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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
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III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet Incubator Lifescape

2. A Consilience as Physics and Biology Grow Together: Active Matter

Mugler, Andrew and Bo Sun. Special Issue on Emergent Collective Behavior form Groups of Cells. Physical Biology. 115/6363, 2018. Purdue University and Oregon State University biophysicists introduce a collection of new findings about how physical phenomena are intimately engaged in biological development and activities. See for example Biophysical Constraints Determine the Selection of Pheneotypic Fluctuations During Directed Evolution by Hong-Yah Shih, et al in this issue.

Single cells perform extraordinary tasks: they follow chemical cues, process environmental information, make life-or-death decisions, and replicate themselves. Yet, few cells are truly 'single'. Even single-celled organisms exist and interact within complex communities. In recent years, it has become particularly evident that when groups of cells act collectively, their performance improves or they perform new tasks altogether. This special issue collects papers focusing on the new and improved behaviors that emerge when cells interact. In these reports cells interact in three major ways: competition, cooperation, and communication, and the interactions may be mechanical or biochemical in nature. A wide range of systems are discussed, from virus-host pathogenesis, growth and evolution of bacteria, to the motility, mechanosensing, and force generation of mammalian cells. (Summary)

Nagel, Sidney. Experimental Soft-Matter Science. Reviews of Modern Physics. 89/025002, 2017. A summary of a January 2016 workshop as admissions and insights grow about these non-equilibrium lively material forms, of which the article is a good tutorial. This heretofore unnoticed realm is cited as disordered, nonlinear, thermal and entropic, observable, gravity-affected, nonlocal, patterned, interfacial elastic, memory retaining, to wit active matter. That is to say it expresses an organic essence.

Soft materials consist of basic units that are significantly larger than an atom but much smaller than the overall dimensions of the sample. The label “soft condensed matter” emphasizes that the large basic building blocks of these materials produce low elastic moduli that govern a material’s ability to withstand deformations. Aside from softness, there are many other properties that are also caused by the large size of the constituent building blocks. Soft matter is dissipative, disordered, far from equilibrium, nonlinear, thermal and entropic, slow, observable, gravity affected, patterned, nonlocal, interfacially elastic, memory forming, and active. This is only a partial list of how matter created from large component particles is distinct from “hard matter” composed of constituents at an atomic scale. (Abstract)

Nardini, Cesare, et al. Entropy Production in Field Theories without Time Reversal Symmetry: Quantifying the Non-Equilibrium Character of Active Matter. Physical Review X. 7/021007, 2017. A six member team with postings in the UK, Scotland, and France press this theoretical frontier researching these lively propensities of material nature as they engender self-emergent animate behaviors.

Nastasiuk, Vadim. Emergent Quantum Mechanics of Finances. Physica A. Online February, 2014. On the shores of the Black Sea, a South Ukrainian National Pedagogical University, Odessa, researcher proposes ways that quantum phenomena might be in dynamic effect even for widely removed economic transactions. If a cross-correspondence can be drawn, it would then aid studies of market volatilities. In regard, might a wider palliative discovery at last accrue by which to realize a single, infinitely iterative, genesis, a natural guidance for peoples to move beyond the guns of 2014 and become planetary patriots?

This paper is an attempt at understanding the quantum-like dynamics of financial markets in terms of non-differentiable price–time continuum having fractal properties. The main steps of this development are the statistical scaling, the non-differentiability hypothesis, and the equations of motion entailed by this hypothesis. From perspective of the proposed theory the dynamics of S&P500 index are analyzed. (Abstract)

Needleman, Daniel and Zvonimir Dogic. Active Matter at the Interface between Materials Science and Cell Biology. Nature Reviews Materials. 2/17048, 2017. We cite this entry by Harvard and Brandeis University physicists as a latest iconic case of human endeavors to learn and express what innate essence that extant nature might actually have. In regard, the paper opens with a quote by Gottfried Leibniz from Jessica Riskin’s fine history The Restless Clock (2016 herein) that intertwines machine and organism aspects. We add three quotes which reflect the conflation. The consideration is that this novel 2010s perception of intrinsic, non-equilibrium, self-organized vitalities may finally achieve a quantified meld of physical matter and animate biology.

