cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10022405
title: Solution-State Methyl NMR Spectroscopy of Large Non-Deuterated Proteins Enabled by Deep Neural Networks

description: This dataset relates to the publications:

Solution-state methyl NMR spectroscopy of large non-deuterated proteins enabled by deep neural networks. Karunanithy G, Shukla VK, Hansen DF. Nat Commun. 2024 Jun 13;15(1):5073. doi: 10.1038/s41467-024-49378-8.



Training data for Deep Neural Networks developed in the manuscript "Solution-State Methyl NMR Spectroscopy of Large Non-Deuterated Proteins Enabled by Deep Neural Networks"

Experimental cross-validation data:



2D spectra of HDAC8, MSG, and a7a7 proteasome

3D NOESY spectra of MSG




Please see GitHub (https://github.com/gogulan-k/FID-Net) for additional scripts and details.
DOI: 10.15468/dl.frtyd8
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Syagrius intrudens Waterhouse, 1903)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 43 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040969-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m27fgh
title: Occurrence Download

description: A dataset containing 6765 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "DatasetKey is iNaturalist Research-grade Observations",
 "Issue is Coordinate rounded",
 "OccurrenceStatus is Present",
 "TaxonKey is Panthera leo (Linnaeus, 1758)",
 "Year 2014-2024"
 ]
}

 The dataset includes 6765 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040970-240626123714530/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.26378740
title: [<sup>68</sup>Ga]PSMA-11 for positron emission tomography (PET) imaging of prostate-specific membrane antigen (PSMA)-positive lesions in men with prostate cancer

description: Theranostics targeting prostate-specific membrane antigen (PSMA) represent a new targeted approach for prostate cancer care that combines diagnostic and therapeutic radiopharmaceuticals to diagnose and treat the disease. Positron emission tomography (PET) is the imaging method of choice and several diagnostic radiopharmaceuticals for quantifying PSMA have received FDA approval and are in clinical use. [<sup>68</sup>Ga]Ga-PSMA-11 is one such imaging agent and the focus of this article. One beta-emitting radioligand therapy ([<sup>177</sup>Lu]Lu-PSMA-617) has also received FDA approval for prostate cancer treatment, and several other alpha- and beta-emitting radioligand therapies are in clinical trials. Theranostics targeting PSMA in men with prostate cancer are discussed with a focus on use of [<sup>68</sup>Ga]Ga-PSMA-11 for imaging PSMA-positive lesions in men with prostate cancer. The review covers [<sup>68</sup>Ga]Ga-PSMA-11 manufacture, current regulatory status, comparison of [<sup>68</sup>Ga]Ga-PSMA-11 to other imaging techniques, clinical updates, and emerging applications of artificial intelligence for [<sup>68</sup>Ga]Ga-PSMA-11 PET. [<sup>68</sup>Ga]Ga-PSMA-11 is used in conjunction with a PET/CT scan to image PSMA positive lesions in men with prostate cancer. It is manufactured by chelating precursor with<sup>68</sup>Ga, either from a generator or cyclotron, and has regulatory approval around the world. It is widely used clinically in conjunction with radioligand therapies like [<sup>177</sup>Lu]Lu-PSMA-617.
DOI: 10.6084/m9.figshare.26378740.v1
title: [<sup>68</sup>Ga]PSMA-11 for positron emission tomography (PET) imaging of prostate-specific membrane antigen (PSMA)-positive lesions in men with prostate cancer

