International Journal of Modern Physics C

This paper proposes an improved community model for social networks based on social mobility. The relationship between the group distribution and the community size is investigated in terms of communication rate and turnover rate. The degree distributions, clustering coefficients, average distances and diameters of networks are analyzed. Experimental results demonstrate that the proposed model possesses the small-world property and can reproduce social networks effectively and efficiently.

In order to promote the use of the lattice Boltzmann method (LBM) for the simulation of isotropic groundwater flow in a confined aquifer with arbitrary geometry, Poisson's equation was transformed into a curvilinear coordinate system. With the metric function between the physical and the computational domain established, Poisson's equation written in Cartesian coordinates was transformed in curvilinear coordinates. Following, the appropriate equilibrium function for the D2Q9 square lattice has been defined. The resulting curvilinear formulation of the LBM for groundwater flow is capable of modeling flow in domains of complex geometry with the opportunity of local refining/coarsening of the computational mesh corresponding to the complexity of the flow pattern and the required accuracy. Since the proposed form of the LBM uses the transformed equation of flow implemented in the equilibrium function, finding a solution does not require supplementary procedures along the curvilinear boundaries, nor in the zones requiring mesh density adjustments. Thus, the basic concept of the LBM is completely maintained. The improvement of the proposed LBM over the previously published classical methods is completely verified by three examples with analytical solutions. The results demonstrate the advantages of the proposed curvilinear LBM in modeling groundwater flow in complex flow domains.

In this paper, a speed gradient viscous continuum model is proposed with the consideration of coupling effect for two-lane freeways. Both the speed gradient viscous term and the lane changing term are introduced into the continuity equations. The numerical simulation is carried out to investigate the shock, rarefaction waves, local clusters and changing behaviors. The results show that speed gradient viscous continuum model can describe some particular traffic behaviors in two-lane traffic system.

Lane-changing is the driver's selection result of the satisfaction degree in different lane driving conditions. There are many different factors influencing lane-changing behavior, such as diversity, randomicity and difficulty of measurement. So it is hard to accurately reflect the uncertainty of drivers' lane-changing behavior. As a result, the research of lane-changing models is behind that of car-following models. Driver's propensity is her/his emotion state or the corresponding preference of a decision or action toward the real objective traffic situations under the influence of various dynamic factors. It represents the psychological characteristics of the driver in the process of vehicle operation and movement. It is an important factor to influence lane-changing. In this paper, dynamic recognition of driver's propensity is considered during simulation based on its time-varying discipline and the analysis of the driver's psycho-physic characteristics. The Analytic Hierarchy Process (AHP) method is used to quantify the hierarchy of driver's dynamic lane-changing decision-making process, especially the influence of the propensity. The model is validated using real data. Test results show that the developed lane-changing model with the dynamic consideration of a driver's time-varying propensity and the AHP method are feasible and with improved accuracy.

We present here new solutions of the focusing one-dimensional nonlinear Schrödinger (NLS) equation which appear as deformations of the Peregrine breather of order 10 with 18 real parameters. With this method, we obtain new families of quasi-rational solutions of the NLS equation, and we obtain explicit quotients of polynomial of degree 110 in x and t by a product of an exponential depending on t. We construct new patterns of different types of rogue waves and recover the triangular configurations as well as rings and concentric rings as found for the lower-orders.

It is hard to experimentally or analytically derive the hydraulic tortuosity (τ) of porous media flow because of their complex microstructures. In this work, we propose a kinematical measurement method for τ by introducing the concept of local tortuosity, which is defined as the ratio of fluid particle velocity to its component along the macro flow. And then, the calculation model of τ is analytically deduced in terms of that τ is the mean value of the local tortuosity. To avoid the impact from the singularity of local tortuosity, the velocity is normalized, and τ is then approximated by the ratio of the mean normalized velocity to the average value of its component along the macro-flow direction. The new estimation method is verified by flow through different types of porous media via the lattice Boltzmann method, and the relationships between permeabilities and tortuosities obtained by different methods are examined. The numerical results show that tortuosity by the novel approach is in good agreement with the existing theory, and the kinematic definition of hydraulic tortuosity is also proven.

