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Evolutionary game based control for biological systems with applications in drug delivery

Evolutionary game based control for biological systems with applications in drug delivery | Papers | Scoop.it

This paper proposes a control framework for biological systems subject to dynamics that exhibit adaptive behavior under evolutionary pressures. The control framework was formulated based on evolutionary game based modeling, which integrates both the internal dynamics and the population dynamics.

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Social status alters immune regulation and response to infection in macaques

Rhesus macaques experience variable levels of stress on the basis of their position in the social hierarchy. To examine how stress affects immune function, Snyder-Mackler et al. manipulated the social status of individual macaques (see the Perspective by Sapolsky). Social status influenced the immune system at multiple levels, from immune cell numbers to gene expression, and altered signaling pathways in a model of response to infection. Macaques possess a plastic and adaptive immune response wherein social subordination promotes antibacterial responses, whereas high social status promotes antiviral responses.
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An Economic Geography of the United States: From Commutes to Megaregions

An Economic Geography of the United States: From Commutes to Megaregions | Papers | Scoop.it

The emergence in the United States of large-scale “megaregions” centered on major metropolitan areas is a phenomenon often taken for granted in both scholarly studies and popular accounts of contemporary economic geography. This paper uses a data set of more than 4,000,000 commuter flows as the basis for an empirical approach to the identification of such megaregions. We compare a method which uses a visual heuristic for understanding areal aggregation to a method which uses a computational partitioning algorithm, and we reflect upon the strengths and limitations of both. We discuss how choices about input parameters and scale of analysis can lead to different results, and stress the importance of comparing computational results with “common sense” interpretations of geographic coherence. The results provide a new perspective on the functional economic geography of the United States from a megaregion perspective, and shed light on the old geographic problem of the division of space into areal units.

 

Dash Nelson G, Rae A (2016) An Economic Geography of the United States: From Commutes to Megaregions. PLoS ONE 11(11): e0166083. doi:10.1371/journal.pone.0166083

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Marcelo Errera's curator insight, Today, 12:16 PM
Could economy be organized otherwise ? Multi-scale activity covering an area.
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Generic temporal features of performance rankings in sports and games

Generic temporal features of performance rankings in sports and games | Papers | Scoop.it

Many complex phenomena, from trait selection in biological systems to hierarchy formation in social and economic entities, show signs of competition and heterogeneous performance in the temporal evolution of their components, which may eventually lead to stratified structures such as the worldwide wealth distribution. However, it is still unclear whether the road to hierarchical complexity is determined by the particularities of each phenomena, or if there are generic mechanisms of stratification common to many systems. Human sports and games, with their (varied but simple) rules of competition and measures of performance, serve as an ideal test-bed to look for universal features of hierarchy formation. With this goal in mind, we analyse here the behaviour of performance rankings over time of players and teams for several sports and games, and find statistical regularities in the dynamics of ranks. Specifically the rank diversity, a measure of the number of elements occupying a given rank over a length of time, has the same functional form in sports and games as in languages, another system where competition is determined by the use or disuse of grammatical structures. We use a Gaussian random walk model to reproduce the rank diversity of the studied sports and games. We also discuss the relation between rank diversity and the cumulative rank distribution. Our results support the notion that hierarchical phenomena may be driven by the same underlying mechanisms of rank formation, regardless of the nature of their components. Moreover, such regularities can in principle be used to predict lifetimes of rank occupancy, thus increasing our ability to forecast stratification in the presence of competition.

 

Generic temporal features of performance rankings in sports and games

José A Morales, Sergio Sánchez, Jorge Flores, Carlos Pineda, Carlos Gershenson, Germinal Cocho, Jerónimo Zizumbo, Rosalío F Rodríguez, Gerardo Iñiguez

EPJ Data Sci. (2016) 5: 33. doi:10.1140/epjds/s13688-016-0096-y

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Marcelo Errera's curator insight, November 29, 7:29 AM
Also on sports rank, here is contribution by the constructal point of view:

RESEARCH ARTICLE The evolution of speed, size and shape in modern athletics Jordan D. Charles, Adrian Bejan Journal of Experimental Biology 2009 212: 2419-2425; doi: 10.1242/jeb.031161

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The many facets of community detection in complex networks

Community detection, the decomposition of a graph into meaningful building blocks, has been a core research topic in network science over the past years. Since a precise notion of what constitutes a community has remained evasive, community detection algorithms have often been compared on benchmark graphs with a particular form of community structure, and classified based on the mathematical techniques they employ. However, this can be misleading because apparent similarities in their mathematical machinery can disguise entirely different objectives. Here we provide a focused review of the different motivations that underpin community detection. This problem-driven classification is useful in applied network science, where it is important to select an appropriate algorithm for the given purpose. Moreover, highlighting the different facets of community detection also delineates the many lines of research, and points out open directions and avenues for future research.

