cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1062739.10fu
title: SH1062739.10FU

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/sh1062741.10fu
title: SH1062741.10FU

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/sh1062742.10fu
title: SH1062742.10FU

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/sh1062743.10fu
title: SH1062743.10FU

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/sh1062745.10fu
title: SH1062745.10FU

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: 10.5281/zenodo.14261080
title: lithobates_vaillanti_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.14261081
title: lithobates_vaillanti_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.14260568
title: Understanding the Nitrogen Reduction Reaction Mechanism on CuFeO2 Photocathodes

description: This is a data set for the corresponding research article. It provides the necessary input files and optimized geometries to reproduce or extend this data set. The folders are uploaded on GitLab (project ID: 62597469). There are two versions one is for windows users (.zip) and the other for Linux users (*.tar.gz). Information on how to navigate through the folder structure is described in the README.md file in the dataset folder.

The work was funded by the DFG through the priority program SPP-2370 (project id 502202153) and project 501805371, and through the collaborative research center SFB-1316 (project 327886311). 

Further questions or remarks can be sent to this dataset's creator (julian.bessner@uni-ulm.de).
DOI: 10.5281/zenodo.14260569
title: Understanding the Nitrogen Reduction Reaction Mechanism on CuFeO2 Photocathodes

description: This is a data set for the corresponding research article. It provides the necessary input files and optimized geometries to reproduce or extend this data set. The folders are uploaded on GitLab (project ID: 62597469). There are two versions one is for windows users (.zip) and the other for Linux users (*.tar.gz). Information on how to navigate through the folder structure is described in the README.md file in the dataset folder.

The work was funded by the DFG through the priority program SPP-2370 (project id 502202153) and project 501805371, and through the collaborative research center SFB-1316 (project 327886311). 

Further questions or remarks can be sent to this dataset's creator (julian.bessner@uni-ulm.de).
DOI: 10.15468/dl.rb3v32
title: Occurrence Download

description: A dataset containing 3535 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Allium textile A.Nelson & J.F.Macbr.",
 "Geometry POLYGON((-141 24, -53 24, -53 83, -141 83, -141 24))"
 ]
}

 The dataset includes 3535 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012290-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ufbe9a
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Begonia cleopatrae Coyle)"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012292-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5519/qd.dc4pu8ff
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (12 records)
DOI: 10.15468/dl.2rdwu3
title: Occurrence Download

description: A dataset listing the 902 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Herbario Virtual Bosques Secos de Colombia - Sección Herbario Universidad de Córdoba (HUC)"
 ]
}

 The dataset's 902 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012254-241126133413365/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.27144827.v1
title: Practical and Optimal Likelihood Intervals and Regions for Weibull and Gumbel Distributions

description: Profile likelihood intervals with good coverage probabilities and convenient simple expressions are presented to estimate separately and efficiently each of the parameters and quantiles of Weibull and Gumbel distributions, widely used in reliability and environmental applications. For the first time, likelihood-confidence intervals for these distributions, that were previously unavailable, can now be easily and quickly calculated with the provided R code for sample sizes n≥10. For simultaneous estimation of both parameters, likelihood-confidence regions are also provided. The proposal takes advantage of the transformation relationship between the Weibull and Gumbel distributions, of the fact that this latter distribution belongs to the Location and Scale family of distributions, and of likelihood symmetrizing parameterizations, all leading to simpler inferences about the parameters. The plot of the relative profile likelihood of a quantile of interest and its corresponding profile likelihood intervals provide decision makers with useful information in many practical applications, particularly when comparing two treatments. The proposed intervals for the Weibull shape parameter facilitate testing if an exponential distribution is reasonable for the data. The proposed methods are illustrated with practical examples.
DOI: 10.6084/m9.figshare.27144827
title: Practical and Optimal Likelihood Intervals and Regions for Weibull and Gumbel Distributions

