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Mind-expanding: America’s neuroscience initiative

Mind-expanding: America’s neuroscience initiative | Papers | Scoop.it

AFTER much trailing, the reality is out. On April 2nd President Barack Obama announced that America’s government will back a project intended to unlock the mysteries of the human brain. It was, according to the trails, to have been known as the Brain Activity Map. But someone clearly spotted that BAM, as an acronym, is a hostage to fortune and the project is now to be known as the Brain Research through Advancing Innovative Neurotechnologies initiative. By what is no doubt a complete coincidence, that spells “BRAIN”.


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Kasia Hein-Peters's curator insight, April 5, 2013 6:22 PM

I am curious what we will learn through the BRAIN project and I have high hopes.

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Algorithmic Cognition and the Computational Nature of the Mind

The idea that complexity or, its reverse, simplicity are essential concepts for cognitive psychology was already understood in the middle of the twentieth century (Mach 1914), and these concepts have remained salient ever since (Oizumi et al. 2014). As early as the 1990s, the algorithmic theory of information was referenced by some researchers in psychology, who recommended the use of algorithmic complexity as a universal normative measure of complexity. Nevertheless, the noncomputability of algorithmic complexity was deemed an insurmountable obstacle, and more often than not it merely served as a point of reference.
In recent years, we have been able to create and use more reliable estimates of algorithmic complexity using the coding theorem method (Gauvrit et al. 2014b, 2016). This has made it possible to deploy a precise and quantitative approximation of algorithmic complexity, with applications in many areas of psychology and the behavioral sciences – sometimes ...

 

Algorithmic Cognition and the Computational Nature of the Mind

Hector Zenil , Nicolas Gauvrit

Living Reference Work Entry
Encyclopedia of Complexity and Systems Science
pp 1-9

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How Self-Organization Happens

Self-organization refers to natural processes of human relating, that are similar at all scales of order in the natural world.The dynamics of self-organization are much more rich and complex than the simple patterns we use to model them.Being able to make sense of these dynamics enables us to build new potentials in teams. The level of trust rises when we recognize our basic human capacity to collaborate with each other. Narrative-based applications can visualize some of the subtle patterns that shape a team’s potential for acting in certain ways (and not others) over time.
There isn't one specific pattern that emerges from self-organization. The processes are so deep and fundamental to human interactions, that you cannot enforce any specific hierarchical or non-hierarchical pattern with rules.  Trust between people is an outcome of allowing people to freely self-organize. Complex networks of trust emerge and change as people continuously negotiate their relationships.


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Stream Graphs and Link Streams for the Modeling of Interactions over Time

Graph theory provides a language for studying the structure of relations, and it is often used to study interactions over time too. However, it poorly captures the both temporal and structural nature of interactions, that calls for a dedicated formalism. In this paper, we generalize graph concepts in order to cope with both aspects in a consistent way. We start with elementary concepts like density, clusters, or paths, and derive from them more advanced concepts like cliques, degrees, clustering coefficients, or connected components. We obtain a language to directly deal with interactions over time, similar to the language provided by graphs to deal with relations. This formalism is self-consistent: usual relations between different concepts are preserved. It is also consistent with graph theory: graph concepts are special cases of the ones we introduce. This makes it easy to generalize higher-level objects such as quotient graphs, line graphs, k-cores, and centralities. This paper also considers discrete versus continuous time assumptions, instantaneous links, and extensions to more complex cases.

 

Stream Graphs and Link Streams for the Modeling of Interactions over Time
Matthieu Latapy, Tiphaine Viard, Clémence Magnien

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Small vulnerable sets determine large network cascades in power grids

Sometimes a power failure can be fairly local, but other times, a seemingly identical initial failure can cascade to cause a massive and costly breakdown in the system. Yang et al. built a model for the North American power grid network based on samples of data covering the years 2008 to 2013 (see the Perspective by D'Souza). Although the observed cascades were widespread, a small fraction of all network components, particularly the ones that were most cohesive within the network, were vulnerable to cascading failures. Larger cascades were associated with concurrent triggering events that were geographically closer to each other and closer to the set of vulnerable components.

