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726 results for “Shear”
Dataset for "Deflected Mantle Flow and Shearing-aligned Lithospheric Melt under the Strike-slip Dead Sea Rift"
<p>Dataset 1: All of the individual shear-wave splitting measurements in the Dead Sea rift, including 1855 A and B measurements and 1088 Null measurements</p> <p>Dataset 2: Three component seismic waveforms used for shear-wave splitting measurement, for PKS, SKKS, and SKS, respectively</p> <p>Dataset 3: Earthquake catalogue with magnitude Mb 2.6 or above in the Dead Sea rift. Downloaded from the International Seismological Centre (https://www.isc.ac.uk/)</p> <p> Reference: International Seismological Centre (2024), On-line Bulletin, [Dataset] doi:10.31905/D808B830</p> <p>Dataset 4: Holocene Volcano List. Downloaded from Global Volcanism Program (https://volcano.si.edu/volcanolist_holocene.cfm)</p> <p> Reference: Global Volcanism Program, 2024. Volcanoes of the World (v. 5.2.2; 22 Aug 2024). Distributed by Smithsonian Institution, compiled by Venzke, E. [Database] doi:10.5479/si.GVP.VOTW5-2024.5.2</p>
Regional scale shear wave velocity profiles for ground response analyses and uncertainties evaluations – the Piedmont Region (NW Italy) Database
<p>The databases provide detailed information for the Piedmont region in Northwest Italy, offering a view of its geological and geophysical characteristics:</p> <ul> <li><strong>Geological-Geomorphological Database</strong>: Includes 13 distinct Geological-Geomorphological Domains (GGD) in shapefile format. It supports spatial analysis and visualization, based on data from the Geological Map of the Piedmont Region at a 1:250,000 scale.</li> <li><strong>Geotechnical Database</strong>: Contains geotechnical data on bedrock depth and texture attributes derived from available logs in CSV format. Georeferenced using UTM coordinates (WGS84 UTM32N), it includes depth values and texture codes (C for clay, G for gravel, S for sand, R for rock, X for not available).</li> <li><strong>Geophysical Database</strong>: Provides data on shear wave velocity (Vs) profiles in CSV format. Georeferenced with UTM coordinates (WGS84 UTM32N), it includes layer interface depth and shear wave velocity above each layer.</li> </ul>
Data files for the manuscript "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes"
<p>This depository contains the data of all DEM simulations used in the manuscript titled "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes" submitted to Soft Matter in July 2024.</p> <p>The data in the excel file are the measurements obtained after the coarse graining procedure.</p>
IODP Expedition 398 Vane shear strength (AVS)
Shear strength was measured on section halves using a GEISA automated vane shear (AVS) frame and device controller. The device is suitable for sediment not affected by cementation (i.e., saturated, clay-rich, soft sediment). Shear strength measurements should be considered only approximate, particularly because the influence of pore pressure changes during the undrained experiment cannot be estimated. Report includes vane shear strength at the sample's failure point, maximum torque angle, penetration direction, and rate of vane rotation.
Data for "Impact of the Out-of-Plane Flow Shear on Magnetic Reconnection at the Flanks of Earth's Magnetopause"
<p>Data for Figures 3-8 in the paper (data for Figures 5 has been updated on 2024-09-20). The data is compatible with all data-analysis software. Here are the guidelines for reading and visualizing the data:</p> <p>(1) The filenames "noshear", "MA0p7", and "MA2p3" correspond to the simulation runs with no flow shear, Mach number M_A=0.7 flow shear, and M_A=2.3 flow shear.</p> <p>(2) The "upper" and "lower" mean upper and lower current sheet, corresponding to dusk-side and dawn-side reconnection respectively. For the "noshear" case, only the "upper" is considered.</p> <p>(3) Each data file (*.dat) is written in ASCII format and has multiple columns. The first row is the header.</p> <ul> <li>The first column is always the x-coordinates of the figure. </li> <li>For the line plots, all columns starting from the second column are the y-coordinates for different variables. The variables names can be found at the header. </li> <li>For the 2D image plots, the second column is the y-coordinates, and the third column is the value of the variable at a given (x,y) location. </li> </ul> <p>(4) The files "fig4_*_field_*.dat" are the magnetic potential in the x-y domain. The contour of this potential gives the in-plane field line configurations.</p>
IODP Expedition 355 Vane shear strength (AVS)
Shear strength was measured on section halves using a GEISA automated vane shear (AVS) frame and device controller. The device is suitable for sediment not affected by cementation (i.e., saturated, clay-rich, soft sediment). Shear strength measurements should be considered only approximate, particularly because the influence of pore pressure changes during the undrained experiment cannot be estimated. Report includes vane shear strength at the sample's failure point, maximum torque angle, penetration direction, and rate of vane rotation.
