cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.gzabxv
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (205318200, 212263770, 205318213, 209346372, Congridae, 204214194, Congridae, 203914553, Congridae, Congridae, 209454601, Congridae, Congridae, 212423187, 205851017, Congridae, 212386410, 205909925, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, 203914570, 212108495, Congridae, 203914564, Congridae, Congridae, Congridae, Congridae, 204357423, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, 212269508, 202995508, Congridae, Congridae, 205994256, 158165280, 209459616, 204975614, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, 205909932, 205982686, 206089731, Congridae, Congridae, 210654773, Congridae, Congridae, 205279700, Congridae, Congridae, Congridae, 157073644, Congridae, Congridae, 210655869, Congridae, 205891476, 209340673, 206023541, Congridae, Congridae, 203914596, Congridae, 197287461, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, CONGRIDAE, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, 210656546, 205318194, Congridae, 205907184, Congridae, 204763166, 204090722, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, 211761762, 203695412, Congridae, Congridae, Congridae, Congridae, Congridae, 212282697, Congridae, 212101642, 205000602, Congridae, Congridae, Congridae, 205973179, 203914590, 212360821, 210217868, Congridae, 206089510, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, 203894376, Congridae, 205913679, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae, Congridae Kaup, 1856, Congridae Kaup, 1856, Congridae Kaup, 1856, Congridae Kaup, 1856, Congridae Gill, 1861, Congridae Smith 2018, Congridae Kaup, 1856, 161470143, Congridae Kaup, 1856, Congridae Kaup, 1856, Congridae Kaup, 1856, Congridae Smith 2018, Congridae Kaup, 1856, Nettastomatidae Bleeker, 1864, Pelagornithidae Fürbringer, 1888, Macrocephenchelyidae, Macrocephenchelyidae, Macrocephenchelyidae Fowler, 1934)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((109.5 20.15,117.25 20.15,117.25 24,109.5 24,109.5 20.15))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 39 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049515-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7pneh4
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A new Dichaetanthera (Melastomataceae: Melastomateae) from Masoala National Park in Madagascar"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049516-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.whfqms
title: Occurrence Download

description: A dataset containing 5499771 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coragyps atratus (Bechstein, 1793)"
 ]
}

 The dataset includes 5499771 records from 735 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049486-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.27957855
title: Laboratory Panel for Intestinal Tuberculosis in Indonesia

description: World Health Organization (WHO) reported through the Global Tuberculosis Report 2022 that Indonesia is in 2nd place with the highest burden of tuberculosis (TB) in 2021. Intestinal tuberculosis (ITB) as part of TB has a prevalence of around 3–16%. The clinical manifestations, radiological features, and histopathology of ITB resemble other gastrointestinal diseases, such as Crohn's disease and colon cancer, making it a challenge in efforts to develop a noninvasive laboratory panel for diagnosing ITB with various laboratory biomarkers. We present data related to laboratory findings and clinical manifestation for ITB diagnosis
DOI: 10.6084/m9.figshare.27957855.v3
title: Laboratory Panel for Intestinal Tuberculosis in Indonesia

description: World Health Organization (WHO) reported through the Global Tuberculosis Report 2022 that Indonesia is in 2nd place with the highest burden of tuberculosis (TB) in 2021. Intestinal tuberculosis (ITB) as part of TB has a prevalence of around 3–16%. The clinical manifestations, radiological features, and histopathology of ITB resemble other gastrointestinal diseases, such as Crohn's disease and colon cancer, making it a challenge in efforts to develop a noninvasive laboratory panel for diagnosing ITB with various laboratory biomarkers. We present data related to laboratory findings and clinical manifestation for ITB diagnosis
DOI: 10.21227/q4mr-wn37
title: 3D seismic data

