Mesoscopic structure conditions the emergence of cooperation on social networks

We study the evolutionary Prisoner's Dilemma on two social networks obtained from actual relational data. We find very different cooperation levels on each of them that can not be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding perfect agreement with the observations in the real networks. Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.Comment: Largely improved version, includes an artificial network model that fully confirms the explanation of the results in terms of inter- and intra-community structur

Damage Detection and Localization on Real Structures Subjected to Strong Motion Earthquakes Using the Curvature Evolution Method: The Navelli (Italy) Case Study

In recent years, structural health monitoring (SHM) has received increasing interest from both research and professional engineering communities. This is due to the limitations related to the use of traditional methods based on visual inspection for a rapid and effective assessment of structures and infrastructures when compared with the great potential offered by newly developed automatic systems. Most of these kinds of systems allow the continuous estimation of structural modal properties that are strictly correlated to the mechanical characteristics of the monitored structure. These can change as a result of material deterioration and structural damage related to earthquake shaking. Furthermore, a suitable configuration of a dense sensor network in a real-time monitoring system can allow to detect and localize structural and non-structural damage by comparing the initial and a final state of the structure after a critical event, such as a relevant earthquake. In this paper, the modal curvature evaluation method, used for damage detection and localization on framed structures, considering the mode curvature variation due to strong earthquake shaking, is further developed. The modified approach is validated by numerical and experimental case studies. The extended procedure, named "Curvature Evolution Method" (CEM), reduces the required computing time and the uncertainties in the results. Furthermore, in this work, an empirical relationship between curvature variation and damage index has been defined for both bare and infilled frames

Rapid identification of mutations in GJC2 in primary lymphoedema using whole exome sequencing combined with linkage analysis with delineation of the phenotype.

Background: Primary lymphoedema describes a chronic, frequently progressive, failure of lymphatic drainage. This disorder is frequently genetic in origin, and a multigenerational family in which eight individuals developed postnatal lymphoedema of all four limbs was ascertained from the joint Lymphoedema/Genetic clinic at St George's Hospital. Methods: Linkage analysis was used to determine a locus, and exome sequencing was employed to look for causative variants. Results: Linkage analysis revealed cosegregation of a 16.1 Mb haplotype on chromosome 1q42 that contained 173 known or predicted genes. Whole exome sequencing in a single affected individual was undertaken, and the search for the causative variant was focused to within the linkage interval. This approach revealed two novel non-synonymous single nucleotide substitutions within the chromosome 1 locus, in NVL and GJC2. NVL and GJC2 were sequenced in an additional cohort of individuals with a similar phenotype and non-synonymous variants were found in GJC2 in four additional families. Conclusion: This report demonstrates the power of exome sequencing efficiently applied to a traditional positional cloning pipeline in disease gene discovery, and suggests that the phenotype produced by GJC2 mutations is predominantly one of 4 limb lymphoedema

Phase diagram of a Bose gas near a wide Feshbach resonance

In this paper, we study the phase diagram of a homogeneous Bose gas with a repulsive interaction near a wide Feshbach resonance at zero temperature. The Bose-Einstein-condensation (BEC) state of atoms is a metastable state. When the scattering length $a$ exceeds a critical value depending on the atom density $n$, $na^3>0.035$, the molecular excitation energy is imaginary and the atomic BEC state is dynamically unstable against molecule formation. The BEC state of diatomic molecules has lower energy, where the atomic excitation is gapped and the molecular excitation is gapless. However when the scattering length is above another critical value, $na^3>0.0164$, the molecular BEC state becomes a unstable coherent mixture of atoms and molecules. In both BEC states, the binding energy of diatomic molecules is reduced due to the many-body effect.Comment: 5 pages, 4 figure

Evolution of Cooperation and Coordination in a Dynamically Networked Society

Situations of conflict giving rise to social dilemmas are widespread in society and game theory is one major way in which they can be investigated. Starting from the observation that individuals in society interact through networks of acquaintances, we model the co-evolution of the agents' strategies and of the social network itself using two prototypical games, the Prisoner's Dilemma and the Stag Hunt. Allowing agents to dismiss ties and establish new ones, we find that cooperation and coordination can be achieved through the self-organization of the social network, a result that is non-trivial, especially in the Prisoner's Dilemma case. The evolution and stability of cooperation implies the condensation of agents exploiting particular game strategies into strong and stable clusters which are more densely connected, even in the more difficult case of the Prisoner's Dilemma.Comment: 18 pages, 14 figures. to appea

