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The Structure of Autocatalytic Sets: Evolvability, Enablement, and Emergence

This paper presents new results from a detailed study of the structure of autocatalytic sets. We show how autocatalytic sets can be decomposed into smaller autocatalytic subsets, and how these subsets can be identified and classified. We then argue how this has important consequences for the evolvability, enablement, and emergence of autocatalytic sets. We end with some speculation on how all this might lead to a generalized theory of autocatalytic sets, which could possibly be applied to entire ecologies or even economies.

 

The Structure of Autocatalytic Sets: Evolvability, Enablement, and Emergence
Wim Hordijk, Mike Steel and Stuart Kauffman

ACTA BIOTHEORETICA
http://dx.doi.org/10.1007/s10441-012-9165-1

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Bond Percolation on Multiplex Networks

Modern society is permeated by systems with many numbers of nodes and connections (e.g., rail networks, airports). A theoretical study of the multiplex network consisting of European Union air routes and the London rail transportation system demonstrates the fragility of such a network.

 

Bond Percolation on Multiplex Networks
A. Hackett, D. Cellai, S. Gómez, A. Arenas, and J. P. Gleeson
Phys. Rev. X 6, 021002 (2016)

http://dx.doi.org/10.1103/PhysRevX.6.021002

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Prediction of Cascading Failures in Spatial Networks

Prediction of Cascading Failures in Spatial Networks | Papers | Scoop.it
Cascading overload failures are widely found in large-scale parallel systems and remain a major threat to system reliability; therefore, they are of great concern to maintainers and managers of different systems. Accurate cascading failure prediction can provide useful information to help control networks. However, for a large, gradually growing network with increasing complexity, it is often impractical to explore the behavior of a single node from the perspective of failure propagation. Fortunately, overload failures that propagate through a network exhibit certain spatial-temporal correlations, which allows the study of a group of nodes that share common spatial and temporal characteristics. Therefore, in this study, we seek to predict the failure rates of nodes in a given group using machine-learning methods.

We simulated overload failure propagations in a weighted lattice network that start with a center attack and predicted the failure percentages of different groups of nodes that are separated by a given distance. The experimental results of a feedforward neural network (FNN), a recurrent neural network (RNN) and support vector regression (SVR) all show that these different models can accurately predict the similar behavior of nodes in a given group during cascading overload propagation.

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Merging evolutionary history into species interaction networks

The occurrence of complex networks of interactions among species not only relies on species co-occurrence, but also on inherited traits and evolutionary events imprinted in species phylogenies. The phylogenetic signal found in ecological networks suggests that evolution plays an important role in determining community assembly and hence could inform about the underpinning mechanisms.

Via Samir
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A model to identify urban traffic congestion hotspots in complex networks

Traffic congestion is one of the most notable problems arising in worldwide urban areas, importantly compromising human mobility and air quality. Current technologies to sense real-time data about cities, and its open distribution for analysis, allow the advent of new approaches for improvement and control. Here, we propose an idealized model, the Microscopic Congestion Model, based on the critical phenomena arising in complex networks, that allows to analytically predict congestion hotspots in urban environments. Results on real cities' road networks, considering, in some experiments, real-traffic data, show that the proposed model is capable of identifying susceptible junctions that might become hotspots if mobility demand increases.

 

A model to identify urban traffic congestion hotspots in complex networks
Albert Solé-Ribalta, Sergio Gómez, Alex Arenas

http://arxiv.org/abs/1604.07728

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Why we need democracy 2.0 and capitalism 2.0 to survive

The world is running into great trouble. 

The anthropocene challenges (including climate change, impending resource shortages, demographic change, conflict, financial and economic crises) call for entirely new answers. 

As a result, we are now seeing the emergence of data-driven societies around the globe. Feudalism 2.0, fascism 2.0, communism 2.0, socialism 2.0, democracy 2.0 and capitalism 2.0 can now be built. 

What framework should we choose? What would be the implications?

