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Sample records for compact self-organizing cellular

  1. SELF-ORGANIZED CRITICALITY AND CELLULAR AUTOMATA

    SciTech Connect

    CREUTZ,M.

    2007-01-01

    Cellular automata provide a fascinating class of dynamical systems based on very simple rules of evolution yet capable of displaying highly complex behavior. These include simplified models for many phenomena seen in nature. Among other things, they provide insight into self-organized criticality, wherein dissipative systems naturally drive themselves to a critical state with important phenomena occurring over a wide range of length and the scales. This article begins with an overview of self-organized criticality. This is followed by a discussion of a few examples of simple cellular automaton systems, some of which may exhibit critical behavior. Finally, some of the fascinating exact mathematical properties of the Bak-Tang-Wiesenfeld sand-pile model [1] are discussed.

  2. Global Self-Organization of the Cellular Metabolic Structure

    PubMed Central

    De La Fuente, Ildefonso M.; Martínez, Luis; Pérez-Samartín, Alberto L.; Ormaetxea, Leire; Amezaga, Cristian; Vera-López, Antonio

    2008-01-01

    Background Over many years, it has been assumed that enzymes work either in an isolated way, or organized in small catalytic groups. Several studies performed using “metabolic networks models” are helping to understand the degree of functional complexity that characterizes enzymatic dynamic systems. In a previous work, we used “dissipative metabolic networks” (DMNs) to show that enzymes can present a self-organized global functional structure, in which several sets of enzymes are always in an active state, whereas the rest of molecular catalytic sets exhibit dynamics of on-off changing states. We suggested that this kind of global metabolic dynamics might be a genuine and universal functional configuration of the cellular metabolic structure, common to all living cells. Later, a different group has shown experimentally that this kind of functional structure does, indeed, exist in several microorganisms. Methodology/Principal Findings Here we have analyzed around 2.500.000 different DMNs in order to investigate the underlying mechanism of this dynamic global configuration. The numerical analyses that we have performed show that this global configuration is an emergent property inherent to the cellular metabolic dynamics. Concretely, we have found that the existence of a high number of enzymatic subsystems belonging to the DMNs is the fundamental element for the spontaneous emergence of a functional reactive structure characterized by a metabolic core formed by several sets of enzymes always in an active state. Conclusions/Significance This self-organized dynamic structure seems to be an intrinsic characteristic of metabolism, common to all living cellular organisms. To better understand cellular functionality, it will be crucial to structurally characterize these enzymatic self-organized global structures. PMID:18769681

  3. Cellular self-organization by autocatalytic alignment feedback

    PubMed Central

    Junkin, Michael; Leung, Siu Ling; Whitman, Samantha; Gregorio, Carol C.; Wong, Pak Kin

    2011-01-01

    Myoblasts aggregate, differentiate and fuse to form skeletal muscle during both embryogenesis and tissue regeneration. For proper muscle function, long-range self-organization of myoblasts is required to create organized muscle architecture globally aligned to neighboring tissue. However, how the cells process geometric information over distances considerably longer than individual cells to self-organize into well-ordered, aligned and multinucleated myofibers remains a central question in developmental biology and regenerative medicine. Using plasma lithography micropatterning to create spatial cues for cell guidance, we show a physical mechanism by which orientation information can propagate for a long distance from a geometric boundary to guide development of muscle tissue. This long-range alignment occurs only in differentiating myoblasts, but not in non-fusing myoblasts perturbed by microfluidic disturbances or other non-fusing cell types. Computational cellular automata analysis of the spatiotemporal evolution of the self-organization process reveals that myogenic fusion in conjunction with rotational inertia functions in a self-reinforcing manner to enhance long-range propagation of alignment information. With this autocatalytic alignment feedback, well-ordered alignment of muscle could reinforce existing orientations and help promote proper arrangement with neighboring tissue and overall organization. Such physical self-enhancement might represent a fundamental mechanism for long-range pattern formation during tissue morphogenesis. PMID:22193956

  4. Quantitative Analysis of Cellular Metabolic Dissipative, Self-Organized Structures

    PubMed Central

    de la Fuente, Ildefonso Martínez

    2010-01-01

    One of the most important goals of the postgenomic era is understanding the metabolic dynamic processes and the functional structures generated by them. Extensive studies during the last three decades have shown that the dissipative self-organization of the functional enzymatic associations, the catalytic reactions produced during the metabolite channeling, the microcompartmentalization of these metabolic processes and the emergence of dissipative networks are the fundamental elements of the dynamical organization of cell metabolism. Here we present an overview of how mathematical models can be used to address the properties of dissipative metabolic structures at different organizational levels, both for individual enzymatic associations and for enzymatic networks. Recent analyses performed with dissipative metabolic networks have shown that unicellular organisms display a singular global enzymatic structure common to all living cellular organisms, which seems to be an intrinsic property of the functional metabolism as a whole. Mathematical models firmly based on experiments and their corresponding computational approaches are needed to fully grasp the molecular mechanisms of metabolic dynamical processes. They are necessary to enable the quantitative and qualitative analysis of the cellular catalytic reactions and also to help comprehend the conditions under which the structural dynamical phenomena and biological rhythms arise. Understanding the molecular mechanisms responsible for the metabolic dissipative structures is crucial for unraveling the dynamics of cellular life. PMID:20957111

  5. Dynamic self-organization of microwell-aggregated cellular mixtures.

    PubMed

    Song, Wei; Tung, Chih-Kuan; Lu, Yen-Chun; Pardo, Yehudah; Wu, Mingming; Das, Moumita; Kao, Der-I; Chen, Shuibing; Ma, Minglin

    2016-06-29

    Cells with different cohesive properties self-assemble in a spatiotemporal and context-dependent manner. Previous studies on cell self-organization mainly focused on the spontaneous structural development within a short period of time during which the cell numbers remained constant. However the effect of cell proliferation over time on the self-organization of cells is largely unexplored. Here, we studied the spatiotemporal dynamics of self-organization of a co-culture of MDA-MB-231 and MCF10A cells seeded in a well defined space (i.e. non-adherent microfabricated wells). When cell-growth was chemically inhibited, high cohesive MCF10A cells formed a core surrounded by low cohesive MDA-MB-231 cells on the periphery, consistent with the differential adhesion hypothesis (DAH). Interestingly, this aggregate morphology was completely inverted when the cells were free to grow. At an initial seeding ratio of 1 : 1 (MDA-MB-231 : MCF10A), the fast growing MCF10A cells segregated in the periphery while the slow growing MDA-MB-231 cells stayed in the core. Another morphology developed at an inequal seeding ratio (4 : 1), that is, the cell mixtures developed a side-by-side aggregate morphology. We conclude that the cell self-organization depends not only on the cell cohesive properties but also on the cell seeding ratio and proliferation. Furthermore, by taking advantage of the cell self-organization, we purified human embryonic stem cells-derived pancreatic progenitors (hESCs-PPs) from co-cultured feeder cells without using any additional tools or labels. PMID:27275624

  6. Cellular chirality arising from the self-organization of the actin cytoskeleton.

    PubMed

    Tee, Yee Han; Shemesh, Tom; Thiagarajan, Visalatchi; Hariadi, Rizal Fajar; Anderson, Karen L; Page, Christopher; Volkmann, Niels; Hanein, Dorit; Sivaramakrishnan, Sivaraj; Kozlov, Michael M; Bershadsky, Alexander D

    2015-04-01

    Cellular mechanisms underlying the development of left-right asymmetry in tissues and embryos remain obscure. Here, the development of a chiral pattern of actomyosin was revealed by studying actin cytoskeleton self-organization in cells with isotropic circular shape. A radially symmetrical system of actin bundles consisting of α-actinin-enriched radial fibres (RFs) and myosin-IIA-enriched transverse fibres (TFs) evolved spontaneously into the chiral system as a result of the unidirectional tilting of all RFs, which was accompanied by a tangential shift in the retrograde movement of TFs. We showed that myosin-IIA-dependent contractile stresses within TFs drive their movement along RFs, which grow centripetally in a formin-dependent fashion. The handedness of the chiral pattern was shown to be regulated by α-actinin-1. Computational modelling demonstrated that the dynamics of the RF-TF system can explain the pattern transition from radial to chiral. Thus, actin cytoskeleton self-organization provides built-in machinery that potentially allows cells to develop left-right asymmetry. PMID:25799062

  7. Disordered cellular automaton traffic flow model: phase separated state, density waves and self organized criticality

    NASA Astrophysics Data System (ADS)

    Fourrate, K.; Loulidi, M.

    2006-01-01

    We suggest a disordered traffic flow model that captures many features of traffic flow. It is an extension of the Nagel-Schreckenberg (NaSch) stochastic cellular automata for single line vehicular traffic model. It incorporates random acceleration and deceleration terms that may be greater than one unit. Our model leads under its intrinsic dynamics, for high values of braking probability pr, to a constant flow at intermediate densities without introducing any spatial inhomogeneities. For a system of fast drivers pr→0, the model exhibits a density wave behavior that was observed in car following models with optimal velocity. The gap of the disordered model we present exhibits, for high values of pr and random deceleration, at a critical density, a power law distribution which is a hall mark of a self organized criticality phenomena.

  8. Visualization of Patterns and Self-organization of Cellular Automata in Urban Traffic Situations

    NASA Astrophysics Data System (ADS)

    Zhou, Lei; Brian, Schwartz

    2001-06-01

    The use of cellular automaton (CA) techniques is very good at modeling complex or nonlinear systems. In dynamic system within the context of discrete mathematical steps for CA simulations, simple local rules produce complex global rules. The simplicity of CA rules enables us to model and investigate more realistic models for the behavior traffic in two-dimensional flow systems. Our numerical solution presents self-organization behavior, which is called grid-lock for urban city street traffic and a phase transitions in the fundamental flow rate vs. density diagrams. We present calculations, which demonstrate the effects of micro CA rules and traffic parameters on the macro properties of traffic flow and behavior. We modified the stochastic parameter p, which is constant in the original CA rules, to a variable depending on the state of the vehicles. This structure of path dependence on history for traffic properties is in many cases analogous to solutions obtained for interactive magnetic systems. Using 3D ray tracer software, we are able to render the visualization of patterns of grid-lock into a 3D virtual urban environment.

  9. Self-organized criticality in a two-dimensional cellular automaton model of a magnetic flux tube with background flow

    NASA Astrophysics Data System (ADS)

    Dănilă, B.; Harko, T.; Mocanu, G.

    2015-11-01

    We investigate the transition to self-organized criticality in a two-dimensional model of a flux tube with a background flow. The magnetic induction equation, represented by a partial differential equation with a stochastic source term, is discretized and implemented on a two-dimensional cellular automaton. The energy released by the automaton during one relaxation event is the magnetic energy. As a result of the simulations, we obtain the time evolution of the energy release, of the system control parameter, of the event lifetime distribution and of the event size distribution, respectively, and we establish that a self-organized critical state is indeed reached by the system. Moreover, energetic initial impulses in the magnetohydrodynamic flow can lead to one-dimensional signatures in the magnetic two-dimensional system, once the self-organized critical regime is established. The applications of the model for the study of gamma-ray bursts (GRBs) is briefly considered, and it is shown that some astrophysical parameters of the bursts, like the light curves, the maximum released energy and the number of peaks in the light curve can be reproduced and explained, at least on a qualitative level, by working in a framework in which the systems settles in a self-organized critical state via magnetic reconnection processes in the magnetized GRB fireball.

  10. Self-organized perturbations enhance class IV behavior and 1/f power spectrum in elementary cellular automata.

    PubMed

    Nakajima, Kohei; Haruna, Taichi

    2011-09-01

    In this paper, we propose a new class of cellular automata based on the modification of its state space. It is introduced to model a computation which is exposed to an environment. We formalized the computation as extension and projection processes of its state space and resulting misidentifications of the state. This is motivated to embed the role of an environment into the system itself, which naturally induces self-organized internal perturbations rather than the usual external perturbations. Implementing this structure into the elementary cellular automata, we characterized its effect by means of input entropy and power spectral analysis. As a result, the cellular automata with this structure showed robust class IV behavior and a 1/f power spectrum in a wide range of rule space comparative to the notion of the edge of chaos. PMID:21600265

  11. INVITED ARTICLE: Partial differential equations for self-organization in cellular and developmental biology

    NASA Astrophysics Data System (ADS)

    Baker, R. E.; Gaffney, E. A.; Maini, P. K.

    2008-11-01

    Understanding the mechanisms governing and regulating the emergence of structure and heterogeneity within cellular systems, such as the developing embryo, represents a multiscale challenge typifying current integrative biology research, namely, explaining the macroscale behaviour of a system from microscale dynamics. This review will focus upon modelling how cell-based dynamics orchestrate the emergence of higher level structure. After surveying representative biological examples and the models used to describe them, we will assess how developments at the scale of molecular biology have impacted on current theoretical frameworks, and the new modelling opportunities that are emerging as a result. We shall restrict our survey of mathematical approaches to partial differential equations and the tools required for their analysis. We will discuss the gap between the modelling abstraction and biological reality, the challenges this presents and highlight some open problems in the field.

  12. Self-organization of waves and pulse trains by molecular motors in cellular protrusions.

    PubMed

    Yochelis, A; Ebrahim, S; Millis, B; Cui, R; Kachar, B; Naoz, M; Gov, N S

    2015-01-01

    Actin-based cellular protrusions are an ubiquitous feature of cells, performing a variety of critical functions ranging from cell-cell communication to cell motility. The formation and maintenance of these protrusions relies on the transport of proteins via myosin motors, to the protrusion tip. While tip-directed motion leads to accumulation of motors (and their molecular cargo) at the protrusion tip, it is observed that motors also form rearward moving, periodic and isolated aggregates. The origins and mechanisms of these aggregates, and whether they are important for the recycling of motors, remain open puzzles. Motivated by novel myosin-XV experiments, a mass conserving reaction-diffusion-advection model is proposed. The model incorporates a non-linear cooperative interaction between motors, which converts them between an active and an inactive state. Specifically, the type of aggregate formed (traveling waves or pulse-trains) is linked to the kinetics of motors at the protrusion tip which is introduced by a boundary condition. These pattern selection mechanisms are found not only to qualitatively agree with empirical observations but open new vistas to the transport phenomena by molecular motors in general. PMID:26335545

  13. Self-organization of waves and pulse trains by molecular motors in cellular protrusions

    PubMed Central

    Yochelis, A.; Ebrahim, S.; Millis, B.; Cui, R.; Kachar, B.; Naoz, M.; Gov, N. S.

    2015-01-01

    Actin-based cellular protrusions are an ubiquitous feature of cells, performing a variety of critical functions ranging from cell-cell communication to cell motility. The formation and maintenance of these protrusions relies on the transport of proteins via myosin motors, to the protrusion tip. While tip-directed motion leads to accumulation of motors (and their molecular cargo) at the protrusion tip, it is observed that motors also form rearward moving, periodic and isolated aggregates. The origins and mechanisms of these aggregates, and whether they are important for the recycling of motors, remain open puzzles. Motivated by novel myosin-XV experiments, a mass conserving reaction-diffusion-advection model is proposed. The model incorporates a non-linear cooperative interaction between motors, which converts them between an active and an inactive state. Specifically, the type of aggregate formed (traveling waves or pulse-trains) is linked to the kinetics of motors at the protrusion tip which is introduced by a boundary condition. These pattern selection mechanisms are found not only to qualitatively agree with empirical observations but open new vistas to the transport phenomena by molecular motors in general. PMID:26335545

  14. Self-Organized Earthquakes

    NASA Astrophysics Data System (ADS)

    Rundle, J. B.; Holliday, J. R.; Turcotte, D. L.; Klein, W.

    2011-12-01

    Self-Organized Criticality was proposed by the Per Bak et al. [1] as a means of explaining scaling laws observed in driven natural systems, usually in (slowly) driven threshold systems. The example used by Bak was a simple cellular automaton model of a sandpile, in which grains of sand were slowly dropped (randomly) onto a flat plate. After a period of time, during which the 'critical state' was approached, a series of self-similar avalanches would begin. Scaling exponents for the frequency-area statistics of the sandpile avalanches were found to be approximately 1, a value that characterizes 'flicker noise' in natural systems. SOC is associated with a critical point in the phase diagram of the system, and it was found that the usual 2-scaling field theory applies. A model related to SOC is the Self-Organized Spinodal (SOS), or intermittent criticality model. Here a slow but persistent driving force leads to quasi-periodic approach to, and retreat from, the classical limit of stability, or spinodal. Scaling exponents for this model can be related to Gutenberg-Richter and Omori exponents observed in earthquake systems. In contrast to SOC models, nucleation, both classical and non-classical types, is possible in SOS systems. Tunneling or nucleation rates can be computed from Langer-Klein-Landau-Ginzburg theories for comparison to observations. Nucleating droplets play a role similar to characteristic earthquake events. Simulations of these systems reveals much of the phenomenology associated with earthquakes and other types of "burst" dynamics. Whereas SOC is characterized by the full scaling spectrum of avalanches, SOS is characterized by both system-size events above the nominal frequency-size scaling curve, and scaling of small events. Applications to other systems including integrate-and-fire neural networks and financial crashes will be discussed. [1] P. Bak, C. Tang and K. Weisenfeld, Self-Organized Criticality, Phys. Rev. Lett., 59, 381 (1987).

  15. Compact Biocompatible Quantum Dots Functionalized for Cellular Imaging

    PubMed Central

    Liu, Wenhao; Howarth, Mark; Greytak, Andrew B.; Zheng, Yi; Nocera, Daniel G.; Ting, Alice Y.; Bawendi, Moungi G.

    2009-01-01

    We present a family of water-soluble quantum dots (QDs) that exhibit low nonspecific binding to cells, small hydrodynamic diameter, tunable surface charge, high quantum yield, and good solution stability across a wide pH range. These QDs are amenable to covalent modification via simple carbodiimide coupling chemistry, which is achieved by functionalizing the surface of QDs with a new class of heterobifunctional ligands incorporating dihydrolipoic acid, a short poly(ethylene glycol) (PEG) spacer, and an amine or carboxylate terminus. The covalent attachment of molecules is demonstrated by appending a rhodamine dye to form a QD-dye conjugate exhibiting fluorescence resonance energy transfer (FRET). High-affinity labeling is demonstrated by covalent attachment of streptavidin, thus enabling the tracking of biotinylated epidermal growth factor (EGF) bound to EGF receptor on live cells. In addition, QDs solubilized with the heterobifunctional ligands retain their metal-affinity driven conjugation chemistry with polyhistidine-tagged proteins. This dual functionality is demonstrated by simultaneous covalent attachment of a rhodamine FRET acceptor and binding of polyhistidine-tagged streptavidin on the same nanocrystal to create a targeted QD, which exhibits dual-wavelength emission. Such emission properties could serve as the basis for ratiometric sensing of the cellular receptor’s local chemical environment. PMID:18177042

  16. Self-organized criticality

    SciTech Connect

    Per Bak ); Kan Chen )

    1991-01-01

    Just as the proverbial straw broke the camel's back, catastrophes, from earthquakes and avalanches to a stock market crash, can be triggered by a minor event. The authors argue that complex systems naturally evolve to a critical state. Their theory already has improved understanding of motion in the earth's crust, economies and ecosystems. The theory of self-organized criticality states that many composite systems naturally evolve to a critical state in which a minor event starts a chain reaction that can affect any number of elements in the system. Although composite systems produce more minor events than catastrophes, chain reactions of all sizes are an integral part of the dynamics. According to the theory, the mechanism that leads to minor events is the same one that leads to major events. Furthermore, composite systems never reach equilibrium but instead evolve from one metastable state to the next. Self-organized criticality is a holistic theory: the global features, such as the relative number of large and small events, do not depend on the microscopic mechanisms. Consequently, global features of the system cannot be understood by analyzing the parts separately. To the authors' knowledge, self-organized criticality is the only model or mathematical description that has led to a holistic theory for dynamic systems.

  17. Self-Organizing Maps

    NASA Astrophysics Data System (ADS)

    Kohonen, Teuvo

    The Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. Many fields of science have adopted the SOM as a standard analytical tool: in statistics,signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. A new area is organization of very large document collections. The SOM is also one of the most realistic models of the biological brain functions.This new edition includes a survey of over 2000 contemporary studies to cover the newest results; the case examples were provided with detailed formulae, illustrations and tables; a new chapter on software tools for SOM was written, other chapters were extended or reorganized.

  18. Self-Organization of Treadmilling Filaments

    NASA Astrophysics Data System (ADS)

    Doubrovinski, K.; Kruse, K.

    2007-11-01

    The cytoskeleton is an active network of polar filaments. The activity can lead to the polymerization of filaments at one end and depolymerization at the other. This phenomenon is called treadmilling and is essential for many cellular processes, in particular, the crawling of cells on a substrate. We develop a microscopic theoretical framework for describing systems of treadmilling filaments. We show that such systems can self-organize into structures observed in cell fragments, in particular, asters and moving spots.

  19. Self-organization of microtubules and motors

    NASA Astrophysics Data System (ADS)

    Ndlec, F. J.; Surrey, T.; Maggs, A. C.; Leibler, S.

    1997-09-01

    Cellular structures are established and maintained through a dynamic interplay between assembly and regulatory processes. Self-organization of molecular components provides a variety of possible spatial structures: the regulatory machinery chooses the most appropriate to express a given cellular function. Here we study the extent and the characteristics of self-organization using microtubules and molecular motors as a model system. These components are known to participate in the formation of many cellular structures, such as the dynamic asters found in mitotic and meiotic spindles. Purified motors and microtubules have previously been observed to form asters in vitro. We have reproduced this result with a simple system consisting solely of multi-headed constructs of the motor protein kinesin and stabilized microtubules. We show that dynamic asters can also be obtained from a homogeneous solution of tubulin and motors. By varying the relative concentrations of the components, we obtain a variety of self-organized structures. Further, by studying this process in a constrained geometry of micro-fabricated glass chambers, we demonstrate that the same final structure can be reached through different assembly `pathways'.

  20. Microtubule self-organization is gravity-dependent

    PubMed Central

    Papaseit, Cyril; Pochon, Nathalie; Tabony, James

    2000-01-01

    Although weightlessness is known to affect living cells, the manner by which this occurs is unknown. Some reaction-diffusion processes have been theoretically predicted as being gravity-dependent. Microtubules, a major constituent of the cellular cytoskeleton, self-organize in vitro by way of reaction-diffusion processes. To investigate how self-organization depends on gravity, microtubules were assembled under low gravity conditions produced during space flight. Contrary to the samples formed on an in-flight 1 × g centrifuge, the samples prepared in microgravity showed almost no self-organization and were locally disordered. PMID:10880562

  1. Self-Organized Criticality Systems

    NASA Astrophysics Data System (ADS)

    Aschwanden, M. J.

    2013-07-01

    Contents: (1) Introduction - Norma B. Crosby --- (2) Theoretical Models of SOC Systems - Markus J. Aschwanden --- (3) SOC and Fractal Geometry - R. T. James McAteer --- (4) Percolation Models of Self-Organized Critical Phenomena - Alexander V. Milovanov --- (5) Criticality and Self-Organization in Branching Processes: Application to Natural Hazards - Álvaro Corral, Francesc Font-Clos --- (6) Power Laws of Recurrence Networks - Yong Zou, Jobst Heitzig, Jürgen Kurths --- (7) SOC computer simolations - Gunnar Pruessner --- (8) SOC Laboratory Experiments - Gunnar Pruessner --- (9) Self-Organizing Complex Earthquakes: Scaling in Data, Models, and Forecasting - Michael K. Sachs et al. --- (10) Wildfires and the Forest-Fire Model - Stefan Hergarten --- (11) SOC in Landslides - Stefan Hergarten --- (12) SOC and Solar Flares - Paul Charbonneau --- (13) SOC Systems in Astrophysics - Markus J. Aschwanden ---

  2. PREFACE: Self-organized nanostructures

    NASA Astrophysics Data System (ADS)

    Rousset, Sylvie; Ortega, Enrique

    2006-04-01

    In order to fabricate ordered arrays of nanostructures, two different strategies might be considered. The `top-down' approach consists of pushing the limit of lithography techniques down to the nanometre scale. However, beyond 10 nm lithography techniques will inevitably face major intrinsic limitations. An alternative method for elaborating ultimate-size nanostructures is based on the reverse `bottom-up' approach, i.e. building up nanostructures (and eventually assemble them to form functional circuits) from individual atoms or molecules. Scanning probe microscopies, including scanning tunnelling microscopy (STM) invented in 1982, have made it possible to create (and visualize) individual structures atom by atom. However, such individual atomic manipulation is not suitable for industrial applications. Self-assembly or self-organization of nanostructures on solid surfaces is a bottom-up approach that allows one to fabricate and assemble nanostructure arrays in a one-step process. For applications, such as high density magnetic storage, self-assembly appears to be the simplest alternative to lithography for massive, parallel fabrication of nanostructure arrays with regular sizes and spacings. These are also necessary for investigating the physical properties of individual nanostructures by means of averaging techniques, i.e. all those using light or particle beams. The state-of-the-art and the current developments in the field of self-organization and physical properties of assembled nanostructures are reviewed in this issue of Journal of Physics: Condensed Matter. The papers have been selected from among the invited and oral presentations of the recent summer workshop held in Cargese (Corsica, France, 17-23 July 2005). All authors are world-renowned in the field. The workshop has been funded by the Marie Curie Actions: Marie Curie Conferences and Training Courses series named `NanosciencesTech' supported by the VI Framework Programme of the European Community, by

  3. Self-organizing biochemical cycles

    NASA Technical Reports Server (NTRS)

    Orgel, L. E.; Bada, J. L. (Principal Investigator)

    2000-01-01

    I examine the plausibility of theories that postulate the development of complex chemical organization without requiring the replication of genetic polymers such as RNA. One conclusion is that theories that involve the organization of complex, small-molecule metabolic cycles such as the reductive citric acid cycle on mineral surfaces make unreasonable assumptions about the catalytic properties of minerals and the ability of minerals to organize sequences of disparate reactions. Another conclusion is that data in the Beilstein Handbook of Organic Chemistry that have been claimed to support the hypothesis that the reductive citric acid cycle originated as a self-organized cycle can more plausibly be interpreted in a different way.

  4. Self-Organized Porphyrinic Materials

    PubMed Central

    Drain, Charles Michael; Varotto, Alessandro; Radivojevic, Ivana

    2009-01-01

    The self-assembly and self-organization of porphyrins and related macrocycles enables the bottom-up fabrication of photonic materials for fundamental studies of the photophysics of these materials and for diverse applications. This rapidly developing field encompasses a broad range of disciplines including molecular design and synthesis, materials formation and characterization, and the design and evaluation of devices. Since the self-assembly of porphyrins by electrostatic interactions in the late 1980s to the present, there has been an ever increasing degree of sophistication in the design of porphyrins that self-assemble into discrete arrays or self-organize into polymeric systems. These strategies exploit ionic interactions, hydrogen bonding, coordination chemistry, and dispersion forces to form supramolecular systems with varying degrees of hierarchical order. This review concentrates on the methods to form supramolecular porphyrinic systems by intermolecular interactions other than coordination chemistry, the characterization and properties of these photonic materials, and the prospects for using these in devices. The review is heuristically organized by the predominant intermolecular interactions used and emphasizes how the organization affects properties and potential performance in devices. PMID:19253946

  5. Self Organization in Compensated Semiconductors

    NASA Astrophysics Data System (ADS)

    Berezin, Alexander A.

    2004-03-01

    In partially compensated semiconductor (PCS) Fermi level is pinned to donor sub-band. Due to positional randomness and almost isoenergetic hoppings, donor-spanned electronic subsystem in PCS forms fluid-like highly mobile collective state. This makes PCS playground for pattern formation, self-organization, complexity emergence, electronic neural networks, and perhaps even for origins of life, bioevolution and consciousness. Through effects of impact and/or Auger ionization of donor sites, whole PCS may collapse (spinodal decomposition) into microblocks potentially capable of replication and protobiological activity (DNA analogue). Electronic screening effects may act in RNA fashion by introducing additional length scale(s) to system. Spontaneous quantum computing on charged/neutral sites becomes potential generator of informationally loaded microstructures akin to "Carl Sagan Effect" (hidden messages in Pi in his "Contact") or informational self-organization of "Library of Babel" of J.L. Borges. Even general relativity effects at Planck scale (R.Penrose) may affect the dynamics through (e.g.) isotopic variations of atomic mass and local density (A.A.Berezin, 1992). Thus, PCS can serve as toy model (experimental and computational) at interface of physics and life sciences.

  6. mFOAM-1.02: A compact version of the cellular event generator FOAM

    NASA Astrophysics Data System (ADS)

    Jadach, S.; Sawicki, P.

    2007-09-01

    The general-purpose self-adapting Monte Carlo (MC) event generator/simulator mFOAM (standing for mini-FOAM) is a new compact version of the FOAM program, with a slightly limited functionality with respect to its parent version. On the other hand, mFOAM is easier to use for the average user. This new version is fully integrated with the ROOT package, the C++ utility library used widely in the particle physics community. The internal structure of the code is simplified and the very valuable feature of the persistency of the objects of the mFOAM class is improved. With the persistency at hand, it is possible to record very easily the complete state of a MC simulator object based on mFOAM and ROOT into a disk-file at any stage of its use: just after object allocation, after full initialization (exploration of the distribution), or at any time during the generation of the long series of MC events. Later on the MC simulator object can be easily restored from the disk-file in the "ready to go" state. Objects of the TFoam class can be used as a stand-alone solution to many everyday problems in the area of the Monte Carlo simulation, or as building blocks in large-scale MC projects, taking full advantage of the object-oriented technology and persistency. Program summaryManuscript title: mFOAM-1.02: A compact version of the cellular event generator FOAM Authors: S. Jadach, P. Sawicki Program title: mFOAM (mini FOAM), version 1.02 Catalogue identifier: ADYX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2 036 711 No. of bytes in distributed program, including test data, etc.: 21 403 104 Distribution format: tar.gz Programming language: ANSI C++ Computer: Most Unix workstations, supercomputers and PC Operating

  7. Geodesic self-organizing map

    NASA Astrophysics Data System (ADS)

    Wu, Yingxin; Takatsuka, Masahiro

    2005-03-01

    Self-Organizing map (SOM) is a widely used tool to find clustering and also to visualize high dimensional data. Several spherical SOMs have been proposed to create a more accurate representation of the data by removing the "border effect". In this paper, we compare several spherical lattices for the purpose of implementation of a SOM. We then introduce a 2D rectangular grid data structure for representing the geodesic dome. This new approach improves the neighborhood searching process in the spherical gird. The new Geodesic SOM and its data structure are tested using socio-demographic data. In the experiments, we try to create a notion of direction in the Geodesic SOM. The direction facilitates more consistent visual comparison of different datasets as well as to assist viewers building their mental maps.

