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37 results for “Azimuth”
LungMAP Azimuth Reference - Human Adult Lung scRNA-Seq
<p>The LungMAP scRNA-Seq reference associated with the Lung CellCards resource. The initial reference integrated 259k cells from 72 donors from five published (PMIDs: 32726565, 32427931, 30554520, 32832599, 32832598) and one unpublished single cell RNA-seq cohort. Non-diseased adult and pediatric healthy lung single-cell 10x Genomics captures (3’ v2 and v3). Cells from different donors were integrated using Batchlor. Preliminary cell types were called based on Leiden clustering analysis and expression patterns of LungMAP cell card markers. UMAP embeddings were generated using monocle3. This reference, along with a corresponding single-nucleus specific version of this atlas, is under active construction. We expect to release the beta version of the reference in November 2021. Conforms to<strong> </strong>Azimuth reference data structure described at <a href="https://github.com/satijalab/azimuth/wiki/Azimuth-Reference-Format">https://github.com/satijalab/azimuth/wiki/Azimuth-Reference-Format</a>.</p>
Sample output of Alt-Azimuth plots from beamModelTester
<p>Sample Output from BeamModelTester operating in various alt-azimuth plotting modes.</p>
Data of Listening Experiments for Azimuthal Localisation in (Local) Sound Field Synthesis
<p>Data of two listening experiments conducted at University of Rostock, Germany. The study investigated the four (Local) Sound Field Synthesis techniques</p> <ul> <li>Wave Field Synthesis</li> <li>Near-Field-Compensated Higher-Order Ambisonics</li> <li>Local Wave Field Synthesis using Spatial Bandwidth Limitation</li> <li>Local Wave Field Synthesis using Virtual Secondary Sources</li> </ul> <p>The corresponding binaural room scanning (BRS) files for the binaural simulation can be found in the directory `brs`. The employed noise stimulus is contained in `stimuli`. The localisation results are stored in `results`. The `analysis` directory includes scripts for parsing the data.</p>
Dataset for supervised learning with a deep neural network to assess azimuthal localisation in sound field synthesis
<p>Dataset for supervised learning with a deep neural network to assess azimuthal localisation in sound field synthesis.<br> Released as part of the Master Thesis 'An Auditory Model for Azimuthal Localisation in Sound Field Synthesis'.</p> <p>This database is calculated from the data of listening experiments.</p>
Azimuth Reference - Mouse PanSci
<p>Here we provide the reference data files used to run the Azimuth Mouse PanSci web application. For a full description of the reference data structure, please see the wiki at <a href="https://github.com/satijalab/azimuth/wiki/Azimuth-Reference-Format">https://github.com/satijalab/azimuth/wiki/Azimuth-Reference-Format</a>.</p>
Seismic Azimuthal Anisotropy Model for the Juan de Fuca ‐ Gorda Plate System
<p>This dataset is supplementary to:</p> <p>Liu, C., et al. (2024) Seismic Azimuthal Anisotropy Within the Juan de Fuca ‐ Gorda Plate System, GRL</p> <div> <p>DOI: 10.1029/2024GL111835</p> <p>Azimuthal anisotropy model from 10-100 km</p> <p> </p> <p>Model 1: <code>JdFG_Azi_anisotropy_model.nc</code>: contains</p> <ul> <li>Anisotropic lithospheric layer: base of sediments to 20km below the Moho</li> <li>Anisotropic asthenospheric zone: 50 km thick layer beneath the lithosphere layer</li> <li>A complementary deeper asthenosphere layer </li> </ul> <p>Model 2:<code>JdFG_Azi_anisotropy_model_ios_crust.nc</code>: </p> <ul> <li>Anisotropic lithospheric layer: the Moho to 30km below the Moho</li> <li>Anisotropic asthenospheric zone: 50 km thick layer beneath the lithosphere layer</li> <li>A complementary deeper asthenosphere layer </li> </ul> </div> <p>The uploaded file uses NetCDF4 format.</p> <p>File format:</p> <p><code>Longitude</code>, <code>Latitude</code>, <code>Depth</code>, <code>fa</code>,<code>unc_fa</code>,<code>amp</code>,<code>unc_amp</code></p> <ul> <li> <p>Dimensions:</p> <ul> <li><code>Longitude</code>: -130.2° to -125.0° with 0.4° interval.</li> <li><code>Latitude</code>: 40.6° to 49.0° with 0.4° interval.</li> <li><code>Depth</code>: 10 to 100 with 10 km interval</li> </ul> </li> <li>Model variables: <ul> <li><code>fa</code>: depth-dependent fast azimuth (deg)</li> <li><code>unc_fa</code>: uncertainty for depth-dependent fast azimuth (deg)</li> <li><code>amp</code>: depth-dependent anisotropy amplitude (%)</li> <li><code>unc_amp</code>: uncertainty for depth-dependent anisotropy amplitude (%)</li> </ul> </li> </ul>
