cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17264824
title: Digital twin of costume #20 – Segmented surface. 3D MODEL

description: The 3D models present segmented surfaces of digital twins of historical costumes. The initial surfaces which were generated by using computer simulations in Clo software is shown on the left. The segments of the surfaces are shown on the right. Those represent areas controlled by parameters that are chosen subjectively divided into three categories, seams, edges and surfaces. The models aim to indicate uncertain areas of the garment resulting from limitations inherent to computer simulations.

The authors thank prof. Victor Kuzmichev and the team from Ivanovo State Polytechnic University for providing data required for 3D modelling.

The authors of the 3D models are Aleksei Moskvin and Mariia Moskvina (Saint Petersburg State University of Industrial Technologies and Design): 

https://sutd-ru.academia.edu/AlekseiMoskvin

https://independent.academia.edu/MariiaMoskvina

The 3D model is available at: https://skfb.ly/psSLz
DOI: 10.5281/zenodo.17264825
title: Digital twin of costume #20 – Segmented surface. 3D MODEL

description: The 3D models present segmented surfaces of digital twins of historical costumes. The initial surfaces which were generated by using computer simulations in Clo software is shown on the left. The segments of the surfaces are shown on the right. Those represent areas controlled by parameters that are chosen subjectively divided into three categories, seams, edges and surfaces. The models aim to indicate uncertain areas of the garment resulting from limitations inherent to computer simulations.

The authors thank prof. Victor Kuzmichev and the team from Ivanovo State Polytechnic University for providing data required for 3D modelling.

The authors of the 3D models are Aleksei Moskvin and Mariia Moskvina (Saint Petersburg State University of Industrial Technologies and Design): 

https://sutd-ru.academia.edu/AlekseiMoskvin

https://independent.academia.edu/MariiaMoskvina

The 3D model is available at: https://skfb.ly/psSLz
DOI: 10.5286/isis.e.rb2520008-1
title: Size-Driven Magnetic Transitions in Electron-Doped Cuprates: A Muon Spin Relaxation Study

description: Nanoscale confinement in correlated electron systems provides a powerful route to manipulate emergent quantum phenomena. Here, we explore size-dependent magnetism in electron-doped cuprate nanoparticles, focusing on Eu1.85Ce0.15CuO4+α-δ (ECCO). Compared to hole-doped cuprates, electron-doped variants face experimental challenges due to the sensitivity of superconductivity and magnetism to oxygen nonstoichiometry. To overcome this, we optimized δ within the critical range of 0.040–0.090, where superconductivity can emerge, by annealing under argon at 700 °C for 8 hours. Using a sol–gel method, we synthesized phase-pure ECCO with sizes of 56, 108, and 169 nm. Magnetic measurements show a transition from paramagnetism at 169 nm to spin-glass behavior and emergent ferromagnetism in smaller particles. Curie-law analysis confirms enhanced magnetic moments with decreasing size. To clarify the magnetic ground state and spin dynamics, we propose muon spin relaxation (μSR) measurements. Zero-field μSR (2–300 K) will detect static magnetism and spin freezing, while longitudinal-field μSR (10–1000 G) will probe fluctuation dynamics near the spin-glass transition. These experiments will advance understanding of size-tuned magnetism and its relation to superconductivity in electron-doped cuprates.
DOI: 10.5286/isis.e.rb2520008
title: Size-Driven Magnetic Transitions in Electron-Doped Cuprates: A Muon Spin Relaxation Study

description: Nanoscale confinement in correlated electron systems provides a powerful route to manipulate emergent quantum phenomena. Here, we explore size-dependent magnetism in electron-doped cuprate nanoparticles, focusing on Eu1.85Ce0.15CuO4+α-δ (ECCO). Compared to hole-doped cuprates, electron-doped variants face experimental challenges due to the sensitivity of superconductivity and magnetism to oxygen nonstoichiometry. To overcome this, we optimized δ within the critical range of 0.040–0.090, where superconductivity can emerge, by annealing under argon at 700 °C for 8 hours. Using a sol–gel method, we synthesized phase-pure ECCO with sizes of 56, 108, and 169 nm. Magnetic measurements show a transition from paramagnetism at 169 nm to spin-glass behavior and emergent ferromagnetism in smaller particles. Curie-law analysis confirms enhanced magnetic moments with decreasing size. To clarify the magnetic ground state and spin dynamics, we propose muon spin relaxation (μSR) measurements. Zero-field μSR (2–300 K) will detect static magnetism and spin freezing, while longitudinal-field μSR (10–1000 G) will probe fluctuation dynamics near the spin-glass transition. These experiments will advance understanding of size-tuned magnetism and its relation to superconductivity in electron-doped cuprates.
DOI: 10.5286/isis.e.rb2500080-1
title: Understanding population heterogeneity of hybrid lipid and block co-polymer vesicles

