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Rapeseed is a crucial oil crop globally, and in recent years, abiotic stress has increasingly affected its growth, development, yield, and quality. Salt stress is a significant abiotic factor that restricts crop production. The EPF gene family is vital in managing salt stress by controlling stomatal development and opening, which reduces water loss and increases plant salt tolerance. To explore the features of the EPF gene family in Brassica napus and their expression under salt stress, this study utilized Arabidopsis EPF protein sequences as seed sequences, including their PF17181 and PF16851 domains. A total of 27 members of the EPF gene family were detected within the rapeseed genome. The study examined the physicochemical properties, gene structure, phylogenetic relationships, and collinearity of BnEPFs . Through transcriptomes, we employed the qPCR method to determine the relative expression levels of BnEPF genes potentially associated with rapeseed stress resistance under both non-salt and salt stress conditions. Subsequently, we assessed their influence on rapeseed plants subjected to salt stress. During salt stress conditions, all BnEPF genes displayed a downregulation trend, indicating their potential impact on stomatal development and signal transduction pathways, consequently improving rapeseed's resistance to salt stress. The study findings establish a basis for exploring the roles of BnEPFs and offer candidate genes for breeding stress-resistant varieties and enhancing the yield in rapeseed.

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., (© 2024 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd.)

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., (© 2024 Acoustical Society of America.)

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., (© 2024. The Author(s).)

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.

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., (© 2023 Acoustical Society of America.)

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.

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.

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.

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., Competing Interests: Conflicts of interest The authors do not have any possible conflicts of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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.

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.

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.

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.

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.

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.

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.

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 easy‑to‑apply 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 stress‑inducing 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 chromatography‑mass 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.

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.

We proposed the use of the evanescent wave generated in a total internal reflection configuration to excite large gold nanospheres and investigated the radiations of the high-order plasmon modes supported in gold nanospheres. It was revealed that the evanescent wave excitation is equivalent to the excitation by using both the incident and reflected light, offering us the opportunity to control the orientation of the electric field used to excite nanoparticles. In addition, it was found that the scattering light intensity is greatly enhanced and the background noise is considerably suppressed, making it possible to detect the radiations from high-order plasmon modes. Moreover, the influence of the mirror images on the scattering induced by a metal substrate is eliminated as compared with the surface plasmon polariton excitation. By exciting a gold nanosphere with s -polarized light and detecting the scattering light with a p -polarized analyzer, we were able to reveal the radiation from the electric quadrupole mode of the gold nanosphere in both the spatial and the frequency domains. Our findings are important for characterizing the radiations from the high-order modes of large nanoparticles and useful for designing nanoscale photonic devices.

Microphone arrays are typically used in room acoustic environments to acquire high fidelity audio and speech signals while suppressing noise, interference, and reverberation. In many application scenarios, interference and reverberation may mainly come from a certain region, and it is therefore necessary to develop beamformers that can preserve signals of interest while minimizing the power of signals coming from the region where interference and reverberation dominate. For this purpose, this paper first reexamines the so-called front-to-back ratio and the classical supercardioid beamformer. To deal with the white noise amplification problem and the limited directivity factor associated with the supercardioid beamformer, a set of reduced-rank beamformers are deduced by using the well-known joint diagonalization technique, which can make compromises between the front-to-back ratio and the amount of white noise amplification or the directivity factor. Then, the definition of the front-to-back ratio is extended to a generalized version, from which another set of reduced-rank beamformers and their regularized versions are developed. Simulations are conducted to illustrate the properties and advantages of the proposed beamformers.

We conduct DNA high-resolution melting (HRM) analysis using optofluidic lasers based on a Fabry-Pérot microcavity. Compared to the fluorescence-based HRM, the laser-based HRM has advantages of higher emission intensity for better signal-to-noise ratio and sharper transition for better temperature resolution. In addition, the melting temperature can be lowered by optimizing the laser conditions such as external pump and cavity Q-factor. In this work, we first theoretically analyze the laser-based HRM. Then experiments are performed on three long DNA sequences as model systems, one being 99 bases and the other two being 130 bases long but with different GC contents. We show that the laser-based HRM is able to distinguish the target and the single-base mismatched DNA as long as 130 bases and with nearly 50% GC content. The dependence of laser threshold on the temperature for each DNA sample is first experimentally investigated and by optimizing the external pump, the melting temperature is reduced by more than 10 °C, compared to the fluorescence-based HRM for long DNA sequences up to 130 bases. Finally, we demonstrate an alternative method of using the laser-based HRM for rapid DNA screening that does not exist for the fluorescence-based HRM, in which laser excitation is scanned at a fixed temperature to distinguish the target and the base-mismatched DNA sequences. It is shown that the 130-bases-long DNA with nearly 50% GC content can have as much as 20% difference in the laser threshold and 40% difference in the laser output slope between the target and the single-base mismatched sequences, despite only 0.5 °C difference in their melting temperature, indicating that the laser-excitation-scanning method can also be suitable for long DNA sequences with higher GC content.

