cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.k9474b
title: Occurrence Download

description: A dataset containing 86 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Batrachochytrium dendrobatidis Longcore, Pessier & D.K.Nichols",
 "Year 2017-2025"
 ]
}

 The dataset includes 86 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069500-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48366/r756711
title: Analysis of Soil for Irrigation and Erosion Control 

description: Various soil samples are analyzed for irrigation and erosion control in agriculture.
DOI: 10.6084/m9.figshare.27854706.v1
title: <b>Clinical </b><b>Characteristics </b><b>and Outcomes </b><b>of Patients Admitted to Intensive Care Units after Surgery</b>

description: This study aimed to examine the characteristics and outcomes of postoperative patients admitted to intensive care units (ICUs) in Nepal. A retrospective analysis was conducted across 18 ICUs from January 1, 2020, to December 31, 2023, involving 4,509 surgical patients. The study found that 65.9% of these patients were admitted directly from operating theaters, while 23.9% were transferred from wards. The readmission rate was higher for ward-admitted patients (11%) compared to those admitted directly from surgery (3.66%). Overall, surgical patient mortality was 9%, with significantly higher mortality among those admitted from wards (15.8%) versus those from operating theaters (6%). These findings highlight the need for targeted interventions to improve outcomes for patients transferred from wards to ICUs.
DOI: 10.6084/m9.figshare.27855188
title: Validation of the Addenbrooke’s Cognitive Examination-III for detecting vascular dementia in Iranian patients with stroke: A secondary data analysis

description: The current study was conducted with the aim of evaluating the third version of Addenbrooke’s Cognitive Examination (ACE-III), and exploring its diagnostic power for a sample of stroke patients in the Iranian population. This was a cross-sectional analytical study, in which 206 patients with stroke were compared with 200 normal individuals as the control group. The patients were diagnosed based on the findings of neuroimaging and clinical examination by a neurologist. ACE-III, Montreal Cognitive Assessment (MoCA), Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), and The Structured Clinical Interview for DSM-5 (SCID-5) were used to gather the data and assess the vascular dementia in the patients. Furthermore, Cronbach’s alpha, Pearson correlation coefficient, discriminant function analysis, and the receiver operating characteristic (ROC) curve were used to respectively measure internal consistency, convergent validity, discriminant validity, sensitivity, specificity, and the cutoff point of ACE-III. Internal consistency of ACE-III was excellent (α = 0.92 − 0.95), and convergent validity was measured through calculating the correlation between the scores of ACE-III and MoCA, which was very high (r = 0.957, P &lt; 0.0001). Moreover, overall classification accuracy of ACE-III revealed that it is able to differentiate 87% of patients with vascular dementia from other patients. The area under the ROC curve was found to be 0.84, and cutoff point was 45/46, at which sensitivity and specificity were obtained as 0.72 and 0.90, respectively. ACE-III is a rapid, inexpensive, and efficient tool for evaluating cognitive deficits in specialized neurology clinics to provide a clinical and differential diagnosis of vascular dementia after stroke.
DOI: 10.6084/m9.figshare.27855188.v1
title: Validation of the Addenbrooke’s Cognitive Examination-III for detecting vascular dementia in Iranian patients with stroke: A secondary data analysis

description: The current study was conducted with the aim of evaluating the third version of Addenbrooke’s Cognitive Examination (ACE-III), and exploring its diagnostic power for a sample of stroke patients in the Iranian population. This was a cross-sectional analytical study, in which 206 patients with stroke were compared with 200 normal individuals as the control group. The patients were diagnosed based on the findings of neuroimaging and clinical examination by a neurologist. ACE-III, Montreal Cognitive Assessment (MoCA), Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), and The Structured Clinical Interview for DSM-5 (SCID-5) were used to gather the data and assess the vascular dementia in the patients. Furthermore, Cronbach’s alpha, Pearson correlation coefficient, discriminant function analysis, and the receiver operating characteristic (ROC) curve were used to respectively measure internal consistency, convergent validity, discriminant validity, sensitivity, specificity, and the cutoff point of ACE-III. Internal consistency of ACE-III was excellent (α = 0.92 − 0.95), and convergent validity was measured through calculating the correlation between the scores of ACE-III and MoCA, which was very high (r = 0.957, P &lt; 0.0001). Moreover, overall classification accuracy of ACE-III revealed that it is able to differentiate 87% of patients with vascular dementia from other patients. The area under the ROC curve was found to be 0.84, and cutoff point was 45/46, at which sensitivity and specificity were obtained as 0.72 and 0.90, respectively. ACE-III is a rapid, inexpensive, and efficient tool for evaluating cognitive deficits in specialized neurology clinics to provide a clinical and differential diagnosis of vascular dementia after stroke.
DOI: 10.15468/dl.upnas6
title: Occurrence Download

description: A dataset listing the 2 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Urocystis kmetiana Magnus"
 ]
}