description: Theranostics targeting prostate-specific membrane antigen (PSMA) represent a new targeted approach for prostate cancer care that combines diagnostic and therapeutic radiopharmaceuticals to diagnose and treat the disease. Positron emission tomography (PET) is the imaging method of choice and several diagnostic radiopharmaceuticals for quantifying PSMA have received FDA approval and are in clinical use. [<sup>68</sup>Ga]Ga-PSMA-11 is one such imaging agent and the focus of this article. One beta-emitting radioligand therapy ([<sup>177</sup>Lu]Lu-PSMA-617) has also received FDA approval for prostate cancer treatment, and several other alpha- and beta-emitting radioligand therapies are in clinical trials. Theranostics targeting PSMA in men with prostate cancer are discussed with a focus on use of [<sup>68</sup>Ga]Ga-PSMA-11 for imaging PSMA-positive lesions in men with prostate cancer. The review covers [<sup>68</sup>Ga]Ga-PSMA-11 manufacture, current regulatory status, comparison of [<sup>68</sup>Ga]Ga-PSMA-11 to other imaging techniques, clinical updates, and emerging applications of artificial intelligence for [<sup>68</sup>Ga]Ga-PSMA-11 PET. [<sup>68</sup>Ga]Ga-PSMA-11 is used in conjunction with a PET/CT scan to image PSMA positive lesions in men with prostate cancer. It is manufactured by chelating precursor with<sup>68</sup>Ga, either from a generator or cyclotron, and has regulatory approval around the world. It is widely used clinically in conjunction with radioligand therapies like [<sup>177</sup>Lu]Lu-PSMA-617.
DOI: 10.6084/m9.figshare.26380073
title: The impact of volcanic eruptions, pyrocumulonimbus plumes, and the Arctic polar vortex intrusions on aerosol loading over Tomsk (Western Siberia, Russia) as observed by lidar from 2018 to 2022

description: Long-term ground-based lidar observations are important in estimating the contribution of different sources (mostly volcanic eruptions and wildfires) to aerosol loading of the atmosphere and in developing and improving various climate models. In this paper, we carefully analyse aerosol scattering ratio profiles and aerosol layers, observed with 532-nm lidar measurements at the Siberian Lidar Station in Tomsk (56.48°N, 85.05°E) over the period 2018–2022, and identify the layers’ potential sources. To compare aerosol loading over Tomsk for the last five years (2018–2022) with that for previous years, we also present and discuss time series of integrated aerosol backscatter coefficient (IABC) for three altitude ranges. The first range (15–30 km) reveals the pure stratospheric aerosol loading provided by volcanic eruptions, the second range (11–15 km) is responsible mainly for aftereffects of wildfire smoke plumes, and the third one (11–30 km) demonstrates aerosol contribution from both sources. In particular, we found for the period 2001–2022 that the annual average IABC reached its maximal values of 2.91 × 10<sup>−4</sup> sr<sup>−1</sup> (15–30 km) and 8.21 × 10<sup>−4</sup> sr<sup>−1</sup> (11–30 km) in 2022 due to the Hunga Tonga-Hunga Ha’apai volcanic eruption. The period 2020–2022 exhibited a significant increase in the relative aerosol content at altitudes of 11–15 km in the total aerosol loading at 11–30 km over Tomsk from 54.4% in 2020 to 64.8% in 2022, which indicates a shift of the main part of aerosol loading to altitudes of 11–15 km due to the increased wildfire activity in North America and north-eastern Asia. The Arctic polar vortex is also revealed to distort the real aerosol vertical distribution over Tomsk by replacing it with the aerosol distribution inside the vortex on measurement days when the vortex is over the lidar site.
DOI: 10.6084/m9.figshare.26380073.v1
title: The impact of volcanic eruptions, pyrocumulonimbus plumes, and the Arctic polar vortex intrusions on aerosol loading over Tomsk (Western Siberia, Russia) as observed by lidar from 2018 to 2022

description: Long-term ground-based lidar observations are important in estimating the contribution of different sources (mostly volcanic eruptions and wildfires) to aerosol loading of the atmosphere and in developing and improving various climate models. In this paper, we carefully analyse aerosol scattering ratio profiles and aerosol layers, observed with 532-nm lidar measurements at the Siberian Lidar Station in Tomsk (56.48°N, 85.05°E) over the period 2018–2022, and identify the layers’ potential sources. To compare aerosol loading over Tomsk for the last five years (2018–2022) with that for previous years, we also present and discuss time series of integrated aerosol backscatter coefficient (IABC) for three altitude ranges. The first range (15–30 km) reveals the pure stratospheric aerosol loading provided by volcanic eruptions, the second range (11–15 km) is responsible mainly for aftereffects of wildfire smoke plumes, and the third one (11–30 km) demonstrates aerosol contribution from both sources. In particular, we found for the period 2001–2022 that the annual average IABC reached its maximal values of 2.91 × 10<sup>−4</sup> sr<sup>−1</sup> (15–30 km) and 8.21 × 10<sup>−4</sup> sr<sup>−1</sup> (11–30 km) in 2022 due to the Hunga Tonga-Hunga Ha’apai volcanic eruption. The period 2020–2022 exhibited a significant increase in the relative aerosol content at altitudes of 11–15 km in the total aerosol loading at 11–30 km over Tomsk from 54.4% in 2020 to 64.8% in 2022, which indicates a shift of the main part of aerosol loading to altitudes of 11–15 km due to the increased wildfire activity in North America and north-eastern Asia. The Arctic polar vortex is also revealed to distort the real aerosol vertical distribution over Tomsk by replacing it with the aerosol distribution inside the vortex on measurement days when the vortex is over the lidar site.
DOI: 10.15468/dl.49e543
title: Occurrence Download

