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490 results for “Propagation”
Fig. 1 in Sarcocystis falcatula-like derived from opossum in Northeastern Brazil: In vitro propagation in avian cells, molecular characterization and bioassay in birds
Fig. 1. Sporocyst of Sarcocystis falcatula-like. Four sporozoites are visualized inside the sporocyst by light microscopy (A). Autofluorescence of the sporocyst wall is observed after excitation with ultraviolet on a fluorescence microscope (B).
Software for performing source, propagation and site convolution in seismology
<p>This repository distributes the software convo.m, written for Matlab/Octave. The goal of the software is to allow students to perform the convolution between a simple seismic source model (Brune model), the propagation of S-waves in a homogeneous half-space (geometric propagation given by the inverse of the distance and anelastic contribution described by the quality factor Q(f)), and considering the site amplification effects in terms of response for a simple 1D homogeneous layer. The instrumental response of a broadband or short-period sensor is also considered. The four terms (source, propagation, site and instrumental response) and their convolution (seismogram) are evaluated in both time and frequency (amplitude spectra) domains. Source and seismograms can be displayed in displacement, velocity and acceleration. Interaction with convo.m is via a GUI and several sliders (seismic moment and stress drop for the source term; distance and quality factor model for propagation; thickness, velocity and damping of the 1D sediment layer). The software is not intended to perform complex simulations, but only to discuss with students the basics of the convolution between source, propagation and site and its impact on the characteristics of the recordings in the time and frequency domains.</p> <p>Software is distributed within the archive convo.tar. </p> <p>THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.</p>
Localized Topological States beyond Fano Resonances via Counter-Propagating Wave Mode Conversion in Piezoelectric Microelectromechanical Devices
<p>Main numerical and experimental data (Matlab .fig files) of the paper <em>Localized Topological States beyond Fano Resonances via Counter-Propagating Wave Mode Conversion in Piezoelectric Microelectromechanical Devices.</em></p>
Citation count error data for "Data inaccuracy quantification and uncertainty propagation for bibliometric indicators"
<p>This is the original collected data on citation count errors resulting from citation matching errors in Web of Science data for the publication "Data inaccuracy quantification and uncertainty propagation for<br>bibliometric indicators". The first column, <code>CITCOUNT_ALL</code>, gives the total (corrected) citation count for a publication, which is the citation count according to WoS plus the additionally manually identified citations (missed by WoS's algorithm). The second column, <code>CITCOUNT_WOS</code>, is the WoS citation count. The numeric difference between the two column values in one row is the number of additionally manually identified citations.</p>
Sonic Boom Propagation Results for Case Study 1 of the MORE&LESS Project
<p>This dataset provides the output of sonic boom simulations under various flight conditions, including predictions using Carlson’s method and higher-fidelity nonlinear propagation simulations (using propaBoom). The data is categorized by flight phase (climb, cruise, descent) and atmosphere models (ISA, SBPW3). Each flight phase includes ray tracing results and sonic boom signatures for multiple azimuth angles.</p> <p>The dataset includes:</p> <ul> <li><strong>Carlson Method Predictions</strong>: Peak overpressure and signal duration for various off-track angles.</li> <li><strong>Nonlinear Propagation Simulations</strong>: Ray tracing data (ground intersections and angles) and shock wave signatures at the beginning of the non-linear shock wave propagation and at ground level.</li> </ul> <p>Files are provided in CSV format for easy analysis using standard tools (e.g., Excel, pandas). The dataset contains simulation results for different azimuth angles, e.g., acoustic pressure, and ray intersections for thorough investigation of sonic boom propagation effects.</p> <p><strong>Folder Structure</strong>:</p> <ul> <li><code>carlson_predictions.zip</code>: Carlson method results for climb, cruise, and descent operating conditions.</li> <li><code>nonlinear_propagation_predictions.zip</code>: High-fidelity simulation outputs including ray tracing and propagated ground signatures.</li> <li><code>readme.md</code>: Readme file with information on the datasets.</li> </ul> <p><strong>Usage</strong>: Researchers can use these datasets to compare sonic boom prediction methods under the effects of flight conditions and atmospheric variations on sonic boom ground signatures.</p> <p><strong>Contact</strong>: For any questions or inquiries regarding this dataset, please contact Jacob Jäschke (jacob.jaeschke[at]tuhh.de) (<a title="Orcid Profile of Jacob Jäschke" href="https://orcid.org/0000-0002-5155-4877" target="_blank" rel="noopener">https://orcid.org/0000-0002-5155-4877</a>).</p>
Fatigue Crack Propagation Benchmark, GDR 3651 FATACRACK
<p>This is a data set for fatigue crack propagation following the benchmark defined within the french research network GDR 3651 FATACRACK funded by CNRS <a href="http://www.gdr3651.cnrs.fr/">http://www.gdr3651.cnrs.fr</a>. </p> <p>Only two test configurations are reported in this data set. But DIC allows to provide for the analysis not only of the crack tip state ( tip position, crack growth rate and stress intensity factors) but also of the displacement amplitude along the boundary of the analyzed domain. The data set can thus be used to validate fatigue crack growth models.</p> <p>A detailed description of the data set is given in the pdf file Fatigue_Crack_Propagation_Benchmark.pdf.</p> <p><strong>!!!!! there is unfortunately a mistake in the pdf document: the sample thickness is 4 mm !!!!!</strong></p> <p><br> </p> <p> </p>
