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Different models of capital exchange among economic agents have been proposed recently trying to explain the emergence of Pareto's wealth power law distribution. One important factor to be considered is the existence of risk aversion. In this paper we study a model where agents posses different levels of risk aversion, going from uniform to a random distribution. In all cases the risk aversion level for a given agent is constant during the simulation. While for a uniform and constant risk aversion the system self-organizes in a distribution that goes from an unfair "one takes all" distribution to a Gaussian one, a random risk aversion can produce distributions going from exponential to log-normal and power-law. Besides, interesting correlations between wealth and risk aversion are found. (J. R. Iglesias). 1 J.R.I. acknowledges support from CNPq (Brazil) and the hospitality and support and G.A. thanks the hospitality of the Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil. We acknowledge partial support from SETCYP (Argentina) and CAPES (Brazil) through the Argentine-Brazilian Cooperation Agreement BR 18/00.

When the full stock of a new product is quickly sold in a few days or weeks, one has the impression that new technologies develop and conquer the market in a very easy way. This may be true for some new technologies, for example the cell phone, but not for others, like the blue-ray. Novelty, usefulness, advertising, price, and fashion are the driving forces behind the adoption of a new product. But, what are the key factors that lead to adopt a new technology? In this paper we propose and investigate a simple model for the adoption of an innovation which depends mainly on three elements: the appeal of the novelty, the inertia or resistance to adopt it, and the interaction with other agents. Social interactions are taken into account in two ways: by imitation and by differentiation, i.e., some agents will be inclined to adopt an innovation if many people do the same, but other will act in the opposite direction, trying to differentiate from the "herd". We determine the conditions for a successful implantation of the new technology, by considering the strength of advertising and the effect of social interactions. We find a balance between the advertising and the number of anti-herding agents that may block the adoption of a new product. We also compare the effect of social interactions, when agents take into account the behavior of the whole society or just a part of it. In a nutshell, the present model reproduces qualitatively the available data on adoption of innovation.PACS. 8 9.65. Ef, 89.75.Fb, 89.65.Gh

Molecular dynamics simulations of a Xe monolayer sliding on Ag(001) and Ag(111) are carried out in order to ascertain the microscopic origin of friction. For several values of the electronic contribution to the friction of individual Xe atoms, the intra-overlayer phonon dissipation is calculated as a function of the corrugation amplitude of the substrate potential, which is a pertinent parameter to consider. Within the accuracy of the numerical results and the uncertainty with which the values of the relevant parameters are known at present, we conclude that electronic and phononic dissipation channels are of similar importance. While phonon friction gives rise to the rapid variation with coverage, the electronic friction provides a roughly coverage-independent contribution to the overall sliding friction.

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Thermal growth of silicon oxide films on Si in dry O 2 is modeled as a dynamical system, assuming that it is basically a reaction-diffusion phenomenon. Relevant findings of the last decade are incorporated, as structure and composition of the oxide/Si interface and O 2 transport and reaction at initial stages of growth. The present model departs from the well-established Deal and Grove framework ͓B. E. Deal and A. S. Grove, J. Appl. Phys. 36, 3770 ͑1965͔͒ indicating that its basic assumptions, steady-state regime, and reaction between O 2 and Si at a sharp oxide/Si interface are only attained asymptotically. Scaling properties of these model equations are explored, and experimental growth kinetics, obtained for a wide range of growth parameters including the small thickness range, are shown to be well described by the model.

Simple agent based exchange models are a commonplace in the study of wealth distribution of artificial societies. Generally, each agent is characterized by its wealth and by a risk-aversion factor, and random exchanges between agents allow for a redistribution of the wealth. However, the detailed influence of the amount of capital exchanged has not been fully analyzed yet. Here we present a comparison of two exchange rules and also a systematic study of the time evolution of the wealth distribution, its functional dependence, the Gini coefficient and time correlation functions. In many cases a stable state is attained, but, interesting, some particular cases are found in which a very slow dynamics develops. Finally, we observe that the time evolution and the final wealth distribution are strongly dependent on the exchange rules in a nontrivial way.PACS numbers:

Law enforcement and intelligence agencies worldwide struggle to find effective ways to fight organized crime and reduce criminality. However, illegal networks operate outside the law and much of the data collected is classified. Therefore, little is known about the structure, topological weaknesses, and control of criminal networks. We fill this gap by presenting a unique criminal intelligence network built directly by the Brazilian Federal Police for intelligence and investigative purposes. We study its structure, its response to different attack strategies, and its structural controllability. Surprisingly, the network composed of individuals involved in multiple crimes of federal jurisdiction in Brazil has a giant component enclosing more than half of all its edges. We focus on the largest connected cluster of this network and show it has many social network features, such as small-worldness and heavy-tail degree distribution. However, it is less dense and less efficient than typical social networks. The giant component also shows a high degree cutoff that is associated with the lack of trust among individuals belonging to clandestine networks. The giant component of the network is also highly modular (Q=0.96) and thence fragile to module-based attacks. The targets in such attacks, i.e. the nodes connecting distinct communities, may be interpreted as individuals with bridging clandestine activities such as accountants, lawyers, or money changers. The network can be disrupted by the removal of approximately 2% of either its nodes or edges, the negligible difference between both approaches being due to low graph density. Finally, we show that 20% of driver nodes can control dynamic variables acting on the whole network, suggesting that non-repressive strategies such as access to basic education or sanitation can be effective in reducing criminality by changing the perception of driver individuals to norm compliance.Electronic supplementary materialThe online version of this article (10.1007/s41109-018-0092-1) contains supplementary material, which is available to authorized users.