This letter deals with the problem of differential beamforming with microphone arrays of arbitrary planar geometry. By approximating the beampattern with the Jacobi-Anger expansion, it develops an algorithm that can form any specified frequency-invariant beampattern with a microphone array of any planar geometry as long as the sensors' coordinates are given and the spacing between neighboring sensors is smaller than the smallest wavelength. This method is rather general and it can be used to design differential beamformers with linear, circular, and concentric circular differential microphone arrays as well as differential arrays of arbitrary planar geometry where sensors are placed in any specified positions.

This paper develops an approach to beamforming with small spacing uniform linear microphone arrays based on the null-steering (NS) principle. It first formulates the beamforming problem from the conventional mean-squared error (MSE) criterion and its normalized version. Several NS algorithms are then derived for beamforming with the constraint of placing nulls to either a single direction or multiple angles. The difference and relationships between different algorithms are discussed and their performances are evaluated. These algorithms can be used to design either fixed or adaptive beamformers. In the former case, the resulting beamformers work as differential microphone arrays (DMAs) since they exhibit frequency-invariant beampatterns and their directivity factors are high with a given number of sensors. In the latter case, the resulting beamformers can be viewed as a combination of DMAs and single-channel noise reduction since they do not only exhibit frequency-invariant beampatterns but also can achieve noise reduction based on the noise statistics.

The maximum directivity (MD) beamformer with spherical microphone arrays has many salient features in processing broadband acoustic and speech signals while suppressing noise and reverberation; but it is sensitive to sensors' self-noise and mismatch among these sensors. One effective way to deal with this sensitivity is by increasing the number of microphones, thereby improving the so-called white noise gain (WNG), but this increase may lead to many other design issues in terms of cost, array aperture, and possibly other performance degradation. This paper is tackling this sensitivity problem and presents a flexible high directivity (HD) beamforming algorithm. By approximating the ideal directivity pattern and the beamformer's beampattern with spherical harmonic series, the relationship between the two is obtained. This relationship is subsequently used to deduce a flexible HD beamformer, which can improve the WNG while achieving a directivity factor (DF) between the DF of an Nth-order MD beamformer and that of an (N-1)th-order MD one. Also derived is the analytical link between the DF and a tuning parameter and the link between the WNG and this parameter. Based on these links, one can easily determine the optimal value of the tuning parameter once the value of the DF or the WNG is specified.

Significantly enhanced electric field in plasmonic hot spots can dramatically increase the linear and nonlinear absorption of light, leading to a high-temperature electron gas which radiates, through mainly intraband transition, a broadband luminescence quite similar to blackbody radiation. Here, we demonstrate that such hot-electron intraband luminescence (HEIL) can also be achieved by exploiting the significantly enhanced electric field at the magnetic dipole resonances of gallium arsenide (GaAs) nanospheres (NSs). We show that monocrystalline GaAs NSs with distinct electric and magnetic dipole (ED and MD) resonances can be obtained by using femtosecond laser ablation and annealing. Significantly enhanced second harmonic generation and broadband HEIL are observed when the MD resonances of such GaAs NSs are resonantly excited. The lifetime of the HEIL is found to be as short as ∼82 ps, indicating a significant enhancement in radiative intraband transition rate. We reveal that the slope extracted from the dependence of the HEIL intensity on the irradiance is linearly proportional to the energy of the emitted photon. The existence of distinct ED and MD resonances in combination with a direct bandgap makes GaAs NSs an attractive candidate for constructing novel all-dielectric metamaterials and active photonic devices.

Circular differential microphone arrays (CDMAs) have been extensively studied in speech and audio applications for their steering flexibility, potential to achieve frequency-invariant directivity patterns, and high directivity factors (DFs). However, CDMAs suffer from both white noise amplification and deep nulls in the DF and in the white noise gain (WNG) due to spatial aliasing, which considerably restricts their use in practical systems. The minimum-norm filter can improve the WNG by using more microphones than required for a given differential array order; but this filter increases the array aperture (radius), which exacerbates the spatial aliasing problem and worsens the nulls problem in the DF. Through theoretical analysis, this research finds that the nulls of the CDMAs are caused by the zeros in the denominators of the filters' coefficients, i.e., the zeros of the Bessel function. To deal with both the white noise amplification and deep nulls problems, this paper develops an approach that combines different rings of microphones together with appropriate radii. The resulting robust concentric circular differential microphone arrays (CCDMAs) can mitigate both problems. Simulation results justify the superiority of the robust CCDMA approach over the traditional CDMAs and robust CDMAs.

