cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.av97kt
title: Occurrence Download

description: A dataset containing 837 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-78.675 2.02318, -78.745306 2.017612, -78.81388 2.001044, -78.879032 1.973885, -78.939156 1.936804, -78.992773 1.890714, -79.03856 1.836752, -79.07539300000001 1.776246, -79.102363 1.710686, -79.118809 1.641689, -79.124325 1.570951, -79.118779 1.500217, -79.102306 1.431226, -79.07531400000001 1.365677, -79.03846900000001 1.305184, -78.992676 1.251236, -78.939064 1.205162, -78.87895399999999 1.168094, -78.813823 1.140945, -78.745276 1.124384, -78.675 1.118818, -78.604724 1.124384, -78.536177 1.140945, -78.471046 1.168094, -78.41093600000001 1.205162, -78.35732400000001 1.251236, -78.311531 1.305184, -78.274686 1.365677, -78.247694 1.431226, -78.23122100000001 1.500217, -78.225675 1.570951, -78.231191 1.641689, -78.247637 1.710686, -78.274607 1.776246, -78.31144 1.836752, -78.35722699999999 1.890714, -78.410844 1.936804, -78.470968 1.973885, -78.53612 2.001044, -78.60469399999999 2.017612, -78.675 2.02318))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 837 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002360-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gsuesc
title: Occurrence Download

description: A dataset containing 1212 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 "GadmGid is one of (COL.21.18_2)",
 "StateProvince is one of (Meta)",
 "Year 2020-2025",
 "TaxonKey is one of (Amphibia [GBIF Backbone Taxonomy])"
 ]
 }
 ]
}

 The dataset includes 1212 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002363-260120142942310/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.28441774
title: Review of community-based interventions for people with serious mental illness, focusing on learning instrumental activities of daily living and enhancing wellbeing

description: This review synthesises evidence on community-based interventions designed to support individuals with serious mental illness (SMI) in learning instrumental activities of daily living (IADLs). Given the increasing prevalence of SMI affecting over 500 million people worldwide, and associated functional impairments, effective interventions are critically needed. This review of thirty studies represented a range of global contexts and intervention types, which were categorised into simple IADLs (e.g. household chores), complex IADLs (e.g. financial management), and recreational IADLs (e.g. leisure activities). Findings demonstrated that community-based interventions significantly improved IADLs, promoting functional independence and overall well-being. Thematic analysis identified five key mechanisms for success: individualised goal-setting, structured programs with practical learning, engagement of support systems, integration into daily life, and use of innovative technologies. The review highlighted that personalised and practical IADL interventions, supported by robust community and technological resources, were most effective. When effective, interventions enhance practical skills of individuals while also contributing to emotional well-being, social connections, and personal fulfilment. Despite promising results, the review notes variability in study designs and outcomes, suggesting a need for consistent and long-term evaluations. Nonetheless, review insights offer valuable guidance for designing future interventions to better support autonomy and community integration of individuals with SMI.
DOI: 10.6084/m9.figshare.28441774.v1
title: Review of community-based interventions for people with serious mental illness, focusing on learning instrumental activities of daily living and enhancing wellbeing

description: This review synthesises evidence on community-based interventions designed to support individuals with serious mental illness (SMI) in learning instrumental activities of daily living (IADLs). Given the increasing prevalence of SMI affecting over 500 million people worldwide, and associated functional impairments, effective interventions are critically needed. This review of thirty studies represented a range of global contexts and intervention types, which were categorised into simple IADLs (e.g. household chores), complex IADLs (e.g. financial management), and recreational IADLs (e.g. leisure activities). Findings demonstrated that community-based interventions significantly improved IADLs, promoting functional independence and overall well-being. Thematic analysis identified five key mechanisms for success: individualised goal-setting, structured programs with practical learning, engagement of support systems, integration into daily life, and use of innovative technologies. The review highlighted that personalised and practical IADL interventions, supported by robust community and technological resources, were most effective. When effective, interventions enhance practical skills of individuals while also contributing to emotional well-being, social connections, and personal fulfilment. Despite promising results, the review notes variability in study designs and outcomes, suggesting a need for consistent and long-term evaluations. Nonetheless, review insights offer valuable guidance for designing future interventions to better support autonomy and community integration of individuals with SMI.
DOI: 10.15468/dl.k7zcum
title: Occurrence Download

