cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30365543
title: Influence of scour hole geometry on lateral bearing capacity of nearshore rigid piles

description: Rigid piles supporting nearshore wind turbines in marine environments are subjected to lateral loads and local scour, which reduces their bearing capacity. This study investigates the influence of scour hole geometry on the lateral bearing capacity of rigid piles utilizing the finite element limit analysis method (FELAM) for efficient prediction. The accuracy of the numerical model is validated against existing studies. Extensive analyses are then conducted, varying scour hole geometry, shear strength parameters, and pile slenderness ratio. Dimensionless lateral bearing capacities and reduction factors are presented in design charts for practical engineering use. Key findings reveal scour depth as the dominant factor affecting capacity, with a critical scour width (3 ∼ 5 times pile diameter) beyond which further increases have a negligible impact. Scour angle positively correlates with capacity, but its influence diminishes beyond a certain scour depth threshold (3 times pile diameter). The internal friction angle exhibits complex behavior, with its influence reduced as scour depth increases. Higher slenderness ratios enhance lateral bearing capacity under scour. The derived reduction factors can be reasonably extended to cases with varying cohesion and slenderness ratio, providing a robust tool for design applications.
DOI: 10.6084/m9.figshare.30365543.v1
title: Influence of scour hole geometry on lateral bearing capacity of nearshore rigid piles

description: Rigid piles supporting nearshore wind turbines in marine environments are subjected to lateral loads and local scour, which reduces their bearing capacity. This study investigates the influence of scour hole geometry on the lateral bearing capacity of rigid piles utilizing the finite element limit analysis method (FELAM) for efficient prediction. The accuracy of the numerical model is validated against existing studies. Extensive analyses are then conducted, varying scour hole geometry, shear strength parameters, and pile slenderness ratio. Dimensionless lateral bearing capacities and reduction factors are presented in design charts for practical engineering use. Key findings reveal scour depth as the dominant factor affecting capacity, with a critical scour width (3 ∼ 5 times pile diameter) beyond which further increases have a negligible impact. Scour angle positively correlates with capacity, but its influence diminishes beyond a certain scour depth threshold (3 times pile diameter). The internal friction angle exhibits complex behavior, with its influence reduced as scour depth increases. Higher slenderness ratios enhance lateral bearing capacity under scour. The derived reduction factors can be reasonably extended to cases with varying cohesion and slenderness ratio, providing a robust tool for design applications.
DOI: 10.15468/dl.hugarv
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Xanthium pensylvanicum",
 "Country is Ukraine",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024211-251009101135966/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.29721867
title: Effect Aliasing in Observational Studies

description: In experimental design, aliasing of effects occurs in fractional factorial experiments, where certain low order factorial effects are indistinguishable from certain high order interactions: low order contrast weights may be orthogonal to one another, while their higher order interactions are aliased and not identified. In observational studies, aliasing occurs when certain combinations of covariates—for example, time period and various eligibility criteria for treatment—perfectly predict the treatment that an individual will receive, so a covariate combination is aliased with a particular treatment. In this situation, when a contrast among several groups is used to estimate a treatment effect, collections of individuals defined by contrast weights may be balanced with respect to summaries of low-order interactions between covariates and treatments, but necessarily not balanced with respect high-order interactions. We develop a theory of aliasing in observational studies, illustrate that theory in an observational study whose aliasing is more robust than conventional difference-in-differences, and develop a new form of matching to construct balanced confounded factorial designs from observational data. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.29721867.v1
title: Effect Aliasing in Observational Studies