This paper presents an approach to the direction-of-arrival (DOA) estimation problem in acoustic environments using microphone arrays. It works in the short-time Fourier transform (STFT) domain. It first transforms the noisy speech signals received at the array into the STFT domain. A Householder transformation is then constructed and applied to the multichannel STFT coefficients in each subband. This transformation converts the multichannel STFT coefficients into two components: one is a single coefficient that is dominated by the signal of interest and the other consists of the M - 1 coefficient that is dominated by noise (or even consists of noise-only if there is no reverberation), where M is the number of sensors. A cost function is then formed from the outputs of the Householder transformation and the DOA information can subsequently be obtained by searching the extremum value of this cost function in the angle range between 0° and 180°. Simulation results are provided to illustrate the performance of this approach.

We report the development of an optofluidic laser array fabricated on a chip using stable plano-concave Fabry-Pérot (FP) microcavities, which are far less susceptible to optical misalignment during device assembly than the commonly used plano-plano FP microcavities. The concave mirrors in our FP microcavities were created by first generating an array of microwells of a few micrometers in depth and a few tens of micrometers in diameter on a fused silica chip using a CO2 laser, followed by coating of distributed Bragg reflection (DBR) layers. The plano-concave FP microcavity had a Q-factor of 5.6 × 10(5) and finesse of 4 × 10(3), over 100 times higher than those for the FP microcavities in existing optofluidic lasers. 1 mM R6G dye in ethanol was used to test the plano-concave FP microcavities, showing an ultralow lasing threshold of only 90 nJ mm(-2), over 10 times lower than that in the corresponding unstable plano-plano FP microcavities formed by the same DBR coatings on the same chip. Simultaneous laser emission from the optofluidic laser array on the chip and single-mode lasing operation were also demonstrated. Our work will lead to the development of optofluidic laser-based biochemical sensors and novel on-chip photonic devices with extremely low lasing thresholds (nJ mm(-2)) and mode volumes (fL).

Differential microphone arrays have the potential to be widely deployed in hands-free communication systems thanks to their frequency-invariant beampatterns, high directivity factors, and small apertures. Traditionally, they are designed and implemented in a multistage way with uniform linear geometries. This paper presents an approach to the design of differential microphone arrays with orthogonal polynomials, more specifically with Jacobi polynomials. It first shows how to express the beampatterns as a function of orthogonal polynomials. Then several differential beamformers are derived and their performance depends on the parameters of the Jacobi polynomials. Simulations show the great flexibility of the proposed method in terms of designing any order differential microphone arrays with different beampatterns and controlling white noise gain.

This paper develops a multistage approach to the implementation of the minimum variance distortionless response (MVDR) beamformer. It first divides the microphone array of M sensors into M/2 subarrays with each subarray having only two microphones, and a two-channel MVDR beamformer is performed with each subarray. The M/2 subarrays' outputs are then treated as the inputs of M/4 subarrays of two channels in the next stage. Similarly, a two-channel MVDR beamformer is performed with each subarray in the second stage. This process is repeated till the last stage that has only a single output. This multistage MVDR beamformer has the following properties: (1) Its performance is identical to that of the conventional MVDR beamformer in spatially uncorrelated noise; (2) it is much more robust than the conventional MVDR beamformer in diffuse noise, i.e., it has a significantly higher white noise gain as compared to the traditional MVDR beamformer; and (3) its complexity is an order of magnitude smaller than that of the traditional MVDR beamformer. This basic principle can also be easily generalized to the case where every subarray has more than two microphones.

This paper proposes a sparse linear prediction based algorithm to estimate time difference of arrival. This algorithm unifies the cross correlation method without prewhitening and that with prewhitening via an ℓ2/ℓ1 optimization process, which is solved by an augmented Lagrangian alternating direction method. It also forms a set of time delay estimators that make a tradeoff between prewhitening and non-prewhitening through adjusting a regularization parameter. The effectiveness of the proposed algorithm is demonstrated in noisy and reverberant environments.

