(logo) Natural Genesis (logo text)
A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
Table of Contents
Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
Recent Additions

IV. Cosmomics: A Genomic Source Code is in Procreative Effect

B. Universality Affirmations: A Critical Complementarity

This is a new section to report scientific confirmations of an evolutionary developmental genesis from universe to us that is in fact being found to repeat patterns and processes of the same self-organizing, complex adaptive network system at every exemplary scale and instance. As we track the prolific literature, in the later 2010s one finds an increased use and affirmation such a “universality,” which then serves to imply an independent, complementary, critically poised, mathematical source code.

Another aspect and sign is the interchangeable employ of (artificial) neural networks along with genetic sequencing techniques, to study disparate realms such as whole genomes and quantum systems to cosmic and cultural phenomena. Further afield, these deep learning algorithm, self-organizing map, astroinformatic, statistical physics, phylogenetic tree methods are widely availed to better quantify areas from cosmology, chemistry to ecosystems and cultures. Into 2018, we cite next a summary for a Stochastic Models in Ecology and Evolutionary Biology conference, search Venice 2018, as a strongest instance (bold added).

Living systems are characterized by the emergence of recurrent dynamical patterns at all scales of magnitude. Self-organized behaviors are observed both in large communities of microscopic components - like neural oscillations and gene network activity - as well as on larger levels - as predator-prey equilibria, to name a few. Such regularities are deemed to be universal in the sense they are due to common mechanisms, independent of the details of the system. This belief justifies investigation through quantitative models able to grasp key features while disregarding inessential complications. (Venice conference)

Bardoscia, Marco, et al. Pathways Toward Instability in Financial Networks. Nature Communications. 8/14416, 2017. In these later 2010s, complex system theorists from Zurich and London including Stefano Battiston and Guido Caldarelli can report a common recurrence between the widely separate domains of market transactions and natural ecological patternings. Once again an independent mathematical source realm is implicated in common effect everywhere

Following the financial crisis of 2007–2008, a deep analogy between the origins of instability in financial systems and complex ecosystems has been pointed out: in both cases, topological features of network structures influence how easily distress can spread within the system. However, in financial network models, the details of how financial institutions interact typically play a decisive role, and a general understanding of precisely how network topology creates instability remains lacking. Here we show how processes that are widely believed to stabilize the financial system, that is, market integration and diversification, can actually drive it towards instability. This result holds irrespective of the details of how institutions interact, showing that policy-relevant analysis of the factors affecting financial stability can be carried out while abstracting away from such details. (Abstract)

Aguilera, Miguel and Manuel Bedia. Adaptation to Criticality through Organizational Invariance in Embodied Agents. arXiv:1712.05284. When we posted this site in the early 2000s, a theoretical and evidential basis for a universally recurrent iconic image was iffy and patchy at best. Back to the 1980s at the Santa Fe Institute, to general systems theory in the 1960s, and before, it was a Grail-like hope and goal. But in these later 2010s, University of Zaragoza, Spain biophysicists, for example, now immersed in a global sapiensphere can describe, the natural presence of a complementary, dynamic reciprocal balance between archetypal fixed and fluid, conservative and procreative, states and options. See also, e.g., physicist Gai Dvali for a cosmic and neural correspondence. In regard, perennial east and west wisdom has long intimated a common, bigender code which graces and moves this fraught existence. By this deep quality, it is made and meant to be humanly known, palliated, and created anew. If me + We = US may at last decipher, read and practice, a genesis code can inform and guide personal and planetary abidance.