description: Design of therapeutics in medicine is seeing a paradigm shift towards use of lipid nanoparticles (LNPs),and have transformed drug delivery by improving efficacy, reducing toxicity, and enhancing the solubility of drugs to target tissues. LNPs typically contain a PEGylated lipid to provide colloidal stability however it is known that lipids can be chemically and structurally labile which can cause leakage of cargo. We have shown that hybrid lipid-block copolymer nanoparticles offer synergistic properties that can be tuned across a broad parameter space. Addition of block copolymers leads to increased NP stability and less permeability, whilst the inclusion of lipids allows for greater biocompatibility. Importantly, NPs possess a complex and diverse range of physicochemical properties that can be difficult to characterise due to the presence of heterogeneity. The role that heterogeneity plays in terms of size, size dispersity, and morphology in biological performance is not fully understood, and can lead to issues in overall product performance and translation into clinical settings. This proposal aims to understand the extent of particle heterogeneity in hybrid lipid and block co-polymer vesicles, by the isolation of well-characterized fractions with a low to high polydispersity from an original polydisperse populations (&lt;0.2) using Multi-Detector Asymmetric-Flow Field-Flow Fractionation and allow us to determine structure-function relationships
DOI: 10.15468/dl.2bmed7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ulva ohnoi",
 "Country is Egypt",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045867-250920141307145/datasets/export for details.
DOI: 10.5286/isis.e.rb2500080
title: Understanding population heterogeneity of hybrid lipid and block co-polymer vesicles

description: Design of therapeutics in medicine is seeing a paradigm shift towards use of lipid nanoparticles (LNPs),and have transformed drug delivery by improving efficacy, reducing toxicity, and enhancing the solubility of drugs to target tissues. LNPs typically contain a PEGylated lipid to provide colloidal stability however it is known that lipids can be chemically and structurally labile which can cause leakage of cargo. We have shown that hybrid lipid-block copolymer nanoparticles offer synergistic properties that can be tuned across a broad parameter space. Addition of block copolymers leads to increased NP stability and less permeability, whilst the inclusion of lipids allows for greater biocompatibility. Importantly, NPs possess a complex and diverse range of physicochemical properties that can be difficult to characterise due to the presence of heterogeneity. The role that heterogeneity plays in terms of size, size dispersity, and morphology in biological performance is not fully understood, and can lead to issues in overall product performance and translation into clinical settings. This proposal aims to understand the extent of particle heterogeneity in hybrid lipid and block co-polymer vesicles, by the isolation of well-characterized fractions with a low to high polydispersity from an original polydisperse populations (&lt;0.2) using Multi-Detector Asymmetric-Flow Field-Flow Fractionation and allow us to determine structure-function relationships
DOI: 10.26023/708j-crzy-nf0c
title: MILAGRO: GOES-12 4KM Satellite Imagery. Version 1.0

description: This dataset contains 4KM satellite imagery from the GOES-12 satellite collected during the MILAGRO field project.
DOI: 10.34740/kaggle/dsv/13257873
title: State Development Bank Analytics
DOI: 10.15468/dl.uxgu6q
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ixora chartacea"
 ]
}

 The dataset includes 23 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045869-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gp6xt2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ulva ohnoi",
 "Country is United Arab Emirates",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045870-250920141307145/datasets/export for details.
DOI: 10.15468/dl.xwk4ha
title: Occurrence Download

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

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045868-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/98th-vtcj-5j0q
title: MILAGRO: Constant Pressure Analysis Imagery. Version 1.0

description: This dataset contains constant pressure analysis imagery collected during the MILAGRO field project.
DOI: 10.34740/kaggle/dsv/13258451
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.gt52tt
title: Occurrence Download

description: A dataset containing 16419 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Styrax japonicus"
 ]
}

 The dataset includes 16419 records from 271 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045872-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a8cguy
title: Occurrence Download

description: A dataset containing 825 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-70.40881 -52.94345,-70.18835 -53.10349,-69.91669 -53.21615,-69.64932 -53.09477,-69.39012 -52.8058,-69.679 -52.66771,-69.9983 -52.41805,-70.52285 -52.34845,-70.68249 -52.4968,-70.79652 -52.56617,-70.73571 -52.75982,-70.40881 -52.94345))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is one of (Speculanas specularis (P.P.King, 1828), Tachyeres patachonicus (P.P.King, 1831), Tachyeres pteneres (J.R.Forster, 1844), Thalassarche melanophris (Temminck, 1828), Theristicus melanopis (Gmelin, 1789), Tinamotis ingoufi Oustalet, 1890, Tringa flavipes (J.F.Gmelin, 1789), Vultur gryphus Linnaeus, 1758)"
 ]
}

 The dataset includes 825 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017317-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f7rdqw
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Eurycea rathbuni (Stejneger, 1896))"
 ]
}

 The dataset includes 53 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017318-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.br976f
title: Occurrence Download

description: A dataset containing 2398 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lynx pardinus (Temminck, 1827)"
 ]
}

 The dataset includes 2398 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017315-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g9sg8q
title: Occurrence Download

description: A dataset containing 2910 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tradescantia Ruppius ex L.",
 "Geometry POLYGON((-105 34, -94 34, -94 43, -105 43, -105 34))"
 ]
}

 The dataset includes 2910 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017316-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0205253.10fu
title: SH0205253.10FU

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/sh0205254.10fu
title: SH0205254.10FU

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/sh0205255.10fu
title: SH0205255.10FU

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/sh0205256.10fu
title: SH0205256.10FU

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/sh0205257.10fu
title: SH0205257.10FU

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/sh0205258.10fu
title: SH0205258.10FU

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/sh0205259.10fu
title: SH0205259.10FU

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/sh0205260.10fu
title: SH0205260.10FU

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/sh0205261.10fu
title: SH0205261.10FU

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.