Timing of the emergence of new successful viral strains in seasonal influenza

High evolvability of influenza virus and the complex nature of its antagonistic interaction with the host immune system make it difficult to predict which strain of virus will become epidemic next and when it will emerge. To investigate the most likely time at which a new successful strain emerges every year in seasonal influenza, we use an individual-based model that takes into account the seasonality in transmission rate and host cross-immunity against a current viral strain due to previous infections with other strains. Our model deals with antigenic evolution of influenza virus that originated by point mutations at the antigen determining sites and is driven by host immune response. Under the range of parameters by which influenza virus shows a .trunk. shape in its phylogenetic tree, as is typical in influenza A virus evolution, we find that most successful mutant strains emerge in an early part of the epidemic season, and that the time when the number of infected hosts reaches a maximum tends to be more than one season after viral emergence. This carryover of the epidemic peak timing implies that we can detect the strain that will become dominant in the epidemic in the following year

Timing of the emergence of new successful viral strains in seasonal influenza

High evolvability of influenza virus and the complex nature of its antagonistic interaction with the host immune system make it difficult to predict which strain of virus will become epidemic next and when it will emerge. To investigate the most likely time at which a new successful strain emerges every year in seasonal influenza, we use an individual-based model that takes into account the seasonality in transmission rate and host cross-immunity against a current viral strain due to previous infections with other strains. Our model deals with antigenic evolution of influenza virus that originated by point mutations at the antigen determining sites and is driven by host immune response. Under the range of parameters by which influenza virus shows a .trunk. shape in its phylogenetic tree, as is typical in influenza A virus evolution, we find that most successful mutant strains emerge in an early part of the epidemic season, and that the time when the number of infected hosts reaches a maximum tends to be more than one season after viral emergence. This carryover of the epidemic peak timing implies that we can detect the strain that will become dominant in the epidemic in the following year

Aging in coherent noise models and natural time

Event correlation between aftershocks in the coherent noise model is studied by making use of natural time, which has recently been introduced in complex time-series analysis. It is found that the aging phenomenon and the associated scaling property discovered in the observed seismic data are well reproduced by the model. It is also found that the scaling function is given by the $q$-exponential function appearing in nonextensive statistical mechanics, showing power-law decay of event correlation in natural time.Comment: 4 pages and 5 figure

How Is vaccine effectiveness scaled by the transmission dynamics of interacting pathogen strains with cross- protective immunity?

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Comparison of the Methods for the Background Reduction of Thick Targets in Routine PIXE Analysis

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Subalgebras with Converging Star Products in Deformation Quantization: An Algebraic Construction for \complex \mbox{\LARGE P}^n

Based on a closed formula for a star product of Wick type on \CP^n, which has been discovered in an earlier article of the authors, we explicitly construct a subalgebra of the formal star-algebra (with coefficients contained in the uniformly dense subspace of representative functions with respect to the canonical action of the unitary group) that consists of {\em converging} power series in the formal parameter, thereby giving an elementary algebraic proof of a convergence result already obtained by Cahen, Gutt, and Rawnsley. In this subalgebra the formal parameter can be substituted by a real number $\alpha$: the resulting associative algebras are infinite-dimensional except for the case $\alpha=1/K$, $K$ a positive integer, where they turn out to be isomorphic to the finite-dimensional algebra of linear operators in the $K$th energy eigenspace of an isotropic harmonic oscillator with $n+1$ degrees of freedom. Other examples like the $2n$-torus and the Poincar\'e disk are discussed.Comment: 16 pages, LaTeX with AMS Font

Determination of Formation Rate Constant of Carrier-Free 111In(III) with EDTA

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The Network of Epicenters of the Olami-Feder-Christensen Model of Earthquakes

We study the dynamics of the Olami-Feder-Christensen (OFC) model of earthquakes, focusing on the behavior of sequences of epicenters regarded as a growing complex network. Besides making a detailed and quantitative study of the effects of the borders (the occurrence of epicenters is dominated by a strong border effect which does not scale with system size), we examine the degree distribution and the degree correlation of the graph. We detect sharp differences between the conservative and nonconservative regimes of the model. Removing border effects, the conservative regime exhibits a Poisson-like degree statistics and is uncorrelated, while the nonconservative has a broad power-law-like distribution of degrees (if the smallest events are ignored), which reproduces the observed behavior of real earthquakes. In this regime the graph has also a unusually strong degree correlation among the vertices with higher degree, which is the result of the existence of temporary attractors for the dynamics: as the system evolves, the epicenters concentrate increasingly on fewer sites, exhibiting strong synchronization, but eventually spread again over the lattice after a series of sufficiently large earthquakes. We propose an analytical description of the dynamics of this growing network, considering a Markov process network with hidden variables, which is able to account for the mentioned properties.Comment: 9 pages, 10 figures. Smaller number of figures, and minor text corrections and modifications. For version with full resolution images see http://fig.if.usp.br/~tpeixoto/cond-mat-0602244.pd

A Gillnet Survey of Charlotte Harbor, Summer 2014

We conducted a gillnet survey from May through September 2014, at two locations in Charlotte Harbor, Florida: Long Point (LP) and Pine Island (PI). Elasmobranchs and teleosts were sampled using two different methodologies: 1) the same methodology as a previous survey conducted by Mote Marine Laboratory from 1995 to 2004 and in 2013; and 2) the methodology used in the NMFS-coordinated Gulf of Mexico Shark Pupping and Nursery (GULFSPAN) program. The goals of our study were to characterize changes in abundance and species composition of coastal sharks between the two survey periods (1995-2004 vs. 2013-2014); evaluate the potential of the fishery-independent survey to monitor trends in abundance of other fish species found in the area; compare the selectivity of the historical single panel net used by Mote with the selectivity of the multi-panel net used in GULFSPAN projects; and estimate seasonal growth patterns for juvenile blacktip sharks