Dataset for "Yield Estimation of the August 2020 Beirut Explosion by Using Physics-Based Propagation Simulations of Regional Infrasound"
<p>Dataset for “Yield Estimation of the August 2020 Beirut Explosion by Using<br> Physics-Based Propagation Simulations of Regional Infrasound”</p> <p>Authors: Keehoon Kim and Michael E. Pasyanos</p> <p>Lawrence Livermore National Laboratory, Livermore, CA, USA</p> <p>Description<br> This datset includes the infrasound waveform data recorded by the array at the<br> Mt. Meron (IMA) in Israel. A five-element array deployed by the National Data<br> Center of Israel (Fee et al., 2013), and all stations had Martec Tekelec MB2005<br> sensors which have a flat frequency response in the infrasound band (0.1–20Hz)<br> (Ponceau and Bosca, 2010). The infrasound data was provided by the National<br> Data Center of Israel, Soreq Nuclear Research Center, and the pressure<br> recordings only relevant to the 2020 Beirut explosion were uploaded to the<br> public repository (https://zenodo.org).</p> <p>File Description<br> IMA_array_infrasound_waveform.txt Pressure values in ASCII format for 5 stations</p> <p>Acknowledgments<br> This research was performed by the support from the U.S. Department of Energy,<br> National Nuclear Security Administration, Office of Defense Nuclear<br> Nonproliferation, Research and Development under the auspices of the U.S.<br> Department of Energy by the Lawrence Livermore National Laboratory under<br> Contract Number DE-AC52-07NA27344. This is LLNL Contribution LLNL-JRNL- 839419</p> <p>References<br> Fee, D., Waxler, R., Assink, J., Gitterman, Y., Given, J., Coyne, J., ... &<br> Grenard, P. (2013). Overview of the 2009 and 2011 Sayarim infrasound<br> calibration experiments. Journal of Geophysical Research Atmospheres, 118(12),<br> 6122-6143.</p> <p>Ponceau, D., & Bosca, L. (2010). Low-noise broadband microbarometers. In<br> Infrasound monitoring for atmospheric studies (pp. 119-140). Springer,<br> Dordrecht.</p>
Force propagation between epithelial cell doublets
<p>Cell-generated forces play a major role in coordinating the large-scale behavior of cell assemblies, in particular during development, wound healing and cancer. Mechanical signals propagate faster than biochemical signals but can have similar effects, especially in epithelial tissues with strong cell-cell adhesion. However, a quantitative description of the transmission chain from force generation in a sender cell, force propagation across cell-cell boundaries, and the concomitant response of receiver cells is missing. For a quantitative analysis of this important situation, here we propose a minimal model system of two epithelial cells on an H-pattern ("cell doublet"). After optogenetically activating RhoA, a major regulator of cell contractility, in the sender cell, we measure the mechanical response of the receiver cell by traction force and monolayer stress microscopies. In general, we find that the receiver cells show an active response so that the cell doublet forms a coherent unit. However, force propagation and response of the receiver cell also strongly depend on the mechano-structural polarization in the cell assembly, which is controlled by cell-matrix adhesion to the adhesive micropattern. We find that the response of the receiver cell is stronger when the mechano-structural polarization axis is oriented perpendicular to the direction of force propagation, reminiscent of the Poisson effect in passive materials. We finally show that the same effects are at work in small tissues. Our work demonstrates that cellular organization and active mechanical response of a tissue is key to maintaining signal strength and leads to the emergence of elasticity, which means that signals are not dissipated like in a viscous system but can propagate over large distances. </p>
Reuse of Model Transformations for Propagating Variability Annotations in Annotative Software Product Lines - Evaluation Data
<p>This package contains all data that was produced for and used in the doctoral thesis for evaluating commutativity of propagating annotations in model-driven product lines.<br> This includes the implementation that conducts the evaluation, the measured results, and the input subjects.</p>
Data from: Fatigue crack propagation in AA5083 structures additively manufactured via multi-layer friction surfacing
<p>This dataset contains the data for the publication " Fatigue crack propagation in AA5083 structures additively manufactured via multi-layer friction surfacing"</p>
Land-Locked Convection as a Barrier to MJO Propagation across the Maritime Continent
<p>This dataset contains the subset model output variables that were used to derive the results presented in the following publication:</p> <p>Savarin, A. & S. S. Chen (2023): Land-Locked Convection as a Barrier to MJO Propagation across the Maritime Continent. <em>Journal of Advances in Modeling Earth Systems</em>, 15, e2022MS003503. https://doi.org/10.1029/2022MS003503</p> <p>For the sake of saving space, the model output variables (file names starting with <em>uwincm_</em>) are separated into 2D fields (latitude, longitude, land mask, precipitation, and surface zonal winds) for the duration of model simulation and 3D fields (pressure, temperature, and 3D winds) for selected times used in the manuscript. </p> <p>Additionally, results of large-scale precipitation tracking for MJO are stored in the file names that begin with <em>lpt_. </em></p> <p>HYCOM (ocean model) bathymetry and surface temperature for initial conditions are stored in <em>HYCOM_IC_</em> files. </p> <p> </p>