  8. Self-organizing biochemical cycles

    PubMed Central

    Orgel, Leslie E.

    2000-01-01

    I examine the plausibility of theories that postulate the development of complex chemical organization without requiring the replication of genetic polymers such as RNA. One conclusion is that theories that involve the organization of complex, small-molecule metabolic cycles such as the reductive citric acid cycle on mineral surfaces make unreasonable assumptions about the catalytic properties of minerals and the ability of minerals to organize sequences of disparate reactions. Another conclusion is that data in the Beilstein Handbook of Organic Chemistry that have been claimed to support the hypothesis that the reductive citric acid cycle originated as a self-organized cycle can more plausibly be interpreted in a different way. PMID:11058157

  9. Self-Organizing Mesh Generation

    Energy Science and Technology Software Center (ESTSC)

    1991-11-01

    A set of five programs which make up a self organizing mesh generation package. QMESH generates meshes having quadrilateral elements on arbitrarily shaped two-dimensional (planar or axisymmetric) bodies. It is designed for use with two-dimensional finite element analysis applications. A flexible hierarchal input scheme is used to describe bodies to QMESH as collections of regions. A mesh for each region is developed independently, with the final assembly and bandwidth minimization performed by the independent program,more » RENUM or RENUM8. RENUM is applied when four-node elements are desired. Eight node elements (with mid side nodes) may be obtained with RENUM8. QPLOT and QPLOT8 are plot programs for meshes generated by the QMESH/RENUM and QMESH/RENUM8 program pairs respectively. QPLOT and QPLOT8 automatically section the mesh into appropriately-sized sections for legible display of node and element numbers, An overall plot showing the position of the selected plot areas is produced.« less

  10. Can dynamical synapses produce true self-organized criticality?

    NASA Astrophysics Data System (ADS)

    Costa, Ariadne de Andrade; Copelli, Mauro; Kinouchi, Osame

    2015-06-01

    Neuronal networks can present activity described by power-law distributed avalanches presumed to be a signature of a critical state. Here we study a random-neighbor network of excitable cellular automata coupled by dynamical synapses. The model exhibits a very similar to conservative self-organized criticality (SOC) models behavior even with dissipative bulk dynamics. This occurs because in the stationary regime the model is conservative on average, and, in the thermodynamic limit, the probability distribution for the global branching ratio converges to a delta-function centered at its critical value. So, this non-conservative model pertain to the same universality class of conservative SOC models and contrasts with other dynamical synapses models that present only self-organized quasi-criticality (SOqC). Analytical results show very good agreement with simulations of the model and enable us to study the emergence of SOC as a function of the parametric derivatives of the stationary branching ratio.

  11. Protein Folding and Self-Organized Criticality

    NASA Astrophysics Data System (ADS)

    Bajracharya, Arun; Murray, Joelle

    Proteins are known to fold into tertiary structures that determine their functionality in living organisms. However, the complex dynamics of protein folding and the way they consistently fold into the same structures is not fully understood. Self-organized criticality (SOC) has provided a framework for understanding complex systems in various systems (earthquakes, forest fires, financial markets, and epidemics) through scale invariance and the associated power law behavior. In this research, we use a simple hydrophobic-polar lattice-bound computational model to investigate self-organized criticality as a possible mechanism for generating complexity in protein folding.

  12. Functional self-organization in complex systems

    SciTech Connect

    Fontana, W. Santa Fe Inst., NM )

    1990-01-01

    A novel approach to functional self-organization is presented. It consists of a universe generated by a formal language that defines objects (=programs), their meaning (=functions), and their interactions (=composition). Results obtained so far are briefly discussed. 17 refs., 5 figs.

  13. Spatio-Temporal Self-Organization in Mudstones (Invited)

    NASA Astrophysics Data System (ADS)

    Dewers, T. A.

    2010-12-01

    Shales and other mudstones are the most abundant rock types in sedimentary basins, yet have received comparatively little attention. Common as hydrocarbon seals, these are increasingly being targeted as unconventional gas reservoirs, caprocks for CO2 sequestration, and storage repositories for waste. The small pore and grain size, large specific surface areas, and clay mineral structures lend themselves to rapid reaction rates, high capillary pressures, and semi-permeable membrane behavior accompanying changes in stress, pressure, temperature and chemical conditions. Under far from equilibrium conditions, mudrocks display a variety of spatio-temporal self-organized phenomena arising from nonlinear thermo-mechano-chemo-hydro coupling. Beginning with a detailed examination of nano-scale pore network structures in mudstones, we discuss the dynamics behind such self-organized phenomena as pressure solitons in unconsolidated muds, chemically-induced flow self focusing and permeability transients, localized compaction, time dependent well-bore failure, and oscillatory osmotic fluxes as they occur in clay-bearing sediments. Examples are draw from experiments, numerical simulation, and the field. These phenomena bear on the ability of these rocks to serve as containment barriers. This work is funded by the US Department of Energy, Office of Basic Energy Sciences. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000

  14. Spatio-temporal self-organization in mudstones.

    SciTech Connect

    Dewers, Thomas A.

    2010-12-01

    Shales and other mudstones are the most abundant rock types in sedimentary basins, yet have received comparatively little attention. Common as hydrocarbon seals, these are increasingly being targeted as unconventional gas reservoirs, caprocks for CO2 sequestration, and storage repositories for waste. The small pore and grain size, large specific surface areas, and clay mineral structures lend themselves to rapid reaction rates, high capillary pressures, and semi-permeable membrane behavior accompanying changes in stress, pressure, temperature and chemical conditions. Under far from equilibrium conditions, mudrocks display a variety of spatio-temporal self-organized phenomena arising from nonlinear thermo-mechano-chemo-hydro coupling. Beginning with a detailed examination of nano-scale pore network structures in mudstones, we discuss the dynamics behind such self-organized phenomena as pressure solitons in unconsolidated muds, chemically-induced flow self focusing and permeability transients, localized compaction, time dependent well-bore failure, and oscillatory osmotic fluxes as they occur in clay-bearing sediments. Examples are draw from experiments, numerical simulation, and the field. These phenomena bear on the ability of these rocks to serve as containment barriers.

  15. Mechanical-chemical coupling and self-organization in mudstones.

    SciTech Connect

    Heath, Jason E.; Dewers, Thomas A.

    2010-06-01

    Shales and other mudstones are the most abundant rock types in sedimentary basins, yet have received comparatively little attention. Common as hydrocarbon seals, these are increasingly being targeted as unconventional gas reservoirs, caprocks for CO{sub 2} sequestration, and storage repositories for waste. The small pore and grain size, large specific surface areas, and clay mineral structures lend themselves to rapid reaction rates accompanying changes in stress, pressure, temperature and chemical conditions. Under far from equilibrium conditions, mudrocks display a variety of spatio-temporal self-organized phenomena arising from the nonlinear coupling of mechanics with chemistry. Beginning with a detailed examination of nano-scale pore network structures in mudstones, we discuss the dynamics behind such self-organized phenomena as pressure solitons, chemically-induced flow self focusing and permeability transients, localized compaction, time dependent well-bore failure, and oscillatory osmotic fluxes as they occur in clay-bearing sediments. Examples are draw from experiments, numerical simulation, and the field. These phenomena bear on the ability of these rocks to serve as containment barriers.

  16. Self-organization in periodically sheared granular materials

    NASA Astrophysics Data System (ADS)

    Wilken, Sam; Hunter, Gary L.; Chaikin, Paul M.

    2015-03-01

    Self-organization as a result of periodic shear is becoming a feature observed in an increasing number of systems. In our experiments, we enforce cyclic shear on a three dimensional system of non-Brownian particles to investigate the global packing behavior of the granular assembly. By starting with a dilated, loosely packed system and measuring the packing fraction after each shear cycle, we find the system compacts to reach a steady state with a well defined packing fraction. The shear amplitude determines the steady state packing fraction, where large amplitude shear produces a lower packing density and small amplitude shear produces a higher packing density. We also study the phase diagram of this system which exhibits caged motion and a transition to vorticity.

  17. Self-Organized Criticality, Optimization and Biodiversity

    NASA Astrophysics Data System (ADS)

    Onody, Roberto N.; de Castro, Paulo A.

    By driving to extinction species that are less or poorly adapted, the Darwinian evolutionary theory is intrinsically an optimization theory. We investigate two optimization algorithms with such evolutionary characteristics: the Bak-Sneppen and the Extremal Optimization. By comparing their mean fitness in the steady state regime, we conclude that the Bak-Sneppen dynamics is more efficient than the Extremal Optimization if the parameter τ is in the interval [0, 0.86]. The determination of the spatial correlation and the probability distribution of the avalanches show that the Extremal Optimization dynamics does not lead the system into a critical self-organized state. Through a discrete form of the Bak-Sneppen model we argue that biodiversity is an essential prerequisite to preserve the self-organized criticality.

  18. Self-organization and clustering algorithms

    NASA Technical Reports Server (NTRS)

    Bezdek, James C.

    1991-01-01

    Kohonen's feature maps approach to clustering is often likened to the k or c-means clustering algorithms. Here, the author identifies some similarities and differences between the hard and fuzzy c-Means (HCM/FCM) or ISODATA algorithms and Kohonen's self-organizing approach. The author concludes that some differences are significant, but at the same time there may be some important unknown relationships between the two methodologies. Several avenues of research are proposed.

  19. Self-Organized Criticality and earthquakes

    SciTech Connect

    Caruso, Filippo; Pluchino, Alessandro; Latora, Vito; Rapisarda, Andrea; Vinciguerra, Sergio

    2007-12-06

    We discuss recent results on a new analysis regarding models showing Self-Organized Criticality (SOC), and in particular on the OFC one. We show that Probability Density Functions (PDFs) for the avalanche size differences at different times have fat tails with a q-Gaussian shape. This behavior does not depend on the time interval adopted and it is also found when considering energy differences between real earthquakes.

  20. Genetic information and self-organized criticality

    NASA Astrophysics Data System (ADS)

    Wills, P. R.; Marshall, J. M.; Smith, P. J.

    2004-12-01

    The numerical fitnesses of species defined in the Bak-Sneppen model of self-organized criticality are interpreted as binary strings. This allows new species to be generated by mutation of survivors. It is shown that selection in Bak-Sneppen systems defined on both uniform and random lattices produces genotypes in conformity with the Eigen criterion for the accumulation of genetic information in macromolecular sequences.

  1. Archetypes, complexes and self-organization.

    PubMed

    Saunders, P; Skar, P

    2001-04-01

    There has always been confusion and disagreement about the nature of the terms archetype and complex in Jungian circles, not to mention non-Jungian ones. Another ongoing concern is whether Jung's concept of the archetype and complex can be justified in terms of current scientific research, most notably that of neurophysiologists and others interested in the brain and consciousness. This paper proposes a theory of the formation of complexes, namely, that they are created through self-organization within the brain/mind. Self-organization is a process typical of large complex systems, and is generally accepted to operate within the brain and to be important in its functioning. Examples of self-organization in biology are related to the psychic processes that form the complexes. It is then natural to define the archetype in terms of the complex, and the authors propose a definition of the archetype as an equivalence class of complexes. On this view, the archetype is an emergent property of the activity of the brain/mind, and is, appropriately, defined at the level at which it emerges. This definition is in line with the original development of Jung's ideas, in that he derived the concept of the archetype from his earlier discovery of the feeling-toned complex. PMID:11307698

  2. Self organizing software research : LDRD final report.

    SciTech Connect

    Osbourn, Gordon Cecil

    2004-01-01

    We have made progress in developing a new statistical mechanics approach to designing self organizing systems that is unique to SNL. The primary application target for this ongoing research has been the development of new kinds of nanoscale components and hardware systems. However, this research also enables an out of the box connection to the field of software development. With appropriate modification, the collective behavior physics ideas for enabling simple hardware components to self organize may also provide design methods for a new class of software modules. Our current physics simulations suggest that populations of these special software components would be able to self assemble into a variety of much larger and more complex software systems. If successful, this would provide a radical (disruptive technology) path to developing complex, high reliability software unlike any known today. This high risk, high payoff opportunity does not fit well into existing SNL funding categories, as it is well outside of the mainstreams of both conventional software development practices and the nanoscience research area that spawned it. This LDRD effort was aimed at developing and extending the capabilities of self organizing/assembling software systems, and to demonstrate the unique capabilities and advantages of this radical new approach for software development.

  3. Perception and self-organized instability

    PubMed Central

    Friston, Karl; Breakspear, Michael; Deco, Gustavo

    2012-01-01

    This paper considers state-dependent dynamics that mediate perception in the brain. In particular, it considers the formal basis of self-organized instabilities that enable perceptual transitions during Bayes-optimal perception. The basic phenomena we consider are perceptual transitions that lead to conscious ignition (Dehaene and Changeux, 2011) and how they depend on dynamical instabilities that underlie chaotic itinerancy (Breakspear, 2001; Tsuda, 2001) and self-organized criticality (Beggs and Plenz, 2003; Plenz and Thiagarajan, 2007; Shew et al., 2011). Our approach is based on a dynamical formulation of perception as approximate Bayesian inference, in terms of variational free energy minimization. This formulation suggests that perception has an inherent tendency to induce dynamical instabilities (critical slowing) that enable the brain to respond sensitively to sensory perturbations. We briefly review the dynamics of perception, in terms of generalized Bayesian filtering and free energy minimization, present a formal conjecture about self-organized instability and then test this conjecture, using neuronal (numerical) simulations of perceptual categorization. PMID:22783185

  4. Self-organizing human cardiac microchambers mediated by geometric confinement

    NASA Astrophysics Data System (ADS)

    Ma, Zhen; Wang, Jason; Loskill, Peter; Huebsch, Nathaniel; Koo, Sangmo; Svedlund, Felicia L.; Marks, Natalie C.; Hua, Ethan W.; Grigoropoulos, Costas P.; Conklin, Bruce R.; Healy, Kevin E.

    2015-07-01

    Tissue morphogenesis and organ formation are the consequences of biochemical and biophysical cues that lead to cellular spatial patterning in development. To model such events in vitro, we use PEG-patterned substrates to geometrically confine human pluripotent stem cell colonies and spatially present mechanical stress. Modulation of the WNT/β-catenin pathway promotes spatial patterning via geometric confinement of the cell condensation process during epithelial-mesenchymal transition, forcing cells at the perimeter to express an OCT4+ annulus, which is coincident with a region of higher cell density and E-cadherin expression. The biochemical and biophysical cues synergistically induce self-organizing lineage specification and creation of a beating human cardiac microchamber confined by the pattern geometry. These highly defined human cardiac microchambers can be used to study aspects of embryonic spatial patterning, early cardiac development and drug-induced developmental toxicity.

  5. Self-organizing human cardiac microchambers mediated by geometric confinement

    PubMed Central

    Ma, Zhen; Wang, Jason; Loskill, Peter; Huebsch, Nathaniel; Koo, Sangmo; Svedlund, Felicia L.; Marks, Natalie C.; Hua, Ethan W.; Grigoropoulos, Costas P.; Conklin, Bruce R.; Healy, Kevin E.

    2015-01-01

    Tissue morphogenesis and organ formation are the consequences of biochemical and biophysical cues that lead to cellular spatial patterning in development. To model such events in vitro, we use PEG-patterned substrates to geometrically confine human pluripotent stem cell colonies and spatially present mechanical stress. Modulation of the WNT/β-catenin pathway promotes spatial patterning via geometric confinement of the cell condensation process during epithelial–mesenchymal transition, forcing cells at the perimeter to express an OCT4+ annulus, which is coincident with a region of higher cell density and E-cadherin expression. The biochemical and biophysical cues synergistically induce self-organizing lineage specification and creation of a beating human cardiac microchamber confined by the pattern geometry. These highly defined human cardiac microchambers can be used to study aspects of embryonic spatial patterning, early cardiac development and drug-induced developmental toxicity. PMID:26172574

  6. Electroluminescence from self-organized ``microdomes''

    NASA Astrophysics Data System (ADS)

    Karthaus, Olaf; Adachi, Chihaya; Kurimura, Shigeya; Oyamada, Takahito

    2004-06-01

    The preparation of a self-organized, microstructured organic electroluminescent device is reported. A dewetting process is used to form (sub)micrometer-sized dewetted patches ("domes") of a hole transport material (tolyl-phenyl-diaminobiphenyl, TPD) on an indium-tin-oxide electrode. The domes are regular in size and spacing. Evaporation of an electron transport material (tris-8-hydroxyquinoline aluminum, Alq3) and an Mg/Ag top electrode leads to a device with electroluminescing spots of micrometer dimensions and a spacing of a few micrometers.

  7. Self-organizing systems and environmental management

    NASA Astrophysics Data System (ADS)

    Hollick, Malcolm

    1993-09-01

    The characteristics of self-organizing systems are described and their implications for environmental management are discussed. It is concluded that the aim of management should be to enhance the capacity of the system for self-management, with active intervention being used only to steer it away from large discontinuities. Environmental managers must view ecosystems and themselves as parts of a larger sociobiophysical system, cultivate the capacity of environmental systems for self-management, and learn to live with change and uncertainty. Practical consequences of this approach for plans, policies, programs, and institutions are discussed.

  8. Self-organization of microtubules and motors.

    SciTech Connect

    Aranson, I. S.; Tsimring, L. S.; Materials Science Division; Univ. of California at San Diego

    2006-01-01

    Here we introduce a model for spatio-temporal self-organization of an ensemble of microtubules interacting via molecular motors. Starting from a generic stochastic model of inelastic polar rods with an anisotropic interaction kernel we derive a set of equations for the local rods concentration and orientation. At large enough mean density of rods and concentration of motors, the model describes orientational instability. We demonstrate that the orientational instability leads to the formation of vortices and (for large density and/or kernel anisotropy) asters seen in recent experiments. The corresponding phase diagram of vortexasters transitions is in qualitative agreement with experiment.

  9. Toward Self-Organizing Search Systems

    NASA Astrophysics Data System (ADS)

    Barton, Stanislav; Dohnal, Vlastislav; Sedmidubsky, Jan; Zezula, Pavel

    The huge amount of images, videos, and music clips produced everyday by various digital devices must be processed. Firstly, this kind of data calls for content-based search or similarity search rather than keyword-based or text-based search. Secondly, new scalable and efficient methods capable of storing and querying such data must be developed. Although many distributed approaches exist, one of the most suitable and flexible is provided by self-organizing systems. These systems exhibit high resistance to failures in dynamically changing environments. In this chapter, we propose a general three-layer model for designing and implementing a self-organizing system that aims at searching in multimedia data. This model gives a developer guidelines about what component must be implemented, and how they should behave. The usability of this model is illustrated on a system called Metric Social Network. The architecture of this system is based on the social network theory that is utilized for establishing links between nodes. The system's properties are verified by organizing and searching in 10 million images.

  10. Non-Equilibrium Nanoscale Self-Organization

    SciTech Connect

    Aziz, Michael J

    2006-03-09

    Self-organized one- and two-dimensional arrays of nanoscale surface features ("ripples" and "dots") sometimes form spontaneously on initially flat surfaces eroded by a directed ion beam in a process called "sputter patterning". Experiments on this sputter patterning process with focused and unfocused ion beams, combined with theoretical advances, have been responsible for a number of scientific advances. Particularly noteworthy are (i) the discovery of propagative, rather than dissipative, behavior under some ion erosion conditions, permitting a pattern to be fabricated at a large length scale and propagated over large distances while maintaining, or even sharpening, the sharpest features; (ii) the first demonstration of guided self-organization of sputter patterns, along with the observation that defect density is minimized when the spacing between boundaries is near an integer times the natural spatial period; and (iii) the discovery of metastability of smooth surfaces, which contradicts the nearly universally accepted linear stability theory that predicts that any surface is linearly unstable to sinusoidal perturbations of some wave vector.

  11. Self-Organization in Granular Slurries

    NASA Astrophysics Data System (ADS)

    Ottino, Julio M.; Jain, Nitin; Lueptow, Richard M.; Khakhar, Devang V.

    2000-11-01

    Mixtures of tumbled granular materials under flow exhibit various intriguing types of un-mixing or self-organization. Small differences in particles' density, size or shape may trigger the effect. Nearly all studies to date have addressed the case of dry granular media, where the interparticle fluid is typically air. Here we report the existence of self-organization in wet granular media or slurries, mixtures of particles of different sizes dispersed in a lower density liquid. Technological examples appear in cement, ceramics, fine chemicals, and in the food industry; examples in nature appear in evolution of landslides and transport in river sediments. In spite of significantly different physics at the particle level, both axial banding (alternating bands rich in small and large particles in a long rotating cylinder) and radial segregation (in quasi 2D containers) are observed in slurries. However, axial segregation is significantly faster and the spectrum of outcomes is richer. Moreover, experiments with suitable fluids, reveal, for the first time, the internal structure of axially segregated systems, something that up to now has been accessible only via magnetic resonance imaging (MRI) experimentation.

  12. Compact plane illumination plugin device to enable light sheet fluorescence imaging of multi-cellular organisms on an inverted wide-field microscope

    PubMed Central

    Guan, Zeyi; Lee, Juhyun; Jiang, Hao; Dong, Siyan; Jen, Nelson; Hsiai, Tzung; Ho, Chih-Ming; Fei, Peng

    2015-01-01

    We developed a compact plane illumination plugin (PIP) device which enabled plane illumination and light sheet fluorescence imaging on a conventional inverted microscope. The PIP device allowed the integration of microscope with tunable laser sheet profile, fast image acquisition, and 3-D scanning. The device is both compact, measuring approximately 15 by 5 by 5 cm, and cost-effective, since we employed consumer electronics and an inexpensive device molding method. We demonstrated that PIP provided significant contrast and resolution enhancement to conventional microscopy through imaging different multi-cellular fluorescent structures, including 3-D branched cells in vitro and live zebrafish embryos. Imaging with the integration of PIP greatly reduced out-of-focus contamination and generated sharper contrast in acquired 2-D plane images when compared with the stand-alone inverted microscope. As a result, the dynamic fluid domain of the beating zebrafish heart was clearly segmented and the functional monitoring of the heart was achieved. Furthermore, the enhanced axial resolution established by thin plane illumination of PIP enabled the 3-D reconstruction of the branched cellular structures, which leads to the improvement on the functionality of the wide field microscopy. PMID:26819828

  13. Cusps, self-organization, and absorbing states.

    PubMed

    Bonachela, Juan A; Alava, Mikko; Muñoz, Miguel A

    2009-05-01

    Elastic interfaces embedded in (quenched) random media exhibit metastability and stick-slip dynamics. These nontrivial dynamical features have been shown to be associated with cusp singularities of the coarse-grained disorder correlator. Here we show that annealed systems with many absorbing states and a conservation law but no quenched disorder exhibit identical cusps. On the other hand, similar nonconserved systems in the directed percolation class are also shown to exhibit cusps but of a different type. These results are obtained both by a recent method to explicitly measure disorder correlators and by defining an alternative new protocol inspired by self-organized criticality, which opens the door to easily accessible experimental realizations. PMID:19518401

  14. Self-Organization, Transformity, and Information

    NASA Astrophysics Data System (ADS)

    Odum, Howard T.

    1988-11-01

    Ecosystems and other self-organizing systems develop system designs and mathematics that reinforce energy use, characteristically with alternate pulsing of production and consumption, increasingly recognized as the new paradigm. Insights from the energetics of ecological food chains suggest the need to redefine work, distinguishing kinds of energy with a new quantity, the transformity (energy of one type required per unit of another). Transformities may be used as an energy-scaling factor for the hierarchies of the universe including information. Solar transformities in the biosphere, expressed as solar emjoules per joule, range from one for solar insolation to trillions for categories of shared information. Resource contributions multiplied by their transformities provide a scientifically based value system for human service, environmental mitigation, foreign trade equity, public policy alternatives, and economic vitality.

  15. Self-organization of collaboration networks.

    PubMed

    Ramasco, José J; Dorogovtsev, S N; Pastor-Satorras, Romualdo

    2004-09-01

    We study collaboration networks in terms of evolving, self-organizing bipartite graph models. We propose a model of a growing network, which combines preferential edge attachment with the bipartite structure, generic for collaboration networks. The model depends exclusively on basic properties of the network, such as the total number of collaborators and acts of collaboration, the mean size of collaborations, etc. The simplest model defined within this framework already allows us to describe many of the main topological characteristics (degree distribution, clustering coefficient, etc.) of one-mode projections of several real collaboration networks, without parameter fitting. We explain the observed dependence of the local clustering on degree and the degree-degree correlations in terms of the "aging" of collaborators and their physical impossibility to participate in an unlimited number of collaborations. PMID:15524586

  16. Supramolecular materials: Self-organized nanostructures

    SciTech Connect

    Stupp, S.I.; LeBonheur, V.; Walker, K.

    1997-04-18

    Miniaturized triblock copolymers have been found to self-assemble into nanostructures that are highly regular in size and shape. Mushroom-shaped supramolecular structures of about 200 kilodaltons form by crystallization of the chemically identical blocks and self-organize into films containing 100 or more layers stacked in a polar arrangement. The polar supramolecular material exhibits spontaneous second-harmonic generation from infrared to green photons and has an adhesive tape-like character with nonadhesive-hydrophobic and hydrophilic-sticky opposite surfaces. The films also have reasonable shear strength and adhere tenaciously to glass surfaces on one side only. The regular and finite size of the supramolecular units is believed to be mediated by repulsive forces among some of the segments in the triblock molecules. A large diversity of multifunctional materials could be formed from regular supramolecular units weighing hundreds of kilodaltons. 21 refs., 10 figs.

  17. Feedback, Lineages and Self-Organizing Morphogenesis

    PubMed Central

    Calof, Anne L.; Lowengrub, John S.; Lander, Arthur D.

    2016-01-01

    Feedback regulation of cell lineage progression plays an important role in tissue size homeostasis, but whether such feedback also plays an important role in tissue morphogenesis has yet to be explored. Here we use mathematical modeling to show that a particular feedback architecture in which both positive and negative diffusible signals act on stem and/or progenitor cells leads to the appearance of bistable or bi-modal growth behaviors, ultrasensitivity to external growth cues, local growth-driven budding, self-sustaining elongation, and the triggering of self-organization in the form of lamellar fingers. Such behaviors arise not through regulation of cell cycle speeds, but through the control of stem or progenitor self-renewal. Even though the spatial patterns that arise in this setting are the result of interactions between diffusible factors with antagonistic effects, morphogenesis is not the consequence of Turing-type instabilities. PMID:26989903

  18. Self-organized defensive behavior in honeybees.

    PubMed

    Millor, J; Pham-Delegue, M; Deneubourg, J L; Camazine, S

    1999-10-26

    We investigated the defensive behavior of honeybees under controlled experimental conditions. During an attack on two identical targets, the spatial distribution of stings varied as a function of the total number of stings, evincing the classic "pitchfork bifurcation" phenomenon of nonlinear dynamics. The experimental results support a model of defensive behavior based on a self-organizing mechanism. The model helps to explain several of the characteristic features of the honeybee defensive response: (i) the ability of the colony to localize and focus its attack, (ii) the strong variability between different hives in the intensity of attack, as well as (iii) the variability observed within the same hive, and (iv) the ability of the colony to amplify small differences between the targets. PMID:10535970

  19. TEMPORAL SELF-ORGANIZATION IN GALAXY FORMATION

    SciTech Connect

    Cen, Renyue

    2014-04-20

    We report on the discovery of a relation between the number of star formation (SF) peaks per unit time, ν{sub peak}, and the size of the temporal smoothing window function, Δt, used to define the peaks: ν{sub peak}∝Δt {sup 1} {sup –} {sup φ} (φ ∼ 1.618). This relation holds over the range of Δt = 10-1000 Myr that can be reliably computed here, using a large sample of galaxies obtained from a state-of-the-art cosmological hydrodynamic simulation. This means that the temporal distribution of SF peaks in galaxies as a population is fractal with a Hausdorff fractal dimension equal to φ – 1. This finding reveals, for the first time, that the superficially chaotic process of galaxy formation is underlined by temporal self-organization up to at least one gigayear. It is tempting to suggest that, given the known existence of spatial fractals (such as the power-law two-point function of galaxies), there is a joint spatio-temporal self-organization in galaxy formation. From an observational perspective, it will be urgent to devise diagnostics to probe the SF histories of galaxies with good temporal resolution to facilitate a test of this prediction. If confirmed, it would provide unambiguous evidence for a new picture of galaxy formation that is interaction driven, cooperative, and coherent in and between time and space. Unravelling its origin may hold the key to understanding galaxy formation.

