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      Field-Control, Phase-Transitions, and Life’s Emergence

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          Abstract

          Instances of critical-like characteristics in living systems at each organizational level (bio-molecules to ecosystems) as well as the spontaneous emergence of computation (Langton), do suggest the relevance of self-organized criticality (SOC). But extrapolating complex bio-systems to life’s origins, brings up a paradox: how could simple organics – lacking the “soft-matter” response properties of today’s complex bio-molecules – have dissipated energy from primordial reactions (eventually reducing CO 2) in a controlled manner for their “ordering”? Nevertheless, a causal link of life’s macroscopic irreversible dynamics to the microscopic reversible laws of statistical mechanics is indicated via the “functional-takeover” of a soft magnetic scaffold by organics (c.f. Cairns-Smith’s “crystal-scaffold”). A field-controlled structure offers a mechanism for boot-strapping – bottom-up assembly with top-down control: its super-paramagnetic colloidal components obey reversible dynamics, but its dissipation of magnetic (H)-field energy for aggregation breaks time-reversal symmetry. The responsive adjustments of the controlled (host) mineral system to environmental changes would bring about mutual coupling between random organic sets supported by it; here the generation of long-range correlations within organic (guest) networks could include SOC-like mechanisms. And, such cooperative adjustments enable the selection of the functional configuration by altering the inorganic dipolar network’s capacity to assist a spontaneous process. A non-equilibrium dynamics could now drive the kinetically oriented system (trimming the phase-space via sterically coupled organics) toward a series of phase-transitions with appropriate organic replacements “taking-over” its functions. Where available, experiments are cited in support of these speculations and for designing appropriate tests.

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          Most cited references183

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          Neural networks and physical systems with emergent collective computational abilities.

          J Hopfield (1982)
          Computational properties of use of biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices.
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            A Mechanism of Magnetic Hysteresis in Heterogeneous Alloys

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              Error and attack tolerance of complex networks

              Many complex systems, such as communication networks, display a surprising degree of robustness: while key components regularly malfunction, local failures rarely lead to the loss of the global information-carrying ability of the network. The stability of these complex systems is often attributed to the redundant wiring of the functional web defined by the systems' components. In this paper we demonstrate that error tolerance is not shared by all redundant systems, but it is displayed only by a class of inhomogeneously wired networks, called scale-free networks. We find that scale-free networks, describing a number of systems, such as the World Wide Web, Internet, social networks or a cell, display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected by even unrealistically high failure rates. However, error tolerance comes at a high price: these networks are extremely vulnerable to attacks, i.e. to the selection and removal of a few nodes that play the most important role in assuring the network's connectivity.
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                Author and article information

                Journal
                Front Physiol
                Front Physiol
                Front. Physio.
                Frontiers in Physiology
                Frontiers Research Foundation
                1664-042X
                05 October 2012
                2012
                : 3
                : 366
                Affiliations
                [1] 1Independent Researcher, St.Denis Reunion, France
                [2] 2Department of Physics, Delhi University New Delhi, India
                Author notes

                Edited by: Zbigniew R. Struzik, The University of Tokyo, Japan

                Reviewed by: Tara Thiagarajan, National Center for Biological Sciences, India; Bela Suki, Boston University, USA

                *Correspondence: Gargi Mitra-Delmotte, Independent Researcher, 39 Cite de l’Ocean, Montgaillard, St.Denis 97400, Reunion, France. e-mail: gargijj@ 123456orange.fr ; A. N. Mitra, Department of Physics, Delhi University, 244 Tagore Park, Delhi 110009, India. e-mail: ganmitra@ 123456nde.vsnl.net.in

                This article was submitted to Frontiers in Fractal Physiology, a specialty of Frontiers in Physiology.

                Article
                10.3389/fphys.2012.00366
                3464435
                23060803
                fd024ddb-b7dd-4478-ac44-af223c87a2c4
                Copyright © 2012 Mitra-Delmotte and Mitra.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                History
                : 28 March 2012
                : 27 August 2012
                Page count
                Figures: 8, Tables: 2, Equations: 0, References: 242, Pages: 0, Words: 19909
                Categories
                Physiology
                Hypothesis and Theory

                Anatomy & Physiology
                feedback,slow driving,long-range correlation,proto-metabolic cycle,organic “takeover,” phase-transition,field-controlled colloids

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