cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14056065
title: Phasic Dopamine Release

description: Fast-scan cyclic voltammograms (FSCV) raw data were obtained from the Laboratory of Central Nervous System of the Federal University of Parana (UFPR) at Curitiba, Brazil, and from D. Robinson’s Laboratory of the University of North Carolina (UNC) at Chapel Hill, United States of America. The images were generated from 30 different experimental records with a total of 1005 electrically evoked dopamine release. Each record has dopamine release evoked with different magnitude of electrical stimulation, resulting in different pattern of form and intensity. All experiments were performed in accordance with the NIH Guide for the Care and Use of Laboratory Animals with procedures approved by the Institutional Animal Care and Use Committee of the University of North Carolina, and the Institutional Ethics Committee for Animal Experimentation of the Federal University of Parana (Protocol 638).

This new dataset version is composed of images generated from all these experimental records, which include those in the version 1 – 2018. Unlike the first version, the new one has not only phasic dopamine release images, but also entire images with no DA release. In total there are 2010 images, 1005 of each of these classes, with resolution of 875×656 pixels representing a 20 seconds recording. During the generation of these FSCV images, a background subtraction is commonly used before applying a fake color palette. Normally for each image, one column or more columns are selected to subtract the values from the others. In the case of the first version of the dataset, this process was done manually during its generation. In this new one, the process is done automatically, choosing 3 different background positions: the Background A was selected from a column at the beginning of each image (0.5 seconds), the Background B from the middle of each image (10 seconds), and the Background C from the end of each image (19.5 seconds).

These images with different background end up generating different results. Thus it is possible to explore different approaches of training and testing, since for each DA release 3 images were generated. Each image containing DA was manually labeled with the approximated information of each release interval and peak. All images were divided into 3 folds with same amount of samples from each of the two classes: (1) phasic DA release images and (2) non-release images. 

The full details are in our papers [  https://doi.org/10.1016/j.compbiomed.2019.103466 ]  and [ http://dx.doi.org/10.1109/IWSSIP.2018.8439339 ].
DOI: 10.5281/zenodo.14056066
title: Phasic Dopamine Release

description: Fast-scan cyclic voltammograms (FSCV) raw data were obtained from the Laboratory of Central Nervous System of the Federal University of Parana (UFPR) at Curitiba, Brazil, and from D. Robinson’s Laboratory of the University of North Carolina (UNC) at Chapel Hill, United States of America. The images were generated from 30 different experimental records with a total of 1005 electrically evoked dopamine release. Each record has dopamine release evoked with different magnitude of electrical stimulation, resulting in different pattern of form and intensity. All experiments were performed in accordance with the NIH Guide for the Care and Use of Laboratory Animals with procedures approved by the Institutional Animal Care and Use Committee of the University of North Carolina, and the Institutional Ethics Committee for Animal Experimentation of the Federal University of Parana (Protocol 638).

This new dataset version is composed of images generated from all these experimental records, which include those in the version 1 – 2018. Unlike the first version, the new one has not only phasic dopamine release images, but also entire images with no DA release. In total there are 2010 images, 1005 of each of these classes, with resolution of 875×656 pixels representing a 20 seconds recording. During the generation of these FSCV images, a background subtraction is commonly used before applying a fake color palette. Normally for each image, one column or more columns are selected to subtract the values from the others. In the case of the first version of the dataset, this process was done manually during its generation. In this new one, the process is done automatically, choosing 3 different background positions: the Background A was selected from a column at the beginning of each image (0.5 seconds), the Background B from the middle of each image (10 seconds), and the Background C from the end of each image (19.5 seconds).

These images with different background end up generating different results. Thus it is possible to explore different approaches of training and testing, since for each DA release 3 images were generated. Each image containing DA was manually labeled with the approximated information of each release interval and peak. All images were divided into 3 folds with same amount of samples from each of the two classes: (1) phasic DA release images and (2) non-release images. 

