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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 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.

  5. 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

  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. 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

  8. 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.

  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.

    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.

  14. 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.

  15. 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

  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. 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.

  19. 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.

  20. 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.

  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. 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.

  10. 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.

  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. 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.

  14. 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

  15. 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.

  16. 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

  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. 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

  20. 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.

  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. 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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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

  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. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  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

    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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  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. 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

  13. 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.

  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. 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

  17. 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…

  18. 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.

  19. 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

  20. 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.

  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. 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.

  3. 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

  4. 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.

  5. 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.

  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. 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.

  10. 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

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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.

  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 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.

  11. 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.

  12. 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.

  13. 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

  14. 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

  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. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12.  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.

  13. 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

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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

  16. 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

  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. 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

  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. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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)].

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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).

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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.

  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. 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.

  5. 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

  6. 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

  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. 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.

  14. 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

  15. 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

  16. Spatial self-organization favors heterotypic cooperation over cheating

    PubMed Central

    Momeni, Babak; Waite, Adam James; Shou, Wenying

    2013-01-01

    Heterotypic cooperation—two populations exchanging distinct benefits that are costly to produce—is widespread. Cheaters, exploiting benefits while evading contribution, can undermine cooperation. Two mechanisms can stabilize heterotypic cooperation. In ‘partner choice’, cooperators recognize and choose cooperating over cheating partners; in ‘partner fidelity feedback’, fitness-feedback from repeated interactions ensures that aiding your partner helps yourself. How might a spatial environment, which facilitates repeated interactions, promote fitness-feedback? We examined this process through mathematical models and engineered Saccharomyces cerevisiae strains incapable of recognition. Here, cooperators and their heterotypic cooperative partners (partners) exchanged distinct essential metabolites. Cheaters exploited partner-produced metabolites without reciprocating, and were competitively superior to cooperators. Despite initially random spatial distributions, cooperators gained more partner neighbors than cheaters did. The less a cheater contributed, the more it was excluded and disfavored. This self-organization, driven by asymmetric fitness effects of cooperators and cheaters on partners during cell growth into open space, achieves assortment. DOI: http://dx.doi.org/10.7554/eLife.00960.001 PMID:24220506

  17. Can Self-Organizing Maps Accurately Predict Photometric Redshifts?

    NASA Astrophysics Data System (ADS)

    Way, M. J.; Klose, C. D.

    2012-03-01

    We present an unsupervised machine-learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization called the self-organizing-map (SOM) approach. A variety of photometrically derived input values were utilized from the Sloan Digital Sky Survey's main galaxy sample, luminous red galaxy, and quasar samples, along with the PHAT0 data set from the Photo-z Accuracy Testing project. Regression results obtained with this new approach were evaluated in terms of root-mean-square error (RMSE) to estimate the accuracy of the photometric redshift estimates. The results demonstrate competitive RMSE and outlier percentages when compared with several other popular approaches, such as artificial neural networks and Gaussian process regression. SOM RMSE results (using Δz = zphot - zspec) are 0.023 for the main galaxy sample, 0.027 for the luminous red galaxy sample, 0.418 for quasars, and 0.022 for PHAT0 synthetic data. The results demonstrate that there are nonunique solutions for estimating SOM RMSEs. Further research is needed in order to find more robust estimation techniques using SOMs, but the results herein are a positive indication of their capabilities when compared with other well-known methods.

  18. Self-Organized Platinum Nanoparticles Elevated on Freestanding Graphene

    NASA Astrophysics Data System (ADS)

    Ackerman, Matthew; Xu, Peng; Barber, Steven; Schoelz, James; Qi, Dejun; Thibado, Paul; Dong, Lifeng; Yu, Jianhua; Xu, Fangfang; Neek-Amal, Mehdi; Peeters, Francois

    2014-03-01

    Freestanding graphene membranes were successfully functionalized with platinum nanoparticles (Pt NPs) using a single-step sputtering deposition process. The membranes were imaged using high-resolution transmission electron microscopy, revealing a homogeneous distribution of uniformly sized, single-crystal Pt NPs that exhibit a preferred orientation and nearest-neighbor distance. The NPs were also found to be partially elevated by the graphene substrate, as deduced from atomic-resolution scanning tunneling microscopy (STM) images. Furthermore, the electrostatic force between the STM tip and sample was utilized to estimate the binding energy of the NPs to the suspended graphene. Local strain accumulation due to elevation during the growth process is thought to be the origin of the NP self-organization. Such detailed insight into the atomic nature of this functionalized system was only possible through the cooperation of dual microscopic techniques combined with molecular dynamics simulations. The findings are expected to shape future approaches to develop high-performance electronics based on nanoparticle-functionalized graphene as well as fuel cells using Pt NP catalysts. ONR Grant No. N00014-10-1-0181, NSF Grant No. DMR-0855358 and DMR-0821159, National Natural Science Foundation of China (51172113), Shandong Natural Science Foundation (JQ201118), Qingdao Municipal Science and Technology Commission (12-1-4-136-hz).

  19. Computational Design of Photovoltaic Materials with Self Organized Nano Structures

    NASA Astrophysics Data System (ADS)

    Sato, Kazunori; Katayama-Yoshida, Hiroshi

    2013-03-01

    Chalcopyrite and II-VI semiconductors, such as Cu(In, Ga)Se2, Cu2ZnSn(S, Se)4 and Cd(S, Te), are one of the most promising materials for low cost photovoltaic solar-cells. In this paper, based on first-principles calculations, we propose that self-organized nano-structures in these compounds will enhance the conversion efficiency. Our calculations are based on the KKR-CPA-LDA with the self-interaction correction. We also use VASP package for calculating mixing energy and effective interactions of the systems by using the cluster expansion method. For phase separating systems, we simulate nano-structure formation by using the Monte Carlo method. It is expected that the photo-generated electron-hole pairs are efficiently separated by the type-II interface and then effectively transferred along the quasi-one-dimensional structures. Moreover, we can expect multiplication of generated carriers due to the multi-exciton effects in nano-structures.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    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.

  1. Dynamic critical approach to self-organized criticality

    NASA Astrophysics Data System (ADS)

    Laneri, Karina; Rozenfeld, Alejandro F.; Albano, Ezequiel V.

    2005-12-01

    A dynamic scaling ansatz for the approach to the self-organized critical (SOC) regime is proposed and tested by means of extensive simulations applied to the Bak-Sneppen model (BS), which exhibits robust SOC behavior. Considering the short-time scaling behavior of the density of sites [ρ(t)] below the critical value, it is shown that (i) starting the dynamics with configurations such that ρ(t=0)→0 one observes an initial increase of the density with exponent θ=0.12(2) ; (ii) using initial configurations with ρ(t=0)→1 , the density decays with exponent δ=0.47(2) . It is also shown that the temporal autocorrelation decays with exponent Ca=0.35(2) . Using these dynamically determined critical exponents and suitable scaling relationships, all known exponents of the BS model can be obtained, e.g., the dynamical exponent z=2.10(5) , the mass dimension exponent D=2.42(5) , and the exponent of all returns of the activity τALL=0.39(2) , in excellent agreement with values already accepted and obtained within the SOC regime.

  2. Self-organized network evolution coupled to extremal dynamics

    NASA Astrophysics Data System (ADS)

    Garlaschelli, Diego; Capocci, Andrea; Caldarelli, Guido

    2007-11-01

    The interplay between topology and dynamics in complex networks is a fundamental but widely unexplored problem. Here, we study this phenomenon on a prototype model in which the network is shaped by a dynamical variable. We couple the dynamics of the Bak-Sneppen evolution model with the rules of the so-called fitness network model for establishing the topology of a network; each vertex is assigned a `fitness', and the vertex with minimum fitness and its neighbours are updated in each iteration. At the same time, the links between the updated vertices and all other vertices are drawn anew with a fitness-dependent connection probability. We show analytically and numerically that the system self-organizes to a non-trivial state that differs from what is obtained when the two processes are decoupled. A power-law decay of dynamical and topological quantities above a threshold emerges spontaneously, as well as a feedback between different dynamical regimes and the underlying correlation and percolation properties of the network.

  3. Self-organization in precipitation reactions far from the equilibrium

    PubMed Central

    Nakouzi, Elias; Steinbock, Oliver

    2016-01-01

    Far from the thermodynamic equilibrium, many precipitation reactions create complex product structures with fascinating features caused by their unusual origins. Unlike the dissipative patterns in other self-organizing reactions, these features can be permanent, suggesting potential applications in materials science and engineering. We review four distinct classes of precipitation reactions, describe similarities and differences, and discuss related challenges for theoretical studies. These classes are hollow micro- and macrotubes in chemical gardens, polycrystalline silica carbonate aggregates (biomorphs), Liesegang bands, and propagating precipitation-dissolution fronts. In many cases, these systems show intricate structural hierarchies that span from the nanometer scale into the macroscopic world. We summarize recent experimental progress that often involves growth under tightly regulated conditions by means of wet stamping, holographic heating, and controlled electric, magnetic, or pH perturbations. In this research field, progress requires mechanistic insights that cannot be derived from experiments alone. We discuss how mesoscopic aspects of the product structures can be modeled by reaction-transport equations and suggest important targets for future studies that should also include materials features at the nanoscale. PMID:27551688

  4. Self-organization of the in vitro attached human embryo.

    PubMed

    Deglincerti, Alessia; Croft, Gist F; Pietila, Lauren N; Zernicka-Goetz, Magdalena; Siggia, Eric D; Brivanlou, Ali H

    2016-05-12

    Implantation of the blastocyst is a developmental milestone in mammalian embryonic development. At this time, a coordinated program of lineage diversification, cell-fate specification, and morphogenetic movements establishes the generation of extra-embryonic tissues and the embryo proper, and determines the conditions for successful pregnancy and gastrulation. Despite its basic and clinical importance, this process remains mysterious in humans. Here we report the use of a novel in vitro system to study the post-implantation development of the human embryo. We unveil the self-organizing abilities and autonomy of in vitro attached human embryos. We find human-specific molecular signatures of early cell lineage, timing, and architecture. Embryos display key landmarks of normal development, including epiblast expansion, lineage segregation, bi-laminar disc formation, amniotic and yolk sac cavitation, and trophoblast diversification. Our findings highlight the species-specificity of these developmental events and provide a new understanding of early human embryonic development beyond the blastocyst stage. In addition, our study establishes a new model system relevant to early human pregnancy loss. Finally, our work will also assist in the rational design of differentiation protocols of human embryonic stem cells to specific cell types for disease modelling and cell replacement therapy. PMID:27144363

  5. Self-organized relaxation in a collisionless gravitating system.

    PubMed

    Sota, Yasuhide; Iguchi, Osamu; Tashiro, Tohru; Morikawa, Masahiro

    2008-05-01

    We propose the self-organized relaxation process which drives a collisionless self-gravitating system to the equilibrium state satisfying local virial (LV) relation. During the violent relaxation process, particles can move widely within the time interval as short as a few free-fall times, because of the effective potential oscillations. Since such particle movement causes further potential oscillations, it is expected that the system approaches the critical state where such particle activities, which we call gravitational fugacity, is independent of the local position as much as possible. Here we demonstrate that gravitational fugacity can be described as the functional of the LV ratio, which means that the LV ratio is a key ingredient estimating the particle activities against gravitational potential. We also demonstrate that the LV relation is attained if the LV ratio exceeds the critical value b=1 everywhere in the bound region during the violent relaxation process. The local region which does not meet this criterion can be trapped into the presaturated state. However, small phase-space perturbation can bring the inactive part into the LV critical state. PMID:18643036

  6. Trading leads to scale-free self-organization

    NASA Astrophysics Data System (ADS)

    Ebert, M.; Paul, W.

    2012-12-01

    Financial markets display scale-free behavior in many different aspects. The power-law behavior of part of the distribution of individual wealth has been recognized by Pareto as early as the nineteenth century. Heavy-tailed and scale-free behavior of the distribution of returns of different financial assets have been confirmed in a series of works. The existence of a Pareto-like distribution of the wealth of market participants has been connected with the scale-free distribution of trading volumes and price-returns. The origin of the Pareto-like wealth distribution, however, remained obscure. Here we show that in a market where the imbalance of supply and demand determines the direction of prize changes, it is the process of trading itself that spontaneously leads to a self-organization of the market with a Pareto-like wealth distribution for the market participants and at the same time to a scale-free behavior of return fluctuations and trading volume distributions.

  7. Self-organized rhythmic patterns in geochemical systems.

    PubMed

    L'Heureux, Ivan

    2013-12-13

    Chemical oscillating patterns are ubiquitous in geochemical systems. Although many such patterns result from systematic variations in the external environmental conditions, it is recognized that some patterns are due to intrinsic self-organized processes in a non-equilibrium nonlinear system with positive feedback. In rocks and minerals, periodic precipitation (Liesegang bands) and oscillatory zoning constitute good examples of patterns that can be explained using concepts from nonlinear dynamics. Generally, as the system parameters exceed some threshold values, the steady (time-independent) state characterizing the system loses its stability. The system then evolves towards other time-dependent solutions ('attractors') that may have an oscillatory behaviour or a complex chaotic one. In this review, we describe many of these pattern types taken from a variety of geological environments: eruptive, sedimentary, hydrothermal or metamorphic. One particular example (periodic precipitation of pyrite bands in an evolving sapropel sediment) is presented here for the first time. This will help in convincing the reader that the tools of nonlinear dynamics may be useful to understand the history of our planet. PMID:24471274

  8. Self-organized rhythmic patterns in geochemical systems.

    PubMed

    L'heureux, Ivan

    2013-01-01

    Chemical oscillating patterns are ubiquitous in geochemical systems. Although many such patterns result from systematic variations in the external environmental conditions, it is recognized that some patterns are due to intrinsic self-organized processes in a non-equilibrium nonlinear system with positive feedback. In rocks and minerals, periodic precipitation (Liesegang bands) and oscillatory zoning constitute good examples of patterns that can be explained using concepts from nonlinear dynamics. Generally, as the system parameters exceed some threshold values, the steady (time-independent) state characterizing the system loses its stability. The system then evolves towards other time-dependent solutions ('attractors') that may have an oscillatory behaviour or a complex chaotic one. In this review, we describe many of these pattern types taken from a variety of geological environments: eruptive, sedimentary, hydrothermal or metamorphic. One particular example (periodic precipitation of pyrite bands in an evolving sapropel sediment) is presented here for the first time. This will help in convincing the reader that the tools of nonlinear dynamics may be useful to understand the history of our planet. PMID:24191110

  9. Application of self-organizing map to stellar spectral classifications

    NASA Astrophysics Data System (ADS)

    Bazarghan, Mahdi

    2012-01-01

    We present an automatic, fast, accurate and robust method of classifying astronomical objects. The Self Organizing Map (SOM) as an unsupervised Artificial Neural Network (ANN) algorithm is used for classification of stellar spectra of stars. The SOM is used to make clusters of different spectral classes of Jacoby, Hunter and Christian (JHC) library. This ANN technique needs no training examples and the stellar spectral data sets are directly fed to the network for the classification. The JHC library contains 161 spectra out of which, 158 spectra are selected for the classification. These 158 spectra are input vectors to the network and mapped into a two dimensional output grid. The input vectors close to each other are mapped into the same or neighboring neurons in the output space. So, the similar objects are making clusters in the output map and making it easy to analyze high dimensional data. After running the SOM algorithm on 158 stellar spectra, with 2799 data points each, the output map is analyzed and found that, there are 7 clusters in the output map corresponding to O to M stellar type. But, there are 12 misclassifications out of 158 and all of them are misclassified into the neighborhood of correct clusters which gives a success rate of about 92.4%.

  10. Comparative, transcriptome analysis of self-organizing optic tissues

    PubMed Central

    Andrabi, Munazah; Kuraku, Shigehiro; Takata, Nozomu; Sasai, Yoshiki; Love, Nick R.

    2015-01-01

    Embryonic stem (ES) cells have a remarkable capacity to self-organize complex, multi-layered optic cups in vitro via a culture technique called SFEBq. During both SFEBq and in vivo optic cup development, Rax (Rx) expressing neural retina epithelial (NRE) tissues utilize Fgf and Wnt/β-catenin signalling pathways to differentiate into neural retina (NR) and retinal-pigmented epithelial (RPE) tissues, respectively. How these signaling pathways affect gene expression during optic tissue formation has remained largely unknown, especially at the transcriptome scale. Here, we address this question using RNA-Seq. We generated Rx+ optic tissue using SFEBq, exposed these tissues to either Fgf or Wnt/β-catenin stimulation, and assayed their gene expression across multiple time points using RNA-Seq. This comparative dataset will help elucidate how Fgf and Wnt/β-catenin signaling affect gene expression during optic tissue differentiation and will help inform future efforts to optimize in vitro optic tissue culture technology. PMID:26110066

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Self-organization in precipitation reactions far from the equilibrium.

    PubMed

    Nakouzi, Elias; Steinbock, Oliver

    2016-08-01

    Far from the thermodynamic equilibrium, many precipitation reactions create complex product structures with fascinating features caused by their unusual origins. Unlike the dissipative patterns in other self-organizing reactions, these features can be permanent, suggesting potential applications in materials science and engineering. We review four distinct classes of precipitation reactions, describe similarities and differences, and discuss related challenges for theoretical studies. These classes are hollow micro- and macrotubes in chemical gardens, polycrystalline silica carbonate aggregates (biomorphs), Liesegang bands, and propagating precipitation-dissolution fronts. In many cases, these systems show intricate structural hierarchies that span from the nanometer scale into the macroscopic world. We summarize recent experimental progress that often involves growth under tightly regulated conditions by means of wet stamping, holographic heating, and controlled electric, magnetic, or pH perturbations. In this research field, progress requires mechanistic insights that cannot be derived from experiments alone. We discuss how mesoscopic aspects of the product structures can be modeled by reaction-transport equations and suggest important targets for future studies that should also include materials features at the nanoscale. PMID:27551688

  1. Sleep dynamics: A self-organized critical system

    NASA Astrophysics Data System (ADS)

    Comte, J. C.; Ravassard, P.; Salin, P. A.

    2006-05-01

    In psychiatric and neurological diseases, sleep is often perturbed. Moreover, recent works on humans and animals tend to show that sleep plays a strong role in memory processes. Reciprocally, sleep dynamics following a learning task is modified [Hubert , Nature (London) 02663, 1 (2004), Peigneux , Neuron 44, 535 (2004)]. However, sleep analysis in humans and animals is often limited to the total sleep and wake duration quantification. These two parameters are not fully able to characterize the sleep dynamics. In mammals sleep presents a complex organization with an alternation of slow wave sleep (SWS) and paradoxical sleep (PS) episodes. Moreover, it has been shown recently that these sleep episodes are frequently interrupted by micro-arousal (without awakening). We present here a detailed analysis of the basal sleep properties emerging from the mechanisms underlying the vigilance states alternation in an animal model. These properties present a self-organized critical system signature and reveal the existence of two W, two SWS, and a PS structure exhibiting a criticality as met in sand piles. We propose a theoretical model of the sleep dynamics based on several interacting neuronal populations. This new model of sleep dynamics presents the same properties as experimentally observed, and explains the variability of the collected data. This experimental and theoretical study suggests that sleep dynamics shares several common features with critical systems.

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

    PubMed

    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

  3. Self-organized pattern formation in motor-microtubule mixtures

    NASA Astrophysics Data System (ADS)

    Sankararaman, Sumithra; Menon, Gautam I.; Sunil Kumar, P. B.

    2004-09-01

    We model the stable self-organized patterns obtained in the nonequilibrium steady states of mixtures of molecular motors and microtubules. In experiments [Nédélec , Nature (London) 389, 305 (1997); Surrey , Science 292, 1167 (2001)] performed in a quasi-two-dimensional geometry, microtubules are oriented by complexes of motor proteins. This interaction yields a variety of patterns, including arrangements of asters, vortices, and disordered configurations. We model this system via a two-dimensional vector field describing the local coarse-grained microtubule orientation and two scalar density fields associated to molecular motors. These scalar fields describe motors which either attach to and move along microtubules or diffuse freely within the solvent. Transitions between single aster, spiral, and vortex states are obtained as a consequence of confinement, as parameters in our model are varied. For systems in which the effects of confinement can be neglected, we present a map of nonequilibrium steady states, which includes arrangements of asters and vortices separately as well as aster-vortex mixtures and fully disordered states. We calculate the steady state distribution of bound and free motors in aster and vortex configurations of microtubules and compare these to our simulation results, providing qualitative arguments for the stability of different patterns in various regimes of parameter space. We study the role of crowding or “saturation” effects on the density profiles of motors in asters, discussing the role of such effects in stabilizing single asters. We also comment on the implications of our results for experiments.

  4. Biosom: gene synonym analysis by self-organizing map.

    PubMed

    Otemaier, K R; Steffens, M B R; Raittz, R T; Brawerman, A; Marchaukoski, J N

    2015-01-01

    There are several guidelines for gene nomenclature, but they are not always applied to the names of newly identified genes. The lack of standardization in naming genes generates inconsistent databases with errors such as genes with the same function and different names, genes with different functions and the same name, and use of an abbreviated name. This paper presents a methodology for predicting synonyms in a given gene nomenclature, thereby detecting and minimizing naming redundancy and inconsistency and facilitating the annotation of new genes and data mining in public databases. To identify gene synonyms, i.e., gene ambiguity, the methodology proposed begins by grouping genes according to their names using a Kohonen self-organizing map artificial neural network. Afterwards, it identifies the groups generated employing the Matrix-U technique. The employment of such techniques allows one to infer the synonyms of genes, to predict probable hypothetical gene names and to point out possible errors in a database record. Many mistakes related to gene nomenclature were detected in this research, demonstrating the importance of predicting synonyms. The methodology developed is applicable for describing hypothetical, putative and other types of genes without a known function. Moreover, it can also indicate a possible function for genes after grouping them. PMID:25730085

  5. The self-organization of grid cells in 3D.

    PubMed

    Stella, Federico; Treves, Alessandro

    2015-01-01

    Do we expect periodic grid cells to emerge in bats, or perhaps dolphins, exploring a three-dimensional environment? How long will it take? Our self-organizing model, based on ring-rate adaptation, points at a complex answer. The mathematical analysis leads to asymptotic states resembling face centered cubic (FCC) and hexagonal close packed (HCP) crystal structures, which are calculated to be very close to each other in terms of cost function. The simulation of the full model, however, shows that the approach to such asymptotic states involves several sub-processes over distinct time scales. The smoothing of the initially irregular multiple fields of individual units and their arrangement into hexagonal grids over certain best planes are observed to occur relatively quickly, even in large 3D volumes. The correct mutual orientation of the planes, though, and the coordinated arrangement of different units, take a longer time, with the network showing no sign of convergence towards either a pure FCC or HCP ordering. PMID:25821989

  6. 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.

