Incorporation of a modified temporal cepstrum smoothing in both signal-to-noise ratio and speech presence probability estimation for speech enhancement.

Numerous advanced and lightweight signal processing methods have been presented for single-channel speech enhancement (SE). It is imperative to carefully explore how to efficiently combine, integrate, and balance these methods. This paper proposes a more effective and less resource-intensive SE system, focused on the integration and adaptation of several approaches, especially the temporal cepstrum smoothing (TCS). First, a more robust fundamental frequency estimator is employed within TCS, mitigating the performance limitations caused by the inaccuracy of the original estimator. Additionally, a harmonic enhancement mechanism is introduced, effectively recovering the weak harmonic components. By incorporation of the modified TCS in the a posteriori speech presence probability estimation, the unbiased minimum mean square error noise power spectral density estimator can be refined. The modified TCS is also utilized for the a priori signal-to-noise ratio estimation. Moreover, this paper enhances the log-spectral amplitude estimator by applying both super-Gaussian speech priors and speech presence uncertainty for further improvement. Experimental evaluations demonstrate that the proposed method yields an improvement in speech quality while maintaining modest computational and storage requirements. Furthermore, the proposed system exhibits comparable performance to several baseline systems based on lightweight deep neural networks.

Exploring the prognostic significance of immunogenic cell death-related genes as risk biomarkers in cervical cancer.

BACKGROUND: Immunogenic cell death (ICD) is a process in which dying cells stimulate an immune response. It is a regulated form of cell death that can remodel the tumor microenvironment (TME) and activate the immune system, making immunotherapy more effective. This work was designed to identify prognostic gene features associated with ICD in cervical cancer (CC). METHODS: Based on CC datasets and a set of ICD-related genes obtained from public databases, we first filtered out ICD-related genes unrelated to CC survival using univariate analysis. Subsequently, LASSO regression and multivariate Cox regression analysis were employed to develop prognostic feature genes based on ICD. For the construction and validation of the model, eight genes (CXCL1, IL1B, TNF, YKT6, PDIA3, ROCK1, CXCR3, and CLEC9A) were chosen. A nomogram was created to forecast the prognosis of CC individuals, and Kaplan-Meier curves were utilized to explore the survival disparities among different risk groups of CC individuals. RESULTS: ssGSEA analysis was employed to investigate immune differences between two risk groups, revealing that the low-risk group exhibited elevated levels of immune cell infiltration, enhanced activation of immune function, and a higher immunophenoscore compared with the other group, which highlighted the relevance of ICD to TME. CONCLUSION: We constructed a prognostic model based on genetic biomarkers of ICD for prognostic prediction of CC patients. Our model demonstrated excellent discriminative and calibration capabilities, providing a valuable tool for prognostic prediction and assessing the potential efficacy of immunotherapy in CC.

Identification and expression analysis of the Xyloglucan transglycosylase/hydrolase (XTH) gene family under abiotic stress in oilseed (Brassica napus L.).

XTH genes are key genes that regulate the hydrolysis and recombination of XG components and plays role in the structure and composition of plant cell walls. Therefore, clarifying the changes that occur in XTHs during plant defense against abiotic stresses is informative for the study of the plant stress regulatory mechanism mediated by plant cell wall signals. XTH proteins in Arabidopsis thaliana was selected as the seed sequences in combination with its protein structural domains, 80 members of the BnXTH gene family were jointly identified from the whole genome of the Brassica napus ZS11, and analyzed for their encoded protein physicochemical properties, phylogenetic relationships, covariance relationships, and interoperating miRNAs. Based on the transcriptome data, the expression patterns of BnXTHs were analyzed in response to different abiotic stress treatments. The relative expression levels of some BnXTH genes under Al, alkali, salt, and drought treatments after 0, 6, 12 and 24 h were analyzed by using qRT-PCR to explore their roles in abiotic stress tolerance in B. napus. BnXTHs showed different expression patterns in response to different abiotic stress signals, indicating that the response mechanisms of oilseed rape against different abiotic stresses are also different. This paper provides a theoretical basis for clarifying the function and molecular genetic mechanism of the BnXTH gene family in abiotic stress tolerance in rapeseed.

Design of fully steerable broadband beamformers with concentric circular superarrays.

