Method and System for Creating Three-Dimensional Spatial Audio

A system and method for rendering a virtual sound source using a plurality of speakers in an arbitrary arrangement includes expanding a wave field of the virtual sound source and a composite wave field generated by the plurality of speakers into multi-pole expansions, and equating the multi-pole expansions to each other to form a continuous equation. A set of constraints is applied to the continuous equation that minimize an error in a sweet spot region resulting in a linear system of equations. The linear system of equations is solved using singular-value decomposition to arrive at a pseudo-inverse representing a multi-dimensional transfer function between the virtual sound source and the plurality of speakers. The multi-dimensional transfer function is then applied to a signal of the virtual sound source to render the virtual sound source in the sweet spot region using the plurality of speakers in the arbitrary arrangement

Coherent Flaw Reflectivity Estimation in Nonstationary Noise

This paper presents a model for RF broadband ultrasonic A-scans obtained from materials composed of microstructures, in which isolated flaws or impurities may exist. The model incorporates both the RF phase and magnitude differences between the microstructure and coherent flaw echo spectra. An adaptive implementation of the maximum-likelihood estimator (MLE) is presented for estimating A-scan amplitudes associated with coherent scatterers embedded in grain echoes. The adaptive implementation is motivated by the nonstationary behavior of the back-scattered energy received over the duration of the A-scan [1]. This nonstationarity results from the frequency dependent absorption, scattering, and diffraction that occurs as the pulse propagates through the materia

Effects of Vocal Fold Nodules on Glottal Cycle Measurements Derived from High-Speed Videoendoscopy in Children

The goal of this study is to quantify the effects of vocal fold nodules on vibratory motion in children using high-speed videoendoscopy. Differences in vibratory motion were evaluated in 20 children with vocal fold nodules (5–11 years) and 20 age and gender matched typically developing children (5–11 years) during sustained phonation at typical pitch and loudness. Normalized kinematic features of vocal fold displacements from the mid-membranous vocal fold point were extracted from the steady-state high-speed video. A total of 12 kinematic features representing spatial and temporal characteristics of vibratory motion were calculated. Average values and standard deviations (cycle-to-cycle variability) of the following kinematic features were computed: normalized peak displacement, normalized average opening velocity, normalized average closing velocity, normalized peak closing velocity, speed quotient, and open quotient. Group differences between children with and without vocal fold nodules were statistically investigated. While a moderate effect size was observed for the spatial feature of speed quotient, and the temporal feature of normalized average closing velocity in children with nodules compared to vocally normal children, none of the features were statistically significant between the groups after Bonferroni correction. The kinematic analysis of the mid-membranous vocal fold displacement revealed that children with nodules primarily differ from typically developing children in closing phase kinematics of the glottal cycle, whereas the opening phase kinematics are similar. Higher speed quotients and similar opening phase velocities suggest greater relative forces are acting on vocal fold in the closing phase. These findings suggest that future large-scale studies should focus on spatial and temporal features related to the closing phase of the glottal cycle for differentiating the kinematics of children with and without vocal fold nodules

Assessment of a non-invasive high-throughput classifier for behaviours associated with sleep and wake in mice

This work presents a non-invasive high-throughput system for automatically detecting characteristic behaviours in mice over extended periods of time, useful for phenotyping experiments. The system classifies time intervals on the order of 2 to 4 seconds as corresponding to motions consistent with either active wake or inactivity associated with sleep. A single Polyvinylidine Difluoride (PVDF) sensor on the cage floor generates signals from motion resulting in pressure. This paper develops a linear classifier based on robust features extracted from normalized power spectra and autocorrelation functions, as well as novel features from the collapsed average (autocorrelation of complex spectrum), which characterize transient and periodic properties of the signal envelope. Performance is analyzed through an experiment comparing results from direct human observation and classification of the different behaviours with an automatic classifier used in conjunction with this system. Experimental results from over 28.5 hours of data from 4 mice indicate a 94% classification rate relative to the human observations. Examples of sequential classifications (2 second increments) over transition regions between sleep and wake behaviour are also presented to demonstrate robust performance to signal variation and explain performance limitations

