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The statistical properties of human mobility have been studied in the framework of complex systems physics. Taking advantage from the new datasets made available by the information and communication technologies, the distributions of mobility path lengths and of trip duration have been considered to discover the fingerprints of complexity characters, but the role of the different transportation means on the statistical properties of urban mobility has not been studied in deep. In this paper we cope with the problem of pointing out the existence of universal features for different type of individual mobility: pedestrian, cycling and vehicular urban mobility. In particular, we propose the use of travel time as universal 'energy' for the mobility and we define a simple survival model that explains the travel time distribution of the different types of mobility. the analysis is performed in the metropolitan area of Bologna (Italy), where GPS datasets were available on individual trips using different transport means. Our results could suggest how to plan the different transportation networks to realize a multimodal mobility compatibly with the citizens propensities to use the different transport means.

Understanding the factors that control the dynamics of interacting species is a fundamental problem in ecology. The nature of the interactions among different species is usually not completely understood, but it is assumed that the species interaction plays an important role in the ecosystem properties as predicted by the niches models for an ecosystem. However, recent studies point out as the neutral hypothesis proposed by Hubbell of non-interacting species with an external source from the surrounding environment, allows to explain the relative species abundance distribution when the ecosystem has reached a stationary situation. In this paper we use the concept of fitness landscape to introduce a random dynamical model that describes the evolution of different communities near a stationary situation. The average dynamics can be associated to a system of Lotka-Volterra equations with mutualistic interactions. Then we derive a Master equation that satisfies the detailed balance condition of thermodynamical equilibria and allows to analytically compute the relative species abundance distribution near the stationary state as a multinomial negative distribution. These results suggest a possible approach to a synthetic theory that joins the niche theories and the Hubbell's neutral theory for RSA distribution.

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In this paper we introduce a spectra preserving relation between graphs with loops and graphs without loops. This relation is achieved in two steps. First, by generalizing spectra results got on (m, k)-stars to a wider class of graphs, the (m, k, s)-stars with or without loops. Second, by defining a covering space of graphs with loops that allows to remove the presence of loops by increasing the graph dimension. The equivalence of the two class of graphs allows to study graph with loops as simple graph without loosing information.

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In this paper we study noise-induced bistability in a specific circuit with many biological implications, namely a single-step enzymatic cycle described by Michaelis Menten equations with quasi-steady state assumption. We study the system both with a Master Equation formalism, and with the Fokker-Planck continuous approximation, characterizing the conditions in which the continuous approach is a good approximation of the exact discrete model. An analysis of the stationary distribution in both cases shows that bimodality can not occur in such a system. We discuss which additional requirements can generate stochastic bimodality, by coupling the system with a chemical reaction involving enzyme production and turnover. This extended system shows a bistable behaviour only in specific parameter windows depending on the number of molecules involved, providing hints about which should be a feasible system size in order that such a phenomenon could be exploited in real biological systems., Comment: 6 pages, 4 figures

Transportation planning is strongly influenced by the assumption that every individual has for his daily mobility a constant daily budget of ~1 hour. However, recent experimental results are proving this assumption as wrong. Here, we study the differences in daily travel-time expenditures among 24 Italian cities, extracted from a large set of GPS data on vehicles mobility. To understand these variations at the level of individual behaviour, we introduce a trip duration model that allows for a description of the distribution of travel-time expenditures in a given city using two parameters. The first parameter reflects the accessibility of desired destinations, whereas the second one can be associated to a travel-time budget and represents physiological limits due to stress and fatigue. Within the same city, we observe variations in the distributions according to home position, number of mobility days and a driver's average number of daily trips. These results can be interpreted by a stochastic time-consumption model, where the generalised cost of travel times is given by a logarithmic-like function, in agreement with the Weber-Fechner law. Our experimental results show a significant variability in the travel-time budgets in different cities and for different categories of drivers within the same city. This explicitly clashes with the idea of the existence of a constant travel-time budget and opens new perspectives for the modeling and governance of urban mobility., Comment: 12+6 Pages, 6+2 Figures, 1+1 Tables