cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25625/i06cgq/bf8om7
title: stress_strain_b_f0.20_taup1.00_T0.00_gd1.d_4

description: :unav
DOI: 10.25625/i06cgq/f0ygkt
title: stress_gd1.d_1_f2.00

description: :unav
DOI: 10.25625/i06cgq/phtsqa
title: orderp_gd1.d_1_f1.40

description: :unav
DOI: 10.25625/i06cgq/hpddli
title: stress_gd2.d_3_f0.40

description: :unav
DOI: 10.25625/i06cgq/8zta05
title: stress_gd5.d_3_f2.00

description: :unav
DOI: 10.25625/i06cgq/tucaoy
title: stress_gd1.d_2_f0.60

description: :unav
DOI: 10.25625/i06cgq/oyxnp8
title: orderp_gd2.d_4_f2.00

description: :unav
DOI: 10.25625/i06cgq/try9it
title: stress_gd2.d_4_f1.00

description: :unav
DOI: 10.25625/i06cgq/qlh6hp
title: orderp_gd1.d_2_f1.80

description: :unav
DOI: 10.25625/i06cgq/yybrap
title: stress_gd5.d_3_f1.00

description: :unav
DOI: 10.25625/i06cgq/f0gimo
title: orderp_gd2.d_3_f0.60

description: :unav
DOI: 10.25625/i06cgq/4jdwph
title: MSDy_av

description: :unav
DOI: 10.25625/i06cgq/v1czdi
title: orderp_gd5.d_4_f0.40

description: :unav
DOI: 10.25625/i06cgq/wyvlm2
title: stress_gd5.d_3_f0.20

description: :unav
DOI: 10.25625/i06cgq/cvfpft
title: orderp_gd1.d_2_f1.00

description: :unav
DOI: 10.25625/i06cgq/jk81eo
title: stress_gd1.d_4_f0.80

description: :unav
DOI: 10.25625/i06cgq/eu0t82
title: stress_gd5.d_3_f1.20

description: :unav
DOI: 10.25625/i06cgq/sspjs6
title: orderp_gd5.d_2_f0.00

description: :unav
DOI: 10.25625/i06cgq/mjmdx3
title: orderp_gd1.d_1_f2.50

description: :unav
DOI: 10.25625/i06cgq/kdmxcq
title: stress_gd2.d_2_f0.20

description: :unav
DOI: 10.25625/i06cgq/rvn8vd
title: stress_gd1.d_2_f1.60

description: :unav
DOI: 10.25625/i06cgq/wl3vmj
title: orderp_gd5.d_2_f1.00

description: :unav
DOI: 10.25625/i06cgq/mvi16x
title: stress_gd1.d_4_f0.00

description: :unav
DOI: 10.25625/i06cgq/21eifq
title: orderp_gd1.d_2_f0.80

description: :unav
DOI: 10.25625/i06cgq/wtvwbs
title: orderp_gd5.d_2_f2.00

description: :unav
DOI: 10.25625/i06cgq/mrag9p
title: orderp_gd2.d_4_f0.80

description: :unav
DOI: 10.25625/i06cgq/vpjysc
title: orderp_gd1.d_2_f0.20

description: :unav
DOI: 10.25625/i06cgq/4dnlkw
title: orderp_gd5.d_4_f0.80

description: :unav
DOI: 10.25625/i06cgq/zcfnsn
title: orderp_gd1.d_1_f0.00

description: :unav
DOI: 10.25625/i06cgq/hm3wrg
title: stress_gd2.d_3_f1.20

description: :unav
DOI: 10.25625/i06cgq/0xmpei
title: orderp_gd2.d_4_f0.00

description: :unav
DOI: 10.25625/i06cgq/ebpptp
title: stress_gd1.d_2_f0.80

description: :unav
DOI: 10.25625/i06cgq/ld3s31
title: orderp_gd1.d_1_f2.00

description: :unav
DOI: 10.25625/i06cgq/g6g6yj
title: stress_gd1.d_3_f0.00

description: :unav
DOI: 10.5281/zenodo.4518480
title: MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2011 at 1-km