Concentric circular microphone arrays have been used in a wide range of applications, such as teleconferencing systems and smarthome devices for speech signal acquisition. Such arrays are generally designed with omnidirectional sensors, and the associated beamformers are fully steerable but only in the sensors' plane. If operated in the three-dimensional space, the performance of those arrays would suffer from significant degradation if the sound sources are out of the sensors' plane, which happens due to the incomplete spatial sampling of the sound field. This paper addresses this issue by presenting a new method to design concentric circular microphone arrays using both omnidirectional microphones and bidirectional microphones (directional sensors with dipole-shaped patterns). Such arrays are referred to as superarrays as they are able to achieve higher array gain as compared to their traditional counterparts with omnidirectional sensors. It is shown that, with the use of bidirectional microphones, the spatial harmonic components that are missing in the traditional arrays are compensated back. A beamforming method is then presented to design beamformers that can achieve frequency-invariant beampatterns with high directivity and are fully steerable in the three-dimensional space. Simulations and real experiments validate the effectiveness and good properties of the presented method.

Non-Intrusive Speech Quality Assessment Based on Deep Neural Networks for Speech Communication.

Traditionally, speech quality evaluation relies on subjective assessments or intrusive methods that require reference signals or additional equipment. However, over recent years, non-intrusive speech quality assessment has emerged as a promising alternative, capturing much attention from researchers and industry professionals. This article presents a deep learning-based method that exploits large-scale intrusive simulated data to improve the accuracy and generalization of non-intrusive methods. The major contributions of this article are as follows. First, it presents a data simulation method, which generates degraded speech signals and labels their speech quality with the perceptual objective listening quality assessment (POLQA). The generated data is proven to be useful for pretraining the deep learning models. Second, it proposes to apply an adversarial speaker classifier to reduce the impact of speaker-dependent information on speech quality evaluation. Third, an autoencoder-based deep learning scheme is proposed following the principle of representation learning and adversarial training (AT) methods, which is able to transfer the knowledge learned from a large amount of simulated speech data labeled by POLQA. With the help of discriminative representations extracted from the autoencoder, the prediction model can be trained well on a relatively small amount of speech data labeled through subjective listening tests. Fourth, an end-to-end speech quality evaluation neural network is developed, which takes magnitude and phase spectral features as its inputs. This phase-aware model is more accurate than the model using only the magnitude spectral features. A large number of experiments are carried out with three datasets: one simulated with labels obtained using POLQA and two recorded with labels obtained using subjective listening tests. The results show that the presented phase-aware method improves the performance of the baseline model and the proposed model with latent representations extracted from the adversarial autoencoder (AAE) outperforms the state-of-the-art objective quality assessment methods, reducing the root mean square error (RMSE) by 10.5% and 12.2% on the Beijing Institute of Technology (BIT) dataset and Tencent Corpus, respectively. The code and supplementary materials are available at https://github.com/liushenme/AAE-SQA.

Identification of GA2ox Family Genes and Expression Analysis under Gibberellin Treatment in Pineapple (Ananas comosus (L.) Merr.).

Gibberellin (GAs) plays an important regulatory role in the development and growth of pineapple (Ananas comosus (L.) Merr.). Bioinformatics was used to confirm the differential expression of GA2 gibberellin oxidase gene AcGA2oxs in the pineapple genome, which laid the foundation for exploring its role in pineapple. In this study, 42 GA2ox genes (AcGA2oxs) were identified in the pineapple genome, named from AcGA2ox1 to AcGA2ox42, and divided into four groups according to phylogenetic analysis. We also analyzed the gene structure, conserved motifs and chromosome localization of AcGA2oxs. AcGA2oxs within the same group had similar gene structure and motifs composition. Collinear analysis and cis-element analysis provided the basis for understanding the evolution and function of GA2ox genes in pineapple. In addition, we selected different tissue parts to analyze the expression profile of AcGA2oxs, and the results show that 41 genes were expressed, except for AcGA2ox18. AcGA2ox18 may not be expressed in these sites or may be pseudogenes. qRT-PCR (real-time fluorescence quantitative PCR) was used to detect the relative expression levels of the GA2ox gene family under different concentrations of GA3 treatment, and it was found that AcGA2ox gene expression was upregulated in different degrees under GA3 treatment. These results provide useful information for further study on the evolution and function of the GA2ox family in pineapple.

