cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.27950703.v1
title: Lepidoptera New Genes - Hoile et al

description: This study assesses the tempo and mode of new gene evolution at the emergence of the insect order Lepidoptera. We determined the relative contribution of different mechanisms of new gene genesis including duplication and sequence divergence, de novo gene genesis, and horizontal gene transfer. We describe the evolution of two specific gene families which were retained and duplicated across Lepidoptera after emerging on the ancestral branch.<br><br>All major data and code used in this study are available on this figshare repository. If there are any queries about any of the files please do not hesitate to contact any of the authors.
DOI: 10.15468/dl.upyzm3
title: Occurrence Download

description: A dataset containing 184122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Waarnemingen.be - Non-native animal occurrences in Flanders and the Brussels Capital Region, Belgium",
 "Year 2024-2024"
 ]
}

 The dataset includes 184122 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002864-250218110819086/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.28449269
title: <b>Synthetic Bone Marrow </b><b>Images</b><b> Augment Real Samples in Developing Acute Myeloid Leukemia Microscopy Classification Models</b>

description: Synthetic Bone marrow Smears using GANs
DOI: 10.18150/mr0qh5
title: PRELUDIUM 4/2021 AT - results of qualitative and quantitative analysis of amino acids in egg samples depending on the type of fodder, UHPLC

description: The database contains the results of the qualitative and quantitative analysis of amino acids. Amino acids were analyzed in eggs of laying hens in terms of the effect of different types of feed mixtures. The database includes automatically generated reports from LabSolution software and results in Excel files, obtained by means of Shimadzu UHPLC. The report contains a chromatogram, as well as concentrations and retention times of individual amino acids. In addition, the database contains the results of the total protein of the eggs tested.
DOI: 10.15468/dl.gn5pn9
title: Occurrence Download

description: A dataset containing 459 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Nymphargus griffithsi (Goin, 1961)"
 ]
}

 The dataset includes 459 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002869-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6mczn9
title: Occurrence Download

description: A dataset containing 78 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Evadne anonyx Sars, 1897"
 ]
}

 The dataset includes 78 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002870-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fsnvb9
title: Occurrence Download

description: A dataset containing 8206 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Spodoptera litura (Fabricius, 1775)"
 ]
}

 The dataset includes 8206 records from 106 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002871-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.74nvyy
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cylindropuntia rosea (DC.) Backeb.",
 "Country is Spain",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002872-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yguuhs
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ajuga pyramidalis L.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 19 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002873-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p4w58v
title: Occurrence Download

description: A dataset listing the 12 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-8.37698 42.5771,-8.17738 42.56074,-8.25365 42.79307,-8.43425 42.78313,-8.47517 42.65922,-8.37698 42.5771))",
 "TaxonKey is one of (Discoglossus galganoi Capula, Nascetti, Lanza, Bullini & Crespo, 1985, Falco subbuteo Linnaeus, 1758, Gallinago gallinago (Linnaeus, 1758), Anthus campestris (Linnaeus, 1758), Caprimulgus europaeus Linnaeus, 1758, Circus cyaneus (Linnaeus, 1766), Lanius collurio Linnaeus, 1758, Lullula arborea (Linnaeus, 1758), Myotis myotis (Borkhausen, 1797), Oenanthe oenanthe (Linnaeus, 1758), Rhinolophus ferrumequinum (Schreber, 1774), Sphagnum pylaesii Brid., Sylvia undata (Boddaert, 1783), Tetrax tetrax (Linnaeus, 1758))",
 "Year 2005-2025"
 ]
}

 The dataset's 12 records were derived from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002868-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4h3kwm
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cymbopogon citratus (DC.) Stapf",
 "Country is Martinique",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 6 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002876-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wkry74
title: Occurrence Download

description: A dataset containing 1560 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-8.37698 42.5771,-8.17738 42.56074,-8.25365 42.79307,-8.43425 42.78313,-8.47517 42.65922,-8.37698 42.5771))",
 "TaxonKey is one of (Discoglossus galganoi Capula, Nascetti, Lanza, Bullini & Crespo, 1985, Falco subbuteo Linnaeus, 1758, Gallinago gallinago (Linnaeus, 1758), Anthus campestris (Linnaeus, 1758), Caprimulgus europaeus Linnaeus, 1758, Circus cyaneus (Linnaeus, 1766), Lanius collurio Linnaeus, 1758, Lullula arborea (Linnaeus, 1758), Myotis myotis (Borkhausen, 1797), Oenanthe oenanthe (Linnaeus, 1758), Rhinolophus ferrumequinum (Schreber, 1774), Sphagnum pylaesii Brid., Sylvia undata (Boddaert, 1783), Tetrax tetrax (Linnaeus, 1758))",
 "Year 2005-2025"
 ]
}

