cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0177504.10fu
title: SH0177504.10FU

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/sh0177505.10fu
title: SH0177505.10FU

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/sh0177506.10fu
title: SH0177506.10FU

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/sh0177507.10fu
title: SH0177507.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.95rwjh
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Didymodon australasiae (Hook. & Grev.) R.H.Zander"
 ]
}

 The dataset includes 7 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057557-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vxgrn8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.400324 -33.193441, 149.400324 -33.195687, 149.402569 -33.195687, 149.402569 -33.193441, 149.400324 -33.193441))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057558-240626123714530/datasets/export for details.
DOI: 10.15468/dl.9dvuys
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Didymodon vinealis Brid"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057559-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3667gg
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.964019 -33.193441, 149.964019 -33.195687, 149.961773 -33.195687, 149.961773 -33.197933, 149.966265 -33.197933, 149.966265 -33.195687, 149.968511 -33.195687, 149.968511 -33.193441, 149.964019 -33.193441))"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057560-240626123714530/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.26525242.v1
title: Supplementary Material for: Epileptic encephalopathy due to CACNA1A variant, a case report and diagnostic challenges from resource-limited settings.

description: Introduction
Epilepsy is one of the most common neurological disorders present in sub-Saharan Africa and most of these cases are underdiagnosed due to a lack of resources. Epileptic encephalopathies are a broad spectrum of seizure disorders characterized by epileptic activity itself impairing cognitive and behavioral function more than what is expected from the underlying pathology alone. Epileptic encephalopathy resulting from CACNA1A variant is extremely challenging to treat and prognosis is poor if prompt diagnosis is not made.
Case presentation
This is a 7-year-old male patient of African descent with a history of recurrent seizures since infancy. He has been kept on several anticonvulsants without success to control seizure attacks. Having more than three attacks in a single month despite being on anticonvulsants. EEG (electro-encephalography) was done and genetic studies showed a diagnosis consistent with CACNA1A variant-associated epileptic encephalopathy. Anticonvulsants were revised and a combination of new medications as suggested by current guidelines was initiated and the patient is followed up closely on monthly basis.
Conclusion
Even though it is challenging to treat epileptic encephalopathies especially, one associated with CACNA1A variant all patients initiated with antiepileptic therapy should be followed closely and monitored for control of seizure attacks. Appropriate investigation should be considered if EEG alone does not point out the pathology, such as genetic studies.Early diagnosis is crucial for prognosis of such kind of cases especially in resource-limited settings were diagnostic equipments are scarce. All clinicians in these areas should have high suspicion index in pediatric patients with recurrent seizure attacks to rule epileptic encephalopathies.
DOI: 10.15468/dl.7rt4q9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.290899 -33.195687, 148.290899 -33.197933, 148.293145 -33.197933, 148.293145 -33.195687, 148.290899 -33.195687))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057561-240626123714530/datasets/export for details.
DOI: 10.1594/pangaea.927689
title: Geochemistry of Siikaneva peat core from Finland

description: Geochemistry data of a high-resolution peat core from the Past Global Changes - Carbon in Peat on EArth through Time (PAGES_C-PEAT) Project.
DOI: 10.1594/pangaea.934154
title: Age determination of Siikaneva peat core from Finland

description: 14C and 210Pb age determination of a high-resolution peat core from the Past Global Changes - Carbon in Peat on EArth through Time (PAGES_C-PEAT) Project.
DOI: 10.1594/pangaea.929399
title: Calibrated ages of Siikaneva peat core from Finland

description: Calibrated ages of a high-resolution peat core from the Past Global Changes - Carbon in Peat on EArth through Time (PAGES_C-PEAT) Project.
DOI: 10.1594/pangaea.929851
title: Calibrated ages of Pulpito (PUL-14) peat core from Patagonia

description: Calibrated ages of a high-resolution peat core from the Past Global Changes - Carbon in Peat on EArth through Time (PAGES_C-PEAT) Project.
DOI: 10.1594/pangaea.906209
title: Involving local communities for effective citizen science: determining game species' reproductive status to assess hunting effects in tropical forests