Diffuse Brain Injury Induces Acute Post-Traumatic Sleep

Objective Clinical observations report excessive sleepiness immediately following traumatic brain injury (TBI); however, there is a lack of experimental evidence to support or refute the benefit of sleep following a brain injury. The aim of this study is to investigate acute post-traumatic sleep. Methods Sham, mild or moderate diffuse TBI was induced by midline fluid percussion injury (mFPI) in male C57BL/6J mice at 9:00 or 21:00 to evaluate injury-induced sleep behavior at sleep and wake onset, respectively. Sleep profiles were measured post-injury using a non-invasive, piezoelectric cage system. In separate cohorts of mice, inflammatory cytokines in the neocortex were quantified by immunoassay, and microglial activation was visualized by immunohistochemistry. Results Immediately after diffuse TBI, quantitative measures of sleep were characterized by a significant increase in sleep (\u3e50%) for the first 6 hours post-injury, resulting from increases in sleep bout length, compared to sham. Acute post-traumatic sleep increased significantly independent of injury severity and time of injury (9:00 vs 21:00). The pro-inflammatory cytokine IL-1β increased in brain-injured mice compared to sham over the first 9 hours post-injury. Iba-1 positive microglia were evident in brain-injured cortex at 6 hours post-injury. Conclusion Post-traumatic sleep occurs for up to 6 hours after diffuse brain injury in the mouse regardless of injury severity or time of day. The temporal profile of secondary injury cascades may be driving the significant increase in post-traumatic sleep and contribute to the natural course of recovery through cellular repair

Nondestructive Detection of Codling Moth Infestation in Apples Using Pixel-Based NIR Hyperspectral Imaging with Machine Learning and Feature Selection

Codling moth (CM) (Cydia pomonella L.), a devastating pest, creates a serious issue for apple production and marketing in apple-producing countries. Therefore, effective nondestructive early detection of external and internal defects in CM-infested apples could remarkably prevent postharvest losses and improve the quality of the final product. In this study, near-infrared (NIR) hyperspectral reflectance imaging in the wavelength range of 900–1700 nm was applied to detect CM infestation at the pixel level for three organic apple cultivars, namely Gala, Fuji and Granny Smith. An effective region of interest (ROI) acquisition procedure along with different machine learning and data processing methods were used to build robust and high accuracy classification models. Optimal wavelength selection was implemented using sequential stepwise selection methods to build multispectral imaging models for fast and effective classification purposes. The results showed that the infested and healthy samples were classified at pixel level with up to 97.4% total accuracy for validation dataset using a gradient tree boosting (GTB) ensemble classifier, among others. The feature selection algorithm obtained a maximum accuracy of 91.6% with only 22 selected wavelengths. These findings indicate the high potential of NIR hyperspectral imaging (HSI) in detecting and classifying latent CM infestation in apples of different cultivars

Non-Destructive Technologies for Detecting Insect Infestation in Fruits and Vegetables under Postharvest Conditions: A Critical Review

In the last two decades, food scientists have attempted to develop new technologies that can improve the detection of insect infestation in fruits and vegetables under postharvest conditions using a multitude of non-destructive technologies. While consumers\u27 expectations for higher nutritive and sensorial value of fresh produce has increased over time, they have also become more critical on using insecticides or synthetic chemicals to preserve food quality from insects\u27 attacks or enhance the quality attributes of minimally processed fresh produce. In addition, the increasingly stringent quarantine measures by regulatory agencies for commercial import-export of fresh produce needs more reliable technologies for quickly detecting insect infestation in fruits and vegetables before their commercialization. For these reasons, the food industry investigates alternative and non-destructive means to improve food quality. Several studies have been conducted on the development of rapid, accurate, and reliable insect infestation monitoring systems to replace invasive and subjective methods that are often inefficient. There are still major limitations to the effective in-field, as well as postharvest on-line, monitoring applications. This review presents a general overview of current non-destructive techniques for the detection of insect damage in fruits and vegetables and discusses basic principles and applications. The paper also elaborates on the specific post-harvest fruit infestation detection methods, which include principles, protocols, specific application examples, merits, and limitations. The methods reviewed include those based on spectroscopy, imaging, acoustic sensing, and chemical interactions, with greater emphasis on the noninvasive methods. This review also discusses the current research gaps as well as the future research directions for non-destructive methods\u27 application in the detection and classification of insect infestation in fruits and vegetables