  7. 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

  8. Self-organized optical device driven by motor proteins.

    PubMed

    Aoyama, Susumu; Shimoike, Masahiko; Hiratsuka, Yuichi

    2013-10-01

    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

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. Microstructural self-organization in granular materials during failure

    NASA Astrophysics Data System (ADS)

    Hadda, Nejib; Nicot, François; Wan, Richard; Darve, Félix

    2015-02-01

    The present paper is concerned with the analysis of microstructural instabilities in granular materials and with their relation to both macroscopic localized and diffuse failure modes. A discrete-element (DEM) computer simulation of deformations in an idealized two-dimensional frictional particle assembly subject to various biaxial loadings-notably drained compression and proportional strain paths-is proposed as a prototype model to investigate the underlying physics of material failure. Based on the transfer of the second-order work criterion to the microscopic level, we seek for contacts tagged as c- within the granular assembly that undergo instabilities during loading history. The DEM computations yield a description of failure as a microstructural self-organization process by which c- contacts aggregate into clusters which can either grow or breakdown as the network of contacts adjusts itself to externally applied loads during deformation history. It is proposed here that there is a close relation between the clustering of c- contacts and the resulting failure mode based on cluster size and spatial distribution. Localized deformations are found to correlate well with sustained growth of the above clusters, while diffuse failure has more to do with smaller clusters experiencing suppressed development. A comprehensive statistical analysis on the clusters lends support to this conclusion.

  14. Self-organization of punishment in structured populations

    NASA Astrophysics Data System (ADS)

    Perc, Matjaž; Szolnoki, Attila

    2012-04-01

    Cooperation is crucial for the remarkable evolutionary success of the human species. Not surprisingly, some individuals are willing to bear additional costs in order to punish defectors. Current models assume that, once set, the fine and cost of punishment do not change over time. Here we show that relaxing this assumption by allowing players to adapt their sanctioning efforts in dependence on the success of cooperation can explain both the spontaneous emergence of punishment and its ability to deter defectors and those unwilling to punish them with globally negligible investments. By means of phase diagrams and the analysis of emerging spatial patterns, we demonstrate that adaptive punishment promotes public cooperation through the invigoration of spatial reciprocity, the prevention of the emergence of cyclic dominance, or the provision of competitive advantages to those that sanction antisocial behavior. The results presented indicate that the process of self-organization significantly elevates the effectiveness of punishment, and they reveal new mechanisms by means of which this fascinating and widespread social behavior could have evolved.

  15. Seismic event classification using Self-Organizing Neural Networks

    SciTech Connect

    Maurer, W.J.; Dowla, F.U.; Jarpe, S.P.

    1991-10-15

    In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. We have studied Self Organizing Neural Networks (SONNs) for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs were developed and tested with a moderately large set of real seismic events. Given the detection of a seismic event and the corresponding signal, we compute the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This preprocessed input is fed into the SONNs. The overall results based on 111 events (43 training and 68 test events) show that SONNs are able to group events that ``look`` similar. We also find that the ART algorithm has an advantage in that the types of cluster groups do not need to be predefined. When a new type of event is detected, the ART network is able to handle the event rather gracefully. The results from the SONNs together with an expert seismologist`s classification are then used to derive event classification probabilities. A strategy to integrate a SONN into the interpretation of seismic events is also proposed.

  16. State-of-the-Art-Symposium: Self-Organization in Chemistry.

    ERIC Educational Resources Information Center

    Soltzberg, Leonard J.; And Others

    1989-01-01

    Presents four articles dealing with chaotic systems. Lists sources for nine demonstrations or experiments dealing with self-organization. Provides a vocabulary review of self-organization. Describes three chemical oscillator models. Discusses the role of chaos in flow systems. (MVL)

  17. Self-Organization in 2D Traffic Flow Model with Jam-Avoiding Drive

    NASA Astrophysics Data System (ADS)

    Nagatani, Takashi

    1995-04-01

    A stochastic cellular automaton (CA) model is presented to investigate the traffic jam by self-organization in the two-dimensional (2D) traffic flow. The CA model is the extended version of the 2D asymmetric exclusion model to take into account jam-avoiding drive. Each site contains either a car moving to the up, a car moving to the right, or is empty. A up car can shift right with probability p ja if it is blocked ahead by other cars. It is shown that the three phases (the low-density phase, the intermediate-density phase and the high-density phase) appear in the traffic flow. The intermediate-density phase is characterized by the right moving of up cars. The jamming transition to the high-density jamming phase occurs with higher density of cars than that without jam-avoiding drive. The jamming transition point p 2c increases with the shifting probability p ja. In the deterministic limit of p ja=1, it is found that a new jamming transition occurs from the low-density synchronized-shifting phase to the high-density moving phase with increasing density of cars. In the synchronized-shifting phase, all up cars do not move to the up but shift to the right by synchronizing with the move of right cars. We show that the jam-avoiding drive has an important effect on the dynamical jamming transition.

  18. Self-organization of the human embryo in the absence of maternal tissues.

    PubMed

    Shahbazi, Marta N; Jedrusik, Agnieszka; Vuoristo, Sanna; Recher, Gaelle; Hupalowska, Anna; Bolton, Virginia; Fogarty, Norah M E; Campbell, Alison; Devito, Liani G; Ilic, Dusko; Khalaf, Yakoub; Niakan, Kathy K; Fishel, Simon; Zernicka-Goetz, Magdalena

    2016-06-01

    Remodelling of the human embryo at implantation is indispensable for successful pregnancy. Yet it has remained mysterious because of the experimental hurdles that beset the study of this developmental phase. Here, we establish an in vitro system to culture human embryos through implantation stages in the absence of maternal tissues and reveal the key events of early human morphogenesis. These include segregation of the pluripotent embryonic and extra-embryonic lineages, and morphogenetic rearrangements leading to generation of a bilaminar disc, formation of a pro-amniotic cavity within the embryonic lineage, appearance of the prospective yolk sac, and trophoblast differentiation. Using human embryos and human pluripotent stem cells, we show that the reorganization of the embryonic lineage is mediated by cellular polarization leading to cavity formation. Together, our results indicate that the critical remodelling events at this stage of human development are embryo-autonomous, highlighting the remarkable and unanticipated self-organizing properties of human embryos. PMID:27144686

  19. Particle acceleration in solar active regions being in the state of self-organized criticality.

    NASA Astrophysics Data System (ADS)

    Vlahos, Loukas

    We review the recent observational results on flare initiation and particle acceleration in solar active regions. Elaborating a statistical approach to describe the spatiotemporally intermittent electric field structures formed inside a flaring solar active region, we investigate the efficiency of such structures in accelerating charged particles (electrons and protons). The large-scale magnetic configuration in the solar atmosphere responds to the strong turbulent flows that convey perturbations across the active region by initiating avalanche-type processes. The resulting unstable structures correspond to small-scale dissipation regions hosting strong electric fields. Previous research on particle acceleration in strongly turbulent plasmas provides a general framework for addressing such a problem. This framework combines various electromagnetic field configurations obtained by magnetohydrodynamical (MHD) or cellular automata (CA) simulations, or by employing a statistical description of the field’s strength and configuration with test particle simulations. We work on data-driven 3D magnetic field extrapolations, based on a self-organized criticality models (SOC). A relativistic test-particle simulation traces each particle’s guiding center within these configurations. Using the simulated particle-energy distributions we test our results against observations, in the framework of the collisional thick target model (CTTM) of solar hard X-ray (HXR) emission and compare our results with the current observations.

  20. A self-organized criticality model for ion temperature gradient mode driven turbulence in confined plasma

    SciTech Connect

    Isliker, H.; Pisokas, Th.; Vlahos, L.; Strintzi, D.

    2010-08-15

    A new self-organized criticality (SOC) model is introduced in the form of a cellular automaton (CA) for ion temperature gradient (ITG) mode driven turbulence in fusion plasmas. Main characteristics of the model are that it is constructed in terms of the actual physical variable, the ion temperature, and that the temporal evolution of the CA, which necessarily is in the form of rules, mimics actual physical processes as they are considered to be active in the system, i.e., a heating process and a local diffusive process that sets on if a threshold in the normalized ITG R/L{sub T} is exceeded. The model reaches the SOC state and yields ion temperature profiles of exponential shape, which exhibit very high stiffness, in that they basically are independent of the loading pattern applied. This implies that there is anomalous heat transport present in the system, despite the fact that diffusion at the local level is imposed to be of a normal kind. The distributions of the heat fluxes in the system and of the heat out-fluxes are of power-law shape. The basic properties of the model are in good qualitative agreement with experimental results.

  1. A Self-Critique of Self-Organized Criticality in Astrophysics

    NASA Astrophysics Data System (ADS)

    Aschwanden, Markus J.

    2015-08-01

    The concept of ``self-organized criticality'' (SOC) was originally proposed as an explanation of 1/f-noise by Bak, Tang, and Wiesenfeld (1987), but turned out to have a far broader significance for scale-free nonlinear energy dissipation processes occurring in the entire universe. Over the last 30 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 numerical SOC toy models. The novel applications stimulated also vigorous debates about the discrimination between SOC-related 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 models applied to astrophysical observations, attempt to describe what physics can be captured by SOC models, and offer a critique of weaknesses and strengths in existing SOC models.

  2. Self-organization in the spatial battle of the sexes with probabilistic updating

    NASA Astrophysics Data System (ADS)

    Alonso-Sanz, Ramón

    2011-08-01

    The dynamics of a spatial formulation of the iterated battle of the sexes with probabilistic updating is assessed in this work. The game is played in the cellular automata manner, i.e., with local and synchronous interaction. The effect of memory of past encounters is also taken into account. 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. With probabilistic updating of choices, both kinds of players reach mean payoffs per encounter that are notably higher than those reached with a deterministic updating mechanism, albeit the evolutionary dynamics does not stabilize, and one of the two possible choices tends to prevail for both kinds of players. Memory of past iterations induces an inertial effect that moderates this tendency, so that intermediate levels of the memory charge tend to favor fairly stable high egalitarian payoffs, without impeding the necessary recovering from their initial plummeting.

  3. Self-Organized Criticality in Phylogenetic-Like Tree Growths

    NASA Astrophysics Data System (ADS)

    Vandewalle, N.; Ausloos, M.

    1995-08-01

    A simple stochastic model of Darwinistic evolution generating phylogenetic-like trees is developed. The model is based on a branching process taking competition-correlation effects into account. In presence of finite and short range correlations, the process self-organizes into a critical steady-state in which intermittent bursts of activity of all sizes are generated. On a geological-like time scale, this behaviour agrees with punctuated equilibrium features of biological evolution. The simulated phylogenetic-like trees are found to be self-similar. The dynamics of the transient regimes show a power law decrease of the order parameter towards the 0^+ value which characterizes an unstable critical state. The genetic range k of competition-correlations between living species is found to be a relevant parameter which determines the universality class of the evolution process. An infinite competition-correlation range destroys however the self-organized critical behaviour. The fractal dimension D_f of the phylogenetic-like trees increases from 2.0 to infinity as k goes from 1 to infinity. The critical exponent tau of avalanche size-distribution decreases from about 3/2 (for k=1) and reaches about 1.2 for k=10. A hyperscaling relation seems to relate the various universality classes. Through a Un simple modèle stochastique d'évolution Darwinienne engendrant des arbres phylogénétiques est développé. Le modèle est basé sur un processus de branchement tenant compte d'effets de compétitions et de corrélations. En présence de corrélations à courte portée, le processus s'auto-organise dans un état critique caractérisé par l'intermittence d'explosions d'activité de toutes tailles. Sur une échelle pseudo-géologique, ce comportement est en accord avec les caractéristiques ponctualistes de l'évolution biologique. Les arbres phylogénétiques simulés sont auto-similaires. La dynamique des régimes transitoires montre une décroissance en loi de puissance du

  4. The mechanism of self-organized beating of cilia

    NASA Astrophysics Data System (ADS)

    Vidyadharan, Jyothish Sulochana

    The internal structure and physical properties of cilia are well known. The relevant hydrodynamics is also well known. But the mechanism behind the coordinated activity of the dynein molecular motors is not known. Based on experimental observations, it has been concluded that this mechanism cannot be due to control from the cell body. The possible mechanism has to be self-organized and the trigger for motor activation/deactivation has to be something related to the geometry of the ciliary axoneme. This thesis critically evaluates the most widely currently cited models and suggests an alternative model for how cilia beat. From the literature we obtained wave forms of ciliary beating at different instants in the beat cycle. These instants were digitized and interpolated. From this data, we were able to calculate the hydrodynamic force distribution (external force distribution) on the cilia and the translational and rotational velocities of the cell body. Once the hydrodynamic force distribution was obtained, we calculated the internal force distribution in the cilium using an equation we derived. Once this was known, we were able to calculate parameters of the ciliary axoneme such as the dynamic stiffness. The stiffness is the ratio of the first Fourier modes of the internal force distribution and the relative sliding between the doublet microtubules that form the axoneme. We found that the first mode was the dominant one and is the one we used for calculations. We were also able to calculate the energy involved in formation and propagation of the wave that produces the ciliary beating. We discovered that the dynamic stiffness varies along the length of a cilium. We determined that in the central region of the cilium, the stiffness is almost purely imaginary which means that the sliding velocity follows the internal force generation in that region rather than sliding. We also found that in Fourier space, the flexural rigidity (kappa=EI where E is Young's modulus and

  5. Geochemical Self-Organization and the Evolution of Permeability

    NASA Astrophysics Data System (ADS)

    Ladd, T.; Szymczak, P.; Upadhyay, V.

    2014-12-01

    Reactive infiltration instabilities occur in a wide range of geophysical and geotechnical systems. The simplest such instability occurs when fluid flows between two soluble plates, which is an idealized model of fractured limestone. Even when the initial aperture is uniform at the nanoscale, an instability in the reaction front develops leading to the formation of pronounced solutional channels or "wormholes". We have previously suggested that this instability may help explain the onset of large underground caves systems, by allowing a much deeper penetration of reactant than is possible by uniform opening of the fracture. Numerical simulations suggest that dissolution may be a form of self-organization where patterns seem to develop in similar ways over a wide range of porosity distribution. If so, this offers the possibility of developing a theoretical understanding of the geomorphologies formed by dissolution-precipitation reactions independent (to some extent) of the initial conditions. We present numerical simulations of the dissolution of a porous matrix to indicate the insensitivity of key statistical markers to the initial distribution of porosity. Theory and simulations predict that a planar dissolution front breaks up into a number of competing fingers. Predictions from a linear stability analysis in porous and fractured rocks vary considerably depending on the underlying assumptions about flow rates and reaction rates. Once fingers develop, the nature of the competition is different in fractured and porous rocks. We are presently trying to understand the growth of individual fingers (see attached image), which numerical simulations show to be steadily propagating in time, much like the better-known phenomena of viscous fingering. We will indicate the difficulties that have so far prevented us from finding an explicit solution to the finger size, shape and velocity. Figure Caption Concentration profiles in a steadily-growing wormhole: Top - diffusion

  6. Identification of lithofacies using Kohonen self-organizing maps

    USGS Publications Warehouse

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.

    2002-01-01

    Lithofacies identification is a primary task in reservoir characterization. Traditional techniques of lithofacies identification from core data are costly, and it is difficult to extrapolate to non-cored wells. We present a low-cost automated technique using Kohonen self-organizing maps (SOMs) to identify systematically and objectively lithofacies from well log data. SOMs are unsupervised artificial neural networks that map the input space into clusters in a topological form whose organization is related to trends in the input data. A case study used five wells located in Appleton Field, Escambia County, Alabama (Smackover Formation, limestone and dolomite, Oxfordian, Jurassic). A five-input, one-dimensional output approach is employed, assuming the lithofacies are in ascending/descending order with respect to paleoenvironmental energy levels. To consider the possible appearance of new logfacies not seen in training mode, which may potentially appear in test wells, the maximum number of outputs is set to 20 instead of four, the designated number of lithosfacies in the study area. This study found eleven major clusters. The clusters were compared to depositional lithofacies identified by manual core examination. The clusters were ordered by the SOM in a pattern consistent with environmental gradients inferred from core examination: bind/boundstone, grainstone, packstone, and wackestone. This new approach predicted lithofacies identity from well log data with 78.8% accuracy which is more accurate than using a backpropagation neural network (57.3%). The clusters produced by the SOM are ordered with respect to paleoenvironmental energy levels. This energy-related clustering provides geologists and petroleum engineers with valuable geologic information about the logfacies and their interrelationships. This advantage is not obtained in backpropagation neural networks and adaptive resonance theory neural networks. ?? 2002 Elsevier Science Ltd. All rights reserved.

  7. Self-organization and the dynamical nature of ventricular fibrillation

    NASA Astrophysics Data System (ADS)

    Jalife, José; Gray, Richard A.; Morley, Gregory E.; Davidenko, Jorge M.

    1998-03-01

    This article reviews recent data supporting the conjecture that, in the structurally and electrophysiologically normal heart, cardiac fibrillation is not a totally random phenomenon. Experimental and numerical studies based on the theory of excitable media suggest that fibrillation in the mammalian ventricles is the result of self-organized three-dimensional (3-D) electrical rotors giving rise to scroll waves that move continuously (i.e., drift) throughout the heart at varying speeds. A brief review of studies on the dynamics of rotors in two-dimensional (2-D) and 3-D excitable media is presented with emphasis on the experimental demonstration of such dynamics in cardiac muscle of various species. The discussion is centered on rotor dynamics in the presence and the absence of structural heterogeneities, and in the phenomena of drifting and anchoring, which in the electrocardiogram (ECG) may manifest as life-threatening cardiac rhythm disturbances. For instance, in the rabbit heart, a single electrical rotor that drifts rapidly throughout the ventricles gives rise to complex patterns of excitation. In the ECG such patterns are indistinguishable from ventricular fibrillation. On the other hand, a rotor that anchors to a discontinuity or defect in the muscle (e.g., a scar, a large artery or a bundle of connective tissue) may result in stationary rotating activity, which in the ECG is manifested as a form of so-called "monomorphic" ventricular tachycardia. More recent data show that ventricular fibrillation occurs in mammals irrespective of size or species. While in small hearts, such as those of mice and rabbits, a single drifting or meandering rotor can result in fibrillation, in larger hearts, such as the sheep and possibly the human, fibrillation occurs in the form of a relatively small number of coexisting but short-lived rotors. Overall, the work discussed here has paved the way for a better understanding of the mechanisms of fibrillation in the normal, as well

  8. 25 Years of Self-organized Criticality: Concepts and Controversies

    NASA Astrophysics Data System (ADS)

    Watkins, Nicholas W.; Pruessner, Gunnar; Chapman, Sandra C.; Crosby, Norma B.; Jensen, Henrik J.

    2016-01-01

    Introduced by the late Per Bak and his colleagues, self-organized criticality (SOC) has been one of the most stimulating concepts to come out of statistical mechanics and condensed matter theory in the last few decades, and has played a significant role in the development of complexity science. SOC, and more generally fractals and power laws, have attracted much comment, ranging from the very positive to the polemical. The other papers (Aschwanden et al. in Space Sci. Rev., 2014, this issue; McAteer et al. in Space Sci. Rev., 2015, this issue; Sharma et al. in Space Sci. Rev. 2015, in preparation) in this special issue showcase the considerable body of observations in solar, magnetospheric and fusion plasma inspired by the SOC idea, and expose the fertile role the new paradigm has played in approaches to modeling and understanding multiscale plasma instabilities. This very broad impact, and the necessary process of adapting a scientific hypothesis to the conditions of a given physical system, has meant that SOC as studied in these fields has sometimes differed significantly from the definition originally given by its creators. In Bak's own field of theoretical physics there are significant observational and theoretical open questions, even 25 years on (Pruessner 2012). One aim of the present review is to address the dichotomy between the great reception SOC has received in some areas, and its shortcomings, as they became manifest in the controversies it triggered. Our article tries to clear up what we think are misunderstandings of SOC in fields more remote from its origins in statistical mechanics, condensed matter and dynamical systems by revisiting Bak, Tang and Wiesenfeld's original papers.

  9. Biomechanical factors contributing to self-organization in seagrass landscapes

    USGS Publications Warehouse

    Fonseca, M.S.; Koehl, M.A.R.; Kopp, B.S.

    2007-01-01

    individual shoot self-organization driven by reduced force and drag on the shoots and somewhat improved light capture.

