cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8030118
title: DA-TCA test data sets (KIAPS-GIST)

description: <strong>About the data sets:</strong> The test datasets from SMOS/ASCAT will be utilized to validate the efficacy of SMAP data assimilation in numerical weather forecasting. This project is being conducted in collaboration with the Korea Institute of Atmospheric Prediction Systems (KIAPS) and the Gwangju Institute of Science and Technology (GIST) in South Korea. <strong>About the project:</strong> Soil moisture assimilation from satellites can significantly improve weather prediction accuracy by providing valuable information about the moisture content in the soil. When integrated into numerical weather forecasting models, satellite-derived soil moisture data enhances the representation of land surface processes and interactions between the atmosphere and the Earth's surface. Here's how soil moisture assimilation benefits weather prediction: Initialization of Models: Accurate initial conditions are crucial for reliable weather forecasting. Satellite-derived soil moisture data serves as an important source of information for initializing models. By incorporating this data, forecast models can start with more realistic representations of the state of the land surface, enabling a better starting point for predictions. Land-Atmosphere Interaction: Soil moisture plays a significant role in land-atmosphere interactions. It influences the partitioning of energy, the transfer of moisture, and the formation of clouds and precipitation. Assimilating satellite-derived soil moisture data allows forecast models to better capture these interactions and improve the representation of feedback mechanisms between the land surface and the atmosphere. Precipitation Forecasting: Soil moisture assimilation also enhances precipitation forecasting. The availability of accurate soil moisture data helps in understanding soil moisture-atmosphere feedback processes, which impact the formation, intensity, and movement of precipitation systems. By incorporating this information into forecasting models, more accurate precipitation predictions can be made. Drought and Flood Monitoring: Satellite-derived soil moisture data aids in monitoring and predicting droughts and floods. Real-time updates of soil moisture conditions can be integrated into forecasting models, allowing for timely and accurate assessments of soil moisture deficits or surpluses. This information is crucial for managing water resources, agriculture, and mitigating the impacts of extreme weather events. <strong>Related code in Github</strong>: https://github.com/Hyunglok-Kim/HydroAI/blob/main/Ex_in_TCA.ipynb
DOI: 10.34740/kaggle/dsv/5912949
title: IPL 2023 Cleaned Data Set
DOI: 10.25345/c50p0x18w
title: MassIVE MSV000092147 - Sharif CC_YuklE_111022_RawData
title: Influence of the Heme Nitric Oxide / Oxygen Binding Protein (H-NOX) on cell cycle regulation in Caulobacter crescentus
DOI: 10.25934/pr00008965.0
title: Available datapackage for study 'Convalescent Plasma to Stem Coronavirus: A Randomized, Blinded Phase 2 Study Comparing the Efficacy and Safety Human Coronavirus Immune Plasma (HCIP) vs. Control (SARS-CoV-2 Non-immune Plasma) Among Adults Exposed to COVID-19'

description: Evaluate the efficacy of treatment with high-titer Anti- SARS-CoV-2 plasma versus control (SARS-CoV-2 non-immune plasma) in subjects exposed to Coronavirus disease (COVID-19) at day 28.
DOI: 10.5281/zenodo.7863332
title: Productes i característiques del catàleg d'electrodomèstics de la web electrocosto.com.