description: In experimental design, aliasing of effects occurs in fractional factorial experiments, where certain low order factorial effects are indistinguishable from certain high order interactions: low order contrast weights may be orthogonal to one another, while their higher order interactions are aliased and not identified. In observational studies, aliasing occurs when certain combinations of covariates—for example, time period and various eligibility criteria for treatment—perfectly predict the treatment that an individual will receive, so a covariate combination is aliased with a particular treatment. In this situation, when a contrast among several groups is used to estimate a treatment effect, collections of individuals defined by contrast weights may be balanced with respect to summaries of low-order interactions between covariates and treatments, but necessarily not balanced with respect high-order interactions. We develop a theory of aliasing in observational studies, illustrate that theory in an observational study whose aliasing is more robust than conventional difference-in-differences, and develop a new form of matching to construct balanced confounded factorial designs from observational data. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.15468/dl.q5un8x
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Passeriformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((80 -70,90 -70,90 -60,80 -60,80 -70))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024209-251009101135966/datasets/export for details.
DOI: 10.6084/m9.figshare.29828784
title: Inference on the Proportion of Variance Explained in Principal Component Analysis

description: Principal component analysis (PCA) is a longstanding approach for dimension reduction. It rests upon the assumption that the underlying signal has low rank, and thus can be well-summarized using a small number of dimensions. The output of PCA is typically represented using a scree plot, which displays the proportion of variance explained (PVE) by each principal component. While the PVE is extensively reported in routine analyses, to the best of our knowledge the notion of <i>inference</i> on the PVE remains unexplored. We consider inference on a new population quantity for the PVE with respect to an unknown matrix mean. Our interest lies in the PVE of the sample principal components (as opposed to unobserved population principal components); thus, the population PVE that we introduce is defined <i>conditional</i> on the sample singular vectors. We show that it is possible to conduct inference, in the sense of confidence intervals, <i>p</i>-values, and point estimates, on this population quantity. Furthermore, we can conduct valid inference on the PVE of a subset of the principal components, even when the subset is selected using a data-driven approach such as the elbow rule. We demonstrate our approach in simulation and in an application to gene expression data. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.29828784.v2
title: Inference on the Proportion of Variance Explained in Principal Component Analysis

description: Principal component analysis (PCA) is a longstanding approach for dimension reduction. It rests upon the assumption that the underlying signal has low rank, and thus can be well-summarized using a small number of dimensions. The output of PCA is typically represented using a scree plot, which displays the proportion of variance explained (PVE) by each principal component. While the PVE is extensively reported in routine analyses, to the best of our knowledge the notion of <i>inference</i> on the PVE remains unexplored. We consider inference on a new population quantity for the PVE with respect to an unknown matrix mean. Our interest lies in the PVE of the sample principal components (as opposed to unobserved population principal components); thus, the population PVE that we introduce is defined <i>conditional</i> on the sample singular vectors. We show that it is possible to conduct inference, in the sense of confidence intervals, <i>p</i>-values, and point estimates, on this population quantity. Furthermore, we can conduct valid inference on the PVE of a subset of the principal components, even when the subset is selected using a data-driven approach such as the elbow rule. We demonstrate our approach in simulation and in an application to gene expression data. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.29828784.v1
title: Inference on the proportion of variance explained in principal component analysis

description: Principal component analysis (PCA) is a longstanding approach for dimension reduction. It rests upon the assumption that the underlying signal has low rank, and thus can be well-summarized using a small number of dimensions. The output of PCA is typically represented using a scree plot, which displays the proportion of variance explained (PVE) by each principal component. While the PVE is extensively reported in routine analyses, to the best of our knowledge the notion of <i>inference</i> on the PVE remains unexplored. We consider inference on a new population quantity for the PVE with respect to an unknown matrix mean. Our interest lies in the PVE of the sample principal components (as opposed to unobserved population principal components); thus, the population PVE that we introduce is defined <i>conditional</i> on the sample singular vectors. We show that it is possible to conduct inference, in the sense of confidence intervals, p-values, and point estimates, on this population quantity. Furthermore, we can conduct valid inference on the PVE of a subset of the principal components, even when the subset is selected using a data-driven approach such as the elbow rule. We demonstrate our approach in simulation and in an application to gene expression data.
DOI: 10.15468/dl.8c66mj
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Procellariiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-70 -80,-60 -80,-60 -70,-70 -70,-70 -80))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024210-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x8ctmv
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Elymus sibiricus",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 119 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005372-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vmdk3w
title: Occurrence Download