  10. IP core implementation of a self-organizing neural network.

    PubMed

    Hendry, D C; Duncan, A A; Lightowler, N

    2003-01-01

    This paper reports on the design issues and subsequent performance of a soft intellectual property (IP) core implementation of a self-organizing neural network. The design is a development of a previous 0.65-/spl mu/m single silicon chip providing an array of 256 neurons, where each neuron stores a 16 element reference vector. Migrating the design to a soft IP core presents challenges in achieving the required performance as regards area, power, and clock speed. This same migration, however, offers opportunities for parameterizing the design in a manner which permits a single soft core to meet the requirements of many end users. Thus, the number of neurons within the single instruction multiple data (SIMD) array, the number of elements per reference vector, and the number of bits of each such element are defined by synthesis time parameters. The construction of the SIMD array of neurons is presented including performance results as regards power, area, and classifications per second . For typical parameters (256 neurons with 16 elements per reference vector) the design provides over 2 000 000 classifications per second using a mainstream 0.18-/spl mu/m digital process. A RISC processor, the array controller (AC), provides both the instruction stream and data to the SIMD array of neurons and an interface to a host processor. The design of this processor is discussed with emphasis on the control aspects which permit supply of a continuous instruction stream to the SIMD array and a flexible interface with the host processor. PMID:18244562

  11. Hierarchical self-organization of non-cooperating individuals.

    PubMed

    Nepusz, Tamás; Vicsek, Tamás

    2013-01-01

    Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introduce an approach which is capable of reproducing the emergence of a multi-levelled network structure based on the plausible assumption that the individuals (representing the nodes of the network) can make the right estimate about the state of their changing environment to a varying degree. Our model accounts for a fundamental feature of knowledge-based organizations: the less capable individuals tend to follow those who are better at solving the problems they all face. We find that relatively simple rules lead to hierarchical self-organization and the specific structures we obtain possess the two, perhaps most important features of complex systems: a simultaneous presence of adaptability and stability. In addition, the performance (success score) of the emerging networks is significantly higher than the average expected score of the individuals without letting them copy the decisions of the others. The results of our calculations are in agreement with a related experiment and can be useful from the point of designing the optimal conditions for constructing a given complex social structure as well as understanding the hierarchical organization of such biological structures of major importance as the regulatory pathways or the dynamics of neural networks. PMID:24349070

  12. Evolution of Self-Organized Task Specialization in Robot Swarms

    PubMed Central

    Ferrante, Eliseo; Turgut, Ali Emre; Duéñez-Guzmán, Edgar; Dorigo, Marco; Wenseleers, Tom

    2015-01-01

    Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as “task partitioning”, whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization. PMID:26247819

  13. Evolution of Self-Organized Task Specialization in Robot Swarms.

    PubMed

    Ferrante, Eliseo; Turgut, Ali Emre; Duéñez-Guzmán, Edgar; Dorigo, Marco; Wenseleers, Tom

    2015-08-01

    Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as "task partitioning", whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization. PMID:26247819

  14. Depositional dynamics and self-organization in travertine sedimentary systems

    NASA Astrophysics Data System (ADS)

    Violante, C.; Marino, G.; Sammartino, S.

    2003-04-01

    limited downhill by steeper slopes. This in turn results in a new sedimentary environments, including ponds and shallow lakes in the flattened areas, and waterfalls along the steeper and steeper downhill edge of the travertine prisms. The sedimentary organization of travertine deposits points to spatial and temporal patterns resulting from dynamics internal to the system. This imply self-organization and non-linear bio-chemical deposition rather then external forcing.

  15. Geomorphometirc Segmentation of Shield Deserts by Self-Organizing Maps

    NASA Astrophysics Data System (ADS)

    Foroutan, M.; Kompanizare, M.; Ehsani, A. H.

    2015-12-01

    Shield deserts have developed on ancient crystalline bedrocks and mainly composed of folded and faulted rocks hardened by heat and pressure over millions of years. They were unearthed by erosion and form steep-sided hills and basins filled with sediments. The Sahara, Arabian, southern African, central Kavir and Australian deserts are in this group. Their ranges usually supply groundwater resources or in some regions contain huge oil reservoirs. Geomorphological segmentation of shield deserts is one of the fundamental tools in their land use or site investigation planning as well as in their surface water and groundwater management. In many studies the morphology of shield deserts has been investigated by limited qualitative and subjective methods using limited number of simple parameters such as surface elevation and slope. However the importance of these regions supports the need for their accurate and quantitative morphologic classification. The present study attempts to implement a quantitative method, Self-Organizing Map (SOM), for geomorphological classification of a typical shield desert within Kavir Desert, Iran. The area is tectonically stable and characterized by flat clay pans, playas, well-developed pediments around scattered and low elevation ranges. Twenty-two multi-scale morphometric parameters were derived from the first- to third-orders partial derivatives of the surface elevation. Seven optimized parameters with their proper scales were selected by Artificial Neural Networks, Optimum Index Factor, Davies-Bouldin Index and statistic models. Finally, the area was segmented to seven homogeneous areas by SOM algorithm. The results revealed the most distinguishing parameter set (MDPS) for morphologic segmentation of shield deserts. The same segmentation results through using MDPS for another shield deserts in Australia proves the applicability of MDPS for shield deserts segmentation.

  16. Identification of lithofacies using Kohonen self-organizing maps

    NASA Astrophysics Data System (ADS)

    Chang, Hsien-Cheng; Kopaska-Merkel, David C.; Chen, Hui-Chuan

    2002-02-01

    Lithofacies identification is a primary task in reservoir characterization. Traditional techniques of lithofacies identification from core data are costly, and it is difficult to extrapolate to non-cored wells. We present a low-cost automated technique using Kohonen self-organizing maps (SOMs) to identify systematically and objectively lithofacies from well log data. SOMs are unsupervised artificial neural networks that map the input space into clusters in a topological form whose organization is related to trends in the input data. A case study used five wells located in Appleton Field, Escambia County, Alabama (Smackover Formation, limestone and dolomite, Oxfordian, Jurassic). A five-input, one-dimensional output approach is employed, assuming the lithofacies are in ascending/descending order with respect to paleoenvironmental energy levels. To consider the possible appearance of new logfacies not seen in training mode, which may potentially appear in test wells, the maximum number of outputs is set to 20 instead of four, the designated number of lithofacies in the study area. This study found eleven major clusters. The clusters were compared to depositional lithofacies identified by manual core examination. The clusters were ordered by the SOM in a pattern consistent with environmental gradients inferred from core examination: bind/boundstone, grainstone, packstone, and wackestone. This new approach predicted lithofacies identity from well log data with 78.8% accuracy which is more accurate than using a backpropagation neural network (57.3%). The clusters produced by the SOM are ordered with respect to paleoenvironmental energy levels. This energy-related clustering provides geologists and petroleum engineers with valuable geologic information about the logfacies and their interrelationships. This advantage is not obtained in backpropagation neural networks and adaptive resonance theory neural networks.

  17. Hierarchical Self-Organization of Non-Cooperating Individuals

    PubMed Central

    Nepusz, Tamás; Vicsek, Tamás

    2013-01-01

    Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introduce an approach which is capable of reproducing the emergence of a multi-levelled network structure based on the plausible assumption that the individuals (representing the nodes of the network) can make the right estimate about the state of their changing environment to a varying degree. Our model accounts for a fundamental feature of knowledge-based organizations: the less capable individuals tend to follow those who are better at solving the problems they all face. We find that relatively simple rules lead to hierarchical self-organization and the specific structures we obtain possess the two, perhaps most important features of complex systems: a simultaneous presence of adaptability and stability. In addition, the performance (success score) of the emerging networks is significantly higher than the average expected score of the individuals without letting them copy the decisions of the others. The results of our calculations are in agreement with a related experiment and can be useful from the point of designing the optimal conditions for constructing a given complex social structure as well as understanding the hierarchical organization of such biological structures of major importance as the regulatory pathways or the dynamics of neural networks. PMID:24349070

  18. Wave extreme characterization using self-organizing maps

    NASA Astrophysics Data System (ADS)

    Barbariol, Francesco; Marcello Falcieri, Francesco; Scotton, Carlotta; Benetazzo, Alvise; Carniel, Sandro; Sclavo, Mauro

    2016-03-01

    The self-organizing map (SOM) technique is considered and extended to assess the extremes of a multivariate sea wave climate at a site. The main purpose is to obtain a more complete representation of the sea states, including the most severe states that otherwise would be missed by a SOM. Indeed, it is commonly recognized, and herein confirmed, that a SOM is a good regressor of a sample if the frequency of events is high (e.g., for low/moderate sea states), while a SOM fails if the frequency is low (e.g., for the most severe sea states). Therefore, we have considered a trivariate wave climate (composed by significant wave height, mean wave period and mean wave direction) collected continuously at the Acqua Alta oceanographic tower (northern Adriatic Sea, Italy) during the period 1979-2008. Three different strategies derived by SOM have been tested in order to capture the most extreme events. The first contemplates a pre-processing of the input data set aimed at reducing redundancies; the second, based on the post-processing of SOM outputs, consists in a two-step SOM where the first step is applied to the original data set, and the second step is applied on the events exceeding a given threshold. A complete graphical representation of the outcomes of a two-step SOM is proposed. Results suggest that the post-processing strategy is more effective than the pre-processing one in order to represent the wave climate extremes. An application of the proposed two-step approach is also provided, showing that a proper representation of the extreme wave climate leads to enhanced quantification of, for instance, the alongshore component of the wave energy flux in shallow water. Finally, the third strategy focuses on the peaks of the storms.

  19. Seismically damaged regolith as self-organized fragile geological feature

    NASA Astrophysics Data System (ADS)

    Sleep, Norman H.

    2011-12-01

    The S-wave velocity in the shallow subsurface within seismically active regions self-organizes so that typical strong dynamic shear stresses marginally exceed the Coulomb elastic limit. The dynamic velocity from major strike-slip faults yields simple dimensional relations. The near-field velocity pulse is essentially a Love wave. The dynamic shear strain is the ratio of the measured particle velocity over the deep S-wave velocity. The shallow dynamic shear stress is this quantity times the local shear modulus. The dynamic shear traction on fault parallel vertical planes is finite at the free surface. Coulomb failure occurs on favorably oriented fractures and internally in intact rock. I obtain the equilibrium shear modulus by starting a sequence of earthquakes with intact stiff rock extending all the way to the surface. The imposed dynamic shear strain in stiff rock causes Coulomb failure at shallow depths and leaves cracks in it wake. Cracked rock is more compliant than the original intact rock. Cracked rock is also weaker in friction, but shear modulus changes have a larger effect. Each subsequent event causes additional shallow cracking until the rock becomes compliant enough that it just reaches Coulomb failure over a shallow depth range of tens to hundreds of meters. Further events maintain the material at the shear modulus as a function where it just fails. The formalism provided in the paper yields reasonable representation of the S-wave velocity in exhumed sediments near Cajon Pass and the San Fernando Valley of California. A general conclusion is that shallow rocks in seismically active areas just become nonlinear during typical shaking. This process causes transient changes in S-wave velocity, but not strong nonlinear attenuation of seismic waves. Wave amplitudes significantly larger than typical ones would strongly attenuate and strongly damage the rock.

  20. Hyperspectral Image Classification using a Self-Organizing Map

    NASA Technical Reports Server (NTRS)

    Martinez, P.; Gualtieri, J. A.; Aguilar, P. L.; Perez, R. M.; Linaje, M.; Preciado, J. C.; Plaza, A.

    2001-01-01

    The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

  1. Evidence of self-organization in a gregarious land-dwelling crustacean (Isopoda: Oniscidea).

    PubMed

    Broly, Pierre; Mullier, Romain; Devigne, Cédric; Deneubourg, Jean-Louis

    2016-01-01

    How individuals modulate their behavior according to social context is a major issue in the understanding of group initiation, group stability and the distribution of individuals. Herein, we investigated the mechanisms of aggregation behavior in Porcellio scaber, a terrestrial isopod member of the Oniscidea, a unique and common group of terrestrial crustaceans. We performed binary choice tests using shelters with a wide range of population densities (from 10 to 150 individuals). First, the observed collective choices of shelters strengthen the demonstration of a social inter-attraction in terrestrial isopods; especially, in less than 10 min, the aggregation reaches its maximal value, and in less than 100 s, the collective choice is made, i.e., one shelter is selected. In addition, the distribution of individuals shows the existence of (1) quorum rules, by which an aggregate cannot emerge under a threshold value of individuals, and (2) a maximum population size, which leads to a splitting of the populations. These collective results are in agreement with the individual's probability of joining and leaving an aggregate attesting to a greater attractiveness of the group to migrants and greater retention of conspecifics with group size. In this respect, we show that the emergence of aggregation in terrestrial isopods is based on amplification mechanisms. And lastly, our results indicate how local cues about the spatial organization of individuals may favor this emergence and how individuals spatiotemporally reorganize toward a compact form reducing the exchange with the environment. This study provides the first evidence of self-organization in a gregarious crustacean, similar as has been widely emphasized in gregarious insects and eusocial insects. PMID:26391028

  2. Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

    PubMed

    Zhang, WenJun

    2007-07-01

    Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance

  3. Evolutionary Cell Computing: From Protocells to Self-Organized Computing

    NASA Technical Reports Server (NTRS)

    Colombano, Silvano; New, Michael H.; Pohorille, Andrew; Scargle, Jeffrey; Stassinopoulos, Dimitris; Pearson, Mark; Warren, James

    2000-01-01

    On the path from inanimate to animate matter, a key step was the self-organization of molecules into protocells - the earliest ancestors of contemporary cells. Studies of the properties of protocells and the mechanisms by which they maintained themselves and reproduced are an important part of astrobiology. These studies also have the potential to greatly impact research in nanotechnology and computer science. Previous studies of protocells have focussed on self-replication. In these systems, Darwinian evolution occurs through a series of small alterations to functional molecules whose identities are stored. Protocells, however, may have been incapable of such storage. We hypothesize that under such conditions, the replication of functions and their interrelationships, rather than the precise identities of the functional molecules, is sufficient for survival and evolution. This process is called non-genomic evolution. Recent breakthroughs in experimental protein chemistry have opened the gates for experimental tests of non-genomic evolution. On the basis of these achievements, we have developed a stochastic model for examining the evolutionary potential of non-genomic systems. In this model, the formation and destruction (hydrolysis) of bonds joining amino acids in proteins occur through catalyzed, albeit possibly inefficient, pathways. Each protein can act as a substrate for polymerization or hydrolysis, or as a catalyst of these chemical reactions. When a protein is hydrolyzed to form two new proteins, or two proteins are joined into a single protein, the catalytic abilities of the product proteins are related to the catalytic abilities of the reactants. We will demonstrate that the catalytic capabilities of such a system can increase. Its evolutionary potential is dependent upon the competition between the formation of bond-forming and bond-cutting catalysts. The degree to which hydrolysis preferentially affects bonds in less efficient, and therefore less well

  4. Biological and Physical Thresholds in Biogeomorphologically Self-organizing Systems.

    NASA Astrophysics Data System (ADS)

    Herman, P.; Bouma, T. J.; Van de Koppel, J.; Borsje, B.; van Belzen, J.; Balke, T.

    2012-12-01

    Many coastal and estuarine landscapes are formed as a consequence of biological-physical interactions. We review examples that we recently studied: coastal vegetations, microphytobenthos-stabilized mudflats, macrofauna-dominated sediments, sand wave formation influenced by animals. In these diverse ecosystems, self-organisation of the coupled landscape results from the existence of positive feedback loops between the physical and biological components. We focus on the question where, in space and/or in time, such feedback systems develop and what determines their persistence and their ability to shape the landscape. We hypothesize that an equilibrium of forces between physical and biological factors is necessary for a feedback loop to develop. This implies a scale match and a commensurate strength of the different factors. There are many examples of systems that are physically too dynamic for the development of biological populations that affect the landscape. We also show an example where biological influence, in the form of strong grazing pressure on microphytobenthos, disrupts a self-organized system on a mudflat. Thus, we define thresholds in parameter space which constrain the development of strongly interacting biogeomorphological systems. The hypothesis of commensurate physical and biological forces as a condition for the development of biogeomorphological systems has important consequences for the establishment and recruitment of such systems. Biological interactions and biological effects on the physical system develop in time with the recruitment and maturation of the biological system. Fully developed systems can therefore be in balance with stronger physical forces than immature, early recruiting phases. This represents a successional threshold that is difficult to overcome. We stress the importance of stochastic variability in physical conditions at a diversity of scales as a prerequisite for phase transitions from physically dominated to

  5. The sequence of self-organization of MHD plasmas

    NASA Astrophysics Data System (ADS)

    Bellan, P. M.

    2007-12-01

    Traditional models of plasma magnetic self-organization assume zero β on the grounds that the actual β is very small. However, a model [1] inspired by laboratory experiments suggest that the behavior of plasma with small β is not the same as a zero β \\ plasma because the behavior involves a competition between β and another small parameter, namely α2a2 where α=μ0I/ψ. Here, ψ is the axial flux in the flux tube, I is the axial current flowing in the flux tube, and a is the flux tube radius. The plasma can be considered as an assembly of small aspect ratio individually pressurized flux tubes, somewhat like strands of spaghetti wrapped around each other. Each flux tube (spaghetti strand) is not force-free, but rather has its axial current I balance a small radial pressure gradient such that the pressure is peaked on the flux tube axis. To an outsider the flux tube appears as an element of force-free current because the outsider is aware that the current I in the flux tube flows parallel to the flux tube axis. The external observer makes this deduction by measuring the azimuthal magnetic field associated with the axial current. Flux tubes interact with each other by the current in one flux tube `feeling' the azimuthal magnetic field due to an adjacent flux tube. The flux tubes collectively try to assume a force-free state whereby the current in each flux tube flows parallel to the magnetic field produced by all the other flux tubes and by any external source for the magnetic field. \\qquad The sequence of evolution is (i) formation of the individual plasma-filled flux tubes via axial pumping of plasma from the ends of the flux tubes to fill up the flux tubes with plasma (this process also collimates [1] the individual flux tubes so that they look like spaghetti strands), (ii) kink instability of the individual collimated flux tubes, and (iii) interaction of adjacent collimated flux tubes with each other resulting in the flux tubes wrapping around each other

  6. Phase transitions in stochastic self-organizing maps

    NASA Astrophysics Data System (ADS)

    Graepel, Thore; Burger, Matthias; Obermayer, Klaus

    1997-10-01

    We describe the development of neighborhood-preserving stochastic maps in terms of a probabilistic clustering problem. Starting from a cost function for central clustering that incorporates distortions from channel noise, we derive a soft topographic vector quantization algorithm (STVQ) which is based on the maximum entropy principle, and which maximizes the corresponding likelihood in an expectation-maximization fashion. Among other algorithms, a probabilistic version of Kohonen's self-organizing map (SOM) is derived from STVQ as a computationally efficient approximation of the E step. The foundation of STVQ in statistical physics motivates a deterministic annealing scheme in the temperature parameter β, and leads to a robust minimization algorithm of the clustering cost function. In particular, this scheme offers an alternative to the common stepwise shrinking of the neighborhood width in the SOM, and makes it possible to use its neighborhood function solely to encode the desired neighborhood relations between the clusters. The annealing in β, which corresponds to a stepwise refinement of the resolution of representation in data space, leads to the splitting of an existing cluster representation during the ``cooling'' process. We describe this phase transition in terms of the covariance matrix C of the data and the transition matrix H of the channel noise, and calculate the critical temperatures and modes as functions of the eigenvalues and eigenvectors of C and H. The analysis is extended to the phenomenon of the automatic selection of feature dimensions in dimension-reducing maps, thus leading to a ``batch'' alternative to the Fokker-Planck formalism for on-line learning. The results provide insights into the relation between the width of the neighborhood and the temperature parameter β: It is shown that the phase transition which leads to the representation of the excess dimensions can be triggered not only by a change in the statistics of the input data

  7. Control of Separation and Diameter of Ag Nanorods through Self-organized Seeds.

    PubMed

    Elliott, Paul R; Stagon, Stephen P; Huang, Hanchen

    2015-01-01

    This paper proposes a mechanism of controlling the diameter and separation of metallic nanorods from physical vapor deposition through self-organized seeds and experimentally demonstrates the feasibility using Ag as the prototype metal, In as the seed, and Si the substrate. Being non-wetting on Si substrates, deposited In atoms self-organize into islands. Subsequently deposited Ag atoms attach to In islands, rather than to Si substrates, due to preferential bonding and geometrical shadowing. The experimental results show that self-organized In seeds of 5 nm nominal thickness give rise to the best separation and the smallest diameter of Ag nanorods. PMID:26585104

  8. Control of Separation and Diameter of Ag Nanorods through Self-organized Seeds

    PubMed Central

    Elliott, Paul R.; Stagon, Stephen P.; Huang, Hanchen

    2015-01-01

    This paper proposes a mechanism of controlling the diameter and separation of metallic nanorods from physical vapor deposition through self-organized seeds and experimentally demonstrates the feasibility using Ag as the prototype metal, In as the seed, and Si the substrate. Being non-wetting on Si substrates, deposited In atoms self-organize into islands. Subsequently deposited Ag atoms attach to In islands, rather than to Si substrates, due to preferential bonding and geometrical shadowing. The experimental results show that self-organized In seeds of 5 nm nominal thickness give rise to the best separation and the smallest diameter of Ag nanorods. PMID:26585104

  9. Kohonen self-organizing feature map and its use in clustering

    NASA Astrophysics Data System (ADS)

    Torma, Markus

    1994-08-01

    Cluster analysis is an important part of pattern recognition. In this paper we present the applicability of one neural network model, namely Kohonen self-organizing feature map, to cluster analysis. The aim is to develop a method which could determine the correct number of clusters by itself. First, the general concept of neural networks and detailed introduction to Kohonen self-organizing feature map are discussed. Then, the suitability of Kohonen self- organizing feature map to cluster analysis is discussed and some simulations are presented.

  10. Development of a compact tomography camera system using a multianode photomultiplier tube for compact torus experiments.

    PubMed

    Tomuro, H; Asai, T; Iguchi, K; Takahashi, Ts; Hirano, Y

    2010-10-01

    A compact tomography camera system consisting of a photomultiplier tube, a multislit optical system, and a band-pass interference filter has been developed. The viewing area and spatial resolution can be configured by the arrangement of the slit system. The camera system has been specially designed for self-organized compact torus experiments having strong magnetohydrodynamics events with a submicrosecond time-scale. The developed system has been tested on a field-reversed configuration formed by the field-reversed theta-pinch. Performance evaluation of the system has been performed by comparison to the former optical system. PMID:21034053

  11. VIBRATION COMPACTION

    DOEpatents

    Hauth, J.J.

    1962-07-01

    A method of compacting a powder in a metal container is described including the steps of vibrating the container at above and below the resonant frequency and also sweeping the frequency of vibration across the resonant frequency several times thereby following the change in resonant frequency caused by compaction of the powder. (AEC)

  12. Multimodal Responses of Self-Organized Circuitry in Electronically Phase Separated Materials

    DOE PAGESBeta

    Herklotz, Andreas; Guo, Hangwen; Wong, Anthony T.; Lee, Ho Nyung; Rack, Philip D.; Ward, Thomas Z.

    2016-07-13

    When confining an electronically phase we separated manganite film to the scale of its coexisting self-organized metallic and these insulating domains allows resistor-capacitor circuit-like responses while providing both electroresistive and magnetoresistive switching functionality.

