Abstract:
we review important issues revealed by the application of the evolutionary theory to epidemiological problems. the scope is restricted to infectious diseases and the evolution of virulence as a consequence of public health strategies to control transmission. we focus on the discussion about the possibility of virulence management and explore current scenarios in which recent advances in molecular biology and genetics offer new tools to monitor and change diversity among pathogens, vertebrate and invertebrate hosts. we stress the need to integrate the analytical framework of epidemiology into population genetics and evolutionary theory. we anticipate as an outcome of this process the development of study designs and analytical tools to predict the evolutionary implications of control measures in the population and surveillance mechanisms to continuously monitor the changes in pathogen virulence patterns. communication among modelers, epidemiologists and molecular biologists is essential in order to design model-driven field trials and to develop data-driven analytical tools leading to conclusive findings that can inform the public health oriented decision making process.

Abstract:
We present a detailed discussion of the role played by memory, and the nature of self-induced shocks, in an evolutionary population competing for limited resources. Our study builds on a previously introduced multi-agent system [Phys. Rev. Lett 82, 3360 (1999)] which has attracted significant attention in the literature. This system exhibits self-segregation of the population based on the `gene' value p (where 0<=p<=1), transitions to `frozen' populations as a function of the global resource level, and self-induced large changes which spontaneously arise as the dynamical system evolves. We find that the large, macroscopic self-induced shocks which arise, are controlled by microscopic changes within extreme subgroups of the population (i.e. subgroups with `gene' values p~0 and p~1).

Abstract:
The competition graph of a digraph $D$ is a (simple undirected) graph which has the same vertex set as $D$ and has an edge between two distinct vertices $x$ and $y$ if and only if there exists a vertex $v$ in $D$ such that $(x,v)$ and $(y,v)$ are arcs of $D$. For any graph $G$, $G$ together with sufficiently many isolated vertices is the competition graph of some acyclic digraph. The competition number $k(G)$ of a graph $G$ is the smallest number of such isolated vertices. Computing the competition number of a graph is an NP-hard problem in general and has been one of the important research problems in the study of competition graphs. Opsut [1982] showed that the competition number of a graph $G$ is related to the edge clique cover number $\theta_E(G)$ of the graph $G$ via $\theta_E(G)-|V(G)|+2 \leq k(G) \leq \theta_E(G)$. We first show that for any positive integer $m$ satisfying $2 \leq m \leq |V(G)|$, there exists a graph $G$ with $k(G)=\theta_E(G)-|V(G)|+m$ and characterize a graph $G$ satisfying $k(G)=\theta_E(G)$. We then focus on what we call \emph{competitively tight graphs} $G$ which satisfy the lower bound, i.e., $k(G)=\theta_E(G)-|V(G)|+2$. We completely characterize the competitively tight graphs having at most two triangles. In addition, we provide a new upper bound for the competition number of a graph from which we derive a sufficient condition and a necessary condition for a graph to be competitively tight.

Abstract:
We present a study of the evolutionary stage of the interacting binary and Double Periodic Variable AU Monocerotis. A multi-parametric Chi2 minimization is made between the observed parameters and those predicted by the grid of non-conservative and conservative evolutionary models by Van Rensbergen et al., finding the model that best represents the current stellar and system parameters. According to this model, the system started with initial masses 4 M_sun and 3.6 M_sun and orbital period 3.0 days, 196 million years ago, and at present undergoes a Case-B mass-exchange episode. This evolutionary stage is consistent with the reported existence of a circumprimary accretion disk. However, the implied high mass transfer rate contrasts with the absence of significant orbital period change if the mass exchange is conservative. We show that this can occur if the system has recently entered in a non-conservative stage of mass transfer and the efficiency of mass and angular momentum loss satisfy certain conditions.

Abstract:
We wish to minimize the resources used for network coding while achieving the desired throughput in a multicast scenario. We employ evolutionary approaches, based on a genetic algorithm, that avoid the computational complexity that makes the problem NP-hard. Our experiments show great improvements over the sub-optimal solutions of prior methods. Our new algorithms improve over our previously proposed algorithm in three ways. First, whereas the previous algorithm can be applied only to acyclic networks, our new method works also with networks with cycles. Second, we enrich the set of components used in the genetic algorithm, which improves the performance. Third, we develop a novel distributed framework. Combining distributed random network coding with our distributed optimization yields a network coding protocol where the resources used for coding are optimized in the setup phase by running our evolutionary algorithm at each node of the network. We demonstrate the effectiveness of our approach by carrying out simulations on a number of different sets of network topologies.

