Traveling length and minimal traveling time for flow through percolation networks with long-range spatial correlations

We study the distributions of traveling length l and minimal traveling time t through two-dimensional percolation porous media characterized by long-range spatial correlations. We model the dynamics of fluid displacement by the convective movement of tracer particles driven by a pressure difference between two fixed sites (''wells'') separated by Euclidean distance r. For strongly correlated pore networks at criticality, we find that the probability distribution functions P(l) and P(t) follow the same scaling Ansatz originally proposed for the uncorrelated case, but with quite different scaling exponents. We relate these changes in dynamical behavior to the main morphological difference between correlated and uncorrelated clusters, namely, the compactness of their backbones. Our simulations reveal that the dynamical scaling exponents for correlated geometries take values intermediate between the uncorrelated and homogeneous limiting cases

Ordering dynamics of the driven lattice gas model

The evolution of a two-dimensional driven lattice-gas model is studied on an L_x X L_y lattice. Scaling arguments and extensive numerical simulations are used to show that starting from random initial configuration the model evolves via two stages: (a) an early stage in which alternating stripes of particles and vacancies are formed along the direction y of the driving field, and (b) a stripe coarsening stage, in which the number of stripes is reduced and their average width increases. The number of stripes formed at the end of the first stage is shown to be a function of L_x/L_y^\phi, with \phi ~ 0.2. Thus, depending on this parameter, the resulting state could be either single or multi striped. In the second, stripe coarsening stage, the coarsening time is found to be proportional to L_y, becoming infinitely long in the thermodynamic limit. This implies that the multi striped state is thermodynamically stable. The results put previous studies of the model in a more general framework

An optimization principle for deriving nonequilibrium statistical models of Hamiltonian dynamics

A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. As in standard projection operator methods, a set of resolved variables is selected to capture the slow, macroscopic behavior of the system, and the family of quasi-equilibrium probability densities on phase space corresponding to these resolved variables is employed as a statistical model. The macroscopic dynamics of the mean resolved variables is determined by optimizing over paths of these probability densities. Specifically, a cost function is introduced that quantifies the lack-of-fit of such paths to the underlying microscopic dynamics; it is an ensemble-averaged, squared-norm of the residual that results from submitting a path of trial densities to the Liouville equation. The evolution of the macrostate is estimated by minimizing the time integral of the cost function. The value function for this optimization satisfies the associated Hamilton-Jacobi equation, and it determines the optimal relation between the statistical parameters and the irreversible fluxes of the resolved variables, thereby closing the reduced dynamics. The resulting equations for the macroscopic variables have the generic form of governing equations for nonequilibrium thermodynamics, and they furnish a rational extension of the classical equations of linear irreversible thermodynamics beyond the near-equilibrium regime. In particular, the value function is a thermodynamic potential that extends the classical dissipation function and supplies the nonlinear relation between thermodynamics forces and fluxes

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For this, we generate synthetic metabolic profiles for benchmarking purposes based on a well-established model for red blood cell metabolism. A variety of data sets is generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We apply ARACNE, a mainstream transcriptional networks reverse engineering algorithm, to these data sets and observe performance comparable to that obtained in the transcriptional domain, for which the algorithm was originally designed.Comment: 14 pages, 3 figures. Presented at the DIMACS Workshop on Dialogue on Reverse Engineering Assessment and Methods (DREAM), Sep 200

Theoretical models of the halo occupation distribution : separating central and satellite galaxies

The halo occupation distribution (HOD) describes the relation between galaxies and dark matter at the level of individual dark matter halos. The properties of galaxies residing at the centers of halos differ from those of satellite galaxies because of differences in their formation histories. Using a smoothed particle hydrodynamics (SPH) simulation and a semianalytic (SA) galaxy formation model, we examine the separate contributions of central and satellite galaxies to the HOD, more specifically to the probability P(N|M) that a halo of virial mass M contains N galaxies of a particular class. In agreement with earlier results for dark matter subhalos, we find that the mean occupation function langNrangM for galaxies above a baryonic mass threshold can be approximated by a step function for central galaxies plus a power law for satellites and that the distribution of satellite numbers is close to Poisson at fixed halo mass. Since the number of central galaxies is always zero or one, the width of P(N|M) is narrower than a Poisson distribution at low N and approaches Poisson at high N. For galaxy samples defined by different baryonic mass thresholds, there is a nearly linear relation between the minimum halo mass Mmin required to host a central galaxy and the mass M1 at which an average halo hosts one satellite, with M1 ≈ 14Mmin (SPH) or M1 ≈ 18Mmin (SA). The stellar population age of central galaxies correlates with halo mass, and this correlation explains much of the age dependence of the galaxy HOD. The mean occupation number of young galaxies exhibits a local minimum at M ~ 10Mmin where halos are too massive to host a young central galaxy but not massive enough to host satellites. Using the SA model, we show that the conditional galaxy mass function at fixed halo mass cannot be described by a Schechter function because central galaxies produce a "bump" at high masses. We suggest parameterizations for the HOD and the conditional luminosity function that can be used to model observed galaxy clustering. Many of our predictions are in good agreement with recent results inferred from clustering in the Sloan Digital Sky Survey

Media Effects Reconsidered

Arguments are presented for looking at cognitive outcomes as dependent variables in communication research rather than placing emphasis only on affective realms. This approach also brings attention to the independent-dependent variable emphases found in the communication literature over the last few decades. The social context of media use and the motivations that spring from this contextual embeddedness are also discussed with regard to information utility and the distribution of information availability. Finally a comment is offered on how these perspectives may relate to developments in new media technology.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66556/2/10.1177_009365027400100205.pd

Spectral Classification; Old and Contemporary

Beginning with a historical account of the spectral classification, its refinement through additional criteria is presented. The line strengths and ratios used in two dimensional classifications of each spectral class are described. A parallel classification scheme for metal-poor stars and the standards used for classification are presented. The extension of spectral classification beyond M to L and T and spectroscopic classification criteria relevant to these classes are described. Contemporary methods of classifications based upon different automated approaches are introduced.Comment: To be published in "Principles and Perspectives in Cosmochemistry" Lecture Notes on Kodai School on Synthesis of Elements in Stars: Ed Aruna Goswami & Eswar Reddy, Springer Verlag, 2009, 17 pages, 10 figure

ESR, ENDOR and TRIPLE resonance studies of the primary donor radical cation P960+ in the photosynthetic bacterium Rhodopseudomonas viridis

The light-induced radical cation of the primary electron donor P960+• in photosynthetic reaction centers from Rhodopseudomonas viridis has been investigated by ESR, ENDOR and TRIPLE techniques. Both the comparison with the cation radical of monomeric bacteriochlorophyll b (BChl b) and with molecular-orbital calculations performed on P960+• using the results of an X-ray structure analysis, consistently show an asymmetric distribution of the unpaired electron over the two BChl b molecules which constitute P960+•. The possible relevance of this result for the primary electron transfer step in the reaction center is briefly discussed