cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25573/serc.29519987
title: Dataset: Equations for predicting leaf area and leaf mass for woody plant species in the SERC chronosequence

description: This project sought coefficients of allometric equations for estimating leaf area and leaf mass for major woody plant species in the vicinity of the Smithsonian Environmental Research Center (SERC; 38.9 N, 76.6 W). Unlike the commonly used destructive analysis, this approach inferred the coefficients from field data on stem and leaf litter production. The derived relations are independent of interannual variation and applicable to stands of many ages. They may be used to estimate stand Leaf Area Index (LAI).The method was to find coefficients which, when applied to all living stems in a plot, produced an estimate of leaf area (or mass) equal to the leaf area (or mass) measured in the plot. There were two sorts of equations. For the typical power law (leaf area or mass = a ∙ DBH<sup>b</sup>) we used non-linear regression. For the linear relation between leaf area and stand basal area (the ‘Support Ratio’) we used ordinary least squares. Equations were validated by applying the predictive equations produced from a training dataset (80% of the full set) to a testing dataset (the remaining 20%).The sources of these cases were field data of leaf area, leaf mass, and stems for many sites of the same forest type (‘tulip poplar”) where both litterfall and stems were measured in the same year and plot. The categories of species or species groups were the same in both the stems and litter datasets.We successfully fitted the power and Support Ratio relations, yielding equations for both leaf area and leaf mass for 21 species groups and three habits (trees, shrubs and vines).
DOI: 10.25573/serc.29519987.v1
title: Dataset: Equations for predicting leaf area and leaf mass for woody plant species in the SERC chronosequence

description: This project sought coefficients of allometric equations for estimating leaf area and leaf mass for major woody plant species in the vicinity of the Smithsonian Environmental Research Center (SERC; 38.9 N, 76.6 W). Unlike the commonly used destructive analysis, this approach inferred the coefficients from field data on stem and leaf litter production. The derived relations are independent of interannual variation and applicable to stands of many ages. They may be used to estimate stand Leaf Area Index (LAI).The method was to find coefficients which, when applied to all living stems in a plot, produced an estimate of leaf area (or mass) equal to the leaf area (or mass) measured in the plot. There were two sorts of equations. For the typical power law (leaf area or mass = a ∙ DBH<sup>b</sup>) we used non-linear regression. For the linear relation between leaf area and stand basal area (the ‘Support Ratio’) we used ordinary least squares. Equations were validated by applying the predictive equations produced from a training dataset (80% of the full set) to a testing dataset (the remaining 20%).The sources of these cases were field data of leaf area, leaf mass, and stems for many sites of the same forest type (‘tulip poplar”) where both litterfall and stems were measured in the same year and plot. The categories of species or species groups were the same in both the stems and litter datasets.We successfully fitted the power and Support Ratio relations, yielding equations for both leaf area and leaf mass for 21 species groups and three habits (trees, shrubs and vines).
DOI: 10.15468/dl.rn77tx
title: Occurrence Download

description: A dataset containing 3345 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Chinese Taipei)",
 "TaxonKey is Verbena officinalis"
 ]
}

 The dataset includes 3345 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023789-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.acx6pg
title: Occurrence Download

description: A dataset containing 11778 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leucanthemum vulgare",
 "Country is Canada",
 "HasCoordinate is true"
 ]
}

 The dataset includes 11778 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023786-250711103210423/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.29565068.v2
title: Logic 14 pdf NEW

description: Logic innovation
DOI: 10.15468/dl.uyqzdj
title: Occurrence Download

description: A dataset containing 489 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Noturus hildebrandi"
 ]
}

 The dataset includes 489 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023790-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15976281
title: Examples of public datasets of spatial metabolomics/lipidomics

description: Explanation

Two datasets are available in this compressed folder, within two subfolders:



LP-example0/

LP-cerebellum-rat/


Each subfolder contains two annotations files (HMDB and LipidMaps) in the form of .csv files,  and the unified intensities into a single `anndata` object in .h5ad file format. 

Instructions:

Download and unzip the folder in your working directory.

Acknowledgements:

To the authors for the two datasets in this folder:



LP-example0: Evan Larson, 2021, at https://metaspace2020.org/dataset/2021-02-10_20h21m12s

LP-cerebellum-rat: Bonjd N, Griffin J, Hall Z et al., 2017, at: https://www.ebi.ac.uk/metabolights/editor/MTBLS487/assays


We also thank Metaspace https://metaspace2020.org where the intensities and annotations can be retrieved with the registires 2021-02-10_20h21m12s and 2025-04-10_14h53m38s respectively (https://metaspace2020.org/dataset/[registry]). 