description: <strong>El dataset consta de les diferents característiques, preus i informació tècnica del conjunt d'electrodomèstics ofertats a la pàgina web de venta d’electrodomèstics electrocosto.com.</strong> <strong>El dataset té dues parts, una part comuna i una part específica. A la part comuna tenim camps que apliquen a tots els tipus de dispositius que poden haver-hi al dataset. Tenim:</strong> <strong>product-name: Nom del producte.</strong> <strong>product-type: Tipus d’electrodomèstic (segons la classificació pròpia de la web)</strong> <strong>price: Preu en el moment de l’extracció de dades.</strong> <strong>ref: Referència del producte.</strong> <strong>marca: Marca/empresa que fabrica el producte.</strong> <strong>val-points: Valoració 1-5 de la qualitat del producte segons els usuaris.</strong> <strong>val-quantity: Nombre de valoracions.</strong> <strong>stock: Si el producte està o no disponible.</strong> <strong>product-sending-value: Costos d’enviament.</strong> <strong>date: Data de l’extracció de dades.</strong> <strong>A la part específica tenim totes les característiques del producte que apareixen a la web. Com no tots els productes les tenen fins i tot sent productes del mateix tipus disposen de molts camps nuls i n’hi ha moltes de diferents. No les detallarem totes però alguns exemples serien:</strong> <strong>ModoECO: Té mode ECO o d’estalvi.</strong> <strong>CapacidadTotalNeta: Capacitat de volum en Litres.</strong> <strong>Cajones: Disposa de calaixos.</strong> <strong>Peso: Pes.</strong> <strong>Les dades pertanyen al període de temps especificat en el camp “date”. D’aquesta manera podem tenir registre de l’evolució dels productes al llarg del temps en aquesta web</strong>
DOI: 10.5281/zenodo.7863333
title: Productes i característiques del catàleg d'electrodomèstics de la web electrocosto.com.

description: <strong>El dataset consta de les diferents característiques, preus i informació tècnica del conjunt d'electrodomèstics ofertats a la pàgina web de venta d’electrodomèstics electrocosto.com.</strong> <strong>El dataset té dues parts, una part comuna i una part específica. A la part comuna tenim camps que apliquen a tots els tipus de dispositius que poden haver-hi al dataset. Tenim:</strong> <strong>product-name: Nom del producte.</strong> <strong>product-type: Tipus d’electrodomèstic (segons la classificació pròpia de la web)</strong> <strong>price: Preu en el moment de l’extracció de dades.</strong> <strong>ref: Referència del producte.</strong> <strong>marca: Marca/empresa que fabrica el producte.</strong> <strong>val-points: Valoració 1-5 de la qualitat del producte segons els usuaris.</strong> <strong>val-quantity: Nombre de valoracions.</strong> <strong>stock: Si el producte està o no disponible.</strong> <strong>product-sending-value: Costos d’enviament.</strong> <strong>date: Data de l’extracció de dades.</strong> <strong>A la part específica tenim totes les característiques del producte que apareixen a la web. Com no tots els productes les tenen fins i tot sent productes del mateix tipus disposen de molts camps nuls i n’hi ha moltes de diferents. No les detallarem totes però alguns exemples serien:</strong> <strong>ModoECO: Té mode ECO o d’estalvi.</strong> <strong>CapacidadTotalNeta: Capacitat de volum en Litres.</strong> <strong>Cajones: Disposa de calaixos.</strong> <strong>Peso: Pes.</strong> <strong>Les dades pertanyen al període de temps especificat en el camp “date”. D’aquesta manera podem tenir registre de l’evolució dels productes al llarg del temps en aquesta web</strong>
DOI: 10.5281/zenodo.8030610
title: Productes i característiques del catàleg d'electrodomèstics de la web electrocosto.com.