  20. A self-organized neural comparator.

    PubMed

    Ludueña, Guillermo A; Gros, Claudius

    2013-04-01

    Learning algorithms need generally the ability to compare several streams of information. Neural learning architectures hence need a unit, a comparator, able to compare several inputs encoding either internal or external information, for instance, predictions and sensory readings. Without the possibility of comparing the values of predictions to actual sensory inputs, reward evaluation and supervised learning would not be possible. Comparators are usually not implemented explicitly. Necessary comparisons are commonly performed by directly comparing the respective activities one-to-one. This implies that the characteristics of the two input streams (like size and encoding) must be provided at the time of designing the system. It is, however, plausible that biological comparators emerge from self-organizing, genetically encoded principles, which allow the system to adapt to the changes in the input and the organism. We propose an unsupervised neural circuitry, where the function of input comparison emerges via self-organization only from the interaction of the system with the respective inputs, without external influence or supervision. The proposed neural comparator adapts in an unsupervised form according to the correlations present in the input streams. The system consists of a multilayer feedforward neural network, which follows a local output minimization (anti-Hebbian) rule for adaptation of the synaptic weights. The local output minimization allows the circuit to autonomously acquire the capability of comparing the neural activities received from different neural populations, which may differ in population size and the neural encoding used. The comparator is able to compare objects never encountered before in the sensory input streams and evaluate a measure of their similarity even when differently encoded. PMID:23339611

  1. Crossover from percolation to self-organized criticality

    NASA Astrophysics Data System (ADS)

    Drossel, Barbara; Clar, Siegfried; Schwabl, Franz

    1994-10-01

    We include immunity against fire into the self-organized critical forest-fire model. When the immunity assumes a critical value, clusters of burnt trees are identical to percolation clusters of random bond percolation. As long as the immunity is below its critical value, the asymptotic critical exponents are those of the original self-organized critical model, i.e., the system performs a crossover from percolation to self-organized criticality. We present a scaling theory and computer simulation results.

  2. Scaling and self-organized criticality in proteins: Lysozyme c

    NASA Astrophysics Data System (ADS)

    Phillips, J. C.

    2009-11-01

    Proteins appear to be the most dramatic natural example of self-organized criticality (SOC), a concept that explains many otherwise apparently unlikely phenomena. Protein functionality is often dominated by long-range hydro(phobic/philic) interactions, which both drive protein compaction and mediate protein-protein interactions. In contrast to previous reductionist short-range hydrophobicity scales, the holistic Moret-Zebende hydrophobicity scale [Phys. Rev. E 75, 011920 (2007)] represents a hydroanalytic tool that bioinformatically quantifies SOC in a way fully compatible with evolution. Hydroprofiling identifies chemical trends in the activities and substrate binding abilities of model enzymes and antibiotic animal lysozymes c , as well as defensins, which have been the subject of tens of thousands of experimental studies. The analysis is simple and easily performed and immediately yields insights not obtainable by traditional methods based on short-range real-space interactions, as described either by classical force fields used in molecular-dynamics simulations, or hydrophobicity scales based on transference energies from water to organic solvents or solvent-accessible areas.

  3. Self-organized discrimination of resources.

    PubMed

    Campo, Alexandre; Garnier, Simon; Dédriche, Olivier; Zekkri, Mouhcine; Dorigo, Marco

    2011-01-01

    When selecting a resource to exploit, an insect colony must take into account at least two constraints: the resource must be abundant enough to sustain the whole group, but not too large to limit exploitation costs, and risks of conflicts with other colonies. Following recent results on cockroaches and ants, we introduce here a behavioral mechanism that satisfies these two constraints. Individuals simply modulate their probability to switch to another resource as a function of the local density of conspecifics locally detected. As a result, the individuals gather at the smallest resource that can host the whole group, hence reducing competition and exploitation costs while fulfilling the overall group's needs. Our analysis reveals that the group becomes better at discriminating between similar resources as it grows in size. Also, the discrimination mechanism is flexible and the group readily switches to a better suited resource as it appears in the environment. The collective decision emerges through the self-organization of individuals, that is, in absence of any centralized control. It also requires a minimal individual cognitive investment, making the proposed mechanism likely to occur in other social species and suitable for the development of distributed decision making tools. PMID:21625643

  4. Self-Organized Discrimination of Resources

    PubMed Central

    Campo, Alexandre; Garnier, Simon; Dédriche, Olivier; Zekkri, Mouhcine; Dorigo, Marco

    2011-01-01

    When selecting a resource to exploit, an insect colony must take into account at least two constraints: the resource must be abundant enough to sustain the whole group, but not too large to limit exploitation costs, and risks of conflicts with other colonies. Following recent results on cockroaches and ants, we introduce here a behavioral mechanism that satisfies these two constraints. Individuals simply modulate their probability to switch to another resource as a function of the local density of conspecifics locally detected. As a result, the individuals gather at the smallest resource that can host the whole group, hence reducing competition and exploitation costs while fulfilling the overall group's needs. Our analysis reveals that the group becomes better at discriminating between similar resources as it grows in size. Also, the discrimination mechanism is flexible and the group readily switches to a better suited resource as it appears in the environment. The collective decision emerges through the self-organization of individuals, that is, in absence of any centralized control. It also requires a minimal individual cognitive investment, making the proposed mechanism likely to occur in other social species and suitable for the development of distributed decision making tools. PMID:21625643

  5. Self-Organizing Maps with Refractory Periods

    NASA Astrophysics Data System (ADS)

    Neme, Antonio; Mireles, Victor

    2008-11-01

    Self-organizing map (SOM) has been studied as a model of map formation in the brain cortex. However, the original model present several oversimplifications. For example, neurons in the cortex present a refractory period in which they are not able to be activated, restriction that should be included in the SOM if a better model is to be achieved. Although several modifications have been studied in order to include this biological restriction to the SOM, they do not reflect biological plausibility. Here, we present a modification in the SOM that allows neurons to enter a refractory period (SOM-RP) if they are the best matching unit (BMU) or if they belong to its neighborhood. This refractory period is the same for all affected neurons, which contrasts with previous models. By including this biological restriction, SOM dynamics resembles in more detail the behavior shown by the cortex, such as non-radial activity patterns and long distance influence, besides the refractory period. As a side effect, two error measures are lower in maps formed by SOM-RP than in those formed by SOM.

  6. Free Energy and Dendritic Self-Organization

    PubMed Central

    Kiebel, Stefan J.; Friston, Karl J.

    2011-01-01

    In this paper, we pursue recent observations that, through selective dendritic filtering, single neurons respond to specific sequences of presynaptic inputs. We try to provide a principled and mechanistic account of this selectivity by applying a recent free-energy principle to a dendrite that is immersed in its neuropil or environment. We assume that neurons self-organize to minimize a variational free-energy bound on the self-information or surprise of presynaptic inputs that are sampled. We model this as a selective pruning of dendritic spines that are expressed on a dendritic branch. This pruning occurs when postsynaptic gain falls below a threshold. Crucially, postsynaptic gain is itself optimized with respect to free energy. Pruning suppresses free energy as the dendrite selects presynaptic signals that conform to its expectations, specified by a generative model implicit in its intracellular kinetics. Not only does this provide a principled account of how neurons organize and selectively sample the myriad of potential presynaptic inputs they are exposed to, but it also connects the optimization of elemental neuronal (dendritic) processing to generic (surprise or evidence-based) schemes in statistics and machine learning, such as Bayesian model selection and automatic relevance determination. PMID:22013413

  7. Emergence, self-organization and developmental science.

    PubMed

    Greenberg, Gary; Callina, Kristina Schmid; Mueller, Megan Kiely

    2013-01-01

    Our understanding is that psychology is a biopsychosocial science as well as a developmental science. Behavioral origins stem from ontogenetic processes, behavioral as well as biological. Biological factors are simply participating factors in behavioral origins and not causal factors. Psychology is not a biological science; it is a unique psychological science, a natural science consistent and compatible with the principles of the other sciences. Accordingly, we show in this chapter how principles and ideas from other sciences play important roles in psychology. While we focus on the concepts from physics of self-organization and emergence, we also address the cosmological and evolutionary biology idea of increased complexity over time, the organizing principle of integrative levels, and the epigenetic processes that are in part responsible for transgenerational trait transmission. Our discussion stresses the developmental science concepts of embodiment and contextualism and how they structure thinking about psychological processes. We conclude with a description of how these ideas support current postpositivist conceptions of relational processes and models in contemporary developmental science. PMID:23834003

  8. Self-Organizing Maps with Refractory Periods

    SciTech Connect

    Neme, Antonio; Mireles, Victor

    2008-11-06

    Self-organizing map (SOM) has been studied as a model of map formation in the brain cortex. However, the original model present several oversimplifications. For example, neurons in the cortex present a refractory period in which they are not able to be activated, restriction that should be included in the SOM if a better model is to be achieved. Although several modifications have been studied in order to include this biological restriction to the SOM, they do not reflect biological plausibility. Here, we present a modification in the SOM that allows neurons to enter a refractory period (SOM-RP) if they are the best matching unit (BMU) or if they belong to its neighborhood. This refractory period is the same for all affected neurons, which contrasts with previous models. By including this biological restriction, SOM dynamics resembles in more detail the behavior shown by the cortex, such as non-radial activity patterns and long distance influence, besides the refractory period. As a side effect, two error measures are lower in maps formed by SOM-RP than in those formed by SOM.

  9. The self-organization of explicit attitudes.

    PubMed

    Wojnowicz, Michael T; Ferguson, Melissa J; Dale, Rick; Spivey, Michael J

    2009-11-01

    How do minds produce explicit attitudes over several hundred milliseconds? Speeded evaluative measures have revealed implicit biases beyond cognitive control and subjective awareness, yet mental processing may culminate in an explicit attitude that feels personally endorsed and corroborates voluntary intentions. We argue that self-reported explicit attitudes derive from a continuous, temporally dynamic process, whereby multiple simultaneously conflicting sources of information self-organize into a meaningful mental representation. While our participants reported their explicit (like vs. dislike) attitudes toward White versus Black people by moving a cursor to a "like" or "dislike" response box, we recorded streaming x- and y-coordinates from their hand-movement trajectories. We found that participants' hand-movement paths exhibited greater curvature toward the "dislike" response when they reported positive explicit attitudes toward Black people than when they reported positive explicit attitudes toward White people. Moreover, these trajectories were characterized by movement disorder and competitive velocity profiles that were predicted under the assumption that the deliberate attitudes emerged from continuous interactions between multiple simultaneously conflicting constraints. PMID:19818047

  10. Emergence, Self-Organization and Prime Numbers

    NASA Astrophysics Data System (ADS)

    Berezin, Alexander A.

    1998-04-01

    Pattern of primes (PP) is critical for dynamics of universal emergence, self-organization and complexity ascendance [1-3]. Due to gradual logarithmic dilution of primes (prime number theorem), PP gives only base envelop for above effects. More informative are full factorizational spectra (FS) of all intermediate composites. Tower exponential mappings like f(N) = 10(N)10 with (N) indicating N vertical arrows [4] lead to infinite fractal-like hierarchy of integer trails; say, FS of intervals between f(N) and f(N+1). This allows FAPP-infinite informational content of PP and FS be "used" as catalyzer of emergence dynamics. This is "Platonic pressure effect" (physical embodiments of PP and FS). Said effect may provide more direct picture for cosmogenesis than traditional quantum tunneling ("Big Bang") and/or inflationary scenarios. Furthermore, we can speculate that metrics of (Mega)universe at tower exponential scales becomes asymptotically Euclidean (multi or infinitely dimensional), due to unchangability of PP and FS. - [1] Arnold Arnold, "The Corrupted Sciences", Paladin (Harper Collins), 1992; [2] Peter Plichta, "God's Secret Formula: Deciphering the Riddle of the Universe and the Prime Number Code", Element, 1997; [3] Alexander Berezin, URAM Journal, 20, 72 (1997); [4] Donald E. Knuth, Science, 194, 1235, 17 Dec 1976. abstract.

  11. Formation And Maintenance of Self-Organizing Wireless Networks

    NASA Technical Reports Server (NTRS)

    Scott, Keith; Bambos, Nicholas

    1997-01-01

    There are numerous military, commercial, and scientific applications for mobile wireless networks which are able to self-Organize without recousre to any pre-existing infrastructure. We present the Self Organizing Wireless Adaptive Network protocol, a distributed networking protocol capable of managing such networks.

  12. 25 Years of Self-Organized Criticality: Solar and Astrophysics

    NASA Astrophysics Data System (ADS)

    Aschwanden, Markus J.; Crosby, Norma B.; Dimitropoulou, Michaila; Georgoulis, Manolis K.; Hergarten, Stefan; McAteer, James; Milovanov, Alexander V.; Mineshige, Shin; Morales, Laura; Nishizuka, Naoto; Pruessner, Gunnar; Sanchez, Raul; Sharma, A. Surja; Strugarek, Antoine; Uritsky, Vadim

    2016-01-01

    Shortly after the seminal paper "Self-Organized Criticality: An explanation of 1/ f noise" by Bak et al. (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. We review SOC studies from the last 25 years and highlight new trends, open questions, and future challenges, as discussed during two recent ISSI workshops on this theme.

  13. Fractal Self-Organization of Bacteria-Inspired Agents

    NASA Astrophysics Data System (ADS)

    Huang, Yufeng; Krumanocker, Ian; Coppens, Marc-Olivier

    2012-06-01

    We develop an agent-based model as a preliminary theoretical basis to guide the synthesis of a new class of materials with dynamic properties similar to bacterial colonies. Each agent in the model is representative of an individual bacterium capable of: the uptake of chemicals (nutrients), which are metabolized; active movement (part viscous, part diffusive), consuming metabolic energy; and cellular division, when agents have doubled in size. The agents grow in number and self-organize into fractal structures, depending on the rules that define the actions of the agents and the parameter values. The environment of the agents includes chemicals responsible for their growth and is described by a diffusion-reaction equation with Michaelis-Menten kinetics. These rules are modeled mathematically by a set of equations with five dimensionless groups that are functions of physical parameters. Simulations are performed for different parameter values. The resulting structures are characterized by their fractal scaling regime, box-counting and mass-radius dimensions, and lacunarity. Each parameter influences the overall structure in a unique way, generating a wide spectrum of structures. For certain combinations of parameter values, the model converges to a steady state, with a finite population of agents that no longer divide.

  14. Active gels: dynamics of patterning and self-organization

    NASA Astrophysics Data System (ADS)

    Backouche, F.; Haviv, L.; Groswasser, D.; Bernheim-Groswasser, A.

    2006-12-01

    The actin cytoskeleton is an active gel which constantly remodels during cellular processes such as motility and division. Myosin II molecular motors are involved in this active remodeling process and therefore control the dynamic self-organization of cytoskeletal structures. Due to the complexity of in vivo systems, it is hard to investigate the role of myosin II in the reorganization process which determines the resulting cytoskeletal structures. Here we use an in vitro model system to show that myosin II actively reorganizes actin into a variety of mesoscopic patterns, but only in the presence of bundling proteins. We find that the nature of the reorganization process is complex, exhibiting patterns and dynamical phenomena not predicted by current theoretical models and not observed in corresponding passive systems (excluding motors). This system generates active networks, asters and even rings depending on motor and bundling protein concentrations. Furthermore, the motors generate the formation of the patterns, but above a critical concentration they can also disassemble them and even totally prevent the polymerization and bundling of actin filaments. These results may suggest that tuning the assembly and disassembly of cytoskeletal structures can be obtained by tuning the local myosin II concentration/activity.

  15. Hierarchical self-organization of cytoskeletal active networks

    NASA Astrophysics Data System (ADS)

    Gordon, Daniel; Bernheim-Groswasser, Anne; Keasar, Chen; Farago, Oded

    2012-04-01

    The structural reorganization of the actin cytoskeleton is facilitated through the action of motor proteins that crosslink the actin filaments and transport them relative to each other. Here, we present a combined experimental-computational study that probes the dynamic evolution of mixtures of actin filaments and clusters of myosin motors. While on small spatial and temporal scales the system behaves in a very noisy manner, on larger scales it evolves into several well distinct patterns such as bundles, asters and networks. These patterns are characterized by junctions with high connectivity, whose formation is possible due to the organization of the motors in ‘oligoclusters’ (intermediate-size aggregates). The simulations reveal that the self-organization process proceeds through a series of hierarchical steps, starting from local microscopic moves and ranging up to the macroscopic large scales where the steady-state structures are formed. Our results shed light on the mechanisms involved in processes such as cytokinesis and cellular contractility, where myosin motors organized in clusters operate cooperatively to induce the structural organization of cytoskeletal networks.

  16. Self-organizing maps and galaxy evolution

    NASA Astrophysics Data System (ADS)

    Beland, Jacques

    Artificial Neural Networks (ANN) have been applied to many areas of research. These techniques use a series of object attributes and can be trained to recognize different classes of objects. The Self-Organizing Map (SOM) is an unsupervised machine learning technique which has been shown to be successful in the mapping of high-dimensional data into a 2D representation referred to as a map. These maps are easier to interpret and aid in the classification of data. In this work, the existing algorithms for the SOM have been extended to generate 3D maps. The higher dimensionality of the map provides for more information to be made available to the interpretation of classifications. The effectiveness of the implementation was verified using three separate standard datasets. Results from these investigations supported the expectation that a 3D SOM would result in a more effective classifier. The 3D SOM algorithm was then applied to an analysis of galaxy morphology classifications. It is postulated that the morphology of a galaxy relates directly to how it will evolve over time. In this work, the Spectral Energy Distribution (SED) will be used as a source for galaxy attributes. The SED data was extracted from the NASA Extragalactic Database (NED). The data was grouped into sample sets of matching frequencies and the 3D SOM application was applied as a morphological classifier. It was shown that the SOMs created were effective as an unsupervised machine learning technique to classify galaxies based solely on their SED. Morphological predictions for a number of galaxies were shown to be in agreement with classifications obtained from new observations in NED.

  17. From Self-Organized to Extended Criticality

    PubMed Central

    Lovecchio, Elisa; Allegrini, Paolo; Geneston, Elvis; West, Bruce J.; Grigolini, Paolo

    2012-01-01

    We address the issue of criticality that is attracting the attention of an increasing number of neurophysiologists. Our main purpose is to establish the specific nature of some dynamical processes that although physically different, are usually termed as “critical,” and we focus on those characterized by the cooperative interaction of many units. We notice that the term “criticality” has been adopted to denote both noise-induced phase transitions and Self-Organized Criticality (SOC) with no clear connection with the traditional phase transitions, namely the transformation of a thermodynamic system from one state of matter to another. We notice the recent attractive proposal of extended criticality advocated by Bailly and Longo, which is realized through a wide set of critical points rather than emerging as a singularity from a unique value of the control parameter. We study a set of cooperatively firing neurons and we show that for an extended set of interaction couplings the system exhibits a form of temporal complexity similar to that emerging at criticality from ordinary phase transitions. This extended criticality regime is characterized by three main properties: (i) In the ideal limiting case of infinitely large time period, temporal complexity corresponds to Mittag-Leffler complexity; (ii) For large values of the interaction coupling the periodic nature of the process becomes predominant while maintaining to some extent, in the intermediate time asymptotic region, the signature of complexity; (iii) Focusing our attention on firing neuron avalanches, we find two of the popular SOC properties, namely the power indexes 2 and 1.5 respectively for time length and for the intensity of the avalanches. We derive the main conclusion that SOC emerges from extended criticality, thereby explaining the experimental observation of Plenz and Beggs: avalanches occur in time with surprisingly regularity, in apparent conflict with the temporal complexity of physical

  18. Self-organized stationary states of tokamaks

    NASA Astrophysics Data System (ADS)

    Jardin, Stephen

    2015-11-01

    We report here on a nonlinear mechanism that forms and maintains a self-organized stationary (sawtooth free) state in tokamaks. This process was discovered by way of extensive long-time simulations using the M3D-C1 3D extended MHD code in which new physics diagnostics have been added. It is well known that most high-performance modes of tokamak operation undergo ``sawtooth'' cycles, in which the peaking of the toroidal current density triggers a periodic core instability which redistributes the current density. However, certain modes of operation are known, such as the ``hybrid'' mode in DIII-D, ASDEX-U, JT-60U and JET, and the long-lived modes in NSTX and MAST, which do not experience this cycle of instability. Empirically, it is observed that these modes maintain a non-axisymmetric equilibrium which somehow limits the peaking of the toroidal current density. The physical mechanism responsible for this has not previously been understood, but is often referred to as ``flux-pumping,'' in which poloidal flux is redistributed in order to maintain q0 >1. In this talk, we show that in long-time simulations of inductively driven plasmas, a steady-state magnetic equilibrium may be obtained in which the condition q0 >1 is maintained by a dynamo driven by a stationary marginal core interchange mode. This interchange mode, unstable because of the pressure gradient in the ultra-low shear region in the center region, causes a (1,1) perturbation in both the electrostatic potential and the magnetic field, which nonlinearly cause a (0,0) component in the loop voltage that acts to sustain the configuration. This hybrid mode may be a preferred mode of operation for ITER. We present parameter scans that indicate when this sawtooth-free operation can be expected.

  19. The concept of self-organizing systems. Why bother?

    NASA Astrophysics Data System (ADS)

    Elverfeldt, Kirsten v.; Embleton-Hamann, Christine; Slaymaker, Olav

    2016-04-01

    Complexity theory and the concept of self-organizing systems provide a rather challenging conceptual framework for explaining earth systems change. Self-organization - understood as the aggregate processes internal to an environmental system that lead to a distinctive spatial or temporal organization - reduces the possibility of implicating a specific process as being causal, and it poses some restrictions on the idea that external drivers cause a system to change. The concept of self-organizing systems suggests that many phenomena result from an orchestration of different mechanisms, so that no causal role can be assigned to an individual factor or process. The idea that system change can be due to system-internal processes of self-organization thus proves a huge challenge to earth system research, especially in the context of global environmental change. In order to understand the concept's implications for the Earth Sciences, we need to know the characteristics of self-organizing systems and how to discern self-organizing systems. Within the talk, we aim firstly at characterizing self-organizing systems, and secondly at highlighting the advantages and difficulties of the concept within earth system sciences. The presentation concludes that: - The concept of self-organizing systems proves especially fruitful for small-scale earth surface systems. Beach cusps and patterned ground are only two of several other prime examples of self-organizing earth surface systems. They display characteristics of self-organization like (i) system-wide order from local interactions, (ii) symmetry breaking, (iii) distributed control, (iv) robustness and resilience, (v) nonlinearity and feedbacks, (vi) organizational closure, (vii) adaptation, and (viii) variation and selection. - It is comparatively easy to discern self-organization in small-scale systems, but to adapt the concept to larger scale systems relevant to global environmental change research is more difficult: Self-organizing

  20. Thought analysis on self-organization theories of MHD plasma

    NASA Astrophysics Data System (ADS)

    Kondoh, Yoshiomi; Sato, Tetsuya

    1992-08-01

    A thought analysis on the self-organization theories of dissipative MHD plasmas is presented to lead to three groups of theories that lead to the same relaxed state of del x B = lambda(B), in order to find an essential physical picture embedded in the self-organization phenomena due to nonlinear and dissipative processes. The self-organized relaxed state due to the dissipation by the Ohm loss is shown to be formulated generally as the state such that yields the minimum dissipation rate of global auto- and/or cross-correlations between two quantities in j, B, and A for their own instantaneous values of the global correlations.

  1. Self-organization: Two's company, three's a crowd

    NASA Astrophysics Data System (ADS)

    Khan, Shahid M.; Molloy, Justin E.

    2015-10-01

    Real-time tracking of self-propelled biomolecules provides insight into the physical rules governing self-organization in complex living systems -- including evidence to suggest that their alignment requires multiple simultaneous interactions.

  2. Research-study of a self-organizing computer

    NASA Technical Reports Server (NTRS)

    Schaffner, M. R.

    1974-01-01

    It is shown that a self organizing system has two main components: an organizable physical part, and a programing part. This report presents the organizable part in the form of a programable hardware and its programing language.

  3. Self-organization in magnetic flux ropes

    NASA Astrophysics Data System (ADS)

    Lukin, Vyacheslav S.

    2014-06-01

    This cross-disciplinary special issue on 'Self-organization in magnetic flux ropes' follows in the footsteps of another collection of manuscripts dedicated to the subject of magnetic flux ropes, a volume on 'Physics of magnetic flux ropes' published in the American Geophysical Union's Geophysical Monograph Series in 1990 [1]. Twenty-four years later, this special issue, composed of invited original contributions highlighting ongoing research on the physics of magnetic flux ropes in astrophysical, space and laboratory plasmas, can be considered an update on our state of understanding of this fundamental constituent of any magnetized plasma. Furthermore, by inviting contributions from research groups focused on the study of the origins and properties of magnetic flux ropes in a variety of different environments, we have attempted to underline both the diversity of and the commonalities among magnetic flux ropes throughout the solar system and, indeed, the universe. So, what is a magnetic flux rope? The answer will undoubtedly depend on whom you ask. A flux rope can be as narrow as a few Larmor radii and as wide as the Sun (see, e.g., the contributions by Heli Hietala et al and by Angelous Vourlidas). As described below by Ward Manchester IV et al , they can stretch from the Sun to the Earth in the form of interplanetary coronal mass ejections. Or, as in the Swarthmore Spheromak Experiment described by David Schaffner et al , they can fit into a meter-long laboratory device tended by college students. They can be helical and line-tied (see, e.g., Walter Gekelman et al or J Sears et al ), or toroidal and periodic (see, e.g., John O'Bryan et al or Philippa Browning et al ). They can form in the low plasma beta environment of the solar corona (Tibor Török et al ), the order unity beta plasmas of the solar wind (Stefan Eriksson et al ) and the plasma pressure dominated stellar convection zones (Nicholas Nelson and Mark Miesch). In this special issue, Setthivoine You

  4. Self-organization is a dynamic and lineage-intrinsic property of mammary epithelial cells

    PubMed Central

    Chanson, Lea; Brownfield, Douglas; Garbe, James C.; Kuhn, Irene; Stampfer, Martha R.; Bissell, Mina J.; LaBarge, Mark A.

    2011-01-01

    Loss of organization is a principle feature of cancers; therefore it is important to understand how normal adult multilineage tissues, such as bilayered secretory epithelia, establish and maintain their architectures. The self-organization process that drives heterogeneous mixtures of cells to form organized tissues is well studied in embryology and with mammalian cell lines that were abnormal or engineered. Here we used a micropatterning approach that confined cells to a cylindrical geometry combined with an algorithm to quantify changes of cellular distribution over time to measure the ability of different cell types to self-organize relative to each other. Using normal human mammary epithelial cells enriched into pools of the two principal lineages, luminal and myoepithelial cells, we demonstrated that bilayered organization in mammary epithelium was driven mainly by lineage-specific differential E-cadherin expression, but that P-cadherin contributed specifically to organization of the myoepithelial layer. Disruption of the actomyosin network or of adherens junction proteins resulted in either prevention of bilayer formation or loss of preformed bilayers, consistent with continual sampling of the local microenvironment by cadherins. Together these data show that self-organization is an innate and reversible property of communities of normal adult human mammary epithelial cells. PMID:21300877

  5. Self-organization is a dynamic and lineage-intrinsic property of mammary epithelial cells

    SciTech Connect

    Chanson, L.; Brownfield, D.; Garbe, J. C.; Kuhn, I.; Stampfer, M. R.; Bissell, M. J.; LaBarge, M. A.

    2011-02-07

    Loss of organization is a principle feature of cancers; therefore it is important to understand how normal adult multilineage tissues, such as bilayered secretory epithelia, establish and maintain their architectures. The self-organization process that drives heterogeneous mixtures of cells to form organized tissues is well studied in embryology and with mammalian cell lines that were abnormal or engineered. Here we used a micropatterning approach that confined cells to a cylindrical geometry combined with an algorithm to quantify changes of cellular distribution over time to measure the ability of different cell types to self-organize relative to each other. Using normal human mammary epithelial cells enriched into pools of the two principal lineages, luminal and myoepithelial cells, we demonstrated that bilayered organization in mammary epithelium was driven mainly by lineage-specific differential E-cadherin expression, but that P-cadherin contributed specifically to organization of the myoepithelial layer. Disruption of the actomyosin network or of adherens junction proteins resulted in either prevention of bilayer formation or loss of preformed bilayers, consistent with continual sampling of the local microenvironment by cadherins. Together these data show that self-organization is an innate and reversible property of communities of normal adult human mammary epithelial cells.

  6. Evidence for Self-organized Criticality in Tokamak Plasma Transport

    NASA Astrophysics Data System (ADS)

    Moyer, R. A.; Lehmer, R.; Rhodes, T. H.; Doyle, E. J.; Peebles, W. A.; Rettig, C. L.; Groebner, R. J.

    1998-11-01

    Measurements of turbulence spectra and particle flux probability distributions from the DIII-D tokamak exhibit significant agreement with predictions of self organized criticality (SOC) theories. Power spectra of density tilde n, floating potential, and particle flux Γ have three regions of frequency dependence: low frequency f^0, intermediate frequency f-1, and high frequency f-4, consistent with power spectra observed in SOC modeling of various systems. The particle flux probability distribution function P(Γ) for radially outgoing flux shows a Γ-1 dependent region extending over two decades of Γ, a clear indication of self organized behavior. Radially inward flux, representing toppling events up the density gradient (which are outside the scope of the models), also displays a Γ-1 dependent region. These measurements indicate that the plasma is in a state consistent with self organized criticality, and place a significant constraint on plasma transport models.

  7. Self-organization of atoms coupled to a chiral reservoir

    NASA Astrophysics Data System (ADS)

    Eldredge, Zachary; Jarzynski, Christopher; Chang, Darrick; Gorshkov, Alexey

    2016-05-01

    Tightly confined modes of light, as in optical nanofibers or photonics crystal waveguides, can lead to large optical coupling in atomic systems, which mediates long-range interactions between atoms. These one-dimensional systems can naturally possess couplings which are asymmetric between modes in different directions. In this poster, we examine the self-organizing behavior of atoms in one dimension coupled to a chiral reservoir. We determine the behavior of the self-organized solution to the equations of motion in different parameter regimes, relative to both the detuning of the pump laser and the degree of reservoir chirality. In addition to the spatial configuration of self-organized atoms, we calculate possible experimental signatures.

