cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25824/redu/n5rbut
title: Climacteric in women with gynecological malignant neoplasms

description: Introduction: Gynecological cancers accounted for 43.1% of the estimated incidence of new oncological cases in women in 2020, with 30 to 40% of these diagnoses made during perimenopause. Women living in menopause may present vasomotor, somatic, psychological and urogenital problems, with reduced quality of life, in addition to changes in the metabolic profile, increasing cardiovascular risk and reducing bone mass. Thus, there is an elderly population recently diagnosed with gynecological cancer or already cured of it, with significant life expectancy, experiencing the physical, psychological, sexual and social effects of the disease, with climacteric symptoms and an increased risk of cardiovascular and osteoporotic diseases, both natural and induced by treatment, which require attention. Although some studies show that hormone replacement therapy (HRT) can improve several climacteric parameters, in women with a history of gynecological cancer, the possibility of hormonal influence on the development of some female neoplastic modalities represents a contraindication for HRT, particularly via systemic route. Objectives: To evaluate the different aspects related to the menopausal transition of women with gynecological malignant neoplasms and compare them to women without this history. Methods: A prospective cohort study will be carried out with climacteric women with and without gynecological malignant neoplasm. All women who start follow-up at the menopause outpatient clinic of Hospital da Mulher Prof. Dr. José Aristodemo Pinotti - CAISM/Unicamp during the period from October 1, 2022 to December 31, 2023 will be invited to participate, or until reaching a sample size of 100 women in each group, who meet the eligibility criteria. They will be included in the study after obtaining the informed consent form (ICF) and then a complete anamnesis will be performed, followed by data collection, consisting of sociodemographic and clinical variables, a questionnaire to measure menopausal symptoms (Menopause Rating Scale), an instrument to assess quality of life (WHQ), an assessment of sexual function (Female Sexual Function Index) and screening for depression (PHQ-9). A general physical examination and gynecological examination will be performed, with assessment of blood pressure, body mass index, vaginal health score index and collection of vaginal cytology. Patients will be referred for collection of biochemical tests and bone densitometry. An Excel file containing all evaluations and participant data will be generated. For reasons of confidentiality, data cannot be made available. For questions and possible reuse of the data, please contact the authors by email.
DOI: 10.15468/dl.g9m8p8
title: Occurrence Download

description: A dataset containing 77364 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation)",
 "License is one of (CC-BY 4.0, CC0 1.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Lynx Kerr, 1792"
 ]
}

 The dataset includes 77364 records from 173 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041750-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ea6k26
title: Occurrence Download

description: A dataset containing 69664 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rangifer tarandus (Linnaeus, 1758)"
 ]
}

 The dataset includes 69664 records from 184 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041752-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wzusvx
title: Occurrence Download

description: A dataset containing 262 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nautichthys oculofasciatus (Girard, 1858)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 262 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041761-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ep2b4g
title: Occurrence Download

description: A dataset containing 10292 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Country derived from coordinates, Continent derived from coordinates, Occurrence status inferred from individual count)",
 "OccurrenceStatus is Present",
 "TaxonKey is Grus grus (Linnaeus, 1758)",
 "Year 1000-1990"
 ]
}

 The dataset includes 10292 records from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041760-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5rr1q01g
title: MassIVE MSV000096703 - An inter-specific Amaranthus pangenome captures genetic variation potentially underlying key leafy vegetable traits in this underutilised crop
title: Metabolomics LCMSMS data files from eight amaranth species: four A. cruentus and four A. hypochondriacus. These accessions are the parents of a Multi-parent Advanced Generation Inter-Cross (MAGIC) population and we demonstrate variation in leafy vegetable traits, including yield and metabolite profiles.
DOI: 10.17605/osf.io/dxy4p
title: Who did it

description: UIST 2024 submission: Who did it? How User Agency is influenced by Visual Properties of Generated Images
DOI: 10.57754/fdat.5nfpj-w5g91
title: Verbal aspect in indirect speech

description: This experiment tests how VPs transform direct speech into indirect speech.
Pretest: Sentence Transformation
Aspect and tense use in subordinate indirect speech.
description: Research carried out in work package C02 of the SFB 833.
DOI: 10.15468/dl.e8mmk5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Euphorbia esula subsp. × pseuodovirgata"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041762-241126133413365/datasets/export for details.
DOI: 10.15468/dl.mx2z9d
title: Occurrence Download

description: A dataset containing 3891 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Daktulosphaira vitifoliae (Fitch, 1855)"
 ]
}