Abstract:
The stabilization of host–symbiont mutualism against the emergence of parasitic individuals is pivotal to the evolution of cooperation. One of the most famous symbioses occurs between legumes and their colonizing rhizobia, in which rhizobia extract nutrients (or benefits) from legume plants while supplying them with nitrogen resources produced by nitrogen fixation (or costs). Natural environments, however, are widely populated by ineffective rhizobia that extract benefits without paying costs and thus proliferate more efficiently than nitrogen-fixing cooperators. How and why this mutualism becomes stabilized and evolutionarily persists has been extensively discussed. To better understand the evolutionary dynamics of this symbiosis system, we construct a simple model based on the continuous snowdrift game with multiple interacting players. We investigate the model using adaptive dynamics and numerical simulations. We find that symbiotic evolution depends on the cost–benefit balance, and that cheaters widely emerge when the cost and benefit are similar in strength. In this scenario, the persistence of the symbiotic system is compatible with the presence of cheaters. This result suggests that the symbiotic relationship is robust to the emergence of cheaters, and may explain the prevalence of cheating rhizobia in nature. In addition, various stabilizing mechanisms, such as partner fidelity feedback, partner choice, and host sanction, can reinforce the symbiotic relationship by affecting the fitness of symbionts in various ways. This result suggests that the symbiotic relationship is cooperatively stabilized by various mechanisms. In addition, mixed nodule populations are thought to encourage cheater emergence, but our model predicts that, in certain situations, cheaters can disappear from such populations. These findings provide a theoretical basis of the evolutionary dynamics of legume–rhizobia symbioses, which is extendable to other single-host, multiple-colonizer systems.

Abstract:
We demonstrate how a genetic algorithm solves the problem of minimizing the resources used for network coding, subject to a throughput constraint, in a multicast scenario. A genetic algorithm avoids the computational complexity that makes the problem NP-hard and, for our experiments, greatly improves on sub-optimal solutions of established methods. We compare two different genotype encodings, which tradeoff search space size with fitness landscape, as well as the associated genetic operators. Our finding favors a smaller encoding despite its fewer intermediate solutions and demonstrates the impact of the modularity enforced by genetic operators on the performance of the algorithm.

Abstract:
We have studied the appearance of chaos in the many-body spectrum of interacting Fermions. The coupling of a single state to the Fermi sea is considered. This state is coupled to a hierarchy of states corresponding to one or several particle-hole excitations. We have considered various couplings between two successive generations of this hierarchy and determined under which conditions this coupling can lead to Wigner-Dyson correlations. We have found that the cross-over from a Poisson to a Wigner distribution is characterized not only by the ratio $V/\Delta_c$, but also by the ratio $\Delta_c/\delta$. $V$ is the typical interaction matrix element, $\delta$ is the energy distance between {\it many-body} states and $\Delta_c$ is the distance between many-body states coupled by the interaction.

Abstract:
The optical absorption of a many (continuum) polaron gas is derived in the framework of a variational approach at zero temperature and weak or intermediate electron-phonon coupling strength. We derive a compact formula for the optical conductivity of the many-polaron system taking into account many-body effects in the electron or hole system. Within the method presented here, these effects are contained completely in the dynamical structure factor of the electron or hole system. This allows to build on well-established studies of the interacting electron gas. Based on this approach a novel feature in the absorption spectrum of the many-polaron gas, related to the emission of a plasmon together with a phonon, is identified. As an application and illustration of the technique, we compare the theoretical many-polaron optical absorption spectrum as derived in the present work with the `d-band' absorption feature in Nd$_{2}$CuO$_{2}$. Similarities are shown between the theoretically and the experimentally derived first frequency moment of the optical absorption of a family of differently doped Nd$_{2-x}$Ce$_{x}$CuO$_{4-y}$ materials.

Abstract:
We present an agent-based model inspired by the Evolutionary Minority Game (EMG), albeit strongly adapted to the case of competition for limited resources in ecology. The agents in this game become able, after some time, to predict the a priori best option as a result of an evolution-driven learning process. We show that a self-segregated social structure can emerge from this process, i.e., extreme learning strategies are always favoured while intermediate learning strategies tend to die out. This result may contribute to understanding some levels of organization and cooperative behaviour in ecological and social systems. We use the ideas and results reported here to discuss an issue of current interest in ecology: the mistimings in egg laying observed for some species of bird as a consequence of their slower rate of adaptation to climate change in comparison with that shown by their prey. Our model supports the hypothesis that habitat-specific constraints could explain why different populations are adapting differently to this situation, in agreement with recent experiments.