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Getting to the Root of Aging

As people live longer, the question arises of how malleable aging is and whether it can be slowed or postponed. The classic evolutionary theories of aging (1–4) provide the theoretical framework that has guided aging research for 60 years. Are the theories consistent with recent evidence?

 

Getting to the Root of Aging
Annette Baudisch, James W. Vaupel

Science 2 November 2012:
Vol. 338 no. 6107 pp. 618-619
http://dx.doi.org/10.1126/science.1226467

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Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

 

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena
Manlio De Domenico
Phys. Rev. Lett. 118, 168301

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Incoherence-Mediated Remote Synchronization

In previously identified forms of remote synchronization between two nodes, the intermediate portion of the network connecting the two nodes is not synchronized with them but generally exhibits some coherent dynamics. Here we report on a network phenomenon we call incoherence-mediated remote synchronization (IMRS), in which two noncontiguous parts of the network are identically synchronized while the dynamics of the intermediate part is statistically and information-theoretically incoherent. We identify mirror symmetry in the network structure as a mechanism allowing for such behavior, and show that IMRS is robust against dynamical noise as well as against parameter changes. IMRS may underlie neuronal information processing and potentially lead to network solutions for encryption key distribution and secure communication.

 

Incoherence-Mediated Remote Synchronization
Liyue Zhang, Adilson E. Motter, and Takashi Nishikawa
Phys. Rev. Lett. 118, 174102

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Evidence of Complex Contagion of Information in Social Media: An Experiment Using Twitter Bots

It has recently become possible to study the dynamics of information diffusion in techno-social systems at scale, due to the emergence of online platforms, such as Twitter, with millions of users. One question that systematically recurs is whether information spreads according to simple or complex dynamics: does each exposure to a piece of information have an independent probability of a user adopting it (simple contagion), or does this probability depend instead on the number of sources of exposure, increasing above some threshold (complex contagion)? Most studies to date are observational and, therefore, unable to disentangle the effects of confounding factors such as social reinforcement, homophily, limited attention, or network community structure. Here we describe a novel controlled experiment that we performed on Twitter using `social bots' deployed to carry out coordinated attempts at spreading information. We propose two Bayesian statistical models describing simple and complex contagion dynamics, and test the competing hypotheses. We provide experimental evidence that the complex contagion model describes the observed information diffusion behavior more accurately than simple contagion. Future applications of our results include more effective defenses against malicious propaganda campaigns on social media, improved marketing and advertisement strategies, and design of effective network intervention techniques.

 

Evidence of Complex Contagion of Information in Social Media: An Experiment Using Twitter Bots

Bjarke Mønsted, Piotr Sapieżyński, Emilio Ferrara, Sune Lehmann

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The world of long-range interactions: A bird's eye view

In recent years, studies of long-range interacting (LRI) systems have taken centre stage in the arena of statistical mechanics and dynamical system studies, due to new theoretical developments involving tools from as diverse a field as kinetic theory, non-equilibrium statistical mechanics, and large deviation theory, but also due to new and exciting experimental realizations of LRI systems. In this invited contribution, we discuss the general features of long-range interactions, emphasizing in particular the main physical phenomenon of non-additivity, which leads to a plethora of distinct effects, both thermodynamic and dynamic, that are not observed with short-range interactions: Ensemble inequivalence, slow relaxation, broken ergodicity. We also discuss several physical systems with long-range interactions: mean-field spin systems, self-gravitating systems, Euler equations in two dimensions, Coulomb systems, one-component electron plasma, dipolar systems, free-electron lasers, atoms trapped in optical cavities.

 

The world of long-range interactions: A bird's eye view
Shamik Gupta, Stefano Ruffo

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Robustness and efficiency in interconnected networks with changes in network assortativity

In this study, the effect of assortativity on the robustness and efficiency of interconnected networks was investigated. This involved constructing a network that possessed the desired degree of assortativity. Additionally, an interconnected network was constructed wherein the assortativity between component networks possessed the desired value. With respect to single networks, the results indicated that a decrease in assortativity provided low hop length, high information diffusion efficiency, and distribution of communication load on edges. The study also revealed that excessive assortativity led to poor network performance. In the study, the assortativity between networks was defined and the following results were demonstrated: assortative connections between networks lowered the average hop length and enhanced information diffusion efficiency, whereas disassortative connections between networks distributed the communication loads of internetwork links and enhanced robustness. Furthermore, it is necessary to carefully adjust assortativity based on the node degree distribution of networks. Finally, the application of the results to the design of robust and efficient information networks was discussed.

