Molecular characterization of chemosensory protein genes in Bactrocera minax (Diptera: Tephritidae)

Wang Zhao‐Xiang,Qi Zhen‐hua,Chen Jian,Wang Fu‐Lian,Gui Lian‐You,Zhang Guo‐Hui 한국곤충학회 2021 Entomological Research Vol.51 No.7

Chemoreception is of great importance for survival of insects. Chemosensory proteins (CSPs) are believed to be involved in the perireceptor events of chemosensory system in many insect species, but this has not been clarified in the citrus fruit fly, Bactrocera minax, a serious dipteran pest of citrus crops. Previous studies indicated that four CSP genes were identified in many fly speices in Diptera. In the present study, we also identified four CSP genes in B. minax,namely BminCSP1–4, from a transcriptome database. All CSP proteins encoded by these genes bear the typical hallmarks of the CSP family: an N-terminal signal peptide and the four highly conserved cysteine residues. Phylogenetic analysis comparing with other dipteran CSPs indicated that dipteran CSPs may evolved from three ancestral CSP genes, and revealed the sequence diversities of BminCSPs and showed that BminCSP1–4 are clustered in separate groups, indicating the possibility of their contrasting function in B. minax. Furthermore, the tissue distribution of the four CSP genes in adult B. minax was analyzed by real-time quantitiative PCR. The results demonstrated that BminCSP3 are significantly transcriptionally enriched in antennae; BminCSP4 expressed primarily in heads; BminCSP1 and BminCSP2 showed high expressions in different tissues, such as antennae, abdomens and wings. Based on these findings, the different implications for the functions of BminCSPs are discussed. This study will offer a significant indication for further functional studies of the CSPs in B. minax

Modeling and designing intelligent adaptive sliding mode controller for an Eight-Rotor MAV

Xiang-jian Chen,Di Li 한국항공우주학회 2013 International Journal of Aeronautical and Space Sc Vol.14 No.2

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-Ⅱ fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-Ⅱ fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-Ⅱ fuzzy neural network based adaptive sliding mode controller could guarantee the Eight- Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-Ⅰ fuzzy neural network based sliding mode controller.

Robusts Adaptive Interval Type II Fuzzy Neural Network Control for the Synchronization of Uncertain Chaotic Systems

Xiang-jian Chen,Di Li 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.12

The proposed RAITIIFNNC system is comprised of a interval type II fuzzy neural network identifier and a robust controller. The identifier is utilized for online estimation of the compound uncertainties. The robust controller is used to attenuate the effects of the approximation error so that the perfect tracking and synchronization of chaotic systems are achieved. All the parameter learning algorithms are derived based on Lyapunov stability theorem to ensure network convergence as well as stable synchronization performance. From the simulation example, to synchronize two Lorenz chaotic systems, it has been shown that the effectiveness of the proposed method has been verified.

Modeling and designing intelligent adaptive sliding mode controller for an Eight-Rotor MAV

Chen, Xiang-Jian,Li, Di The Korean Society for Aeronautical and Space Scie 2013 International Journal of Aeronautical and Space Sc Vol.14 No.2

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-II fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-II fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-II fuzzy neural network based adaptive sliding mode controller could guarantee the Eight-Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-I fuzzy neural network based sliding mode controller.

Comparison Study of the Band-gap Structure of a 1D-Photonic Crystal by Using TMM and FDTD Analyses

Jian-Bo Chen,Yan Shen,Wei-Xi Zhou,Yu-Xiang Zheng,Hai-Bin Zhao,Liang-Yao Chen 한국물리학회 2011 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.58 No.42

A variety of numerical methods has been developed to demonstrate the nature of photons propagating in an artificially-composed periodic structure. Differences will be generated by different kinds of numerical approaches. In this work, we carry out two types of numerical calculations, TMM (transfer matrix method) and FDTD (finite different time domain) calculations. In terms of the 1D-photonic crystal structures with two different structures, we illustrate the energy band spectra, and the results show dispersive characteristics for the optical transmission and reflection of the crystal material. Through a discussion of the mechanism, detailed comparison studies are preformed based on the different physical conditions. The results given in the work will help in better understanding the ways in which photons propagate in an artificially-composed periodic structure.

