cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18529057
title: SuperDARN data in netCDF format (2020-Aug)

description: 2020-Aug SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7309073
title: SuperDARN data in netCDF format (2020-Aug)

description: 2020-Aug SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.17632/tcvbsw3f4y
title: Stable isotopic compositions of the Siang-Brahmaputra system

description: Stable isotopic compositions of the Siang-Brahmaputra system
DOI: 10.17632/tcvbsw3f4y.2
title: Stable isotopic compositions of the Siang-Brahmaputra system

description: Stable isotopic compositions of the Siang-Brahmaputra system
DOI: 10.17632/2895dk9twh.1
title: Tolerance Mechanisms and Metabolomic Profiling of Kosteletzkya pentacarpos in Saline Environments

description: Kosteletzkya pentacarpos is a halophyte with significant potential for ecological restoration and phytoremediation in saline environments. This study investigated the growth, biochemical response, metabolomic profiling and seed germination of plants under increasing sodium chloride (NaCl) concentrations, from 0 to 0.3 M. Several growth parameters such as plant height, root length, fresh weight as well as reproductive traits were studied. Higher NaCl concentrations resulted in a significant reduction in morphological parameters. Germination tests revealed that seeds were affected by the highest salt concentrations tested, starting with 0.15 M NaCl and that seeds from plants exposed to 0.05 M NaCl exhibited higher germination rates than seeds from the control conditions. Levels of osmolytes (proline and glycine betaine) and oxidative stress markers (malondialdehyde) increased in response to salinity. Significant alterations in ionic balance, were also detected, including increased sodium and chloride accumulation and potassium retention. For the first time, a metabolomic analysis of K. pentacarpos is presented, providing key insights into the metabolites involved in salinity tolerance. The metabolomic profiling revealed significant changes in carbohydrates, amino acids, and other metabolites, suggesting metabolic reprogramming to mitigate salinity stress. This study emphasizes K. pentacarpos adaptive mechanisms, including osmoprotectant accumulation, ionic regulation and metabolomic adjustments, to tolerate moderate salinity. Understanding these responses is essential for advancing the use of K. pentacarpos in saline agriculture and environmental management.
DOI: 10.5281/zenodo.18525614
title: A Convolutional Method for Fitting Sharply Peaked  Distributions with Long Tails Paper Data

description: Data used for the analysis in the paper. May be inserted into the corresponding places in the github directory as to run the analysis.
DOI: 10.5281/zenodo.18525615
title: A Convolutional Method for Fitting Sharply Peaked  Distributions with Long Tails Paper Data

description: Data used for the analysis in the paper. May be inserted into the corresponding places in the github directory as to run the analysis.
DOI: 10.5281/zenodo.14837658
title: Assessment of relationship between body image perception and food habits among medical students at a teaching hospital in Northern Karnataka, India

description: This is a dataset containing results from our study titled " Assessment of relationship between body image perception and food habits among medical students at a teaching hospital in Northern Karnataka, India "
DOI: 10.34740/kaggle/dsv/14777725
title: SEC EDGAR Filings Index
DOI: 10.5281/zenodo.18529272
title: DADOS DA PESQUISA OS PRIMÓDIOS DAS DISCUSSÕES SOBRE O USO DO CHATGPT NA EDUCAÇÃO

description: Trata-se dos autores incluídos na pesquisa sobre as discussões iniciais acerca do ChatGPT aplicado à educação, cujo objetivo geral foi analisar as evidências científicas sobre a interface entre ChatGPT e educação no ano inicial de sua utilização.
DOI: 10.5281/zenodo.18529273
title: DADOS DA PESQUISA OS PRIMÓDIOS DAS DISCUSSÕES SOBRE O USO DO CHATGPT NA EDUCAÇÃO

description: Trata-se dos autores incluídos na pesquisa sobre as discussões iniciais acerca do ChatGPT aplicado à educação, cujo objetivo geral foi analisar as evidências científicas sobre a interface entre ChatGPT e educação no ano inicial de sua utilização.
DOI: 10.15468/dl.pwtr25
title: Occurrence Download

description: A dataset containing 15763 records in GBIF matching the query:

