cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.hje2w5
title: Occurrence Download

description: A dataset containing 1696 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chionochloa conspicua (G.Forst.) Zotov",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1696 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078741-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9826hm
title: Occurrence Download

description: A dataset containing 1011 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Podocarpus latifolius (Thunb.) R.Br. ex Mirb."
 ]
}

 The dataset includes 1011 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038526-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dme9ah
title: Occurrence Download

description: A dataset containing 3631650 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material sample)",
 "OccurrenceStatus is Present",
 "PublishingOrg is 19456090-b49a-11d8-abeb-b8a03c50a862",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 3631650 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000316-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y9xyyv
title: Occurrence Download

description: A dataset containing 120772 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Calamagrostis breviligulata (Fernald) Saarela, Calamagrostis arenaria (L.) Roth, Polypogon interruptus Kunth, Calamagrostis pseudophragmites (Haller f.) Koeler, Calamagrostis epigeios Steud.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 120772 records from 729 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000308-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w8hpdc
title: Occurrence Download

description: A dataset containing 709 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is greater than or equal to 1981",
 "Year is less than or equal to 2010",
 "HasCoordinate is true",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "VerbatimScientificName is Cryptogramma crispa",
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 709 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000318-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14886961
title: Data set 1  for semi-structured interviews with older adults in Flanders for Digital Ageing Consortium

description: This dataset documents a series of online interviews conducted between January and March 2021 during the COVID-19 lockdown in Belgium (Flanders). The study aimed to explore older adults’ experiences and perspectives on digital technology in their ageing process. Given the restrictions on in-person interactions, three PhD researchers, who received additional training in online interviewing techniques, facilitated these discussions remotely. 

A total of 50 individuals expressed interest in participating, and 37 interviews were conducted after 13 individuals did not respond to follow-up scheduling emails. Participants selected their preferred communication platform for the interview, enhancing accessibility. Prior to the interviews, they received a confirmation email with an information sheet and an informed consent form, which they could return digitally or via a pre-paid postal envelope. Verbal consent for recording was reconfirmed at the start of each session.
DOI: 10.5281/zenodo.14886962
title: Data set 1  for semi-structured interviews with older adults in Flanders for Digital Ageing Consortium

description: This dataset documents a series of online interviews conducted between January and March 2021 during the COVID-19 lockdown in Belgium (Flanders). The study aimed to explore older adults’ experiences and perspectives on digital technology in their ageing process. Given the restrictions on in-person interactions, three PhD researchers, who received additional training in online interviewing techniques, facilitated these discussions remotely. 

A total of 50 individuals expressed interest in participating, and 37 interviews were conducted after 13 individuals did not respond to follow-up scheduling emails. Participants selected their preferred communication platform for the interview, enhancing accessibility. Prior to the interviews, they received a confirmation email with an information sheet and an informed consent form, which they could return digitally or via a pre-paid postal envelope. Verbal consent for recording was reconfirmed at the start of each session.
DOI: 10.48511/0t3xi57o
title: Ben Hur Lake (BEN01)

description: Lake level and water temperature data collected from Ben Hur Lake.The High Elevation Monitoring Program is part of the Columbia Basin Water Monitoring Framework program (CBWMF). The CBWMF is a coordinated monitoring network that tracks how climate change and other impacts are affecting water supply for communities and ecosystems across the Canadian Columbia Basin region.
DOI: 10.15468/dl.3y7p8x
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Altiphylax Yeriomtschenko & Szczerbak, 1984",
 "HasCoordinate is true"
 ]
}

 The dataset includes 45 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000319-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/1290-xm38
title: A High-Power Radio Frequency Converter with Wide-Range Power Regulation and ZVS Operation Via Outphasing Modulation