 

http://futurict.blogspot.ch/2016/04/why-we-need-democracy-20-and-capitalism.html

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An Experimental Study of Team Size and Performance on a Complex Task

The relationship between team size and productivity is a question of broad relevance across economics, psychology, and management science. For complex tasks, however, where both the potential benefits and costs of coordinated work increase with the number of workers, neither theoretical arguments nor empirical evidence consistently favor larger vs. smaller teams. Experimental findings, meanwhile, have relied on small groups and highly stylized tasks, hence are hard to generalize to realistic settings. Here we narrow the gap between real-world task complexity and experimental control, reporting results from an online experiment in which 47 teams of size ranging from n = 1 to 32 collaborated on a realistic crisis mapping task. We find that individuals in teams exerted lower overall effort than independent workers, in part by allocating their effort to less demanding (and less productive) sub-tasks; however, we also find that individuals in teams collaborated more with increasing team size. Directly comparing these competing effects, we find that the largest teams outperformed an equivalent number of independent workers, suggesting that gains to collaboration dominated losses to effort. Importantly, these teams also performed comparably to a field deployment of crisis mappers, suggesting that experiments of the type described here can help solve practical problems as well as advancing the science of collective intelligence.

 

Mao A, Mason W, Suri S, Watts DJ (2016) An Experimental Study of Team Size and Performance on a Complex Task. PLoS ONE 11(4): e0153048. http://dx.doi.org/10.1371/journal.pone.0153048

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Waste not, want not, emit less

Ensuring a sufficient supply of quality food for a growing human population is a major challenge, aggravated by climate change and already-strained natural resources. Food security requires production of some food surpluses to safeguard against unpredictable fluctuations (1). However, when food is wasted, not only has carbon been emitted to no avail, but disposal and decomposition in landfills create additional environmental impacts. Decreasing the current high scale of food waste is thus crucial for achieving resource-efficient, sustainable food systems (2). But, although avoiding food waste seems an obvious step toward sustainability, especially given that most people perceive wasting food as grossly unethical (3), food waste is a challenge that is not easily solved.

 

Waste not, want not, emit less
Jessica Aschemann-Witzel

Science  22 Apr 2016:
Vol. 352, Issue 6284, pp. 408-409
http://dx.doi.org/10.1126/science.aaf2978

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Understanding how biodiversity unfolds through time under neutral theory

Theoretical predictions for biodiversity patterns are typically derived under the assumption that ecological systems have reached a dynamic equilibrium. Yet, there is increasing evidence that various aspects of ecological systems, including (but not limited to) species richness, are not at equilibrium. Here, we use simulations to analyse how biodiversity patterns unfold through time. In particular, we focus on the relative time required for various biodiversity patterns (macroecological or phylogenetic) to reach equilibrium. We simulate spatially explicit metacommunities according to the Neutral Theory of Biodiversity (NTB) under three modes of speciation, which differ in how evenly a parent species is split between its two daughter species. We find that species richness stabilizes first, followed by species area relationships (SAR) and finally species abundance distributions (SAD). The difference in timing of equilibrium between these different macroecological patterns is the largest when the split of individuals between sibling species at speciation is the most uneven. Phylogenetic patterns of biodiversity take even longer to stabilize (tens to hundreds of times longer than species richness) so that equilibrium predictions from neutral theory for these patterns are unlikely to be relevant. Our results suggest that it may be unwise to assume that biodiversity patterns are at equilibrium and provide a first step in studying how these patterns unfold through time.

