IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Generative Code-Script Source
5. Common Code: A Further Report of Reliable, Invariant Principles
Buchanan, Mark. The Mathematical Mirror to Animal Nature. Nature. 453/714, 2008. A note on the growing perception of universally recurrent behavior patterns from social insects and migratory birds to financial investors and mobile phone users. The subject here involves “Levy flights” as “random walks” distinguished by a probability distribution that generates a scale invariance. These many findings lead investigators to postulate the presence of an independent, underlying source. A companion article, "The Cambrian Smorgasbord" by Arran Frood, cites the work of ecologist Jennifer Dunne as illuminating common recurrences across evolutionary time and space.
Caetano-Anolles, Derek, et al.
Evolution of Macromolecular Structure: A ‘Double Tale’ of Biological Accretion.
A son Derek, MPI Evolutionary Biology, daughter Kelsey, Seoul National University agricultural biotechnology, and father Gustavo (search), University of Illinois plant sciences, collaborate on an iterative cosmic to organic to cultural synthesis just becoming evident. The entry draws on earlier versions such as Piecemeal Buildup of the Genetic Code (Life, 6/43, 2016), Early History and Emergence of Molecular Functions (Nature Scientific Reports, 6/25058, 2016), Computing the Origin and Evolution of the Ribosome (Computational and Structural Biotechnology, 13/427, 2015), and Structural Phylogenomics Retrodicts the Origin of the Genetic Code (PLoS One, 8/8, 2013). An initial notice is that, akin to Geoffrey West 2017, Naoki Sato 2018, and others, it is lately possible to view the entire course of universe to human evolution as a single, complex, emergent phenomenon which springs from, and exemplifies, its own procreative qualities.
The evolution of structure in biology is driven by accretion and change. Accretion brings together disparate parts to form bigger wholes. Change provides opportunities for growth and innovation. Here we review patterns and processes that are responsible for a 'double tale' of evolutionary accretion at various levels of complexity, from proteins and nucleic acids to high-rise building structures in cities. Parts are at first weakly linked and associate variously. As they diversify, they compete with each other and are selected for performance. The emerging interactions constrain their structure and associations. This causes parts to self-organize into modules with tight linkage. In a second phase, variants of the modules evolve and become new parts for a new generative cycle of higher-level organization. Evolutionary genomics and network biology support the 'double tale' of structural module creation and validate an evolutionary principle of maximum abundance that drives the gain and loss of modules. (Abstract)
Callebaut, Werner and Diego Rasskin-Gutman, eds. Modularity: Understanding the Development and Evolution of Natural Complex Systems. Cambridge: MIT Press, 2005. Reviewed more in Part V, this volume complements: Schlosser, Gerhard and Gunter Wagner, eds. Modularity in Development and Evolution. (2003). Altogether they report in detail and breadth the discovery that nature repeats, by way of semiautonomous components and entities, the same universal pattern and process over and over. Still another aspect and perspective serves to reveal an iterative, “modular” universe.
Camazine, Scott, et al, eds. Self-Organization in Biological Systems. Princeton: Princeton University Press, 2001. A primer for generic self-emergent systems whose many interactions between simpler components and local rules give rise to global degrees of order. The book moves on to describe their presence throughout the natural kingdom from shell patterns to social insect structures.
Capra, Fritjof. The Hidden Connections: Integrating the Biological, Cognitive, and Social Dimensions of Life into a Science of Sustainability. New York: Doubleday, 2002. Fritjof’s latest essay on how an apprecitation of the systemic relations between component entities or objects, as exemplified by the symbiotic cell, can provide natural, ecological principles to guide the self-organization of sustainable, humane communities.
When we study living systems from the perspective of form, we find that their pattern of organization is that of a self-generating network. From the perspective of matter, the material structure of a living system is a dissipative structure, i.e., an open system operating far from equilibrium. From the process perspective, finally, living systems are cognitive systems in which the process of cognition is closely linked to the pattern of autopoiesis. In a nutshell, this is my synthesis of the new scientific understanding of life. (71)
Carletti, Timoteo and Simone Righi. Weighted Fractal Networks. Physica A. 389/2134, 2010. Universitaires Notre Dame de la Paix, Belgium, mathematicians join the prolific studies of network phenomena that emphasize their nested fractal self-similarity, as if arising from an independent implication. By such an advance, one more entry is gained to nature’s universal recurrence, as if a developmental phenotype springing from such a creative organic genotype.