description: Profile likelihood intervals with good coverage probabilities and convenient simple expressions are presented to estimate separately and efficiently each of the parameters and quantiles of Weibull and Gumbel distributions, widely used in reliability and environmental applications. For the first time, likelihood-confidence intervals for these distributions, that were previously unavailable, can now be easily and quickly calculated with the provided R code for sample sizes n≥10. For simultaneous estimation of both parameters, likelihood-confidence regions are also provided. The proposal takes advantage of the transformation relationship between the Weibull and Gumbel distributions, of the fact that this latter distribution belongs to the Location and Scale family of distributions, and of likelihood symmetrizing parameterizations, all leading to simpler inferences about the parameters. The plot of the relative profile likelihood of a quantile of interest and its corresponding profile likelihood intervals provide decision makers with useful information in many practical applications, particularly when comparing two treatments. The proposed intervals for the Weibull shape parameter facilitate testing if an exponential distribution is reasonable for the data. The proposed methods are illustrated with practical examples.
DOI: 10.6084/m9.figshare.27252229
title: Strata Design for Variance Reduction in Stochastic Simulation

description: Stratified sampling is one of the powerful variance reduction methods for analyzing system performance, such as reliability, with stochastic simulation. It divides the input space into disjoint subsets, called strata, to draw samples from each stratum. Partitioning the input space properly and allocating greater computational effort to crucial strata can help accurately estimate system performance with a limited computational budget. How to create strata, however, has yet to be thoroughly examined. Strata design faces the curse of dimensionality and data scarcity as the input dimension increases. We analytically derive the optimal stratification structure that minimizes the estimation variance for univariate problems. Further, reconciling the optimal stratification into decision trees, we devise a robust algorithm for multi-dimensional problems. Numerical experiments and a wind turbine case study demonstrate the superiority of the proposed method in terms of variance reduction, leading to computational efficiency and scalability.
DOI: 10.6084/m9.figshare.27252229.v1
title: Strata Design for Variance Reduction in Stochastic Simulation

description: Stratified sampling is one of the powerful variance reduction methods for analyzing system performance, such as reliability, with stochastic simulation. It divides the input space into disjoint subsets, called strata, to draw samples from each stratum. Partitioning the input space properly and allocating greater computational effort to crucial strata can help accurately estimate system performance with a limited computational budget. How to create strata, however, has yet to be thoroughly examined. Strata design faces the curse of dimensionality and data scarcity as the input dimension increases. We analytically derive the optimal stratification structure that minimizes the estimation variance for univariate problems. Further, reconciling the optimal stratification into decision trees, we devise a robust algorithm for multi-dimensional problems. Numerical experiments and a wind turbine case study demonstrate the superiority of the proposed method in terms of variance reduction, leading to computational efficiency and scalability.
DOI: 10.6084/m9.figshare.27325309
title: Remaining Useful Life Prediction Based on Forward Intensity

description: Remaining useful life (RUL) prediction is an essential tool for enhancing the reliability and resilience of systems. Most existing RUL prediction methods consider degradation-induced failures, and assume there exists a fixed failure threshold for degradation signals. In many real applications, however, it is difficult or even impossible to find such failure thresholds, making the RUL prediction a challenging task. This study addresses the challenge by exploiting the method of forward intensity, a novel tool introduced in econometrics. In particular, the historical degradation signals are treated as time-varying covariates for the forward intensity. The dynamics of unobserved future degradation signals are captured by a time-varying regression parameter in the forward intensity function, which are usually estimated using the maximum pseudolikelihood method in existing studies. To improve prediction accuracy, this study proposes a new estimation method based on smoothing splines. The proposed method not only allows RUL prediction in the absence of a fixed failure threshold, but also achieves satisfactory prediction accuracy with reasonable interpretability of covariate effects. Prediction intervals for the RUL are also developed. The effectiveness of the proposed method is validated through Monte Carlo simulations and three real-data examples. The results show that the proposed method outperforms existing methods in terms of prediction accuracy.
DOI: 10.6084/m9.figshare.27325309.v1
title: Remaining Useful Life Prediction Based on Forward Intensity

