A Weighted Evolving Network with Community Size Preferential Attachment

Community structure is an important characteristic in real complex network. It is a network consists of groups of nodes within which links are dense but among which links are sparse. In this paper, the evolving network include node, link and community growth and we apply the community size preferential attachment and strength preferential attachment to a growing weighted network model and utilize weight assigning mechanism from BBV model. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes' degrees and strengths.     

Multi-scaling Networks from Vertex Intrinsic Fitness

Defining and detecting the community structure is an important topic on exploring the complex networks. Previous works were mostly based on the so-called modularity method, in which vertices that interconnect to each other form modules in the network, In many real-world networks, however, vertices are grouped not by their connectivity but by their functions. To demonstrate this idea, we propose a new kind of network, in which the vertices are catalogued into several types and are assigned intrinsic fitness, Each type of vertices may satisfy a different fitness distribution. It is found that the whole network exhibits a multi-scaling degree distribution. The clustering coefficients of the subnetworks are modified by the interlinks between vertices in the subnetworks.     

Size distribution of sulfur species in fine and ultrafine aerosol particles using sulfur K-edge XANES

The sulfur species existing in different size aerosol particles were determined based on the ＇white line＇ energy shift and the features of post edge structure of sulfur K-edge XANES （X-ray Absorption Near Edge Structure）. The results indicated that sulfates were dominant sulfur species in aerosol particles. However, small amount of reductive sulfur species were also found in the ultrafine aerosol particles（〈0.1 μm）. Sulfates in aerosols mostly exhibited as （NH4）2SO4 and gypsum. than 0.952 μm, while gypsum was the dominant sulfate Most （NH4）2SO4 distributed in aerosol particles finer in coarse aerosols.     

Weighted scale-free networks induced by group preferential mechanism

Based on the BBV model [A. Barrat, M. Barthelemy, A. Vespignani, Phys. Rev. Lett. 92 (22) (2004)], we propose a weighted group preferential model, which is generated by the group preferential mechanism. We derive analytically the various statistical properties, such as the distribution of degree, strength and weight, the degree-strength relationship. Finally, we provide a contrast with the BBV model on the synchronization robustness and fragility through numerical simulation.     

Weighted Evolving Networks with Self-organized Communities

In order to describe the self-organization of communities in the evolution of weighted networks, we propose a new evolving model for weighted community-structured networks with the preferential mechanisms functioned in different levels according to community sizes and node strengths, respectively. Theoretical analyses and numerical simulations show that our model captures power-law distributions of community sizes, node strengths, and link weights, with tunable exponents of v ≥ 1, γ 〉 2, and α 〉 2, respectively, sharing large clustering coefficients and scaling clustering spectra, and covering the range from disassortative networks to assortative networks. Finally, we apply our new model to the scientific co-authorship networks with both their weighted and unweighted datasets to verify its effectiveness.     

Rayleigh-like distribution of particle transverse momenta in collisions at high energies

The transverse momentum distributions of final-state particles produced in collisions at high en-ergies are studied by using a two-component Rayleigh-like distribution.This representation is based on Liu＇s multisource ideal gas model which describes protons and fragments in high energy nucleus-nucleus collisions.The calculated results are in good agreement with the experimental data of Au-Au,Cu-Cu,d-Au,and pp collisions at the relativistic heavy ion collider energies.The experimental particle momentum distributions of p-Be collisions at 6.4,12.3,and 17.5 GeV/c,as well as Au-Au collisions at 1.5 AGeV are well described by a model based on a single Rayleigh-like distribution of particle transverse momenta.     

Undetermination of the synchronizability and relation between network betweenness centrality

Betweenness centrality is taken as a sensible indicator of the synchronizability of complex networks. To test whether betweenness centrality is a proper measure of the synchronizability in specific realizations of random networks, this paper adds edges to the networks and then evaluates the changes of betweenness centrality and network synchronizability. It finds that the two quantities vary independently.     

Cooperative Dynamics in Lattice-Embedded Scale-Free Networks

We investigate cooperative behaviors of lattice-embedded scale-free networking agents in the prisoner＇s dilemma game model by employing two initial strategy distribution mechanisms, which are specific distribution to the most connected sites （hubs） and random distribution. Our study indicates that the game dynamics crucially depends on the underlying spatial network structure with different strategy distribution mechanism. The cooperators＇ specific distribution contributes to an enhanced level of cooperation in the system compared with random one, and cooperation is robust to cooperators＇ specific distribution but fragile to defectors＇ specific distribution. Especially, unlike the specific case, increasing heterogeneity of network does not always favor the emergence of cooperation under random mechanism. Furthermore, we study the geographical effects and find that the graphically constrained network structure tends to improve the evolution of cooperation in random case and in specific one for a large temptation to defect.     

Poor rich demarcation of Matthew effect on scale-free systems and its application

In a scale-free network,only a minority of nodes are connected very often,while the majority of nodes are connected rarely. However,what is the ratio of minority nodes to majority nodes resulting from the Matthew effect In this paper,based on a simple preferential random model,the poor-rich demarcation points are found to vary in a limited range,and form a poor-rich demarcation interval that approximates to k/m ∈ [3,4]. As a result,the (cumulative) degree distribution of a scale-free network can be divided into three intervals: the poor interval,the demarcation interval and the rich interval. The inequality of the degree distribution in each interval is measured. Finally,the Matthew effect is applied to the ABC analysis of project management.     

Fluctuation Analysis of Decoy State QKD with Finite Data-Set Size

Decoy state method quantum key distribution （QKD） is one of the promising practical solutions for BB84 QKD with coherent light pulses. The number of data-set size in practical QKD protocol is always finite, which will cause statistical fluctuations. In this paper, we apply absolutely statistical fluctuation to amend the yield and error rate of the quantum state. The relationship between exchanged number of quantum signals and key generation rate is analyzed in our simulation, which offers a useful reference for experiment.     