 

The many facets of community detection in complex networks
Michael T. Schaub, Jean-Charles Delvenne, Martin Rosvall, Renaud Lambiotte

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The impact of anticipation in dynamical systems

The flocking of animals is often modelled as a dynamical system, in which individuals are represented as particles whose interactions are determined by the current state of the system. Many animals, however, including humans, have predictive capabilities, and presumably base their behavioural decisions---at least partially---upon an anticipated state of their environment. We explore a minimal version of this idea in the context of particles that interact according to a pairwise potential. Anticipation enters the picture by calculating the interparticle forces from linear extrapolation of the positions some time τ into the future. Our analysis shows that for intermediate values of τ the particles rapidly form milling structures, induced by velocity alignment that emerges from the prediction. We also show that for τ>0, any dynamical system governed by an even potential becomes dissipative. These results suggest that anticipation could play an important role in collective behaviour, since it induces pattern formation and stabilises the dynamics of the system.

 

 

The impact of anticipation in dynamical systems
P. Gerlee, K. Tunstrøm, T. Lundh, B. Wennberg

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Minorities report: optimal incentives for collective intelligence

Collective intelligence is the ability of a group to perform more effectively than any individual alone. Diversity among group members is a key condition for the emergence of collective intelligence, but maintaining diversity is challenging in the face of social pressure to imitate one's peers. We investigate the role incentives play in maintaining useful diversity through an evolutionary game-theoretic model of collective prediction. We show that market-based incentive systems produce herding effects, reduce information available to the group and suppress collective intelligence. In response, we propose a new incentive scheme that rewards accurate minority predictions, and show that this produces optimal diversity and collective predictive accuracy. We conclude that real-world systems should reward those who have demonstrated accuracy when majority opinion has been in error.

 

Minorities report: optimal incentives for collective intelligence

Richard P. Mann, Dirk Helbing

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Science of the World Wide Web

Ten years ago, Wikipedia was still in its infancy (and totally dismissed by the establishment), Facebook was still restricted to university users, Twitter was in beta testing, and improving search capabilities was the topic that dominated Web conference research agendas. There were virtually no smartphones, online surveillance of activity and data storage was largely unknown beyond security services, and no one knew that being a data scientist was one day going to be “the sexiest job in the world”

 

Science of the World Wide Web
James Hendler, Wendy Hall
Science  11 Nov 2016:
Vol. 354, Issue 6313, pp. 703-704
DOI: 10.1126/science.aai9150

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Circularity and the Micro-Macro-Difference

Context: Referring to a recent proposition by Kauffman about the “fundamental nature of circularity in cybernetics and in scientific work in general,” I try to advance this insight with the help of system scientific concepts and a computational model. Problem: Often circularity seems to be taken as a metaphor that does not provide a firm epistemological base that fosters analysis. Method: The methodology builds on mathematics, computer-based modeling, and reasoning. Results: By building on conceptual suggestions for grasping the micro-macro difference of complex systems in terms of computational power, circularity can be conceived of as an emerging macro-level phenomenon. Implications: I show that the seemingly irritating - and traditionally evaded - concept of circularity is a fundamental and ubiquitous phenomenon in complex systems that can be grasped on a firm physical basis open to computational analysis. The proposal could support constructivist reasoning and help to eventually bridge the disconcerting gap between the humanities and natural sciences. Constructivist content: Circularity is a fundamental principle in the conception of second-order cybernetics and in particular in the observation of observing systems, as suggested by von Foerster. Trying to set it up on a firm analytical basis could advance the constructivist approach and further support it in becoming the contemporary scientific epistemology it deserves to be.

