Capturing the time-varying drivers of an epidemic using stochastic dynamical systems

Epidemics are often modelled using non-linear dynamical systems observed through partial and noisy data. In this paper, we consider stochastic extensions in order to capture unknown influences (changing behaviors, public interventions, seasonal effects etc). These models assign diffusion processes to the time-varying parameters, and our inferential procedure is based on a suitably adjusted adaptive particle MCMC algorithm. The performance of the proposed computational methods is validated on simulated data and the adopted model is applied to the 2009 H1N1 pandemic in England. In addition to estimating the effective contact rate trajectories, the methodology is applied in real time to provide evidence in related public health decisions. Diffusion driven SEIR-type models with age structure are also introduced.Comment: 21 pages, 5 figure

Coherent control for the spherical symmetric box potential in short and intensive XUV laser fields

Coherent control calculations are presented for a spherically symmetric box potential for non-resonant two photon transition probabilities. With the help of a genetic algorithm (GA) the population of the excited states are maximized and minimized. The external driving field is a superposition of three intensive extreme ultraviolet (XUV) linearly polarized laser pulses with different frequencies in the femtosecond duration range. We solved the quantum mechanical problem within the dipole approximation. Our investigation clearly shows that the dynamics of the electron current has a strong correlation with the optimized and neutralizing pulse shape.Comment: 11 Pages 3 Figure

An application of simulated annealing to the optimum design of reinforced concrete retaining structures

This paper reports on the application of a simulated annealing algorithm to the minimum cost design of reinforced concrete retaining structures. Cantilever retaining walls are investigated, being representative of reinforced concrete retaining structures that are required to resist a combination of earth and hydrostatic loading. To solve such a constrained optimisation problem, a modified simulated annealing algorithm is proposed that avoids the simple rejection of infeasible solutions and improves convergence to a minimum cost. The algorithm was implemented using an object-orientated visual programming language, offering facilities for continual monitoring, assessing and changing of the simulated annealing control parameters. Results show that the simulated annealing can be successfully applied to the minimum cost design of reinforced concrete retaining walls, overcoming the difficulties associated with the practical and realistic assessment of the structural costs and their complex inter-relationship with the imposed constraints on the solution space