Investigations on the Optimal Estimation of Speech Envelopes for the Two-Stage Speech Enhancement.

Using the source-filter model of speech production, clean speech signals can be decomposed into an excitation component and an envelope component that is related to the phoneme being uttered. Therefore, restoring the envelope of degraded speech during speech enhancement can improve the intelligibility and quality of output. As the number of phonemes in spoken speech is limited, they can be adequately represented by a correspondingly limited number of envelopes. This can be exploited to improve the estimation of speech envelopes from a degraded signal in a data-driven manner. The improved envelopes are then used in a second stage to refine the final speech estimate. Envelopes are typically derived from the linear prediction coefficients (LPCs) or from the cepstral coefficients (CCs). The improved envelope is obtained either by mapping the degraded envelope onto pre-trained codebooks (classification approach) or by directly estimating it from the degraded envelope (regression approach). In this work, we first investigate the optimal features for envelope representation and codebook generation by a series of oracle tests. We demonstrate that CCs provide better envelope representation compared to using the LPCs. Further, we demonstrate that a unified speech codebook is advantageous compared to the typical codebook that manually splits speech and silence as separate entries. Next, we investigate low-complexity neural network architectures to map degraded envelopes to the optimal codebook entry in practical systems. We confirm that simple recurrent neural networks yield good performance with a low complexity and number of parameters. We also demonstrate that with a careful choice of the feature and architecture, a regression approach can further improve the performance at a lower computational cost. However, as also seen from the oracle tests, the benefit of the two-stage framework is now chiefly limited by the statistical noise floor estimate, leading to only a limited improvement in extremely adverse conditions. This highlights the need for further research on joint estimation of speech and noise for optimum enhancement.

Exosomal miR-27b-3p secreted by visceral adipocytes contributes to endothelial inflammation and atherogenesis.

Obesity, particularly increased visceral fat, positively correlates with various metabolic challenges, including atherosclerosis, but the mechanism is not fully understood. The aim of this study is to determine the role of visceral-fat-derived exosomes (Exo) in endothelial cells and atherosclerosis. We show that obesity changes the miRNA profile of visceral adipose exosomes in mice. Importantly, exosomal miR-27b-3p efficiently enters into the vascular endothelial cells and activates the NF-κB pathway by downregulating PPARα. Mechanistically, miR-27b-3p binds directly to the CDS region of PPARα mRNA, thereby promoting mRNA degradation and suppressing translation. In ApoE-deficient mice, administration of miR-27b-3p mimic increases inflammation and atherogenesis, while overexpression of PPARα protects against atherosclerosis. Thus, obesity-induced exosomal miR-27b-3p promotes endothelial inflammation and facilitates atherogenesis by PPARα suppression. We reveal an exosomal pathway by which obesity aggravates atherosclerosis and proposed therapeutic strategies for atherosclerosis in people with obesity.

Bone morphogenetic protein 4 in perivascular adipose tissue ameliorates hypertension through regulation of angiotensinogen.

Background: Perivascular adipose tissue (PVAT), an active endocrine organ, exerts direct effect on vascular tone through paracrine. Activation of PVAT metabolism plays an inhibitory role in atherosclerosis via secreting relaxing factors. The present studies were designed to investigate the role of PVAT metabolism in regulation of hypertension. Materials and methods: Apolipoprotein E (ApoE) knockout mice with BMP4 knockout in adipose tissue or brown adipose tissue (aP2-DKO or UCP1-DKO, respectively) were used for exploring the role of impaired PVAT metabolism in hypertension. Vascular function was assessed using wire myography. The potential regulatory factor of vascular function was explored using qPCR and ELISA and further confirmed in perivascular fat cell line. Results: Knockout of BMP4 either in adipose tissue or specifically in BAT aggravates high-fat diet (HFD, 40% fat)-induced hypertension and endothelial dysfunction in ApoE-/- mice. In the meanwhile, deficiency of BMP4 also aggravates Ang II (angiotensin II) -induced hypertension and vascular remodeling in ApoE-/- mice. Moreover, deficiency of BMP4 inhibits NO release and induces ROS production. In vitro system, aortic rings pretreated with PVAT extracts from BMP4-DKO mice showed increased vasoconstriction and reduced endothelial-dependent relaxation compared with the controls. We further demonstrated that PVAT of BMP4-DKO mice expressed higher level of angiotensinogen (AGT) and Ang II compared with the controls. Conclusion: Impaired PVAT metabolism aggravates hypertension, and this effect is dependent on the activation of local renin-angiotensin-aldosterone system (RAAS). The results of this study first demonstrate the regulatory role of PVAT metabolism in hypertension.

Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals.

Remote, automated querying of fill-states of liquid-freight containers can significantly boost the operational efficiency of rail- and storage-yards. Most existing methods for fill-state detection are intrusive, or require sophisticated instrumentation and specific testing conditions, making them unsuitable here, due to the noisy and changeable surroundings and restricted access to the interior. We present a non-intrusive system that exploits the influence of the fill-state on the container's response to an external excitation. Using a solenoid and accelerometer mounted on the exterior wall of the container, to generate pulsed excitation and to measure the container response, the fill-state can be detected. The decision can be either a binary (empty/non-empty) label or a (quantised) prediction of the liquid level. We also investigate the choice of the signal features for the detection/classification, and the placement of the sensor and actuator. Experiments conducted in real settings validate the algorithms and the prototypes. Results show that the placement of the sensor and actuator along the base of the container is the best in terms of detection accuracy. In terms of signal features, linear predictive cepstral coefficients possess sufficient discriminative information. The prediction accuracy is 100% for binary classification and exceeds 80% for quantised level prediction.

BMP4-mediated browning of perivascular adipose tissue governs an anti-inflammatory program and prevents atherosclerosis.

Loss of perivascular adipose tissue (PVAT) impairs endothelial function and enhances atherosclerosis. However, the roles of PVAT thermoregulation in vascular inflammation and the development of atherosclerosis remains unclear. Bone morphogenetic protein 4 (BMP4) transforms white adipocyte to beige adipocyte, while promotes a brown-to-white shift in inter-scapular brown adipose tissue (BAT). Here, we found that knockdown of BMP4 in PVAT reduced expression of brown adipocyte-characteristic genes and increased endothelial inflammation in vitro co-culture system. Ablating BMP4 expression either in adipose tissues or specifically in BAT in ApoE-/- mice demonstrated a marked exacerbation of atherosclerotic plaque formation in vivo. We further demonstrated that proinflammatory factors (especially IL-1ß) increased in the supernatant of BMP4 knockdown adipocytes. Overexpression of BMP4 in adipose tissues promotes browning of PVAT and protects against atherosclerosis in ApoE-/- mice. These findings uncover an organ crosstalk between PVAT and blood endothelial cells that is engaged in atherosclerosis.