Continuous Modeling of the Denoising Process for Speech Enhancement Based on Deep Learning

In this paper, we explore a continuous modeling approach for deep-learning-based speech enhancement, focusing on the denoising process. We use a state variable to indicate the denoising process. The starting state is noisy speech and the ending state is clean speech. The noise component in the state variable decreases with the change of the state index until the noise component is 0. During training, a UNet-like neural network learns to estimate every state variable sampled from the continuous denoising process. In testing, we introduce a controlling factor as an embedding, ranging from zero to one, to the neural network, allowing us to control the level of noise reduction. This approach enables controllable speech enhancement and is adaptable to various application scenarios. Experimental results indicate that preserving a small amount of noise in the clean target benefits speech enhancement, as evidenced by improvements in both objective speech measures and automatic speech recognition performance

Variance-Preserving-Based Interpolation Diffusion Models for Speech Enhancement

The goal of this study is to implement diffusion models for speech enhancement (SE). The first step is to emphasize the theoretical foundation of variance-preserving (VP)-based interpolation diffusion under continuous conditions. Subsequently, we present a more concise framework that encapsulates both the VP- and variance-exploding (VE)-based interpolation diffusion methods. We demonstrate that these two methods are special cases of the proposed framework. Additionally, we provide a practical example of VP-based interpolation diffusion for the SE task. To improve performance and ease model training, we analyze the common difficulties encountered in diffusion models and suggest amenable hyper-parameters. Finally, we evaluate our model against several methods using a public benchmark to showcase the effectiveness of our approac

Effect of visit-to-visit blood pressure variability on mild cognitive impairment and probable dementia in hypertensive patients receiving standard and intensive blood pressure treatment

BackgroundHigh visit-to-visit blood pressure variability (BPV) and hypertension are risk factors for mild cognitive impairment (MCI) and probable dementia (PD). Few articles assessed the effect of BPV on the MCI and PD in intensive blood pressure treatment and the different functions of three types of visit-to-visit BPV: systolic blood pressure variability (SBPV), diastolic blood pressure variability (DBPV) and pulse pressure variability (PPV).MethodsWe performed a post hoc analysis of the SPRINT MIND trial. The primary outcomes were MCI and PD. BPV was measured by average real variability (ARV). The Kaplan-Meier curves were used to clarify the difference in tertiles of BPV. We fit Cox proportional hazards models to our outcome. We also did an interaction analysis between the intensive and standard groups.ResultsWe enrolled 8,346 patients in the SPRINT MIND trial. The incidence of MCI and PD in the intensive group was lower than that in the standard group. 353 patients had MCI and 101 patients had PD in the standard group while 285 patients had MCI and 75 patients had PD in the intensive group. Tertiles with higher SBPV, DBPV and PPV in the standard group had a higher risk of MCI and PD (all p < 0.05). Meanwhile, higher SBPV and PPV in the intensive group were associated with an increased risk of PD (SBPV: HR(95%) = 2.1 (1.1–3.9), p = 0.026; PPV: HR(95%) = 2.0 (1.1–3.8), p = 0.025 in model 3) and higher SBPV in the intensive group was associated with an increased risk of MCI(HR(95%) = 1.4 (1.2–1.8), p < 0.001 in model 3). The difference between intensive and standard blood pressure treatment was not statistically significant when we considered the effect of the higher BPV on the risk of MCI and PD (all p for interaction >0.05).ConclusionIn this post hoc analysis of the SPRINT MIND trial, we found that higher SBPV and PPV were associated with an increased risk of PD in the intensive group, and higher SBPV was associated with an increased risk of MCI in the intensive group. The effect of higher BPV on the risk of MCI and PD was not significantly different in intensive and standard blood pressure treatment. These findings emphasized the need for clinical work to monitor BPV in intensive blood pressure treatment

Pain sensitivity related to gamma oscillation of parvalbumin interneuron in primary somatosensory cortex in Dync1i1−/− mice

Cytoplasmic dynein is an important intracellular motor protein that plays an important role in neuronal growth, axonal polarity formation, dendritic differentiation, and dendritic spine development among others. The intermediate chain of dynein, encoded by Dync1i1, plays a vital role in the dynein complex. Therefore, we assessed the behavioral and related neuronal activities in mice with dync1i1 gene knockout. Neuronal activities in primary somatosensory cortex were recorded by in vivo electrophysiology and manipulated by optogenetic and chemogenetics. Nociception of mechanical, thermal, and cold pain in Dync1i1−/− mice were impaired. The activities of parvalbumin (PV) interneurons and gamma oscillation in primary somatosensory were also impaired when exposed to mechanical nociceptive stimulation. This neuronal dysfunction was rescued by optogenetic activation of PV neurons in Dync1i1−/− mice, and mimicked by suppressing PV neurons using chemogenetics in WT mice. Impaired pain sensations in Dync1i1−/− mice were correlated with impaired gamma oscillations due to a loss of interneurons, especially the PV type. This genotype-driven approach revealed an association between impaired pain sensation and cytoplasmic dynein complex

