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Estimating Potential Infection Transmission Routes in Hospital Wards Using Wearable Proximity Sensors

Wearable sensors represent a novel tool for the measurement of contact patterns in hospitals. The collected data can provide information on important aspects that impact the spreading patterns of infectious diseases, such as the strong heterogeneity of contact numbers and durations across individuals, the variability in the number of contacts during a day, and the fraction of repeated contacts across days. This variability is however associated with a marked statistical stability of contact and mixing patterns across days. Our results highlight the need for such measurement efforts in order to correctly inform mathematical models of HAIs and use them to inform the design and evaluation of prevention strategies. Vanhems P, Barrat A, Cattuto C, Pinton J-F, Khanafer N, et al. (2013) Estimating Potential Infection Transmission Routes in Hospital Wards Using Wearable Proximity Sensors. PLoS ONE 8(9): e73970. http://dx.doi.org/10.1371/journal.pone.0073970
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18 Things Highly Creative People Do Differently

18 Things Highly Creative People Do Differently | Complex Network Science | Scoop.it
“ Creativity works in mysterious and often paradoxical ways. Creative thinking is a stable, defining characteristic in some personalities, but it may also change based on situation and context. Inspiration and ideas often arise seemingly out of nowhere...”
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FuturICT: Manifesto of computational social science

FuturICT: Manifesto of computational social science | Complex Network Science | Scoop.it
R. Conte, N. Gilbert, G. Bonelli, C. Cioffi-Revilla, G. Deffuant, J. Kertesz, V. Loreto, S. Moat, J. -P. Nadal, A. Sanchez, A. Nowak, A. Flache, M. San Miguel, D. Helbing Abstract. The increasing integration of technology into our lives has created unprecedented volumes of data on society’s everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems, within the realms of a new discipline known as Computational Social Science. Against a background of financial crises, riots and international epidemics, the urgent need for a greater comprehension of the complexity of our interconnected global society and an ability to apply such insights in policy decisions is clear. This manifesto outlines the objectives of this new scientific direction, considering the challenges involved in it, and the extensive impact on science, technology and society that the success of this endeavour is likely to bring about.
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Tree rings map 700 years of Asian monsoons for the first time

Tree rings map 700 years of Asian monsoons for the first time | Complex Network Science | Scoop.it
Tree-ring data from more than 300 sites in Asia have allowed scientists to piece together a year-by-year history of the region's monsoon rains as far back as 1300 AD.The new database, called the Monsoon Asia Drought Atlas, is important because the summer monsoon, which affects half of the world's population, is little understood by climate modellers. In fact, says tree-ring expert Edward Cook, the models are poor enough that they don't even agree on whether global climate change will strengthen the Asian monsoon or weaken it. "That gives you an idea of just how difficult the problem is," he says.The problem, says Cook — who is director of the Tree-Ring Laboratory at Columbia University's Lamont-Doherty Earth Observatory in Palisades, New York, and lead author of the monsoon study — is that the good weather records that are necessary for validating climate models don't exist for much of Asia before about 1950. Filling this gap, he says, is one of the reasons his team compiled the drought atlas, the first analysis of which is published in Science1.The data were compiled from tree-ring chronologies showing the year-to-year growth of ancient trees at 327 sites. Although these sites are, by necessity, clustered in regions where there are old trees, the rest of the map can be filled in by statistical analyses, explains Cook. These analyses used tree-ring data from recent years, comparing them to existing weather data to find correlations with the older data and so extrapolate to the regions for which no such records were available.In addition to mapping annual rainfall across thousands of kilometres of Asia, encompassing the Indian, east Asian and Australian monsoon areas, the team also correlated rainfall patterns with nearly 150 years of sea-surface-temperature recordings throughout the Pacific and Atlantic oceans.
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Haunted by His Brother, He Revolutionized Physics

Haunted by His Brother, He Revolutionized Physics | Complex Network Science | Scoop.it
Time. As a physicist, Wheeler had always been curious to untangle the nature of that mysterious dimension. But now, in the wake of Joe’s death, it was personal.Wheeler would spend the rest of his life struggling against time. His journals, which he always kept at hand (and which today are stashed, unpublished, in the archives of the American Philosophical Society Library in Philadelphia), reveal a stunning portrait of an obsessed thinker, ever-aware of his looming mortality, caught in a race against time to answer not a question, but the question: “How come existence?”“Of all obstacles to a thoroughly penetrating account of existence, none looms up more dismayingly than ‘time,’” Wheeler wrote. “Explain time? Not without explaining existence. Explain existence? Not without explaining time.”
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The Uses of Big Data in Cities

