III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

2. A Consilience as Physics, Biology and People Become One

Leng, Biao, et al. Gravitational Scaling in Beijing Subway Network. arXiv:1606.01208. Beihang University (a major public research facility in Beijing) physicists, along with Shlomo Havlin, the veteran Israeli systems theorist, draw upon the physics of Newtonian gravity, self-organized criticality, and network dynamics to discern an independent motive source which serves to organize commuter traffic. The study follows up a similar work as Scaling and Renormalization in the Seoul Bus System by Segun Goh, et al (PLoS One 9/3, 2014), second Abstract. And to reflect, these findings, among many more, infer a double domain of human activities which are actually guided by and exemplify an independent self-organizing mathematics.

Recently, with the availability of various traffic datasets, human mobility has been studied in different contexts. Researchers attempt to understand the collective behaviors of human movement with respect to the spatio-temporal distribution in traffic dynamics, from which a gravitational scaling law characterizing the relation between the traffic flow, population and distance has been found. However, most studies focus on the integrated properties of gravitational scaling, neglecting its dynamical evolution during different hours of a day. Investigating the hourly traffic flow data of Beijing subway network, based on the hop-count distance of passengers, we find that the scaling exponent of the gravitational law is smaller in Beijing subway system compared to that reported in Seoul subway system. This means that traffic demand in Beijing is much stronger and less sensitive to the travel distance. Furthermore, we analyzed the temporal evolution of the scaling exponents in weekdays and weekends. Our findings may help to understand and improve the traffic congestion control in different subway systems. (Leng abstract)

Social systems have recently attracted much attention, with attempts to understand social behavior with the aid of statistical mechanics applied to complex systems. Collective properties of such systems emerge from couplings between components, for example, individual persons, transportation nodes such as airports or subway stations, and administrative districts. Among various collective properties, criticality is known as a characteristic property of a complex system, which helps the systems to respond flexibly to external perturbations. This work considers the criticality of the urban transportation system entailed in the massive smart card data on the Seoul transportation network. Analyzing the passenger flow on the Seoul bus system during one week, we find explicit power-law correlations in the system, that is, power-law behavior of the strength correlation function of bus stops and verify scale invariance of the strength fluctuations. Such criticality is probed by means of the scaling and renormalization analysis of the modified gravity model applied to the system. Here a group of nearby (bare) bus stops are transformed into a (renormalized) “block stop” and the scaling relations of the network density turn out to be closely related to the fractal dimensions of the system, revealing the underlying structure. It is thus demonstrated that such ideas of physics as scaling and renormalization can be applied successfully to social phenomena exemplified by the passenger flow. (Goh abstract)

Lou, Yuting, et al. Homeostasis and Systematic Ageing as Non-equilibrium Phase Transitions in Computational Multicellular Organizations. Royal Society Open Science. Online July 10, 2019. University of Tokyo and Fudan University, Shanghai systems biologists provide another notice of physical principles at work throughout life’s somatic activities and long developmental course.

The breakdown of homeostasis in tissues involves multiscale factors ranging from the accumulation of genetic damages to the deregulation of metabolic processes. Here, we present a multicellular homeostasis model in the form of a two-dimensional stochastic cellular automaton with three cellular states, cell division, cell death and cell cycle arrest. Our model illustrates how organisms can develop into diverse homeostatic patterns with distinct morphologies, turnover rates and lifespans without considering genetic, metabolic or other variations. Those homeostatic states exist in extinctive, proliferative and degenerative phases, which undergo a systematic ageing akin to a transition in non-equilibrium physical systems. (Abstract excerpt)

Love, Alan, et al. Perspectives on Integrating Genetic and Physical Explanations of Evolution and Development. Integrative & Comparative Biology. 57/6, 2017. In this Oxford Academic journal, Love, Thomas Stewart, Gunter Wagner, and Stuart Newman introduce this symposium, notably a century after D’Arcy Thompson’s On Growth and Form, about many intrinsic structural constraints that do in fact affect life’s anatomy and physiology. See, herein for example, The Origin of Novelty through the Evolution of Scaling Relationships, by Fred Nijhout and Ken McKenna.

In the 20th century, genetic explanatory approaches became dominant in both developmental and evolutionary biological research. By contrast, physical approaches, which appeal to properties such as mechanical forces, were largely relegated to the margins, despite important advances in modeling. Recently, there have been renewed attempts to find balanced viewpoints that integrate both biological physics and molecular genetics into explanations of developmental and evolutionary phenomena. Here we introduce the 2017 SICB symposium “Physical and Genetic Mechanisms for Evolutionary Novelty” that was dedicated to exploring empirical cases where both biological physics and developmental genetic considerations are crucial. We conclude by arguing that intentional reflection on conceptual questions about investigation, explanation, and integration is critical to achieving significant empirical and theoretical advances in our understanding of how novel forms originate across the tree of life. (Abstract)

Marais, Adriana, et al. The Future of Quantum Biology. Journal of the Royal Society Interface. Vol.15/Iss.148, 2018. A dozen scientists from the University of KwaZulu-Natal, Durban, VU University, Amsterdam, and Cambridge University offer a latest report with 133 references of how a quantum transfer of energy and charge which involves superposition, coherence and entanglement can be seen at work in such areas as photosynthesis, enzyme catalysis, olfaction, respiration, neuronal sensations and onto cognition. Still another instance is their presence at life’s biophysical and biochemical origin and complexification.

