cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10726581
title: Simulated Local Electrical Impedance in Atrial Tissue With Varying Contact Force

description: In this dataset we can find geometrical setups that served as an input to carry forward electrical impedance simulations with EIDORS. A 3D geometrical models of one ablation catheters combining measurements of local impedance (LI) and contact force (CF) commercially available is included. The objective of these in silico experiments laid on understanding how CF and tissue deformation affect LI measurements.To achieve it, using the catheter against the tissue, several grams of force are applying.The dataset consists of the original geometrical models before deformation and a couple of examples of the deformed one.

Data structure



geos: original geometries of the catheter and the tissue in stl



catheter.stl

tissue.stl



geos_deformed: deformed geometries at 5 and 10 grams, respectively. Includes the catheter, the mesh, and the tissue



5 g



catheter.stl

tissue_5g.stl

mesh_5g.stl



10 g



catheter.stl

tissue_10g.stl

mesh_10g.stl
DOI: 10.15468/j8tarb
title: The MOVECLIM – AZORES project: Bryophytes from Pico Island (2012)

description: In September 2012, Pico Island was surveyed along an elevational transept starting on Manhenha, at 10 m a.s.l., and ending on the Pico Mountain caldera, at 2200 m a.s.l. to obtain a systematic inventory of the bryophytes living in natural environments. A total of twelve sites were examined, separated by 200 m elevation steps. At each site, two 10 m x 10 m plots were established within 10-15 m from each other, and within each plot, three 2 m x 2 m quadrats were randomly selected and thoroughly sampled for bryophytes using microplots of 10 cm x 5 cm, collected to paper bags. Six substrates were explored within each quadrat: rock, soil, humus, organic matter, tree bark and leaves/fronds; three replicates were made for each substrate, whenever available and colonized by bryophytes, totalling a maximum of 18 microplots per quadrat, 54 microplots per plot, 108 microplots per site and 1296 microplots on the 12 sites of Pico Island. It was possible to collect two thirds of the maximum expected number of microplots (N=878; 67,75%), resulting in 4896 specimens, the great majority of which (n=4869) were identified to the species/subspecies level. Overall, it was possible to identify 70 moss’ and 71 liverwort’ species and subspecies. The elevation levels both with a greater number of microplots and higher richness of species were those between 600-1000 m a.s.l., coinciding with the native forest plots. The study contributed to improve the knowledge of Azorean bryophyte diversity and distribution at both local and regional scales, including the recording of new taxa for Pico Island and the Azores.
DOI: 10.48597/z4bp-kjhz
title: Measurement of Zinc at Terningvatn

description: Measurement of Zinc at Terningvatn
DOI: 10.48597/zpmq-nf8m
title: Measurement of Lead at Vorhegg

description: Measurement of Lead at Vorhegg
DOI: 10.48597/zz4m-smx4
title: Measurement of Inorganics in air and particle phase at Hurdal

description: Measurement of Inorganics in air and particle phase at Hurdal
DOI: 10.48597/28tu-6vn3
title: Inorganics in precipitation at Fagernes

description: Measurement of Inorganics in precipitation at Fagernes
DOI: 10.5281/zenodo.10727270
title: Impedance Reconstruction of Non-transmural Cardiac Fibrosis

description: In this dataset we can find geometrical setups that served as an input to carry simulations with openCARP and EIDORS. The setup consists of a Lasso with point electrodes placed on patch of tissue and embedded in a box of blood. The tissue simulates a myocardium that can be either fully healthy, fully scarred, or healthy with a 8-mm width line of scar tissue.

In addition, the voltage and local impedance maps obtained as results are included.

Two kinds of simulations were performed: reconstruction the forward injection of a 5µA current at 14.6kHz with EIDORS, and the electrical wave propagation with openCARP.

For the impedance reconstruction, a four electrode circuit was always used, meaning that two electrodes were part of the injecting pattern and a potential difference was measured between another two. The stimulating pair were sequentially changed among all pairs of neighbouring electrodes, whereas the rest of them contributed to the measurement.

The voltage maps were computed taking the recovered EGMs from the electrode positions.

 

Data structure





inputGeometries: 24 vtk files representing the input setup for simulations. The file names are of the form imageXX_append_cleanToGrid_LOCATION, where XX is a number among 06, 11, 52, and 55, and LOCATION refers to the position in z-axis (transmural, endo-, midmyo-, epicardio).







results:



BidomainSimulations: the extracellular potentials of each electrical propagation simulation using the Courtemanche model are saved in each of the 16 folders. All the corresponding outputs from a pseudobidomain openCARP simulation are located in each folder.



