Complex Networks Everywhere
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Complex Networks Everywhere
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Network analysis of hazard interconnections – Aaron Clark-Ginsberg

Network analysis of hazard interconnections – Aaron Clark-Ginsberg | Complex Networks Everywhere | Scoop.it
This post is the first in a series focused on using network analysis to analyse disaster risk. Disasters beget disasters. The 2010 Haiti earthquake for...

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Coupled catastrophes: sudden shifts cascade and hop among interdependent systems

Coupled catastrophes: sudden shifts cascade and hop among interdependent systems | Complex Networks Everywhere | Scoop.it

An important challenge in several disciplines is to understand how sudden changes can propagate among coupled systems. Examples include the synchronization of business cycles, population collapse in patchy ecosystems, markets shifting to a new technology platform, collapses in prices and in confidence in financial markets, and protests erupting in multiple countries. A number of mathematical models of these phenomena have multiple equilibria separated by saddle-node bifurcations. We study this behaviour in its normal form as fast–slow ordinary differential equations. In our model, a system consists of multiple subsystems, such as countries in the global economy or patches of an ecosystem. Each subsystem is described by a scalar quantity, such as economic output or population, that undergoes sudden changes via saddle-node bifurcations. The subsystems are coupled via their scalar quantity (e.g. trade couples economic output; diffusion couples populations); that coupling moves the locations of their bifurcations. The model demonstrates two ways in which sudden changes can propagate: they can cascade (one causing the next), or they can hop over subsystems. The latter is absent from classic models of cascades. For an application, we study the Arab Spring protests. After connecting the model to sociological theories that have bistability, we use socioeconomic data to estimate relative proximities to tipping points and Facebook data to estimate couplings among countries. We find that although protests tend to spread locally, they also seem to ‘hop' over countries, like in the stylized model; this result highlights a new class of temporal motifs in longitudinal network datasets.

 

 

Coupled catastrophes: sudden shifts cascade and hop among interdependent systems

Charles D. Brummitt, George Barnett, Raissa M. D'Souza

J. R. Soc. Interface 2015 12 20150712; http://dx.doi.org/10.1098/rsif.2015.0712. Published 11 November 2015. Open Access.

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Self-Repair Networks: A Mechanism Design (by Yoshiteru Ishida)

This book describes the struggle to introduce a mechanism that enables next-generation information systems to maintain themselves. Our generation observed the birth and growth of information systems, and the Internet in particular. Surprisingly information systems are quite different from conventional (energy, material-intensive) artificial systems, and rather resemble biological systems (information-intensive systems). Many artificial systems are designed based on (Newtonian) physics assuming that every element obeys simple and static rules; however, the experience of the Internet suggests a different way of designing where growth cannot be controlled but self-organized with autonomous and selfish agents. This book suggests using game theory, a mechanism design in particular, for designing next-generation information systems which will be self-organized by collective acts with autonomous components. The challenge of mapping a probability to time appears repeatedly in many forms throughout this book.

The book contains interdisciplinary research encompassing game theory, complex systems, reliability theory and particle physics. All devoted to its central theme: what happens if systems self-repair themselves?

 

 


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Operational resilience: concepts, design and analysis

Building resilience into today’s complex infrastructures is critical to the daily functioning of society and its ability to withstand and recover from natural disasters, epidemics, and cyber-threats. This study proposes quantitative measures that capture and implement the definition of engineering resilience advanced by the National Academy of Sciences. The approach is applicable across physical, information, and social domains. It evaluates the critical functionality, defined as a performance function of time set by the stakeholders. Critical functionality is a source of valuable information, such as the integrated system resilience over a time interval, and its robustness. The paper demonstrates the formulation on two classes of models: 1) multi-level directed acyclic graphs, and 2) interdependent coupled networks. For both models synthetic case studies are used to explore trends. For the first class, the approach is also applied to the Linux operating system. Results indicate that desired resilience and robustness levels are achievable by trading off different design parameters, such as redundancy, node recovery time, and backup supply available. The nonlinear relationship between network parameters and resilience levels confirms the utility of the proposed approach, which is of benefit to analysts and designers of complex systems and networks.