Biological systems are dynamical, constantly exchanging energy and matter with the environment in order to maintain the non-equilibrium state synonymous with living. Developments in observational techniques have allowed us to study biological dynamics on increasingly small scales. Such studies have revealed evidence of quantum mechanical effects, which cannot be accounted for by classical physics, in a range of biological processes. Quantum biology is the study of such processes, and here we provide an outline of the current state of the field, as well as insights into future directions. (Abstract)

Marson, G. Ajmone, et al. Stochastic Evolutionary Differential Games toward a System of Behavioral Social Dynamics. Mathematical Models and Methods in Applied Sciences. 26/6, 2016. In a well rated World Scientific journal, this paper by mathematicians G. A. Marsan, Organization for Economic Cooperation and Development OECD, Paris, Nicola Bellomo, King Abdulaziz University, Jeddah, and Livio Gibelli, Polytechnic University of Turin was cited as the most read of the year. Also at arXiv:1506.05699. It is an inquiry into how novel theories of self-active kinetic matter might, by way of “big data” networks, be applied far afield to a range of social and economic systems. See also Mathematical Models of Self-Propelled Particles by N. Bellomo and F. Brezzi in this journal (27/6, 2017).

This paper proposes a systems approach to social sciences based on a mathematical framework derived from a generalization of the mathematical kinetic theory and of theoretical tools of game theory. Social systems are modeled as a living evolutionary ensemble composed of many individuals, who express specific strategies, cooperate, compete and might aggregate into groups which pursue a common interest. A critical analysis on the complexity features of social system is developed and a differential structure is derived to provide a general framework toward modeling. (Abstract)

McFadden, Johnjoe and Jim Al-Khalili. Life on the Edge: The Coming of Age of Quantum Biology. New York: Bantam, 2014. A geneticist and a physicist, both at the University of Surrey, draw upon the leading edges of biological and physical science to explain a grand cross-integration of evolutionary organisms and a lively natural cosmos.

McFadden, Johnjoe and Jim Al-Khalili. The Origins of Quantum Biology. Proceedings of the Royal Society A. Vol.474/Iss.2220, 2018. A University of Surrey, UK biologist and a physicist who have each authored prior works (search) achieve a unique, thorough history of this incipient synthesis from A. N. Whitehead, Erwin Schrodinger and others such as organicists and vitalists, aka the Cambridge Theoretical Biology Club, to its worldwise fruition today. From this retro-vista, an Order from Order phrase can be coined, which is seen in effect by a flow of recent findings, as the abstract notes.

Quantum biology is usually considered to be a new discipline, arising from recent research that suggests that biological phenomena such as photosynthesis, enzyme catalysis, avian navigation or olfaction may not only operate within the bounds of classical physics but also make use of a number of the non-trivial features of quantum mechanics, such as coherence, tunnelling and, perhaps, entanglement. However, although the most significant findings have emerged in the past two decades, the roots of quantum biology go much deeper—to the quantum pioneers of the early twentieth century. We will argue that some of the insights provided by these pioneering physicists remain relevant to our understanding of quantum biology today. (Abstract)

Clearly, quantization applies to all matter at the microscopic scale and has long been assimilated into standard molecular biology and biochemistry. Today, quantum biology refers to a small, but growing, number of rather more specific phenomena, well known in physics and chemistry, but until recently thought not to play any meaningful role within the complex environment of living cells. (1)

What remains indisputable is that the quantum dynamics that are undoubtedly taking place within living systems have been subject to 3.5 billion years of optimizing evolution. It is likely that, in that time, life has learned to manipulate quantum systems to its advantage in ways that we do not yet fully understand. They may have had to wait many decades, but the quantum pioneers were indeed right to be excited about the future of quantum biology. (11)

Melkikh, Alexey and Andrei Khrennikov. Mechanisms of Directed Evolution of Morphological Structures and the Problems of Morphogenesis. Biosystems. 168/26, 2018. Reviewed more in Systems Evolution, a latest essay by the Ural Federal University, Russia and Linnaeus University, Sweden theorists.

Mohseni, Masoud, et al. Quantum Effects in Biology. Cambridge: Cambridge University Press,, 2014. Among the editors and authors are Martin Plenio, Seth Lloyd, Graham Fleming, and Elisabet Romero (See Nature Physics 10/9, 2014). One of the first book-length collections which gathers years of research and realizations that, if properly understood, “quantum” phenomena are not arcane and off-putting. Instead, as the quote notes, their creative presence can then be found across all realms of living, quickening nature.

