Excerpts from Complexity Digest 2010.10 (5/11) by Bruce Hannon
A telescope for spotting global crises, The Great Beyond
Excerpt: The good news is that your future can be predicted. The bad news is that it’ll cost a billion euros. That, at least, is what a team of scientists led by Dirk Helbing of the ETH in Switzerland believes. And as they point out, a billion euros is small fare compared with the bill for the current financial crisis" which might conceivably have been anticipated with the massive social-science simulations they want to establish.
- Source: A telescope for spotting global crises, Philip Ball, The Great Beyond [Nature blog], 2010/04/30
Meaning-Making Neurons, Science
Excerpt: In The Brain and the Meaning of Life, philosopher, psychologist, and computer scientist Paul Thagard (University of Waterloo) has elegantly employed the pithiness principle. He offers a tightly reasoned, often humorous, and original contribution to the emerging practice of applying science to areas heretofore the province of philosophers, theologians, ethicists, and politicians: What is reality and how can we know it? Are mind and brain one or two? What is the source of the sense of self? What is love? What is the difference between right and wrong, and how can we know it? What is the most legitimate form of government? What is the meaning of life, and how can we find happiness in it?
- Source: Meaning-Making Neurons, Michael Shermer, DOI: 10.1126/science.1189752, Science Vol. 328. no. 5979, pp. 693 - 694, 2010/05/07
George Whitesides: Toward a science of simplicity, TED.com
About this talk: Simplicity: We know it when we see it -- but what is it, exactly? In this funny, philosophical talk, George Whitesides chisels out an answer.
- Source: George Whitesides: Toward a science of simplicity, TED.com, 2010/04
Nicholas Christakis: The hidden influence of social networks, TED.com
About this talk: We're all embedded in vast social networks of friends, family, co-workers and more. Nicholas Christakis tracks how a wide variety of traits -- from happiness to obesity -- can spread from person to person, showing how your location in the network might impact your life in ways you don't even know.
- Source: Nicholas Christakis: The hidden influence of social networks, TED.com, 2010/05
Dynamics and Control of Diseases in Networks with Community Structure, PLoS Comput Biol
Excerpt: Here we use both data from social networking websites and computer generated networks to study the effect of community structure on epidemic spread. We find that community structure not only affects the dynamics of epidemics in networks, but that it also has implications for how networks can be protected from large-scale epidemics.
- Source: Dynamics and Control of Diseases in Networks with Community Structure, Marcel Salathé, James H. Jones, DOI: 10.1371/journal.pcbi.1000736, PLoS Comput Biol 6(4): e1000736, 2010/04/08
The Envelope, Please: From Eight Great Innovative Tools, Which Ones Are the Winners?, Knowledge@Wharton
Summary: Ramping up customer satisfaction, maximizing the effectiveness of human capital and repairing supply chains were just a few of the ambitious aims of the ground-breaking "tools" entered in the Wipro-Knowledge@Wharton Innovation Tournament, whose final round of judging took place on March 23 in Philadelphia. Eight finalists, selected from among 120 entries, presented their concepts to a panel of judges during the event. We present the final eight and announce the three competitors who came out on top.
- Source: The Envelope, Please: From Eight Great Innovative Tools, Which Ones Are the Winners?, Knowledge@Wharton, 2010/04/22
The self-organization of genomes, Complexity
Abstract: Menzerath-Altmann law is a general law of human language stating, for instance, that the longer a word, the shorter its syllables. With the metaphor that genomes are words and chromosomes are syllables, we examine if genomes also obey the law. We find that longer genomes tend to be made of smaller chromosomes in organisms from three different kingdoms: fungi, plants, and animals. Our findings suggest that genomes self-organize under principles similar to those of human language.
- Source: The self-organization of genomes, Ramon Ferrer-I-Cancho, Núria Forns, DOI: 10.1002/cplx.20296, Complexity Volume 15 Issue 5, Pages 34 - 36, 2010
The cause of universality in growth fluctuations, arXiv
Excerpt: Phenomena as diverse as breeding bird populations, the size of U.S. firms, money invested in mutual funds, the GDP of individual countries and the scientific output of universities all show unusual but remarkably similar growth fluctuations. The fluctuations display characteristic features, including double exponential scaling in the body of the distribution and power law scaling of the standard deviation as a function of size. To explain this we propose a remarkably simple additive replication model
- Source: The cause of universality in growth fluctuations, Yonathan Schwarzkopf and Robert L. Axtell and J. Doyne Farmer, arXiv:1004.5397, 2010/04/29
Social Network Sensors for Early Detection of Contagious Outbreaks, arXiv
Excerpt: Current methods for the detection of contagious outbreaks give contemporaneous information about the course of an epidemic at best. Individuals at the center of a social network are likely to be infected sooner, on average, than those at the periphery. However, mapping a whole network to identify central individuals whom to monitor is typically very difficult. We propose an alternative strategy that does not require ascertainment of global network structure, namely, monitoring the friends of randomly selected individuals.
- Source: Social Network Sensors for Early Detection of Contagious Outbreaks, Nicholas A. Christakis, James H. Fowler, arXiv:1004.4792, 2010/04/27
How Cooperation Is Maintained in Human Societies: Punishment, Study Suggests, ScienceDaily
Excerpts: Humans are incredibly cooperative, but why do people cooperate and how is cooperation maintained? A new research (�) suggests cooperation in large groups is maintained by punishment. The finding challenges previous cooperation/punishment models that argue punishment is uncoordinated and unconditional. (�) To understand the study, let's start with a small group of friends. In small groups, individuals often have personal connections with other group members and cooperation typically is maintained by a "you help me, I'll help you" reciprocity system. Group members cooperate because they do not want to hurt their friends by not participating in group efforts, and also because they may want help in the future. (�)
- Source: How Cooperation Is Maintained in Human Societies: Punishment, Study Suggests, ScienceDaily & National Science Foundation, 2010/05/03
The Quick And The Dead: When Reaction Beats Intention, Proc. R. Soc. B
Excerpt: Everyday behaviour involves a trade-off between planned actions and reaction to environmental events. Evidence from neurophysiology, neurology and functional brain imaging suggests different neural bases for the control of different movement types. Here we develop a behavioural paradigm to test movement dynamics for intentional versus reaction movements and provide evidence for a �reactive advantage� in movement execution, whereby the same action is executed faster in reaction to an opponent. We placed pairs of participants in competition with each other to make a series of button presses. Within-subject analysis of movement times revealed a 10 per cent benefit for reactive actions. (�)
- Source: The Quick And The Dead: When Reaction Beats Intention, A. E. Welchman - a.e.welchmanbham.ac.uk, J. Stanley, M. R. Schomers, R. Chris Miall, H. H. B�lthoff, DOI: 10.1098/rspb.2009.2123, Proc. R. Soc. B, 2010/06/07, online 2010/02/03
Causal Models: How People Think About the World and Its Alternatives, Oxford University Press
Human beings are active agents who can think. To understand how thought serves action requires understanding how people conceive of the relation between cause and effect, between action and outcome. In cognitive terms, how do people construct and reason with the causal models we use to represent our world? A revolution is occurring in how statisticians, philosophers, and computer scientists answer this question. Those fields have ushered in new insights about causal models by thinking about how to represent causal structure mathematically, in a framework that uses graphs and probability theory to develop what are called causal Bayesian networks. (...)
- Source: Causal Models: How People Think About the World and Its Alternatives, Steven Sloman, Oxford University Press, 2010/05/01