Geostrophic wind shear from CFSR v2 data for usage in WAsP
<p>The change of the geostrophic wind speed has an impact on boundary layer mixing that can be important for microscale flow modelling for wind energy purposes. The WAsP software is often used for this purpose. This dataset contains the climatological geostrophic wind shear and direction over the whole global on a 0.5 degree grid that has been used in WAsP 12. It was obtained from the 6-hourly CFSR v2 reanalysis for the period 2011 to 2017 (see https://doi.org/10.5065/D61C1TXF). The omni-directional geostrophic wind shear vector denotes how much the geostrophic wind speed is changing over a certain vertical distance. Because we are interested in geostrophic wind shear changes that contribute to turbulent mixing in the atmospheric boundary layer, it was estimated by using the data on pressure levels from the pressure level closest to the surface up to 500 hPa above that heights.p><p dir="ltr">More details about the implementation of the model in the WAsP software and a validation can be found in the corresponding technical report:<br>Floors, R. R., Troen, I., & Kelly, M. C. (2018). <i>Implementation of large-scale average geostrophic wind shear in WAsP12.1i>. DTU Wind Energy. DTU Wind Energy E No. 0169p><p><br>p><ul><li>meandgdz_2010_2017_CFSRv3.nc: version with coordinate reference system in the coordinates for usage in GIS programs. NaN values at the poles are filled with 0.0, i.e. assuming barotropic atmosphere, which avoids crashes in the pywasp code. A single sector variable has been added, indicating that these values are valid for all wind direction, as opposed to other files that have values for each wind direction sector (for example: https://data.dtu.dk/articles/dataset/ERA5_atmospheric_stability_for_usage_in_WAsP_12_8/19576042). Naming conventions are in accordance with the windkit package (https://docs.wasp.dk/windkit/)</p> <p>Mirror of https://data.dtu.dk/articles/dataset/Geostrophic_wind_shear_from_CFSR_v2_data_for_usage_in_WAsP/21975482</p>
IODP Expedition 356 Vane shear strength (Torvane)
Sediment strength was measured on section halves using a Humbolt Manufacturing Torvane handheld instrument. The Torvane is suitable for sediment not affected by cementation (i.e., saturated, clay-rich, soft sediment).
IODP Expedition 353 Vane shear strength (AVS)
Shear strength was measured on section halves using a GEISA automated vane shear (AVS) frame and device controller. The device is suitable for sediment not affected by cementation (i.e., saturated, clay-rich, soft sediment). Shear strength measurements should be considered only approximate, particularly because the influence of pore pressure changes during the undrained experiment cannot be estimated. Report includes vane shear strength at the sample's failure point, maximum torque angle, penetration direction, and rate of vane rotation.
IODP Expedition 359 Vane shear strength (Torvane)
Sediment strength was measured on section halves using a Humbolt Manufacturing Torvane handheld instrument. The Torvane is suitable for sediment not affected by cementation (i.e., saturated, clay-rich, soft sediment).
Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound - Elastic Wave Simulations (Open Scanning Paths)
<p><strong>Elastic Wave Simulations - Open Scanning Paths</strong></p> <p>This dataset is part of a larger repository (DOI: 10.5281/zenodo.5248082) which houses links to the data used in the publication "Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound" <a href="http://www.science.org/doi/10.1126/sciadv.adf2037">(Reardon et al., 2023)</a>. If you use these simulated data please cite our publication (<a href="http://www.science.org/doi/10.1126/sciadv.adf2037">http://www.science.org/doi/10.1126/sciadv.adf2037</a>) and the software package k-Wave (DOI: 10.1109/ULTSYM.2014.0037).</p> <p>This dataset contains the normal shear surface velocity in a cylindrical slab of tissue-like material excited by an acoustic source with a Gaussian spatial profile simulated via a pseudo-spectral numerical method. The data is provided as .mat files. The files are separated by the type of scanning path, the scanning speed of the acoustic source, and the parameters of the scanning path. Details of the simulation parameters can be found in our publication.</p> <p><strong>Line Paths</strong> - The acoustic source scanned along a linear trajectory at speeds ranging from 2 m/s to 12 m/s (scanning speed is indicated in the filename).</p> <p><strong>Zigzag Paths</strong> - The acoustic source scanned along a zigzag path on the surface of the simulated medium with x-axis scanning speed <em>v<sub>x</sub></em> = 3, 4, 5, 6 m/s. At all speeds, the ultrasound focus was modulated transverse to its primary motion direction at a speed, <em>v<sub>y</sub></em>, of +-2.5 m/s yielding a zigzag path (2 cm path width). The x-axis scanning speed is designated in the filename.</p> <p><strong>Letter Paths</strong> - The acoustic source scanned the a trajectory in the shape of the letter "Z." Scanning speeds ranged from 2 m/s to 12 m/s (scanning speed is designated in the filename).