 

Füllsack M. (2016) Circularity and the Micro-Macro-Difference. Constructivist Foundations 12(1): 1–10. Available at http://constructivist.info/12/1/001.fuellsack

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Vocal Interactivity in-and-between Humans, Animals, and Robots

Almost all animals exploit vocal signals for a range of ecologically motivated purposes: detecting predators/prey and marking territory, expressing emotions, establishing social relations, and sharing information. Whether it is a bird raising an alarm, a whale calling to potential partners, a dog responding to human commands, a parent reading a story with a child, or a business-person accessing stock prices using Siri, vocalization provides a valuable communication channel through which behavior may be coordinated and controlled, and information may be distributed and acquired. Indeed, the ubiquity of vocal interaction has led to research across an extremely diverse array of fields, from assessing animal welfare, to understanding the precursors of human language, to developing voice-based human–machine interaction. Opportunities for cross-fertilization between these fields abound; for example, using artificial cognitive agents to investigate contemporary theories of language grounding, using machine learning to analyze different habitats or adding vocal expressivity to the next generation of language-enabled autonomous social agents. However, much of the research is conducted within well-defined disciplinary boundaries, and many fundamental issues remain. This paper attempts to redress the balance by presenting a comparative review of vocal interaction within-and-between humans, animals, and artificial agents (such as robots), and it identifies a rich set of open research questions that may benefit from an interdisciplinary analysis.

 

Vocal Interactivity in-and-between Humans, Animals, and Robots
Roger K. Moore, Ricard Marxer and Serge Thill

Front. Robot. AI, 25 October 2016 | http://dx.doi.org/10.3389/frobt.2016.00061

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Complex systems: physics beyond physics

Complex systems are characterized by specific time-dependent interactions among their many constituents. As a consequence they often manifest rich, non-trivial and unexpected behavior. Examples arise both in the physical and non-physical world. The study of complex systems forms a new interdisciplinary research area that cuts across physics, biology, ecology, economics, sociology, and the humanities. In this paper we review the essence of complex systems from a physicist's point of view, and try to clarify what makes them conceptually different from systems that are traditionally studied in physics. Our goal is to demonstrate how the dynamics of such systems may be conceptualized in quantitative and predictive terms by extending notions from statistical physics and how they can often be captured in a framework of co-evolving multiplex network structures. We mention three areas of complex-systems science that are currently studied extensively, the science of cities, dynamics of societies, and the representation of texts as evolutionary objects. We discuss why these areas form complex systems in the above sense. We argue that there exists plenty of new land for physicists to explore and that methodical and conceptual progress is needed most.

 

Complex systems: physics beyond physics

Yurij Holovatch, Ralph Kenna, Stefan Thurner

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Immigrant community integration in world cities

Migrant and hosting communities face long-term challenges in the integration process. Immigrants must adapt to new laws and ways of life, while hosts need to adjust to multicultural societies. Integration impacts many facets of life such as access to jobs, real state and public services and can be well approximated by the extent of spatial segregation of minority group residence. Here we conduct an extensive study of immigrant integration in 53 world cities by using Twitter language detection and by introducing metrics of spatial segregation. In this way, we quantify the Power of Integration of cities (their capacity to integrate diverse cultures), and characterize the relations between cultures when they act in the role of hosts and immigrants.

 

Immigrant community integration in world cities

Fabio Lamanna, Maxime Lenormand, María Henar Salas-Olmedo, Gustavo Romanillos, Bruno Gonçalves, José J. Ramasco

Complexity Digest's insight:

Spoiler: and the most integrated city according to this study is... London!

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Multiplex Modeling of the Society

The society has a multi-layered structure, where the layers represent the different contexts. To model this structure we begin with a single-layer weighted social network (WSN) model showing the Granovetterian structure. We find that when merging such WSN models, a sufficient amount of inter-layer correlation is needed to maintain the relationship between topology and link weights, while these correlations destroy the enhancement in the community overlap due to multiple layers. To resolve this, we devise a geographic multi-layer WSN model, where the indirect inter-layer correlations due to the geographic constraints of individuals enhance the overlaps between the communities and, at the same time, the Granovetterian structure is preserved. Furthermore, the network of social interactions can be considered as a multiplex from another point of view too: each layer corresponds to one communication channel and the aggregate of all them constitutes the entire social network. However, usually one has information only about one of the channels, which should be considered as a sample of the whole. Here we show by simulations and analytical methods that this sampling may lead to bias. For example, while it is expected that the degree distribution of the whole social network has a maximum at a value larger than one, we get with reasonable assumptions about the sampling process a monotonously decreasing distribution as observed in empirical studies of single channel data. We analyse the far-reaching consequences of our findings.