Identification and Expression Analysis of the Isopentenyl Transferase (IPT) Gene Family under Lack of Nitrogen Stress in Oilseed (Brassica napus L.).

BnIPT gene family members in Brassica napus and analyzing their expression under different exogenous hormones and abiotic stress treatments to provide a theoretical basis for clarifying their functions and molecular genetic mechanisms in nitrogen deficiency stress tolerance of B. napus. Using the Arabidopsis IPT protein as the seed sequence, combined with the IPT protein domain PF01715, 26 members of the BnIPT gene family were identified from the whole genome of the rape variety ZS11. Additionally, the physicochemical properties and structures, phylogenetic relationships, synteny relationships, protein-protein interaction network, and gene ontology enrichment were analyzed. Based on transcriptome data, the expression patterns of the BnIPT gene under different exogenous hormone and abiotic stress treatments were analyzed. We used the qPCR method to identify the relative expression level of BnIPT genes that may be related to the stress resistance of rapeseed in transcriptome analysis under normal nitrogen (N: 6 mmol·L-1) and nitrogen deficiency (N: 0) conditions and analyzed its effect on rapeseed under nitrogen deficiency stress role in tolerance. In response to nitrogen deficiency signals, the BnIPT gene showed a trend of up-regulation in shoots and down-regulation in roots, indicating that it may affect the process of nitrogen transport and redistribution to enhance the stress resistance of rapeseed to respond to the nitrogen deficiency stress. This study provides a theoretical basis for clarifying the function and molecular genetic mechanism of the BnIPT gene family in nitrogen deficiency stress tolerance in rape.

CBNet: A Composite Backbone Network Architecture for Object Detection.

top-performing object detectors depend heavily on backbone networks, whose advances bring consistent performance gains through exploring more effective network structures. In this paper, we propose a novel and flexible backbone framework, namely CBNet, to construct high-performance detectors using existing open-source pre-trained backbones under the pre-training fine-tuning paradigm. In particular, CBNet architecture groups multiple identical backbones, which are connected through composite connections. Specifically, it integrates the high- and low-level features of multiple identical backbone networks and gradually expands the receptive field to more effectively perform object detection. We also propose a better training strategy with auxiliary supervision for CBNet-based detectors. CBNet has strong generalization capabilities for different backbones and head designs of the detector architecture. Without additional pre-training of the composite backbone, CBNet can be adapted to various backbones (i.e., CNN-based vs. Transformer-based) and head designs of most mainstream detectors (i.e., one-stage vs. two-stage, anchor-based vs. anchor-free-based). Experiments provide strong evidence that, compared with simply increasing the depth and width of the network, CBNet introduces a more efficient, effective, and resource-friendly way to build high-performance backbone networks. Particularly, our CB-Swin-L achieves 59.4% box AP and 51.6% mask AP on COCO test-dev under the single-model and single-scale testing protocol, which are significantly better than the state-of-the-art results (i.e., 57.7% box AP and 50.2% mask AP) achieved by Swin-L, while reducing the training time by 6×. With multi-scale testing, we push the current best single model result to a new record of 60.1% box AP and 52.3% mask AP without using extra training data. Code is available at https://github.com/VDIGPKU/CBNetV2.

Optical Introduction and Manipulation of Plasmon-Exciton-Trion Coupling in a Si/WS2/Au Nanocavity.

Strong plasmon-exciton coupling, which has potential applications in nanophotonics, plasmonics, and quantum electrodynamics, has been successfully demonstrated by using metallic nanocavities and two-dimensional materials. Dynamical control of plasmon-exciton coupling strength, especially by using optical methods, remains a big challenge although it is highly desirable. Here, we report the optical introduction and manipulation of plasmon-exciton-trion coupling realized in a dielectric-metal hybrid nanocavity, which is composed of a silicon (Si) nanoparticle and a thin gold (Au) film, with an embedded tungsten disulfide (WS2) monolayer. We employ scattering and photoluminescence spectra to characterize the coupling strength between plasmons and excitons in Si/WS2/Au nanocavities constructed by using Si nanoparticles with different diameters. We enhance the plasmon-exciton and plasmon-trion coupling strength by injecting excitons and trions into the WS2 monolayer with a 488 nm laser beam. It is revealed that the emission intensities of excitons and trions with respect to the reference WS2 monolayer can be modified through the change in the coupling strength induced by the laser light. Interestingly, the coupling strength between the plasmons and the excitons/trions can be manipulated from weak to strong coupling regime by simply increasing the laser power, which is clearly resolved in the scattering spectra of Si/WS2/Au nanocavities. More importantly, the plasmon-exciton-trion coupling induced by the laser light is confirmed by the energy exchange between excitons and trions. Our findings indicate the possibility for optically manipulating plasmon-exciton interaction and suggest the practical applications of dielectric-metal hybrid nanocavities in nanoscale plasmonic devices.

