International Journal of Modern Physics C

In this paper a local trade web (LTW) in the Asia-Pacific region is examined using the data derived from the United Nations and the International Monetary Fund. The topology of the LTW has been specified, based upon which the impacts of US financial crisis on the structural and behavior pattern of the LTW are further investigated. The major findings are given as follows. Firstly, the LTW is much more integrated than the global trade web; secondly, after the financial crisis, the fundamental structure of the network remains relatively stable but the strength of the web has been changed and the structure of the web has evolved over time. Economic implications for what have been observed are also discussed.

This paper evaluates three widely used particle stochastic separated flow (SSF) models through large eddy simulation (LES) of gas-particle two-phase turbulent flows over a backward-facing step. The ability of the models to predict mean velocities, fluctuating velocities, and spatial dispersion of particles are carefully examined in comparison with LES reference results. Evaluation shows that the improved time-series SSF model produces good predictions on mean and fluctuating velocities in the particle phase which highly agree with LES results. However, the time-series SSF model has higher computational cost. Further, compared with the two other models, the time-series SSF model predicts better results on the spatial dispersion of particles. It has an overall advantage in terms of accuracy and efficiency in predicting velocity moments and particle dispersion even without the presence of so many particles. The dependence of different SSF models on the number of computational particles in a converged flow field is also discussed. This paper is useful for the selection and application of SSF models in numerical simulations of practical two-phase turbulent flows.

In this paper, the statistical property of the bipartite network, namely clustering coefficient C₄ is taken into account and be embedded into the collaborative filtering (CF) algorithm to improve the algorithmic accuracy and diversity. In the improved CF algorithm, the user similarity is defined by the mass diffusion process, and we argue that the object clustering C₄ of the bipartite network should be considered to improve the user similarity measurement. The statistical result shows that the clustering coefficient of the MovieLens data approximately has Poisson distribution. By considering the clustering effects of object nodes, the numerical simulation on a benchmark data set shows that the accuracy of the improved algorithm, measured by the average ranking score and precision, could be improved 15.3 and 13.0%, respectively, in the optimal case. In addition, numerical results show that the improved algorithm can provide more diverse recommendation results, for example, when the recommendation list contains 20 objects, the diversity, measured by the hamming distance, is improved by 28.7%. Since all of the real recommendation data are evolving with time, this work may shed some light on the adaptive recommendation algorithm according to the statistical properties of the user-object bipartite network.

We propose a modified Invasion Percolation (IP) model to simulate the infiltration of glue into a porous medium under gravity in 2D. Initially, the medium is saturated with air and then invaded by a fluid that has a hardening effect taking place from the interface towards the interior by contact with the air. To take into account that interfacial hardening, we use an IP model where capillary pressures of the growth sites are increased with time. In our model, if a site stays for a certain time at interface, it becomes a hard site and cannot be invaded anymore. That represents the glue interface becoming hard due to exposition with the air. Buoyancy forces are included in this system through the Bond number which represents the competition between the hydrostatic and capillary forces. We then compare our results with results from literature of non-hardening fluids in each regime of Bond number. We see that the invasion patterns change strongly with hardening while the non-hardening behavior remains basically not affected.

In view that drivers would pay attention to the variation of headway on roads, an extended optimal velocity model is proposed by considering anticipation driving behavior. A stability criterion is given through linear stability analysis of traffic flows. The mKdV equation is derived with the reductive perturbation method for headway evolution which could be used to describe the stop-and-go traffic phenomenon. The results show a good effect of anticipation driving behavior on the stabilization of car flows and the anticipation driving behavior can improve the numerical stability of the model as well. In addition, the fluctuation of kinetic energy and the consumption of average energy in congested traffic flows are systematically analyzed. The results show that the reasonable level of anticipation driving behavior can save energy consumption in deceleration process effectively and lead to an associated relation like a "bow-tie" between the energy-saving and the value of anticipation factor.

This paper investigates collisions of gliders generated by one-dimensional Rule 110 cellular automaton. A specific value associated with each glider and an algebraic equation that describes the collision between two gliders were found. Because the products of the collision between two gliders may result in no gliders or one, two or more gliders, this equation states that the total sum of the associated values corresponding to colliding gliders equals the sum of the values of the gliders which are products of the collision. Moreover, an analogy is proposed between the glider collisions and the collisions of physical particles with the equation corresponding to colliding gliders being similar to the equation of energy conservation in physics. In this scheme, even without carrying out the temporal evolution for a collision, it can be determined if a possible combination of resulting gliders accomplishes the equation corresponding to that collision.

The corona discharge commonly occurs in many engineering devices and processes. Their application is still largely based on empirical knowledge; accordingly it is very important to predict the physical properties of corona discharge by the appropriate numerical method. To control corona discharge properly by understanding of corona discharge properties at different discharge stages, time-varying characteristics of discharge which are resulted from electron collision with the gas molecules should be investigated. A numerical study of a corona discharge in nitrogen in a point to plane geometry is presented. It is obtained by Monte Carlo method and concerns space-time evolution of electron and ion densities as well as electric field distributions along the discharge axis.

Studying attention behavior has its social significance because such behavior is considered to lead the evolution of the friendship network. However, this type of behavior in social networks has attracted relatively little attention before, which is mainly because, in reality, such behaviors are always transitory and rarely recorded. In this paper, we collected the attention behaviors as well as the friendship network from Douban database and then carefully studied the attention behaviors in the friendship network as a latent metric space. The revealed similar patterns of attention behavior and friendship suggest that attention behavior may be the pre-stage of friendship to a certain extent, which can be further validated by the fact that pairwise nodes in Douban network connected by attention links beforehand are indeed far more likely to be connected by friendship links in the near future. This phenomenon can also be used to explain the high clustering of many social networks. More interestingly, it seems that attention behaviors are more likely to take place between individuals who have more mutual friends as well as more different friends, which seems a little different from the principles of many link prediction algorithms. Moreover, it is also found that forward attention is preferred to inverse attention, which is quite natural because, usually, an individual must be more interested in others that he is paying attention to than those paying attention to him. All of these findings can be used to guide the design of more appropriate social network models in the future.

In this paper we analytically and numerically investigate the dynamics of a nonlinear three-dimensional autonomous first-order ordinary differential equation system, obtained from paradigmatic Lorenz system by suppressing the y variable in the right-hand side of the second equation. The Routh–Hurwitz criterion is used to decide on the stability of the nontrivial equilibrium points of the system, as a function of the parameters. The dynamics of the system is numerically characterized by using diagrams that associate colors to largest Lyapunov exponent values in the parameter-space. Additionally, phase-space plots and bifurcation diagrams are used to characterize periodic and chaotic attractors.