The datasets were downloaded using the `metaspace-converter` python package, articulated within a custom Python script to unify the intensities into a single anndata object for each dataset.
DOI: 10.15468/dl.m43s8t
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leucanthemum vulgare",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 42 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023791-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.euztu7
title: Occurrence Download

description: A dataset containing 55595 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sturnus vulgaris",
 "Country is Argentina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 55595 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023772-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g36kzd
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Noturus hildebrandi hildebrandi"
 ]
}

 The dataset includes 29 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023793-250711103210423/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.29581775
title: Sr data.xlsx

description: This dataset includes strontium isotope (⁸⁷Sr/⁸⁶Sr) ratio measurements from Well A and Well B. Data columns include sample depth (in feet and meters), formation name, material type, measured ⁸⁷Sr/⁸⁶Sr ratio, analytical error, and interpreted numerical age (in million years, Ma). Ages were calculated using the global seawater ⁸⁷Sr/⁸⁶Sr curve from McArthur and Howarth (GTS2020 timescale), based on linear regression fitting.The dataset also includes the reference age-to-ratio table from McArthur and Howarth (used for calibration), listing mean, minimum, and maximum ⁸⁷Sr/⁸⁶Sr ratios for each geological age.This dataset was used to produce Table 1 and to generate Figure 1 (age-depth plot based on ⁸⁷Sr/⁸⁶Sr-derived ages). Age interpretations are based on linear regression against the global seawater ⁸⁷Sr/⁸⁶Sr curve of McArthur and Howarth (GTS2020 timescale).
DOI: 10.6084/m9.figshare.29581775.v1
title: Sr data.xlsx

description: This dataset includes strontium isotope (⁸⁷Sr/⁸⁶Sr) ratio measurements from Well A and Well B. Data columns include sample depth (in feet and meters), formation name, material type, measured ⁸⁷Sr/⁸⁶Sr ratio, analytical error, and interpreted numerical age (in million years, Ma). Ages were calculated using the global seawater ⁸⁷Sr/⁸⁶Sr curve from McArthur and Howarth (GTS2020 timescale), based on linear regression fitting.The dataset also includes the reference age-to-ratio table from McArthur and Howarth (used for calibration), listing mean, minimum, and maximum ⁸⁷Sr/⁸⁶Sr ratios for each geological age.This dataset was used to produce Table 1 and to generate Figure 1 (age-depth plot based on ⁸⁷Sr/⁸⁶Sr-derived ages). Age interpretations are based on linear regression against the global seawater ⁸⁷Sr/⁸⁶Sr curve of McArthur and Howarth (GTS2020 timescale).
DOI: 10.5281/zenodo.15971891
title: NMRSI: A database of 3.3 million experimental NMR spectra

description: This dataset contains over 3 million NMR spectra entries (1H, 13C, 19F) extracted from the Supporting Information of chemistry publications between 2010 and 2024.
DOI: 10.5281/zenodo.15971892
title: NMRSI: A database of 3.3 million experimental NMR spectra

description: This dataset contains over 3 million NMR spectra entries (1H, 13C, 19F) extracted from the Supporting Information of chemistry publications between 2010 and 2024.
DOI: 10.5284/1106778
title: Discover Brightwater Project - Historic Buildings Digital Photograph Archive, Skerne Valley, County Durham, 2020-2022

description: This collection comprises the photographic archive recording historic buildings for the Discover Brightwater Project, all of the buildings are located within a defined area of the Skerne Valley, County Durham and include a selection of farms, mills and a castle.
DOI: 10.6084/m9.figshare.29582320
title: Analyzing extreme muti-vehicle rear-end collision risks in adverse weather through Generalized Pareto Regression Trees

