International Journal of Modern Physics C

In human societies, personal heterogeneity may affect the strategy adoption capability of the individuals. In this paper, we study the effects of heterogeneous learning ability on the evolution of cooperation by introducing heterogeneous imitation capability of players. We design a pre-factor ${\omega }_x$ to represent the heterogeneous learning ability of players, which is related to the degree of players. And a parameter $\alpha$ is used to tune the learning levels. If $\alpha >0$, the learning ability of players decreases and the low-degree player has the higher reduction level, but if $\alpha <0$, the learning ability of low-degree players enhances to a higher level. By carrying out extensive simulations, it reveals that the evolution of cooperation is influenced significantly by introducing player’s heterogeneous learning ability and can be promoted under the right circumstances. This finding sheds some light on the important effect of individual heterogeneity on the evolutionary game.

We explore the impact of positive news on rumor spreading in this paper. It is a fact that most of the rumors related to hot events or emergencies can be propagated rapidly on the hotbed of online social networks. In Chinese words, it is better to divert rather than block. Therefore, we propose the spreading model $IS{S}_{P}R$ in which positive news is a good factor to guide rumor spreading. Based on transition probability method, we have got the spreading parameters of the $IS{S}_{P}R$ model by running the rumor spreading process in online social networks with scale-free characteristics. The results give a good proof that improving the activity of the positive news spreader $S_P$ derived from the $IS{S}_{P}R$ model can guide and restrain the spreading speed of rumor smoothly.

The aim of this work is to conduct numerical study of fluid flow and natural convection heat transfer by utilizing the nanofluid in a two-dimensional horizontal channel consisting of a sinusoidal obstacle by lattice Boltzmann method (LBM). The fluid in the channel is a water-based nanofluid containing Cuo nanoparticles. Thermal conductivity and nanofluid’s viscosity are calculated by Patel and Brinkman models, respectively. A wide range of parameters such as the Reynolds number ($\mathrm{\text{Re}}=100$–400) and the solid volume fraction ranging ($\mathrm{\Phi }=0$–0.05) at different non-dimensional amplitude of the wavy wall of the sinusoidal obstacle ($A=0$–20) on the streamlines and temperature contours are investigated in the present study. In addition, the local and average Nusselt numbers are illustrated on lower wall of the channel. The sensitivity to the resolution and representation of the sinusoidal obstacle’s shape on flow field and heat transfer by LBM simulations are the main interest and innovation of this study. The results showed that increasing the solid volume fraction $\mathrm{\Phi }$ and Reynolds number Re leads to increase the average Nusselt numbers. The maximum average Nusselt number occurs when the Reynolds number and solid volume fraction are maximum and amplitude of the wavy wall is minimum. Also, by decreasing the $A$, the vortex shedding forms up at higher Reynolds number in the wake region downstream of the obstacle.

A type of discrete Boltzmann model for simulating shallow water flows is derived by using the Hermite expansion approach. Through analytical analysis, we study the impact of truncating distribution function and discretizing particle velocity space. It is found that the convergence behavior of expansion is nontrivial while the conservation laws are naturally satisfied. Moreover, the balance of source terms and flux terms for steady solutions is not sacrificed. Further numerical validations show that the capability of simulating supercritical flows is enhanced by employing higher-order expansion and quadrature.

Various feedback strategies are proposed to improve the traffic flow. However, most of these works did not take road safety into consideration. In this paper, we studied the impact of four feedback strategies on the probability of rear-end collisions ($P_{\mathrm{\text{ac}}}$). We proposed a new feedback strategy named Accidents Coefficient Feedback Strategy (ACFS) in which dynamic information can be generated and displayed on a board at the entrance of two-route scenario with intersection to help drivers to choose the appropriate road. This new strategy can greatly improve road safety and make the flow smooth as possible at the same time. Moreover, the impact of the intersection and boundary rates ($\alpha$ and $\beta$) on $P_{\mathrm{\text{ac}}}$ is also studied.

This paper shows that orbital equations generated by iteration of polynomial maps do not necessarily have a unique representation. Remarkably, they may be represented in an infinity of ways, all interconnected by certain nonlinear transformations. Five direct and five inverse transformations are established explicitly between a pair of orbits defined by cyclic quintic polynomials with real roots and minimum discriminant. In addition, infinite sequences of transformations generated recursively are introduced and shown to produce unlimited supplies of equivalent orbital equations. Such transformations are generic and valid for arbitrary dynamics governed by algebraic equations of motion.

In this paper, the flux difference memory integral (FDMI) effect is introduced into the lattice hydrodynamic model for a two-lane freeway. The FDMI effect plays an important role on the linear stability condition, from theoretic analysis, in a two-lane system. The FDMI effect including the intensity reaction coefficient and the integral historical time are investigated on two lanes via simulation. From numerical simulation, both lane changing rate and FDMI effect strengthening the stability of traffic flow on two lanes is determined.

