Another phase transition in the Axelrod model

Axelrod's model of cultural dissemination, despite its apparent simplicity, demonstrates complex behavior that has been of much interest in statistical physics. Despite the many variations and extensions of the model that have been investigated, a systematic investigation of the effects of changing the size of the neighborhood on the lattice in which interactions can occur has not been made. Here we investigate the effect of varying the radius R of the von Neumann neighborhood in which agents can interact. We show, in addition to the well-known phase transition at the critical value of q, the number of traits, another phase transition at a critical value of R, and draw a q - R phase diagram for the Axelrod model on a square lattice. In addition, we present a mean-field approximation of the model in which behavior on an infinite lattice can be analyzed

Tableau-based protein substructure search using quadratic programming

<p>Abstract</p> <p>Background</p> <p>Searching for proteins that contain similar substructures is an important task in structural biology. The exact solution of most formulations of this problem, including a recently published method based on tableaux, is too slow for practical use in scanning a large database.</p> <p>Results</p> <p>We developed an improved method for detecting substructural similarities in proteins using tableaux. Tableaux are compared efficiently by solving the quadratic program (QP) corresponding to the quadratic integer program (QIP) formulation of the extraction of maximally-similar tableaux. We compare the accuracy of the method in classifying protein folds with some existing techniques.</p> <p>Conclusion</p> <p>We find that including constraints based on the separation of secondary structure elements increases the accuracy of protein structure search using maximally-similar subtableau extraction, to a level where it has comparable or superior accuracy to existing techniques. We demonstrate that our implementation is able to search a structural database in a matter of hours on a standard PC.</p

Exponential random graph model parameter estimation for very large directed networks

Exponential random graph models (ERGMs) are widely used for modeling social networks observed at one point in time. However the computational difficulty of ERGM parameter estimation has limited the practical application of this class of models to relatively small networks, up to a few thousand nodes at most, with usually only a few hundred nodes or fewer. In the case of undirected networks, snowball sampling can be used to find ERGM parameter estimates of larger networks via network samples, and recently published improvements in ERGM network distribution sampling and ERGM estimation algorithms have allowed ERGM parameter estimates of undirected networks with over one hundred thousand nodes to be made. However the implementations of these algorithms to date have been limited in their scalability, and also restricted to undirected networks. Here we describe an implementation of the recently published Equilibrium Expectation (EE) algorithm for ERGM parameter estimation of large directed networks. We test it on some simulated networks, and demonstrate its application to an online social network with over 1.6 million nodes.Comment: Minor correction of discussion of coverage and Type II error rat

A Man’s world? Comparing the structural positions of men and women in an organized criminal network

The crime gender gap is the difference between the levels of participation of men and women in crime, with men responsible for more crime than women. Recent evidence suggests that the crime gender gap is closing, both in crime in general and in organized crime. However, organized crime differs from other forms of criminal activity in that it entails an organizational structure of cooperation among offenders. Assessing whether the gender gap in organized crime is narrowing is not only about the overall levels of involvement of women, but about their roles and positions within the organized criminal structure, because the involvement of women does not mean that they are in influential positions, or that they have power or access to resources important for the commission of organized crime. This paper uses a social network approach to systematically compare the structural positions of men and women in an organized criminal network. We use a dataset collected by Canadian Law Enforcement consisting of 1390 individuals known or suspected to be involved in organized crime, 185 of whom are women. Our analysis provides evidence for an ongoing gender gap in organized crime, with women occupying structural positions that are generally associated with a lack of power. Overall, women are less present in the network, tend to collaborate with other women rather than with men, and are more often in the disadvantageous position of being connected by male intermediaries. Implications for theory and law enforcement practice are discussed