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In this study, asynchronous sliding-mode control (SMC) for discrete-time networked hidden stochastic jump systems subjected to the semi-Markov kernel (SMK) and cyber attacks is investigated. Considering the statistical characteristic of the SMK, which is challenging to acquire in engineering, this study recognizes the SMK to be incomplete. Due to the mode mismatch between the original system and the control law in the operating process, a hidden semi-Markov model is proposed to describe the considered asynchronous situation. The main aim of this study is to construct an asynchronous SMC mechanism based on an incomplete SMK framework under the condition of random denial-of-service attacks so that the resulting closed-loop system can realize the mean-square stability. By virtue of the upper bound of the sojourn time in each mode, innovative techniques are developed for mean-square stability analysis under an incomplete SMK. Furthermore, an asynchronous SMC scheme is designed to achieve the reachability of the quasi-sliding mode. Finally, the effectiveness is verified using an electronic throttle model.

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This work investigates the protocol-based synchronization of inertial neural networks (INNs) with stochastic semi-Markovian jumping parameters and image encryption application. The semi-Markovian jumping process is adopted to characterize INNs under sudden complex changes. To conserve the limited available network bandwidth, an adaptive event-driven protocol (AEDP) is developed in the corresponding semi-Markovian jumping INNs (S-MJINNs), which not only reduces the amount of data transmission but also avoids the Zeno phenomenon. The objective is to construct an adaptive event-driven controller so that the drive and response systems maintain synchronous relationships. Based on the appropriate Lyapunov functional, integral inequality, and free weighting matrix, novel criteria are derived to realize the synchronization. Moreover, the desired adaptive event-driven controller is designed under a semi-Markovian jumping process. The proposed method is demonstrated through a numerical example and an image encryption process.

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The event-triggered sliding-mode control (SMC) for discrete-time networked Markov jumping systems (MJSs) with channel fading is investigated by means of a genetic algorithm. In order to reduce resource consumption in the transmission process, an event-triggered protocol is adopted for networked MJSs. A key feature is that the signal transmission is inevitably affected by fading phenomenon due to delay, random noise, and amplitude attenuation in a networked environment. With the aid of a common sliding surface, an event-triggered SMC law is designed by adjusting the system network mode. Under the framework of stochastic Lyapunov stability, sufficient conditions are constructed to ensure the mean-square stability of the closed-loop networked MJSs, and the sliding region is reached around the specified sliding surface. Moreover, based on the iteration optimizing accessibility of objective function, an effective SMC approach under genetic algorithm is proposed to minimize the convergence region around the sliding surface. Finally, the effectiveness of the proposed method is proved by the F-404 aircraft model.

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The finite-time event-triggered stabilization is studied for a class of discrete-time nonlinear Markov jump singularly perturbed models with partially unknown transition probabilities (TPs). T-S fuzzy strategy is adopted to characterize the related nonlinear Markov jump singularly perturbed models. The control objective is to make sure that the system states remain within a bounded domain during a fixed-time interval. First, a mode-dependent event-triggered scheme is constructed to reduce the communication burden and save the network bandwidth. On that basis, by using a new Lyapunov function, a developed finite-time stability criterion is derived for the corresponding system to avoid an ill-conditioned issue due to a small singular perturbation parameter. Moreover, the mode-dependent fuzzy controller gain and the event-triggered parameter are co-designed under the framework of partially unknown TPs. Finally, the feasibility of the main results is provided to verify the finite-time event-triggered control strategy.

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This article is concerned with the issue of quantized sliding-mode control (SMC) design methodology for nonlinear stochastic switching systems subject to semi-Markovian switching parameters, T-S fuzzy strategy, uncertainty, signal quantization, and nonlinearity. Compared with the previous literature, the quantized control input is first considered in studying T-S fuzzy stochastic switching systems with a semi-Markovian process. A mode-independent sliding surface is adopted to avoid the potential repetitive jumping effects. Then, by means of the Lyapunov function, stochastic stability criteria are proposed to be dependent of sojourn time for the corresponding sliding-mode dynamics. Furthermore, the fuzzy-model-based SMC law is proposed to ensure the finite-time reachability of the sliding-mode dynamics. Finally, an application example of a modified series dc motor model is provided to demonstrate the effectiveness of the theoretical findings.

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The fault detection issue is investigated for complex stochastic delayed systems in the presence of positivity constraints and semi-Markov switching parameters. By choosing a mode-dependent fault detection filter (FDF) as a residual generator, the corresponding fault detection is formulated as a positive [Formula: see text] filter problem. Attention is focused on the design of a mode-dependent FDF to minimize the error between the residual signal and the fault signal. The designed FDF features good sensitivity of the faults and robustness against the external disturbances. Subsequently, by means of the linear copositive Lyapunov functional (LCLF), stochastic stability is proposed to satisfy an expected [Formula: see text]-gain performance. Some solvability conditions for the desired mode-dependent FDF are established with the help of a linear programming approach. Finally, an application example of a data communication network model is provided to demonstrate the effectiveness of the theoretical findings.

