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Date: Mon, 20 Oct 2014 11:41:41 -0500
From: Complexity Digest Administration <[log in to unmask]>
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Subject: [comdig] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at

Site-specific group selection drives locally adapted group compositions

    Group selection may be defined as selection caused by the differential extinction or proliferation of groups. The socially polymorphic spider Anelosimus studiosus exhibits a behavioural polymorphism in which females exhibit either a ˙˙docile˙˙ or ˙˙aggressive˙˙ behavioural phenotype. Natural colonies are composed of a mixture of related docile and aggressive individuals, and populations differ in colonies˙˙ characteristic docile:aggressive ratios. Using experimentally constructed colonies of known composition, here we demonstrate that population-level divergence in docile:aggressive ratios is driven by site-specific selection at the group level˙˙certain ratios yield high survivorship at some sites but not others. Our data also indicate that colonies responded to the risk of extinction: perturbed colonies tended to adjust their composition over two generations to match the ratio characteristic of their native site, thus promoting their long-term survival in their natal habitat.
However, colonies of displaced individuals continued to shift their compositions towards mixtures that would have promoted their survival had they remained at their home sites, regardless of their contemporary environment. Thus, the regulatory mechanisms that colonies use to adjust their composition appear to be locally adapted. Our data provide experimental evidence of group selection driving collective traits in wild populations.

Site-specific group selection drives locally adapted group compositions
˙˙ Jonathan N. Pruitt & Charles J. Goodnight

Nature 514, 359˙˙362 (16 October 2014)

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Explosive synchronization in adaptive and multilayer networks

    Explosive synchronization (ES) is nowadays a hot topic of interest in nonlinear science and complex networks. So far, it is conjectured that ES is rooted in the setting of specific microscopic correlation features between the natural frequencies of the networked oscillators and their effective coupling strengths. We show that ES, in fact, is far more general, and can occur in adaptive and multilayer networks also in the absence of such correlation properties. Precisely, we first report evidence of ES in the absence of correlation for networks where a fraction f of the nodes have links adaptively controlled by a local order parameter, and then we extend the study to a variety of two-layer networks with a fraction f of their nodes coupled each other by means of dependency links. In this latter case, we even show that ES sets in, regardless of the differences in the frequency distribution and/or in the topology of connections between the two layers. Finally, we provide a
rigorous, analytical, treatment to properly ground all the observed scenario, and to facilitate the understanding of the actual mechanisms at the basis of ES in real-world systems.

Explosive synchronization in adaptive and multilayer networks
Xiyun Zhang, Stefano Boccaletti, Shuguang Guan, Zonghua Liu

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Networks of Military Alliances, Wars, and International Trade

    We investigate the role of networks of alliances in preventing (multilateral) interstate wars. We first show that, in the absence of international trade, no network of alliances is peaceful and stable. We then show that international trade induces peaceful and stable networks: trade increases the density of alliances so that countries are less vulnerable to attack and also reduces countries' incentives to attack an ally. We present historical data on wars and trade, noting that the dramatic drop in interstate wars since 1950, and accompanying densification and stabilization of alliances, are consistent with the model but not other prominent theories.

Networks of Military Alliances, Wars, and International Trade
Matthew O. Jackson, Stephen M. Nei

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The LinkedIn Economic Graph Challenge

    There are approximately 3 billion people in the global workforce. LinkedIn's vision is to create economic opportunity for every one of them. The development of the world's first Economic Graph will lead to making that vision a reality. This, of course, is no easy task. Our vision is grand, but it's not unattainable.

So, here's the challenge: Given the wealth of data that exists within LinkedIn, what research would you propose that has the potential to create greater economic opportunity?

We are launching the LinkedIn Economic Graph Challenge to encourage researchers, academics and data-driven thinkers to solve some of the most challenging economic problems of our times.

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A Stochastic Process Approach to Model Distributed Computing on Complex Networks

    In this work we present analytic expressions for the expected values of the performance metrics of parallel applications when the distributed computing infrastructure has a complex topology. Through active probing tests we analyse the structure of a real distributed computing environment. From the resulting network we both validate the analytic expressions and explore the performance metrics under different conditions through Monte Carlo simulations. In particular we gauge computing paradigms with different hierarchical structures in computing services. Fully decentralised (i.e., peer-to-peer) environments provide the best performance. Moreover, we show that it is possible to improve significantly the parallel efficiency by implementing more intelligent configurations of computing services and task allocation strategies (e.g., by using a betweenness centrality measure). We qualitatively reproduce results of previous works and provide closed-form solutions that link topology,
application˙˙s structure and allocation parameters when job dependencies and a complex network structure are considered.

Distributed Computing on Complex Networks
Francisco Prieto-Castrillo, Antonio Astillero, María Botón-Fernández

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Complex networks: theory, methods and applications | Lake Como School of Advanced Studies

    Many real systems can be modeled as networks, where the elements of the system are nodes and interactions between elements are edges. An even larger set of systems can be modeled using dynamical processes on networks, which are in turn affected by the dynamics. Networks thus represent the backbone of many complex systems, and their theoretical and computational analysis makes it possible to gain insights into numerous applications. Networks permeate almost every conceivable discipline ˙˙including sociology, transportation, economics and finance, biology, and myriad others ˙˙ and the study of ˙˙network science˙˙ has thus become a crucial component of modern scientific education.

The school ˙˙Complex Networks: Theory, Methods, and Applications˙˙ offers a succinct education in network science. It is open to all aspiring scholars in any area of science or engineering who wish to study networks of any kind (whether theoretical or applied), and it is especially addressed to doctoral students and young postdoctoral scholars. The aim of the school is to deepen into both theoretical developments and applications in targeted fields.

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Mediated attachment as a mechanism for growth of complex networks

    Connection topologies of many networked systems like human brain, biological cell, world wide web, power grids, human society and ecological food webs markedly deviate from that of completely random networks indicating the presence of organizing principles behind their evolution. The five important features that characterize such networks are scale-free topology, small average path length, high clustering, hierarchical community structure and assortative mixing. Till now the generic mechanisms underlying the existence of these properties are not well understood. Here we show that potentially a single mechanism, which we call "mediated attachment", where two nodes get connected through a mediator or common neighbor, could be responsible for the emergence of all important properties of real networks. The mediated attachment naturally unifies scale-free topology, high clustering, small world nature, hierarchical community structure and dissortative nature of networks. Further,
with additional mixing by age, this can also explain the assortative structure of social networks. The mechanism of mediated attachment seems to be directly present in acquaintance networks, co-authorships, World Wide Web, metabolic networks, co-citations and linguistics. We anticipate that this mechanism will shed new light on percolation and robustness properties of real world networks as well as would give new insights in processes like epidemics spreading and emergent dynamics taking place on them.

Mediated attachment as a mechanism for growth of complex networks
Snehal M. Shekatkar, G. Ambika

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Socioinformatics - The Social Impact of Interactions between Humans and IT (by Katharina Zweig et al.)

    Socioinformatics is a new scientific approach to study the interactions between humans and IT. These proceedings are a collection of the contributions during a workshop of the Gesellschaft für Informatik (GI). Researchers in this emerging field discuss the main aspects of interactions between IT and humans with respect to; social connections, social changes, acceptance of IT and the social conditions affecting this acceptance, effects of IT on humans and in response changes of IT, structures of the society and the influence of IT on these structures, changes of metaphysics influenced by IT and the social context of a knowledge society.

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Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.

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