Data of Two-fluid Modeling of Acoustic Wave Propagation in Gravitationally Stratified Isothermal Media
<p>Fully data of the paper "Two-fluid Modeling of Acoustic Wave Propagation in Gravitationally Stratified Isothermal Media" in the Astrophysical Journal.</p> <p>The Astrophysical Journal, 911:119 (18pp), 2021 April 20.</p>
Data from: Reverse plasticity underlies rapid evolution by clonal selection within populations of fibroblasts propagated on a novel soft substrate
<p>Mechanical properties such as substrate stiffness are a ubiquitous feature of a cell's environment. Many types of animal cells exhibit canonical phenotypic plasticity when grown on substrates of differing stiffness, in vitro and in vivo. Whether such plasticity is a multivariate optimum due to hundreds of millions of years of animal evolution, or instead is a compromise between conflicting selective demands, is unknown. We addressed these questions by means of experimental evolution of populations of mouse fibroblasts propagated for approximately 90 cell generations on soft or stiff substrates. The ancestral cells grow twice as fast on stiff substrate as on soft substrate and exhibit the canonical phenotypic plasticity. Soft-selected lines derived from a genetically diverse ancestral population increased growth rate on soft substrate to the ancestral level on stiff substrate and evolved the same multivariate phenotype. The pattern of plasticity in the soft-selected lines was opposite of the ancestral pattern, suggesting that reverse plasticity underlies the observed rapid evolution. Conversely, growth rate and phenotypes did not change in selected lines derived from clonal cells. Overall, our results suggest that the changes were the result of genetic evolution and not phenotypic plasticity per se. Whole-transcriptome analysis revealed consistent differentiation between ancestral and soft-selected populations, and that both emergent phenotypes and gene expression tended to revert in the soft-selected lines. However, the selected populations appear to have achieved the same phenotypic outcome by means of at least two distinct transcriptional architectures related to mechanotransduction and proliferation.</p>
Software for optimizing treatment to slow the spatial propagation of invasive species: Code and results
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Data from: Reverse plasticity underlies rapid evolution by clonal selection within populations of fibroblasts propagated on a novel soft substrate
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Urbanization alters the song propagation of two human-commensal songbird species: Active space, amplitude, and attenuation code
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Force propagation between epithelial cell doublets
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Oblique extension favours propagation pulses during continental break-up, Models Results/code version/option file
<p>Models results, code version of pTatin3D used to produce these models and example option file to run the models.</p>
Large scale simulation of pressure induced phase-field fracture propagation using Utopia
<p>Utopia is an open-source C++ library for parallel non-linear multilevel solution strategies. Utopia provides the advantages of high-level programming interfaces while at same time a framework to access low level data-structures without breaking code encapsulation. Complex numerical procedures can be expressed with few lines of code, and evaluated by different implementations, libraries, or computing hardware. In this paper we investigate the parallel performance of our implementation of the recursive multilevel trust-region (RMTR) method based on the Utopia library. RMTR is a globally convergent multilevel solution strategy designed to solve non-convex constrained minimization problems. In particular, we solve pressure induced phase-field fracture propagation in large and complex fracture networks. Solving such problems is deemed challenging even for a few fractures, however, here we are considering realistic and idealized networks with up to 1000 fractures.</p>
Wave propagation of local earthquakess in a subduction zone
<p>The movie shows wave propagation simulations that we used to model the synthetic seismograms presented in the manuscript "Toward waveform-based characterization of slab & mantle wedge (SAM) earthquakes" by Felix Halpaap, Stéphane Rondenay, Qinya Liu, Florian Millet, Lars Ottemöller. The movie contains four panels, corresponding to four waveform simulations of earthquakes occurring (i, top left) in the mantle wedge, (ii, bottom left) on the subduction interface, (iii, top right) in the slab crust, (iv, bottom right) in the slab mantle. In the movie, the simulation runs are synchronized to show the P-wave arrival at a station vertically above the earthquake at the same time. The counter in the top left corner indicates the simulation time relative to the P-wave arrival at that station. To enhance the visibility of small-amplitude wavefronts, the color intensity of the wavefronts corresponds to a logarithmic scaling of the wavefront amplitudes, with wavefront amplitudes below 0.5 % muted. The amplitudes here correspond to the norm of the displacement vector (i.e., showing particle motion in the horizontal and vertical directions).</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.