2023-04-16_image06_endo_00

2023-04-16_image06_epi_00

2023-04-16_image06_mid_00

2023-04-16_image06_transmural_00

2023-04-16_image11_endo_00

2023-04-16_image11_epi_00

2023-04-16_image11_mid_00

2023-04-16_image11_transmural_00

2023-04-16_image52_endo_00

2023-04-16_image52_epi_00

2023-04-16_image52_mid_00

2023-04-16_image52_transmural_00

2023-04-16_image55_endo_00

2023-04-16_image55_epi_00

2023-04-16_image55_mid_00

2023-04-16_image55_transmural_00



ImpedanceSimulations: mat and vtk files corresponding to either local electrical impedance reconstruction simulation. The file names are of the form imageXX_append_cleanToGrid_LOCATION, where XX is a number among 06, 11, 52, and 55, and LOCATION refers to the position in z-axis (transmural, endo-, midmyo-, epicardio).
DOI: 10.5281/zenodo.10727271
title: Impedance Reconstruction of Non-transmural Cardiac Fibrosis

description: In this dataset we can find geometrical setups that served as an input to carry simulations with openCARP and EIDORS. The setup consists of a Lasso with point electrodes placed on patch of tissue and embedded in a box of blood. The tissue simulates a myocardium that can be either fully healthy, fully scarred, or healthy with a 8-mm width line of scar tissue.

In addition, the voltage and local impedance maps obtained as results are included.

Two kinds of simulations were performed: reconstruction the forward injection of a 5µA current at 14.6kHz with EIDORS, and the electrical wave propagation with openCARP.

For the impedance reconstruction, a four electrode circuit was always used, meaning that two electrodes were part of the injecting pattern and a potential difference was measured between another two. The stimulating pair were sequentially changed among all pairs of neighbouring electrodes, whereas the rest of them contributed to the measurement.

The voltage maps were computed taking the recovered EGMs from the electrode positions.

 

Data structure





inputGeometries: 24 vtk files representing the input setup for simulations. The file names are of the form imageXX_append_cleanToGrid_LOCATION, where XX is a number among 06, 11, 52, and 55, and LOCATION refers to the position in z-axis (transmural, endo-, midmyo-, epicardio).







results:



BidomainSimulations: the extracellular potentials of each electrical propagation simulation using the Courtemanche model are saved in each of the 16 folders. All the corresponding outputs from a pseudobidomain openCARP simulation are located in each folder.



2023-04-16_image06_endo_00

2023-04-16_image06_epi_00

2023-04-16_image06_mid_00

2023-04-16_image06_transmural_00

2023-04-16_image11_endo_00

2023-04-16_image11_epi_00

2023-04-16_image11_mid_00

2023-04-16_image11_transmural_00

2023-04-16_image52_endo_00

2023-04-16_image52_epi_00

2023-04-16_image52_mid_00

2023-04-16_image52_transmural_00

2023-04-16_image55_endo_00

2023-04-16_image55_epi_00

2023-04-16_image55_mid_00

2023-04-16_image55_transmural_00



ImpedanceSimulations: mat and vtk files corresponding to either local electrical impedance reconstruction simulation. The file names are of the form imageXX_append_cleanToGrid_LOCATION, where XX is a number among 06, 11, 52, and 55, and LOCATION refers to the position in z-axis (transmural, endo-, midmyo-, epicardio).
DOI: 10.48597/2c5w-by3u
title: Inorganics in precipitation at Gulsvik

description: Measurement of Inorganics in precipitation at Gulsvik
DOI: 10.48597/2kxg-j2fv
title: Inorganics in precipitation at Lillestrøm (NILU Volla)

description: Measurement of Inorganics in precipitation at Lillestrøm (NILU Volla)
DOI: 10.48597/2stv-4nva
title: Inorganics in precipitation at Søgne 1

description: Measurement of Inorganics in precipitation at Søgne 1
DOI: 10.48597/2wm8-m8kh
title: Inorganics in precipitation at Børselv

description: Measurement of Inorganics in precipitation at Børselv
DOI: 10.48597/327g-gpec
title: Inorganics in precipitation at Kise

description: Measurement of Inorganics in precipitation at Kise
DOI: 10.6084/m9.figshare.7289723
title: Expt Formation Enthalpy Data

