The K−p→Σ0π0K^-p\to \Sigma^0\pi^0 reaction at low energies in a chiral quark model

A chiral quark-model approach is extended to the study of the $\bar{K}N$ scattering at low energies. The process of $K^-p\to \Sigma^0\pi^0$ at $P_K\lesssim 800$ MeV/c (i.e. the center mass energy $W\lesssim 1.7$ GeV) is investigated. This approach is successful in describing the differential cross sections and total cross section with the roles of the low-lying $\Lambda$ resonances in $n=1$ shells clarified. The $\Lambda(1405)S_{01}$ dominates the reactions over the energy region considered here. Around $P_K\simeq 400$ MeV/c, the $\Lambda(1520)D_{03}$ is responsible for a strong resonant peak in the cross section. The $\Lambda(1670)S_{01}$ has obvious contributions around $P_K=750$ MeV/c, while the contribution of $\Lambda(1690)D_{03}$ is less important in this energy region. The non-resonant background contributions, i.e. $u$-channel and $t$-channel, also play important roles in the explanation of the angular distributions due to amplitude interferences.Comment: 18 pages and 7 figure

Gene Expression Based Leukemia Sub-Classification Using Committee Neural Networks

Analysis of gene expression data provides an objective and efficient technique for sub-classification of leukemia. The purpose of the present study was to design a committee neural networks based classification systems to subcategorize leukemia gene expression data. In the study, a binary classification system was considered to differentiate acute lymphoblastic leukemia from acute myeloid leukemia. A ternary classification system which classifies leukemia expression data into three subclasses including B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia and acute myeloid leukemia was also developed. In each classification system gene expression profiles of leukemia patients were first subjected to a sequence of simple preprocessing steps. This resulted in filtering out approximately 95 percent of the non-informative genes. The remaining 5 percent of the informative genes were used to train a set of artificial neural networks with different parameters and architectures. The networks that gave the best results during initial testing were recruited into a committee. The committee decision was by majority voting. The committee neural network system was later evaluated using data not used in training. The binary classification system classified microarray gene expression profiles into two categories with 100 percent accuracy and the ternary system correctly predicted the three subclasses of leukemia in over 97 percent of the cases

Networking Effects on Cooperation in Evolutionary Snowdrift Game

The effects of networking on the extent of cooperation emerging in a competitive setting are studied. The evolutionary snowdrift game, which represents a realistic alternative to the well-known Prisoner's Dilemma, is studied in the Watts-Strogatz network that spans the regular, small-world, and random networks through random re-wiring. Over a wide range of payoffs, a re-wired network is found to suppress cooperation when compared with a well-mixed or fully connected system. Two extinction payoffs, that characterize the emergence of a homogeneous steady state, are identified. It is found that, unlike in the Prisoner's Dilemma, the standard deviation of the degree distribution is the dominant network property that governs the extinction payoffs.Comment: Changed conten

Pure multiplicative stochastic resonance of anti-tumor model with seasonal modulability

The effects of pure multiplicative noise on stochastic resonance in an anti-tumor system modulated by a seasonal external field are investigated by using theoretical analyses of the generalized potential and numerical simulations. For optimally selected values of the multiplicative noise intensity quasi-symmetry of two potential minima and stochastic resonance are observed. Theoretical results and numerical simulations are in good quantitative agreement.Comment: 5 pages, 5 figure

Spatiotemporal Fluctuation Induced Transition in a Tumor Model with Immune Surveillance

We report on a simple model of spatial extend anti-tumor system with a fluctuation in growth rate, which can undergo a nonequilibrium phase transition. Three states as excited, sub-excited and non-excited states of a tumor are defined to describe its growth. The multiplicative noise is found to be double-face: The positive effect on a non-excited tumor and the negative effect on an excited tumor.Comment: 8pages,5figure

Effects of Contrarians in the Minority Game

We study the effects of the presence of contrarians in an agent-based model of competing populations. Contrarians are common in societies. These contrarians are agents who deliberately prefer to hold an opinion that is contrary to the prevailing idea of the commons or normal agents. Contrarians are introduced within the context of the Minority Game (MG), which is a binary model for an evolving and adaptive population of agents competing for a limited resource. Results of numerical simulations reveal that the average success rate among the agents depends non-monotonically on the fraction $a_{c}$ of contrarians. For small $a_{c}$, the contrarians systematically outperform the normal agents by avoiding the crowd effect and enhance the overall success rate. For high $a_{c}$, the anti-persistent nature of the MG is disturbed and the few normal agents outperform the contrarians. Qualitative discussion and analytic results for the small $a_{c}$ and high $a_{c}$ regimes are also presented, and the crossover behavior between the two regimes is discussed.Comment: revtex, 11 pages, 4 figure

A Tracker Solution for a Holographic Dark Energy Model

We investigate a kind of holographic dark energy model with the future event horizon the IR cutoff and the equation of state -1. In this model, the constraint on the equation of state automatically specifies an interaction between matter and dark energy. With this interaction included, an accelerating expansion is obtained as well as the transition from deceleration to acceleration. It is found that there exists a stable tracker solution for the numerical parameter $d>1$, and $d$ smaller than one will not lead to a physical solution. This model provides another possible phenomenological framework to alleviate the cosmological coincidence problem in the context of holographic dark energy. Some properties of the evolution which are relevant to cosmological parameters are also discussed.Comment: 10 pages, 3 figures; accepted for publication in Int.J.Mod.Phys.