  8. Emergence of cooperation with self-organized criticality

    NASA Astrophysics Data System (ADS)

    Park, Sangmin; Jeong, Hyeong-Chai

    2012-02-01

    Cooperation and self-organized criticality are two main keywords in current studies of evolution. We propose a generalized Bak-Sneppen model and provide a natural mechanism which accounts for both phenomena simultaneously. We use the prisoner's dilemma games to mimic the interactions among the members in the population. Each member is identified by its cooperation probability, and its fitness is given by the payoffs from neighbors. The least fit member with the minimum payoff is replaced by a new member with a random cooperation probability. When the neighbors of the least fit one are also replaced with a non-zero probability, a strong cooperation emerges. The Bak-Sneppen process builds a self-organized structure so that the cooperation can emerge even in the parameter region where a uniform or random population decreases the number of cooperators. The emergence of cooperation is due to the same dynamical correlation that leads to self-organized criticality in replacement activities.

  9. Measuring the Complexity of Self-Organizing Traffic Lights

    NASA Astrophysics Data System (ADS)

    Zubillaga, Darío; Cruz, Geovany; Aguilar, Luis; Zapotécatl, Jorge; Fernández, Nelson; Aguilar, José; Rosenblueth, David; Gershenson, Carlos

    2014-04-01

    We apply measures of complexity, emergence and self-organization to an abstract city traffic model for comparing a traditional traffic coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only traffic is a non-stationary problem, which requires controllers to adapt constantly. Controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures, we can say that the self-organizing method achieves an adaptability level comparable to a living system.

  10. Ageing dynamics of ion bombardment induced self-organization processes

    PubMed Central

    Bikondoa, Oier; Carbone, Dina; Chamard, Virginie; Metzger, Till Hartmut

    2013-01-01

    Instabilities caused during the erosion of a surface by an ion beam can lead to the formation of self-organized patterns of nanostructures. Understanding the self-organization process requires not only the in-situ characterization of ensemble averaged properties but also probing the dynamics. This can be done with the use of coherent X-rays and analyzing the temporal correlations of the scattered intensity. Here, we show that the dynamics of a semiconductor surface nanopatterned by normal incidence ion beam sputtering are age-dependent and slow down with sputtering time. This work provides a novel insight into the erosion dynamics and opens new perspectives for the understanding of self-organization mechanisms. PMID:23685386

  11. Atmospheric Convective Organization: Self-Organized Criticality or Homeostasis?

    NASA Astrophysics Data System (ADS)

    Yano, Jun-Ichi

    2015-04-01

    Atmospheric convection has a tendency organized on a hierarchy of scales ranging from the mesoscale to the planetary scales, with the latter especially manifested by the Madden-Julian oscillation. The present talk examines two major possible mechanisms of self-organization identified in wider literature from a phenomenological thermodynamic point of view by analysing a planetary-scale cloud-resolving model simulation. The first mechanism is self-organized criticality. A saturation tendency of precipitation rate with the increasing column-integrated water, reminiscence of critical phenomena, indicates self-organized criticality. The second is a self-regulation mechanism that is known as homeostasis in biology. A thermodynamic argument suggests that such self-regulation maintains the column-integrated water below a threshold by increasing the precipitation rate. Previous analyses of both observational data as well as cloud-resolving model (CRM) experiments give mixed results. A satellite data analysis suggests self-organized criticality. Some observational data as well as CRM experiments support homeostasis. Other analyses point to a combination of these two interpretations. In this study, a CRM experiment over a planetary-scale domain with a constant sea-surface temperature is analyzed. This analysis shows that the relation between the column-integrated total water and precipitation suggests self-organized criticality, whereas the one between the column-integrated water vapor and precipitation suggests homeostasis. The concurrent presence of these two mechanisms are further elaborated by detailed statistical and budget analyses. These statistics are scale invariant, reflecting a spatial scaling of precipitation processes. These self-organization mechanisms are most likely be best theoretically understood by the energy cycle of the convective systems consisting of the kinetic energy and the cloud-work function. The author has already investigated the behavior of this

  12. Biomimetic sensory abstraction using hierarchical quilted self-organizing maps

    NASA Astrophysics Data System (ADS)

    Miller, Jeffrey W.; Lommel, Peter H.

    2006-10-01

    We present an approach for abstracting invariant classifications of spatiotemporal patterns presented in a high-dimensionality input stream, and apply an early proof-of-concept to shift and scale invariant shape recognition. A model called Hierarchical Quilted Self-Organizing Map (HQSOM) is developed, using recurrent self-organizing maps (RSOM) arranged in a pyramidal hierarchy, attempting to mimic the parallel/hierarchical pattern of isocortical processing in the brain. The results of experiments are presented in which the algorithm learns to classify multiple shapes, invariant to shift and scale transformations, in a very small (7×7 pixel) field of view.

  13. Variants of guided self-organization for robot control.

    PubMed

    Martius, Georg; Herrmann, J Michael

    2012-09-01

    Autonomous robots can generate exploratory behavior by self-organization of the sensorimotor loop. We show that the behavioral manifold that is covered in this way can be modified in a goal-dependent way without reducing the self-induced activity of the robot. We present three strategies for guided self-organization, namely by using external rewards, a problem-specific error function, or assumptions about the symmetries of the desired behavior. The strategies are analyzed for two different robots in a physically realistic simulation. PMID:22116785

  14. Magnetospheric vortex formation: self-organized confinement of charged particles.

    PubMed

    Yoshida, Z; Saitoh, H; Morikawa, J; Yano, Y; Watanabe, S; Ogawa, Y

    2010-06-11

    A magnetospheric configuration gives rise to various peculiar plasma phenomena that pose conundrums to astrophysical studies; at the same time, innovative technologies may draw on the rich physics of magnetospheric plasmas. We have created a "laboratory magnetosphere" with a levitating superconducting ring magnet. Here we show that charged particles (electrons) self-organize a stable vortex, in which particles diffuse inward to steepen the density gradient. The rotating electron cloud is sustained for more than 300 s. Because of its simple geometry and self-organization, this system will have wide applications in confining single- and multispecies charged particles. PMID:20867249

  15. Perspectives of experimental and theoretical studies of self-organized dust structures in complex plasmas under microgravity conditions

    NASA Astrophysics Data System (ADS)

    Tsytovich, V. N.

    2015-02-01

    We review research aimed at understanding the phenomena occurring in a complex plasma under microgravity conditions. Some aspects of the work already performed are considered that have not previously been given sufficient attention but which are potentially crucial for future work. These aspects, in particular, include the observation of compact dust structures that are estimated to be capable of confining all components of a dust plasma in a bounded spatial volume; experimental evidence of the nonlinear screening of dust particles; and experimental evidence of the excitation of collective electric fields. In theoretical terms, novel collective attraction processes between likely charged dust particles are discussed and all schemes of the shadowy attraction between dust particles used earlier, including in attempts to interpret observations, are reviewed and evaluated. Dust structures are considered from the standpoint of the current self-organization theory. It is emphasized that phase transitions between states of self-organized systems differ significantly from those in homogeneous states and that the phase diagrams should be constructed in terms of the parameters of a self-organized structure and cannot be constructed in terms of the temperature and density or similar parameters of homogeneous structures. Using the existing theoretical approaches to modeling self-organized structures in dust plasmas, the parameter distribution of a structure is recalculated for a simpler model that includes the quasineutrality condition and neglects diffusion. These calculations indicate that under microgravity conditions, any self-organized structure can contain a limited number of dust particles and is finite in size. The maximum possible number of particles in a structure determines the characteristic inter-grain distance in dust crystals that can be created under microgravity conditions. Crystallization criteria for the structures are examined and the quasispherical

  16. Parallelization of analyses using self-organizing maps with PVM

    NASA Astrophysics Data System (ADS)

    Lange, J. S.; Schönmeier, P.; Freiesleben, H.

    1997-02-01

    An analysis task applying self-organizing maps of the Kohonen type was parallelized using (a) ksh shell scripts and (b) the message parsing system PVM 3.1. The parallelization was performed on an IBM RS/6000 workstation cluster using ethernet as well as FDDi network adapters.

  17. Self-organization of intense light within erosive gas discharges

    NASA Astrophysics Data System (ADS)

    Torchigin, V. P.; Torchigin, A. V.

    2007-01-01

    Process of appearance of fire balls at gas discharges is considered. It is shown that the intense white light radiated by atoms excited at gas discharge is subject to self-organization in such a way that miniature ball lightnings appear.

  18. Infant Externalizing Behavior as a Self-Organizing Construct

    ERIC Educational Resources Information Center

    Lorber, Michael F.; Del Vecchio, Tamara; Slep, Amy M. Smith

    2014-01-01

    We evaluated the extent to which the externalizing behavior construct is self-organizing in the first 2 years of life. Based on dynamic systems theory, we hypothesized that changes in physical aggression, defiance, activity level, and distress to limitations would each be predicted by earlier manifestations of one another. These hypotheses were…

  19. Simple model of self-organized biological evolution

    SciTech Connect

    de Boer, J.; Derrida, B.; Flyvbjerg, H.; Jackson, A.D.; Wettig, T. The Isaac Newton Institute for Mathematical Sciences, 20 Clarkson Road, Cambridge, CB4 0EH Laboratoire de Physique Statistique, Ecole Normale Superieure, 24 rue Lhomond, F-75005 Paris Service de Physique Theorique, Centre de Etudes Nucleaires de Saclay, F-91191, Gif-Sur-Yvette CONNECT, The Niels Bohr Institute, Blegdamsvej 17, DK-2100 Copenhagen )

    1994-08-08

    We give an exact solution of a recently proposed self-organized critical model of biological evolution. We show that the model has a power law distribution of durations of coevolutionary avalanches'' with a mean field exponent 3/2. We also calculate analytically the finite size effects which cut off this power law at times of the order of the system size.

  20. String tightening as a self-organizing phenomenon.

    PubMed

    Banerjee, Bonny

    2007-09-01

    The phenomenon of self-organization has been of special interest to the neural network community throughout the last couple of decades. In this paper, we study a variant of the self-organizing map (SOM) that models the phenomenon of self-organization of the particles forming a string when the string is tightened from one or both of its ends. The proposed variant, called the string tightening self-organizing neural network (STON), can be used to solve certain practical problems, such as computation of shortest homotopic paths, smoothing paths to avoid sharp turns, computation of convex hull, etc. These problems are of considerable interest in computational geometry, robotics path-planning, artificial intelligence (AI) (diagrammatic reasoning), very large scale integration (VLSI) routing, and geographical information systems. Given a set of obstacles and a string with two fixed terminal points in a 2-D space, the STON model continuously tightens the given string until the unique shortest configuration in terms of the Euclidean metric is reached. The STON minimizes the total length of a string on convergence by dynamically creating and selecting feature vectors in a competitive manner. Proof of correctness of this anytime algorithm and experimental results obtained by its deployment have been presented in the paper. PMID:18220194

  1. Self-organizing neural network as a fuzzy classifier

    SciTech Connect

    Mitra, S.; Pal, S.K.

    1994-03-01

    This paper describes a self-organizing artificial neural network, based on Kohonen`s model of self-organization, which is capable of handling fuzzy input and of providing fuzzy classification. Unlike conventional neural net models, this algorithm incorporates fuzzy set-theoretic concepts at various stages. The input vector consists of membership values for linguistic properties along with some contextual class membership information which is used during self-organization to permit efficient modeling of fuzzy (ambiguous) patterns. A new definition of gain factor for weight updating is proposed. An index of disorder involving mean square distance between the input and weight vectors is used to determine a measure of the ordering of the output space. This controls the number of sweeps required in the process. Incorporation of the concept of fuzzy partitioning allows natural self-organization of the input data, especially when they have ill-defined boundaries. The output of unknown test patterns is generated in terms of class membership values. Incorporation of fuzziness in input and output is seen to provide better performance as compared to the original Kohonen model and the hard version. The effectiveness of this algorithm is demonstrated on the speech recognition problem for various network array sizes, training sets and gain factors. 24 refs.

  2. Parameters of self-organization in Hydra aggregates

    PubMed Central

    Technau, Ulrich; Cramer von Laue, Christoph; Rentzsch, Fabian; Luft, Susanne; Hobmayer, Bert; Bode, Hans R.; Holstein, Thomas W.

    2000-01-01

    Self-organization has been demonstrated in a variety of systems ranging from chemical-molecular to ecosystem levels, and evidence is accumulating that it is also fundamental for animal development. Yet, self-organization can be approached experimentally in only a few animal systems. Cells isolated from the simple metazoan Hydra can aggregate and form a complete animal by self-organization. By using this experimental system, we found that clusters of 5–15 epithelial cells are necessary and sufficient to form de novo head-organizing centers in an aggregate. Such organizers presumably arise by a community effect from a small number of cells that express the conserved HyBra1 and HyWnt genes. These local sources then act to pattern and instruct the surrounding cells as well as generate a field of lateral inhibition that ranges up to 1,000 μm. We propose that conserved patterning systems in higher animals originate from extremely robust and flexible molecular self-organizing systems that were selected for during early metazoan evolution. PMID:11050241

  3. Self-organized topology of recurrence-based complex networks

    SciTech Connect

    Yang, Hui Liu, Gang

    2013-12-15

    With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

  4. Self-organized topology of recurrence-based complex networks

    NASA Astrophysics Data System (ADS)

    Yang, Hui; Liu, Gang

    2013-12-01

    With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., "what is the self-organizing geometry of a recurrence network?" and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

  5. Self-Organization of Blood Pressure Regulation: Experimental Evidence

    PubMed Central

    Fortrat, Jacques-Olivier; Levrard, Thibaud; Courcinous, Sandrine; Victor, Jacques

    2016-01-01

    Blood pressure regulation is a prime example of homeostatic regulation. However, some characteristics of the cardiovascular system better match a non-linear self-organized system than a homeostatic one. To determine whether blood pressure regulation is self-organized, we repeated the seminal demonstration of self-organized control of movement, but applied it to the cardiovascular system. We looked for two distinctive features peculiar to self-organization: non-equilibrium phase transitions and hysteresis in their occurrence when the system is challenged. We challenged the cardiovascular system by means of slow, 20-min Tilt-Up and Tilt-Down tilt table tests in random order. We continuously determined the phase between oscillations at the breathing frequency of Total Peripheral Resistances and Heart Rate Variability by means of cross-spectral analysis. We looked for a significant phase drift during these procedures, which signed a non-equilibrium phase transition. We determined at which head-up tilt angle it occurred. We checked that this angle was significantly different between Tilt-Up and Tilt-Down to demonstrate hysteresis. We observed a significant non-equilibrium phase transition in nine healthy volunteers out of 11 with significant hysteresis (48.1 ± 7.5° and 21.8 ± 3.9° during Tilt-Up and Tilt-Down, respectively, p < 0.05). Our study shows experimental evidence of self-organized short-term blood pressure regulation. It provides new insights into blood pressure regulation and its related disorders. PMID:27065880

  6. Self-Organization of Embryonic Genetic Oscillators into Spatiotemporal Wave Patterns

    PubMed Central

    Tsiairis, Charisios D.; Aulehla, Alexander

    2016-01-01

    Summary In vertebrate embryos, somites, the precursor of vertebrae, form from the presomitic mesoderm (PSM), which is composed of cells displaying signaling oscillations. Cellular oscillatory activity leads to periodic wave patterns in the PSM. Here, we address the origin of such complex wave patterns. We employed an in vitro randomization and real-time imaging strategy to probe for the ability of cells to generate order from disorder. We found that, after randomization, PSM cells self-organized into several miniature emergent PSM structures (ePSM). Our results show an ordered macroscopic spatial arrangement of ePSM with evidence of an intrinsic length scale. Furthermore, cells actively synchronize oscillations in a Notch-signaling-dependent manner, re-establishing wave-like patterns of gene activity. We demonstrate that PSM cells self-organize by tuning oscillation dynamics in response to surrounding cells, leading to collective synchronization with an average frequency. These findings reveal emergent properties within an ensemble of coupled genetic oscillators. PMID:26871631

  7. Fluid flows created by swimming bacteria drive self-organization in confined suspensions

    NASA Astrophysics Data System (ADS)

    Lushi, Enkeleida; Wioland, Hugo; Goldstein, Raymond

    Concentrated suspensions of micro-swimmers can display intricate self-organized spatiotemporal patterns on scales larger than those of the individual motile units. The collective dynamics of swimming microorganisms exhibits a complex interplay with the surrounding fluid: the motile cells stir the fluid, which in turn can reorient and advect them. This feedback loop can result in long-range interactions between the cells. We present a computational model that takes into account these cell-fluid interactions and cell-cell forces and that predicts counterintuitive cellular order driven by long-range flows. The predictions are confirmed by new experiments with Bacillus Subtilis bacteria. Simulations and experiments show that if the micro-swimmers are confined inside thin cylindrical chambers the suspension self-organizes into a stable swirling vortex. If the micro-swimmers are confined in thin racetracks, a persistent unidirectional stream can emerge. Both these phenomena emerge as a result of the complex interplay between the swimmers, the specific confining boundaries and the fluid flow.

  8. Self-organization of neural patterns and structures in 3D culture of stem cells

    NASA Astrophysics Data System (ADS)

    Sasai, Yoshiki

    2013-05-01

    Over the last several years, much progress has been made for in vitro culture of mouse and human ES cells. Our laboratory focuses on the molecular and cellular mechanisms of neural differentiation from pluripotent cells. Pluripotent cells first become committed to the ectodermal fate and subsequently differentiate into uncommitted neuroectodermal cells. Both previous mammalian and amphibian studies on pluripotent cells have indicated that the neural fate is a sort of the basal direction of the differentiation of these cells while mesoendodermal differentiation requires extrinsic inductive signals. ES cells differentiate into neuroectodermal cells with a rostral-most character (telencephalon and hypothalamus) when they are cultured in the absence of strong patterning signals. In this talk, I first discuss this issue by referring to our recent data on the mechanism of spontaneous neural differentiation in serum-free culture of mouse ES cells. Then, I will talk about self-organization phenomena observed in 3D culture of ES cells, which lead to tissue-autonomous formation of regional structures such as layered cortical tissues. I also discuss our new attempt to monitor these in vitro morphogenetic processes by live imaging, in particular, self-organizing morphogenesis of the optic cup in three-dimensional cultures.

  9. Evolution as a Self-Organized Critical Phenomenon

    NASA Astrophysics Data System (ADS)

    Sneppen, Kim; Bak, Per; Flyvbjerg, Henrik; Jensen, Mogens H.

    1995-05-01

    We present a simple mathematical model of biological macroevolution. The model describes an ecology of adapting, interacting species. The environment of any given species is affected by other evolving species; hence, it is not constant in time. The ecology as a whole evolves to a "self-organized critical" state where periods of stasis alternate with avalanches of causally connected evolutionary changes. This characteristic behavior of natural history, known as "punctuated equilibrium," thus finds a theoretical explanation as a self-organized critical phenomenon. The evolutionary behavior of single species is intermittent. Also, large bursts of apparently simultaneous evolutionary activity require no external cause. Extinctions of all sizes, including mass extinctions, may be a simple consequence of ecosystem dynamics. Our results are compared with data from the fossil record

  10. Secure steganographic communication algorithm based on self-organizing patterns

    NASA Astrophysics Data System (ADS)

    Saunoriene, Loreta; Ragulskis, Minvydas

    2011-11-01

    A secure steganographic communication algorithm based on patterns evolving in a Beddington-de Angelis-type predator-prey model with self- and cross-diffusion is proposed in this paper. Small perturbations of initial states of the system around the state of equilibrium result in the evolution of self-organizing patterns. Small differences between initial perturbations result in slight differences also in the evolving patterns. It is shown that the generation of interpretable target patterns cannot be considered as a secure mean of communication because contours of the secret image can be retrieved from the cover image using statistical techniques if only it represents small perturbations of the initial states of the system. An alternative approach when the cover image represents the self-organizing pattern that has evolved from initial states perturbed using the dot-skeleton representation of the secret image can be considered as a safe visual communication technique protecting both the secret image and communicating parties.

  11. Self-organized service negotiation for collaborative decision making.

    PubMed

    Zhang, Bo; Huang, Zhenhua; Zheng, Ziming

    2014-01-01

    This paper proposes a self-organized service negotiation method for CDM in intelligent and automatic manners. It mainly includes three phases: semantic-based capacity evaluation for the CDM sponsor, trust computation of the CDM organization, and negotiation selection of the decision-making service provider (DMSP). In the first phase, the CDM sponsor produces the formal semantic description of the complex decision task for DMSP and computes the capacity evaluation values according to participator instructions from different DMSPs. In the second phase, a novel trust computation approach is presented to compute the subjective belief value, the objective reputation value, and the recommended trust value. And in the third phase, based on the capacity evaluation and trust computation, a negotiation mechanism is given to efficiently implement the service selection. The simulation experiment results show that our self-organized service negotiation method is feasible and effective for CDM. PMID:25243228

  12. Evolution as a self-organized critical phenomenon

    SciTech Connect

    Sneppen, K.; Bak, P. |; Flyvbjerg, H. |; Jensen, M.H.

    1995-05-23

    We present a simple mathematical model of biological macroevolution. The model describes an ecology of adapting, interacting species. The environment of any given species is affected by other evolving species; hence, it is not constant in time. The ecology as a whole evolves to a {open_quotes}self-organized critical{close_quotes} state where periods of stasis alternate with avalanches of casually connected evolutionary changes. This characteristic behavior of natural history, known as {open_quotes}punctuated equilibrium,{close_quotes} thus finds a theoretical explanation as a self-organized critical phenomenon. The evolutionary behavior of single species is intermittent. Also, large bursts of apparently simultaneous evolutionary activity require no external cause. Extinctions of all sizes, including mass extinctions, may be a simple consequence of ecosystem dynamics. Our results are compared with data from the fossil record. 35 refs., 7 figs.

  13. Developing neuronal networks: Self-organized criticality predicts the future

    NASA Astrophysics Data System (ADS)

    Pu, Jiangbo; Gong, Hui; Li, Xiangning; Luo, Qingming

    2013-01-01

    Self-organized criticality emerged in neural activity is one of the key concepts to describe the formation and the function of developing neuronal networks. The relationship between critical dynamics and neural development is both theoretically and experimentally appealing. However, whereas it is well-known that cortical networks exhibit a rich repertoire of activity patterns at different stages during in vitro maturation, dynamical activity patterns through the entire neural development still remains unclear. Here we show that a series of metastable network states emerged in the developing and ``aging'' process of hippocampal networks cultured from dissociated rat neurons. The unidirectional sequence of state transitions could be only observed in networks showing power-law scaling of distributed neuronal avalanches. Our data suggest that self-organized criticality may guide spontaneous activity into a sequential succession of homeostatically-regulated transient patterns during development, which may help to predict the tendency of neural development at early ages in the future.

  14. Self-Organizing OFDMA System for Broadband Communication

    NASA Technical Reports Server (NTRS)

    Roy, Aloke (Inventor); Anandappan, Thanga (Inventor); Malve, Sharath Babu (Inventor)

    2016-01-01

    Systems and methods for a self-organizing OFDMA system for broadband communication are provided. In certain embodiments a communication node for a self organizing network comprises a communication interface configured to transmit data to and receive data from a plurality of nodes; and a processing unit configured to execute computer readable instructions. Further, computer readable instructions direct the processing unit to identify a sub-region within a cell, wherein the communication node is located in the sub-region; and transmit at least one data frame, wherein the data from the communication node is transmitted at a particular time and frequency as defined within the at least one data frame, where the time and frequency are associated with the sub-region.

  15. Topics in the mechanics of self-organizing systems

    NASA Astrophysics Data System (ADS)

    Tambe, Dhananjay

    Self-organization, in one of its accepted definitions, is the appearance of non-random structures in a system without explicit constraints from forces outside the system. In this thesis two self-organizing systems are studied from the viewpoint of mechanics. In the first system---semiconductor crystal surfaces---the internal constraints that lead to self-assembly of nanoscale structures on silicon-germanium (SiGe) films are studied. In the second system---actin cytoskeleton---a consequence of dynamic self-organization of actin filaments in the form of motion of micron-sized beads through a cytoplasmic medium is studied. When Ge film is deposited on Si(001) substrate, nanoscale features form on the surface and self-organize by minimizing energy contributions from the surface and the strain resulting from difference in lattice constants of the film and the substrate. Clean Si(001) and Ge(001) surfaces are very similar, but experiments to date have shown that atomic scale defects such as dimer-vacancies self-organize into vacancy lines only on Si(001). Through atomic simulations, we show that the observed difference originate from the magnitude of compressive surface strain which reduces formation energy of the dimer-vacancies. During initial stages of the film deposition, the surface is composed of steps and vacancy lines organized in periodic patterns. Using theory of elasticity and atomic simulations we show that these line defects self-organize due to monopolar nature of steps and dipolar nature of the vacancy lines. This self-organized pattern further develops to form pyramidal islands bounded with (105) facets and high Ge content. Mismatch strain of the island is then reduced by incorporation of Si from the substrate surrounding the island leaving behind trenches whose depth is proportional to the basewidth of the island. Using finite element simulations we show that such a relationship is an outcome of competition between elastic energy and surface energy. Some

  16. Self-Organized Service Negotiation for Collaborative Decision Making

    PubMed Central

    Zhang, Bo; Zheng, Ziming

    2014-01-01

    This paper proposes a self-organized service negotiation method for CDM in intelligent and automatic manners. It mainly includes three phases: semantic-based capacity evaluation for the CDM sponsor, trust computation of the CDM organization, and negotiation selection of the decision-making service provider (DMSP). In the first phase, the CDM sponsor produces the formal semantic description of the complex decision task for DMSP and computes the capacity evaluation values according to participator instructions from different DMSPs. In the second phase, a novel trust computation approach is presented to compute the subjective belief value, the objective reputation value, and the recommended trust value. And in the third phase, based on the capacity evaluation and trust computation, a negotiation mechanism is given to efficiently implement the service selection. The simulation experiment results show that our self-organized service negotiation method is feasible and effective for CDM. PMID:25243228

  17. Analytical investigation of self-organized criticality in neural networks

    PubMed Central

    Droste, Felix; Do, Anne-Ly; Gross, Thilo

    2013-01-01

    Dynamical criticality has been shown to enhance information processing in dynamical systems, and there is evidence for self-organized criticality in neural networks. A plausible mechanism for such self-organization is activity-dependent synaptic plasticity. Here, we model neurons as discrete-state nodes on an adaptive network following stochastic dynamics. At a threshold connectivity, this system undergoes a dynamical phase transition at which persistent activity sets in. In a low-dimensional representation of the macroscopic dynamics, this corresponds to a transcritical bifurcation. We show analytically that adding activity-dependent rewiring rules, inspired by homeostatic plasticity, leads to the emergence of an attractive steady state at criticality and present numerical evidence for the system's evolution to such a state. PMID:22977096

  18. Self-organized lattice of ordered quantum dot molecules

    SciTech Connect

    Lippen, T. von; Noetzel, R.; Hamhuis, G.J.; Wolter, J.H.

    2004-07-05

    Ordered groups of InAs quantum dots (QDs), lateral QD molecules, are created by self-organized anisotropic strain engineering of a (In,Ga)As/GaAs superlattice (SL) template on GaAs (311)B in molecular-beam epitaxy. During stacking, the SL template self-organizes into a two-dimensionally ordered strain modulated network on a mesoscopic length scale. InAs QDs preferentially grow on top of the nodes of the network due to local strain recognition. The QDs form a lattice of separated groups of closely spaced ordered QDs whose number can be controlled by the GaAs separation layer thickness on top of the SL template. The QD groups exhibit excellent optical properties up to room temperature.

  19. Self-organization of gold nanoparticles on silanated surfaces

    PubMed Central

    Kyaw, Htet H; Sellai, Azzouz; Dutta, Joydeep

    2015-01-01

    Summary The self-organization of monolayer gold nanoparticles (AuNPs) on 3-aminopropyltriethoxysilane (APTES)-functionalized glass substrate is reported. The orientation of APTES molecules on glass substrates plays an important role in the interaction between AuNPs and APTES molecules on the glass substrates. Different orientations of APTES affect the self-organization of AuNps on APTES-functionalized glass substrates. The as grown monolayers and films annealed in ultrahigh vacuum and air (600 °C) were studied by water contact angle measurements, atomic force microscopy, X-ray photoelectron spectroscopy, UV–visible spectroscopy and ultraviolet photoelectron spectroscopy. Results of this study are fundamentally important and also can be applied for designing and modelling of surface plasmon resonance based sensor applications. PMID:26734526

  20. Self-organizing hierarchies in sensor and communication networks.

    PubMed

    Prokopenko, Mikhail; Wang, Peter; Valencia, Philip; Price, Don; Foreman, Mark; Farmer, Anthony

    2005-01-01

    We consider a hierarchical multicellular sensing and communication network, embedded in an ageless aerospace vehicle that is expected to detect and react to multiple impacts and damage over a wide range of impact energies. In particular, we investigate self-organization of impact boundaries enclosing critically damaged areas, and impact networks connecting remote cells that have detected noncritical impacts. Each level of the hierarchy is shown to have distinct higher-order emergent properties, desirable in self-monitoring and self-repairing vehicles. In addition, cells and communication messages are shown to need memory (hysteresis) in order to retain desirable emergent behavior within and between various hierarchical levels. Spatiotemporal robustness of self-organizing hierarchies is quantitatively measured with graph-theoretic and information-theoretic techniques, such as the Shannon entropy. This allows us to clearly identify phase transitions separating chaotic dynamics from ordered and robust patterns. PMID:16197671

  1. Self-Organization and Forces in the Mitotic Spindle.

    PubMed

    Pavin, Nenad; Tolić, Iva M

    2016-07-01

    At the onset of division, the cell forms a spindle, a precise self-constructed micromachine composed of microtubules and the associated proteins, which divides the chromosomes between the two nascent daughter cells. The spindle arises from self-organization of microtubules and chromosomes, whose different types of motion help them explore the space and eventually approach and interact with each other. Once the interactions between the chromosomes and the microtubules have been established, the chromosomes are moved to the equatorial plane of the spindle and ultimately toward the opposite spindle poles. These transport processes rely on directed forces that are precisely regulated in space and time. In this review, we discuss how microtubule dynamics and their rotational movement drive spindle self-organization, as well as how the forces acting in the spindle are generated, balanced, and regulated. PMID:27145873

  2. Self-Organization in the Battle of the Sexes

    NASA Astrophysics Data System (ADS)

    Alonso-Sanz, Ramón

    This paper presents a spatial version of the iterated battle of the sexes game in which every one individual plays with his nearest partners and imitates the optimal strategy of his nearest mate neighbors. It is concluded that the spatial structure enables the emergence of clusters of coincident choices, leading to the mean payoff per encounter to values that are accessible only in the cooperative two-person game scenario, which constitutes a notable case of self-organization.

