International Journal of Modern Physics C

We have developed a new computational traffic model in which security aspects are fundamental. In this paper we show that this model reproduces many known empirical aspects of vehicular traffic such as the three states of traffic flow and the backward speed of the downstream front of a traffic jam (C), without the aid of adjustable parameters. The model is studied for both open and closed single lane traffic systems. Also, we were able to analytically compute the value of C as 15.37 km/h from a relation that only includes the human reaction time, the mean vehicle length and the effective friction coefficient during the braking process of a vehicle as its main components.

The damage of DNA chains by environmental factors like radiation or chemical pollutants is a topic that has been frequently explored from an experimental and a theoretical perspective. Such damages, like the damage of the strands of a DNA chain, are toxic for the cell and can induce mutagenesis or apoptosis. Several models make strong assumptions for the distribution of damages; for instance a frequent supposition is that these damages are Poisson distributed. [L. Ma, J. J. Wagner, W. Hu, A. J. Levine and G. A. Stolovitzki, Proc. Natl. Acad. Sci.PNAS 102, 14266 (2005).] Only few models describe in detail the damage and the mechanisms associated to the formation and evolution of this damage distribution [H. Nikjoo, P. O'neill and D. T. Goodhead, Radiat. Res. 156, 577 (2001).] Nevertheless, such models do not include the repair processes which are continuously active inside the cell. In this work we present a novel model, based on a depolymerization process, describing the distribution of damages on DNA chains coupled to the dynamics associated to its repair processes. The central aim is not to give a final and comprehensive model, but a hint to represent in more detail the complex dynamics involved in the damage and repair of DNA. We show that there are critical parameters associated to this repair process, in particular we show how critical doses can be relevant in deciding whether the cell continues its repair process or starts apoptosis. We also find out that the damage concentration is related to the dose via a power law relation.

We investigate the nonequilibrium roughening transition of a one-dimensional restricted solid-on-solid model by directly sampling the stationary probability density of a suitable order parameter as the surface adsorption rate varies. The shapes of the probability density histograms suggest a typical Ginzburg–Landau scenario for the phase transition of the model, and estimates of the "magnetic" exponent seem to confirm its mean-field critical behavior. We also found that the flipping times between the metastable phases of the model scale exponentially with the system size, signaling the breaking of ergodicity in the thermodynamic limit. Incidentally, we discovered that a closely related model not considered before also displays a phase transition with the same critical behavior as the original model. Our results support the usefulness of off-critical histogram techniques in the investigation of nonequilibrium phase transitions. We also briefly discuss in the appendix a good and simple pseudo-random number generator used in our simulations.

Long-range interactions are introduced to a two-dimensional model of agents with time-dependent internal variables e_i = 0, ±1 corresponding to valencies of agent emotions. Effects of spontaneous emotion emergence and emotional relaxation processes are taken into account. The valence of agent i depends on valencies of its four nearest neighbors but it is also influenced by long-range interactions corresponding to social relations developed for example by Internet contacts to a randomly chosen community. Two types of such interactions are considered. In the first model the community emotional influence depends only on the sign of its temporary emotion. When the coupling parameter approaches a critical value a phase transition takes place and as result for larger coupling constants the mean group emotion of all agents is nonzero over long time periods. In the second model the community influence is proportional to magnitude of community average emotion. The ordered emotional phase was here observed for a narrow set of system parameters.

An interacting-agent model of speculative activity explaining price formation in financial markets is considered in the present paper, which based on the stochastic Ising model and the mean field theory. The model describes the interaction strength among the agents as well as an external field, and the corresponding random logarithmic price return process is investigated. According to the empirical research of the model, the time series formed by this Ising model exhibits the bursting typical of volatility clustering, the fat-tail phenomenon, the power-law distribution tails and the long-time memory. The statistical properties of the returns of Hushen 300 Index, Shanghai Stock Exchange (SSE) Composite Index and Shenzhen Stock Exchange (SZSE) Component Index are also studied for comparison between the real time series and the simulated ones. Further, the multifractal detrended fluctuation analysis is applied to investigate the time series returns simulated by Ising model have the distribution multifractality as well as the correlation multifractality.

Pseudo-random bit sequence have a wide range of applications in the field of cryptography and communications. For the good chaotic dynamical properties of chaotic systems sequence such as randomness and initial sensitivity, chaotic systems have a strong advantage in generating the pseudo-random bit sequence. However, in practical use, the dynamical properties of chaotic systems will be degraded because of the limited calculation accuracy and it even could cause a variety of security issues. To improve the security, in full analyses of the pseudo-random bit generator proposed in our former paper, we point out some problems in our former design and redesign a better pseudo-random bit generator base on it. At the same time, we make some relevant theoretical and experimental analyses on it. The experiments show that the design proposed in this paper has good statistical properties and security features.

A novel lattice traffic flow model with a slope effect is proposed. Neutral stability condition is obtained by the use of the linear stability theory. The standard KdV equation is derived in the meta-stable region and soliton solution is obtained near the neutral stability line. The solitary waves are reproduced through the numerical simulations. Results show that the solitary density wave appears in upward form when the average density is less than critical density, otherwise it exhibits downward form.

We study the synchronization of Hodgkin–Huxley (HH) neurons connected in a directed lattice network under the influence of varying coupling strength (g) and random link malfunctions in the form of probabilistic deletion (probability q) and link direction flipping (p). We quantify the extent of synchronization of the neurons in the network by averaging the fraction of firing neurons that produce action potentials (exceeding a threshold potential of V_th) across the entire observation time. By extensively scanning over the values of g, synchronization of this network type can be enhanced by increasing g until it reaches a threshold value wherein synchronization will deteriorate abruptly due to suppression of neural firings. We also extensively probe the interplay of p and q and show that there are certain combinations for which the synchronization will improve, defying negative notions of how we perceive random malfunctions.