Epidemic spreading in a scale-free network of regular lattices

The susceptible-infected-susceptible (SIS) epidemics in a scale-free network in which each node is a square lattice itself is investigated through large-scale computer simulations. The model combines a local contact process among individuals in a node (or city) with stochastic long-range infections due to people traveling between cities interconnected by the national transportation scale-free network. A nonzero epidemic threshold is found and it is approached with a power-law behavior by the density of infected individuals, as observed in the small-world network of Watts and Strogatz. Also, the epidemic propagation follows a 1/f$1/f$, hierarchical dynamics from the highly connected square lattices to the smaller degree nodes in outbreaks with sizes distributed accordingly a Gaussian function.     

Dynamic properties of epidemic spreading on finite size complex networks

The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS （susceptibleinfected-susceptible） model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.     

Phase diagram of speed gradient model with an on-ramp

In this paper, phase transitions are investigated in speed gradient model with an on-ramp. Phase diagrams of traffic flow composed of manually driven vehicles and adaptive cruise control (ACC) vehicles are studied, respectively. The traffic flow composed of ACC vehicles is modeled by enhancing propagation speed of small disturbance. The phase diagram of traffic flow composed of manually driven vehicles is similar to that in previous works, in which such states as pinned localized cluster (PLC), moving localized cluster (MLC), triggered stop-and-go traffic (TSG), oscillatory congested traffic (OCT), and homogeneous congested traffic (HCT) are reproduced. In the phase diagram of traffic flow composed of ACC vehicles, traffic stability is enhanced and such states as PLC, MLC, and TSG disappear. Furthermore, some interesting phenomena, such as stationary OCT upstream of on-ramp and appearance of second OCT in HCT, are identified.     

Effects of delayed recovery and nonuniform transmission on the spreading of diseases in complex networks

We investigate the effects of delaying the time to recovery (delayed recovery) and of nonuniform transmission on the propagation of diseases on structured populations. Through a mean-field approximation and large-scale numerical simulations, we find that postponing the transition from the infectious to the recovered states can largely reduce the epidemic threshold, therefore promoting the outbreak of epidemics. On the other hand, if we consider nonuniform transmission among individuals, the epidemic threshold increases, thus inhibiting the spreading process. When both mechanisms are at work, the latter might prevail, hence resulting in an increase of the epidemic threshold with respect to the standard case, in which both ingredients are absent. Our findings are of interest for a better understanding of how diseases propagate on structured populations and to a further design of efficient immunization strategies.     

Roy-型奇偶非线性相干态的位相概率分布

借助于数值计算方法，研究了Roy-型奇偶非线性相干态的位相概率分布特性.结果表明，它们的位相概率分布不同；与通常的奇偶相干态不同，在这种新的奇偶非线性相干态中，Pegg-Barnett位相概率分布能明显地反映出不同的量子干涉特性. 关键词： Roy-型奇偶非线性相干态 Pegg-Barnett位相算符公式 位相概率分布     

Influence of chemical disorder on the magnetic behaviour and phase diagram of the FexNi1−x system

In this paper, we calculate the equilibrium phase diagram and the magnetic moment curve for the Fe_xNi_1−x system and simulate their Mössbauer spectra assuming a binomial distribution to reproduce the chemical disorder in these alloys. We also assume that the high-spin/low-spin transition for a central iron atom is governed by the number of nearest neighbours and next nearest neighbours of the iron atoms. The calculated equilibrium phase diagram and the magnetic moment curve are very close to that presented in the literature and the simulated Mössbauer spectra are in excellent agreement with that of their corresponding phases measured in our lab.     

Formation and decay kinetics of nickel nitrides resulting from nitrogen ion implantation. The nickel–nitrogen phase diagram

Structural transformations in nickel films exposed to N⁺ ions were investigated through the use of electron diffraction, electron microscopy, Rutherford backscattering (RBS) of He⁺ ions, thermal desorption spectroscopy (TDS).

With an increasing exposure dose, there occurred a smooth transition of the FCC structure of Ni to the HCP phase -Ni₃N with the lattice parameters a=0.266 nm and c=0.430 nm. The completion of the transition was observed once the implanted nitrogen concentration corresponding to the stoichiometric ratio of Ni₃N was attained, this giving evidence for the chemical nature of the structural change observed.

During annealing, structure variations were traced, enabling one to observe the following four nickel nitrides: (1) -Ni₃N with a disordered arrangement of nitrogen atoms (HCP-phase with a=0.266 nm and c=0.430 nm), (2) β-Ni₃N with an ordered arrangement of nitrogen atoms (two hexagonal lattices: one with a=0.266 nm, c=0.430 nm, and the other with a=0.466 nm and c=0.43 nm), (3) Ni₄N having a primitive cubic lattice structure with a=0.377 nm, (4) Ni₈N having the FCC structure with a=0.725 nm.

The results of an investigation have led to building up a phase diagram for the Ni–N system.     

Ranking the spreading influence of nodes in complex networks: An extended weighted degree centrality based on a remaining minimum degree decomposition

Ranking the spreading influence of nodes is crucial for developing strategies to control the spreading process on complex networks. In this letter, we define, for the first time, a remaining minimum degree (RMD) decomposition by removing the node(s) with the minimum degree iteratively. Based on the RMD decomposition, a weighted degree (WD) is presented by utilizing the RMD indices of the nearest neighbors of a node. WD assigns a weight to each degree of this node, which can distinguish the contribution of each degree to the spreading influence. Further, an extended weighted degree (EWD) centrality is proposed by extending the WD of the nearest neighbors of a node. Assuming that the spreading process on networks follows the Susceptible-Infectious-Recovered (SIR) model, we perform extensive experiments on a series of synthetic and real networks to comprehensively evaluate the performance of EWD and other eleven representative measures. The experimental results show that EWD is a relatively efficient measure in running efficiency, it exposes an advantage in accuracy in the networks with a relatively small degree heterogeneity, as well as exposes a competitive performance in resolution.