cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.n8gg8z
title: Occurrence Download

description: A dataset containing 569811 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Observation)",
 "Country is United States of America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "StateProvince is one of (Michigan, Wisconsin)",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 569811 records from 204 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005391-260120142942310/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.29039858
title: A Data-Driven Machine Learning Model for Predicting Demand-to-Capacity Ratio for RC Jacketing of Seismically Deficient Buildings

description: Existing reinforced concrete (RC) buildings are often vulnerable to earthquakes for various reasons, including noncompliance with seismic design standards, irregularities in mass and architectural plans, and construction defects. The columns of these buildings are not designed to withstand seismic forces; instead, they are meant mainly to support only gravity loads, making them susceptible to partial damage or system collapse during earthquakes. To enhance the capacity of such columns against seismic force, they are typically retrofitted using an RC jacketing system. The parametric modelling and design of any RC jacketed structure using computer-aided analysis and design can involve significant effort with time consumption. Therefore, to achieve a reasonable accuracy in design with lesser computational time, this work proposes a novel data-driven method to predict the demand-to-capacity ratio (DCR) of RC jacketed columns using an artificial neural network (ANN). To predict the DCR, various design variables associated with RC column jacketing are considered, like retrofit placement, concrete compressive strength, cross-sectional characteristics, jacket thickness, longitudinal reinforcement ratio, transverse reinforcement area, and slenderness ratio. In this study, a finite element (FE) program is used to generate datasets of jacket design to train a multilayer feedforward neural network (MLFFNN). Performance evaluations of the developed model are made by using four statistical measures - mean absolute error (MAE), mean absolute percentage error (MAPE), mean squared error (MSE), and the coefficient of determination (R2). The results show that the model successfully predicts DCR values with less than 7% variation compared to the FE solution, demonstrating the model's reliability, accuracy, and computation cost saving in predicting the DCR of seismically deficient columns in an RC building.
DOI: 10.6084/m9.figshare.29039858.v2
title: A Data-Driven Machine Learning Model for Predicting Demand-to-Capacity Ratio for RC Jacketing of Seismically Deficient Buildings

description: Existing reinforced concrete (RC) buildings are often vulnerable to earthquakes for various reasons, including noncompliance with seismic design standards, irregularities in mass and architectural plans, and construction defects. The columns of these buildings are not designed to withstand seismic forces; instead, they are meant mainly to support only gravity loads, making them susceptible to partial damage or system collapse during earthquakes. To enhance the capacity of such columns against seismic force, they are typically retrofitted using an RC jacketing system. The parametric modelling and design of any RC jacketed structure using computer-aided analysis and design can involve significant effort with time consumption. Therefore, to achieve a reasonable accuracy in design with lesser computational time, this work proposes a novel data-driven method to predict the demand-to-capacity ratio (DCR) of RC jacketed columns using an artificial neural network (ANN). To predict the DCR, various design variables associated with RC column jacketing are considered, like retrofit placement, concrete compressive strength, cross-sectional characteristics, jacket thickness, longitudinal reinforcement ratio, transverse reinforcement area, and slenderness ratio. In this study, a finite element (FE) program is used to generate datasets of jacket design to train a multilayer feedforward neural network (MLFFNN). Performance evaluations of the developed model are made by using four statistical measures - mean absolute error (MAE), mean absolute percentage error (MAPE), mean squared error (MSE), and the coefficient of determination (R2). The results show that the model successfully predicts DCR values with less than 7% variation compared to the FE solution, demonstrating the model's reliability, accuracy, and computation cost saving in predicting the DCR of seismically deficient columns in an RC building.
DOI: 10.6084/m9.figshare.29039858.v3
title: A Data-Driven Machine Learning Model for Predicting Demand-to-Capacity Ratio for RC Jacketing of Seismically Deficient Buildings

description: Existing reinforced concrete (RC) buildings are often vulnerable to earthquakes for various reasons, including noncompliance with seismic design standards, irregularities in mass and architectural plans, and construction defects. The columns of these buildings are not designed to withstand seismic forces; instead, they are meant mainly to support only gravity loads, making them susceptible to partial damage or system collapse during earthquakes. To enhance the capacity of such columns against seismic force, they are typically retrofitted using an RC jacketing system. The parametric modelling and design of any RC jacketed structure using computer-aided analysis and design can involve significant effort with time consumption. Therefore, to achieve a reasonable accuracy in design with lesser computational time, this work proposes a novel data-driven method to predict the demand-to-capacity ratio (DCR) of RC jacketed columns using an artificial neural network (ANN). To predict the DCR, various design variables associated with RC column jacketing are considered, like retrofit placement, concrete compressive strength, cross-sectional characteristics, jacket thickness, longitudinal reinforcement ratio, transverse reinforcement area, and slenderness ratio. In this study, a finite element (FE) program is used to generate datasets of jacket design to train a multilayer feedforward neural network (MLFFNN). Performance evaluations of the developed model are made by using four statistical measures - mean absolute error (MAE), mean absolute percentage error (MAPE), mean squared error (MSE), and the coefficient of determination (R2). The results show that the model successfully predicts DCR values with less than 7% variation compared to the FE solution, demonstrating the model's reliability, accuracy, and computation cost saving in predicting the DCR of seismically deficient columns in an RC building.
DOI: 10.6084/m9.figshare.25909050
title: The mediating role of science intrinsic motivation: effects of homework on science achievement in Western and Asian regions