Optimal interdependence between networks for the evolution of cooperation

Recent research has identified interactions between networks as crucial for the outcome of evolutionary games taking place on them. While the consensus is that interdependence does promote cooperation by means of organizational complexity and enhanced reciprocity that is out of reach on isolated networks, we here address the question just how much interdependence there should be. Intuitively, one might assume the more the better. However, we show that in fact only an intermediate density of sufficiently strong interactions between networks warrants an optimal resolution of social dilemmas. This is due to an intricate interplay between the heterogeneity that causes an asymmetric strategy flow because of the additional links between the networks, and the independent formation of cooperative patterns on each individual network. Presented results are robust to variations of the strategy updating rule, the topology of interdependent networks, and the governing social dilemma, thus suggesting a high degree of universality

Interdependent network reciprocity in evolutionary games

Besides the structure of interactions within networks, also the interactions between networks are of the outmost importance. We therefore study the outcome of the public goods game on two interdependent networks that are connected by means of a utility function, which determines how payoffs on both networks jointly influence the success of players in each individual network. We show that an unbiased coupling allows the spontaneous emergence of interdependent network reciprocity, which is capable to maintain healthy levels of public cooperation even in extremely adverse conditions. The mechanism, however, requires simultaneous formation of correlated cooperator clusters on both networks. If this does not emerge or if the coordination process is disturbed, network reciprocity fails, resulting in the total collapse of cooperation. Network interdependence can thus be exploited effectively to promote cooperation past the limits imposed by isolated networks, but only if the coordination between the interdependent networks is not disturbe

Knowledge Transfer and Teaching Public Administration: the Academy Model

Since the beginnings of Public Administration in the US and its accompanying education in other parts of the world, government and policy have become more complex. The education in Public Administration created a professional pathway to public service. The addition of education to Public Administration came out of the Progressive Movement in the United States to make knowledge in Public Administration more important in the face of corruption brought on by patronage appointments. When nonprofits became part the US public sector as elsewhere along with nonprofit healthcare, the complexity expanded enormously, requiring professionals to know more in what has become a multidisciplinary field of study. Given the diversity and complexity of the public sector and the need for Public Administration to embrace more knowledge from many disciplines, it stands to reason that an earlier start on the education portion of Public Administration or a pathway would be beneficial. A model of early Public Administration knowledge transfer is described and illustrated below. The Academy described is based on the US career pathways and high school academies as part of the school to work educational movement. The success of the combination of these two areas will also be pointed out in the academy described. Translation of lessons learned from the Acdemy to Europe and Asia are also considered

Resolution of the stochastic strategy spatial prisoner's dilemma by means of particle swarm optimization

We study the evolution of cooperation among selfish individuals in the stochastic strategy spatial prisoner's dilemma game. We equip players with the particle swarm optimization technique, and find that it may lead to highly cooperative states even if the temptations to defect are strong. The concept of particle swarm optimization was originally introduced within a simple model of social dynamics that can describe the formation of a swarm, i.e., analogous to a swarm of bees searching for a food source. Essentially, particle swarm optimization foresees changes in the velocity profile of each player, such that the best locations are targeted and eventually occupied. In our case, each player keeps track of the highest payoff attained within a local topological neighborhood and its individual highest payoff. Thus, players make use of their own memory that keeps score of the most profitable strategy in previous actions, as well as use of the knowledge gained by the swarm as a whole, to find the best available strategy for themselves and the society. Following extensive simulations of this setup, we find a significant increase in the level of cooperation for a wide range of parameters, and also a full resolution of the prisoner's dilemma. We also demonstrate extreme efficiency of the optimization algorithm when dealing with environments that strongly favor the proliferation of defection, which in turn suggests that swarming could be an important phenomenon by means of which cooperation can be sustained even under highly unfavorable conditions. We thus present an alternative way of understanding the evolution of cooperative behavior and its ubiquitous presence in nature, and we hope that this study will be inspirational for future efforts aimed in this direction.Comment: 12 pages, 4 figures; accepted for publication in PLoS ON

Self-organized network evolution coupled to extremal dynamics

The interplay between topology and dynamics in complex networks is a fundamental but widely unexplored problem. Here, we study this phenomenon on a prototype model in which the network is shaped by a dynamical variable. We couple the dynamics of the Bak-Sneppen evolution model with the rules of the so-called fitness network model for establishing the topology of a network; each vertex is assigned a fitness, and the vertex with minimum fitness and its neighbours are updated in each iteration. At the same time, the links between the updated vertices and all other vertices are drawn anew with a fitness-dependent connection probability. We show analytically and numerically that the system self-organizes to a non-trivial state that differs from what is obtained when the two processes are decoupled. A power-law decay of dynamical and topological quantities above a threshold emerges spontaneously, as well as a feedback between different dynamical regimes and the underlying correlation and percolation properties of the network.Comment: Accepted version. Supplementary information at http://www.nature.com/nphys/journal/v3/n11/suppinfo/nphys729_S1.htm