 

Understanding how biodiversity unfolds through time under neutral theory

Olivier Missa, Calvin Dytham, Hélène Morlon

RSTB
http://dx.doi.org/10.1098/rstb.2015.0226

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Control of complex networks requires both structure and dynamics

The study of network structure has uncovered signatures of the organization of complex systems. However, there is also a need to understand how to control them; for example, identifying strategies to revert a diseased cell to a healthy state, or a mature cell to a pluripotent state. Two recent methodologies suggest that the controllability of complex systems can be predicted solely from the graph of interactions between variables, without considering their dynamics: structural controllability and minimum dominating sets. We demonstrate that such structure-only methods fail to characterize controllability when dynamics are introduced. We study Boolean network ensembles of network motifs as well as three models of biochemical regulation: the segment polarity network in Drosophila melanogaster, the cell cycle of budding yeast Saccharomyces cerevisiae, and the floral organ arrangement in Arabidopsis thaliana. We demonstrate that structure-only methods both undershoot and overshoot the number and which sets of critical variables best control the dynamics of these models, highlighting the importance of the actual system dynamics in determining control. Our analysis further shows that the logic of automata transition functions, namely how canalizing they are, plays an important role in the extent to which structure predicts dynamics.

 

Control of complex networks requires both structure and dynamics
Alexander J. Gates & Luis M. Rocha
Scientific Reports 6, Article number: 24456 (2016)
http://dx.doi.org/10.1038/srep24456

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Topical issue: Temporal Network Theory and Applications Eur. Phys. J. B 

The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it is more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.

 

Modern temporal network theory: a colloquium*
Petter Holme

Topical issue: Temporal Network Theory and Applications
Eur. Phys. J. B (2015) 88: 234
http://dx.doi.org/10.1140/epjb/e2015-60657-4

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See Topical Issue: http://epjb.epj.org/component/toc/?task=topic&id=492

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Linking Individual and Collective Behavior in Adaptive Social Networks

Adaptive social structures are known to promote the evolution of cooperation. However, up to now the characterization of the collective, population-wide dynamics resulting from the self-organization of individual strategies on a coevolving, adaptive network has remained unfeasible. Here we establish a (reversible) link between individual (micro)behavior and collective (macro)behavior for coevolutionary processes. We demonstrate that an adaptive network transforms a two-person social dilemma locally faced by individuals into a collective dynamics that resembles that associated with an N-person coordination game, whose characterization depends sensitively on the relative time scales between the entangled behavioral and network evolutions. In particular, we show that the faster the relative rate of adaptation of the network, the smaller the critical fraction of cooperators required for cooperation to prevail, thus establishing a direct link between network adaptation and the evolution of cooperation. The framework developed here is general and may be readily applied to other dynamical processes occurring on adaptive networks, notably, the spreading of contagious diseases or the diffusion of innovations.

 

Linking Individual and Collective Behavior in Adaptive Social Networks
Flávio L. Pinheiro, Francisco C. Santos, and Jorge M. Pacheco
Phys. Rev. Lett. 116, 128702

http://dx.doi.org/10.1103/PhysRevLett.116.128702

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If networks adapt faster, then less cooperators are required for cooperation to prevail.

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Exploring the quantum speed limit with computer games

Exploring the quantum speed limit with computer games | Papers | Scoop.it

Humans routinely solve problems of immense computational complexity by intuitively forming simple, low-dimensional heuristic strategies1, 2. Citizen science (or crowd sourcing) is a way of exploiting this ability by presenting scientific research problems to non-experts. ‘Gamification’—the application of game elements in a non-game context—is . an effective tool with which to enable citizen scientists to provide solutions to research problems. The citizen science games Foldit3, EteRNA4 and EyeWire5 have been used successfully to study protein and RNA folding and neuron mapping, but so far gamification has not been applied to problems in quantum physics. Here . we report on Quantum Moves, an online platform gamifying optimization problems in quantum physics. We show that human players are able to find solutions to difficult problems associated with the task of quantum computing6. Players succeed where purely numerical optimization fails, and analyses of their solutions provide insights into the problem of optimization of a more profound and general nature. Using player strategies, we have thus developed a few-parameter heuristic optimization method that efficiently outperforms the most prominent established numerical methods. The numerical complexity associated with time-optimal solutions increases for shorter process durations. To understand this better, we produced a low-dimensional rendering of the optimization landscape. This rendering reveals why traditional optimization methods fail near the quantum speed limit (that is, the shortest process duration with perfect fidelity)7, 8, 9. Combined analyses of optimization landscapes and heuristic solution strategies may benefit wider classes of optimization problems in quantum physics and beyond.

