cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e246548v1
title: (2026/2027) Topfaith University{Applicant] Admission form is out , for futher assistance call Dr Martins 09017730052. Call +2349017730052 or WhatsApp 08169753031.

description: (2026/2027) Topfaith University{Applicant] Admission form is out , for futher assistance call Dr Martins 09017730052. Call +2349017730052 or WhatsApp 08169753031.
DOI: 10.5281/zenodo.18814367
title: malva_aegyptia_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18814366
title: malva_aegyptia_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18814372
title: malva_alcea_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18814371
title: malva_alcea_decontaminated_FSCR.fasta.gz
DOI: 10.15468/dl.safm3g
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Russian Federation",
 "TaxonKey is one of (Astacus astacus, Astacus leptodactylus)"
 ]
}

 The dataset includes 41 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004231-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xypzkj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Epigonus ctenolepis"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004230-260226173443078/datasets/export for details.
DOI: 10.15468/dl.aam7ur
title: Occurrence Download

description: A dataset containing 61957 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.13.12_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1000-2026"
 ]
}

 The dataset includes 61957 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004215-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/6aqsx8
title: pbzt_insect_biodiversity

description: Our data concerns coleptera diversity hold at Parc Botanique et Zoologique de Tsimbazaza, Madagascar. This is the first published record at this collection largely publish on GBIF portal. This data was published to make data available, accessible and useful for biodvidersity conservation.
DOI: 10.15468/dl.teq3m6
title: Occurrence Download

description: A dataset containing 21565 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Chenopodium hybridum, , , , , , , , Chenopodium hybridum, , , , , , , , , , , , , , , , , , , , , , , , , , , Chenopodium hybridum, , , , , , , , , , , , , , , Biosteres carbonarius, , , , , , , , , , , , )",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 21565 records from 319 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004232-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wrb6r9
title: Occurrence Download

description: A dataset containing 211 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Collichthys niveatus"
 ]
}

 The dataset includes 211 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004233-260226173443078/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.28547018.v1
title: The Application of Technology Acceptance Model in Older Adult’s Healthcare Services: A Systematic Review

description: Healthcare services provide promising opportunities for older adult people, particularly in the face of a growing ageing demographic. Despite this, the older adult population exhibits low acceptance of healthcare services, which may stem from a multitude of variables. The technology acceptance model (TAM) serves as a widely recognized framework for comprehending users' acceptance of new technology. However, the relationship between ageing-related variables and TAM model for older adult individuals remains largely unexplored within the context of their utilization of healthcare services. Therefore, this paper aims to identify the relationships among these different technology acceptance models and conclude the variables within these identified models. This paper adopted a systematic review approach. Three reference databases, Scopus, Web of Science, and IEEE were consulted; 36 articles were screened in the final analysis. Results emphasize the importance of "perceived usefulness" in TAM and "performance expectancy" in UTAUT, with additional variables such as "social influence" identified as critical. Furthermore, a range of factors including economic, social, psychological, and demographic influences shape older adult acceptance behaviours, underscoring the need for holistic approaches to adoption barriers. This finding offers insights for practitioners, and researchers to develop healthcare services for older adult groups, emphasizing the importance of considering identified variables in future designs.
DOI: 10.34804/supra.20210928350
title: NMR Investigation of the complexation of neutral guests by cucurbituril

description: The effect of acidity on the stability of the complexes of neutral guests with cucurbituril (CB), a synthetic receptor, in aqueous Na2SO4 solutions is investigated by 129Xe, 19F and 1H NMR spectroscopy. The apparent affinity constants of THF and xenon for CB were measured and found to be independent of the p
DOI: 10.5281/zenodo.18814392
title: malva_arborea_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18814391
title: malva_arborea_decontaminated_FSCR.fasta.gz
DOI: 10.3886/e246549
title: The Nigeria Army College Of Nursing yaba Lagos 2026/2027 Admission Form is out Call 09017730052 To Apply And further admission assistance. Call Dr Martins. +2349017730052 or WhatsApp 08169753031