</p> <p><strong>Focus Control Rate</strong> - The acoustic source scanned along a linear trajectory at 7 m/s but at different focus control sample rates <em>f<sub>c</sub></em>. These paths amount to a courser sampling of the linear trajectory. In lieu of updating the location of the acoustic source at each timepoint in the simulation, we specified a rate at which the location of the acoustic source would be updated. We set <em>f<sub>c</sub></em> to approximately 0.7, 1.4, and 4.2 kHz (designated at the end of the filename as VeryCoarse, Coarse, and Fine, respectively). (Compare with Line_07, which has the finest path sampling and an *f<sub>c</sub>* of approximately 200 kHz.)</p> <p> </p> <p><strong>Data Fields</strong></p> <p><strong>surfaceData</strong> (NxNxM) - 3D array containing the normal shear velocity of the simulated medium (in m/s) on a NxN Cartesian grid of locations at M timepoints. The simulated tissue medium was cylindrical, so locations outside the circular top surface are NaN.</p> <p><strong>sourceSignals</strong> (NxNxQ) - 3D array containing the acoustic source distribution on the NxN Cartesian grid of locations used to excite the surface of the simulated tissue medium for Q timepoints.</p> <p><strong>sourceEnvelope</strong> (Qx1) - Vector containing the amplitude envelope that was applied to sourceSignals at each timestep Q</p> <p><strong>dt</strong> - The time between adjacent timepoints in seconds (i.e. fs = 1/dt)</p> <p><strong>dx/dy</strong> - The distance between adjacent grid locations in the x/y direction of the Cartesian grid (in m)</p>
Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound
<p>This repository contains links to the data used in the publication "Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound" (<a href="http://www.science.org/doi/10.1126/sciadv.adf2037">Reardon et al., 2023</a>). If you use these data please cite our publication found here: <a href="http://www.science.org/doi/10.1126/sciadv.adf2037">http://www.science.org/doi/10.1126/sciadv.adf2037</a>.</p> <p> </p> <p><strong>Abstract From Manuscript</strong></p> <p>Emerging holographic haptic interfaces focus ultrasound in air to enable their users to touch, feel, and manipulate three-dimensional virtual objects. However, current holographic haptic systems furnish tactile sensations that are diffuse and faint, with apparent spatial resolutions that are far coarser than would be theoretically predicted from acoustic focusing. Here, we show how the effective spatial resolution and dynamic range of holographic haptic displays are determined by ultrasound-driven elastic wave transport in soft tissues. Using time-resolved optical imaging and numerical simulations, we show that ultrasound-based holographic displays excite shear shock wave patterns in the skin. The spatial dimensions of these wave patterns can exceed nominal focal dimensions by more than an order of magnitude. Analyses of data from behavioral and vibrometry experiments indicate that shock formation diminishes perceptual acuity. For holographic haptic displays to attain their potential, techniques for circumventing shock wave artifacts, or for exploiting these phenomena, are needed.</p> <p> </p> <p><strong>Dataset Description</strong></p> <p>This dataset comprises surface velocity responses of materials to ultrasound-based holographic haptic displays. The dataset is split into three parts: numerical simulations on a tissue-like material, experimental measurements on a tissue phantom, and in vivo experimental measurements on a human hand. For details on our numerical and experimental procedure, please see our publication.</p> <p> </p> <p><strong>Elastic Wave Simulations</strong></p> <p>The elastic wave simulation dataset contains the surface velocity response of a tissue-like material to an acoustic source scanned across the medium surface and is split into two parts: closed scanning paths (circle and square paths) and open scanning paths (line, zigzag, and letter). These datasets can be found at the following DOIs: 10.5281/zenodo.7686542 and 10.5281/zenodo.7686550.</p> <p> </p> <p><strong>Vibrometry Measurements with Elastomer Plate</strong></p> <p>Data on our tissue phantom was captured via laser doppler vibrometer. This dataset contains the tissue phantom response to focused ultrasound scanned across the tissue phantom surface along linear and zigzag paths. This dataset can be found at the following DOI: 10.5281/zenodo.7686555.</p> <p> </p> <p><strong>Human Hand: Wave Patterns and Perception</strong></p> <p>In vivo measurements on the human hand were captured via laser doppler vibrometer. This dataset contains the skin response to focused ultrasound scanned in a zigzag path from the wrist to the distal end of digit 2 (and vice-versa) of a single participant. We also captured a behavioral dataset that assessed tactile motion direction discrimination. Participants reported the direction of scanning via a two-alternative forced-choice task. Written, informed consent was gathered from all participants in this study, and the protocol was approved by the human subjects committee of our institution. This dataset can be found at the following DOI: 10.5281/zenodo.7686561.</p>
Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound - Elastic Wave Simulations (Closed Scanning Paths)
<p><strong>Elastic Wave Simulations - Closed Scanning Paths</strong></p> <p>This dataset is part of a larger repository (DOI: 10.5281/zenodo.5248082) which houses links to the data used in the publication "Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound" (<a href="http://www.science.org/doi/10.1126/sciadv.adf2037">Reardon et al., 2023</a>). If you use these simulated data please cite our publication (<a href="http://www.science.org/doi/10.1126/sciadv.adf2037">http://www.science.org/doi/10.1126/sciadv.adf2037</a>) and the software package k-Wave (DOI: 10.1109/ULTSYM.2014.0037).</p> <p>This dataset contains the normal shear surface velocity in a cylindrical slab of tissue-like material excited by an acoustic source with a Gaussian spatial profile simulated via a pseudo-spectral numerical method. The data is provided as .mat files. The files are separated by the type of scanning path, the scanning speed of the acoustic source, and the parameters of the scanning path. Details of the simulation parameters can be found in our publication.</p> <p><strong>Circle Paths</strong> - The acoustic source was scanned at a constant linear speed along a circular trajectories with two different diameters - 1 cm and 3 cm (indicated in the filename) and for at least 2 pattern repetitions. The linear scanning speed ranged from 2 to 20 m/s and is designated in the filename.</p> <p><strong>Square Paths</strong> - The acoustic source was scanned at a constant speed along square trajectories with two different edge lengths - 1 cm and 3 cm (indicated in the filename) and for at least 2 pattern repetitions. The scan speed ranged from 2 m/s to 10 m/s and is designated in the filename.</p> <p> </p> <p><strong>Data Fields</strong></p> <p><strong>surfaceData</strong> (NxNxM) - 3D array containing the normal shear velocity of the simulated medium (in m/s) on a NxN Cartesian grid of locations at M timepoints. The simulated tissue medium was cylindrical, so locations outside the circular top surface are NaN</p> <p><strong>sourceSignals</strong> (NxNxQ) - 3D array containing the acoustic source distribution on the NxN Cartesian grid of locations used to excite the surface of the simulated tissue medium for Q timepoints</p> <p><strong>sourceEnvelope</strong> (Qx1) - Vector containing the amplitude envelope that was applied to sourceSignals at each timestep</p> <p><strong>nCycles</strong> - Number of pattern repetitions</p> <p><strong>dt</strong> - The time between adjacent timepoints in seconds (i.e. fs = 1/dt)</p> <p><strong>dx/dy</strong> - The distance between adjacent grid locations in the x/y direction of the Cartesian grid (in m)</p>
Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound - Human Hand: Wave Patterns and Perception
<p><strong>Human Hand: Wave Patterns and Perception</strong></p> <p>This dataset is part of a larger repository (DOI: 10.5281/zenodo.5248082) which houses links to the data used in the publication "Shear Shock Waves Mediate Haptic Holography via Focused Ultrasound" (<a href="http://www.science.org/doi/10.1126/sciadv.adf2037">Reardon et al., 2023</a>). If you use these data please cite our publication (<a href="http://www.science.org/doi/10.1126/sciadv.adf2037">http://www.science.org/doi/10.1126/sciadv.adf2037</a>).</p> <p>This dataset contains the in vivo response of a single participant's hand to focused ultrasound (UHEV1, Ultrahaptics) scanned in a zigzag path from the wrist to the distal end of digit 2 (and vice-versa). The data is provided as .mat files. The files are separated via longitudinal scanning speed, <em>v<sub>l</sub></em> = 1, 2, 4, 7, 11 m/s. At all speeds, the ultrasound focus was modulated transverse to its primary motion direction at a speed, <em>v<sub>mod</sub></em> of +-2.5 m/s yielding a zigzag path (2 cm path width). The longitudinal speed is designated in the filename. The direction of scanning - either from the wrist to the distal end of digit 2 (Distal direction) or from the distal end of digit 2 to the wrist (Proximal direction) - is also designated in the filename. Written, informed consent was gathered from the participant in this study, and the protocol was approved by the human subjects committee of our institution. Details about our experimental procedure can be found in our publication.</p> <p>IMPORTANT - The data is the unprocessed output from a laser doppler vibrometer (PSV-500, Polytec). The data is NOT time-aligned and must be reconstructed using the reference signal and the map of the measurement locations.