description: Conventional high-power radio frequency converters (RFCs) need to deliver a wide-range power against variable load impedance. However, it is difficult to achieve a wide-range power regulation and zero voltage switching (ZVS) simultaneously. To address thi.s issue, this paper proposes a DC-link parallel AC-link series (DPAS) multiple power amplifier (MPA) architecture with outphasing modulation. The generalized mathematical model of the proposed topology is presented. The system’s soft-switching range and criterion are analyzed. In addition, the mathematical results of harmonic synthesis are compared with the simulation results and experimental results. The proposed system can achieve low harmonics, natural over-power protection under variable loads, ZVS operation, and wide-range power regulation. A 400-kHz and 2.4-kW RFC experimental prototype with two cells is built. The output power ranges from 1.2 kW to 2.4 kW with efficiencies of 93%-97.6%, demonstrating the high performance of the proposed system.
DOI: 10.6084/m9.figshare.28425476
title: Datasets and codes for manuscript "Development policy affects coastal risk in China more than sea-level rise"

description: Effective coastal risk assessments are crucial for adaptively managing threats from sea-level rise (SLR). Despite recent advancements, global and regional assessments remain limited by omitting critical factors like land-use change, oversimplifying land subsidence, and failing to disaggregate potential impacts across different land uses. This study addresses these gaps by developing context-specific scenarios based on a comprehensive analysis of Chinese coastal development policies. We integrate high-resolution simulations of population and land system changes with inundation exposure assessments that incorporate SLR, land subsidence, tides, and storm surges, offering a more nuanced understanding of coastal risks. Our findings reveal that transitioning from strict ecological protection to aggressive economic development policies significantly alters the land systems exposed to flooding. While SLR and subsidence affect flood hazard (inundation and depth), policy scenarios dictate exposure (and vulnerability) of land functions. The analysis sheds new light on who has agency for managing coastal risk.
DOI: 10.15468/dl.m2z8va
title: Occurrence Download

description: A dataset containing 222994 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pimpinella saxifraga L.",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "Year is greater than or equal to 1900",
 "Year is less than or equal to 2010"
 ]
}

 The dataset includes 222994 records from 627 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000312-250218110819086/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.28203089
title: Predicting delayed neurological sequelae in patients with carbon monoxide poisoning using machine learning models

description: Delayed neurological sequelae is a common complication following carbon monoxide poisoning, which significantly affects the quality of life of patients with the condition. We aimed to develop a machine learning-based prediction model to predict the frequency of delayed neurological sequelae in patients with carbon monoxide poisoning. A single-center retrospective analysis was conducted in an emergency department from January 01, 2018, to December 31, 2023. We analyzed data from patients with carbon monoxide poisoning, which were divided into training and test sets. We developed and evaluated sixteen machine learning models, using accuracy, sensitivity, specificity, and other relevant metrics. Threshold adjustments were performed to determine the most accurate model for predicting patients with carbon monoxide poisoning at risk of delayed neurological sequelae. A total of 360 patients with carbon monoxide poisoning were investigated in the present study, of whom 103 (28.6%) were diagnosed with delayed neurological sequelae, and two (0.6%) died. After threshold adjustment, the synthetic minority oversampling technique-random forest model demonstrated superior performance with an area under the receiver operating characteristic curve of 0.89 and an accuracy of 0.83. The sensitivity and specificity of the model were 0.9 and 0.8, respectively. The study developed a machine learning-based synthetic minority oversampling technique-random forest model to predict delayed neurological sequelae in patients with carbon monoxide poisoning, achieving an area under the receiver operating characteristic curve of 0.89. This technique was used to handle class imbalance, and shapley additive explanations analysis helped explain the model predictions, highlighting important factors such as the Glasgow Coma Scale, hyperbaric oxygen therapy, kidney function, immune response, liver function, and blood clotting. The machine learning-based synthetic minority oversampling technique-random forest model developed in this study effectively identifies patients with carbon monoxide poisoning at high risk for delayed neurological sequelae.
DOI: 10.6084/m9.figshare.28203089.v1
title: Predicting delayed neurological sequelae in patients with carbon monoxide poisoning using machine learning models