description: The Nigeria Army College Of Nursing yaba Lagos 2026/2027 Admission Form is out Call 09017730052 To Apply And further admission assistance. Call Dr Martins. +2349017730052 or WhatsApp 08169753031
DOI: 10.3886/e246549v1
title: The Nigeria Army College Of Nursing yaba Lagos 2026/2027 Admission Form is out Call 09017730052 To Apply And further admission assistance. Call Dr Martins. +2349017730052 or WhatsApp 08169753031

description: The Nigeria Army College Of Nursing yaba Lagos 2026/2027 Admission Form is out Call 09017730052 To Apply And further admission assistance. Call Dr Martins. +2349017730052 or WhatsApp 08169753031
DOI: 10.15468/dl.ap8ruk
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Owstonia tosaensis"
 ]
}

 The dataset includes 19 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004234-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18814394
title: malva_cretica_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18814395
title: malva_cretica_decontaminated_FSCR.fasta.gz
DOI: 10.15468/dl.rta7cs
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Owstonia taeniosoma"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004236-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e246550
title: Abia state school of nursing, Amachara Basic Nursing 2026/2027 Admission Form is out Call 09017730052 To Apply And further admission assistance. Call Dr Martins. +2349017730052 or WhatsApp 08169753031

description: Abia state school of nursing, Amachara Basic Nursing 2026/2027 Admission Form is out Call 09017730052 To Apply And further admission assistance. Call Dr Martins. +2349017730052 or WhatsApp 08169753031
DOI: 10.5281/zenodo.18814419
title: malva_olbia_decontaminated_FSCR.fasta.gz
DOI: 10.3886/e246550v1
title: Abia state school of nursing, Amachara Basic Nursing 2026/2027 Admission Form is out Call 09017730052 To Apply And further admission assistance. Call Dr Martins. +2349017730052 or WhatsApp 08169753031

description: Abia state school of nursing, Amachara Basic Nursing 2026/2027 Admission Form is out Call 09017730052 To Apply And further admission assistance. Call Dr Martins. +2349017730052 or WhatsApp 08169753031
DOI: 10.5281/zenodo.18814420
title: malva_olbia_decontaminated_FSCR.fasta.gz
DOI: 10.15468/dl.7h8jb9
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Iniistius melanopus"
 ]
}

 The dataset includes 17 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004237-260226173443078/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.30032800
title: bppMigration-algorithms-data.tgz

description: Population phylogenomics uses sampled genomes to jointly infer population genetic processes (ancestral and contemporary population sizes, historical gene flow) and a phylogenetic tree relating species or populations including species divergence times. This challenging problem has been tackled most successfully in the Bayesian framework under the multispecies coalescent (MSC) model via Markov chain Monte Carlo (MCMC) computational algorithms. However, MCMC methods suffer from two serious problems: (i) mixing difficulties due to the high-dimensional state space with complex constraints, and (ii) the intrinsically serial nature of MCMC algorithms that defies parallelisation. We develop a new method, called Virtual Dimension Reduction allowing Parallelisation (VDRoP), that achieves the same MCMC mixing efficiency as dimension reduction through analytical integration of parameters, but without sacrificing parallel computation and without the restriction to conjugate priors. We implement the new method in the Bayesian program BPP and apply it to genomic datasets from <i>Adansonia</i> baobab trees, <i>Anopheles</i> mosquitoes, and<i> Heliconius</i> butterflies. The new algorithms reduce the run-time of MCMC analyses by 3 to 8 fold and improve the mixing efficiency by up to 50 fold for representative empirical datasets.
DOI: 10.6084/m9.figshare.30032800.v2
title: bppMigration-algorithms-data.tgz