 

Operational resilience: concepts, design and analysis
Alexander A. Ganin, Emanuele Massaro, Alexander Gutfraind, Nicolas Steen, Jeffrey M. Keisler, Alexander Kott, Rami Mangoubi & Igor Linkov
Scientific Reports 6, Article number: 19540 (2016)
http://dx.doi.org/10.1038/srep19540


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New center focuses on complex systems - Binghamton University Research News - Insights and Innovations

New center focuses on complex systems - Binghamton University Research News - Insights and Innovations | Complex Networks Everywhere | Scoop.it
New center focuses on complex systems Binghamton University Research News - Insights and Innovations Statistics and calculus help us understand our world in important ways, but scientists need new tools to make sense of increasingly complex and...
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The Critical Few

The Critical Few | Complex Networks Everywhere | Scoop.it

To maintain stability yet retain the flexibility to adapt to changing circumstances, social systems must strike a balance between the maintenance of a shared reality and the survival of minority opinion. A computational model is presented that investigates the interplay of two basic, oppositional social processes—conformity and anticonformity—in promoting the emergence of this balance. Computer simulations employing a cellular automata platform tested hypotheses concerning the survival of minority opinion and the maintenance of system stability for different proportions of anticonformity. Results revealed that a relatively small proportion of anticonformists facilitated the survival of a minority opinion held by a larger number of conformists who would otherwise succumb to pressures for social consensus. Beyond a critical threshold, however, increased proportions of anticonformists undermined social stability. Understanding the adaptive benefits of balanced oppositional forces has implications for optimal functioning in psychological and social processes in general.

 

The Critical Few: Anticonformists at the Crossroads of Minority Opinion Survival and Collapse
by Matthew Jarman, Andrzej Nowak, Wojciech Borkowski, David Serfass, Alexander Wong and Robin Vallacher
http://jasss.soc.surrey.ac.uk/18/1/6.html


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The Heterogeneous Dynamics of Economic Complexity

What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita . This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method— the selective predictability scheme —in which we adopt a strategy similar to the methods of analogues , firstly introduced by Lorenz, to assess future evolution of countries.

by 

Matthieu Cristelli , Andrea Tacchella, Luciano Pietronero


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The New Laws of Explosive Networks

The New Laws of Explosive Networks | Complex Networks Everywhere | Scoop.it

Researchers are uncovering the hidden laws that reveal how the Internet grows, how viruses spread, and how financial bubbles burst.

 

https://www.quantamagazine.org/20150714-explosive-percolation-networks/ ;


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A Design Pattern for Decentralised Decision Making

The engineering of large-scale decentralised systems requires sound methodologies to guarantee the attainment of the desired macroscopic system-level behaviour given the microscopic individual-level implementation. While a general-purpose methodology is currently out of reach, specific solutions can be given to broad classes of problems by means of well-conceived design patterns. We propose a design pattern for collective decision making grounded on experimental/theoretical studies of the nest-site selection behaviour observed in honeybee swarms (Apis mellifera). The way in which honeybee swarms arrive at consensus is fairly well-understood at the macroscopic level. We provide formal guidelines for the microscopic implementation of collective decisions to quantitatively match the macroscopic predictions. We discuss implementation strategies based on both homogeneous and heterogeneous multiagent systems, and we provide means to deal with spatial and topological factors that have a bearing on the micro-macro link. Finally, we exploit the design pattern in two case studies that showcase the viability of the approach. Besides engineering, such a design pattern can prove useful for a deeper understanding of decision making in natural systems thanks to the inclusion of individual heterogeneities and spatial factors, which are often disregarded in theoretical modelling.