  3. Self-organization via active exploration in robotic applications

    NASA Technical Reports Server (NTRS)

    Ogmen, H.; Prakash, R. V.

    1992-01-01

    We describe a neural network based robotic system. Unlike traditional robotic systems, our approach focussed on non-stationary problems. We indicate that self-organization capability is necessary for any system to operate successfully in a non-stationary environment. We suggest that self-organization should be based on an active exploration process. We investigated neural architectures having novelty sensitivity, selective attention, reinforcement learning, habit formation, flexible criteria categorization properties and analyzed the resulting behavior (consisting of an intelligent initiation of exploration) by computer simulations. While various computer vision researchers acknowledged recently the importance of active processes (Swain and Stricker, 1991), the proposed approaches within the new framework still suffer from a lack of self-organization (Aloimonos and Bandyopadhyay, 1987; Bajcsy, 1988). A self-organizing, neural network based robot (MAVIN) has been recently proposed (Baloch and Waxman, 1991). This robot has the capability of position, size rotation invariant pattern categorization, recognition and pavlovian conditioning. Our robot does not have initially invariant processing properties. The reason for this is the emphasis we put on active exploration. We maintain the point of view that such invariant properties emerge from an internalization of exploratory sensory-motor activity. Rather than coding the equilibria of such mental capabilities, we are seeking to capture its dynamics to understand on the one hand how the emergence of such invariances is possible and on the other hand the dynamics that lead to these invariances. The second point is crucial for an adaptive robot to acquire new invariances in non-stationary environments, as demonstrated by the inverting glass experiments of Helmholtz. We will introduce Pavlovian conditioning circuits in our future work for the precise objective of achieving the generation, coordination, and internalization

  4. Self-Organized Transition to Coherent Activity in Disordered Media

    NASA Astrophysics Data System (ADS)

    Singh, Rajeev; Xu, Jinshan; Garnier, Nicolas G.; Pumir, Alain; Sinha, Sitabhra

    2012-02-01

    Synchronized oscillations are of critical functional importance in many biological systems. We show that such oscillations can arise without centralized coordination in a disordered system of electrically coupled excitable and passive cells. Increasing the coupling strength results in waves that lead to coherent periodic activity, exhibiting cluster, local and global synchronization under different conditions. Our results may explain the self-organized transition in a pregnant uterus from transient, localized activity initially to system-wide coherent excitations just before delivery.

  5. Self-Organizing Maps and Parton Distribution Functions

    SciTech Connect

    K. Holcomb, Simonetta Liuti, D. Z. Perry

    2011-05-01

    We present a new method to extract parton distribution functions from high energy experimental data based on a specific type of neural networks, the Self-Organizing Maps. We illustrate the features of our new procedure that are particularly useful for an anaysis directed at extracting generalized parton distributions from data. We show quantitative results of our initial analysis of the parton distribution functions from inclusive deep inelastic scattering.

  6. Subharmonic instability of a self-organized granular jet

    PubMed Central

    Kollmer, J. E.; Pöschel, T.

    2016-01-01

    Downhill flows of granular matter colliding in the lowest point of a valley, may induce a self-organized jet. By means of a quasi two-dimensional experiment where fine grained sand flows in a vertically sinusoidally agitated cylinder, we show that the emergent jet, that is, a sheet of ejecta, does not follow the frequency of agitation but reveals subharmonic response. The order of the subharmonics is a complex function of the parameters of driving. PMID:27001207

  7. Subharmonic instability of a self-organized granular jet

    NASA Astrophysics Data System (ADS)

    Kollmer, J. E.; Pöschel, T.

    2016-03-01

    Downhill flows of granular matter colliding in the lowest point of a valley, may induce a self-organized jet. By means of a quasi two-dimensional experiment where fine grained sand flows in a vertically sinusoidally agitated cylinder, we show that the emergent jet, that is, a sheet of ejecta, does not follow the frequency of agitation but reveals subharmonic response. The order of the subharmonics is a complex function of the parameters of driving.

  8. Mechanical models for the self-organization of tubular patterns

    PubMed Central

    2013-01-01

    Organogenesis, such as long tubule self-organization, requires long-range coordination of cell mechanics to arrange cell positions and to remodel the extracellular matrix. While the current mainstream in the field of tissue morphogenesis focuses primarily on genetics and chemical signaling, the influence of cell mechanics on the programming of patterning cues in tissue morphogenesis has not been adequately addressed. Here, we review experimental evidence and propose quantitative mechanical models by which cells can create tubular patterns. PMID:23719257

  9. Dynamic Self-Organization and Early Lexical Development in Children

    ERIC Educational Resources Information Center

    Li, Ping; Zhao, Xiaowei; Whinney, Brian Mac

    2007-01-01

    In this study we present a self-organizing connectionist model of early lexical development. We call this model DevLex-II, based on the earlier DevLex model. DevLex-II can simulate a variety of empirical patterns in children's acquisition of words. These include a clear vocabulary spurt, effects of word frequency and length on age of acquisition,…

  10. Self Organizing Maps for use in Deep Inelastic Scattering

    NASA Astrophysics Data System (ADS)

    Askanazi, Evan

    2015-04-01

    Self Organizing Maps are a type of artificial neural network that has been proven to be particularly useful in solving complex problems in neural biology, engineering, robotics and physics. We are attempting to use the Self Organizing Map to solve problems and probe phenomenological patterns in subatomic physics, specifically in Deep Inelastic Scattering (DIS). In DIS there is a cross section in electron hadron scattering that is dependent on the momentum fraction x of the partons in the hadron and the momentum transfer of the virtual photon exchanged. There is a soft cross part of this cross section that currently can only be found through experimentation; this soft part is comprised of Structure Functions which in turn are comprised of the Parton Distribution Functions (PDFs). We aim to use the Self Organizing Process, or SOP, to take theoretical models of these PDFs and fit it to the previous, known data. The SOP will also be used to probe the behavior of the PDFs in particular at large x values, in order to observe how they congregate. The ability of the SOPto take multidimensional data and convert it into two dimensional output is anticipated to be particularly useful in achieving this aim.

  11. On the self-organization of migrating individuals

    NASA Astrophysics Data System (ADS)

    Albano, E.

    A model which describes the self-organized cooperative displacement of self-driving and self-replicating individuals is proposed and studied. The spreading of small colonies in an otherwise empty landscape is investigated. If the available space for spreading is large enough, the colonies have a high average survivability (roughly 70%) while extinction, which takes place at early times, is mostly due to unfavorable initial conditions. In finite spaces, however, a stationary state is achieved such as the population self-organize to keep constant both, the local and the global density. The addition of an individual (i.e. a small perturbation) in the stationary state triggers avalanches of all sizes, i.e. the system lacks of any characteristic time- and size-scale. This behavior is the signature that the system self-organize in a critical state. So, the emergency of a very rich and complex critical behaviour at global scale, originated in simple local rules, is observed.

  12. Self-organization of functional materials in confinement.

    PubMed

    Gentili, Denis; Valle, Francesco; Albonetti, Cristiano; Liscio, Fabiola; Cavallini, Massimiliano

    2014-08-19

    This Account aims to describe our experience in the use of patterning techniques for addressing the self-organization processes of materials into spatially confined regions on technologically relevant surfaces. Functional properties of materials depend on their chemical structure, their assembly, and spatial distribution at the solid state; the combination of these factors determines their properties and their technological applications. In fact, by controlling the assembly processes and the spatial distribution of the resulting structures, functional materials can be guided to technological and specific applications. We considered the principal self-organizing processes, such as crystallization, dewetting and phase segregation. Usually, these phenomena produce defective molecular films, compromising their use in many technological applications. This issue can be overcome by using patterning techniques, which induce molecules to self-organize into well-defined patterned structures, by means of spatial confinement. In particular, we focus our attention on the confinement effect achieved by stamp-assisted deposition for controlling size, density, and positions of material assemblies, giving them new chemical/physical functionalities. We review the methods and principles of the stamp-assisted spatial confinement and we discuss how they can be advantageously exploited to control crystalline order/orientation, dewetting phenomena, and spontaneous phase segregation. Moreover, we highlight how physical/chemical properties of soluble functional materials can be driven in constructive ways, by integrating them into operating technological devices. PMID:25068634

  13. Natural selection and self-organization in complex adaptive systems.

    PubMed

    Di Bernardo, Mirko

    2010-01-01

    The central theme of this work is self-organization "interpreted" both from the point of view of theoretical biology, and from a philosophical point of view. By analysing, on the one hand, those which are now considered--not only in the field of physics--some of the most important discoveries, that is complex systems and deterministic chaos and, on the other hand, the new frontiers of systemic biology, this work highlights how large thermodynamic systems which are open can spontaneously stay in an orderly regime. Such systems can represent the natural source of the order required for a stable self-organization, for homoeostasis and for hereditary variations. The order, emerging in enormous randomly interconnected nets of binary variables, is almost certainly only the precursor of similar orders emerging in all the varieties of complex systems. Hence, this work, by finding new foundations for the order pervading the living world, advances the daring hypothesis according to which Darwinian natural selection is not the only source of order in the biosphere. Thus, the article, by examining the passage from Prigogine's dissipative structures theory to the contemporary theory of biological complexity, highlights the development of a coherent and continuous line of research which is set to individuate the general principles marking the profound reality of that mysterious self-organization characterizing the complexity of life. PMID:20882479

  14. Self-organizing team formation for target observation

    NASA Astrophysics Data System (ADS)

    Bowyer, Richard S.; Bogner, Robert E.

    2001-08-01

    Target observation is a problem where the application of multiple sensors can improve the probability of detection and observation of the target. Team formation is one method by which seemingly unsophisticated heterogeneous sensors may be organized to achieve a coordinated observation system. The sensors, which we shall refer to as agents, are situated in an area of interest with the goal of observing a moving target. We apply a team approach to this problem, which combines the strengths of individual agents into a cohesive entity - the team. In autonomous systems, the mechanisms that underlie the formation of a team are of interest. Teams may be formed by various mechanisms, which include an externally imposed grouping of agents, or an internally, self-organized (SO) grouping of agents. Internally motivated mechanisms are particularly challenging, but offer the benefit of being unsupervised, an important quality for groups of autonomous cooperating machines. This is the focus of our research. By studying natural systems such as colonies of ants, we obtain insight into these mechanisms of self organization. We propose that the team is an expression of a distributed agent-self, and that a particular realization of the agent-self exists, whilst the environmental conditions are conducive to that existence. We describe an algorithms for agent team formation that is inspired by the self-organizing behavior of ants, and describe simulation results for team formation amongst a lattice of networked sensors.

  15. Drift- or fluctuation-induced ordering and self-organization in driven many-particle systems

    NASA Astrophysics Data System (ADS)

    Helbing, D.; Platkowski, T.

    2002-10-01

    According to empirical observations, some pattern formation phenomena in driven many-particle systems are more pronounced in the presence of a certain noise level. We investigate this phenomenon of fluctuation-driven ordering with a cellular-automaton model of interactive motion in space and find an optimal noise strength, while order breaks down at high(er) fluctuation levels. Additionally, we discuss the phenomenon of noise- and drift-induced self-organization in systems that would show disorder in the absence of fluctuations. In the future, related studies may have applications to the control of many-particle systems such as the efficient separation of particles. The rather general formulation of our model in the spirit of game theory may allow to shed some light on several different kinds of noise-induced ordering phenomena observed in physical, chemical, biological, and socio-economic systems (e.g., attractive and repulsive agglomeration, or segregation).

  16. Self-organization of traffic jams in cities: Effects of stochastic dynamics and signal periods

    NASA Astrophysics Data System (ADS)

    Chowdhury, Debashish; Schadschneider, Andreas

    1999-02-01

    We propose a cellular automata model for vehicular traffic in cities by combining (and appropriately modifying) ideas borrowed from the Biham-Middleton-Levine (BML) model of city traffic and the Nagel-Schreckenberg (NS) model of highway traffic. We demonstrate a phase transition from the ``free-flowing'' dynamical phase to the completely ``jammed'' phase at a vehicle density which depends on the time periods of the synchronized signals and the separation between them. The intrinsic stochasticity of the dynamics, which triggers the onset of jamming, is similar to that in the NS model, while the phenomenon of complete jamming through self-organization as well as the final jammed configurations are similar to those in the BML model. Using our model, we have made an investigation of the time dependence of the average speeds of the cars in the ``free-flowing'' phase as well as the dependence of flux and jamming on the time period of the signals.

  17. Epithelial self-organization in fruit fly embryogenesis

    NASA Astrophysics Data System (ADS)

    Hutson, M. Shane

    2010-03-01

    During fruit fly embryogenesis, there are several morphogenetic events in which sheets of epithelial cells expand, contract and bend due to coordinated intra- and intercellular forces. This tissue-level reshaping is accompanied by changes in the shape and arrangement of individual cells -- changes that can be measured quantitatively and dynamically using modern live-cell imaging techniques. Such data sets represent rich targets for computational modeling of self-organization; however, reproducing the observed cell- and tissue-level reshaping is not enough. The inverse problem of using cell shape changes to determine cell-level forces is ill-posed -- yielding non-unique solutions that cannot discriminate between active changes in cell shape and passive deformation. These non-unique solutions can be tested experimentally using in vivo laser-microsurgery -- i.e., cutting a targeted region of an epithelium and carefully tracking the temporal and spatial dependence of the subsequent strain relaxation. This technique uses a variety of incisions (hole, line or closed curve) to probe different aspects of epithelial mechanics: the local mesoscopic strain; the distribution of intracellular forces; changes in the cell-level power-law rheology; and the question of active versus passive deformation. I will discuss my group's work using laser-microsurgery to investigate two morphogenetic events in fruit fly embryogenesis: germband retraction and dorsal closure. In both cases, we find a substantial active mechanical role for the amnioserosa -- an epithelium that undergoes apoptosis near the end of embryogenesis and makes no part of the fly larva -- in reshaping an adjacent epithelium that becomes the larval epidermis. In these examples, self-organization of the fly embryo relies not only on self-organization of individual tissues, but also on the mechanical interactions between tissues.

  18. Robust Electrografting on Self-Organized 3D Graphene Electrodes.

    PubMed

    Fortgang, Philippe; Tite, Teddy; Barnier, Vincent; Zehani, Nedjla; Maddi, Chiranjeevi; Lagarde, Florence; Loir, Anne-Sophie; Jaffrezic-Renault, Nicole; Donnet, Christophe; Garrelie, Florence; Chaix, Carole

    2016-01-20

    Improving graphene-based electrode fabrication processes and developing robust methods for its functionalization are two key research routes to develop new high-performance electrodes for electrochemical applications. Here, a self-organized three-dimensional (3D) graphene electrode processed by pulsed laser deposition with thermal annealing is reported. This substrate shows great performance in electron transfer kinetics regarding ferrocene redox probes in solution. A robust electrografting strategy for covalently attaching a redox probe onto these graphene electrodes is also reported. The modification protocol consists of a combination of diazonium salt electrografting and click chemistry. An alkyne-terminated phenyl ring is first electrografted onto the self-organized 3D graphene electrode by in situ electrochemical reduction of 4-ethynylphenyl diazonium. Then the ethynylphenyl-modified surface efficiently reacts with the redox probe bearing a terminal azide moiety (2-azidoethyl ferrocene) by means of Cu(I)-catalyzed alkyne-azide cycloaddition. Our modification strategy applied to 3D graphene electrodes was analyzed by means of atomic force microscopy, scanning electron microscopy, Raman spectroscopy, cyclic voltammetry, and X-ray photoelectron spectroscopy (XPS). For XPS chemical surface analysis, special attention was paid to the distribution and chemical state of iron and nitrogen in order to highlight the functionalization of the graphene-based substrate by electrochemically grafting a ferrocene derivative. Dense grafting was observed, offering 4.9 × 10(-10) mol cm(-2) surface coverage and showing a stable signal over 22 days. The electrografting was performed in the form of multilayers, which offers higher ferrocene loading than a dense monolayer on a flat surface. This work opens highly promising perspectives for the development of self-organized 3D graphene electrodes with various sensing functionalities. PMID:26710829

  19. Integration of Self-Organizing Map (SOM) and Kernel Density Estimation (KDE) for network intrusion detection

    NASA Astrophysics Data System (ADS)

    Cao, Yuan; He, Haibo; Man, Hong; Shen, Xiaoping

    2009-09-01

    This paper proposes an approach to integrate the self-organizing map (SOM) and kernel density estimation (KDE) techniques for the anomaly-based network intrusion detection (ABNID) system to monitor the network traffic and capture potential abnormal behaviors. With the continuous development of network technology, information security has become a major concern for the cyber system research. In the modern net-centric and tactical warfare networks, the situation is more critical to provide real-time protection for the availability, confidentiality, and integrity of the networked information. To this end, in this work we propose to explore the learning capabilities of SOM, and integrate it with KDE for the network intrusion detection. KDE is used to estimate the distributions of the observed random variables that describe the network system and determine whether the network traffic is normal or abnormal. Meanwhile, the learning and clustering capabilities of SOM are employed to obtain well-defined data clusters to reduce the computational cost of the KDE. The principle of learning in SOM is to self-organize the network of neurons to seek similar properties for certain input patterns. Therefore, SOM can form an approximation of the distribution of input space in a compact fashion, reduce the number of terms in a kernel density estimator, and thus improve the efficiency for the intrusion detection. We test the proposed algorithm over the real-world data sets obtained from the Integrated Network Based Ohio University's Network Detective Service (INBOUNDS) system to show the effectiveness and efficiency of this method.

  20. Scaling and Regeneration of Self-Organized Patterns

    NASA Astrophysics Data System (ADS)

    Werner, Steffen; Stückemann, Tom; Beirán Amigo, Manuel; Rink, Jochen C.; Jülicher, Frank; Friedrich, Benjamin M.

    2015-04-01

    Biological patterns generated during development and regeneration often scale with organism size. Some organisms, e.g., flatworms, can regenerate a rescaled body plan from tissue fragments of varying sizes. Inspired by these examples, we introduce a generalization of Turing patterns that is self-organized and self-scaling. A feedback loop involving diffusing expander molecules regulates the reaction rates of a Turing system, thereby adjusting pattern length scales proportional to system size. Our model captures essential features of body plan regeneration in flatworms as observed in experiments.

  1. Self-organization of hydrophobic soil and granular surfaces

    NASA Astrophysics Data System (ADS)

    McHale, Glen; Shirtcliffe, Neil J.; Newton, Michael I.; Pyatt, F. Brian; Doerr, Stefan H.

    2007-01-01

    Soil can become extremely water repellent following forest fires or oil spillages, thus preventing penetration of water and increasing runoff and soil erosion. Here the authors show that evaporation of a droplet from the surface of a hydrophobic granular material can be an active process, lifting, self-coating, and selectively concentrating small solid grains. Droplet evaporation leads to the formation of temporary liquid marbles and, as droplet volume reduces, particles of different wettabilities compete for water-air interfacial surface area. This can result in a sorting effect with self-organization of a mixed hydrophobic-hydrophilic aggregate into a hydrophobic shell surrounding a hydrophilic core.

  2. Bifurcation and "self-organization" of a system

    NASA Astrophysics Data System (ADS)

    Aldabergenov, M.; Balakaeva, G.

    2016-04-01

    Triangulation of a multicomponent system was shown on example of the CaO-SiO2-H2O system. "The Gibbs function normalized to the total number of electrons" was applied in order to reflect all the possible transformations of components of the system at non-equilibrium as well as at equilibrium conditions. The bifurcation points of the system are located at the each intersection of the line connected compositions of the interacting components and the stable secant line. It was shown the possibility of the "self-organization" processes which is based on the exchange as well as that reactions.

  3. Self-Organized Synchronization in Decentralized Power Grids

    NASA Astrophysics Data System (ADS)

    Rohden, Martin; Sorge, Andreas; Timme, Marc; Witthaut, Dirk

    2012-08-01

    Robust synchronization (phase locking) of power plants and consumers centrally underlies the stable operation of electric power grids. Despite current attempts to control large-scale networks, even their uncontrolled collective dynamics is not fully understood. Here we analyze conditions enabling self-organized synchronization in oscillator networks that serve as coarse-scale models for power grids, focusing on decentralizing power sources. Intriguingly, we find that whereas more decentralized grids become more sensitive to dynamical perturbations, they simultaneously become more robust to topological failures. Decentralizing power sources may thus facilitate the onset of synchronization in modern power grids.

  4. Energy minimization for self-organized structure formation and actuation

    NASA Astrophysics Data System (ADS)

    Kofod, Guggi; Wirges, Werner; Paajanen, Mika; Bauer, Siegfried

    2007-02-01

    An approach for creating complex structures with embedded actuation in planar manufacturing steps is presented. Self-organization and energy minimization are central to this approach, illustrated with a model based on minimization of the hyperelastic free energy strain function of a stretched elastomer and the bending elastic energy of a plastic frame. A tulip-shaped gripper structure illustrates the technological potential of the approach. Advantages are simplicity of manufacture, complexity of final structures, and the ease with which any electroactive material can be exploited as means of actuation.

  5. Growing self-organizing trees for autonomous hierarchical clustering.

    PubMed

    Doan, Nhat-Quang; Azzag, Hanane; Lebbah, Mustapha

    2013-05-01

    This paper presents a new unsupervised learning method based on growing processes and autonomous self-assembly rules. This method, called Growing Self-organizing Trees (GSoT), can grow both network size and tree topology to represent the topological and hierarchical dataset organization, allowing a rapid and interactive visualization. Tree construction rules draw inspiration from elusive properties of biological organization to build hierarchical structures. Experiments conducted on real datasets demonstrate good GSoT performance and provide visual results that are generated during the training process. PMID:23041056

  6. Self-organization, embodiment, and biologically inspired robotics.

    PubMed

    Pfeifer, Rolf; Lungarella, Max; Iida, Fumiya

    2007-11-16

    Robotics researchers increasingly agree that ideas from biology and self-organization can strongly benefit the design of autonomous robots. Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, indefinite richness, and limited availability of information. Industrial robots, in contrast, operate in highly controlled environments with no or very little uncertainty. Although many challenges remain, concepts from biologically inspired (bio-inspired) robotics will eventually enable researchers to engineer machines for the real world that possess at least some of the desirable properties of biological organisms, such as adaptivity, robustness, versatility, and agility. PMID:18006736

  7. Self-organized criticality of plastic shear bands in rocks

    SciTech Connect

    Poliakov, A.N.B.; Herrmann, H.J.

    1994-09-01

    We show that the shear bands that appear during the pure shear numerical simulations of rocks with a non-associated plastic flow rule form fractal networks. The system drives spontaneously into a state in which the length distribution of shear bands follows a power law (self-organized criticality) with exponent 2.07. The distribution of local gradients in deviatoric strain rate has different scaling exponents for each moment, in particular the geometrical fractal dimension is 1.7. Samples of granodiorite sheared under high confining pressure from the Pyrenees are analyzed and their properties compared with the numerical results.

  8. Grid topologies for the self-organizing map.

    PubMed

    López-Rubio, Ezequiel; Díaz Ramos, Antonio

    2014-08-01

    The original Self-Organizing Feature Map (SOFM) has been extended in many ways to suit different goals and application domains. However, the topologies of the map lattice that we can found in literature are nearly always square or, more rarely, hexagonal. In this paper we study alternative grid topologies, which are derived from the geometrical theory of tessellations. Experimental results are presented for unsupervised clustering, color image segmentation and classification tasks, which show that the differences among the topologies are statistically significant in most cases, and that the optimal topology depends on the problem at hand. A theoretical interpretation of these results is also developed. PMID:24861385

  9. Optimization and self-organized criticality in a magnetic system

    NASA Astrophysics Data System (ADS)

    Onody, Roberto N.; de Castro, Paulo A.

    2003-05-01

    We propose a kind of Bak-Sneppen dynamics as a general optimization technique to treat magnetic systems. The resulting dynamics shows self-organized criticality with power-law scaling of the spatial and temporal correlations. An alternative method of the extremal optimization (EO) is also analyzed here. We provided a numerical confirmation that, for any possible value of its free parameter τ, the EO dynamics exhibits a non-critical behavior with an infinite spatial range and exponential decay of the avalanches. Using the chiral clock model as our test system, we compare the efficiency of the two dynamics with regard to their abilities to find the system's ground state.

  10. Sperm whale identification using self-organizing maps

    NASA Astrophysics Data System (ADS)

    Ioup, Juliette W.; Ioup, George E.

    2001-05-01

    Self-organizing maps (SOMs) are a neural network technique for clustering data with similar features. Sperm whale phonations are among the many sounds that can be heard in the Littoral Acoustic Demonstration Center underwater acoustic data from three bottom-mounted hydrophones in the northern Gulf of Mexico during the summer of 2001. When more than one whale is present, it would be useful to associate particular clicks or click trains with specific whales. SOMs are employed using various features including the time series itself, Fourier transform coefficients, and wavelet transform coefficients. Preliminary results with a relatively small data set will be presented. [Research supported by ONR.

  11. Self-organization and self-avoiding limit cycles

    NASA Astrophysics Data System (ADS)

    Hexner, D.; Levine, D.

    2015-02-01

    A simple periodically driven system displaying rich behavior is introduced and studied. The system self-organizes into a mosaic of static ordered regions with three possible patterns, which are threaded by one-dimensional paths on which a small number of mobile particles travel. These trajectories are self-avoiding and non-intersecting, and their relationship to self-avoiding random walks is explored. Near ρ=0.5 the distribution of path lengths becomes power-law-like up to some cutoff length, suggesting a possible critical state.

  12. Multimodal registration of retinal images using self organizing maps.

    PubMed

    Matsopoulos, George K; Asvestas, Pantelis A; Mouravliansky, Nikolaos A; Delibasis, Konstantinos K

    2004-12-01

    In this paper, an automatic method for registering multimodal retinal images is presented. The method consists of three steps: the vessel centerline detection and extraction of bifurcation points only in the reference image, the automatic correspondence of bifurcation points in the two images using a novel implementation of the self organizing maps and the extraction of the parameters of the affine transform using the previously obtained correspondences. The proposed registration algorithm was tested on 24 multimodal retinal pairs and the obtained results show an advantageous performance in terms of accuracy with respect to the manual registration. PMID:15575412

  13.  Introduction: Self-organization in nonequilibrium chemical systems

    NASA Astrophysics Data System (ADS)

    Epstein, Irving R.; Pojman, John A.; Steinbock, Oliver

    2006-09-01

    The field of self-organization in nonequilibrium chemical systems comprises the study of dynamical phenomena in chemically reacting systems far from equilibrium. Systematic exploration of this area began with investigations of the temporal behavior of the Belousov-Zhabotinsky oscillating reaction, discovered accidentally in the former Soviet Union in the 1950s. The field soon advanced into chemical waves in excitable media and propagating fronts. With the systematic design of oscillating reactions in the 1980s and the discovery of Turing patterns in the 1990s, the scope of these studies expanded dramatically. The articles in this Focus Issue provide an overview of the development and current state of the field.

  14. Analysis of gene expression data using self-organizing maps.

    PubMed

    Törönen, P; Kolehmainen, M; Wong, G; Castrén, E

    1999-05-21

    DNA microarray technologies together with rapidly increasing genomic sequence information is leading to an explosion in available gene expression data. Currently there is a great need for efficient methods to analyze and visualize these massive data sets. A self-organizing map (SOM) is an unsupervised neural network learning algorithm which has been successfully used for the analysis and organization of large data files. We have here applied the SOM algorithm to analyze published data of yeast gene expression and show that SOM is an excellent tool for the analysis and visualization of gene expression profiles. PMID:10371154

  15. Scaling and regeneration of self-organized patterns.

    PubMed

    Werner, Steffen; Stückemann, Tom; Beirán Amigo, Manuel; Rink, Jochen C; Jülicher, Frank; Friedrich, Benjamin M

    2015-04-01

    Biological patterns generated during development and regeneration often scale with organism size. Some organisms, e.g., flatworms, can regenerate a rescaled body plan from tissue fragments of varying sizes. Inspired by these examples, we introduce a generalization of Turing patterns that is self-organized and self-scaling. A feedback loop involving diffusing expander molecules regulates the reaction rates of a Turing system, thereby adjusting pattern length scales proportional to system size. Our model captures essential features of body plan regeneration in flatworms as observed in experiments. PMID:25884138

  16. Physical Properties Determining Self-Organization of Motors and Microtubules

    NASA Astrophysics Data System (ADS)

    Surrey, Thomas; Nédélec, François; Leibler, Stanislas; Karsenti, Eric

    2001-05-01

    In eukaryotic cells, microtubules and their associated motor proteins can be organized into various large-scale patterns. Using a simplified experimental system combined with computer simulations, we examined how the concentrations and kinetic parameters of the motors contribute to their collective behavior. We observed self-organization of generic steady-state structures such as asters, vortices, and a network of interconnected poles. We identified parameter combinations that determine the generation of each of these structures. In general, this approach may become useful for correlating the morphogenetic phenomena taking place in a biological system with the biophysical characteristics of its constituents.

