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121 results for “Surface Wave”
Geometric Model Wave Surface
* This white plaster model of the outer shell of a Fresnel wave surface for a biaxial crystal consists of two pieces that fit together. Parts of two small and two larger circles are drawn on the surface. * *(метка 9)* Source: Objaverse 1.0 / Sketchfab
Data for "Hunting for gravity waves in non-orographic winter storms using 3+ years of regional surface air pressure networks and radar observations"
<p>These data are shown in the figures included with the article "Hunting for gravity waves in non-orographic winter storms using 3+ years of regional surface air pressure networks and radar observations," submitted to Atmospheric Chemistry and Physics.</p>
Research Data - Magnetic Field Controlled Surface Localization of Spin-Wave Ferromagnetic Resonance Modes in 3D Nanostructures
<p>Source data from micromagnetic simulations performed in COMSOL Multiphysics software and Python codes for data post-processing utilized in the paper "Magnetic Field Controlled Surface Localization of Spin-Wave Ferromagnetic Resonance Modes in 3D Nanostructures."</p> <p>The files from Comsol (.mph) are without simulation solutions due to their large size - please contact me if needed.</p>
Retrieving 2D laterally varying structures from multi-station surface wave dispersion curves using multiscale window analysis
<p>Here are the waveform data used in the Geophysical Journal International paper entitled "Retrieving 2D laterally varying structures from multi-station surface wave dispersion curves using multiscale window analysis". The dataset is used for the reader who wants to reproduce the result in the paper.</p>
Waveform Data for paper "Eikonal surface-wave phase-velocity tomography of continental China"
<p>The files uploaded here contain the vertical component records of earthquakes used to measure Rayleigh wave phase velocities in continental China.</p>
Dataset of: "Surface-Wave Dispersion in Partially Saturated Soils: the Role of Capillary Forces"
<p>This package contains the dataset of the paper entitled: Surface-Wave Dispersion in Partially Saturated Soils: the Role of Capillary Forces. Further information is given in the README files located within each folder.</p>
Attenuating surface gravity waves with mechanical metamaterials
<p>Videos showing simulations of one or more submerged oscillators attenuating surface gravity waves, related to the publication </p> <p><a href="https://aip.scitation.org/author/de+Vita%2C+F">F. De Vita</a><em>, </em><a href="https://aip.scitation.org/author/de+Lillo%2C+F">F. De Lillo</a><em>, </em><a href="https://aip.scitation.org/author/Bosia%2C+F">F. Bosia</a><em>, and </em><a href="https://aip.scitation.org/author/Onorato%2C+M">M. Onorato</a>, "Attenuating surface gravity waves with mechanical metamaterials", Physics of Fluids 33, 047113 (2021) <a href="https://doi.org/10.1063/5.0048613">https://doi.org/10.1063/5.0048613</a></p> <p>Also included are Data relative to Figs. 3, 5, 6, 8 and gnuplot scripts to generate the figures.</p>
Dataset for "Surf-Net: A deep-learning-based method for extracting surface-wave dispersion curves"
<p>dataset for the article "Surf-Net: A deep-learning-based method for extracting surface-wave dispersion curves"<br> corrLSynV8.h5: the generated synthetic waveform<br> dispersion.tar : the dispersion curves set for the generated synthetic waveform; the dispersion curves extracted in Northeast China; the dispersion curves extracted in Southeast China</p>
Simulation datasets for: Intense surface winds from gravity wave breaking in simulations of a destructive macroburst
<p>Shortly after 0600 UTC (midnight local time) 9 June 2020, a convective line produced severe winds across parts of northeast Colorado that caused extensive damage, especially in the town of Akron. High-resolution observations showed gusts exceeding 50 m s<sup>−1</sup>, accompanied by extremely large pressure fluctuations, including a 5-hPa pressure surge in 19 s immediately following the strongest winds and a 15-hPa pressure drop in the following 3 min. Numerical simulations of this event (using the WRF Model) and with horizontally homogeneous initial conditions (using Cloud Model 1) reveal that the severe winds in this event were associated with gravity wave dynamics. In a very stable postfrontal environment, elevated convection initiated and led to a long-lived gravity wave. Strong low-level vertical wind shear supported the amplification and eventual breaking of this wave, resulting in at least two sequential strong downbursts. This wave-breaking mechanism is different from the usual downburst mechanism associated with negative buoyancy resulting from latent cooling. The model output reproduces key features of the high-resolution observations, including similar convective structures, large temperature and pressure fluctuations, and intense near-surface wind speeds. The findings of this study reveal a series of previously unexplored mesoscale and storm-scale processes that can result in destructive winds.</p> <p><strong>Significance Statement </strong></p> <p>Downbursts of intense wind can produce significant damage, as was the case on 9 June 2020 in Akron, Colorado. Past research on downbursts has shown that they occur when raindrops, graupel, and hail in thunderstorms evaporate and melt, cooling the air and causing it to sink rapidly. In this research, we used numerical models of the atmosphere, along with high-resolution observations, to show that the Akron downburst was different. Unlike typical lines of thunderstorms, those responsible for the Akron macroburst produced a wave in the atmosphere, which broke, resulting in rapidly sinking air and severe surface winds.</p>
Data from: A surface acoustic wave (SAW)-based lab-on-chip for the detection of active α-glycosidase
Enzyme detection in liquid samples is a complex laboratory procedure, based on assays that are generally time- and cost-consuming, and require specialized personnel. Surface acoustic wave sensors can be used for this application, overcoming the cited limitations. To give our contribution, in this work we present the bottom-up development of a surface acoustic wave biosensor to detect active α-glycosidase in aqueous solutions. Our device, optimized to work at an ultra-high frequency (around 740 MHz), is functionalized with a newly synthesized probe 7-mercapto-1-eptyl-D-maltoside, bringing one maltoside terminal moiety. The probe is designed ad hoc for this application and tested in-cuvette to analyze the enzymatic conversion kinetics at different times, temperatures and enzyme concentrations. Preliminary data are used to optimize the detection protocol with the SAW device. In around 60 min, the SAW device is able to detect the enzymatic conversion of the maltoside unit into glucose in the presence of the active enzyme. We obtained successful α-glycosidase detection in the concentration range 0.15–150 U/mL, with an increasing signal in the range up to 15 U/mL. We also checked the sensor performance in the presence of an enzyme inhibitor as a control test, with a signal decrease of 80% in the presence of the inhibitor. The results demonstrate the synergic effect of our SAW Lab-on-a-Chip and probe design as a valid alternative to conventional laboratory tests.
