Variance of spectral entropy (VSE): an SNR estimator for speech enhancement in hearing aids

In everyday situations an individual can encounter a variety of acoustic environments. For an individual with a hearing aid following speech in different types of background noise can often present a challenge. For this reason, estimating the signal-to-noise ratio (SNR) is a key factor to consider in hearing-aid design. The ability to adjust a noise reduction algorithm according to the SNR could provide the flexibility required to improve speech intelligibility in varying levels of background noise. However, most of the current high-accuracy SNR estimation methods are relatively complex and may inhibit the performance of hearing aids. This study investigates the advantages of incorporating a spectral entropy method to estimate SNR for speech enhancement in hearing aids; in particular a variance of spectral entropy (VSE) measure. The VSE approach avoids some of the complex computational steps of traditional statistical-model based SNR estimation methods by only measuring the spectral entropy among frequency channels of interest within the hearing aid. For this study, the SNR was estimated using the spectral entropy method in different types of noise. The variance of the spectral entropy in a hearing-aid model with 10 peripheral frequency channels was used to measure the SNR. By measuring the variance of the spectral entropy at input SNR levels between -10 dB to 20 dB, the relationship function between the SNR and the VSE was estimated. The VSE for the speech-in-noise was measured at temporal intervals of 1.5s. The VSE method demonstrates a more reliable performance in different types of background noise, in particular for low-number of speakers babble noise when compared to the US National Institute of Standards and Technology (NIST) or Waveform Amplitude Distribution Analysis (WADA) methods. The VSE method may also reduce additional computational steps (reducing system delays) making it more appropriate for implementation in hearing aids where system delays should be minimized as much as possible

Insights into the dynamics of mafic magmatic-hydromagmatic eruptions from volatile degassing behaviour: The Hverfjall Fires, Iceland

The style and intensity of hydromagmatic activity is governed by a complex interplay between the relative volumes of magma and water that interact, their relative viscosities, the depth of subsurface explosions, the substrate properties, and the vent geometry. Fundamental questions remain, however, regarding the role of magmatic vesiculation in determining the dynamics of magma-water interaction (MWI). Petrological reconstructions of magmatic degassing histories are commonly employed to interpret the pre- and syn-eruptive conditions during ‘dry’ magmatic eruptions, but the application of similar techniques to hydromagmatic activity has not yet been fully explored. In this study, we integrate glass volatile measurements (S, Cl, H2O and CO2) with field observations and microtextural measurements to examine the relationship between degassing and eruptive style during the Hverfjall Fires fissure eruption, Iceland. Here, coeval fissure vents produced both ‘dry’ magmatic (Jarðbaðshólar scoria cone complex) and variably wet hydromagmatic (Hverfjall tuff ring) activity, generating physically distinct pyroclastic deposits with contrasting volatile signatures. Matrix glass volatile concentrations in hydromagmatic ash (883 ± 172 [1σ] ppm S; 0.45 ± 0.03 [1σ] wt% H2O; ≤20 ppm CO2) are consistently elevated relative to magmatic ash and scoria lapilli (418 ± 93 [1σ] ppm S; 0.12 ± 0.48 [1σ] wt% H2O; CO2 below detection) and overlap with the range for co-erupted phenocryst-hosted melt inclusions (1522 ± 127 [1σ] ppm S; 165 ± 27 [1σ] ppm Cl). Measurements of hydromagmatic glasses indicate that the magma has degassed between 17 and 70% of its initial sulfur prior to premature quenching at variably elevated confining pressures. By comparing volatile saturation pressures for both magmatic and hydromagmatic glasses, and how these vary through the eruptive stratigraphy, we place constraints on the conditions of MWI. Crucially, our data demonstrate that the magma was already vesiculating when it encountered groundwater at depths of 100–200 m, and that the external water supply was sufficient to maintain MWI throughout the eruption with no significant vertical or lateral migration of the fragmentation surface. We propose that development of an in-vent water-sediment slurry provides a mechanism through which the elevated confining pressures of ~1.6–2.6 MPa (or up to 6 MPa accounting for uncertainty in CO2 below analytical detection) could be maintained and buffered throughout the eruption, whilst enabling vertical mixing and ejection of fragmented juvenile and lithic material from a range of depths. Importantly, these results demonstrate that the volatile contents of hydromagmatic deposits provide valuable records of (1) the environment of MWI (e.g., groundwater versus surface water, vertical migration of the fragmentation level) and (2) the state of the magma at the time of fragmentation and quenching. We further suggest that the volatile content of tephra glasses provides a reliable alternative (or additional) indicator of a hydromagmatic origin, particularly for reduced Ocean Island Basalts where late-stage volatile saturation and degassing (S, H2O) occurs over a pressure range relevant to typical MWI environments.Postgraduate scholarship from University of Bristol AXA Research Fund Royal Society Wolfson Merit Award Royal Society University Research Fellowship New Researchers Award from the Geologists’ Associatio