description: Remaining useful life (RUL) prediction is an essential tool for enhancing the reliability and resilience of systems. Most existing RUL prediction methods consider degradation-induced failures, and assume there exists a fixed failure threshold for degradation signals. In many real applications, however, it is difficult or even impossible to find such failure thresholds, making the RUL prediction a challenging task. This study addresses the challenge by exploiting the method of forward intensity, a novel tool introduced in econometrics. In particular, the historical degradation signals are treated as time-varying covariates for the forward intensity. The dynamics of unobserved future degradation signals are captured by a time-varying regression parameter in the forward intensity function, which are usually estimated using the maximum pseudolikelihood method in existing studies. To improve prediction accuracy, this study proposes a new estimation method based on smoothing splines. The proposed method not only allows RUL prediction in the absence of a fixed failure threshold, but also achieves satisfactory prediction accuracy with reasonable interpretability of covariate effects. Prediction intervals for the RUL are also developed. The effectiveness of the proposed method is validated through Monte Carlo simulations and three real-data examples. The results show that the proposed method outperforms existing methods in terms of prediction accuracy.
DOI: 10.15468/dl.6jzy34
title: Occurrence Download

description: A dataset containing 18497 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Incilius valliceps (Wiegmann, 1833)"
 ]
}

 The dataset includes 18497 records from 141 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012293-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rpvmkw
title: Occurrence Download

description: A dataset containing 439 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Anaxyrus fowleri (Hinckley, 1882)"
 ]
}

 The dataset includes 439 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012296-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qjm328
title: Occurrence Download

description: A dataset containing 70891 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Calidris alpina (Linnaeus, 1758)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 70891 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012291-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e9hkq7
title: Occurrence Download

description: A dataset containing 1767 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "OccurrenceStatus is Present",
 "TaxonKey is Mastigodryas Amaral, 1935"
 ]
}

 The dataset includes 1767 records from 145 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012294-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gzcc52
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Begonia copelandii Merr.)"
 ]
}

 The dataset includes 10 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012297-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g3nv6g
title: Occurrence Download

description: A dataset containing 1931874 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "DatasetKey is EOD – eBird Observation Dataset",
 "Year 2019-2024"
 ]
}

 The dataset includes 1931874 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012258-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.99wbbn
title: Occurrence Download

description: A dataset containing 5032 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cirsium undulatum (Nutt.) Spreng.",
 "Geometry POLYGON((-141 24, -53 24, -53 83, -141 83, -141 24))"
 ]
}

 The dataset includes 5032 records from 99 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012298-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14261117
title: ranunculus_cortusifolius_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.14261118
title: ranunculus_cortusifolius_zanfona_1.fasta.gz
DOI: 10.15468/dl.5jpnve
title: Occurrence Download

description: A dataset containing 36125 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.99194 8.65951,-75.67372 8.65951,-75.67372 8.86234,-75.99194 8.86234,-75.99194 8.65951))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 36125 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012295-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zhfaed
title: Occurrence Download

description: A dataset containing 1118108 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corylus avellana L."
 ]
}

 The dataset includes 1118108 records from 3538 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012276-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ak2rbg
title: Occurrence Download

description: A dataset containing 43179 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Galeocerdo cuvier (Péron & Lesueur, 1822)"
 ]
}

 The dataset includes 43179 records from 214 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000675-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xca9qr
title: Occurrence Download

description: A dataset containing 630339 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ficaria verna Huds.)",
 "BasisOfRecord is one of (Machine Observation, Human Observation, Observation, Literature Occurrence)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 630339 records from 1870 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000639-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uhnpgm
title: Occurrence Download

description: A dataset containing 1803 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Actinidia chinensis var. deliciosa (A.Chev.) A.Chev."
 ]
}

 The dataset includes 1803 records from 106 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017232-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.