description: A dataset containing 371128 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "GadmGid is DEU.10.48_1",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 371128 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002343-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6xa7vd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((117.022 1.562182, 116.951711 1.556614, 116.883154 1.540047, 116.818018 1.512889, 116.757907 1.47581, 116.704301 1.429722, 116.658521 1.375762, 116.621694 1.315258, 116.594725 1.2497, 116.578279 1.180703, 116.572759 1.109966, 116.5783 1.03923, 116.594765 0.970238, 116.621749 0.904687, 116.658586 0.844193, 116.704369 0.790242, 116.757971 0.744165, 116.818073 0.707095, 116.883194 0.679945, 116.951732 0.6633829999999999, 117.022 0.657816, 117.092268 0.6633829999999999, 117.160806 0.679945, 117.225927 0.707095, 117.286029 0.744165, 117.339631 0.790242, 117.385414 0.844193, 117.422251 0.904687, 117.449235 0.970238, 117.4657 1.03923, 117.471241 1.109966, 117.465721 1.180703, 117.449275 1.2497, 117.422306 1.315258, 117.385479 1.375762, 117.339699 1.429722, 117.286093 1.47581, 117.225982 1.512889, 117.160846 1.540047, 117.092289 1.556614, 117.022 1.562182))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002366-260120142942310/datasets/export for details.
DOI: 10.15468/dl.7wuqdr
title: Occurrence Download

description: A dataset containing 32987 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Perdix perdix)",
 "Year is one of (2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024)",
 "DecimalLatitude is greater than or equal to 47.53364139636112",
 "DecimalLatitude is less than or equal to 54.8769089978912",
 "DecimalLongitude is greater than or equal to 6.033629",
 "DecimalLongitude is less than or equal to 15.037743",
 "Year is not null",
 "HasCoordinate is TRUE",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is FALSE",
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)"
 ]
}

 The dataset includes 32987 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002367-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zddhwb
title: Occurrence Download

description: A dataset containing 5145 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Polyscias elegans"
 ]
}

 The dataset includes 5145 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002365-260120142942310/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.28452459
title: Soft-sediment deformation structures in the Lower Cretaceous Robberg Formation, South Africa: distinguishing the effects of dinosaurs and earthquakes in an estuarine, rift basin setting

description: The Early Cretaceous Robberg Formation is a clastic, syn-tectonic unit deposited near the updip limit of the Pletmos Basin during initial separation of Africa and South America. Robberg sandstones were deposited in estuarine tidal channels whereas siltstones fill abandoned channels. Abundant soft-sediment deformation and dewatering structures have previously been attributed to earthquakes. Our re-examination of a part of the Robberg Formation confirmed the presence of load casts due to inverse density stratification, whereas sand dikes probably record seismically triggered dewatering. Layers of siltstone pervasively disrupted by microfaults are probably seismogenic and matrix-supported, intraclastic breccia is interpreted to record seismogenic liquefaction and channel-bank collapse. However, the most common types of soft-sediment deformation, seen mainly in vertical cross-section and spatially and stratigraphically isolated in undeformed sediment, are attributed to dinosaurs. Track preservation takes five main types: (1) Undeformed to obliquely stratified sandstone fills sharply defined track impressions in siltstone in which lamination is truncated and deformed downward. (2) Bowl-shaped depressions, 50 cm to &gt;1 m in diameter, in heterolithic channel-plug facies are transmitted undertracks, probably produced by sauropods. (3) Dinosaurs walking on a thin sand layer on the bottom of a tidal channel punched the sand down into underlying channel-plug siltstone, the latter being highly deformed. (4) Dinosaurs walked or waded in the mud of abandoned channels, producing highly deformed, destratified and sheared sediment, surrounded by wholly undeformed sediment. (5) Dinosaurs walked on moist sandy channel point-bars producing locally deformed, brecciated, and de-stratified, bowl-shaped depressions, bordered by folds and thrusts. The majority of tracks appear to be broadly cylindrical, and lack obvious digits, which together with size, suggest a sauropod (or possibly other quadruped) origin. A few tracks, seen in plan, have three digits, suggesting a bipedal trackmaker. This track assemblage appears to be the first recognized in the Cretaceous of southern Africa.
DOI: 10.6084/m9.figshare.28452459.v1
title: Soft-sediment deformation structures in the Lower Cretaceous Robberg Formation, South Africa: distinguishing the effects of dinosaurs and earthquakes in an estuarine, rift basin setting

