The adaptive immune system uses the experience of past infections to prepare its limited repertoire of specialized receptors to protect organisms from future threats. What is the best way of doing this? Building a theoretical framework from first principles, we predict the composition of receptor repertoires that are optimally adapted to minimize the cost of infections from a given pathogenic environment. A naive repertoire can reach these optima through a biologically plausible competitive mechanism. Our findings explain how limited populations of immune receptors can self-organize to provide effective immunity against highly diverse pathogens. Our results also inform the design and interpretation of experiments surveying immune repertoires.
How a well-adapted immune system is organized Andreas Mayer, Vijay Balasubramanian, Thierry Mora, and Aleksandra M. Walczak
We perform a multifractal analysis of the evolution of London's street network from 1786 to 2010. First, we show that a single fractal dimension, commonly associated with the morphological description of cities, does not su ce to capture the dynamics of the system. Instead, for a proper characterization of such a dynamics, the multifractal spectrum needs to be considered. Our analysis reveals that London evolves from an inhomogeneous fractal structure, that can be described in terms of a multifractal, to a homogeneous one, that converges to monofractality. We argue that London's multifractal to monofracal evolution might be a special outcome of the constraint imposed on its growth by a green belt. Through a series of simulations, we show that multifractal objects, constructed through di usion limited aggregation, evolve towards monofractality if their growth is constrained by a non-permeable boundary.
Multifractal to monofractal evolution of the London's street network Roberto Murcio, A. Paolo Masucci, Elsa Arcaute, Michael Batty
Cascades are ubiquitous in various network environments. How to predict these cascades is highly nontrivial in several vital applications, such as viral marketing, epidemic prevention and traffic management. Most previous works mainly focus on predicting the final cascade sizes. As cascades are typical dynamic processes, it is always interesting and important to predict the cascade size at any time, or predict the time when a cascade will reach a certain size (e.g. an threshold for outbreak). In this paper, we unify all these tasks into a fundamental problem: cascading process prediction. That is, given the early stage of a cascade, how to predict its cumulative cascade size of any later time? For such a challenging problem, how to understand the micro mechanism that drives and generates the macro phenomenons (i.e. cascading proceese) is essential. Here we introduce behavioral dynamics as the micro mechanism to describe the dynamic process of a node's neighbors get infected by a cascade after this node get infected (i.e. one-hop subcascades). Through data-driven analysis, we find out the common principles and patterns lying in behavioral dynamics and propose a novel Networked Weibull Regression model for behavioral dynamics modeling. After that we propose a novel method for predicting cascading processes by effectively aggregating behavioral dynamics, and propose a scalable solution to approximate the cascading process with a theoretical guarantee. We extensively evaluate the proposed method on a large scale social network dataset. The results demonstrate that the proposed method can significantly outperform other state-of-the-art baselines in multiple tasks including cascade size prediction, outbreak time prediction and cascading process prediction.
From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics Linyun Yu, Peng Cui, Fei Wang, Chaoming Song, Shiqiang Yang
Neighborland empowers people to take action on local issues. We are providing residents, organizations, and city agencies a powerful civic engagement platform designed to move community projects forward.
Want to know what makes us stand apart from our ape cousins?
Cooperation—no other animal does it quite like us. Developmental psychologist Michael Tomasello explains why if chimps had a self-help bestseller, it would be titled, How to Outwit Rivals and Get More Fruit.
Carefully considering all well-known worries about privacy, professor Dirk Helbing raises a great concept: The Planetary Nervous System (PNS). Roughly, this idea involves connecting our smartphones worldwide to build a global measurement network and create a flow of information on all kinds of topics.
The determination of the most central agents in complex networks is important because they are responsible for a faster propagation of information, epidemics, failures and congestion, among others. A challenging problem is to identify them in networked systems characterized by different types of interactions, forming interconnected multilayer networks. Here we describe a mathematical framework that allows us to calculate centrality in such networks and rank nodes accordingly, finding the ones that play the most central roles in the cohesion of the whole structure, bridging together different types of relations. These nodes are the most versatile in the multilayer network. We investigate empirical interconnected multilayer networks and show that the approaches based on aggregating—or neglecting—the multilayer structure lead to a wrong identification of the most versatile nodes, overestimating the importance of more marginal agents and demonstrating the power of versatility in predicting their role in diffusive and congestion processes.
Ranking in interconnected multilayer networks reveals versatile nodes Manlio De Domenico, Albert Solé-Ribalta, Elisa Omodei, Sergio Gómez & Alex Arenas
The 2014 Ebola outbreak in west Africa raised many questions about the control of infectious disease in an increasingly connected global society. Limited availability of contact information has made contact tracing difficult or impractical in combating the outbreak. We consider the development of multi-scale public health strategies and simulate policies for community-level response aimed at early screening of communities rather than individuals, as well as travel restrictions to prevent community cross-contamination. Our analysis shows community screening to be effective even at a relatively low level of compliance. In our simulations, 40% of individuals conforming to this policy is enough to stop the outbreak. Simulations with a 50% compliance rate are consistent with the case counts in Liberia during the period of rapid decline after mid September, 2014. We also find the travel restriction policies to be effective at reducing the risks associated with compliance substantially below the 40% level, shortening the outbreak and enabling efforts to be focused on affected areas. Our results suggest that the multi-scale approach could be applied to help end the outbreaks in Guinea and Sierra Leone, and the generality of our model can be used to further evolve public health strategy for defeating emerging epidemics.
D. Cooney, V. Wong, Y. Bar-Yam, Beyond contact tracing: Community-based early detection for Ebola response, ArXiv:1505.07020 [physics.soc-ph] (May 26, 2014); New England Complex Systems Institute Report 15-05-01
Editor’s Note: MAPP (Mobilizing for Action through Planning and Partnerships) is a local coalition that aims to foster connections and build on our strengths to improve our individual, family, and community health. Health is defined broadly to include cultural, economic, educational, environmental, mental, physical and spiritual health.
"Every one of the major challenges facing us is complex. But our organizations are not designed for complexity. Our education institutions do not teach an understanding of complexity. Our workplace training does not factor in complexity. While not all of our problems are complex, the simpler issues are being dealt with. We need to take what Clay Shirky calls the cognitive surplus, and use it to wrestle with complex problems. Understanding complexity must be part of any informed discussions on government policy or governance. We ignore it at our peril."
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