In this paper, according to the similarity of chain reaction principle and the characteristics of information propagation on social network, we proposed a new word "information bomb". Based on the complex networks and SIR model, dynamical evolution equations were setup. Then methods used to evaluate the four indexes of bomb power were given, including influence breadth, influence strength, peak time and relaxation time. At last, the power of information was ascertained through these indexes. The process of information propagation is simulated to illustrate the spreading characteristics through the results. Then parameters which impact on the power of information bomb are analyzed and some methods which control the propagation of information are given.

In this work, a cellular automaton model is presented to depict the traffic flow at such a crosswalk with push button. The characteristics of vehicle flow with various arriving rate of pedestrians are investigated. Flux curves and spatiotemporal diagrams are plotted to show different traffic states and the phase transition features. A parameter, named as button reaction time, is introduced to represent the green time for vehicle flow after the button is pushed by a pedestrian. The effect of button reaction time on saturated flux is investigated. The results show that there is a critical value of button reaction time. The saturated flux increases rapidly when button reaction time is smaller than the critical value, while it increases slowly otherwise. Furthermore, theoretical analysis is performed and the results coincide with the simulation ones.

The (Mg, Fe)O solid solution is one of the major lower mantle minerals, and studying its properties and structures under high pressure is a fundamental step toward understanding Earth's deep interior. Here within the framework of density functional theory, we first discuss the relationship between the total energy and iron doped positions of (Mg, Fe)O, and find that the doped iron favors to be dispersive. Then the pressure-induced phase transitions of (Mg, Fe)O from NaCl-type (B1) to CsCl-type (B2) are probed. It is found that the phase transition pressure of (Mg, Fe)O decreases with damped oscillation, as the increase of iron concentration. This phenomenon is essentially determined by the iron concentration as well as iron doped positions. The electronic structures of MgO and (Mg_0.75Fe_0.25)O at 436 GPa are calculated, and the results show that the doped irons play a crucial role in the metallicity of (Mg_0.75Fe_0.25)O. Our results are in agreement with the experimental counterparts. This study would provide some useful information for understanding the behavior of pressure-induced phase transition and geoscience.

In this paper, we wish to examine the stochastic bifurcation induced by multiplicative Gaussian colored noise in a dynamical model of love where the random factor is used to describe the complexity and unpredictability of psychological systems. First, the dynamics in deterministic love-triangle model are considered briefly including equilibrium points and their stability, chaotic behaviors and chaotic attractors. Then, the influences of Gaussian colored noise with different parameters are explored such as the phase plots, top Lyapunov exponents, stationary probability density function (PDF) and stochastic bifurcation. The stochastic P-bifurcation through a qualitative change of the stationary PDF will be observed and bifurcation diagram on parameter plane of correlation time and noise intensity is presented to find the bifurcation behaviors in detail. Finally, the top Lyapunov exponent is computed to determine the D-bifurcation when the noise intensity achieves to a critical value. By comparison, we find there is no connection between two kinds of stochastic bifurcation.

The dynamical properties will degrade when chaotic systems are implemented in digital computers with finite precisions, and such degradation often has serious negative influence on some digital chaos-based systems. Degradation reduction for a class of digital chaotic systems is investigated in this paper. A varying parameter control method is proposed based on the state feedback control technology at first. Then two chaotic maps are applied to verify its validity. Finally, a novel pseudorandom number generator is constructed, which can pass all the tests of NIST SP800-22 at both level-one and level-two approaches and also most of the tests of TestU01. Moreover, it performs better than some existing pseudorandom number generators. Thus, it has acceptable quality of randomness and can be used for cryptography and other applications.

Many real-world networks are essentially heterogeneous, where the nodes have different abilities to gain connections. Such networks are difficult to be embedded into low-dimensional Euclidean space if we ignore the heterogeneity and treat all the nodes equally. In this paper, based on a newly defined heterogeneous distance and a generalized network distance under the constraints of network and triangle inequalities, respectively, we propose a new heterogeneous multidimensional scaling method (HMDS) to embed different networks into proper Euclidean spaces. We find that HMDS behaves much better than the traditional multidimensional scaling method (MDS) in embedding different artificial and real-world networks into Euclidean spaces. Besides, we also propose a method to estimate the appropriate dimensions of Euclidean spaces for different networks, and find that the estimated dimensions are quite close to the real dimensions for those geometrical networks under study. These methods thus can help to better understand the evolution of real-world networks, and have practical importance in network visualization, community detection, link prediction and localization of wireless sensors.