 

Robustness and efficiency in interconnected networks with changes in network assortativity
Masaya Murakami, Shu Ishikura, Daichi Kominami, Tetsuya Shimokawa and Masayuki Murata
Applied Network Science 2017 2:6
DOI: 10.1007/s41109-017-0025-4

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Exercise contagion in a global social network

Exercise contagion in a global social network | Papers | Scoop.it
We leveraged exogenous variation in weather patterns across geographies to identify social contagion in exercise behaviours across a global social network. We estimated these contagion effects by combining daily global weather data, which creates exogenous variation in running among friends, with data on the network ties and daily exercise patterns of ∼1.1M individuals who ran over 350M km in a global social network over 5 years. Here we show that exercise is socially contagious and that its contagiousness varies with the relative activity of and gender relationships between friends. Less active runners influence more active runners, but not the reverse. Both men and women influence men, while only women influence other women. While the Embeddedness and Structural Diversity theories of social contagion explain the influence effects we observe, the Complex Contagion theory does not. These results suggest interventions that account for social contagion will spread behaviour change more effectively.

 

Exercise contagion in a global social network
Sinan Aral & Christos Nicolaides
Nature Communications 8, Article number: 14753 (2017)
doi:10.1038/ncomms14753

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Cumulative culture can emerge from collective intelligence in animal groups

Cumulative culture can emerge from collective intelligence in animal groups | Papers | Scoop.it
Studies of collective intelligence in animal groups typically overlook potential improvement through learning. Although knowledge accumulation is recognized as a major advantage of group living within the framework of Cumulative Cultural Evolution (CCE), the interplay between CCE and collective intelligence has remained unexplored. Here, we use homing pigeons to investigate whether the repeated removal and replacement of individuals in experimental groups (a key method in testing for CCE) alters the groups’ solution efficiency over successive generations. Homing performance improves continuously over generations, and later-generation groups eventually outperform both solo individuals and fixed-membership groups. Homing routes are more similar in consecutive generations within the same chains than between chains, indicating cross-generational knowledge transfer. Our findings thus show that collective intelligence in animal groups can accumulate progressive modifications over time. Furthermore, our results satisfy the main criteria for CCE and suggest potential mechanisms for CCE that do not rely on complex cognition.

 

Cumulative culture can emerge from collective intelligence in animal groups
Takao Sasaki & Dora Biro
Nature Communications 8, Article number: 15049 (2017)
doi:10.1038/ncomms15049

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Ecosystem Earth

Ecosystem Earth | Papers | Scoop.it

An ecosystem consists of communities of interacting species and the physical environment on which they depend. Although it is well accepted that Earth consists of many different ecosystems, human societies much less readily recognize that Earth itself is an ecosystem, dependent on interacting species and consisting of finite resources. As the human population has grown and increasingly dominated available resources, “ecosystem Earth” has begun to show increasing signs of stress. Loss of biodiversity, environmental degradation, and conflict over resources among the dominant species are typical signs that a biological system is nearing a state change, which could range from collapse of the dominant species, to development of alternative biological communities, to collapse of the entire system. In this special issue, we identify our impacts on ecosystem Earth, seek to understand the barriers to change, and explore potential solutions. Decades of research on ecosystem dynamics can help to guide our thinking about a sustainable future. Bottom-up reductions in human population growth and resource consumption, changes to how we think about our place in the system, and a willingness to prioritize persistence of the other species within our biological community will lead to a healthier planetary ecosystem. It is essential that humanity begins to better appreciate our role as just one part of a large and interdependent biological community. Our ability to dominate the planet's resources makes us directly responsible for determining the future of the ecosystem on which we, and all other forms of life, depend.