 

Small vulnerable sets determine large network cascades in power grids
Yang Yang, Takashi Nishikawa, Adilson E. Motter

Science  17 Nov 2017:
Vol. 358, Issue 6365, eaan3184
DOI: 10.1126/science.aan3184

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Building Codes for Bacterial Cities | Quanta Magazine

Building Codes for Bacterial Cities | Quanta Magazine | Papers | Scoop.it
Biofilms are bacterial fortresses, but understanding how hydrodynamics and competition shape their architecture could reveal their subtle weaknesses.
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A Plea for not Watering Down the Unseemly: Reconsidering Francisco Varela’s Contribution to Science

A Plea for not Watering Down the Unseemly: Reconsidering Francisco Varela’s Contribution to Science | Papers | Scoop.it

Context: In the past three decades, the work of Varela has had an enormous impact on current developments in contemporary science. Problem: Varela’s thought was extremely complex and multifaceted, and while some aspects - notably his contributions to the autopoietic theory of living and enactivist approach to cognition - have gained widespread acclaim, others have been ignored or watered down. Method: We identify three dimensions of Varela’s thought: (i) anti-realism of the “middle way”; (ii) anti-foundationalism of the circular/recursive onto-epistemology; and (iii) ethical/social implications of the circularity/recursivity. The discussion of these dimensions is followed by a concise overview of the individual target articles in this issue and the topics they cover. Finally, we discuss in what ways the articles extend and relate to Varela’s work. We do this by means of a concrete example: the relation between “enaction” and “enactivism. Results: We show that the ignoring-cum-watering-down process of Varela’s contributions to science is at least partly linked to the three dimensions of Varela’s thought. Based on our examination we also find that the more narrow research topics are always interrelated with broader philosophical reflection. Researching into ignored and watered-down aspects of Varela’s work enables us to not only gain fresh insights into Varela’s overall philosophy and rekindle interest in the topics and themes that have been brushed aside, but also cast a fresh light on those that are currently in full bloom. Implications: Reviving interest in Varela’s work in toto could lead to fruitful research and discussion in numerous scientific fields. To illustrate this idea, we delineate, tentatively, three domains - theoretical, empirical, and existential - where Varela’s contribution to philosophy and science could instigate prolific exchange of views. Constructivist content: All three dimensions of Varela’s philosophy have strong affinities with radical constructivist critique of realism and some of its epistemological and ethical implications.

 

A Plea for not Watering Down the Unseemly: Reconsidering Francisco Varela’s Contribution to Science
Sebastjan Vörös & Alexander Riegler

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Enacting Enaction: A Dialectic Between Knowing and Being

Context: The notion of “enaction,” as originally expounded by Varela and his colleagues, was introduced into cognitive science as part of a broad philosophical framework combining science, phenomenology, and Buddhist philosophy. Its intention was to help the researchers in the field avoid falling prey to various dichotomies (mind/body, self/world, self/other) bedeviling modern philosophy and science, and serve as a “conceptual evocation” of “non-duality” or “groundlessness: an ongoing and irreducible circulation between the flux of lived experience (being) and the search of reason for conceptual invariants (knowing. Problem: It seems that, within the burgeoning field of “enactivism,” these far-reaching dimensions of the original proposal are often either dismissed or simply ignored. For this reason, the article tries to answer the following questions: Does the move away from the original exposition of enaction matter? What, if anything, has been lost along the way? What are the implications of the elements that have been discarded? Method: By drawing on some of the less well-known works of Varela, we spell out and elucidate some of the more radical aspects of the notion of enaction and the broader philosophical framework into which it was originally embedded. Results: We argue that this broader philosophical framework is of utmost importance, as it shows that enaction is only one part of the multi-layered “change in the context” that Varela felt was needed to successfully instantiate a move towards the non-dual. This “change of context” involves not only a change in the way we think about dualities, but also a change in the way we experience them. The role of new scientific metaphors, such as enaction (but also autopoiesis, embodiment, etc.), is to function as conceptual evocations of this back-and-forth exchange between knowing and being. However, if this overall framework is discarded, as is often the case in contemporary accounts, enaction loses its radical impetus and becomes mellowed down to yet another version of naturalized epistemology. Implications: Taking the notion of enaction seriously implies a radical shift in our conceptions of science and knowledge, as it encompasses a theoretical and existential move away from a detached observer to embedded and engaged cognizer. Thus, our manner of thinking can no longer be considered in isolation from our manner of being, which indicates a deep interconnection between epistemology and ethics, and may entail profound changes in the definition of the aims, methods, and values of the research community: self-transformation as a consequence of, and condition for, understanding. Constructivist content: The target article advocates a critical approach to realist presuppositions in contemporary science and philosophy, and emphasizes a deep interrelation between being and knowing, between ethics and epistemology.

