International Journal of Modern Physics C

Density functional (DF) theory is used to study confined two-dimensional molecular fluids. The approximate DF used here is based upon a functional Taylor series expansion of the excess grand potential about the density of a uniform molecular liquid. This formalism is applied to obtain the density profiles of the hard-ellipse fluid confined between two parallel hard walls. The required direct correlation function is obtained using Percus–Yevick and hypernetted chain approximations for low- and high-number density, respectively. Both the restricted orientation model and the extension of this model are used. Generally, we obtained that the number density of the hard ellipses with the major axes parallel to the wall is larger near the walls than the other directions. To check the results, we show that for isotropic hard-ellipse fluids the average number density in the middle of the wall is almost equal to the bulk density and as we expect the average number density of the ellipses at the wall is nearly equal to the amount of the reduced pressure, βP. We also perform Monte Carlo simulation and find reasonable agreement with our results.

A weighted scale-free OFC model improving the redistribution rule of the original model has been introduced. Our model displays self-organized criticality behaviors with different network parameters, and the average earthquake size has been introduced to show the different effects of these parameters. Transient and oscillatory activity have been detected based on our weighted network, and the transient time increases with decreasing dissipative parameter.

The point canonical transformation (PCT) approach is used to solve the Schrödinger equation for an arbitrary dimension D with a power-law position-dependent effective mass (PDEM) distribution function for the pseudoharmonic and modified Kratzer (Mie-type) diatomic molecular potentials. In mapping the transformed exactly solvable D-dimensional (D ≥ 2) Schrödinger equation with constant mass into the effective mass equation by using a proper transformation, the exact bound state solutions including the energy eigenvalues and corresponding wave functions are derived. The well-known pseudoharmonic and modified Kratzer exact eigenstates of various dimensionality is manifested.

In this paper, we employ united-residue (UNRES) approach to study folding processes of a six-helix protein domain (the C-terminal domain of Ku86 protein, PDB ID: 1Q2Z). We simulated forty-eight 110-ns independent molecular dynamics trajectories with UNRES starting from extended conformations for this protein. The protein domain successfully folds into its native state and the results show that its folding process is relatively simple: first, the secondary structures form very fast with the hydrophobic collapse, then helix pairs form, and finally these pairs assemble into the tertiary structure. We also find the first-half (the first three helices) and last-half (the last three helices) parts of this protein domain can fold into their native conformations independently and this suggests that this protein may be evolved from smaller polypeptide or protein.

We present a new explicit Numerov-type method for the solution of second-order linear initial value problems with oscillating solutions. The new method attains algebraic order seven at a cost of six function evaluations per step. The method has the characteristic of zero dissipation and high phase-lag order making it suitable for the solution of problems with oscillatory solutions. The numerical tests in a variety of problems justify our effort.

The combination of large eddy simulation (LES) and newly proposed Taylor-series expansion method of moments (TEMOM) is performed for simulating particulate matters emitted from vehicle engine tailpipe. The momentum, heat and mass transfer, binary homogeneous nucleation, Brownian coagulation, Brownian and turbulent diffusion, condensation and thermophoresis are simultaneously taken into account. Good agreements between the experimental and simulated results with respect to the pollutant dispersion are obtained. Compared to other published methods, the present TEMOM requires the least computational time with much accuracy for predicting nanoparticle dynamics. The instantaneous results show that large eddies dominate the evolution of particulate dynamics as exhaust develops, while binary homogeneous sulfuric-water nucleation mainly appears at the interface between the exhaust and ambient cool gases. The increasing of fuel sulfur content and relative humidity or the decreasing of environment temperature leads to an increase in particulate product rate, while volume-averaged particle diameter increases with increasing fuel sulfur content and environment temperature. The variation of geometric standard deviation suggests the nucleated particles eventually approach the asymptotic distribution in the dilution atmosphere, and this distribution is independent of the fuel sulfur content. The variance of upstream turbulence intensity significantly affects the evolution of particulate matters inside the plume.

This paper confirms the applicability of a newly developed efficient algorithm, the direct electrifying method, for identifying backbone for 3D site and bond percolating networks. This algorithm is based on the current-carrying definition of backbone and carried out on the predetermined spanning cluster, which is assumed to be a resistor network. The scaling exponents so obtained for backbone mass, red bonds, and conductivity are in very good agreement with some existing results. The perfectly balanced bonds in 3D backbone structures are predicted first time to be 0.00179 ± 0.00009 and 0.00604 ± 0.00008 of the backbone mass for bond and site percolations, respectively.

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules.

Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

In this paper a Traffic Cellular Automata (TCA) simulation of a highly congested round-about in Mauritius is performed. The simulations are performed using a multi-cell model that includes anticipation and probability randomization. The simulation model is first calibrated to match actual traffic count statistics taken at the round-about. The topology of the round-about is then modified and the TCA model is used to predict the impact on the congestion level of different changes made. The simulation results enable the assessment of the impact on the traffic density and travel time of the different modifications made. It has been found that the construction of a flyover bridge at the round-about will be the most convenient solution to alleviate congestion and improve the flux significantly.

Effects of noise and coupling on the dynamics of a square lattice neuronal network are studied in this paper. Patterns and collective phenomena such as firing synchronization are investigated in networks with dynamics of each neuron described by FitzHugh–Nagumo model. As the noise intensity is increased, typical patterns emerge spatially, which propagate through the networks in the form of circular waves. Further increasing noise can destroy the circular wave, and then some random portraits appear. Moreover, the spatio-temporal coherence and the transitions of firing synchronization characterized by the rate of firing are investigated as the noise intensity and the coupling strength vary. The maximal coherence of the oscillations could be found at two optimal noise intensities (or coupling strength) for appropriate coupling strength (or noise intensity), displaying coherence bi-resonance. Finally, the critical relation between the noise intensity and the coupling strength is given to investigate the occurrence of firing synchronization in the network.

In this paper, a new model of opinion formation within the framework of evolutionary game theory is presented. The model simulates strategic situations when people are in opinion discussion. Heterogeneous agents adjust their behaviors to the environment during discussions, and their interacting strategies evolve together with opinions. In the proposed game, we take into account payoff discount to join a discussion, and the situation that people might drop out of an unpromising game. Analytical and emulational results show that evolution of opinion and strategy always tend to converge, with utility threshold, memory length, and decision uncertainty parameters influencing the convergence time. The model displays different dynamical regimes when we set differently the rule when people are at a loss in strategy.

We further study the competition among loner, cooperative and defective strategies by considering an evolutionary prisoner's dilemma (PD) game with some troublemakers in the random network by means of Monte Carlo simulations. It can be observed that the frequency of cooperators (f_c) decreases with increasing of loners' (e) and defectors' payoffs (b). In particular, f_c has a sharp decline when the loners' payoffs approximate 1.0. In addition, we find that introduction of troublemaker strategies prevents the uniform defection in the spatial evolutionary PD games for large b values and small e values. In practice, it also prevents cooperative strategies and defective strategies from vanishing for large e values.