cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17169/refubium-51196
title: HiRISE mosaic of the northern delta of Jezero Crater, Mars

description: The mosaic comprises four HiRISE (High Resolution Imaging Science Experiment, McEwen et al., 2007) images: ESP_035141_1990_RED, ESP_037330_1990_RED, ESP_037607_1990_RED and PSP_002743_1985_RED. Individual images were co-registered to a single CTX (Context Camera) ortho-image scene G12_022957_1985_XN_18N282W (5 m/pixel) (Malin et al., 2007), which was itself co-registered to the HRSC Mars Chart (HMC_13E10) ortho-rectified image mosaic (12.5 m/pixel) (Gwinner et al., 2016). Co-registration was performed using the “Georeferencing” tool in ArcGIS software with manually selected control points and spline transformations. Following co-registration, brightness normalization was applied to harmonize the individual HiRISE images with the reference CTX image, thereby eliminating albedo discontinuities at image boundaries and achieving a visually homogeneous mosaic. Each HiRISE scene was subdivided into a grid of 12 × 36 patches (x-direction × y-direction), and the average brightness was calculated for each patch along with the corresponding patch from the reference CTX image. A normalization ratio for each patch was computed by dividing the reference brightness value by the original image brightness value. Transitions between patches were interpolated to eliminate visible boundary effects. Finally, the normalized images were mosaicked using standard GDAL command-line tools. The brightness adjustment algorithm was implemented in Python.
DOI: 10.17169/refubium-51214
title: Morphological map of the northern delta in Jezero crater, Mars

description: The dataset contains the morphological map of the northern delta in Jezero crater on Mars in ArcGIS mapfile (.mapx) format, or (in case ArcGIS is not available) as separate shapefiles (then without layer styling). The mapping was done in ArcGIS Pro 3.5.1 using HiRISE Jezero Northern Delta mosaic (DOI: 10.17169/refubium-51196), created from HiRISE data (High Resolution Imaging Science Experiment, McEwen et al., 2007, DOI: 10.1016/j.icarus.2023.115795). The mapping was done at the digitalization scale 1:10000.
DOI: 10.34740/kaggle/dsv/14787710
title: Balochi Language to English Translation Dataset
DOI: 10.21227/hyqx-bn32
title: "Agentic Decentralized Autonomous Machines Dataset"

description: "Decentralized Physical Infrastructure Networks (DePINs) often rely on static, rule-based protocols that degrade under sensor drift, noise, and intermittent connectivity, and offer limited support for coordinated, context-aware decisions across distributed IoT devices. This paper presents \\emph{Agentic Decentralized Autonomous Machines} (ADAM), a crew-based multi-agent architecture in which edge nodes form task-specific teams on demand, share context via semantic memory, selectively invoke structured LLM inference through an API, and enforce policy validation with immutable audit logging on a Proof-of-Authority (PoA) blockchain. ADAM follows a hybrid edge--cloud design: edge devices perform continuous sensing and event-driven coordination, while semantic interpretation is offloaded only when needed. On a methane monitoring testbed, ADAM improves $F_1$ by 13.1 percentage points over a static-threshold baseline, while sustaining a mean end-to-end decision latency of 1.26\\,s over a 72-hour deployment and operating at \\emph{25.1}\\% average CPU utilization on Raspberry Pi--class devices. These results indicate that crew-based, LLM-assisted coordination with governance-backed validation can improve robustness in non-stationary edge monitoring without exceeding practical resource budgets."
DOI: 10.15468/dl.22gn4q
title: Occurrence Download

description: A dataset containing 74135 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Spain",
 "Geometry POLYGON((-6.68064 36.85042,-6.05137 35.9857,-5.43179 35.94652,-4.71539 36.46988,-4.66699 37.78201,-6.25467 37.74375,-6.68064 36.85042))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 74135 records from 154 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003262-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qszb4g
title: Occurrence Download

description: A dataset containing 1651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Vampyressa thyone"
 ]
}

 The dataset includes 1651 records from 152 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003275-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u9w3v7
title: Occurrence Download

description: A dataset containing 1060 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Vampyriscus bidens"
 ]
}