 

Enacting Enaction: A Dialectic Between Knowing and Being
Sebastjan Vörös & Michel Bitbol

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Constraints on physical reality arising from a formalization of knowledge

There are (at least) four ways that an agent can acquire information concerning the state of the universe: via observation, control, prediction, or via retrodiction, i.e., memory. Each of these four ways of acquiring information seems to rely on a different kind of physical device (resp., an observation device, a control device, etc.). However it turns out that certain mathematical structure is common to those four types of device. Any device that possesses a certain subset of that structure is known as an "inference device" (ID).
Here I review some of the properties of IDs, including their relation with Turing machines, and (more loosely) quantum mechanics. I also review the bounds of the joint abilities of any set of IDs to know facts about the physical universe that contains them. These bounds constrain the possible properties of any universe that contains agents who can acquire information concerning that universe.
I then extend this previous work on IDs, by adding to the definition of IDs some of the other mathematical structure that is common to the four ways of acquiring information about the universe but is not captured in the (minimal) definition of IDs. I discuss these extensions of IDs in the context of epistemic logic (especially possible worlds formalisms like Kripke structures and Aumann structures). In particular, I show that these extensions of IDs are not subject to the problem of logical omniscience that plagues many previously studied forms of epistemic logic.

 

Constraints on physical reality arising from a formalization of knowledge
David Wolpert

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The Unforgiving Math That Stops Epidemics

The Unforgiving Math That Stops Epidemics | Papers | Scoop.it
As the annual flu season approaches, medical professionals are again encouraging people to get flu shots. Perhaps you are among those who rationalize skipping the shot on the grounds that “I never get the flu” or “if I get sick, I get sick” or “I’m healthy, so I’ll get over it.” What you might not realize is that these vaccination campaigns for flu and other diseases are about much more than your health. They’re about achieving a collective resistance to disease that goes beyond individual well-being — and that is governed by mathematical principles unforgiving of unwise individual choices.
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Phase Coexistence in Insect Swarms

Animal aggregations are visually striking, and as such are popular examples of collective behavior in the natural world. Quantitatively demonstrating the collective nature of such groups, however, remains surprisingly difficult. Inspired by thermodynamics, we applied topological data analysis to laboratory insect swarms and found evidence for emergent, material-like states. We show that the swarms consist of a core “condensed” phase surrounded by a dilute “vapor” phase. These two phases coexist in equilibrium, and maintain their distinct macroscopic properties even though individual insects pass freely between them. We further define a pressure and chemical potential to describe these phases, extending theories of active matter to aggregations of macroscopic animals and laying the groundwork for a thermodynamic description of collective animal groups.

 

Phase Coexistence in Insect Swarms
Michael Sinhuber and Nicholas T. Ouellette
Phys. Rev. Lett. 119, 178003 – Published 24 October 2017

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Measuring Influence in Science: Standing on the Shoulders of Which Giants?

I study the measurement of the influence of scientists based on bibliographic data. I propose a new measure that accounts for indirect influence and allows to compare scientists across different fields of science. By contrast, common measures of influence that "count citations", such as the h-index, are unable to satisfy either of these two properties. I use the axiomatic method in two opposite ways: to highlight the two limitations of citation-counting schemes and their independence, and to carefully justify the assumptions made in the construction of the proposed measure.