description: This study investigated cross-cultural differences in the relationships between science intrinsic motivation, teacher-perceived and student-perceived homework practices, and science achievement in Asian (Chinese Taipei, Japan, South Korean, and Singapore) and Western (Australia, US, England, and Ireland) top-performing regions according to ranking of science achievement in TIMSS. Multilevel confirmatory factor analysis and multilevel structural equation modelling were conducted using data from 45,448 eighth graders in the 2019 TIMSS study. In Western regions, the teacher control of homework was significantly negatively associated with whole-class science achievement and positively associated with whole-class intrinsic motivation. A higher student-perceived frequency of homework is negatively related to their individual intrinsic motivation and science achievement. However, in Asian regions, teacher-perceived frequency and time spent on homework positively predicted the whole-class intrinsic motivation and science achievement, while in contrast, a higher student-perceived frequency of homework was positively associated with their individual intrinsic motivation and a longer time spent on homework was negatively associated with their intrinsic motivation. Intrinsic motivation in science plays a significant mediating role between students’ and teachers’ homework practices and science achievement at individual and whole-class levels in Asian top performers. There, we discuss at the end that the cultural contexts might influence how teachers and students can use homework best to promote science intrinsic motivation and hence their science achievement.
DOI: 10.6084/m9.figshare.25909050.v2
title: The mediating role of science intrinsic motivation: effects of homework on science achievement in Western and Asian regions

description: This study investigated cross-cultural differences in the relationships between science intrinsic motivation, teacher-perceived and student-perceived homework practices, and science achievement in Asian (Chinese Taipei, Japan, South Korean, and Singapore) and Western (Australia, US, England, and Ireland) top-performing regions according to ranking of science achievement in TIMSS. Multilevel confirmatory factor analysis and multilevel structural equation modelling were conducted using data from 45,448 eighth graders in the 2019 TIMSS study. In Western regions, the teacher control of homework was significantly negatively associated with whole-class science achievement and positively associated with whole-class intrinsic motivation. A higher student-perceived frequency of homework is negatively related to their individual intrinsic motivation and science achievement. However, in Asian regions, teacher-perceived frequency and time spent on homework positively predicted the whole-class intrinsic motivation and science achievement, while in contrast, a higher student-perceived frequency of homework was positively associated with their individual intrinsic motivation and a longer time spent on homework was negatively associated with their intrinsic motivation. Intrinsic motivation in science plays a significant mediating role between students’ and teachers’ homework practices and science achievement at individual and whole-class levels in Asian top performers. There, we discuss at the end that the cultural contexts might influence how teachers and students can use homework best to promote science intrinsic motivation and hence their science achievement.
DOI: 10.6084/m9.figshare.25909050.v1
title: The mediating role of science intrinsic motivation: effects of homework on science achievement in Western and Asian regions

description: This study investigated cross-cultural differences in the relationships between science intrinsic motivation, teacher-perceived and student-perceived homework practices, and science achievement in Asian (Chinese Taipei, Japan, South Korean, and Singapore) and Western (Australia, US, England, and Ireland) top-performing regions according to ranking of science achievement in TIMSS. Multilevel confirmatory factor analysis and multilevel structural equation modelling were conducted using data from 45,448 eighth graders in the 2019 TIMSS study. In Western regions, the teacher control of homework was significantly negatively associated with whole-class science achievement and positively associated with whole-class intrinsic motivation. A higher student-perceived frequency of homework is negatively related to their individual intrinsic motivation and science achievement. However, in Asian regions, teacher-perceived frequency and time spent on homework positively predicted the whole-class intrinsic motivation and science achievement, while in contrast, a higher student-perceived frequency of homework was positively associated with their individual intrinsic motivation and a longer time spent on homework was negatively associated with their intrinsic motivation. Intrinsic motivation in science plays a significant mediating role between students’ and teachers’ homework practices and science achievement at individual and whole-class levels in Asian top performers. There, we discuss at the end that the cultural contexts might influence how teachers and students can use homework best to promote science intrinsic motivation and hence their science achievement.
DOI: 10.15468/dl.5d3t28
title: Occurrence Download

description: A dataset containing 7440 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen",
 "TaxonKey is one of (Hymenophyllum capillare, Hymenophyllum hirsutum, Hymenophyllum kuhnii, Crepidomanes africanum, Didymoglossum ballardianum, Didymoglossum chamaedrys, Crepidomanes chevalieri, Crepidomanes clarenceanum, Trichomanes crispiforme, Polyphlebium diaphanum, Abrodictyum dregei, Didymoglossum erosum, Crepidomanes fallax, Vandenboschia gigantea, Abrodictyum guineense, Didymoglossum liberiense, Crepidomanes parvulum, Crepidomanes melanotrichum, Crepidomanes mettenii)"
 ]
}