There is much enthusiasm currently about the possibilities created by new and more extensive sources of data to better understand and manage cities. Here, I explore how big data can be useful in urban planning by formalizing the planning process as a general computational problem. I show that, under general conditions, new sources of data coordinated with urban policy can be applied following fundamental principles of engineering to achieve new solutions to important age-old urban problems. I also show, that comprehensive urban planning is computationally intractable (i.e. practically impossible) in large cities, regardless of the amounts of data available. This dilemma between the need for planning and coordination and its impossibility in detail is resolved by the recognition that cities are first and foremost self-organizing social networks embedded in space and enabled by urban infrastructure and services. As such the primary role of big data in cities is to facilitate information flows and mechanisms of learning and coordination by heterogeneous individuals. However, processes of self-organization in cities, as well as of service improvement and expansion, must rely on general principles that enforce necessary conditions for cities to operate and evolve. Such ideas are the core a developing scientific theory of cities, which is itself enabled by the growing availability of quantitative data on thousands of cities worldwide, across different geographies and levels of development. These three uses of data and information technologies in cities constitute then the necessary pillars for more successful urban policy and management that encourages, and does not stifle, the fundamental role of cities as engines of development and innovation in human societies. The Uses of Big Data in Cities Luís M. A. Bettencourt http://www.santafe.edu/research/working-papers/abstract/1c669193b79cb42f44ce5e0e63928bb0/
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The diminishing role of hubs in dynamical processes on complex networks

It is notoriously difficult to predict the behaviour of a complex self-organizing system, where the interactions among dynamical units form a heterogeneous topology. Even if the dynamics of each microscopic unit is known, a real understanding of their contributions to the macroscopic system behaviour is still lacking. Here, we develop information-theoretical methods to distinguish the contribution of each individual unit to the collective out-of-equilibrium dynamics. We show that for a system of units connected by a network of interaction potentials with an arbitrary degree distribution, highly connected units have less impact on the system dynamics when compared with intermediately connected units. In an equilibrium setting, the hubs are often found to dictate the long-term behaviour. However, we find both analytically and experimentally that the instantaneous states of these units have a short-lasting effect on the state trajectory of the entire system. We present qualitative evidence of this phenomenon from empirical findings about a social network of product recommendations, a protein–protein interaction network and a neural network, suggesting that it might indeed be a widespread property in nature. "The diminishing role of hubs in dynamical processes on complex networks" Quax R, Apolloni A and Sloot P.M.A. Journal of the Royal Society Interface, 10, 20130568, published 4 September 2013 http://dx.doi.org/10.1098/rsif.2013.0568
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Most Influential Emotions on Social Networks Revealed (Anger > Joy)

Most Influential Emotions on Social Networks Revealed (Anger > Joy) | Complex Network Science | Scoop.it
Anger spreads faster and more broadly than joy, say computer scientists who have analysed sentiment on the Chinese Twitter-like service Weibo. One well-known feature of social networks is that similar people tend to attract each other: birds of a feather flock together. So an interesting question is whether these similarities cause people to behave in the same way online, whether it might lead to flocking or herding behaviour, for example. Today, we get an interesting insight into this phenomena thanks to the work of Rui Fan and pals at Beihang University in China. These guys have compared the way that tweets labelled with specific emotions influence other people on the network. And their conclusion is surprising. They say the results clearly show that anger is more influential than other emotions such as joy or sadness, a finding that could have significant implications for our understanding of the way information spreads through social networks. These guys got their data from Weibo, a Twitter-like service that has become hugely popular in China. In just four years, it has attracted more than 500 million users who post around 100 million messages a day. Research Paper: http://arxiv.org/abs/1309.2402 (Anger is More Influential Than Joy: Sentiment Correlation in Weibo Rui Fan, Jichang Zhao, Yan Chen, Ke Xu)
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Estimating Potential Infection Transmission Routes in Hospital Wards Using Wearable Proximity Sensors

Wearable sensors represent a novel tool for the measurement of contact patterns in hospitals. The collected data can provide information on important aspects that impact the spreading patterns of infectious diseases, such as the strong heterogeneity of contact numbers and durations across individuals, the variability in the number of contacts during a day, and the fraction of repeated contacts across days. This variability is however associated with a marked statistical stability of contact and mixing patterns across days. Our results highlight the need for such measurement efforts in order to correctly inform mathematical models of HAIs and use them to inform the design and evaluation of prevention strategies. Vanhems P, Barrat A, Cattuto C, Pinton J-F, Khanafer N, et al. (2013) Estimating Potential Infection Transmission Routes in Hospital Wards Using Wearable Proximity Sensors. PLoS ONE 8(9): e73970. http://dx.doi.org/10.1371/journal.pone.0073970
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March Nature Physics: Complex Networks in Finance issue #FuturICT

