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Objective/Hypothesis Vocal fold vibration is associated with four distinct vibratory patterns: those of the right-upper, right-lower, left-upper, and left-lower vocal fold lips. The purpose of this study was to propose a least squares method to quantify the vibratory properties of each of the four vocal fold lips via videokymography (VKG). Study Design This was a methodological study designed to examine the impact of subglottal pressure and line-scan position on mucosal wave parameters. Methods VKG, a line-scan imaging technique, has proven to be an effective method for studying vocal fold vibratory patterns. This study used VKG images and an automatic mucosal wave extraction method to examine the vibration of each individual vocal fold lip of 17 excised canine larynges under differing subglottal pressures and line-scan positions. Results Varying subglottal pressure led to results consistent with previous studies. Examination of the vocal folds at different line-scan positions along its length revealed that amplitude is greatest at the midpoint of the vocal fold, followed by the anterior portion of the vocal fold, with the posterior portion having the lowest amplitude (P < .001). Frequency and phase delay did not change significantly throughout the length of the vocal fold. Conclusions The method used in this study allows for easy determination of four sets of vibratory parameters, and examination of the effect of biomechanical parameters on vocal fold vibrations.

This paper considers uplink massive MIMO systems with 1-bit analog-to-digital converters (ADCs) and develops a deep-learning based channel estimation framework. In this framework, the prior channel estimation observations and deep neural network models are leveraged to learn the non-trivial mapping from quantized received measurements to channels. For that, we derive the sufficient length and structure of the pilot sequence to guarantee the existence of this mapping function. This leads to the interesting, and counter-intuitive, observation that when more antennas are employed by the massive MIMO base station, our proposed deep learning approach achieves better channel estimation performance, for the same pilot sequence length. Equivalently, for the same channel estimation performance, this means that when more antennas are employed, fewer pilots are required. This observation is also analytically proved for some special channel models. Simulation results confirm our observations and show that more antennas lead to better channel estimation both in terms of the normalized mean squared error and the achievable signal-to-noise ratio per antenna.

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Objective: We aim to examine the abilities of objective acoustic analysis methods (nonlinear dynamic and traditional perturbation measures) to describe voices from individuals with vocal nodules and polyps. Subjects and Methods: Sustained vowel recordings from normal subjects, patients with vocal nodules, and patients with vocal polyps were analyzed. Perturbation measures of jitter and shimmer were obtained with the Multi-Dimensional Voice Program (MDVP) and CSpeech. Signal-to-noise ratio was calculated using CSpeech. Nonlinear dynamic measures of phase space reconstruction and correlation dimension were also applied to analyze the voices. Results: A significant difference between normal and polyp groups was found in jitter and shimmer obtained from MDVP, as well as in jitter and signal-to-noise ratio from CSpeech. However, no parameters significantly differentiated between normal and nodule groups. Shimmer from CSpeech did not reveal any significant differences among any of the groups. Correlation dimension values for the nodule and polyp groups were significantly higher than the normal group. Conclusion: Nonlinear dynamic analysis has great potential value for the characterization of voice from patients with vocal nodules and polyps. The combination of traditional perturbation and nonlinear dynamic measures may improve our ability to provide objective clinical analysis of voices with vocal mass lesions.

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We formulate reverse-time migration (RTM) based on the theory of true-amplitude migration, and we give formulations for true-amplitude RTM angle-domain common-image gathers. Then we address some implementation issues for RTM. Specifically, we compare RTM's efficiency using different orders of finite differencing along the time direction. Finally, we propose "harmonic-source migration", a phase-encoding technique that allows increased efficiency in a delayed-shot implementation of RTM.

The commercial implementation of aqueous Zn-ion batteries is being impeded by the rampant dendrite growth and exacerbated side reactions on the Zn metal anodes. Herein, a 60 nm artificial protective layer with spatial dielectric–metallic gradient composition (denoted as GZH) is developed via Zn and HfO2 cosputtering. In this design, the top HfO2 layer with high permittivity and low electronic conductivity effectively suppresses hydrogen evolution. The intermediate Zn-rich oxide region promotes the dendrite-free Zn deposition and reinforces the contact between Zn and the sputtered layer. This design allows stable battery operation at high currents. Symmetric cells with Zn-GZH exhibit stable voltage separation over 500 h at 10 mA cm–2 with a cutoff capacity of 5 mAh cm–2. When paired with a vanadate cathode, the full-cell battery delivers a capacity retention of around 75% after 2000 cycles. This design concept may apply to other aqueous metal batteries.