Many biological and cognitive systems do not operate deep within one or other regime of activity. Instead, they are poised at critical points located at phase transitions in their parameter space. The pervasiveness of criticality suggests that there may be general principles inducing this behaviour, yet there is no well-founded theory for understanding how criticality is generated at a wide span of levels and contexts. In order to explore how criticality might emerge from general adaptive mechanisms, we propose a simple learning rule that maintains an internal organizational structure from a specific family of systems at criticality. (Abstract excerpt)

In physics, the concept of universality allows to group a great variety of different critical phenomena into a small number of universality classes in such a way that all systems belonging to a given universality class are essentially identical near the critical point. Thus, systems belonging to the same universality class, even if defined by very different material parameters or physical properties, have the same critical exponents. (2) This surprising property provides a perspective on criticality in terms of universal relations, suggesting that we could model criticality using simple and non-specific mechanisms independently of the individual parameters of the system. (2)

Aguilera, Miguel and Manuel Bedia. Criticality as It Could Be: Organizational Invariance as Self-Organized Criticality in Embodied Agents. arXiv:1704.05255. Akin to Recent Advances in Phase Transitions and Critical Phenomena (Bachmann), in 2017 University of Zaragoza, Spain system theorists cite a robust presence of an optimum balance between too little or too many interconnections, as exemplified by dynamic neural architectures.

This paper outlines a methodological approach to generate adaptive agents driving themselves near points of criticality. Using a synthetic approach we construct a conceptual model that, instead of specifying mechanistic requirements to generate criticality, exploits the maintenance of an organizational structure capable of reproducing critical behavior. Our approach captures the well-known principle of universality that classifies critical phenomena inside a few universality classes of systems without relying on specific mechanisms or topologies. (Abstract)

Ahn, Sungsook and Sang Joon Lee. Collective Ordering of Microscale Matters in Natural Analogy. Nature Scientific Reports. 5/10790, 2015. Based on many sophisticated, clever experiments, Pohang University of Science, Biofluid and Biomimic Research Center, engineers again confirm a constant, whole scale natural repetition of the same analogous phenomena everywhere.

Collective interaction occurs in many natural and artificial matters in broad scales. In a biological system, collective spatial organization of live individuals in a colony is important for their viability determination. Interactive motions between a single individual and an agglomerate are critical for whole procedure of the collective behaviors, but few has been clarified for these intermediate range behaviors. Here, collective interactions of microscale matters are investigated with human cells, plant seeds and artificial microspheres in terms of commonly occurring spatial arrangements. (Abstract)

In conclusion, this study demonstrates the collective interaction of microscale particulate systems in natural analogy. The representative natural systems of human cells, plant seeds and artificial spheres in microscale, already start collective interactions before the individual components are physically agglomerated. These are generally expressed by an optimized distance distribution determined by equilibrated force balance. The present results demonstrate the characteristic collective behaviors occurring in microscale and quantitative analogy between biological and artificial systems, which are plausible in nature. (14)

Allard, Antoine, et al. The Geometric Nature of Weights in Real Complex Networks. Nature Communications. 8/14103, 2017. We note this entry by University of Barcelona, Institute of Complex Systems, theorists including Marian Boguna as a 2017 fulfillment of a constant invariance from cosmos to civilization. As many such papers do, generic network topologies and dynamics are first described, which are then be seen to be instantiated everywhere. This particular works notes their presence from cellular functions to global commerce.

The topology of many real complex networks has been conjectured to be embedded in hidden metric spaces, where distances between nodes encode their likelihood of being connected. Besides of providing a natural geometrical interpretation of their complex topologies, this hypothesis yields the recipe for sustainable Internet’s routing protocols, sheds light on the hierarchical organization of biochemical pathways in cells, and allows for a rich characterization of the evolution of international trade. Here we present empirical evidence that this geometric interpretation also applies to the weighted organization of real complex networks. (Abstract)

Arnold, Carrie. Ants Swarm Like Brains Think. Nautilus. Issue 23, 2015. A report on the decade-long field and laboratory project of the Stanford University biologist Deborah Gordon to study the intelligent behavior, organization, and ecology of ant colonies in the Arizona desert. These intricate insect societies are lately seen as an archetypal example of a complex system which exhibits robust communality along with integral cognitive qualities. Recently the dynamic phenomena she found was noted by the UC Davis computational neuroscientist Mark Goldman as inherently similar to layered neural network activities. Both instances involve many, interconnected entities whether ants or neurons, from which emerges a coherent, intelligent response. Thus in 2015, still another confirmation of nature’s grand, infinitely reiterated, genetic universality is achieved.