Contrasting mechanisms of magma fragmentation during coeval magmatic and hydromagmatic activity: the Hverfjall Fires fissure eruption, Iceland

Growing evidence for significant magmatic vesiculation prior to magma-water interaction (MWI) has brought into question the use of ‘diagnostic’ features, such as low vesicularities and blocky morphologies, to identify hydromagmatic pyroclasts. We address this question by quantifying co-variations in particle size, shape and texture in both magmatic and hydromagmatic deposits from the Hverfjall Fires fissure eruption, Iceland. Overlapping vesicularity and bubble number density distributions measured in rapidly quenched magmatic and hydromagmatic pyroclasts indicate a shared initial history of bubble nucleation and growth, with substantial vesiculation prior to MWI. Hydromagmatic fragmentation occurred principally by brittle mechanisms, where the length scale and geometry of fracturing was controlled by the bubble population. This suggests that the elevated fragmentation efficiency of hydromagmatic deposits is driven, at least in part, by brittle disintegration of vesicular pyroclasts due to high thermal stress generated during rapid cooling. In this way, the shape and size distributions of hydromagmatic pyroclasts, both critical input parameters for ash dispersion models, are strongly influenced by the dynamics of vesiculation prior to MWI. This result underlines the need to analyse multiple grain-size fractions to characterise the balance between magmatic and hydromagmatic processes. During the Hverfjall Fires eruption, the external water supply was sufficient to maintain MWI throughout the eruption, with no evidence for progressive exhaustion of a water reservoir. We suggest that both the longevity and the spatial distribution of MWI were determined by the pre-existing regional hydrology and represent continuous interaction between a propagating dike and a strong groundwater flow system hosted within permeable basalt lavas

Export production fluctuations in the eastern equatorial Pacific during the Pliocene-Pleistocene: Reconstruction using barite accumulation rates

published_or_final_versio

Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data.

Numerous Bayesian Network (BN) structure learning algorithms have been proposed in the literature over the past few decades. Each publication makes an empirical or theoretical case for the algorithm proposed in that publication and results across studies are often inconsistent in their claims about which algorithm is ‘best’. This is partly because there is no agreed evaluation approach to determine their effectiveness. Moreover, each algorithm is based on a set of assumptions, such as complete data and causal sufficiency, and tend to be evaluated with data that conforms to these assumptions, however unrealistic these assumptions may be in the real world. As a result, it is widely accepted that synthetic performance overestimates real performance, although to what degree this may happen remains unknown. This paper investigates the performance of 15 state-of-the-art, well-established, or recent promising structure learning algorithms. We propose a methodology that applies the algorithms to data that incorporates synthetic noise, in an effort to better understand the performance of structure learning algorithms when applied to real data. Each algorithm is tested over multiple case studies, sample sizes, types of noise, and assessed with multiple evaluation criteria. This work involved learning approximately 10,000 graphs with a total structure learning runtime of seven months. In investigating the impact of data noise, we provide the first large scale empirical comparison of BN structure learning algorithms under different assumptions of data noise. The results suggest that traditional synthetic performance may overestimate real-world performance by anywhere between 10% and more than 50%. They also show that while score-based learning is generally superior to constraint-based learning, a higher fitting score does not necessarily imply a more accurate causal graph. The comparisons extend to other outcomes of interest, such as runtime, reliability, and resilience to noise, assessed over both small and large networks, and with both limited and big data. To facilitate comparisons with future studies, we have made all data, raw results, graphs and BN models freely available online

Determination of buprenorphine, norbuprenorphine, naloxone, and their glucuronides in urine by liquid chromatography–tandem mass spectrometry

Publisher Copyright: © 2021 The Authors. Drug Testing and Analysis published by John Wiley & Sons Ltd.A liquid chromatography–tandem mass spectrometry method for the simultaneous quantification of buprenorphine (BUP), norbuprenorphine (NBUP), naloxone (NAL), and their glucuronide conjugates BUP-G, NBUP-G, and NAL-G in urine samples was developed. The method, omitting a hydrolysis step, involved non-polar solid-phase extraction, liquid chromatography on a C18 column, electrospray positive ionization, and mass analysis by multiple reaction monitoring. Quantification was based on the corresponding deuterium-labelled internal standards for each of the six analytes. The limit of quantification was 0.5 μg/L for BUP and NAL, 1 μg/L for NAL-G, and 3 μg/L for NBUP, BUP-G, and NBUP-G. Using the developed method, 72 urine samples from buprenorphine-dependent patients were analysed to cover the concentration ranges encountered in a clinical setting. The median (maximum) concentration was 4.2 μg/L (102 μg/L) for BUP, 74.7 μg/L (580 μg/L) for NBUP, 0.9 μg/L (85.5 μg/L) for NAL, 159.5 μg/L (1370 μg/L) for BUP-G, 307.5 μg/L (1970 μg/L) for NBUP-G, and 79.6 μg/L (2310 μg/L) for NAL-G.Peer reviewe

Subclinical myocardial disease by cardiac magnetic resonance imaging and spectroscopy in healthy HIV/Hepatitis C virus-coinfected persons.

