A sophisticated, multi-channel data acquisition and processing system for high frequency noise research

A sophisticated, multi-channel computerized data acquisition and processing system was developed at the NASA LeRC for use in noise experiments. This technology, which is available for transfer to industry, provides a convenient, cost-effective alternative to analog tape recording for high frequency acoustic measurements. This system provides 32-channel acquisition of microphone signals with an analysis bandwidth up to 100 kHz per channel. Cost was minimized through the use of off-the-shelf components. Requirements to allow for future expansion were met by choosing equipment which adheres to established industry standards for hardware and software. Data processing capabilities include narrow band and 1/3 octave spectral analysis, compensation for microphone frequency response/directivity, and correction of acoustic data to standard day conditions. The system was used successfully in a major wind tunnel test program at NASA LeRC to acquire and analyze jet noise data in support of the High Speed Civil Transport (HSCT) program

Propfan Test Assessment (PTA): Flight test report

The Propfan Test Assessment (PTA) aircraft was flown to obtain glade stress and noise data for a 2.74m (9 ft.) diameter single rotation propfan. Tests were performed at Mach numbers to 0.85 and altitudes to 12,192m (40,000 ft.). The propfan was well-behaved structurally over the entire flight envelope, demonstrating that the blade design technology was completely adequate. Noise data were characterized by strong signals at blade passage frequency and up to 10 harmonics. Cabin noise was not so high as to preclude attainment of comfortable levels with suitable wall treatment. Community noise was not excessive

Convolutional neural network for breathing phase detection in lung sounds

We applied deep learning to create an algorithm for breathing phase detection in lung sound recordings, and we compared the breathing phases detected by the algorithm and manually annotated by two experienced lung sound researchers. Our algorithm uses a convolutional neural network with spectrograms as the features, removing the need to specify features explicitly. We trained and evaluated the algorithm using three subsets that are larger than previously seen in the literature. We evaluated the performance of the method using two methods. First, discrete count of agreed breathing phases (using 50% overlap between a pair of boxes), shows a mean agreement with lung sound experts of 97% for inspiration and 87% for expiration. Second, the fraction of time of agreement (in seconds) gives higher pseudo-kappa values for inspiration (0.73-0.88) than expiration (0.63-0.84), showing an average sensitivity of 97% and an average specificity of 84%. With both evaluation methods, the agreement between the annotators and the algorithm shows human level performance for the algorithm. The developed algorithm is valid for detecting breathing phases in lung sound recordings

Thinking Inside the Box: A New Integrated Approach to Mixed Music Composition and Performance

The Thinking Inside the Box project (TItB) seeks to address pragmatic concerns inherent to mixed music performance, and proposes ways to better consider the sound of the acoustic reality of the concert space at studio composition time. This is achieved through empirical investigation into subversive use of recent developments in hardware and software technologies. The primary concerns are (1) optimising the integration of live instruments and electroacoustic sound in the concert hall environment for both the performers and the public, by carefully choosing loudspeaker types and placement at commission time, and by avoiding sound reinforcement; (2) minimizing for studio composers the insitu trauma of the first live rendition of the piece, by bringing the concert hall acoustic environment into the studio composition process, using convolution reverb to reproduce in the studio the given loudspeaker setup through its impulse responses. This paper presents the conclusions of the project's early experiments in the form of three case study sets, and describes how this approach will be of use for any composer of mixed music

Comprehension of familiar and unfamiliar native accents under adverse listening conditions

This study aimed to determine the relative processing cost associated with comprehension of an unfamiliar native accent under adverse listening conditions. Two sentence verification experiments were conducted in which listeners heard sentences at various signal-to-noise ratios. In Experiment 1, these sentences were spoken in a familiar or an unfamiliar native accent or in two familiar native accents. In Experiment 2, they were spoken in a familiar or unfamiliar native accent or in a nonnative accent. The results indicated that the differences between the native accents influenced the speed of language processing under adverse listening conditions and that this processing speed was modulated by the relative familiarity of the listener with the native accent. Furthermore, the results showed that the processing cost associated with the nonnative accent was larger than for the unfamiliar native accent

Translational outcomes in a full gene deletion of ubiquitin protein ligase E3A rat model of Angelman syndrome.

Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by developmental delay, impaired communication, motor deficits and ataxia, intellectual disabilities, microcephaly, and seizures. The genetic cause of AS is the loss of expression of UBE3A (ubiquitin protein ligase E6-AP) in the brain, typically due to a deletion of the maternal 15q11-q13 region. Previous studies have been performed using a mouse model with a deletion of a single exon of Ube3a. Since three splice variants of Ube3a exist, this has led to a lack of consistent reports and the theory that perhaps not all mouse studies were assessing the effects of an absence of all functional UBE3A. Herein, we report the generation and functional characterization of a novel model of Angelman syndrome by deleting the entire Ube3a gene in the rat. We validated that this resulted in the first comprehensive gene deletion rodent model. Ultrasonic vocalizations from newborn Ube3am-/p+ were reduced in the maternal inherited deletion group with no observable change in the Ube3am+/p- paternal transmission cohort. We also discovered Ube3am-/p+ exhibited delayed reflex development, motor deficits in rearing and fine motor skills, aberrant social communication, and impaired touchscreen learning and memory in young adults. These behavioral deficits were large in effect size and easily apparent in the larger rodent species. Low social communication was detected using a playback task that is unique to rats. Structural imaging illustrated decreased brain volume in Ube3am-/p+ and a variety of intriguing neuroanatomical phenotypes while Ube3am+/p- did not exhibit altered neuroanatomy. Our report identifies, for the first time, unique AS relevant functional phenotypes and anatomical markers as preclinical outcomes to test various strategies for gene and molecular therapies in AS