description: The study seeks to explore rear-end collision risks in multi-vehicle car-following scenarios under adverse weather conditions by proposing an integrated framework. The integrated framework is applied to a case study of three-vehicle car-following scenario in Norway without loss of generality. For identifying car-following groups with extreme collision risks, the collision risk of each group in the raw dataset is evaluated using an extended probabilistic driving risk field. Quantitative collision risks are analyzed to fit the Generalized Pareto distribution, and high-risk scenarios screened <i>via</i> mean residual life plots and threshold stability plots. To determine risk-contributing factors, Generalized Pareto Regression Trees (GPRT) are constructed to pinpoint significant influences on rear-end collision risks. By integrating the classification and regression trees with extreme value theory, the GPRT discards data assumptions and covariate continuity requirements of most extreme value analysis (e.g., extreme quantile regression). Moreover, the GPRT not only identifies the hierarchical structure of variables affecting rear-end collision risks but also determines risk-impact thresholds for covariates, offering superior interpretability and engineering applicability. The results show that revealed risks conform well to the Generalized Pareto distribution, allowing for the formulating Generalized Pareto regression trees. Compared to the Generalized Additive Model (GAM) and Negative Binomial Regression (NBR) methods, the GPRT approach demonstrates superior performance in balancing risk fitting accuracy and model complexity. Vehicle speeds, weights, and headways emerge as critical factors for collision risks under clear, rainy, and snowy conditions. As weather conditions deteriorate from clear to rainy or snowy, the influence of vehicle speed and weight diminishes, while the influence of headway and road surface conditions becomes more pronounced. Collision risks are high on sunny days, regardless of whether the middle vehicles of three-vehicle groups are light or heavy vehicles. The integrated evaluation framework developed in this study provides a tool for car-following safety assessment under extreme weather conditions.
DOI: 10.6084/m9.figshare.29582320.v1
title: Analyzing extreme muti-vehicle rear-end collision risks in adverse weather through Generalized Pareto Regression Trees

description: The study seeks to explore rear-end collision risks in multi-vehicle car-following scenarios under adverse weather conditions by proposing an integrated framework. The integrated framework is applied to a case study of three-vehicle car-following scenario in Norway without loss of generality. For identifying car-following groups with extreme collision risks, the collision risk of each group in the raw dataset is evaluated using an extended probabilistic driving risk field. Quantitative collision risks are analyzed to fit the Generalized Pareto distribution, and high-risk scenarios screened <i>via</i> mean residual life plots and threshold stability plots. To determine risk-contributing factors, Generalized Pareto Regression Trees (GPRT) are constructed to pinpoint significant influences on rear-end collision risks. By integrating the classification and regression trees with extreme value theory, the GPRT discards data assumptions and covariate continuity requirements of most extreme value analysis (e.g., extreme quantile regression). Moreover, the GPRT not only identifies the hierarchical structure of variables affecting rear-end collision risks but also determines risk-impact thresholds for covariates, offering superior interpretability and engineering applicability. The results show that revealed risks conform well to the Generalized Pareto distribution, allowing for the formulating Generalized Pareto regression trees. Compared to the Generalized Additive Model (GAM) and Negative Binomial Regression (NBR) methods, the GPRT approach demonstrates superior performance in balancing risk fitting accuracy and model complexity. Vehicle speeds, weights, and headways emerge as critical factors for collision risks under clear, rainy, and snowy conditions. As weather conditions deteriorate from clear to rainy or snowy, the influence of vehicle speed and weight diminishes, while the influence of headway and road surface conditions becomes more pronounced. Collision risks are high on sunny days, regardless of whether the middle vehicles of three-vehicle groups are light or heavy vehicles. The integrated evaluation framework developed in this study provides a tool for car-following safety assessment under extreme weather conditions.
DOI: 10.6084/m9.figshare.29582325
title: Injury patterns in motor vehicle collision-adult pedestrian deaths

description: To describe fatal pedestrian injury patterns in adults 25–64 years old and correlate them with motor vehicle collision (MVC) dynamics and pedestrian kinematics using medicolegal death investigations data of MVCs occurring in the current Canadian MV fleet. MVC-pedestrian injuries were collated in an Injury Data Collection Form (IDCF) and coded using the Abbreviated Injury Scale (AIS) 2015 revision. The AIS of the most frequent severe injury was noted for individual body regions. The Maximum AIS (MAIS) was used to define the most severe injury to the body overall and by body regions (MAISBR). This study focused on serious to maximal injuries (AIS 3–6), that had an increasing likelihood of causing death. The IDCF was used to extract collision and injury data from the Office of the Chief Coroner for Ontario database of postmortem examinations done at the Provincial Forensic Pathology Unit in Toronto, Canada and other provincial facilities between 2013 and 2019. Injury data were correlated with data about the MVs, and MV dynamics and pedestrian kinematics. The study was approved by the Western University Health Science Research Ethics Board. There were 318 adults: 200 (62.9%) males and 118 (37.1%) females. Adult pedestrians comprised 47.5% (318/670) of all autopsied pedestrians. Vehicle type was known in 292 cases, and cars (<i>n</i> = 99/292, 33.9%) were the most frequent type of vehicle in single vehicle impacts; however, collectively vehicles with high hood edges (i.e., greater distance between the ground and hood edge) such as light trucks, heavy trucks and buses were in the majority. Pedestrian kinematics were known in 288/299 single impact-related deaths. Forward projection (<i>n</i> = 113/288, 39.2%) was the most frequent type and resulted from impacts with high hood edge vehicles. Compared to car impacts, pedestrians struck by high hood edge vehicles were more likely to be runover. Based on MAISBR ≥3 injuries, the head was the most severely injured (median MAISBR = 4), followed by neck (median MAISBR = 3), thorax (median MAISBR = 4), abdomen/retroperitoneum (median MAISBR = 4) and pelvis (median MAISBR = 3). About 70% of the pedestrians were in circumstances which increased their risk of being struck. More than half (176/318, 55.3%) had a positive toxicology result. About ¼ (27.4%) had a positive blood ethanol result. Nearly all pedestrians with positive alcohol results did not have the right of way when struck. The current study was a comprehensive analysis of fatal injury patterns and specific injuries in adult pedestrians struck by motor vehicles. By collation and analysis of comprehensive data derived from postmortem examinations, associations between injury patterns in the adult age group were correlated with a range of factors related to motor vehicle types, reflective of the current Canadian fleet, collision dynamics and pedestrian post-collision kinematics.
DOI: 10.6084/m9.figshare.29582325.v1
title: Injury patterns in motor vehicle collision-adult pedestrian deaths

