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Unconventional Computation & Natural Computation 2014

The International Conference on Unconventional Computation and Natural Computation has been a forum where scientists with different backgrounds, yet sharing a common interest in novel forms of computation, human-designed computation inspired by nature, and the computational aspects of processes taking place in nature, meet and present their latest results.

 

Unconventional Computation & Natural Computation 2014
University of Western Ontario, London, Ontario, Canada, July 14-18

http://conferences.csd.uwo.ca/ucnc2014/


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Imagination and reality flow in opposite directions in the brain

Imagination and reality flow in opposite directions in the brain | collectibles from scoop.it | Scoop.it

As real as that daydream may seem, its path through your brain runs opposite reality. Aiming to discern discrete neural circuits, researchers at the University of Wisconsin-Madison have tracked electrical activity in the brains of people who alternately imagined scenes or watched videos.


"A really important problem in brain research is understanding how different parts of the brain are functionally connected. What areas are interacting? What is the direction of communication?" says Barry Van Veen, a UW-Madison professor of electrical and computer engineering. "We know that the brain does not function as a set of independent areas, but as a network of specialized areas that collaborate."


Van Veen, along with Giulio Tononi, a UW-Madison psychiatry professor and neuroscientist, Daniela Dentico, a scientist at UW-Madison's Waisman Center, and collaborators from the University of Liege in Belgium, published results recently in the journal NeuroImage. Their work could lead to the development of new tools to help Tononi untangle what happens in the brain during sleep and dreaming, while Van Veen hopes to apply the study's new methods to understand how the brain uses networks to encode short-term memory.


During imagination, the researchers found an increase in the flow of information from the parietal lobe of the brain to the occipital lobe -- from a higher-order region that combines inputs from several of the senses out to a lower-order region. In contrast, visual information taken in by the eyes tends to flow from the occipital lobe -- which makes up much of the brain's visual cortex -- "up" to the parietal lobe.


"There seems to be a lot in our brains and animal brains that is directional, that neural signals move in a particular direction, then stop, and start somewhere else," says. "I think this is really a new theme that had not been explored."


The researchers approached the study as an opportunity to test the power of electroencephalography (EEG) -- which uses sensors on the scalp to measure underlying electrical activity -- to discriminate between different parts of the brain's network.

Brains are rarely quiet, though, and EEG tends to record plenty of activity not necessarily related to a particular process researchers want to study.


To zero in on a set of target circuits, the researchers asked their subjects to watch short video clips before trying to replay the action from memory in their heads. Others were asked to imagine traveling on a magic bicycle -- focusing on the details of shapes, colors and textures -- before watching a short video of silent nature scenes.

Using an algorithm Van Veen developed to parse the detailed EEG data, the researchers were able to compile strong evidence of the directional flow of information.


"We were very interested in seeing if our signal-processing methods were sensitive enough to discriminate between these conditions," says Van Veen, whose work is supported by the National Institute of Biomedical Imaging and Bioengineering. "These types of demonstrations are important for gaining confidence in new tools."


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Vloasis's curator insight, Today, 11:10 AM

So imagination input flows from the parietal to the occipital lobe, while visual input flows vice versa.

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Gut–brain link grabs neuroscientists

Gut–brain link grabs neuroscientists | collectibles from scoop.it | Scoop.it

Companies selling ‘probiotic’ foods have long claimed that cultivating the right gut bacteria can benefit mental well-being, but neuroscientists have generally been sceptical. Now there is hard evidence linking conditions such as autism and depression to the gut’s microbial residents, known as the microbiome. And neuroscientists are taking notice — not just of the clinical implications but also of what the link could mean for experimental design.

 

http://www.nature.com/news/gut-brain-link-grabs-neuroscientists-1.16316


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Only ten midges needed to make a swarm

Only ten midges needed to make a swarm | collectibles from scoop.it | Scoop.it
High-speed cameras reveal when insects become self-organizing.

