In one important way, the recipient of a heart transplant ignores its new organ: Its nervous system usually doesn’t rewire to communicate with it. The 40,000 neurons controlling a heart operate so perfectly, and are so self-contained, that a heart can be cut out of one body, placed into another, and continue to function perfectly, even in the absence of external control, for a decade or more. This seems necessary: The parts of our nervous system managing our most essential functions behave like a Swiss watch, precisely timed and impervious to perturbations. Chaotic behavior has been throttled out.
Or has it? Two simple pendulums that swing with perfect regularity can, when yoked together, move in a chaotic trajectory. Given that the billions of neurons in our brain are each like a pendulum, oscillating back and forth between resting and firing, and connected to 10,000 other neurons, isn’t chaos in our nervous system unavoidable?
Oscillating diurnal rhythms of gene transcription, metabolic activity, and behavior are found in all three domains of life. However, diel cycles in naturally occurring heterotrophic bacteria and archaea have rarely been observed. Here, we report time-resolved whole-genome transcriptome profiles of multiple, naturally occurring oceanic bacterial populations sampled in situ over 3 days. As anticipated, the cyanobacterial transcriptome exhibited pronounced diel periodicity. Unexpectedly, several different heterotrophic bacterioplankton groups also displayed diel cycling in many of their gene transcripts. Furthermore, diel oscillations in different heterotrophic bacterial groups suggested population-specific timing of peak transcript expression in a variety of metabolic gene suites. These staggered multispecies waves of diel gene transcription may influence both the tempo and the mode of matter and energy transformation in the sea.
Multispecies diel transcriptional oscillations in open ocean heterotrophic bacterial assemblages Elizabeth A. Ottesen, et al.
The spatial dissemination of a directly transmitted infectious disease in a population is driven by population movements from one region to another allowing mixing and importation. Public health policy and planning may thus be more accurate if reliable descriptions of population movements can be considered in the epidemic evaluations. Next to census data, generally available in developed countries, alternative solutions can be found to describe population movements where official data is missing. These include mobility models, such as the radiation model, and the analysis of mobile phone activity records providing individual geo-temporal information. Here we explore to what extent mobility proxies, such as mobile phone data or mobility models, can effectively be used in epidemic models for influenza-like-illnesses and how they compare to official census data. By focusing on three European countries, we find that phone data matches the commuting patterns reported by census well but tends to overestimate the number of commuters, leading to a faster diffusion of simulated epidemics. The order of infection of newly infected locations is however well preserved, whereas the pattern of epidemic invasion is captured with higher accuracy by the radiation model for centrally seeded epidemics and by phone proxy for peripherally seeded epidemics.
Group-level cognitive states are widely observed in human social systems, but their discussion is often ruled out a priori in quantitative approaches. In this paper, we show how reference to the irreducible mental states and psychological dynamics of a group is necessary to make sense of large scale social phenomena. We introduce the problem of mental boundaries by reference to a classic problem in the evolution of cooperation. We then provide an explicit quantitative example drawn from ongoing work on cooperation and conflict among Wikipedia editors. We show the limitations of methodological individualism, and the substantial benefits that come from being able to refer to collective intentions and attributions of cognitive states of the form "what the group believes" and "what the group values".
Mitigating traffic congestion on urban roads, with paramount importance in urban development and reduction of energy consumption and air pollution, depends on our ability to foresee road usage and traffic conditions pertaining to the collective behavior of drivers, raising a significant question: to what degree is road traffic predictable in urban areas? Here we rely on the precise records of daily vehicle mobility based on GPS positioning device installed in taxis to uncover the potential daily predictability of urban traffic patterns. Using the mapping from the degree of congestion on roads into a time series of symbols and measuring its entropy, we find a relatively high daily predictability of traffic conditions despite the absence of any a priori knowledge of drivers' origins and destinations and quite different travel patterns between weekdays and weekends. Moreover, we find a counterintuitive dependence of the predictability on travel speed: the road segment associated with intermediate average travel speed is most difficult to be predicted. We also explore the possibility of recovering the traffic condition of an inaccessible segment from its adjacent segments with respect to limited observability. The highly predictable traffic patterns in spite of the heterogeneity of drivers' behaviors and the variability of their origins and destinations enables development of accurate predictive models for eventually devising practical strategies to mitigate urban road congestion.