Differential microphone array (DMA), a particular kind of sensor array that is responsive to the differential sound pressure field, has a broad range of applications in sound recording, noise reduction, signal separation, dereverberation, etc. Traditionally, an Nth-order DMA is formed by combining, in a linear manner, the outputs of a number of DMAs up to (including) the order of N - 1. This method, though simple and easy to implement, suffers from a number of drawbacks and practical limitations. This paper presents an approach to the design of linear DMAs. The proposed technique first transforms the microphone array signals into the short-time Fourier transform (STFT) domain and then converts the DMA beamforming design to simple linear systems to solve. It is shown that this approach is much more flexible as compared to the traditional methods in the design of different directivity patterns. Methods are also presented to deal with the white noise amplification problem that is considered to be the biggest hurdle for DMAs, particularly higher-order implementations.

Blind multichannel identification is generally sensitive to background noise. Although there have been some efforts in the literature devoted to improving the robustness of blind multichannel identification with respect to noise, most of those works assume that the noise is Gaussian distributed, which is often not valid in real room acoustic environments. This paper deals with the more practical scenario where the noise is not Gaussian. To improve the robustness of blind multichannel identification to non-Gaussian noise, a robust normalized multichannel frequency-domain least-mean M-estimate algorithm is developed. Unlike the traditional approaches that use the squared error as the cost function, the proposed algorithm uses an M-estimator to form the cost function, which is shown to be immune to non-Gaussian noise with a symmetric α-stable distribution. Experiments based on the identification of a single-input/multiple-output acoustic system demonstrate the robustness of the proposed algorithm.

Blood analysis plays a major role in medical and science applications and white blood cells (WBCs) are an important target of analysis. We proposed an integrated microfluidic chip for direct and rapid trapping WBCs from whole blood. The microfluidic chip consists of two basic functional units: a winding channel to mix and arrays of two-layer trapping structures to trap WBCs. Red blood cells (RBCs) were eliminated through moving the winding channel and then WBCs were trapped by the arrays of trapping structures. We fabricated the PDMS (polydimethylsiloxane) chip using soft lithography and determined the critical flow velocities of tartrazine and brilliant blue water mixing and whole blood and red blood cell lysis buffer mixing in the winding channel. They are 0.25 μl/min and 0.05 μl/min, respectively. The critical flow velocity of the whole blood and red blood cell lysis buffer is lower due to larger volume of the RBCs and higher kinematic viscosity of the whole blood. The time taken for complete lysis of whole blood was about 85 s under the flow velocity 0.05 μl/min. The RBCs were lysed completely by mixing and the WBCs were trapped by the trapping structures. The chip trapped about 2.0 × 10(3) from 3.3 × 10(3) WBCs.

This paper studies the problem of single-channel noise reduction in the time domain and presents a block-based approach where a vector of the desired speech signal is recovered by filtering a frame of the noisy signal with a rectangular filtering matrix. With this formulation, the noise reduction problem becomes one of estimating an optimal filtering matrix. To achieve such estimation, a method is introduced to decompose a frame of the clean speech signal into two orthogonal components: One correlated and the other uncorrelated with the current desired speech vector to be estimated. Different optimization cost functions are then formulated from which non-causal optimal filtering matrices are derived. The relationships among these optimal filtering matrices are discussed. In comparison with the classical sample-based technique that uses only forward prediction, the block-based method presented in this paper exploits both the forward and backward prediction as well as the temporal interpolation and, therefore, can improve the noise reduction performance by fully taking advantage of the speech property of self correlation. There is also a side advantage of this block-based method as compared to the sample-based technique, i.e., it is computationally more efficient and, as a result, more suitable for practical implementation.

This paper addresses the problem of noise reduction in the time domain where the clean speech sample at every time instant is estimated by filtering a vector of the noisy speech signal. Such a clean speech estimate consists of both the filtered speech and residual noise (filtered noise) as the noisy vector is the sum of the clean speech and noise vectors. Traditionally, the filtered speech is treated as the desired signal after noise reduction. This paper proposes to decompose the clean speech vector into two orthogonal components: one is correlated and the other is uncorrelated with the current clean speech sample. While the correlated component helps estimate the clean speech, it is shown that the uncorrelated component interferes with the estimation, just as the additive noise. Based on this orthogonal decomposition, the paper presents a way to define the error signal and cost functions and addresses the issue of how to design different optimal noise reduction filters by optimizing these cost functions. Specifically, it discusses how to design the maximum SNR filter, the Wiener filter, the minimum variance distortionless response (MVDR) filter, the tradeoff filter, and the linearly constrained minimum variance (LCMV) filter. It demonstrates that the maximum SNR, Wiener, MVDR, and tradeoff filters are identical up to a scaling factor. It also shows from the orthogonal decomposition that many performance measures can be defined, which seem to be more appropriate than the traditional ones for the evaluation of the noise reduction filters.