description: Layers include: Land Surface Temperature daytime low (0.05), median (0.50) and high (0.95) temperatures for the year 2011. Derived using the data.table package and quantile function in R. For more info about the MODIS LST product see: https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mod11a2_v006. Antarctica is not included. To access and visualize maps use: OpenLandMap.org To download and compute with maps using Cloud-Optimized-GeoTIFF see <strong>this tutorial</strong>. If you discover a bug, artifact or inconsistency in the OpenLandMap maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/-/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: clm = theme: climate, lst = variable: land surface temperature, mod11a2.daytime = determination method: MOD11A2 product, day time values, d = median value / sd = standard deviation / u.95 = aggregation/statistics method: 95% probability upper quantile, 1km = spatial resolution / block support: 1 km, s0..0cm = vertical reference: land surface, 2000..2020 = time reference: from 2000 to 2020, v1.1 = version number: 1.1,
description: This work has received funding from the European Union's the Innovation and Networks Executive Agency (INEA) under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.25625/i06cgq/mujhr3
title: orderp_gd2.d_4_f1.00

description: :unav
DOI: 10.5281/zenodo.4518479
title: MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2011 at 1-km

description: Layers include: Land Surface Temperature daytime low (0.05), median (0.50) and high (0.95) temperatures for the year 2011. Derived using the data.table package and quantile function in R. For more info about the MODIS LST product see: https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mod11a2_v006. Antarctica is not included. To access and visualize maps use: OpenLandMap.org To download and compute with maps using Cloud-Optimized-GeoTIFF see <strong>this tutorial</strong>. If you discover a bug, artifact or inconsistency in the OpenLandMap maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/-/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: clm = theme: climate, lst = variable: land surface temperature, mod11a2.daytime = determination method: MOD11A2 product, day time values, d = median value / sd = standard deviation / u.95 = aggregation/statistics method: 95% probability upper quantile, 1km = spatial resolution / block support: 1 km, s0..0cm = vertical reference: land surface, 2000..2020 = time reference: from 2000 to 2020, v1.1 = version number: 1.1,
description: This work has received funding from the European Union's the Innovation and Networks Executive Agency (INEA) under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.25625/i06cgq/hlband
title: orderp_gd1.d_4_f1.00

description: :unav
DOI: 10.25625/i06cgq/palb8m
title: velpro_gd5.d_4_f0.40_0000_200

