cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0201742.10fu
title: SH0201742.10FU

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/sh0201743.10fu
title: SH0201743.10FU

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/sh0201744.10fu
title: SH0201744.10FU

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/sh0201745.10fu
title: SH0201745.10FU

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/sh0201746.10fu
title: SH0201746.10FU

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: 10.3886/e242949
title: Legacy University, Okija Anambra State 2026/27 JUPEB/IJMB Form is out ☎️(08039478772) DR MERCY☎️ (+23408039478772) Direct-Entry Form, Transfer Form, Change of institution form, Change of Course form, Post graduate Diploma form, Masters form

description: Legacy University, Okija Anambra State 2026/27 JUPEB/IJMB Form is out ☎️(08039478772) DR MERCY☎️ (+23408039478772) Direct-Entry Form, Transfer Form, Change of institution form, Change of Course form, Post graduate Diploma form, Masters form, Phd form call ☎️(+23408039478772) for more inquiry and admission assistance.
DOI: 10.15156/bio/sh0201747.10fu
title: SH0201747.10FU

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/sh0201748.10fu
title: SH0201748.10FU

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/sh0201749.10fu
title: SH0201749.10FU

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/sh0201750.10fu
title: SH0201750.10FU

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/sh0201751.10fu
title: SH0201751.10FU

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.7n5q9h
title: Occurrence Download

description: A dataset containing 218884 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Royal BC Museum - Herbarium (V)"
 ]
}

 The dataset includes 218884 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019973-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tge8bs
title: Occurrence Download

description: A dataset containing 222223 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is University of Michigan Museum of Zoology, Division of Reptiles & Amphibians"
 ]
}

 The dataset includes 222223 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019971-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8z9ary
title: Occurrence Download

description: A dataset containing 98124 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Smilax aspera)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 98124 records from 448 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040974-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pw245x
title: Occurrence Download

description: A dataset containing 432 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vespidae",
 "Year is 1957",
 "Continent is Europe",
 "HasCoordinate is true"
 ]
}

 The dataset includes 432 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040999-250920141307145/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/13244889
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.26023/71c2-a6wp-xq0x
title: Holographic Detector for Clouds (HOLODEC) sample-rate binned particle count and concentration data. Version 1.0

description: This dataset contains binned histograms of sample rate counts and concentrations from cloud particles collected during the CSET project using an airborne holographic instrument (HOLODEC) mounted on the NSF/NCAR Gulfstream V (N677F). The timestamp indicates the hologram in which the particle was imaged. The data contains per-hologram total and binned counts and concentrations.
DOI: 10.15468/dl.hygsnw
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gratiola neglecta",
 "Country is Czechia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041001-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.577g7j
title: Occurrence Download

description: A dataset containing 2255 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Bartlettina"
 ]
}

 The dataset includes 2255 records from 100 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041004-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9hxek6
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "BasisOfRecord is Human Observation",
 "Country is one of (Sri Lanka)",
 "TaxonKey is one of (Crocidura goliath, Crocidura hildegardeae, Crocidura poensis, Lemniscomys striatus, Lophuromys sikapusi, Mus musculus, Rattus rattus, Sylvisorex ollula, Mus minutoides, Praomys misonnei, Lophuromys sabunii, Hybomys univittatus, Oenomys hypoxanthus, Stochomys longicaudatus, Atherurus africanus, Cricetomys emini)"
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041003-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/gwk8-b9gp-730n
title: CSET: Holographic Detector for Clouds (HOLODEC) LRT (1sps) binned particle count and concentration data - NetCDF format. Version 1.0

description: This dataset contains averaged and binned histograms of counts and concentrations from cloud particles collected during the CSET project using an airborne holographic instrument (HOLODEC) mounted on the NSF/NCAR Gulfstream V (N677F). The data contains per-second total and binned counts and concentrations.
DOI: 10.5281/zenodo.17161044
title: Corresponding dataset for: "Within-litter variation in maternal care is a key contributor to individual differences in offspring behavior and monoamine neurochemistry in female Long-Evans rats"
DOI: 10.5281/zenodo.17161045
title: Corresponding dataset for: "Within-litter variation in maternal care is a key contributor to individual differences in offspring behavior and monoamine neurochemistry in female Long-Evans rats"
DOI: 10.15468/dl.9tmutr
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gratiola neglecta",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041002-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/6kg67m
title: Replication Data for: "The Origin of the State: Land Productivity or Appropriability? Comment"

description: This is the replication package for "The Origin of the State: Land Productivity or Appropriability? Comment," accepted in 2025 by the Journal of Political Economy.
DOI: 10.26023/a1dv-sew2-7z06
title: Holographic Detector for Clouds (HOLODEC) LRT (1sps) binned particle count and concentration data - CSV format. Version 1.0