 The dataset's 2 records were derived from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022182-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ybh6ka
title: Occurrence Download

description: A dataset containing 79028 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bituminaria bituminosa (L.) C.H.Stirt."
 ]
}

 The dataset includes 79028 records from 726 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022188-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5w99km
title: Occurrence Download

description: A dataset containing 14484 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Gopherus polyphemus (Daudin, 1801)"
 ]
}

 The dataset includes 14484 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022189-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mtgw5a
title: Occurrence Download

description: A dataset listing the 3162 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is DEU.3_1",
 "Geometry POLYGON((13.39688 52.50485,13.42605 52.50485,13.42605 52.52369,13.39688 52.52369,13.39688 52.50485))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 3162 records were derived from 179 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022185-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vtwt33
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"10145011","matchCase":false},{"type":"equals","key":"HAS_COORDINATE","value":"true","matchCase":false},{"type":"equals","key":"BASIS_OF_RECORD","value":"PRESERVED SPECIMEN","matchCase":false},{"type":"equals","key":"COUNTRY","value":"CO","matchCase":false}]}

 The dataset includes 28 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022190-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ysyzwj
title: Occurrence Download

description: A dataset containing 335 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Continent is North America",
 "Country is Mexico",
 "DatasetKey is Digitalización y Sistematización de las Colecciones Biológicas Nacionales del Instituto de Biología, UNAM (Plantas vasculares)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Tecoma stans (L.) Juss. ex Kunth"
 ]
}

 The dataset includes 335 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022191-241107131044228/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.27288489
title: <b>Genome-Wide Association Study and Genomic Prediction of Soft Wheat End-Use Quality Traits Under Post-Anthesis Heat-Stressed Conditions</b>

description: This study aimed to identify genomic regions associated with wheat quality traits using genome-wide association studies (GWAS) and evaluate prediction accuracy of different genomic selection (GS) models. A panel of 236 soft red facultative wheat genotypes was evaluated for end-use quality traits across four heat-stressed environments over three years.
DOI: 10.5281/zenodo.14187143
title: kentropyx_calcarata_decontaminated_FSCR.fasta.gz
DOI: 10.5281/zenodo.14187144
title: kentropyx_calcarata_decontaminated_FSCR.fasta.gz
DOI: 10.15468/dl.zdrrxj
title: Occurrence Download

description: A dataset containing 193 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Diversidad y conservación del germoplasma de henequén Agave fourcroydes Lem. y su posible ancestro silvestre Agave angustifolia Haw."
 ]
}

 The dataset includes 193 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022192-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.25ftdc
title: Occurrence Download

description: A dataset containing 599 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Distribución histórica, prospección actual y áreas potenciales para reintroducir lobo mexicano (Canis lupus baileyi) en Durango, sur de la Sierra Madre Occidental, México",
 "TaxonKey is Canis lupus baileyi Nelson & Goldman, 1929"
 ]
}

 The dataset includes 599 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022193-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7hhu6m
title: Occurrence Download

description: A dataset containing 114 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Chlamydopus meyenianus (Klotzsch) Lloyd)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Human Observation, Material citation, Machine Observation, Living Specimen, Observation, Occurrence evidence)"
 ]
 }
 }
 ]
}

 The dataset includes 114 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022194-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/9954082
title: Mouse Pose
DOI: 10.5281/zenodo.10622272
title: Predictability of abrupt shifts in dryland ecosystem functioning

description: Data and code accompanying the paper:

Bernardino, P., De Keersmaecker, W., Horion, S., Oehmcke, S., Gieseke, F., Fensholt, R., Van De Kerchove, R., Lhermitte, S., Abel, C., Van Meerbeek, K., Verbesselt, J., and Somers, B. 2024. Predictability of abrupt shifts in dryland ecosystem functioning.
DOI: 10.5281/zenodo.10550436
title: Predictability of abrupt shifts in dryland ecosystem functioning

description: Data and code accompanying the paper:

Bernardino, P., De Keersmaecker, W., Horion, S., Oehmcke, S., Gieseke, F., Fensholt, R., Van De Kerchove, R., Lhermitte, S., Abel, C., Van Meerbeek, K., Verbesselt, J., and Somers, B. 2024. Predictability of abrupt shifts in dryland ecosystem functioning. Nature Climate Change, doi.org/10.1038/s41558-024-02201-0.
DOI: 10.5281/zenodo.10550437
title: Predictability of abrupt shifts in dryland ecosystem functioning

description: Data accompanying the paper:

Bernardino, P., De Keersmaecker, W., Horion, S., Oehmcke, S., Gieseke, F., Fensholt, R., Van De Kerchove, R., Lhermitte, S., Abel, C., Van Meerbeek, K., Verbesselt, J., and Somers, B. 2024. Predictability of abrupt shifts in dryland ecosystem functioning.
DOI: 10.5281/zenodo.10636821
title: Predictability of abrupt shifts in dryland ecosystem functioning

description: Data and code accompanying the paper:

Bernardino, P., De Keersmaecker, W., Horion, S., Oehmcke, S., Gieseke, F., Fensholt, R., Van De Kerchove, R., Lhermitte, S., Abel, C., Van Meerbeek, K., Verbesselt, J., and Somers, B. 2024. Predictability of abrupt shifts in dryland ecosystem functioning. Nature Climate Change, doi.org/10.1038/s41558-024-02201-0.
DOI: 10.15468/dl.zxhwwe
title: Occurrence Download

description: A dataset containing 955 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Material sample, Material citation, Fossil, Specimen, Living Specimen, Occurrence evidence, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Turdoides hindei (Sharpe, 1900)"
 ]
}

 The dataset includes 955 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022195-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13644719
title: Unique composition and evolution histories of low velocity mantle domains: Data and analysis

description: Dataset and Jupyter notebook accompanying 'Unique composition and evolution histories of low velocity mantle domains'. 

Dataset includes:



Present day properties of simulated mantle for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRM, MER.

Present day predicted seismic properties for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, MER.

Present day predicted seismic properties for simulation PRM assuming 'primordial' material to be i) basaltic oceanic crust ii) chondrite enriched basalt (CEB).

Present day delta Vs for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRM, MER, filtered using the resolution of seismic tomography model S40RTS.

Properties of simulated mantle at 100 Myr intervals from 900 Ma - 100 Ma inclusive for simulation RCY. 

P-T tables with predicted abundance of post-perovskite for different mantle lithologies (harzburgite, lherzolite and basalt - as defined in the paper).


Jupyter notebook `s-llvps.ipynb` contains code for identifying simulated large low-velocity provinces (S-LLVPs), extracting assoicated model properties and plotting results. Python module files terra_utils.py and ppv.py are also included and required by the code in the notebook. 

There are a number of pre-requisite packages that will need to be installed in order to run the Jupyter notebook, including terratools, a software package written specifically for reading and postprocessing outputs from TERRA simulations. Installation instructions can be found on the GitHub repository. 

Due to the TERRA code pre-dating open source licensing, we do not currently have permission to publicly share all aspects of the code. In code_pieces.F90 we include code snippets which were implemented for this study. 

Simulations were conducted using ARCHER2, the UK's national super-computing service.
DOI: 10.5281/zenodo.14187340
title: Unique composition and evolution histories of low velocity mantle domains: Data and analysis

description: Dataset and Jupyter notebook accompanying 'Unique composition and evolution histories of low velocity mantle domains'. 

Dataset includes:



Present day properties of simulated mantle for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRM, MER.

Present day predicted seismic properties for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, MER.

Present day predicted seismic properties for simulation PRM assuming 'primordial' material to be i) basaltic oceanic crust ii) chondrite enriched basalt (CEB).

Present day delta Vs for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRM, MER, filtered using the resolution of seismic tomography model S40RTS.

Properties of simulated mantle at 100 Myr intervals from 900 Ma - 100 Ma inclusive for simulation RCY. 

P-T tables with predicted abundance of post-perovskite for different mantle lithologies (harzburgite, lherzolite and basalt - as defined in the paper).


Jupyter notebook `s-llvps.ipynb` contains code for identifying simulated large low-velocity provinces (S-LLVPs), extracting assoicated model properties and plotting results. Python module files terra_utils.py and ppv.py are also included and required by the code in the notebook. 