 

Reina A, Valentini G, Fernández-Oto C, Dorigo M, Trianni V (2015) A Design Pattern for Decentralised Decision Making. PLoS ONE 10(10): e0140950. http://dx.doi.org/10.1371/journal.pone.0140950


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Mechanism of organization increase in complex systems

This article proposes a variational approach to describe the evolution of organization of complex systems from first principles, as increased efficiency of physical action. Most simply stated, physical action is the product of the energy and time necessary for motion. When complex systems are modeled as flow networks, this efficiency is defined as a decrease of action for one element to cross between two nodes, or endpoints of motion—a principle of least unit action. We find a connection with another principle, that of most total action, or a tendency for increase of the total action of a system. This increase provides more energy and time for minimization of the constraints to motion to decrease unit action, and therefore, to increase organization. Also, with the decrease of unit action in a system, its capacity for total amount of action increases. We present a model of positive feedback between action efficiency and the total amount of action in a complex system, based on a system of ordinary differential equations, which leads to an exponential growth with time of each and a power law relation between the two. We present an agreement of our model with data for core processing units of computers. This approach can help to describe, measure, manage, design, and predict future behavior of complex systems to achieve the highest rates of self-organization and robustness

 

Mechanism of organization increase in complex systems
Georgi Yordanov Georgiev, et al.

Complexity
Volume 21, Issue 2, pages 18–28, November/December 2015

http://dx.doi.org/10.1002/cplx.21574 ;


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A multi-source dataset of urban life in the city of Milan and the Province of Trentino

A multi-source dataset of urban life in the city of Milan and the Province of Trentino | Complex Networks Everywhere | Scoop.it

The study of socio-technical systems has been revolutionized by the unprecedented amount of digital records that are constantly being produced by human activities such as accessing Internet services, using mobile devices, and consuming energy and knowledge. In this paper, we describe the richest open multi-source dataset ever released on two geographical areas. The dataset is composed of telecommunications, weather, news, social networks and electricity data from the city of Milan and the Province of Trentino. The unique multi-source composition of the dataset makes it an ideal testbed for methodologies and approaches aimed at tackling a wide range of problems including energy consumption, mobility planning, tourist and migrant flows, urban structures and interactions, event detection, urban well-being and many others.

 

A multi-source dataset of urban life in the city of Milan and the Province of Trentino
Gianni Barlacchi, Marco De Nadai, Roberto Larcher, Antonio Casella, Cristiana Chitic, Giovanni Torrisi, Fabrizio Antonelli, Alessandro Vespignani, Alex Pentland & Bruno Lepri

Scientific Data 2, Article number: 150055 (2015) http://dx.doi.org/10.1038/sdata.2015.55


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Prebiotic network evolution: six key parameters

The origins of life likely required the cooperation among a set of molecular species interacting in a network. If so, then the earliest modes of evolutionary change would have been governed by the manners and mechanisms by which networks change their compositions over time. For molecular events, especially those in a pre-biological setting, these mechanisms have rarely been considered. We are only recently learning to apply the results of mathematical analyses of network dynamics to prebiotic events. Here, we attempt to forge connections between such analyses and the current state of knowledge in prebiotic chemistry. Of the many possible influences that could direct primordial network, six parameters emerge as the most influential when one considers the molecular characteristics of the best candidates for the emergence of biological information: polypeptides, RNA-like polymers, and lipids. These parameters are viable cores, connectivity kinetics, information control, scalability, resource availability, and compartmentalization. These parameters, both individually and jointly, guide the aggregate evolution of collectively autocatalytic sets. We are now in a position to translate these conclusions into a laboratory setting and test empirically the dynamics of prebiotic network evolution.

 

Prebiotic network evolution: six key parameters
Philippe Nghe,  Wim Hordijk,   Stuart A. Kauffman,   Sara I. Walker, Francis J. Schmidt,   Harry Kemble,   Jessica A. M. Yeates, and   Niles Lehman

Mol. BioSyst., 2015

http://dx.doi.org/10.1039/C5MB00593K


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Lifelong memories may reside in nets around brain cells

Lifelong memories may reside in nets around brain cells | Complex Networks Everywhere | Scoop.it

In 1898, Italian biologist Camillo Golgi saw something odd in the slices of brain tissue he examined under his micro scope: weblike lattices surrounding many neurons. Golgi could not discern their purpose, and many dismissed the nets as an artifact of his staining technique. For the next century, the lattices remained largely obscure. But last week at the annual meeting of the Society for Neuroscience here, researchers offered tantalizing new evidence that holes in these nets could be the storage sites for long-term memories.