description: Population phylogenomics uses sampled genomes to jointly infer population genetic processes (ancestral and contemporary population sizes, historical gene flow) and a phylogenetic tree relating species or populations including species divergence times. This challenging problem has been tackled most successfully in the Bayesian framework under the multispecies coalescent (MSC) model via Markov chain Monte Carlo (MCMC) computational algorithms. However, MCMC methods suffer from two serious problems: (i) mixing difficulties due to the high-dimensional state space with complex constraints, and (ii) the intrinsically serial nature of MCMC algorithms that defies parallelisation. We develop a new method, called Virtual Dimension Reduction allowing Parallelisation (VDRoP), that achieves the same MCMC mixing efficiency as dimension reduction through analytical integration of parameters, but without sacrificing parallel computation and without the restriction to conjugate priors. We implement the new method in the Bayesian program BPP and apply it to genomic datasets from <i>Adansonia</i> baobab trees, <i>Anopheles</i> mosquitoes, and<i> Heliconius</i> butterflies. The new algorithms reduce the run-time of MCMC analyses by 3 to 8 fold and improve the mixing efficiency by up to 50 fold for representative empirical datasets.
DOI: 10.6084/m9.figshare.30032800.v1
title: bppMigration-algorithms-data.tgz

description: Population phylogenomics uses sampled genomes to jointly infer population genetic processes (ancestral and contemporary population sizes, historical gene flow) and a phylogenetic tree relating species or populations including species divergence times. This challenging problem has been tackled most successfully in the Bayesian framework under the multispecies coalescent (MSC) model via Markov chain Monte Carlo (MCMC) computational algorithms. However, MCMC methods suffer from two serious problems: (i) mixing difficulties due to the high-dimensional state space with complex constraints, and (ii) the intrinsically serial nature of MCMC algorithms that defies parallelisation. We develop a new method, called Virtual Dimension Reduction allowing Parallelisation (VDRoP), that achieves the same MCMC mixing efficiency as dimension reduction through analytical integration of parameters, but without sacrificing parallel computation and without the restriction to conjugate priors. We implement the new method in the Bayesian program BPP and apply it to genomic datasets from <i>Adansonia</i> baobab trees, <i>Anopheles</i> mosquitoes, and<i> Heliconius</i> butterflies. The new algorithms reduce the run-time of MCMC analyses by 3 to 8 fold and improve the mixing efficiency by up to 50 fold for representative empirical datasets.
DOI: 10.5281/zenodo.18814432
title: malva_phoenicea_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18814431
title: malva_phoenicea_decontaminated_FSCR.fasta.gz
DOI: 10.15468/dl.58wbm6
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "Continent is Africa",
 "Country is South Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Raphicerus melanotis",
 "Year 2013-2014"
 ]
}

 The dataset includes 48 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004238-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e246551
title: Zamfara State School of Nursing and Midwifery, Gusau Admission Form 2026/2027 is Out, call 09017730052 To Apply and further admission assistance. Call Dr Martins +2349017730052 or WhatsApp 08169753031.

description: Zamfara State School of Nursing and Midwifery, Gusau Admission Form 2026/2027 is Out, call 09017730052 To Apply and further admission assistance. Call Dr Martins +2349017730052 or WhatsApp 08169753031.
DOI: 10.3886/e246551v1
title: Zamfara State School of Nursing and Midwifery, Gusau Admission Form 2026/2027 is Out, call 09017730052 To Apply and further admission assistance. Call Dr Martins +2349017730052 or WhatsApp 08169753031.

description: Zamfara State School of Nursing and Midwifery, Gusau Admission Form 2026/2027 is Out, call 09017730052 To Apply and further admission assistance. Call Dr Martins +2349017730052 or WhatsApp 08169753031.
DOI: 10.15468/dl.p4x3pg
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Bodianus cylindriatus"
 ]
}

 The dataset includes 17 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004239-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18814450
title: malva_trifida_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18814449
title: malva_trifida_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.18814444
title: Air Quality Monitoring and Prediction System

description: This dataset was generated as part of an IoT-based Air Quality Monitoring and Prediction System designed to collect, analyze, and evaluate environmental parameters in real time. The system integrates multiple sensors with a microcontroller platform to measure air quality indicators such as particulate matter, gas concentration, temperature, and humidity. The collected data is transmitted to a cloud platform for storage and visualization, enabling continuous environmental monitoring.

The dataset contains time-stamped sensor readings recorded at regular intervals and reflects real-world atmospheric conditions from the deployment location. It is structured in CSV format for ease of use and compatibility with data analysis tools and machine learning frameworks. The data can be utilized for air quality assessment, trend analysis, anomaly detection, and predictive modeling.