  17. A self-organizing CMAC network with gray credit assignment.

    PubMed

    Yeh, Ming-Feng; Chang, Kuang-Chiung

    2006-06-01

    This paper attempts to incorporate the structure of the cerebellar-model-articulation-controller (CMAC) network into the Kohonen layer of the self-organizing map (SOM) to construct a self-organizing CMAC (SOCMAC) network. The proposed SOCMAC network can perform the function of an SOM and can distribute the learning error into the memory contents of all addressed hypercubes as a CMAC. The learning of the SOCMAC is in an unsupervised manner. The neighborhood region of the SOCMAC is implicit in the structure of a two-dimensional CMAC network and needs not be defined in advance. Based on gray relational analysis, a credit-assignment technique for SOCMAC learning is introduced to hasten the overall learning process. This paper also analyzes the convergence properties of the SOCMAC. It is shown that under the proposed updating rule, both the memory contents and the state outputs of the SOCMAC converge almost surely. The SOCMAC is applied to solve both data-clustering and data-classification problems, and simulation results show that the proposed network achieves better performance than other known SOMs. PMID:16761815

  18. Stacked Multilayer Self-Organizing Map for Background Modeling.

    PubMed

    Zhao, Zhenjie; Zhang, Xuebo; Fang, Yongchun

    2015-09-01

    In this paper, a new background modeling method called stacked multilayer self-organizing map background model (SMSOM-BM) is proposed, which presents several merits such as strong representative ability for complex scenarios, easy to use, and so on. In order to enhance the representative ability of the background model and make the parameters learned automatically, the recently developed idea of representative learning (or deep learning) is elegantly employed to extend the existing single-layer self-organizing map background model to a multilayer one (namely, the proposed SMSOM-BM). As a consequence, the SMSOM-BM gains several merits including strong representative ability to learn background model of challenging scenarios, and automatic determination for most network parameters. More specifically, every pixel is modeled by a SMSOM, and spatial consistency is considered at each layer. By introducing a novel over-layer filtering process, we can train the background model layer by layer in an efficient manner. Furthermore, for real-time performance consideration, we have implemented the proposed method using NVIDIA CUDA platform. Comparative experimental results show superior performance of the proposed approach. PMID:25935034

  19. Termini of calving glaciers as self-organized critical systems

    NASA Astrophysics Data System (ADS)

    Åström, J. A.; Vallot, D.; Schäfer, M.; Welty, E. Z.; O'Neel, S.; Bartholomaus, T. C.; Liu, Yan; Riikilä, T. I.; Zwinger, T.; Timonen, J.; Moore, J. C.

    2014-12-01

    Over the next century, one of the largest contributions to sea level rise will come from ice sheets and glaciers calving ice into the ocean. Factors controlling the rapid and nonlinear variations in calving fluxes are poorly understood, and therefore difficult to include in prognostic climate-forced land-ice models. Here we analyse globally distributed calving data sets from Svalbard, Alaska (USA), Greenland and Antarctica in combination with simulations from a first-principles, particle-based numerical calving model to investigate the size and inter-event time of calving events. We find that calving events triggered by the brittle fracture of glacier ice are governed by the same power-law distributions as avalanches in the canonical Abelian sandpile model. This similarity suggests that calving termini behave as self-organized critical systems that readily flip between states of sub-critical advance and super-critical retreat in response to changes in climate and geometric conditions. Observations of sudden ice-shelf collapse and tidewater glacier retreat in response to gradual warming of their environment are consistent with a system fluctuating around its critical point in response to changing external forcing. We propose that self-organized criticality provides a yet unexplored framework for investigations into calving and projections of sea level rise.

  20. Geometry sensing by self-organized protein patterns

    PubMed Central

    Schweizer, Jakob; Loose, Martin; Bonny, Mike; Kruse, Karsten; Mönch, Ingolf; Schwille, Petra

    2012-01-01

    In the living cell, proteins are able to organize space much larger than their dimensions. In return, changes of intracellular space can influence biochemical reactions, allowing cells to sense their size and shape. Despite the possibility to reconstitute protein self-organization with only a few purified components, we still lack knowledge of how geometrical boundaries affect spatiotemporal protein patterns. Following a minimal systems approach, we used purified proteins and photolithographically patterned membranes to study the influence of spatial confinement on the self-organization of the Min system, a spatial regulator of bacterial cytokinesis, in vitro. We found that the emerging protein pattern responds even to the lateral, two-dimensional geometry of the membrane such that, as in the three-dimensional cell, Min protein waves travel along the longest axis of the membrane patch. This shows that for spatial sensing the Min system does not need to be enclosed in a three-dimensional compartment. Using a computational model we quantitatively analyzed our experimental findings and identified persistent binding of MinE to the membrane as requirement for the Min system to sense geometry. Our results give insight into the interplay between geometrical confinement and biochemical patterns emerging from a nonlinear reaction–diffusion system. PMID:22949703

  1. Granular self-organization by autotuning of friction

    PubMed Central

    Kumar, Deepak; Nitsure, Nitin; Bhattacharya, S.; Ghosh, Shankar

    2015-01-01

    A monolayer of granular spheres in a cylindrical vial, driven continuously by an orbital shaker and subjected to a symmetric confining centrifugal potential, self-organizes to form a distinctively asymmetric structure which occupies only the rear half-space. It is marked by a sharp leading edge at the potential minimum and a curved rear. The area of the structure obeys a power-law scaling with the number of spheres. Imaging shows that the regulation of motion of individual spheres occurs via toggling between two types of motion, namely, rolling and sliding. A low density of weakly frictional rollers congregates near the sharp leading edge whereas a denser rear comprises highly frictional sliders. Experiments further suggest that because the rolling and sliding friction coefficients differ substantially, the spheres acquire a local time-averaged coefficient of friction within a large range of intermediate values in the system. The various sets of spatial and temporal configurations of the rollers and sliders constitute the internal states of the system. Experiments demonstrate and simulations confirm that the global features of the structure are maintained robustly by autotuning of friction through these internal states, providing a previously unidentified route to self-organization of a many-body system. PMID:26324918

  2. Stochastic models for plant microtubule self-organization and structure.

    PubMed

    Eren, Ezgi C; Dixit, Ram; Gautam, Natarajan

    2015-12-01

    One of the key enablers of shape and growth in plant cells is the cortical microtubule (CMT) system, which is a polymer array that forms an appropriately-structured scaffolding in each cell. Plant biologists have shown that stochastic dynamics and simple rules of interactions between CMTs can lead to a coaligned CMT array structure. However, the mechanisms and conditions that cause CMT arrays to become organized are not well understood. It is prohibitively time-consuming to use actual plants to study the effect of various genetic mutations and environmental conditions on CMT self-organization. In fact, even computer simulations with multiple replications are not fast enough due to the spatio-temporal complexity of the system. To redress this shortcoming, we develop analytical models and methods for expeditiously computing CMT system metrics that are related to self-organization and array structure. In particular, we formulate a mean-field model to derive sufficient conditions for the organization to occur. We show that growth-prone dynamics itself is sufficient to lead to organization in presence of interactions in the system. In addition, for such systems, we develop predictive methods for estimation of system metrics such as expected average length and number of CMTs over time, using a stochastic fluid-flow model, transient analysis, and approximation algorithms tailored to our problem. We illustrate the effectiveness of our approach through numerical test instances and discuss biological insights. PMID:25700800

  3. Ice Shape Characterization Using Self-Organizing Maps

    NASA Technical Reports Server (NTRS)

    McClain, Stephen T.; Tino, Peter; Kreeger, Richard E.

    2011-01-01

    A method for characterizing ice shapes using a self-organizing map (SOM) technique is presented. Self-organizing maps are neural-network techniques for representing noisy, multi-dimensional data aligned along a lower-dimensional and possibly nonlinear manifold. For a large set of noisy data, each element of a finite set of codebook vectors is iteratively moved in the direction of the data closest to the winner codebook vector. Through successive iterations, the codebook vectors begin to align with the trends of the higher-dimensional data. In information processing, the intent of SOM methods is to transmit the codebook vectors, which contains far fewer elements and requires much less memory or bandwidth, than the original noisy data set. When applied to airfoil ice accretion shapes, the properties of the codebook vectors and the statistical nature of the SOM methods allows for a quantitative comparison of experimentally measured mean or average ice shapes to ice shapes predicted using computer codes such as LEWICE. The nature of the codebook vectors also enables grid generation and surface roughness descriptions for use with the discrete-element roughness approach. In the present study, SOM characterizations are applied to a rime ice shape, a glaze ice shape at an angle of attack, a bi-modal glaze ice shape, and a multi-horn glaze ice shape. Improvements and future explorations will be discussed.

  4. Self-organization of network dynamics into local quantized states

    DOE PAGESBeta

    Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

    2016-02-17

    Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of themore » Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Thus, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.« less

  5. Self-organization of multivalent counterions in polyelectrolyte brushes

    NASA Astrophysics Data System (ADS)

    Wu, Jianzhong

    2013-03-01

    The structure and interfacial properties of a polyelectrolyte brush (PEB) depend on a broad range of parameters such as the polymer charge and grafting density, counterion valence, salt concentration, and solvent conditions. These properties are of fundamental importance in technological applications of PEBs including colloid stabilization, surface modification and lubrication, and in functioning of biological systems such as genome packaging in single-strand DNA/RNA viruses. Despite intensive studies by experiments, molecular simulations, and myriad analytical methods including scaling analyses, self-consistent-field theory, and most recently density functional theory, the behavior of PEBs in the presence of multivalent counterions remains poorly understood. In this talk, I will present a density functional method for polyelectrolyte brushes and discuss self-organization of multivalent counterions within highly charged polyelectrolyte brushes. The counterion-mediated attraction between polyions leads to a first-order phase transition similar to that for a neutral brush in a poor solvent. The self-organization of multivalent counterions results in a wavelike electrostatic potential and charge density that oscillate between positive and negative values.

  6. Self-Organization of Blood Pressure Regulation: Clinical Evidence.

    PubMed

    Fortrat, Jacques-Olivier; Gharib, Claude

    2016-01-01

    The pathogenesis of vasovagal syncope has remained elusive despite many efforts to identify an underlying dysfunction. Catastrophe theory explains the spontaneous occurrence of sudden events in some mathematically complex systems known as self-organized systems poised at criticality. These systems universally exhibit a power law initially described in earthquake occurrence: the Gutenberg Richter law. The magnitude plotted against the total number of earthquakes of at least this magnitude draw a straight line on log-log graph. We hypothesized that vasovagal syncope is a catastrophe occurring spontaneously in the cardiovascular system. We counted the number and magnitude (number of beats) of vasovagal reactions (simultaneous decreases in both blood pressure and heart rate on consecutive beats) in 24 patients with vasovagal symptoms during a head-up tilt test and 24 paired patients with no symptoms during the test. For each patient, we checked whether vasovagal reaction occurrence followed the Gutenberg Richter law. The occurrence followed the Gutenberg Richter law in 43 patients (correlation coefficient |r| = 0.986 ± 0.001, mean ± SEM) out of 48, with no difference between patients with and without symptoms. We demonstrated that vasovagal syncope matches a catastrophe model occurring in a self-organized cardiovascular complex system poised at criticality. This is a new vision of cardiovascular regulation and its related disorders. PMID:27065881

  7. Distributed coordination of simulated robots based on self-organization.

    PubMed

    Baldassarre, Gianluca; Parisi, Domenico; Nolfi, Stefano

    2006-01-01

    Distributed coordination of groups of individuals accomplishing a common task without leaders, with little communication, and on the basis of self-organizing principles, is an important research issue within the study of collective behavior of animals, humans, and robots. The article shows how distributed coordination allows a group of evolved, physically linked simulated robots (inspired by a robot under construction) to display a variety of highly coordinated basic behaviors such as collective motion, collective obstacle avoidance, and collective approach to light, and to integrate them in a coherent fashion. In this way the group is capable of searching and approaching a lighted target in an environment scattered with obstacles, furrows, and holes, where robots acting individually fail. The article shows how the emerged coordination of the group relies upon robust self-organizing principles (e.g., positive feedback) based on a novel sensor that allows the single robots to perceive the group's "average" motion direction. The article also presents a robust solution to a difficult coordination problem, which might also be encountered by some organisms, caused by the fact that the robots have to be capable of moving in any direction while being physically connected. Finally, the article shows how the evolved distributed coordination mechanisms scale very well with respect to the number of robots, the way in which robots are assembled, the structure of the environment, and several other aspects. PMID:16859442

  8. Conservative Self-Organized Extremal Model for Wealth Distribution

    NASA Astrophysics Data System (ADS)

    Chakraborty, Abhijit; Mukherjee, G.; Manna, S. S.

    2012-06-01

    We present an extensive numerical study of the modified version of a conservative self-organized extremal model introduced by Pianegonda et al. (Physica A322 (2003) 667-675) in the context of wealth distribution of the people in a society. Here the trading process has been modified by the stochastic bipartite trading rule. More specifically in a trade one of the agents is necessarily the one with the globally minimal value of wealth, the other one being selected randomly from the neighbors of the first agent. The pair of agents then randomly re-shuffle their entire amount of wealth without saving. This model has most of the characteristics similar to the self-organized critical Bak-Sneppen model of evolutionary dynamics. Numerical estimates of a number of critical exponents indicate this model is likely to belong to a new universality class different from the well known models in the literature. In addition the persistence time, which is the time interval between two successive updates of wealth of an agent has been observed to have a non-trivial power law distribution. An opposite version of the model has also been studied where the agent with maximal wealth is selected instead of the one with minimal wealth, which however, exhibits similar behavior as the Minimal Wealth model.

  9. Adaptive self-organization in a realistic neural network model

    NASA Astrophysics Data System (ADS)

    Meisel, Christian; Gross, Thilo

    2009-12-01

    Information processing in complex systems is often found to be maximally efficient close to critical states associated with phase transitions. It is therefore conceivable that also neural information processing operates close to criticality. This is further supported by the observation of power-law distributions, which are a hallmark of phase transitions. An important open question is how neural networks could remain close to a critical point while undergoing a continual change in the course of development, adaptation, learning, and more. An influential contribution was made by Bornholdt and Rohlf, introducing a generic mechanism of robust self-organized criticality in adaptive networks. Here, we address the question whether this mechanism is relevant for real neural networks. We show in a realistic model that spike-time-dependent synaptic plasticity can self-organize neural networks robustly toward criticality. Our model reproduces several empirical observations and makes testable predictions on the distribution of synaptic strength, relating them to the critical state of the network. These results suggest that the interplay between dynamics and topology may be essential for neural information processing.

  10. Self-organized formation of regular nanostripes on vicinal surfaces

    NASA Astrophysics Data System (ADS)

    Yu, Yan-Mei; Liu, Bang-Gui

    2004-11-01

    We explore the mechanism of self-organized formation of regular arrays of nanostripes on vicinal surfaces by using a phase-field model. Epitaxial growth during deposition usually results in both nanostripes and islands on terraces of a vicinal substrate. Postdeposition annealing at elevated temperatures induces growth of the nanostripes but makes the islands shrink. It is a ripening process of the mixed system of the nanostripes and the islands, being dependent upon the temperature and strain. It is accompanied by a transition from the diffusion-limited regime to the detachment-limited regime induced by the strain at high temperatures. This ripening makes the islands diminish and on the other hand makes the nanostripes smoother. As a result, the islands disappear completely and the regular arrays of nanostripes are formed on the vicinal substrate. This theory can explain the self-organized formation of nanostripes and nanowires on vicinal surfaces, such as the intriguing regular arrays of Fe nanostripes on the vicinal W surfaces.

  11. Self-organizing and adaptive peer-to-peer network.

    PubMed

    Ghanea-Hercock, Robert A; Wang, Fang; Sun, Yaoru

    2006-12-01

    In this paper, an algorithm that forms a dynamic and self-organizing network is demonstrated. The hypothesis of this work is that in order to achieve a resilient and adaptive peer-to-peer (P2P) network, each network node must proactively maintain a minimum number of edges. Specifically, low-level communication protocols are not sufficient by themselves to achieve high-service availability, especially in the case of ad hoc or dynamic networks with a high degree of node addition and deletion. The concept has been evaluated within a P2P agent application in which each agent has a goal to maintain a preferred number of connections to a number of service providing agents. Using this algorithm, the agents update a weight value associated with each connection, based on the perceived utility of the connection to the corresponding agent. This utility function can be a combination of several node or edge parameters, such as degree k of the target node, or frequency of the message response from the node. This weight is updated using a set of Hebbian-style learning rules, such that the network as a whole exhibits adaptive self-organizing behavior. The principal result is the finding that by limiting the connection neighborhood within the overlay topology, the resulting P2P network can be made highly resilient to targeted attacks on high-degree nodes, while maintaining search efficiency. PMID:17186799

  12. Self-Organizing Hidden Markov Model Map (SOHMMM).

    PubMed

    Ferles, Christos; Stafylopatis, Andreas

    2013-12-01

    A hybrid approach combining the Self-Organizing Map (SOM) and the Hidden Markov Model (HMM) is presented. The Self-Organizing Hidden Markov Model Map (SOHMMM) establishes a cross-section between the theoretic foundations and algorithmic realizations of its constituents. The respective architectures and learning methodologies are fused in an attempt to meet the increasing requirements imposed by the properties of deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and protein chain molecules. The fusion and synergy of the SOM unsupervised training and the HMM dynamic programming algorithms bring forth a novel on-line gradient descent unsupervised learning algorithm, which is fully integrated into the SOHMMM. Since the SOHMMM carries out probabilistic sequence analysis with little or no prior knowledge, it can have a variety of applications in clustering, dimensionality reduction and visualization of large-scale sequence spaces, and also, in sequence discrimination, search and classification. Two series of experiments based on artificial sequence data and splice junction gene sequences demonstrate the SOHMMM's characteristics and capabilities. PMID:24001407

  13. Self-organized pulse switching for binary sensing and actuation

    NASA Astrophysics Data System (ADS)

    Huo, Qiong; Dong, Bo; Biswas, Subir

    2013-05-01

    This paper presents a novel energy-efficient distributed self-organized pulse switching architecture with a cell based event localization for wireless sensor and actuator network applications. The key idea of this pulse switching architecture is to abstract a single pulse, as opposed to multi-bit packets, as the information exchange mechanism. Unlike multi-bit packet communication, the proposed pulse switching architecture is based on pulse communications where a node either transmits a pulse or keeps silent at every time unit. Specifically, an event can be coded as a single pulse in a specific time unit with respect to the global clock. Then the pulse is transported multi-hop while preserving the event's localization information in the form of temporal pulse position representing its originating cell, destination cell and next-hop cell. The proposed distributed pulse switching is shown to be energy-efficient compared to traditional packet switching especially for binary event sensing and actuation applications. Binary event sensing and actuation with conventional packet transport can be prohibitively energy-inefficient due to the communication, processing, and buffering overheads of the large number of bits within a packet's data, header, and preambles. This paper presents a joint MAC and Routing architecture for self-organized distributed pulse switching. Through simulation experiments, it is shown that pulse switching can be an effective distributed means for event based networking in wireless sensor and actuator networks, which can potentially replace the packet transport when the information to be transported is binary in nature.

  14. Taming Self-Organization Dynamics to Dramatically Control Porous Architectures.

    PubMed

    Daly, Ronan; Sader, John E; Boland, John J

    2016-03-22

    We demonstrate templating of functional materials with unexpected and intricate micro- and nanostructures by controlling the condensation, packing, and evaporation of water droplets on a polymer solution. Spontaneous evaporation of a polymer solution induces cooling of the liquid surface and water microdroplet condensation from the ambient vapor. These droplets pack together and act as a template to imprint an entangled polymer film. This breath figure (BF) phenomenon is an example of self-organization that involves the long-range ordering of droplets. Equilibrium-based analysis provides many insights into contact angles and drop stability of individual drops, but the BF phenomenon remains poorly understood thus far, preventing translation to real applications. Here we investigate the dynamics of this phenomenon to separate out the competing influences and then introduce a modulation scheme to ultimately manipulate the water vapor-liquid equilibrium independently from the solvent evaporation. This approach to BF control provides insights into the mechanism, a rationale for microstructure design, and evidence for the benefits of dynamical control of self-organization systems. We finally present dramatically different porous architectures from this approach reminiscent of microscale Petri dishes, conical flasks, and test tubes. PMID:26828573

  15. Self-Organization of Blood Pressure Regulation: Clinical Evidence

    PubMed Central

    Fortrat, Jacques-Olivier; Gharib, Claude

    2016-01-01

    The pathogenesis of vasovagal syncope has remained elusive despite many efforts to identify an underlying dysfunction. Catastrophe theory explains the spontaneous occurrence of sudden events in some mathematically complex systems known as self-organized systems poised at criticality. These systems universally exhibit a power law initially described in earthquake occurrence: the Gutenberg Richter law. The magnitude plotted against the total number of earthquakes of at least this magnitude draw a straight line on log-log graph. We hypothesized that vasovagal syncope is a catastrophe occurring spontaneously in the cardiovascular system. We counted the number and magnitude (number of beats) of vasovagal reactions (simultaneous decreases in both blood pressure and heart rate on consecutive beats) in 24 patients with vasovagal symptoms during a head-up tilt test and 24 paired patients with no symptoms during the test. For each patient, we checked whether vasovagal reaction occurrence followed the Gutenberg Richter law. The occurrence followed the Gutenberg Richter law in 43 patients (correlation coefficient |r| = 0.986 ± 0.001, mean ± SEM) out of 48, with no difference between patients with and without symptoms. We demonstrated that vasovagal syncope matches a catastrophe model occurring in a self-organized cardiovascular complex system poised at criticality. This is a new vision of cardiovascular regulation and its related disorders. PMID:27065881

  16. Self-organization of network dynamics into local quantized states.

    PubMed

    Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

    2016-01-01

    Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model-a minimal-ingredients model of nodal activation and interaction within a complex network-is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements. PMID:26883170

  17. Self-organization of network dynamics into local quantized states

    PubMed Central

    Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

    2016-01-01

    Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements. PMID:26883170

  18. Self-organization of network dynamics into local quantized states

    NASA Astrophysics Data System (ADS)

    Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

    2016-02-01

    Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.

  19. Lipopolysaccharide O-Chain Core Region Required for Cellular Cohesion and Compaction of In Vitro and Root Biofilms Developed by Rhizobium leguminosarum

    PubMed Central

    Russo, Daniela M.; Abdian, Patricia L.; Posadas, Diana M.; Williams, Alan; Vozza, Nicolás; Giordano, Walter; Kannenberg, Elmar; Downie, J. Allan

    2014-01-01

    The formation of biofilms is an important survival strategy allowing rhizobia to live on soil particles and plant roots. Within the microcolonies of the biofilm developed by Rhizobium leguminosarum, rhizobial cells interact tightly through lateral and polar connections, forming organized and compact cell aggregates. These microcolonies are embedded in a biofilm matrix, whose main component is the acidic exopolysaccharide (EPS). Our work shows that the O-chain core region of the R. leguminosarum lipopolysaccharide (LPS) (which stretches out of the cell surface) strongly influences bacterial adhesive properties and cell-cell cohesion. Mutants defective in the O chain or O-chain core moiety developed premature microcolonies in which lateral bacterial contacts were greatly reduced. Furthermore, cell-cell interactions within the microcolonies of the LPS mutants were mediated mostly through their poles, resulting in a biofilm with an altered three-dimensional structure and increased thickness. In addition, on the root epidermis and on root hairs, O-antigen core-defective strains showed altered biofilm patterns with the typical microcolony compaction impaired. Taken together, these results indicate that the surface-exposed moiety of the LPS is crucial for proper cell-to-cell interactions and for the formation of robust biofilms on different surfaces. PMID:25416773

  20. Systems biology beyond networks: generating order from disorder through self-organization

    PubMed Central

    Saetzler, K.; Sonnenschein, C.; Soto, A.M.

    2011-01-01

    Erwin Schrödinger pointed out in his 1944 book “What is Life” that one defining attribute of biological systems seems to be their tendency to generate order from disorder defying the second law of thermodynamics. Almost parallel to his findings, the science of complex systems was founded based on observations on physical and chemical systems showing that inanimate matter can exhibit complex structures although their interacting parts follow simple rules. This is explained by a process known as self-organization and it is now widely accepted that multi-cellular biological organisms are themselves self-organizing complex systems in which the relations among their parts are dynamic, contextual and interdependent. In order to fully understand such systems, we are required to computationally and mathematically model their interactions as promulgated in systems biology. The preponderance of network models in the practice of systems biology inspired by a reductionist, bottom-up view, seems to neglect, however, the importance of bidirectional interactions across spatial scales and domains. This approach introduces a shortcoming that may hinder research on emergent phenomena such as those of tissue morphogenesis and related diseases, such as cancer. Another hindrance of current modeling attempts is that those systems operate in a parameter space that seems far removed from biological reality. This misperception calls for more tightly coupled mathematical and computational models to biological experiments by creating and designing biological model systems that are accessible to a wide range of experimental manipulations. In this way, a comprehensive understanding of fundamental processes in normal development or of aberrations, like cancer, will be generated. PMID:21569848

  1. Self-organization of engineered epithelial tubules by differential cellular motility

    SciTech Connect

    Mori, Hidetoshi; Gjorevski, Nikolce; Inman, Jamie L; Bissell, Mina J; Nelson, Celeste M

    2009-02-04

    Patterning of developing tissues arises from a number of mechanisms, including cell shape change, cell proliferation, and cell sorting from differential cohesion or tension. Here, we reveal that differences in cell motility can also lead to cell sorting within tissues. Using mosaic engineered mammary epithelial tubules, we found that cells sorted depending on their expression level of the membrane-anchored collagenase matrix metalloproteinase (MMP)-14. These rearrangements were independent of the catalytic activity of MMP14 but absolutely required the hemopexin domain. We describe a signaling cascade downstream of MMP14 through Rho kinase that allows cells to sort within the model tissues. Cell speed and persistence time were enhanced by MMP14 expression, but only the latter motility parameter was required for sorting. These results indicate that differential directional persistence can give rise to patterns within model developing tissues.

  2. Adaptive, associative, and self-organizing functions in neural computing.

    PubMed

    Kohonen, T

    1987-12-01

    This paper contains an attempt to describe certain adaptive and cooperative functions encountered in neural networks. The approach is a compromise between biological accuracy and mathematical clarity. two types of differential equation seem to describe the basic effects underlying the information of these functions: the equation for the electrical activity of the neuron and the adaptation equation that describes changes in its input connectivities. Various phenomena and operations are derivable from them: clustering of activity in a laterally interconnected nework; adaptive formation of feature detectors; the autoassociative memory function; and self-organized formation of ordered sensory maps. The discussion tends to reason what functions are readily amenable to analytical modeling and which phenomena seem to ensue from the more complex interactions that take place in the brain. PMID:20523469

  3. SERS Amplification from Self-Organized Arrays of Plasmonic Nanocrescents.

    PubMed

    Giordano, Maria Caterina; Foti, Antonino; Messina, Elena; Gucciardi, Pietro Giuseppe; Comoretto, Davide; Buatier de Mongeot, Francesco

    2016-03-01

    We report on the surface-enhanced Raman scattering (SERS) efficiency of self-organized arrays of Au nanocrescents confined on monolayers of polystyrene nanospheres. A dichroic SERS emission in the visible spectrum is observed due to the selective excitation of a localized surface plasmon (LSP) resonance along the "short axis" of the Au nanocrescents. Under these conditions SERS signal amplifications in the range of 10(3) have been observed with respect to a flat reference Au film. The far field and near field plasmonic response of Au nanocrescent arrays have been investigated as a function of the metal dose deposited onto the polymeric spheres. In this way, we show the possibility of simply tailoring the SERS emission by engineering the morphology of the plasmonic nanocrescents. We highlight the SERS activity of chains of satellite nanoclusters that decorate the border of each connected crescent and sustain isotropic high energy LSP resonances in the visible spectrum. PMID:26824254

  4. Vector representation of user's view using self-organizing map

    NASA Astrophysics Data System (ADS)

    Ae, Tadashi; Yamaguchi, Tomohisa; Monden, Eri; Kawabata, Shunji; Kamitani, Motoki

    2004-05-01

    There exist various objects, such as pictures, music, texts, etc., around our environment. We have a view for these objects by looking, reading or listening. Our view is concerned with our behaviors deeply, and is very important to understand our behaviors. Therefore, we propose a method which acquires a view as a vector, and apply the vector to sequence generation. We focus on sequences of the data of which a user selects from a multimedia database containing pictures, music, movie, etc.. These data cannot be stereotyped because user's view for them changes by each user. Therefore, we represent the structure of the multimedia database as the vector representing user's view and the stereotyped vector, and acquire sequences containing the structure as elements. We demonstrate a city-sequence generation system which reflects user's intension as an application of sequence generation containing user's view. We apply the self-organizing map to this system to represent user's view.

  5. Self-organized internal architectures of chiral micro-particles

    SciTech Connect

    Provenzano, Clementina; Mazzulla, Alfredo; Desiderio, Giovanni; Pagliusi, Pasquale; De Santo, Maria P.; Cipparrone, Gabriella; Perrotta, Ida

    2014-02-01

    The internal architecture of polymeric self-assembled chiral micro-particles is studied by exploring the effect of the chirality, of the particle sizes, and of the interface/surface properties in the ordering of the helicoidal planes. The experimental investigations, performed by means of different microscopy techniques, show that the polymeric beads, resulting from light induced polymerization of cholesteric liquid crystal droplets, preserve both the spherical shape and the internal self-organized structures. The method used to create the micro-particles with controlled internal chiral architectures presents great flexibility providing several advantages connected to the acquired optical and photonics capabilities and allowing to envisage novel strategies for the development of chiral colloidal systems and materials.

