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IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Generative Code-Script Source

5. Common Code: A Further Report of Reliable, Invariant Principles

Christensen, Kim, et al. Universality in Ant Behavior. Journal of the Royal Society Interface. Online November, 2014. Imperial College London, University of Bristol, and University of the West of England system entomologists, including Nigel and Ana Franks, report on a constant scaling function that applies to colony movements at any speed or length. It is then alluded that such general principles must exist on their independent own, and should hold for any animal, or human, grouping. If properly understood, these insights can aid more felicitous social organizations.

Our results are based on the activity of ants but we are convinced that our main conclusion that the duration of an activity event is determined before it commences is likely to be applicable as a general principle of animal behaviour across taxa, including humans. As our results also demonstrate, such a principle is not fixed and works in a feedback loop with the environment. Furthermore, the colonies in our experiment were in everyday, static conditions. If these conditions are perturbed and the system is under stress, things could change. Such hypotheses should be tested in future experiments using the generic framework applied here. This will elucidate further the underlying causal relationships in the way biological social systems work and inform the engineering and control of artificial social systems. (7)

Coen, Enrico. Cells to Civilizations: The Principles of Change That Shape Life. Princeton: Princeton University Press, 2012. Review more in Current Vistas, from 2012 a geneticist can articulate a nature's constant avail of the same principles at each and every emergent phase.

Cofre, Rodrigo, et al. A Comparison of the Maximum Entropy Principle Across Biological Spatial Scales. Entropy. 21/10, 2019. University of Valparaiso, Pontifical Catholic University, Chile and Imperial College London mathematical physicists cite another perceptive method to discern nature’s recurrent geometries as they track and rise from life’s origin to we peoples. See also Quantifying High-Order Interdependencies via Mutual Information (Rosas 2019 herein) for a companion effort. The endeavor and its findings are quite timely as public demonstrations rile Chilean cities, and many other nations, for better governmental, economic, and climatic policies.

Despite their differences, biological systems arrayed as nested levels tend to exhibit common organizational patterns. But these commonalities are often hard to grasp due to the specialized nature of modern science and parcelled terminology employed by scientific sub-disciplines. To explore these organizational features, this paper provides a comparative study of diverse applications of the maximum entropy principle, which has found many uses at different biological stages ranging from amino acids up to societies. By presenting these studies under an accessible approach and language, our aim is to establish a unified view over these seemingly heterogeneous scenarios. (Abstract)

One of the most powerful features of the MEP is its generality, which enables its use over an extremely broad range of scenarios. This section explores six case studies of the application of the MEP in biology at different spatial scales, employing a unified methodology and notation. The cases are amino acids in proteins, retinal ganglion cells, whole brain networks, plant communities, macroecologic biodiversity, and human vote interactions in the US Supreme Court. (4-5)

Csermely, Peter. Weak Links: Stabilizers of Complex Systems from Proteins to Social Networks.. Heidelberg: Springer, 2006. A biochemist from Semmelweis University in Budapest presents his theory that loose connections between elements or components in a dynamic network yet provides a modicum of glue which endows an inherent robustness. As an exception to such technical works, it is a well-written, accessible entry to the expanses of natural and social complexity, along with a huge bibliography. By clever rhetorical devices, a self-similar universality, (as above, so below), is initially discerned, which can then be noticed everywhere from genomes to Gaia. A deep nestedness accrues, whereof nodes are themselves networks, which persists throughout a self-creating cosmos.

Practically every complex system can be imagined as a network. Atoms form a network making macromolecules. Proteins form a network making cells. Cells form a network making organs and bodies. We form a network making our societies, and so on. Most of these networks are a result of self-organization. In fact, self-organization seems to be an inherent property of matter in our Universe. (xi) Recent evidence indicates that many scale-free networks can be simplified, renormalized to a self-similar, fractal hierarchy of network motifs. (22) Modularization is a spontaneously occurring property of networks, where the links are gradually reorganized. Module formation is related to the fractal growth of networks. (38)

DeDeo, Simon and David Krakauer. Dynamics and Processing in Finite Self-Similar Networks. Journal of the Royal Society Interface. September 7,, 2012. Also posted as a PDF at arXiv:1109.2648. As complex systems science reaches a robust maturity, Santa Fe Institute resident theorists verify its ubiquitous aspects of component identity, structural topology, signal communication, recursive loops, and their nested iteration across life, genomes, cognition, and societies. An extensive bibliography provides further support. Nodes and links, hubs and connections, weight, communicate, branch, ramify, develop, merge and evolve everywhere.