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Bayesian Inference of Natural Rankings in Incomplete Competition Networks

Bayesian Inference of Natural Rankings in Incomplete Competition Networks | collectibles from scoop.it | Scoop.it
Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest - essential in determining reward and penalty - is frequently an ambiguous task due to the incomplete (partially filled) nature of competition networks. Here we introduce the [ldquo]Natural Ranking,[rdquo] an unambiguous ranking method applicable to a round robin tournament, and formulate an analytical model based on the Bayesian formula for inferring the expected mean and error of the natural ranking of nodes from an incomplete network. We investigate its potential and uses in resolving important issues of ranking by applying it to real-world competition networks.

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​There Are Only Four Types of City in the World, Says Math

​There Are Only Four Types of City in the World, Says Math | collectibles from scoop.it | Scoop.it
Physicists discover that Brooklyn has a touch of Brussels and that Buenos Aires is in a class all its own.

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Can Government Be Self-Organized? A Mathematical Model of the Collective Social Organization of Ancient Teotihuacan, Central Mexico

Can Government Be Self-Organized? A Mathematical Model of the Collective Social Organization of Ancient Teotihuacan, Central Mexico | collectibles from scoop.it | Scoop.it

Teotihuacan was the first urban civilization of Mesoamerica and one of the largest of the ancient world. Following a tradition in archaeology to equate social complexity with centralized hierarchy, it is widely believed that the city’s origin and growth was controlled by a lineage of powerful individuals. However, much data is indicative of a government of co-rulers, and artistic traditions expressed an egalitarian ideology. Yet this alternative keeps being marginalized because the problems of collective action make it difficult to conceive how such a coalition could have functioned in principle. We therefore devised a mathematical model of the city’s hypothetical network of representatives as a formal proof of concept that widespread cooperation was realizable in a fully distributed manner. In the model, decisions become self-organized into globally optimal configurations even though local representatives behave and modify their relations in a rational and selfish manner. This self-optimization crucially depends on occasional communal interruptions of normal activity, and it is impeded when sections of the network are too independent. We relate these insights to theories about community-wide rituals at Teotihuacan and the city’s eventual disintegration.

 

Froese, T., Gershenson, C., and Manzanilla, L. R. (2014). Can government be self-organized? a mathematical model of the collective social organization of ancient teotihuacan, central mexico.PLoS ONE 9 (10) (10): e109966.


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Both information and social cohesion determine collective decisions in animal groups

During consensus decision making, individuals in groups balance personal information (based on their own past experiences) with social information (based on the behavior of other individuals), allowing the group to reach a single collective choice. Previous studies of consensus decision making processes have focused on the informational aspects of behavioral choice, assuming that individuals make choices based solely on their likelihood of being beneficial (e.g., rewarded). However, decisions by both humans and nonhuman animals systematically violate such expectations. Furthermore, the typical experimental paradigm of assessing binary decisions, those between two mutually exclusive options, confounds two aspects common to most group decisions: minimizing uncertainty (through the use of personal and social information) and maintaining group cohesion (for example, to reduce predation risk). Here we experimentally disassociate cohesion-based decisions from information-based decisions using a three-choice paradigm and demonstrate that both factors are crucial to understanding the collective decision making of schooling fish. 

 

Both information and social cohesion determine collective decisions in animal groups
Noam Miller, Simon Garnier, Andrew T. Hartnett, and Iain D. Couzin

http://dx.doi.org/10.1073/pnas.1217513110
PNAS February 25, 2013 201217513


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At the Far Ends of a New Universal Law

At the Far Ends of a New Universal Law | collectibles from scoop.it | Scoop.it

Systems of many interacting components — be they species, integers or subatomic particles — kept producing the same statistical curve, which had become known as the Tracy-Widom distribution. This puzzling curve seemed to be the complex cousin of the familiar bell curve, or Gaussian distribution, which represents the natural variation of independent random variables like the heights of students in a classroom or their test scores. Like the Gaussian, the Tracy-Widom distribution exhibits “universality,” a mysterious phenomenon in which diverse microscopic effects give rise to the same collective behavior. “The surprise is it’s as universal as it is,” said Tracy, a professor at the University of California, Davis.

 

http://www.quantamagazine.org/20141015-at-the-far-ends-of-a-new-universal-law/


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Gary Bamford's curator insight, October 29, 4:16 AM

Possibly a lesson for the 'Big Data' analytics you intent to perform, when you have the time!