</p> <p> </p> <p><strong>Data Fields</strong></p> <p><strong>y</strong> (NxMx2) - 3D array containing the skin velocity normal to the laser doppler vibrometer (in m/s) at N measurement locations for M timepoints and 2 repetitions</p> <p><strong>ref</strong> (NxMx2) - 3D array containing a reference voltage signal taken from the ultrasound phased array. The beginning of the reference signal can be used to time-align each of the measurements and repetitions</p> <p><strong>fs</strong> - Laser doppler vibrometer sampling rate (in Hz)</p> <p><strong>measurementLocations</strong> (Nx3) - 3D locations on the hand (x,y,z; in m) for each of N measurement locations<br> <br> </p> <p> </p> <p><strong>BehavioralDataset.zip</strong></p> <p>Contains the responses from three different perception experiments on tactile motion direction discrimination. The experiments are provided in three separate files; the results are provided as a MATLAB table. Written, informed consent was gathered from all participants in this study, and the protocol was approved by the human subjects committee of our institution. Details about our experimental procedure can be found in our publication.</p> <p>In the first experiment, SSW_PrimaryDataset.mat, participants (N=12) identified the direction of the focused ultrasound as either moving from the wrist to the end of digit 2 (Distal direction) or from the end of digit 2 to the wrist (Proximal direction).</p> <p>The second experiment, SSW_SecondaryDataset-Zigzag.mat, was nearly identical to the first experiment, except we cyclically repeated the stimuli such that the total integrated time in which the stimulus was applied to the skin was approximately constant between all of the different scan speeds. The participants (N=3) identified the motion direction of the focused ultrasound as either "Distal" or "Proximal" under two conditions - one in which there was no delay between our cyclical repeats (No Delay condition) and a second in which there was a 500 ms time delay between subsequent repetitions (With Delay condition).</p> <p>The third file, SSW_SecondaryDataset-Circle.mat, presents the pilot results (N=1) of a similar tactile motion experiment, except with circular trajectories (radius 2.8 cm) drawn on the palm of the hand in either a clockwise or counterclockwise direction. The stimuli were also repeated cyclically (with and without delay between repetitions), similar to experiment two.</p> <p> </p> <p> </p> <p><strong>Table Fields - SSW_PrimaryDataset.mat</strong></p> <p><strong>Participant</strong> - Participant label</p> <p><strong>Speed</strong> - Longitudinal speed, *v<sub>l</sub>*, of the focused ultrasound stimulus (in m/s)</p> <p><strong>Response</strong> - Participant response as a binary 0 (Distal direction) or 1 (Proximal direction)</p> <p><strong>Direction</strong> - True direction of the stimulus as a binary 0 (Distal direction) or 1 (Proximal direction)</p> <p><strong>isCorrect</strong> - Indicates whether the participant's response matches the true stimulus direction</p> <p><strong>Repetition</strong> - Stimuli were block randomized and "Repetition" refers to how many times the participant has seen that specific stimulus</p> <p><strong>ResponseLabel </strong>- Participant response as either "Distal" or "Proximal"</p> <p><strong>DirectionLabel </strong>- True label of the stimulus as either "Distal" or "Proximal"</p> <p><strong>Plays</strong> - Number of times the participant felt the stimulus before selecting a response</p> <p> </p> <p><strong>Table Fields - SSW_SecondaryDataset-Zigzag.mat</strong></p> <p><strong>Participant</strong> - Participant label</p> <p><strong>Speed </strong>- Longitudinal speed, *v<sub>l</sub>*, of the focused ultrasound stimulus (in m/s)</p> <p><strong>Response </strong>- Participant response as a binary 0 (Distal direction) or 1 (Proximal direction)</p> <p><strong>Direction </strong>- True direction of the stimulus as a binary 0 (Distal direction) or 1 (Proximal direction)</p> <p><strong>isCorrect </strong>- Indicates whether the participant's response matches the true stimulus direction</p> <p><strong>Repetition </strong>- Stimuli were block randomized and "Repetition" refers to how many times the participant has seen that specific stimulus</p> <p><strong>ResponseLabel </strong>- Participant response as either "Distal" or "Proximal"</p> <p><strong>DirectionLabel </strong>- True label of the stimulus as either "Distal" or "Proximal"</p> <p><strong>Condition </strong>- Indicates the experimental condition ("NoDelay" or "WithDelay")</p> <p> </p> <p><strong>Table Fields - SSW_SecondaryDataset-Circle.mat</strong></p> <p><strong>Participant </strong>- Participant label</p> <p><strong>Speed </strong>- Linear speed of the focused ultrasound stimulus along the circular trajectory (in m/s)</p> <p><strong>Response </strong>- Participant response as a binary 0 (Counterclockwise direction) or 1 (Clockwise direction)</p> <p><strong>Direction </strong>- True direction of the stimulus as a binary 0 (Counterclockwise direction) or 1 (Clockwise direction)</p> <p><strong>isCorrect </strong>- Indicates whether the participant's response matches the true stimulus direction</p> <p><strong>Repetition </strong>- Stimuli were block randomized and "Repetition" refers to how many times the participant has seen that specific stimulus</p> <p><strong>ResponseLabel </strong>- Participant response as either "Counterclockwise" or "Clockwise"</p> <p><strong>DirectionLabel </strong>- True label of the stimulus as either "Counterclockwise" or "Clockwise"</p> <p><strong>Condition </strong>- Indicates the experimental condition ("NoDelay" or "WithDelay")</p>