Objective The contribution of hepatitis C virus (HCV) infection to the risk of heart failure in human immunodeficiency virus (HIV)-coinfected persons is unknown. The objective was to characterize cardiac function and morphology in HIV-treated coinfected persons. Methods In a cross-sectional study, HIV-infected patients virologically suppressed on antiretroviral therapy without known cardiovascular disease or diabetes mellitus underwent cardiac magnetic resonance imaging and spectroscopy for measures of cardiac function, myocardial fibrosis, and steatosis. Results The study included 18 male patients with a median age of 44 years. Of these, 10 had untreated HCV coinfection and eight had HIV monoinfection. Global systolic and diastolic function in the cohort were normal, and median myocardial fat content was 0.48% (interquartile range 0.35-1.54). Left ventricular (LV) mass index and LV mass/volume ratio were significantly greater in the HIV/HCV-coinfected group compared with the HIV-monoinfected group. In the HIV-monoinfected group, there was more myocardial fibrosis as measured by extracellular volume fraction. Conclusions There were differences between HIV/HCV-coinfected and HIV-monoinfected patients in cardiac structure and morphology. Larger studies are needed to examine whether HIV and HCV independently contribute to mechanisms of heart failure

Microbiology testing associated with antibiotic dispensing in older community-dwelling adults.

BACKGROUND:It is commonly recommended that microbiological assessment should accompany the use of antibiotics prone to resistance. We sought to estimate the rate of microbiology testing and compare this to dispensing of the World Health Organization classified "watch" group antibiotics in primary care. METHODS:Data from a cohort of older adults (mean age 69 years) were linked to Australian national health insurance (Pharmaceutical Benefits Scheme & Medicare Benefits Schedule) records of community-based antibiotic dispensing and microbiology testing in 2015. Participant characteristics associated with greater watch group antibiotic dispensing and microbiology testing were estimated using adjusted incidence rate ratios (aIRR) and 95% confidence intervals (CI) in multivariable zero-inflated negative binomial regression models. RESULTS:In 2015, among 244,299 participants, there were 63,306 watch group antibiotic prescriptions dispensed and 149,182 microbiology tests conducted; the incidence rate was 0.26 per person-year for watch group antibiotic dispensing and 0.62 for microbiology testing. Of those antibiotic prescriptions, only 19% were accompanied by microbiology testing within - 14 to + 7 days. After adjusting for socio-demographic factors and co-morbidities, individuals with chronic respiratory diseases were more likely to receive watch group antibiotics than those without, e.g. asthma (aIRR:1.59, 95%CI:1.52-1.66) and chronic obstructive pulmonary disease (COPD) (aIRR:2.71, 95%CI:2.48-2.95). However, the rate of microbiology testing was not comparably higher among them (with asthma aIRR:1.03, 95%CI:1.00-1.05; with COPD aIRR:1.00, 95%CI:0.94-1.06). CONCLUSIONS:Priority antibiotics with high resistance risk are commonly dispensed among community-dwelling older adults. The discord between the rate of microbiology testing and antibiotic dispensing in adults with chronic respiratory diseases suggests the potential for excessive empirical prescribing

Reliability Evaluation for Clustered WSNs under Malware Propagation.

We consider a clustered wireless sensor network (WSN) under epidemic-malware propagation conditions and solve the problem of how to evaluate its reliability so as to ensure efficient, continuous, and dependable transmission of sensed data from sensor nodes to the sink. Facing the contradiction between malware intention and continuous-time Markov chain (CTMC) randomness, we introduce a strategic game that can predict malware infection in order to model a successful infection as a CTMC state transition. Next, we devise a novel measure to compute the Mean Time to Failure (MTTF) of a sensor node, which represents the reliability of a sensor node continuously performing tasks such as sensing, transmitting, and fusing data. Since clustered WSNs can be regarded as parallel-serial-parallel systems, the reliability of a clustered WSN can be evaluated via classical reliability theory. Numerical results show the influence of parameters such as the true positive rate and the false positive rate on a sensor node's MTTF. Furthermore, we validate the method of reliability evaluation for a clustered WSN according to the number of sensor nodes in a cluster, the number of clusters in a route, and the number of routes in the WSN