Damien Thouvenin's curator insight, October 29, 10:15 AM

Un article intéressant : la courbe de fréquence d'apparition d'un état dans un réseau interconnectant de nombreux éléments (de nombreux systèmes complexes donc) ne suit pas la fameuse courbe de Gauss mais plutôt celle, asymétrique, de la distribution Tracy-Widom. Le modèle a été prouvé pour un certain nombre de cas mais on ne sait pas encore identifier les critères nécessaires et suffisants à son apparition mais cela semble corroborer les effets de seuil que l'on constate dans les réseaux massivement interconnectés.

 

António F Fonseca's curator insight, November 2, 6:38 AM

A new powerful law. Curiosly very similar to the profile of the quantity of retweets on Twitter.

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Controlling extreme events on complex networks

Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network “mobile” can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

 

Controlling extreme events on complex networks
• Yu-Zhong Chen, Zi-Gang Huang & Ying-Cheng Lai

Scientific Reports 4, Article number: 6121 http://dx.doi.org/10.1038/srep06121


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Complexity and Dynamical Depth

Complexity and Dynamical Depth | collectibles from scoop.it | Scoop.it
We argue that a critical difference distinguishing machines from organisms and computers from brains is not complexity in a structural sense, but a difference in dynamical organization that is not well accounted for by current complexity measures. We propose a measure of the complexity of a system that is largely orthogonal to computational, information theoretic, or thermodynamic conceptions of structural complexity. What we call a system’s dynamical depth is a separate dimension of system complexity that measures the degree to which it exhibits discrete levels of nonlinear dynamical organization in which successive levels are distinguished by local entropy reduction and constraint generation. A system with greater dynamical depth than another consists of a greater number of such nested dynamical levels. Thus, a mechanical or linear thermodynamic system has less dynamical depth than an inorganic self-organized system, which has less dynamical depth than a living system. Including an assessment of dynamical depth can provide a more precise and systematic account of the fundamental difference between inorganic systems (low dynamical depth) and living systems (high dynamical depth), irrespective of the number of their parts and the causal relations between them.

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Towards a Global Systems Science

Dirk Helbing, ETH Zurich

 

Talk given at the European Conference on Complex Systems 2014 in Lucca, Italy

 

http://youtu.be/UHp0lV6ppQQ

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Complexity and Dynamical Depth

Complexity and Dynamical Depth | collectibles from scoop.it | Scoop.it
We argue that a critical difference distinguishing machines from organisms and computers from brains is not complexity in a structural sense, but a difference in dynamical organization that is not well accounted for by current complexity measures. We propose a measure of the complexity of a system that is largely orthogonal to computational, information theoretic, or thermodynamic conceptions of structural complexity. What we call a system’s dynamical depth is a separate dimension of system complexity that measures the degree to which it exhibits discrete levels of nonlinear dynamical organization in which successive levels are distinguished by local entropy reduction and constraint generation. A system with greater dynamical depth than another consists of a greater number of such nested dynamical levels. Thus, a mechanical or linear thermodynamic system has less dynamical depth than an inorganic self-organized system, which has less dynamical depth than a living system. Including an assessment of dynamical depth can provide a more precise and systematic account of the fundamental difference between inorganic systems (low dynamical depth) and living systems (high dynamical depth), irrespective of the number of their parts and the causal relations between them.

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Strategic Islands in Economic Games: Isolating Economies From Better Outcomes

Many of the issues we face as a society are made more problematic by the rapidly changing context in which important decisions are made. For example buying a petrol powered car is most advantageous when there are many petrol pumps providing cheap petrol whereas buying an electric car is most advantageous when there are many electrical recharge points or high capacity batteries available. Such collective decision-making is often studied using economic game theory where the focus is on how individuals might reach an agreement regarding the supply and demand for the different energy types. But even if the two parties find a mutually agreeable strategy, as technology and costs change over time, for example through cheaper and more efficient batteries and a more accurate pricing of the total cost of oil consumption, so too do the incentives for the choices buyers and sellers make, the result of which can be the stranding of an industry or even a whole economy on an island of inefficient outcomes. In this article we consider the issue of how changes in the underlying incentives can move us from an optimal economy to a sub-optimal economy while at the same time making it impossible to collectively navigate our way to a better strategy without forcing us to pass through a socially undesirable “tipping point”. We show that different perturbations to underlying incentives results in the creation or destruction of “strategic islands” isolated by disruptive transitions between strategies. The significant result in this work is the illustration that an economy that remains strategically stationary can over time become stranded in a suboptimal outcome from which there is no easy way to put the economy on a path to better outcomes without going through an economic tipping point.

