cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/ddaff441-e18e-4f17-b3a4-6a827ea214b5
title: Virkisjökull-Falljökull glacier icefall timelapse images

description: This image dataset was captured as part of the operation of an automated weather station at the Virkisjökull-Falljökull Glacier, SE Iceland. The station formed part of the BGS Iceland Glacier Observatory network of sensors, deployed between 2009 and 2020 in order to characterise and identify glacial, geomorphological and hydrological drivers and processes and their timescales across the deglaciating Virkisjökull-Falljökull catchment in SE Iceland.  
This image time series was captured at (WGS-84) 63°58’12.78″N 16°47’5.64″W, on a lateral moraine sequence adjacent to the glacier icefall and were generated alongside the continuous operation of two further weather stations, river gauging, a network of groundwater level gauges and numerous other forms of monitoring.
The records presented here begin in September 2011 with the installation of the camera on the weather station, and continue to February 2018. 
The data complements the published groundwater and river gauging datasets published here, and will be of use to researchers, teachers and students wishing to see an excellent example of glacier flow, or those interested in the processes observed in a rapidly deglaciating landscape, including anyone interested to follow up on the various research studies published from this site in the international literature.
The BGS project was led and coordinated by Dr Jez Everest, and during earlier years Tom Bradwell (Uni of Stirling, formerly BGS). Technical support and implementation was provided by Heiko Buxel and Tom Shanahan.  The dataset is not fully continuous as certain periods were lost due to equipment downtime. Enquiries are welcome and should be directed to Dr Everest.
DOI: 10.6084/m9.figshare.24657362
title: Differentiating between segmental arterial mediolysis and other arterial vasculopathies to establish an early diagnosis – a systematic literature review and proposal of new diagnostic criteria

description: Segmental arterial mediolysis (SAM) is a rare vascular disease, characterized by acute but transient vulnerability of the wall of medium-sized arteries. The most characteristic feature of SAM is its biphasic course: an injurious phase marked by acute weakness of the arterial wall leading to acute dissection and/or hemorrhage, followed by a reparative phase in which granulation tissue and fibrosis restore the injured arterial wall. Residual stenosis, aneurysms, and/or arterial wall irregularities may remain visible on future imaging studies. Differentiating between SAM and other arterial vasculopathies is difficult due to its similarities with many other vascular diseases, such as vasculitis, fibromuscular dysplasia, inherited connective tissue disorders, and isolated visceral artery dissection. In this systematic review, we provide an overview on SAM, with an emphasis on the differential diagnosis and diagnostic work-up. We propose new diagnostic criteria to help establish a prompt diagnosis of SAM, illustrated by case examples from our multidisciplinary vascular clinic.
DOI: 10.6084/m9.figshare.24657362.v1
title: Differentiating between segmental arterial mediolysis and other arterial vasculopathies to establish an early diagnosis – a systematic literature review and proposal of new diagnostic criteria

description: Segmental arterial mediolysis (SAM) is a rare vascular disease, characterized by acute but transient vulnerability of the wall of medium-sized arteries. The most characteristic feature of SAM is its biphasic course: an injurious phase marked by acute weakness of the arterial wall leading to acute dissection and/or hemorrhage, followed by a reparative phase in which granulation tissue and fibrosis restore the injured arterial wall. Residual stenosis, aneurysms, and/or arterial wall irregularities may remain visible on future imaging studies. Differentiating between SAM and other arterial vasculopathies is difficult due to its similarities with many other vascular diseases, such as vasculitis, fibromuscular dysplasia, inherited connective tissue disorders, and isolated visceral artery dissection. In this systematic review, we provide an overview on SAM, with an emphasis on the differential diagnosis and diagnostic work-up. We propose new diagnostic criteria to help establish a prompt diagnosis of SAM, illustrated by case examples from our multidisciplinary vascular clinic.
DOI: 10.6084/m9.figshare.25144453
title: Machine learning-based risk prediction of hypoxemia for outpatients undergoing sedation colonoscopy: a practical clinical tool

