Chaos, percolation and the coronavirus spread: a two-step model.

We discuss a two-step model for the rise and decay of a new coronavirus (Severe Acute Respiratory Syndrome-CoV-2) first reported in December 2019, COVID-19. The first stage is well described by the same equation for turbulent flows, population growth and chaotic maps: a small number of infected, , grows exponentially to a saturation value, . The typical growth time (aggressive spreading of the virus) is given by where is the Lyapunov exponent.

The coronavirus spread: the Italian case.

A model based on population growth, chaotic maps, and turbulent flows is applied to the spread of Coronavirus for each Italian region in order to obtain useful information and help to contrast it. We divide the regions into different risk categories and discuss anomalies. The worst cases are confined between the Appenine and the Alps mountain ranges but the situation seem to improve closer to the sea.

Mapping heart dynamics by using nonlinear indicators.

A novel approach for the nonlinear characterization of Electrocardiogram (ECG) signals has been developed. The new developed methodology is based on a numerical algorithm that extracts the value of dinfinity (d-infinite) characterizing the asymptotic chaotic behavior of a system. This algorithm also extracts a measure of the maximum Lyapunov exponent and it is applicable to time series where the knowledge of the system structure and laws is not necessary.

Chaos driven fusion enhancement factor at astrophysical energies.

We perform molecular dynamics simulations of screening by bound target electrons in low energy nuclear reactions. Quantum effects corresponding to the Pauli and Heisenberg principles are enforced by constraints. We show that the enhancement of the average cross section and of its variance is due to the perturbations induced by the electrons.