 The dataset includes 1060 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003276-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18560947
title: DIGITAL STOMATOLOGIYA: IMKONIYATLAR VA MUAMMOLAR

description: So‘nggi yillarda stomatologiya sohasida raqamli texnologiyalar keng joriy etilmoqda. Digital stomatologiya — bu kompyuter texnologiyalari, raqamli diagnostika, CAD/CAM tizimlari, intraoral skanerlar va 3D texnologiyalar asosida davolash jarayonini amalga oshirishdir. Ushbu yondashuv stomatologik muolajalarning aniqligi va samaradorligini oshirishga xizmat qiladi.

Digital stomatologiyaning asosiy imkoniyatlari qatoriga tashxisning aniqligi, davolash vaqtining qisqarishi, bemor uchun qulaylik, estetik natijaning yaxshilanishi va inson omili ta’sirining kamayishi kiradi. Intraoral skanerlar yordamida an’anaviy qolip olish jarayoniga ehtiyoj kamayadi, CAD/CAM texnologiyalari esa yuqori aniqlikdagi protez va restavratsiyalar tayyorlash imkonini beradi.

Biroq, digital stomatologiya bilan bog‘liq muammolar ham mavjud. Jumladan, uskunalarning qimmatligi, mutaxassislarning yetarli darajada tayyor emasligi, texnik nosozliklar va texnologiyalarga moslashish jarayonining murakkabligi muhim muammolar sirasiga kiradi. Shuningdek, barcha klinikalarda raqamli texnologiyalarni joriy etish imkoniyati mavjud emas.

Xulosa qilib aytganda, digital stomatologiya zamonaviy stomatologiyaning ajralmas qismi bo‘lib, uning imkoniyatlari muammolariga nisbatan ustunlik qiladi. Kelajakda bu texnologiyalarni rivojlantirish va mutaxassislarni tayyorlash muhim ahamiyat kasb etadi.
DOI: 10.5281/zenodo.18560948
title: DIGITAL STOMATOLOGIYA: IMKONIYATLAR VA MUAMMOLAR

description: So‘nggi yillarda stomatologiya sohasida raqamli texnologiyalar keng joriy etilmoqda. Digital stomatologiya — bu kompyuter texnologiyalari, raqamli diagnostika, CAD/CAM tizimlari, intraoral skanerlar va 3D texnologiyalar asosida davolash jarayonini amalga oshirishdir. Ushbu yondashuv stomatologik muolajalarning aniqligi va samaradorligini oshirishga xizmat qiladi.

Digital stomatologiyaning asosiy imkoniyatlari qatoriga tashxisning aniqligi, davolash vaqtining qisqarishi, bemor uchun qulaylik, estetik natijaning yaxshilanishi va inson omili ta’sirining kamayishi kiradi. Intraoral skanerlar yordamida an’anaviy qolip olish jarayoniga ehtiyoj kamayadi, CAD/CAM texnologiyalari esa yuqori aniqlikdagi protez va restavratsiyalar tayyorlash imkonini beradi.

Biroq, digital stomatologiya bilan bog‘liq muammolar ham mavjud. Jumladan, uskunalarning qimmatligi, mutaxassislarning yetarli darajada tayyor emasligi, texnik nosozliklar va texnologiyalarga moslashish jarayonining murakkabligi muhim muammolar sirasiga kiradi. Shuningdek, barcha klinikalarda raqamli texnologiyalarni joriy etish imkoniyati mavjud emas.

