cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48723/bbag-t656
title: Data from immunocompromised individuals vaccinated with SARS-CoV2 vaccines: antibody titers, B cell receptor repertoire sequencing, and B cell immunophenotyping
title: Data från immunosupprimerade individer vaccinerade med SARS-CoV-2-vacciner: antikroppstitrar, sekvensering av B-cellsreceptorrepertoar och immunfenotypning av B-celler

description: The dataset contains B cell receptor (BCR) sequencing data. Two types of data are included:

Antigen-specific BCR sequences obtained by sorting B cells (CD19+, CD20+, IgG+, IgM-, Spike+) followed by PCR and Sanger sequencing for SARS-CoV-2. Sequences are provided per individual and also as a combined dataset.

Bulk BCR repertoire sequencing for IgM and IgG, with one FASTQ file per individual and sample.

All sequences are provided as FASTQ or FASTA files. Users will need to realign and re-annotate VDJ segments using their preferred reference database and software.

More details on the experimental design and sorting strategy can be found in the published paper: DOI 10.1002/cti2.70077

No direct identifiers are included; sample IDs are pseudonymized. The size of the dataset is approximately 30 GB.
description: Datasetet innehåller B-cellsreceptor (BCR) sekvenseringsdata. Två typer av data ingår:

Antigenspecifika BCR-sekvenser framtagna genom sortering av B-celler (CD19+, CD20+, IgG+, IgM-, Spike+) följt av PCR och Sanger-sekvensering för SARS-CoV-2. Sekvenserna tillhandahålls per individ samt som en kombinerad dataset.

Bulk BCR-repertoire sekvensering för IgM och IgG, med en FASTQ-fil per individ och prov.

Alla sekvenser tillhandahålls som FASTQ- eller FASTA-filer. Användare behöver realignera och reannotera VDJ-segment med sitt val av referensdatabas och programvara.

Mer information om experimentell design och sorteringsstrategi finns i den publicerade artikeln: DOI 10.1002/cti2.70077


Inga direkta identifierare ingår; prov-ID är pseudonymiserade. Datasetets storlek är ca 30 GB.
DOI: 10.48723/g2m1-jm64
title: Data from immunocompromised individuals vaccinated with SARS-CoV2 vaccines: antibody titers, B cell receptor repertoire sequencing, and B cell immunophenotyping
title: Data från immunosupprimerade individer vaccinerade med SARS-CoV-2-vacciner: antikroppstitrar, sekvensering av B-cellsreceptorrepertoar och immunfenotypning av B-celler

description: The dataset contains B cell receptor (BCR) sequencing data. Two types of data are included:

Antigen-specific BCR sequences obtained by sorting B cells (CD19+, CD20+, IgG+, IgM-, Spike+) followed by PCR and Sanger sequencing for SARS-CoV-2. Sequences are provided per individual and also as a combined dataset.

Bulk BCR repertoire sequencing for IgM and IgG, with one FASTQ file per individual and sample.

All sequences are provided as FASTQ or FASTA files. Users will need to realign and re-annotate VDJ segments using their preferred reference database and software.

More details on the experimental design and sorting strategy can be found in the published paper: DOI 10.1002/cti2.70077

No direct identifiers are included; sample IDs are pseudonymized. The size of the dataset is approximately 30 GB.
description: Datasetet innehåller B-cellsreceptor (BCR) sekvenseringsdata. Två typer av data ingår:

Antigenspecifika BCR-sekvenser framtagna genom sortering av B-celler (CD19+, CD20+, IgG+, IgM-, Spike+) följt av PCR och Sanger-sekvensering för SARS-CoV-2. Sekvenserna tillhandahålls per individ samt som en kombinerad dataset.

Bulk BCR-repertoire sekvensering för IgM och IgG, med en FASTQ-fil per individ och prov.

Alla sekvenser tillhandahålls som FASTQ- eller FASTA-filer. Användare behöver realignera och reannotera VDJ-segment med sitt val av referensdatabas och programvara.