 The dataset includes 3891 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041763-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sfb5n7
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nectoliparis pelagicus Gilbert & Burke, 1912",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041765-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ugcjb7
title: Occurrence Download

description: A dataset containing 160 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Strigops habroptila G.R.Gray, 1845",
 "Year 1963-2024"
 ]
}

 The dataset includes 160 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041764-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.54s6qt
title: Occurrence Download

description: A dataset containing 413855 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bombus terrestris (Linnaeus, 1758)"
 ]
}

 The dataset includes 413855 records from 1186 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041734-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/5ndrsys7rn.1
title: Two-Stage joint distillation strategy for unsupervised anomaly detection in wire arc additive manufacturing

description: In wire arc additive manufacturing (WAAM), real-time defect detection is essential for quality assurance, yet the process is hindered by the scarcity of anomaly samples and the inherent unpredictability of anomaly types. To address the above challenges, this paper proposes an online unsupervised anomaly detection model based on knowledge distillation. A two-stage joint distillation strategy is developed to address the generalization limitations of symmetric teacher-student architectures. The designed model contains both forward distillation and reverse distillation stages, which improves the accuracy of the model in recognizing anomalies. In addition, before verifying the effect of the model, this paper produces a WAAM defect dataset using a welding anomaly detection system. The experimental results show that the average AUROC value for image-level anomaly detection can reach 93.3%. The developed method has practical application prospects in industrial anomaly detection and is of great significance for anomaly feedback in the additive manufacturing process.
DOI: 10.15468/dl.p88x2b
title: Occurrence Download

description: A dataset containing 422 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hedeoma hispida Pursh",
 "Geometry POLYGON((-105 34, -94 34, -94 43, -105 43, -105 34))"
 ]
}

 The dataset includes 422 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003934-250402121839773/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.28732223
title: Raw Life-history Data Kabus et al.csv

description: Associated raw data of phenotypic measurements for manuscript "Morphological crypsis within a crustacean species complex is driven by within-species phenotypic diversification"
DOI: 10.17632/x7tdmsf27x.1
title: Comprehensive Vehicular Communication Network Attack Dataset

description: Abstract: This dataset captures critical vehicular-specific attacks (Position Spoofing, Sybil, and Wormhole) in Vehicular Communication Networks (VCNs). It incorporates legitimate and malicious instances generated using realistic mobility patterns, positional dynamics, and temporal interactions.

Dataset Details:

Instances:

Spoofing: 45,975 legitimate, 589 malicious

Wormhole: 52,237 legitimate, 5,219 malicious

Sybil: 14,829 legitimate, 1,753 malicious

Features Included: Mobility dynamics (speed, rate of distance change), Positional features (location, inter-vehicle distances), Temporal features (time intervals), Communication metrics (packets count, transmission rates, reception rates, hop counts), Attack-specific labels (Spoofing, Sybil, Wormhole)
DOI: 10.15156/bio/sh1157725.10fu
title: SH1157725.10FU

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/sh1157727.10fu
title: SH1157727.10FU

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/sh1157731.10fu
title: SH1157731.10FU

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/sh1157732.10fu
title: SH1157732.10FU

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/sh1157734.10fu
title: SH1157734.10FU

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/sh1157735.10fu
title: SH1157735.10FU

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/sh1157738.10fu
title: SH1157738.10FU

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/sh1157739.10fu
title: SH1157739.10FU

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/sh1157743.10fu
title: SH1157743.10FU

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/sh1157745.10fu
title: SH1157745.10FU

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.