This book is not yet featured on Listopia. Community Reviews. Showing Rating details. Sort order. Jan 29, Bryan rated it it was ok. As with all books on the origin of life the author's theories are highly speculative. The reason for the two Star review is more for the books flaws of other sorts. First, it suffers from poor organization.
The authors periodically wander off topic, sometimes for pages st a time. Secondly, there are pages and pages of math with integrals, derivatives and partial derivatives with often minimal explanation, and then to top it off the authors have the temerity to repeatedly use variations of the ph As with all books on the origin of life the author's theories are highly speculative.
Secondly, there are pages and pages of math with integrals, derivatives and partial derivatives with often minimal explanation, and then to top it off the authors have the temerity to repeatedly use variations of the phrase, "it is obvious that. On the plus side, the authors do make a valiant attempt at breathing new life into what is essentially a rehashing of origin arguments that have long been considered unrealistic at best. Fortunately, in a few spots they do admit the current insurmountable difficulties in producing a compelling origin of life model.
There are no discussion topics on this book yet. About Rainer Feistel. We show analytically and numerically that the system self-organizes to a non-trivial state that differs from what is obtained when the two processes are decoupled. A power-law decay of dynamical and topological quantities above a threshold emerges spontaneously, as well as a feedback between different dynamical regimes and the underlying correlation and percolation properties of the network.
This thoroughly updated version of the German authoritative work on self- organization has been completely rewritten by internationally renowned experts and. This thoroughly updated version of the German authoritative work on self- organization has been completely rewritten by internationally.
Press, Oxford, Albert, R. Statistical mechanics of complex networks.
Newman, M. The structure and function of complex networks. SIAM Rev. Garlaschelli, D. Fitness-dependent topological properties of the world trade web. The scale-free topology of market investments. Physica A , — Balcan, D. Content-based networks: A pedagogical overview. Chaos 17 , Scale-free networks from varying vertex intrinsic fitness.
General formalism for inhomogeneous random graphs. E 66 , Bianconi, G.
Competition and multiscaling in evolving networks. Class of correlated random networks with hidden variables. E 68 , Servedio, V. Vertex intrinsic fitness: How to produce arbitrary scale-free networks. E 70 , Modelling coevolution in multispecies communities. Jain, S. Autocatalytic sets and the growth of complexity in an evolutionary model.
Clogging and self-organized criticality in complex networks.
E 70 , R Fronczak, P. The virtue of their idea is that it resolves what they perceive as a "clash of doctrines" about the nature of time in physics. Most physicists would agree that there is neither empirical evidence to support their view, nor is there a mathematical necessity for it.
There is no "clash of doctrines. In theology , Thomas Aquinas — in his Summa Theologica assumes a teleological created universe in rejecting the idea that something can be a self-sufficient cause of its own organization: . Since nature works for a determinate end under the direction of a higher agent, whatever is done by nature must needs be traced back to God, as to its first cause. So also whatever is done voluntarily must also be traced back to some higher cause other than human reason or will, since these can change or fail; for all things that are changeable and capable of defect must be traced back to an immovable and self-necessary first principle, as was shown in the body of the Article.
From Wikipedia, the free encyclopedia. It has been suggested that Spontaneous order be merged into this article. Discuss Proposed since May Further information: Spontaneous order.
See also: Self-assembly and Self-assembly of nanoparticles. Further information: Biological organisation. Main article: Self-organization in cybernetics. Main article: Spontaneous order. Main article: Three-phase traffic theory. Autopoiesis Autowave Self-organized criticality control Free energy principle Information theory Constructal law Emergence. Journal of Materials Chemistry A. International Journal of Signs and Semiotic Systems. Self-organization in Biological Systems. Those who study creative thinking also see parallels with complex systems.
Humans sometimes organize almost random pieces of information, often subconsciously while doing other things, and come up with brilliant creative insights. The development of language is another complex adaptive system that may show similar tendencies. Artificial intelligence is an overt attempt to devise an adaptive system that will self-organize and evolve in the same manner as an intelligent living being learns.
These are a few of the broad range of topics being studied by those who investigate complexity. There are now institutes, journals, and meetings, as well as popularizations of the emerging topic of complexity. In traditional physics, the discipline of complexity may yield insights in certain areas.
Thermodynamics treats systems on the average, while statistical mechanics deals in some detail with complex systems of atoms and molecules in random thermal motion.
Fractal dimension of interfaces in Edwards-Anderson spin glasses for up to six space dimensions. McWilliams, J. Although unifying explanations of universal phenomena are inherently dangerous, it does appear plausible that complexity can emerge only in nonergodic systems, and nonergodicity is caused by competing interactions. These upflows frequently happen during solar flares, but equally occur as a consequence of other coronal heating mechanisms also, in active regions, in Quiet Sun regions explosive events, EUV brightenings , and even in coronal holes plumes, jets. Buchler, Z. Wolf , a Mikhail I. Jenkins et al.
Yet there is organization, adaptation, and evolution in those complex systems. Non-equilibrium phenomena, such as heat transfer and phase changes, are characteristically complex in detail, and new approaches to them may evolve from complexity as a discipline. Crystal growth is another example of self-organization spontaneously emerging in a complex system. Alloys are also inherently complex mixtures that show certain simple characteristics implying some self-organization.
The organization of iron atoms into magnetic domains as they cool is another. Perhaps insights into these difficult areas will emerge from complexity. But at the minimum, the discipline of complexity is another example of human effort to understand and organize the universe around us, partly rooted in the discipline of physics. A predecessor to complexity is the topic of chaos, which has been widely publicized and has become a discipline of its own.
It is also based partly in physics and treats broad classes of phenomena from many disciplines. Chaos is a word used to describe systems whose outcomes are extremely sensitive to initial conditions. The orbit of the planet Pluto, for example, may be chaotic in that it can change tremendously due to small interactions with other planets. This makes its long-term behavior impossible to predict with precision, just as we cannot tell precisely where a decaying Earth satellite will land or how many pieces it will break into.
But the discipline of chaos has found ways to deal with such systems and has been applied to apparently unrelated systems. For example, the heartbeat of people with certain types of potentially lethal arrhythmias seems to be chaotic, and this knowledge may allow more sophisticated monitoring and recognition of the need for intervention. Figure 1. This image is related to the Mandelbrot set, a complex mathematical form that is chaotic. The patterns are infinitely fine as you look closer and closer, and they indicate order in the presence of chaos. Chaos is related to complexity.
Some chaotic systems are also inherently complex; for example, vortices in a fluid as opposed to a double pendulum. Both are chaotic and not predictable in the same sense as other systems. But there can be organization in chaos and it can also be quantified. Examples of chaotic systems are beautiful fractal patterns such as in Figure 1.