  13. Number theoretic example of scale-free topology inducing self-organized criticality.

    PubMed

    Luque, Bartolo; Miramontes, Octavio; Lacasa, Lucas

    2008-10-10

    In this Letter we present a general mechanism by which simple dynamics running on networks become self-organized critical for scale-free topologies. We illustrate this mechanism with a simple arithmetic model of division between integers, the division model. This is the simplest self-organized critical model advanced so far, and in this sense it may help to elucidate the mechanism of self-organization to criticality. Its simplicity allows analytical tractability, characterizing several scaling relations. Furthermore, its mathematical nature brings about interesting connections between statistical physics and number theoretical concepts. We show how this model can be understood as a self-organized stochastic process embedded on a network, where the onset of criticality is induced by the topology. PMID:18999649

  14. Self-organization with equilibration: a model for the intermediate phase in rigidity percolation.

    PubMed

    Chubynsky, M V; Brière, M-A; Mousseau, Normand

    2006-07-01

    Recent experimental results for covalent glasses suggest the existence of an intermediate phase attributed to the self-organization of the glass network resulting from the tendency to minimize its internal stress. However, the exact nature of this experimentally measured phase remains unclear. We modified a previously proposed model of self-organization by generating a uniform sampling of stress-free networks. In our model, studied on a diluted triangular lattice, an unusual intermediate phase appears, in which both rigid and floppy networks have a chance to occur, a result also observed in a related model on a Bethe lattice by Barré et al[Phys. Rev. Lett. 94, 208701 (2005)]. Our results for the bond-configurational entropy of self-organized networks, which turns out to be only about 2% lower than that of random networks, suggest that a self-organized intermediate phase could be common in systems near the rigidity percolation threshold. PMID:16907160

  15. Quantum ground state of self-organized atomic crystals in optical resonators

    SciTech Connect

    Fernandez-Vidal, Sonia; De Chiara, Gabriele; Larson, Jonas; Morigi, Giovanna

    2010-04-15

    Cold atoms, driven by a laser and simultaneously coupled to the quantum field of an optical resonator, may self-organize in periodic structures. These structures are supported by the optical lattice, which emerges from the laser light they scatter into the cavity mode and form when the laser intensity exceeds a threshold value. We study theoretically the quantum ground state of these structures above the pump threshold of self-organization by mapping the atomic dynamics of the self-organized crystal to a Bose-Hubbard model. We find that the quantum ground state of the self-organized structure can be the one of a Mott insulator, depending on the pump strength of the driving laser. For very large pump strengths, where the intracavity-field intensity is maximum and one would expect a Mott-insulator state, we find intervals of parameters where the phase is compressible. These states could be realized in existing experimental setups.

  16. Self organization of wireless sensor networks using ultra-wideband radios

    DOEpatents

    Dowla, Farid U.; Nekoogar, Franak; Spiridon, Alex

    2009-06-16

    A novel UWB communications method and system that provides self-organization for wireless sensor networks is introduced. The self-organization is in terms of scalability, power conservation, channel estimation, and node synchronization in wireless sensor networks. The UWB receiver in the present invention adds two new tasks to conventional TR receivers. The two additional units are SNR enhancing unit and timing acquisition and tracking unit.

  17. Creation of ''Quantum Platelets'' via Strain-Controlled Self-Organization at Steps

    SciTech Connect

    Li, Adam; Liu, Feng; Petrovykh, D. Y.; Lin, J.-L.; Viernow, J.; Himpsel, F. J.; Lagally, M. G.

    2000-12-18

    We demonstrate, by both theory and experiment, the strain-induced self-organized formation of ''quantum platelets,'' monolayer-thick islands of finite dimensions. They form at the early stage of heteroepitaxial growth on a substrate with regularly spaced steps, and align along the steps. In the direction perpendicular to substrate steps, the island position and spacing can be preselected through substrate miscut. Along the steps, the island size and density are controlled by self-organized growth.

  18. On the wavelength of self-organized shoreline sand waves

    NASA Astrophysics Data System (ADS)

    Falqués, A.; van den Berg, N.; Ribas, F.; Caballeria, M.; Calvete, D.

    2012-04-01

    Shoreline sand waves are undulations of the shoreline that extend into the bathymetry up to a certain depth. Here we will focus on self-organized sand waves that form due to shoreline instability in case of very oblique wave incidence (Ashton et al., 2001). The model of Ashton and co-authors did not predict any wavelength selection for the emerging sand waves whereas Falqués and Calvete (2005) predicted a wavelength selection in the range 4-15 km. This difference is attributable to that Falqués and Calvete (2005) computed wave refraction and shoaling over the actual curvilinear depth contours while Ashton et al. (2001) assumed locally rectilinear and parallel contours. Although there exist shoreline features at a larger scale (Ashton et al. 2001; Falqués et al. 2011) sand waves at a few km scale are more common (Ruessink and Jeuken, 2002; Davidson-Arnott and van Heyningen, 2003; Falqués et al., 2011; Medellin et al., 2008) . While their characteristic wavelength is a robust model output (Falqués and Calvete, 2005; Uguccioni et al., 2006; van den Berg et al., 2011) the physical reasons for the existence of a wavelength selection are still unknown. Furthermore, the parameter dependence of the dominant wavelength, Lm, is largely unexplored. In particular, the disparity between the large length scale of sand waves and the relevant length scales of the problem: width of the surf zone, water wave wavelength, etc. is intriguing. The aim of the present contribution is to gain insight into those physical reasons and the dependence of Lm on beach profile and water wave properties. The essence of sandwave behaviour can be captured with the simple one-line shoreline modelling concept by looking at the alongshore position of the maximum in total transport rate Q, which is here investigated with both the linearized model of Falqués and Calvete (2005) and the nonlinear model of van den Berg et al. (2011) . It is found that the position of that maximum is largely controlled

  19. The Three-Dimensional Dynamics of Actin Waves, a Model of Cytoskeletal Self-Organization

    PubMed Central

    Bretschneider, Till; Anderson, Kurt; Ecke, Mary; Müller-Taubenberger, Annette; Schroth-Diez, Britta; Ishikawa-Ankerhold, Hellen C.; Gerisch, Günther

    2009-01-01

    Actin polymerization is typically initiated at specific sites in a cell by membrane-bound protein complexes, and the resulting structures are involved in specialized cellular functions, such as migration, particle uptake, or mitotic division. Here we analyze the potential of the actin system to self-organize into waves that propagate on the planar, substrate-attached membrane of a cell. We show that self-assembly involves the ordered recruitment of proteins from the cytoplasmic pool and relate the organization of actin waves to their capacity for applying force. Three proteins are shown to form distinct three-dimensional patterns in the actin waves. Myosin-IB is enriched at the wave front and close to the plasma membrane, the Arp2/3 complex is distributed throughout the waves, and coronin forms a sloping layer on top of them. CARMIL, a protein that links myosin-IB to the Arp2/3 complex, is also recruited to the waves. Wave formation does not depend on signals transmitted by heterotrimeric G-proteins, nor does their propagation require SCAR, a regulator upstream of the Arp2/3 complex. Propagation of the waves is based on an actin treadmilling mechanism, indicating a program that couples actin assembly to disassembly in a three-dimensional pattern. When waves impinge on the cell perimeter, they push the edge forward; when they reverse direction, the cell border is paralyzed. These data show that force-generating, highly organized supramolecular networks are autonomously formed in live cells from molecular motors and proteins controlling actin polymerization and depolymerization. PMID:19348770

  20. Self-organized Motion During Dictyostelium amoebae aggregation

    NASA Astrophysics Data System (ADS)

    Levine, Herbert

    2004-03-01

    After starvation, amoeba of the cellular slime mold Dictyostelium discoideum aggregate to form rudimentary multicellular organisms. The coordination of the individual motions of hundreds of thousands of individual cells is an important ingredient in the success of this process. This coordination is accomplished by chemical signaling during the early stages and by direct cell-cell interactions once the cells reach the nascent mound. This talk will review the basic nonequilibrium physics underlying the spatial patterns formed by these cooperative motions, including high-density incoming streams and spontaneously rotating mounds.

  1. Signatures of Divergence and Self-Organization in Soils and Weathering Profiles.

    PubMed

    Phillips

    2000-01-01

    Complex system behaviors such as self-organization are difficult to address in geology. System evolution often cannot be directly observed and, in geology models and theory, must be reconciled with field evidence. However, self-organization can be addressed within the historical-interpretive paradigm by applying a measure of the degree of self-organization of geologic features, using standard interpretive methods to determine the nature of changes, and determining whether those changes result in an increase or decrease in organization. In this way, stable non-self-organizing convergent development can be distinguished from unstable chaotic self-organizing divergent development. Kolmogorov entropy (K-entropy) was used as a measure of the self-organization of soil profiles in eastern North Carolina. In general, the profiles are low in K-entropy, indicating a generally high level of predictability and information in the vertical arrangement of pedogenetic horizons. As a broad generality, the study profiles appear to be decreasing in entropy if or when surface erosion is minimal and increasing in entropy otherwise. However, results show that whether the profiles demonstrate evidence of convergent or divergent behavior is determined by the relative rates or magnitudes of three main processes: (1) horizon differentiation in surficial horizons by the formation of transitional AE or A&E horizons due to secondary podzolization, (2) thickening of the solum at the weathering front, and (3) surface erosion. There is no direct relationship between the degree of pedogenic development and self-organization. The results suggest that complex system behaviors are controlled by, and can be linked to, specific pedologic and geomorphic processes and that soils and regoliths may be characterized by both convergent and divergent developmental pathways. PMID:10618192

  2. Self-organized behavior in thin-film recording media

    NASA Astrophysics Data System (ADS)

    Zhu, Jian-Gang; Bertram, H. Neal

    1991-04-01

    Magnetization domain structures in thin metallic films utilized as recording media are modeled by a cellular automation on a two-dimensional triangular lattice. This alternative approach permits significantly large arrays (≳ 106 grains) to be investigated as compared to an exact calculation (≊ 5 × 103 grains). Thus a study of the statistical distribution of the domain sizes and their power spectra can be made. Magnetostatic interactions and intergranular exchange coupling are included in a simple manner so that collective behavior is incorporated. It is found that away from the saturation remanent state, the distribution of the size of the avalanches (or the number of sites reversed in a single reversal sequence) follows a power-law behavior: D(S) = AS-α where S is the avalanche size and α varies in the vicinity of 1 depending on the interaction strength. The reversal field keeps the system marginally stable. It is found that the reproduce noise power varies as the derivative of the M-H loop.

  3. 3-D structure and dynamics of microtubule self-organization

    NASA Astrophysics Data System (ADS)

    Wang, Jing; Ou-Yang, H. Daniel

    2008-03-01

    Laser scanning confocal microscopy was used to study the dynamics of 3D assemblies spontaneously formed in microtubule (MT) solutions. Microtubule solutions prepared by mixing and incubating tubulin in the presence of GTP and Oregon Green conjugated taxol in PM buffer were placed in long, sub-millimeter thin glass cells by the capillary action. Within 24 hours, starting with a uniform distribution, microtubules were found to be gradually separated into a few large ``buckled'' bundles along the long direction, and in the middle plane, of the sample cell. A well-defined wavelength of the buckling sinusoids was around 510 μm. The cross section of these round bundles was approximately 40 μm in diameter and the lengths were several centimeters. Detailed analysis of the 3-D image within the bundles revealed that each bundle seemed to consist of loosely packed MTs. It appeared that MTs were phase separated resulting from attractive interactions between charged MT fibers. The ``buckling'' behavior could be the result of geometrical constraints of the repulsive cell walls and the repulsive interaction between bundles. Detailed 3-D observations of the dynamic evolution of MT assembly could provide insight to the mechanisms of cellular MT organization and phase separation of charged colloidal rods.

  4. Brain basis of self: self-organization and lessons from dreaming

    PubMed Central

    Kahn, David

    2013-01-01

    Through dreaming, a different facet of the self is created as a result of a self-organizing process in the brain. Self-organization in biological systems often happens as an answer to an environmental change for which the existing system cannot cope; self-organization creates a system that can cope in the newly changed environment. In dreaming, self-organization serves the function of organizing disparate memories into a dream since the dreamer herself is not able to control how individual memories become weaved into a dream. The self-organized dream provides, thereby, a wide repertoire of experiences; this expanded repertoire of experience results in an expansion of the self beyond that obtainable when awake. Since expression of the self is associated with activity in specific areas of the brain, the article also discusses the brain basis of the self by reviewing studies of brain injured patients, discussing brain imaging studies in normal brain functioning when focused, when daydreaming and when asleep and dreaming. PMID:23882232

  5. Self-organization of the earth's biosphere-geochemical or geophysiological?

    NASA Technical Reports Server (NTRS)

    Schwartzman, David W.; Shore, Steven N.; Volk, Tyler; Mcmenamin, Mark

    1994-01-01

    We explore the implications of indicating the biosphere's self-organization by the trend over time of the net entropic flow from the Earth's surface, the actual physical boundary of virtually all biotic mass. This flow, derived from the radiative surface entropy budget, is approximately inversely related to the surface temperature when the solar incident flux remains constant. In the geophysiological ('gaian') interpretation, biospheric self-organization has increased with the progressive colonization of the continents and evolutionary developments in the land biota, as a result of surface cooling arising from biotic enhancement of weathering. The key site for this self-organization is at the interface between land and atmosphere, the soil, where carbon is sequestered by its reaction (as carbonic and organic acids) with calcium magnesium silicates. Along with disequilibrium (steady-state) levels of carbon dioxide in the atmosphere, the occurrence of differentiated soil is the critical material evidence for biospheric self-organization, whether it be geophysiological or geochemical (ie., purely result of inorganic reactions). The computed equilibrium levels of carbon dioxide and corresponding equilibrium temperatures in the past are dramatically different from the steady-state levels. With future solar luminosity increase, the biospheric capacity for climatic regulation will decrease, leading to the ending of self-organization some two billion years from now. The Earth's surface will then approach chemical equilibrium with respect to the carbonate-silicate cycle.

  6. Ureilite compaction

    NASA Astrophysics Data System (ADS)

    Walker, D.; Agee, C. B.

    1988-03-01

    Ureilite meteorites show the simple mineralogy and compact recrystallized textures of adcumulate rock or melting residues. A certain amount of controversy exists about whether they are in fact adcumulate rocks or melting residues and about the nature of the precursor liquid or solid assemblage. The authors undertook a limited experimental study which made possible the evaluation of the potential of the thermal migration mechanism (diffusion on a saturation gradient) for forming ureilite-like aggregates from carbonaceous chondrite precursors. They find that the process can produce compact recrystallized aggregates of silicate crystals which do resemble the ureilities and other interstitial-liquid-free adcumulate rocks in texture.

  7. Global Consensus Theorem and Self-Organized Criticality: Unifying Principles for Understanding Self-Organization, Swarm Intelligence and Mechanisms of Carcinogenesis

    PubMed Central

    Rosenfeld, Simon

    2013-01-01

    Complex biological systems manifest a large variety of emergent phenomena among which prominent roles belong to self-organization and swarm intelligence. Generally, each level in a biological hierarchy possesses its own systemic properties and requires its own way of observation, conceptualization, and modeling. In this work, an attempt is made to outline general guiding principles in exploration of a wide range of seemingly dissimilar phenomena observed in large communities of individuals devoid of any personal intelligence and interacting with each other through simple stimulus-response rules. Mathematically, these guiding principles are well captured by the Global Consensus Theorem (GCT) equally applicable to neural networks and to Lotka-Volterra population dynamics. Universality of the mechanistic principles outlined by GCT allows for a unified approach to such diverse systems as biological networks, communities of social insects, robotic communities, microbial communities, communities of somatic cells, social networks and many other systems. Another cluster of universal laws governing the self-organization in large communities of locally interacting individuals is built around the principle of self-organized criticality (SOC). The GCT and SOC, separately or in combination, provide a conceptual basis for understanding the phenomena of self-organization occurring in large communities without involvement of a supervisory authority, without system-wide informational infrastructure, and without mapping of general plan of action onto cognitive/behavioral faculties of its individual members. Cancer onset and proliferation serves as an important example of application of these conceptual approaches. In this paper, the point of view is put forward that apparently irreconcilable contradictions between two opposing theories of carcinogenesis, that is, the Somatic Mutation Theory and the Tissue Organization Field Theory, may be resolved using the systemic approaches

  8. Social integration of robots into groups of cockroaches to control self-organized choices.

    PubMed

    Halloy, J; Sempo, G; Caprari, G; Rivault, C; Asadpour, M; Tâche, F; Saïd, I; Durier, V; Canonge, S; Amé, J M; Detrain, C; Correll, N; Martinoli, A; Mondada, F; Siegwart, R; Deneubourg, J L

    2007-11-16

    Collective behavior based on self-organization has been shown in group-living animals from insects to vertebrates. These findings have stimulated engineers to investigate approaches for the coordination of autonomous multirobot systems based on self-organization. In this experimental study, we show collective decision-making by mixed groups of cockroaches and socially integrated autonomous robots, leading to shared shelter selection. Individuals, natural or artificial, are perceived as equivalent, and the collective decision emerges from nonlinear feedbacks based on local interactions. Even when in the minority, robots can modulate the collective decision-making process and produce a global pattern not observed in their absence. These results demonstrate the possibility of using intelligent autonomous devices to study and control self-organized behavioral patterns in group-living animals. PMID:18006751

  9. A self-organized model for network evolution. Coupling network evolution and extremal dynamics

    NASA Astrophysics Data System (ADS)

    Caldarelli, G.; Capocci, A.; Garlaschelli, D.

    2008-08-01

    Here we provide a detailed analysis, along with some extensions and additonal investigations, of a recently proposed [1] self-organized model for the evolution of complex networks. Vertices of the network are characterized by a fitness variable evolving through an extremal dynamics process, as in the Bak-Sneppen [2] model representing a prototype of Self-Organized Criticality. The network topology is in turn shaped by the fitness variable itself, as in the fitness network model [3]. The system self-organizes to a nontrivial state, characterized by a power-law decay of dynamical and topological quantities above a critical threshold. The interplay between topology and dynamics in the system is the key ingredient leading to an unexpected behaviour of these quantities.

  10. Self-organizing approximation-based control for higher order systems.

    PubMed

    Zhao, Yuanyuan; Farrell, Jay A

    2007-07-01

    Adaptive approximation-based control typically uses approximators with a predefined set of basis functions. Recently, spatially dependent methods have defined self-organizing approximators where new locally supported basis elements were incorporated when existing basis elements were insufficiently excited. In this paper, performance-dependent self-organizing approximators will be defined. The designer specifies a positive tracking error criteria. The self-organizing approximation-based controller then monitors the tracking performance and adds basis elements only as needed to achieve the tracking specification. The method of this paper is applicable to general nth-order input-state feedback linearizable systems. This paper includes a complete stability analysis and a detailed simulation example. PMID:17668673

  11. On the self-organizing process of large scale shear flows

    SciTech Connect

    Newton, Andrew P. L.; Kim, Eun-jin; Liu, Han-Li

    2013-09-15

    Self organization is invoked as a paradigm to explore the processes governing the evolution of shear flows. By examining the probability density function (PDF) of the local flow gradient (shear), we show that shear flows reach a quasi-equilibrium state as its growth of shear is balanced by shear relaxation. Specifically, the PDFs of the local shear are calculated numerically and analytically in reduced 1D and 0D models, where the PDFs are shown to converge to a bimodal distribution in the case of finite correlated temporal forcing. This bimodal PDF is then shown to be reproduced in nonlinear simulation of 2D hydrodynamic turbulence. Furthermore, the bimodal PDF is demonstrated to result from a self-organizing shear flow with linear profile. Similar bimodal structure and linear profile of the shear flow are observed in gulf stream, suggesting self-organization.

  12. Nano-structure fabrication by using self-organizing properties of materials

    SciTech Connect

    Hayashi, T.; Maruno, T.; Ishii, Y.

    1994-12-31

    Self-organizing properties of materials can be used to fabricate well-ordered nanostructures on a large scale and also to develop new advanced materials. Three examples of self-organized nanostructures are described in this paper. A unidirectionally ordered metallo-phthalocyanine thin film was formed over the entire surface of a sapphire (1{bar 1}02) substrate by using a newly synthesized dibenzo[b,t] phthalocyaninato-Zn(II), which has a unique two-fold symmetrical molecular structure. A buried SiO{sub 2} layer with atomically abrupt Si/SiO{sub 2} interface was formed by oxygen ion implantation into silicon and subsequent annealing. A nano-particle consisting of outer graphitic shells and a core nano-crystal of LaC{sub 2} was formed in a self-organizing manner when a hot carbon-lanthanum particle was cooled on an arc-discharge electrode in a He atmosphere.

  13. Self-organizing Symbol Acquisition and Motion Generation based on Dynamics-based Information Processing System

    NASA Astrophysics Data System (ADS)

    Okada, Masafumi; Nakamura, Daisuke; Nakamura, Yoshihiko

    The symbol acquisition and manipulation abilities are one of the inherent characteristics of human beings comparing with other creatures. In this paper, based on recurrent self-organizing map and dynamics-based information processing system, we propose a dynamics based self-organizing map (DBSOM). This method enables designing a topological map using time sequence data, which causes recognition and generation of the robot motion. Using this method, we design the self-organizing symbol acquisition system and robot motion generation system for a humanoid robot. By implementing DBSOM to the robot in the real world, we realize the symbol acquisition from the experimental data and investigate the spatial property of the obtained DBSOM.