Shear modulus reduction and damping ratio curves collected from multiple literature sources available in Italy
<p><em>Data</em> are 485 G/G<sub>0 </sub>(γ) and damping ratio, D(γ) curves collected from multiple literature sources available in Italy. Each curve was associated with the related engineering geological units considered in seismic microzonation studies. The data focus on providing reference information that can serve as key data for large-scale hazard assessments worldwide and to guide the translation of information from the laboratory scale to the scale of geological-engineering cross-sections.</p>
Dataset and Software for The Relationships Between Large-scale Variations in Shear Velocity, Density, and Compressional Velocity in the Earth's Mantle
<p><strong>Is there a chemically distinct reservoir in the Earth?</strong><br><strong>Do superplumes overly denser-than-average material?</strong><br><strong>Can we detect these anomalies with seismic data?</strong><br><strong>Can we evaluate statistical significance of the features in tomography?</strong></p><p>This study presents the <strong>strongest evidence</strong> to date (ca. 2015) of <strong>large-scale thermo-chemical heterogeneities in the lowermost mantle</strong> using the full spectrum of seismic data. A large data set of surface-wave phase anomalies, body-wave travel times, normal-mode splitting functions and long-period waveforms is used to investigate the scaling between shear velocity, density and compressional velocity in the Earth's mantle (ϱ=dln ρ/dln vS, ν=dln vS/dln vP). Our preferred joint model consists of denser-than-average anomalies (∼1% peak-to-peak) at the base of the mantle roughly coincident with the low-velocity superplumes. The relative variation of shear velocity, density and compressional velocity in our study disfavors a purely thermal contribution to heterogeneity in the lowermost mantle, with implications for the long-term stability and evolution of superplumes.</p><p><strong>Note on Odd Degree Structure:</strong></p><p>Since the self-coupled normal-mode splitting observations constrain only even-degree density variations, all inversions strongly disfavored even-degree vS-ρ correlation (R2 ~ –0.46 to –0.25) in the lowermost mantle, which also disfavors a purely thermal contribution to heterogeneity in this region. However, the starting assumptions on positive vS-ρ correlation persisted in the remaining regions and for odd degree variations. In viscosity inversions with the geoid, opposing sign of the correlation of the longest wavelength even-versus odd-degree structure maps into a region of reduced viscosity in the lower mantle (Rudolph et al., 2020, doi:10.1029/2020gc009335). While important for such dynamical implications, <strong>odd-degree density variations in the lowermost mantle are poorly constrained in this study and should not be interpreted</strong>. We therefore used even-degree variations up to degree 6 for our inferences on thermo-chemical variations in the lowermost mantle (Figure 14), and provide those values in the files below.</p><p><strong>Feedback/Questions?</strong> Please contact Raj Moulik (<a href="https://rajmoulik.com">rajmoulik.com</a>) at <a href="mailto:moulik@caa.columbia.edu?subject=Query%20from%20Zenodo">moulik@caa.columbia.edu</a> </p><p><strong>Reference:</strong></p><p><i>Please cite the following work if you use this data or software.</i></p><ul><li>Moulik, P. & Ekström, G., 2016. The relationships between large-scale variations in shear velocity, density and compressional velocity in the Earth's mantle, <i>J. Geophys. Res.</i>, <strong>121</strong>, doi: <a href="http://dx.doi.org/10.1002/2015JB012679">10.1002/2015JB012679</a>. <a href="https://rajmoulik.com/Publications/MoulikEkstrom_JGR2016.pdf"><i>pdf</i></a></li></ul><p><i>You can also cite the dataset and software from this Zenodo page (Optional).