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Differential Outcomes of Western along with Mediterranean-Type Diet plans on Gut Microbiota: A Metagenomics and also Metabolomics Strategy.
The truncation effects in the channel estimation are also investigated. Experimental data are used to validate the findings.It is difficult to localize the source of a tone in a room because standing waves lead to complicated interaural differences that become uninterpretable localization cues. This paper tests the conjecture that localization improves if the listener can move to explore the complicated sound field over space and time. Listener head and torso movements were free and uninstructed. Experiments at low and high frequencies with eight human listeners in a relatively dry room indicated some modest improvement when listeners were allowed to move, especially at high frequencies. The experiments sought to understand listener dynamic localization strategies in detail. Head position and orientation were tracked electronically, and ear-canal signals were recorded throughout the 9 s of each moving localization trial. https://www.selleckchem.com/products/px-12.html The availability of complete physical information enabled the testing of two model strategies (1) relative null strategy, using instantaneous zeros of the listener-related source angle; and (2) inferred source strategy, using a continuum of apparent source locations implied by the listener's instantaneous forward direction and listener-related source angle. The predicted sources were given weights determined by the listener motion. Both models were statistically successful in coping with a great variety of listener motions and temporally evolving cues.This article presents the study of a passive acoustic dataset recorded on the Chukchi Shelf from October 2016 to July 2017 during the Canada Basin Acoustic Propagation Experiment (CANAPE). The study focuses on the low-frequency (250-350 Hz) ambient noise (after individual transient signals are removed) and its environmental drivers. A specificity of the experimental area is the Beaufort Duct, a persistent warm layer intrusion of variable extent created by climate change, which favors long-range acoustic propagation. The Chukchi Shelf ambient noise shows traditional polar features it is quieter and wind force influence is reduced when the sea is ice-covered. However, the study reveals two other striking features. First, if the experimental area is covered with ice, the ambient noise drops by up to 10 dB/Hz when the Beaufort Duct disappears. Further, a large part of the noise variability is driven by distant cryogenic events, hundreds of kilometers away from the acoustic receivers. This was quantified using correlations between the CANAPE acoustic data and distant ice-drift magnitude data (National Snow and Ice Data Center).Acoustic metamaterials are becoming promising solutions for many industry applications, but the gap between theory and practice is still difficult to close. This research proposes an optimization methodology of acoustic metamaterial designs for sound insulation that aims to start bridging this gap. The proposed methodology takes advantage of a hybrid analytical-numerical approach for computing the sound transmission loss of the designs efficiently. As a result, the implementation of optimization techniques on numerical model designs becomes practically possible. This is exemplified with two test cases (i) optimization of the sound transmission loss of a single gypsum board panel and (ii) optimization of the noise reduction of outdoor HVAC units. Two resonator designs, one used previously for sound radiation in flat panel speakers and the other for enhancing the sound transmission loss at the mass-air-mass resonance of double panels, are here optimized for the two test cases. This shows how an existing resonator can be adapted for new purposes, thus making the design of acoustic metamaterials efficient. The optimized metamaterials outperform the original designs as well as traditional approaches to sound insulation.In this paper, a meta-learning-based underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) system is proposed to deal with the environment mismatch in real-world UWA applications, which can effectively drive the model from the given UWA environment to the new UWA environment with a relatively small amount of data. With meta-learning, we consider multiple UWA environments as multi-UWA-tasks, wherein the meta-training strategy is utilized to learn a robust model from previously observed multi-UWA-tasks, and it can be quickly adapted to the unknown UWA environment with only a small number of updates. The experiments with the at-sea-measured WATERMARK dataset and the lake trial indicate that, compared with the traditional UWA-OFDM system and the conventional machine learning-based framework, the proposed method shows better bit error rate performance and stronger learning ability under various UWA scenarios.Large scale studies of underwater noise during rain are important for assessing the ocean environment and enabling remote sensing of rain rates over the open ocean. In this study, approximately 3.5 yrs of acoustical and meteorological data recorded at the northeast Pacific continental margin are evaluated. The acoustic data are recorded at a sampling rate of 64 kHz and depths of 81 and 581 m at the continental shelf and slope, respectively. Rain rates and wind speeds are provided by surface buoys located in the vicinity of each hydrophone. Average power spectra have been computed for different rain rates and wind speeds, and linear and nonlinear regression have been performed. The main findings are (1) the linear regression slopes highly depends on the frequency range, rain rate, wind speed, and measurement depth; (2) noise levels during rain between 200 Hz and 10 kHz significantly increase with increasing wind speed; and (3) the highest correlation between the spectral level and rain rate occurs at 13 kHz, thus, coinciding with the spectral peak due to small raindrops. The results of this study indicate that previously proposed algorithms for estimating rain rates from acoustic data are not universally applicable but rather have to be adapted for different locations.A psychophysical experiment was conducted to perceptually validate several spectral audio features through ordinal scaling spectral centroid, spectral spread, spectral skewness, odd-to-even harmonic ratio, spectral slope, and harmonic spectral deviation. Several sets of stimuli per audio feature were synthesized at different fundamental frequencies and spectral centroids by controlling (wherever possible) each spectral feature independently of the others, thus isolating the effect that each feature had on the stimulus rankings within each sound set. Listeners were overall able to order stimuli varying along all the spectral features tested when presented with an appropriate spacing of feature values. For specific cases of stimuli in which the ordering task partially failed, psychophysical interpretations are provided to explain listeners' confusions. The results of the ordinal scaling experiment outline trajectories of spectral features that correspond to listeners' perceptions and suggest a number of sound synthesis parameters that could carry timbral contour information.
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