International Journal of Modern Physics C

In this paper, we study the dynamics of a multi-connected network which has been used recently to simulate the evolution of the immune repertoire. In particular, we used this model to reproduce experimental results about immunization and aging performed with mice. Here, we investigate the main features which are responsible for those effects by obtaining the cluster size and the activation time distributions. We observe a power law behavior for the activation time distribution below and at the critical region whereas the cluster size distribution exhibits a characteristic length scale in the biologically relevant region of the parameter space. Only at the transition, we obtain a power law behavior for this distribution. The characteristic cluster size is responsible for the loss of plasticity during the time evolution of the system, leading to aging effects, while the absence of a characteristic time scale in the activation time is associated with memory effects.

Although NP-Complete problems are the most difficult decisional problems, it is possible to discover in them polynomial (or easy) observables. We study the Graph Partitioning Problem showing that it is possible to recognize in it two correlated polynomial observables. The particular behavior of one of them with respect to the connectivity of the graph suggests the presence of a phase transition in partitionability.

Synchronization is introduced into a chaotic neural network model to discuss its associative memory. The relative time of synchronization of trajectories is used as a measure of pattern recognition by chaotic neural networks. The retrievability of memory is shown to be connected to synapses, initial conditions and storage capacity. The technique is simple and easy to apply to neural systems.

This study presents a stepsize control method for the numerical integration of ordinary differential equations. The method is based on the difference between a Verlet coordinates evaluation and an Adams–Bashforth coordinates predictor and can be easily implemented in existing Molecular Dynamics simulations. Numerical tests are made on the equilibrium configuration of crystalline silicon at low temperature.

The Sznajd model for the spread of opinions is applied to the incipient infinite percolation cluster on the square lattice, with and without power-law correlations for the occupied sites. We trace the phase transition between the two fixed points of all spins up and all spins down.

It is a common belief that the behavior of shareholders depends upon the direction of price fluctuations: if prices increase they buy, if prices decrease they sell. That belief, however, is more based on "common sense" than on facts. In this paper, we present evidence for a specific class of shareholders which shows that the actual behavior of shareholders can be markedly different. For instance, they may continue to buy despite a prolonged fall in prices or they may sell even though prices climb. A closer analysis shows that a substantial proportion of investors are more influenced by the "general social climate" than by actual price changes. The percentage of speculative investors who optimize their portfolio on a monthly basis can be estimated and turns out to be about 5 to 10%. The results presented in this paper can be of usefulness in order to test the assumptions or the results of market simulations and models.

We have developed a method for the detection of clusters of microcalcifications in digital mammograms. Here, we present a genetic algorithm used to optimize the choice of the parameters in the detection scheme. The optimization has allowed the improvement of the performance, the detailed study of the influence of the various parameters on the performance and an accurate investigation of the behavior of the detection method on unknown cases. We reach a sensitivity of 96.2% with 0.7 false positive clusters per image on the Nijmegen database; we are also able to identify the most significant parameters. In addition, we have examined the feasibility of a distributed genetic algorithm implemented on a non-dedicated Cluster Of Workstations. We get very good results both in terms of quality and efficiency.

The scaling properties of interfaces generated by a disaggregation model in 1+1 dimensions are studied by numerical simulations. The model presented here for the disaggregation process takes into account the possibility of having quenched disorder in the bulk under deconstruction. The disorder can be considered to model several types of irregularities appearing in real materials (dislocations, impurities). The presence of irregularities makes the intensity of the attack to be not uniform. In order to include this effect, the computational bulk is considered to be composed by two types of particles: those particles which can be easily detached and other particles that are not sensible to the etching attack. As the detachment of particles proceeds in time, the dynamical properties of the rough interface are studied. The resulting one-dimensional surface show self-affine properties and the values of the scaling exponents are reported when the interface is still moving near the depinning transition. According to the scaling exponents presented here, the model must be considered to belong to a new universality class.

Here, we review the classical Hamming associative memory and we discuss a cellular implementation. We show how the patterns to be stored can be superimposed or enfolded onto a single memory element with exponential storage capacity and how these memory elements can be organized in a cellular network architecture suitable for pattern association.

In the mesoscale, mixing dynamics involving immiscible fluids is truly an outstanding problem in many fields, ranging from biology to geology, because of the multiscale nature which causes severe difficulties for conventional methods using partial differential equations. The existing macroscopic models incorporating the two microstructural mechanisms of breakup and coalescence do not have the necessary physical ingredients for feedback dynamics. We demonstrate here that the approach of dissipative particle dynamics (DPD) does include the feedback mechanism and thus can yield much deeper insight into the nature of immiscible mixing. We have employed the DPD method for simulating numerically the highly nonlinear aspects of the Rayleigh–Taylor (R–T) instability developed over the mesoscale for viscous, immiscible, elastically compressible fluids. In the initial stages, we encounter the spontaneous, vertical oscillations in the incipient period of mixing. The long-term dynamics are controlled by the initial breakup and the subsequent coalescence of the microstructures and the termination of the chaotic stage in the development of the R–T instability. In the regime with high capillary number, breakup plays a dominant role in the mixing whereas in the low capillary number regime, the flow decelerates and coalescence takes over and causes a more rapid turnover. The speed of mixing and the turnover depend on the immiscibility factor which results from microscopic interactions between the binary fluid components. Both the speed of mixing and the overturn dynamics depend not only on the mascrocopic fluid properties but also on the breakup and coalescent patterns, and most importantly on the nonlinear interactions between the microstructural dynamics and the large-scale flow.

We generalize our previously given calculational procedure based on orthogonal polynomial expansions for curve fitting applicable to data with errors only in the dependent variable to the case when both independent and dependent variables have errors. We apply this procedure to an effect of water physics, namely water aeration, with importance also to environmental and biological issues.

The settling dynamics of spherical and elliptical particles in a viscous Newtonian fluid are investigated numerically using a finite difference technique. The terminal velocity for spherical particles is calculated for different system sizes and the extrapolated value for an infinite system size is compared to the Oseen approximation. Special attention is given to the settling and tumbling motion of elliptical particles where their terminal velocity is compared with the one of the surface equivalent spherical particle.