cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15112015
title: Willingness to Pay for Nanotechnology Products: The Czech Republic Experience

description: The current development of nanotechnology responds to climate change, sustainability issues, the energy crisis, and the need to improve the quality of life. The question, however, is what are the societal impacts and public acceptance of nanotechnology? To explore this, a pilot cross-sectional study was conducted in the Czech Republic.

The main objective of this study is to discuss consumers' willingness to pay for products containing nanotechnology. A sub-objective is to present the results of a pilot cross-sectional study on willingness to pay for nanotechnology products in the Czech Republic. The methods of literature review, questionnaire survey and subsequent statistical evaluation are used. The number of respondents in the pilot cross-sectional study is 216. Respondents commented on 2 groups of products: 1) products containing nanotechnology, identical to conventional products, and 2) products containing nanotechnology with improved properties and/or design.

The findings reveal that people's willingness to pay for nanotechnology products varies, largely depending on their knowledge of nanomaterials, education, and income. Importantly, respondents showed a higher willingness to pay for products with nanotech- enhanced performance or design. Educating the public and raising awareness about the benefits of nanotechnology could be crucial steps in increasing its societal acceptance and promoting its role in addressing global challenges.

The work was supported from ERDF/ESF project TECHSCALE (No. CZ.02.01.01/00/22_008/0004587).
DOI: 10.5281/zenodo.15112016
title: Willingness to Pay for Nanotechnology Products: The Czech Republic Experience

description: The current development of nanotechnology responds to climate change, sustainability issues, the energy crisis, and the need to improve the quality of life. The question, however, is what are the societal impacts and public acceptance of nanotechnology? To explore this, a pilot cross-sectional study was conducted in the Czech Republic.

The main objective of this study is to discuss consumers' willingness to pay for products containing nanotechnology. A sub-objective is to present the results of a pilot cross-sectional study on willingness to pay for nanotechnology products in the Czech Republic. The methods of literature review, questionnaire survey and subsequent statistical evaluation are used. The number of respondents in the pilot cross-sectional study is 216. Respondents commented on 2 groups of products: 1) products containing nanotechnology, identical to conventional products, and 2) products containing nanotechnology with improved properties and/or design.

The findings reveal that people's willingness to pay for nanotechnology products varies, largely depending on their knowledge of nanomaterials, education, and income. Importantly, respondents showed a higher willingness to pay for products with nanotech- enhanced performance or design. Educating the public and raising awareness about the benefits of nanotechnology could be crucial steps in increasing its societal acceptance and promoting its role in addressing global challenges.

The work was supported from ERDF/ESF project TECHSCALE (No. CZ.02.01.01/00/22_008/0004587).
DOI: 10.15468/dl.8rsqyw
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Meliscaeva omogensis (Shiraki & Edashige, 1953)",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 41 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0212018-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.asbpdz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Steatoda erigoniformis (O.Pickard-Cambridge, 1872)",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0224460-220831081235567/datasets/export for details.
DOI: 10.15468/dl.s9jjdw
title: Occurrence Download

description: A dataset containing 918 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-72.2052 38.5592,-75.39056 41.1019,-85.70105 40.93425,-90.81098 39.84892,-96.7729 37.1095,-100.36081 33.18669,-96.37834 28.57736,-84.72595 27.69237,-82.37306 25.31788,-78.43532 24.72721,-72.2052 38.5592))",
 "TaxonKey is Quercus lyrata Walter"
 ]
}

 The dataset includes 918 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0258957-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ksek2f
title: Occurrence Download

description: A dataset containing 632 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((26.58624 46.71903,27.72633 47.0565,26.9318 48.15761,26.07915 47.9178,26.58624 46.71903))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 632 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0220319-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bnp75y
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Guzmania bismarckii Rauh"
 ]
}

 The dataset includes 12 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0234197-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fpc2a9
title: Occurrence Download

description: A dataset containing 138 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-7.01042 36.01762,-2.37999 36.01762,-2.37999 38.17292,-7.01042 38.17292,-7.01042 36.01762))",
 "HasGeospatialIssue is false",
 "TaxonKey is Quercus suber L."
 ]
}

