cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0156858.10fu
title: SH0156858.10FU

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/sh0156859.10fu
title: SH0156859.10FU

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/sh0156860.10fu
title: SH0156860.10FU

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/sh0156861.10fu
title: SH0156861.10FU

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: 10.25502/0zkd-zf95/d
title: Phenotypic data of the 300 diallel crosses and 6 checks evaluated in Abuja and Mokwa under Striga-infestated and optimum environments
DOI: 10.15156/bio/sh0156862.10fu
title: SH0156862.10FU

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/sh0156863.10fu
title: SH0156863.10FU

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/sh0156864.10fu
title: SH0156864.10FU

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: 10.15468/dl.ypbbq4
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((-65.71999 43.25398,-64.54333 43.65025,-61.56339 44.75515,-59.2 45.55224,-59.25137 46.69175,-59.81653 47.35719,-61.10099 46.79737,-62.48167 45.82201,-63.57106 46.02868,-64.46491 45.72465,-64.91571 45.52592,-65.13135 45.19413,-66.42635 44.71091,-66.61472 43.91911,-65.71999 43.25398))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Fuscopannaria leucosticta",
 "Year 2010-2026"
 ]
}

 The dataset includes 60 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014650-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18498907
title: THE INTERACTION OF STATE AND MARKET MECHANISMS IN THE FORMATION OF AN INNOVATIVE ECONOMY

description: This article examines the role of the regions of the Republic of Uzbekistan in creating an institutional environment, supporting innovation, and stimulating research and development activities, as well as the influence of market mechanisms—competition, supply, and demand—on innovation processes. The significance of cooperation between the state and the private sector in innovative development is highlighted, and the theoretical and practical aspects of maintaining a balance between state regulation and market freedom for the sustainable development of an innovative economy are revealed.
DOI: 10.5281/zenodo.18498214
title: SuperDARN data in netCDF format (2014-Apr)

description: 2014-Apr 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.18498906
title: THE INTERACTION OF STATE AND MARKET MECHANISMS IN THE FORMATION OF AN INNOVATIVE ECONOMY

description: This article examines the role of the regions of the Republic of Uzbekistan in creating an institutional environment, supporting innovation, and stimulating research and development activities, as well as the influence of market mechanisms—competition, supply, and demand—on innovation processes. The significance of cooperation between the state and the private sector in innovative development is highlighted, and the theoretical and practical aspects of maintaining a balance between state regulation and market freedom for the sustainable development of an innovative economy are revealed.
DOI: 10.5281/zenodo.6476825
title: SuperDARN data in netCDF format (2014-Apr)

description: 2014-Apr 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: 10.15468/dl.pyx977
title: Occurrence Download

description: A dataset containing 3755 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Chordata",
 "DecimalLatitude is greater than or equal to 34.8313174312504",
 "DecimalLatitude is less than or equal to 34.9211485487495",
 "DecimalLongitude is greater than or equal to -118.656790089957",
 "DecimalLongitude is less than or equal to -118.547291910043",
 "Year is greater than or equal to 1927",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 3755 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014651-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18395764
title: Supplemental files for Proteome-wide discovery of novel diagnostic antigens for coccidioidomycosis

description: Coccidioidomycosis (CM), caused by Coccidioides spp., accounts for a significant proportion of community-acquired pneumonia in endemic regions such as the southwestern United States. However, CM remains underdiagnosed, in part because of the limitations of existing diagnostic assays. There are likely uncharacterized antigens with diagnostic potential in the Coccidioides spp. proteome, however identifying these antigenic proteins from the large and poorly-understood proteomic space poses a significant challenge. PepSeq is a highly-multiplexed serology platform that measures antibody reactivity against a broad range of fully-customizable DNA-barcoded peptide antigens. Here, we develop a 244,000-plex PepSeq library providing proteome-wide representation of Coccidioides spp. We utilize this library to characterize protein and epitope-level antibody reactivity in CM patients, naturally infected pigtail macaques, and healthy human and animal controls. Our analysis revealed a panel of previously unidentified protein antigens, many containing multiple epitopes that were frequently recognized by IgG antibodies in CM patients. A subset of these epitopes were also commonly targeted by IgG in PTMs with CM. We adapted several of these targets into a pooled peptide ELISA that discriminated cases from controls in an independent validation cohort with high accuracy (AUC 0.95). Together, these results demonstrate the power of peptide-based highly-multiplexed serology to discover novel fungal antigens, and successfully identify CM specific epitope-resolved targets for new diagnostic assays.
DOI: 10.5281/zenodo.18395765
title: Supplemental files for Proteome-wide discovery of novel diagnostic antigens for coccidioidomycosis