description: These three datasets are related to the analyses conducted in the article "Involving local communities for effective citizen science: determining game species' reproductive status to assess hunting effects in tropical forests".The first dataset (1_Archive_Interviews_Pregnancy_Diagnoses_Final) consists of interviews through which diagnoses of reproductive status of lowland paca (Cuniculus paca) were performed by local people in the Amazon.The second dataset (2_Archive_Hunting_Registers_Pregnancy_Immatures) consists of all records of pacas hunted voluntarily collected by local people over a 17-years citizen science project in one of the study sites.The third dataset (3_Archive_Hunting_Registers_CPUE) consists of data on the catch-per-unit-effort of lowland paca hunting events in the same site over 17 years.Specific explanations of columns' attributes are presented in the sheet "Explanations" within each dataset.The study areas and the coordinates related to the dataset are:Amanã Sustainable Development Reserve: -64.538 W; -2,492 SYavarí-Mirín River:-71,958 W; - 4,357 SJuruá River: -67,659 W; -5,517 S
DOI: 10.1594/pangaea.970160
title: UAV thermal orthomosaics from Fuglebekken and Ariebekken (June, July and September 2022-2023) from the vicinity of the Polish Polar Station Hornsund, Spitsbergen, Svalbard

description: The rapidly changing climate in the High Arctic region is posing significant challenges to its ecosystem. To better understand the changes, this study utilises Uncrewed Aerial Vehicle (UAV) technology equipped with a thermal camera to investigate ground and water temperatures in the catchments of southwest Spitsbergen. This approach provides high-resolution, real-time data, offering a detailed understanding of surface temperatures in this remote and harsh environment. Integrating UAV technology with in-situ measurements enables data collection at high spatial and temporal scales, facilitating a thorough analysis of temperature trends and patterns. The research introduces a new processing workflow using open-source packages to create thermal orthomosaics, which enhances the accuracy and efficiency of the analysis. The final developed orthomosaics, with a spatial resolution of 5cm, examine spatial variations in ground temperature and explore factors influencing land and water surface temperatures. Additionally, it investigates thermal patterns in Arctic hydrological systems, such as channels and ponds, allowing for identifying and characterising flow paths in the catchments, including groundwater intrusions and surface water mixing. This multidimensional approach aims to provide valuable insights into the complex interactions between cryo-, hydro-, and meteorological dynamics in the High Arctic.
DOI: 10.15468/dl.z7c2tn
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is China",
 "GadmGid is CHN.24.1.10_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Aves",
 "Year is 2010"
 ]
}

 The dataset includes 62 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057562-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/fyrf-wm34
title: new_data

description: This study used a benchmark dataset, applying different embedding like LASER and FastText to capture contextual information, which was combined to create a new hybrid embedding. This hybrid embedding was fed to machine-learning (ML) and deep learning (DL) classifiers. ML classifiers consist of three ensembles: bagging utilizes Random Forest (RF), boosting with Light Gradient Boosting Machine (LGBM) and Xtreme Gradient Boosting (XGB), and stacking with Support Vector Machine (SVC) and XGB as base learners and Logistic Regression (LR) as the Meta classifier. DL classifiers such as fully connected network (FCN), Convolutional neural network (CNN), long short-term memory (LSTM), and gated recurrent unit (GRU) have been employed. The model's performance was assessed through independent set and k-fold testing with 5 and 10 folds, using evaluation metrics such as Accuracy, Recall, Precision, and F1 score. In experiments, DL classifiers have outperformed ML classifiers regarding accuracy score. The proposed model outperformed previous benchmark studies, achieving an Accuracy of 0.86, Recall of 0.901, Precision of 0.866, and F1 score of 0.883 in the independent set test. This method contributes to NLP research by showcasing the utility of a hybrid embedding approach.
DOI: 10.15468/dl.nbcwgh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.605311 -33.195687, 148.605311 -33.197933, 148.612048 -33.197933, 148.612048 -33.195687, 148.605311 -33.195687))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057563-240626123714530/datasets/export for details.
DOI: 10.15468/dl.hsfv8q
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.643489 -33.195687, 148.643489 -33.202424, 148.645735 -33.202424, 148.645735 -33.195687, 148.643489 -33.195687))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057564-240626123714530/datasets/export for details.
DOI: 10.15468/dl.rtfm2j
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.668193 -33.195687, 148.668193 -33.197933, 148.672685 -33.197933, 148.672685 -33.195687, 148.668193 -33.195687))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057565-240626123714530/datasets/export for details.
DOI: 10.15468/dl.7mum9x
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.710863 -33.193441, 148.710863 -33.195687, 148.706372 -33.195687, 148.706372 -33.200179, 148.710863 -33.200179, 148.710863 -33.197933, 148.715355 -33.197933, 148.715355 -33.202424, 148.719846 -33.202424, 148.719846 -33.197933, 148.717601 -33.197933, 148.717601 -33.195687, 148.719846 -33.195687, 148.719846 -33.193441, 148.710863 -33.193441))"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057567-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vys3nd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.722092 -33.195687, 148.722092 -33.197933, 148.726584 -33.197933, 148.726584 -33.202424, 148.72883 -33.202424, 148.72883 -33.197933, 148.733321 -33.197933, 148.733321 -33.195687, 148.722092 -33.195687))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057568-240626123714530/datasets/export for details.
DOI: 10.15468/dl.6vdffp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.218414 -33.195687, 149.218414 -33.197933, 149.22066 -33.197933, 149.22066 -33.202424, 149.225151 -33.202424, 149.225151 -33.195687, 149.218414 -33.195687))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057569-240626123714530/datasets/export for details.
DOI: 10.15468/dl.xyy5ja
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Ustilago maydis (DC.) Corda"
 ]
}