  6. Self-organized sorting limits behavioral variability in swarms

    PubMed Central

    Copenhagen, Katherine; Quint, David A.; Gopinathan, Ajay

    2016-01-01

    Swarming is a phenomenon where collective motion arises from simple local interactions between typically identical individuals. Here, we investigate the effects of variability in behavior among the agents in finite swarms with both alignment and cohesive interactions. We show that swarming is abolished above a critical fraction of non-aligners who do not participate in alignment. In certain regimes, however, swarms above the critical threshold can dynamically reorganize and sort out excess non-aligners to maintain the average fraction close to the critical value. This persists even in swarms with a distribution of alignment interactions, suggesting a simple, robust and efficient mechanism that allows heterogeneously mixed populations to naturally regulate their composition and remain in a collective swarming state or even differentiate among behavioral phenotypes. We show that, for evolving swarms, this self-organized sorting behavior can couple to the evolutionary dynamics leading to new evolutionarily stable equilibrium populations set by the physical swarm parameters. PMID:27550316

  7. Self-organized sorting limits behavioral variability in swarms.

    PubMed

    Copenhagen, Katherine; Quint, David A; Gopinathan, Ajay

    2016-01-01

    Swarming is a phenomenon where collective motion arises from simple local interactions between typically identical individuals. Here, we investigate the effects of variability in behavior among the agents in finite swarms with both alignment and cohesive interactions. We show that swarming is abolished above a critical fraction of non-aligners who do not participate in alignment. In certain regimes, however, swarms above the critical threshold can dynamically reorganize and sort out excess non-aligners to maintain the average fraction close to the critical value. This persists even in swarms with a distribution of alignment interactions, suggesting a simple, robust and efficient mechanism that allows heterogeneously mixed populations to naturally regulate their composition and remain in a collective swarming state or even differentiate among behavioral phenotypes. We show that, for evolving swarms, this self-organized sorting behavior can couple to the evolutionary dynamics leading to new evolutionarily stable equilibrium populations set by the physical swarm parameters. PMID:27550316

  8. Self-Organizing Maps-based ocean currents forecasting system.

    PubMed

    Vilibić, Ivica; Šepić, Jadranka; Mihanović, Hrvoje; Kalinić, Hrvoje; Cosoli, Simone; Janeković, Ivica; Žagar, Nedjeljka; Jesenko, Blaž; Tudor, Martina; Dadić, Vlado; Ivanković, Damir

    2016-01-01

    An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training. PMID:26979129

  9. Self-Organizing Maps-based ocean currents forecasting system

    PubMed Central

    Vilibić, Ivica; Šepić, Jadranka; Mihanović, Hrvoje; Kalinić, Hrvoje; Cosoli, Simone; Janeković, Ivica; Žagar, Nedjeljka; Jesenko, Blaž; Tudor, Martina; Dadić, Vlado; Ivanković, Damir

    2016-01-01

    An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training. PMID:26979129

  10. Self-organization of progress across the century of physics

    NASA Astrophysics Data System (ADS)

    Perc, Matjaž

    2013-04-01

    We make use of information provided in the titles and abstracts of over half a million publications that were published by the American Physical Society during the past 119 years. By identifying all unique words and phrases and determining their monthly usage patterns, we obtain quantifiable insights into the trends of physics discovery from the end of the 19th century to today. We show that the magnitudes of upward and downward trends yield heavy-tailed distributions, and that their emergence is due to the Matthew effect. This indicates that both the rise and fall of scientific paradigms is driven by robust principles of self-organization. Data also confirm that periods of war decelerate scientific progress, and that the later is very much subject to globalisation.

  11. Self-organization in a simple brain model

    SciTech Connect

    Stassinopoulos, D.; Bak, P.; Alstroem, P.

    1994-03-10

    Simulations on a simple model of the brain are presented. The model consists of a set of randomly connected neurons. Inputs and outputs are also connected randomly to a subset of neurons. For each input there is a set of output neurons which must fire in order to achieve success. A signal giving information as to whether or not the action was successful is fed back to the brain from the environment. The connections between firing neurons are strengthened or weakened according to whether or not the action was successful. The system learns, through a self-organization process, to react intelligently to input signals, i.e. it learns to quickly select the correct output for each input. If part of the network is damaged, the system relearns the correct response after a training period.

  12. Self-Organized and Cu-Coordinated Surface Linear Polymerization

    PubMed Central

    Li, Qing; Owens, Jonathan R.; Han, Chengbo; Sumpter, Bobby G.; Lu, Wenchang; Bernholc, Jerzy; Meunier, V.; Maksymovych, Peter; Fuentes-Cabrera, Miguel; Pan, Minghu

    2013-01-01

    We demonstrate a controllable surface-coordinated linear polymerization of long-chain poly(phenylacetylenyl)s that are self-organized into a “circuit-board” pattern on a Cu(100) surface. Scanning tunneling microscopy/spectroscopy (STM/S) corroborated by ab initio calculations, reveals the atomistic details of the molecular structure, and provides a clear signature of electronic and vibrational properties of the poly(phenylacetylene)s chains. Notably, the polymerization reaction is confined epitaxially to the copper lattice, despite a large strain along the polymerized chain that subsequently renders it metallic. Polymerization and depolymerization reactions can be controlled locally at the nanoscale by using a charged metal tip. This control demonstrates the possibility of precisely accessing and controlling conjugated chain-growth polymerization at low temperature. This finding may lead to the bottom-up design and realization of sophisticated architectures for molecular nano-devices. PMID:23811605

  13. Multistrategy self-organizing map learning for classification problems.

    PubMed

    Hasan, S; Shamsuddin, S M

    2011-01-01

    Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test. PMID:21876686

  14. Self-organization of progress across the century of physics

    PubMed Central

    Perc, Matjaž

    2013-01-01

    We make use of information provided in the titles and abstracts of over half a million publications that were published by the American Physical Society during the past 119 years. By identifying all unique words and phrases and determining their monthly usage patterns, we obtain quantifiable insights into the trends of physics discovery from the end of the 19th century to today. We show that the magnitudes of upward and downward trends yield heavy-tailed distributions, and that their emergence is due to the Matthew effect. This indicates that both the rise and fall of scientific paradigms is driven by robust principles of self-organization. Data also confirm that periods of war decelerate scientific progress, and that the later is very much subject to globalisation.

  15. Similarity interaction in information-theoretic self-organizing maps

    NASA Astrophysics Data System (ADS)

    Kamimura, Ryotaro

    2013-04-01

    In this paper, we propose a new information-theoretic computational method called 'similarity interaction' for improving visualization. Due to the fixed arrangement of neurons in the self-organizing maps, similarity between neurons is not necessarily a faithful representation of the actual similarity between neurons. To relax the fixed arrangement, we introduce a method called 'similarity interaction', because we integrate the information of connection weights into that of neurons. We applied our method to three problems, namely teaching assistant evaluation, automobile data, and dermatology data. In all three problems, we succeeded in demonstrating the better performance of our method through visual inspection and quantitative evaluation. Our method is the first step towards the interaction of multiple components in a neural network for finer representations of input patterns.

  16. Evidence of Self-Organized Criticality in Dry Sliding Friction

    NASA Technical Reports Server (NTRS)

    Zypman, Fredy R.; Ferrante, John; Jansen, Mark; Scanlon, Kathleen; Abel, Phillip

    2003-01-01

    This letter presents experimental results on unlubricated friction, which suggests that stick-slip is described by self-organized criticality (SOC). The data, obtained with a pin-on-disc tribometer examines the variation of the friction force as a function of time-or sliding distance. This is the first time that standard tribological equipment has been used to examine the possibility of SOC. The materials were matching pins and discs of aluminium loaded with 250, 500 and 1000 g masses, and matching M50 steel couples loaded with a 1000 g mass. An analysis of the data shows that the probability distribution of slip sizes follows a power law. We perform a careful analysis of all the properties, beyond the two just mentioned, which are required to imply the presence of SOC. Our data strongly support the existence of SOC for stick-slip in dry sliding friction.

  17. Self-organization of a critical state on complex networks

    SciTech Connect

    Ginzburg, S. L.; Nakin, A. V.; Savitskaya, N. E.

    2009-12-15

    The critical dynamics of a two-threshold system with the law of conservation of the basic quantity z and in the absence of sink on a scale-free network has been studied. It has been shown that the critical state that is a set of metastable states appears in such a system. The structure of the metastable states is a set of stable clusters of nodes at which the z values are close to the positive and negative threshold values. Avalanches transforming the system from one metastable state to another state appear in the system. The absence of sink is effectively replaced by the annihilation process. The statistics of avalanches in such a system has been analyzed. It has been shown that the self-organized critical state can appear in the system.

  18. Self-organization of step bunching instability on vicinal substrate

    SciTech Connect

    Pascale, A.; Berbezier, I.; Ronda, A.; Videcoq, A.; Pimpinelli, A.

    2006-09-04

    The authors investigate quantitatively the self-organization of step bunching instability during epitaxy of Si on vicinal Si(001). They show that growth instability evolution can be fitted by power laws L{approx}t{sup {alpha}} and A{approx}t{sup {beta}} (where L is the correlation length and A is the instability amplitude) with critical exponents {alpha}{approx}0.3 and {beta}{approx}0.5 in good agreement with previous studies and well reproduced by kinetic Monte Carlo simulation. They demonstrate that the main phenomenon controlling step bunching is the anisotropy of surface diffusion. The microscopic origin of the instability is attributed to an easier adatom detachment from S{sub A} step, which can be interpreted as a pseudoinverse Ehrlich-Schwoebel barrier [J. Appl. Phys. 37, 3682 (1967); J. Chem. Phys. 44, 1039 (1966)].

  19. Self-Organized Criticality Model for Brain Plasticity

    NASA Astrophysics Data System (ADS)

    de Arcangelis, Lucilla; Perrone-Capano, Carla; Herrmann, Hans J.

    2006-01-01

    Networks of living neurons exhibit an avalanche mode of activity, experimentally found in organotypic cultures. Here we present a model that is based on self-organized criticality and takes into account brain plasticity, which is able to reproduce the spectrum of electroencephalograms (EEG). The model consists of an electrical network with threshold firing and activity-dependent synapse strengths. The system exhibits an avalanche activity in a power-law distribution. The analysis of the power spectra of the electrical signal reproduces very robustly the power-law behavior with the exponent 0.8, experimentally measured in EEG spectra. The same value of the exponent is found on small-world lattices and for leaky neurons, indicating that universality holds for a wide class of brain models.

  20. Multiparameter image visualization with self-organizing maps

    NASA Astrophysics Data System (ADS)

    Manduca, Armando

    1994-05-01

    The effective display of multiparameter medical image data sets is assuming increasing importance as more distinct imaging modalities are becoming available. For medical purposes, one desirable goal is to fuse such data sets into a single most informative gray-scale image without making rigid classification decisions. A visualization technique based on a non-linear projection onto a 1D self-organizing map is described and examples are shown. The SOM visualization technique is fast, theoretically attractive, a useful complement to projection- pursuit or other linear techniques, and may be of particular value in calling attention to specific regions in a multiparameter image where the component images should be examined in detail.

  1. Multiparameter image visualization with self-organizing maps

    NASA Astrophysics Data System (ADS)

    Manduca, Armando

    1994-09-01

    The effective display of multi-parameter medical image data sets is assuming increasing importance as more distinct imaging modalities are becoming available. For medical pruposes, one desirable goal is to fuse such data sets into a single most informative gray-scale image without making rigid classification decisions. A visualization technique based on a non-linear projection onto a 1D self-organizing map is described and examples are shown. The SOM visualization technique is fast, theoretically attractive, and has properties which compliment those of projection-pursuit or other linear techniques. It may be of particular value in calling attention to specific regions in a multi-parameter image where the component images should be examined in detail.

  2. Refining of image using self-organizing map with clustering

    NASA Astrophysics Data System (ADS)

    Dahiya, Neeraj; Dalal, Surjeet; Tanwar, Gundeep

    2016-03-01

    Self Organization Map(SOM) is an automatic tool in data analysis in data mining,it is used to explore the multi-dimentional data which simplifies complexity and produce meaningful relation with each other or high dimentional into low dimentional .the powerful method of SOM i.e learning method results excellent performance .the SOM algorithum have various steps from starting stage to the final neuron and their weight updation and modification, these procedure resultant a lot of compplexity accoording to the parameters on the basis of experiments .this paper will compare and discuss various papameters and their result or factors that can improve and refine the image through varius process of SOM.

  3. Self-organized escape of oscillator chains in nonlinear potentials.

    PubMed

    Hennig, D; Fugmann, S; Schimansky-Geier, L; Hänggi, P

    2007-10-01

    We present the noise-free escape of a chain of linearly interacting units from a metastable state over a cubic on-site potential barrier. The underlying dynamics is conservative and purely deterministic. The mutual interplay between nonlinearity and harmonic interactions causes an initially uniform lattice state to become unstable, leading to an energy redistribution with strong localization. As a result, a spontaneously emerging localized mode grows into a critical nucleus. By surpassing this transition state, the nonlinear chain manages a self-organized, deterministic barrier crossing. Most strikingly, these noise-free, collective nonlinear escape events proceed generally by far faster than transitions assisted by thermal noise when the ratio between the average energy supplied per unit in the chain and the potential barrier energy assumes small values. PMID:17994939

  4. Modeling financial markets by self-organized criticality

    NASA Astrophysics Data System (ADS)

    Biondo, Alessio Emanuele; Pluchino, Alessandro; Rapisarda, Andrea

    2015-10-01

    We present a financial market model, characterized by self-organized criticality, that is able to generate endogenously a realistic price dynamics and to reproduce well-known stylized facts. We consider a community of heterogeneous traders, composed by chartists and fundamentalists, and focus on the role of informative pressure on market participants, showing how the spreading of information, based on a realistic imitative behavior, drives contagion and causes market fragility. In this model imitation is not intended as a change in the agent's group of origin, but is referred only to the price formation process. We introduce in the community also a variable number of random traders in order to study their possible beneficial role in stabilizing the market, as found in other studies. Finally, we also suggest some counterintuitive policy strategies able to dampen fluctuations by means of a partial reduction of information.

  5. Topology-based clustering using polar self-organizing map.

    PubMed

    Xu, Lu; Chow, Tommy W S; Ma, Eden W M

    2015-04-01

    Cluster analysis of unlabeled data sets has been recognized as a key research topic in varieties of fields. In many practical cases, no a priori knowledge is specified, for example, the number of clusters is unknown. In this paper, grid clustering based on the polar self-organizing map (PolSOM) is developed to automatically identify the optimal number of partitions. The data topology consisting of both the distance and density is exploited in the grid clustering. The proposed clustering method also provides a visual representation as PolSOM allows the characteristics of clusters to be presented as a 2-D polar map in terms of the data feature and value. Experimental studies on synthetic and real data sets demonstrate that the proposed algorithm provides higher clustering accuracy and lower computational cost compared with six conventional methods. PMID:25312942

  6. Bregman divergences for growing hierarchical self-organizing networks.

    PubMed

    López-Rubio, Ezequiel; Palomo, Esteban José; Domínguez, Enrique

    2014-06-01

    Growing hierarchical self-organizing models are characterized by the flexibility of their structure, which can easily accommodate for complex input datasets. However, most proposals use the Euclidean distance as the only error measure. Here we propose a way to introduce Bregman divergences in these models, which is based on stochastic approximation principles, so that more general distortion measures can be employed. A procedure is derived to compare the performance of networks using different divergences. Moreover, a probabilistic interpretation of the model is provided, which enables its use as a Bayesian classifier. Experimental results are presented for classification and data visualization applications, which show the advantages of these divergences with respect to the classical Euclidean distance. PMID:24694171

  7. Self-organized criticality and 1/f noise in traffic

    SciTech Connect

    Paczuski, M.; Nagel, K.

    1995-12-31

    Phantom traffic jams may emerge ``out of nowhere`` from small fluctuations rather than being triggered by large, exceptional events. We show how phantom jams arise in a model of single lane highway traffic, which mimics human driving behavior. Surprisingly, the optimal state of highest efficiency, with the largest throughput, is a critical state with traffic jams of all sizes. We demonstrate that open systems self-organize to the most efficient state. In the model we study, this critical state is a percolation transition for the phantom traffic jams. At criticality, the individual jams have a complicated fractal structure where cars follow an intermittent stop and go pattern. We analytically derive the form of the corresponding power spectrum to be 1/f{sup {alpha}} with {alpha} = 1 exactly. This theoretical prediction agrees with our numerical simulations and with observations of 1/f noise in real traffic.

  8. Experimental econophysics: Complexity, self-organization, and emergent properties

    NASA Astrophysics Data System (ADS)

    Huang, J. P.

    2015-03-01

    Experimental econophysics is concerned with statistical physics of humans in the laboratory, and it is based on controlled human experiments developed by physicists to study some problems related to economics or finance. It relies on controlled human experiments in the laboratory together with agent-based modeling (for computer simulations and/or analytical theory), with an attempt to reveal the general cause-effect relationship between specific conditions and emergent properties of real economic/financial markets (a kind of complex adaptive systems). Here I review the latest progress in the field, namely, stylized facts, herd behavior, contrarian behavior, spontaneous cooperation, partial information, and risk management. Also, I highlight the connections between such progress and other topics of traditional statistical physics. The main theme of the review is to show diverse emergent properties of the laboratory markets, originating from self-organization due to the nonlinear interactions among heterogeneous humans or agents (complexity).

  9. Self-Organizing Maps-based ocean currents forecasting system

    NASA Astrophysics Data System (ADS)

    Vilibić, Ivica; Šepić, Jadranka; Mihanović, Hrvoje; Kalinić, Hrvoje; Cosoli, Simone; Janeković, Ivica; Žagar, Nedjeljka; Jesenko, Blaž; Tudor, Martina; Dadić, Vlado; Ivanković, Damir

    2016-03-01

    An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.

  10. Self-organization: the basic principle of neural functions.

    PubMed

    Szentágothai, J

    1993-06-01

    Recent neurophysiological observations are giving rise to the expectation that in the near future genuine biological experiments may contribute more than will premature speculations to the understanding of global and cognitive functions. The classical reflex principle--as the basis of neural functions--has to yield to new ideas, like autopoiesis and/or self-organization, as the basic paradigm in the framework of which the essence of the neural can be better understood. Neural activity starts in the very earliest stages of development well before receptors and afferent input become functional. Under suitable conditions, both in nervous tissue cultures and in embryonic tissue recombination experiments, the conditions of such initial autopoietic activity can be studied. This paper tries to generalize this elementary concept for various neural centers, notably for the spinal segmental apparatus and the cerebral cortex. PMID:8236059

  11. Self-organization of protrusions and polarity during eukaryotic chemotaxis

    PubMed Central

    Graziano, Brian R.; Weiner, Orion D.

    2014-01-01

    Many eukaryotic cells regulate their polarity and motility in response to external chemical cues. While we know many of the linear connections that link receptors with downstream actin polymerization events, we have a much murkier understanding of the higher order positive and negative feedback loops that organize these processes in space and time. Importantly, physical forces and actin polymerization events don't simply act downstream of chemotactic inputs but are rather involved in a web of reciprocal interactions with signaling components to generate self-organizing pseudopods and cell polarity. Here we focus on recent progress and open questions in the field, including the basic unit of actin organization, how cells regulate the number and speed of protrusions, and 2D vs. 3D migration. PMID:24998184

  12. Self-organized architectures from assorted DNA-framed nanoparticles.

    PubMed

    Liu, Wenyan; Halverson, Jonathan; Tian, Ye; Tkachenko, Alexei V; Gang, Oleg

    2016-09-01

    The science of self-assembly has undergone a radical shift from asking questions about why individual components self-organize into ordered structures, to manipulating the resultant order. However, the quest for far-reaching nanomanufacturing requires addressing an even more challenging question: how to form nanoparticle (NP) structures with designed architectures without explicitly prescribing particle positions. Here we report an assembly concept in which building instructions are embedded into NPs via DNA frames. The integration of NPs and DNA origami frames enables the fabrication of NPs with designed anisotropic and selective interactions. Using a pre-defined set of different DNA-framed NPs, we show it is possible to design diverse planar architectures, which include periodic structures and shaped meso-objects that spontaneously emerge on mixing of the different topological types of NP. Even objects of non-trivial shapes, such as a nanoscale model of Leonardo da Vinci's Vitruvian Man, can be self-assembled successfully. PMID:27554413

  13. Emergence, self-organization and morphogenesis in biological structures.

    PubMed

    Dobrescu, R; Purcarea, V I

    2011-01-01

    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. PMID:21505578

  14. Introduction: Self-organization in nonequilibrium chemical systems.

    PubMed

    Epstein, Irving R; Pojman, John A; Steinbock, Oliver

    2006-09-01

    The field of self-organization in nonequilibrium chemical systems comprises the study of dynamical phenomena in chemically reacting systems far from equilibrium. Systematic exploration of this area began with investigations of the temporal behavior of the Belousov-Zhabotinsky oscillating reaction, discovered accidentally in the former Soviet Union in the 1950s. The field soon advanced into chemical waves in excitable media and propagating fronts. With the systematic design of oscillating reactions in the 1980s and the discovery of Turing patterns in the 1990s, the scope of these studies expanded dramatically. The articles in this Focus Issue provide an overview of the development and current state of the field. PMID:17014235

  15. Self-organized global control of carbon emissions

    NASA Astrophysics Data System (ADS)

    Zhao, Zhenyuan; Fenn, Daniel J.; Hui, Pak Ming; Johnson, Neil F.

    2010-09-01

    There is much disagreement concerning how best to control global carbon emissions. We explore quantitatively how different control schemes affect the collective emission dynamics of a population of emitting entities. We uncover a complex trade-off which arises between average emissions (affecting the global climate), peak pollution levels (affecting citizens’ everyday health), industrial efficiency (affecting the nation’s economy), frequency of institutional intervention (affecting governmental costs), common information (affecting trading behavior) and market volatility (affecting financial stability). Our findings predict that a self-organized free-market approach at the level of a sector, state, country or continent can provide better control than a top-down regulated scheme in terms of market volatility and monthly pollution peaks. The control of volatility also has important implications for any future derivative carbon emissions market.

  16. Self-organization of dynein motors generates meiotic nuclear oscillations.

    PubMed

    Vogel, Sven K; Pavin, Nenad; Maghelli, Nicola; Jülicher, Frank; Tolić-Nørrelykke, Iva M

    2009-04-21

    Meiotic nuclear oscillations in the fission yeast Schizosaccharomyces pombe are crucial for proper chromosome pairing and recombination. We report a mechanism of these oscillations on the basis of collective behavior of dynein motors linking the cell cortex and dynamic microtubules that extend from the spindle pole body in opposite directions. By combining quantitative live cell imaging and laser ablation with a theoretical description, we show that dynein dynamically redistributes in the cell in response to load forces, resulting in more dynein attached to the leading than to the trailing microtubules. The redistribution of motors introduces an asymmetry of motor forces pulling in opposite directions, leading to the generation of oscillations. Our work provides the first direct in vivo observation of self-organized dynamic dynein distributions, which, owing to the intrinsic motor properties, generate regular large-scale movements in the cell. PMID:19385717

  17. Self Organized Criticality as a new paradigm of sleep regulation

    NASA Astrophysics Data System (ADS)

    Ivanov, Plamen Ch.; Bartsch, Ronny P.

    2012-02-01

    Humans and animals often exhibit brief awakenings from sleep (arousals), which are traditionally viewed as random disruptions of sleep caused by external stimuli or pathologic perturbations. However, our recent findings show that arousals exhibit complex temporal organization and scale-invariant behavior, characterized by a power-law probability distribution for their durations, while sleep stage durations exhibit exponential behavior. The co-existence of both scale-invariant and exponential processes generated by a single regulatory mechanism has not been observed in physiological systems until now. Such co-existence resembles the dynamical features of non-equilibrium systems exhibiting self-organized criticality (SOC). Our empirical analysis and modeling approaches based on modern concepts from statistical physics indicate that arousals are an integral part of sleep regulation and may be necessary to maintain and regulate healthy sleep by releasing accumulated excitations in the regulatory neuronal networks, following a SOC-type temporal organization.

  18. Self-organized plasmonic metasurfaces for all-optical modulation

    NASA Astrophysics Data System (ADS)

    Della Valle, G.; Polli, D.; Biagioni, P.; Martella, C.; Giordano, M. C.; Finazzi, M.; Longhi, S.; Duò, L.; Cerullo, G.; Buatier de Mongeot, F.

    2015-06-01

    We experimentally demonstrate a self-organized metasurface with a polarization dependent transmittance that can be dynamically controlled by optical means. The configuration consists of tightly packed plasmonic nanowires with a large dispersion of width and height produced by the defocused ion-beam sputtering of a thin gold film supported on a silica glass. Our results are quantitatively interpreted according to a theoretical model based on the thermomodulational nonlinearity of gold and a finite-element numerical analysis of the absorption and scattering cross-sections of the nanowires. We found that the polarization sensitivity of the metasurface can be strongly enhanced by pumping with ultrashort laser pulses, leading to potential applications in ultrafast all-optical modulation and switching of light.

  19. Self-organization approach for THz polaritonic metamaterials

    SciTech Connect

    Reyes-Coronado, A.; Acosta, M.F.; Merino, R.I.; Orera,, V.M.; Kenanakis, G.; Katsarakis, n.; Kafesaki, M.; Mavidis, Ch.; Garcia de Abajo, J.; Economou, E.N.; Soukoulis, Costas M.

    2012-06-15

    In this paper we discuss the fabrication and the electromagnetic (EM) characterization of anisotropic eutectic metamaterials, consisting of cylindrical polaritonic LiF rods embedded in either KCl or NaCl polaritonic host. The fabrication was performed using the eutectics directional solidification self-organization approach. For the EM characterization the specular reflectance at far infrared, between 3 THz and 11 THz, was measured and also calculated by numerically solving Maxwell equations, obtaining good agreement between experimental and calculated spectra. Applying an effective medium approach to describe the response of our samples, we predicted a range of frequencies in which most of our systems behave as homogeneous anisotropic media with a hyperbolic dispersion relation, opening thus possibilities for using them in negative refractive index and imaging applications at THz range.

  20. Dynamic speckle image segmentation using self-organizing maps

    NASA Astrophysics Data System (ADS)

    Pra, Ana L. Dai; Meschino, Gustavo J.; Guzmán, Marcelo N.; Scandurra, Adriana G.; González, Mariela A.; Weber, Christian; Trivi, Marcelo; Rabal, Héctor; Passoni, Lucía I.

    2016-08-01

    The aim of this work is to build a computational model able to automatically identify, after training, dynamic speckle pattern regions with similar properties. The process is carried out using a set of descriptors applied to the intensity variations with time in every pixel of a speckle image sequence. An image obtained by projecting a self-organized map is converted into regions of similar activity that can be easily distinguished. We propose a general procedure that could be applied to numerous situations. As examples we show different situations: (a) an activity test in a simplified situation; (b) a non-biological example and (c) biological active specimens. The results obtained are encouraging; they significantly improve upon those obtained using a single descriptor and will eventually permit automatic quantitative assessment.

  1. Bending induced self-organized switchable gratings on polymeric substrates.

    PubMed

    Parra-Barranco, Julian; Oliva-Ramirez, Manuel; Gonzalez-Garcia, Lola; Alcaire, Maria; Macias-Montero, Manuel; Borras, Ana; Frutos, Fabian; Gonzalez-Elipe, Agustin R; Barranco, Angel

    2014-08-13

    We present a straightforward procedure of self-surface patterning with potential applications as large area gratings, invisible labeling, optomechanical transducers, or smart windows. The methodology is based in the formation of parallel micrometric crack patterns when polydimethylsiloxane foils coated with tilted nanocolumnar SiO2 thin films are manually bent. The SiO2 thin films are grown by glancing angle deposition at room temperature. The results indicate that crack spacing is controlled by the film nanostructure independently of the film thickness and bending curvature. They also show that the in-plane microstructural anisotropy of the SiO2 films due to column association perpendicular to the growth direction determines the anisotropic formation of parallel cracks along two main axes. These self-organized patterned foils are completely transparent and work as customized reversible diffraction gratings under mechanical activation. PMID:25007108

  2. Pathways to self-organization: Crystallization via nucleation and growth.

    PubMed

    Jungblut, S; Dellago, C

    2016-08-01

    Crystallization, a prototypical self-organization process during which a disordered state spontaneously transforms into a crystal characterized by a regular arrangement of its building blocks, usually proceeds by nucleation and growth. In the initial stages of the transformation, a localized nucleus of the new phase forms in the old one due to a random fluctuation. Most of these nuclei disappear after a short time, but rarely a crystalline embryo may reach a critical size after which further growth becomes thermodynamically favorable and the entire system is converted into the new phase. In this article, we will discuss several theoretical concepts and computational methods to study crystallization. More specifically, we will address the rare event problem arising in the simulation of nucleation processes and explain how to calculate nucleation rates accurately. Particular attention is directed towards discussing statistical tools to analyze crystallization trajectories and identify the transition mechanism. PMID:27498980

  3. A self-organized critical model for evolution

    SciTech Connect

    Flyvbjerg, H.; Bak, P.; Jensen, M.H.; Sneppen, K.

    1996-01-01

    A simple mathematical model of biological macroevolution is presented. It describes an ecology of adapting, interacting species. Species evolve to maximize their individual fitness in their environment. The environment of any given species is affected by other evolving species; hence it is not constant in time. The ecology evolves to a ``self-organized critical`` state where periods of stasis alternate with avalanches of causally connected evolutionary changes. This characteristic intermittent behaviour of natural history, known as ``punctuated equilibrium,`` thus finds a theoretical explanation as a selforganized critical phenomenon. In particular, large bursts of apparently simultaneous evolutionary activity require no external cause. They occur as the less frequent result of the very same dynamics that governs the more frequent small-scale evolutionary activity. Our results are compared with data from the fossil record collected by J. Sepkoski, Jr., and others.