Perineuronal nets (PNNs), as they are known today, are scaffolds of linked proteins and sugars that resemble cartilage. A growing body of research suggests that PNNs may control the formation and function of synapses, the microscopic junctions between neurons that allow cells to communicate and that may play a role in learning and memory, says neuroscientist Sakina Palida (...)

 

Lifelong memories may reside in nets around brain cells
Emily Underwood

Science 30 October 2015:
Vol. 350 no. 6260 pp. 491-492
http://dx.doi.org/10.1126/science.350.6260.491


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Complexity Digest's curator insight, October 30, 2015 1:14 PM

It is commonly considered that neuronal patterns store memories. This research suggests that memories are fixed at the molecular scale, increasing by orders of magnitude the estimated information storage of nervous systems.

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Network theory sheds new light on origins of consciousness

Network theory sheds new light on origins of consciousness | Complex Networks Everywhere | Scoop.it
Vanderbilt University researchers took a significant step toward answering longstanding questions about the origins of consciousness with a recent discovery of global changes in how brain areas communicate with one another during awareness.

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ukituki's curator insight, December 18, 2015 9:02 AM

“We know there are numerous brain networks that control distinct cognitive functions such as attention, language and control, with each node of a network densely interconnected with other nodes of the same network, but not with other networks,” Marois said. “Consciousness appears to break down the modularity of these networks, as we observed a broad increase in functional connectivity between these networks with awareness.”

Ruan O'Tiarnaigh's curator insight, April 13, 10:29 AM
Food for thought
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Eigencentrality based on dissimilarity measures reveals central nodes in complex networks

One of the most important problems in complex network’s theory is the location of the entities that are essential or have a main role within the network. For this purpose, the use of dissimilarity measures (specific to theory of classification and data mining) to enrich the centrality measures in complex networks is proposed. The centrality method used is the eigencentrality which is based on the heuristic that the centrality of a node depends on how central are the nodes in the immediate neighbourhood (like rich get richer phenomenon). This can be described by an eigenvalues problem, however the information of the neighbourhood and the connections between neighbours is not taken in account, neglecting their relevance when is one evaluates the centrality/importance/influence of a node. The contribution calculated by the dissimilarity measure is parameter independent, making the proposed method is also parameter independent. Finally, we perform a comparative study of our method versus other methods reported in the literature, obtaining more accurate and less expensive computational results in most cases.

 

Eigencentrality based on dissimilarity measures reveals central nodes in complex networks
A. J. Alvarez-Socorro, G. C. Herrera-Almarza & L. A. González-Díaz

Scientific Reports 5, Article number: 17095 (2015)
http://dx.doi.org/10.1038/srep17095 ;


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How does misinformation spread online?

How does misinformation spread online? | Complex Networks Everywhere | Scoop.it
Recent studies that focus on misinformation online pointed out that the selective exposure to specific contents lead to ‘echo-chambers’ in which users tend to shape and reinforce their beliefs.

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Eigencentrality based on dissimilarity measures reveals central nodes in complex networks

Eigencentrality based on dissimilarity measures reveals central nodes in complex networks | Complex Networks Everywhere | Scoop.it
One of the most important problems in complex network’s theory is the location of the entities that are essential or have a main role within the network.
A. J. Alvarez-Socorro's insight:

One of the most important problems in complex network’s theory is the location of the entities that are essential or have a main role within the network. For this purpose, the use of dissimilarity measures (specific to theory of classification and data mining) to enrich the centrality measures in complex networks is proposed. The centrality method used is the eigencentrality which is based on the heuristic that the centrality of a node depends on how central are the nodes in the immediate neighbourhood (like rich get richer phenomenon). This can be described by an eigenvalues problem, however the information of the neighbourhood and the connections between neighbours is not taken in account, neglecting their relevance when is one evaluates the centrality/importance/influence of a node. The contribution calculated by the dissimilarity measure is parameter independent, making the proposed method is also parameter independent. Finally, we perform a comparative study of our method versus other methods reported in the literature, obtaining more accurate and less expensive computational results in most cases.