 

Measuring Influence in Science: Standing on the Shoulders of Which Giants?
Antonin Macé

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Self-referential basis of undecidable dynamics: from The Liar Paradox and The Halting Problem to The Edge of Chaos

In this paper we explore several fundamental relations between formal systems, algorithms, and dynamical systems, focussing on the roles of undecidability, universality, diagonalization, and self-reference in each of these computational frameworks. Some of these interconnections are well-known, while some are clarified in this study as a result of a fine-grained comparison between recursive formal systems, Turing machines, and Cellular Automata (CAs). In particular, we elaborate on the diagonalization argument applied to distributed computation carried out by CAs, illustrating the key elements of G\"odel's proof for CAs. The comparative analysis emphasizes three factors which underlie the capacity to generate undecidable dynamics within the examined computational frameworks: (i) the program-data duality; (ii) the potential to access an infinite computational medium; and (iii) the ability to implement negation. The considered adaptations of G\"odel's proof distinguish between computational universality and undecidability, and show how the diagonalization argument exploits, on several levels, the self-referential basis of undecidability.

 

Self-referential basis of undecidable dynamics: from The Liar Paradox and The Halting Problem to The Edge of Chaos
Mikhail Prokopenko, Michael Harré, Joseph Lizier, Fabio Boschetti, Pavlos Peppas, Stuart Kauffman

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The Trouble With Scientists

The Trouble With Scientists | Papers | Scoop.it

Sometimes it seems surprising that science functions at all. In 2005, medical science was shaken by a paper with the provocative title “Why most published research findings are false.” Written by John Ioannidis, a professor of medicine at Stanford University, it didn’t actually show that any particular result was wrong. Instead, it showed that the statistics of reported positive findings was not consistent with how often one should expect to find them. As Ioannidis concluded more recently, “many published research findings are false or exaggerated, and an estimated 85 percent of research resources are wasted.”

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Modelling the effects of phylogeny and body size on within-host pathogen replication and immune response

Understanding how quickly pathogens replicate and how quickly the immune system responds is important for predicting the epidemic spread of emerging pathogens. Host body size, through its correlation with metabolic rates, is theoretically predicted to impact pathogen replication rates and immune system response rates. Here, we use mathematical models of viral time courses from multiple species of birds infected by a generalist pathogen (West Nile Virus; WNV) to test more thoroughly how disease progression and immune response depend on mass and host phylogeny. We use hierarchical Bayesian models coupled with nonlinear dynamical models of disease dynamics to incorporate the hierarchical nature of host phylogeny. Our analysis suggests an important role for both host phylogeny and species mass in determining factors important for viral spread such as the basic reproductive number, WNV production rate, peak viraemia in blood and competency of a host to infect mosquitoes. Our model is based on a principled analysis and gives a quantitative prediction for key epidemiological determinants and how they vary with species mass and phylogeny. This leads to new hypotheses about the mechanisms that cause certain taxonomic groups to have higher viraemia. For example, our models suggest that higher viral burst sizes cause corvids to have higher levels of viraemia and that the cellular rate of virus production is lower in larger species. We derive a metric of competency of a host to infect disease vectors and thereby sustain the disease between hosts. This suggests that smaller passerine species are highly competent at spreading the disease compared with larger non-passerine species. Our models lend mechanistic insight into why some species (smaller passerine species) are pathogen reservoirs and some (larger non-passerine species) are potentially dead-end hosts for WNV. Our techniques give insights into the role of body mass and host phylogeny in the spread of WNV and potentially other zoonotic diseases. The major contribution of this work is a computational framework for infectious disease modelling at the within-host level that leverages data from multiple species. This is likely to be of interest to modellers of infectious diseases that jump species barriers and infect multiple species. Our method can be used to computationally determine the competency of a host to infect mosquitoes that will sustain WNV and other zoonotic diseases. We find that smaller passerine species are more competent in spreading the disease than larger non-passerine species. This suggests the role of host phylogeny as an important determinant of within-host pathogen replication. Ultimately, we view our work as an important step in linking within-host viral dynamics models to between-host models that determine spread of infectious disease between different hosts.