Mer information om experimentell design och sorteringsstrategi finns i den publicerade artikeln: DOI 10.1002/cti2.70077


Inga direkta identifierare ingår; prov-ID är pseudonymiserade. Datasetets storlek är ca 30 GB.
DOI: 10.57745/b3thlz
title: Sous ensemble de données annotées - Acteurs des circuits courts des systèmes alimentaires territoriaux

description: Ce jeu de données regroupe une partie du corpus thématique, en français, collecté auprès d'agrégateurs de presse (Factiva, Europresse) et annoté manuellement, constituant une ressource de référence pour l'extraction d'entités et la construction d'ontologies appliquées aux systèmes alimentaires territoriaux. A partir d’un guide d’annotation co-construit entre les UMR TETIS et Innovation, une session d'annotation a été réalisée afin d’annoter un sous-ensemble de documents. Les annotateurs ayant participé à la session d’annotation sont Grégori Akermann, Manon Pradère de l'UMR Innovation ainsi que 14 étudiants (Rémi Bourgault, Sarah Bourlet, Joris Drilles, Ozan Emre, Lena Gassimov, Maiwenn Guenin, Malo Jourde, Eliane Lagrange, Solène Malpel, Tauhiti Mooria Lisa Nobre) issus des formations suivantes : Licence Pro ABCD - Agriculture Biologique Conseil et Développement du CFPPA de Rennes-Le Rheu et de St-Affrique. Ces étudiants étaient encadrés par leurs enseignantes : Catherine Polcwiartek et Anne Sanchez. Ce jeu de données comprend les 3 éléments suivants : - Le fichier Echantillon_Articles_Circuits_Courts présente un échantillon représentatif extrait du fichier Corpus_Complet_Presse_Circuits_Courts du jeu de données
DOI: 10.15468/dl.bdry4j
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Wooleya farinosa",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021751-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18595890
title: Data for study: Experimental evaluation of a Modular Phase-Change Material-Based Thermal Energy Storage System

description: 1. Journal article: Experimental evaluation of a Modular Phase-Change Material-Based Thermal Energy Storage System

2. DOI: https://doi.org/10.5281/zenodo.18595890

3. Contact information    Name: Zdenek Machacek   Institution: VSB-Technical University of Ostrava   E-mail: zdenek.machacek@vsb.cz   ORCID: https://orcid.org/0000-0002-6127-0763

4. Dataset archiving (publication) date: 2026-02-16

5. Place of archiving (publication): Ostrava, Czechia

 

6. Dataset description: original data from original research within the project esearch Platform for Digital Transformation and Society 5.0.  Precisely there are 6,7,8,9,10 number of Figures,  4 Datasets of the study:

Datasets and Python scripts for Dynamic Temperature measurements.

This package contains Excel data files and Python scripts, where each script processes and data represents specific graphical types: 

Data files:

Fig6,7.zip

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Comparison of Temperature Profiles and Energy Consumption Across 12 Replicate Test Scenarios

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Temperature trajectories of individual sensors across chains A–E over the full charge–discharge cycle.

Fig8.zip

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Time courses of the average temperature in chains A–E during charging and discharging.

Fig9.zip

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Temperature histories during controlled charging, cooling (supercooled state), andmechanically triggered discharge (latent heat release).

Fig10.zip

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Two-dimensional thermal maps illustrating the advance of the thermal front during 1charging.

 

7. Funding: This work was supported by the European Regional Development Fund under the project Research Platform for Digital Transformation and Society 5.0 CZ.02.01.01/00/23_021/0012599 within the Jan Amos Komensky Operational Program supported by the Ministry of Education, Youth and Sports and co-financed by the European Union.
DOI: 10.5281/zenodo.18595889
title: Data for study: Experimental evaluation of a Modular Phase-Change Material-Based Thermal Energy Storage System

description: 1. Journal article: Experimental evaluation of a Modular Phase-Change Material-Based Thermal Energy Storage System

2. DOI: https://doi.org/10.5281/zenodo.18595890

3. Contact information    Name: Zdenek Machacek   Institution: VSB-Technical University of Ostrava   E-mail: zdenek.machacek@vsb.cz   ORCID: https://orcid.org/0000-0002-6127-0763

4. Dataset archiving (publication) date: 2026-02-16

5. Place of archiving (publication): Ostrava, Czechia

 

6. Dataset description: original data from original research within the project esearch Platform for Digital Transformation and Society 5.0.  Precisely there are 6,7,8,9,10 number of Figures,  4 Datasets of the study:

Datasets and Python scripts for Dynamic Temperature measurements.

This package contains Excel data files and Python scripts, where each script processes and data represents specific graphical types: 

Data files:

Fig6,7.zip

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Comparison of Temperature Profiles and Energy Consumption Across 12 Replicate Test Scenarios

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Temperature trajectories of individual sensors across chains A–E over the full charge–discharge cycle.