 The dataset includes 138 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035839-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a4sujb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tabanus yaeyamaensis Hayakawa & Hasegawa, 1981",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0212012-220831081235567/datasets/export for details.
DOI: 10.15468/dl.u2b9sa
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Namibia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "PublishingOrg is c8d737e0-2ff8-42e8-b8fc-6b805d26fc5f",
 "TaxonKey is Sphingomorpha chlorea Cramer, 1777"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0247988-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kc4efj
title: Occurrence Download

description: A dataset containing 17657 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acer palmatum Thunb.",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 17657 records from 398 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0258986-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cwa42b
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chrysotoxum festivum (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0212023-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jk5rju
title: Occurrence Download

description: A dataset containing 7349 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Odobenus rosmarus (Linnaeus, 1758)"
 ]
}

 The dataset includes 7349 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007365-240425142415019/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5zdak5
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Guzmania bicolor L.B.Sm."
 ]
}

 The dataset includes 14 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0234194-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.arsf97
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Rusa unicolor (Kerr, 1792)"
 ]
}

 The dataset includes 42 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0232214-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4pcjbk
title: Occurrence Download

description: A dataset containing 442655 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Amaranthus tricolor L., Amaranthus tuberculatus (Moq.) Sauer, Amaryllis belladonna L., Ambrosia artemisiifolia L., Ambrosia confertiflora DC., Ambrosia psilostachya DC., Ambrosia tenuifolia Spreng., Ambrosia trifida L., Amelanchier Medik., Amelanchier ×lamarckii F.G.Schroed.)"
 ]
}

 The dataset includes 442655 records from 1638 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0266076-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0181180.10fu
title: SH0181180.10FU

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/sh0181181.10fu
title: SH0181181.10FU

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/sh0181182.10fu
title: SH0181182.10FU

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/sh0181183.10fu
title: SH0181183.10FU

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: 10.24435/materialscloud:mr-nj
title: Precision verification results data for DFTK@PW|PseudoDojo-v0.5

description: Density-functional theory (DFT) is a cornerstone of computational materials science. The Density-Functional Toolkit (DFTK) is a recent plane-wave DFT code, written with a flexible architecture and in a high-level language to facilitate development of new methods and support fundamental mathematical research on DFT. DFTK has been instrumental in a good dozen of recent papers, and its core DFT routines are considered stable. So far a systematic precision benchmark against other codes and approaches had not yet been performed. In this work, we apply the verification protocol established by E. Bosoni et al. [Nat. Rev. Phys. 6, 45-58 (2024)] based on the AiiDA high-throughput engine, to validate the precision of DFTK against the existing all-electron and pseudopotential data. This record contains our results, as well as the scripts needed to reproduce them. Out of the 720 systems, DFTK achieves excellent agreement with the all-electron average (ε<0.06) on 181 systems and good-but-not-excellent agreement (0.06<=&epsilon;<0.2) on 329 systems. Comparing DFTK with Quantum ESPRESSO (QE@PW|PseudoDojo-v0.4), the agreement is excellent on 624 systems and good-but-not-excellent on 9 systems; the agreement is bad (ε>=0.2) for most systems in the lower right corner of the periodic table (elements: Te, I, Xe, Tl, Pb, Bi, Po, Rn) as well as Ba systems.

We acknowledge and thank Yihan Wu for the initial versions of aiida-dftk and the DFTK support in aiida-common-workflows.
DOI: 10.15156/bio/sh0181184.10fu
title: SH0181184.10FU

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: 10.34894/ozrhtu
title: China, 2004-2015

description: Data collected by CLB and Manfred Elfstrom were streamlined and put into one dataset by Sjaak van der Velden
DOI: 10.15156/bio/sh0181185.10fu
title: SH0181185.10FU

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/sh0181186.10fu
title: SH0181186.10FU

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/sh0181187.10fu
title: SH0181187.10FU

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/sh0181188.10fu
title: SH0181188.10FU

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.