description: The Early Cretaceous Robberg Formation is a clastic, syn-tectonic unit deposited near the updip limit of the Pletmos Basin during initial separation of Africa and South America. Robberg sandstones were deposited in estuarine tidal channels whereas siltstones fill abandoned channels. Abundant soft-sediment deformation and dewatering structures have previously been attributed to earthquakes. Our re-examination of a part of the Robberg Formation confirmed the presence of load casts due to inverse density stratification, whereas sand dikes probably record seismically triggered dewatering. Layers of siltstone pervasively disrupted by microfaults are probably seismogenic and matrix-supported, intraclastic breccia is interpreted to record seismogenic liquefaction and channel-bank collapse. However, the most common types of soft-sediment deformation, seen mainly in vertical cross-section and spatially and stratigraphically isolated in undeformed sediment, are attributed to dinosaurs. Track preservation takes five main types: (1) Undeformed to obliquely stratified sandstone fills sharply defined track impressions in siltstone in which lamination is truncated and deformed downward. (2) Bowl-shaped depressions, 50 cm to &gt;1 m in diameter, in heterolithic channel-plug facies are transmitted undertracks, probably produced by sauropods. (3) Dinosaurs walking on a thin sand layer on the bottom of a tidal channel punched the sand down into underlying channel-plug siltstone, the latter being highly deformed. (4) Dinosaurs walked or waded in the mud of abandoned channels, producing highly deformed, destratified and sheared sediment, surrounded by wholly undeformed sediment. (5) Dinosaurs walked on moist sandy channel point-bars producing locally deformed, brecciated, and de-stratified, bowl-shaped depressions, bordered by folds and thrusts. The majority of tracks appear to be broadly cylindrical, and lack obvious digits, which together with size, suggest a sauropod (or possibly other quadruped) origin. A few tracks, seen in plan, have three digits, suggesting a bipedal trackmaker. This track assemblage appears to be the first recognized in the Cretaceous of southern Africa.
DOI: 10.34740/kaggle/dsv/14569961
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.yexd4c
title: Occurrence Download

description: A dataset containing 312 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Perdix perdix)",
 "Year is one of (2020, 2021, 2022, 2023, 2024)",
 "DecimalLatitude is greater than or equal to 49.93222657137567",
 "DecimalLatitude is less than or equal to 50.14557407126429",
 "DecimalLongitude is greater than or equal to 10.019266876108597",
 "DecimalLongitude is less than or equal to 10.497817533935098",
 "Year is not null",
 "HasCoordinate is TRUE",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is FALSE",
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)"
 ]
}

 The dataset includes 312 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002368-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2muk4p
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-72.203 3.46517, -72.27339000000001 3.459601, -72.342045 3.44303, -72.40727200000001 3.415867, -72.467463 3.37878, -72.521135 3.332685, -72.56696700000001 3.278717, -72.603829 3.218206, -72.63081699999999 3.152643, -72.647267 3.083644, -72.65277500000001 3.012907, -72.647209 2.942174, -72.630708 2.873188, -72.603679 2.807645, -72.56679 2.74716, -72.52095 2.69322, -72.467287 2.647153, -72.407122 2.610092, -72.341936 2.582949, -72.27333299999999 2.566391, -72.203 2.560826, -72.132667 2.566391, -72.064064 2.582949, -71.998878 2.610092, -71.93871300000001 2.647153, -71.88505000000001 2.69322, -71.83920999999999 2.74716, -71.80232100000001 2.807645, -71.77529199999999 2.873188, -71.758791 2.942174, -71.753225 3.012907, -71.75873300000001 3.083644, -71.775183 3.152643, -71.802171 3.218206, -71.839033 3.278717, -71.884865 3.332685, -71.938537 3.37878, -71.998728 3.415867, -72.06395500000001 3.44303, -72.13261 3.459601, -72.203 3.46517))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 27 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002370-260120142942310/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.27177901
title: Corporate bond coupon prediction based on deep learning