 

Modelling the effects of phylogeny and body size on within-host pathogen replication and immune response
Soumya Banerjee, Alan S. Perelson, Melanie Moses
Published 15 November 2017.DOI: 10.1098/rsif.2017.0479

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Analytical framework for the study of epidemic models on activity driven networks

Network theory has greatly contributed to an improved understanding of epidemic processes, offering an empowering framework for the analysis of real-world data, prediction of disease outbreaks, and formulation of containment strategies. However, the current state of knowledge largely relies on time-invariant networks, which are not adequate to capture several key features of a number of infectious diseases. Activity driven networks (ADNs) constitute a promising modelling framework to describe epidemic spreading over time varying networks, but a number of technical and theoretical gaps remain open. Here, we lay the foundations for a novel theory to model general epidemic spreading processes over time-varying, ADNs. Our theory derives a continuous-time model, based on ordinary differential equations (ODEs), which can reproduce the dynamics of any discrete-time epidemic model evolving over an ADN. A rigorous, formal framework is developed, so that a general epidemic process can be systematically mapped, at first, on a Markov jump process, and then, in the thermodynamic limit, on a system of ODEs. The obtained ODEs can be integrated to simulate the system dynamics, instead of using computationally intensive Monte Carlo simulations. An array of mathematical tools for the analysis of the proposed model is offered, together with techniques to approximate and predict the dynamics of the epidemic spreading, from its inception to the endemic equilibrium. The theoretical framework is illustrated step-by-step through the analysis of a susceptible–infected–susceptible process. Once the framework is established, applications to more complex epidemic models are presented, along with numerical results that corroborate the validity of our approach. Our framework is expected to find application in the study of a number of critical phenomena, including behavioural changes due to the infection, unconscious spread of the disease by exposed individuals, or the removal of nodes from the network of contacts.

 

An analytical framework for the study of epidemic models on activity driven networks
Lorenzo Zino Alessandro Rizzo Maurizio Porfiri
Journal of Complex Networks, cnx056, https://doi.org/10.1093/comnet/cnx056

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Curtailing cascading failures

Cascading behaviors are ubiquitous, from power-grid failures (1) to “flash crashes” in financial markets (2, 3) to the spread of political movements such as the “Arab Spring” (4). The causes of these cascades are varied with many unknowns, which make them extremely difficult to predict or contain. Particularly challenging are cascading failures that arise from the reorganization of flows on a network, such as in electric power grids, supply chains, and transportation networks. Here, the network edges (or “links”) have some fixed capacity, and we see that some small disturbances easily dampen out, but other seemingly similar ones lead to massive failures. On page 886 of this issue, Yang et al. (5) establish that a small “vulnerable set” of components in the power grid is implicated in large-scale outages. Although the exact elements in this set vary with operating conditions, they reveal intriguing correlations with network structure.

 

 Curtailing cascading failures
Raissa M. D'Souza

Science  17 Nov 2017:
Vol. 358, Issue 6365, pp. 860-861
DOI: 10.1126/science.aaq0474

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Re-conceptualizing the origins of life

Over the last several hundred years of scientific progress, we have arrived at a deep understanding of the non-living world. We have not yet achieved an analogous, deep understanding of the living world. The origins of life is our best chance at discovering scientific laws governing life, because it marks the point of departure from the predictable physical and chemical world to the novel, history-dependent living world. This theme issue aims to explore ways to build a deeper understanding of the nature of biology, by modelling the origins of life on a sufficiently abstract level, starting from prebiotic conditions on Earth and possibly on other planets and bridging quantitative frameworks approaching universal aspects of life. The aim of the editors is to stimulate new directions for solving the origins of life. The present introduction represents the point of view of the editors on some of the most promising future directions.

