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A complex network analysis of the seismic activity in the central zone of Chile is made, where each node corresponds to a location, where a seism occurs. The $$M_w =$$ 8.3 Illapel earthquake (16 September 2015) is included in the data set studied. Assuming a self-similar data network, the value of the power law characteristic exponent $$\gamma$$ for the link probability distribution of the directed network and the value of the power law characteristic exponent $$\delta$$ for the cumulative distribution of the betweenness centrality are studied, before and after the earthquake. Both exponents have a different values before and after the earthquake when the network is built with cell size of 5 $$\times$$ 5 $$\times$$ 5 km, but there is no difference when the cell size is 10 $$\times$$ 10 $$\times$$ 10 km. The exponents were evaluated for the data set with the total number of seismic events and for three cutoffs in magnitude. There is not much variation when applying the cutoff. Variations of both exponents are found when both subsets, before and after the main event, are compared, suggesting that the topological features of the complex network of seisms are modified by major events. [ABSTRACT FROM AUTHOR]

We propose a model of a bus traveling through a sequence of traffic lights, which is required to stop between the traffic signals to pick up passengers. A two dimensional model, of velocity and traveled time at each traffic light, is constructed, which shows non-trivial and chaotic behaviors for realistic city traffic parameters. We restrict the parameter values where these non-trivial and chaotic behaviors occur, by following analytically and numerically the fixed points and period 2 orbits. We define conditions where chaos may arise by determining regions in parameter space where the maximum Lyapunov exponent is positive. Chaos seems to occur as long as the ratio of the braking and accelerating capacities are greater than about ~3. [ABSTRACT FROM AUTHOR]