 

Ecosystem Earth
Sacha Vignieri, Julia Fahrenkamp-Uppenbrink

Science  21 Apr 2017:
Vol. 356, Issue 6335, pp. 258-259
DOI: 10.1126/science.356.6335.258

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A living mesoscopic cellular automaton made of skin scales

A living mesoscopic cellular automaton made of skin scales | Papers | Scoop.it

In vertebrates, skin colour patterns emerge from nonlinear dynamical microscopic systems of cell interactions. Here we show that in ocellated lizards a quasi-hexagonal lattice of skin scales, rather than individual chromatophore cells, establishes a green and black labyrinthine pattern of skin colour. We analysed time series of lizard scale colour dynamics over four years of their development and demonstrate that this pattern is produced by a cellular automaton (a grid of elements whose states are iterated according to a set of rules based on the states of neighbouring elements) that dynamically computes the colour states of individual mesoscopic skin scales to produce the corresponding macroscopic colour pattern. Using numerical simulations and mathematical derivation, we identify how a discrete von Neumann cellular automaton emerges from a continuous Turing reaction–diffusion system. Skin thickness variation generated by three-dimensional morphogenesis of skin scales causes the underlying reaction–diffusion dynamics to separate into microscopic and mesoscopic spatial scales, the latter generating a cellular automaton. Our study indicates that cellular automata are not merely abstract computational systems, but can directly correspond to processes generated by biological evolution.

 

A living mesoscopic cellular automaton made of skin scales

Liana Manukyan, Sophie A. Montandon, Anamarija Fofonjka, Stanislav Smirnov & Michel C. Milinkovitch

Nature 544, 173–179 (13 April 2017) doi:10.1038/nature22031

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The evolution of extreme cooperation via shared dysphoric experiences

Willingness to lay down one’s life for a group of non-kin, well documented historically and ethnographically, represents an evolutionary puzzle. Building on research in social psychology, we develop a mathematical model showing how conditioning cooperation on previous shared experience can allow individually costly pro-group behavior to evolve. The model generates a series of predictions that we then test empirically in a range of special sample populations (including military veterans, college fraternity/sorority members, football fans, martial arts practitioners, and twins). Our empirical results show that sharing painful experiences produces “identity fusion” – a visceral sense of oneness – which in turn can motivate self-sacrifice, including willingness to fight and die for the group. Practically, our account of how shared dysphoric experiences produce identity fusion helps us better understand such pressing social issues as suicide terrorism, holy wars, sectarian violence, gang-related violence, and other forms of intergroup conflict.

 

The evolution of extreme cooperation via shared dysphoric experiences
Harvey Whitehouse, Jonathan Jong, Michael D. Buhrmester, Ángel Gómez, Brock Bastian, Christopher M. Kavanagh, Martha Newson, Miriam Matthews, Jonathan A. Lanman, Ryan McKay & Sergey Gavrilets

Scientific Reports 7, Article number: 44292 (2017)
doi:10.1038/srep44292

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New article reveals the algorithmic nature of the human mind 

Random Item Generation tasks (RIG) are commonly used to assess high cognitive abilities such as inhibition or sustained attention. They also draw upon our approximate sense of complexity. A detrimental effect of ageing on pseudo-random productions has been demonstrated for some tasks, but little is as yet known about the developmental curve of cognitive complexity over the lifespan. We investigate the complexity trajectory across the lifespan of human responses to five common RIG tasks, using a large sample (n = 3429). Our main finding is that the developmental curve of the estimated algorithmic complexity of responses is similar to what may be expected of a measure of higher cognitive abilities, with a performance peak around 25 and a decline starting around 60, suggesting that RIG tasks yield good estimates of such cognitive abilities. Our study illustrates that very short strings of, i.e., 10 items, are sufficient to have their complexity reliably estimated and to allow the documentation of an age-dependent decline in the approximate sense of complexity.

 

Original article: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005408

 An animated video from the authors show the approach taken to conduct the experiment: https://www.youtube.com/watch?v=E-YjBE5qm7c

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Unearthing democracy's roots

For decades, archaeologists thought democratic republics such as classical Athens and medieval Venice were a purely European phenomenon. Conventional wisdom held that in premodern, non-Western societies, despots simply extracted labor and wealth from their subjects. But archaeologists have identified several societies in pre-Columbian Mesoamerica that upend that model. They argue that societies such as Tlaxcallan in the central Mexican highlands and Tres Zapotes along the Mexican gulf coast were organized collectively, meaning that rulers shared power and commoners had a say in the government that presided over their lives. These societies were not necessarily full democracies in which citizens cast votes, but they were radically different from the autocratic, inherited rule found—or assumed—in most ancient societies. Archaeologists now say that these collective societies left telltale traces in their material culture and urban planning, such as repetitive architecture, an emphasis on public space over palaces, reliance on local production over exotic trade goods, and a narrowing of wealth gaps between elites and commoners.

