., respectively. Detailed micro-morphological descriptions, illustrations, and DNA molecular data are provided to confirm their taxonomic placements.