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Beyond contact-based transmission networks: the role of spatial coincidence

Beyond contact-based transmission networks: the role of spatial coincidence | Complex Networks Everywhere | Scoop.it

Animal societies rely on interactions between group members to effectively communicate and coordinate their actions. To date, the transmission properties of interaction networks formed by direct physical contacts have been extensively studied for many animal societies and in all cases found to inhibit spreading. Such direct interactions do not, however, represent the only viable pathways. When spreading agents can persist in the environment, indirect transmission via ‘same-place, different-time’ spatial coincidences becomes possible. Previous studies have neglected these indirect pathways and their role in transmission. Here, we use rock ant colonies, a model social species whose flat nest geometry, coupled with individually tagged workers, allowed us to build temporally and spatially explicit interaction networks in which edges represent either direct physical contacts or indirect spatial coincidences. We show how the addition of indirect pathways allows the network to enhance or inhibit the spreading of different types of agent. This dual-functionality arises from an interplay between the interaction-strength distribution generated by the ants' movement and environmental decay characteristics of the spreading agent. These findings offer a general mechanism for understanding how interaction patterns might be tuned in animal societies to control the simultaneous transmission of harmful and beneficial agents.

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Self-Organization, Emergence, and Constraint in Complex Natural Systems

Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity and dynamical systems theory, several authors have turned to the notion of constraints on state transitions. Drawing on complexity theory directly, this paper builds on those accounts, further developing the constraint-based interpretation of emergence and arguing that such accounts recover many of the features of more traditional accounts. We show that the constraint-based account of emergence also leads naturally into a meaningful definition of self-organization, another concept that has received increasing attention recently. Along the way, we distinguish between order and organization, two concepts which are frequently conflated. Finally, we consider possibilities for future research in the philosophy of complex systems, as well as applications of the distinctions made in this paper.

 

Self-Organization, Emergence, and Constraint in Complex Natural Systems
Jonathan Lawhead

http://arxiv.org/abs/1502.01476


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Eli Levine's curator insight, February 14, 2015 9:23 PM

We are naturally constrained by many natural laws in our universe.  Our governments are likewise constrained by physical laws of nature as well as the natural laws behind people, societies, economies, and ecosystems.  Where the constraints came from in nature, I don't know.  But what I do see, is that like the natural laws of the universe, societies impose other constraints upon our actions, behaviors, perceptions, chosen courses of action, abilities to frame issues and topics, abilities to define conditions within our social systems.  Governments can likewise make and define constraints for behaviors or willingness and ability to behave on the part of the citizenry, either by offering incentives to get people to behave in a particular way or to penalize and possibly limit some actions and chosen patterns of behavior. 

 

It should be noted that the laws and chosen constraints and incentives of the government on this level of existence can only be as good as the people who sit within them and make choices.  They are also limited by the physical laws of the universe and the natural laws, conditions, desires, and motives of the general public that composes the whole of society in aggregate and as that which is greater than the aggregate; the combined whole of human thought, behavior, and sentiment. 

 

These human-made constraints (created by governments and social authority figures) are also imperfect in their ability to contain and constrain the society, since the society and its members have autonomy from the government.  Humans and human societies are more constrained by the natural laws and the limitations of knowledge and perception that are present in our brains and neural systems.  Therefore, it can be said that human-made social constraints are less important than the natural ones that exist amongst ourselves and within the universe that we are apart of.

