Search

A massive mortality event concerning farmed Chinese tongue soles occurred in Tianjin, China, and the causative agent remains unknown. Here, a novel Cynoglossus semilaevis papillomavirus (CsPaV) and parvovirus (CsPV) were simultaneously isolated and identified from diseased fish via electron microscopy, virus isolation, genome sequencing, experimental challenges, and fluorescence in situ hybridization (FISH). Electron microscopy showed large numbers of virus particles present in the tissues of diseased fish. Viruses that were isolated and propagated in flounder gill cells (FG) induced typical cytopathic effects (CPE). The cumulative mortality of fish given intraperitoneal injections reached 100% at 7 dpi. The complete genomes of CsPaV and CsPV comprised 5939 bp and 3663 bp, respectively, and the genomes shared no nucleotide sequence similarities with other viruses. Phylogenetic analysis based on the L1 and NS1 protein sequences revealed that CsPaV and CsPV were novel members of the Papillomaviridae and Parvoviridae families. The FISH results showed positive signals in the spleen tissues of infected fish, and both viruses could co-infect single cells. This study represents the first report where novel papillomavirus and parvovirus are identified in farmed marine cultured fish, and it provides a basis for further studies on the prevention and treatment of emerging viral diseases.

This paper considers a multi-user multiple-input multiple-output (MU-MIMO) system with independent phase noise (PN) at user terminals (UTs) due to non-synchronous noisy local oscillators. The conventional factor graph of MU-MIMO involves an observation factor with multiple high-dimensional variables in the form of multiplication and summation. In this work, the MU-MIMO factor graph is represented by introducing auxiliary variables, which enables the decomposition of the observation factor into several simpler sub-factors and then use different message passing techniques to obtain approximate marginals. Specifically, belief propagation and expectation propagation (BP-EP) are used for the linear factors for random walk process, modulation and coding, while mean field (MF) is used for non-linear factor in exponential form. To reduce the computational complexity, the non-Gaussian MF messages are approximated to be Gaussian by using the second order Taylor expansion at its belief obtained in the previous iteration. The proposed receiver has a quadratic computational complexity per symbol per iteration. Simulation results show that the performance of the proposed receiver is better than existing methods and is close to the matched filter bound (MFB) in terms of the bit error rate (BER).

A novel method for the generation of an optical frequency comb (OFC) is presented. The proposed approach uses a laser diode with optical feedback and operating at a specific nonlinear dynamic state named periodic window. In this case, the laser spectrum exhibits a feature with a series of discrete, equally spaced frequency components, and the repetition rate can be flexibly adjusted by varying the system parameters (e.g., external cavity length), which can provide many potential applications. As an application example, a dual-OFC system for distance measurement is presented. The results demonstrate the system’s ability to achieve target distance detection, underscoring its potential for real-world applications in this field.

In this study, a multiple-dimensional displacement measurement technology is demonstrated by using self-mixing interferometry (SMI) cooperating with a frequency division multiplexing (FDM) technique. The proposed SMI configuration with a single laser generates three modulated light beams with different carrier frequencies. Each beam is incident on a planar grating with its own auto-collimation diffraction angle. The diffracted beams return to the laser cavity and then self-mixing interference occurs. An algorithm based on FDM is developed for multiple-dimensional displacement reconstruction from a single SMI signal. Experiments are conducted to verify the proposed approach. This paper shows an attractive sensing system for multiple-dimensional displacement featuring compact configuration, high resolution and better immunity to environmental disturbances.

Fringe projection profilometry (FPP) has been widely studied for measurements of three-dimensional (3D) shapes. However, the measurement of moving objects is still a challenging problem associated with commonly used methods. Phase-shifting profilometry (PSP) suffers from motion-induced errors when applied to moving objects, while Fourier transform profilometry (FTP) is sensitive to background light and noise. This paper proposes a novel data fusion approach to improve the measurement of moving objects by alleviating noise-induced errors. Firstly, a set of coarse measurements on the shape of the object are obtained at different time instants by FTP. Then the parameters associated with the motion of the object over these time instants are retrieved from these coarse estimates by applying the iterative closest point (ICP) method. Finally, the parameters are utilized to adaptively fuse the coarse measurements based on their quality. Simulations and experiments verify that the proposed approach can significantly improve the measurement accuracy.

