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In this paper, the state estimation problem for singularly perturbed switched complex dynamic networks (CDNs) is addressed, in which the persistent dwell-time (DT) switching mechanism is employed to depict the switchings among parameters of each node. In the aforementioned switching mechanism, the concept of stage consisting of the persistent portion and the DT portion is introduced. Based on the singular perturbation theory, a two-time-scaling variables containing fast and slow states are taken into account on the CDNs simultaneously, which make the constructed networks more realistic. Furthermore, the main aim is to design a mode-dependent estimator to track the state information that cannot be directly obtained and further ensures the global uniform exponential stability of the investigated systems with a generalized dissipativity property. Some sufficient criteria on the existence of the desired mode-dependent state estimator are established by utilizing a modified matrix decoupling method. Finally, the availability of the estimator design procedures is verified by a simulation example. [ABSTRACT FROM AUTHOR]

This paper aims to solve the sliding mode control issue for the discrete nonlinear two-dimensional (2D) Fornasini–Marchesini second (FMII) model under the influence of quantisation error and stochastic packet loss. Firstly, an innovative stochastic 2D FMII sliding mode control model is constructed by considering quantisation error and Bernoulli packet loss process. And then we study the stability issue and formulate the corresponding stability criterion by virtue of the 2D sliding mode surface and a 2D sliding mode control law with data compensation. Subsequently, the reachability for the 2D sliding surface is verified by a innovative and executable 2D sliding mode control law. Besides, the article also formulates the adaptive intelligent iterative algorithms for the sliding mode surface gain and 2D sliding mode control algorithm, respectively. To conclude the paper, an example is provided to analyse its SMC problem under quantisation and stochastic packet loss. This example also shows the effectiveness of the theorems and algorithms proposed in this paper. [ABSTRACT FROM AUTHOR]

A 2-year field experiment was conducted to analyze the growth conditions, physical features, yield, and nitrogen use efficiency (NUE) of sugar-beet under limited irrigation conditions in northeast of China. A cultivar H003 was used as plant materials; six treatments (C1–C6) were included: C1, no nitrogen applied, rain-fed; C2, nitrogen (120.00 kg ha−1), rain-fed; C3, no nitrogen applied, hole irrigation for seeding; C4, nitrogen (120.00 kg ha−1), hole irrigation for seeding; C5, no nitrogen applied, hole irrigation for seeding; and C6, nitrogen (120.00 kg ha−1), hole irrigation for seeding, and irrigation at foliage rapid growth stage. The irrigation supply was only 500 mL/plant once. Results showed C6 showed the highest chlorophyll content, dry matter accumulation, yield, etc. and had the best NUE among all the treatments. In conclusion, under the routine fertilization conditions of northeast of China, the cultivation measure of hole irrigation 500 mL/plant for seeding combined with irrigation 500 mL/plant at foliage rapid growth stage greatly improved sugar-beet yield and NUE. [ABSTRACT FROM AUTHOR]

An online adaptive optimal control problem for a class of nonlinear Markov jump systems (MJSs) is studied. It is worth noting that the dynamic information of MJSs is partially unknown. Applying the neural network linear differential inclusion techniques, the nonlinear terms in MJSs are approximately converted to linear forms. By using subsystem transformation schemes, we can transfer the nonlinear MJSs to N new coupled linear subsystems. Then a new online policy iteration algorithm is put forward to obtain the adaptive optimal controller. Some theorems are given afterward to ensure the convergence of the new algorithm. At last, a simulation example is provided to verify the applicability of the algorithm. [ABSTRACT FROM AUTHOR]

For a class of conic‐type non‐linear time‐delay Markov jump systems, the asynchronous dissipative output feedback controller based on the guaranteed cost control and quantiser is designed in this study. In real applications, the system and the controller modes are always non‐synchronous, so we introduce the hidden Markov model to solve this problem. Furthermore, we define three novel auxiliary variables and use quantisers to accomplish the output feedback controller design. Then, the finite‐time boundedness and strict dissipativity of the closed‐loop systems are guaranteed by sufficient conditions, and the controller also meets the guaranteed cost‐control performance. By solving a set of linear matrix inequalities, we get the controller gains, the guaranteed cost control performance index J*, and the dissipative performance index α. Finally, the correctness and feasibility of this designed approach are demonstrated by a given example. [ABSTRACT FROM AUTHOR]

