Wideband acoustic immittance (WAI) measures are noninvasive diagnostic measurements that require an estimate of the ear canal's area at the measurement location. Yet, physical measurements of the area at WAI probe locations are lacking. Methods to measure ear-canal areas from silicone molds were developed and applied to 169 subjects, ages 18-75 years. The average areas at the canal's first bend and at 12 mm insertion depth, which are likely WAI probe locations, were 63.4 ± 13.5 and 61.6 ± 13.5 mm2, respectively. These areas are substantially larger than those assumed by current FDA-approved WAI measurement devices as well as areas estimated with acoustical methods or measured on cadaver ears. Left and right ears from the same subject had similar areas. Sex, height, and weight were not significant factors in predicting area. Age cohort was a significant predictor of area, with area increasing with decade of life. A subset of areas from the youngest female subjects did not show an effect of race on area (White or Chinese). Areas were also measured as a function of insertion depth of 4.8-13.2 mm from the canal entrance; area was largest closest to the canal entrance and systematically decreased with insertion depth.Microbubble-mediated ultrasound therapies have a common need for methods that can noninvasively monitor the treatment. One approach is to use the bubbles' acoustic emissions as feedback to the operator or a control unit. Current methods interpret the emissions' frequency content to infer the microbubble activities and predict therapeutic outcomes. However, different studies placed their sensors at different angles relative to the emitter and bubble cloud. Here, it is evaluated whether such angles influence the captured emissions such as the frequency content. In computer simulations, 128 coupled bubbles were sonicated with a 0.5-MHz, 0.35-MPa pulse, and the acoustic emissions generated by the bubbles were captured with two sensors placed at different angles. The simulation was replicated in experiments using a microbubble-filled gel channel (0.5-MHz, 0.19-0.75-MPa pulses). A hydrophone captured the emissions at two different angles. https://www.selleckchem.com/products/blebbistatin.html In both the simulation and the experiments, one angle captured periodic time-domain signals, which had high contributions from the first three harmonics. In contrast, the other angle captured visually aperiodic time-domain features, which had much higher harmonic and broadband content. Thus, by placing acoustic sensors at different positions, substantially different acoustic emissions were captured, potentially leading to very different conclusions about the treatment outcome.A hybrid time-frequency domain method for predicting insertion loss (IL) of intake systems is investigated with detailed evaluation and optimization in terms of acoustic performance and intake efficiency for an automotive engine intake system. Instead of progressively coupling of both domain variables, as in the existing hybrid methods, the proposed method uses frequency-domain source impedance to characterize the acoustic source, and a time-domain method to analyze the acoustic transmission. A simplified equation is derived to predict IL using noise reduction (NR) and acoustic impedance Zl rather than four-pole transfer matrices as used in the traditional frequency-domain method and hybrid-domain method. The NR and Zl of intake systems calculated by the time-domain method are used to predict IL for the first time. This hybrid method has advantages of requiring no numerical engine model while considering the convective and dissipative effect of intake flow on a complex intake system. The predicted ILs of a quarter-wavelength tube and an optimized air cleaner were validated with the measured results. The proposed method and results are applicable and useful to the design of an intake system at an early stage of engine development.High temperature structural acoustic sensors play an important role in many applications. Fused quartz waveguide is a popular choice due to its resistance to harsh environments and its convenience of modification. However, time of flight between pulse and echo, which is widely used in these sensors, tends to encounter drifts in fast temperature changing process even after temperature returns to initial value. In this article, different annealing process are performed for a special modified fused quartz waveguide with a sensor node. Annealing treatment is found able to reduce the drift when the waveguide undergoes a sudden temperature spike to 1000 °C at 500 kHz operating acoustic frequency, and the best annealing condition could make the drift one magnitude smaller. A following temperature test up to 1000 °C shows consistent measurement readings.This work aims to predict speech intelligibility against harmonic maskers. Unlike noise maskers, harmonic maskers (including speech) have a harmonic structure that may allow for a release from masking based on fundamental frequency (F0). Mechanisms, such as spectral glimpsing and harmonic cancellation, have been proposed to explain F0 segregation, but their relative contributions and ability to predict behavioral data have not been explored. A speech intelligibility model was developed that includes both spectral glimpsing and harmonic cancellation. The model was used to fit the data of two experiments from Deroche, Culling, Chatterjee, and Limb [J. Acoust. Soc. Am. 135, 2873-2884 (2014)], in which speech reception thresholds were measured for stationary harmonic maskers varying in their F0 and degree of harmonicity. Key model parameters (jitter in the masker F0, shape of the cancellation filter, frequency limit for cancellation, and signal-to-noise ratio ceiling) were optimized by maximizing the correspondence between the predictions and data. The model was able to accurately describe the effects associated with varying the masker F0 and harmonicity. Across both experiments, the correlation between data and predictions was 0.99, and the mean and largest absolute prediction errors were lower than 0.5 and 1 dB, respectively.A listening test is proposed in which human participants detect talker changes in two natural, multi-talker speech stimuli sets-a familiar language (English) and an unfamiliar language (Chinese). Miss rate, false-alarm rate, and response times (RT) showed a significant dependence on language familiarity. Linear regression modeling of RTs using diverse acoustic features derived from the stimuli showed recruitment of a pool of acoustic features for the talker change detection task. Further, benchmarking the same task against the state-of-the-art machine diarization system showed that the machine system achieves human parity for the familiar language but not for the unfamiliar language.