description: Delayed neurological sequelae is a common complication following carbon monoxide poisoning, which significantly affects the quality of life of patients with the condition. We aimed to develop a machine learning-based prediction model to predict the frequency of delayed neurological sequelae in patients with carbon monoxide poisoning. A single-center retrospective analysis was conducted in an emergency department from January 01, 2018, to December 31, 2023. We analyzed data from patients with carbon monoxide poisoning, which were divided into training and test sets. We developed and evaluated sixteen machine learning models, using accuracy, sensitivity, specificity, and other relevant metrics. Threshold adjustments were performed to determine the most accurate model for predicting patients with carbon monoxide poisoning at risk of delayed neurological sequelae. A total of 360 patients with carbon monoxide poisoning were investigated in the present study, of whom 103 (28.6%) were diagnosed with delayed neurological sequelae, and two (0.6%) died. After threshold adjustment, the synthetic minority oversampling technique-random forest model demonstrated superior performance with an area under the receiver operating characteristic curve of 0.89 and an accuracy of 0.83. The sensitivity and specificity of the model were 0.9 and 0.8, respectively. The study developed a machine learning-based synthetic minority oversampling technique-random forest model to predict delayed neurological sequelae in patients with carbon monoxide poisoning, achieving an area under the receiver operating characteristic curve of 0.89. This technique was used to handle class imbalance, and shapley additive explanations analysis helped explain the model predictions, highlighting important factors such as the Glasgow Coma Scale, hyperbaric oxygen therapy, kidney function, immune response, liver function, and blood clotting. The machine learning-based synthetic minority oversampling technique-random forest model developed in this study effectively identifies patients with carbon monoxide poisoning at high risk for delayed neurological sequelae.
DOI: 10.5281/zenodo.13752986
title: Data regarding the manuscript: Quantifying Ultrafast Energy Transfer from Plasmonic Hot Carriers for Pulsed Photocatalysis on Nanostructures
DOI: 10.5281/zenodo.13752987
title: Data regarding the manuscript: Quantifying Ultrafast Energy Transfer from Plasmonic Hot Carriers for Pulsed Photocatalysis on Nanostructures
DOI: 10.5281/zenodo.13753187
title: Data regarding the manuscript: Transient optical symmetry breaking for ultrafast broadband dichroism in plasmonic metasurfaces
DOI: 10.5281/zenodo.13753188
title: Data regarding the manuscript: Transient optical symmetry breaking for ultrafast broadband dichroism in plasmonic metasurfaces
DOI: 10.6084/m9.figshare.28131660
title: GeoWarp: Warped Spatial Processes for Inferring Subsea Sediment Properties

description: For offshore structures like wind turbines, subsea infrastructure, pipelines, and cables, it is crucial to quantify the properties of the seabed sediments at a proposed site. However, data collection offshore is costly, so analysis of the seabed sediments must be made from measurements that are spatially sparse. Adding to this challenge, the structure of the seabed sediments exhibits both nonstationarity and anisotropy. To address these issues, we propose GeoWarp, a hierarchical spatial statistical modeling framework for inferring the 3-D geotechnical properties of subsea sediments. GeoWarp decomposes the seabed properties into a region-wide vertical mean profile (modeled using B-splines), and a nonstationary 3-D spatial Gaussian process. Process nonstationarity and anisotropy are accommodated by warping space in three dimensions and by allowing the process variance to change with depth. We apply GeoWarp to measurements of the seabed made using cone penetrometer tests (CPTs) at six sites on the North West Shelf of Australia. We show that GeoWarp captures the complex spatial distribution of the sediment properties, and produces realistic 3-D simulations suitable for downstream engineering analyses. Through cross-validation, we show that GeoWarp has predictive performance superior to other state-of-the-art methods, demonstrating its value as a tool in offshore geotechnical engineering. 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.28131660.v1
title: GeoWarp: Warped spatial processes for inferring subsea sediment properties

description: For offshore structures like wind turbines, subsea infrastructure, pipelines, and cables, it is crucial to quantify the properties of the seabed sediments at a proposed site. However, data collection offshore is costly, so analysis of the seabed sediments must be made from measurements that are spatially sparse. Adding to this challenge, the structure of the seabed sediments exhibits both nonstationarity and anisotropy. To address these issues, we propose GeoWarp, a hierarchical spatial statistical modeling framework for inferring the 3-D geotechnical properties of subsea sediments. GeoWarp decomposes the seabed properties into a region-wide vertical mean profile (modeled using B-splines), and a nonstationary 3-D spatial Gaussian process. Process nonstationarity and anisotropy are accommodated by warping space in three dimensions and by allowing the process variance to change with depth. We apply GeoWarp to measurements of the seabed made using cone penetrometer tests (CPTs) at six sites on the North West Shelf of Australia. We show that GeoWarp captures the complex spatial distribution of the sediment properties, and produces realistic 3-D simulations suitable for downstream engineering analyses. Through cross-validation, we show that GeoWarp has predictive performance superior to other state-of-the-art methods, demonstrating its value as a tool in offshore geotechnical engineering.
DOI: 10.6084/m9.figshare.28131660.v2
title: GeoWarp: Warped Spatial Processes for Inferring Subsea Sediment Properties