Aschwanden, Markus, et al. 25 Years of Self-Organized Criticality: Solar and Astrophysics. arXiv:1403.6528. A 137 page review of International Space Science Institute (ISSI) meetings in Bern, Switzerland in 2012 and 2013 upon this ubiquitous phenomena. As these studies reach mature veracity, researchers from the USA, Belgium, Greece, Germany, Italy, Russia, Japan, Canada, and the UK attest to their dynamic presence everywhere. As the quotes convey, a summary observation can now be made that could apply to all natural and social complex systems. A double domain is noted of their manifest exemplification across celestial realms, which then implies an independent, mathematical source from which they arise and occur. After decades of study, these confirmations of the iterative, scalar breadth and depth of a genesis nature, as it evokes a universal informative impetus, merit to be seen as a historic discovery. See also Aschwanden below in the Astrophysical Journal and as editor of the online work Self-Organized Criticality Systems.

Shortly after the seminal paper "Self-Organized Criticality: An Explanation of 1/f noise" by Bak, Tang, and Wiesenfeld (1987), the idea has been applied to solar physics, in "Avalanches and the Distribution of Solar Flares" by Lu and Hamilton (1991). In the following years, an inspiring cross-fertilization from complexity theory to solar and astrophysics took place, where the SOC concept was initially applied to solar flares, stellar flares, and magnetospheric substorms, and later extended to the radiation belt, the heliosphere, lunar craters, the asteroid belt, the Saturn ring, pulsar glitches, soft X-ray repeaters, blazars, black-hole objects, cosmic rays, and boson clouds. The application of SOC concepts has been performed by numerical cellular automaton simulations, by analytical calculations of statistical (powerlaw-like) distributions based on physical scaling laws, and by observational tests of theoretically predicted size distributions and waiting time distributions. Attempts have been undertaken to import physical models into the numerical SOC toy models, such as the discretization of magneto-hydrodynamics (MHD) processes. The novel applications stimulated also vigorous debates about the discrimination between SOC models, SOC-like, and non-SOC processes, such as phase transitions, turbulence, random-walk diffusion, percolation, branching processes, network theory, chaos theory, fractality, multi-scale, and other complexity phenomena. (Abstract)

A Dual Approach to Self-Organized Criticality Systems In this review we stress the dual nature of SOC models, in the sense that they include (i) universal statistical aspects that apply to all SOC systems, and (ii) special physical mechanisms that are idiosyncratic to a particular SOC phenomenon. There is a consensus that the powerlaw function of the size distribution of a SOC observable is a universal statistical aspect that is common to all SOC systems, regardless whether we sample statistics of solar flares or earthquakes, while the underlying physical mechanisms are completely different, such as magnetic reconnection in solar flares, or mechanical stressing in earthquakes. If we accept this dichotomy, we should be able to build a generalized SOC theory that predicts the universal statistical properties, which should be purely of “mathematical nature” and “physics-free”, while the nonlinear energy dissipation process of a SOC event still can be described with (single or multiple) specific physical SOC models that are different for every SOC manifestation. (93)

Universal Aspects of SOC Systems In astrophysical applications, the energy dissipation rate F is generally measured by the flux or intensity of electromagnetic radiation in some wavelength, but the universal meaning of the energy dissipation rate is simply the instantaneous avalanche size during a snapshot, while the total energy is the time-integrated avalanche volume. Thus this generalized SOC concept is still universally applicable to every SOC system, regardless if it is observed by an astronomical instrument, by a geophysical monitor, by financial statistics or by computer lattice stimulations. (94)

The Meaning of Self-Organized Criticality answer this question we remind again our pragmatic generalized definition of a SOC system: SOC is a critical state of a nonlinear energy dissipation system that is slowly and continuously driven towards a critical value of a system-wide instability threshold, producing scale-free, fractal-diffusive, and intermittent avalanches with powerlaw-like size distributions. This definition is independent of any particular physical mechanism, but describes only some universal system behavior that is common to virtually all threshold-operated nonlinear energy dissipation processes, in the limit of slow driving. (96)