 

Therefore, I think that in order to continue to advance humanity and contribute to our potential to survive, endure, and thrive, we should be constantly and safely pushing at the constraints of what we already know and can do as individuals and as a species.  Our government(s) should focus on studying the universal natural laws of societies, economies, human behavior, and environmental functions in addition to the particular laws of their own societies, making laws and legal systems that work better and better with the natural laws of their own societies and amongst all human societies.  We should capitalize on our differences of perspective and opinion, sifting out those that don't fall into line with discovered reality while using that which is accurate to complete the puzzles of our universe in order to produce something greater than what we've presently got and to continue to advance ourselves safely and in accordance with what is actually helpful, healthful, and ethical for all sentient life in the universe.  Study, research, observation, and exploration are what will make tomorrow better than today, even as the natural laws and some conditions remain the same.  Health, well-being, quality of life, sustainability, and the ability to thrive for all are what we need to prioritize and produce as a society over financial profits and short term economic gains for a few.  Some constraints can be pushed, some can't, and some really shouldn't from the perspective of health, well-being, quality of life, and the ability to thrive for all.  Welcome to nature.

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The Amazing, Autotuning Sandpile

The Amazing, Autotuning Sandpile | Complex Networks Everywhere | Scoop.it

Remember domino theory? One country going Communist was supposed to topple the next, and then the next, and the next. The metaphor drove much of United States foreign policy in the middle of the 20th century. But it had the wrong name. From a physical point of view, it should have been called the “sandpile theory.”
Real-world political phase transitions tend to happen not in neat sequences, but in sudden coordinated fits, like the Arab Spring, or the collapse of the Eastern Bloc. These reflect quiet periods punctuated by crises—like a sandpile. You can add grains of sand to the top of a sandpile for a while, to no apparent effect. Then, all at once, an avalanche sweeps sand down from the top in an irregular pattern, possibly setting off little sub-avalanches as it goes.

 

http://nautil.us/issue/23/dominoes/the-amazing-autotuning-sandpile ;


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Weighting dissimilarities to detect communities in networks

Weighting dissimilarities to detect communities in networks | Complex Networks Everywhere | Scoop.it

Many complex systems can be described as networks exhibiting inner organization as communities of nodes. The identification of communities is a key factor to understand community-based functionality. We propose a family of measures based on the weighted sum of two dissimilarity quantifiers that facilitates efficient classification of communities by tuning the quantifiers’ relative weight to the network’s particularities. Additionally, two new dissimilarities are introduced and incorporated in our analysis. The effectiveness of our approach is tested by examining the Zachary’s Karate Club Network and the Caenorhabditis elegans reactions network. The analysis reveals the method’s classification power as confirmed by the efficient detection of intrapathway metabolic functions in C. elegans.

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Cooperation, competition and the emergence of criticality in communities of adaptive systems

The hypothesis that living systems can benefit from operating at the vicinity of critical points has gained momentum in recent years. Criticality may confer an optimal balance between exceedingly ordered and too noisy states. We here present a model, based on information theory and statistical mechanics, illustrating how and why a community of agents aimed at understanding and communicating with each other converges to a globally coherent state in which all individuals are close to an internal critical state, i.e. at the borderline between order and disorder. We study --both analytically and computationally-- the circumstances under which criticality is the best possible outcome of the dynamical process, confirming the convergence to critical points under very generic conditions. Finally, we analyze the effect of cooperation (agents try to enhance not only their fitness, but also that of other individuals) and competition (agents try to improve their own fitness and to diminish those of competitors) within our setting. The conclusion is that, while competition fosters criticality, cooperation hinders it and can lead to more ordered or more disordered consensual solutions.