Predictability of road traffic and congestion in urban areas Jingyuan Wang, Yu Mao, Jing Li, Chao Li, Zhang Xiong, Wen-Xu Wang
The exponential growth in world population is feeding a steadily increasing global need for arable farmland, a resource that is already in high demand. This trend has led to increased farming on subprime arid and semi-arid lands, where limited availability of water and a host of environmental stresses often severely reduce crop productivity. The conventional approach to mitigating the abiotic stresses associated with arid climes is to breed for stress-tolerant cultivars, a time and labor intensive venture that often neglects the complex ecological context of the soil environment in which the crop is grown. In recent years, studies have attempted to identify microbial symbionts capable of conferring the same stress-tolerance to their plant hosts, and new developments in genomic technologies have greatly facilitated such research. Here, we highlight many of the advantages of these symbiont-based approaches and argue in favor of the broader recognition of crop species as ecological niches for a diverse community of microorganisms that function in concert with their plant hosts and each other to thrive under fluctuating environmental conditions.
A study led by Alfonso Valencia, Vice-Director of Basic Research at the Spanish National Cancer Research Centre (CNIO) and head of the Structural Computational Biology Group, and Michael Tress, researcher at the Group, updates the number of human genes -those that can generate proteins- to 19,000; 1,700 fewer than the genes in the most recent annotation, and well below the initial estimations of 100,000 genes. The work, published in the journal Human Molecular Genetics, concludes that almost all of these genes have ancestors prior to the appearance of primates 50 million years ago.
We present an in-depth study of co-following on Twitter based on the observation that two Twitter users whose followers have similar friends are also similar, even though they might not share any direct links or a single mutual follower. We show how this observation contributes to (i) a better understanding of language-agnostic user classification on Twitter, (ii) eliciting opportunities for Computational Social Science, and (iii) improving online marketing by identifying cross-selling opportunities.
Co-Following on Twitter Venkata Rama Kiran Garimella, Ingmar Weber
To further advance our understanding of the brain, new concepts and theories are needed. In particular, the ability of the brain to create information flows must be reconciled with its propensity for synchronization and mass action. The theoretical and empirical framework of Coordination Dynamics, a key aspect of which is metastability, are presented as a starting point to study the interplay of integrative and segregative tendencies that are expressed in space and time during the normal course of brain and behavioral function. Some recent shifts in perspective are emphasized, that may ultimately lead to a better understanding of brain complexity.
Evolutionary Robotics is a field that “aims to apply evolutionary computation techniques to evolve the overall design or controllers, or both, for real and simulated autonomous robots” (Vargas et al., 2014). This approach is “useful both for investigating the design space of robotic applications and for testing scientific hypotheses of biological mechanisms and processes” (Floreano et al., 2008). However, as noted in Bongard (2013) “the use of metaheuristics (i.e., evolution) sets this subfield of robotics apart from the mainstream of robotics research,” which “aims to continuously generate better behavior for a given robot, while the long-term goal of Evolutionary Robotics is to create general, robot-generating algorithms.”
In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal- or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to understanding how the multilayer nature of the network affects processes and dynamics.
The structure and dynamics of multilayer networks S. Boccaletti, G. Bianconi, R. Criado, C.I. del Genio, J. Gómez-Gardeñes, M. Romance, I. Sendiña-Nadal, Z. Wang, M. Zanin
Sommerfeld had been contacted by the Isar Company of Munich, which was contracted to prevent the Isar River from flooding by building up its banks. The company wanted to know at what point the river flow changed from being smooth (the technical term is “laminar”) to being turbulent, beset with eddies. That question requires some understanding of what turbulence is. Heisenberg’s work on the problem was impressive—he solved the mathematical equations of flow at the point of the laminar-to-turbulent change—and it stimulated ideas for decades afterward. But he didn’t really crack it—he couldn’t construct a comprehensive theory of turbulence.
The Internet has become an important source of information that significantly affects social, economical and political life. The content available in the Web is the basis for the operation of the digital economy. Moreover, Web content has become essential for many Web users that have to make decisions. Meanwhile, more and more often we encounter Web content of low credibility due to incorrect opinions, lack of knowledge, and, even worse, manipulation attempts for the benefit of the authors or content providers. While mechanisms for the support of credibility evaluation in practice have been proposed, little is known about their effectiveness, and about their influence on the global picture of Web content production and consumption. We use a game-theoretic model to analyze the impact of reputation on the evaluation of content credibility by consumers with varying expertise, in the presence of producers who have incentives to manipulate information.