Seismic radial and azimuthal anisotropy tomography beneath Greenland and surrounding regions
<p>Dear readers,</p> <p>These four files contain P-wave velocity model beneath Greenland and surrounding regions obtained by regional anisotropy tomography (Toyokuni & Zhao, 2021, ESS). </p> <p>P-wave radial anisotropy (RAN) model<br> RAN_DV0.DAT: Isotropic component (DV0) of RAN tomography<br> -FORMAT: Latitude(deg), Longitude(deg), Depth(km), dVp0(%)</p> <p>RAN_AI.DAT: Anisotropic component RAN tomography<br> -FORMAT: Longitude(deg), Latitude(deg), Depth(km), alpha(%)</p> <p>P-wave azimuthal anisotropy (AAN) model<br> AAN_DV0.DAT: Isotropic component (DV0) of AAN tomography<br> -FORMAT: Latitude(deg), Longitude(deg), Depth(km), dVp0(%)</p> <p>AAN_AI.DAT: Anisotropic component AAN tomography<br> -FORMAT: Longitude(deg), Latitude(deg), Depth(km), FVD(deg), beta(%)</p> <p>We note that the tomography was conducted in the transformed coordinates. The details of the coordinate transformation are described in the above paper. We also note that the fast velocity direction (FVD) of the AAN model is in the transformed coordinates. Please contact us if you want any program to convert it back to the geographical coordinates.</p> <p>We hope it is useful to you.</p> <p>Kind wishes,</p> <p>Genti Toyokuni & Dapeng Zhao<br> Tohoku University, Japan<br> E-mail: toyokuni@tohoku.ac.jp</p> <p>Reference:<br> Toyokuni, G. & Zhao, D. (2021).<br> P wave tomography for 3-D radial and azimuthal anisotropy beneath Greenland and surrounding regions.<br> Earth and Space Science, under review.</p>
Depth dependent azimuthal anisotropy beneath the Juan de Fuca plate system
Open the record for dataset details and reuse information.
Azimuthally averaged tangential wind and radial wind for Hurricane Patricia simulations and SAMURAI analysis at validation time
<p>Azimuthally averaged tangential wind and radial wind for Hurricane Patricia simulations (the data format is .mat) and SAMURAI analysis at validation time (the data format is netcdf).</p>
Isotropic and azimuthally anisotropic lithospheric Vs models beneath the central-southern Tanlu fault
<p>We obtained high-resolution isotropic and azimuthally anisotropic Vs models beneath the central and southern Tanlu fault from ambient noise and earthquake surface waves.</p> <p>The Tanlu3D_iso.mod is a 3D isotropic Vs model with a grid spacing of 0.25deg*0.25deg. The data format is "longitude, latitude, depth, Vs, Vp, density."</p> <p>The Tanlu3D_anis.mod is the 3D azimuthally anisotropic Vs model with a grid spacing of 0.5deg*0.5deg. The data format follows "longitude, latitude, depth, Vs, Vp, density, anis_azimuth, anis_amplitude, azimuth_uncertanty, amplitude_uncertainty".</p> <p> </p> <p>Reference</p> <p>Luo S.*, Yao H.*, Zhang Z., Bem T. S. 2022. High-resolution crustal and upper mantle shear-wave structure beneath the central-southern Tanlu fault: Implications for its initiation and evolution. Earth and Planetary Science Letters, 595. doi:10.1016/j.epsl.2022.117763.</p>
Effect of plasma initialization on 3D PIC simulation of Hall 1 thruster azimuthal instability
<p>This dataset only includes the plotting scripts for the research, because the data is too big. More may be uploaded in a later time.</p>
Data set for: Crustal Azimuthal Anisotropy Beneath the Southeastern Tibetan Plateau and its Geodynamic Implications
<p>Abstract of the original paper:</p> <p>Zheng, T., Ding, Z., Ning, J., Chang, L., Wang, X., Kong, F., Liu, K.H., & Gao, S.S. (2018).<br> Crustal azimuthal anisotropy beneath the southeastern Tibetan Plateau and its geodynamic implications.<br> <em><strong>Journal of Geophysical Research: Solid Earth, 123(11)</strong>, 9733-9749. </em> <a href="https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018JB015995"> https://doi.org/10.1029/2018JB015995</a></p> <p>The fast orientation and magnitude of crustal azimuthal anisotropy beneath the southeastern Tibetan Plateau and adjacent areas are measured by analyzing the sinusoidal moveout of the <em>P</em> to <em>S</em> converted phase from the Moho. Beneath the tectonically active plateau, the mean magnitude is 0.48 ± 0.13 s, which is about twice as large as that observed in the stable Sichuan Basin (0.23 ± 0.10 s). The two areas are separated by the Longmenshan fault zone, a zone of devastating earthquakes including the 12 May 2008 <em>M</em><sub><em>W</em></sub> 7.9 Wenchuan earthquake. Fault orthogonal fast orientations observed