description: As coal mining extends to greater depths, accurately detecting coal seam floor undulations, identifying coal thickness variations, and recognizing complex geological features such as collapse columns has become increasingly essential. These challenges raise higher demands for safety and efficiency in mining operations. This study proposes a dynamic interpretation method for intelligent mining faces based on 3D seismic data to enhance the accuracy of detecting coal seam geological structures. The method comprehensively applies target processing and dynamic interpretation to conduct an accurate analysis of the coal seam floor elevation and average velocity field. By dynamically updating the data model and combining surface drilling and roadway data, significantly enhancing model accuracy and reliability. The study shows that the improved data correction method significantly enhances model accuracy and reliability. The accuracy of channel wave detection in structural prediction reaches 75%, while maintaining the maximum absolute error for floor profile prediction within 1.33 m. The random forest model was improved by combining gray correlation and particle swarm optimization (PSO) algorithms, further revealing the complex relationship between coal seam floor elevation and two-way travel time (TWTT). The method proposed not only enhances the precision and efficiency of intelligent face detection but also offers reliable geological support for safe coal mining operations. As geological data are continuously and dynamically updated, the method enables real-time optimization of mining decisions and reduces the risk of geological hazards.
DOI: 10.15468/dl.xhvfbr
title: Occurrence Download

description: A dataset containing 16180 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Gymnadenia orchidis Lindl., Habenaria tibetica Schltr., Habenaria davidii Franch., Neottia acuminata Schltr., Neottia listeroides Lindl., Cypripedium henryi Rolfe, Platanthera chlorantha (Custer) Rchb., Herminium monorchis (L.) R.Br., Herminium alaschanicum Maxim., Goodyera repens (L.) R.Br., Rhodiola discolor (Franch.) S.H.Fu, Rhodiola tangutica (Maxim.) S.H.Fu, Rhodiola atuntsuensis (Praeger) S.H.Fu, Rhodiola crenulata (Hook.fil. & Thomson) H.Ohba, Rhodiola tibetica (Hook.fil. & Thomson) S.H.Fu, Rhodiola nobilis (Franch.) S.H.Fu, Saussurea aster Hemsl., Saussurea medusa Maxim., Saussurea laniceps Hand.-Mazz., Aconitum brachypodum Diels, Circaeaster agrestis Maxim., Sinopodophyllum hexandrum (Royle) T.S.Ying, Fritillaria cirrhosa D.Don, Hansenia weberbaueriana (Fedde ex H.Wolff) Pimenov & Kljuykov, Actinocarya acaulis (W.W.Sm.) I.M.Johnst., Rheum tanguticum Maxim. ex Balf., Abies squamata Mast., Larix potaninii Batalin, Picea brachytyla (Franch.) E.Pritz., Picea likiangensis (Franch.) E.Pritz., Picea crassifolia Kom., Picea purpurea Mast., Juniperus przewalskii Kom., Juniperus komarovii Florin, Juniperus przewalskii Kom., Juniperus tibetica Kom., Juniperus convallium Rehd. & E.H.Wilson, Haloxylon ammodendron (C.A.Mey.) Bunge ex Fenzl, Ephedra minuta Florin, Ephedra monosperma J.G.Gmel. ex C.A.Mey., Salix sclerophylla Andersson, Habenaria aitchisonii Rchb.f., Neottia puberula (Maxim.) Szlach., Dactylorhiza viridis (L.) R.M.Bateman, Pridgeon & M.W.Chase, Dactylorhiza hatagirea (D.Don) Soó, Hemipilia cucullata (L.) Y.Tang, H.Peng & T.Yukawa, Galearis wardii (W.W.Sm.) P.F.Hunt, Herminium pugioniforme Lindl. ex Hook.f., Rhodiola chrysanthemifolia (H.Lév.) S.H.Fu, Saussurea wellbyi Hemsl., Saussurea obvallata (DC.) Sch.Bip., Dysosma tsayuensis T.S.Ying, Polystichum glaciale Christ, Taxus wallichiana Zucc., Populus euphratica Olivier, Syringa pinnatifolia Hemsl., Stachys geobombycis C.Y.Wu, Tricholoma matsutake (S.Ito & S.Imai) Singer)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((70 20,120 20,120 50,70 50,70 20))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 16180 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049520-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.355nee
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is The genera of Lauraceae in Madagascar with nomenclatural novelties in Cryptocarya"
 ]
}