In this paper we define a new class of weighted complex networks sharing several properties with fractal sets, and whose topology can be completely analytically characterized in terms of the involved parameters and of the fractal dimension. General networks with fractal or hierarchical structures can be set in the proposed framework that moreover could be used to provide some answers to the widespread emergence of fractal structures in nature. (Abstract, 2134)
Carloni Calame, Carlo, et al, eds. Preface. Physica A. 338/1-2, 2004. An introduction to a special issue of papers presented at the Frontier Science 2003 conference held in Pavia, Italy. As the quote below attests, they exemplify the worldwide discovery of a universally recurrent complex creative system throughout the scientific literature that this website is trying to communicate.
Examples of complex systems extend from the microscopic scale of sub-nuclear particles to the cosmic scale of galaxies, and hold across a range of different phenomena characterized by a high complexity, many of which taking place in the everyday real world. The statistical features of hadronic jets in high-energy physics, the fractal properties of genomic sequences, the fluctuations of an economic index, the time of turbulence, as well as the topology of the Internet and the clustering of cosmic structures, share striking similarities, consistent with the possibility that all these systems and phenomena have some underlying features in common. (xvi)
Changizi, Mark and Darren He.
Four Correlates of Complex Behavioral Networks: Differentiation, Behavior, Connectivity, and Compartmentalization.
A hierarchical universality of these features is reported across a wide range of phenomena such as nervous systems, organisms, social groups, economies, and ecosystems.
Changizi, Mark and Marc Destefano. Common Scaling Laws for City Highway Systems and the Mammalian Neocortex. Complexity. Early View Online, N, 2009. Rensselaer Polytechnic Institute cognitive scientists offer an example of a growing literature that finds the same neural geometries and dynamics everywhere.
Chater, Nick and Gordon Brown. From Universal Laws of Cognition to Specific Cognitive Models. Cognitive Science. 32/1, 2008. A contribution to a special section on the project of the Stanford University’s Roger Shepard to discern common psychological principles that proposes a recent notice of recurrent invariances across a wide range of neural and functional scales could aid such an integration. Moreover this feature would connect human intellect with similar topologies throughout physical nature. (Compare with Hierarchical Approaches to Understanding Consciousness by L. Andrew Coward and Ron Sun, which reaches the same surmise.)
Scale invariance provides an explanation for a wide range of psychological regularities, including many that aspire to the status of psychological laws. We suggest that scale-invariance should be expected, as a null hypothesis in cognitive science, as it is in the natural and social sciences. (39)
Chen, Yanguang. Analogies between Urban Hierarchies and River Networks: Fractals, Symmetry, and Self-organized Criticality. Chaos, Solitons, & Fractals. 40/4, 2009. As the quote describes, a Peking University systems geographer finds nature’s innate nonlinear patterns and processes to be equally manifest in the disparate realms of geological fluid flow and citified human settlements. “Both networks of rivers and systems of cities reach the same goal through different paths in that they are governed by the same natural laws.”
A pair of nonlinear programming models is built to explain the fractal structure of systems of cities and those of rivers. The hierarchies of cities can be characterized by a set of exponential functions, which is identical in form to the Horton–Strahler’s laws of the river networks. Four power laws can be derived from these exponential functions. The evolution of both systems of cities and rivers are then represented as nonlinear dual programming models: to maximize information entropy subject to a certain energy use or to minimize energy dissipation subject to certain information capacity. The optimal solutions of the programming problems are just the exponential equations associated with scaling relations. By doing so, fractals and the self-organized criticality marked by the power laws are interpreted using the idea from the entropy-maximization principle, which gives further weight to the suggestion that optimality of the system as a whole defines the dynamical origin of fractal forms in both nature and society. (Abstract, 1766)
Cherednik, Ivan. Modeling the Waves of COVID 19. Acta Biotheoretica. December, 2021. We cite this entry by a University of North Carolina mathematician as a record of myriad similar complexity analyses the world over since 2020 which have found and articulated an independent, universal source code program underlying viral epidemic phenomena. See also, e.g., SARS-Cov-2 Emerging Complexity and Global Dynamics by Francesca Bertacchini, et al in Chaos (December 2021).
The challenges with modeling the spread of Covid-19 are its power-type growth during the middle stages of the waves with the exponents depending on time. The two-phase solution we propose for modeling the total number of detected cases of Covid-19 describes the actual curves for its waves in many countries, almost with the accuracy of physics laws. Bessel functions play the key role and the differential equations we obtain are universal in kind as also present for behavioral psychology, invasion ecology, etc. This theory provides a convincing explanation of the surprising uniformity of the Covid-19 waves and can help forecast the epidemic spread. (Abstract excerpt)