 The dataset includes 1560 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002877-250218110819086/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.28448582
title: Data.xlsx

description: This research is on Artificial intelligence based assistive device for blind individuals
DOI: 10.15468/dl.6d92vd
title: Occurrence Download

description: A dataset containing 4173 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((125.00691 32.62717,129.6266 32.62717,129.6266 39.27915,125.00691 39.27915,125.00691 32.62717))",
 "OccurrenceStatus is Present",
 {
 "or" : [
 "TaxonKey is Trachemys scripta (Thunberg In Schoepff, 1792)",
 "TaxonKey is Lithobates catesbeianus (Shaw, 1802)"
 ]
 }
 ]
}

 The dataset includes 4173 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0192859-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14889715
title: DBS (Percept) and TDT Recordings

description: DBS (Percept) and TDT Recordings, to accompany a Timing Reconstruction Algorithm.

Code also attached here.

See paper.

See github for latest version of code.
DOI: 10.5281/zenodo.14899198
title: Heat stress driven by climate warming and ENSO variability
DOI: 10.5281/zenodo.14899199
title: Heat stress driven by climate warming and ENSO variability
DOI: 10.5281/zenodo.14899211
title: Drone Garbage Detection Dataset

description: Description:







This comprehensive Drone Garbage Detection Dataset is designed for the classification, detection, and analysis of waste materials found in coastal areas, specifically for environmental monitoring and recycling efforts. It contains drone-captured images of various waste types scattered on beaches, making it an invaluable resource for training machine learning models. The dataset is structured to seamlessly integrate with the YOLOv8 object detection model.

 







Download Dataset

 









Key Applications



Recycling Automation: The dataset supports the development of systems that can automate the sorting of recyclable waste materials, significantly reducing manual labor and enhancing recycling efforts.

Environmental Monitoring: The drone-captured images provide real-time data that can be used for monitoring pollution levels in coastal areas, helping organizations to track waste accumulation and its environmental impact.

Sustainability Research: With detailed waste categorization, researchers can use this dataset to analyze trends in waste generation, informing future waste management strategies.


Dataset Structure

The dataset is divided into three key subsets:



Training Set: Includes the majority of the images, used to train machine learning models.

Testing Set: Reserved for testing the trained models to assess performance.

Validation Set: Used for fine-tuning models and preventing overfitting during training.


Image and Annotation Details



Format: All images are in JPEG format for easy integration with image-processing libraries.

Resolution: The images are high-resolution, allowing for detailed object detection.

Annotation: Each image comes with corresponding labels that define the waste category, making it suitable for object detection models.

Naming Convention: The image file names follow a structured format, indicating the source video and frame number from which they were extracted. This allows users to easily trace the original context of the waste material captured by the drone.


Conclusion

This drone garbage detection dataset is a valuable resource for both AI researchers and environmental scientists. By enabling accurate waste classification and trend analysis, it paves the way for better waste management strategies and contributes to global sustainability efforts.

This dataset is sourced from Kaggle.
DOI: 10.5281/zenodo.14899210
title: Drone Garbage Detection Dataset

description: Description:







This comprehensive Drone Garbage Detection Dataset is designed for the classification, detection, and analysis of waste materials found in coastal areas, specifically for environmental monitoring and recycling efforts. It contains drone-captured images of various waste types scattered on beaches, making it an invaluable resource for training machine learning models. The dataset is structured to seamlessly integrate with the YOLOv8 object detection model.

 







Download Dataset

 









Key Applications



Recycling Automation: The dataset supports the development of systems that can automate the sorting of recyclable waste materials, significantly reducing manual labor and enhancing recycling efforts.

Environmental Monitoring: The drone-captured images provide real-time data that can be used for monitoring pollution levels in coastal areas, helping organizations to track waste accumulation and its environmental impact.

Sustainability Research: With detailed waste categorization, researchers can use this dataset to analyze trends in waste generation, informing future waste management strategies.