Atay, Fatihcan, et al. Perspectives on Multi-Level Dynamics. arXiv:1606.05665. This complex paper is another example of realizations that a grand scientific synthesis from cosmic physics to social media can just now be gathered and achieved. A team of MPI Mathematics in the Sciences and University of Bielefeld researchers first cite an independent, generic model, and then illume its presence from information theory, Markov processes, agent-based models, mean-field methods in neuroscience, renormalization group theory, to quantum decoherence. While highly technical, the work conveys a broad conviction that as global collaborations build and converge, this historic goal is at last within reach.

As Physics did in previous centuries, there is currently a common dream of extracting generic laws of nature in economics, sociology, neuroscience, by focalising the description of phenomena to a minimal set of variables and parameters, linked together by causal equations of evolution whose structure may reveal hidden principles. (Abstract) It is generally agreed that complex systems are comprised of a large number of subcomponents and their interactions. Moreover, they often exhibit structures at various spatial and temporal levels. As a somewhat extreme example, spanning length and time scales of vastly different magnitudes, one can cite the hierarchy of molecules, neurons, brain areas, brains, individuals, social organizations, economies, etc., which can be viewed as manifestations of the same collective physical reality at different levels. (1).

Bachmann, Michael, et al. Recent Advances in Phase Transitions and Critical Phenomena. European Physical Journal Special Topics. 226/4, 2017. University of Georgia, USA, Coventry University, UK, Heidelberg University, and Leipzig University physicists, including Ralph Kenna, introduce a special issue on nature’s apparent propensity to move into and reside at a poised state betwixt chaos and order (chaorder?) everywhere from cosmos to culture. A typical paper might be From Dynamical Scaling to Local Scale-Invariance by Malte Henkel. For more, see also herein Criticality as It Could Be by Miguel Aguilera and Manuel Bedia.

Phase transitions and critical phenomena are of ubiquitous importance from the femtometre scale in quantum chromodynamics to galaxy formation in the universe, from the folding, adsorption or denaturation of bio-polymers to the magnetisation effects in storage media, from percolation in complex social networks to fragmentation transitions in atomic nuclei. The present issue discusses a cross section of the current research on phase transitions and critical phenomena in condensed-matter physics, with a focus on soft and hard matter systems as well as the most important methods used for studying such problems. (Abstract)

The study of phase transitions is by now a quite mature subject. Early notions akin to modern ideas of phase transitions are already present in ancient Greek philosophical texts, for instance in Aristotle’s theory of the elements. Still, it was only in the late 18th and early 19th century that the advent of the steam engine necessitated a profound theoretical description. (533) The character of this special point was only fully understood with the introduction of the renormalization group by (Leo) Kadanoff and (Kenneth) Wilson about 50 years ago, which explains scaling and universality and now serves as a complete fundamental theory of critical phenomena. (533-534)

Bar-Yam, Yaneer. From Big Data to Important Information. arXiv:1604.00976. As the quotes cite, the physicist, founder and president of the New England Complex Systems Institute since the 1990s, after some pages of technical discussion, contends in 2016 that a universal systemic recurrence is indeed evident across widely disparate realms.

Advances in science are being sought in newly available opportunities to collect massive quantities of data about complex systems. While key advances are being made in detailed mapping of systems, how to relate this data to solving many of the challenges facing humanity is unclear. The questions we often wish to address require identifying the impact of interventions on the system and that impact is not apparent in the detailed data that is available. Here we review key concepts and motivate a general framework for building larger scale views of complex systems and for characterizing the importance of information in physical, biological and social systems. We provide examples of its application to evolutionary biology with relevance to ecology, biodiversity, pandemics, and human lifespan, and in the context of social systems with relevance to ethnic violence, global food prices, and stock market panic. Framing scientific inquiry as an effort to determine what is important and unimportant is a means for advancing our understanding and addressing many practical concerns, such as economic development or treating disease. (Abstract)