The remarkable processes that characterize living organisms, such as motility, self-healing and reproduction, are fuelled by a continuous injection of energy at the microscale. The field of active matter focuses on understanding how the collective behaviours of internally driven components can give rise to these biological phenomena, while also striving to produce synthetic materials composed of active energy-consuming components. The synergistic approach of studying active matter in both living cells and reconstituted systems assembled from biochemical building blocks has the potential to transform our understanding of both cell biology and materials science. This methodology can provide insight into the fundamental principles that govern the dynamical behaviours of self-organizing subcellular structures, and can lead to the design of artificial materials and machines that operate away from equilibrium and can thus attain life-like properties. In this Review, we focus on active materials made of cytoskeletal components, highlighting the role of active stresses and how they drive self-organization of both cellular structures and macroscale materials, which are machines powered by nanomachines. (Abstract)

Figure 1: Organisms are machines made from machines. Organisms are composed of tissues, which are non-equilibrium assemblages of cells. Cells are built from non-equilibrium self-organized structures, and subcellular structures are composed of energy-transducing molecular motors and filaments. In the schematic, one cell is undergoing cell division and contains a spindle (a structure that segregates chromosomes during cell division), which is made of microtubules (filament structures in the cytoskeleton) and molecular motors. The close-up views show a molecular motor that is crosslinking and sliding between two microtubules and the end of a microtubule that is dynamically shrinking. (2)

Here we review recent advances that have transformed active matter into a mature and rapidly expanding research field that spans diverse disciplines, ranging from soft matter physics to cell biology, to materials science, and to engineering. We focus on experimental
work at the interface between cell biology and materials science, as well as on the potential for each of these lines of research to influence and benefit the others. We first provide a brief historical perspective on the importance of active processes in the biological organization of cells. Next, we discuss active materials assembled from purified cytoskeletal components, which are classified according to the symmetries of their structures and stresses, and we review advances that demonstrate the essential role of active stresses and out-of-equilibrium self-organization in cytoskeletal systems in cells. We conclude by placing these topics in the broader context of other realizations of active matter. We also note that active matter is a much broader field that is being investigated using a wide array of synthetic model systems that are either externally or internally driven. (2)

Nourmohammad, Armita, et al. Universality and Predictability in Molecular Quantitative Genetics. arXiv:1309.3312. Posted November 2013, Nourmohammad, and Torsten Held, Princeton University integrative geneticists, and Michael Lassig, University of Colonge biophysicist, convey the present merger of statistical, condensed matter physics with all aspects of life’s evolution, along with the popular trend to report and affirm a universal recurrence of the same phenomena across every domain and instance. The paper is forthcoming in Current Opinion in Genetics and Development. See also among Lassig’s prior papers “From Fitness Landscapes to Seascapes: Non-Equilibrium Dynamics of Selection and Adaptation” with Ville Mustonen in Trends in Genetics (25/3, 2009).

Molecular traits, such as gene expression levels or protein binding affinities, are increasingly accessible to quantitative measurement by modern high-throughput techniques. Such traits measure molecular functions and, from an evolutionary point of view, are important as targets of natural selection. We review recent developments in evolutionary theory and experiments that are expected to become building blocks of a quantitative genetics of molecular traits. We focus on universal evolutionary characteristics: these are largely independent of a trait's genetic basis, which is often at least partially unknown. We show that universal measurements can be used to infer selection on a quantitative trait, which determines its evolutionary mode of conservation or adaptation. Furthermore, universality is closely linked to predictability of trait evolution across lineages. We argue that universal trait statistics extends over a range of cellular scales and opens new avenues of quantitative evolutionary systems biology. (Abstract)

This article is on universality in molecular evolution. We introduce universality as an emerging statistical property of complex traits, which are encoded by multiple genomic loci. We give examples of experimentally observable universal trait characteristics, and we argue that universality is a key concept for a new quantitative genetics of molecular traits. Three aspects of this concept are discussed in detail. First, universal statistics governs evolutionary modes of conservation and adaptation for quantitative traits, which can be used to infer natural selection that determines these modes. Furthermore, there is a close link between universality and predictability of evolutionary processes. Finally, universality extends to the evolution of higher-level units such as metabolic and regulatory networks, which provides a link between quantitative genetics and systems biology. (1)

In a broad sense, universality means that properties of a large system can become independent of details of its constituent parts. This term has been coined in statistical physics, where it refers to macroscopic properties of large systems that are independent of details at the molecular scale. Universality also arises in evolutionary biology. As in physics, it is a property of systems with a large number of components, and it has strong consequences for experiment and data analysis. (1)

Again, the reason for universality is that changes in one pathway component tend to be buffered by compensatory changes in other components. These compensations can be statistical or systematic, that is, generated by feedback loops in the pathway organization. Universality and predictability of pathway output emerge primarily in complex, higher-level pathways, which have multiple compensatory channels. This suggests the hierarchy of molecular functions is reflected by an evolutionary hierarchy: universality and predictability increase, while stochasticity decreases with increasing level of complexity. (10)

Nussinov, Zohar, et al. Inference of Hidden Structures in Complex Physical Systems by Multi-Scale Clustering. arXiv:1503.01626. American and Indian physicists contend that condensed matter/statistical mechanic studies, which are lately coming to assume an intricately networked nature, have found a persistent tendency to form modular communities. Such whole units, with their own integrity while immersed in multiple layers, are a prime, natural feature. And if we might avail, a much better society could be conceived as many, interlinked communal villages in a local and global organic, physiological milieu.