description: This dataset contains binned histograms of sample rate counts and concentrations from cloud particles collected during the CSET project using an airborne holographic instrument (HOLODEC) mounted on the NSF/NCAR Gulfstream V (N677F). The data contains 1 second averages of total and binned counts and concentrations. As the HOLODEC collects 3.3 holograms per second, their are either three or four holograms averaged into each second of data.
DOI: 10.15468/dl.4gw5jm
title: Occurrence Download

description: A dataset containing 21036 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Smilax australis)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 21036 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041006-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15657018
title: Supporting Data for: Nudged-Elastic Band Calculations of Polymorph Transitions and Solid-State Reactions in Molecular Crystals

description: The modeling of solid-state transformations, such as polymorphic transitions and chemical reactions in molecular crystals, is vital for many applications including drug design or the development of new synthesis methods. However, a description via nudged-elastic band (NEB) calculations faces several crucial challenges.  First, the automatic initial pathway generation based on a linear interpolation often fails for periodic systems, leading to unrealistic geometries and atomic collisions. Second, the necessary system sizes are typically beyond the scope of density functional theory (DFT) calculations in terms of computational cost, but the associated accuracy is vitally needed. To address these issues, we introduce a hybrid interpolation method that combines linear interpolation for cell parameters with spherical linear interpolation (SLERP) for molecular structures or intramolecular fragments, ensuring smooth and realistic transitions. Moreover, we train and benchmark machine-learned force fields (MLFFs) based on the SO3krates equivariant neural network architecture to accelerate NEB calculations while retaining near-DFT accuracy. We apply our approach to two polymorph transitions and a solid-state Diels-Alder reaction and show that our new interpolation method reliably produces viable initial pathways. The MLFFs are trained on PBE+MBD reference data and reproduce DFT lattice energies with a mean absolute error of 0.4 kJ/mol along the minimum-energy paths. These results highlight the potential of combining advanced interpolation techniques with MLFFs to enable automated, accurate, and efficient exploration of solid-state transformations in molecular crystals.This supporting dataset includes the python code for structure interpolation, the PBE+MBD reference data for all three systems in ASE trajectory files, optimized structures and transition-state estimates in CIF format, as well as initial pathways. The related preprint can be found at https://arxiv.org/abs/2410.10506.
DOI: 10.5281/zenodo.17253311
title: Supporting Data for: Nudged-Elastic Band Calculations of Polymorph Transitions and Solid-State Reactions in Molecular Crystals

description: The modeling of solid-state transformations, such as polymorphic transitions and chemical reactions in molecular crystals, is vital for many applications including drug design or the development of new synthesis methods. However, a description via nudged-elastic band (NEB) calculations faces several crucial challenges.  First, the automatic initial pathway generation based on a linear interpolation often fails for periodic systems, leading to unrealistic geometries and atomic collisions. Second, the necessary system sizes are typically beyond the scope of density functional theory (DFT) calculations in terms of computational cost, but the associated accuracy is vitally needed. To address these issues, we introduce a hybrid interpolation method that combines linear interpolation for cell parameters with spherical linear interpolation (SLERP) for molecular structures or intramolecular fragments, ensuring smooth and realistic transitions. Moreover, we train and benchmark machine-learned force fields (MLFFs) based on the SO3krates equivariant neural network architecture to accelerate NEB calculations while retaining near-DFT accuracy. We apply our approach to two polymorph transitions and a solid-state Diels-Alder reaction and show that our new interpolation method reliably produces viable initial pathways. The MLFFs are trained on PBE+MBD reference data and reproduce DFT lattice energies with a mean absolute error of 0.4 kJ/mol along the minimum-energy paths. These results highlight the potential of combining advanced interpolation techniques with MLFFs to enable automated, accurate, and efficient exploration of solid-state transformations in molecular crystals.This supporting dataset includes the python code for structure interpolation, the PBE+MBD reference data for all three systems in ASE trajectory files, optimized structures and transition-state estimates in CIF format, as well as initial pathways. The related preprint can be found at https://arxiv.org/abs/2410.10506.
DOI: 10.26023/n3m4-1a0t-ze0n
title: ASOS 1-minute Data. Version 1.0

description: This data set contains the 1-minute resolution observations from the Automated Surface Observing System (ASOS) network of ~860 stations in the contiguous United States. These data were collected and archived by the National Centers for Environmental Information (NCEI; formerly the National Climatic Data Center). These data are provided as is, NCAR/EOL has conducted no processing or quality control on these data.