description: <strong>El dataset consta de les diferents característiques, preus i informació tècnica del conjunt d'electrodomèstics ofertats a la pàgina web de venta d’electrodomèstics electrocosto.com.</strong> <strong>El dataset té dues parts, una part comuna i una part específica. A la part comuna tenim camps que apliquen a tots els tipus de dispositius que poden haver-hi al dataset. Tenim:</strong> <strong>product-name: Nom del producte.</strong> <strong>product-type: Tipus d’electrodomèstic (segons la classificació pròpia de la web)</strong> <strong>price: Preu en el moment de l’extracció de dades.</strong> <strong>ref: Referència del producte.</strong> <strong>marca: Marca/empresa que fabrica el producte.</strong> <strong>val-points: Valoració 1-5 de la qualitat del producte segons els usuaris.</strong> <strong>val-quantity: Nombre de valoracions.</strong> <strong>stock: Si el producte està o no disponible.</strong> <strong>product-sending-value: Costos d’enviament.</strong> <strong>date: Data de l’extracció de dades.</strong> <strong>A la part específica tenim totes les característiques del producte que apareixen a la web. Com no tots els productes les tenen fins i tot sent productes del mateix tipus disposen de molts camps nuls i n’hi ha moltes de diferents. No les detallarem totes però alguns exemples serien:</strong> <strong>ModoECO: Té mode ECO o d’estalvi.</strong> <strong>CapacidadTotalNeta: Capacitat de volum en Litres.</strong> <strong>Cajones: Disposa de calaixos.</strong> <strong>Peso: Pes.</strong> <strong>Les dades pertanyen al període de temps especificat en el camp “date”. D’aquesta manera podem tenir registre de l’evolució dels productes al llarg del temps en aquesta web</strong>
DOI: 10.5281/zenodo.8030588
title: MHD/PSD data: Simulation of Radiation Belt Wave-Particle Interactions in an MHD-particle Framework

description: MHD and phase space density simulation results.
DOI: 10.5281/zenodo.8030587
title: MHD/PSD data: Simulation of Radiation Belt Wave-Particle Interactions in an MHD-particle Framework

description: MHD and phase space density simulation results.
DOI: 10.5281/zenodo.8030630
title: nothura_maculosa_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8030629
title: nothura_maculosa_zanfona_1.fasta.gz

description: .
DOI: 10.35077/add-own
title: EM derived morphology of 50k neurons from mouse visual cortex: Synapse and morphology data of a neuron in a P87 male mouse

description: 3D anatomical reconstruction and synapse map of neuron in mouse visual cortex obtained from serial section Electron Microscopy imaging from the IARPA MICrONS dataset. More information on the can be found on MICrONS Explorer https://www.microns- explorer.org/cortical-mm3. Most of the included h5, json and swc files represent dendrite and soma morphologies of excitatory neurons that have been automatically reconstructed with little to no human proofreading. These span much of the millimeter cubed of the MICrONS dataset except for the edges where the majority of the morphology would be cut off. There is a smaller subset of human proofread excitatory and inhibitory neurons with axons, dendrite and soma reconstruction. This information is accessible in the json files. h5 files here can be ingested into a meshwork object in python with the package MeshParty https://github.com/sdorkenw/MeshParty. This meshwork integrates anatomical data and other user defined annotations such as synapses. The meshworks here contain annotation tables including pre and post synaptic chemical synapses on the given neuron and the ids of the post or presynaptic neurons respectively. Unless the neuron has had a high level of proofreading, the axon has been masked and removed. json files contain metadata and morphological features of the neuron skeleton including the proofreading version of the MICrONS dataset, the various ids of the given body, and lenghts of certain compartments. More information on the contents of this filetype can be found on the MicRONS explorer skeleton page.
description: Please see README.xlsx for more information.
description: DATASET METADATA: title:'EM derived morphology of 50k neurons from mouse visual cortex: Synapse and morphology data of a neuron in a P87 male mouse', socialMedia:'Synapse and morphology data of a neuron in a P87 male mouse visual cortex', Subjectscheme:'soma and root ids for IARPA MICrONS neurons. Ids tied to tables from CAVE (Connectome Annotation Versioning Engine)', GeneralModality:'connectivity', Technique:'other', Other:'anatomical data derived from serial section EM image stack' SPECIMEN METADATA: LocalID:'M180517', Species:'Mouse', NCBITaxonomy:'NCBI:txid10090', Age:'87.0', Ageunit:'Days', Sex:'Male', Genotype:'SLC17a7-Cre';Reporter_Name='Ai162';', OrganName:'Brain', SampleLocalID:'M180517', Atlas:'AllenMouseV2', Locations:'VIS - Visual cortex' INSTRUMENT METADATA: MicroscopeType:'Electron Microscope', MicroscopeManufacturerAndModel:'JEOL 1200EXII 120kV TEM', ObjectiveImmersion:'Oil', DetectorType:'CMOS', DetectorModel:'Ximea CB500MG-CM', IlluminationWavelength:'400–850 nm' IMAGE METADATA: xAxis:'NA', yAxis:'NA', zAxis:'NA', Number:'NA', displayColor:'NA', stepSizeX:'NA', stepSizeY:'NA'
DOI: 10.5281/zenodo.8030188
title: Dataset for the manuscript "In silico evaluation of variant calling methods for bacterial whole genome sequencing"