description: Experimental formation enthalpies for inorganic compounds, collected from years of calorimetric experiments. There are 1,276 entries in this dataset, mostly binary compounds. Matching mpids or oqmdids as well as the DFT-computed formation energies are also added (if any).<br>Data is available as 
Monty Encoder encoded JSON and as a CSV file. Recommended access method is with
 the matminer Python package using the datasets module.<br>Note on citations: If you found this dataset useful and would like to 
cite it in your work, please be sure to cite its original sources below 
rather than or in addition to this page.<br>Dataset discussed in:<br>Kim, G. <i>et al.</i> Experimental formation enthalpies for intermetallic phases and other inorganic compounds. <i>Sci. Data</i> 4:170162 doi: 10.1038/sdata.2017.162 (2017).<br>Dataset sourced and modified from:Kim, 
George; Meschel, Susan; Nash, Philip; Chen, Wei (2017): Experimental 
formation enthalpies for intermetallic phases and other inorganic 
compounds. figshare. Collection.<br>
DOI: 10.48597/3gkz-dwrj
title: Inorganics in precipitation at Dividalen

description: Measurement of Inorganics in precipitation at Dividalen
DOI: 10.48597/4a5g-4mps
title: Inorganics in precipitation at Vatnedalen

description: Measurement of Inorganics in precipitation at Vatnedalen
DOI: 10.48597/4teu-3x53
title: Inorganics in precipitation at Dividalen

description: Measurement of Inorganics in precipitation at Dividalen
DOI: 10.48597/5bkg-6me6
title: Inorganics in precipitation at Bislingen

description: Measurement of Inorganics in precipitation at Bislingen
DOI: 10.48597/5ye8-y8hw
title: Inorganics in precipitation at Mandal

description: Measurement of Inorganics in precipitation at Mandal
DOI: 10.48597/67y4-4nvh
title: Inorganics in precipitation at Fitjar

description: Measurement of Inorganics in precipitation at Fitjar
DOI: 10.48597/7m6p-jrdz
title: Inorganics in precipitation at Dalelva

description: Measurement of Inorganics in precipitation at Dalelva
DOI: 10.48597/7r7y-tr38
title: Inorganics in precipitation at Kaupanger

description: Measurement of Inorganics in precipitation at Kaupanger
DOI: 10.48597/8jgk-rrj8
title: Inorganics in precipitation at Gjerstad

description: Measurement of Inorganics in precipitation at Gjerstad
DOI: 10.6084/m9.figshare.15153820.v1
title: Additional file 2 of Mesenchymal stem cell-derived exosomal miR-146a reverses diabetic β-cell dedifferentiation

description: Additional file 2.
DOI: 10.48597/8mzq-qm6h
title: Inorganics in precipitation at Frihetsli

description: Measurement of Inorganics in precipitation at Frihetsli
DOI: 10.48597/8qq5-263n
title: Inorganics in precipitation at Tovdal

description: Measurement of Inorganics in precipitation at Tovdal
DOI: 10.48597/8r7d-ec3y
title: Inorganics in precipitation at Kaupanger

description: Measurement of Inorganics in precipitation at Kaupanger
DOI: 10.48597/8rms-h622
title: Inorganics in precipitation at Hvasser

description: Measurement of Inorganics in precipitation at Hvasser
DOI: 10.48597/8xz5-s6nx
title: Inorganics in precipitation at Kise

description: Measurement of Inorganics in precipitation at Kise
DOI: 10.48597/a8up-8xxe
title: Inorganics in precipitation at Haukeland

description: Measurement of Inorganics in precipitation at Haukeland
DOI: 10.48597/bd6k-wwn9
title: Inorganics in precipitation at Grubhei

description: Measurement of Inorganics in precipitation at Grubhei
DOI: 10.48597/bpeq-cba5
title: Inorganics in precipitation at Bokn

description: Measurement of Inorganics in precipitation at Bokn
DOI: 10.48597/c4db-pxdg
title: Calcium at Risdalsheia

description: Measurement of Calcium at Risdalsheia
DOI: 10.21227/9twx-eb68
title: Autonomous Rover Enables Radar Profiling of Ice-Fabric Properties in Antarctica