MiR-210-3p accelerates tumor-relevant cell functions of endometrial carcinoma by repressing RUNX1T1.

BACKGROUND: Biological mechanism of miR-210-3p in endometrial carcinoma (EC) remains unclear. Here, our purpose is to study effects of miR-210-3p on malignant progression of EC. METHODS: Bioinformatics analysis showed miRNA and mRNA are abnormally expressed in EC tissues. Quantitative real-time fluorescence polymerase chain reaction (qRT-PCR) was utilized to compare miR-210-3p mRNA level in EC cells and tissues. qRT-PCR and western blot were used to measure RUNX1T1 and NCAM1 at mRNA and protein levels, and western blot for p-AKT and AKT proteins related to PI3K/AKT signaling pathway. Furthermore, EC cell behaviors were assayed via Cell Counting Kit-8, cell colony formation assay, wound healing, transwell and flow cytometry experiments. Interaction between RUNX1T1 and miR-210-3p was verified through dual-luciferase assay. Immunohistochemistry was used to analyze RUNX1T1 expression in clinical samples RESULTS: MiR-210-3p was considerably upregulated and RUNX1T1 was significantly under-expressed in EC. Overexpression of miR-210-3p stimulated cell proliferation, migration, invasion, and restrained cell apoptosis in EC. Dual-luciferase assay proved that RUNX1T1 was a target gene of miR-210-3p. The level of RUNX1T1 in EC was downregulated after overexpressing miR-210-3p. Rescue assay showed that overexpression of RUNX1T1 had an inhibitory impact on tumor-relevant cell behaviors, whereas overexpression of miR-210-3p rescued such inhibition. Overexpression of RUNX1T1 reduced p-AKT expression, which was restored with concomitantly overexpressed miR-210-3p. CONCLUSION: In general, miR-210-3p behaves as an oncogene in EC by down-regulating the expression of RUNX1T1. This study elucidates a new functional mechanism in EC, and indicates miR-210-3p an underlying target.

Greatly Enhanced Plasmon-Exciton Coupling in Si/WS2/Au Nanocavities.

A strong light-matter interaction is highly desirable from the viewpoint of both fundamental research and practical application. Here, we propose a dielectric-metal hybrid nanocavity composed of a silicon (Si) nanoparticle and a thin gold (Au) film and investigate numerically and experimentally the coupling between the plasmons supported by the nanocavity and the excitons in an embedded tungsten disulfide (WS2) monolayer. When a Si/WS2/Au nanocavity is excited by the surface plasmon polariton generated on the surface of the Au film, greatly enhanced plasmon-exciton coupling originating from the hybridization of the surface plasmon polariton, the mirror-image-induced magnetic dipole, and the exciton modes is clearly revealed in the angle- or size-resolved scattering spectra. A Rabi splitting as large as ∼240 meV is extracted by fitting the experimental data with a coupled harmonic oscillator model containing three oscillators. Our findings open new horizons for constructing nanoscale photonic devices by exploiting dielectric-metal hybrid nanocavities.

On the compromise between noise reduction and speech/noise spatial information preservation in binaural speech enhancement.