 

Re-conceptualizing the origins of life
Sara I. Walker, N. Packard, G. D. Cody
Published 13 November 2017.DOI: 10.1098/rsta.2016.0337

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The Beautiful Intelligence of Bacteria and Other Microbes

The Beautiful Intelligence of Bacteria and Other Microbes | Papers | Scoop.it
Bacterial biofilms and slime molds are more than crude patches of goo. Detailed time-lapse microscopy reveals how they sense and explore their surroundings,
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Mathematical Work of Francisco Varela

Purpose: This target article explicates mathematical themes in the work of Varela that remain of current interest in present-day second-order cybernetics. Problem: Varela’s approach extended biological autonomy to mathematical models of autonomy using reflexivity, category theory and eigenform. I will show specific ways that this mathematical modeling can contribute further to both biology and cybernetics. Method: The method of this article is to use elementary mathematics based in distinctions (and some excursions into category theory and other constructions that are also based in distinctions) to consistently make all constructions and thereby show how the observer is involved in the models that are so produced. Results: By following the line of mathematics constructed through the imagination of distinctions, we find direct access and construction for the autonomy postulated by Varela in his book Principles of Biological Autonomy. We do not need to impose autonomy at the base of the structure, but rather can construct it in the context of a reflexive domain. This sheds new light on the original approach to autonomy by Varela, who also constructed autonomous states but took them as axiomatic in his calculus for self-reference. Implications: The subject of the relationship of mathematical models, eigenforms and reflexivity should be reexamined in relation to biology, biology of cognition and cybernetics. The approach of Maturana to use only linguistic and philosophical approaches should now be reexamined and combined with Varela’s more mathematical approach and its present-day extensions.

 

Mathematical Work of Francisco Varela
Louis H. Kauffman

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Social Systems Programming I: neural and behavioral control mechanisms

Social systems can be defined as autopoietic networks of distinctions and rules that specify which actions should be performed under which conditions. Social systems have an enormous power over human individuals, as they can “program” them to sacrifice resources, happiness, loved ones and even themselves to the perpetuation of the system—as exemplified by religious celibacy, honor killings and suicide bombings. Such overriding of the biological instincts of survival and procreation demands powerful control mechanisms. The present paper surveys some of the basic neural and behavioral mechanisms used for programming within social systems, and is followed by another paper surveying emotional and structural mechanism. Basic conditioning happens through rewarding or reinforcement of socially sanctioned actions. Its power is extended by the conformist transmission of narratives that promise as yet virtual rewards, and by ritualized behaviors that suppress non-conforming beliefs through cognitive dissonance. Through such mechanisms, social systems commonly impede individual emancipation, self-actualization and societal progress.

 

Social Systems Programming I: neural and behavioral control mechanisms
Francis Heylighen, Marta Lenartowicz, Kate Kingsbury, Shima Beigi & Tjorven Harmsen
 
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It should be noted that similar mechanisms are also useful for promoting cooperation and limiting selfish behaviors.

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Dissipative structures and irreversibility in nature: Celebrating 100th birth anniversary of Ilya Prigogine (1917–2003)

Friends and colleagues who knew Ilya Prigogine well called him “A poet of thermodynamics.” It is an apt description. When Prigogine talked about thermodynamics and irreversible processes, one had the sense he understood or knew more than what his words conveyed. Natural processes all around us are irreversible; it is a fact. Their consequence is not merely to increase the entropy of the universe and destroy order. They can also do the opposite: create highly ordered complex structures with extraordinary properties and create life itself. Prigogine saw this as a profound aspect of nature that thermodynamics has revealed. When he came across the famed South Indian sculpture of Nataraja, the dancing Shiva, that depicts as a cosmic dance the perfect balance between creation and destruction that originate from the same source, he made sure he had a bronze statue of Nataraja of highest artistic quality in his art collection. A picture of it became the cover art for the book Thermodynamic Theory of Structure Stability and Fluctuations, that he coauthored with Paul Glansdorff. It was poetry of thermodynamics, creation and destruction emerging from a common source, a perfectly balanced cosmic dance. One could surmise all this from Prigogine's discourses on thermodynamics.