 

Cooperation, competition and the emergence of criticality in communities of adaptive systems
Jorge Hidalgo, Jacopo Grilli, Samir Suweis, Amos Maritan, Miguel A. Munoz

http://arxiv.org/abs/1510.05941


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Long-range Acoustic Interactions in Insect Swarms: An Adaptive Gravity Model

The collective motion of groups of animals emerges from the net effect of the interactions between individual members of the group. In many cases, such as birds, fish, or ungulates, these interactions are mediated by sensory stimuli that predominantly arise from nearby neighbors. But not all stimuli in animal groups are short range. Here, we consider mating swarms of midges, which interact primarily via long-range acoustic stimuli. We exploit the similarity in form between the decay of acoustic and gravitational sources to build a model for swarm behavior. By accounting for the adaptive nature of the midges' acoustic sensing, we show that our "adaptive gravity" model makes mean-field predictions that agree well with experimental observations of laboratory swarms. Our results highlight the role of sensory mechanisms and interaction range in collective animal behavior. The adaptive interactions that we present here open a new class of equations of motion, which may appear in other biological contexts.

 

Long-range Acoustic Interactions in Insect Swarms: An Adaptive Gravity Model
Dan Gorbonos, Reuven Ianconescu, James G. Puckett, Rui Ni, Nicholas T. Ouellette, Nir S. Gov

http://arxiv.org/abs/1510.07259


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Collective action problem in heterogeneous groups

Collective action problem in heterogeneous groups | Complex Networks Everywhere | Scoop.it

I review the theoretical and experimental literature on the collective action problem in groups whose members differ in various characteristics affecting individual costs, benefits and preferences in collective actions. I focus on evolutionary models that predict how individual efforts and fitnesses, group efforts and the amount of produced collective goods depend on the group's size and heterogeneity, as well as on the benefit and cost functions and parameters. I consider collective actions that aim to overcome the challenges from nature or win competition with neighbouring groups of co-specifics. I show that the largest contributors towards production of collective goods will typically be group members with the highest stake in it or for whom the effort is least costly, or those who have the largest capability or initial endowment. Under some conditions, such group members end up with smaller net pay-offs than the rest of the group. That is, they effectively behave as altruists. With weak nonlinearity in benefit and cost functions, the group effort typically decreases with group size and increases with within-group heterogeneity. With strong nonlinearity in benefit and cost functions, these patterns are reversed. I discuss the implications of theoretical results for animal behaviour, human origins and psychology.

 

Collective action problem in heterogeneous groups
Sergey Gavrilets

Phil. Trans. B

December 2015
Volume: 370 Issue: 1683

http://dx.doi.org/10.1098/rstb.2015.0016


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António F Fonseca's curator insight, November 4, 2015 4:54 AM

A very good review paper about collective action. Applying Mancur Olson's insights to Biology and groups.

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A unified initiative to harness Earth's microbiomes

Despite their centrality to life on Earth, we know little about how microbes (1) interact with each other, their hosts, or their environment. Although DNA sequencing technologies have enabled a new view of the ubiquity and diversity of microorganisms, this has mainly yielded snapshots that shed limited light on microbial functions or community dynamics. Given that nearly every habitat and organism hosts a diverse constellation of microorganisms—its “microbiome”—such knowledge could transform our understanding of the world and launch innovations in agriculture, energy, health, the environment, and more (see the photo). We propose an interdisciplinary Unified Microbiome Initiative (UMI) to discover and advance tools to understand and harness the capabilities of Earth's microbial ecosystems. The impacts of oceans and soil microbes on atmospheric CO2 are critical for understanding climate change (2). By manipulating interactions at the root-soil-microbe interface, we may reduce agricultural pesticide, fertilizer, and water use enrich marginal land and rehabilitate degraded soils. Microbes can degrade plant cell walls (for biofuels), and synthesize myriad small molecules for new bioproducts, including antibiotics (3). Restoring normal human microbial ecosystems can save lives [e.g., fecal microbiome transplantation for Clostridium difficile infections (4)]. Rational management of microbial communities in and around us has implications for asthma, diabetes, obesity, infectious diseases, psychiatric illnesses, and other afflictions (5, 6). The human microbiome is a target and a source for new drugs (7) and an essential tool for precision medicine (8).

 

A unified initiative to harness Earth's microbiomes
(...) Unified Microbiome Initiative Consortium

Science 30 October 2015:
Vol. 350 no. 6260 pp. 507-508
http://dx.doi.org/10.1126/science.aac8480


Via Complexity Digest
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