in the southern Longmenshan fault zone, where previous studies have revealed high crustal <em>V</em><sub><em>p</em></sub>/<em>V</em><sub><em>s</em></sub> and suggested the presence of mid‐lower crustal flow, may reflect flow‐induced lattice preferred orientation of anisotropic minerals. Fault parallel anisotropy in the central segment of the fault zone is most likely related to fluid filled fractures, and fault perpendicular extensional cracks are probably responsible for the observed anisotropy in the northern segment. The crustal anisotropy measurements, when combined with results from previous studies, suggest the existence of mid‐lower crustal flow beneath the southeastern margin of the plateau. Comparison of crustal anisotropy obtained before and after the Wenchuan earthquake suggests that the earthquake has limited influence on whole crustal anisotropy, although temporal changes of anisotropy associated with the earthquake have been reported using splitting of shear waves from local earthquakes occurred in the upper crust.</p>
Marlim R3D (MR3D) - The full azimuth noise-free CSEM dataset
<p>Marlim R3D (MR3D) is an open-source realistic geoelectric model for CSEM simulations of the post-salt turbiditic reservoirs at the Brazilian offshore margin.<br> Here we make available the complete noise-free CSEM dataset, with inline and broadside geometries, of two simulated surveys on the MR3D model. We computed the six electromagnetic field components (Ex, Ey, Ez, Hx, Hy, and Hz) at six frequencies in the 0.125–1.25 Hz range.<br> The output dataset was generated in the current industry netCDF-based data format.<br> You can follow the updates of the marlim project at:<br> https://www.researchgate.net/project/Marlim-R3D-A-realistic-model-for-mCSEM-simulations</p>
Azimuthal C/O Variations in a Planet-Forming Disk
<p><strong>DALI physical-chemical disk models presented in 'Azimuthal C/O Variations in a Planet-Forming Disk' (Keyte et al. 2023).</strong></p> <p>There are two individual models included here. The 'baseline' model is used to produce outputs for the region of the disk where C/O=0.5. The 'elevated' model is used to produce outputs for the regions of the disk where C/O=1.5.</p> <p>The baseline model can be run in the normal way, but the outputs themselves are already included in the folder.</p> <p>The 'elevated' model will not run in the regular way. The source code has been edited so that it can take in the abundances from a previous run as the starting point for the chemistry (in the form of an <em>out.dat</em> style table). The outputs are already included, but should you want to rerun the model yourself, follow the steps in the readme file within the folder.</p> <p>The final 'composite' model presented in the paper is created by splicing together the outputs (as described in Keyte et al. 2023). This is achieved using a custom Python script, please contact me if you would like to use this.</p>
Azimuthally averaged tangential wind and radial wind for 3D WRF tropical cyclone simulations
<p>MAT-file </p> <p>setup number 1 to 9: V20B0.75R75, V20B0.75R100, V20B0.75R125; V20B1.0R75, V20B1.0R100, V20B1.0R125; V30B0.75R75, V30B0.75R100, V30B0.75R125</p> <p>time: hourly output</p> <p>iradius: radial grids, radius=(iradius-1)*2 km</p> <p>Vt(setup, time, iradius): tangential wind calculated from 10-m wind</p> <p>Vr(setup, time, iradius): radial wind calculated from 10-m wind</p> <p>M(setup, time, iradius): absolute angular momentum calculated using M=Vt*r+1/2*f*r^2</p> <p>nt(setup): maximum time step, 1 h interval</p> <p>nr(setup): maximum grid for radius, starting from center (0km) with 2 km interval</p> <p>Vmax(setup, time): maximum 10-m tangential wind</p> <p>RMW(setup, time): radius of maximum 10-m tangential wind</p> <p>MRMW(setup, time): absolute angular momentum at RMW</p> <p>SL(setup, time): M*(r*) slope calculated using best linear fit</p> <p>RIstart(setup): RI onset time</p> <p>RIend(setup): RI end time</p>
Azimuthal ion movement in HiPIMS plasmas - Part I: velocity distribution function
<p>Data affiliated to the submission of the research paper " Azimuthal ion movement in HiPIMS plasmas - Part I:<br> velocity distribution function" to the journal Plasma Sources Science and Technology. The data contains measurements, analytical calculations and computer simulation results.</p>
EVOLVING AZIMUTH IN MUSA CONTEXT
ClinicalTrials.gov study NCT07022067. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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