description: A dataset containing 26234 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Sylvirana guentheri (Boulenger, 1882))",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 26234 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040971-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13121022
title: Analysis of the effectiveness and safety of conventional anticoagulants in preventing deep vein thrombosis after total knee arthroplasty in patients undergoing total knee arthroplasty at high altitudes

description: Analysis of the effectiveness and safety of conventional anticoagulants in preventing deep vein thrombosis after total knee arthroplasty in patients undergoing total knee arthroplasty at high altitudes
DOI: 10.5281/zenodo.13121023
title: Analysis of the effectiveness and safety of conventional anticoagulants in preventing deep vein thrombosis after total knee arthroplasty in patients undergoing total knee arthroplasty at high altitudes

description: Analysis of the effectiveness and safety of conventional anticoagulants in preventing deep vein thrombosis after total knee arthroplasty in patients undergoing total knee arthroplasty at high altitudes
DOI: 10.15468/dl.sk9mmb
title: Occurrence Download

description: A dataset containing 5178 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Symphoricarpos albus var. laevigatus (Fernald) S.F.Blake)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 5178 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040972-240626123714530/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.25558785.v2
title: ATAC Data and code

description: <b>ATAC data</b><b> </b><b>and code</b><b> </b><b>of mononuclear chromatin structure in mice with ischemic stroke</b><br>
DOI: 10.15468/dl.nedke4
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Symphoricarpos microphyllus x orbiculatus)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 16 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040973-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wqaykb
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Symphyotrichum falcatum var. commutatum (Torr. & A.Gray) G.L.Nesom)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040974-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10233475
title: Data and code for "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. 2024

description: This data and code is made available to support the article: "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. 2024".

Includes: TMOC method output tide correlation, Antarctic Peninsula grounding line, DInSAR data, TMOC Code.

 

For the data:

These data are made available to acompany the article "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. (2024)

This datset contains:

AP_TMOC_tide_correlation_2019_2020.tif - Significance adjusted tide correlation values for the TMOC method for 2019-2020 for the Antarctic Peninsula.

AP_GL_TMOC_2019_2020.shp - A continuous grounding line made from TMOC data and British Antarctic Survey Coastline Data. Intended for use by others.

AP_GL_TMOC_2019_2020_source.shp - A discontinuous grounding line made from TMOC data and British Antarctic Survey Coastline Data including the source of each line segment.

The folder 'Interferograms' contains the DInSAR products used in the manuscript, sorted by Sentinel-1 frame

 

For the code:

This code is made available to support the article "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al.

The authors take no responsibility for the quality of results derived using this code.

This code is licensed under a Creative Commons Attribution 4.0 International Licence: http://creativecommons.org/licenses/by/4.0/

external functions required:geoimread - https://uk.mathworks.com/matlabcentral/fileexchange/46904-geoimreadpolarstreo_inv - https://uk.mathworks.com/matlabcentral/fileexchange/32907-polar-stereographic-coordinate-transformation-map-to-lat-lonCATS208 tide model and TMD 2.5 matlab toolbox - https://www.esr.org/research/polar-tide-models/tmd-software/

The function TMOC_GL_v8 implements the TMOC method descibed in Wallis et al. 2024. This is a 'bring your own data' version.

The script pp_folder prost-processes the outputs using the functuon LPfilt_cc
DOI: 10.5281/zenodo.10233476
title: Reviewer Assets for "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. 2023

description: Includes: TMOC method output tide correlation, Antarctic Peninsula grounding line, DInSAR data, TMOC Code for review purposes.
description: This data is to be used exclusively by those involved in reviewing the article: "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. 2023".
DOI: 10.5281/zenodo.13120995
title: Data and code for "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. 2024

description: This data and code is made available to support the article: "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. 2024".

Includes: TMOC method output tide correlation, Antarctic Peninsula grounding line, DInSAR data, TMOC Code.