  14. Origin and Evolution of the Self-Organizing Cytoskeleton in the Network of Eukaryotic Organelles

    PubMed Central

    Jékely, Gáspár

    2014-01-01

    The eukaryotic cytoskeleton evolved from prokaryotic cytomotive filaments. Prokaryotic filament systems show bewildering structural and dynamic complexity and, in many aspects, prefigure the self-organizing properties of the eukaryotic cytoskeleton. Here, the dynamic properties of the prokaryotic and eukaryotic cytoskeleton are compared, and how these relate to function and evolution of organellar networks is discussed. The evolution of new aspects of filament dynamics in eukaryotes, including severing and branching, and the advent of molecular motors converted the eukaryotic cytoskeleton into a self-organizing “active gel,” the dynamics of which can only be described with computational models. Advances in modeling and comparative genomics hold promise of a better understanding of the evolution of the self-organizing cytoskeleton in early eukaryotes, and its role in the evolution of novel eukaryotic functions, such as amoeboid motility, mitosis, and ciliary swimming. PMID:25183829

  15. Self-Organized Biological Dynamics and Nonlinear Control

    NASA Astrophysics Data System (ADS)

    Walleczek, Jan

    2006-04-01

    The frontiers and challenges of biodynamics research Jan Walleczek; Part I. Nonlinear Dynamics in Biology and Response to Stimuli: 1. External signals and internal oscillation dynamics - principal aspects and response of stimulated rhythmic processes Friedemann Kaiser; 2. Nonlinear dynamics in biochemical and biophysical systems: from enzyme kinetics to epilepsy Raima Larter, Robert Worth and Brent Speelman; 3. Fractal mechanisms in neural control: human heartbeat and gait dynamics in health and disease Chung-Kang Peng, Jeffrey M. Hausdorff and Ary L. Goldberger; 4. Self-organising dynamics in human coordination and perception Mingzhou Ding, Yanqing Chen, J. A. Scott Kelso and Betty Tuller; 5. Signal processing in biochemical reaction networks Adam P. Arkin; Part II. Nonlinear Sensitivity of Biological Systems to Electromagnetic Stimuli: 6. Electrical signal detection and noise in systems with long-range coherence Paul C. Gailey; 7. Oscillatory signals in migrating neutrophils: effects of time-varying chemical and electrical fields Howard R. Petty; 8. Enzyme kinetics and nonlinear biochemical amplification in response to static and oscillating magnetic fields Jan Walleczek and Clemens F. Eichwald; 9. Magnetic field sensitivity in the hippocampus Stefan Engström, Suzanne Bawin and W. Ross Adey; Part III. Stochastic Noise-Induced Dynamics and Transport in Biological Systems: 10. Stochastic resonance: looking forward Frank Moss; 11. Stochastic resonance and small-amplitude signal transduction in voltage-gated ion channels Sergey M. Bezrukov and Igor Vodyanoy; 12. Ratchets, rectifiers and demons: the constructive role of noise in free energy and signal transduction R. Dean Astumian; 13. Cellular transduction of periodic and stochastic energy signals by electroconformational coupling Tian Y. Tsong; Part IV. Nonlinear Control of Biological and Other Excitable Systems: 14. Controlling chaos in dynamical systems Kenneth Showalter; 15. Electromagnetic fields and biological

  16. Self-Organized Bistability Associated with First-Order Phase Transitions

    NASA Astrophysics Data System (ADS)

    di Santo, Serena; Burioni, Raffaella; Vezzani, Alessandro; Muñoz, Miguel A.

    2016-06-01

    Self-organized criticality elucidates the conditions under which physical and biological systems tune themselves to the edge of a second-order phase transition, with scale invariance. Motivated by the empirical observation of bimodal distributions of activity in neuroscience and other fields, we propose and analyze a theory for the self-organization to the point of phase coexistence in systems exhibiting a first-order phase transition. It explains the emergence of regular avalanches with attributes of scale invariance that coexist with huge anomalous ones, with realizations in many fields.

  17. Self-Organized Bistability Associated with First-Order Phase Transitions.

    PubMed

    di Santo, Serena; Burioni, Raffaella; Vezzani, Alessandro; Muñoz, Miguel A

    2016-06-17

    Self-organized criticality elucidates the conditions under which physical and biological systems tune themselves to the edge of a second-order phase transition, with scale invariance. Motivated by the empirical observation of bimodal distributions of activity in neuroscience and other fields, we propose and analyze a theory for the self-organization to the point of phase coexistence in systems exhibiting a first-order phase transition. It explains the emergence of regular avalanches with attributes of scale invariance that coexist with huge anomalous ones, with realizations in many fields. PMID:27367373

  18. Empirical Evidence for Self-Organized Patterns in California Wildfire Sizes: Implications for Landscape Resilience

    NASA Astrophysics Data System (ADS)

    Povak, N. A.; Hessburg, P. F.

    2009-05-01

    Wildfires are an important disturbance in many western US ecosystems and are integral in shaping spatial and temporal vegetation patterns. Ecological resilience has been described as the amount of disturbance that an ecosystem could withstand without changing self-organized processes and structures. Inherent in resilient systems are observable self-organized patterns in vegetation and processes on the landscape. It is theorized that self-organized systems are capable of withstanding a large range of disturbance sizes and intensities without significantly changing the resultant distribution of vegetation patch sizes over time. Past research has used power-law statistics to describe self-organization in wildfire behavior, and we extend this research using several different methods to identify evidence for landscape resilience over a large geographic area. We used a catalogue of California wildfires (>1ha; 1950-2007) grouped at multiple levels within Bailey's hierarchy of ecoregions to (1) identify self-organized patterns in wildfire size distributions across the state, (2) identify lower and upper limits on self-organized behavior, and (3) find links between these patterns and top-down and bottom-up processes. Within most ecoregions we found reliable evidence for self-organized behavior in wildfire size distributions. Evidence included good fits of: (1) 2-3 parameter statistical distributions within the Pareto and Generalized Beta II (P/GB2) family of distributions over the entire range of fire event sizes; these distributions all have in common a power-law tail, (2) the Pareto I (power-law) distribution to the right-tail of the fire-size distributions, and (3) broken-stick regression models to the inverse cumulative distribution functions for fire sizes. For most ecoregions, self-organized properties were generally limited to fires within 100 to 10000 ha, indicating that meso-scale processes controlling fire sizes likely are acting at this scale. Scaling parameters

  19. A Modeling substorm Dynamics of the Magnetosphere Using Self-Organized Criticality Approach

    NASA Astrophysics Data System (ADS)

    Bolzan, Mauricio; Rosa, Reinaldo

    2016-07-01

    Responses of Earth magnetic field during substorms exhibits a number of characteristics features such as the power-law spectra of fluctuations on different scales and signatures of low effective dimensions. Due the magnetosphere are constantly out-equilibrium their behavior is similar to real sandpiles during substorms, features of self-organized criticality (SOC) systems. Thus, in this work we presented a simple mathematical model to AE-index based on self-organizing sandpile mentioned by Uritsky and Pudovkin (1998), but we input the dissipation process inside the model. The statistical and multifractal tools to characterization of dynamical processes was used.

  20. Self-Organization Leads to Supraoptimal Performance in Public Transportation Systems

    PubMed Central

    Gershenson, Carlos

    2011-01-01

    The performance of public transportation systems affects a large part of the population. Current theory assumes that passengers are served optimally when vehicles arrive at stations with regular intervals. In this paper, it is shown that self-organization can improve the performance of public transportation systems beyond the theoretical optimum by responding adaptively to local conditions. This is possible because of a “slower-is-faster” effect, where passengers wait more time at stations but total travel times are reduced. The proposed self-organizing method uses “antipheromones” to regulate headways, which are inspired by the stigmergy (communication via environment) of some ant colonies. PMID:21738674

  1. Self-organization leads to supraoptimal performance in public transportation systems.

    PubMed

    Gershenson, Carlos

    2011-01-01

    The performance of public transportation systems affects a large part of the population. Current theory assumes that passengers are served optimally when vehicles arrive at stations with regular intervals. In this paper, it is shown that self-organization can improve the performance of public transportation systems beyond the theoretical optimum by responding adaptively to local conditions. This is possible because of a "slower-is-faster" effect, where passengers wait more time at stations but total travel times are reduced. The proposed self-organizing method uses "antipheromones" to regulate headways, which are inspired by the stigmergy (communication via environment) of some ant colonies. PMID:21738674

  2. Interacting and self-organized two-level states in tunnel barriers

    NASA Technical Reports Server (NTRS)

    Pesenson, L.; Robertazzi, R. P.; Buhrman, R. A.; Cypher, S. R.; Hunt, B. D.

    1991-01-01

    The excess low-frequency 1/f noise and discrete two-level resistance fluctuations (TLFs) were studied in small-area NbN-MgO-NbN tunnel junctions with a high, low-temperature density of active defects. Strong and evolving interactions between large TLFs indicate that these fluctuations result from the self-organization of interacting defect elements. In the low-T tunneling regime, an unusual slowing down of the rates and a decrease in amplitude with increasing T is sometimes observed indicative of a thermally induced change in the self-organized two-level state.

  3. The Effect of Anode Material and Secondary Gas Injection on Self-organized Patterns in Atmospheric Pressure Glows

    NASA Astrophysics Data System (ADS)

    Kovach, Yao; Foster, John

    2015-09-01

    Plasma self-organization on anode surfaces in DC glow discharges remains poorly understood. This effort aims to elucidate the nature of self-organization through the study of resulting patterns on both liquid and metal electrode surfaces. Self-organization pattern formation and behavior were studied as a function of inter-electrode spacing, electrode material type, gas composition and gas flow rate using emission spectroscopy and fast camera imaging. The response of the patterns to variation in these parameters is reported. These results are used as a basis for speculating upon the underlying physical processes that give rise to the self-organization. NSF CBET 1336375.

  4. Compact accelerator

    DOEpatents

    Caporaso, George J.; Sampayan, Stephen E.; Kirbie, Hugh C.

    2007-02-06

    A compact linear accelerator having at least one strip-shaped Blumlein module which guides a propagating wavefront between first and second ends and controls the output pulse at the second end. Each Blumlein module has first, second, and third planar conductor strips, with a first dielectric strip between the first and second conductor strips, and a second dielectric strip between the second and third conductor strips. Additionally, the compact linear accelerator includes a high voltage power supply connected to charge the second conductor strip to a high potential, and a switch for switching the high potential in the second conductor strip to at least one of the first and third conductor strips so as to initiate a propagating reverse polarity wavefront(s) in the corresponding dielectric strip(s).

  5. Compact dusty clouds in a cosmic environment

    SciTech Connect

    Tsytovich, V. N.; Ivlev, A. V.; Burkert, A.; Morfill, G. E.

    2014-01-10

    A novel mechanism of the formation of compact dusty clouds in astrophysical environments is discussed. It is shown that the balance of collective forces operating in space dusty plasmas can result in the effect of dust self-confinement, generating equilibrium spherical clusters. The distribution of dust and plasma density inside such objects and their stability are investigated. Spherical dusty clouds can be formed in a broad range of plasma parameters, suggesting that this process of dust self-organization might be a generic phenomenon occurring in different astrophysical media. We argue that compact dusty clouds can represent condensation seeds for a population of small-scale, cold, gaseous clumps in the diffuse interstellar medium. They could play an important role in regulating its small-scale structure and its thermodynamical evolution.

  6. Self-organization in the movement activity of social insects (Hymenoptera: Formicidae)

    NASA Astrophysics Data System (ADS)

    Neves, Felipe Marcel; Pie, Marcio Roberto; Viana, Ricardo Luiz

    2012-09-01

    Social insects present behavioral, morphologic and social variation, which bring ideal situations to study emergent temporal-spatial patterns. In this study, we observe the self-organization in the movement activity of social insects in different species and densities. In our preliminary results, all the species observed present a pattern more complex in higher densities and with structural differences between them.

  7. Nonlinear dynamics analysis of a self-organizing recurrent neural network: chaos waning.

    PubMed

    Eser, Jürgen; Zheng, Pengsheng; Triesch, Jochen

    2014-01-01

    Self-organization is thought to play an important role in structuring nervous systems. It frequently arises as a consequence of plasticity mechanisms in neural networks: connectivity determines network dynamics which in turn feed back on network structure through various forms of plasticity. Recently, self-organizing recurrent neural network models (SORNs) have been shown to learn non-trivial structure in their inputs and to reproduce the experimentally observed statistics and fluctuations of synaptic connection strengths in cortex and hippocampus. However, the dynamics in these networks and how they change with network evolution are still poorly understood. Here we investigate the degree of chaos in SORNs by studying how the networks' self-organization changes their response to small perturbations. We study the effect of perturbations to the excitatory-to-excitatory weight matrix on connection strengths and on unit activities. We find that the network dynamics, characterized by an estimate of the maximum Lyapunov exponent, becomes less chaotic during its self-organization, developing into a regime where only few perturbations become amplified. We also find that due to the mixing of discrete and (quasi-)continuous variables in SORNs, small perturbations to the synaptic weights may become amplified only after a substantial delay, a phenomenon we propose to call deferred chaos. PMID:24466301

  8. Self-Organization and Migration of Dielectric Barrier Discharge Filaments in Argon Gas Flow

    PubMed Central

    Yang, Yong; Cho, Young I.; Friedman, Gary; Fridman, Alexander; Fridman, Greg

    2012-01-01

    Observations of atmospheric-pressure dielectric barrier discharge are conducted through a water-filled electrode in atmospheric-pressure argon gas flow. Quasi-symmetric self-organized discharge filaments were observed. The streamers moved with the gas flow, and the migration velocity increased with increasing gas velocity. PMID:22287814

  9. Towards a Knowledge Building Community: From Guided to Self-Organized Inquiry

    ERIC Educational Resources Information Center

    Cacciamani, Stefano

    2010-01-01

    Over four academic years a design experiment was conducted involving four online university courses with the goal of shifting from Guided to Self-Organized Inquiry to foster Knowledge Building communities in the classroom. Quantitative analyses focused on notes contributed to collective knowledge spaces, as well as reading and building-on notes of…

  10. On self-organizing during transition from a laminar to a turbulent flow for nonextensive systems

    NASA Astrophysics Data System (ADS)

    Zaripov, R. G.

    2016-06-01

    The evolution of parametric q-entropy and q-information divergence to the equilibrium state during spontaneous transitions and transitions from a laminar to a turbulent flow is considered as applied to nonextensive self-organizing systems. The S- and I-theorems on the variations of measures with constant mean energies are proved.

  11. Entropy in the Bak-Sneppen Model for Self-Organized Criticality

    NASA Astrophysics Data System (ADS)

    Yang, Chun-Bin

    2003-03-01

    The distributions of fitness on the sites of one- and two-dimensional lattices are studied for the nearest-neighbour Bak-Sneppen model on self-organized criticality. The distributions show complicated behaviour showing that the system is far from equilibrium. By introducing the ``energy'' of a site, the entropy flow from the system to its environment is investigated.

  12. Of Slumdogs and Schoolmasters: Jacotot, Ranciere and Mitra on Self-Organized Learning

    ERIC Educational Resources Information Center

    Stamp, Richard

    2013-01-01

    This article argues that the concept and practice of "self-organized learning", as pioneered by Sugata Mitra (and his team) in the "Hole-in-the-Wall" experiments (1999-2005) that inspired the novel "Q & A" (2006) and the resulting movie, "Slumdog millionaire" (2008) bear direct, but not uncritical…

  13. Self-organized Au nanoarrays on vertical graphenes: an advanced three-dimensional sensing platform.

    PubMed

    Rider, Amanda Evelyn; Kumar, Shailesh; Furman, Scott A; Ostrikov, Kostya Ken

    2012-03-11

    A three-dimensional surface enhanced Raman scattering (SERS)/plasmonic sensing platform based on plasma-enabled, catalyst-free, few-layer vertical graphenes decorated with self-organized Au nanoparticle arrays is demonstrated. This platform is viable for multiple species detection and overcomes several limitations of two-dimensional sensors. PMID:22227575

  14. Self-Organized Patterns of Spots In DC Glow Microdischarges in Krypton

    NASA Astrophysics Data System (ADS)

    Zhu, Weidong; Almeida, Pedro G. C.; Benilov, Mikhail S.; Santos, Diego F.; Niraula, Prajwal

    2013-09-01

    Self-organized patterns of cathodic spots have been observed in DC microdischarges in xenon. Modeling of microdischarges in xenon has revealed existence of multiple solutions. Some of the solutions describe normal discharges, others describe 2D patterns of cathodic spots, and others describe 3D patterns similar to those observed in experiments. A very interesting question is why modes with self-organized patterns have been observed in DC microdischarges in xenon but not in other gases. Modeling suggests that self-organized patterns can be observed in gases other than xenon provided that conditions are right. In the present work, self-organized patterns of spots observed in DC microdischarges in krypton are reported. The experiments are guided by modeling and the discharge device employed in the experiments consists of a molybdenum foil as the anode, an aluminum oxide plate as the dielectric spacer and another molybdenum foil as the cathode. Each layer of the device is 0.25 mm thick. Circular openings of 0.75 mm in diameter are prepared on both anode and dielectric spacer and are aligned. The whole device is assembled by Torr Seal epoxy. Research grade krypton is used to fill the chamber to a pressure of 200-1200 Torr. This work was supported by FCT through the projects PTDC/FIS-PLA/2708/2012 and PEst-OE/MAT/UI0219/2011.

  15. Topology assisted self-organization of colloidal nanoparticles: application to 2D large-scale nanomastering

    PubMed Central

    Kostcheev, Serguei; Turover, Daniel; Salas-Montiel, Rafael; Nomenyo, Komla; Gokarna, Anisha; Lerondel, Gilles

    2014-01-01

    Summary Our aim was to elaborate a novel method for fully controllable large-scale nanopatterning. We investigated the influence of the surface topology, i.e., a pre-pattern of hydrogen silsesquioxane (HSQ) posts, on the self-organization of polystyrene beads (PS) dispersed over a large surface. Depending on the post size and spacing, long-range ordering of self-organized polystyrene beads is observed wherein guide posts were used leading to single crystal structure. Topology assisted self-organization has proved to be one of the solutions to obtain large-scale ordering. Besides post size and spacing, the colloidal concentration and the nature of solvent were found to have a significant effect on the self-organization of the PS beads. Scanning electron microscope and associated Fourier transform analysis were used to characterize the morphology of the ordered surfaces. Finally, the production of silicon molds is demonstrated by using the beads as a template for dry etching. PMID:25161854

  16. Self-organization in a model of economic system with scale invariant interactions

    NASA Astrophysics Data System (ADS)

    Pis`mak, Yu. M.

    2001-10-01

    The method of constructing the local scale invariant stochastic models is proposed. The possible extension of minimal scale-invariant interaction principle for stochastic systems is formulated. A simple scale invariant model that possesses an economical interpretation is considered. Essential characteristics of its self-organization mechanisms are discussed.

  17. Leadership of Self-Organized Networks Lessons from the War on Terror

    ERIC Educational Resources Information Center

    Wheatley, Margaret J.

    2007-01-01

    In the past few decades, scientists have developed a rich understanding of how living systems organize and function. They describe life's capacity to self-organize as networks of interdependent relationships, to learn and adapt, and to grow more capable and orderly over time. These dynamics and descriptions stand in stark contrast to how we humans…

  18. Assessing self-organization of plant communities--A thermodynamic approach

    NASA Astrophysics Data System (ADS)

    Lin, H.; Cao, M.; Stoy, P.; Zhang, Y.

    2013-12-01

    Thermodynamics is a powerful tool for the study of system development and has the potential to be applied to studies of ecological complexity. Here, we develop a set of thermodynamic indicators including energy capture and energy dissipation to quantify plant community self-organization. The study ecosystems included a tropical seasonal rainforest, an artificial tropical rainforest, a rubber plantation, and two Chromolaena odorata (L.) R.M. King & H. Robinson communities aged 13 years and 1 year. The communities represent a complexity transect from primary vegetation, to transitional community, economic plantation, and fallows and are typical for Xishuangbanna, southwestern China. The indicators of ecosystem self-organization are sensitive to plant community type and seasonality, and demonstrate that the tropical seasonal rainforest is highly self-organized and plays an important role in local environmental stability via the land surface thermal regulation. The rubber plantation is at a very low level of self-organization as quantified by the thermodynamic indicators, especially during the dry season. The expansion of the area of rubber plantation and shrinkage of tropical seasonal rainforest would likely induce local surface warming and a larger daily temperature range.

  19. Critical Periods and Catastrophic Interference Effects in the Development of Self-Organizing Feature Maps

    ERIC Educational Resources Information Center

    Richardson, Fiona M.; Thomas, Michael S. C.

    2008-01-01

    The use of self-organizing feature maps (SOFM) in models of cognitive development has frequently been associated with explanations of "critical" or "sensitive periods". By contrast, error-driven connectionist models of development have been linked with "catastrophic interference" between new knowledge and old knowledge. We introduce a set of…

  20. Effect of prediction on the self-organization of pedestrian counter flow

    NASA Astrophysics Data System (ADS)

    Wang, Ziyang; Ma, Jian; Zhao, Hui; Qin, Yong; Jia, Limin

    2012-08-01

    Pedestrians may predict the behavior of others and then adjust their movement accordingly to avoid potential conflicts in advance. Motivated by this fact, we propose a predictive control theory-based pedestrian counter flow model, which describes the predictive mechanism underlying pedestrian self-organization phenomena. In this model, a pedestrian will make in-advance-avoid behavior based on the estimation of future moving gain within a given predictive length to reduce potential conflicts. The future gain in the present model is affected by three factors, i.e. the predictive length, the smooth degree of entrance and the influential area of coming pedestrians. Simulation results of the model show that increasing predictive length has a remarkable effect on reducing conflicts, improving pedestrian velocity, smoothing pedestrian movement and stabilizing the self-organized lanes. When enlarging the influential area of coming pedestrians, pedestrians tend to aggregate to the formed self-organized lanes, which makes the lanes wider and the lane number reduced. Interestingly, moderate enlargement (of the influential area) will reduce conflicts significantly, while excessive enlargement will lead to an increase in conflicts. We also discuss the predictive effect toward the smooth degree of entrance. When there are some formed self-organized lanes in the system, the effect is significant, and it will make the lanes more regular and stable, while when the existing lanes are unstable, the effect has little impact on the system.

  1. Critical exponents and scaling relations for self-organized critical phenomena

    NASA Technical Reports Server (NTRS)

    Tang, Chao; Bak, Per

    1988-01-01

    Critical indices beta, gamma delta, nv, etc. are defined and calculated for self-organized critical phenomena. Scaling relations are derived and checked numerically. The order-parameter exponent beta describes the spontaneous current and the relaxation to the criticl point. The power spectrum has 'l/f' behavior with the exponent phi = nv x z, where z is the dynamical critical exponent.

  2. Self-organization theories and environmental management: The case of South Moresby, Canada

    NASA Astrophysics Data System (ADS)

    Grzybowski, Alex G. S.; Slocombe, D. Scott

    1988-07-01

    This article presents a new approach to the analysis and management of large-scale societal problems with complex ecological, economic, and social dimensions. The approach is based on the theory of self-organizing systems—complex, open, far-from-equilibrium systems with nonlinear dynamics. A brief overview and comparison of different self-organization theories (synergetics, self-organization theory, hypercycles, and autopoiesis) is presented in order to isolate the key characteristics of such systems. The approach is used to develop an analysis of the landuse controversy in the South Moresby area of the Queen Charlotte Islands, British Columbia, Canada. Critical variables are identified for each subsystem and classified by spatial and temporal scale, and discussed in terms of information content and internal/external origin. Eradication of sea otters, introduction of black-tailed deer, impacts of large-scale clearcut logging, sustainability of the coastal forest industry, and changing relations between native peoples and governments are discussed in detail to illustrate the system dynamics of the South Moresby “sociobiophysical” system. Finally, implications of the self-organizing sociobiophysical system view for regional analysis and management are identified.

