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Gaming the Attention Economy

The future of human computation (HC) benefits from examining tasks that agents already perform and designing environments to give those tasks computational significance. We call this natural human computation (NHC). We consider the possible future of NHC through the lens of Swarm!, an application under development for Google Glass. Swarm! motivates users to compute the solutions to a class of economic optimization problems by engaging the attention dynamics of crowds. We argue that anticipating and managing economies of attention provides one of the most tantalizing future applications for NHC.

 

Gaming the Attention Economy
Daniel Estrada, Jonathan Lawhead

http://arxiv.org/abs/1306.6376

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The Minimal Complexity of Adapting Agents Increases with Fitness

The Minimal Complexity of Adapting Agents Increases with Fitness | Papers | Scoop.it

What is the relationship between the complexity and the fitness of evolved organisms, whether natural or artificial? It has been asserted, primarily based on empirical data, that the complexity of plants and animals increases as their fitness within a particular environment increases via evolution by natural selection. We simulate the evolution of the brains of simple organisms living in a planar maze that they have to traverse as rapidly as possible. Their connectome evolves over 10,000s of generations. We evaluate their circuit complexity, using four information-theoretical measures, including one that emphasizes the extent to which any network is an irreducible entity. We find that their minimal complexity increases with their fitness.


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Arjen ten Have's curator insight, July 14, 2013 5:25 AM

Very interesting this measure of irreducible entity, minimal complexity.

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systems. connecting matter, life, culture and technology

The journal intends to facilitate discussions of the foundations of systemic thinking whatever its approach is; papers are encouraged to ask questions like: what do different approaches have in common? What is the difference that is made when using different concepts?
 The journal intends to lay emphasis on the impact on society that various findings have, might have and shall have.
This task is a necessary task as we live in an age of global challenges that endanger the continuation of civilised life on Earth. Global challenges are complex in nature. Systemic thinking is the best method to cope with them. However, this method is in need of continuous reassessment and improvement. Our journal wants to contribute to that task.

 

Why another journal on systems?
Manfred Füllsack, Wolfgang Hofkirchner, Stefan Blachfellner, Robert M. Bichler

http://www.systems-journal.eu/index.php/systems/index

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NECO - A scalable algorithm for NEtwork COntrol

NECO - A scalable algorithm for NEtwork COntrol      
Sean P. Cornelius  and Adilson E. Motter
Protocol Exchange (2013) doi:10.1038/protex.2013.063
http://www.nature.com/protocolexchange/protocols/2747
Summary:  We present an algorithm for the control of complex networks and other nonlinear, high-dimensional dynamical systems. The algorithm is highly scalable, with the computational cost scaling as the number of dynamical variables to the power 2.5. This protocol includes ready-to-use software that can be applied to identify eligible control interventions in a general system described by coupled ordinary differential equations, whose specific form can be specified by the user.

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Citizen scientist: Out of the lab and onto the streets | New Scientist

Citizen scientist: Out of the lab and onto the streets | New Scientist | Papers | Scoop.it
With a bit of spare time, community labs and the power of the internet, anyone can do science on their own terms, says Kat Austen

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Collective Chasing Behavior between Cooperators and Defectors in the Spatial Prisoner’s Dilemma

Cooperation is one of the essential factors for all biological organisms in major evolutionary transitions. Recent studies have investigated the effect of migration for the evolution of cooperation. However, little is known about whether and how an individuals’ cooperativeness coevolves with mobility. One possibility is that mobility enhances cooperation by enabling cooperators to escape from defectors and form clusters; the other possibility is that mobility inhibits cooperation by helping the defectors to catch and exploit the groups of cooperators. In this study we investigate the coevolutionary dynamics by using the prisoner’s dilemma game model on a lattice structure. The computer simulations demonstrate that natural selection maintains cooperation in the form of evolutionary chasing between the cooperators and defectors. First, cooperative groups grow and collectively move in the same direction. Then, mutant defectors emerge and invade the cooperative groups, after which the defectors exploit the cooperators. Then other cooperative groups emerge due to mutation and the cycle is repeated. Here, it is worth noting that, as a result of natural selection, the mobility evolves towards directional migration, but not to random or completely fixed migration. Furthermore, with directional migration, the rate of global population extinction is lower when compared with other cases without the evolution of mobility (i.e., when mobility is preset to random or fixed). These findings illustrate the coevolutionary dynamics of cooperation and mobility through the directional chasing between cooperators and defectors.

