Armando Gallegos

On S 1 as an alternative continuous opinion space in a three-party regime

In this work, we propose a discrete system to model the dynamics of individual opinions when the agents of a population have three equally likely choices. The social network consists of a finite number of agents with pairwise interactions at discrete times, and the opinion space is identified as a triangle in the plane. After a suitable homotopic transformation, one may convert the opinion space into the classical circle S 1 of the Cartesian plane. The opinion of each agent is updated following a general nonlinear law which considers individual parameters of the members. We establish conditions that guarantee the existence of attracting points (or strong consensus), and infer the existence of attracting intervals (identified here as weak consensus). Moreover, we notice that the conditions that lead to global consensuses are independent of the weight matrix and the number of agents in the network. The simulations obtained in this work confirm the validity of the analytical results.

A modified Bhattacharya exponential method to approximate positive and bounded solutions of the Burgers-Fisher equation

In this work, we investigate numerically the classical Burgers-Fisher equation using a modified Bhattacharya method. The partial differential equation under investigation possesses nonnegative and bounded solutions and, under some suitable parameter conditions, these solutions are traveling waves. It is well known that the use of the Bhattacharya approach leads to the design of numerical techniques that are sensitive to zero solutions. However, in this manuscript, we provide a correction of that technique in order to approximate solutions of the Burgers-Fisher equation that are bounded in 0 , 1 . The proposed methodology is explicit, and we establish thoroughly the capability of the technique to preserve the non-negativity, the boundedness and the monotonicity of the numerical approximations, as well as the constant solutions of the continuous model. The new class of methods introduced in this work considers the presence of a free parameter, and we show that this family tends to an explicit and standard discretization of the Burgers-Fisher equation when the free parameter tends to infinity. Some simulations illustrate the main features of the method.

A structure-preserving computational method in the simulation of the dynamics of cancer growth with radiotherapy

In this work, we consider a two-dimensional mathematical model that describes the growth dynamics of cancer when radiotherapy is considered. The mathematical model for the local density of the tumor is described by a parabolic partial differential equation with variable diffusion coefficient. The nonlinear reaction term considers both the logistic law of proliferation of tumor cells and the effect of a treatment against cancer. Suitable initial-boundary conditions are imposed on a bounded spatial domain, and a theorem on the existence and the uniqueness of solutions for the initial-boundary-value problem is proved. Motivated by this result, we design a finite-difference methodology to approximate the solutions of our mathematical model. The scheme is a linear method that is capable of preserving the positivity and the boundedness of the approximations. Some simulations are presented in order to illustrate the performance of the method. Among other conclusions, the numerical results show that the method is able to preserve the analytical features of the relevant solutions of the model.

A mathematical model for the pre-diagnostic of glioma growth based on blood glucose levels

In this paper, we propose a stochastic model in which the values of the factors involved in the development of a glioma vary randomly in a biologically congruent range. Stability analysis revealed three fixed points which allude to patients with a growing glioma, with an advanced stage glioma and without glioma, respectively. The graphics of the solutions and the diagrams of asymptotic behavior of some of the parameters are presented. We also show the order of influence of them. The results obtained show a decay in serum glucose levels in the presence of a glioma. Moreover, they indicate that the immune system is an important element in the prevention of the growth of gliomata.

Superenergy flux of Einstein–Rosen waves

In this work, we consider the propagation speed of the superenergy flux associated to the Einstein–Rosen cylindrical waves propagating in vacuum and over the background of the gravitational field of an infinitely long mass line distribution. The velocity of the flux is determined considering the reference frame in which the super-Poynting vector vanishes. This reference frame is then considered as comoving with the flux. The explicit expressions for the velocities are given with respect to a reference frame at rest with the symmetry axis.

Consensus formation simulation in a social network modeling controversial opinion dynamics with pairwise interactions

In this work, we consider a system of coupled finite-difference equations which incorporates a variety of opinion formation models, and use it to describe the dynamics of opinions on controversial subjects. The social network consists of a finite number of agents with pairwise interactions at discrete times. Meanwhile, the opinion of each agent is updated following a general nonlinear law which considers parameters identified as the personal constants of each of the members. We establish conditions that guarantee the existence of global attracting points (strong consensus) and intervals (weak consensus). Moreover, we note that these conditions are independent of the weight matrix and the number of agents of the network. Two particular scenarios are investigated numerically in order to confirm the validity of the analytical results.