 

Exploring the quantum speed limit with computer games
• Jens Jakob W. H. Sørensen, Mads Kock Pedersen, Michael Munch, Pinja Haikka, Jesper Halkjær Jensen, Tilo Planke, Morten Ginnerup Andreasen, Miroslav Gajdacz, Klaus Mølmer, Andreas Lieberoth & Jacob F. Sherson

Nature 532, 210–213 (14 April 2016) http://dx.doi.org/10.1038/nature17620

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A Possible Link Between Pyriproxyfen and Microcephaly

The Zika virus is the primary suspect in the large increase in microcephaly cases in 2015-6 in Brazil, however its role is unconfirmed despite individual cases of viral infections found in neural tissue. Here we consider the alternative that the insecticide pyriproxyfen, used in Brazilian drinking water for mosquito control, may actually be the cause. Pyriproxifen is an analog of juvenile hormone, which corresponds in mammals to regulatory molecules including retinoic acid, a vitamin A metabolite, with which it has cross-reactivity and whose application during development causes microcephaly. Methoprene, another juvenile hormone analog approved as an insecticide has metabolites that bind to the retinoid X receptor, and causes developmental disorders in mammals. Isotretinoin is another example of a retinoid causing microcephaly in human babies via activation of the retinoid X receptor. Moreover, tests of pyriproxyfen by the manufacturer, Sumitomo, widely quoted as giving no evidence for developmental toxicity, actually found some evidence for such an effect, including low brain mass and arhinencephaly--incomplete formation of the anterior cerebral hemispheres--in rat pups. Finally, the pyriproxyfen use in Brazil is unprecedented--it has never before been applied to a water supply on such a scale. Claims that it is not being used in Recife, the epicenter of microcephaly cases, do not distinguish the metropolitan area of Recife, where it is widely used, and the municipality, where it is not. Given this combination of information we strongly recommend that the use of pyriproxyfen in Brazil be suspended pending further investigation.

 

A Possible Link Between Pyriproxyfen and Microcephaly
Dan Evans, Fred Nijhout, Raphael Parens, Alfredo J. Morales, Yaneer Bar-Yam

http://arxiv.org/abs/1604.03834

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Competition between global and local online social networks

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probabilit

 

Competition between global and local online social networks
Kaj-Kolja Kleineberg & Marián Boguñá

Scientific Reports 6, Article number: 25116 (2016)
http://dx.doi.org/10.1038/srep25116

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Efficient network structures with separable heterogeneous connection costs

  • We provide the analytical solution for the efficient network with heterogeneous, separable connection costs.
  • The efficient network has a diameter no bigger than two and exhibits a core–periphery structure.
  • We calculate the lower bound for clustering coefficient of the efficient network.

 

Efficient network structures with separable heterogeneous connection costs
Babak Heydari, Mohsen Mosleh, Kia Dalili

Economics Letters
Volume 134, September 2015, Pages 82–85

http://dx.doi.org/10.1016/j.econlet.2015.06.014

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Spatial Patterns in Urban Systems

Understanding the morphology of an urban system is an important step toward unveiling the dynamical processes of its growth and development. At the foundation of every urban system, transportation system is undeniably a crucial component in powering the life of the entire urban system. In this work, we study the spatial pattern of 73 cities across the globe by analysing the distribution of public transport points within the cities. The analysis reveals that different spatial distributions of points could be classified into four groups with distinct features, indicating whether the points are clustered, dispersed or regularly distributed. From visual inspection, we observe that the cities with regularly distributed patterns do not have apparent centre in contrast to the other two types in which star-node structure, i.e. monocentric, can be clearly observed. Furthermore, the results provide evidence for the existence of two different types of urban system: well-planned and organically grown. We also study the spatial distribution of another important urban entity, the amenities, and find that it possesses universal properties regardless of the city's spatial pattern type. This result has one important implication that at small scale of locality, the urban dynamics cannot be controlled even though the regulation can be done at large scale of the entire urban system. The relation between the distribution of amenities within the city and its spatial pattern is also discussed.