Fig8.zip

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Time courses of the average temperature in chains A–E during charging and discharging.

Fig9.zip

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Temperature histories during controlled charging, cooling (supercooled state), andmechanically triggered discharge (latent heat release).

Fig10.zip

Dataset from Modular Phase-Change Material-Based Thermal Energy Storage System. Two-dimensional thermal maps illustrating the advance of the thermal front during 1charging.

 

7. Funding: This work was supported by the European Regional Development Fund under the project Research Platform for Digital Transformation and Society 5.0 CZ.02.01.01/00/23_021/0012599 within the Jan Amos Komensky Operational Program supported by the Ministry of Education, Youth and Sports and co-financed by the European Union.
DOI: 10.15468/dl.xckzpr
title: Occurrence Download

description: A dataset containing 417 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Zaleya pentandra",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 417 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021754-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18657287
title: Dataset for machine learning model case study
DOI: 10.5281/zenodo.18657288
title: Dataset for machine learning model case study
DOI: 10.5281/zenodo.18657289
title: QR Code Payments as Phygital Marketing Touchpoints: Gendered Insights into Tourist Satisfaction, Loyalty and Revisit Intention

description: This study examines the role of QR code–based digital payments as phygital marketing touchpoints in shaping tourist satisfaction, loyalty, and revisit intention, while also investigating the moderating role of gender. As tourism experiences increasingly integrate digital and physical service interactions, payment technologies have emerged as critical components of the customer journey that may influence behavioral outcomes. Using a quantitative research design, data were collected from 240 tourists with prior experience using QR-based payments during their travel activities. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the relationships among QR payment experience, tourist satisfaction, loyalty, and revisit intention.

The findings reveal that QR payment significantly enhances tourist satisfaction, which in turn strongly influences both loyalty and revisit intention. However, QR payment does not directly affect loyalty or revisit intention, indicating that tourist satisfaction fully mediates these relationships. The results highlight satisfaction as the key psychological mechanism linking digital payment experiences to post-visit behavioral intentions. Furthermore, the study finds no significant moderating effect of gender on the relationship between satisfaction and behavioral outcomes, suggesting that male and female tourists respond similarly to QR-enabled service experiences.

This study contributes to tourism and service technology literature by positioning payment systems as experiential value drivers rather than merely transactional tools. From a managerial perspective, the findings suggest that tourism businesses should prioritize seamless and reliable QR payment integration to enhance customer satisfaction and foster long-term destination loyalty and revisit behavior.
DOI: 10.5281/zenodo.18657290
title: QR Code Payments as Phygital Marketing Touchpoints: Gendered Insights into Tourist Satisfaction, Loyalty and Revisit Intention

description: This study examines the role of QR code–based digital payments as phygital marketing touchpoints in shaping tourist satisfaction, loyalty, and revisit intention, while also investigating the moderating role of gender. As tourism experiences increasingly integrate digital and physical service interactions, payment technologies have emerged as critical components of the customer journey that may influence behavioral outcomes. Using a quantitative research design, data were collected from 240 tourists with prior experience using QR-based payments during their travel activities. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the relationships among QR payment experience, tourist satisfaction, loyalty, and revisit intention.

The findings reveal that QR payment significantly enhances tourist satisfaction, which in turn strongly influences both loyalty and revisit intention. However, QR payment does not directly affect loyalty or revisit intention, indicating that tourist satisfaction fully mediates these relationships. The results highlight satisfaction as the key psychological mechanism linking digital payment experiences to post-visit behavioral intentions. Furthermore, the study finds no significant moderating effect of gender on the relationship between satisfaction and behavioral outcomes, suggesting that male and female tourists respond similarly to QR-enabled service experiences.