Xulosa qilib aytganda, digital stomatologiya zamonaviy stomatologiyaning ajralmas qismi bo‘lib, uning imkoniyatlari muammolariga nisbatan ustunlik qiladi. Kelajakda bu texnologiyalarni rivojlantirish va mutaxassislarni tayyorlash muhim ahamiyat kasb etadi.
DOI: 10.15468/8kgtx5
title: NUP - Coleção Ictiológica do Nupélia

description: A Coleção de peixes do Núcleo de Pesquisas em Limnologia, Ictiologia e Aqüicultura (Nupélia) foi criada no início da década de 1990, com o incremento das pesquisas do Nupélia. Seu objetivo inicial era manter espécimes-testemunho daquelas pesquisas, mas tem ampliado seu tamanho, importância e escopo. Atualmente, abriga material comparativo de diferentes localidades, principalmente da bacia do Prata, parátipos de diversas espécies novas, além de exemplares-testemunho de teses, livros e artigos publicados por pesquisadores e estudantes do Nupélia. Todo material está disponível para a comunidade científica. Empréstimos, intercâmbios e outras transações têm sido efetuadas com diferentes instituições do Brasil e outros países. A maior parte da Coleção está preservada em etanol 70º GL, mas um pequeno conjunto de espécimes diafanizados, corados e preservados em glicerina vem gradualmente aumentando. A representatividade geográfica da Coleção é neotropical, mas com forte ênfase na ictiofauna da bacia do Prata, incluindo os estados brasileiros de Goiás, Mato Grosso, Mato Grosso do Sul, São Paulo e Paraná, dentre outros menos representados. Mais de 5.000 lotes de peixes estão no banco de dados e aproximadamente 5.000 estão ainda por catalogar. A totalidade do banco de dados catalogados da Coleção está disponível para busca. Uma seção de ictioplâncton de água doce do Laboratório de Ictioplâncton do Nupélia tem sido incorporada à Coleção Ictiológica, e pode ser acessada da mesma maneira. A Coleção é credenciada no Conselho de Gestão do Patrimônio Genético (CGEN), conforme deliberação número 137, de 22 de fevereiro de 2006, a qual foi publicada no Diário Oficial da União em 4 de abril de 2006.
DOI: 10.15468/dl.5t8uvh
title: Occurrence Download

description: A dataset containing 32206856 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 32206856 records from 4314 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003225-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0167648.10fu
title: SH0167648.10FU

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/sh0167649.10fu
title: SH0167649.10FU

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/sh0167650.10fu
title: SH0167650.10FU

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/sh0167651.10fu
title: SH0167651.10FU

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/sh0167652.10fu
title: SH0167652.10FU

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/sh0167653.10fu
title: SH0167653.10FU

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/sh0167654.10fu
title: SH0167654.10FU

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/sh0167655.10fu
title: SH0167655.10FU

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/sh0167656.10fu
title: SH0167656.10FU

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: 10.5285/59e3be5c-8ac8-45cd-8e98-a69732755dc6
title: Vegetation plot data from the Environment and Rural Affairs Monitoring & Modelling Programme, Wales, 2021-2023

description: This dataset includes records of plant species and abundance from within a wide range of land use types across Wales, collected as part of the Environment and Rural Affairs Monitoring & Modelling Programme (ERAMMP) National Field Survey (NFS) between 2021-2023.

ERAMMP NFS is a resurvey of all of the 300 locations from the initial Glastir Monitoring and Evaluation Programme (GMEP) monitoring program (300 1km squares) on a rolling annual basis, with the aim to resurvey all sites between 2021 and 2025. Between 2021-2023 ERAMMP National Field Survey resurveyed 225 of those 300 for plant species and abundance. The initial monitoring program, GMEP, was set up by the Welsh Government in 2013 to report national trends and monitor the effects of the Glastir agri-environment scheme on the environment and ran from 2013 to 2016.

The field survey element was based on a stratified random sampling design of 300 x 1km square sites across Wales, and was managed by the UK Centre for Ecology & Hydrology.
description: Within each of 225 x 1km sample squares across Wales, a set of vegetation plots of varying sizes were recorded by professional botanists, comprising covers of vascular plants. Data were recorded on electronic recording devices, and then transferred to secure databases at the UK Centre for Ecology & Hydrology.

To ensure confidentiality of the data with respect to land owners and managers, the locations of 1km squares and survey sites were converted to the centres of the containing 10km Ordnance Survey grid squares.
DOI: 10.15156/bio/sh0167657.10fu
title: SH0167657.10FU

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.