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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

A. A Survey of Common Principles

Villegas, Pablo, et al. Evolution in the Debian GNU/Linux Software Network: Analogies and Differences with Gene Regulatory Networks. Journal of the Royal Society Interface. February, 2020. In this visionary, consummate year, University of Granada, Spain including Miguel Munoz (search) proceed to recognize many structural and operational parallels between these widely separate domains as they both engage in information processing and conveyance. Convergent comparisons such as this quite imply the reality of an independent mathematical program with a generic neural and genomic essence across all natural and social realms. See also Keil, Petr, et al. Macroecological and Macroevolutionary Patterns Emerge in the Universe of GNU/Linux Operating Systems by Petr Keil et al in Ecography (41/11, 2018).

Gene regulatory networks GRN as they process information in the cell display non-trivial architectural features such as scale-free degree distributions, high modularity and low average distance between connected genes. Such networks result from complex evolutionary and adaptive processes difficult to track empirically. On the other hand, the developmental (or evolutionary) stages of open-software networks that result from self-organized growth across versions are well known. Here, we study the evolution of the Debian GNU/Linux software network, focusing on changes of key structural and statistical features over time. Our results show that this has led to a structure in which the out-degree distribution is scale-free and the in-degree distribution is a stretched exponential. These features resemble closely those shown by GRNs, which suggests the existence of common adaptive pathways for the architectural design of information-processing networks. (Abstract)

Understanding the collective properties stemming from the interactions of a large number of units such as genes, proteins or metabolites is of paramount importance in biology. Theoretical work focusing on the changes over time of self-organizing networks can provide key information about these natural systems. Particularly, network theory provides us with a highly insightful systems-level perspective to extremely complicated biological problems, which has helped advance knowledge in fields such as neuroscience, ecology and epidemiology. The study of information processing in living systems has greatly benefited from this network perspective, complementing parallel endeavours for the analysis of single pathways, and providing a much richer understanding of collective phenomena emerging from a large number of basic inter-related units. (1)

Visentin-Bugoni, Jeferson, et al. Structure, Spatial Dynamics and Stability of Novel Seed Dispersal Mutualistic Networks in Hawai’i. Science. 364/78, 2019. Eight systems ecologists posted in Illinois, Wyoming, New Hampshire, and Honolulu report the presence of common topological forms as alien fauna and flora proceed to invade complex ecosystems. We thus record the presence of an independent mathematical source in universal formative effect.

Increasing rates of human-caused species invasions and extinctions may reshape communities and modify the structure, dynamics, and stability of species interactions. To investigate how such changes affect communities, we performed multiscale analyses of seed dispersal networks on Oahu, Hawaii. Networks consisted exclusively of novel interactions, were largely dominated by introduced species, and exhibited specialized and modular structure at local and regional scales, despite high interaction dissimilarity across communities. Furthermore, the structure and stability of the novel networks were similar to native-dominated communities worldwide. Our findings suggest that the emergence of complex network structure, and interaction patterns may be highly conserved, regardless of species identity and environment. (Abstract)

Vitiello, Giuseppe. On the Isomorphism between Dissipative Systems, Fractal Self-Similarity and Electrodynamics: Toward an Integrated Vision of Nature. Systems. 2/203, 2014. In this online journal, the University of Salerno theoretical physicist summarizes two decades of studies, with colleagues, upon a universal form and theme that seems to be exemplified and repeated in kind everywhere. The project is to achieve a unified, viable “living matter physics” situated in and aligned with a conducive quantum cosmos. See also Fractals, Coherent States and Self-Similarity Induced Noncommutative Geometry by GV at arXiv:1206.1854.

One more aspect which is related with the discussion here presented concerns with the description of fractal-like structures with self-similarity properties in terms of non-homogeneous Bose condensation. Indeed, in the present scheme they appear to be generated by coherent SU(1; 1) quantum condensation processes at the microscopic level, similar to “extended objects” or macroscopic quantum systems. The macroscopic appearances (forms) of the fractals seems to emerge out of a process of morphogenesis as the macroscopic manifestation of the underlying dissipative, coherent quantum dynamics at the elementary level. An integrated vision of Nature resting, in its essence, on the paradigm of coherence and dissipation thus emerges. Nature appears to be modulated by coherence, rather than being hierarchically layered in isolated compartments, in multi-coded collections of isolated systems and phenomena. (213)

The DNA genetic code appears in conclusion to be the output of the coherent dynamics. In this way, it is subtracted from its purely phenomenological characterization, which is sometimes at the origin of dogmatic or even miraculous beliefs. In this view, DNA appears to be the vehicle through which the laws of form express themselves in living systems and coherence and its deformations propagate through duplication and multiplication processes. (214)

Walleczek, Jan, ed. Self-Organized Biological Dynamics and Nonlinear Control. Cambridge, UK: Cambridge University Press, 2000. A theoretical appreciation of organisms as energy-driven, open systems which gives rise to an emergent fractal organization and viability. For these reasons, a physical basis for evolving life is defined.