March Nature Physics: Complex Networks in Finance issue #FuturICT | Complex Network Science | Scoop.it

The 2008 financial crisis has highlighted major limitations in the modelling of financial and economic systems. However, an emerging field of research at the frontiers of both physics and economics aims to provide a more fundamental understanding of economic networks, as well as practical insights for policymakers. In this Nature Physics Focus, physicists and economists consider the state-of-the-art in the application of network science to finance.

 

 

Editorial

Net gains -p119

doi:10.1038/nphys2588

Physics — and physicists — have had much to contribute to economic and finance. Now the science of complex networks sets a way forward to understanding and managing the complex financial networks of the world's markets.

PDF (138KB)- Net gains

 

Commentaries

Network opportunity -pp121 – 122

Michele Catanzaro and Mark Buchanan

doi:10.1038/nphys2570

Our developing scientific understanding of complex networks is being usefully applied in a wide set of financial systems. What we've learned from the 2008 crisis could be the basis of better management of the economy — and a means to avert future disaster.

 

Complex derivatives -pp123 – 125

Stefano Battiston, Guido Caldarelli, Co-Pierre Georg, Robert May and Joseph Stiglitz

doi:10.1038/nphys2575

The intrinsic complexity of the financial derivatives market has emerged as both an incentive to engage in it, and a key source of its inherent instability. Regulators now faced with the challenge of taming this beast may find inspiration in the budding science of complex systems.

PDF (152KB)- Complex derivatives

 

Reconstructing a credit network -pp125 – 126

Guido Caldarelli, Alessandro Chessa, Andrea Gabrielli, Fabio Pammolli and Michelangelo Puliga

doi:10.1038/nphys2580

The science of complex networks can be usefully applied in finance, although there is limited data available with which to develop our understanding. All is not lost, however: ideas from statistical physics make it possible to reconstruct details of a financial network from partial sets of information.

Reconstructing a credit network

 

The power to control -pp126 – 128

Marco Galbiati, Danilo Delpini & Stefano Battiston

doi:10.1038/nphys2581

Understanding something of the complexity of a financial network is one thing, influencing the behaviour of that system is another. But new tools from network science define a notion of 'controllability' that, coupled with 'centrality', could prove useful to economists and financial regulators.

 


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FuturICT's curator insight, March 5, 2013 3:53 AM

Nature Physics Focus: Complex Networks in Finance

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March Nature Physics: Complex Networks in Finance issue #FuturICT

March Nature Physics: Complex Networks in Finance issue #FuturICT | Complex Network Science | Scoop.it

The 2008 financial crisis has highlighted major limitations in the modelling of financial and economic systems. However, an emerging field of research at the frontiers of both physics and economics aims to provide a more fundamental understanding of economic networks, as well as practical insights for policymakers. In this Nature Physics Focus, physicists and economists consider the state-of-the-art in the application of network science to finance.

 

 

Editorial

Net gains -p119

doi:10.1038/nphys2588

Physics — and physicists — have had much to contribute to economic and finance. Now the science of complex networks sets a way forward to understanding and managing the complex financial networks of the world's markets.

PDF (138KB)- Net gains

 

Commentaries

Network opportunity -pp121 – 122

Michele Catanzaro and Mark Buchanan

doi:10.1038/nphys2570

Our developing scientific understanding of complex networks is being usefully applied in a wide set of financial systems. What we've learned from the 2008 crisis could be the basis of better management of the economy — and a means to avert future disaster.

 

Complex derivatives -pp123 – 125

Stefano Battiston, Guido Caldarelli, Co-Pierre Georg, Robert May and Joseph Stiglitz

doi:10.1038/nphys2575

The intrinsic complexity of the financial derivatives market has emerged as both an incentive to engage in it, and a key source of its inherent instability. Regulators now faced with the challenge of taming this beast may find inspiration in the budding science of complex systems.

PDF (152KB)- Complex derivatives

 

Reconstructing a credit network -pp125 – 126

Guido Caldarelli, Alessandro Chessa, Andrea Gabrielli, Fabio Pammolli and Michelangelo Puliga

doi:10.1038/nphys2580

The science of complex networks can be usefully applied in finance, although there is limited data available with which to develop our understanding. All is not lost, however: ideas from statistical physics make it possible to reconstruct details of a financial network from partial sets of information.