Structural optimization of ternary Pd_mPt${}_{(13-m)}$Ag${}_{42}$ nanoalloys was performed using the basin-hopping algorithm, and the Gupta many-body potential was adopted to model interatomic interaction. The optimization results show that all compositions have a structure based on icosahedron with a core–shell segregation. While the Ag atoms prefer to segregate to the surface, Pd and Pt atoms were located at the core of the cluster due to the higher surface and cohesive energy. The single platinum atom with the highest cohesive energy in Pd${}_{12}$Pt₁Ag${}_{42}$ nanoalloy was located at the center of the cluster. Also in all other compositions except Pd${}_{13}$Ag${}_{42}$, Pd atoms occupy the second shell position of the icosahedron structure. We used classical molecular dynamics (MD) simulations in canonical ensemble conditions (NVT) to investigate the melting temperatures of ternary Pd_mPt${}_{(13-m)}$Ag${}_{42}$ nanoalloys with the interatomic interactions modeled by the same potential with optimizations. The icosahedral structures were taken as the initial configurations for MD simulations. We obtained caloric curves and Lindemann indexes to investigate the melting transitions. The simulation results showed that varying the composition gives rise to a fluctuation in melting temperatures. The highest melting temperature belongs to the Pd₉Pt₄Ag${}_{42}$ nanoalloy cluster within the other compositions. However, the relative stability investigation indicates the Pd₈Pt₅Ag${}_{42}$ nanoalloy cluster as the most stable composition. The Lindemann indexes obtained for the second and third shell of icosahedral structures show that the melting takes place as a whole without any surface premelting.

A new methodology was introduced to investigate the pattern formation in time series systems due to their viscoelastic behavior. Four stochastic processes, uniform distribution, normal distribution, Nasdaq-100 stock market index, and a melody were studied within this context. The time series data were converted into vectorial forms in a scattering diagram. The sequential vectors can be split into its in-line (or conservative) and out-of-line (or dissipative) components. Thus, one can define the storage and loss modulus for conservative, and dissipative components, respectively. Instead of using the geometric Brownian equation which involves Wiener noise term, the changes were taken into consideration at every step by introducing “lethargy” concept and the deviation from it. Thus, the mathematics is somehow simplified, and the dynamical behavior of time series systems can be elucidated at every step of change. The viscoelastic behavior of time series systems reveals patterns of the viscoelastic parameters such as storage and loss modulus, and also of thermodynamic work-like and heat-like properties. Besides, there occur some minima and maxima in the distribution of the angles between the sequential vectors in the scattering diagram. The same is true for the change of entropy of the system.

This paper explores $3$-neighborhood $3$-state cellular automata (CAs) to find a list of potential pseudo-random number generators (PRNGs). As the rule-space is huge ($3^{27}$), we have taken two greedy strategies to select the initial set of rules. These CAs are analyzed theoretically and empirically to find the CAs with consistently good randomness properties. Finally, we have listed $596$ good CAs which qualify as potential PRNGs.

In this paper, we study how the lifetime of packets impacts the overall transmission capacity of scale-free communication networks. In our model, we observed an abrupt phase transition of packet loss rate when the packet generation rate increases, based on which we redefined the network capacity as the critical packet generation rate of packet loss. Then, we found a sharp phase transition of network capacity with the increase of packet lifetime, which is also predicted by our analytical results of network capacity. Moreover, we obtained that there is an optimal routing parameter of the tunable path routing algorithm corresponding to the maximum network capacity. Finally, we discussed the influence of network topological structure on the network capacity.

This research deals with an analysis of the Hall current effect on the mixed convective magneto-micropolar fluid flow over a permeable stretching/shrinking sheet. Impact of the Newtonian heating parameter is analyzed in the slip flow regime. The nonlinear equations of the fluid flow are derived with the help of a similarity transform and its solutions are obtained by Optimal Homotopy Analysis Method (OHAM). For limiting cases, obtained results are in excellent agreement with the available exact and numerical results in the literature. The graphical and tabular representations of the obtained results show significant effects of the physical parameters on the magneto-micropolar fluid flow and heat transfer characteristics. In particular, it is observed that, as the sheet stretches, a change in the Hall current parameter yields a higher horizontal velocity component for the lower value of the magnetic field parameter; while it produces a higher and shorter transverse velocity profile at high intensity of the magnetic field. In Magnetohydrodynamics (MHD) generators, Hall effects are an important consideration to analyze the heat transfer phenomenon with high temperature conducting fluids.

The sensitivities of both time and energy resolutions of a typical scintillation detector to major optical parameters (i.e. paint reflectivity, quantum efficiency of photomultiplier tube and attenuation coefficient) have been estimated using a dedicated Monte Carlo (MC) optical photon transport (OPT) simulation code, PHOTRACK, and the OPT capabilities of general-purpose code, FLUKA. Both cylindrical and parallelepiped geometries have been considered for the scintillator cell and lightguide. The results determine the scintillation light wavelength regions that the energy and time resolution represent enhanced sensitivities to small change/uncertainty in optical parameters.

Adsorption of hydrogen atoms on pure and modified graphene layers was studied by density functional theory (DFT). Modifications were made to the graphene layers by adding M adatom (M $=$ O or F). The relaxed structures, energetic, electronic and magnetic properties of the M-graphene, H-graphene and M-graphene-NH layers were studied theoretically using the full-potential linearized augmented plane wave (FP-LAPW) within the generalized gradient approximation (GGA). The results showed that the presence of O or F as adatom on graphene allowed the stability of multi-H atom adsorption with a large and positive adsorption energy. A bandgap opening was observed for O-graphene-3H and O-graphene-4H sheets. Also, O-graphene, O-graphene-H and F-graphene-NH were found to have metallic behavior. O-graphene-3H sheet was found to have a half-metallic ferromagnetic behavior since its total magnetic moments is equal to an integer. In addition, the band structure shows that O-graphene-3H sheet is a semiconductor. Useful optical applications are predicted for M-graphene-NH sheet due to the absorption and reflectivity results.