 

Unearthing democracy's roots
Lizzie Wade

Science  17 Mar 2017:
Vol. 355, Issue 6330, pp. 1114-1118
DOI: 10.1126/science.355.6330.1114

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There Is “Noise,” and Noise

What is noise? Common sense tells us it is a disturbance, an invasion of our perceptual space, a nuisance. But this is only part of a more complex story that the sciences and modern technologies might help us unravel. ‘Noise’ has a contextual meaning, but it also points at something ‘in nature’ (or in society)—and something that might also have a function and/or beneficial effects. In this article I show that what is categorized as ‘noise’ is there not necessarily to be removed or to be dispensed with, but to be used and taken advantage of.

 

There Is “Noise,” and Noise

Eleonora Montuschi

Perspectives on Science

March-April 2017, Vol. 25, No. 2, Pages: 204-225
Posted Online March 29, 2017.
(doi:10.1162/POSC_a_00241)

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The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System

Natural evolution has produced a tremendous diversity of functional organisms. Many believe an essential component of this process was the evolution of evolvability, whereby evolution speeds up its ability to innovate by generating a more adaptive pool of offspring. One hypothesized mechanism for evolvability is developmental canalization, wherein certain dimensions of variation become more likely to be traversed and others are prevented from being explored (e.g. offspring tend to have similarly sized legs, and mutations affect the length of both legs, not each leg individually). While ubiquitous in nature, canalization almost never evolves in computational simulations of evolution. Not only does that deprive us of in silico models in which to study the evolution of evolvability, but it also raises the question of which conditions give rise to this form of evolvability. Answering this question would shed light on why such evolvability emerged naturally and could accelerate engineering efforts to harness evolution to solve important engineering challenges. In this paper we reveal a unique system in which canalization did emerge in computational evolution. We document that genomes entrench certain dimensions of variation that were frequently explored during their evolutionary history. The genetic representation of these organisms also evolved to be highly modular and hierarchical, and we show that these organizational properties correlate with increased fitness. Interestingly, the type of computational evolutionary experiment that produced this evolvability was very different from traditional digital evolution in that there was no objective, suggesting that open-ended, divergent evolutionary processes may be necessary for the evolution of evolvability.

 

The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System
Joost Huizinga, Kenneth O. Stanley, Jeff Clune

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Evolving as a holobiont

Evolving as a holobiont | Papers | Scoop.it

Some of the most exciting recent advances in biology have been in our understanding of how the microbiome—the community of bacteria, fungi, and other single-celled microorganisms—influences host functions and behaviors. From the way we eat, to the way we think, to our susceptibility to diseases (just to name a few), the microbiome has a huge impact on human physiology. But microbiomes aren’t just for humans, or even just for mammals. The composition and function of microbiomes are critical for most animals and plants, so much so that many scientists believe that hosts and their microbiomes should be considered as single ecological unit—the holobiont. Given their ubiquity and importance, researchers are now investigating how this symbiotic relationship between hosts and microbes has evolved over time.

 

Richardson LA (2017) Evolving as a holobiont. PLoS Biol 15(2): e2002168. https://doi.org/10.1371/journal.pbio.2002168

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Reversing the irreversible: from limit cycles to emergent time symmetry

In 1979 Penrose hypothesized that the arrows of time are explained by the hypothesis that the fundamental laws are time irreversible. That is, our reversible laws, such as the standard model and general relativity are effective, and emerge from an underlying fundamental theory which is time irreversible. In Cort\^{e}s and Smolin (2014a, 2014b, 2016) we put forward a research program aiming at realizing just this. The aim is to find a fundamental description of physics above the planck scale, based on irreversible laws, from which will emerge the apparently reversible dynamics we observe on intermediate scales. Here we continue that program and note that a class of discrete dynamical systems are known to exhibit this very property: they have an underlying discrete irreversible evolution, but in the long term exhibit the properties of a time reversible system, in the form of limit cycles. We connect this to our original model proposal in Cort\^{e}s and Smolin (2014a), and show that the behaviours obtained there can be explained in terms of the same phenomenon: the attraction of the system to a basin of limit cycles, where the dynamics appears to be time reversible. Further than that, we show that our original models exhibit the very same feature: the emergence of quasi-particle excitations obtained in the earlier work in the space-time description is an expression of the system's convergence to limit cycles when seen in the causal set description.