This dataset supports the development and evaluation of machine learning models aimed at forecasting air quality levels. It is particularly useful for researchers working in environmental monitoring, smart city applications, IoT systems, and environmental data analytics. The dataset may also assist in academic projects, research experiments, and comparative performance studies of classification and regression algorithms.

By making this dataset publicly available, we aim to promote transparency, reproducibility, and further research in the domain of intelligent environmental monitoring systems.
DOI: 10.5281/zenodo.18814443
title: Air Quality Monitoring and Prediction System

description: This dataset was generated as part of an IoT-based Air Quality Monitoring and Prediction System designed to collect, analyze, and evaluate environmental parameters in real time. The system integrates multiple sensors with a microcontroller platform to measure air quality indicators such as particulate matter, gas concentration, temperature, and humidity. The collected data is transmitted to a cloud platform for storage and visualization, enabling continuous environmental monitoring.

The dataset contains time-stamped sensor readings recorded at regular intervals and reflects real-world atmospheric conditions from the deployment location. It is structured in CSV format for ease of use and compatibility with data analysis tools and machine learning frameworks. The data can be utilized for air quality assessment, trend analysis, anomaly detection, and predictive modeling.

This dataset supports the development and evaluation of machine learning models aimed at forecasting air quality levels. It is particularly useful for researchers working in environmental monitoring, smart city applications, IoT systems, and environmental data analytics. The dataset may also assist in academic projects, research experiments, and comparative performance studies of classification and regression algorithms.

By making this dataset publicly available, we aim to promote transparency, reproducibility, and further research in the domain of intelligent environmental monitoring systems.
DOI: 10.6084/m9.figshare.31436824
title: <i>Dataset for:</i><b>Enhanced Antitumor Efficacy of Combined PTC596 and PD1 Blockade in Hepatocellular Carcinoma</b>

description: This dataset contains the processed RNA-sequencing data generated for the study "Enhanced Antitumor Efficacy of Combined PTC596 and PD1 Blockade in Hepatocellular Carcinoma". The data supports the findings in <b>Supplementary Figure 2 (In vitro)</b> and <b>Figure 5 / Supplementary Figure 7 (In vivo)</b>.<b>Files included in this dataset:</b><br><b>1. In Vitro Experiments (HepG2 and HCCLM3 cells):</b>InVitro_gene_count_matrix.xlsx: Raw read counts for differential expression analysis.InVitro_gene_fpkm.xlsx: Normalized gene expression levels.(Includes transcript counts and QC files)<b>2. In Vivo Experiments (H22 tumor-bearing mice):</b>InVivo_gene_count.xlsx: Raw read counts from tumor tissues.InVivo_gene_fpkm.xlsx: Normalized gene expression levels from tumor tissues.InVivo_data_table.xlsx: Sample grouping information.
DOI: 10.6084/m9.figshare.31436824.v1
title: <i>Dataset for:</i><b>Enhanced Antitumor Efficacy of Combined PTC596 and PD1 Blockade in Hepatocellular Carcinoma</b>

description: This dataset contains the processed RNA-sequencing data generated for the study "Enhanced Antitumor Efficacy of Combined PTC596 and PD1 Blockade in Hepatocellular Carcinoma". The data supports the findings in <b>Supplementary Figure 2 (In vitro)</b> and <b>Figure 5 / Supplementary Figure 7 (In vivo)</b>.<b>Files included in this dataset:</b><br><b>1. In Vitro Experiments (HepG2 and HCCLM3 cells):</b>InVitro_gene_count_matrix.xlsx: Raw read counts for differential expression analysis.InVitro_gene_fpkm.xlsx: Normalized gene expression levels.(Includes transcript counts and QC files)<b>2. In Vivo Experiments (H22 tumor-bearing mice):</b>InVivo_gene_count.xlsx: Raw read counts from tumor tissues.InVivo_gene_fpkm.xlsx: Normalized gene expression levels from tumor tissues.InVivo_data_table.xlsx: Sample grouping information.