description: Input data and associated analysis code for reproducing results reported in the manuscript.
DOI: 10.5281/zenodo.8030187
title: Dataset for the manuscript "In silico evaluation of variant calling methods for bacterial whole genome sequencing"

description: Input data and associated analysis code for reproducing results reported in the manuscript.
DOI: 10.5517/ccdc.csd.cc2bttzz
title: CCDC 2169782: Experimental Crystal Structure Determination

description: Related Article: Hoang-Long Pham, Thayalan Rajeshkumar, Lily Ueh-hsi Wang, Yat Hei Ng, Kai-Hong Wong, Yat-Ming So, Herman H. Y. Sung, Rolf Lortz, Ian D. Williams, Laurent Maron, Wa-Hung Leung|2023|Organometallics|42|1094|doi:10.1021/acs.organomet.2c00569
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2btv01
title: CCDC 2169783: Experimental Crystal Structure Determination

description: Related Article: Hoang-Long Pham, Thayalan Rajeshkumar, Lily Ueh-hsi Wang, Yat Hei Ng, Kai-Hong Wong, Yat-Ming So, Herman H. Y. Sung, Rolf Lortz, Ian D. Williams, Laurent Maron, Wa-Hung Leung|2023|Organometallics|42|1094|doi:10.1021/acs.organomet.2c00569
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2btv12
title: CCDC 2169784: Experimental Crystal Structure Determination

description: Related Article: Hoang-Long Pham, Thayalan Rajeshkumar, Lily Ueh-hsi Wang, Yat Hei Ng, Kai-Hong Wong, Yat-Ming So, Herman H. Y. Sung, Rolf Lortz, Ian D. Williams, Laurent Maron, Wa-Hung Leung|2023|Organometallics|42|1094|doi:10.1021/acs.organomet.2c00569
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2btv34
title: CCDC 2169786: Experimental Crystal Structure Determination

description: Related Article: Hoang-Long Pham, Thayalan Rajeshkumar, Lily Ueh-hsi Wang, Yat Hei Ng, Kai-Hong Wong, Yat-Ming So, Herman H. Y. Sung, Rolf Lortz, Ian D. Williams, Laurent Maron, Wa-Hung Leung|2023|Organometallics|42|1094|doi:10.1021/acs.organomet.2c00569
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2btv45
title: CCDC 2169787: Experimental Crystal Structure Determination

description: Related Article: Hoang-Long Pham, Thayalan Rajeshkumar, Lily Ueh-hsi Wang, Yat Hei Ng, Kai-Hong Wong, Yat-Ming So, Herman H. Y. Sung, Rolf Lortz, Ian D. Williams, Laurent Maron, Wa-Hung Leung|2023|Organometallics|42|1094|doi:10.1021/acs.organomet.2c00569
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2btv56
title: CCDC 2169788: Experimental Crystal Structure Determination

description: Related Article: Hoang-Long Pham, Thayalan Rajeshkumar, Lily Ueh-hsi Wang, Yat Hei Ng, Kai-Hong Wong, Yat-Ming So, Herman H. Y. Sung, Rolf Lortz, Ian D. Williams, Laurent Maron, Wa-Hung Leung|2023|Organometallics|42|1094|doi:10.1021/acs.organomet.2c00569
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2btv67
title: CCDC 2169789: Experimental Crystal Structure Determination