  3. Self-organization processes in field-invasion team sports : implications for leadership.

    PubMed

    Passos, Pedro; Araújo, Duarte; Davids, Keith

    2013-01-01

    In nature, the interactions between agents in a complex system (fish schools; colonies of ants) are governed by information that is locally created. Each agent self-organizes (adjusts) its behaviour, not through a central command centre, but based on variables that emerge from the interactions with other system agents in the neighbourhood. Self-organization has been proposed as a mechanism to explain the tendencies for individual performers to interact with each other in field-invasion sports teams, displaying functional co-adaptive behaviours, without the need for central control. The relevance of self-organization as a mechanism that explains pattern-forming dynamics within attacker-defender interactions in field-invasion sports has been sustained in the literature. Nonetheless, other levels of interpersonal coordination, such as intra-team interactions, still raise important questions, particularly with reference to the role of leadership or match strategies that have been prescribed in advance by a coach. The existence of key properties of complex systems, such as system degeneracy, nonlinearity or contextual dependency, suggests that self-organization is a functional mechanism to explain the emergence of interpersonal coordination tendencies within intra-team interactions. In this opinion article we propose how leadership may act as a key constraint on the emergent, self-organizational tendencies of performers in field-invasion sports. PMID:23315752

  4. Monitoring Scientific Developments from a Dynamic Perspective: Self-Organized Structuring To Map Neural Network Research.

    ERIC Educational Resources Information Center

    Noyons, E. C. M.; van Raan, A. F. J.

    1998-01-01

    Using bibliometric mapping techniques, authors developed a methodology of self-organized structuring of scientific fields which was applied to neural network research. Explores the evolution of a data generated field structure by monitoring the interrelationships between subfields, the internal structure of subfields, and the dynamic features of…

  5. SELF-ORGANIZING MAPS FOR INTEGRATED ASSESSMENT OF THE MID-ATLANTIC REGION

    EPA Science Inventory

    A. new method was developed to perform an environmental assessment for the
    Mid-Atlantic Region (MAR). This was a combination of the self-organizing map (SOM) neural network and principal component analysis (PCA). The method is capable of clustering ecosystems in terms of envi...

  6. Neighborhoods in Development: Human Development Index and Self-Organizing Maps

    ERIC Educational Resources Information Center

    Rende, Sevinc; Donduran, Murat

    2013-01-01

    The Human Development Index (HDI) has been instrumental in broadening the discussion of economic development beyond money-metric progress, in particular, by ranking a country against other countries in terms of the well being of their citizens. We propose self-organizing maps to explore similarities among countries using the components of the HDI…

  7. Study of the self-organization processes in lead sulfide quantum dots

    SciTech Connect

    Tarasov, S. A. Aleksandrova, O. A.; Maksimov, A. I.; Maraeva, E. V.; Matyushkin, L. B.; Men’kovich, E. A.; Moshnikov, V. A.; Musikhin, S. F.

    2014-12-15

    A procedure is described for the synthesis of nanoparticles based on lead chalcogenides. The procedure combines the synthesis of colloidal quantum dots (QDs) in aqueous solutions with simultaneous organization of the QDs into ordered arrays. The processes of the self-organization of QDs are analyzed at the nano- and microscopic levels by the photoluminescence method, atomic-force microscopy, and optical microscopy.

  8. Self-organizing change? On drivers, causes and global environmental change

    NASA Astrophysics Data System (ADS)

    von Elverfeldt, Kirsten; Embleton-Hamann, Christine; Slaymaker, Olav

    2016-01-01

    Within global environmental change research, certain external drivers generally are assumed to cause the environmental system to change. The most commonly considered drivers are relief, sea level, hydroclimate, and/or people. However, complexity theory and self-organizing systems provide a very different framework and means of explanation. Self-organization - understood as the aggregate processes internal to an environmental system that lead to a distinctive spatial, temporal, or other organization - reduces the possibility of implicating a specific process as being causal. The principle of equifinality, whereby two or more different drivers can generate the same form, has long been recognized within a process-response framework, as well as the concept of divergence, which states that similar causes or processes result in different effects. Both ideas differ from self-organization in that they (i) deal with drivers external to the system and (ii) imply concrete cause-and-effect relations that might be difficult to discern. The assumption is, however, that careful study will eventually lead to the true causes and processes. Studies of self-organization deal with the ways in which internal processes interact and may drive a system toward an instability threshold, the so-called bifurcation point. At this point, the system develops by chance and no single external or internal cause for the change can be defined. For research into environmental change this is a crucial theory for two reasons:

  9. Suppression of self-organized structure coarsening in homogenous isotropic turbulence

    NASA Astrophysics Data System (ADS)

    Takagi, Youhei

    2014-11-01

    Self-organized structure by spinodal decomposition is often seen in quenched binary mixture. Complex network structure is formed through coarsening process of self-organized structure when the phase separation due to spinodal decomposition proceeds. The phase separation governed by the Cahn-Hilliard equation have been well investigated for stationary fluid in previous studies, however, the turbulent effect on the formation of structures was not fully discussed. In this study, we carried out a numerical simulation for homogenous isotropic turbulence with phase separation, the relation between turbulent vortex formation and self-organized structure coarsening. The governing equations are incompressible Navier-Stokes equation considering phase separation force and Cahn-Hilliard equation with the chemical potential based on the Landau-Ginzburg free energy. From the identification and visualization of turbulent structures, it was found that the local entrainment of small eddy structure suppressed the coarsening process of self-organized structure. The energy used in phase separation was related to the initial process of vortex sheet-tube transition in turbulent flow, and the energy cascade from large turbulent structure to small eddy was different from that without phase separation.

  10. Symbiotic intelligence: Self-organizing knowledge on distributed networks, driven by human interaction

    SciTech Connect

    Johnson, N.; Joslyn, C.; Rocha, L.; Smith, S.; Kantor, M.; Rasmussen, S. |

    1998-07-01

    This work addresses how human societies, and other diverse and distributed systems, solve collective challenges that are not approachable from the level of the individual, and how the Internet will change the way societies and organizations view problem solving. The authors apply the ideas developed in self-organizing systems to understand self-organization in informational systems. The simplest explanation as to why animals (for example, ants, wolves, and humans) are organized into societies is that these societies enhance the survival of the individuals which make up the populations. Individuals contribute to, as well as adapt to, these societies because they make life easier in one way or another, even though they may not always understand the process, either individually or collectively. Despite the lack of understanding of the how of the process, society during its existence as a species has changed significantly, from separate, small hunting tribes to a highly technological, globally integrated society. The authors combine this understanding of societal dynamics with self-organization on the Internet (the Net). The unique capability of the Net is that it combines, in a common medium, the entire human-technological system in both breadth and depth: breadth in the integration of heterogeneous systems of machines, information and people; and depth in the detailed capturing of the entire complexity of human use and creation of information. When the full diversity of societal dynamics is combined with the accuracy of communication on the Net, a phase transition is argued to occur in problem solving capability. Through conceptual examples, an experiment of collective decision making on the Net and a simulation showing the effect of noise and loss on collective decision making, the authors argue that the resulting symbiotic structure of humans and the Net will evolve as an alternative problem solving approach for groups, organizations and society. Self-organizing

  11. Punctuated-equilibrium model of biological evolution is also a self-organized-criticality model of earthquakes

    NASA Astrophysics Data System (ADS)

    Ito, Keisuke

    1995-09-01

    Bak and Sneppen proposed a self-organized-criticality model to explain the punctuated equilibrium of biological evolution. The model, as it is, is a good self-organized-criticality model of earthquakes. Real earthquakes satisfy the required conditions of criticality; that is, power laws in (1) the size distribution of earthquakes, and (2) both the spatial and the temporal correlation functions.

  12. Use of a Kohonen Self-Organizing Map To Classify Career Clients on the Basis of Aptitudes.

    ERIC Educational Resources Information Center

    Carson, Andrew D.

    1999-01-01

    A Kohonen Self-Organizing Map, a type of artificial neural network, was used to classify 547 counseling clients into eight categories based on aptitudes. Categories resembled the major typologies of people and jobs by Holland and others, suggesting the usefulness of self-organizing neural networks for career counseling. (SK)

  13. Compact magnetograph

    NASA Technical Reports Server (NTRS)

    Title, A. M.; Gillespie, B. A.; Mosher, J. W.

    1982-01-01

    A compact magnetograph system based on solid Fabry-Perot interferometers as the spectral isolation elements was studied. The theory of operation of several Fabry-Perot systems, the suitability of various magnetic lines, signal levels expected for different modes of operation, and the optimal detector systems were investigated. The requirements that the lack of a polarization modulator placed upon the electronic signal chain was emphasized. The PLZT modulator was chosen as a satisfactory component with both high reliability and elatively low voltage requirements. Thermal control, line centering and velocity offset problems were solved by a Fabry-Perot configuration.

  14. Nucleolus-tethering system (NoTS) reveals that assembly of photobodies follows a self-organization model.

    PubMed

    Liu, Yin; Liu, Qi; Yan, Qingqing; Shi, Leilei; Fang, Yuda

    2014-04-01

    Protein-protein interactions play essential roles in regulating many biological processes. At the cellular level, many proteins form nuclear foci known as nuclear bodies in which many components interact with each other. Photobodies are nuclear bodies containing proteins for light-signaling pathways in plants. What initiates the formation of photobodies is poorly understood. Here we develop a nucleolar marker protein nucleolin2 (Nuc2)-based method called the nucleolus-tethering system (NoTS) by artificially tethering a protein of interest to the nucleolus to analyze the initiation of photobodies. A candidate initiator is evaluated by visualizing whether a protein fused with Nuc2 forms body-like structures at the periphery of the nucleolus, and other components are recruited to the de novo-formed bodies. The interaction between two proteins can also be revealed through relocation and recruitment of interacting proteins to the nucleolus. Using the NoTS, we test the interactions among components in photobodies. In addition, we demonstrate that components of photobodies such as CONSTITUTIVELY PHOTOMORPHOGENIC 1, photoreceptors, and transcription factors tethered to the nucleolus have the capacity to form body-like structures at the periphery of the nucleolus, which contain other components of photobodies, suggesting a self-organization model for the biogenesis of photobodies. PMID:24554768

  15. Modeling of Instabilities and Self-organization at the Frictional Interface

    NASA Astrophysics Data System (ADS)

    Mortazavi, Vahid

    The field of friction-induced self-organization and its practical importance remains unknown territory to many tribologists. Friction is usually thought of as irreversible dissipation of energy and deterioration; however, under certain conditions, friction can lead to the formation of new structures at the interface, including in-situ tribofilms and various patterns at the interface. This thesis studies self-organization and instabilities at the frictional interface, including the instability due to the temperature-dependency of the coefficient of friction, the transient process of frictional running-in, frictional Turing systems, the stick-and-slip phenomenon, and, finally, contact angle (CA) hysteresis as an example of solid-liquid friction and dissipation. All these problems are chosen to bridge the gap between fundamental interest in understanding the conditions leading to self-organization and practical motivation. We study the relationship between friction-induced instabilities and friction-induced self-organization. Friction is usually thought of as a stabilizing factor; however, sometimes it leads to the instability of sliding, in particular when friction is coupled with another process. Instabilities constitute the main mechanism for pattern formation. At first, a stationary structure loses its stability; after that, vibrations with increasing amplitude occur, leading to a limit cycle corresponding to a periodic pattern. The self-organization is usually beneficial for friction and wear reduction because the tribological systems tend to enter a state with the lowest energy dissipation. The introductory chapter starts with basic definitions related to self-organization, instabilities and friction, literature review, and objectives. We discuss fundamental concepts that provide a methodological tool to investigate, understand and enhance beneficial processes in tribosystems which might lead to self-organization. These processes could result in the ability of a

  16. Energy-efficient downlink resource management in self-organized OFDMA-based two-tier femtocell networks

    NASA Astrophysics Data System (ADS)

    Shahid, Adnan; Aslam, Saleem; Kim, Hyung Seok; Lee, Kyung-Geun

    2015-12-01

    Femtocell is a novel technology that is used for escalating indoor coverage as well as the capacity of traditional cellular networks. However, interference is the limiting factor for performance improvement due to co-channel deployment between macrocells and femtocells. The traditional network planning is not feasible because of the random deployment of femtocells. Therefore, self-organization approaches are the key to having successful deployment of femtocells. This study presents the joint resource block (RB) and power allocation task for the two-tier femtocell network in a self-organizing manner, with the concern to minimizing the impact of interference and maximizing the energy efficiency. In this study, we analyze the performance of the system in terms of the energy efficiency, which is composed of both the transmission and circuit power. Most of the previous studies investigate the performance regarding the throughput requirement of the two-tier femtocell network while the energy efficiency aspect is largely ignored. Here, the joint allocation task is modeled as a non-cooperative game which is demonstrated to exhibit pure and unique Nash equilibrium. In order to reduce the complexity of the proposed non-cooperative game, the joint RB and power allocation task is divided into two subproblems: an RB allocation and a particle swarm optimization-based power allocation. The analysis of the proposed game is carried out in terms of not only energy efficiency but also throughput. With practical 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) parameters, the simulation results illustrate the superior performance of the proposed game as compared to the traditional methods. Also, the comparison is carried out with the joint allocation scheme which only considers the throughput as the objective function. The results illustrate that significant performance improvement is achieved in terms of energy efficiency with slight loss in the throughput. The

  17. The importance of structured noise in the generation of self-organizing tissue patterns through contact-mediated cell–cell signalling

    PubMed Central

    Cohen, Michael; Baum, Buzz; Miodownik, Mark

    2011-01-01

    Lateral inhibition provides the basis for a self-organizing patterning system in which distinct cell states emerge from an otherwise uniform field of cells. The development of the microchaete bristle pattern on the notum of the fruitfly, Drosophila melanogaster, has long served as a popular model of this process. We recently showed that this bristle pattern depends upon a population of dynamic, basal actin-based filopodia, which span multiple cell diameters. These protrusions establish transient signalling contacts between non-neighbouring cells, generating a type of structured noise that helps to yield a well-ordered and spaced pattern of bristles. Here, we develop a general model of protrusion-based patterning to analyse the role of noise in this process. Using a simple asynchronous cellular automata rule-based model we show that this type of structured noise drives the gradual refinement of lateral inhibition-mediated patterning, as the system moves towards a stable configuration in which cells expressing the inhibitory signal are near-optimally packed. By analysing the effects of introducing thresholds required for signal detection in this model of lateral inhibition, our study shows how filopodia-mediated cell–cell communication can generate complex patterns of spots and stripes, which, in the presence of signalling noise, align themselves across a patterning field. Thus, intermittent protrusion-based signalling has the potential to yield robust self-organizing tissue-wide patterns without the need to invoke diffusion-mediated signalling. PMID:21084342

  18. Control of the NASA Langley 16-Foot Transonic Tunnel with the Self-Organizing Map

    NASA Technical Reports Server (NTRS)

    Motter, Mark A.

    1999-01-01

    A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a self-organizing map (SOM). Multiple self-organizing maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experiential knowledge gained from decades of operation. Each SOM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.

  19. Self-Organized Criticality and Stock Market Dynamics: an Empirical Study

    SciTech Connect

    M. Bartolozzi; D. B. Leinweber; A. W. Thomas

    2004-05-01

    The Stock Market is a complex self-interacting system, characterized by an intermittent behavior. Periods of high activity alternate with periods of relative calm. In the present work we investigate empirically about the possibility that the market is in a self-organized critical state (SOC). A wavelet transform method is used in order to separate high activity periods, related to the avalanches of sandpile models, from quiescent. A statistical analysis of the filtered data show a power law behavior in the avalanche size, duration and laminar times. The memory process, implied by the power law distribution, of the laminar times is not consistent with classical conservative models for self-organized criticality. We argue that a ''near-SOC'' state or a time dependence in the driver, which may be chaotic, can explain this behavior.

  20. Statistics of avalanches in the self-organized criticality state of a Josephson junction

    SciTech Connect

    Matizen, E. V.; Martynets, V. G. Bezverkhii, P. P.

    2010-08-15

    Magnetic flux avalanches in Josephson junctions that include superconductor-insulator-superconductor (SIS) tunnel junctions and are magnetized at temperatures lower than approximately 5 K have been studied in detail. Avalanches are of stochastic character and appear when the magnetic field penetration depth {lambda} into a junction becomes equal to the length a of the Josephson junction with a decrease in the temperature. The statistical properties of such avalanches are presented. The size distribution of the avalanches is a power law with a negative noninteger exponent about unity, indicating the self-organized criticality state. The self-organized criticality state is not observed in Josephson junctions with a superconductor-normal metal-superconductor (SNS) junction.

  1. REVIEW ARTICLE: Forest fires and other examples of self-organized criticality

    NASA Astrophysics Data System (ADS)

    Clar, Siegfried; Drossel, Barbara; Schwabl, Franz

    1996-09-01

    We review the properties of the self-organized critical (SOC) forest-fire model. The paradigm of self-organized criticality refers to the tendency of certain large dissipative systems to drive themselves into a critical state independent of the initial conditions and without fine tuning of the parameters. After an introduction, we define the rules of the model and discuss various large-scale structures which may appear in this system. The origin of the critical behaviour is explained, critical exponents are introduced and scaling relations between the exponents are derived. Results of computer simulations and analytical calculations are summarized. The existence of an upper critical dimension and the universality of the critical behaviour under changes of lattice symmetry or the introduction of immunity are discussed. A survey of interesting modifications of the forest-fire model is given. Finally, several other important SOC models are briefly described.

  2. Modeling self-organization of communication and topology in Social Networks

    NASA Astrophysics Data System (ADS)

    Sneppen, Kim

    2007-03-01

    We introduce a model of self-organization of communication and topology in social networks with a feedback between different communication habits and the topology. To study this feedback, we let agents communicate to build a perception of a network and use this information to create strategic links. We observe a narrow distribution of links when the communication is low and a system with a broad distribution of links when the communication is high. We also analyze the outcome of chatting, cheating, and lying, as strategies to get better access to information in the network. Chatting, although only adopted by a few agents, gives a global gain in the system. Contrary, in a system with too many liars a global loss is inevitable. References: M. Rosvall and K. Sneppen. ``Modeling self-organization of communication and topology in social networks.'' Phys. Rev. E 74:16108 (2006)

  3. Self-Organization of Light in Optical Media with Competing Nonlinearities.

    PubMed

    Maucher, F; Pohl, T; Skupin, S; Krolikowski, W

    2016-04-22

    We study the propagation of light beams through optical media with competing nonlocal nonlinearities. We demonstrate that the nonlocality of competing focusing and defocusing nonlinearities gives rise to self-organization and stationary states with stable hexagonal intensity patterns, akin to transverse crystals of light filaments. Signatures of this long-range ordering are shown to be observable in the propagation of light in optical waveguides and even in free space. We consider a specific form of the nonlinear response that arises in atomic vapor upon proper light coupling. Yet, the general phenomenon of self-organization is a generic consequence of competing nonlocal nonlinearities, and may, hence, also be observed in other settings. PMID:27152806

  4. A self-organizing neural network for job scheduling in distributed systems

    NASA Astrophysics Data System (ADS)

    Newman, Harvey B.; Legrand, Iosif C.

    2001-08-01

    The aim of this work is to describe a possible approach for the optimization of the job scheduling in large distributed systems, based on a self-organizing Neural Network. This dynamic scheduling system should be seen as adaptive middle layer software, aware of current available resources and making the scheduling decisions using the "past experience." It aims to optimize job specific parameters as well as the resource utilization. The scheduling system is able to dynamically learn and cluster information in a large dimensional parameter space and at the same time to explore new regions in the parameters space. This self-organizing scheduling system may offer a possible solution to provide an effective use of resources for the off-line data processing jobs for future HEP experiments.

  5. Exploring the patterns and evolution of self-organized urban street networks through modeling

    NASA Astrophysics Data System (ADS)

    Rui, Yikang; Ban, Yifang; Wang, Jiechen; Haas, Jan

    2013-03-01

    As one of the most important subsystems in cities, urban street networks have recently been well studied by using the approach of complex networks. This paper proposes a growing model for self-organized urban street networks. The model involves a competition among new centers with different values of attraction radius and a local optimal principle of both geometrical and topological factors. We find that with the model growth, the local optimization in the connection process and appropriate probability for the loop construction well reflect the evolution strategy in real-world cities. Moreover, different values of attraction radius in centers competition process lead to morphological change in patterns including urban network, polycentric and monocentric structures. The model succeeds in reproducing a large diversity of road network patterns by varying parameters. The similarity between the properties of our model and empirical results implies that a simple universal growth mechanism exists in self-organized cities.

  6. Self-Organized Criticality in Glassy Spin Systems Requires a Diverging Number of Neighbors

    NASA Astrophysics Data System (ADS)

    Andresen, Juan Carlos; Zhu, Zheng; Andrist, Ruben S.; Katzgraber, Helmut G.; Dobrosavljević, V.; Zimanyi, Gergely T.

    2013-08-01

    We investigate the conditions required for general spin systems with frustration and disorder to display self-organized criticality, a property which so far has been established only for the fully connected infinite-range Sherrington-Kirkpatrick Ising spin-glass model [Phys. Rev. Lett. 83, 1034 (1999)]. Here, we study both avalanche and magnetization jump distributions triggered by an external magnetic field, as well as internal field distributions in the short-range Edwards-Anderson Ising spin glass for various space dimensions between 2 and 8, as well as the fixed-connectivity mean-field Viana-Bray model. Our numerical results, obtained on systems of unprecedented size, demonstrate that self-organized criticality is recovered only in the strict limit of a diverging number of neighbors and is not a generic property of spin-glass models in finite space dimensions.