description: Hypoxemia as a common complication in colonoscopy under sedation and may result in serious consequences. Unfortunately, a hypoxemia prediction model for outpatient colonoscopy has not been developed. Consequently, the objective of our study was to develop a practical and accurate model to predict the risk of hypoxemia in outpatient colonoscopy under sedation. In this study, we included patients who received colonoscopy with anesthesia in Nanjing First Hospital from July to September 2021. Risk factors were selected through the least absolute shrinkage and selection operator (LASSO). Prediction models based on logistic regression (LR), random forest classifier (RFC), extreme gradient boosting (XGBoost), support vector machine (SVM), and stacking classifier (SCLF) model were implemented and assessed by standard metrics such as the area under the receiver operating characteristic curve (AUROC), sensitivity and specificity. Then choose the best model to develop an online tool for clinical use. We ultimately included 839 patients. After LASSO, body mass index (BMI) (coefficient = 0.36), obstructive sleep apnea-hypopnea syndrome (OSAHS) (coefficient = 1.32), basal oxygen saturation (coefficient = -0.14), and remifentanil dosage (coefficient = 0.04) were independent risk factors for hypoxemia. The XGBoost model with an AUROC of 0.913 showed the best performance among the five models. Our study selected the XGBoost as the first model especially for colonoscopy, with over 95% accuracy and excellent specificity. The XGBoost includes four variables that can be quickly obtained. Moreover, an online prediction practical tool has been provided, which helps screen high-risk outpatients with hypoxemia swiftly and conveniently. Colonoscopy under sedation is an effective technique for the inspection and treatment of alimentary canal diseases, but hypoxemia associated with this process cannot be ignored, since prolonged or severe hypoxemia may result in several serious consequences. We wanted to develop a practical and accurate model to predict the risk of hypoxemia for outpatient colonoscopy under sedation, which could help clinicians make more accurate and objective judgments to prevent patients from being harmed. A total of 839 patients were included in our study and we constructed five machine learning models and selected the best one, which demonstrated satisfactory performance. On this basis, a user-friendly data interface has been developed for convenient application. Clinicians can log in to this interface at any time and it will automatically calculate the patient’s risk of hypoxemia when entering patient information. This study offers evidence that machine learning algorithms can accurately predict the risk of hypoxemia for outpatient colonoscopy under sedation and the model we developed is a practical and interpretable tool that could be used as a clinical decision-making aid.
DOI: 10.6084/m9.figshare.25144453.v1
title: Machine learning-based risk prediction of hypoxemia for outpatients undergoing sedation colonoscopy: a practical clinical tool

description: Hypoxemia as a common complication in colonoscopy under sedation and may result in serious consequences. Unfortunately, a hypoxemia prediction model for outpatient colonoscopy has not been developed. Consequently, the objective of our study was to develop a practical and accurate model to predict the risk of hypoxemia in outpatient colonoscopy under sedation. In this study, we included patients who received colonoscopy with anesthesia in Nanjing First Hospital from July to September 2021. Risk factors were selected through the least absolute shrinkage and selection operator (LASSO). Prediction models based on logistic regression (LR), random forest classifier (RFC), extreme gradient boosting (XGBoost), support vector machine (SVM), and stacking classifier (SCLF) model were implemented and assessed by standard metrics such as the area under the receiver operating characteristic curve (AUROC), sensitivity and specificity. Then choose the best model to develop an online tool for clinical use. We ultimately included 839 patients. After LASSO, body mass index (BMI) (coefficient = 0.36), obstructive sleep apnea-hypopnea syndrome (OSAHS) (coefficient = 1.32), basal oxygen saturation (coefficient = -0.14), and remifentanil dosage (coefficient = 0.04) were independent risk factors for hypoxemia. The XGBoost model with an AUROC of 0.913 showed the best performance among the five models. Our study selected the XGBoost as the first model especially for colonoscopy, with over 95% accuracy and excellent specificity. The XGBoost includes four variables that can be quickly obtained. Moreover, an online prediction practical tool has been provided, which helps screen high-risk outpatients with hypoxemia swiftly and conveniently. Colonoscopy under sedation is an effective technique for the inspection and treatment of alimentary canal diseases, but hypoxemia associated with this process cannot be ignored, since prolonged or severe hypoxemia may result in several serious consequences. We wanted to develop a practical and accurate model to predict the risk of hypoxemia for outpatient colonoscopy under sedation, which could help clinicians make more accurate and objective judgments to prevent patients from being harmed. A total of 839 patients were included in our study and we constructed five machine learning models and selected the best one, which demonstrated satisfactory performance. On this basis, a user-friendly data interface has been developed for convenient application. Clinicians can log in to this interface at any time and it will automatically calculate the patient’s risk of hypoxemia when entering patient information. This study offers evidence that machine learning algorithms can accurately predict the risk of hypoxemia for outpatient colonoscopy under sedation and the model we developed is a practical and interpretable tool that could be used as a clinical decision-making aid.
DOI: 10.15468/dl.xko7e2
title: Occurrence Download

