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Fumia H.F.,Federal University of Viçosa | 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.


Anteneodo C.,RIO SYSTEMS
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

We analyze the impact of the sampling interval on the estimation of Kramers-Moyal coefficients. We obtain the finite-time expressions of these coefficients for several standard processes. We also analyze extreme situations such as the independence and no-fluctuation limits that constitute useful references. Our results aim at aiding the proper extraction of information in data-driven analysis. © 2010 The American Physical Society.


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.


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.


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.


Random number generators are a core component of heuristic search algorithms. They are used to build candidate solutions and reduce bias while transforming these solutions during the search. Despite their usefulness, random numbers also have drawbacks, as one cannot guarantee that all portions of the search space are covered by the search and must run an algorithm many times to statistically assess its behavior. Determine whether deterministic quasi-random sequences can be used as an alternative to pseudo-random numbers in feeding "randomness" into Hill Climbing searches addressing Software Engineering problems. We have designed and executed three experimental studies in which a Hill Climbing search was used to find solutions for two Software Engineering problems: software module clustering and requirement selection. The algorithm was executed using both pseudo-random numbers and three distinct quasi-random sequences (Faure, Halton, and Sobol). The software clustering problem was evaluated for 32 real-world instances and the requirement selection problem was addressed using 15 instances reused from previous research works. The experimental studies were chained to allow varying as few as possible experimental factors between any given study and its subsequent one. Results found by searches powered by distinct quasi-random sequences were compared to those produced by the pseudo-random search on a per instance basis. The comparison evaluated search efficiency (processing time required to run the search) and effectiveness (quality of results produced by the search). Contrary to previous findings observed in the context of other heuristic search algorithms, we found evidence that quasi-random sequences cannot outperform pseudo-random numbers regularly in Hill Climbing searches. Detailed statistical analysis is provided to support the evidence favoring pseudo-random numbers. © 2014 Springer Science+Business Media New York.


Disclosed are methods, circuits and systems for generating satellite navigation beacon signals. There is provided a multi-system beacon transmitter adapted to generate a beacon signal for navigation systems. The multi-system beacon transmitter may include: (1) a baseband data processor adapted to process a navigation data based data signal in baseband; (2) an adjustable radio-frequency (RF) transmission module adapted to process and up-convert the baseband data signal, and further adapted to transmit the RF signal via one or more functionally associated antenna(s); and (3) a multi-system interfacing module adapted to convey the navigation signal and to control the RF transmission module based on a determined RF transmission mode. The determined RF transmission mode may be selected from a set of navigation system transmission modes. The need for external frequency selectable elements (e.g. filters) may be obviated.


Disclosed are methods, circuits and systems for regulating the output power of a transmission system. There may be provided a power amplifier (PA) adapted to operate across a range of supply voltages. The PA may operate under different bias profiles. There may be provided power amplifier regulation circuitry which may include a PA bias profile generator adapted to generate one or more bias profiles, wherein a given bias profile is associated with a given bias signal for the PA. A bias profile associated with a given bias signal for a given PA may include one or more PA parameters or settings to be applied to the given PA when it is operating with the given bias signal.


Disclosed are methods, circuits and systems for modulating supply voltage to a power amplifier. An input voltage signal may be received and used to drive a switching regulator (or the like), which regulator may be adapted to modulate (convert) battery supply voltage into a supply voltage of an amplifier. An output signal combining stage may include a signal combiner which may be adapted to combine a modulated battery supply voltage (i.e. modulated by the input voltage) with a residual error correction signal (RECS). The residual error correction signal may be based on an estimate of the switching regulator characteristics. The estimate may be at least partially based on feedback from an output of the regulator. The estimate may be at least partially based on a prediction model of the switch regulator.


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