  7. Design of vector quantizer for image compression using self-organizing feature map and surface fitting.

    PubMed

    Laha, Arijit; Pal, Nikhil R; Chanda, Bhabatosh

    2004-10-01

    We propose a new scheme of designing a vector quantizer for image compression. First, a set of codevectors is generated using the self-organizing feature map algorithm. Then, the set of blocks associated with each code vector is modeled by a cubic surface for better perceptual fidelity of the reconstructed images. Mean-removed vectors from a set of training images is used for the construction of a generic codebook. Further, Huffman coding of the indices generated by the encoder and the difference-coded mean values of the blocks are used to achieve better compression ratio. We proposed two indices for quantitative assessment of the psychovisual quality (blocking effect) of the reconstructed image. Our experiments on several training and test images demonstrate that the proposed scheme can produce reconstructed images of good quality while achieving compression at low bit rates. Index Terms-Cubic surface fitting, generic codebook, image compression, self-organizing feature map, vector quantization. PMID:15462140

  8. A link between nonlinear self-organization and dissipation in drift-wave turbulence

    SciTech Connect

    Manz, P.; Birkenmeier, G.; Stroth, U.; Ramisch, M.

    2012-08-15

    Structure formation and self-organization in two-dimensional drift-wave turbulence show up in many different faces. Fluctuation data from a magnetized plasma are analyzed and three mechanisms transferring kinetic energy to large-scale structures are identified. Beside the common vortex merger, clustering of vortices constituting a large-scale strain field and vortex thinning, where due to the interactions of vortices of different scales larger vortices are amplified by the smaller ones, are observed. The vortex thinning mechanism appears to be the most efficient one to generate large scale structures in drift-wave turbulence. Vortex merging as well as vortex clustering are accompanied by strong energy transfer to small-scale noncoherent fluctuations (dissipation) balancing the negative entropy generation due to the self-organization process.

  9. Self-organized highly ordered TiO{sub 2} nanotubes in organic aqueous system

    SciTech Connect

    Wan Jun; Yan Xia; Ding Junjie; Wang Meng; Hu Kongcheng

    2009-12-15

    A simple method to achieve self-organized, freestanding TiO{sub 2} nanotube array was constructed, free of corrosive etching process which was traditionally employed to separate TiO{sub 2} nanotubes from the metallic Ti substrate. The TiO{sub 2} nanotube arrays were constructed through potentiostatic anodization of Ti foil in aqueous electrolyte containing NH{sub 4}F and ethylene glycol. The nanotubes in the array were of 45 {mu}m lengths and 100 nm average pore diameters. The effect of NH{sub 4}F concentration on the length of the self-organized nanotube arrays was investigated. Electrochemical and spectroscopic measurements showed that the as-prepared nanotubes possessed large surface areas, good uniformity, and were ready for enzyme immobilization. The as-prepared nanotube arrays were amorphous, but crystallized with annealing at elevated temperatures, as demonstrated by X-ray diffraction (XRD).

  10. Microscopic mechanism for self-organized quasiperiodicity in random networks of nonlinear oscillators

    NASA Astrophysics Data System (ADS)

    Burioni, Raffaella; di Santo, Serena; di Volo, Matteo; Vezzani, Alessandro

    2014-10-01

    Self-organized quasiperiodicity is one of the most puzzling dynamical phases observed in systems of nonlinear coupled oscillators. The single dynamical units are not locked to the periodic mean field they produce, but they still feature a coherent behavior, through an unexplained complex form of correlation. We consider a class of leaky integrate-and-fire oscillators on random sparse and massive networks with dynamical synapses, featuring self-organized quasiperiodicity, and we show how complex collective oscillations arise from constructive interference of microscopic dynamics. In particular, we find a simple quantitative relationship between two relevant microscopic dynamical time scales and the macroscopic time scale of the global signal. We show that the proposed relation is a general property of collective oscillations, common to all the partially synchronous dynamical phases analyzed. We argue that an analogous mechanism could be at the origin of similar network dynamics.

  11. On the Computational Power of Spiking Neural P Systems with Self-Organization

    PubMed Central

    Wang, Xun; Song, Tao; Gong, Faming; Zheng, Pan

    2016-01-01

    Neural-like computing models are versatile computing mechanisms in the field of artificial intelligence. Spiking neural P systems (SN P systems for short) are one of the recently developed spiking neural network models inspired by the way neurons communicate. The communications among neurons are essentially achieved by spikes, i. e. short electrical pulses. In terms of motivation, SN P systems fall into the third generation of neural network models. In this study, a novel variant of SN P systems, namely SN P systems with self-organization, is introduced, and the computational power of the system is investigated and evaluated. It is proved that SN P systems with self-organization are capable of computing and accept the family of sets of Turing computable natural numbers. Moreover, with 87 neurons the system can compute any Turing computable recursive function, thus achieves Turing universality. These results demonstrate promising initiatives to solve an open problem arisen by Gh Păun. PMID:27283843

  12. Self Organized Spatial-Temporal Structure within the Fractured Vadose Zone: Influence of Fracture Intersections

    SciTech Connect

    Randall A. Laviolette; Robert J. Glass

    2004-08-01

    Under conditions of unsaturated flow, others have shown experimentally that fracture intersections can direct flow to a single exiting fracture. In addition, they have been found to gather water from above to release as a pulse below. We formulate a simple model where these two behaviors are embedded within a network. With slow steady inflow distributed randomly along the top of the network, the system self organizes to form avalanches of water that can penetrate to great depths. When all intersections split their outflow, flow diverges with depth and develops into a self-organized dynamical state where the distribution of avalanche sizes follows a power-law over many decades. As the fraction of intersections that direct outflow singly is increased, spatial structure passes from divergent through braided to a fully convergent, hierarchical flow regime where avalanche size is minimized along one-dimensional slender pathways.

  13. Derivations and Comparisons of Three Groups ofSelf-Organization Theories for Magnetohydrodynamic Plasmas

    NASA Astrophysics Data System (ADS)

    Kondoh, Yoshiomi; Sato, Tetsuya

    1994-04-01

    A theoretical investigation on self-organization theories ofdissipative MHD plasmas is presented to derive three groups oftheories that lead to the same relaxed state of ∇ × B=λ B, in order to find more essential physicalpicture embedded in self-organization phenomena due to nonlinear anddissipative processes. Comparisons among all of the theories treatedand derived here suggest that a theory standing upon spectrumspreadings and selective dissipations of eigenmodes for thedissipative operator -∇ ×η j and leading toself-organized relaxed states of ∇ ×ηj=α B/2 with the minimum dissipation rate is the most agreeable to various results obtained by experiments and by 3-D MHD simulations reported so far.

  14. Least action and entropy considerations of self-organization in Benard cells

    NASA Astrophysics Data System (ADS)

    Georgiev, Georgi; Iannacchione, Germano

    We study self-organization in complex systems using first principles in physics. Our approach involves the principle of least action and the second law of thermodynamics. In far from equilibrium systems, energy gradients cause internal ordering to facilitate the dissipation of energy in the environment. This internal ordering decreases their internal entropy in order to obey the principle of least action, minimizing the product of time and energy for transport through the system. We are considering the connection between action and entropy decrease inside Benard cells in order to derive some general features of self-organization. We are developing mathematical treatment of this coupling and comparing it to results from experiments and simulations.

  15. On the Computational Power of Spiking Neural P Systems with Self-Organization.

    PubMed

    Wang, Xun; Song, Tao; Gong, Faming; Zheng, Pan

    2016-01-01

    Neural-like computing models are versatile computing mechanisms in the field of artificial intelligence. Spiking neural P systems (SN P systems for short) are one of the recently developed spiking neural network models inspired by the way neurons communicate. The communications among neurons are essentially achieved by spikes, i. e. short electrical pulses. In terms of motivation, SN P systems fall into the third generation of neural network models. In this study, a novel variant of SN P systems, namely SN P systems with self-organization, is introduced, and the computational power of the system is investigated and evaluated. It is proved that SN P systems with self-organization are capable of computing and accept the family of sets of Turing computable natural numbers. Moreover, with 87 neurons the system can compute any Turing computable recursive function, thus achieves Turing universality. These results demonstrate promising initiatives to solve an open problem arisen by Gh Păun. PMID:27283843

  16. Kohonen Self-organizing Feature Maps as a Means to Benchmark College and University Websites

    NASA Astrophysics Data System (ADS)

    Cooper, Cameron; Burns, Andrew

    2007-06-01

    Websites for colleges and universities have become the primary means for students to obtain information in the college search process. Consequently, institutions of higher education should target their websites toward prospective and current students' needs, interests, and tastes. Numerous parameters must be determined in creating a school website (e.g. number of links, page size, use of graphics, utilization of dynamic elements, and menuing options). This research details a decision support framework based upon Kohonen self-organizing feature maps to determine students' specific preferences for school websites. This research attempts to remove some of the subjectivity in designing a school website by finding the commonalities among websites that students find appealing and effective. Self-organizing feature maps are employed as a clustering method to compare the school's current website to other sites that students find both appealing and effective.

  17. Self organization of exotic oil-in-oil phases driven by tunable electrohydrodynamics

    PubMed Central

    Varshney, Atul; Ghosh, Shankar; Bhattacharya, S.; Yethiraj, Anand

    2012-01-01

    Self organization of large-scale structures in nature - either coherent structures like crystals, or incoherent dynamic structures like clouds - is governed by long-range interactions. In many problems, hydrodynamics and electrostatics are the source of such long-range interactions. The tuning of electrostatic interactions has helped to elucidate when coherent crystalline structures or incoherent amorphous structures form in colloidal systems. However, there is little understanding of self organization in situations where both electrostatic and hydrodynamic interactions are present. We present a minimal two-component oil-in-oil model system where we can control the strength and lengthscale of the electrohydrodynamic interactions by tuning the amplitude and frequency of the imposed electric field. As a function of the hydrodynamic lengthscale, we observe a rich phenomenology of exotic structure and dynamics, from incoherent cloud-like structures and chaotic droplet dynamics, to polyhedral droplet phases, to coherent droplet arrays. PMID:23071902

  18. Self-organized electromagnetic field structures in laser-produced counter-streaming plasmas

    NASA Astrophysics Data System (ADS)

    Kugland, N. L.; Ryutov, D. D.; Chang, P.-Y.; Drake, R. P.; Fiksel, G.; Froula, D. H.; Glenzer, S. H.; Gregori, G.; Grosskopf, M.; Koenig, M.; Kuramitsu, Y.; Kuranz, C.; Levy, M. C.; Liang, E.; Meinecke, J.; Miniati, F.; Morita, T.; Pelka, A.; Plechaty, C.; Presura, R.; Ravasio, A.; Remington, B. A.; Reville, B.; Ross, J. S.; Sakawa, Y.; Spitkovsky, A.; Takabe, H.; Park, H.-S.

    2012-11-01

    Self-organization occurs in plasmas when energy progressively transfers from smaller to larger scales in an inverse cascade. Global structures that emerge from turbulent plasmas can be found in the laboratory and in astrophysical settings; for example, the cosmic magnetic field, collisionless shocks in supernova remnants and the internal structures of newly formed stars known as Herbig-Haro objects. Here we show that large, stable electromagnetic field structures can also arise within counter-streaming supersonic plasmas in the laboratory. These surprising structures, formed by a yet unexplained mechanism, are predominantly oriented transverse to the primary flow direction, extend for much larger distances than the intrinsic plasma spatial scales and persist for much longer than the plasma kinetic timescales. Our results challenge existing models of counter-streaming plasmas and can be used to better understand large-scale and long-time plasma self-organization.

  19. Handwritten digit recognition by adaptive-subspace self-organizing map (ASSOM).

    PubMed

    Zhang, B; Fu, M; Yan, H; Jabri, M A

    1999-01-01

    The adaptive-subspace self-organizing map (ASSOM) proposed by Kohonen is a recent development in self-organizing map (SOM) computation. In this paper, we propose a method to realize ASSOM using a neural learning algorithm in nonlinear autoencoder networks. Our method has the advantage of numerical stability. We have applied our ASSOM model to build a modular classification system for handwritten digit recognition. Ten ASSOM modules are used to capture different features in the ten classes of digits. When a test digit is presented to all the modules, each module provides a reconstructed pattern and the system outputs a class label by comparing the ten reconstruction errors. Our experiments show promising results. For relatively small size modules, the classification accuracy reaches 99.3% on the training set and over 97% on the testing set. PMID:18252591

  20. Plasmonic electric near-field enhancement in self-organized gold nanoparticles in macroscopic arrays

    NASA Astrophysics Data System (ADS)

    Mondes, V.; Antonsson, E.; Plenge, J.; Raschpichler, C.; Halfpap, I.; Menski, A.; Graf, C.; Kling, M. F.; Rühl, E.

    2016-06-01

    When plasmonic nanoparticles are incorporated into nanostructures and they are exposed to external optical fields, plasmonic coupling causes electric near-field enhancement which is significantly larger than that of isolated nanoparticles. We report on the plasmonic coupling in arrays of gold nanospheres (20 ± 3 and 50 ± 4 nm) prepared by colloidal chemistry and self-organization. This yields field enhancement in arrays with areas of several mm2 and provides an alternative approach to lithographic methods for preparation of nanostructures for plasmonic applications. Gold nanospheres are surface-functionalized by organic ligands, which define the interparticle distance in the array upon self-organization of the nanoparticles. The experiments are accompanied by finite-difference time-domain simulations, which quantify the dependence of the field enhancement on the interparticle distance.

  1. First-Order Transition in a Spin Model for Self-Organization

    NASA Astrophysics Data System (ADS)

    Bauvin, R.; Kamp, Y.

    The paper examines the emergence of self-organization in a population where tandem recruitment is combined with individual memory. The time evolution is modeled as a two-dimensional spin system with local interaction along the time axis and a mean-field interaction along the other axis. We generalize a previous result obtained with this model from the case of two sources to the multisource situation and show a twofold connection with the Potts model. First, when individual memory exceeds a critical value, a phase transition sets in, which is second order for two sources but first order beyond, similarly to the mean-field theory of the Potts model. In addition, the self-organization problem considered here relies on a special case of the one-dimensional nearest-neighbor Potts model with external field, which is shown to be explicitly solvable.

  2. Fe and Co nanostructures embedded into the Cu(100) surface: Self-Organization and magnetic properties

    SciTech Connect

    Kolesnikov, S. V. Klavsyuk, A. L.; Saletsky, A. M.

    2015-10-15

    The self-organization and magnetic properties of small iron and cobalt nanostructures embedded into the first layer of a Cu(100) surface are investigated using the self-learning kinetic Monte Carlo method and density functional theory. The similarities and differences between the Fe/Cu(100) and the Co/Cu(100) are underlined. The time evolution of magnetic properties of a copper monolayer with embedded magnetic atoms at 380 K is discussed.

  3. Self-Organized Criticality in Small-World Networks Based on the Social Balance Dynamics

    NASA Astrophysics Data System (ADS)

    Meng, Qing-Kuan

    2011-11-01

    A node model is proposed to study the self-organized criticality in the small-world networks which represent the social networks. Based on the node model and the social balance dynamics, the social networks are mapped to the thermodynamic systems and the phenomena are studied with physical methods. It is found that the avalanche in the small-world networks at the critical state satisfies the power-law distribution spatially and temporally.

  4. Self-organization and forcing templates in coastal barrier response to storms

    NASA Astrophysics Data System (ADS)

    Lazarus, E.

    2015-12-01

    When a storm event pushes water up and over a coastal barrier, cross-shore flow transports sediment from the barrier face to the back-barrier environment. This natural physical process is called "overwash", and "washover" is the sedimentary deposit it forms. Overwash and washover support critical coastal habitats, and enable barriers to maintain their height and width relative to rising sea level. On developed barrier coasts, overwash constitutes a natural hazard, which sea-level rise will exacerbate. Overwash is also a prerequisite for barrier breaching and coastal flooding. Predicting occurrence and characteristics of overwash and washover has significant societal value. Hazard models typically assume that pre-storm barrier morphology determines how the barrier changes during a storm. However, classic work has documented the absence of a relationship between pre/post-storm topography in some cases, and has also identified rhythmic patterns in washover alongshore. Previous explanations for these spatial patterns have looked to forcing templates, forms that get imprinted in the barrier shape. An alternative explanation is that washover patterns self-organize, emerging from feedbacks between water flow and sediment transport. Self-organization and forcing templates are often framed as mutually exclusive, but patterns likely form across a continuum of conditions. Here, I use data from a new physical experiment to suggest that spatial patterns in washover can self-organize within the limit of a forcing template of some critical "strength", beyond which pre/post-storm morphologies are highly correlated. Quantifying spatial patterns in washover deposits opens exciting questions regarding coastal morphodynamic response to storms. Measurement of relative template strength over extended spatial (and temporal) scales has the potential to improve hazard assessment and prediction, particularly where template strength is low and self-organization dominates barrier change.

  5. Feature discovery on segmented objects in SAR imagery using self-organizing neural networks

    SciTech Connect

    Fogler, R.J.; Koch, M.W.; Moya, M.M. ); Hush, D.R. . Dept. of Electrical and Computer Engineering)

    1992-01-01

    In this paper we investigate the applicability of the feature extraction mechanisms found in the neurophysiology of mammals to the problem of object recognition in synthetic aperture radar imagery. Our approach is to present multiple views of objects to be recognized to a two-stage self-organizing neural network architecture. The first stage, a two-layer Neocognitron, performs feature extraction in each layer The resulting feature vectors are presented to the second stage, an ART-2A classifier self-organizing neural network which clusters the features into multiple object categories. The feature extraction operators resulting from the self-organization process are compared to the feature extraction mechanisms found in the neurophysiology of vision. In a previous paper, the Neocognitron was trained on raw SAR imagery. The architecture was able to recognize a simulated vehicle at arbitrary azimuthal orientations at a single depression angle while rejecting clutter as well as other vehicles. Feature extraction on raw imagery yielded features that were robust but very difficult to interpret. In this paper we report the results of some new experiments in which the self-organization process is applied separately to shadow and bright returns from objects to be recognized. Feature extraction on shadow returns yield oriented contrast edge operators suggestive of bipartite simple cells observed in the striate cortex of mammals. Feature extraction on the specularity patterns in bright returns yield a collection of operators resembling a twodimensional Haar basis set. We compare the performance of the earlier two-stage neural network trained on raw imagery with a modified network using the new feature set.

  6. Feature discovery on segmented objects in SAR imagery using self-organizing neural networks

    SciTech Connect

    Fogler, R.J.; Koch, M.W.; Moya, M.M.; Hush, D.R.

    1992-12-31

    In this paper we investigate the applicability of the feature extraction mechanisms found in the neurophysiology of mammals to the problem of object recognition in synthetic aperture radar imagery. Our approach is to present multiple views of objects to be recognized to a two-stage self-organizing neural network architecture. The first stage, a two-layer Neocognitron, performs feature extraction in each layer The resulting feature vectors are presented to the second stage, an ART-2A classifier self-organizing neural network which clusters the features into multiple object categories. The feature extraction operators resulting from the self-organization process are compared to the feature extraction mechanisms found in the neurophysiology of vision. In a previous paper, the Neocognitron was trained on raw SAR imagery. The architecture was able to recognize a simulated vehicle at arbitrary azimuthal orientations at a single depression angle while rejecting clutter as well as other vehicles. Feature extraction on raw imagery yielded features that were robust but very difficult to interpret. In this paper we report the results of some new experiments in which the self-organization process is applied separately to shadow and bright returns from objects to be recognized. Feature extraction on shadow returns yield oriented contrast edge operators suggestive of bipartite simple cells observed in the striate cortex of mammals. Feature extraction on the specularity patterns in bright returns yield a collection of operators resembling a twodimensional Haar basis set. We compare the performance of the earlier two-stage neural network trained on raw imagery with a modified network using the new feature set.

  7. Online algorithm for the self-organizing map of symbol strings.

    PubMed

    Somervuo, Panu J

    2004-01-01

    In this work an online algorithm is presented for the construction of the self-organizing map (SOM) of symbol strings. Each node of the SOM grid is associated with a model string which is a variable-vector sequence. Smooth interpolation method is applied in the training which performs simultaneous adaptation of the symbol content and the length of the model string. The efficiency of the method is demonstrated by the clustering of a 100,000-word English dictionary. PMID:15555863

  8. The Advancement of Family Therapy Theory Based on the Science of Self-Organizing Complex Systems.

    NASA Astrophysics Data System (ADS)

    Ramsey-Kemper, Valerie Ann

    1995-01-01

    Problem. The purpose of this study was to review the literature which presents the latest advancements in the field of family therapy theory. Since such advancement has relied on the scientific developments in the study of autopoietic self-organizing complex systems, then the review began with an historical overview of the development of these natural scientific concepts. The study then examined how the latest scientific concepts have been integrated with family therapy practice. The document is built on the theory that individuals are living, complex, self-organizing, autopoietic systems. When individual systems interact with other individual systems (such as in family interaction, or in interaction between therapist and client), then a third system emerges, which is the relationship. It is through interaction in the relationship that transformation of an individual system can occur. Method. The historical antecedents of the field of family therapy were outlined. It was demonstrated, via literature review, that the field of family therapy has traditionally paralleled developments in the hard sciences. Further, it was demonstrated via literature review that the newest understandings of the development of individuals, family systems, and therapeutic systems also parallel recent natural science developments, namely those developments based on the science of self-organizing complex systems. Outcome. The results of the study are twofold. First, the study articulates an expanded theory of the therapist, individual, and family as autopoietic self-organizing complex systems. Second, the study provides an expanded hypothesis which concerns recommendations for future research which will further advance the latest theories of family therapy. More precisely, the expanded hypothesis suggests that qualitative research, rather than quantitative research, is the method of choice for studying the effectiveness of phenomenological therapy.