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Resibufogenin (RB) has been used for cancer treatment, but the underlying mechanisms are still unclear. This study aimed to investigate the effects of RB treatment on colorectal cancer (CRC) cells, and to determine the underlying mechanisms. The cell counting kit-8 assay was used to determine cell viability. Cell morphology was observed under light microscopy, and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling assay was employed to detect cell apoptosis. Intracellular ferrous iron (Fe2+ ), malondialdehyde (MDA), glutathione (GSH), and reactive oxygen species levels were detected by using commercial iron assay kit, MDA assay kit, GSH assay kit, and 2,7-dichlorodihydrofluorescein diacetate probes, respectively. The protein expressions were determined by Western blot and immunohistochemistry. RB inhibited cell viability in the CRC cell lines (HT29 and SW480) in a dose- and time-dependent manner, and caused cytotoxicity to the normal colonic epithelial cell line (NCM460) at high dose. Similarly, RB induced morphological changes in CRC cells from normal to round shape, and promoted cell death. Of note, RB triggered oxidative stress and ferroptotic cell death in CRC cells, and only ferroptosis inhibitors (deferoxamine and ferrostatin-1), instead of inhibitors for other types of cell death (apoptosis, autophagy, and necroptosis), reversed the inhibitory effects of RB on CRC cell proliferation. Furthermore, glutathione peroxidase 4 (GPX4) was inactivated by RB treatment, and overexpression of GPX4 alleviated RB-induced oxidative cell death in CRC cells. Consistently, the in vivo experiments validated that RB also triggered oxidative stress, and inhibited CRC cells growth and tumorigenicity in mice models. RB can inhibit CRC cells growth and tumorigenesis by triggering ferroptotic cell death in a GPX4 inactivation-dependent manner.

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Finite-time synchronization (FTS) is discussed for delayed semi-Markov switching neural networks (S-MSNNs) with quantized measurement, in which a logarithmic quantizer is employed. The stochastic phenomena of structural and parametrical changes are modeled by a semi-Markov process whose transition rates are time-varying to depend on the sojourn time. Practical systems subject to unpredictable structural changes, such as quadruple-tank process systems, are described by delayed S-MSNNs. A key issue under the consideration is how to design a feedback controller to guarantee the FTS between the master system and the slave system. For this purpose, by using the weak infinitesimal operator, sufficient conditions are constructed to realize FTS of the resulting error system over a finite-time interval. Then, the solvability conditions for the desired finite-time controller can be determined under a linear matrix inequality framework. Finally, the theoretical findings are illustrated by the quadruple-tank process model.

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This paper focuses on the state estimator design problem for a switched neural network (SNN) with probabilistic quantized outputs, where the switching process is governed by a sojourn probability. It is assumed that both packet dropouts and signal quantization exist in communication channels. Asynchronous estimator and quantification function are described by two different hidden Markov model between the SNNs and its estimator. To deal with the small uncertain of estimators in a random way, a probabilistic nonfragile state estimator is introduced, where uncertain information is described by the interval type of gain variation. A sufficient condition on mean square stable of the estimation error system is obtained and then the desired estimator is designed. Finally, a simulation result is provided to verify the effectiveness of the proposed design method.

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This article addresses the issue of asynchronous partially mode-dependent filtering for networked Markov switching repeated scalar nonlinear systems (MSRSNSs) subject to quantized measurements (QMs). Especially, a novel partially mode-dependent filter (PMDF) is constructed, where the signal transmission of a filter mode occurred randomly and is modeled by a Bernoulli distributed sequence. The designed PMDF is different from state mode, which is governed by an asynchronous switching rule. By utilizing a diagonally dominant-type Lyapunov functional (DDTLF), sufficient conditions ensure that the existence of the PMDF and the l2-l∞ performance index are derived. Finally, an economic example is adopted to substantiate the applicability of the developed theoretical results.

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OBJECTIVE: Autophagy is a cellular pathway that regulates the transportation and degradation of cytoplasmic macromolecules and organelles towards lysosome, which is often related to the tumorigenesis and tumor suppression. Here, we investigate the regulating effect of PTEN gene on autophagy-related protein P62 in rat colorectal cancer (CRC) cells and explore the application value of PTEN gene in clinic. METHODS: Rat colorectal cancer was induced by intraperitoneal injection of 1,2-dimethyl hydrazine in male ACI rats. A total of 20 rats were randomly selected from those successfully induced with CRC as the experimental group, while 10 healthy rats as control. The rat CRC cells were isolated and cultured. After transfecting the rat CRC cells with pEGFP-N1-PTEN plasmid, RT-PCR was adopted to examine that gene expression of p62 and PTEN, while Western blotting was used to detect the protein expression of p62 and PTEN. Also, the proliferation of CRC cells was measured by MTT assay. RESULTS: The expression of PTEN gene in the experimental group was significantly inhibited as compared with the control group, while the expression of P62 gene was significantly increased (p < 0.05). Western blotting demonstrated that the PTEN protein in the experimental group was lower, while the expression of P62 protein was higher. When the CRC cells were transfected with pEGFP-N1-PTEN plasmid, the PTEN expressions were elevated, while p62 was down-regulated. Also, the proliferation of CRC cells was inhibited. CONCLUSION: The expression of PTEN gene is negatively correlated with the expression of P62 gene in rat CRC cells. And the expression of PTEN gene can inhibit the occurrence and development of colorectal cancer, thus providing theoretical basis for future clinical treatment.

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The problem of event-triggered reliable control for fuzzy Markovian jump system (FMJS) with mismatched membership functions (MMFs) is addressed. Based on the mode-dependent reliable control and event-triggered communication scheme, the stability conditions and control design procedure are formulated. More precisely, a general actuator-failure is designed such that the FMJS is reliable in the sense of stochastically stable and reduce the utilization of network resources. Furthermore, the improved MMFs are introduced to reduce the conservativeness of obtained results. Finally, simulation results indicate the effectiveness of the proposed methodology.