 

Spatial Patterns in Urban Systems
Hoai Nguyen Huynh, Evgeny Makarov, Erika Fille Legara, Christopher Monterola, Lock Yue Chew

http://arxiv.org/abs/1604.07119

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Estimating biologically relevant parameters under uncertainty for experimental within-host murine West Nile virus infection

West Nile virus (WNV) causes viral encephalitis in humans, and is related to viruses such as Dengue and Zika that are also of significant public health concern. We have developed a computational method to determine characteristics of WNV infection even in the face of limited experimental data. This could be applicable to other emerging diseases like Zika virus for which there is little data. It may be particularly useful to estimate the potential rate of within-host viral reproduction early in an outbreak in order to assess the epidemic potential of emerging pathogens.

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Why Physics Is Not a Discipline 

Why Physics Is Not a Discipline  | Papers | Scoop.it

Saying that physics knows no boundaries is not the same as saying that physicists can solve everything. They too have been brought up inside a discipline, and are as prone as any of us to blunder when they step outside. The issue is not who “owns” particular problems in science, but about developing useful tools for thinking about how things work—which is what Aristotle tried to do over two millennia ago. Physics is not what happens in the Department of Physics. The world really doesn’t care about labels, and if we want to understand it then neither should we.

 

http://nautil.us/issue/35/boundaries/why-physics-is-not-a-discipline

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Marcelo Errera's curator insight, April 24, 4:09 PM
Indeed.  We just have to look back at history and make sure we are not blocking today's progress due to misconceptions of who should or should not produce understanding of Nature.  Let the scientific method decide.
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Microbiome: Eating for trillions

Microbiome: Eating for trillions | Papers | Scoop.it

Three studies investigate the bacteria in the guts of malnourished children and find that, when this microbiota is transferred into mice, supplements of certain microbes or sugars from human breast milk can restore normal growth.

 

Microbiome: Eating for trillions
Derrick M. Chu & Kjersti M. Aagaard

Nature 532, 316–317 (21 April 2016) http://dx.doi.org/10.1038/nature17887

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Parasites Are Us

Parasites Are Us | Papers | Scoop.it

But if the mitochondria are me, doesn’t this mean I have two sets of genes? Aren’t I a mosaic of both my own cellular DNA and that of my mitochondria? The fact is that all of the “others”—whether they are parasitic or mutualistic, cheaters or straight-shooters, long-term residents or one-night stands—have a significant characteristic in common: They each carry their own DNA. And this means that, for however long they are inside their host’s body, two genetically distinct organisms are living under the same skin and, to one extent or another, are biologically intertwined. Deep down, at the core of our tissue, we are a gigantic, symbiotic array, a ragtag assortment of organisms. All of these are to some degree us.

 

http://nautil.us/issue/35/boundaries/parasites-are-us

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Similarity of Symbol Frequency Distributions with Heavy Tails

Similarity of Symbol Frequency Distributions with Heavy Tails | Papers | Scoop.it

A mathematical technique for comparing large symbol sets suggests that less frequently used words are mainly responsible for the evolution of the English language over the past two centuries.

 

Similarity of Symbol Frequency Distributions with Heavy Tails
Martin Gerlach, Francesc Font-Clos, and Eduardo G. Altmann
Phys. Rev. X 6, 021009

http://dx.doi.org/10.1103/PhysRevX.6.021009

 

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Is this scaling nonlinear?

