There was no evidence of a group difference in RFM in either paradigm.P-wave conversion to slow diffusion (Biot) modes at mesoscopic (small-scale) inhomogeneities in porous media is believed to be the most important attenuation mechanisms at seismic frequencies. This study considers three periodic thin layers saturated with gas, oil, and water, respectively, a realistic scenario in hydrocarbon reservoirs, and perform finite-element numerical simulations to obtain the wave velocities and quality factors along the direction perpendicular to layering.  https://www.selleckchem.com/products/npd4928.html  The results are validated by comparison to the Norris-Cavallini analytical solution, constituting a cross-check for both theory and numerical simulations. The approach is not restricted to partial saturation but also applies to relevant properties in reservoir geophysics, such as porosity and permeability heterogeneities. This paper considers two cases, namely, the same rock skeleton and different fluids, and the same fluid and different dry-rock properties. Unlike the two-layer case (two fluids), the results show two relaxation peaks and the agreement between numerical and analytical solutions is excellent.Listeners often experience challenges understanding an interlocutor (target) in the presence of competing talkers (maskers). However, during linguistic release from masking (LRM), this difficulty decreases for native language targets (English) when paired with different language maskers (e.g., Dutch). There is considerable evidence that the linguistic similarity between target-masker pairs determines the size of LRM. This study investigated whether and how LRM is affected when the streams also differed in talker sex. Experiment 1 investigated intelligibility for English targets in sex-matched and mismatched conditions with Dutch or English maskers. While typical LRM effects were obtained when sex was matched, opposite effects were detected when sex was mismatched. In experiment 2, Mandarin maskers were used to increase linguistic dissimilarity and elicit stronger LRM effects. Despite the greater linguistic dissimilarity, the surprising reverse LRM effect in the sex-mismatch condition persisted. In experiment 3, the target stream was held constant and talker sex and language were manipulated in the masker. Here, expected LRM effects were obtained for both the sex-matched and sex-mismatched conditions. This indicated that the locus of the dissimilarities and not just relative properties affect LRM. Broadly, this study suggests that using naturally varying listening situations advances understanding of factors underlying LRM.Materials with sub-wavelength asymmetry and long-range order have recently been shown to demonstrate acoustical properties analogous to electromagnetic bianisotropy. One characteristic of bianisotropic acoustic media is the existence of direction-dependent acoustic impedance. Therefore, the magnitude and phase of the acoustic fields transmitted through bianisotropic acoustic media are dependent on the direction of bianisotropic polarization. These materials can therefore be used as acoustic metasurfaces to control acoustic fields. To demonstrate this behavior, a numerical model of bianisotropic acoustic waveguides is utilized to design a lens that focuses an incident plane wave by only manipulating the orientation of the bianisotropic coupling vector.This paper investigates the problem of dim frequency line detection and recovery in the so-called lofargram. Theoretically, long enough time integration can always enhance the detection characteristic. But this does not hold for irregularly fluctuating lines. Deep learning has been shown to perform very well for sophisticated visual inference tasks. With the composition of multiple processing layers, very complex high level representations that amplify the important aspects of input while suppressing irrelevant variations can be learned. Hence, DeepLofargram is proposed, composed of a deep convolutional neural network and its visualization counterpart. Plugging into specifically designed multi-task loss, an end-to-end training jointly learns to detect and recover the spatial location of potential lines. Leveraging on this deep architecture, performance limits of low SNR can be achieved as low as -24 dB on average and -26 dB for some. This is far beyond the perception of human vision and significantly improves the state-of-the-art.Measurements of the phase velocity of compressional sound waves in water-saturated granular materials are reported for the 1.0-2.0 MHz frequency range. The sound speed estimates are based on travel times through granular layer thicknesses ranging from 8 to 17 mm. Three types of granular media were used 336 μm median diameter glass beads and two natural sands with median diameters of 219 and 406 μm. These grain sizes and frequency range correspond to 0.5 0.5. Scaling the data by a factor depending on porosity and grain density reduces the spread among the available phase speed estimates by nearly a factor of 2, from 12.5% to 6.9%.Convincing simulation of diffraction around obstacles is critical in modeling sound propagation in virtual environments. Due to the computational complexity of large-scale wavefield simulations, ray-based models of diffraction are used in real-time interactive multimedia applications. Among popular diffraction models, the Biot-Tolstoy-Medwin (BTM) edge diffraction model is the most accurate, but it suffers from high computational complexity and hence is difficult to apply in real time. This paper introduces an alternative ray-based approach to approximating diffraction, called Volumetric Diffraction and Transmission (VDaT). VDaT is a volumetric diffraction model, meaning it performs spatial sampling of paths along which sound can traverse the scene around obstacles. VDaT uses the spatial sampling results to estimate the BTM edge-diffraction amplitude response and path length, with a much lower computational cost than computing BTM directly. On average, VDaT matches BTM results within 1-3 dB over a wide range of size scales and frequencies in basic cases, and VDaT can handle small objects and gaps better than comparable state-of-the-art real-time diffraction implementations. A GPU-parallelized implementation of VDaT is shown to be capable of simulating diffraction on thousands of direct and specular reflection path segments in small-to-medium-size scenes, within strict real-time constraints and without any precomputed scene information.