 The dataset includes 15 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049521-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rm2sz2
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((19.93835 38.86407,20.46055 37.59264,20.90852 38.49639,20.77125 38.80194,19.93835 38.86407))",
 "TaxonKey is Lithophaga lithophaga (Linnaeus, 1758)"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049522-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/n871-cw30
title: Secrecy Capacity Maximization for IRS-Assisted High-Speed Train Communications

description: In this letter, we propose an IRS-assisted MIMO communication system model in the presence of an eavesdropper (Eve). A distance-dependent Rician factor and real-time Doppler frequency offset (DFO) compensation mechanismare utilized to characterize highly time-varying wireless channels. The secrecy capacity optimization problem is formulated by jointly optimizing the transmit beamforming, artificial noise (AN) matrix, and IRS phase shifts, subject to constraints on the maximum transmit power and unit-modulus IRS phase shifts. To solve the non-convex problem, the weighted minimum mean square error (WMMSE) algorithm transforms it into a convex optimization problem, and the optimal solution is derived using an alternating optimization strategy with coupled variables. Simulation results show that the optimization algorithm proposed in this letter converges quickly and achieves higher secrecy capacity.
DOI: 10.15468/dl.khbpr8
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Glutodon gen. nov. (Hymenoptera, Bethylidae), a flap-metasomed Pristocerinae from Madagascar"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049524-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z236wz
title: Occurrence Download

description: A dataset containing 28138 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Monarda fistulosa L."
 ]
}

 The dataset includes 28138 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049523-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7xaqvt
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Bauhinia darainensis Thulin & Nusb. (Fabaceae), a new species from northern Madagascar"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049525-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.au97x3
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anguillidae, 212108460, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, 210217835, 205973171, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, 211761465, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, 212263781, Anguillidae, Anguillidae, 203894366, Anguillidae, Anguillidae, Anguillidae, 205873892, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, 212430254, 212269513, Anguillidae, Anguillidae, Anguillidae, 212360819, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, 210654888, Anguillidae, 209346398, ANGUILLIDAE, 116776235, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, 209405124, 209454605, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, ANGUILLIDAE, Anguillidae, 209432342, 209667155, Anguillidae, 197295436, Anguillidae, 212386407, Anguillidae, 212282688, Anguillidae, Anguillidae, Anguillidae, Anguillidae, 204357429, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, 158165200, Anguillidae, 194286246, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae, Anguillidae Rafinesque 1810, Anguillidae Rafinesque, 1810, 161470393, Anguillidae Rafinesque, 1810, Anguillidae Rafinesque 1810, Anguillidae Rafinesque, 1810, Anguillidae Rafinesque, 1810, Anguillidae Rafinesque 1810, Anguillidae Rafinesque, 1810, Anguillidae Rafinesque 1810, Anguillidae Rafinesque 1810, Anguillidae Rafinesque, 1810, Pelagornithidae Fürbringer, 1888)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((109.5 20.15,117.25 20.15,117.25 24,109.5 24,109.5 20.15))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 48 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049526-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rwgkz5
title: Occurrence Download

description: A dataset containing 4370997 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Australia",
 "TaxonKey is Mammalia",
 "Year 1950-2024"
 ]
}

 The dataset includes 4370997 records from 268 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049517-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7uawkh
title: Occurrence Download

description: A dataset containing 35219582 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((80.31977 10.17003,81.2935 13.26826,84.09296 17.02706,87.37928 19.22473,86.89242 21.50669,82.99752 23.976,79.46776 24.53086,73.86884 24.42009,71.79968 23.41874,71.67796 19.79836,73.01684 15.62541,74.72085 8.36822,77.76374 7.16224,80.31977 10.17003))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1000-2024"
 ]
}

 The dataset includes 35219582 records from 899 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049519-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1181846.10fu
title: SH1181846.10FU

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: 10.34740/kaggle/dsv/14459047
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15156/bio/sh1181871.10fu
title: SH1181871.10FU

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/sh1181872.10fu
title: SH1181872.10FU

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/sh1181874.10fu
title: SH1181874.10FU

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/sh1181875.10fu
title: SH1181875.10FU

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.