 

Dissipative structures and irreversibility in nature: Celebrating 100th birth anniversary of Ilya Prigogine (1917–2003)
Chaos 27, 104501 (2017); https://doi.org/10.1063/1.5008858
Dilip Kondepudi, Tomio Petrosky, and John A. Pojman

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Characterizing the structural diversity of complex networks across domains

The structure of complex networks has been of interest in many scientific and engineering disciplines over the decades. A number of studies in the field have been focused on finding the common properties among different kinds of networks such as heavy-tail degree distribution, small-worldness and modular structure and they have tried to establish a theory of structural universality in complex networks. However, there is no comprehensive study of network structure across a diverse set of domains in order to explain the structural diversity we observe in the real-world networks. In this paper, we study 986 real-world networks of diverse domains ranging from ecological food webs to online social networks along with 575 networks generated from four popular network models. Our study utilizes a number of machine learning techniques such as random forest and confusion matrix in order to show the relationships among network domains in terms of network structure. Our results indicate that there are some partitions of network categories in which networks are hard to distinguish based purely on network structure. We have found that these partitions of network categories tend to have similar underlying functions, constraints and/or generative mechanisms of networks even though networks in the same partition have different origins, e.g., biological processes, results of engineering by human being, etc. This suggests that the origin of a network, whether it's biological, technological or social, may not necessarily be a decisive factor of the formation of similar network structure. Our findings shed light on the possible direction along which we could uncover the hidden principles for the structural diversity of complex networks.

 

Characterizing the structural diversity of complex networks across domains
Kansuke Ikehara, Aaron Clauset

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Saberes Sin Fronteras OVS's curator insight, November 11, 1:49 PM

Frente a las ópticas simplificadoras, como la del separatismo catalán o el nacionalcatolicismo centralista del PP, es necesario aprender a ver la complejidad de lo real, en ciencia, educación etc. Y para eso hay que utilizar las herramientas del trabajo en RED

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Large-scale study of social network structure and team performance in a multiplayer online game

A question of interest in both theory and practice is if and how familiarity between members of a team, expressed in terms of social network structure, relates to the success of the team in a given task. In this paper we revisit this important question in a novel manner by employing game outcome statistics from Dota 2, a popular team-based multiplayer online game, combined with network data from Steam Community, a social networking service for gamers. We conduct a large-scale analysis of 4168 teams to study how network density, and the minimum and maximum degree of the within-team social network are associated with team performance, and determine how this association is moderated by team skill. We observe that minimum degree is strongly associated with good performance, especially in teams with lower skill. Together with previous results on network density that we corroborate in this paper, our findings suggest that a successful team is not only moderately connected overall, but its members should also individually have not too few nor too many within team connections.

 

Large-scale study of social network structure and team performance in a multiplayer online game
Antti Ukkonen, Juho Hamari

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Breaking the spell of nestedness

Mutualistic interactions, which are beneficial for both interacting species, are recurrently present in ecosystems. Observations of natural systems showed that, if we draw mutualistic relationships as binary links between species, the resulting bipartite network of interactions displays a widespread particular ordering called nestedness. On the other hand, theoretical works have shown that a nested structure has a positive impact on a number of relevant features ranging from species coexistence to a higher structural stability of communities and biodiversity. However, how nestedness emerges and what are its determinants, are still open challenges that have led to multiple debates to date. Here, we show, by applying a theoretical approach to the analysis of 167 real mutualistic networks, that nestedness is not an irreducible feature, but a consequence of the degree sequences of both guilds of the mutualistic network. Remarkably, we find that an outstanding majority of the analyzed networks does not show statistical significant nestedness. These findings point to the need of revising previous claims about the role of nestedness and might contribute to expanding our understanding of how evolution shapes mutualistic interactions and communities by placing the focus on the local properties rather than on global quantities.

 

Breaking the spell of nestedness
Claudia Payrato Borras, Laura Hernandez, Yamir Moreno
doi: https://doi.org/10.1101/216564

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True AI is both logically possible and utterly implausible

True AI is both logically possible and utterly implausible | Papers | Scoop.it
Machines seem to be getting smarter and smarter and much better at human jobs, yet true AI is utterly implausible. Why?
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