Time-Series Monitoring of Dust-Proof Nets Covering Urban Construction Waste by Multispectral Images in Zhengzhou, China

Rapid urbanization has produced a huge amount of construction waste. The operations and consequences of construction and demolition can lead to windblown dust problems, profoundly affecting the living environment of residents. Fortunately, dust-proof nets have been used in construction sites to reduce and prevent pollution by fine particles such as dust, so it is important to monitor and evaluate their efficacy. In this study, Earth observation techniques were used for the extraction and monitoring of solid waste and dust-proof nets. In order to fully perceive the validity and necessity of dust-proof nets for urban air health, we conducted a case study in Zhengzhou, China. We explored the potential of multispectral remote sensing available for monitoring urban construction waste and proposed a multi-layer classification method to identify construction waste and dust-proof nets based on Landsat-8 OLI and Sentinel-2 MSI data, with an average identification accuracy and Kappa coefficient of 96.27% and 0.93 for construction waste in the study area from 2015 to 2020, respectively. In addition, our study revealed the driving factors and impact of temporal variations in regional construction waste areas and dust-proof nets coverage. The results indicate the classification can track municipal solid waste management and changes in air pollutant concentrations and is useful for achieving SDG 11.6 (reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management). This study has the potential to monitor construction waste and dust-proof nets, paving the way for better urban environmental governance and surveillance actions in the future, especially involving big data

The Impact of Manufacturing Imperfections on the Performance of Metalenses and a Manufacturing-Tolerant Design Method

Metalenses play an important role in optoelectronic integrated devices, given their advantages in miniaturization and integration. Due to its high aspect ratio subwavelength structure, fabricating metalenses requires a high-level dry etching technology. Consequently, structure deformation of the metalens will exist if the etching process of the material is not mature enough, which will impair the metalens’ performance. In this paper, a polarization-independent InP dielectric metalens is designed to focus the incident light from air into the substrate, which is used for monolithically integrating with the InGaAs/InP photodetector in the future. Subsequently, with the simulation method, we investigated the impact of the structure deformation on the metalens’ performance, which was found in our InP dry etching process development. We have found that the sidewall slope and aspect ratio-dependent etching effect greatly impaired the focusing efficiency because of the phase modulation deviation. To solve this problem, we proposed a manufacturing-tolerant design method, which effectively improved the performance of the device with structural deformation. Our work is instructive for developing metalenses and can accelerate their integration application

Image1_Effect of visit-to-visit blood pressure variability on mild cognitive impairment and probable dementia in hypertensive patients receiving standard and intensive blood pressure treatment.jpeg

BackgroundHigh visit-to-visit blood pressure variability (BPV) and hypertension are risk factors for mild cognitive impairment (MCI) and probable dementia (PD). Few articles assessed the effect of BPV on the MCI and PD in intensive blood pressure treatment and the different functions of three types of visit-to-visit BPV: systolic blood pressure variability (SBPV), diastolic blood pressure variability (DBPV) and pulse pressure variability (PPV).MethodsWe performed a post hoc analysis of the SPRINT MIND trial. The primary outcomes were MCI and PD. BPV was measured by average real variability (ARV). The Kaplan-Meier curves were used to clarify the difference in tertiles of BPV. We fit Cox proportional hazards models to our outcome. We also did an interaction analysis between the intensive and standard groups.ResultsWe enrolled 8,346 patients in the SPRINT MIND trial. The incidence of MCI and PD in the intensive group was lower than that in the standard group. 353 patients had MCI and 101 patients had PD in the standard group while 285 patients had MCI and 75 patients had PD in the intensive group. Tertiles with higher SBPV, DBPV and PPV in the standard group had a higher risk of MCI and PD (all p 0.05).ConclusionIn this post hoc analysis of the SPRINT MIND trial, we found that higher SBPV and PPV were associated with an increased risk of PD in the intensive group, and higher SBPV was associated with an increased risk of MCI in the intensive group. The effect of higher BPV on the risk of MCI and PD was not significantly different in intensive and standard blood pressure treatment. These findings emphasized the need for clinical work to monitor BPV in intensive blood pressure treatment.</p