 

Reversing the irreversible: from limit cycles to emergent time symmetry
Marina Cortês, Lee Smolin

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Where There is Life There is Mind: In Support of a Strong Life-Mind Continuity Thesis

Where There is Life There is Mind: In Support of a Strong Life-Mind Continuity Thesis | Papers | Scoop.it

This paper considers questions about continuity and discontinuity between life and mind. It begins by examining such questions from the perspective of the free energy principle (FEP). The FEP is becoming increasingly influential in neuroscience and cognitive science. It says that organisms act to maintain themselves in their expected biological and cognitive states, and that they can do so only by minimizing their free energy given that the long-term average of free energy is entropy. The paper then argues that there is no singular interpretation of the FEP for thinking about the relation between life and mind. Some FEP formulations express what we call an independence view of life and mind. One independence view is a cognitivist view of the FEP. It turns on information processing with semantic content, thus restricting the range of systems capable of exhibiting mentality. Other independence views exemplify what we call an overly generous non-cognitivist view of the FEP, and these appear to go in the opposite direction. That is, they imply that mentality is nearly everywhere. The paper proceeds to argue that non-cognitivist FEP, and its implications for thinking about the relation between life and mind, can be usefully constrained by key ideas in recent enactive approaches to cognitive science. We conclude that the most compelling account of the relationship between life and mind treats them as strongly continuous, and that this continuity is based on particular concepts of life (autopoiesis and adaptivity) and mind (basic and non-semantic).

 

Kirchhoff, M.D.; Froese, T. Where There is Life There is Mind: In Support of a Strong Life-Mind Continuity Thesis. Entropy 2017, 19, 169.

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PAFit: An R Package for Modeling and Estimating Preferential Attachment and Node Fitness in Temporal Complex Networks

Many real-world systems are profitably described as complex networks that grow over time. Preferential attachment and node fitness are two ubiquitous growth mechanisms that not only explain certain structural properties commonly observed in real-world systems, but are also tied to a number of applications in modeling and inference. While there are standard statistical packages for estimating the structural properties of complex networks, there is no corresponding package when it comes to the estimation of growth mechanisms. This paper introduces the R package PAFit, which implements well-established statistical methods for estimating preferential attachment and node fitness, as well as a number of functions for generating complex networks from these two mechanisms. The main computational part of the package is implemented in C++ with OpenMP to ensure good performance for large-scale networks. In this paper, we first introduce the main functionalities of PAFit using simulated examples, and then use the package to analyze a collaboration network between scientists in the field of complex networks.

 

PAFit: An R Package for Modeling and Estimating Preferential Attachment and Node Fitness in Temporal Complex Networks
Thong Pham, Paul Sheridan, Hidetoshi Shimodaira

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Marching for the Right to Be Wrong

Marching for the Right to Be Wrong | Papers | Scoop.it
Government, where decisions made in a moment can affect millions of people for a lifetime, needs constant reminders of its fallibility. A big part of that has to be a proper respect for the methods of science, as well as for its substantive discoveries. Psychologists assure us that human beings have a strong desire to accept things as true because we want them to be true, not only because they are the best explanation for what we observe. In the hands of policy-makers, that natural tendency can have deadly consequences. Science has developed impressive (though not infallible) techniques for correcting for such biases; our government could stand to do a bit better.
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Five hacks for digital democracy

Five hacks for digital democracy | Papers | Scoop.it
  1. Data-driven decision-making.
  2. Open government data.
  3. Responsible data use.
  4. Citizen engagement.
  5. Incentives.

 

Five hacks for digital democracy
Beth Simone Noveck

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Is Matter Conscious?

Is Matter Conscious? | Papers | Scoop.it

But perhaps consciousness is not uniquely troublesome. Going back to Gottfried Leibniz and Immanuel Kant, philosophers of science have struggled with a lesser known, but equally hard, problem of matter. What is physical matter in and of itself, behind the mathematical structure described by physics? This problem, too, seems to lie beyond the traditional methods of science, because all we can observe is what matter does, not what it is in itself—the “software” of the universe but not its ultimate “hardware.” On the surface, these problems seem entirely separate. But a closer look reveals that they might be deeply connected.