Reconstructing a credit network

 

The power to control -pp126 – 128

Marco Galbiati, Danilo Delpini & Stefano Battiston

doi:10.1038/nphys2581

Understanding something of the complexity of a financial network is one thing, influencing the behaviour of that system is another. But new tools from network science define a notion of 'controllability' that, coupled with 'centrality', could prove useful to economists and financial regulators.

 


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FuturICT's curator insight, March 5, 2013 3:53 AM

Nature Physics Focus: Complex Networks in Finance

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In the next half hour, you can have access to millions of datasets, right from inside Excel

In the next half hour, you can have access to millions of datasets, right from inside Excel | Complex Network Science | Scoop.it
“ I found a great tool for integrating Quandl free, public data into Excel PowerBI. I made a quick screencast too. There are over 8,000,000 datasets ...”
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How to Save Human Lives with Complexity Science

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are not effective and sufficient to contain them. The failure of many conventional approaches results from their neglection of feedback loops, instabilities and/or cascade effects, due to which equilibrium models do often not provide a good picture of the actual system behavior. However, the complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be understood by means of complexity science, which enables one to address the aforementioned problems more successfully. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.How to Save Human Lives with Complexity ScienceDirk Helbing, Dirk Brockmann, Thomas Chadefaux, Karsten Donnay, Ulf Blanke, Olivia Woolley-Meza, Mehdi Moussaid, Anders Johansson, Jens Krause, Sebastian Schutte, Matjaz Perchttp://arxiv.org/abs/1402.7011
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Dirk Helbing on complexity in economic theory

This interview with Dirk Helbing on the Future of the economy is part of the Futurium Talking Futures interview series. More information is available here: https://ec.europa.eu/digital-agenda/futurium/en/interviews ;
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From mobile phone data to the spatial structure of cities

Pervasive infrastructures, such as cell phone networks, enable to capture large amounts of human behavioral data but also provide information about the structure of cities and their dynamical properties. In this article, we focus on these last aspects by studying phone data recorded during 55 days in 31 Spanish metropolitan areas. We first define an urban dilatation index which measures how the average distance between individuals evolves during the day, allowing us to highlight different types of city structure. We then focus on hotspots, the most crowded places in the city. We propose a parameter free method to detect them and to test the robustness of our results. The number of these hotspots scales sublinearly with the population size, a result in agreement with previous theoretical arguments and measures on employment datasets. We study the lifetime of these hotspots and show in particular that the hierarchy of permanent ones, which constitute the "heart" of the city, is very stable whatever the size of the city. The spatial structure of these hotspots is also of interest and allows us to distinguish different categories of cities, from monocentric and "segregated" where the spatial distribution is very dependent on land use, to polycentric where the spatial mixing between land uses is much more important. These results point towards the possibility of a new, quantitative classification of cities using high resolution spatio-temporal data.From mobile phone data to the spatial structure of citiesThomas Louail, Maxime Lenormand, Oliva García Cantú, Miguel Picornell, Ricardo Herranz, Enrique Frias-Martinez, José J. Ramasco, Marc Barthelemyhttp://arxiv.org/abs/1401.4540
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Using a complex system approach to address world challenges in Food and Agriculture

World food supply is crucial to the well-being of every human on the planet in the basic sense that we need food to live. It also has a profound impact on the world economy, international trade and global political stability. Furthermore, consumption of certain types and amounts foods can affect health, and the choice of livestock and plants for food production can impact sustainable use of global resources. There are communities where insufficient food causes nutritional deficiencies, and at the same time other communities eating too much food leading to obesity and accompanying diseases. These aspects reflect the utmost importance of agricultural production and conversion of commodities to food products. Moreover, all factors contributing to the food supply are interdependent, and they are an integrative part of the continuously changing, adaptive and interdependent systems in the world around us. The properties of such interdependent systems usually cannot be inferred from the properties of its parts. In addressing current challenges, like the apparent incongruences of obesity and hunger, we have to account for the complex interdependencies among areas such as physics and sociology. This is possible using the complex system approach. It encompasses an integrative multi-scale and inter-disciplinary approach. Using a complex system approach that accounts for the needs of stakeholders in the agriculture and food domain, and determines which research programs will enable these stakeholders to better anticipate emerging developments in the world around them, will enable them to determine effective intervention strategies to simultaneously optimise and safeguard their interests and the interests of the environment. Using a complex system approach to address world challenges in Food and Agriculture H.G.J. van Mil, E.A. Foegeding, E.J. Windhab, N. Perrot, E. van der Linden http://arxiv.org/abs/1309.0614
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Pedestrian, Crowd, and Evacuation Dynamics