description: :unav
DOI: 10.25625/i06cgq/dyxzjv
title: stress_gd5.d_3_f0.60

description: :unav
DOI: 10.25625/i06cgq/bibpdx
title: stress_gd5.d_4_f1.60

description: :unav
DOI: 10.25625/i06cgq/aupkic
title: orderp_gd1.d_2_f0.60

description: :unav
DOI: 10.25625/i06cgq/akse9i
title: stress_gd2.d_4_f0.80

description: :unav
DOI: 10.25625/i06cgq/bqzmql
title: orderp_gd1.d_4_f1.60

description: :unav
DOI: 10.25625/i06cgq/n505v4
title: orderp_gd1.d_3_f0.20

description: :unav
DOI: 10.25625/i06cgq/l38hkg
title: orderp_gd1.d_1_f0.80

description: :unav
DOI: 10.25625/i06cgq/huoppw
title: orderp_gd5.d_2_f0.20

description: :unav
DOI: 10.25625/i06cgq/s1whs2
title: orderp_gd2.d_4_f1.60

description: :unav
DOI: 10.25625/i06cgq/t87np3
title: stress_gd5.d_4_f0.40

description: :unav
DOI: 10.25625/i06cgq/gntz6t
title: stress_gd1.d_1_f0.80

description: :unav
DOI: 10.25625/i06cgq/g7zdl8
title: stress_gd5.d_2_f0.40

description: :unav
DOI: 10.25625/i06cgq/f8kooj
title: stress_gd1.d_3_f1.60

description: :unav
DOI: 10.25625/i06cgq/1kfofv
title: orderp_gd2.d_3_f2.00

description: :unav
DOI: 10.25625/i06cgq/idwj6u
title: orderp_gd2.d_2_f0.20

description: :unav
DOI: 10.25625/i06cgq/e6gkeh
title: stress_gd1.d_1_f1.40

description: :unav
DOI: 10.25625/i06cgq/hiascd
title: orderp_gd1.d_4_f0.20

description: :unav
DOI: 10.25625/i06cgq/gnamwi
title: orderp_gd5.d_2_f1.40

description: :unav
DOI: 10.25625/i06cgq/hoggld
title: thetapos_PDF_analytical

description: :unav
DOI: 10.25625/i06cgq/0ja1ce
title: orderp_gd2.d_3_f0.40

description: :unav
DOI: 10.25625/i06cgq/jsrehe
title: stress_gd1.d_3_f1.00

description: :unav
DOI: 10.25625/i06cgq/oima0p
title: orderp_gd1.d_1_f1.80

description: :unav
DOI: 10.25625/i06cgq/imbsmx
title: orderp_gd1.d_3_f1.80

description: :unav
DOI: 10.25625/i06cgq/fmofva
title: stress_gd1.d_3_f1.40

description: :unav
DOI: 10.25625/i06cgq/ca6pte
title: stress_gd1.d_3_f0.60

description: :unav
DOI: 10.25625/i06cgq/qpcdk9
title: orderp_gd2.d_4_f1.20

description: :unav
DOI: 10.25625/i06cgq/c4jdk5
title: stress_gd1.d_4_f1.40

description: :unav
DOI: 10.25625/i06cgq/rapwqa
title: stress_gd1.d_3_f0.20

description: :unav
DOI: 10.25625/i06cgq/fsnrdl
title: orderp_gd5.d_3_f1.60

description: :unav
DOI: 10.25625/i06cgq/y0uwjc
title: orderp_gd2.d_4_f1.40

description: :unav
DOI: 10.25625/i06cgq/oyz2sx
title: orderp_gd1.d_2_f0.00

description: :unav
DOI: 10.25625/i06cgq/sowmzd
title: stress_gd2.d_3_f1.40

description: :unav
DOI: 10.25625/i06cgq/o2o81a
title: stress_gd1.d_3_f1.20

description: :unav
DOI: 10.25625/i06cgq/envnea
title: orderp_gd2.d_2_f0.80

description: :unav
DOI: 10.25625/i06cgq/opxjcy
title: orderp_gd5.d_3_f1.80

description: :unav
DOI: 10.25625/i06cgq/j2koy1
title: stress_gd2.d_3_f1.00

description: :unav
DOI: 10.25625/i06cgq/paw3fb
title: stress_gd2.d_4_f1.60

description: :unav
DOI: 10.25625/i06cgq/xezafa
title: orderp_gd1.d_1_f1.60

description: :unav
DOI: 10.25625/i06cgq
title: Data for Rheology of Active Glass Project

description: This set of files contain data for sheared active glassy system.
DOI: 10.5063/v986fn
title: Testing the generality of sea otter-mediated trophic cascades in seagrass meadows

description: Enclosed data and code are and archive for the Oikos publication "Testing the generality of sea otter-mediated trophic cascades in seagrass meadows" doi: 10.1111/oik.07681. A single data file is presented here as a reference for certain calculations (detailed in included scripts). The vast majority of the data are archived in separate KNB data packages under the Sustainable Marine Ecology Lab. These data are referenced through stable URLs in included code. Code and data presented here are also archived on GitHub https://github.com/wraymond/Raymond_etal_Oikos.Manuscript abstractThe presence and strength of trophic cascades can be a function of the local abiotic environment and relative abundance of key species. The reintroduction and expansion of sea otters (Enhydra lutris), a known keystone species in kelp ecosystems, in Southeast Alaska provides a rare natural experiment to test the generality of a apex-predator – seagrass trophic cascades across a broad spatial scale. We conducted an in-depth seagrass community survey at 21 sites spanning ~100 km with variable sea otter presence to test for patterns of alternating abundance and direct relationships between species indicative of trophic cascades. Our analysis revealed some of the trophic relationships predicted by the apex predator-seagrass trophic cascades theory, including a strong negative relationship between sea otters and crabs and many of the expected relationships between nitrate, seagrass, epiphytes, and epifauna. Other expected relationships within a trophic cascade, however, were not supported – including no relationship between crabs and epifauna, a critical link in the trophic cascade. Given the lack of evidence for all hypothesized direct relationships, we conclude that a sea otter mediated trophic cascade may not be present in Southeast Alaska and could be due to local scale factors including the spatial heterogeneity, low resource availability, and non-linear food chains in Southeast Alaska seagrass communities. However, correlation analyses suggest further interactions among biological and environmental variables in Southeast Alaska seagrass communities, including a positive correlation between sea otters and seagrass biomass. These results suggest that the effects of recovering apex-predator populations may not be generalizable across regions and spatial scales, highlighting a need for local assessment on the ecology and management of these populations.
DOI: 10.5281/zenodo.4519500
title: Decomposition of Potamogeton perfoliatus; Effected by gammarid grazing and the influence of macrophyte decomposition on the sediment.

