Stability and synchronization of fractional-order reaction-diffusion inertial time-delayed neural networks with parameters perturbation.

This study is centered around the dynamic behaviors observed in a class of fractional-order generalized reaction-diffusion inertial neural networks (FGRDINNs) with time delays. These networks are characterized by differential equations involving two distinct fractional derivatives of the state. The global uniform stability of FGRDINNs with time delays is explored utilizing Lyapunov comparison principles.

Stability analysis and optimal control of a fractional-order generalized SEIR model for the COVID-19 pandemic.

In view of the spread of corona virus disease 2019 (COVID-19), this paper proposes a fractional-order generalized SEIR model. The non-negativity of the solution of the model is discussed. Based on the established threshold , the existence of the disease-free equilibrium and endemic equilibrium is analyzed.

Quasi-projective and complete synchronization of discrete-time fractional-order delayed neural networks.

This paper presents new theoretical results on quasi-projective synchronization (Q-PS) and complete synchronization (CS) of one kind of discrete-time fractional-order delayed neural networks (DFDNNs). At first, three new fractional difference inequalities for exploring the upper bound of quasi-synchronization error and adaptive synchronization are established by dint of Laplace transform and properties of discrete Mittag-Leffler function, which vastly expand a number of available results. Furthermore, two controllers are designed including nonlinear controller and adaptive controller.

The effect mitigation measures for COVID-19 by a fractional-order SEIHRDP model with individuals migration.

In this paper, the generalized SEIHRDP (susceptible-exposed-infective-hospitalized-recovered-death-insusceptible) fractional-order epidemic model is established with individual migration. Firstly, the global properties of the proposed system are studied. Particularly, the sensitivity of parameters to the basic reproduction number are analyzed both theoretically and numerically.

Stability analysis of a nonlocal SIHRDP epidemic model with memory effects.

The prediction and control of COVID-19 is critical for ending this pandemic. In this paper, a nonlocal SIHRDP (S-susceptible class, I-infective class (infected but not hospitalized), H-hospitalized class, R-recovered class, D-death class and P-isolated class) epidemic model with long memory is proposed to describe the multi-wave peaks for the spread of COVID-19. Based on the basic reproduction number , which is completely controlled by fractional order, the stability of the proposed system is studied.

Forecast analysis of the epidemics trend of COVID-19 in the USA by a generalized fractional-order SEIR model.

In this paper, a generalized fractional-order SEIR model is proposed, denoted by SEIQRP model, which divided the population into susceptible, exposed, infectious, quarantined, recovered and insusceptible individuals and has a basic guiding significance for the prediction of the possible outbreak of infectious diseases like the coronavirus disease in 2019 (COVID-19) and other insect diseases in the future. Firstly, some qualitative properties of the model are analyzed. The basic reproduction number is derived.

A fractional-order SEIHDR model for COVID-19 with inter-city networked coupling effects.

In the end of 2019, a new type of coronavirus first appeared in Wuhan. Through the real-data of COVID-19 from January 23 to March 18, 2020, this paper proposes a fractional SEIHDR model based on the coupling effect of inter-city networks. At the same time, the proposed model considers the mortality rates (exposure, infection and hospitalization) and the infectivity of individuals during the incubation period.

Mean-square H antagonistic formations of second-order multi-agent systems with multiplicative noises and external disturbances.

In physical systems, since the acceleration is always regard as the control input, it is meaningful to study the coordination problems of the second-order multi-agent system. This paper devotes to the mean-square H antagonistic formation control of second-order multi-agent systems with multiplicative noises and external disturbances under directed signed topologies. To force all agents achieve antagonistic formation and attenuate the effect of communication noises and external disturbances, a novel distributed consensus control protocol with a time-invariant control gain is proposed where only the information that received from neighbors is utilized.

Necessary and Sufficient Conditions for Group Consensus of Fractional Multiagent Systems Under Fixed and Switching Topologies via Pinning Control.

The group consensus problem for fractional-order multiagent systems is investigated in this paper. With the help of double-tree-form transformations, the group consensus problem of fractional-order multiagent systems is proved to be equivalent to the asymptotical stability problem of reduced-order error systems. A class of distributed control protocols and some simple LMI sufficient conditions as well as necessary and sufficient conditions are proposed in this paper to solve the group consensus problem for fractional multiagent systems.

Extinction Analysis of Stochastic Predator-Prey System with Stage Structure and Crowley-Martin Functional Response.

In this paper, we researched some dynamical behaviors of a stochastic predator-prey system, which is considered under the combination of Crowley-Martin functional response and stage structure. First, we obtained the existence and uniqueness of the global positive solution of the system. Then, we studied the stochastically ultimate boundedness of the solution.

LMI Conditions for Global Stability of Fractional-Order Neural Networks.

Fractional-order neural networks play a vital role in modeling the information processing of neuronal interactions. It is still an open and necessary topic for fractional-order neural networks to investigate their global stability. This paper proposes some simplified linear matrix inequality (LMI) stability conditions for fractional-order linear and nonlinear systems.

Function projective synchronization between integer-order and stochastic fractional-order nonlinear systems.

In this paper, the function projective synchronization between integer-order and stochastic fractional-order nonlinear systems is investigated. Firstly, according to the stability theory of fractional-order systems and tracking control, a controller is designed. At the same time, based on the orthogonal polynomial approximation, the method of transforming stochastic error system into an equivalent deterministic system is given.

Stability analysis of fractional-order Hopfield neural networks with time delays.

This paper investigates the stability for fractional-order Hopfield neural networks with time delays. Firstly, the fractional-order Hopfield neural networks with hub structure and time delays are studied. Some sufficient conditions for stability of the systems are obtained.

[Correlation between the changes of oxidation reduction potential values and postmortem interval of heart blood in rabbits after death].

Objective: To investigate correlation between the changes of oxidation reduction potential (ORP) values of heart blood in rabbits after death and postmortem interval (PMI) at different temperatures.

Methods: Forty-eight rabbits were randomly divided into 6 groups and sacrificed by air embolism. Blood samples were taken from the right ventricle of each rabbit and stored at different temperatures of 10, 15, 20, 25, 30 and 35 degrees C, respectively.