This contribution describes efforts to model the behavior of individual pedestrians and their interactions in crowds, which generate certain kinds of self-organized patterns of motion. Moreover, this article focusses on the dynamics of crowds in panic or evacuation situations, methods to optimize building designs for egress, and factors potentially causing the breakdown of orderly motion. Pedestrian, Crowd, and Evacuation Dynamics Dirk Helbing, Anders Johansson http://arxiv.org/abs/1309.1609
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Human mobility and time spent at destination: Impact on spatial epidemic spreading

Host mobility plays a fundamental role in the spatial spread of infectious diseases. Previous theoretical works based on the integration of network theory into the metapopulation framework have shown that the heterogeneities that characterize real mobility networks favor the propagation of epidemics. Nevertheless, the studies conducted so far assumed the mobility process to be either Markovian or non-Markovian with a fixed traveling time scale. Available statistics however show that the time spent by travelers at destination is characterized by wide fluctuations, ranging between a single day up to several months. Such varying length of stay crucially affects the chance and duration of mixing events among hosts and may therefore have a strong impact on the spread of an emerging disease. Here, we present an analytical and computational study of epidemic processes on a complex subpopulation network where travelers have memory of their origin and spend a heterogeneously distributed time interval at their destination. Through analytical calculations and numerical simulations we show that the heterogeneity of the length of stay alters the expression of the threshold between local outbreak and global invasion, and, moreover, it changes the epidemic behavior of the system in case of a global outbreak. Additionally, our theoretical framework allows us to study the effect of changes in the traveling behavior in response to the infection, by considering a scenario in which sick individuals do not leave their home location. Finally, we compare the results of our non-Markovian framework with those obtained with a classic Markovian approach and find relevant differences between the two, in the estimate of the epidemic invasion potential, as well as of the timing and the pattern of its spatial spread. Human mobility and time spent at destination: Impact on spatial epidemic spreading Chiara Poletto, Michele Tizzoni, Vittoria Colizza http://arxiv.org/abs/1309.6618
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Anger is More Influential Than Joy: Sentiment Correlation in Weibo

Recent years have witnessed the tremendous growth of the online social media. In China, Weibo, a Twitter-like service, has attracted more than 500 million users in less than four years. Connected by online social ties, different users influence each other emotionally. We find the correlation of anger among users is significantly higher than that of joy, which indicates that angry emotion could spread more quickly and broadly in the network. While the correlation of sadness is surprisingly low and highly fluctuated. Moreover, there is a stronger sentiment correlation between a pair of users if they share more interactions. And users with larger number of friends posses more significant sentiment influence to their neighborhoods. Our findings could provide insights for modeling sentiment influence and propagation in online social networks. Anger is More Influential Than Joy: Sentiment Correlation in Weibo Rui Fan, Jichang Zhao, Yan Chen, Ke Xu http://arxiv.org/abs/1309.2402
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Unlocking the Value of Personal Data: From Collection to Usage

Our world is changing. It is complex, hyperconnected, and increasingly driven by insights derived from big data.1 And the rate of change shows no sign of slowing. Nor does the volume of data show any sign of shrinking. But, the economic and social value of big data does not come just from its quantity. It also comes from its quality – the ways in which individual bits of data can be interconnected to reveal new insights with the potential to transform business and society. Fully tapping that potential holds much promise, and much risk. By themselves, technology and data are neutral. It is their use that can both generate great value and create significant harm, sometimes simultaneously. This requires a rethink of traditional approaches to data governance, particularly a shift from focusing away from trying to control the data itself to focusing on the uses of data. It is up to the individuals and institutions of various societies to govern and decide how to unlock the value – both economic and social – and ensure suitable protections.


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Modelling the Air Transport with Complex Networks: a short review

Air transport is a key infrastructure of modern societies. In this paper we review some recent approaches to air transport, which make extensive use of theory of complex networks. We discuss possible networks that can be defined for the air transport and we focus our attention to networks of airports connected by flights. We review several papers investigating the topology of these networks and their dynamics for time scales ranging from years to intraday intervals, and consider also the resilience properties of air networks to extreme events. Finally we discuss the results of some recent papers investigating the dynamics on air transport network, with emphasis on passengers traveling in the network and epidemic spreading mediated by air transport.

 

Modelling the Air Transport with Complex Networks: a short review

Massimiliano Zanin, Fabrizio Lillo

http://arxiv.org/abs/1302.7017


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