Data from: Surface Acoustic Wave-based Lab-On-a-Chip for the fast detection of Legionella pneumophila in water
<p><span>Surface acoustic wave (SAW) -based immuno-biosensors are used for several applications, thanks to their versatility and faster response than conventional analytical methods. SAW immuno-biosensors can be usefully applied to promptly detect bacteria and prevent bacterial infections that can lead to severe diseases. Here, we present a SAW immuno-biosensor to detect <em>Legionella</em> <em>pneumophila</em> in water. Our device, working at ultra-high frequency (740 MHz), is functionalized with an anti-<em>L</em>. <em>pneumophila</em> antibody to maximize the specificity. We report the characteristic curve of the sensor, calculated measuring bacterial samples at known densities, and its related parameters. We also measure <em>L</em>. <em>pneumophila</em> samples contaminated with different Gram-positive and Gram-negative bacterial species (<em>Escherichia</em> <em>coli</em> and <em>Enterococcus</em> <em>faecium</em>) and samples diluted in mains waters. The proposed device is able to detect <em>L</em>. <em>pneumophila</em> in the range from 1</span><span>×</span><span>10<sup>6</sup> to 1</span><span>×</span><span>10<sup>8</sup> CFU/mL, with a limit of blank of 1.22</span><span>×</span><span>10<sup>6</sup> CFU/mL and a limit of detection of 2.01</span><span>×</span><span>10<sup>6</sup> CFU/mL. The nonspecific signal due to contaminant bacteria is very limited and measurements of <em>L</em>. <em>pneumophila</em> are not affected by contamination. We obtain a good detection also in mains water, representing a realistic matrix for <em>L</em>. <em>pneumophila</em>. Our results are encouraging and pave the way to the use of fast, easy-to-use, reliable and precise sensors to prevent bacterial infections in human activities.</span></p>
Velocity models from "Investigation of Martian regional crustal structure near the dichotomy using S1222a surface-wave group velocities"
<p>The isotropic velocity models from joint inversion of Rayleigh- and Love-wave group-velocity measurements of S1222a. The details about these models and the joint inversion are in "Investigation of Martian regional crustal structure near the dichotomy using S1222a surface-wave group velocities" which is submitted to GRL.</p>
Mode characterization and sensitivity evaluation of an ultra-high-frequency surface acoustic wave (UHF-SAW) resonator biosensor: application to the glial-fibrillary-acidic-protein (GFAP) biomarker detection
<p>Biosensors detect specific bio-analytes by generating a measurable signal from the interaction between the sensing element and the target molecule. Surface acoustic wave (SAW) biosensors offer unique advantages due to their high sensitivity, real-time response capability, and label-free detection. The typical SAW modes are the Rayleigh mode and the shear-horizontal mode. Both present pros and cons for biosensing applications and generally need different substrates and device geometries to be efficiently generated. This study investigates and characterizes ultra-high-frequency (UHF-) SAW resonator biosensors. It reveals the simultaneous presence of the two typical SAW modes, clearly separated in frequency, called slow and fast. The two modes are studied by numerical simulations and biosensing experiments with the glial-fibrillary-acidic-protein (GFAP) biomarker. The slow mode is generally more sensitive to changes in surface properties, such as temperature and mass changes, by a factor of about 1.4 with respect to the fast mode.</p>
Data from: Surface Acoustic Wave-based Lab-On-a-Chip for the fast detection of Legionella pneumophila in water
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Simulation datasets for: Intense surface winds from gravity wave breaking in simulations of a destructive macroburst
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Data from: Validation of surface wave spectral measurements from velocity profiling floats
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Statistics of bubble plumes generated by breaking surface waves
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Dielectric induced surface wave radiation loss
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Data from: A surface acoustic wave (SAW)-based lab-on-chip for the detection of active α-glycosidase
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Data on frequency-wavenumber spectra of water waves from videos of the river surface: River Sheaf, UK, Feb-Jun 2019
<p>This data set contains sequences of orthorectified images of the free surface of the River Sheaf, Sheffield, United Kingdom (Latitude: 53.373056$^\circ$ Longitude: -1.463913$^\circ$ (WGS 84)), recorded between February and June 2019, as well as their 3D space-time Fourier power spectrum, and gauging survey data of the stage and flow discharge.</p>
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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.