 The dataset includes 7440 records from 219 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005434-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cj4d9d
title: Occurrence Download

description: A dataset containing 60241 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is ReefSYN | Standardized datasets of Brazilian reef diversity in space and time - Dataset II: Abrolhos Bank monitoring"
 ]
}

 The dataset includes 60241 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005404-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t7mkbh
title: Occurrence Download

description: A dataset containing 56605 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is one of (Congo, Democratic Republic of the, Malawi, Cameroon, Tanzania, United Republic of, Gabon, Zambia)",
 "OccurrenceStatus is Present",
 "TaxonKey is Orchidaceae"
 ]
}

 The dataset includes 56605 records from 120 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005379-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14586413
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.fjq9dn
title: Occurrence Download

description: A dataset containing 228 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-98.91668 18.49958,-97.27294 18.49958,-97.27294 20.08468,-98.91668 20.08468,-98.91668 18.49958))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Lampyridae"
 ]
}

 The dataset includes 228 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005439-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.29tj8y
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "GadmGid is MEX.11_1",
 "TaxonKey is Polystemma viridiflora"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005440-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q9upwx
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Vipera aspis ",
 "Country is Albania",
 "Country is Austria",
 "Country is Bosnia and Herzegovina",
 "Country is Belgium",
 "Country is Bulgaria",
 "Country is Belarus",
 "Country is Switzerland",
 "Country is Cyprus",
 "Country is Czechia",
 "Country is Germany",
 "Country is Denmark",
 "Country is Estonia",
 "Country is Spain",
 "Country is Finland",
 "Country is France",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "Country is Greece",
 "Country is Croatia",
 "Country is Hungary",
 "Country is Ireland",
 "Country is Italy",
 "Country is Lithuania",
 "Country is Luxembourg",
 "Country is Latvia",
 "Country is Moldova, Republic of",
 "Country is Montenegro",
 "Country is North Macedonia",
 "Country is Malta",
 "Country is Netherlands",
 "Country is Norway",
 "Country is Poland",
 "Country is Portugal",
 "Country is Romania",
 "Country is Serbia",
 "Country is Sweden",
 "Country is Slovenia",
 "Country is Slovakia",
 "Country is Türkiye",
 "Country is Ukraine",
 "Country is Kosovo",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005438-260120142942310/datasets/export for details.
DOI: 10.15468/dl.ewmvk6
title: Occurrence Download

description: A dataset containing 610 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "TaxonKey is Herpailurus yagouaroundi"
 ]
}

 The dataset includes 610 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005437-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10679167
title: Sex ratio and sex-specific chick mortality in a species with moderate sexual size dimorphism and female brood desertion - Whiskered Tern Chlidonias hybrida

description: The data refers to publication in the Journal of Ornithology. Data refers to HSR (Hatching Sex Ratio) and FSR (Fledging Sex Ratio) in the Whiskered Tern Chlidonias hybrida (Upper Vistula Valley, Poland) obtained by the Whiskered Tern Reseacrch Team (Ledwon@isez.pan.krakow.pl).
DOI: 10.5281/zenodo.10679168
title: Sex ratio and sex-specific chick mortality in a species with moderate sexual size dimorphism and female brood desertion - Whiskered Tern Chlidonias hybrida

description: The data refers to publication in the Journal of Ornithology. Data refers to HSR (Hatching Sex Ratio) and FSR (Fledging Sex Ratio) in the Whiskered Tern Chlidonias hybrida (Upper Vistula Valley, Poland) obtained by the Whiskered Tern Reseacrch Team (Ledwon@isez.pan.krakow.pl).
DOI: 10.15468/dl.vncjbz
title: Occurrence Download

description: A dataset containing 36249 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Physella acuta"
 ]
}

 The dataset includes 36249 records from 451 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005441-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u7vtp9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lathyrus sativus",
 "Country is Moldova, Republic of",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024714-250811113504898/datasets/export for details.
DOI: 10.15468/dl.vgmvs3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lathyrus sativus",
 "Country is Latvia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024713-250811113504898/datasets/export for details.
DOI: 10.15468/dl.ehkpte
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lathyrus sativus",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 30 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024712-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rve2j8
title: Occurrence Download

description: A dataset containing 8096 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Global Register of Introduced and Invasive Species - United States (Contiguous) (ver.2.0, 2022)",
 "EstablishmentMeans is one of (introduced)"
 ]
}

 The dataset includes 8096 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009177-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xamd2m
title: Occurrence Download

description: A dataset containing 9982041 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((11.83149 51.29958,11.66493 48.09954,19.16497 48.09965,19.33152 51.29969,14.64381 51.29962,11.83149 51.29958))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 9982041 records from 428 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009157-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.