A total variation-based reconstruction method for dynamic MRI.
A transient density-dependent diffusion-reaction model for the limitation of antibiotic penetration in biofilms.
A two-dimensional model for the transmission of dengue fever disease.
A two-species cooperative Lotka-Volterra system of degenerate parabolic equations.
A viral infection model with a nonlinear infection rate.
A viscoelastic model with non-local damping application to the human lungs
In this paper we elaborate a model to describe some aspects of the human lung considered as a continuous, deformable, medium. To that purpose, we study the asymptotic behavior of a spring-mass system with dissipation. The key feature of our approach is the nature of this dissipation phenomena, which is related here to the flow of a viscous fluid through a dyadic tree of pipes (the branches), each exit of which being connected to an air pocket (alvelola) delimited by two successive masses. The...
A weighted HP model for protein folding with diagonal contacts
The HP model is one of the most popular discretized models for attacking the protein folding problem, i.e., for the computational prediction of the tertiary structure of a protein from its amino acid sequence. It is based on the assumption that interactions between hydrophobic amino acids are the main force in the folding process. Therefore, it distinguishes between polar and hydrophobic amino acids only and tries to embed the amino acid sequence into a two- or three-dimensional grid lattice...
A within-host dengue infection model with immune response and nonlinear incidence rate
A model of viral infection of monocytes population by the dengue virus is formulated as a system of four ordinary differential equations. The model takes into account the immune response and nonlinear incidence rate of susceptible and free virus particles. Global stability of the uninfected steady state is investigated. Such a steady state always exists. If it is the only steady state, then it is globally asymptotically stable. If any infected steady state exists, then the uninfected...
Aalen additive model: an application to data of sinusitis in patients with AIDS.
About a problem arising in chemical reactor theory.
About the maximum information and maximum likelihood principles
Neural networks with radial basis functions are considered, and the Shannon information in their output concerning input. The role of information- preserving input transformations is discussed when the network is specified by the maximum information principle and by the maximum likelihood principle. A transformation is found which simplifies the input structure in the sense that it minimizes the entropy in the class of all information-preserving transformations. Such transformation need not be unique...
About the properties of a modified generalized Beverton-Holt equation in ecology models.
Absolute stability of nonlinear systems with time delays and applications to neural networks.
Absorption in stochastic epidemics
A two dimensional stochastic differential equation is suggested as a stochastic model for the Kermack–McKendrick epidemics. Its strong (weak) existence and uniqueness and absorption properties are investigated. The examples presented in Section 5 are meant to illustrate possible different asymptotics of a solution to the equation.
Abstract action potential models for toxin recognition.
Abstract formulation of an age-physiology dependent population dynamics problem
Acceleration of Le Bail fitting method on parallel platforms
Le Bail fitting method is procedure used in the applied crystallography mainly during the crystal structure determination. As in many other applications, there is a need for a great performance and short execution time. In this paper, we describe utilization of parallel computing for mathematical operations used in Le Bail fitting. We present an algorithm implementing this method with highlighted possible approaches to its aforementioned parallelization. Then, we propose a sample parallel version...
Accurate reduction of a model of circadian rhythms by delayed quasi-steady state assumptions
Quasi-steady state assumptions are often used to simplify complex systems of ordinary differential equations in the modelling of biochemical processes. The simplified system is designed to have the same qualitative properties as the original system and to have a small number of variables. This enables to use the stability and bifurcation analysis to reveal a deeper structure in the dynamics of the original system. This contribution shows that introducing delays to quasi-steady state assumptions...
Activities in a one-dimensional continuous neural network
Adaptive bacterial foraging optimization.