description: To describe fatal pedestrian injury patterns in adults 25–64 years old and correlate them with motor vehicle collision (MVC) dynamics and pedestrian kinematics using medicolegal death investigations data of MVCs occurring in the current Canadian MV fleet. MVC-pedestrian injuries were collated in an Injury Data Collection Form (IDCF) and coded using the Abbreviated Injury Scale (AIS) 2015 revision. The AIS of the most frequent severe injury was noted for individual body regions. The Maximum AIS (MAIS) was used to define the most severe injury to the body overall and by body regions (MAISBR). This study focused on serious to maximal injuries (AIS 3–6), that had an increasing likelihood of causing death. The IDCF was used to extract collision and injury data from the Office of the Chief Coroner for Ontario database of postmortem examinations done at the Provincial Forensic Pathology Unit in Toronto, Canada and other provincial facilities between 2013 and 2019. Injury data were correlated with data about the MVs, and MV dynamics and pedestrian kinematics. The study was approved by the Western University Health Science Research Ethics Board. There were 318 adults: 200 (62.9%) males and 118 (37.1%) females. Adult pedestrians comprised 47.5% (318/670) of all autopsied pedestrians. Vehicle type was known in 292 cases, and cars (<i>n</i> = 99/292, 33.9%) were the most frequent type of vehicle in single vehicle impacts; however, collectively vehicles with high hood edges (i.e., greater distance between the ground and hood edge) such as light trucks, heavy trucks and buses were in the majority. Pedestrian kinematics were known in 288/299 single impact-related deaths. Forward projection (<i>n</i> = 113/288, 39.2%) was the most frequent type and resulted from impacts with high hood edge vehicles. Compared to car impacts, pedestrians struck by high hood edge vehicles were more likely to be runover. Based on MAISBR ≥3 injuries, the head was the most severely injured (median MAISBR = 4), followed by neck (median MAISBR = 3), thorax (median MAISBR = 4), abdomen/retroperitoneum (median MAISBR = 4) and pelvis (median MAISBR = 3). About 70% of the pedestrians were in circumstances which increased their risk of being struck. More than half (176/318, 55.3%) had a positive toxicology result. About ¼ (27.4%) had a positive blood ethanol result. Nearly all pedestrians with positive alcohol results did not have the right of way when struck. The current study was a comprehensive analysis of fatal injury patterns and specific injuries in adult pedestrians struck by motor vehicles. By collation and analysis of comprehensive data derived from postmortem examinations, associations between injury patterns in the adult age group were correlated with a range of factors related to motor vehicle types, reflective of the current Canadian fleet, collision dynamics and pedestrian post-collision kinematics.
DOI: 10.15468/dl.pm35pq
title: Occurrence Download

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

 The dataset includes 30 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023795-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xycbg5
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leucanthemum vulgare",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023794-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8mgnp2
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Noturus hildebrandi lautus"
 ]
}

 The dataset includes 25 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023797-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.btm578
title: Occurrence Download

description: A dataset containing 14717774 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sturnus vulgaris",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 14717774 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023773-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.da5nmn
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-70.49899 12.38574,-69.52104 11.82226,-60.63795 11.47619,-60.48231 18.77941,-67.36877 18.91493,-70.49899 12.38574))",
 "TaxonKey is Stenella longirostris",
 "Year 2010-2024"
 ]
}

 The dataset includes 11 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023799-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.