 

Entropy 2014, 16(9), 5102-5121; http://dx.doi.org/10.3390/e16095102


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Researchers Provide First Peek at How Neurons Multitask

Researchers Provide First Peek at How Neurons Multitask | collectibles from scoop.it | Scoop.it

Researchers at the University of Michigan have shown how a single neuron can perform multiple functions in a model organism, illuminating for the first time this fundamental biological mechanism and shedding light on the human brain.

Investigators in the lab of Shawn Xu at the Life Sciences Institute found that a neuron in C. elegans, a tiny worm with a simple nervous system used as a model for studying sensation, movement and other neurological function, regulates both the speed and direction in which the worm moves. The individual neurons can route information through multiple downstream neural circuits, with each circuit controlling a specific behavioral output.

The findings are scheduled for online publication in the journal Cell on Nov. 6. The research is also featured on the cover.

"Understanding how the nervous system and genes lead to behavior is a fundamental question in neuroscience, and we wanted to figure out how C. elegans are able to perform a wide range of complex behaviors with their small nervous systems," Xu said.

The C. elegans nervous system contains 302 neurons.

"Scientists think that even though humans have billions of neurons, some perform multiple functions. Seeing the mechanism in worms will help to understand the human brain," Xu said.

The model neuron studied, AIY, regulates at least two distinct motor outputs: locomotion speed and direction-switch. AIY interacts with two circuits, one that is inhibitory and controls changes in the direction of the worm's movement, and a second that is excitatory and controls speed.

"It's important to note that these two circuits have connections with other neurons and may cross-talk with each other," Xu said. "Neuronal control of behavior is very complex."

Xu is a faculty member in the U-M Life Sciences Institute, where his laboratory is located and research conducted. He is also a professor of molecular and integrative physiology at the U-M Medical School.

Other authors on the paper were Zhaoyu Li, Jie Liu and Maohua Zheng, also of the Life Sciences Institute and Department of Molecular and Integrative Physiology in the U-M Medical School.
The research was supported by the National Institutes of Health.
Shawn Xu: www.lsi.umich.edu/labs/shawn-xu-lab ;


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Contraction Analysis for a Class of NonDifferentiable Systems with Applications to Stability and Network Synchronization

Contraction Analysis for a Class of NonDifferentiable Systems with Applications to Stability and Network Synchronization | collectibles from scoop.it | Scoop.it

In this paper we extend to a generic class of piecewise smooth dynamical systems a fundamental tool for the analysis of convergence of smooth dynamical systems: contraction theory. We focus on switched nondifferentiable systems satisfying Carathéodory conditions for the existence and uniqueness of a solution. After generalizing the classical definition of contraction to this class of dynamical systems, we give sufficient conditions for global convergence of their trajectories. The theoretical results are then applied to solve a set of representative problems such as proving global asymptotic stability of switched linear systems, giving conditions for incremental stability of piecewise smooth systems, and analyzing the convergence of networked switched systems.

Contraction Analysis for a Class of NonDifferentiable Systems with Applications to Stability and Network Synchronization

Mario di Bernardo, Davide Liuzza, and Giovanni Russo
http://dx.doi.org/10.1137/120883001

SIAM J. Control Optim., 52(5), 3203–3227


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Scaling of Chaos versus Periodicity: How Certain is it that an Attractor is Chaotic?

Scaling of Chaos versus Periodicity: How Certain is it that an Attractor is Chaotic? | collectibles from scoop.it | Scoop.it
A small perturbation in a system's parameter can convert its attractor from chaotic to periodic, where the probability of obtaining a chaotic regime scales as a power law with respect to the perturbation size.

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Scientists Cannot Explain This Crazy Ant Behavior, but They Love It

Scientists Cannot Explain This Crazy Ant Behavior, but They Love It | collectibles from scoop.it | Scoop.it
Watch as this colony forms a daisy chain to pull a millipede—a behavior researchers have never seen before.

