In a reverberant environment, interferences such as reflections and background noise can degrade the perception of the sound source signal. Although the DNN-based methods have made a tremendous breakthrough in addressing this issue, the performance of these models is highly dependent on the completeness of the training dataset, which will limit its generalization under unknown environments. In this article, we propose a physical model-based self-supervised learning (PMSSL) method to realize the DNN model optimization under unknown scenarios. This method incorporates a room reverberation physical model into the sound source enhancement model optimization process, realizing the self-learning of the DNN model under physical constraints. In this process, the time-frequency characteristics of the input signal and the spatial feature of the reverberation environment are utilized for parameter optimization, improving the adaptability of the DNN model under unknown scenarios. Experimental results based on simulated and measured data prove that the proposed method can obtain much more accurate source signal enhancement results compared with the pre-trained models, verifying its effectiveness and adaptability in new environments.
Summary The geographic distribution of plant diversity matches the gradient of habitat heterogeneity from lowlands to mountain regions. However, little is known about how much this relationship is conserved across scales. Using the World Checklist of Vascular Plants and high-resolution biodiversity maps developed by species distribution models, we investigated the associations between species richness and habitat heterogeneity at the scales of Eurasia and the Hengduan Mountains (HDM) in China. Habitat heterogeneity explains seed plant species richness across Eurasia, but the plant species richness of 41/97 HDM families is even higher than expected from fitted statistical relationships. A habitat heterogeneity index combining growing degree days, site water balance, and bedrock type performs better than heterogeneity based on single variables in explaining species richness. In the HDM, the association between heterogeneity and species richness is stronger at larger scales. Our findings suggest that high environmental heterogeneity provides suitable conditions for the diversification of lineages in the HDM. Nevertheless, habitat heterogeneity alone cannot fully explain the distribution of species richness in the HDM, especially in the western HDM, and complementary mechanisms, such as the complex geological history of the region, may have contributed to shaping this exceptional biodiversity hotspot.
Ferroelectric diodes can generate a polarization-controlled bidirectional photoresponse to simulate inhibition and promotion behaviors in the artificial neuromorphic system with fast speed, high energy efficiency, and nonvolatility. However, the existing ferroelectric diodes based on ferroelectric oxides suffer from a weak bidirectional photoresponse (below 1 mA/W), difficult miniaturization, and a large response photon energy (over 3 eV). Here, we design a series of van der Waals �−In2Se3/Nb�2 (� = S, Se, and Te) ferroelectric diodes with bidirectional photoresponse by using ab initio quantum transport simulation. These devices show a maximum bidirectional photoresponse of 30 (−19) mA/W and a minimum response photon energy of 1.3 eV at the monolayer thickness. Our work shows advanced optoelectronic applications of the van der Waals ferroelectric diodes in the future artificial neuromorphic system.
Abstract Accurate estimates of aerosol refractive index (RI) are critical for modeling aerosol-radiation interaction, yet this information is limited for ambient organic aerosols, leading to large uncertainties in estimating aerosol radiative effects. We present a semi-empirical model that predicts the real RI n of organic aerosol material from its widely measured oxygen-to-carbon (O:C) and hydrogen-to-carbon (H:C) elemental ratios. The model was based on the theoretical framework of Lorenz-Lorentz equation and trained with n-values at 589 nm () of 160 pure compounds. The predictions can be expanded to predict n-values in a wide spectrum between 300 and 1,200 nm. The model was validated with newly measured and literature datasets of n-values for laboratory secondary organic aerosol (SOA) materials. Uncertainties of predictions for all SOA samples are within 5%. The model suggests that -values of organic aerosols may vary within a relatively small range for typical O:C and H:C values observed in the atmosphere.
Numerous functional magnetic resonance imaging (fMRI) studies have examined the neural mechanisms of negative emotional words, but scarce evidence is available for the interactions among related brain regions from the functional brain connectivity perspective. Moreover, few studies have addressed the neural networks for negative word processing in bilinguals. To fill this gap, the current study examined the brain networks for processing negative words in the first language (L1) and the second language (L2) with Chinese-English bilinguals. To identify objective indicators associated with negative word processing, we first conducted a coordinate-based meta-analysis on contrasts between negative and neutral words (including 32 contrasts from 1589 participants) using the activation likelihood estimation method. Results showed that the left medial prefrontal cortex (mPFC), the left inferior frontal gyrus (IFG), the left posterior cingulate cortex (PCC), the left amygdala, the left inferior temporal gyrus (ITG), and the left thalamus were involved in processing negative words. Next, these six clusters were used as regions of interest in effective connectivity analyses using extended unified structural equation modeling to pinpoint the brain networks for bilingual negative word processing. Brain network results revealed two pathways for negative word processing in L1: a dorsal pathway consisting of the left IFG, the left mPFC, and the left PCC, and a ventral pathway involving the left amygdala, the left ITG, and the left thalamus. We further investigated the similarity and difference between brain networks for negative word processing in L1 and L2. The findings revealed similarities in the dorsal pathway, as well as differences primarily in the ventral pathway, indicating both neural assimilation and accommodation across processing negative emotion in two languages of bilinguals.
Summary Despite the unique switching characteristics of CO2-responsive foaming, its stability remains questionable. In this protocol, we describe steps to synthesize a stable CO2-responsive foam by adding the preferably selected hydrophilic nanoparticle N20 into the surfactant C12A. We detail the selection of the most suitable nanoparticles for the surfactant by measuring the foaming volume and half-life of the dispersion. The protocol can be extended to manufacture with other types of responsive foams (e.g., light responsive foams, magnetic responsive foams). For complete details on the use and execution of this protocol, please refer to Li et al. (2022).1
Ozone reactions on human body surfaces produce volatile organic compounds (VOCs) that influence indoor air quality. However, the dependence of VOC emissions on the ozone concentration has received limited attention. In this study, we conducted 36 sets of single-person chamber experiments with three volunteers exposed to ozone concentrations ranging from 0 to 32 ppb. Emission fluxes from human body surfaces were measured for 11 targeted skin-oil oxidation products. For the majority of these products, the emission fluxes linearly correlated with ozone concentration, indicating a constant surface yield (moles of VOC emitted per mole of ozone deposited). However, for the second-generation oxidation product 4-oxopentanal, a higher surface yield was observed at higher ozone concentrations. Furthermore, many VOCs have substantial emissions in the absence of ozone. Overall, these results suggest that the complex surface reactions and mass transfer processes involved in ozone-dependent VOC emissions from the human body can be represented using a simplified parametrization based on surface yield and baseline emission flux. Values of these two parameters were quantified for targeted products and estimated for other semiquantified VOC signals, facilitating the inclusion of ozone/skin oil chemistry in indoor air quality models and providing new insights on skin oil chemistry.
Adaptive radiative cooling offers smart thermal regulation that saves energy for conditioning regardless of the variation in environment or requirements. In a recent study by Banerjee and colleagues, an electrochromic device based on the redox process of PEDOT was developed, enabling tunable surface temperature by applied electrical bias at ambient conditions.