description: Dataset Bsc thesis of Biology
DOI: 10.5281/zenodo.4519498
title: Supporting files for "Building an intuition for binding free energy calculations: bound state definition, restraints, and symmetry"

description: The archived folder contains the input files necessary to reproduce the decoupling simulations reported in our paper "Building an intuition for binding free energy calculations: bound state definition, restraints, and symmetry", as well as the python scripts used to analyse the data and the log files of the simulations. For any additional information, the authors can be contacted by email: duboue-dijon at ibpc.fr and henin at ibpc.fr
DOI: 10.5281/zenodo.4519497
title: Supporting files for "Building an intuition for binding free energy calculations: bound state definition, restraints, and symmetry"

description: The archived folder contains the input files necessary to reproduce the decoupling simulations reported in our paper "Building an intuition for binding free energy calculations: bound state definition, restraints, and symmetry", as well as the python scripts used to analyse the data and the log files of the simulations. For any additional information, the authors can be contacted by email: duboue-dijon at ibpc.fr and henin at ibpc.fr
DOI: 10.5281/zenodo.3893661
title: Research data supporting for Stress-induced amorphization triggers deformation in the lithospheric mantle

description: Original TEM micrographs used to prepare the figures of the article
DOI: 10.5281/zenodo.3893394
title: Research data supporting for Stress-induced amorphization triggers deformation in the lithospheric mantle

description: Original TEM micrographs used to prepare the figures of the article
DOI: 10.6084/m9.figshare.13333973.v1
title: Chiara et al 2021, Tables

description: This repository contains the main tables of the Chiara et al, manuscript entitled:<br>"Comparative genomics reveals early emergence and biased spatio-temporal distribution of SARS-CoV-2 "<br><br>The manuscript is currently under peer review
DOI: 10.6084/m9.figshare.12608828
title: Data for 'Comparing patterns of hurricane washover into built and unbuilt environments'

description: This data accompanies the article 'Comparing patterns of hurricane washover into built and unbuilt environments’ by Lazarus<i> et al.,</i> (2021).<br> This repository contains csv files for the physical parameters of both unbuilt and built coastal sediment deposits along the east and gulf coasts of the USA. The deposits were digitised from NOAA post-storm imagery (National Geodetic Survey, 2020) and the hurricanes used are Irene(2011), Sandy (2012), Matthew (2016), Nate (2017) and Michael (2018). Building footprints (https://github.com/microsoft/USBuildingFootprints) were intersected with a bounding box around the digitised built deposits, whilst streets (https://download.geofabrik.de/) were clipped by the deposit extent. Two csv files, unbuilt and built, provide the raw data extracted from the respective shapefiles. <br> The unbuilt_deposits.csv has 7 columns: 1) source hurricane 2) object ID - for respective hurricane 3) length (m)4) perimeter (m) 5) area (m<sup>2</sup>) 6) calculated ideal perimeter 7) distortion index (DI)<br> The built_deposits.csv has 11 columns: 1) source hurricane 2) object ID - for respective hurricane 3) length (m)4) perimeter (m) 5) area (m<sup>2</sup>) 6) ideal perimeter 7) distortion index (DI) 8) bounding box area (m<sup>2</sup>) 9) building area (m<sup>2</sup>) 10) built fraction 11) street length (m)<br>This repository also contains model results from a simplified numerical model of washover deposition into a generic built environment (https://github.com/envidynxlab/Model-World). The DIDX_built_modeldata.csv has seven columns:1) deposit length (units L)<br> 2) perimeter (L)<br> 3) area (L^2)<br> 4) ideal perimeter (as a function of area; L)<br> 5) distortion index (L/L)<br> 6) built fraction (L^2/L^2)<br> 7) breach depth (as proportion of barrier height; L/L) <br><br>
DOI: 10.6084/m9.figshare.12608828.v1
title: Data for 'Comparing patterns of hurricane washover into built and unbuilt environments'