description: Related Article: Hoang-Long Pham, Thayalan Rajeshkumar, Lily Ueh-hsi Wang, Yat Hei Ng, Kai-Hong Wong, Yat-Ming So, Herman H. Y. Sung, Rolf Lortz, Ian D. Williams, Laurent Maron, Wa-Hung Leung|2023|Organometallics|42|1094|doi:10.1021/acs.organomet.2c00569
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2btv89
title: CCDC 2169791: Experimental Crystal Structure Determination

description: Related Article: Hoang-Long Pham, Thayalan Rajeshkumar, Lily Ueh-hsi Wang, Yat Hei Ng, Kai-Hong Wong, Yat-Ming So, Herman H. Y. Sung, Rolf Lortz, Ian D. Williams, Laurent Maron, Wa-Hung Leung|2023|Organometallics|42|1094|doi:10.1021/acs.organomet.2c00569
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.8030711
title: User Unfairness Mitigation by Graph Data Augmentation in Recommendation

description: Dataset for the paper submission `User Unfairness Mitigation by Graph Data Augmentation in Recommendation`. The included datasets are: MovieLens-1M, Last.FM 1K.
DOI: 10.5281/zenodo.8030710
title: User Unfairness Mitigation by Graph Data Augmentation in Recommendation

description: Dataset for the paper submission `User Unfairness Mitigation by Graph Data Augmentation in Recommendation`. The included datasets are: MovieLens-1M, Last.FM 1K.
DOI: 10.25919/dedt-4589
title: Parkes observations for project PX600 semester 2020APRS_87

description: The Galactic Center (GC) is a key target for the radio component of Breakthrough Listen (BL) program. Offering the largest amount of stars in any given direction in the sky, the GC is widely cited as a location believed to harbour advanced civilizations, and it is also the most energetic region in the Milky Way. We aim to conduct BL-GC Survey with Parkes radio telescope for around 350 hours. We will cover the frequency range from 700 MHz to 4 GHz, utilizing the newly installed ultra-wideband receiver. Our team has already leveraged both standard and bespoke tools to construct a flexible software stack to search data for signals of interest. We will look for signals from extraterrestrial intelligence (ETI) by searching for both simple narrow-band signals and complex modulated signals. Along with that, as an ancillary science, we will also search for accelerated pulsars — likely orbiting a supermassive black hole at the centre of the Milky Way Galaxy. Data products produced during this program will also be publically available to engage larger pulsar community
DOI: 10.5281/zenodo.8030725
title: spatula_querquedula_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.8030724
title: spatula_querquedula_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7510757
title: iPlacenta: hIPSC placenta-on-a-chip RNAseq data from 3D vs 2D, day 0 vs day 4 differentiation