Dataset Structure

The dataset is divided into three key subsets:



Training Set: Includes the majority of the images, used to train machine learning models.

Testing Set: Reserved for testing the trained models to assess performance.

Validation Set: Used for fine-tuning models and preventing overfitting during training.


Image and Annotation Details



Format: All images are in JPEG format for easy integration with image-processing libraries.

Resolution: The images are high-resolution, allowing for detailed object detection.

Annotation: Each image comes with corresponding labels that define the waste category, making it suitable for object detection models.

Naming Convention: The image file names follow a structured format, indicating the source video and frame number from which they were extracted. This allows users to easily trace the original context of the waste material captured by the drone.


Conclusion

This drone garbage detection dataset is a valuable resource for both AI researchers and environmental scientists. By enabling accurate waste classification and trend analysis, it paves the way for better waste management strategies and contributes to global sustainability efforts.

This dataset is sourced from Kaggle.
DOI: 10.34808/hd3b-0383
title: Representative open-circuit potential vs. time and potentiodynamic polarization data recorded for uncoated Ti13Zr13Nb and 136_600_sin_300 specimens and XRD results for uncoated and all coated specimens

description: This dataset includes open-circuit potential and potentiodynamic polarization data for uncoated and MAO/UMAO-treated Ti13Zr13Nb specimens. It also contains XRD phase analysis results. The study explores the impact of ultrasound-assisted MAO on coating properties, including morphology, composition, thickness, hardness, corrosion resistance, and cytocompatibility for biomedical applications.
DOI: 10.5281/zenodo.14898872
title: Data for "Quality Characteristics for Software in HPC Environments: A Systematic Literature Review"

description: This dataset includes the extracted data from the included publications of the systematic literature review presented in "Quality Characteristics for Software in HPC Environments: A Systematic Literature Review".
DOI: 10.5281/zenodo.14898873
title: Data for "Quality Characteristics for Software in HPC Environments: A Systematic Literature Review"

description: This dataset includes the extracted data from the included publications of the systematic literature review presented in "Quality Characteristics for Software in HPC Environments: A Systematic Literature Review".
DOI: 10.5281/zenodo.14899302
title: Friend or foe: A mosquito parasite with mixed transmission mode displays mutualistic traits promoting oogenesis

description: Theoretical and empirical data suggest that mutualistic traits are more often selected in vertically transmitted symbionts while parasitic traits are favored by horizontal transmission. However, selection of such traits remains unclear in symbionts combining both transmission modes. In this study, we evidenced that Ascogregarina taiwanensis, previously known as a weak parasite of mosquitoes with a horizontal transmission mode, has acquired mutualistic traits favoring embryogenesis and extending the egg laying period. Meanwhile we evidenced that most parasites are pseudo-vertically transmitted by females to their progeny while being released in oviposition sites. Gene expression of mosquitoes and their parasite are shifted during early oogenesis toward an increased nitrogen metabolism, blood waste detoxification and egg development signals. This led to a better assimilation of blood proteins that are mandatory for oogenesis. It constitutes an empirical example where mutualistic traits co-occur with parasitic ones for a microorganism showing a mixed transmission mode. 

The deposit includes transcriptome and analysis for both mosquitoes and parasites as much as results from related experiments.
DOI: 10.25416/edgehill.28444574
title: Investigating stakeholder perception of the term 'employability': research data

description: This dataset contains details of the research questions used to investigate the understanding of the term ‘employability’ amongst stakeholders of education studies programmes at a North-West post-92 university in England. Due to the terms of participants’ consent, supporting data cannot be made openly available.The data was collected between January 2022 and November 2022This data will be linked to the publication when published.Overarching themes identified from the research are also provided.
DOI: 10.25416/edgehill.28444574.v1
title: Investigating stakeholder perception of the term 'employability': research data

description: This dataset contains details of the research questions used to investigate the understanding of the term ‘employability’ amongst stakeholders of education studies programmes at a North-West post-92 university in England. Due to the terms of participants’ consent, supporting data cannot be made openly available.The data was collected between January 2022 and November 2022This data will be linked to the publication when published.Overarching themes identified from the research are also provided.
DOI: 10.15156/bio/sh0208820.10fu
title: SH0208820.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0208821.10fu
title: SH0208821.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0208822.10fu
title: SH0208822.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0208823.10fu
title: SH0208823.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0208824.10fu
title: SH0208824.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.