Radar Emitter Signals Identification with a Optimal Recurrent Type 2 Wavelet Fuzzy Neural Network

Xiang-jian Chen,Di Li,Xi-Bei Yang,Hongmei Li 한국항공우주학회 2018 International Journal of Aeronautical and Space Sc Vol.19 No.3

One optimal recurrent type 2-wavelet fuzzy neural network (RT2WFNN) is proposed in this paper to deal with the problem of emitter identification caused by some types of noise. The RT2WFNN has both an on-line parameter and structure learning ability. The new adaptive method based on gradient decent with Lyapunov theorem used for parameter learning can improve the learning ability of RT2WFNN; the type 2 FCM and optimal improved EKM algorithm are used to select the cluster centers of the membership functions in the antecedent part of fuzzy rules of the RT2WFNN for shortening the adjustment time. A number of simulations are presented to demonstrate the identification capability of the RT2WFNN algorithm for the radar emitter identification. The simulation and actual experimental results illustrated that the proposed RT2WFNN cannot only have better identification capability, but also is relatively more insensitive to noise and accelerate the computing speed.

Modeling and Real-timecontrol of MAV with Multi-rotors

Xiang-jian Chen,Di Li,Zhi-jun Xu,Yue Bai 보안공학연구지원센터 2013 International Journal of Control and Automation Vol.6 No.5

miR-340 Reverses Cisplatin Resistance of Hepatocellular Carcinoma Cell Lines by Targeting Nrf2-dependent Antioxidant Pathway

Shi, Liang,Chen, Zhan-Guo,Wu, Li-li,Zheng, Jian-Jian,Yang, Jian-Rong,Chen, Xiao-Fei,Chen, Zeng-Qiang,Liu, Cun-Li,Chi, Sheng-Ying,Zheng, Jia-Ying,Huang, Hai-Xia,Lin, Xiang-Yang,Zheng, Fang Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.23

Many chemotherapeutic agents have been successfully used to treat hepatocellular carcinoma (HCC); however, the development of chemoresistance in liver cancer cells usually results in a relapse and worsening of prognosis. It has been demonstrated that DNA methylation and histone modification play crucial roles in chemotherapy resistance. Currently, extensive research has shown that there is another potential mechanism of gene expression control, which is mediated through the function of short noncoding RNAs, especially for microRNAs (miRNAs), but little is known about their roles in cancer cell drug resistance. In present study, by taking advantage of miRNA effects on the resistance of human hepatocellular carcinoma cells line to cisplatin, it has been demonstrated that miR-340 were significantly downregulated whereas Nrf2 was upregulated in HepG2/CDDP (cisplatin) cells, compared with parental HepG2 cells. Bioinformatics analysis and luciferase assays of Nrf2-3'-untranslated region-based reporter constructor indicated that Nrf2 was the direct target gene of miR-340, miR-340 mimics suppressing Nrf2-dependent antioxidant pathway and enhancing the sensitivity of HepG2/CDDP cells to cisplatin. Interestingly, transfection with miR-340 mimics combined with miR-340 inhibitors reactivated the Nrf2 related pathway and restored the resistance of HepG2/CDDP cells to CDDP. Collectively, the results first suggested that lower expression of miR-340 is involved in the development of CDDP resistance in hepatocellular carcinoma cell line, at least partly due to regulating Nrf2-dependent antioxidant pathway.

Study of the Band-gap Structure of a 1D-photonic Crystal by Using Different Numerical Approaches

Liang-Yao Chen,Jian-Bo Chen,Yue-Rui Chen,Yan Shen,Wei-Xi Zhou,Jiu-Chun Ren,Yu-Xiang Zheng 한국물리학회 2010 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.56 No.4

Comparative studies between the transfer matrices method (TMM) and plane wave method (PWM) approaches have been performed on 1D photonics crystal under different conditions to show the differences between these two kinds of calculations. TMM is suitable for the design of 1D photonic crystal device with high precision and is in good agreement with experimental results, but is not suitable for the 2D and 3D photonic structures which are limited by the complicated boundary conditions at micro interfaces. The result based on the PWM approach to deal approximately with the photonic structure in approximation has not yet been strictly verified by experiment, not even for 1D photonic crystal structures. More efforts will be required to explore its validation under all physical conditions to enhance its application.

Modeling and Design Adaptive Double Neural Network Controller for Eight-Rotor Micro Aircraft Vehicle

Di Li,Zhihong Lu,Xiang-jian Chen 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.11

In this article, a dynamic model of a six degrees of freedom (6 DOF) Eight-Rotor MAV (micro aerial vehicles) is derived on the basis of the Newton-Euler formalism. The derivation comprises determining equations of the motion of the Eight-Rotor MAV in three dimensions and approximating the actuation forces through the modelling of aerodynamic coefficients and electric motor dynamics. For Eight-Rotor MAV is inherently unstable as they are highly sensitive to external perturb, here provides an adaptive double neural network controller for the motion control of the Eight-Rotor MAV autonomous flight. This controller is developed in three parts around each of the variables. The experimental results show that the proposed adaptive double neural network controller outperforms the conventional PID controller due to its fast adaptive qualities in the presence of sensor measurement noise and the parameters variations of Eight-Rotor MAV.