Cosmological model of the interaction between dark matter and dark energy

In this paper, we test the dark matter-dark energy interacting cosmological model with a dynamic equation of state $w_{DE}(z)=w_{0}+w_{1}z/(1+z)$, using type Ia supernovae (SNe Ia), Hubble parameter data, baryonic acoustic oscillation (BAO) measurements, and the cosmic microwave background (CMB) observation. This interacting cosmological model has not been studied before. The best-fitted parameters with $1 \sigma$ uncertainties are $\delta=-0.022 \pm 0.006$, $\Omega_{DM}^{0}=0.213 \pm 0.008$, $w_0 =-1.210 \pm 0.033$ and $w_1=0.872 \pm 0.072$ with $\chi^2_{min}/dof = 0.990$. At the $1 \sigma$ confidence level, we find $\delta<0$, which means that the energy transfer prefers from dark matter to dark energy. We also find that the SNe Ia are in tension with the combination of CMB, BAO and Hubble parameter data. The evolution of $\rho_{DM}/\rho_{DE}$ indicates that this interacting model is a good approach to solve the coincidence problem, because the $\rho_{DE}$ decrease with scale factor $a$. The transition redshift is $z_{tr}=0.63 \pm 0.07$ in this model.Comment: 6 pages, 6 figures, published in A&

Self-organizing peer-to-peer social networks

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 The Authors.Peer-to-peer (P2P) systems provide a new solution to distributed information and resource sharing because of its outstanding properties in decentralization, dynamics, flexibility, autonomy, and cooperation, summarized as DDFAC in this paper. After a detailed analysis of the current P2P literature, this paper suggests to better exploit peer social relationships and peer autonomy to achieve efficient P2P structure design. Accordingly, this paper proposes Self-organizing peer-to-peer social networks (SoPPSoNs) to self-organize distributed peers in a decentralized way, in which neuron-like agents following extended Hebbian rules found in the brain activity represent peers to discover useful peer connections. The self-organized networks capture social associations of peers in resource sharing, and hence are called P2P social networks. SoPPSoNs have improved search speed and success rate as peer social networks are correctly formed. This has been verified through tests on real data collected from the Gnutella system. Analysis on the Gnutella data has verified that social associations of peers in reality are directed, asymmetric and weighted, validating the design of SoPPSoN. The tests presented in this paper have also evaluated the scalability of SoPPSoN, its performance under varied initial network connectivity and the effects of different learning rules.National Natural Science of Foundation of Chin

Study of glass preforms for glass fiber optics applications (study of space processing of ceramic materials)

The feasibility, and technical and economic desirability was studied of space processing of glass preforms for optical fiber transmission applications. The results indicate that space processing can produce glass preforms of equal quality at lower cost than earth bound production, and can produce diameter modulation in the glass preform which promotes mode coupling and lowers the dispersion. The glass composition can be modified through the evaporative and diffusion processes, and graded refractive index profiles can be produced. A brief summary of the state of the art in optical fiber transmission is included