description: Ground-penetrating radar is an extensively used geophysical tool in cryosphere sciences (ice sheets and glaciers) with sounding depths of several kilometers due to the small radio-wave attenuation in ice sheets. Detection of the ice thickness and internal ice stratigraphy with commercial radars has become standard. However, there is still an observational gap in determining dielectric and mechanical ice-fabric anisotropy and basal properties using these systems. Recently, ground-based phase coherent radar has shown its potential to fill this gap. However, this requires that the corresponding ground-based radars cover profiles several tens of kilometers in length. We address this challenge by modifying an autonomous rover to collect phase-coherent, quad-polarimetric radar data geolocated with real-time kinematic positioning. In a proof-of-concept study in Antarctica, we demonstrate that this allows the collection of quad-polarimetric data along a 23 km profile, mapping anisotropic ice-fabric properties at &lt;100 m intervals across the transition of grounded to floating ice. This study shows the possibility of collecting data that will refine ice-flow models by providing missing rheological parameters. This work also demonstrates the versatility of the autonomous ground vehicle with its ability to tow more than 200 kg payload, with a battery run time of over six hours, and with a modular design that enables future integration of different radars or other geophysical sensors.
DOI: 10.48597/ccq8-gvdw
title: Inorganics in precipitation at Skei i Jølster

description: Measurement of Inorganics in precipitation at Skei i Jølster
DOI: 10.48597/cd37-y5vz
title: Inorganics in precipitation at Skei i Jølster

description: Measurement of Inorganics in precipitation at Skei i Jølster
DOI: 10.48597/ctkq-muhr
title: Inorganics in precipitation at Kjeller

description: Measurement of Inorganics in precipitation at Kjeller
DOI: 10.48597/cy3s-q9rg
title: Inorganics in precipitation at Grubhei

description: Measurement of Inorganics in precipitation at Grubhei
DOI: 10.48597/ddwr-dyvf
title: Inorganics in precipitation at Kårvatn 2

description: Measurement of Inorganics in precipitation at Kårvatn 2
DOI: 10.48597/dg3d-25ps
title: Inorganics in precipitation at Bakko

description: Measurement of Inorganics in precipitation at Bakko
DOI: 10.48597/dqbm-ucqw
title: Inorganics in precipitation at Tveitdalen

description: Measurement of Inorganics in precipitation at Tveitdalen
DOI: 10.48597/ek2n-jb6e
title: Inorganics in precipitation at Grimelid

description: Measurement of Inorganics in precipitation at Grimelid
DOI: 10.48597/f23g-bc68
title: Inorganics in precipitation at Haukeland

description: Measurement of Inorganics in precipitation at Haukeland
DOI: 10.48597/fetx-gp9q
title: Inorganics in precipitation at Gulsvik

description: Measurement of Inorganics in precipitation at Gulsvik
DOI: 10.48597/fghk-ce6j
title: Inorganics in precipitation at Valle

description: Measurement of Inorganics in precipitation at Valle
DOI: 10.48597/g8mk-wg3j
title: Inorganics in precipitation at Risdalsheia

description: Measurement of Inorganics in precipitation at Risdalsheia
DOI: 10.48597/gngk-t5ar
title: Inorganics in precipitation at Risdalsheia

description: Measurement of Inorganics in precipitation at Risdalsheia
DOI: 10.48597/gs8g-w6ub
title: Inorganics in precipitation at Haukeland

description: Measurement of Inorganics in precipitation at Haukeland
DOI: 10.48597/gymp-8tcn
title: Inorganics in precipitation at Lyngør

description: Measurement of Inorganics in precipitation at Lyngør
DOI: 10.48597/hpjf-7h4w
title: Inorganics in precipitation at Selbu

description: Measurement of Inorganics in precipitation at Selbu
DOI: 10.48597/jh7x-bbnn
title: Inorganics in precipitation at Tågmyra

description: Measurement of Inorganics in precipitation at Tågmyra
DOI: 10.48597/jnzz-nkbt
title: Inorganics in precipitation at Førde

description: Measurement of Inorganics in precipitation at Førde
DOI: 10.48597/k8by-smc3
title: Inorganics in precipitation at Bislingen

description: Measurement of Inorganics in precipitation at Bislingen
DOI: 10.48597/kpba-wb5e
title: Inorganics in precipitation at Lillestrøm (NILU Volla)

description: Measurement of Inorganics in precipitation at Lillestrøm (NILU Volla)
DOI: 10.48597/m9s6-z99a
title: Inorganics in precipitation at Tovdal

description: Measurement of Inorganics in precipitation at Tovdal
DOI: 10.48597/m9y6-kmkf
title: Inorganics in precipitation at Sandvik