description: A dataset containing 5884628 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Natural History Museum (London) Collection Specimens"
 ]
}

 The dataset includes 5884628 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009402-170826194755519/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3nk28a
title: Occurrence Download

description: A dataset containing 1186 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Phaethornis stuarti Hartert, 1897"
 ]
}

 The dataset includes 1186 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050657-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u4ysam
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eugenia radiciflora H.Perrier"
 ]
}

 The dataset includes 36 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046662-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xqa3jw
title: Occurrence Download

description: A dataset containing 561 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 {
 "or" : [
 "TaxonKey is Iberis procumbens subsp. microcarpa Franco & P.Silva",
 "TaxonKey is Iberis runemarkii Greuter & Burdet",
 "TaxonKey is Iris aphylla L.",
 "TaxonKey is Iris humilis Georgi",
 "TaxonKey is Iris humilis subsp. arenaria (Waldst. & Kit.) Á.Löve & D.Löve",
 "TaxonKey is Iris marsica I.Ricci & Colas.",
 "TaxonKey is Isoetes boryana Durieu",
 "TaxonKey is Jacobaea vulgaris subsp. gotlandica (Neuman) B.Nord.",
 "TaxonKey is Jankaea heldreichii (Boiss.) Boiss.",
 "TaxonKey is Jasione crispa subsp. serpentinica P.Silva",
 "TaxonKey is Jasminum azoricum L.",
 "TaxonKey is Jonopsidium acaule (Desf.) Rchb.",
 "TaxonKey is Juncus valvatus Link",
 "TaxonKey is Jurinea cyanoides (L.) Rchb.",
 "TaxonKey is Klasea lycopifolia (Vill.) Á.Löve & D.Löve",
 "TaxonKey is Kochia saxicola Guss.",
 "TaxonKey is Kosteletzkya pentacarpos (L.) Ledeb.",
 "TaxonKey is Lactuca watsoniana Trel.",
 "TaxonKey is Lamyropsis microcephala (Moris) Dittrich & Greuter",
 "TaxonKey is Leontodon siculus (Guss.) Nyman",
 "TaxonKey is Leopoldia gussonei Parl.",
 "TaxonKey is Lepidotis inundata (L.) P.Beauv.",
 "TaxonKey is Leucojum nicaeense Ardoino",
 "TaxonKey is Leuzea centauroides (L.) Holub",
 "TaxonKey is Leuzea longifolia Hoffmanns. & Link"
 ]
 }
 ]
}

 The dataset includes 561 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009403-151016162008034/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xvdmdg
title: Occurrence Download

description: A dataset containing 22570 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Erodium malacoides (L.) L'Hér."
 ]
}

 The dataset includes 22570 records from 408 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046679-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.npamsc
title: Occurrence Download

description: A dataset containing 131 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Malaysia, Indonesia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Echinosorex gymnura (Raffles, 1822)"
 ]
}

 The dataset includes 131 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050718-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f2d3fj
title: Occurrence Download

description: A dataset containing 60010 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pelophylax ridibundus (Pallas, 1771)"
 ]
}

 The dataset includes 60010 records from 1080 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050745-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x18fdb
title: Occurrence Download

description: A dataset containing 162 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Touit costaricensis (Cory, 1913)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 162 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009403-160118175350007/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.avz9zw
title: Occurrence Download

description: A dataset containing 4389 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Euphorbia sieboldiana C.Morren & Decne."
 ]
}