A common feature of biological networks is the geometric property of self-similarity. Molecular regulatory networks through to circulatory systems, nervous systems, social systems and ecological trophic networks, show self-similar connectivity at multiple scales. (Abstract, 2131)

Biological networks exhibit a wide range of structural features at multiple spatial scales. These include local circuitry reflecting the logic of regulation among small numbers of elements, and motifs of statistically over-represented patterns within larger networks of interactions, through to macroscopic properties of complete networks including the description of the degree distributions and the large scale geometric features of networks. Among the most interesting geometric properties of biological networks is the property of self-similarity or scale invariance, in which characteristic topological features are present at all scales from the local organization of individual nodes, through to aggregations at the largest network scales. (2131)

Visually, our constructions possess fractal-like properties, with self-similarity upon coarse-graining. Our formal definition of the construction of these networks amounts, in the reverse direction, to a specification of a renormalization group transformation. The two simplest choices of node replacement lead to two different kinds of network: a branching topology, characterized by the absence of large-scale loops, and a nested topology, where the loop structure of the base motif is replicated on all scales. (2135)

Deisboeck, Thomas and J. Yasha Kresh, eds. Complex Systems Science in Biomedicine. New York: Springer, 2006. An 850 page compendium which covers both the range of nonlinear complexity, especially network phenomena, and their dynamic presence in organisms from genes and cells to developmental, metabolic, neurological, cardiac, immune, and other functions. These novel understandings of anatomy and physiology by way of complex adaptive systems then opens up new approaches to treat diseases, cancer, the aging process, genetic disorders, and so on. A luminous array of authors includes mathematical theorists and physician researchers, along with a preface by Stuart Kauffman, MD. As befitting, the full text can be accessed in the cyberspace noosphere through Google Book Search, via title and editors.

Dobrescu, R. and Purcarea, V. Emergence, Self-Organization and Morphogenesis in Biological Structures. Journal of Medicine and Life. 4/82, 2011. When I spoke at in 2005 at Palacky University in the Czech Republic (slides on home page) a professor from the close by University of Brno, where Gregor Mendel’s garden resides, told me in so many words that Eastern Europe does not accept a Western (US & UK, Dawkins & Co.) evolutionary theory that rejects any formative cause other than post-selection. “We know it is wrong.” This paper by Polytechnic University of Bucharest and Carol Davila University of Medicine, Bucharest, researchers is cited as an exemplary witness of a prior dynamic agency that provides a universal, repetitive source. We ought to remember how much science is bent by personalities, biases, preconditions, and so on, which govern what can be seen and permitted or not. The text is online in full at the journal site.

The paper discusses the connection between emergence, pattern formation and nonlinear dynamics, focusing on the similarity between discrete patterns and fractal structures, and then describes different solutions to model reaction-diffusion systems as representative processes in morphogenesis. A specific example is the diffusion limited aggregation growth process, illustrated by the simulation of the evolution of a bacterial colony that shows the roles of instability and sensitivity in non-equilibrium pattern formation. Based on this particular case, it is shown how self-organization could be achieved from non-organized agglomeration of separate entities, in a region of space. We conclude with some brief remarks about universality, predictability and long-term prospects for this field of research. (Abstract)

It is important to note that the main properties such as the existence of distinct cell types, the homeostatic stability of cell types, the number of cell types in an organism, the similarity in gene expression patterns in different cell types, the fact that development from the fertilized egg is organized around branching pathways of cell differentiation, and many other aspects of differentiation are all consequences of properties of self organization, so profoundly immanent in complex regulatory networks whose order selection cannot avoid. All aspects of differentiation appear to be properties of complex parallel–processing systems lying in the ordered regime. These properties may therefore reflect quasi–universal features of organisms due not to selection alone, but also to the spontaneous order of the systems on which selection has been privileged to act. (89)

Dorit, Robert. The Humpty-Dumpty Problem. American Scientist. July-August, 2011. The Smith College biologist muses that a major, dedicated effort is overdue to put life and everything back together again, after centuries of partitioning and fragmenting. Lately driven by computer prowess, such an interactionist perspective for living systems can illume and quantify, within a “new harmony,” a reciprocal interplay of parts and their iterative, modular, vital organizations.