description: This data accompanies the article 'Comparing patterns of hurricane washover into built and unbuilt environments’ by Lazarus<i> et al.,</i> (2021).<br> This repository contains csv files for the physical parameters of both unbuilt and built coastal sediment deposits along the east and gulf coasts of the USA. The deposits were digitised from NOAA post-storm imagery (National Geodetic Survey, 2020) and the hurricanes used are Irene(2011), Sandy (2012), Matthew (2016), Nate (2017) and Michael (2018). Building footprints (https://github.com/microsoft/USBuildingFootprints) were intersected with a bounding box around the digitised built deposits, whilst streets (https://download.geofabrik.de/) were clipped by the deposit extent. Two csv files, unbuilt and built, provide the raw data extracted from the respective shapefiles. <br> The unbuilt_deposits.csv has 7 columns: 1) source hurricane 2) object ID - for respective hurricane 3) length (m)4) perimeter (m) 5) area (m<sup>2</sup>) 6) calculated ideal perimeter 7) distortion index (DI)<br> The built_deposits.csv has 11 columns: 1) source hurricane 2) object ID - for respective hurricane 3) length (m)4) perimeter (m) 5) area (m<sup>2</sup>) 6) ideal perimeter 7) distortion index (DI) 8) bounding box area (m<sup>2</sup>) 9) building area (m<sup>2</sup>) 10) built fraction 11) street length (m)<br>This repository also contains model results from a simplified numerical model of washover deposition into a generic built environment (https://github.com/envidynxlab/Model-World). The DIDX_built_modeldata.csv has seven columns:1) deposit length (units L)<br> 2) perimeter (L)<br> 3) area (L^2)<br> 4) ideal perimeter (as a function of area; L)<br> 5) distortion index (L/L)<br> 6) built fraction (L^2/L^2)<br> 7) breach depth (as proportion of barrier height; L/L) <br><br>
DOI: 10.6084/m9.figshare.12857573.v2
title: Schatz_Park_code_data.zip

description: Data and code for analyses in manuscript "Host and parsite traits predict cross-species parasite acquisition by introduced mammals" (Schatz and Park, in submission).
DOI: 10.6084/m9.figshare.13353020
title: Chiara et al 2021, Supplementary Figures

description: This repository contains the supplementary figures of the Chiara et al, manuscript entitled:<br>"Comparative genomics reveals early emergence and biased spatio-temporal distribution of SARS-CoV-2 "<br>
DOI: 10.6084/m9.figshare.12857573.v1
title: Schatz_Park_code_data.zip

description: Data and code for analyses in manuscript "Host and parsite traits predict cross-species parasite acquisition by mammals" (Schatz and Park, in submission).
DOI: 10.6084/m9.figshare.13353020.v1
title: Chiara et al 2021, Supplementary Figures

description: This repository contains the supplementary figures of the Chiara et al, manuscript entitled:<br>"Comparative genomics reveals early emergence and biased spatio-temporal distribution of SARS-CoV-2 "<br>
DOI: 10.6084/m9.figshare.13333877.v1
title: Data and images from Chiara et 2020.

description: This repository contains the complete datasets, including all the images, tables, genome accessions and software produced and or analysed in Chiara et al 2020.<br>Comparative genomics reveals early emergence and biased spatio-temporal distribution of SARS-CoV-2<br><br>The paper is currently under review
DOI: 10.6084/m9.figshare.13333877.v2
title: Updates to Chiara et 2021.