Temporal phase unwrapping is among the most robust and efficient phase unwrapping methods in fringe projection profilometry. They can recover the fringe orders even in the presence of surface discontinuities. However, fringe order errors may occur due to phase noise and poor measurement conditions. Such errors often exhibit an impulsive nature and introduce errors to the absolute phase map. Most existing fringe order error correction methods detect and correct the errors in a pixel-by-pixel manner, which may under-utilize the correlation of the fringe orders on different pixels. In this paper, we propose a new method to cope with the fringe order errors associated with temporal phase unwrapping. By exploiting the low-rankness of the fringe order map and sparse nature of the impulsive fringe order errors, we develop a robust principal component analysis (RPCA)-based approach to remove the impulsive fringe order errors. Experiments demonstrate that the proposed method is valid in eliminating the fringe order errors.

Using self-mixing interferometry (SMI) with a periodical modulated injection current, high resolution displacement sensing can be achieved by retrieving the initial phase of an SMI signal at each modulation period. However, the existing initial-phase-based detection methods can only obtain a single point measurement of displacement within each single modulation period. Thus, they are only effective when the target is subject to slow movement, or the injection current is modulated by a signal of very high frequency, which are not practical in many applications. In this work, a new method is proposed to tackle the problem. Firstly, a reference signal is obtained by setting the target still. Then Fast Fourier Transform and its inverse (FFT/IFFT) are applied to the reference signal and the SMI signal, leading to a formulation to obtain the SMI signal phase, which enables the SMI system to retrieve the time varying displacement in each modulation period. As the proposed method is able to measure displacement at multiple discrete time instances (dependent on the number of samples for FFT), the measurement resolution is significantly improved over existing method. Hence, the measurement capability of the SMI system is enhanced greatly. Both simulation and experiments are conducted and the results are presented to verify the proposed algorithm.

Precision matrix, i.e., inverse covariance matrix, is widely used in signal processing, and often estimated from training samples. Regularization techniques, such as banding and rank reduction, can be applied to the covariance matrix or precision matrix estimation for improving the estimation accuracy when the training samples are limited. In this paper, exploiting regression interpretations of the precision matrix, we introduce two data-driven, distribution-free methods to tune the parameter for regularized precision matrix estimation. The numerical examples are provided to demonstrate the effectiveness of the proposed methods and example applications in the design of minimum mean squared error (MMSE) channel estimators for large-scale multiple-input multiple-output (MIMO) communication systems are demonstrated.

Self-mixing interferometry (SMI) is a promising sensing technology. As well as its compact structure, self-alignment and low implementation cost, it has an important advantage that conventional two-beam interferometry does not have, i.e., SMI signal fringe evolves into asymmetrical shape with increasing optical feedback level, which leads to discrimination of target movement directions for unambiguous displacement measurement possible by a single-channel interferometric signal. It is usually achieved by using SMI signals in moderate feedback regime, where the signals exhibit hysteresis and discontinuity. However, in some applications, e.g., in biomedical sensing where the target has a low reflectivity, it is hard for the SMI system to operate in a moderate feedback regime. In this work, we present comprehensive analyses on SMI signal waveforms for determining system parameters and movement directions by a single-channel weak feedback SMI signal. We first investigated the influence of two system parameters, i.e., linewidth enhancement factor and optical feedback factor, on the symmetry of SMI signals. Based on the analyses on signal waveform, we then proposed a method of estimating the system parameters and displacement directions. The method was finally verified by experiments. The results are helpful for developing sensing applications based on weak feedback SMI systems.