 

Multiplex Modeling of the Society

Janos Kertesz, Janos Torok, Yohsuke Murase, Hang-Hyun Jo, Kimmo Kaski

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nukem777's curator insight, November 12, 10:58 AM
Big takeaway: geographical distance is not "dead" and the channels matter!
Luciano Lampi's curator insight, November 13, 11:53 AM
Voting standards are very complex!

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Traffic gridlock on a honeycomb city

As a clear signature of modern urban design concepts, urban street networks in dense populated zones are evolving nowadays towards grid-like layouts with rectangular shapes, and most studies on traffic flow assume street networks as square lattices. However, ideas from forgotten design schools bring unexplored alternatives that might improve traffic flow in many circumstances. Inspired on an old and almost in oblivion urban plan, we report the behavior of the Biham-Middleton-Levine model (BML) \-- a paradigm for studying phase transitions of traffic flow \-- on a hypothetical city with a perfect honeycomb street network. In contrast with the original BML model on a square lattice, the same model on a honeycomb does not show any anisotropy or intermediate states, but a single continuous phase transition between free and totally congested flow, a transition that can be completely characterized by the tools of classical percolation. Although the transition occurs at a lower density than for the conventional BML, simple modifications, like randomly stopping the cars with a very small probability or increasing the traffic light periods, drives the model to perform better on honeycomb lattices. As traffic lights and disordered perturbations are inherent to real traffic, these results question the actual role of the square grid-like designs and suggests the honeycombs as an interesting alternative for urban planning in real cities.

 

Traffic gridlock on a honeycomb city
L.E. Olmos, J.D. Muñoz

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Visual Analysis of Nonlinear Dynamical Systems: Chaos, Fractals, Self-Similarity and the Limits of Prediction

Visual Analysis of Nonlinear Dynamical Systems: Chaos, Fractals, Self-Similarity and the Limits of Prediction | Papers | Scoop.it

Nearly all nontrivial real-world systems are nonlinear dynamical systems. Chaos describes certain nonlinear dynamical systems that have a very sensitive dependence on initial conditions. Chaotic systems are always deterministic and may be very simple, yet they produce completely unpredictable and divergent behavior. Systems of nonlinear equations are difficult to solve analytically, and scientists have relied heavily on visual and qualitative approaches to discover and analyze the dynamics of nonlinearity. Indeed, few fields have drawn as heavily from visualization methods for their seminal innovations: from strange attractors, to bifurcation diagrams, to cobweb plots, to phase diagrams and embedding. Although the social sciences are increasingly studying these types of systems, seminal concepts remain murky or loosely adopted. This article has three aims. First, it argues for several visualization methods to critically analyze and understand the behavior of nonlinear dynamical systems. Second, it uses these visualizations to introduce the foundations of nonlinear dynamics, chaos, fractals, self-similarity and the limits of prediction. Finally, it presents Pynamical, an open-source Python package to easily visualize and explore nonlinear dynamical systems’ behavior.

 

Visual Analysis of Nonlinear Dynamical Systems: Chaos, Fractals, Self-Similarity and the Limits of Prediction
Geoff Boeing

Systems 2016, 4(4), 37; doi:10.3390/systems4040037

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Marcelo Errera's curator insight, Today, 12:02 PM
Though not directly related to Constructal Law, it s a very interesting tool to communicate studies in complexity.
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X-Rule's Precursor is also Logically Universal

We re-examine the isotropic Precursor-Rule (of the anisotropic X-Rule) and show that it is also logically universal. The Precursor-Rule was selected from a sample of biased cellular automata rules classified by input-entropy. These biases followed most "Life-Like" constraints --- in particular isotropy, but not simple birth/survival logic. The Precursor-Rule was chosen for its spontaneously emergent mobile and stable patterns, gliders and eaters/reflectors, but glider-guns, originally absent, have recently been discovered, as well as other complex structures from the Game-of-Life lexicon. We demonstrate these newly discovered structures, and build the logical gates required for universality in the logical sense.