Complex Behavior in a Selective Aging Neuron Model Based on Small World Networks

Complex behavior in a selective aging simple neuron model based on small world networks is investigated. The basic elements of the model are endowed with the main features of a neuron function. The structure of the selective aging neuron model is discussed. We also give some properties of the new network and find that the neuron model displays a power-law behavior. If the brain network is small world-like network, the mean avalanche size is almost the same unless the aging parameter is big enough.     

Transferring Multi-Dimensional Quantum States and Preparing Quantum Networks in Cavity QED

In this paper we propose a scheme for transferring quantum states and preparing quantum networks. Compared with the previous schemes, this scheme is more efficient, since three or four-dimensional quantum states can be transferred with a single step and information interchange of three-dimensional quantum states can be realized, which is a significant improvement. It is based on the resonant interaction of a three-mode cavity field with an atom. As a consequence, the interaction time is shortened greatly. Furthermore, we give some discussions about the feasibility of the scheme.     

Effect of Polynomial Expressed Distribution Dust Particles for Unmagnetized Two-Ion-Temperature Dusty Plasma

Linear dispersion relation for linear wave and a Kadomtsev-Petviashvili （KP） equation for nonlinear wave are given for the unmagnetized two-ion-temperature cold dusty plasma with many different dust grain species, The numerical results of variations of linear dispersion with respect to the different dust size distribution are given, Moreover, how the amplitude, width, and propagation velocity of solitary wave vary vs different dust size distribution is also studied numerically in this paper.     

Stability analysis of Markovian jumping stochastic Cohen Grossberg neural networks with discrete and distributed time varying delays

In this paper, the global asymptotic stability problem of Markovian jumping stochastic Cohen-Grossberg neural networks with discrete and distributed time-varying delays （MJSCGNNs） is considered. A novel LMI-based stability criterion is obtained by constructing a new Lyapunov functional to guarantee the asymptotic stability of MJSCGNNs. Our results can be easily verified and they are also less restrictive than previously known criteria and can be applied to Cohen-Grossberg neural networks, recurrent neural networks, and cellular neural networks. Finally, the proposed stability conditions are demonstrated with numerical examples.     

H∞ synchronization of chaotic neural networks with time-varying delays

In this paper,we investigate the problem of H∞ synchronization for chaotic neural networks with time-varying delays.A new model of the networks with disturbances in both master and slave systems is presented.By constructing a suitable Lyapunov–Krasovskii functional and using a reciprocally convex approach,a novel H∞ synchronization criterion for the networks concerned is established in terms of linear matrix inequalities(LMIs)which can be easily solved by various effective optimization algorithms.Two numerical examples are given to illustrate the effectiveness of the proposed method.     

y2-y∞learnlngof dynamic neural.networks

This paper proposes an y2-y∞ learning law as a new learning method for dynamic neural networks with external disturbance. Based on linear matrix inequality （LMI） formulation, the y2-y∞ learning law is presented to not only guarantee asymptotical stability of dynamic neural networks but also reduce the effect of external disturbance to an y2-y∞ induced norm constraint. It is shown that the design of the y2-y∞ learning law for such neural networks can be achieved by solving LMIs, which can be easily facilitated by using some standard numerical packages. A numerical example is presented to demonstrate the validity of the proposed learning law.     

Exponential Synchronization of Uncertain Complex Dynamical Networks with Delay Coupling

This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches.     

Unified description of angular distributions of target particles in light and heavy ion induced interactions in nuclear emulsions at high energies

Some investigations show that in light ion （LI） induced reactions, such as He, O, Ne, and Ar in nuclear emulsions （Em） at high energies, the angular distributions of the target particles show a wide structure around the polar angle V ≈ 60°. With heavy ions （HI） such as Kr and Au such a wide structure has not been observed. The experimental results on Mg-Em and Si-Em interactions also do not show such a wide structure in the angular distribution of the target particles. Using a multisource ideal gas model we uniformly describe the angular distributions of the target particles produced in LI-Em and HI-Em interactions. The result is not only in agreement with the mean trend, but also with the fluctuations of the experimental data. We conclude that the wide structure observed in LI-Em interactions may be the result of statistical fluctuations.     

Cation distributions estimated using the magnetic moments of the spinel ferrites Co_(1-x)Cr_xFe_2O_4 at 10K

（A）[B]2O4 ferrite samples with the composition COl_xCrxFe204 （0.0 ≤ x ≤1.0） are prepared using a hydrothermal method, and subjected to calcining in a tube furnace with an argon-flow at 1673 K for 2 h. X-ray diffraction patterns indicate that each of all the samples has a single phase cubic spinel structure with a space group of Fd3m. Magnetic measurements show that the saturation magnetization decreases with as the Cr content x increases. The cation distribution of the samples is estimated by fitting the dependence of the magnetic moments on x at l 0 K, using the quantum mechanical model previously proposed by our group. The calculated sum of the content values of the Cr3＋ and Cr2＋ cations occupying the （A） sites increases as the value of x increases. In the fitting process, the magnetic moment directions of the Cr3＋ and Cr2＋ cations are assumed to be antiparallel to those of the Fe and Co cations, respectively, which is in accordance with Hund＇s rules.     

Quantum Statistical Properties of Binomial Field Interacting with Two Entangled Atoms

Quantum statistical properties of the binomial field interacting with the two entangled atoms are investigated for the different initial conditions. It is found that the sub-Poissonian distribution and the antibunching effect can be presented for the certain ranges of the involved parameters.