A revolution is underway in the physical sciences, based on insights from nonlinear dynamics, which includes the areas popularly known as chaos and complexity studies. As described in the previous chapters, this revolution is beginning to affect greatly the biological and medical sciences as well. (409) The nonlinear dynamical systems view, which I also referred to in the Introduction to this book as the paradigm of self-organization, thus provides biology with a theoretically sound approach toward a ‘holistic biology’ for the first time in the history of science. (417)

Watson, Richard A., et al. Global Adaptation in Networks of Selfish Components: Emergent Associative Memory at the System Scale. Artificial Life. Early View, May, 2011. Watson and Rob Mills, Natural Systems, University of Southampton, and Chris Buckley, Informatics, Sussex University, post an advanced, technical analysis of the presence and activity of dynamic network phenomena across life’s nested evolution. By this work, and many akin, a growing quantification and admission accrues that something much more creative is going on to drive and direct life’s historic development. A universal complementarity of semi-autonomous agents or entities and communicative interrelations that serves both self and society is described as it repeats from biomolecules to ecosystems. For a further take see also next Watson, Richard A., et al. “Adaptation Without Natural Selection.” Both articles are available on Watson’s web publication page. We offer extended quotes to convey the technical verbatim, which may suggest, in translation, a cosmic genetic code at work.

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organise into structures that enhance global adaptation, efficiency or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalisation and optimisation, are well-understood. (Abstract, 1)

Specifically, the key to understanding this result is that selfish agents necessarily modify connections in a manner consistent with Hebb’s rule – a simple learning rule familiar in computational neuroscience (Methods). This means that a system of selfish agents, each modifying its connections with other agents selfishly and in a completely distributed manner, will produce dynamical consequences for the system as a whole that are functionally identical to a learning neural network. (3)

Conclusions: We have shown that organisational principles familiar in organismic learning occur implicitly in distributed complex adaptive systems. System-level ‘learning’ or associative induction happens as a direct consequence of the fact that selfish modifications to relationships between components are equivalent to Hebb’s rule. Thus networks of selfish agents self-organise the connection structure of a network in a manner that creates an associative memory of state configurations that the system experiences. (22) These findings suggest that distributed complex adaptive systems of self-interested components, such as individuals in a social network or species in an ecosystem, may exhibit organisational principles in common with those familiar in organismic learning, developing an associative memory of their past behaviour that enhances system-level efficiency in future. This work thereby demonstrates a completely distributed adaptive process that we view as a natural extension to the “emergent collective computational abilities” that come ‘for free’ in physical systems [22].

West, Geoffrey. The Surprising Math of Cities and Corporations. http://www.ted.com/talks/geoffrey_west_the_surprising_math_of_cities_and_corporations.html.. The physicist and philosopher, once president of Santa Fe Institute, describes in this July 2011, Edinburgh, TED video presentation, the remarkable findings of research teams he has mentored and contributed to over 15 years. In the later 1990s West joined with ecologists James Brown and Brian Enquist in an endeavor to quantify within creaturely anatomy and physiology from mice to elephants, and biota from leaves to a forest, a pervasive recurrence of the same pattern and process, such metabolic rate. This project met with much success (search names herein) so that West extended the effort in the 2000s with Luis Bettencourt, Deborah Strumsky, Jose Lobo, and other colleagues to human settlements and commercial institutions. The talk is mainly on this aspect, but covers the whole expanse over orders of magnitude from microbes to a metropolis.

A significant difference then arises. While flora and fauna are seen as “sublinear,” i.e., metabolisms slow down from voles to whales, for villages to megacities, energy usages, and all activities, become “superlinear” as they increase with urban size and density. But notably, as we know, business companies hold to the sublinear range. The bigger they get, the more bureaucracy sets in, and viability decreases. As a result of this grand scenario, “generic universal principles” of nested network geometries that repeat with fractal-like self-similarity become robustly evident. What accrues is an historic discovery of a constant, iterative recurrence, as if from a mathematical source, across nature and culture. Galileo would say tell me about it. Geoffrey West, of British birth, brings to mind William Blake: “To see a world in a grain of sand, And a heaven in a wild flower, Hold infinity in the palm of your hand, And eternity in an hour.”