In this study, a novel distance sensing method is presented by using a semiconductor laser (SL) with optical feedback (OF) and operating the SL at a switching status happened between two nonlinear dynamic states (stable state and period-one state). In this case, without the need for any electronic or optical modulation devices, the laser intensity can be modulated in a square wave form due to the switching via utilizing the inherent SL dynamics. The periodicity in the switching enables us to develop a new approach for long-distance sensing compared to other SL with OF-based distance measurement systems and lift the relevant restrictions that existed in the systems. Moreover, the impact of system controllable parameters on the duty cycle of the square wave signals generated was investigated on how to maintain the proposed system robustly operating at the switching status. Both simulation and experiment verified the proposed sensing approach.

When a part of light emitted by a laser is back-reflected or back-scattered from an external target and re-enters the laser cavity, both the laser intensity and its wavelength can be modulated. This is so-called self-mixing effect (SME). An SME-based displacement sensor is featured with compact physical setup and interferometric measurement resolution. However, when a target has a surface with very low reflectivity, the sensing signal is very weak and noisy. The system may even lose its sensing capability. It is desired to develop a method for improving the sensing performance in this case. We propose a configuration of dual external cavities for the SME-based sensing system, where one of the cavities is used to provide prefeedback for improving the sensing sensitivity and the other is related to the target to be measured. First, a sensing model is derived for the proposed configuration and shows that the magnitude of the sensing signal can be enhanced by setting the prefeedback cavity with suitable location and high optical feedback strength. Then, experimental investigations are conducted to demonstrate the feasibility of the proposed approach. This paper provides an important guidance for designing an SME-based sensor with high sensitivity.

The light-emitting diode (LED) is the major source of nonlinearity in LED communications, and the nonlinearity needs to be effectively modeled and mitigated to avoid the degradation of communication performance. In indoor LED communications, multipath dispersion can lead to inter-symbol interference (ISI) at high data rates. In this paper, we jointly estimate the LED nonlinearity and ISI channel based on an orthogonal polynomial based technique. Then, frequency domain equalization and post-distortion are adopted to mitigate the ISI and nonlinearity. Simulation results are provided to demonstrate the effectiveness of the proposed technique.

Hybrid massive MIMO structures with reduced hardware complexity and power consumption have been widely studied as a potential candidate for millimeter wave communications. Channel estimators that require knowledge of the array response, such as those using compressive sensing (CS) methods, may suffer from performance degradation when array-inherent impairments bring unknown phase errors and gain errors to the antenna elements. In this paper, we design matrix completion (MC)-based channel estimation schemes which are robust against the array-inherent impairments. We first design an open-loop training scheme that can sample entries from the effective channel matrix randomly and is compatible with the phase shifter-based hybrid system. Leveraging the low-rank property of the effective channel matrix, we then design a channel estimator based on the generalized conditional gradient framework and the alternating minimization approach. The resulting estimator is immune to array-inherent impairments and can be implemented to systems with any array shapes for its independence of the array response. In addition, we extend our design to sample a transformed channel matrix following the concept of inductive matrix completion (IMC), which can be solved efficiently using our proposed channel estimator and can achieve similar performance with a lower requirement of the dynamic range of the transmission power per antenna. Numerical results demonstrate the advantages of our proposed MC-based channel estimator in terms of estimation performance, computational complexity, and robustness against array-inherent impairments over the orthogonal matching pursuit-based CS channel estimator.

The light-emitting diode (LED) is the major source of nonlinearity in LED communications, and the nonlinearity needs to be effectively modeled and thereby mitigated through predistortion or postdistortion to avoid degradation of communication performance. A memory polynomial is often used for LED nonlinearity modeling and mitigation in the literature. However, the estimation of memory polynomial coefficients suffers from numerical instability, resulting in inaccurate modeling and poor performance in nonlinearity mitigation. In this paper, we propose an orthogonal polynomial-based nonlinearity modeling and mitigation technique for LED communications with pulse amplitude modulation (PAM) signaling and show that the proposed technique significantly outperforms the conventional memory polynomial-based techniques.