The full details are in our papers [  https://doi.org/10.1016/j.compbiomed.2019.103466 ]  and [ http://dx.doi.org/10.1109/IWSSIP.2018.8439339 ].
DOI: 10.15468/dl.abtb8a
title: Occurrence Download

description: A dataset containing 2659281 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "GadmGid is one of (GBR.1_1, GBR.4_1, GBR.3_1)",
 "TaxonKey is Plantae",
 "Year 2011-2013"
 ]
}

 The dataset includes 2659281 records from 166 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002965-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vqtsbm
title: Occurrence Download

description: A dataset containing 3795 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "ScientificName is Odonata",
 "HasCoordinate is True"
 ]
}

 The dataset includes 3795 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002983-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14056110
title: ETM-EQUIPMENT TECHNOLOGIES MATERIALS

description: ETM-EQUIPMENT TECHNOLOGIES MATERIALS
DOI: 10.5281/zenodo.14056111
title: ETM-EQUIPMENT TECHNOLOGIES MATERIALS

description: ETM-EQUIPMENT TECHNOLOGIES MATERIALS
DOI: 10.5281/zenodo.11484354
title: Impact of Metformin vs SGLT-2i on urinary parameters
DOI: 10.5281/zenodo.11484355
title: Impact of Metformin vs SGLT-2i on urinary parameters
DOI: 10.15468/dl.7zbtay
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "DatasetKey is Bengal Tiger (Panthera tigris) Sighting based on Photographs from Facebook in India",
 "GadmGid is IND.36.15_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Panthera tigris tigris",
 "Year 1000-2024"
 ]
}

 The dataset's 1 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002972-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5rmzc7
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Philippines",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Myotis rufopictus (Waterhouse, 1845)"
 ]
}

 The dataset includes 18 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002985-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9763es
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Philippines",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Philetor brachypterus (Temminck, 1840)"
 ]
}

 The dataset includes 53 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002986-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p5vc44
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Philippines",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Phoniscus jagorii (Peters, 1866)"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002988-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4d9nsw
title: Occurrence Download

description: A dataset containing 1494 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Cybianthus detergens Mart., Weigeltia detergens (Mart.) Mart.)"
 ]
}

 The dataset includes 1494 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002989-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rwwe7r
title: Occurrence Download

description: A dataset containing 1494 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Cybianthus detergens Mart., Weigeltia detergens (Mart.) Mart.)"
 ]
}

 The dataset includes 1494 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002990-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14051160
title: Comparison Results for Global Optimization Solvers Using a MIMO System With Two, Three and Four Active Layers as a Benchmark

description: Benchmark data for GPU-based interval optimization of a simulated MIMO system with two, three and four active layers. We compare popular optimization tools from C-XSC and GNU Octave to purely brute-force based techniques for the GPU. Execution times were measured in seconds.
DOI: 10.5281/zenodo.14051161
title: Comparison Results for Global Optimization Solvers Using a MIMO System With Two, Three and Four Active Layers as a Benchmark

description: Benchmark data for GPU-based interval optimization of a simulated MIMO system with two, three and four active layers. We compare popular optimization tools from C-XSC and GNU Octave to purely brute-force based techniques for the GPU. Execution times were measured in seconds.
DOI: 10.5281/zenodo.14056125
title: betancur_QC_20241105.xlsx
DOI: 10.5281/zenodo.14056126
title: betancur_QC_20241105.xlsx
DOI: 10.15468/dl.zxu9z8
title: Occurrence Download

description: A dataset containing 129 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Denmark",
 "ScientificName is Odonata",
 "HasCoordinate is True"
 ]
}

 The dataset includes 129 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002993-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.brdad2
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Belgium",
 "ScientificName is Odonata",
 "HasCoordinate is True"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002992-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ztpyes
title: Occurrence Download

description: A dataset containing 15548 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hippoglossus hippoglossus (Linnaeus, 1758)"
 ]
}

 The dataset includes 15548 records from 93 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002994-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0183138.10fu
title: SH0183138.10FU

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/sh0183139.10fu
title: SH0183139.10FU

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/sh0183140.10fu
title: SH0183140.10FU

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/sh0183141.10fu
title: SH0183141.10FU

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/sh0183142.10fu
title: SH0183142.10FU

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/sh0183143.10fu
title: SH0183143.10FU

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/sh0183144.10fu
title: SH0183144.10FU

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/sh0183145.10fu
title: SH0183145.10FU

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/sh0183146.10fu
title: SH0183146.10FU

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/sh0183147.10fu
title: SH0183147.10FU

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.