 

Ichinose G, Saito M, Suzuki S (2013) Collective Chasing Behavior between Cooperators and Defectors in the Spatial Prisoner’s Dilemma. PLoS ONE 8(7): e67702. http://dx.doi.org/10.1371/journal.pone.0067702

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Luciano Lampi's curator insight, July 9, 2013 5:13 AM

are the political parties behaving like this?

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The Hitchhiker’s Guide to Adaptive Dynamics

Adaptive dynamics is a mathematical framework for studying evolution.This is a practical guide to adaptive dynamics that aims to illustrate how the methodology can be applied to the study of specific systems.

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The Global Prevalence of Intimate Partner Violence Against Women

Violence against women is a phenomenon that persists in all countries. Since the 1993 World Conference on Human Rights and the Declaration on the Elimination of Violence against Women, the international community has acknowledged that violence against women is an important public health, social policy, and human rights concern. However, documenting the magnitude of violence against women and producing reliable comparative data to guide policy and monitor progress has been difficult.

The Global Prevalence of Intimate Partner Violence Against Women
K. M. Devries et al.
Science 28 June 2013:
Vol. 340 no. 6140 pp. 1527-1528
http://dx.doi.org/10.1126/science.1240937

Complexity Digest's insight:

Many social problems are difficult to solve precisely because of lack of data. Everybody knows about violence against women, but it is appalling once the magnitude worldwide is known.

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Replication and replacement in dynamic delivery networks

In previous work we proposed a hormone-based algorithm that delivers content, and optimizes the distribution of replicas. Clients express demands by creating hormones that will be released to the network. The corresponding resources are attracted by this hormone and travel towards a higher hormone concentration. This leads to a placement of content close to their most frequent requesters. In addition to that the hormone-based delivery requires an appropriate replication and clean-up strategy to balance the replicas throughout the network without exceeding the nodes' storage limits or the networks communication capacity.

 

Replication and replacement in dynamic delivery networks
Anita Sobe and Wilfried Elmenreich

Complex Adaptive Systems Modeling 2013, 1:13 http://dx.doi.org/10.1186/2194-3206-1-13

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Data reliability in complex directed networks

The availability of data from many different sources and fields of science has made it possible to map out an increasing number of networks of contacts and interactions. However, quantifying how reliable these data are remains an open problem. From Biology to Sociology and Economy, the identification of false and missing positives has become a problem that calls for a solution. In this work we extend one of newest, best performing models -due to Guimera and Sales-Pardo in 2009- to directed networks. The new methodology is able to identify missing and spurious directed interactions, which renders it particularly useful to analyze data reliability in systems like trophic webs, gene regulatory networks, communication patterns and social systems. We also show, using real-world networks, how the method can be employed to help searching for new interactions in an efficient way.

 

Data reliability in complex directed networks

Joaquín Sanz, Emanuele Cozzo, Yamir Moreno

http://arxiv.org/abs/1306.6318

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Earth is surrounded by a 'bubble' of live bacteria - at 33 000 feet

Earth is surrounded by a 'bubble' of live bacteria - at 33 000 feet | Papers | Scoop.it

Earth’s upper atmosphere—below freezing, nearly without oxygen, flooded by UV radiation—is no place to live. But last winter, scientists from the Georgia Institute of Technology discovered that billions of bacteria actually thrive up there. Expecting only a smattering of microorganisms, the researchers flew six miles above Earth’s surface in a NASA jet plane. There, they pumped outside air through a filter to collect particles. Back on the ground, they tallied the organisms, and the count was staggering: 20 percent of what they had assumed to be just dust or other particles was alive. Earth, it seems, is surrounded by a bubble of bacteria.

 

Scientists don’t yet know what the bacteria are doing up there, but they may be essential to how the atmosphere functions, says Kostas Konstantinidis, an environmental microbiologist on the Georgia Tech team. For example, they could be responsible for recycling nutrients in the atmosphere, like they do on Earth. And similar to other particles, they could influence weather patterns by helping clouds form. However, they also may be transmitting diseases from one side of the globe to the other. The researchers found E. coli in their samples (which they think hurricanes lifted from cities), and they plan to investigate whether plagues are raining down on us. If we can find out more about the role of bacteria in the atmosphere, says Ann Womack, a microbial ecologist at the University of Oregon, scientists could even fight climate change by engineering the bacteria to break down greenhouse gases into other, less harmful compounds.