description: As the second largest bond market in the world, China's bond market has attracted extensive attention in recent years. Given its importance in facilitating financing arrangements and informing investment decisions, accurate bond coupon prediction is valuable. This paper proposes an ensemble model combining TabNet, DeepFM, and XGBoost for predicting the coupons of investment-grade corporate bonds. Specifically, to optimize the hyperparameters of the proposed model, an improved butterfly optimization algorithm incorporating the concepts of good point sets, refraction opposition-based learning, switching probability adjustment, and Solis & Wets search strategies is developed. Extensive experiments using data on China's investment-grade corporate bonds demonstrate the superior performance of the proposed model in the accuracy of bond coupon predictions. Additionally, the importance of various features has been discussed. The results show that the base interest rate for valuation and term to maturity are important to bond coupon predictions obtained by the proposed model.
DOI: 10.6084/m9.figshare.27177901.v1
title: Corporate bond coupon prediction based on deep learning

description: As the second largest bond market in the world, China's bond market has attracted extensive attention in recent years. Given its importance in facilitating financing arrangements and informing investment decisions, accurate bond coupon prediction is valuable. This paper proposes an ensemble model combining TabNet, DeepFM, and XGBoost for predicting the coupons of investment-grade corporate bonds. Specifically, to optimize the hyperparameters of the proposed model, an improved butterfly optimization algorithm incorporating the concepts of good point sets, refraction opposition-based learning, switching probability adjustment, and Solis & Wets search strategies is developed. Extensive experiments using data on China's investment-grade corporate bonds demonstrate the superior performance of the proposed model in the accuracy of bond coupon predictions. Additionally, the importance of various features has been discussed. The results show that the base interest rate for valuation and term to maturity are important to bond coupon predictions obtained by the proposed model.
DOI: 10.13140/rg.2.2.16855.74406
title: Transcripts of the Selected TV talk Shows
DOI: 10.3886/e244540
title: College of Nursing Sciences, Amichi, Anambra State, 2026/2027 ADMISSION FORM is out call 09031383306 DR MR JAMES (+249031383306) for TRANSCRIPT Collection School Admin Line 09031383306 To apply Also 2026/2027 Nursing form

description: College of Nursing Sciences, Amichi, Anambra State, 2026/2027 ADMISSION FORM is out call 09031383306 DR MR JAMES (+249031383306) for TRANSCRIPT Collection School Admin Line 09031383306 To apply Also 2026/2027 Nursing form
DOI: 10.6084/m9.figshare.28435275
title: Model Selection for Mixed-Effects Location-Scale Models with Confidence Interval for LOO or WAIC Difference

description: LOO (Leave-One-Out cross-validation) and WAIC (Widely Applicable Information Criterion) are widely used for model selection in Bayesian statistics. Most studies select the model with the smallest value based on point estimates, often without considering the differences in fit indices or the uncertainty of the estimates. To address this gap, we propose a sequential method for comparing models based on confidence intervals for ΔLOO or ΔWAIC. A simulation study was conducted to evaluate this method in selecting mixed-effects location-scale models (MELSMs). Our study revealed that the sequential methods, especially when using a 90% confidence interval, achieved a higher accuracy rate of model selection compared to the point method when the true model was simple, had a large magnitude of random intercept in the scale model, or had a large sample size. Models selected by the sequential methods demonstrated higher power, narrower credible interval width, smaller standard errors for the fixed effect in the location model, and lower bias for the random effect of the intercept in the location model. Differences between LOO and WAIC were significant only when the level-1 sample size was small, with LOO performing better when the true model had homogeneous or severe heterogeneity in residual variances.
DOI: 10.6084/m9.figshare.28435275.v3
title: Model Selection for Mixed-Effects Location-Scale Models with Confidence Interval for LOO or WAIC Difference

description: LOO (Leave-One-Out cross-validation) and WAIC (Widely Applicable Information Criterion) are widely used for model selection in Bayesian statistics. Most studies select the model with the smallest value based on point estimates, often without considering the differences in fit indices or the uncertainty of the estimates. To address this gap, we propose a sequential method for comparing models based on confidence intervals for ΔLOO or ΔWAIC. A simulation study was conducted to evaluate this method in selecting mixed-effects location-scale models (MELSMs). Our study revealed that the sequential methods, especially when using a 90% confidence interval, achieved a higher accuracy rate of model selection compared to the point method when the true model was simple, had a large magnitude of random intercept in the scale model, or had a large sample size. Models selected by the sequential methods demonstrated higher power, narrower credible interval width, smaller standard errors for the fixed effect in the location model, and lower bias for the random effect of the intercept in the location model. Differences between LOO and WAIC were significant only when the level-1 sample size was small, with LOO performing better when the true model had homogeneous or severe heterogeneity in residual variances.