Most communication networks are complex. In this paper, we address one of the fundamental problems we are facing nowadays, namely, how we can efficiently protect these networks. To this end, we study an immunization s...
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Most communication networks are complex. In this paper, we address one of the fundamental problems we are facing nowadays, namely, how we can efficiently protect these networks. To this end, we study an immunization strategy and found that it works almost as good as targeted immunization, but using only local information about the network topology. Our findings are supported with numerical simulations of the Susceptible-Infected-Removed (SIR) model on top of real communication networks, where immune nodes are previously identified by a covering algorithm. The results provide useful hints in the way to designing and deploying a digital immune system.
The dynamics of cancer evolution is studied by means of a simple quasispecies model involving cells displaying high levels of genetic instability. Both continuous, mean-field and discrete, bit-string models are analys...
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The dynamics of cancer evolution is studied by means of a simple quasispecies model involving cells displaying high levels of genetic instability. Both continuous, mean-field and discrete, bit-string models are analysed. The string model is simulated on a single-peak landscape. It is shown that a phase transition exists at high levels of genetic instability, thus separating two phases of slow and rapid growth. The results suggest that, under a conserved level of genetic instability the cancer cell population will be close to the threshold level. Implications for therapy are outlined.
Recent theoretical and empirical studies have focused on the topology of large networks of communication/interactions in biological, social and technological systems. Most of them have been studied in the scope of the...
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Recent theoretical and empirical studies have focused on the topology of large networks of communication/interactions in biological, social and technological systems. Most of them have been studied in the scope of the small-world and scale-free networks' theory. Here we analyze the characteristics of ant networks of galleries produced in a 2-D experimental setup. These networks are neither small-worlds nor scale-free networks and belong to a particular class of network, i.e. embedded planar graphs emerging from a distributed growth mechanism. We compare the networks of galleries with both minimal spanning trees and greedy triangulations. We show that the networks of galleries have a path system efficiency and robustness to disconnections closer to the one observed in triangulated networks though their cost is closer to the one of a tree. These networks may have been prevented to evolve toward the classes of small-world and scale-free networks because of the strong spatial constraints under which they grow, but they may share with many real networks a similar trend to result from a balance of constraints leading them to achieve both path system efficiency and robustness at low cost.
We present results of a numerical study of phase separation dynamics of a two-dimensional quenched system which has a small-world topology, both with and without the conserved order parameter. We examine how the domai...
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We present results of a numerical study of phase separation dynamics of a two-dimensional quenched system which has a small-world topology, both with and without the conserved order parameter. We examine how the domain coarsening changes with the density of long-range connections (shortcuts). It is demonstrated that the shortcuts have directly opposite effects, i.e., a speeding up of the coarsening process of reaching a fully uniform state, and a freezing of the system in a disordered metastable state.
Inspired by Axelrod's model of culture dissemination, we introduce and analyze a model for a population of coupled oscillators where different levels of synchronization can be assimilated to different degrees of c...
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Inspired by Axelrod's model of culture dissemination, we introduce and analyze a model for a population of coupled oscillators where different levels of synchronization can be assimilated to different degrees of cultural organization. The state of each oscillator is represented by a set of phases, and the interaction - which occurs between homologous phases - is weighted by a decreasing function of the distance between individual states. Both ordered arrays and random networks are considered. We find that the transition between synchronization and incoherent behaviour is mediated by a clustering regime with rich organizational structure, where any two oscillators can be synchronized in some of their phases, while their remain unsynchronized in the others.
The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Mini...
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The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x(1)), Final Consumption Expenditure (x(2)), Gross Capital Formation (x(3)), Net Exports (x(4)), Consumer Price Index (y(1)), Rates of Interest of the Central Banks (y(2)), Labour Force (z(1)), Unemployment (z(2)), GDP/hour worked (z(3)), GDP/capita (w(1)) and Gini coefficient (w(2)). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.
We use q-exponential distributions, which maximize the nonextensive entropy S-q (defined as S-q equivalent to (1 - Sigma(i)p(i)(q)) / (q - 1), to study the size distributions of non-coding DNA (including introns and i...
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We use q-exponential distributions, which maximize the nonextensive entropy S-q (defined as S-q equivalent to (1 - Sigma(i)p(i)(q)) / (q - 1), to study the size distributions of non-coding DNA (including introns and intergenic regions) in all human chromosomes. We show that the value of the exponent q describing the non-coding size distributions is similar for all chromosomes and varies between 2 <= q <= 2.3 with the exception of chromosomes X and Y (C) 2007 Elsevier B.V. All rights reserved.
This article investigates the functional properties of complex networks used as grid computing systems. complex networks following the Erdos-Renyi model and other models with a preferential attachment rule ( with and ...
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This article investigates the functional properties of complex networks used as grid computing systems. complex networks following the Erdos-Renyi model and other models with a preferential attachment rule ( with and without growth) or priority to the connection of isolated nodes are studied. Regular networks are also considered for comparison. The processing load of the parallel program executed on the grid is assigned to the nodes on demand, and the efficiency of the overall computation is quantified in terms of the parallel speedup. It is found that networks with preferential attachment allow lower computing efficiency than networks with uniform link attachment. At the same time, considering only node clusters of the same size, preferential attachment networks display better efficiencies. The regular networks, on the other hand, display a poor efficiency, due to their implied larger internode distances. A correlation is observed between the topological properties of the network, specially average cluster size, and their respective computing efficiency.
We present a family of scale-free network model consisting of cliques, which is established by a simple recursive algorithm. We investigate the networks both analytically and numerically. The obtained analytical solut...
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We present a family of scale-free network model consisting of cliques, which is established by a simple recursive algorithm. We investigate the networks both analytically and numerically. The obtained analytical solutions show that the networks follow a power-law degree distribution, with degree exponent continuously tuned between 2 and 3. The exact expression of clustering coefficient is also provided for the networks. Furthermore, the investigation of the average path length reveals that the networks possess small-world feature. Interestingly, we find that a special case of our model can be mapped into the Yule process.
We evaluate the probability that a Boolean network returns to an attractor after perturbing h nodes. We find that the return probability as function of h can display a variety of different behaviours, which yields ins...
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We evaluate the probability that a Boolean network returns to an attractor after perturbing h nodes. We find that the return probability as function of h can display a variety of different behaviours, which yields insights into the state-space structure. In addition to performing computer simulations, we derive analytical results for several types of Boolean networks, in particular for Random Boolean Networks. We also apply our method to networks that have been evolved for robustness to small perturbations, and to a biological example.
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