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Ed Rybicki's comment, June 25, 2013 12:39 AM
Hey, it's a microbial world - literally! From way above our heads, to way below our feet.
Dmitry Alexeev's curator insight, June 26, 2013 10:21 PM

we are everywhere)

Dmitry Alexeev's curator insight, July 28, 2013 4:31 AM

we'll have that one in our book as well

 

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Expanding the landscape of biological computation with synthetic multicellular consortia

Computation is an intrinsic attribute of biological entities. All of them gather and process information and respond in predictable ways to an uncertain external environment. Are these computations similar to those performed by artificial systems? Can a living computer be constructed following standard engineering practices? Despite the similarities between molecular networks associated to information processing and the wiring diagrams used to represent electronic circuits, major differences arise. Such differences are specially relevant while engineering molecular circuits in order to build novel functionalities. Among others, wiring molecular components within a cell becomes a great challenge as soon as the complexity of the circuit becomes larger than simple gates. An alternative approach has been recently introduced based on a non-standard approach to cellular computation. By breaking some standard assumptions of engineering design, it allows the synthesis of multicellular engineered circuits able to perform complex functions and open a novel form of computation. Here we review previous studies dealing with both natural and synthetic forms of computation. We compare different systems spanning many spatial and temporal scales and outline a possible “space” of biological forms of computation. We suggest that a novel approach to build synthetic devices using multicellular consortia allows expanding this space in new directions.

 

Expanding the landscape of biological computation with synthetic multicellular consortia
Ricard V. Solé, Javier Macia

Natural Computing
June 2013

http://link.springer.com/article/10.1007/s11047-013-9380-y

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Probing crowd density through smartphones in city-scale mass gatherings

City-scale mass gatherings attract hundreds of thousands of pedestrians. These pedestrians need to be monitored constantly to detect critical crowd situations at an early stage and to mitigate the risk that situations evolve towards dangerous incidents. Hereby, the crowd density is an important characteristics to assess the criticality of crowd situations. In this work, we consider location-aware smartphones for monitoring crowds during mass gatherings as an alternative to established video-based solutions. 

 

Probing crowd density through smartphones in city-scale mass gatherings
Martin Wirz, Tobias Franke, Daniel Roggen, Eve Mitleton-Kelly, Paul Lukowicz and Gerhard Tröster

EPJ Data Science 2013, 2:5 http://dx.doi.org/10.1140/epjds17

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Self-organization versus top-down planning in the evolution of a city

Interventions of central, top-down planning are serious limitations to the possibility of modelling the dynamics of cities. An example is the city of Paris (France), which during the 19th century experienced large modifications supervised by a central authority, the `Haussmann period'. In this article, we report an empirical analysis of more than 200 years (1789-2010) of the evolution of the street network of Paris. We show that the usual network measures display a smooth behavior and that the most important quantitative signatures of central planning is the spatial reorganization of centrality and the modification of the block shape distribution. Such effects can only be obtained by structural modifications at a large-scale level, with the creation of new roads not constrained by the existing geometry. The evolution of a city thus seems to result from the superimposition of continuous, local growth processes and punctual changes operating at large spatial scales.

 

Self-organization versus top-down planning in the evolution of a city
Marc Barthelemy, Patricia Bordin, Henri Berestycki, Maurizio Gribaudi

http://arxiv.org/abs/1307.2203

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Complexity Economics: A Different Framework for Economic Thought

This paper provides a logical framework for complexity economics. Complexity economics builds from the proposition that the economy is not necessarily in equilibrium: economic agents (firms, consumers, investors) constantly change their actions and strategies in response to the outcome they mutually create. This further changes the outcome, which requires them to adjust afresh. Agents thus live in a world where their beliefs and strategies are constantly being “tested” for survival within an outcome or “ecology” these beliefs and strategies together create. Economics has largely avoided this nonequilibrium view in the past, but if we allow it, we see patterns or phenomena not visible to equilibrium analysis. These emerge probabilistically, last for some time and dissipate, and they correspond to complex structures in other fields. We also see the economy not as something given and existing but forming from a constantly developing set of technological innovations, institutions, and arrangements that draw forth further innovations, institutions and arrangements.(...) 

 

Complexity Economics: A Different Framework for Economic Thought
W. Brian Arthur
SFI WP 13-04-012

http://www.santafe.edu/research/working-papers/abstract/36df2f7d8ecd8941d8fab92ded2c4547/

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Bill Aukett's curator insight, July 16, 2013 7:24 PM

If you've read Waldrop's account of the development of the complexity paradigm at the Sante Fe Institute (Waldrop, M, (1992) Complexity: The Emerging Science at the Edge of Chaos, Simon & Schuster, New York), the name Brian Arthur will be familiar.