Adam Wierzbicki, Paulina Adamska, Katarzyna Abramczuk, Thanasis Papaioannou, Karl Aberer and Emilia Rejmund (2014) Studying Web Content Credibility by Social Simulation Journal of Artificial Societies and Social Simulation 17 (3) 6 http://jasss.soc.surrey.ac.uk/17/3/6.html
Core percolation is a fundamental structural transition in complex networks related to a wide range of important problems. Recent advances have provided us an analytical framework of core percolation in uncorrelated random networks with arbitrary degree distributions. Here we apply the tools in analysis of network controllability. We confirm analytically that the emergence of the bifurcation in control coincides with the formation of the core and the structure of the core determines the control mode of the network. We also derive the analytical expression related to the controllability robustness by extending the deduction in core percolation. These findings help us better understand the interesting interplay between the structural and dynamical properties of complex networks.
Connecting Core Percolation and Controllability of Complex Networks • Tao Jia & Márton Pósfai
GitHub is the most popular repository for open source code. It has more than 3.5 million users, as the company declared in April 2013, and more than 10 million repositories, as of December 2013. It has a publicly accessible API and, since March 2012, it also publishes a stream of all the events occurring on public projects. Interactions among GitHub users are of a complex nature and take place in different forms. Developers create and fork repositories, push code, approve code pushed by others, bookmark their favorite projects and follow other developers to keep track of their activities. In this paper we present a characterization of GitHub, as both a social network and a collaborative platform. To the best of our knowledge, this is the first quantitative study about the interactions happening on GitHub. We analyze the logs from the service over 18 months (between March 11, 2012 and September 11, 2013), describing 183.54 million events and we obtain information about 2.19 million users and 5.68 million repositories, both growing linearly in time. We show that the distributions of the number of contributors per project, watchers per project and followers per user show a power-law-like shape. We analyze social ties and repository-mediated collaboration patterns, and we observe a remarkably low level of reciprocity of the social connections. We also measure the activity of each user in terms of authored events and we observe that very active users do not necessarily have a large number of followers. Finally, we provide a geographic characterization of the centers of activity and we investigate how distance influences collaboration.
Coding Together at Scale: GitHub as a Collaborative Social Network Antonio Lima, Luca Rossi, Mirco Musolesi
Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point.
While numerous changes in human lifestyle constitute modern life, our diet has been gaining attention as a potential contributor to the increase in immune-mediated diseases. The Western diet is characterized by an over consumption and reduced variety of refined sugars, salt, and saturated fat. Herein our objective is to detail the mechanisms for the Western diet’s impact on immune function. The manuscript reviews the impacts and mechanisms of harm for our over-indulgence in sugar, salt, and fat, as well as the data outlining the impacts of artificial sweeteners, gluten, and genetically modified foods; attention is given to revealing where the literature on the immune impacts of macronutrients is limited to either animal or in vitro models versus where human trials exist. Detailed attention is given to the dietary impact on the gut microbiome and the mechanisms by which our poor dietary choices are encoded into our gut, our genes, and are passed to our offspring. While today’s modern diet may provide beneficial protection from micro- and macronutrient deficiencies, our over abundance of calories and the macronutrients that compose our diet may all lead to increased inflammation, reduced control of infection, increased rates of cancer, and increased risk for allergic and auto-inflammatory disease.
Fast food fever: reviewing the impacts of the Western diet on immunity Ian A Myles
To account for the dissipative mechanisms found in nature, non-conservative elements have been incorporated in the energy redistribution rules of sandpiles and similar models of hazard phenomena. In this work, we found that incorporating non-conservation in the form of spatially-distributed sink sites affect both the external driving and internal cascade mechanisms of the sandpile. Increasing sink densities result in the loss of critical behavior, as evidenced by the gradual evolution of the avalanche size distribution from power-law (correlated) to exponential (random). For low density cases, we found no optimal configuration that will minimize the risk of producing large avalanches. Our model is inspired by analogs in natural avalanche systems, where non-conservative elements have an inherent spatial distribution.
Loss of criticality in the avalanche statistics of sandpiles with dissipative sites
Antonino A. Paguirigan Jr., Christopher P. Monterola, Rene C. Batac
The cohesive motion of autonomous agents is ubiquitous in natural, social and technological settings. Its current models are often discretized in time and include one or more of the following components: explicit velocity alignment (also called neighbor following), attraction/adhesion, inelastic collisions and friction. However, real moving agents (animals, humans, robots, etc.) are usually asynchronous and perceive the coordinates of others with higher precision than their velocities. Therefore, here we work with a minimal model that applies none of the listed components and is continuous in both time and space. The model contains (i) radial repulsion among the particles, (ii) self-propelling parallel to each particle's velocity and (iii) noise. First, we show that in this model two particles colliding symmetrically in 2 dimensions at a large angle leave at a smaller angle, i.e., their total momentum grows. For many particles we find that such local gains of momentum can lead to stable global ordering. As a function of noise amplitudes we observe a critical slowing down at the order-disorder boundary, indicating a dynamical phase transition. Our current numerical results -- limited by the system's slowing down -- show that the transition is discontinuous.