This study contributes to tourism and service technology literature by positioning payment systems as experiential value drivers rather than merely transactional tools. From a managerial perspective, the findings suggest that tourism businesses should prioritize seamless and reliable QR payment integration to enhance customer satisfaction and foster long-term destination loyalty and revisit behavior.
DOI: 10.21227/nva2-kn07
title: "Camera-only self driving vehicle dataset for end to end trajectory prediction and vehicle control in autonomous driving"

description: "Autonomous driving constitutes a rapidly advancing field that leverages artificial intelligence, computer vision, and machine learning to enable safe and efficient vehicle navigation. However the barrier to enter this field of research and product development is high, requiring expensive sensor arrays and proprietary, large scale datasets. This work explores a camera-only approach to autonomous navigation for passenger vehicles, aiming to reduce both system complexity and implementation costs. The proposed methodology relies on simulated environments for data collection, model training, and evaluation, allowing for rapid iteration and testing under diverse conditions. Three heterogeneous deep learning architectures\u2014namely Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers\u2014were investigated for their ability to process visual input and predict future vehicle trajectories. The findings suggest that the camera-only end-to-end approach, combined with simulation-based development, holds potential as a scalable and cost-effective foundation for future autonomous systems. This dataset represents the data collected and used to produce these findings."
DOI: 10.15468/dl.8gxjw9
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Zeuktophyllum suppositum",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021755-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18442413
title: Data from: How to estimate overall population trends when sites show varying population counts over time?

description: Simulated time series mimic counts of subpopulations over time. Includes 250 time series for each of the 8 scenarios described in the simulation study of the journal article "How to estimate overall population trends when sites show varying population counts over time?". The naming follows the logic: is the overall trend non-linear (FALSE: it is log-linear, TRUE: it is non-linear in a way that cannot be described by log-linearity)? Are there differences in subpopulation development over time (FALSE: no, subpopulations are homogeneous, TRUE: yes, subpopulations are heterogeneous)? Does overdispersion follow a negative-binomial distribution (FALSE: no, it is simulated comparable to quasi-poisson, TRUE: yes, it is negative-binomial and quasi-poisson cannot cover this kind of overdispersion)? For more details, see the article. The data set is created by the code on github.
DOI: 10.5281/zenodo.18442412
title: Data from: How to estimate overall population trends when sites show varying population counts over time?

description: Simulated time series mimic counts of subpopulations over time. Includes 250 time series for each of the 8 scenarios described in the simulation study of the journal article "How to estimate overall population trends when sites show varying population counts over time?". The naming follows the logic: is the overall trend non-linear (FALSE: it is log-linear, TRUE: it is non-linear in a way that cannot be described by log-linearity)? Are there differences in subpopulation development over time (FALSE: no, subpopulations are homogeneous, TRUE: yes, subpopulations are heterogeneous)? Does overdispersion follow a negative-binomial distribution (FALSE: no, it is simulated comparable to quasi-poisson, TRUE: yes, it is negative-binomial and quasi-poisson cannot cover this kind of overdispersion)? For more details, see the article. The data set is created by the code on github.
DOI: 10.15468/dl.tj5g4j
title: Occurrence Download

description: A dataset containing 132 records in GBIF matching the query:

SELECT
 countryCode,
 GBIF_ISEA3HCode(
 7, 
 decimalLatitude,
 decimalLongitude,
 COALESCE(coordinateUncertaintyInMeters, 1000)
 ) AS geogrid_id,
 COUNT(DISTINCT speciesKey) AS unique_species_count
FROM occurrence
WHERE countryCode = 'PG'
AND coordinateUncertaintyInMeters &lt;= 2000
AND hasGeospatialIssues = FALSE
AND hasCoordinate = TRUE
AND occurrenceStatus = 'PRESENT'
GROUP BY countryCode, geogrid_id;


 The dataset's 132 records were derived from 203 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021752-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f8cfby
title: Occurrence Download

description: A dataset containing 1010 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is The wild bees (Hymenoptera, Apoidea, Anthophila) of the urban nature reserves of Rome (Italy, Latium): a preliminary survey"
 ]
}

 The dataset includes 1010 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021758-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f69wfr
title: Occurrence Download

description: A dataset containing 6091 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Achyranthes bidentata",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 6091 records from 126 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021760-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h8xcqm
title: Occurrence Download

description: A dataset containing 45375 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (EOD – eBird Observation Dataset, Anillamiento SEO_Bird ringing, Observation.org, Nature data from around the World)",
 "Geometry POLYGON((-12.24898 35.0202,4.98758 35.0202,4.98758 44.39137,-12.24898 44.39137,-12.24898 35.0202))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Otus scops"
 ]
}

 The dataset includes 45375 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021759-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3tcgrx
title: Occurrence Download

description: A dataset containing 780986 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-20 -38,55 -38,55 38,-20 38,-20 -38))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Coliiformes"
 ]
}

 The dataset includes 780986 records from 103 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021725-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.