description: A dataset containing 600 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tagetes minuta",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 600 records from 107 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005374-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2ac78d
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mimosa pigra",
 "Country is Myanmar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005373-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.72aa96
title: Occurrence Download

description: A dataset containing 16131 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((130.9579 42.32992,131.43816 42.32992,131.43816 42.86218,130.9579 42.86218,130.9579 42.32992))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 16131 records from 113 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005375-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2b85pz
title: Occurrence Download

description: A dataset containing 16131 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((130.9579 42.32992,131.43816 42.32992,131.43816 42.86218,130.9579 42.86218,130.9579 42.32992))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 16131 records from 113 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005376-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a4at7t
title: Occurrence Download

description: A dataset containing 197 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((72.01940 9.10727,86.14696 9.10727,86.14696 14.76412,72.01940 14.76412,72.01940 9.10727))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Calotes calotes"
 ]
}

 The dataset includes 197 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005377-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/342-7wy-8k4
title: Dicotyledoneae DC.

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.15468/dl.msfwre
title: Occurrence Download

description: A dataset containing 17202 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Deroceras laeve"
 ]
}

 The dataset includes 17202 records from 284 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005379-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wnryf4
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tagetes minuta",
 "Country is Burundi",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005381-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j7qap6
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mimosa pigra",
 "Country is Niger",
 "HasCoordinate is true"
 ]
}

 The dataset includes 74 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005380-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.21606
title: Logic Syllogistic reasoning Algorithms
title: Logic Syllogistic reasoning Algorithms

description: Logic Syllogistic Reasoning Algorithms
description: Logic Syllogistic Reasoning Algorithms
DOI: 10.15468/dl.fugyqw
title: Occurrence Download

description: A dataset containing 1682 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Scutellaria siphocampyloides"
 ]
}

 The dataset includes 1682 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005382-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g2hc8g
title: Occurrence Download

description: A dataset containing 3758 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calochortus amabilis"
 ]
}

 The dataset includes 3758 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005384-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7223na
title: Occurrence Download

description: A dataset containing 32886 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Celastrus orbiculatus, Celastrus articulatus papillosus, Celastrus crispulus, Celastrus orbiculatus major, Celastrus articulatus papillosus, Celastrus orbiculatus aureoarillatus, Celastrus articulatus humilis, Celastrus orbiculatus punctatus, Celastrus articulatus, Celastrus tatarinowii, Celastrus articulatus, Ilex leucantha, Celastrus insularis, Celastrus jeholensis, Celastrus orbiculatus major, Celastrus orbiculatus strigillosus, Celastrus articulatus orbiculata, Celastrus orbiculatus papillosus, Celastrus orbiculatus papillosus, Celastrus orbiculatus aureoarillatus, Catha articulata)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 32886 records from 196 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005383-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hgjbpw
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pennellia microsperma"
 ]
}

 The dataset includes 11 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005386-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5g7skf
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is RUS.18_1",
 "TaxonKey is Rorippa sylvestris"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005387-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xja66x
title: Occurrence Download

description: A dataset containing 10191 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Artemisia pontica sericea, Artemisia tenuifolia, Asperugo procumbens, Asperugo alba, Asperugo alba, Asperugo erecta, Asperugo vulgaris, Asperugo vulgaris, Astragalus sulcatus, Astragalus holopterus)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Continent is Europe",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 10191 records from 213 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005385-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k3kugn
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eutrema sulphureum"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005388-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wcmssr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Setophaga virens)",
 "Country is one of (American Samoa, Australia, Christmas Island, Cocos (Keeling) Islands, Cook Islands, Fiji, French Polynesia, Guam, Heard Island and McDonald Islands, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia, New Zealand, Niue, Norfolk Island, Northern Mariana Islands, Palau, Papua New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, United States Minor Outlying Islands, Vanuatu, Wallis and Futuna)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005390-250717081556266/datasets/export for details.