Earnest, Tyler, et al. Simulating Biological Processes: Stochastic Physics from Whole Cells to Colonies. Reports on Progress in Physics. 81/5, 2018. University of Illinois, Urbana computational physicists and chemists including Zaida Luthey-Schulten pursue a translational interpretation of (multi) cellular biology by way of dynamic physical principles. Per the second quote, their goal is to quantify living phenomena in a way to better join and assimilate life within the encompassing natural cosmos. If to reflect, the past decades and centuries of scientific studies now appear as a single endeavor from individuals and groups to our global collaboration so as to achieve this integral, imperative organic unity.

The last few decades have revealed the living cell to be a crowded spatially heterogeneous space teeming with biomolecules whose concentrations and activities are governed by intrinsically random forces. It is from this randomness, however, that a vast array of precisely timed and intricately coordinated biological functions emerge to the complex forms and behaviors in the biosphere around us. This seemingly paradoxical nature of life has drawn the interest of an increasing number of physicists, and recently stochastic modeling has grow into a major subdiscipline within biological physics. We describe how stochasticity impacts key biological functions, including transcription, translation, ribosome biogenesis, chromosome replication, and metabolism, as they may be coupled into a comprehensive model of a 'minimal cell'. We consider the future of the field, focusing on how mesoscopic stochastic methods may be augmented with atomic-scale molecular modeling approaches to understand life across a range of length and time scales. (Abstract edited excerpts)

The ultimate goal of constructing whole-cell simulations is to describe life in the language of physics. The vocabulary is, of course, well known – we speak of thermodynamic potentials, molecular conformations, chemical transformations and reactions – but the grammar, the system of integrating methods that span vastly different time and length scales, and whose applicabilities are often mutually exclusive, into a cohesive picture of the living cell remains elusive. This final section is intended to outline in broad terms our expectations for the future of the field. (28)

Eisler, Zoltan, et al. Fluctuation Scaling in Complex Systems. Advances in Physics. 57/1, 2008. In the study of nonlinear phenomena from galaxies to Gaia, two approaches can be taken: to view each subject tree (scientific field) or the whole (temporal cosmos) forest. Most often, metabolic networks e.g., the task is to quantify patterns and processes in a specific domain. The other approach, which might be termed ‘systems physics,’ reported in journals such as Physical Review E and the above, is to distill and extract common generalities across nature’s nested hierarchy from universe to human. Researchers from Hungary, France and the U.S. here pursue the latter path as they emphasize a salient feature whereby “the fluctuation in the activity of an (interactive) element grows monotonically with the average activity” and go on to show this quality indeed characterizes dynamic nature everywhere.

Interacting systems of many units with emergent collective behavior are often termed ‘complex.’ Such complex systems are ubiquitous in many fields of research ranging from engineering sciences through physics and biology to sociology. An advantage of the related multi-disciplinary approach is that the universal appearance of several phenomena can be revealed more easily. Such generally observed characteristics include (multi-)fractality or scale invariance, the related Pareto or Zipf laws, self-organized and critical behavior. (91) We believe that a possible common origin of all FS laws is the generality of these underlying mean-field mathematical structures. (134)

Etxeberria, Arantza and Kepa Ruiz-Moreno. The Challenging Biology of Transients. EMBO Reports. 10/Special Issue, 2009. Within an issue on “Science and Society,” University of the Basque Country philosophers content that the systems turn in many fields, notably biological and genetics research, can offer new appreciations of cooperative, autopoietic relations which actually enhance an autonomous individuality for members. By these lights, a better definition of living organisms is gained, to further distinguish from mere machines. As a result, self-organized life can be seen to spread deeper roots into basic physical realms.

Feagin, R. A., et al. Individual versus Community Level Processes and Pattern Formation in a Model of Sand Dune Succession. Ecological Modelling. 183/4, 2005. This specific study provides a microcosm of nature’s reciprocal interplay of entity (plant, person) and relevant group. Pierre Teilhard de Chardin termed this “creative union.” In so doing, nature can teach a common principle and wisdom that could well serve our human abide.

The results showed that the plant patterns were due to individual plant responses to their environment within their local neighborhood, yet these responses were constrained by the global history of the community. (Abstract 435) The results of this study are an important contribution to the theoretical debate over whether individualistic or community-unit processes drive the formation of pattern in plant communities. The model demonstrates that within sand dune plant communities, both processes affect pattern formation. (447)

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