  4. Flexible flapping wings with self-organized microwrinkles.

    PubMed

    Tanaka, Hiroto; Okada, Hiroyuki; Shimasue, Yosuke; Liu, Hao

    2015-08-01

    Bio-inspired flapping wings with a wrinkled wing membrane were designed and fabricated. The wings consist of carbon fibre-reinforced plastic frames and a polymer film with microscale wrinkles inspired by bird feathers and the corrugations of insect wings. The flexural and tensile stiffness of the wrinkled film can be controlled by modifying the orientations and waveforms of the wrinkles, thereby expanding the design space of flexible wings for micro flapping-wing aerial robots. A self-organization phenomenon was exploited in the fabrication of the microwrinkles such that microscale wrinkles spanning a broad wing area were spontaneously created. The wavy shape of these self-organized wrinkles was used as a mould, and a Parylene film was deposited onto the mould to form a wrinkled wing film. The effect of the waveforms of the wrinkles on the film stiffness was investigated theoretically, computationally and experimentally. Compared with a flat film, the flexural stiffness was increased by two orders of magnitude, and the tensile stiffness was reduced by two orders of magnitude. To demonstrate the effect of the wrinkles on the actual deformation of the flapping wings and the resulting aerodynamic forces, the fabricated wrinkled wings were tested using a tethered electric flapping mechanism. Chordwise unidirectional wrinkles were found to prevent fluttering near the trailing edge and to produce a greater aerodynamic lift compared with a flat wing or a wing with spanwise wrinkles. Our results suggest that the fine stiffness control of the wing film that can be achieved by tuning the microwrinkles can improve the aerodynamic performance of future flapping-wing aerial robots. PMID:26119657

  5. Self-organization of convective clouds and extreme precipitation

    NASA Astrophysics Data System (ADS)

    Moseley, Christopher; Hohenegger, Cathy; Berg, Peter; Haerter, Jan

    2016-04-01

    The response of convective-type cloud and associated precipitation rates to temperature changes is far from clear. Observational studies have identified a strong sensitivity of convective precipitation extreme intensities to surface temperature --- even exceeding the thermodynamic constraint through the Clausius-Clapayron relationship (Berg et al., Nature Geoscience, 2013). It has been speculated that such strong changes may result from dynamical changes of the atmospheric flow, whereby thermodynamic constraints could be bypassed. Indeed, convective cloud has long been suspected to self-organize or even aggregate, but whether and how such structural transitions relate to modified precipitation rates is largely unexplored. Large-eddy simulations (LES) are a versatile tool suited for high-resolution numerical experiments of the convective cloud field. At horizontal resolutions on the scale of 100 m, they now allow 3d simulations of the moist atmospheric dynamics within domains of hundreds of kilometers laterally. Such simulations grant access to virtually all relevant observables. Using LES along with precipitation cell tracking, we isolate the effect of self-organization, quantify structural changes within the cloud field as a function of time and extract mechanisms that lead to increased convective precipitation intensities. We make contact to classical measures of large-scale convective potential, e.g. CAPE, CIN and moisture convergence, and contrast cloud-scale feedbacks to those previously implicated in quasi-equilibrium, large-scale, aggregation processes. Together, our results suggest that the build-up of extreme precipitation must ultimately be understood within a non-equilibrium framework. We relate our findings to current developments in global and regional climate modeling.

  6. Traffic Instabilities in Self-Organized Pedestrian Crowds

    PubMed Central

    Moussaïd, Mehdi; Guillot, Elsa G.; Moreau, Mathieu; Fehrenbach, Jérôme; Chabiron, Olivier; Lemercier, Samuel; Pettré, Julien; Appert-Rolland, Cécile; Degond, Pierre; Theraulaz, Guy

    2012-01-01

    In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds. PMID:22457615

  7. Xtoys: Cellular automata on xwindows

    SciTech Connect

    Creutz, M.

    1995-08-15

    Xtoys is a collection of xwindow programs for demonstrating simulations of various statistical models. Included are xising, for the two dimensional Ising model, xpotts, for the q-state Potts model, xautomalab, for a fairly general class of totalistic cellular automata, xsand, for the Bak-Tang-Wiesenfield model of self organized criticality, and xfires, a simple forest fire simulation. The programs should compile on any machine supporting xwindows.

  8. Self-organized patchiness facilitates survival in a cooperatively growing Bacillus subtilis population.

    PubMed

    Ratzke, Christoph; Gore, Jeff

    2016-01-01

    Ecosystems are highly structured. Organisms are not randomly distributed but can be found in spatial aggregates at many scales, leading to spatial heterogeneity or even regular patterns(1). The widespread occurrence of these aggregates in many different ecosystems suggests that generic factors intrinsic to the populations-such as interactions between the organisms-play a major role in their emergence(1,2). Beyond the emergence of spatial patchiness, its functional consequences remain unclear. Here we show in Bacillus subtilis that cooperative interactions in a spatial environment are sufficient to form self-organized patches. These patches allow for survival even when the microbe density is too low to sustain growth in a well-mixed environment. Decreasing cell mobility leads to more compact patches that enhance this survival advantage but also reduce the overall growth. Our results highlight that even populations lacking specific group-forming mechanisms can nonetheless form spatial patterns that allow for group survival in challenging environments. PMID:27572641

  9. Self-organized criticality in proteins: Hydropathic roughening profiles of G-protein-coupled receptors

    NASA Astrophysics Data System (ADS)

    Phillips, J. C.

    2013-03-01

    Proteins appear to be the most dramatic natural example of self-organized criticality (SOC), a concept that explains many otherwise apparently unlikely phenomena. Protein conformational functionality is often dominated by long-range hydrophobic or hydrophilic interactions which both drive protein compaction and mediate protein-protein interactions. Superfamily transmembrane G-protein-coupled receptors (GPCRs) are the largest family of proteins in the human genome; their amino acid sequences form the largest database for protein-membrane interactions. While there are now structural data on the heptad transmembrane structures of representatives of several heptad families, here we show how fresh insights into global and some local chemical trends in GPCR properties can be obtained accurately from sequences alone, especially by algebraically separating the extracellular and cytoplasmic loops from transmembrane segments. The global mediation of long-range water-protein interactions occurs in conjunction with modulation of these interactions by roughened interfaces. Hydropathic roughening profiles are defined here solely in terms of amino acid sequences, and knowledge of protein coordinates is not required. Roughening profiles both for GPCR and some simpler protein families display accurate and transparent connections to protein functionality, and identify natural length scales for protein functionality.

  10. Self-organization of chaos in mythology from a scientific point of view

    NASA Astrophysics Data System (ADS)

    Melker, Alexander I.

    2007-04-01

    In this contribution ancient Greek myths describing world's creation are analyzed as if they were a scientific paper. The 'paper' divided into the following parts: initial and boundary conditions, self-organization of chaos, world lines of self-organization, conclusion. It is shown that the self-organization of chaos consists of several stages during which two motive forces (attractive and repulsive) are generated, and totally disordered chaos transforms into partially ordered. It is found that there are five world lines of self-organization: water, light, cosmos-weather, water-fire, and State evolution.

  11. Thermodynamic and dynamic behaviors of self-organizing polymeric systems

    NASA Astrophysics Data System (ADS)

    Zhao, Yiqiang

    Two topics of self-organizing polymeric systems are explored in this work: thermodynamic and dynamic properties of liquid crystal polymers in solutions and rheological behaviors of self-organizing gels. For dilute nematic solutions of end-on side-chain liquid crystal polysiloxanes (SCLCP) dissolved in 5CB, the chain anisotropies R∥/R ⊥, obtained from electrorheological(ER) analysis based on the Brochard model, are consistent with independent measurements of Rg∥/R g⊥ via small-angle neutron scattering (SANS), which unambiguously demonstrating a slightly prolate SCLCP chain conformation. Dissolution of this prolate SCLCP in flow-aligning 5CB produces a tumbling flow, clearly indicating a discrepancy with the Brochard hydrodynamic theory which predicts such a transition only for oblate conformation. A numerical comparison using a modified version of the Brochard model leads to improved self-consistent agreement between SANS, ER and shear transient experiments. The molecular weight dependence of the chain conformational relaxation time it indicates an extended SCLCP chain conformation in 5CB. SANS analysis suggests that the SCLCP conformation is sensitive to the solvent interaction, i.e. a more extended conformation is observed in isotropic acetone-d6 than in nematic 5CB. A SANS conformational study of SCLCCs with methoxyphenylbenzoate mesogenic side group in CDC13 demonstrates that the form factor of a single comb-like SCLCP chain is well described by a wormlike chain model with finite cross-sectional thickness over the entire q range, taking into account the molecular weight polydispersity. Consistent with measurement of a large R g from low q analysis, the resulting persistence length lp is in the range 28˜32 A, substantially larger than that of unsubstituted polydimethylsiloxane (PDMS) chain (l p =5.8 A), which suggests a relatively rigid SCLCP chain due to the influence of densely attached mesogenic groups. For nematic mixtures of copolysiloxane SCLCP in

  12. Adult Compacts.

    ERIC Educational Resources Information Center

    Further Education Unit, London (England).

    This bulletin focuses on adult compacts, three-way agreements among employers, potential employees, and trainers to provide the right kind of quality training to meet the employers' requirements. Part 1 is an executive summary of a report of the Adult Compacts Project, which studied three adult compacts in Birmingham and Loughborough, England, and…

  13. Self-Organized Maps in Scientific Data Analysis

    NASA Astrophysics Data System (ADS)

    Soo Hoo, J.; Pollock, C. J.; Jahn, J.; Lim, D.; Weatherwax, A. T.

    2008-12-01

    The Thermal Ion Dynamics Experiment (TIDE) investigates low energy (0.1 - 450 eV) plasma in the Earth's magnetosphere, especially in the polar regions. It is part of NASA's larger Polar mission. After six months in orbit it became necessary for TIDE to operate in a mode that did not directly provide mass discrimination. However, in this mode, energy-time and spin-time spectrograms of differential ion flux were routinely available. The number of peaks in the energy-time spectrograms relates to the composition of the plasma. Kohonen self-organized maps (SOMs,) a type of neural network, are particularly suited to this problem due to the amount of data that needs to be analyzed and the algorithm's ability to find patterns within data. The algorithm leads to clustering of similar data points on the map. Ultimately, the location of the input data point on the map allows for determination of how many peaks the data point contains, and thus the composition of the plasma at that time. The SOM correctly classified 99% of the input data, making it a viable solution to the problem. Further research is planned, namely the possibility of extending this concept to investigate energetic neural atom (ENA) images in order to determine the source of these atoms.

  14. Morphogenesis as a macroscopic self-organizing process.

    PubMed

    Beloussov, Lev V

    2012-09-01

    We start from reviewing different epistemological constructions used for explaining morphogenesis. Among them, we explore the explanatory power of a law-centered approach which includes top-down causation and the basic concepts of a self-organization theory. Within such a framework, we discuss the morphomechanical models based upon the presumption of feedbacks between mechanical stresses imposed onto a given embryo part from outside and those generated within the latter as a kind of active response. A number of elementary morphogenetic events demonstrating that these feedbacks are directed towards hyper-restoration (restoration with an overshoot) of the initial state of mechanical stresses are described. Moreover, we show that these reactions are bound together into the larger scale feedbacks. That permits to suggest a reconstruction of morphogenetic successions in early Metazoan development concentrated around two main archetypes distinguished by the blastopores geometry. The perspectives of applying the same approach to cell differentiation are outlined. By discussing the problem of positional information we suggest that the developmental pathway of a given embryo part depends upon its preceded deformations and the corresponding mechanical stresses rather than upon its static position at any moment of development. PMID:22609495

  15. Identifying individual sperm whales acoustically using self-organizing maps

    NASA Astrophysics Data System (ADS)

    Ioup, Juliette W.; Ioup, George E.

    2005-09-01

    The Littoral Acoustic Demonstration Center (LADC) is a consortium at Stennis Space Center comprising the University of New Orleans, the University of Southern Mississippi, the Naval Research Laboratory, and the University of Louisiana at Lafayette. LADC deployed three Environmental Acoustic Recording System (EARS) buoys in the northern Gulf of Mexico during the summer of 2001 to study ambient noise and marine mammals. Each LADC EARS was an autonomous, self-recording buoy capable of 36 days of continuous recording of a single channel at an 11.7-kHz sampling rate (bandwidth to 5859 Hz). The hydrophone selected for this analysis was approximately 50 m from the bottom in a water depth of 800 m on the continental slope off the Mississippi River delta. This paper contains recent analysis results for sperm whale codas recorded during a 3-min period. Results are presented for the identification of individual sperm whales from their codas, using the acoustic properties of the clicks within each coda. The recorded time series, the Fourier transform magnitude, and the wavelet transform coefficients are each used separately with a self-organizing map procedure for 43 codas. All show the codas as coming from four or five individual whales. [Research supported by ONR.

  16. Self-organized optical device driven by motor proteins

    PubMed Central

    Aoyama, Susumu; Shimoike, Masahiko; Hiratsuka, Yuichi

    2013-01-01

    Protein molecules produce diverse functions according to their combination and arrangement as is evident in a living cell. Therefore, they have a great potential for application in future devices. However, it is currently very difficult to construct systems in which a large number of different protein molecules work cooperatively. As an approach to this challenge, we arranged protein molecules in artificial microstructures and assembled an optical device inspired by a molecular system of a fish melanophore. We prepared arrays of cell-like microchambers, each of which contained a scaffold of microtubule seeds at the center. By polymerizing tubulin from the fixed microtubule seeds, we obtained radially arranged microtubules in the chambers. We subsequently prepared pigment granules associated with dynein motors and attached them to the radial microtubule arrays, which made a melanophore-like system. When ATP was added to the system, the color patterns of the chamber successfully changed, due to active transportation of pigments. Furthermore, as an application of the system, image formation on the array of the optical units was performed. This study demonstrates that a properly designed microstructure facilitates arrangement and self-organization of molecules and enables assembly of functional molecular systems. PMID:24065817

  17. Self-Organized Criticality in Developing Neuronal Networks

    PubMed Central

    Tetzlaff, Christian; Okujeni, Samora; Egert, Ulrich; Wörgötter, Florentin; Butz, Markus

    2010-01-01

    Recently evidence has accumulated that many neural networks exhibit self-organized criticality. In this state, activity is similar across temporal scales and this is beneficial with respect to information flow. If subcritical, activity can die out, if supercritical epileptiform patterns may occur. Little is known about how developing networks will reach and stabilize criticality. Here we monitor the development between 13 and 95 days in vitro (DIV) of cortical cell cultures (n = 20) and find four different phases, related to their morphological maturation: An initial low-activity state (≈19 DIV) is followed by a supercritical (≈20 DIV) and then a subcritical one (≈36 DIV) until the network finally reaches stable criticality (≈58 DIV). Using network modeling and mathematical analysis we describe the dynamics of the emergent connectivity in such developing systems. Based on physiological observations, the synaptic development in the model is determined by the drive of the neurons to adjust their connectivity for reaching on average firing rate homeostasis. We predict a specific time course for the maturation of inhibition, with strong onset and delayed pruning, and that total synaptic connectivity should be strongly linked to the relative levels of excitation and inhibition. These results demonstrate that the interplay between activity and connectivity guides developing networks into criticality suggesting that this may be a generic and stable state of many networks in vivo and in vitro. PMID:21152008

  18. Fast CEUS image segmentation based on self organizing maps

    NASA Astrophysics Data System (ADS)

    Paire, Julie; Sauvage, Vincent; Albouy-Kissi, Adelaïde; Ladam Marcus, Viviane; Marcus, Claude; Hoeffel, Christine

    2014-03-01

    Contrast-enhanced ultrasound (CEUS) has recently become an important technology for lesion detection and characterization. CEUS is used to investigate the perfusion kinetics in tissue over time, which relates to tissue vascularization. In this paper, we present an interactive segmentation method based on the neural networks, which enables to segment malignant tissue over CEUS sequences. We use Self-Organizing-Maps (SOM), an unsupervised neural network, to project high dimensional data to low dimensional space, named a map of neurons. The algorithm gathers the observations in clusters, respecting the topology of the observations space. This means that a notion of neighborhood between classes is defined. Adjacent observations in variables space belong to the same class or related classes after classification. Thanks to this neighborhood conservation property and associated with suitable feature extraction, this map provides user friendly segmentation tool. It will assist the expert in tumor segmentation with fast and easy intervention. We implement SOM on a Graphics Processing Unit (GPU) to accelerate treatment. This allows a greater number of iterations and the learning process to converge more precisely. We get a better quality of learning so a better classification. Our approach allows us to identify and delineate lesions accurately. Our results show that this method improves markedly the recognition of liver lesions and opens the way for future precise quantification of contrast enhancement.

  19. Self-organized task assignment for distributed sensors

    NASA Astrophysics Data System (ADS)

    Molnar, Peter; Lockett, Emily J.; Kaplan, Lance M.

    2000-10-01

    A new paradigm in ground surveillance consists of swarms of autonomous internetted sensors that can be used for target localization and environmental monitoring. The individual component is an inexpensive device containing multiple sensor types, a processor and wireless communication hardware. Scattered over a certain region, these devices are able to detect the direction or proximity of targets. One of the most limiting factors of the devices is the battery supply. In order to conserve power, these units should be able to adjust their activities to the current situations. Energy consuming signal processing should only be performed if the quality of the raw sensor data promises a significant improvement to the localization results. We propose a self-organized control system that allows the devices to select the algorithm complexity which balances the requirements for good localization performance and energy conservation. The devices make their selection autonomously, based on their own sensor data, information that they receive from other devices in the region, and the amount of energy they have left. The capability of this system will be demonstrated via computer simulations.

  20. Self-organized tubular structures as platforms for quantum dots.

    PubMed

    Makki, Rabih; Ji, Xin; Mattoussi, Hedi; Steinbock, Oliver

    2014-04-30

    The combination of top-down and bottom-up approaches offers great opportunities for the production of complex materials and devices. We demonstrate this approach by incorporating luminescent CdSe-ZnS nanoparticles into macroscopic tube structures that form as the result of externally controlled self-organization. The 1-2 mm wide hollow tubes consist of silica-supported zinc oxide/hydroxide and are formed by controlled injection of aqueous zinc sulfate into a sodium silicate solution. The primary growth region at the top of the tube is pinned to a robotic arm that moves upward at constant speed. Dispersed within the injected zinc solution are 3.4 nm CdSe-ZnS quantum dots (QDs) capped by DHLA-PEG-OCH3 ligands. Fluorescence measurements of the washed and dried tubes reveal the presence of trapped QDs at an estimated number density of 10(10) QDs per millimeter of tube length. The successful inclusion of the nanoparticles is further supported by electron microscopy and energy dispersive X-ray spectroscopy, with the latter suggesting a nearly homogeneous QD distribution across the tube wall. Exposure of the samples to copper sulfate solution induces quenching of about 90% of the tubes' fluorescence intensity. This quenching shows that the large majority of the QDs is chemically accessible within the microporous, about 15-μm-wide tube wall. We suggest possible applications of such QD-hosting tube systems as convenient sensors in microfluidic and related applications. PMID:24702437

  1. Structure of self-organized multilayer nanoparticles for drug delivery.

    PubMed

    Gerelli, Y; Barbieri, S; Di Bari, M T; Deriu, A; Cantù, L; Brocca, P; Sonvico, F; Colombo, P; May, R; Motta, S

    2008-10-21

    The combined use of cryo-TEM, dynamic light scattering, and small-angle X-ray and neutron scattering techniques allows a detailed structural model of complex pharmaceutical preparations of soybean lecithin/chitosan nanoparticles used as drug vectors to be worked out. Charge-driven self-organization of the lipid(-)/polysaccharide(+) vesicles occurs during rapid injection, under mechanical stirring, of an ethanol solution of soybean lecithin into a chitosan aqueous solution. We conclude that beyond the charge inversion region of the phase diagram, i.e., entering the redissolution region, the initial stages of particle formation are likely to be affected by a re-entrant condensation effect at the nanoscale. This behavior resembles that at the mesoscale which is well-known for polyion/amphiphile systems. Close to the boundary of the charge inversion region, nanoparticle formation occurs under a maximum condensation condition at the nanoscale and the complexation-aggregation process is driven toward a maximum multilamellarity. Interestingly, the formulation that maximizes vesicle multilamellarity corresponds to that displaying the highest drug loading efficiency. PMID:18816016

  2. Spontaneous neuronal activity as a self-organized critical phenomenon

    NASA Astrophysics Data System (ADS)

    de Arcangelis, L.; Herrmann, H. J.

    2013-01-01

    Neuronal avalanches are a novel mode of activity in neuronal networks, experimentally found in vitro and in vivo, and exhibit a robust critical behaviour. Avalanche activity can be modelled within the self-organized criticality framework, including threshold firing, refractory period and activity-dependent synaptic plasticity. The size and duration distributions confirm that the system acts in a critical state, whose scaling behaviour is very robust. Next, we discuss the temporal organization of neuronal avalanches. This is given by the alternation between states of high and low activity, named up and down states, leading to a balance between excitation and inhibition controlled by a single parameter. During these periods both the single neuron state and the network excitability level, keeping memory of past activity, are tuned by homeostatic mechanisms. Finally, we verify if a system with no characteristic response can ever learn in a controlled and reproducible way. Learning in the model occurs via plastic adaptation of synaptic strengths by a non-uniform negative feedback mechanism. Learning is a truly collective process and the learning dynamics exhibits universal features. Even complex rules can be learned provided that the plastic adaptation is sufficiently slow.

  3. Self-organization of mega-scale glacial lineations

    NASA Astrophysics Data System (ADS)

    Martin, Carlos; Hilmar Gudmundsson, G.; Hogan, Kelly A.; King, Edward; Stokes, Chris R.

    2015-04-01

    Mega-scale glacial lineations (MSGL) are elongate corrugations in sediment that develop under fast-flowing regions in ice sheets. Their distinctive shape and distribution contains information about ice and sediment that is essential to understand the mass imbalance of present and past glaciated areas. Here we use a high-resolution full-Stokes numerical model of coupled flow of ice and sediment to investigate the genesis and evolution of MSGL. We compare our results with field examples from the base of Rutford Ice Stream, Antarctica, and from the now-exposed beds of paleo-ice streams at Anvers Trough, West Antarctic Peninsula, Dotson-Getz Trough, Amundsen Sea, and Dubawnt Lake in the Canadian Shield. We show that the origin of MSGL could be explained by naturally occurring perturbations in the geometry or mechanical properties of the sediment. These original perturbations grow, redistribute and elongate, as the sediment is transported downstream, until they reach a steady configuration. We find that MSGL amplitude is dependent of the strength of the original perturbation; their length is related to the time elapsed from the genesis of the feature; and the lateral spacing between lineations depends mainly on the macroscopic mechanical properties of the sediment. Finally, we conclude that MSGL can be understood as a self-organized system as their geometry and distribution is determined by local interactions between individual lineations and not as a response to the global flow of ice and sediment.

  4. SELF-ORGANIZED BRAIDING AND THE STRUCTURE OF CORONAL LOOPS

    SciTech Connect

    Berger, Mitchell A.; Asgari-Targhi, Mahboubeh E-mail: m.asgari@ucl.ac.u

    2009-11-01

    The Parker model for heating of the solar corona involves reconnection of braided magnetic flux elements. Much of this braiding is thought to occur at as yet unresolved scales, for example, braiding of threads within an extreme-ultraviolet or X-ray loop. However, some braiding may be still visible at scales accessible to TRACE or Hinode. We suggest that attempts to estimate the amount of braiding at these scales must take into account the degree of coherence of the braid structure. In this paper, we examine the effect of reconnection on the structure of a braided magnetic field. We demonstrate that simple models of braided magnetic fields which balance the input of topological structure with reconnection evolve to a self-organized critical state. An initially random braid can become highly ordered, with coherence lengths obeying power-law distributions. The energy released during reconnection also obeys a power law. Our model gives more frequent (but smaller) energy releases nearer to the ends of a coronal loop.

  5. Self-Organizing-Map Program for Analyzing Multivariate Data

    NASA Technical Reports Server (NTRS)

    Li, P. Peggy; Jacob, Joseph C.; Block, Gary L.; Braverman, Amy J.

    2005-01-01

    SOM_VIS is a computer program for analysis and display of multidimensional sets of Earth-image data typified by the data acquired by the Multi-angle Imaging Spectro-Radiometer [MISR (a spaceborne instrument)]. In SOM_VIS, an enhanced self-organizing-map (SOM) algorithm is first used to project a multidimensional set of data into a nonuniform three-dimensional lattice structure. The lattice structure is mapped to a color space to obtain a color map for an image. The Voronoi cell-refinement algorithm is used to map the SOM lattice structure to various levels of color resolution. The final result is a false-color image in which similar colors represent similar characteristics across all its data dimensions. SOM_VIS provides a control panel for selection of a subset of suitably preprocessed MISR radiance data, and a control panel for choosing parameters to run SOM training. SOM_VIS also includes a component for displaying the false-color SOM image, a color map for the trained SOM lattice, a plot showing an original input vector in 36 dimensions of a selected pixel from the SOM image, the SOM vector that represents the input vector, and the Euclidean distance between the two vectors.

  6. Topology and structural self-organization in folded proteins

    NASA Astrophysics Data System (ADS)

    Lundgren, M.; Krokhotin, Andrey; Niemi, Antti J.

    2013-10-01

    Topological methods are indispensable in theoretical studies of particle physics, condensed matter physics, and gravity. These powerful techniques have also been applied to biological physics. For example, knowledge of DNA topology is pivotal to the understanding as to how living cells function. Here, the biophysical repertoire of topological methods is extended, with the aim to understand and characterize the global structure of a folded protein. For this, the elementary concept of winding number of a vector field on a plane is utilized to introduce a topological quantity called the folding index of a crystallographic protein. It is observed that in the case of high resolution protein crystals, the folding index, when evaluated over the entire length of the crystallized protein backbone, has a very clear and strong propensity towards integer values. The observation proposes that the way how a protein folds into its biologically active conformation is a structural self-organization process with a topological facet that relates to the concept of solitons. It is proposed that the folding index has a potential to become a useful tool for the global, topological characterization of the folding pathways.

  7. A conciliation mechanism for self-organizing dynamic small groups.

    PubMed

    Ren, Minglun; Hu, Zhongfeng; Jain, Hemant

    2016-01-01

    A group of individuals, organizations or things in internet of things (IoT) often dynamically self-organizes in small groups to accomplish certain tasks. This is common in virtual organization, social networks and the evolving field of IoT. These small groups have different behavioral characteristics than large groups. Members individually have some requirements and contribute some resources to the group. The organization and operation of such a group requires dynamic identification of group requirements that can be fulfilled by available resources and is approved by the group. We apply design science methods to develop an artifact that helps in conciliation of collective requirements and resources of small groups while maintaining each member's satisfaction. The mechanism also supports dynamic conciliation as members leave and new members join the group. Each member's requirement is specified as an explicit/implicit objective that is feasible/not feasible based on resources available to the group and whether the requirement is in alignment with other members' objectives. We validate the artifact by using it for a manufacturing service group and simulating the change in collective group requirements and resources as group membership changes dynamically. PMID:27390641

  8. 25 Years of Self-organized Criticality: Numerical Detection Methods

    NASA Astrophysics Data System (ADS)

    McAteer, R. T. James; Aschwanden, Markus J.; Dimitropoulou, Michaila; Georgoulis, Manolis K.; Pruessner, Gunnar; Morales, Laura; Ireland, Jack; Abramenko, Valentyna

    2016-01-01

    The detection and characterization of self-organized criticality (SOC), in both real and simulated data, has undergone many significant revisions over the past 25 years. The explosive advances in the many numerical methods available for detecting, discriminating, and ultimately testing, SOC have played a critical role in developing our understanding of how systems experience and exhibit SOC. In this article, methods of detecting SOC are reviewed; from correlations to complexity to critical quantities. A description of the basic autocorrelation method leads into a detailed analysis of application-oriented methods developed in the last 25 years. In the second half of this manuscript space-based, time-based and spatial-temporal methods are reviewed and the prevalence of power laws in nature is described, with an emphasis on event detection and characterization. The search for numerical methods to clearly and unambiguously detect SOC in data often leads us outside the comfort zone of our own disciplines—the answers to these questions are often obtained by studying the advances made in other fields of study. In addition, numerical detection methods often provide the optimum link between simulations and experiments in scientific research. We seek to explore this boundary where the rubber meets the road, to review this expanding field of research of numerical detection of SOC systems over the past 25 years, and to iterate forwards so as to provide some foresight and guidance into developing breakthroughs in this subject over the next quarter of a century.

  9. Growth, collapse, and self-organized criticality in complex networks

    PubMed Central

    Wang, Yafeng; Fan, Huawei; Lin, Weijie; Lai, Ying-Cheng; Wang, Xingang

    2016-01-01

    Network growth is ubiquitous in nature (e.g., biological networks) and technological systems (e.g., modern infrastructures). To understand how certain dynamical behaviors can or cannot persist as the underlying network grows is a problem of increasing importance in complex dynamical systems as well as sustainability science and engineering. We address the question of whether a complex network of nonlinear oscillators can maintain its synchronization stability as it expands. We find that a large scale avalanche over the entire network can be triggered in the sense that the individual nodal dynamics diverges from the synchronous state in a cascading manner within a relatively short time period. In particular, after an initial stage of linear growth, the network typically evolves into a critical state where the addition of a single new node can cause a group of nodes to lose synchronization, leading to synchronization collapse for the entire network. A statistical analysis reveals that the collapse size is approximately algebraically distributed, indicating the emergence of self-organized criticality. We demonstrate the generality of the phenomenon of synchronization collapse using a variety of complex network models, and uncover the underlying dynamical mechanism through an eigenvector analysis. PMID:27079515

  10. Self-organizing approach for meta-genomes.

    PubMed

    Zhu, Jianfeng; Zheng, Wei-Mou

    2014-12-01

    We extend the self-organizing approach for annotation of a bacterial genome to analyze the raw sequencing data of the human gut metagenome without sequence assembling. The original approach divides the genomic sequence of a bacterium into non-overlapping segments of equal length and assigns to each segment one of seven 'phases', among which one is for the noncoding regions, three for the direct coding regions to indicate the three possible codon positions of the segment starting site, and three for the reverse coding regions. The noncoding phase and the six coding phases are described by two frequency tables of the 64 triplet types or 'codon usages'. A set of codon usages can be used to update the phase assignment and vice versa. An iteration after an initialization leads to a convergent phase assignment to give an annotation of the genome. In the extension of the approach to a metagenome, we consider a mixture model of a number of categories described by different codon usages. The Illumina Genome Analyzer sequencing data of the total DNA from faecal samples are then examined to understand the diversity of the human gut microbiome. PMID:25213854