cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1402753.10fu
title: SH1402753.10FU

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/sh1402761.10fu
title: SH1402761.10FU

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/sh1402762.10fu
title: SH1402762.10FU

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/sh1402765.10fu
title: SH1402765.10FU

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/sh1402769.10fu
title: SH1402769.10FU

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/sh1402770.10fu
title: SH1402770.10FU

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/sh1402771.10fu
title: SH1402771.10FU

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/sh1402773.10fu
title: SH1402773.10FU

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: 10.17028/rd.lboro.30178018
title: Underlying data: Enhancing incremental capacity and differential voltage diagnostics for lithium-ion battery cells connected in parallel

description: Underlying experimental data, models and analysis for the journal paper Enhancing incremental capacity and differential voltage diagnostics for lithium-ion battery cells connected in parallel.Article abstractVoltage profile diagnostic techniques such as Incremental Capacity Analysis (ICA) and Differential Voltage Analysis (DVA) are powerful tools that can extract degradation modes directly from cell voltage data using measured half-cell voltage profiles and simple models. As multiple individual cells are connected in parallel, cell-to-cell variations and cell interconnection resistances will alter the current distribution and measured voltage, blending and smoothing features in the voltage profile, impacting degradation diagnostics. This work experimentally investigates the application of voltage profile diagnostics on 16 NMC811/Graphite 21700 cells connected in parallel. Experimental results show that whilst the influence of cell-to-cell variation is small for unaged cells, the influence of cell interconnection resistance creates inhomogeneous current distribution between parallel cells which can significantly reduce the accuracy of ICA and DVA, even at low C-rates of C/25, due to reduced definition of degradation features caused by a distribution of phase transitions between cells. This effect is most significant in ‘U-shape’ parallel strings where the positive and negative connections are located close to the same cell, compared to ‘Z-shape’ where the connections are at opposite ends. A numerical model is presented and validated to quantify inhomogeneous current distribution at low C-rates. A simple voltage fitting process is introduced and validated to compensate for these effects by conducting a resistance based voltage shift prior to fitting half-cell voltage profiles to obtain a corrected low C-rate voltage profile, improving the accuracy of degradation diagnostics in parallel cells.© the authors
DOI: 10.17028/rd.lboro.30178018.v1
title: Underlying data: Enhancing incremental capacity and differential voltage diagnostics for lithium-ion battery cells connected in parallel

description: Underlying experimental data, models and analysis for the journal paper Enhancing incremental capacity and differential voltage diagnostics for lithium-ion battery cells connected in parallel.Article abstractVoltage profile diagnostic techniques such as Incremental Capacity Analysis (ICA) and Differential Voltage Analysis (DVA) are powerful tools that can extract degradation modes directly from cell voltage data using measured half-cell voltage profiles and simple models. As multiple individual cells are connected in parallel, cell-to-cell variations and cell interconnection resistances will alter the current distribution and measured voltage, blending and smoothing features in the voltage profile, impacting degradation diagnostics. This work experimentally investigates the application of voltage profile diagnostics on 16 NMC811/Graphite 21700 cells connected in parallel. Experimental results show that whilst the influence of cell-to-cell variation is small for unaged cells, the influence of cell interconnection resistance creates inhomogeneous current distribution between parallel cells which can significantly reduce the accuracy of ICA and DVA, even at low C-rates of C/25, due to reduced definition of degradation features caused by a distribution of phase transitions between cells. This effect is most significant in ‘U-shape’ parallel strings where the positive and negative connections are located close to the same cell, compared to ‘Z-shape’ where the connections are at opposite ends. A numerical model is presented and validated to quantify inhomogeneous current distribution at low C-rates. A simple voltage fitting process is introduced and validated to compensate for these effects by conducting a resistance based voltage shift prior to fitting half-cell voltage profiles to obtain a corrected low C-rate voltage profile, improving the accuracy of degradation diagnostics in parallel cells.© the authors
DOI: 10.15156/bio/sh1402775.10fu
title: SH1402775.10FU

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: 10.5281/zenodo.18206898
title: Notas de leitura do processo "Proyecto de Guardería Infantil, en la parcela número 44 del Polígono de La Candelaria, Zamora [1974-1981]"

description: Notas de leitura do processo “Proyecto de Guardería Infantil, en la parcela número 44 del Polígono de La Candelaria, Zamora [1974-1981]” existente no Archivo Histórico Provincial de Zamora, em Zamora. 