A novel Dual-frequency Doppler LiDAR (DFDL) is presented where the dual-frequency light source is generated by using external optical feedback (EOF) effect in a laser diode (LD). By operating a LD at period-one (P1) state and choosing suitable LD related parameters, a dual-frequency light source can be achieved. Such a dual-frequency source has advantages of the minimum part-count scheme, low cost in implementation, and ease in optical alignment. Theory and system design are presented for the proposed DFDL for velocity measurement with high measurement resolution. The proposed design has a potential contribution to the Light Detection And Ranging (LiDAR) in practical engineering applications.

Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as potential candidates for millimeter wave (mmWave) communications. Channel covariance information can be used for designing transmitter precoders, receiver combiners, channel estimators, etc. However, hybrid structures allow only a lower-dimensional signal to be observed, which adds difficulties for channel covariance matrix estimation. In this paper, we formulate the channel covariance estimation as a structured low-rank matrix sensing problem via Kronecker product expansion and use a low-complexity algorithm to solve this problem. Numerical results with uniform linear arrays (ULA) and uniform squared planar arrays (USPA) are provided to demonstrate the effectiveness of our proposed method.

This paper presents a new method for measuring the linewidth enhancement factor (alpha factor) by the relaxation oscillation (RO) frequency of a laser with external optical feedback (EOF). A measurement formula for alpha is derived which shows the alpha can be determined by only using the RO frequencies and no need to know any other parameters related to the internal or external parameters associated to the laser. Unlike the existing EOF based alpha measurement methods which require an external target has a symmetric reciprocate movement. The proposed method only needs to move the target to be in a few different positions along the light beam. Furthermore, this method also suits for the case with alpha less than 1. Both simulation and experiment are performed to verify the proposed method.

Fiber Bragg grating (FBG) is considered a good candidate for acoustic emission (AE) measurement. The sensing and measurement in traditional FBG-based AE systems are based on the variation in laser intensity induced by the Bragg wavelength shift. This paper presents a sensing system by combining self-mixing interference (SMI) in a laser diode and FBG for AE measurement, aiming to form a new compact and cost-effective sensing system. The measurement model of the overall system was derived. The performance of the presented system was investigated from both aspects of theory and experiment. The results show that the proposed system is able to measure AE events with high resolution and over a wide dynamic frequency range.

When a fraction of the light reflected by an external cavity re-enters the laser cavity, both the amplitude and the frequency of the lasing field can be modulated. This phenomenon is called the self-mixing effect (SME). A self-mixing laser diode (SM-LD) is a sensor using the SME. Usually, such LDs operate below the stability boundary where no relaxation oscillation happens. The boundary is determined by the operation condition including the injection current, optical feedback strength and external cavity length. This paper discovers the features of an SM-LD where the LD operates beyond the stability boundary, that is, near the relaxation oscillation (RO) status. We call the signals from such a SM-LD as RO-SM signals to differentiate them from the conventional SM signals reported in the literature. Firstly, simulations are made based on the well-known Lang and Kobayashi (L-K) equations. Then the experiments are conducted on different LDs to verify the simulation results. It shows that a RO-SM signal exhibits high frequency oscillation with its amplitude modulated by a slow time varying envelop which corresponds to the movement of the external target. The envelope has same fringe structure (half-wavelength displacement resolution) with the conventional SM signals. However, the amplitudes of the RO-SM signals are much higher compared to conventional SM signals. The results presented reveal that an SM-LD operating near the RO has potential for achieving sensing with improved sensitivity.

This paper presents the design of a fiber-coupled self-mixing laser diode (SMLD) for non-contact and non-destructive measurement of Young’s modulus. By the presented measuring system, the Young’s modulus of aluminum 6061 and brass are measured as 70.0 GPa and 116.7 GPa, respectively, showing a good agreement within the standards in the literature and yielding a much smaller deviation and a higher repeatability compared with traditional tensile testing. Its fiber-coupled characteristics make the system quite easy to be installed in many application cases.