One of the most celebrated findings in complex systems in the last decade is that different indexes y (e.g., patents) scale nonlinearly with the population~x of the cities in which they appear, i.e., y∼x^β, β≠1. More recently, the generality of this finding has been questioned in studies using new databases and different definitions of city boundaries. In this paper we investigate the existence of nonlinear scaling using a probabilistic framework in which fluctuations are accounted explicitly. In particular, we show that this allows not only to (a) estimate β and confidence intervals, but also to (b) quantify the evidence in favor of β≠1 and (c) test the hypothesis that the observations are compatible with the nonlinear scaling. We employ this framework to compare 5 different models to 15 different datasets and we find that the answers to points (a)-(c) crucially depend on the fluctuations contained in the data, on how they are modeled, and on the fact that the city sizes are heavy-tailed distributed.

 

Is this scaling nonlinear?
J. C. Leitao, J.M. Miotto, M. Gerlach, E. G. Altmann

http://arxiv.org/abs/1604.02872

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The physics of multilayer networks

The study of networks plays a crucial role in investigating the structure, dynamics, and function of a wide variety of complex systems in myriad disciplines. Despite the success of traditional network analysis, standard networks provide a limited representation of these systems, which often includes different types of relationships (i.e., "multiplexity") among their constituent components and/or multiple interacting subsystems. Such structural complexity has a significant effect on both dynamics and function. Throwing away or aggregating available structural information can generate misleading results and provide a major obstacle towards attempts to understand the system under analysis. The recent "multilayer' approach for modeling networked systems explicitly allows the incorporation of multiplexity and other features of realistic networked systems. On one hand, it allows one to couple different structural relationships by encoding them in a convenient mathematical object. On the other hand, it also allows one to couple different dynamical processes on top of such interconnected structures. The resulting framework plays a crucial role in helping to achieve a thorough, accurate understanding of complex systems. The study of multilayer networks has also revealed new physical phenomena that remained hidden when using the traditional network representation of graphs. Here we survey progress towards a deeper understanding of dynamical processes on multilayer networks, and we highlight some of the physical phenomena that emerge from multilayer structure and dynamics.

 

The physics of multilayer networks
Manlio De Domenico, Clara Granell, Mason A. Porter, Alex Arenas

http://arxiv.org/abs/1604.02021#

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From Big Data To Important Information

Advances in science are being sought in newly available opportunities to collect massive quantities of data about complex systems. While key advances are being made in detailed mapping of systems, how to relate this data to solving many of the challenges facing humanity is unclear. The questions we often wish to address require identifying the impact of interventions on the system and that impact is not apparent in the detailed data that is available. Here we review key concepts and motivate a general framework for building larger scale views of complex systems and for characterizing the importance of information in physical, biological and social systems. We provide examples of its application to evolutionary biology with relevance to ecology, biodiversity, pandemics, and human lifespan, and in the context of social systems with relevance to ethnic violence, global food prices, and stock market panic. Framing scientific inquiry as an effort to determine what is important and unimportant is a means for advancing our understanding and addressing many practical concerns, such as economic development or treating disease.

 

From Big Data To Important Information
Yaneer Bar-Yam

http://arxiv.org/abs/1604.00976

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Time Slices: What Is the Duration of a Percept?

We experience the world as a seamless stream of percepts. However, intriguing illusions and recent experiments suggest that the world is not continuously translated into conscious perception. Instead, perception seems to operate in a discrete manner, just like movies appear continuous although they consist of discrete images. To explain how the temporal resolution of human vision can be fast compared to sluggish conscious perception, we propose a novel conceptual framework in which features of objects, such as their color, are quasi-continuously and unconsciously analyzed with high temporal resolution. Like other features, temporal features, such as duration, are coded as quantitative labels. When unconscious processing is “completed,” all features are simultaneously rendered conscious at discrete moments in time, sometimes even hundreds of milliseconds after stimuli were presented.

 

Time Slices: What Is the Duration of a Percept?
Michael H. Herzog, Thomas Kammer,  Frank Scharnowski

PLoS Biol 14(4): e1002433. http://dx.doi.org/10.1371/journal.pbio.1002433 

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