Quantum biology, as introduced in the previous chapter, mainly studies the dynamical influence of quantum effects in biological systems. In processes such as exciton transport in photosynthetic complexes, radical pair spin dynamics in magnetoreception, and photo-induced retinal isomerization in the rhodopsin protein, a quantum description is a necessity rather than an option. The quantum modelling of biological processes is not limited to solving the Schrödinger equation for an isolated molecular structure. Natural systems are open to the exchange of particles, energy or information with their surrounding environments that often have complex structures. Therefore the theory of open quantum systems plays a key role in dynamical modelling of quantum-biological systems. Research in quantum biology and open quantum system theory have found a bilateral relationship. Quantum biology employs open quantum system methods to a great extent while serving as a new paradigm for development of advanced formalisms for non-equilibrium biological processes. (Chapter 2, Open Quantum System Approaches to Biological Systems)

Mora, Thierry, et al. Questioning the Activity of Active Matter in Natural Flocks of Birds. arXiv:1511.01958. A team of nine physicists across Europe including Irene Giardina, Leonardo Parisi, Aleksandra Walczak, and Andrea Cavagna continue to expand and finesse a viewing animal groupings as exemplars of complex adaptive self-organizing systems. For a philosophical surmise, one might imagine a universally iterative nature not as only a book, an encyclopedia testament, but as a three dimensional, graphic revelation which our phenomenal human phase is meant to read, and to enhance anew.

The correlated motion of large bird flocks is an instance of self-organization where global order emerges from local interactions. Despite the analogy with ferromagnetic systems, a major difference is that flocks are active -- animals move relative to each other, thereby dynamically rearranging their interaction network. Although the theoretical importance of this off-equilibrium ingredient has long been appreciated, its relevance to actual biological flocks remains unexplored. Here we introduce a novel dynamical inference technique based on the principle of maximum entropy, which takes into account network reshuffling and overcomes the limitations of slow experimental sampling rates. We apply this method to three-dimensional data of large natural flocks of starlings, inferring independently the strength of the social alignment forces, the range of these forces, and the noise.

Moretti, Paolo and Miguel Munoz. Griffiths Phases and the Stretching of Criticality in Brain Networks. Nature Communications. Online October, 2013. We cite this paper as a good example of a growing sense, often by translation of terms, of the deepest affinities between all manner of biological and cerebral form and behavior with such basic physical phenomena. In this case University of Granada, Spain, computational neuroscientists draw parallels between the definitive self-organized critical poise of neural activity and mechanisms of statistical physics. The import of this study was noted by Claus Hilegetag and Marc-Thorsten Hutt in “Hierarchical Modular Brain Connectivity is a Stretch for Criticality” in Trends in Cognitive Sciences (Online November 2013).

Hallmarks of criticality, such as power-laws and scale invariance, have been empirically found in cortical-network dynamics and it has been conjectured that operating at criticality entails functional advantages, such as optimal computational capabilities, memory and large dynamical ranges. As critical behaviour requires a high degree of fine tuning to emerge, some type of self-tuning mechanism needs to be invoked. Here we show that, taking into account the complex hierarchical-modular architecture of cortical networks, the singular critical point is replaced by an extended critical-like region that corresponds—in the jargon of statistical mechanics — to a Griffiths phase. Using computational and analytical approaches, we find Griffiths phases in synthetic hierarchical networks and also in empirical brain networks such as the human connectome and that of Caenorhabditis elegans. Stretched critical regions, stemming from structural disorder, yield enhanced functionality in a generic way, facilitating the task of self-organizing, adaptive and evolutionary mechanisms selecting for criticality. (Abstract)

A new paper shows that a characteristic feature of the arrangement of brain networks, their modular organization across several scales, is responsible for an expanded range of critical neural dynamics. This finding solves several puzzles in computational neuroscience and links fundamental aspects of neural network organization and brain dynamics. (Hilgetag, Hutt Abstract)

Morone, Flaviano, et al. Fibration Symmetries Uncover the Building Blocks of Biological Networks. Proceedings of the National Academy of Sciences. 117/8306, 2020. CCNY systems physicists including Hernan Makse describe a novel geometric intersect between living systems and their physical substrate by way of these webwork intricacies. Notably then the contribution serve belies its own inorganic building block metaphor.

The success of symmetries in explaining the physical world, from general relativity to particle physics and all phases of matter, raises the question of whether the same concept could explain emergent properties of biological systems. In other words, if life is an emergent property of physics then the symmetry principles that inform physics should also apply to the organizing principles of life. Here we show that a form of symmetry called fibration can describe the nodes and links of biological networks and other social and infrastructure networks. This result broadly opens the way to understand how information-processing networks are assembled from the bottom up. (Significance)

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