It's important to pay great attention to the detection of CN− due to its high toxicity. Based on ESIPT characteristics, we design, synthesize and characterize the colorimetric and fluorescence "turn-on" probe AHAM to recognize CN−, which has the large Stokes shift (228 nm), exhibits high sensitivity and excellent selectivity. The limit detection of the probe AHAM for CN− was 1.94 × 10−8 M, which was much lower than the standard set by WHO and many previously reported probes. The recognition mechanism between AHAM and CN− was investigated by spectroscopic analysis, 1H NMR titration and mass spectrometry. To our surprise, AHAM could not only identify CN− reversibly, but also recognize CN− accurately in test paper and silica gel plate applications. Furthermore, AHAM was successfully used for fluorescence imaging in C. elegans and mice. It provides the new easy, fast and accurate method to detect CN−. [Display omitted] • The Stokes shift of AHAM toward CN− reached 228 nm. • AHAM recognized CN− with low LOD selectively, sensitively and reversibly. • AHAM achieved to visualize CN− in C. elegans and mice. [ABSTRACT FROM AUTHOR]

The asynchronous resilient observer design problem for a class of non‐linear switched systems with time‐delays and uncertainties in a given finite‐time interval is studied here. By constructing appropriate multiple Lyapunov–Krasovskii functions and applying the average dwell‐time method, the switching law and the asynchronous resilient observer are designed to guarantee the finite‐time boundedness of the augment system with a specified H∞ performance. The resilient observer design problems can be derived to solve a set of linear matrix inequalities. A numerical simulation is employed to demonstrate the availability of the proposed methods. [ABSTRACT FROM AUTHOR]

Summary: Anthocyanins protect plants from biotic and abiotic stressors and provide great health benefits to consumers. In this study, we cloned four genes (Red Lettuce Leaves 1 to 4: RLL1 to RLL4) that contribute to colour variations in lettuce. The RLL1 gene encodes a bHLH transcription factor, and a 5‐bp deletion in some cultivars abolishes its function to activate the anthocyanin biosynthesis pathway. The RLL2 gene encodes an R2R3‐MYB transcription factor, which was derived from a duplication followed by mutations in its promoter region. The RLL3 gene encodes an R2‐MYB transcription factor, which down‐regulates anthocyanin biosynthesis through competing with RLL2 for interaction with RLL1; a mis‐sense mutation compromises the capacity of RLL3 to bind RLL1. The RLL4 gene encodes a WD‐40 transcription factor, homologous to the RUP genes suppressing the UV‐B signal transduction pathway in Arabidopsis; a mis‐sense mutation in rll4 attenuates its suppressing function, leading to a high concentration of anthocyanins. Sequence analysis of the RLL1‐RLL4 genes from wild and cultivated lettuce showed that their function‐changing mutations occurred after domestication. The mutations in rll1 disrupt anthocyanin biosynthesis, while the mutations in RLL2, rll3 and rll4 activate anthocyanin biosynthesis, showing disruptive selection for leaf colour during domestication of lettuce. The characterization of multiple polymorphic genes in this study provides the necessary molecular resources for the rational breeding of lettuce cultivars with distinct levels of red pigments and green cultivars with high levels of health‐promoting flavonoids. [ABSTRACT FROM AUTHOR]

• An ETS is proposed to reduce energy consumption. • An event-triggered-based controller is designed for MJCPSs. • The uniform upper/lower bounds are used to describe DoS attacks. • Sufficient conditions are given to stabilize the MJCPSs. This paper is concerned with the event-triggered-based H ∞ control problem for Markov jump cyber-physical systems against denial-of-service attacks. The uniform upper and lower bounds are used to describe the characteristics of aperiodic denial-of-service attacks. An event-triggered scheme is introduced to reduce the waste of resources and avoid communication channel congestion. Based on multi-Lyapunov functions, sufficient conditions are proposed to guarantee the asymptotic mean-square stability and H ∞ performance of the switched closed-loop Markov jump cyber-physical systems. By solving linear matrix inequalities, the event-triggered-based controller gain matrices, and H ∞ performance index are obtained. In the simulation, an F-404 aircraft engine system is employed to clarify the validity of the proposed event-triggered-based controller design approach in face of denial-of-service attacks. [ABSTRACT FROM AUTHOR]

This paper presents an integrated self-triggered control strategy with convergence guarantees for model-free continuous-time systems using reinforcement learning. To consider the control cost and triggering consumption in the self-triggered scheme simultaneously, an integrated cost function is proposed. With this integrated cost function, the trade-off between the triggering occupation and control performance could be adjusted according to different requirements. Then, the actor-critic framework of reinforcement learning is employed to learn the control inputs and triggering intervals by minimizing the corresponding integrated cost function. Considering the divergent characteristics between the control inputs and triggering intervals, two different actors are utilized to learn the triggering strategy and control policy, respectively. Also, the convergence of the developed model-free self-triggered control learning algorithm is proved to ensure the limited learning duration of both the control policy and triggering strategy. The proposed framework can be used to design self-triggered controllers for a wide range of engineering systems with unknow dynamics, including control of aircraft, robots, chemical processes, and other automated systems. Finally, the effectiveness and superiorities of the proposed method are verified by an illustrative example. [ABSTRACT FROM AUTHOR]