We survey the application of a relatively new branch of statistical physics--"community detection"-- to data mining. In particular, we focus on the diagnosis of materials and automated image segmentation. Community detection describes the quest of partitioning a complex system involving many elements into optimally decoupled subsets or communities of such elements. We review a multiresolution variant which is used to ascertain structures at different spatial and temporal scales. Significant patterns are obtained by examining the correlations between different independent solvers. Similar to other combinatorial optimization problems in the NP complexity class, community detection exhibits several phases. (Abstract)

Pauls, James, et al. Quantum Coherence and Entanglement in the Avian Compass. Physical Review E. 87/062704, 2013. Reviewed more in Cooperative Societies, Purdue University and LANL physicists including Sabre Kais advance the reconception and unity of physics and life as they find deep similarities and explanations. The artificial quantum-classical barrier is being removed to reveal a creative reiteration in kind and time from universe to human.

Perunov, Nikolai, et al. Statistical Physics of Adaption. arXiv.1412.1875. As the Abstract notes, MIT Physics of Living Systems Group researchers including Jeremy England contribute to the ongoing synthesis of these fields of study which serve to integrate and root life’s evolution, and our collaborative comprehension, within a fertile cosmic ground.

All living things exhibit adaptations that enable them to survive and reproduce in the natural environment that they inhabit. From a biological standpoint, it has long been understood that adaptation comes from natural selection, whereby maladapted individuals do not pass their traits effectively to future generations. However, we may also consider the phenomenon of adaptation from the standpoint of physics, and ask whether it is possible to delineate what the difference is in terms of physical properties between something that is well-adapted to its surrounding environment, and something that is not. In this work, we undertake to address this question from a theoretical standpoint. Building on past fundamental results in far-from-equilibrium statistical mechanics, we demonstrate a generalization of the Helmholtz free energy for the finite-time stochastic evolution of driven Newtonian matter. By analyzing this expression term by term, we are able to argue for a general tendency in driven many-particle systems towards self-organization into states formed through exceptionally reliable absorption and dissipation of work energy from the surrounding environment. (Abstract)

Picoli, Sergio, et al. Universal Bursty Behavior in Human Violent Conflicts. Nature Scientific Reports. 4/4773, 2014. Universidade Estadual de Maringa, Brazil, and Universidad Nacional Autonoma de Mexico, systems physicists quantify that even the most chaotic carnage can yet be seen to exhibit a common structure and activity. However and whenever might we finally altogether come to realize and understand, as so implied, that an independent mathematical source is in formative effect everywhere? Then as so edified be able to at last to declare a truce and break free from this obsession?

Understanding the mechanisms and processes underlying the dynamics of collective violence is of considerable current interest. Recent studies indicated the presence of robust patterns characterizing the size and timing of violent events in human conflicts. Since the size and timing of violent events arises as the result of a dynamical process, we explore the possibility of unifying these observations. By analyzing available catalogs on violent events in Iraq (2003–2005), Afghanistan (2008–2010) and Northern Ireland (1969–2001), we show that the inter-event time distributions (calculated for a range of minimum sizes) obeys approximately a simple scaling law which holds for more than three orders of magnitude. This robust pattern suggests a hierarchical organization in size and time providing a unified picture of the dynamics of violent conflicts. (Abstract)

Despite the fact that human activities and natural phenomena are very different in nature, it has been suggested that both could be described by a common approach. For example, the occurrence of earthquakes has been related to the relaxation of accumulated stress after reaching a threshold as in self-organized criticality (SOC). Analogously, violent events in human conflicts could be associated with a threshold mechanism. In this scenario, a description of human conflicts in terms of SOC seems plausible. Our findings are consistent with this possibility, providing quantitative support for the analogy between patterns in human conflicts and natural phenomena exhibiting SOC. (3)

Popkin, Gabriel. The Physics of Life. Nature. 529/16, 2016. A report on the growing realization of inherent material propensities, via the new field of “active matter” research, to organize and arrange into similar biological forms and motions from proteins to people.

From flocking birds to swarming molecules, physicists are seeking to understand ‘active matter’ – and looking for a fundamental theory of the living world.

Prechl, Jozsef. Statistical thermodynamics of self-organization in the adaptive immune system. arXiv:2306.04665. A senior Eotvos Lorand University, Budapest researcher contributes to the ongoing integral rooting of viable, persistent organisms withi a conducive, substantial milieu which is then seen to spontaneously vivify into a processive animate development. A Table of cardinal features from physical self-organization to an adaptive immunity enlists a thermal energy, dynamic non-linearity, multiple interactions, and more.

A steady flow of energy can be seen to arrange matter and information in particular ways by a process known as self-organization. Adaptive immunity is an instance implemented as a complex adaptive biological system that vivifies and informs itself by the maintenance of a steady state which can be modeled mathematically and physically. Here I summarize arguments for such a statistical thermodynamic interpretation of immune function and key variables that characterize self-organization in the context of biochemical energies, and network structurations. (Abstract)

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