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Barros M.D.O.,RIO SYSTEMS
GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation | Year: 2012

The application of multiobjective optimization to address Software Engineering problems is a growing trend. Multiobjective algorithms provide a balance between the ability of the computer to search a large solution space for valuable solutions and the capacity of the human decision-maker to select an alternative when two or more incomparable objectives are presented. However, when more than a single objective is available, the set of objectives to be considered by the search becomes part of the decision. In this paper, we address the efficiency and effectiveness of using two composite objectives while searching solutions for the software clustering problem. We designed an experimental study which shows that a multiobjective genetic algorithm can find a set of solutions with increased quality and using less processing time if these composite objectives are suppressed from the formulation for the software clustering problem. © 2012 ACM. Source


Fumia H.F.,Federal University of Vicosa | Martins M.L.,RIO SYSTEMS
PLoS ONE | Year: 2013

A Boolean dynamical system integrating the main signaling pathways involved in cancer is constructed based on the currently known protein-protein interaction network. This system exhibits stationary protein activation patterns - attractors - dependent on the cell's microenvironment. These dynamical attractors were determined through simulations and their stabilities against mutations were tested. In a higher hierarchical level, it was possible to group the network attractors into distinct cell phenotypes and determine driver mutations that promote phenotypic transitions. We find that driver nodes are not necessarily central in the network topology, but at least they are direct regulators of central components towards which converge or through which crosstalk distinct cancer signaling pathways. The predicted drivers are in agreement with those pointed out by diverse census of cancer genes recently performed for several human cancers. Furthermore, our results demonstrate that cell phenotypes can evolve towards full malignancy through distinct sequences of accumulated mutations. In particular, the network model supports routes of carcinogenesis known for some tumor types. Finally, the Boolean network model is employed to evaluate the outcome of molecularly targeted cancer therapies. The major find is that monotherapies were additive in their effects and that the association of targeted drugs is necessary for cancer eradication. © 2013 Fumiã, Martins. Source


Crokidakis N.,Pontifical Catholic University of Rio de Janeiro | Anteneodo C.,Pontifical Catholic University of Rio de Janeiro | Anteneodo C.,RIO SYSTEMS
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2012

We analyze the critical behavior of a class of discrete opinion models in the presence of disorder. Within this class, each agent opinion takes a discrete value (±1 or 0) and its time evolution is ruled by two terms, one representing agent-agent interactions and the other the degree of conviction or persuasion (a self-interaction). The mean-field limit, where each agent can interact evenly with any other, is considered. Disorder is introduced in the strength of both interactions, with either quenched or annealed random variables. With probability p (1-p), a pairwise interaction reflects a negative (positive) coupling, while the degree of conviction also follows a binary probability distribution (two different discrete probability distributions are considered). Numerical simulations show that a nonequilibrium continuous phase transition, from a disordered state to a state with a prevailing opinion, occurs at a critical point pc that depends on the distribution of the convictions, with the transition being spoiled in some cases. We also show how the critical line, for each model, is affected by the update scheme (either parallel or sequential) as well as by the kind of disorder (either quenched or annealed). © 2012 American Physical Society. Source


Vallejos R.O.,Brazilian Center for Research in Physics (CBPF) | Anteneodo C.,RIO SYSTEMS
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2012

The cumulant expansion is used to estimate generalized Lyapunov exponents of the random-frequency harmonic oscillator. Three stochastic processes are considered: Gaussian white noise, Ornstein-Uhlenbeck, and Poisson shot noise. In some cases, nontrivial numerical difficulties arise. These are mostly solved by implementing an appropriate importance-sampling Monte Carlo scheme. We analyze the relation between random-frequency oscillators and many-particle systems with pairwise interactions like the Lennard-Jones gas. © 2012 American Physical Society. Source


Morgado W.A.M.,RIO SYSTEMS | Duarte Queiros S.M.,Brazilian Center for Research in Physics (CBPF)
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2014

We discuss the statistical properties of small mechanothermodynamic systems (one- and two-particle cases) subject to nonlinear coupling and in contact with standard Gaussian reservoirs. We use a method that applies averages in the Laplace-Fourier space, which relates to a generalization of the final-value theorem. The key advantage of this method lies in the possibility of eschewing the explicit computation of the propagator, traditionally required in alternative methods like path integral calculations, which is hardly obtainable in the majority of the cases. For one-particle equilibrium systems we are able to compute the instantaneous (equilibrium) probability density functions of injected and dissipated power as well as the respective large deviation functions. Our thorough calculations explicitly show that for such models nonlinearities are irrelevant in the long-term statistics, which preserve the exact same values as computed for linear cases. Actually, we verify that the thermostatistical effect of the nonlinearities is constricted to the transient towards equilibrium, since it affects the average total energy of the system. For the two-particle system we consider each element in contact with a heat reservoir, at different temperatures, and focus on the problem of heat flux between them. Contrarily to the one-particle case, in this steady state nonequilibrium model we prove that the heat flux probability density function reflects the existence of nonlinearities in the system. An important consequence of that it is the temperature dependence of the conductance, which is unobserved in linear(harmonic) models. Our results are complemented by fluctuation relations for the injected power (equilibrium case) and heat flux (nonequilibrium case). © 2014 American Physical Society. Source

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