Complexity Digest 2012.02

[John T. Maloney (jheuristic)]

01. No entailing laws, but enablement in the evolution of the biosphere , arXiv

Excerpt: Biological evolution is a complex blend of ever changing structural
stability, variability and emergence of new phenotypes, niches, ecosystems. We
wish to argue that the evolution of life marks the end of a physics world view
of law entailed dynamics. Our considerations depend upon discussing the
variability of the very "contexts of life": the interactions between organisms,
biological niches and ecosystems. These are ever changing, intrinsically
indeterminate and even unprestatable: we do not know ahead of time the "niches"
which constitute the boundary conditions on selection. More generally, by the
mathematical unprestatability of the "phase space" (space of possibilities), no
laws of motion can be formulated for evolution. We call this radical emergence,
from life to life. (…)

* [1] No entailing laws, but enablement in the evolution of the biosphere,
Giuseppe Longo and Maël Montévil and Stuart Kauffman, 2012/01/10,
arXiv:1201.2069

[1] http://arXiv.org/abs/1201.2069


03. Five technologies to watch , McKinsey Quaterly [sic]

Excerpt: Innovation in energy technology is taking place rapidly. Five
technologies you may not have heard of could be ready to change the energy
landscape by 2020.  Grid-scale storage. Digital-power conversion. Compressorless
air conditioning and electrochromic windows. Clean coal. Biofuels and
electrofuels.
Editor's Note: Technology can reduce the pollution produced by burning coal.
However, the ecological damage of coal extraction should also be considered.

* [3] Five technologies to watch, Matt Rogers, 2012/01, McKinsey Quaterly

[3]
http://www.mckinseyquarterly.com/Energy_Resources_Materials/Strategy_Analysis/Five_technologies_to_watch_2902

 

04. What is your favorite deep, elegant, or beautiful explanation? , edge.org

Excerpt: Since this question is about explanation, answers may embrace
scientific thinking in the broadest sense: as the most reliable way of gaining
knowledge about anything, including other fields of inquiry such as philosophy,
mathematics, economics, history, political theory, literary theory, or the human
spirit. The only requirement is that some simple and non-obvious idea explain
some diverse and complicated set of phenomena. [192 contributors]

* [4] What is your favorite deep, elegant, or beautiful explanation?, 2012,
edge.org

[4]
http://edge.org/annual-question/what-is-your-favorite-deep-elegant-or-beautiful-explanation

 

08. Evolution of increased complexity in a molecular machine , Nature

Excerpt: Many cellular processes are carried out by molecular
‘machines’—assemblies of multiple differentiated proteins that physically
interact to execute biological functions. Despite much speculation, strong
evidence of the mechanisms by which these assemblies evolved is lacking. Here we
use ancestral gene resurrectionand manipulative genetic experiments to determine
how the complexity of an essential molecular machine (…) increased hundreds of
millions of years ago. (…) Our experiments show that increased complexity in
an essential molecular machine evolved because of simple, high-probability
evolutionary processes, without the apparent evolution of novel functions. They
point to a plausible mechanism for the evolution of complexity in other
multi-paralogue protein complexes.

* [13] Evolution of increased complexity in a molecular machine, Gregory C.
Finnigan, Victor Hanson-Smith, Tom H. Stevens & Joseph W. Thornton, 2012/01/9,
DOI: 10.1038/nature10724, Nature 481, 360–364

[13] http://dx.doi.org/10.1038/nature10724

 

14. Complexity of networks (Reprise) , Complexity

Excerpt: Network or graph structures are ubiquitous in the study of complex
systems. Often, we are interested in complexity trends of these system as it
evolves under some dynamic. An example might be looking at the complexity of a
food web as species enter an ecosystem via migration or speciation, and leave
via extinction. (…) In this article, I propose a new representation language
that encodes the number of links along with the number of nodes and a
representation of the linklist. This, like zcomplexity, exhibits minimal
complexity for fully connected and empty networks, but is as tractable as the
original measure. This measure is extended to directed and weighted links, and
several real-world networks have their network complexities compared with
randomly generated model networks with matched node and link counts, and matched
link weight distributions. (…)

* [20] Complexity of networks (Reprise), Russell K. Standish, 2012/01-02, DOI:
10.1002/cplx.20393, Complexity Volume 17, Issue 3, pages 50–61

[20] http://dx.doi.org/10.1002/cplx.20393

_________________________________________________________________

14.01. The influence of assortativity on the robustness of signal-integration
logic in gene regulatory networks , Journal of Theoretical Biology

Highlights: ► We study how topology affects the robustness of gene regulatory
networks (GRNs). ► We examine the effects on robustness of varying
assortativity in models of GRNs. ► Robustness increases with increasing
assortativity. ► Increased assortativity reduces in-component sizes, which
leads to higher robustness.

* [21] The influence of assortativity on the robustness of signal-integration
logic in gene regulatory networks, Dov A. Pechenick,  Joshua L. Payne,  Jason H.
Moore, 2012/03/12, DOI: 10.1016/j.jtbi.2011.11.029, Journal of Theoretical
Biology Volume 296, Pages 21–32

[21] http://dx.doi.org/10.1016/j.jtbi.2011.11.029


17. The earthquakes network: the role of cell size , Eur. Phys. J. B

Abstract: The complex network theory is a way to investigate the complex systems
with minimum information about their entities and corresponding interactions.
There is a growing interest to studying the earthquake phenomena by the method
of networks. Several network features characterize the complexity of seismic
events. Unfortunately they depend on how we construct the network. Here we study
the role of cell size or in other word the resolution on the network properties
for the Iran’s seismic data. We have found that all the network topological
features vary as a power of the resolution. Furthermore by increasing the
resolution, the networks become random and uncorrelated.

* [25] The earthquakes network: the role of cell size, N. Lotfi and A.H.
Darooneh, 2012/01/18, DOI: 10.1140/epjb/e2011-20623-x, Eur. Phys. J. B Volume
85, Number 1, January 2012

[25] http://dx.doi.org/10.1140/epjb/e2011-20623-x

 

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John McCreery
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