Shenglong Chen

This work is devoted to the hyperbolic sine function (HSF) control-based finite-time bipartite synchronization of fractional-order spatiotemporal networks and its application in image encryption. Initially, the addressed networks adequately take into account the nature of anisotropic diffusion, i.e., the diffusion matrix can be not only non-diagonal but also non-square, without the conservative requirements in plenty of the existing literature. Next, an equation transformation and an inequality estimate for the anisotropic diffusion term are established, which are fundamental for analyzing the diffusion phenomenon in network dynamics. Subsequently, three control laws are devised to offer a detailed discussion for HSF control law’s outstanding performances, including the swifter convergence rate, the tighter bound of the settling time and the suppression of chattering. Following this, by a designed chaotic system with multi-scroll chaotic attractors tested with bifurcation diagrams, Poincaré map, and Turing pattern, several simulations are pvorided to attest the correctness of our developed findings. Finally, a formulated image encryption algorithm, which is evaluated through imperative security tests, reveals the effectiveness and superiority of the obtained results.

This paper is devoted to the study of adaptive synchronization for fractional-order uncertain complex-valued competitive neural networks (FOUCVCNNs) using the non-decomposition method. Firstly, a new network model named FOUCVCNNs is proposed, which is not separated into two real-valued subsystems in order to keep its intrinsic speciality. In addition, a novel adaptive controller is designed to reduce the cost of control. Meanwhile, with the help of fractional Lyapunov theory, 1-norm analysis framework and inequality techniques, several effective synchronization criteria for FOUCVCNNs are obtained by constructing an appropriate Lyapunov function. Finally, the reliability of the results obtained is tested through numerical simulation.

This paper focuses on the event-triggered synchronization of coupled neural networks with reaction–diffusion terms. At first, an effective event-triggered controller was designed based on time sampling. It is worth noting that the data of the controller for this type can be updated only when corresponding triggering conditions are satisfied, which can significantly reduce the communication burden of the control systems compared to other control strategies. Furthermore, some sufficient criteria were obtained to ensure the event-triggered synchronization of the considered systems through the use of an inequality techniques as well as the designed controller. Finally, the validity of the theoretical results was confirmed using numerical examples.

Objective: Coronary artery bypass grafting (CABG) is associated with antithrombotic therapy in terms of postoperative adverse events; however, it is still unknown whether the early use of such drugs after CABG is safe and effective. In this study, we aim to evaluate the relationship between different postoperative antithrombotic strategies and in-hospital adverse events in patients undergoing isolated coronary artery bypass grafting surgery. Methods: This was a single-center, retrospective cohort analysis of patients undergoing isolated CABG due to CAD between 2001 and 2012. Data were extracted from the Medical Information Mart for Intensive Care III database.The patients involved were divided into the ASA (aspirin only) or DAPT (aspirin plus clopidogrel) group according to the antiplatelet strategy. Patients were also stratified into subgroups based on the type of anticoagulation. The risk of bleeding and adverse events was investigated and compared between groups. Results: A total of 3274 patients were included in this study, with 2358 in the ASA group and 889 in the DAPT group. No significant difference was seen in the risk of major bleeding between the two groups according to the PLATO, TIMI or GUSTO criteria. There was no difference in the postoperative mortality. In subgroup analysis, patients given anticoagulant therapy had an increased incidence of bleeding-related events. Multivariable analysis revealed that postoperative anticoagulant therapy and the early use of heparin, but not DAPT, were independent predictors of bleeding-related events. Conclusions: Postoperative DAPT was not associated with an increased occurrence of bleeding-related events in patients undergoing isolated CABG and appears to be a safe antiplatelet therapy. The addition of anticoagulants to antiplatelet therapy increased the risk of bleeding and should be considered cautiously in clinical practice.

This paper presents a stochastic vector-borne epidemic model with direct transmission and media coverage. It proves the existence and uniqueness of positive solutions through the construction of a suitable Lyapunov function. Immediately after that, we study the transmission mechanism of vector-borne diseases and give threshold conditions for disease extinction and persistence; in addition we show that the model has a stationary distribution that is determined by a threshold value, i.e., the existence of a stationary distribution is unique under specific conditions. Finally, a stochastic model that describes the dynamics of vector-borne diseases has been numerically simulated to illustrate our mathematical findings.

In clinical studies, paired binary metadata are often encountered during collecting information from paired organs or parts. The risk difference, relative risk ratio, and odds ratios of response rates are widely used to measure cured effects for such data. Under Dallal’s model, the paper extends these measures to the general case in g groups. We propose eight test statistics for various functions when the dependency measures γ i i = 1 , … , g are equal or not. Simulation results show that the Score and Rosner-type tests can produce robust empirical type I error rates, while Wald-type and likelihood ratio tests have better power in testing the risk difference, relative risk ratio, and odds ratios. Finally, two real examples illustrate our proposed method’s practicability.

Based on direct quaternion method, this paper explores the finite-time adaptive synchronization (FAS) of fractional-order delayed quaternion-valued fuzzy neural networks (FODQVFNNs). Firstly, a useful fractional differential inequality is created, which offers an effective way to investigate FAS. Then two novel quaternion-valued adaptive control strategies are designed. By means of our newly proposed inequality, the basic knowledge about fractional calculus, reduction to absurdity as well as several inequality techniques of quaternion and fuzzy logic, several sufficient FAS criteria are derived for FODQVFNNs. Moreover, the settling time of FAS is estimated, which is in connection with the order and initial values of considered systems as well as the controller parameters. Ultimately, the validity of obtained FAS criteria is corroborated by numerical simulations.