Optimal and Memristor-Based Control of A Nonlinear Fractional Tumor-Immune Model

In this article,the reduced differential transform method is introduced to solve the nonlinear fractional model of Tumor-Immune.The fractional derivatives are described in the Caputo sense.The solutions derived using this method are easy and very accurate.The model is given by its signal flow diagram.Moreover,a simulation of the system by the Simulink of MATLAB is given.The disease-free equilibrium and stability of the equilibrium point are calculated.Formulation of a fractional optimal control for the cancer model is calculated.In addition,to control the system,we propose a novel modification of its model.This modification is based on converting the model to a memristive one,which is a first time in the literature that such idea is used to control this type of diseases.Also,we study the system’s stability via the Lyapunov exponents and Poincare maps before and after control.Fractional order differential equations(FDEs)are commonly utilized to model systems that have memory,and exist in several physical phenomena,models in thermoelasticity field,and biological paradigms.FDEs have been utilized to model the realistic biphasic decline manner of elastic systems and infection of diseases with a slower rate of change.FDEs are more useful than integer-order in modeling sophisticated models that contain physical phenomena.

Dynamical Behaviors of Nonlinear Coronavirus (COVID-19) Model with Numerical Studies

The development of mathematical modeling of infectious diseases is a key research area in various elds including ecology and epidemiology.One aim of these models is to understand the dynamics of behavior in infectious diseases.For the new strain of coronavirus(COVID-19),there is no vaccine to protect people and to prevent its spread so far.Instead,control strategies associated with health care,such as social distancing,quarantine,travel restrictions,can be adopted to control the pandemic of COVID-19.This article sheds light on the dynamical behaviors of nonlinear COVID-19 models based on two methods:the homotopy perturbation method(HPM)and the modied reduced differential transform method(MRDTM).We invoke a novel signal ow graph that is used to describe the COVID-19 model.Through our mathematical studies,it is revealed that social distancing between potentially infected individuals who are carrying the virus and healthy individuals can decrease or interrupt the spread of the virus.The numerical simulation results are in reasonable agreement with the study predictions.The free equilibrium and stability point for the COVID-19 model are investigated.Also,the existence of a uniformly stable solution is proved.

Describe the Mathematical Model for Exchanging Waves Between Bacterial and Cellular DNA

In this article,we have shown that bacterial DNA could act like some coils which interact with coil-like DNA of host cells.By decreasing the separating distance between two bacterial cellular DNA,the interaction potential,entropy,and the number of microstates of the system grow.Moreover,the system gives its energy to the medium and the temperature of the host body grows.This could be seen as fever in diseases.By emitting some special waves and changing the temperature of the medium,the effects of bacterial waves could be reduced and bacterial diseases could be controlled.Many investigators have shown that bacterial DNA could emit or absorb electromagnetic waves.One of the main experiments about bacterial waves has been done by Montagnier and his group.They have shown that the genomic DNA of most pathogenic bacteria includes sequences that are able to emit electromagnetic waves.The results have shown that wave affects the crucial physicochemical processes in both Gram-positive and Gram-negative bacteria.The emphasis in this survey is on the development of controlling model equations and computer emulation of the model equations rather than on mathematical methods for solving the model equations and differential equations of epidemics.

An Approximate Numerical Methods for Mathematical and Physical Studies for Covid-19 Models

The advancement in numerical models of serious resistant illnesses is a key research territory in different fields including the nature and the study of disease transmission.One of the aims of these models is to comprehend the elements of conduction of these infections.For the new strain of Covid-19(Coronavirus),there has been no immunization to protect individuals from the virus and to forestall its spread so far.All things being equal,control procedures related to medical services,for example,social distancing or separation,isolation,and travel limitations can be adjusted to control this pandemic.This article reveals some insights into the dynamic practices of nonlinear Coronavirus models dependent on the homotopy annoyance strategy(HPM).We summon a novel sign stream chart that is utilized to depict the Coronavirus model.Through the numerical investigations,it is uncovered that social separation of the possibly tainted people who might be conveying the infection and the healthy virus-free people can diminish or interrupt the spread of the infection.The mathematical simulation results are highly concurrent with the statistical forecasts.The free balance and dependability focus for the Coronavirus model is discussed and the presence of a consistently steady arrangement is demonstrated.