Advances in Complex Systems

Computer simulations of complex food-webs are important tools for deepening our understanding of these systems. Yet most computer models assume, rather than generate, key system-level patterns, or use mathematical modeling approaches that make it difficult to fully account for nonlinear dynamics. In this paper, we present a computer simulation model that addresses these concerns by focusing on assumptions of agent attributes rather than agent outcomes. Our model utilizes the techniques of complex adaptive systems and agent-based modeling so that system level patterns of a marine ecosystem emerge from the interactions of thousands of individual computer agents. This methodology is validated by using this general simulation model to replicate fundamental properties of a marine ecosystem, including: (i) the predator–prey oscillations found in Lotka–Volterra; (ii) the stepped pattern of biomass accrual from resource enrichment; (iii) the Paradox of Enrichment; and (iv) Gause's Law.

This paper describes the applications of network methods for understanding interaction within members of sport teams. We analyze the interaction of batsmen in international cricket matches. We generate batting partnership network (BPN) for different teams and determine the exact values of clustering coefficient, average degree, average shortest path length of the networks and compare them with the Erdös–Rényi model. We observe that the networks display small-world behavior. We find that most connected batsman is not necessarily the most central and most central players are not necessarily the one with high batting averages. We study the community structure of the BPNs and identify each player's role based on inter-community and intra-community links. We observe that Sir DG Bradman, regarded as the best batsman in cricket history does not occupy the central position in the network — the so-called connector hub. We extend our analysis to quantify the performance, relative importance and effect of removing a player from the team, based on different centrality scores.

Microtubules (MTs) are cytoskeletal protein polymers orchestrating a host of important cellular functions including, but not limited to, cell support, cell division, cell motility and cell transport. We construct a toy-model of the MT lattice composed of classical vector Ising spins (dipole moments) representing the tubulin molecules, the building block of MTs. Nearest-neighbor (NN) and next-nearest-neighbor (NNN) interactions are considered within an anisotropic dielectric medium. As a consequence of the helical topology, certain spin orientations render the lattice frustrated with NN ferroelectric and NNN antiferroelectric bonds. Mapping the problem to a 2D Ising model and employing Monte Carlo methods we find that frozen clusters of spins exist at human physiological temperatures. This suggests a novel biological mechanism for storing information in living organisms, whereby the classical tubulin spin states become information bits and information gets stored in MTs in a way that is robust to thermal fluctuations.

Different from previous studies of tag-based cooperation, we assume that individuals fail to recognize their own tag. Due to such incomplete information, the action taken against the opponent cannot be based on similarity, although it is still motivated by the tag displayed by the opponent. We present stability conditions for the case when individuals play unconditional cooperation, unconditional defection or conditional cooperation. We then consider the removal of one or two strategies. Results show that conditional cooperators are the most resilient agents against extinction and that the removal of unconditional cooperators may lead to the extinction of unconditional defectors.

Measuring culture and its dynamics through surveys has important limitations, but the emerging field of computational social science allows us to overcome them by analyzing large-scale datasets. In this paper, we study cultural dynamics through the votes in the Eurovision song contest, which are decided by a crowd-based scheme in which viewers vote through mobile phone messages. Taking into account asymmetries and imperfect perception of culture, we measure cultural relations among European countries in terms of cultural affinity. We propose the Friend-or-Foe coefficient, a metric to measure voting biases among participants of a Eurovision contest. We validate how this metric represents cultural affinity through its relation with known cultural distances, and through numerical analysis of biased Eurovision contests. We apply this metric to the historical set of Eurovision contests from 1975 to 2012, finding new patterns of stronger modularity than using votes alone. Furthermore, we define a measure of polarization that, when applied to empirical data, shows a sharp increase within EU countries during 2010 and 2011. We empirically validate the relation between this polarization and economic indicators in the EU, showing how political decisions influence both the economy and the way citizens relate to the culture of other EU members.