 

X-Rule's Precursor is also Logically Universal
José Manuel Gómez Soto, Andrew Wuensche

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An Information Criterion for Inferring Coupling of Distributed Dynamical Systems

The behavior of many real-world phenomena can be modeled by non-linear dynamical systems whereby a latent system state is observed through a filter. We are interested in interacting subsystems of this form, which we model by a set of coupled maps as a synchronous update graph dynamical system. Specifically, we study the structure learning problem for spatially distributed dynamical systems coupled via a directed acyclic graph. Unlike established structure learning procedures that find locally maximum posterior probabilities of a network structure containing latent variables, our work exploits the properties of dynamical systems to compute globally optimal approximations of these distributions. We arrive at this result by the use of time delay embedding theorems. Taking an information-theoretic perspective, we show that the log-likelihood has an intuitive interpretation in terms of information transfer.

 

 

An Information Criterion for Inferring Coupling of Distributed Dynamical Systems

Oliver M. Cliff, Mikhail Prokopenko and Robert Fitch

Front. Robot. AI, 28 November 2016 | http://dx.doi.org/10.3389/frobt.2016.00071

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Untangling the role of diverse social dimensions in the diffusion of microfinance

Ties between individuals on a social network can represent different dimensions of interactions, and the spreading of information and innovations on these networks could potentially be driven by some dimensions more than by others. In this paper we investigate this issue by studying the diffusion of microfinance within rural India villages and accounting for the whole multilayer structure of the underlying social networks. We define a new measure of node centrality, diffusion versatility, and show that this is a better predictor of microfinance participation rate than previously introduced measures defined on aggregated single-layer social networks. Moreover, we untangle the role played by each social dimension and find that the most prominent role is played by the nodes that are central on layers concerned with trust, shedding new light on the key triggers of the diffusion of microfinance.

 

Untangling the role of diverse social dimensions in the diffusion of microfinance
Elisa Omodei and Alex Arenas
Applied Network Science20161:14
DOI: 10.1007/s41109-016-0016-x

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Collective navigation of complex networks: Participatory greedy routing

Many networks are used to transfer information or goods, in other words, they are navigated. The larger the network, the more difficult it is to navigate efficiently. Indeed, information routing in the Internet faces serious scalability problems due to its rapid growth, recently accelerated by the rise of the Internet of Things. Large networks like the Internet can be navigated efficiently if nodes, or agents, actively forward information based on hidden maps underlying these systems. However, in reality most agents will deny to forward messages, which has a cost, and navigation is impossible. Can we design appropriate incentives that lead to participation and global navigability? Here, we present an evolutionary game where agents share the value generated by successful delivery of information or goods. We show that global navigability can emerge, but its complete breakdown is possible as well. Furthermore, we show that the system tends to self-organize into local clusters of agents who participate in the navigation. This organizational principle can be exploited to favor the emergence of global navigability in the system.

 

Collective navigation of complex networks: Participatory greedy routing

Kaj-Kolja Kleineberg, Dirk Helbing

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A Data Driven Network Approach to Rank Countries Production Diversity and Food Specialization

By Chengyi Tu, Joel Carr & Samir Suweis


The easy access to large data sets has allowed for leveraging methodology in network physics and complexity science to disentangle patterns and processes directly from the data, leading to key insights in the behavior of systems. Here we use country specific food production data to study binary and weighted topological properties of the bipartite country-food production matrix. This country-food production matrix can be: 1) transformed into overlap matrices which embed information regarding shared production of products among countries, and or shared countries for individual products, 2) identify subsets of countries which produce similar commodities or subsets of commodities shared by a given country allowing for visualization of correlations in large networks, and 3) used to rank country fitness (the ability to produce a diverse array of products weighted on the type of food commodities) and food specialization (quantified on the number of countries producing a specific food product weighted on their fitness). Our results show that, on average, countries with high fitness produce both low and high specializion food commodities, whereas nations with low fitness tend to produce a small basket of diverse food products, typically comprised of low specializion food commodities.


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Shaking up the Tree of Life

In 2010 a comparison between a Neandertal genome and genomes from people today turned up evidence of ancient liaisons, a discovery that belied the common idea that animal species can't hybridize or, if they do, will produce infertile offspring—think mules. Such reproductive isolation is part of the classic definition of a species. This discovery brought credence to other work in plants, Darwin's finches in the Galápagos Islands, tropical butterflies, mosquitoes, and a few other animals showing that hybridization was not just common, but also important in shaping evolution. The techniques that revealed the Neandertal and Denisovan legacy in our own genome are now making it possible to peer into the genomic histories of many organisms to check for interbreeding. As more examples are discovered, researchers are questioning the definition of species and rethinking whether the tree of life is really a "net" of life.