</i></p><p>Moulik, P. & Ekström, G. (2016). Dataset and Software for The Relationships Between Large-scale Variations in Shear Velocity, Density, and Compressional Velocity in the Earth's Mantle. In J. Geophys. Res. Solid Earth (v1.0, Vol. 121, pp. 2737–2771). Zenodo. doi: <a href="https://doi.org/10.5281/zenodo.8356540">10.5281/zenodo.8356540</a></p><p><strong>Data Products:</strong></p><ul><li><strong>ME16_Figures(</strong><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16_Figures.tar.gz"><strong>.tar.gz</strong></a><strong> or </strong><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16_Figures.pdf"><strong>.pdf</strong></a><strong>)</strong> - contains all figures from the paper in .png format</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16"><strong>ME16</strong></a><strong> - </strong>Coefficients of the spline basis functions for each parameter. Refer cij in equation 3. This is our preferred global model of anisotropic elastic parameters and density. Density variations are allowed to deviate from a constant scaling with shear-velocity variations in the lowermost mantle, which is required to fit the longest-period normal modes (e.g. 0S2). Radial anisotropy is confined to the uppermost mantle (that is, since the anisotropy is parameterized with only the four uppermost splines, it becomes very small below a depth of 250 km, and vanishes at 410 km). This is an updated version of S362ANI+M (Moulik and Ekström, 2014) which did not solve independently for density and compressional-wave velocity variations and imposed a constant scaling throughout the mantle instead (ϱ=0, ν=1/0.55).</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/STW105"><strong>STW105</strong></a> - reference model used in ME16. Described in Kustowski et al. (2008)</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/setup.cfg"><strong>setup.cfg</strong></a><strong> - </strong>Some configuration metadata relevant to this model for reproducibility.</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/epix.tar.gz"><strong>epix.tar.gz</strong></a> - Perturbations in horizontally (<i>vsh</i>) and vertically polarized shear velocity (<i>vsv</i>), Voigt-average isotropic shear-wave (<i>vs</i>) and compressional-wave velocity (<i>vp</i>), density (<i>rho</i>). anisotropy (<i>as</i>) and topography of the internal boundaries. This is calculated from the spline coefficients at every 1 by 1 degree cell-centered pixel and at every ~25 km depth region from Moho to the core-mantle boundary and stored in extended pixel format (.epix) ASCII files. Even-degree variations up to degree 6 are provided for density (<i>rho_even6)</i> and isotropic shear-wave velocity (<i>vs_even6</i>), which should be used for density inferences on thermochemical structure (See note above).</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16.BOX25km_PIX1X1.avni.nc4"><strong>ME16.BOX25km_PIX1X1.avni.nc4</strong></a> - The perturbations in a standard AVNI format that utilizes the NETCDF4 container format. This file can be read in Python using either xarray or AVNI libraries. For example, to plot even-degree variations up to degree 6 in Voigt-averaged shear velocity perturbations at the bottom of the mantle (2875-2891 km depth)<ul><li><i>import xarray as xr</i></li><li><i>ds = xr.open_dataset('ME16.BOX25km_PIX1X1.avni.nc4')</i></li><li><i>ds['vs_even6'][-1].plot()</i></li></ul></li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/PROGRAMS.tar.gz"><strong>PROGRAMS.tar.gz</strong></a> - Fortran tools for obtaining model values at specific locations. After creating the executables from source code in the <i>src</i> folder, the <i>readme</i> script generates most of the epix files provided in epix.tar.gz above<strong>.</strong></li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/profilescaling.txt"><strong>profilescaling.txt</strong></a> - contains the median scaling ratios as used in Figure 15(a).</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/scaling3D_MoulikJGR16.tar.gz"><strong>scaling3D_MoulikJGR16.tar.gz</strong></a> - contains the scaling ratios and poisson ratio calculated from the joint model, as used in Figure 15(b).</li></ul>
Shear Stress, Biomass, Bulk Density, Organic Matter on the Bank of the York River, VA 2018
This dataset includes data used to assess marsh vulnerability to sea-level rise by quantifying marsh erodibility along a salinity gradient in the York River in southeastern Virginia. We measured the erodibility of marshes along a salinity gradient in the York River, a tributary of the Chesapeake Bay (Virginia, USA). We chose five marshes along the York River salinity gradient for this study. Salinity decreases upriver from 18 ppt at the Goodwin Islands to 0 ppt at the Pamunkey Indian Reservation. Within these overall sites, we chose sampling locations along tidal creeks 5-10 m wide, with marsh widths beyond 20 meters and consistent elevations across all study sites. We collected samples from both the tidal channel marsh edge and from the marsh interior. Edge sites were located between the tidal channel and any levee (1 m from edge), while interior sites were located at a measured distance of 10-12 m away from the edge site. All field work was done in July-August 2018, except for the collection of cores for belowground biomass at the Sweet Hall Marsh and Pamunkey Indian Reservation marsh edge sites (September 2018) and elevation profiles of the Pamunkey Indian Reservation (March 2020). Data tables are: 1) shear strength, 2) aboveground biomass, 3) belowground biomass, 4) LOI (loss on ignition), 5) kinematic GPS data along the transects and 6) averages for each station of variables in tables 1, 3 and 4.