description: Coccidioidomycosis (CM), caused by Coccidioides spp., accounts for a significant proportion of community-acquired pneumonia in endemic regions such as the southwestern United States. However, CM remains underdiagnosed, in part because of the limitations of existing diagnostic assays. There are likely uncharacterized antigens with diagnostic potential in the Coccidioides spp. proteome, however identifying these antigenic proteins from the large and poorly-understood proteomic space poses a significant challenge. PepSeq is a highly-multiplexed serology platform that measures antibody reactivity against a broad range of fully-customizable DNA-barcoded peptide antigens. Here, we develop a 244,000-plex PepSeq library providing proteome-wide representation of Coccidioides spp. We utilize this library to characterize protein and epitope-level antibody reactivity in CM patients, naturally infected pigtail macaques, and healthy human and animal controls. Our analysis revealed a panel of previously unidentified protein antigens, many containing multiple epitopes that were frequently recognized by IgG antibodies in CM patients. A subset of these epitopes were also commonly targeted by IgG in PTMs with CM. We adapted several of these targets into a pooled peptide ELISA that discriminated cases from controls in an independent validation cohort with high accuracy (AUC 0.95). Together, these results demonstrate the power of peptide-based highly-multiplexed serology to discover novel fungal antigens, and successfully identify CM specific epitope-resolved targets for new diagnostic assays.
DOI: 10.15468/dl.86zw65
title: Occurrence Download

description: A dataset containing 1260282 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "HasCoordinate is true",
 "Year is greater than or equal to 1995",
 "Year is less than or equal to 1999",
 "Geometry POLYGON((-25.0 39.0, 45.0 39.0, 45.0 44.0, -25.0 44.0, -25.0 39.0))"
 ]
}

 The dataset includes 1260282 records from 299 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014613-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e215441
title: Data and Code for "Disemployment Effects of Unemployment Insurance: A Meta-Analysis"

description: We systematically review studies of how unemployment benefits affect unemploy- ment duration. Statistically significant findings are eight times more likely to be published. Correcting for publication bias cuts the average elasticity by a third. Meta-analysis is a data-driven way to aggregate estimates across policy contexts and generalize sufficient statistics methods to compute the global optimal policy. Although existing consumption drop-based approaches typically imply an optimal replacement rate near zero, our corrected estimates imply an optimal replacement rate of 28% in the US. We are unable to reject the hypothesis that the “micro” elasticity is equal to the “macro” elasticity.
description: Studies of the effect of unemployment insurance .
DOI: 10.3886/e215441v1
title: Data and Code for "Disemployment Effects of Unemployment Insurance: A Meta-Analysis"

description: We systematically review studies of how unemployment benefits affect unemploy- ment duration. Statistically significant findings are eight times more likely to be published. Correcting for publication bias cuts the average elasticity by a third. Meta-analysis is a data-driven way to aggregate estimates across policy contexts and generalize sufficient statistics methods to compute the global optimal policy. Although existing consumption drop-based approaches typically imply an optimal replacement rate near zero, our corrected estimates imply an optimal replacement rate of 28% in the US. We are unable to reject the hypothesis that the “micro” elasticity is equal to the “macro” elasticity.
description: Studies of the effect of unemployment insurance .
DOI: 10.15468/dl.4yc6v8
title: Occurrence Download

description: A dataset containing 626 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Continent is Africa",
 "Country is South Africa",
 "DatasetKey is one of (Botanical Database of Southern Africa (BODATSA): Botanical Collections, iNaturalist Research-grade Observations)",
 "Geometry POLYGON((32.60893 -27.48166,32.09261 -22.27315,28.47835 -22.86911,17.24836 -29.57947,19.70089 -35.81966,27.51025 -33.91348,32.60893 -27.48166))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "PublishingOrg is one of (c5f7ef70-e233-11d9-a4d6-b8a03c50a862, 28eb1a3f-1c15-4a95-931a-4af90ecb574d)",
 "TaxonKey is Cyphostemma",
 "Year 2006-2026"
 ]
}

 The dataset includes 626 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014654-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25934/pr00012496.0
title: Available datapackage for study 'Using the Multiphase Optimization Strategy (MOST) to Optimize an Intervention to Increase COVID-19 Testing for Black and Latino/Hispanic Frontline Essential Workers'

description: COVID-19 testing is essential to controlling the COVID-19 pandemic to break transmission chains and reduce community transmission. However, Black and Latino/Hispanic populations in lower status frontline essential occupations such as food preparation, retail, building maintenance, personal services, and in-home health care have serious barriers to COVID-19 testing and, therefore, insufficient testing rates. The proposed study will use the multiphase optimization strategy framework to address the problem of low COVID-19 testing rates for this population: We will test the effects of four distinct candidate intervention components and then create an efficient multicomponent made up of the most effective combination of the components that can be rapidly scaled up in community settings to boost COVID-19 testing rates.
DOI: 10.15468/dl.hjbp5s
title: Occurrence Download

description: A dataset containing 3470 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Chordata",
 "DecimalLatitude is greater than or equal to 36.0172714412505",
 "DecimalLatitude is less than or equal to 36.1071025587496",
 "DecimalLongitude is greater than or equal to -120.1573715313",
 "DecimalLongitude is less than or equal to -120.0462464687",
 "Year is greater than or equal to 1927",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 3470 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014655-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h5tr9m
title: Occurrence Download

description: A dataset containing 115 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Chordata",
 "DecimalLatitude is greater than or equal to 35.0491354412504",
 "DecimalLatitude is less than or equal to 35.1389665587496",
 "DecimalLongitude is greater than or equal to -116.889794942411",
 "DecimalLongitude is less than or equal to -116.780005057589",
 "Year is greater than or equal to 1927",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 115 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014657-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2s6bnh
title: Occurrence Download

description: A dataset containing 13708 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Andrena denticulata"
 ]
}

 The dataset includes 13708 records from 143 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014658-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.