Spatial information is important for human perception of speech and sound signals. However, this information is often either distorted or completely neglected in noise reduction because it is challenging, to say the least, to achieve optimal noise reduction and accurate spatial information preservation at the same time. This paper studies the problem of binaural speech enhancement. By jointly diagonalizing the speech and noise correlation matrices, we present a method to construct the noise reduction filter as a linear combination of different eigenvectors, which span a certain subspace of the entire space. A different dimension of the subspace gives a different trade-off between noise reduction and speech/noise spatial information preservation. On the one side, if the dimension is equal to 1, maximum noise reduction is achieved but at the price of significant spatial information distortion. On the other extreme, if the dimension of the subspace is equal to that of the entire space, spatial information is accurately preserved but at the cost of no noise reduction. Therefore, one can achieve different levels of compromises between the amount of noise reduction and the level of speech/noise spatial information preservation by adjusting the dimension of the used subspace.

On microphone array beamforming and insights into the underlying signal models in the short-time-Fourier-transform domain.

This paper studies signal models for microphone array beamforming in the short-time-Fourier-transform (STFT) domain with long acoustic impulse responses. The major contributions are as follows. First, the signal modeling problem is investigated in the STFT domain and a general decomposition is proposed for the convolved source signal. Second, new insights into the array manifold are presented: the STFT of the windowed acoustic impulse response from the source to the sensors. Third, the structure of the reference signal is analyzed: it can be viewed as the output of a beamformer without considering the noise in the observation signal. Fourth, based on the new perspectives and decomposition, a signal model is derived based on the use of the superdirective beamformer. Finally, three performance measures are defined, based on which three optimal/suboptimal signal models are derived and their performance is assessed under different acoustic environments and analysis window lengths. The performance of the well-known minimum variance distortionless response (MVDR) beamformer is evaluated, which justifies the properties of the developed signal models.

On the design of differential loudspeaker arrays with broadside radiation patterns.

Loudspeaker arrays with high directivity are desirable in many acoustic and sound applications to direct sounds into a desired region. One way of designing such arrays is through the differential operator to maximize the directivity factor. However, this method generally works for linear arrays with endfire steering direction and its usage to generate a broadside radiation pattern is restricted to the second-order with three loudspeakers. This paper presents a general approach to the design of differential linear loudspeaker arrays with broadside radiation patterns of any-order. Three methods are presented to find the beamforming filter with design examples provided.

Binaural Heterophasic Superdirective Beamforming.

The superdirective beamformer, while attractive for processing broadband acoustic signals, often suffers from the problem of white noise amplification. So, its application requires well-designed acoustic arrays with sensors of extremely low self-noise level, which is difficult if not impossible to attain. In this paper, a new binaural superdirective beamformer is proposed, which is divided into two sub-beamformers. Based on studies and facts in psychoacoustics, these two filters are designed in such a way that they are orthogonal to each other to make the white noise components in the binaural beamforming outputs incoherent while maximizing the output interaural coherence of the diffuse noise, which is important for the brain to localize the sound source of interest. As a result, the signal of interest in the binaural superdirective beamformer's outputs is in phase but the white noise components in the outputs are random phase, so the human auditory system can better separate the acoustic signal of interest from white noise by listening to the outputs of the proposed approach. Experimental results show that the derived binaural superdirective beamformer is superior to its conventional monaural counterpart.

Continuously steerable differential beamformers with null constraints for circular microphone arrays.

Differential beamforming combined with microphone arrays can be used in a wide range of applications related to acoustic and speech signal acquisition and recovery. A practical and useful method for designing differential beamformers is the so-called null-constrained method, which was developed based on linear arrays and requires only the nulls' information from the target directivity pattern. While it is effective and easy to use, this method is found not suitable for designing steerable differential beamformers with circular arrays. This paper reexamines this technique in the context of circular differential microphone arrays. By analyzing the properties of the circular array topology, the null-constrained method is extended to include symmetric constraints, which is inherent in the design of circular arrays. This extension yields a design method for fully steerable differential beamformers that require only minimum information from the target beampattern. Simulations justify the theoretical analysis and demonstrate the good properties of the developed method.

Design and experimental analysis of dual-band polarization converting metasurface for microwave applications.