“The same principles, the same dynamics, the same organization is at work in all of these, including us, and it can scale over a range of 100 million in size. And that is one of the main reasons life is so resilient and robust -- scalability.”

West, Geoffrey and James Brown. Life’s Universal Scaling Laws. Physics Today. September, 2004. A popular survey of the theory that common properties of biological networks can explain the structural organization and metabolic dynamics of living systems.

Among the many fundamental variables that obey such scaling laws….are metabolic rate, life span, growth rate, heart rate, lengths of aortas and genomes, tree height, mass of cerebral grey matter, density of mitochondria, and concentration of RNA. (36) The starting point was to recognize that highly complex, self-sustaining, reproducing, living structures require close integration of enormous numbers of localized microscopic units that need to be serviced in an approximately “democratic” and efficient fashion. (38) Thus, growth and life-history events are, in general, universal phenomena governed primarily be basic cellular properties and quarter-power scaling. (40)

West, Geoffrey and James Brown. The Origin of Allometric Scaling Laws in Biology from Genomes to Ecosystems. Journal of Experimental Biology. 208/9, 2005. Physicist West and ecologist Brown, with other colleagues over the past decade, have achieved a significant articulation via complexity science of a quantitative theory of biological organization. This latest report discusses hierarchical branching networks which exhibit a nested self-similarity distinguished by power-law behavior across the entire realm of living nature. The implication of such findings, along with much other work, is the (re)discovery that our reality is distinguished by a repetition of the same pattern and process everywhere.

For example, metabolic rate scales as the ¾ power of mass over 27 orders of magnitude, from molecular and intracellular levels up to the largest organisms. Similarly, time-scales (such as lifespans and growth rates) and sizes (such as bacterial genome lengths, tree heights and mitochondrial densities) scale with exponents that are typically simple powers of ¼. The universality and simplicity of these relationships suggest that fundamental universal principles underlie much of the coarse-grained generic structure and organization of living systems. (1575)

Whitfield, John. Across the Curious Parallel of Language and Species Evolution. PLoS Biology. 6/7, 2008. The British science writer reports in this online journal on the dawning realization that the molecular DNA code is strongly isomorphic and isodynamic with linguistic structures. One might add that an implication of this has not yet registered that human knowledge is genetic in kind, and that both codes must spring from the same innate source. By its employ, much as if people are as “genes,” we might intentionally continue creation.

Languages are extraordinarily like genomes…there could be very general laws of lexical evolution to rival those of genetic evolution. (1370)

Yang, Ang and Yin Shan, eds. Intelligent Complex Adaptive Systems. Hershey, PA: IGI Publishing, 2008. This technical volume illustrates a revolution in conceptual modeling as applied across a wide range from computational processes to international conflicts. All such phenomena can now be expressed as universally manifest multi-agent, interactive, modular, information-driven dynamic networks.

Yeung, Chi Ho, et al. From the Physics of Interacting Polymers to Optimizing Routes on the London Underground. Proceedings of the National Academy of Sciences. 110/13717, 2013. As the Abstract and Synopsis detail, Aston University, Birmingham, UK, and Hong Kong University of Science and Technology, systems physicists quantify nature’s universal preference for metabolic movement from biochemicals to biocities, so as carry it forth for a better organic design of our human scale dynamic systems.

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii) the global airport network. (Abstract)

From Polymer Physics to Quicker Commuter Travel. Whether planning water distribution routes, military convoy movements, internet traffic, or simply the best way to the airport, path optimization algorithms are essential for everyday logistics. Global optimization techniques that consider all path choices simultaneously are computationally difficult. As a result, most existing routing algorithms choose paths individually, but these methods tend to favor the shortest path regardless of the choice’s impact on other routes. Chi Ho Yeung et al. have borrowed from the physics of polymers to create a simple, generic, and distributed global path optimizing algorithm. The researchers tested their statistical physics-based technique on large real-world data sets, including the London Underground subway system and global air traffic. Compared to current methods, the algorithm decreased overall congestion at the cost of a slightly longer path length. (PNAS Summary)

Yu, Haiyuan and Mark Gerstein. Genomic Analysis of the Hierarchical Structure of Regulatory Networks. Proceedings of the National Academy of Sciences. 103/14724, 2006. Genomic systems employ a consistent network motif to achieve viable translation, which is found to be the same organization as present in human societies. Another contribution to the discovery of a natural genesis that recycles a common pattern and process from atom to cosmos.

A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationship between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic layouts. (14724) In general, our results show that there is a pyramid-shaped hierarchical structure in regulatory networks, which is well organized in a clearly nonrandom manner. The decision making scheme in this hierarchy is a cogitation-like multistep process. (14730)

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