There are a number of pre-requisite packages that will need to be installed in order to run the Jupyter notebook, including terratools, a software package written specifically for reading and postprocessing outputs from TERRA simulations. Installation instructions can be found on the GitHub repository. 

Due to the TERRA code pre-dating open source licensing, we do not currently have permission to publicly share all aspects of the code. In code_pieces.F90 we include code snippets which were implemented for this study. 

Simulations were conducted using ARCHER2, the UK's national super-computing service. 

RCY.mp4 is a movie produced for simualtion RCY, visualising the evolution of temperature (right panels) and bulk composition (left panels). Hot iso-surface (red) drawn at +500 K and cold iso-surface (blue) drawn at -400 K, composition iso-surface drawn at C=0.6. Red and blue lines indicate overlying ridges / subduction zones taken from the plate motion reconstructions of Müller et al (2022).
DOI: 10.5281/zenodo.11220932
title: Unique composition and evolution histories of low velocity mantle domains: Data and analysis

description: Dataset and Jupyter notebook accompanying 'Unique composition and evolution histories of low velocity mantle domains'. 

Dataset includes:



Present day properties of simulated mantle for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRM, MER.

Present day predicted seismic properties for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, MER.

Present day predicted seismic properties for simulation PRM assuming 'primordial' material to be i) basaltic oceanic crust ii) chondrite enriched basalt (CEB).

Present day delta Vs for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRM, MER, filtered using the resolution of seismic tomography model S40RTS.

Properties of simulated mantle at 100 Myr intervals from 900 Ma - 100 Ma inclusive for simulation RCY. 

P-T tables with predicted abundance of post-perovskite for different mantle lithologies (harzburgite, lherzolite and basalt - as defined in the paper).


Jupyter notebook `s-llvps.ipynb` contains code for identifying simulated large low-velocity provinces (S-LLVPs), extracting assoicated model properties and plotting results. Python module files terra_utils.py and ppv.py are also included and required by the code in the notebook. 

There are a number of pre-requisite packages that will need to be installed in order to run the Jupyter notebook, including terratools, a software package written specifically for reading and postprocessing outputs from TERRA simulations. Installation instructions can be found on the GitHub repository. 

Due to the TERRA code pre-dating open source licensing, we do not currently have permission to publicly share all aspects of the code. In code_pieces.F90 we include code snippets which were implemented for this study. 

Simulations were conducted using ARCHER2, the UK's national super-computing service. 

RCY.mp4 is a movie produced for simualtion RCY, visualising the evolution of temperature (right panels) and bulk composition (left panels). Hot iso-surface (red) drawn at +500 K and cold iso-surface (blue) drawn at -400 K, composition iso-surface drawn at C=0.6. Red and blue lines indicate overlying ridges / subduction zones taken from the plate motion reconstructions of Müller et al (2022).
DOI: 10.5281/zenodo.11220933
title: Unique composition and evolution histories of low velocity mantle domains: Data and analysis

description: Dataset and Jupyter notebook accompanying 'Unique composition and evolution histories of low velocity mantle domains'. 

Dataset includes:



Present day properties of simulated mantle for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRIM.

Present day predicted seismic properties for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRIM.

Present day delta Vs for simulations RCY, B=0.22, B=0.44, visc2, visc3, CMB2600, CMB2800, COMP, PRIM, filtered using the resolution of seismic tomography model S40RTS.

Properties of simulated mantle at 100 Myr intervals from 900 Ma - 100 Ma inclusive for simulation RCY. 

P-T tables with predicted abundance of post-perovskite for different mantle lithologies (harzburgite, lherzolite and basalt - as defined in the paper).


Jupyter notebook `s-llvps.ipynb` contains code for identifying simulated large low-velocity provinces (S-LLVPs), extracting assoicated model properties and plotting results. Python module files terra_utils.py and ppv.py are also included and required by the code in the notebook. 

There are a number of pre-requisite packages that will need to be installed in order to run the Jupyter notebook, including terratools, a software package written specifically for reading and postprocessing outputs from TERRA simulations. Installation instructions can be found on the GitHub repository. 

Due to the TERRA code pre-dating open source licensing, we do not currently have permission to publicly share all aspects of the code. In code_pieces.F90 we include code snippets which were implemented for this study. 

Simulations were conducted using ARCHER2, the UK's national super-computing service.