 

For the data:

These data are made available to acompany the article "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al. (2024)

This datset contains:

AP_TMOC_tide_correlation_2019_2020.tif - Significance adjusted tide correlation values for the TMOC method for 2019-2020 for the Antarctic Peninsula.

AP_GL_TMOC_2019_2020.shp - A continuous grounding line made from TMOC data and British Antarctic Survey Coastline Data. Intended for use by others.

AP_GL_TMOC_2019_2020_source.shp - A discontinuous grounding line made from TMOC data and British Antarctic Survey Coastline Data including the source of each line segment.

The folder 'Interferograms' contains the DInSAR products used in the manuscript, sorted by Sentinel-1 frame

 

For the code:

This code is made available to support the article "Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method" by Wallis et al.

The authors take no responsibility for the quality of results derived using this code.

This code is licensed under a Creative Commons Attribution 4.0 International Licence: http://creativecommons.org/licenses/by/4.0/

external functions required:geoimread - https://uk.mathworks.com/matlabcentral/fileexchange/46904-geoimreadpolarstreo_inv - https://uk.mathworks.com/matlabcentral/fileexchange/32907-polar-stereographic-coordinate-transformation-map-to-lat-lonCATS208 tide model and TMD 2.5 matlab toolbox - https://www.esr.org/research/polar-tide-models/tmd-software/

The function TMOC_GL_v8 implements the TMOC method descibed in Wallis et al. 2024. This is a 'bring your own data' version.

The script pp_folder prost-processes the outputs using the functuon LPfilt_cc
DOI: 10.15468/dl.awb7mz
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Symphyotrichum laeve var. geyeri (A.Gray) G.L.Nesom)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 7 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040975-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wdurff
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-41.464 26.43204,-5.00309 26.43204,-5.00309 48.20653,-41.464 48.20653,-41.464 26.43204))",
 "TaxonKey is Polyipnus polli Schultz, 1961"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040976-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vx7axu
title: Occurrence Download

description: A dataset containing 23025 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Symphyotrichum lanceolatum (Willd.) G.L.Nesom)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 23025 records from 302 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040977-240626123714530/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.26394838
title: Metabolomics data Mock and RV-SA11 6 and 12 hpi.xlsx

description: The metabolomics dataset represent host cell (HT-29) metabolites altered in Rotavirus (RV-SA11) infection scenario at two time-points, i.e., 6 and 12 hours post infection.
DOI: 10.15468/dl.c2q3mh
title: Occurrence Download

description: A dataset containing 122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Symphyotrichum pilosum var. pringlei (A.Gray) G.L.Nesom)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 122 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040978-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10715568
title: Test-SM
DOI: 10.5281/zenodo.10715569
title: Test1
DOI: 10.5281/zenodo.13120979
title: Test
title: Supplementary
DOI: 10.5281/zenodo.13121042
title: Test-SM
DOI: 10.5281/zenodo.13103632
title: Habitat suitability of European land systems for terrestrial vertebrate species

description: This dataset documents the habitat suitability of European land systems for 1155 terrestrial vertebrate species, based on a novel land system classification of Europe that factors in land use intensity (Dou et al., 2021). This information can be used to refine species spatial distributions based on the known suitability of land use classes for species. This dataset also includes data on distance to water requirements for species that depend on water ecosystems for food or as habitat, as it is an additional information that is useful for refining species distributions. 

File structure and content: - habitatPreferences.csv contains a dataframe that documents the suitability of all land use classes (in columns) to serve as habitats for European terrestrial vertebrate species (in rows, with taxonomy information in the first columns). Land use classes are indicated in codes, and their meaning is found in the file LandUseCodesCorrespondance.csv.  A value of 0 indicates unsuitability of the land use class to serve as habitat for the species; a value of 1 indicates suitable habitat; a value of 2 indicates optimal habitat. For some species, all habitats appear as suitable when either no information on the ecology was available, or when the EOO was so small that no further refinement of their range is relevant (following on Maiorano et al., 2013). - LandUseCodesCorrespondance.csv contains the correspondance between the land use class codes (in the HabitatPreferences.csv file) and their meaning. - DistWater.csv documents the distance from water (m) that is suitable for water-dependent species (in rows).- OUTPUT contains AOH maps for terrestrial vertebrate species in Europe for which there is available information on the geographic range and habitat preferences. - script.R contains the code for creating the habitat suitability table and AOH maps.