 The dataset includes 4389 records from 135 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046710-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/rhdnp7
title: A new species of Tapajosa Melichar from Curaçao, Lesser Antilles (Hemiptera: Cicadellidae: Proconiini)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Haas, Matthé Cornelis De, Gaiani, Marco A. (2024): A new species of Tapajosa Melichar from Curaçao, Lesser Antilles (Hemiptera: Cicadellidae: Proconiini). Zootaxa 5497 (1): 133-141, DOI: 10.11646/zootaxa.5497.1.8, URL: http://dx.doi.org/10.11646/zootaxa.5497.1.8AbstractA new species of the Neotropical genus Tapajosa Melichar 1924 from Curaçao is proposed, described, and illustrated. Tapajosa arawaka sp. nov. differs from other species of the genus mainly in the shape of male genitalia. Its close morphological affinity with Tapajosa spinata Young, 1968 suggests that ancestors of the new species migrated from mainland Venezuela.
DOI: 10.15468/dl.2w6p77
title: Occurrence Download

description: A dataset containing 75689 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "OccurrenceStatus is Present",
 "TaxonKey is Pandion haliaetus (Linnaeus, 1758)"
 ]
}

 The dataset includes 75689 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000166-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.49qfux
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate rounded, Geodetic datum assumed WGS84, Country derived from coordinates, Continent derived from coordinates, Coordinate reprojected)",
 "TaxonKey is Steatoda autumnalis (Banks, 1898)"
 ]
}

 The dataset includes 48 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000167-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f5w97x
title: Occurrence Download

description: A dataset containing 79510 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ukraine",
 "TaxonKey is Anseriformes"
 ]
}

 The dataset includes 79510 records from 129 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000165-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nsfw8n
title: Occurrence Download

description: A dataset containing 1616628 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Labridae",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1616628 records from 763 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000151-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n9xfqm
title: Occurrence Download

description: A dataset containing 367 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Panthera uncia (Schreber, 1775)"
 ]
}

 The dataset includes 367 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000168-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hnwg5x
title: Occurrence Download

description: A dataset containing 6110 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Desmognathus conanti Rossman, 1958)"
 ]
}

 The dataset includes 6110 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000169-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8azn3z
title: Occurrence Download

description: A dataset containing 138010 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate rounded, Coordinate reprojected, Geodetic datum assumed WGS84, Country derived from coordinates, Continent derived from coordinates)",
 "TaxonKey is Canis lupus Linnaeus, 1758"
 ]
}

 The dataset includes 138010 records from 512 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000156-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g27zpn
title: Occurrence Download

description: A dataset containing 472 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "TaxonKey is Grallaria carrikeri Schulenberg & M.D.Williams, 1982"
 ]
}

 The dataset includes 472 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000170-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccr4rrc
title: CCDC 689773: Experimental Crystal Structure Determination

description: Related Article: D.Basavaiah, D.V.Lenin, B.Devendar|2009|Tetrahedron Lett.|50|3538|doi:10.1016/j.tetlet.2009.03.038
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.13140/rg.2.2.12537.60002
title: IMG 6906 RG Achievement - April 25, 2021
DOI: 10.15468/pgezdw
title: Données naturalistes opportunistes issues de la plateforme INaturalist-Données naturalistes opportunistes Knut Jäger (kjaeger)

description: Données naturalistes opportunistes saisies sur iNaturalist à partir du compte "kjaeger"
DOI: 10.5517/ccrx02q
title: CCDC 712103: Experimental Crystal Structure Determination

description: Related Article: Timothy J. Blackburn, Michael J. Kilner, Eric J. Thomas|2015|Tetrahedron|71|7293|doi:10.1016/j.tet.2015.04.005
description: Related Article: T.J.Blackburn, M.Helliwell, M.J.Kilner, A.T.L.Lee, E.J.Thomas|2009|Tetrahedron Lett.|50|3550|doi:10.1016/j.tetlet.2009.03.042
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.