Betty Cares's curator insight, July 17, 2013 6:39 AM

Another interesting paper from one of our great complexity thinkers, Brian Arthur, author of the El Farol Problem.  I will publish that here soon too!

Luciano Lampi's curator insight, July 18, 2013 5:11 AM

does democracy represent the best tool to face non-equilibrium states and emergence? 

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Realistic Control of Network Dynamics

Realistic Control of Network Dynamics, 
Sean P. Cornelius, William L. Kath, and Adilson E. Motter
Nature Communications   4,  1942 (2013)
http://www.nature.com/ncomms/2013/130627/ncomms2939/full/ncomms2939.html
Summary: Nonlinearity is a hallmark of complex systems, but has generally been regarded as an obstacle to controlling their behavior. Here Cornelius et al. show how nonlinear dynamics can be harnessed to control a network and drive it to desired states. The new approach can be used to identify control interventions in a range of large complex networks, from cells to power grids.

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Auerbach’s legacy

It is evident that throughout the world there are many towns, fewer large cities, and very few metropolises. This observation is not coincidental, but in effect follows a pattern and is often described by a power-law size distribution: that is, the probability of finding a city of size S is proportional to S-g with g being close to 2. Today, this statistical regularity is referred to as Zipf’s law for cities, being commonly attributed to the linguist and philologist George Kingsley Zipf, who originally studied the frequency of words in written texts, where he found an analogous distribution (Zipf, 2012). However, many researchers are not aware of the fact that the regularity of city sizes was described decades before by the theoretical physicist Felix Auerbach (1913). Zipf himself wrote “The first person to my knowledge to note the rectilinear distribution of communities in a country was Felix Auerbach in 1913” (2012, page 374). This year marks the centenary jubilee of this ground-breaking publication—an opportunity to review the legacy of Auerbach’s paper, which is in danger of sinking into oblivion.

 

Rybski D, 2013, "Auerbach’s legacy" Environment and Planning A 45(6) 1266 – 1268

http://www.envplan.com/abstract.cgi?id=a4678

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Synergy, redundancy, and multivariate information measures: an experimentalist’s perspective

Information theory has long been used to quantify interactions between two variables. With the rise of complex systems research, multivariate information measures have been increasingly used to investigate interactions between groups of three or more variables, often with an emphasis on so called synergistic and redundant interactions. While bivariate information measures are commonly agreed upon, the multivariate information measures in use today have been developed by many different groups, and differ in subtle, yet significant ways. Here, we will review these multivariate information measures with special emphasis paid to their relationship to synergy and redundancy, as well as examine the differences between these measures by applying them to several simple model systems. In addition to these systems, we will illustrate the usefulness of the information measures by analyzing neural spiking data from a dissociated culture through early stages of its development. Our aim is that this work will aid other researchers as they seek the best multivariate information measure for their specific research goals and system. Finally, we have made software available online which allows the user to calculate all of the information measures discussed within this paper.

 

Nicholas Timme, Wesley Alford, Benjamin Flecker, John M. Beggs
Synergy, redundancy, and multivariate information measures: an experimentalist’s perspective
Journal of Computational Neuroscience
July 2013

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Asking the Oracle

This paper presents a set of guidelines, imported from the field of forecasting, that can help social simulation and, more specifically, agent-based modelling practitioners to improve the predictive performance and the robustness of their models.

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The Nexus of Food, Energy and Water

The Nexus of Food, Energy and Water | Papers | Scoop.it

More than one billion people lack access to clean drinking water, sufficient food and electricity. Meanwhile, the global population is growing by some 80 million people every year. By 2030, the nine billion people living on earth will need 30% more water, 40% more energy and 50% more food to survive.
Given the complex relationships among all three resources -- the nexus of food, energy and water -- meeting these demands will require thinking in terms of systems, not silos. It will take collaborative approaches that embrace rather than battle natural processes. And it will mean new technologies and approaches to everything from bio-fuels to desalination. This special report, produced in coordination with Wharton's Initiative for Global Environmental Leadership (IGEL), takes a close look at the key issues.

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Evolutionary Information Theory

Evolutionary information theory is a constructive approach that studies information in the context of evolutionary processes, which are ubiquitous in nature and society. In this paper, we develop foundations of evolutionary information theory, building several measures of evolutionary information and obtaining their properties. These measures are based on mathematical models of evolutionary computations, machines and automata. 