IODP Expedition 366 Vane shear strength (AVS)
<p>Shear strength was measured on section halves using a GEISA automated vane shear (AVS) frame and device controller. The device is suitable for sediment not affected by cementation (i.e., saturated, clay-rich, soft sediment). Shear strength measurements should be considered only approximate, particularly because the influence of pore pressure changes during the undrained experiment cannot be estimated. Report includes vane shear strength at the sample's failure point, maximum torque angle, penetration direction, and rate of vane rotation.</p>
40Ar/39Ar dating of the East Tenda Shear Zone: Chemical composition of white mica and ages data
<p>In order to clarify the link between <sup>40</sup>Ar/<sup>39</sup>Ar record in white mica and deformation, we performed <em>in situ</em> and bulkwise <sup>40</sup>Ar/<sup>39</sup>Ar dating over the East Tenda Shear Zone (Tenda massif, alpine Corsica). White micas from 11 samples were selected and extensively analyzed using <em>in situ</em> techniques across nested scales of strain-intensity gradients developed at the expense of a Late-Variscan protolith. <sup>40</sup>Ar/<sup>39</sup>Ar systematics are unaffected by inherited Ar and directly linked to deformation with little or no Ar lattice (volume) diffusion. Extensive sampling allows constraining the end of deformation related to burial and exhumation respectively at ~34 and ~22 Ma, bracketing the duration of regional extensional shear to ~12 Myr. Results also highlight a regional strain localization toward the upper contact of the unit with smaller-scale localization in specific lithologies, notably meta-aplites.</p> <p> Second-order complications exist, such as local ill-defined correlations between ages and finite-strain microstructures. Thus, the use of a strain gradient as a proxy for strain localization in time is regionally valid but sometimes locally too complex to track or resolve strain partitioning/localization trends at the meter (outcrop) scale and below. Age mixing and incomplete isotopic homogenization by dissolution/precipitation are identified as the main causes of local discrepancies that complicate the link between age and microstructure and the derivation of strain localization rates. Tracking temporal trends in shear distribution across regional-scale deformation gradients in such settings is possible but requires a multi-scale approach as implemented here to reveal younging patterns associated to strain localization.</p>
3D cell tracking dataset of bacterial biofilm deformation and recovery under shear flow
<p>This MAT file includes dataset in the scientific article "<i>In vivo</i> microrheology reveals elastic and plastic responses inside three-dimensional bacterial biofilms" by the following authors: Takuya Ohmura, Dominic Skinner, Konstantin Neuhaus, Gary Choi, Jörn Dunkel, Knut Drescher. This MAT file can be conveniently opened with Matlab. </p><p>When you open this file with Matlab, you will find 4 variables stored in the file "Data_v3_loop2_newRxy_bidx1_274.mat"</p><p><strong>Variable 1: name_parameter</strong></p><p>Names of 31 parameters for columns in 3 variables: 'deformation_all', 'recovery_all' , 'plasticity_all'. The parameters have cell displacements, orientations, coordinates, biofilm indexes and experimental conditions. When the parameters have units, they are shown in the names. </p><ul><li>'x_Frame1[um]'</li><li>'y_Frame1[um]'</li><li>'z_Frame1[um]'</li><li>'Normalized_x_Frame1'</li><li>'Normalized_y_Frame1'</li><li>'Normalized_z_Frame1'</li><li>'LocalDensity_Frame1(VolumeFractionAround30px)'</li><li>'LocalCellNumberDensity_Frame1(VolumeFractionAround30px)'</li><li>'NematicOrderParameter_Frame1'</li><li>'AlignmentFlow_Frame1[rad]'</li><li>'AlignmentRadial_Frame1[rad]'</li><li>'AlignmentZaxis_Frame1[rad]'</li><li>'d_x[um]'</li><li>'d_y[um]'</li><li>'d_z[um]'</li><li>'Normalized_d_x'</li><li>'Normalized_d_y'</li><li>'Normalized_d_z'</li><li>'d_LocalDensity'</li><li>'d_LocalNumberDensity[um^-3]'</li><li>'d_NematicOrderParameter'</li><li>'d_AlignmentFlow[rad]'</li><li>'d_AlignmentRadial[rad]'</li><li>'d_AlignmentZaxis[rad]'</li><li>'CrossProduct[um^2]'</li><li>'BiofilmIndexNumber'</li><li>'Biofilm_width[um]'</li><li>'Biofilm_height[um]'</li><li>'Biofilm_volume[um^3]'</li><li>'FlowRate[ul/min]'</li><li>'Duration[min]'</li></ul><p><strong>Variable 2: deformation_all</strong></p><p>The rows indicate 704198 single-cell trackings in deformations of 274 bacterial biofilms. Each of the 274 bacterial biofilms has a different 'BiofilmIndexNumber'. The columns indicate 31 parameters which names are shown in 'name_parameter'.</p><p><strong>Variable 3: recovery_all</strong></p><p>The rows indicate 685991 single-cell trackings in recoveries of 274 bacterial biofilms. Each of the 274 bacterial biofilms has a different 'BiofilmIndexNumber'. The columns indicate 31 parameters which names are shown in 'name_parameter'.</p><p><strong>Variable 4: plasticity_all</strong></p><p>The rows indicate 665749 single-cell trackings in plasticities of 274 bacterial biofilms. Each of the 274 bacterial biofilms has a different 'BiofilmIndexNumber'. The columns indicate 31 parameters which names are shown in 'name_parameter'.</p><p> </p><p>To plot the cell tracked data in the figures of the article, use our MATLAB code uploaded in our GitHub (https://github.com/knutdrescher/biofilm-rheology).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.