Cytosolic phospholipase A2alpha (cPLA2α) is a key mediator of tumorigenesis. In this study, by using a combination of pharmacological and genetic approaches in cell models and patient samples, we identify cPLA2α as a selective target to increase chemosensitivity in cervical cancer. We found that transcript and protein levels of cPLA2α but not other forms of cPLA2 (e.g., cPLA2β and cPLA2αδ) were consistently increased in all tested malignant cervical cancer cells and tissues compared to normal counterparts, suggesting that cPLA2α upregulation is a common feature in cervical cancer. We further found that promoting growth and survival rather than invasion were the predominant roles of cPLA2α on cervical cancer. In addition, chemotherapeutic agents achieved ~100% inhibition efficacy in cPLA2α-depleted cervical cancer cells, demonstrating the important role of cPLA2α in chemoresistance. Importantly, we identify that β-catenin is critically involved in the molecular mechanism of cPLA2α's action in cervical cancer. In summary, our work demonstrates the multiple essential roles of cPLA2α in cervical cancer, particularly in chemoresistance, via a β-catenin-dependent manner. Our work also suggests that targeting cPLA2α has a therapeutic value in overcoming chemoresistance in cervical cancer or other cPLA2α-regulated cancers. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of finite-time H∞ resilient filtering for a class of switch systems. The filtering error dynamics is constructed based on the H∞ resilient filter. The objective is to design a filter such that the finite-time H∞ gain from the unknown input to an estimation error is minimized or guaranteed to be less than or equal to a prescribed value. By selecting the proper multiple Lyapunov function and using the average dwell-time approach, sufficient conditions are obtained for the existence of the desired H∞ resilient filter, which also guarantee the finite-time boundedness of the filtering error dynamic systems. The design criteria are proposed in the form of linear matrix inequalities and then described as an optimization algorithm. Finally, a numerical example is employed to illustrate the effectiveness of the developed techniques. [ABSTRACT FROM AUTHOR]

• A novel online mode-free integral reinforcement learning algorithm is proposed to solve the mutiplayer non-zero sum games. • The online learning is used to compute the corresponding N coupled algebraic Riccati equations. • The policy iterative algorithm is applied to solve the coupled algebraic Riccati equations corresponding to the multiplayer nonzero sum games. In this paper, a novel online mode-free integral reinforcement learning algorithm is proposed to solve the multiplayer non-zero sum games. We first collect and learn the subsystems information of states and inputs; then we use the online learning to compute the corresponding N coupled algebraic Riccati equations. The policy iterative algorithm proposed in this paper can solve the coupled algebraic Riccati equations corresponding to the multiplayer non-zero sum games. Finally, the effectiveness and feasibility of the design method of this paper is proved by simulation example with three players. [ABSTRACT FROM AUTHOR]

In this paper, we study the asynchronous observer-based sliding mode control for a class of discrete-time Markov jump systems with time-delay and conic-type nonlinearities. Firstly, we assume there exists a detector described by the hidden Markov model that provides estimated information of the system mode. Based on the detector, a common sliding surface and an observer-based controller are devised. Secondly, we select the appropriate Lyapunov functional and applying linear matrix inequalities techniques to get sufficient conditions such that the controller and observer gains are obtained, which can guarantee the stochastic stability and strict dissipativity of the sliding mode dynamics. Furthermore, the given H ∞ and passive performance are also discussed. Thirdly, to make the system trajectory get to the predetermined sliding surface, a sliding mode control law is proposed. Finally, an application related to the automotive electronic throttle body control system is given to illustrate the correctness and feasibility of this designed approach. [Display omitted] • For nonlinear MJSs, the observer-based asynchronous SMC scheme is designed. • For the reachability of the sliding surface, a SMC law is given. • By a practical example, the effectiveness of this designed approach is illustrated. [ABSTRACT FROM AUTHOR]

• Design an asynchronous fault detection filter for non-homogeneous MJSs. • The system modes can be traced by an asynchronous fault detection filter. • Sufficient conditions are devised to ensure the designed system performance. • The AETB is used to validate the devised asynchronous fault detection filter. This work investigates the asynchronous fault detection filtering issue for discrete-time piecewise homogeneous Markov jump systems. By resorting to a dual hidden Markov model, an asynchronous fault detection filter is presented which can follow up the system modes. Utilizing the stochastic Lyapunov function approach, sufficient conditions are devised to make the resultant Markov jump systems be stochastically stable and hold a specified H ∞ performance level. Finally, a real-time experiment based on the automotive electronic throttle body is employed to validate the devised asynchronous fault detection filter which can find the faults after the occurrences in the case of no false alarm. [ABSTRACT FROM AUTHOR]