 

Evolutionary Information Theory
Mark Burgin

Information 2013, 4(2), 124-168; http://dx.doi.org/10.3390/info4020124

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ComplexInsight's curator insight, July 1, 2013 1:07 AM

This looks very promising - one for reading list for holidays. 

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Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling

Recent work has attempted to capture the behavior of users on social media by modeling them as computational units processing information. We propose to extend this perspective by explicitly examining the predictive power of such a view. We consider a network of fifteen thousand users on Twitter over a seven week period. To evaluate the predictability of the users, we apply two contrasting modeling paradigms: computational mechanics and echo state networks. Computational mechanics seeks to construct the simplest model with the maximal predictive capability, while echo state networks relax from very complicated dynamics until predictive capability is reached. We demonstrate that the behavior of users on Twitter can be well-modeled as processes with self-feedback. We find that the two modeling approaches perform very similarly for most users, but that users where the two methods differ in performance highlight the challenges faced in applying predictive models to dynamic social data.

 

Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling

David Darmon, Jared Sylvester, Michelle Girvan, William Rand

http://arxiv.org/abs/1306.6111

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A Note on Elementary Cellular Automata Classification

We overview and compare classifications of elementary cellular automata, including Wolfram's, Wuensche's, Li and Packard, communication complexity, power spectral, topological, surface, compression, lattices, and morphological diversity classifications. This paper summarises several classifications of elementary cellular automata (ECA) and compares them with a newly proposed one, that induced by endowing rules with memory.

 

A Note on Elementary Cellular Automata Classification

Genaro J. Martinez

http://arxiv.org/abs/1306.5577

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Contagion of Cooperation in Static and Fluid Social Networks

Cooperation is essential for successful human societies. Thus, understanding how cooperative and selfish behaviors spread from person to person is a topic of theoretical and practical importance. Previous laboratory experiments provide clear evidence of social contagion in the domain of cooperation, both in fixed networks and in randomly shuffled networks, but leave open the possibility of asymmetries in the spread of cooperative and selfish behaviors. Additionally, many real human interaction structures are dynamic: we often have control over whom we interact with. Dynamic networks may differ importantly in the goals and strategic considerations they promote, and thus the question of how cooperative and selfish behaviors spread in dynamic networks remains open. Here, we address these questions with data from a social dilemma laboratory experiment. We measure the contagion of both cooperative and selfish behavior over time across three different network structures that vary in the extent to which they afford individuals control over their network ties. We find that in relatively fixed networks, both cooperative and selfish behaviors are contagious. In contrast, in more dynamic networks, selfish behavior is contagious, but cooperative behavior is not: subjects are fairly likely to switch to cooperation regardless of the behavior of their neighbors. We hypothesize that this insensitivity to the behavior of neighbors in dynamic networks is the result of subjects’ desire to attract new cooperative partners: even if many of one’s current neighbors are defectors, it may still make sense to switch to cooperation. We further hypothesize that selfishness remains contagious in dynamic networks because of the well-documented willingness of cooperators to retaliate against selfishness, even when doing so is costly. These results shed light on the contagion of cooperative behavior in fixed and fluid networks, and have implications for influence-based interventions aiming at increasing cooperative behavior.

 

Jordan JJ, Rand DG, Arbesman S, Fowler JH, Christakis NA (2013) Contagion of Cooperation in Static and Fluid Social Networks. PLoS ONE 8(6): e66199. http://dx.doi.org/10.1371/journal.pone.0066199

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wintrotech's curator insight, September 21, 2013 4:40 AM

the new domain hasing and domain selection is always help in good domain rankinh.

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The Origins of Scaling in Cities

Despite the increasing importance of cities in human societies, our ability to understand them scientifically and manage them in practice has remained limited. The greatest difficulties to any scientific approach to cities have resulted from their many interdependent facets, as social, economic, infrastructural, and spatial complex systems that exist in similar but changing forms over a huge range of scales. Here, I show how all cities may evolve according to a small set of basic principles that operate locally. A theoretical framework was developed to predict the average social, spatial, and infrastructural properties of cities as a set of scaling relations that apply to all urban systems. Confirmation of these predictions was observed for thousands of cities worldwide, from many urban systems at different levels of development. Measures of urban efficiency, capturing the balance between socioeconomic outputs and infrastructural costs, were shown to be independent of city size and might be a useful means to evaluate urban planning strategies.

 

The Origins of Scaling in Cities
Luís M. A. Bettencourt

Science 21 June 2013:
Vol. 340 no. 6139 pp. 1438-1441
http://dx.doi.org/10.1126/science.1235823

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