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Universal Scaling Laws in Metro Area Election Results

We explain the anomaly of election results between large cities and rural areas in terms of urban scaling in the 1948-2016 US elections and in the 2016 EU referendum of the UK. The scaling curves are all universal and depend on a single parameter only, and one of the parties always shows superlinear scaling and drives the process, while the sublinear exponent of the other party is merely the consequence of probability conservation. Based on the recently developed model of urban scaling, we give a microscopic model of voter behavior in which we replace diversity characterizing humans in creative aspects with social diversity and tolerance. The model can also predict new political developments such as the fragmentation of the left and 'the immigration paradox'.

 

Universal Scaling Laws in Metro Area Election Results

Eszter Bokányi, Zoltán Szállási, Gábor Vattay

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Using convolutional networks and satellite imagery to identify patterns in urban environments at a large scale

Urban planning applications (energy audits, investment, etc.) require an understanding of built infrastructure and its environment, i.e., both low-level, physical features (amount of vegetation, building area and geometry etc.), as well as higher-level concepts such as land use classes (which encode expert understanding of socio-economic end uses). This kind of data is expensive and labor-intensive to obtain, which limits its availability (particularly in developing countries). We analyze patterns in land use in urban neighborhoods using large-scale satellite imagery data (which is available worldwide from third-party providers) and state-of-the-art computer vision techniques based on deep convolutional neural networks. For supervision, given the limited availability of standard benchmarks for remote-sensing data, we obtain ground truth land use class labels carefully sampled from open-source surveys, in particular the Urban Atlas land classification dataset of 20 land use classes across  300 European cities. We use this data to train and compare deep architectures which have recently shown good performance on standard computer vision tasks (image classification and segmentation), including on geospatial data. Furthermore, we show that the deep representations extracted from satellite imagery of urban environments can be used to compare neighborhoods across several cities. We make our dataset available for other machine learning researchers to use for remote-sensing applications.

 

Using convolutional networks and satellite imagery to identify patterns in urban environments at a large scale
Adrian Albert, Jasleen Kaur, Marta Gonzalez

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Harnessing legal complexity

Complexity science has spread from its origins in the physical sciences into biological and social sciences (1). Increasingly, the social sciences frame policy problems from the financial system to the food system as complex adaptive systems (CAS) and urge policy-makers to design legal solutions with CAS properties in mind. What is often poorly recognized in these initiatives is that legal systems are also complex adaptive systems (2). Just as it seems unwise to pursue regulatory measures while ignoring known CAS properties of the systems targeted for regulation, so too might failure to appreciate CAS qualities of legal systems yield policies founded upon unrealistic assumptions. Despite a long empirical studies tradition in law, there has been little use of complexity science. With few robust empirical studies of legal systems as CAS, researchers are left to gesture at seemingly evident assertions, with limited scientific support. We outline a research agenda to help fill this knowledge gap and advance practical applications.

 

Harnessing legal complexity
J. B. Ruhl, Daniel Martin Katz, Michael J. Bommarito II

Science  31 Mar 2017:
Vol. 355, Issue 6332, pp. 1377-1378
DOI: 10.1126/science.aag3013

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From chaos to order in active fluids

There are few sights more spectacular than the swarming of a school of fish or a flock of birds that suddenly gives way to a directional motion. Arguably, our admiration is rooted in the surprise that individual organisms, capable of self-propulsion on their own, organize to move en masse in a coherent fashion. Coherent motion is common in a large class of biological and synthetic materials that are often referred to as active matter. Such materials consist of particles immersed in a fluid that can extract energy from their surroundings (or internal fuel) and convert it into directed motion. Living organisms, biological tissues, rods on a vibrated plate, and self-phoretic colloids are just a few examples (1). Similar to schools of fish and flocks of birds, active matter often exhibits random swarming motion (2–5) that until now was impossible to control or use. On page 1284 of this issue, Wu et al. (6) demonstrate that an active fluid can be manipulated to flow in a particular direction without any external stimuli by confining it in microchannels.

 

From chaos to order in active fluids
Alexander Morozov

Science  24 Mar 2017:
Vol. 355, Issue 6331, pp. 1262-1263
DOI: 10.1126/science.aam8998

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