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Snowflake-shaped networks are easiest to mend

Snowflake-shaped networks are easiest to mend | collectibles from scoop.it | Scoop.it
Power grids and other networks with the branching quality of snowflakes are easiest to fix when damaged links can't simply be restored in the same place

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Underestimating extreme events in power-law behavior due to machine-dependent cutoffs

Underestimating extreme events in power-law behavior due to machine-dependent cutoffs | collectibles from scoop.it | Scoop.it
Power-law distributions are typical macroscopic features occurring in almost all complex systems observable in nature. As a result, researchers in quantitative analyses must often generate random synthetic variates obeying power-law distributions. The task is usually performed through standard methods that map uniform random variates into the desired probability space. Whereas all these algorithms are theoretically solid, in this paper we show that they are subject to severe machine-dependent limitations. As a result, two dramatic consequences arise: (i) the sampling in the tail of the distribution is not random but deterministic; (ii) the moments of the sample distribution, which are theoretically expected to diverge as functions of the sample sizes, converge instead to finite values. We provide quantitative indications for the range of distribution parameters that can be safely handled by standard libraries used in computational analyses. Whereas our findings indicate possible reinterpretations of numerical results obtained through flawed sampling methodologies, they also pave the way for the search for a concrete solution to this central issue shared by all quantitative sciences dealing with complexity.

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Mediated attachment as a mechanism for growth of complex networks

Connection topologies of many networked systems like human brain, biological cell, world wide web, power grids, human society and ecological food webs markedly deviate from that of completely random networks indicating the presence of organizing principles behind their evolution. The five important features that characterize such networks are scale-free topology, small average path length, high clustering, hierarchical community structure and assortative mixing. Till now the generic mechanisms underlying the existence of these properties are not well understood. Here we show that potentially a single mechanism, which we call "mediated attachment", where two nodes get connected through a mediator or common neighbor, could be responsible for the emergence of all important properties of real networks. The mediated attachment naturally unifies scale-free topology, high clustering, small world nature, hierarchical community structure and dissortative nature of networks. Further, with additional mixing by age, this can also explain the assortative structure of social networks. The mechanism of mediated attachment seems to be directly present in acquaintance networks, co-authorships, World Wide Web, metabolic networks, co-citations and linguistics. We anticipate that this mechanism will shed new light on percolation and robustness properties of real world networks as well as would give new insights in processes like epidemics spreading and emergent dynamics taking place on them.

 

Mediated attachment as a mechanism for growth of complex networks
Snehal M. Shekatkar, G. Ambika

http://arxiv.org/abs/1410.1870

 


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From decisions to disorders: how neuroscience is changing what we know about ourselves

From decisions to disorders: how neuroscience is changing what we know about ourselves | collectibles from scoop.it | Scoop.it

People have wanted to understand our motivations, thoughts and behaviors since the ancient Greeks inscribed “know thyself” on the Temple of Apollo at Delphi. And understanding the brain’s place in health and disease is one of this century’s greatest challenges – take Alzheimer’s, dementia and depression for example.


There are many exciting contributions from neuroscience that have given insight into our thoughts and actions. Three neuroscientists have just been awarded the 2014 Nobel Prize for their discoveries of cells that act as a positioning system in the brain – in other words, the mechanism that allows us to navigate spaces using spatial information and memory at a cellular level.


There are many exciting contributions from neuroscience that have given insight into our thoughts and actions. For example, the neural basis of how we make fast and slow decisions and decision-making under conditions of uncertainty. There is also an understanding how the brain is affected by stress and how these stresses might switch our brains into habit mode, for example operating on “automatic pilot” and forgetting to carry out planned tasks, or the opposite goal-directed system, which would see you going out of your usual routine, for example, popping into a different supermarket to get special ingredients for a recipe.


Disruption in the balance between the two is evident in neuro-psychiatric disorders, such as obsessive compulsive disorder, and recent evidence suggests that lower grey matter volumes in the brain can bias towards habit formation. Neuroscience is also demonstrating commonalities in disorders of compulsivity, methamphetamine abuse and obese subjects with eating disorders.