 The dataset includes 33 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057570-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.be9dqv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.598573 -33.197933, 148.598573 -33.200179, 148.603065 -33.200179, 148.603065 -33.197933, 148.598573 -33.197933))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057571-240626123714530/datasets/export for details.
DOI: 10.15468/dl.c8g2yu
title: Occurrence Download

description: A dataset containing 1368852 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Haliaeetus albicilla (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 1368852 records from 239 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057566-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tuxfpp
title: Occurrence Download

description: A dataset containing 4250 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Eudyptes schlegeli Finsch, 1876"
 ]
}

 The dataset includes 4250 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057572-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vdtn6b
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((149.478926 -33.197933, 149.478926 -33.202424, 149.481172 -33.202424, 149.481172 -33.197933, 149.478926 -33.197933)), ((149.481172 -33.202424, 149.481172 -33.20467, 149.48791 -33.20467, 149.48791 -33.202424, 149.481172 -33.202424)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057573-240626123714530/datasets/export for details.
DOI: 10.15468/dl.5277x8
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.293145 -33.150771, 148.293145 -33.155263, 148.290899 -33.155263, 148.290899 -33.157508, 148.284161 -33.157508, 148.284161 -33.170983, 148.288653 -33.170983, 148.288653 -33.159754, 148.290899 -33.159754, 148.290899 -33.164246, 148.293145 -33.164246, 148.293145 -33.159754, 148.297636 -33.159754, 148.297636 -33.166492, 148.299882 -33.166492, 148.299882 -33.157508, 148.297636 -33.157508, 148.297636 -33.150771, 148.293145 -33.150771)), ((148.299882 -33.166492, 148.299882 -33.170983, 148.304374 -33.170983, 148.304374 -33.166492, 148.299882 -33.166492)), ((148.304374 -33.170983, 148.304374 -33.173229, 148.308865 -33.173229, 148.308865 -33.170983, 148.304374 -33.170983)), ((148.308865 -33.173229, 148.308865 -33.179966, 148.315603 -33.179966, 148.315603 -33.173229, 148.308865 -33.173229)), ((148.315603 -33.179966, 148.315603 -33.182212, 148.320094 -33.182212, 148.320094 -33.179966, 148.315603 -33.179966)), ((148.320094 -33.182212, 148.320094 -33.186704, 148.326832 -33.186704, 148.326832 -33.182212, 148.320094 -33.182212)), ((148.326832 -33.186704, 148.326832 -33.195687, 148.315603 -33.195687, 148.315603 -33.202424, 148.320094 -33.202424, 148.320094 -33.20467, 148.32234 -33.20467, 148.32234 -33.202424, 148.326832 -33.202424, 148.326832 -33.218145, 148.329077 -33.218145, 148.329077 -33.186704, 148.326832 -33.186704)))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057575-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n222tq
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.683914 -33.197933, 148.683914 -33.20467, 148.681668 -33.20467, 148.681668 -33.206916, 148.688405 -33.206916, 148.688405 -33.20467, 148.692897 -33.20467, 148.692897 -33.202424, 148.688405 -33.202424, 148.688405 -33.197933, 148.683914 -33.197933))"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057577-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.