Registo efetuado em janeiro de 2025 no âmbito do projeto de investigação ReARQ.IB – Built Environment Knowledge for Resilient, Sustainable Communities: Understanding Everyday Modern Architecture and Urban Design in the Iberian Peninsula (1939-1985) (ERC GA949686) e publicado online em https://arquitecturaaqui.eu/es/documentacion/expedientes/55284/proyecto-de-guarderia-infantil-en-la-parcela-numero-44-del-poligono-de-la-candelaria-zamora-1974-1981. 

Dados exportados da plataforma Arquitectura Aqui (https://arquitecturaaqui.eu), repositório do referido projeto, em janeiro de 2026.
DOI: 10.5281/zenodo.18206899
title: Notas de leitura do processo "Proyecto de Guardería Infantil, en la parcela número 44 del Polígono de La Candelaria, Zamora [1974-1981]"

description: Notas de leitura do processo “Proyecto de Guardería Infantil, en la parcela número 44 del Polígono de La Candelaria, Zamora [1974-1981]” existente no Archivo Histórico Provincial de Zamora, em Zamora. 

Registo efetuado em janeiro de 2025 no âmbito do projeto de investigação ReARQ.IB – Built Environment Knowledge for Resilient, Sustainable Communities: Understanding Everyday Modern Architecture and Urban Design in the Iberian Peninsula (1939-1985) (ERC GA949686) e publicado online em https://arquitecturaaqui.eu/es/documentacion/expedientes/55284/proyecto-de-guarderia-infantil-en-la-parcela-numero-44-del-poligono-de-la-candelaria-zamora-1974-1981. 

Dados exportados da plataforma Arquitectura Aqui (https://arquitecturaaqui.eu), repositório do referido projeto, em janeiro de 2026.
DOI: 10.15156/bio/sh1402777.10fu
title: SH1402777.10FU

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.gxcgue
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Myodes smithii (Thomas, 1905)"
 ]
}

 The dataset includes 33 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005714-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kxdl4m
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/0027113-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.76qm6m
title: Occurrence Download

description: A dataset containing 327567333 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "Year 2018-2021"
 ]
}

 The dataset includes 327567333 records from 4194 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0200366-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25954/3wx2-5t05
title: Lipoceramic Technologies: a Solution to Low and Variable Bioavailability of Poorly Soluble Anti-Inflammatory Drugs [IWEMC-210]
DOI: 10.15468/dl.2ctcfr
title: Occurrence Download

description: A dataset containing 41296 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sternula superciliaris)",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 41296 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076965-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rjg8dk
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aerodramus nuditarsus)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076968-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gu3e67
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Laportea interrupta",
 "Country is Fiji",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076970-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16519017
title: Ayuyu Cave Radiometric Data - July 14 2020 (1500)

description: This orthomosaic of Ayuyu Cave was created from 182 images taken on July 14 2020, at 130 ft AGL, with a DJI XT2 Sensor mounted to a DJI Matrice 210 UAV. The mission was planned using the DJI Pilot application and post-processed using DroneDeploy.
description: Disclaimer: The following aerial imagery is intended solely for research purposes related to the assessment of the captured area. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization.The University of Guam Drone Corps funded by NASA Guam Space Grant and NASA Guam EPSCoR retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer. Privacy Disclaimer: The aerial imagery captured for assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and related parties disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.