Neuroscience can challenge previously accepted views. For example, major abnormalities in dopamine function were thought the main cause of adult attention deficit hyperactivity disorder (ADHD). However, recent work suggests that the main cause of the disorder may instead be associated with structural differences in grey matter in the brain.


What neuroscience has made evidently clear is that changes in the brain cause changes in your thinking and actions, but the relationship is two-way. Environmental stressors, including psychological and substance abuse, can also change the brain. We also now know our brains continue developing into late adolescence or early young adulthood, it is not surprising that these environmental influences are particularly potent in a number of disorders during childhood and adolescence including autism.



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Top-Down Causation and the Rise of Information in the Emergence of Life

Biological systems represent a unique class of physical systems in how they process and manage information. This suggests that changes in the flow and distribution of information played a prominent role in the origin of life. Here I review and expand on an emerging conceptual framework suggesting that the origin of life may be identified as a transition in causal structure and information flow, and detail some of the implications for understanding the early stages chemical evolution.

 

Top-Down Causation and the Rise of Information in the Emergence of Life
Sara Imari Walker

Information 2014, 5(3), 424-439; http://dx.doi.org/10.3390/info5030424


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Eli Levine's curator insight, October 11, 5:17 PM

If this is the case, then it confirms a lot of what I've been hypothesizing about government and its role in shaping the legal landscape of our social world (which then influences our ecological, social, environmental, and political world).  Government is always beholden to the natural laws of physics, biology, psychology/neurology, sociology, and economics.  However, government can play a significant role in determining the effects that we experience in our world, based on their obedience to natural laws and limits.

 

We can make a better, healthier, more sustainable, and more resilient world for ourselves within the context of our environment, social, ecological, and cosmological.  The question is, do we have the will, intelligence, wisdom, sense, and accuracy of perception to do anything with it?

 

We'll see, I guess.

 

Here's hoping for a permanent leap forward for humanity.  One that will not end until the universe itself comes to an end (it always does).

 

 

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Top-Down Causation and the Rise of Information in the Emergence of Life

Biological systems represent a unique class of physical systems in how they process and manage information. This suggests that changes in the flow and distribution of information played a prominent role in the origin of life. Here I review and expand on an emerging conceptual framework suggesting that the origin of life may be identified as a transition in causal structure and information flow, and detail some of the implications for understanding the early stages chemical evolution.

 

Top-Down Causation and the Rise of Information in the Emergence of Life
Sara Imari Walker

Information 2014, 5(3), 424-439; http://dx.doi.org/10.3390/info5030424


Via Complexity Digest
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Eli Levine's curator insight, October 11, 5:17 PM

If this is the case, then it confirms a lot of what I've been hypothesizing about government and its role in shaping the legal landscape of our social world (which then influences our ecological, social, environmental, and political world).  Government is always beholden to the natural laws of physics, biology, psychology/neurology, sociology, and economics.  However, government can play a significant role in determining the effects that we experience in our world, based on their obedience to natural laws and limits.

 

We can make a better, healthier, more sustainable, and more resilient world for ourselves within the context of our environment, social, ecological, and cosmological.  The question is, do we have the will, intelligence, wisdom, sense, and accuracy of perception to do anything with it?

 

We'll see, I guess.

 

Here's hoping for a permanent leap forward for humanity.  One that will not end until the universe itself comes to an end (it always does).

 

 

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▶ Cities as complex adaptative systems. Luis Bettencourt

http://youtu.be/vp6eKjQHNl0

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The Outlaw Spirit: Giordano Bruno

The Outlaw Spirit: Giordano Bruno | collectibles from scoop.it | Scoop.it
By coincidence, an article by Brian Logan appeared this morning in The Guardian newspaper that very much illustrates what I wrote about yesterday in “The Outlaw Spirit” in connection with Francis Bacon’s fateful question whether science or magic (that is, Natural Philosophy or Hermetic Philosophy) were best for the mind’s mastery of its circumstances. The end result, after four centuries, has been that “scientia” is now equated with “rationalism” (therefore “realist” and truthful) and “magic” trivialised as illusionism and trickery.

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Eva Rider's curator insight, October 4, 10:41 PM

More on the enigmatic philosopher Giordano Bruno