description: This repository contains updates to the Chiara et al 2021 MBE paper entitled: "Comparative genomics reveals early emergence and biased spatio-temporal distribution of SARS-CoV-2 " . <br>These include: <br>1) Novel MacroHaplogroups (MHGs) and Haplogroups (HGs) based on newly released SARS-CoV-2 genomic sequences<br>2) Assignment of newly released genomes to MHGs and HGs as defined above.<br>At every novel update a brief report will be released which will highlight the most relevant novelties<br>
DOI: 10.6084/m9.figshare.13726237.v1
title: JDM31_CameraE

description: 1 of 6 cameras for JDM31<br>
DOI: 10.5281/zenodo.4498304
title: Dataset for: Robust SARS-CoV-2-specific T-cell immunity is maintained at 6 months following primary infection

description: This is the ELISPOT, clinical data and ICS data for this cohort
DOI: 10.5281/zenodo.4498303
title: Dataset for: Robust SARS-CoV-2-specific T-cell immunity is maintained at 6 months following primary infection

description: This is the ELISPOT, clinical data and ICS data for this cohort
DOI: 10.17025/1764126
title: Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 1a Raw Data

description: 10 hours chronoamperometry (CA) testing under 1 sun illumination and constant bias at -0.6 V vs RHE, the corresponding Faradaic efficiency reveals a self-improving nature of GaN, inset: CA testing on bare Si for 5 hours under 1 sun illumination and -0.6 V vs RHE, this bare Si photocathode rapidly drops down to &lt; 0.05 mA/cm2 within an hour. Both CA testing performed in 0.5 M H2SO4 (pH=0.4).
DOI: 10.6084/m9.figshare.13148765.v2
title: Herbaceous and woody plants providing resources for bees in a semi-arid tropical climate

description: Dataset of plant inventory and phenology of herbaceous and woody strata in in three 0.5-ha plots located in the Vale do Curu Experimental Farm of Unversidade Federal do Ceará, Pentecoste, Ceará State, Brazil. The climate zone <br> corresponding to semi-arid (BSh) and the plots were installed in Caatinga vegetation.<br><br>Each plot was divided into 50 10x10 m subplots to identify the floristic composition and the abundance of each species and to facilitate the phenological evaluation. <br><br>The dataset includes 4 spreadsheet: <br>1) inventory of all woody individuals in the plots with stem perimeter at the ground level equal to or greater than<br>9 cm. <br>2) phenology of woody plants int the plots. the flowering intensity of each plant observed with flowers,using the semi-quantitative method of Fournier (1974). This method estimates visually the percentage of the canopy covered with flowers, classifying it in one of the five cover classes<br>(0 to 4): 0 = absence of phenophase, 1 = 1-25%, 2 = 26-50%, 3 = 51-75%, and 4 = 76-100%.3) floral cover of herbaceous plants in 25 of the 50 10x10m<br>subplots of each plot. To assess the flowering in herbaceous strata we used the semi-quantitative method of Daubenmire<br>(1959), which also uses cover classes to estimate the population abundance of each species. To this aim we used a 50x50 cm PVC square. We used six classes to<br>estimate floral cover per species: 1 = up to 5%, 2 = 6-25%, 3 = 26-50%, 4 = 51-75%, 5 = 76-95%, 6 = 96-100% . <br>4) List of species recorded in the three plots, their classification in growth and life forms, indicating <br>whether bees visit the species and the resources collected by the bees. <br> <br> <br>
DOI: 10.5519/qd.s8rt023v
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5519/qd.joja62x8
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.13726237
title: s1-d1-camera3

description: Camera 1 (of 6) for Subject 1, Day 1<br>
DOI: 10.6084/m9.figshare.13726237.v2
title: s1-d1-camera1

description: Camera 1 (of 6) for Subject 1, Day 1<br>
DOI: 10.5281/zenodo.3885403
title: Gravity modeling of the Alpine lithosphere affected by magmatism based on seismic tomography

description: The Southern Alpine regions have been affected by several magmatic and volcanic events between the Paleozoic and the Tertiary. This activity has undoubtedly had an important effect on the density distribution and structural setting at lithosphere scale. Combining the information from gravity field and a high-resolution seismic tomography has been carried out a new 3D lithosphere density model of the Alpine region.
description: {"references": ["Tadiello D., Braitenberg C., 2021, \"Gravity modelling of the Alpine lithosphere affected by magmatism based on seismic tomography\", Solid Earth, https://doi.org/10.5194/se-12-1-2021."]}