 

Shaking up the Tree of Life
Elizabeth Pennisi
Science  18 Nov 2016:
Vol. 354, Issue 6314, pp. 817-821
DOI: 10.1126/science.354.6314.817

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Traffic Games: Modeling Freeway Traffic with Game Theory

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers’ interactions.

 

Cortés-Berrueco LE, Gershenson C, Stephens CR (2016) Traffic Games: Modeling Freeway Traffic with Game Theory. PLoS ONE 11(11): e0165381. doi:10.1371/journal.pone.0165381

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Twitter Predicts Citation Rates of Ecological Research

The relationship between traditional metrics of research impact (e.g., number of citations) and alternative metrics (altmetrics) such as Twitter activity are of great interest, but remain imprecisely quantified. We used generalized linear mixed modeling to estimate the relative effects of Twitter activity, journal impact factor, and time since publication on Web of Science citation rates of 1,599 primary research articles from 20 ecology journals published from 2012–2014. We found a strong positive relationship between Twitter activity (i.e., the number of unique tweets about an article) and number of citations. Twitter activity was a more important predictor of citation rates than 5-year journal impact factor. Moreover, Twitter activity was not driven by journal impact factor; the ‘highest-impact’ journals were not necessarily the most discussed online. The effect of Twitter activity was only about a fifth as strong as time since publication; accounting for this confounding factor was critical for estimating the true effects of Twitter use. Articles in impactful journals can become heavily cited, but articles in journals with lower impact factors can generate considerable Twitter activity and also become heavily cited. Authors may benefit from establishing a strong social media presence, but should not expect research to become highly cited solely through social media promotion. Our research demonstrates that altmetrics and traditional metrics can be closely related, but not identical. We suggest that both altmetrics and traditional citation rates can be useful metrics of research impact.

 

Peoples BK, Midway SR, Sackett D, Lynch A, Cooney PB (2016) Twitter Predicts Citation Rates of Ecological Research. PLoS ONE 11(11): e0166570. doi:10.1371/journal.pone.0166570

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Scaling Law of Urban Ride Sharing

Sharing rides could drastically improve the efficiency of car and taxi transportation. Unleashing such potential, however, requires understanding how urban parameters affect the fraction of individual trips that can be shared, a quantity that we call shareability. Using data on millions of taxi trips in New York City, San Francisco, Singapore, and Vienna, we compute the shareability curves for each city, and find that a natural rescaling collapses them onto a single, universal curve. We explain this scaling law theoretically with a simple model that predicts the potential for ride sharing in any city, using a few basic urban quantities and no adjustable parameters. Accurate extrapolations of this type will help planners, transportation companies, and society at large to shape a sustainable path for urban growth.

 

Scaling Law of Urban Ride Sharing

Remi Tachet, Oleguer Sagarra, Paolo Santi, Giovanni Resta, Michael Szell, Steven Strogatz, Carlo Ratti

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An Information-theoretic Classification of Complex Systems

Using elementary cellular automata as an example, a novel, information-based classification of complex systems is proposed that circumvents the problems associated with isolating the complexity generated as a product of an initial state from that which is intrinsic to a dynamical rule. Transfer entropy variations processed by the system for different initial states split the 256 elementary rules into three information classes. These classes form a hierarchy such that coarse-graining transitions permitted among automata rules predominately occur within each information-based class, or much more rarely down the hierarchy.

 

An Information-theoretic Classification of Complex Systems

Enrico Borriello, Sara Imari Walker

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A Universal Rank-Size Law

A Universal Rank-Size Law | Papers | Scoop.it

A mere hyperbolic law, like the Zipf’s law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the “best (or optimal) distribution”, is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations.

 

Ausloos M, Cerqueti R (2016) A Universal Rank-Size Law. PLoS ONE 11(11): e0166011. doi:10.1371/journal.pone.0166011

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Marcelo Errera's curator insight, November 12, 7:11 AM
The quest for universal natural laws belongs to the discipline of Physics. Zipf's Law and the new findings of this interesting paper goes in that direction. This paper is based on an optimality criterion of entropy production.  Prof. Antonio Heitor Reis has shown that such "ad-hoc" uses of "optimality" of entropy production are not first principles. They are corollaries of the Constructal Law. (ref: http://www.sciencedirect.com/science/article/pii/S0003491614000682 )