description: Measurement of Inorganics in precipitation at Sandvik
DOI: 10.48597/mneh-e7z5
title: Inorganics in precipitation at Åmotsdalen

description: Measurement of Inorganics in precipitation at Åmotsdalen
DOI: 10.48597/mtvm-rygg
title: Inorganics in precipitation at Fitjar

description: Measurement of Inorganics in precipitation at Fitjar
DOI: 10.48597/p2d2-s4fd
title: Inorganics in precipitation at Finsland

description: Measurement of Inorganics in precipitation at Finsland
DOI: 10.5281/zenodo.10727242
title: The CluMPR Galaxy Cluster Catalogue for DESI Legacy Survey DR9

description: Galaxy cluster catalog and cluster member galaxy catalogs compiled using the CluMPR cluster-finding algorithm. 

Paper decribing the CluMPR algorithms and cluster catalogs: The CluMPR Galaxy Cluster-Finding Algorithm and DESI Legacy Survey Galaxy Cluster catalogue (M. J. Yantovski-Barth et al.)

File description: 

DESI_clusters_2024_simple contains the official cluster catalog,

DESI_clusters_2024_extended is the official cluster catalog + some clusters which were flagged and removed,

north_members_reweighted contains the member galaxies for clusters in the north region of DESI Legacy Survey,

south_members_reweighted contains the member galaxies for clusters in the south region of DESI Legacy Survey.
DOI: 10.5281/zenodo.8157751
title: The CluMPR Galaxy Cluster Catalogue for DESI Legacy Survey DR9

description: Galaxy cluster catalog and cluster member galaxy catalogs compiled using the CluMPR cluster-finding algorithm. 

Paper decribing the CluMPR algorithms and cluster catalogs: The CluMPR Galaxy Cluster-Finding Algorithm and DESI Legacy Survey Galaxy Cluster catalogue (M. J. Yantovski-Barth et al.)

File description: 

DESI_clusters_2024_simple contains the official cluster catalog,

DESI_clusters_2024_extended is the official cluster catalog + some clusters which were flagged and removed,

north_members_reweighted contains the member galaxies for clusters in the north region of DESI Legacy Survey,

south_members_reweighted contains the member galaxies for clusters in the south region of DESI Legacy Survey.
DOI: 10.3886/e198742
title: food choice

description: This study looks into the mediating role of food choice motives
DOI: 10.3886/e198742v1
title: food choice

description: This study looks into the mediating role of food choice motives
DOI: 10.6084/m9.figshare.25115966
title: Additional file 2 of Chromosome-level assembly and analysis of Camelina neglecta: a novel diploid model for Camelina biotechnology research

description: Additional file 2: Table S1. Raw sequencing data. Table S2. Anchored chromosome length of C. neglecta. Table S3. Evaluation of C. neglecta genome based on RNA-seq of different tissues. Table S4. Evaluation of assembly completeness. Table S5. Genetic structure of C. neglecta. Table S6. Gene function annotation statistics. Table S7. Statistics of transposable element of C. neglecta. Table S8. LTR insertion time in C. neglecta genome. Table S9. Statistics of annotated non-coding RNAs. Table S10. The GO enrichment analysis of unique gene families of C. neglecta. Table S11. The key genes involved in the oil biosynthesis pathway and their TPM in C. neglecta. Table S12. Comparison with published C. neglecta assemblies. Table S13. Gene annotation quality statistics.
DOI: 10.6084/m9.figshare.25115966.v1
title: Additional file 2 of Chromosome-level assembly and analysis of Camelina neglecta: a novel diploid model for Camelina biotechnology research

description: Additional file 2: Table S1. Raw sequencing data. Table S2. Anchored chromosome length of C. neglecta. Table S3. Evaluation of C. neglecta genome based on RNA-seq of different tissues. Table S4. Evaluation of assembly completeness. Table S5. Genetic structure of C. neglecta. Table S6. Gene function annotation statistics. Table S7. Statistics of transposable element of C. neglecta. Table S8. LTR insertion time in C. neglecta genome. Table S9. Statistics of annotated non-coding RNAs. Table S10. The GO enrichment analysis of unique gene families of C. neglecta. Table S11. The key genes involved in the oil biosynthesis pathway and their TPM in C. neglecta. Table S12. Comparison with published C. neglecta assemblies. Table S13. Gene annotation quality statistics.