Genetic variation regulates opioid-induced respiratory depression in mice.

In the U.S., opioid prescription for treatment of pain nearly quadrupled from 1999 to 2014. The diversion and misuse of prescription opioids along with increased use of drugs like heroin and fentanyl, has led to an epidemic in addiction and overdose deaths. The most common cause of opioid overdose and death is opioid-induced respiratory depression (OIRD), a life-threatening depression in respiratory rate thought to be caused by stimulation of opioid receptors in the inspiratory-generating regions of the brain. Studies in mice have revealed that variation in opiate lethality is associated with strain differences, suggesting that sensitivity to OIRD is genetically determined. We first tested the hypothesis that genetic variation in inbred strains of mice influences the innate variability in opioid-induced responses in respiratory depression, recovery time and survival time. Using the founders of the advanced, high-diversity mouse population, the Diversity Outbred (DO), we found substantial sex and genetic effects on respiratory sensitivity and opiate lethality. We used DO mice treated with morphine to map quantitative trait loci for respiratory depression, recovery time and survival time. Trait mapping and integrative functional genomic analysis in GeneWeaver has allowed us to implicate Galnt11, an N-acetylgalactosaminyltransferase, as a gene that regulates OIRD

Effects of gabapentin on muscle spasticity and both induced as well as spontaneous autonomic dysreflexia after complete spinal cord injury

We recently reported that the neuropathic pain medication, gabapentin (GBP; Neurontin), significantly attenuated both noxious colorectal distension (CRD)-induced autonomic dysreflexia (AD) and tail pinch-induced spasticity compared to saline-treated cohorts 2–3 weeks after complete high thoracic (T4) spinal cord injury (SCI). Here we employed long-term blood pressure telemetry to test, firstly, the efficacy of daily versus acute GBP treatment in modulating AD and tail spasticity in response to noxious stimuli at 2 and 3 weeks post-injury. Secondly, we determined whether daily GBP alters baseline cardiovascular parameters, as well as spontaneous AD events detected using a novel algorithm based on blood pressure telemetry data. At both 14 and 21 days after SCI, irrespective of daily treatment, acute GBP given 1 h prior to stimulus significantly attenuated CRD-induced AD and pinch-evoked tail spasticity; conversely, acute saline had no such effects. Moreover, daily GBP did not alter 24 h mean arterial pressure (MAP) or heart rate (HR) values compared to saline treatment, nor did it reduce the incidence of spontaneous AD events compared to saline over the three week assessment period. Power spectral density (PSD) analysis of the MAP signals demonstrated relative power losses in mid frequency ranges (0.2–0.8 Hz) for all injured animals relative to low frequency MAP power (0.02–0.08 Hz). However, there was no significant difference between groups over time post-injury; hence, GBP had no effect on the persistent loss of MAP fluctuations in the mid frequency range after injury. In summary, the mechanism(s) by which acute GBP treatment mitigate aberrant somatosensory and cardiophysiological responses to noxious stimuli after SCI remain unclear. Nevertheless, with further refinements in defining the dynamics associated with AD events, such as eliminating requisite concomitant bradycardia, the objective repeatability of automatic detection of hypertensive crises provides a potentially useful tool for assessing autonomic function pre- and post-SCI, in conjunction with experimental pharmacotherapeutics for neuropathic pain, such as GBP