The mapping of water to vapor transitions onto magnetic transitions illustrates how one type of behavior can describe many possible systems. As renormalization group was more widely applied, many instances were found of systems that have the same behavior even though they differ in detail, a concept that became referred to as universality. Still, while many systems have the same behavior, there are systems that have distinct behaviors. Together this means that systems fall into classes of behaviors, leading to the term `universality class.' Power laws often arise in the context of behaviors that exist across scales, and the value of the exponent became used as a signature of the universality class. (6)

The study of universality enables us to identify classes of systems whose behaviors can be described the same way and can be captured by a common mathematical model. This is the principle of universality that is formalized by the analysis of renormalization group and generalized by the application of multiscale information theory to the scientific study of complex systems. A good way to think about this is that the mathematical model describes one member of the class. (7)

Baran, Nicole, et al. Applying Gene Regulatory Network Logic to the Evolution of Social Behavior. Proceedings of the National Academy of Sciences. 114/5886, 2917. With Patrick McGrath and Todd Streelman, Georgia Tech biologists (no longer just rambling wrecks) discern an innate affinity between genomic and neural (neuromic) network complexities, which can then be traced to and tracked by creaturely activities. As a surmise, a generic, independent source of node and link topologies and dynamics is quite implied.

Animal behavior is ultimately the product of gene regulatory networks (GRNs) for brain development and neural networks for brain function. The GRN approach has advanced the fields of genomics and development, and we identify organizational similarities between networks of genes that build the brain and networks of neurons that encode brain function. In this perspective, we engage the analogy between developmental networks and neural networks, exploring the advantages of using GRN logic to study behavior. Applying the GRN approach to the brain and behavior provides a quantitative and manipulative framework for discovery. We illustrate features of this framework using the example of social behavior and the neural circuitry of aggression. (Abstract)

Bashan, Amir, et al. Universality of Human Microbial Dynamics. Nature. 534/259, 2016. In the currency of the Human Microbiome Project to quantify our myriad bacterial species that suffuse, help or harm us, Harvard Medical School, MIT Physics of Living Systems, and Dana-Farber Cancer Institute researchers apply the latest algorithmic, computational methods to reveal common patterns and processes in anatomical forms and physiological functions. A commentary, Rules of the Game for Microbiota, in the same issue (534/182) lauds the findings as proof that for everyone, bacteria behave in a common, repeatable fashion. As a result, this makes medical treatments more amenable.

Human-associated microbial communities have a crucial role in determining our health and well-being, and this has led to the continuing development of microbiome-based therapies such as faecal microbiota transplantation. These microbial communities are very complex, dynamic and highly personalized ecosystems, exhibiting a high degree of inter-individual variability in both species assemblages and abundance profiles. It is not known whether the underlying ecological dynamics of these communities, which can be parameterized by growth rates, and intra- and inter-species interactions in population dynamics models, are largely host-independent (that is, universal) or host-specific. If the inter-individual variability reflects host-specific dynamics due to differences in host lifestyle, physiology or genetics, then generic microbiome manipulations may have unintended consequences. Alternatively, microbial ecosystems of different subjects may exhibit universal dynamics, with the inter-individual variability mainly originating from differences in the sets of colonizing species.

Here we develop a new computational method to characterize human microbial dynamics. By applying this method to cross-sectional data from two large-scale metagenomic studies—the Human Microbiome Project and the Student Microbiome Project—we show that gut and mouth microbiomes display pronounced universal dynamics, whereas communities associated with certain skin sites are probably shaped by differences in the host environment. Notably, the universality of gut microbial dynamics is not observed in subjects with recurrent Clostridium difficile infection but is observed in the same set of subjects after faecal microbiota transplantation. These results fundamentally improve our understanding of the processes that shape human microbial ecosystems, and pave the way to designing general microbiome-based therapies. (Abstract)

1 | 2 | 3 | 4 | 5 | 6 | 7  Next