 SELECT gbifid, datasetkey, specieskey, kingdom, phylum, class, "order", family, genus, species, scientificname, decimallatitude, decimallongitude, eventdate, institutioncode, "year" AS obs_year, basisofrecord, coordinateuncertaintyinmeters, issue
 FROM occurrence
 WHERE
 decimallatitude IS NOT NULL
 AND decimallongitude IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND coordinateuncertaintyinmeters IS NOT NULL
 AND coordinateuncertaintyinmeters &gt; 0
 AND coordinateuncertaintyinmeters &lt;= 200.0
 AND decimallatitude &gt;= 33.06103686093294
 AND decimallatitude &lt;= 37.42857426825602
 AND decimallongitude &gt;= 50.095048890307076
 AND decimallongitude &lt;= 57.564121794054664
 AND GBIF_Within('POLYGON ((57.564122 33.061037, 57.564122 37.428574, 50.095049 37.428574, 50.095049 33.061037, 57.564122 33.061037))', decimallatitude, decimallongitude) = TRUE
 

 The dataset's 15763 records were derived from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001777-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nx9t9g
title: Occurrence Download

description: A dataset containing 225860 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lampetra",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 225860 records from 399 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001768-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18529331
title: ERA5 reanalysis data for Upshot-Knothole Nancy nuclear test (24-27 March 1953)

description: Subsetted ERA5 model-level reanalysis data (T, U, V, omega, surface pressure) for the Nevada Test Site region. Lat 35-42°N, lon 120-110°W, 137 hybrid levels, hourly timesteps. 24 NetCDF files covering 24-27 March 1953. Preprocessed for use with NuclearDetonation.jl.
DOI: 10.5281/zenodo.18529330
title: ERA5 reanalysis data for Upshot-Knothole Nancy nuclear test (24-27 March 1953)

description: Subsetted ERA5 model-level reanalysis data (T, U, V, omega, surface pressure) for the Nevada Test Site region. Lat 35-42°N, lon 120-110°W, 137 hybrid levels, hourly timesteps. 24 NetCDF files covering 24-27 March 1953. Preprocessed for use with NuclearDetonation.jl.
DOI: 10.15468/dl.fy6g6c
title: Occurrence Download

description: A dataset containing 4950 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is one of (Benin, Togo, Ghana)",
 "OccurrenceStatus is Present",
 "TaxonKey is Afzelia africana",
 "Year 1970-2026"
 ]
}

 The dataset includes 4950 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001784-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14777552
title: MLB Pitcher Arsenal 2020-2025
DOI: 10.34740/kaggle/dsv/14777763
title: MLB Pitcher Arsenal 2020-2025
DOI: 10.15468/dl.7arf2m
title: Occurrence Download

description: A dataset containing 1571 records in GBIF matching the query:

 SELECT gbifid, datasetkey, specieskey, kingdom, phylum, class, "order", family, genus, species, scientificname, decimallatitude, decimallongitude, eventdate, institutioncode, "year" AS obs_year, basisofrecord, coordinateuncertaintyinmeters, issue
 FROM occurrence
 WHERE
 decimallatitude IS NOT NULL
 AND decimallongitude IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND coordinateuncertaintyinmeters IS NOT NULL
 AND coordinateuncertaintyinmeters &gt; 0
 AND coordinateuncertaintyinmeters &lt;= 200.0
 AND decimallatitude &gt;= 33.06103686093294
 AND decimallatitude &lt;= 37.42857426825602
 AND decimallongitude &gt;= 55.661165433674526
 AND decimallongitude &lt;= 63.32053397346014
 AND GBIF_Within('POLYGON ((63.320534 33.061037, 63.320534 37.428574, 55.661165 37.428574, 55.661165 33.061037, 63.320534 33.061037))', decimallatitude, decimallongitude) = TRUE
 

 The dataset's 1571 records were derived from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001781-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q9h6pg
title: Occurrence Download

description: A dataset containing 93532 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Ricinus communis"
 ]
}

 The dataset includes 93532 records from 1053 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001741-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nsy1gc
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009899-160623103540712/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uwkw3u
title: Occurrence Download

description: A dataset containing 561852542 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is EOD – eBird Observation Dataset"
 ]
}

 The dataset includes 561852542 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006028-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eyuf8j
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014420-160311141623029/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dre7qb
title: Occurrence Download

description: A dataset containing 375279838 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Plantae"
 ]
}

 The dataset includes 375279838 records from 8302 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0292490-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0163501.10fu
title: SH0163501.10FU

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/sh0163502.10fu
title: SH0163502.10FU

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/sh0163503.10fu
title: SH0163503.10FU

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/sh0163504.10fu
title: SH0163504.10FU

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/sh0163505.10fu
title: SH0163505.10FU

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/sh0163506.10fu
title: SH0163506.10FU

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/sh0163507.10fu
title: SH0163507.10FU

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/sh0163508.10fu
title: SH0163508.10FU

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.