The manipulation of polarization state of electromagnetic waves is of great importance in many practical applications. In this paper, the reflection characteristics of a thin and dual-band metasurface are examined in the microwave frequency regime. The metasurface consists of a 22 × 22 element array of periodic unit cells. The geometry of the unit cell consists of three layers, including a 45° inclined dipole shape metal patch on top, which is backed by a 1.6 mm thick FR-4 substrate in the middle, and a fully reflective metallic mirror at the bottom. The proposed surface is exposed to horizontally (x) or vertically (y) polarized plane waves and the co and cross polarization reflection coefficients of the reflected waves are investigated experimentally in the 6-26 GHz frequency range. The metasurface is designed to convert incident waves of known polarization state (horizontal or vertical) to orthogonal polarization state (vertical and horizontal) in two distinct frequency bands, i.e. 7.1-8 GHz and 13.3-25.8 GHz. In these two frequency bands the simulated and experimental results are in good agreement. The polarization conversion ratio (PCR) of the surface is greater than 95% in the targeted frequency bands. A detailed parametric analysis of the metasurface is also discussed in this work and it has been estimated that the surface has the additional ability to convert linearly polarized waves to circularly polarized waves at several distinct frequencies. The proposed metasurface can be utilized in sensor applications, stealth technology, electromagnetic measurements, and antennas design.

Model-based distributed node clustering and multi-speaker speech presence probability estimation in wireless acoustic sensor networks.

The knowledge of speech presence probability (SPP) plays an essential role in noise estimation and speech enhancement. Single channel SPP estimation and centralized multi-channel SPP estimation have been well studied. However, how to estimate SPP in wireless acoustic sensor networks (WASNs) remains a great challenge and few efforts can be found in this topic, particularly for WASN applications with multiple speakers. Accordingly, this paper is devoted to the problem of SPP estimation in WASNs and it presents a distributed model-based SPP estimation method for multi-speaker detection, which does not need any fusion center. A distributed k-means clustering method is first used to cluster the nodes into subnetworks, which detect different speakers. For each node in the subnetwork, the speech and noise power spectral densities are estimated locally by using a model-based method, then a distributed SPP estimator is developed and applied in every subnetwork. A distributed consensus method is used to obtain the distributed clustering and the distributed SPP estimation. Simulation results show that the proposed distributed clustering method can assign nodes into subnetworks based on their noisy observations. Moreover, the proposed distributed SPP estimator achieves robust speech detection performance under different noise conditions.

Metabolic disparities of different oxidative stress­inducing conditions in HTR8/SVneo cells.

Placental oxidative stress is present throughout the duration of pregnancy, but it is when oxidative stress exceeds the normal physiological level that complications can occur. Trophoblast cell lines are commonly utilized for oxidative stress research due to their distinct uniform cell population and easy­to­apply interventions. However, conflicting results are often reported when different oxidative stress cell models are used. In this study, the aim was to characterize the intracellular and extracellular metabolite profiles of different oxidative stress cell models commonly used in the research of pregnancy complications. HTR8/SVneo human trophoblast cell lines were treated with five different oxidative stress­inducing conditions: Hypoxia (1% oxygen); hypoxia and reoxygenation; cobalt chloride (CoCl2; 300 µmol/l); sodium nitroprusside (SNP; 2.5 mmol/l); and the serum of women with preeclampsia (10% v/v). Intracellular metabolites were extracted from cells and extracellular metabolites were collected from spent media for metabolomic analysis via gas chromatography­mass spectrometry. The results demonstrated that there were distinct differences in the intracellular and extracellular metabolome between the different cell models. Meanwhile, treatments with exogenous drugs, such as CoCl2 and SNP, resulted in more similar metabolite profiles. These disparities between the different oxidative stress cell models will have implications for the applications of these results, and highlight the need for the standardization of oxidative stress cell models in obstetric research.

Window-Based Constant Beamwidth Beamformer.

Beamformers have been widely used to enhance signals from a desired direction and suppress noise and interfering signals from other directions. Constant beamwidth beamformers enable a fixed beamwidth over a wide range of frequencies. Most of the existing approaches to design constant beamwidth beamformers are based on optimization algorithms with high computational complexity and are often sensitive to microphone mismatches. Other existing methods are based on adjusting the number of sensors according to the frequency, which simplify the design, but cannot control the sidelobe level. Here, we propose a window-based technique to attain the beamwidth constancy, in which different shapes of standard window functions are applied for different frequency bins as the real weighting coefficients of microphones. Thereby, not only do we keep the beamwidth constant, but we also control the sidelobe level. Simulation results show the advantages of our method compared with existing methods, including lower sidelobe level, higher directivity factor, and higher white noise gain.