description: RNAseq data from hIPSC dervived trophoblasts seeded in 3D (OrganoPlate) or 2D surface at day 0 or day 4 differentiation. Description of file names found below <strong>SampleID/File name</strong> <strong>Condition- Differentiation day</strong> iPSC-THB-2D-D0-1 2D-Day0 iPSC-THB-2D-D0-2 2D-Day0 iPSC-THB-2D-D0-3 2D-Day0 iPSC-THB-2D-D4-4 2D-Day4 iPSC-THB-2D-D4-5 2D-Day4 iPSC-THB-2D-D4-6 2D-Day4 iPSC-THB-3D-D0-7 3D-Day0 iPSC-THB-3D-D0-8 3D-Day0 iPSC-THB-3D-D0-9 3D-Day0 iPSC-THB-3D-D4-10 3D-Day4 iPSC-THB-3D-D4-11 3D-Day4 iPSC-THB-3D-D4-12 3D-Day4 iPSC-THB-3D-D4-13 3D-Day4
description: SampleID/File name Condition- Differentiation day iPSC-THB-2D-D0-1 2D-Day0 iPSC-THB-2D-D0-2 2D-Day0 iPSC-THB-2D-D0-3 2D-Day0 iPSC-THB-2D-D4-4 2D-Day4 iPSC-THB-2D-D4-5 2D-Day4 iPSC-THB-2D-D4-6 2D-Day4 iPSC-THB-3D-D0-7 3D-Day0 iPSC-THB-3D-D0-8 3D-Day0 iPSC-THB-3D-D0-9 3D-Day0 iPSC-THB-3D-D4-10 3D-Day4 iPSC-THB-3D-D4-11 3D-Day4 iPSC-THB-3D-D4-12 3D-Day4 iPSC-THB-3D-D4-13 3D-Day4
description: {"references": ["Lermant, Agathe and Rabussier, Gwena\u00eblle and Lanz, Henri\u00ebtte L. and Davidson, Lindsay and Porter, Iain M. and Murdoch, Colin E., Development of a Human iPSC-Derived Placental Barrier-On-Chip Model. Available at SSRN: https://ssrn.com/abstract=4336829 or http://dx.doi.org/10.2139/ssrn.4336829"]}
DOI: 10.5281/zenodo.7510756
title: iPlacenta: hIPSC placenta-on-a-chip RNAseq data from 3D vs 2D, day 0 vs day 4 differentiation

description: RNAseq data from hIPSC dervived trophoblasts seeded in 3D (OrganoPlate) or 2D surface at day 0 or day 4 differentiation. Description of file names found below <strong>SampleID/File name</strong> <strong>Condition- Differentiation day</strong> iPSC-THB-2D-D0-1 2D-Day0 iPSC-THB-2D-D0-2 2D-Day0 iPSC-THB-2D-D0-3 2D-Day0 iPSC-THB-2D-D4-4 2D-Day4 iPSC-THB-2D-D4-5 2D-Day4 iPSC-THB-2D-D4-6 2D-Day4 iPSC-THB-3D-D0-7 3D-Day0 iPSC-THB-3D-D0-8 3D-Day0 iPSC-THB-3D-D0-9 3D-Day0 iPSC-THB-3D-D4-10 3D-Day4 iPSC-THB-3D-D4-11 3D-Day4 iPSC-THB-3D-D4-12 3D-Day4 iPSC-THB-3D-D4-13 3D-Day4
description: SampleID/File name Condition- Differentiation day iPSC-THB-2D-D0-1 2D-Day0 iPSC-THB-2D-D0-2 2D-Day0 iPSC-THB-2D-D0-3 2D-Day0 iPSC-THB-2D-D4-4 2D-Day4 iPSC-THB-2D-D4-5 2D-Day4 iPSC-THB-2D-D4-6 2D-Day4 iPSC-THB-3D-D0-7 3D-Day0 iPSC-THB-3D-D0-8 3D-Day0 iPSC-THB-3D-D0-9 3D-Day0 iPSC-THB-3D-D4-10 3D-Day4 iPSC-THB-3D-D4-11 3D-Day4 iPSC-THB-3D-D4-12 3D-Day4 iPSC-THB-3D-D4-13 3D-Day4
description: {"references": ["Lermant, Agathe and Rabussier, Gwena\u00eblle and Lanz, Henri\u00ebtte L. and Davidson, Lindsay and Porter, Iain M. and Murdoch, Colin E., Development of a Human iPSC-Derived Placental Barrier-On-Chip Model. Available at SSRN: https://ssrn.com/abstract=4336829 or http://dx.doi.org/10.2139/ssrn.4336829"]}
DOI: 10.5281/zenodo.8030729
title: Seafloor and volcanic seismic horizons from NZ3D

description: This file (horizons.csv) contains picked seismic horizons for the seafloor and top of volcanic basement in the NZ3D volume within 15 km of the deformation front. The columns are formatted as crossline, inline, seafloor depth (m), top of volcanic basement (m). Raw and processed NZ3D seismic data can be downloaded here: https://www.marine-geo.org/tools/entry/MGL1801.