description: For offshore structures like wind turbines, subsea infrastructure, pipelines, and cables, it is crucial to quantify the properties of the seabed sediments at a proposed site. However, data collection offshore is costly, so analysis of the seabed sediments must be made from measurements that are spatially sparse. Adding to this challenge, the structure of the seabed sediments exhibits both nonstationarity and anisotropy. To address these issues, we propose GeoWarp, a hierarchical spatial statistical modeling framework for inferring the 3-D geotechnical properties of subsea sediments. GeoWarp decomposes the seabed properties into a region-wide vertical mean profile (modeled using B-splines), and a nonstationary 3-D spatial Gaussian process. Process nonstationarity and anisotropy are accommodated by warping space in three dimensions and by allowing the process variance to change with depth. We apply GeoWarp to measurements of the seabed made using cone penetrometer tests (CPTs) at six sites on the North West Shelf of Australia. We show that GeoWarp captures the complex spatial distribution of the sediment properties, and produces realistic 3-D simulations suitable for downstream engineering analyses. Through cross-validation, we show that GeoWarp has predictive performance superior to other state-of-the-art methods, demonstrating its value as a tool in offshore geotechnical engineering. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.15468/dl.e4q67s
title: Occurrence Download

description: A dataset containing 2749 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Paracentrotus lividus (Lamarck, 1816)"
 ]
}

 The dataset includes 2749 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000320-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gscx99
title: Occurrence Download

description: A dataset containing 11288 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Meise Botanic Garden Herbarium (BR)",
 "Country is Sweden"
 ]
}

 The dataset includes 11288 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000321-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vqgad2
title: Occurrence Download

description: A dataset containing 11793 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Natural History Museum (London) Collection Specimens",
 "Country is Sweden"
 ]
}

 The dataset includes 11793 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000322-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aamgz2
title: Occurrence Download

description: A dataset containing 12094 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Amino acid addition experiment Metagenome",
 "Country is Sweden"
 ]
}

 The dataset includes 12094 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000323-250218110819086/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.28436456
title: A novel endophytic fungus, Alternaria semiverrucosa and its ethyl acetate extract inhibits the proliferation, migration and invasion of cervical cancer cells

description: LC-MS was performed to identify bioactive compounds present in the ethyl acetate extract (EAE) of the fungal strain A. semiverrucosa. In total, 34 significant compounds were identified in the fungal extract, along with their respective molecular formulas and molecular weights.
DOI: 10.6084/m9.figshare.28436456.v1
title: A novel endophytic fungus, Alternaria semiverrucosa and its ethyl acetate extract inhibits the proliferation, migration and invasion of cervical cancer cells

description: LC-MS was performed to identify bioactive compounds present in the ethyl acetate extract (EAE) of the fungal strain A. semiverrucosa. In total, 34 significant compounds were identified in the fungal extract, along with their respective molecular formulas and molecular weights.
DOI: 10.15468/dl.nxcxt4
title: Occurrence Download

description: A dataset containing 5231 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Lupinus perennis L.",
 "Country is one of (Canada, United States of America)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5231 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000325-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14809805
title: Data regarding the manuscript: Ultrafast, All Optically Reconfigurable, Nonlinear Nanoantenna
DOI: 10.5281/zenodo.14809806
title: Data regarding the manuscript: Ultrafast, All Optically Reconfigurable, Nonlinear Nanoantenna
DOI: 10.15468/dl.3fhpn4
title: Occurrence Download

description: A dataset containing 10606 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Vascular plant herbarium TRH, NTNU University Museum",
 "Country is Sweden"
 ]
}

 The dataset includes 10606 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000326-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.