Collective motion in a minimal continuous model Illes J. Farkas, Jeromos Kun, Yi Jin, Gaoqi He, Mingliang Xu
The size of cities is known to play a fundamental role in social and economic life. Yet, its relation to the structure of the underlying network of human interactions has not been investigated empirically in detail. In this paper, we map society-wide communication networks to the urban areas of two European countries. We show that both the total number of contacts and the total communication activity grow superlinearly with city population size, according to well-defined scaling relations and resulting from a multiplicative increase that affects most citizens. Perhaps surprisingly, however, the probability that an individual's contacts are also connected with each other remains largely unaffected. These empirical results predict a systematic and scale-invariant acceleration of interaction-based spreading phenomena as cities get bigger, which is numerically confirmed by applying epidemiological models to the studied networks. Our findings should provide a microscopic basis towards understanding the superlinear increase of different socioeconomic quantities with city size, that applies to almost all urban systems and includes, for instance, the creation of new inventions or the prevalence of certain contagious diseases.
Markus Schläpfer, Luís M. A. Bettencourt, Sébastian Grauwin, Mathias Raschke, Rob Claxton, Zbigniew Smoreda, Geoffrey B. West, and Carlo Ratti The scaling of human interactions with city size J. R. Soc. Interface. 2014 11 20130789; http://dx.doi.org/10.1098/rsif.2013.0789
Mutually beneficial associations between individuals of different species, called mutualistic symbioses, have enabled major ecological innovations and underlie some of the major transitions in evolution. For example, the ancestor of plants domesticated endosymbiotic photosynthetic bacteria, today's chloroplasts, for carbon fixation. This association dramatically increased the habitat of these photosynthetic bacteria from the sea to terrestrial ecosystems. However, the colonization of land by plants required an additional symbiotic association, with fungal root symbionts that facilitate nutrient uptake. Yet, surprisingly little is known about how mutualistic symbioses evolved and persist.
The birth of cooperation Duur K. Aanen, Ton Bisseling
Sexual reproduction is an ancient feature of life on earth, and the familiar X and Y chromosomes in humans and other model species have led to the impression that sex determination mechanisms are old and conserved. In fact, males and females are determined by diverse mechanisms that evolve rapidly in many taxa. Yet this diversity in primary sex-determining signals is coupled with conserved molecular pathways that trigger male or female development. Conflicting selection on different parts of the genome and on the two sexes may drive many of these transitions, but few systems with rapid turnover of sex determination mechanisms have been rigorously studied. Here we survey our current understanding of how and why sex determination evolves in animals and plants and identify important gaps in our knowledge that present exciting research opportunities to characterize the evolutionary forces and molecular pathways underlying the evolution of sex determination.
Water flowing through a pipe is perhaps the least complicated regime in which to study turbulence. But, amazingly, researchers have still not fully explained Reynolds’ observations.
(...) It’s not that the stakes are low. A thorough explication of turbulence in pipes could help illuminate the transition to turbulence in a wide range of settings. Understanding how to minimize turbulence in air and fluids could ultimately help engineers pump oil through long pipelines more efficiently and build cars that generate less wind resistance. It could also allow them to harness turbulence more effectively in the settings in which it is helpful, as when vortices near an airplane wing pull a smooth layer of air toward the wing and allow the plane to come in for a slower and gentler landing.
We investigate the emergence and persistence of communities through a recently proposed mechanism of adaptive rewiring in coevolutionary networks. We characterize the topological structures arising in a coevolutionary network subject to an adaptive rewiring process and a node dynamics given by a simple voterlike rule. We find that, for some values of the parameters describing the adaptive rewiring process, a community structure emerges on a connected network. We show that the emergence of communities is associated to a decrease in the number of active links in the system, i.e. links that connect two nodes in different states. The lifetime of the community structure state scales exponentially with the size of the system. Additionally, we find that a small noise in the node dynamics can sustain a diversity of states and a community structure in time in a finite size system. Thus, large system size and/or local noise can explain the persistence of communities and diversity in many real systems.
Emergence and persistence of communities in coevolutionary networks J. C. González-Avella, M. G. Cosenza, J. L. Herrera, K. Tucci