  9. Biogenic gradients in algal density affect the emergent properties of spatially self-organized mussel beds

    PubMed Central

    Liu, Quan-Xing; Weerman, Ellen J.; Gupta, Rohit; Herman, Peter M. J.; Olff, Han; van de Koppel, Johan

    2014-01-01

    Theoretical models highlight that spatially self-organized patterns can have important emergent effects on the functioning of ecosystems, for instance by increasing productivity and affecting the vulnerability to catastrophic shifts. However, most theoretical studies presume idealized homogeneous conditions, which are rarely met in real ecosystems. Using self-organized mussel beds as a case study, we reveal that spatial heterogeneity, resulting from the large-scale effects of mussel beds on their environment, significantly alters the emergent properties predicted by idealized self-organization models that assume homogeneous conditions. The proposed model explicitly considers that the suspended algae, the prime food for the mussels, are supplied by water flow from the seaward boundary of the bed, which causes in combination with consumption a gradual depletion of algae over the simulated domain. Predictions of the model are consistent with properties of natural mussel patterns observed in the field, featuring a decline in mussel biomass and a change in patterning. Model analyses reveal a fundamental change in ecosystem functioning when this self-induced algal depletion gradient is included in the model. First, no enhancement of secondary productivity of the mussels comparing with non-patterns states is predicted, irrespective of parameter setting; the equilibrium amount of mussels is entirely set by the input of algae. Second, alternate stable states, potentially present in the original (no algal gradient) model, are absent when gradual depletion of algae in the overflowing water layer is allowed. Our findings stress the importance of including sufficiently realistic environmental conditions when assessing the emergent properties of self-organized ecosystems. PMID:24759542

  10. Emergence of self-organized long-period fiber gratings in supercontinuum-generating optical fibers

    PubMed Central

    Tu, Haohua; Liang, Xing; Marks, Daniel L.; Boppart, Stephen A.

    2010-01-01

    A localized long-period fiber grating emerges in a silica optical fiber transmitting femtosecond pulse-induced supercontinuum. Simultaneously, a specific higher-order fiber cladding mode associated with the grating gains amplification at the expense of the fiber core mode. The grating has a period dependent on the dielectric structure of the fiber and is therefore classified as a self-organized structure. PMID:19252587

  11. Modeling the Self-organized Critical Behavior of the Plasma Sheet Reconnection Dynamics

    NASA Technical Reports Server (NTRS)

    Klimas, Alex; Uritsky, Vadim; Baker, Daniel

    2006-01-01

    Analyses of Polar UVI auroral image data reviewed in our other presentation at this meeting (V. Uritsky, A. Klimas) show that bright night-side high-latitude UV emissions exhibit so many of the key properties of systems in self-organized criticality (SOC) that an alternate interpretation has become virtually impossible. It is now necessary to find and model the source of this behavior. We note that the most common models of self-organized criticality are numerical sandpiles. These are, at root, models that govern the transport of some quantity from a region where it is loaded to another where it is unloaded. Transport is enabled by the excitation of a local threshold instability; it is intermittent and bursty, and it exhibits a number of scale-free statistical properties. Searching for a system in the magnetosphere that is analogous and that, in addition, is known to produce auroral signatures, we focus on the reconnection dynamics of the plasma sheet. In our previous work, a driven reconnection model has been constructed and has been under study. The transport of electromagnetic (primarily magnetic) energy carried by the Poynting flux into the reconnection region of the model has been examined. All of the analysis techniques, and more, that have been applied to the auroral image data have also been applied to this Poynting flux. Here, we report new results showing that this model also exhibits so many of the key properties of systems in self-organized criticality that an alternate interpretation is implausible. Further, we find a strong correlation between these key properties of the model and those of the auroral UV emissions. We suggest that, in general, the driven reconnection model is an important step toward a realistic plasma physical model of self-organized criticality and we conclude, more specifically, that it is also a step in the right direction toward modeling the multiscale reconnection dynamics of the magnetotail.

  12. Modeling the Self-organized Critical Behavior of Earth's Plasma Sheet Reconnection Dynamics

    NASA Technical Reports Server (NTRS)

    Klimas, Alexander J.

    2006-01-01

    Analyses of Polar UVI auroral image data show that bright night-side high-latitude W emissions exhibit so many of the key properties of systems in self-organized criticality that an alternate interpretation has become virtually impossible. These analyses will be reviewed. It is now necessary to find and model the source of this behavior. We note that the most common models of self-organized criticality are numerical sandpiles. These are, at root, models that govern the transport of some quantity from a region where it is loaded to another where it is unloaded. Transport is enabled by the excitation of a local threshold instability; it is intermittent and bursty, and it exhibits a number of scale-free statistical properties. Searching for a system in the magnetosphere that is analogous and that, in addition, is known to produce auroral signatures, we focus on the reconnection dynamics of the magnetotail plasma sheet. In our previous work, a driven reconnection model has been constructed and has been under study. The transport of electromagnetic (primarily magnetic) energy carried by the Poynting flux into the reconnection region of the model has been examined. All of the analysis techniques (and more) that have been applied to the auroral image data have also been applied to this Poynting flux. New results will be presented showing that this model also exhibits so many of the key properties of systems in self-organized criticality that an alternate interpretation is implausible. A strong correlation between these key properties of the model and those of the auroral UV emissions will be demonstrated. We suggest that, in general, the driven reconnection model is an important step toward a realistic plasma physical model of self-organized criticality and we conclude, more specifically, that it is also a step in the right direction toward modeling the multiscale reconnection dynamics of the magnetotail.

  13. Fe and Co nanostructures embedded into the Cu(100) surface: Self-Organization and magnetic properties

    NASA Astrophysics Data System (ADS)

    Kolesnikov, S. V.; Klavsyuk, A. L.; Saletsky, A. M.

    2015-10-01

    The self-organization and magnetic properties of small iron and cobalt nanostructures embedded into the first layer of a Cu(100) surface are investigated using the self-learning kinetic Monte Carlo method and density functional theory. The similarities and differences between the Fe/Cu(100) and the Co/Cu(100) are underlined. The time evolution of magnetic properties of a copper monolayer with embedded magnetic atoms at 380 K is discussed.

  14. Self-organization in psychotherapy: testing the synergetic model of change processes

    PubMed Central

    Schiepek, Günter K.; Tominschek, Igor; Heinzel, Stephan

    2014-01-01

    In recent years, models have been developed that conceive psychotherapy as a self-organizing process of bio-psycho-social systems. These models originate from the theory of self-organization (Synergetics), from the theory of deterministic chaos, or from the approach of self-organized criticality. This process-outcome study examines several hypotheses mainly derived from Synergetics, including the assumption of discontinuous changes in psychotherapy (instead of linear incremental gains), the occurrence of critical instabilities in temporal proximity of pattern transitions, the hypothesis of necessary stable boundary conditions during destabilization processes, and of motivation to change playing the role of a control parameter for psychotherapeutic self-organization. Our study was realized at a day treatment center; 23 patients with obsessive compulsive disorder (OCD) were included. Client self-assessment was performed by an Internet-based process monitoring (referred to as the Synergetic Navigation System), whereby daily ratings were recorded through administering the Therapy Process Questionnaire (TPQ). The process measures of the study were extracted from the subscale dynamics (including the dynamic complexity of their time series) of the TPQ. The outcome criterion was measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) which was completed pre-post and on a bi-weekly schedule by all patients. A second outcome criterion was based on the symptom severity subscale of the TPQ. Results supported the hypothesis of discontinuous changes (pattern transitions), the occurrence of critical instabilities preparing pattern transitions, and of stable boundary conditions as prerequisites for such transitions, but not the assumption of motivation to change as a control parameter. PMID:25324801

  15. How to make large self-organizing maps for nonvectorial data.

    PubMed

    Kohonen, Teuvo; Somervuo, Panu

    2002-01-01

    The self-organizing map (SOM) represents an open set of input samples by a topologically organized, finite set of models. In this paper, a new version of the SOM is used for the clustering, organization, and visualization of a large database of symbol sequences (viz. protein sequences). This method combines two principles: the batch computing version of the SOM, and computation of the generalized median of symbol strings. PMID:12416685

  16. Mitotic chromosome compaction via active loop extrusion

    NASA Astrophysics Data System (ADS)

    Goloborodko, Anton; Imakaev, Maxim; Marko, John; Mirny, Leonid; MIT-Northwestern Team

    During cell division, two copies of each chromosome are segregated from each other and compacted more than hundred-fold into the canonical X-shaped structures. According to earlier microscopic observations and the recent Hi-C study, chromosomes are compacted into arrays of consecutive loops of ~100 kilobases. Mechanisms that lead to formation of such loop arrays are largely unknown. Here we propose that, during cell division, chromosomes can be compacted by enzymes that extrude loops on chromatin fibers. First, we use computer simulations and analytical modeling to show that a system of loop-extruding enzymes on a chromatin fiber self-organizes into an array of consecutive dynamic loops. Second, we model the process of loop extrusion in 3D and show that, coupled with the topo II strand-passing activity, it leads to robust compaction and segregation of sister chromatids. This mechanism of chromosomal condensation and segregation does not require additional proteins or specific DNA markup and is robust against variations in the number and properties of such loop extruding enzymes. Work at NU was supported by the NSF through Grants DMR-1206868 and MCB-1022117, and by the NIH through Grants GM105847 and CA193419. Work at MIT was supported by the NIH through Grants GM114190 R01HG003143.

  17. Self-organization of thin polymer films guided by electrostatic charges on the substrate.

    PubMed

    Zhao, Dan; Martinez, Aaron D; Xi, Xiaolei; Ma, Xinlei; Wu, Ning; Cao, Tingbing

    2011-08-22

    The self-organization of thin polymer films into functional patterns is important both scientifically and technologically. Electric fields have been exploited as an efficient and powerful means to induce the destabilization and self-organization of soft materials. Previous attention, however, has mainly focused on externally applied electric fields. It is shown herein that the internal electric field is strong enough to guide the self-organization of thin polymer films as well. Patterns of electrostatic charges with micrometer resolution are first introduced on a dielectric substrate. A thin polymer film is then spin-coated onto the topographically flat substrate. Upon thermal annealing, the thin polymer film destabilizes due to a lateral gradient of electrostatic stress and flows away from the electroneutral regime to the charged area, resembling the patterns of charges on the substrate. Theoretical and numerical modeling based on the electrohydrodynamic instability shows excellent agreement with experimental observations both qualitatively and quantitatively. It is also demonstrated that the interplay between charge-driven instability with spinodal dewetting and Rayleigh instabilities can generate finer and hierarchical polymeric patterns that are completely different from the charge patterns preintroduced on the substrate. This study provides direct evidence that the internal electric field caused by charges on the substrate is strong enough to destabilize thin polymeric films and generate patterns. This study also demonstrates new strategies for bottom-up fabrication of structured functional materials. PMID:21638784

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

    PubMed Central

    Lushi, Enkeleida; Wioland, Hugo; Goldstein, Raymond E.

    2014-01-01

    Concentrated suspensions of swimming microorganisms and other forms of active matter are known to display complex, self-organized spatiotemporal patterns on scales that are large compared with those of the individual motile units. Despite intensive experimental and theoretical study, it has remained unclear the extent to which the hydrodynamic flows generated by swimming cells, rather than purely steric interactions between them, drive the self-organization. Here we use the recent discovery of a spiral-vortex state in confined suspensions of Bacillus subtilis to study this issue in detail. Those experiments showed that if the radius of confinement in a thin cylindrical chamber is below a critical value, the suspension will spontaneously form a steady single-vortex state encircled by a counter-rotating cell boundary layer, with spiral cell orientation within the vortex. Left unclear, however, was the flagellar orientation, and hence the cell swimming direction, within the spiral vortex. Here, using a fast simulation method that captures oriented cell–cell and cell–fluid interactions in a minimal model of discrete particle systems, we predict the striking, counterintuitive result that in the presence of collectively generated fluid motion, the cells within the spiral vortex actually swim upstream against those flows. This prediction is then confirmed by the experiments reported here, which include measurements of flagella bundle orientation and cell tracking in the self-organized state. These results highlight the complex interplay between cell orientation and hydrodynamic flows in concentrated suspensions of microorganisms. PMID:24958878

  19. Self-organization of intertidal snails facilitates evolution of aggregation behavior.

    PubMed

    Stafford, Richard; Davies, Mark S; Williams, Gray A

    2008-01-01

    Many intertidal snails form aggregations during emersion to minimize desiccation stress. Here we investigate possible mechanisms for the evolution of such behavior. Two behavioral traits (following of mucus trails, and crevice occupation), which both provide selective advantages to individuals that possess the traits over individuals that do not, result in self-organization of aggregations in crevices in the rock surface. We suggest that the existence of self-organizing aggregations provides a mechanism by which aggregation behavior can evolve. The inclusion of an explicitly coded third behavior, aggregation, in a simulated population produces patterns statistically similar to those found on real rocky shores. Allowing these three behaviors to evolve using an evolutionary algorithm, however, results in aggregation behavior being selected against on shores with high crevice density. The inclusion of broadcast spawning dispersal mechanisms in the simulation, however, results in aggregation behavior evolving as predicted on shores with both high crevice density and low crevice density (evolving in crevices first, and then both in crevices and on flat rock), indicating the importance of environmental interactions in understanding evolutionary processes. We propose that self-organization can be an important factor in the evolution of group behaviors. PMID:18573064

  20. Dynamic polarization random walk model and fishbone-like instability for self-organized critical systems

    NASA Astrophysics Data System (ADS)

    Milovanov, Alexander V.

    2011-04-01

    We study the phenomenon of self-organized criticality (SOC) as a transport problem for electrically charged particles. A model for SOC based on the idea of a dynamic polarization response with random walks of the charge carriers gives critical exponents consistent with the results of numerical simulations of the traditional 'sandpile' SOC models, and stability properties, associated with the scaling of the control parameter versus distance to criticality. Relaxations of a supercritical system to SOC are stretched-exponential similar to the typically observed properties of non-Debye relaxation in disordered amorphous dielectrics. Overdriving the system near self-organized criticality is shown to have a destabilizing effect on the SOC state. This instability of the critical state constitutes a fascinating nonlinear system in which SOC and nonlocal properties can appear on an equal footing. The instability cycle is qualitatively similar to the internal kink ('fishbone') mode in a magnetically confined toroidal plasma where beams of energetic particles are injected at high power, and has serious implications for the functioning of complex systems. Theoretical analyses, presented here, are the basis for addressing the various patterns of self-organized critical behavior in connection with the strength of the driving. The results of this work also suggest a type of mixed behavior in which the typical multi-scale features due to SOC can coexist along with the global or coherent features as a consequence of the instability present. An example of this coexistence is speculated for the solar wind-magnetosphere interaction.

  1. Self-organized criticality attributed to a central limit-like convergence effect

    NASA Astrophysics Data System (ADS)

    Kendal, Wayne S.

    2015-03-01

    Self-organized criticality is a hypothesis used to explain the origin of 1 / f noise and other scaling behaviors. Despite being proposed nearly 30 years ago, no consensus exists as to its exact definition or mathematical mechanism(s). Recently, a model for 1 / f noise was proposed based on a family of statistical distributions known as the Tweedie exponential dispersion models. These distributions are characterized by an inherent scale invariance that manifests as a variance to mean power law, called fluctuation scaling; they also serve as foci of convergence in a limit theorem on independent and identically distributed distributions. Fluctuation scaling can be modeled by self-similar stochastic processes that relate the variance to mean power law to 1 / f noise through their correlation structure. A hypothesis is proposed whereby the effects of self-organized criticality are mathematically modeled by the Tweedie distributions and their convergence behavior as applied to self-similar stochastic processes. Sandpile model fluctuations are shown to manifest 1 / f noise, fluctuation scaling, and to conform to the Tweedie compound Poisson distribution. The Tweedie models and their convergence theorem allow for a mechanistic explanation of 1 / f noise and fluctuation scaling in phenomena conventionally attributed to self-organized criticality, thus providing a paradigm shift in our understanding of these phenomena.

  2. Self-organizing CMAC control for a class of MIMO uncertain nonlinear systems.

    PubMed

    Lin, Chih-Min; Chen, Te-Yu

    2009-09-01

    This paper presents a self-organizing control system based on cerebellar model articulation controller (CMAC) for a class of multiple-input-multiple-output (MIMO) uncertain nonlinear systems. The proposed control system merges a CMAC and sliding-mode control (SMC), so the input space dimension of CMAC can be simplified. The structure of CMAC will be self-organized; that is, the layers of CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The control system consists of a self-organizing CMAC (SOCM) and a robust controller. SOCM containing a CMAC uncertainty observer is used as the principal controller and the robust controller is designed to dispel the effect of approximation error. The gradient-descent method is used to online tune the parameters of CMAC and the Lyapunov function is applied to guarantee the stability of the system. A simulation study of inverted double pendulums system and an experimental result of linear ultrasonic motor motion control show that favorable tracking performance can be achieved by using the proposed control system. PMID:19398404

  3. Entropy production rate in a flux-driven self-organizing system

    SciTech Connect

    Kawazura, Y.; Yoshida, Z.

    2010-12-15

    Entropy production rate (EPR) is often effective to describe how a structure is self-organized in a nonequilibrium thermodynamic system. The 'minimum EPR principle' is widely applicable to characterizing self-organized structures, but is sometimes disproved by observations of 'maximum EPR states'. Here we delineate a dual relation between the minimum and maximum principles; the mathematical representation of the duality is given by a Legendre transformation. For explicit formulation, we consider heat transport in the boundary layer of fusion plasma [Z. Yoshida and S. M. Mahajan, Phys. Plasmas 15, 032307 (2008)]. The mechanism of bifurcation and hysteresis (which are the determining characteristics of the so-called H-mode, a self-organized state of reduced thermal conduction) is explained by multiple tangent lines to a pleated graph of an appropriate thermodynamic potential. In the nonlinear regime, we have to generalize Onsager's dissipation function. The generalized function is no longer equivalent to EPR; then EPR ceases to be the determinant of the operating point, and may take either minimum or maximum values depending on how the system is driven.

  4. Microbial diversity affects self-organization of the soil–microbe system with consequences for function

    PubMed Central

    Crawford, John W.; Deacon, Lewis; Grinev, Dmitri; Harris, James A.; Ritz, Karl; Singh, Brajesh K.; Young, Iain

    2012-01-01

    Soils are complex ecosystems and the pore-scale physical structure regulates key processes that support terrestrial life. These include maintaining an appropriate mixture of air and water in soil, nutrient cycling and carbon sequestration. There is evidence that this structure is not random, although the organizing mechanism is not known. Using X-ray microtomography and controlled microcosms, we provide evidence that organization of pore-scale structure arises spontaneously out of the interaction between microbial activity, particle aggregation and resource flows in soil. A simple computational model shows that these interactions give rise to self-organization involving both physical particles and microbes that gives soil unique material properties. The consequence of self-organization for the functioning of soil is determined using lattice Boltzmann simulation of fluid flow through the observed structures, and predicts that the resultant micro-structural changes can significantly increase hydraulic conductivity. Manipulation of the diversity of the microbial community reveals a link between the measured change in micro-porosity and the ratio of fungal to bacterial biomass. We suggest that this behaviour may play an important role in the way that soil responds to management and climatic change, but that this capacity for self-organization has limits. PMID:22158839

  5. Self-Organized Superlattices in GaInAsSb Grown on Vicinal Substrates

    SciTech Connect

    C.A. Wang; C.J. Vineis; D.R. Calawa

    2003-06-09

    Self-organized superlattices are observed in GaInAsSb epilayers grown lattice matched to vicinal GaSb substrates. The natural superlattice (NSL) is oriented at a slight angle of about 4{sup o} with respect to the vicinal (001) GaSb substrate. This vertical composition modulation is detected at the onset of growth. Layers in the NSL are continuous over the lateral extent of the substrate. Furthermore, the NSL persists throughout several microns of deposition. The NSLs have a period ranging from 10 to 30 nm, which is dependent on deposition temperature and GaInAsSb alloy composition. While the principle driving force for this type of phase separation is chemical, the mechanism for the self-organized microstructure is related to local strains associated with surface undulations. By using a substrate with surface undulations, the tilted NSL can be induced in layers with alloy compositions that normally do not exhibit this self-organized microstructure under typical growth conditions. These results underscore the complex interactions between compositional and morphological perturbations.

  6. Structural characterization of wind-sheared turbulent flow using self-organized mapping

    NASA Astrophysics Data System (ADS)

    Scott, Nicholas V.; Handler, Robert A.

    2016-05-01

    A nonlinear cluster analysis algorithm is used to characterize the spatial structure of a wind-sheared turbulent flow obtained from the direct numerical simulation (DNS) of the three-dimensional temperature and momentum fields. The application of self-organizing mapping to DNS data for data reduction is utilized because of the dimensional similitude in structure between DNS data and remotely sensed hyperspectral and multispectral data where the technique has been used extensively. For the three Reynolds numbers of 150, 180, and 220 used in the DNS, self-organized mapping is successful in the extraction of boundary layer streaky structures from the turbulent temperature and momentum fields. In addition, it preserves the cross-wind scale structure of the streaks exhibited in both fields which loosely scale with the inverse of the Reynolds number. Self-organizing mapping of the along wind component of the helicity density shows a layer of the turbulence field which is spotty suggesting significant direct coupling between the large and small-scale turbulent structures. The spatial correlation of the temperature and momentum fields allows for the possibility of the remote extrapolation of the momentum structure from thermal structure.

  7. Construction of Supramolecular Assemblies from Self-Organization of Amphiphilic Molecular Isomers.

    PubMed

    Li, Zhaohua; Yang, Yuntian; Wang, Yanqiu; Chen, Tie; Jin, Long Yi; Lee, Myongsoo

    2016-08-19

    Amphiphilic coil-rod-coil molecules, incorporating flexible and rigid blocks, have a strong affinity to self-organize into various supramolecular aggregates in bulk and in aqueous solutions. In this paper, we report the self-assembling behavior of amphiphilic coil-rod-coil molecular isomers. These molecules consist of biphenyl and phenyl units connected by ether bonds as the rod segment, and poly(ethylene oxide) (PEO) with a degree of polymerization of 7 and 12 as the flexible chains. Their aggregation behavior was investigated by differential scanning calorimetry, thermal optical polarized microscopy, small-angle X-ray scattering spectroscopy, and transmission electron microscopy. The results imply that the molecular structure of the rod building block and the length of the PEO chains dramatically influence the creation of supramolecular aggregates in bulk and in aqueous solutions. In the bulk state, these molecules self-organize into a hexagonal perforated lamellar and an oblique columnar structure, respectively, depending on the sequence of the rod building block. In aqueous solution, the molecule with a linear rod segment self-assembles into sheet-like nanoribbons. In contrast, its isomer, with a rod building block substituted at the meta-position of the aryl group, self-organizes into nanofibers. This is achieved through the control of the non-covalent interactions of the rod building blocks. PMID:27348276

  8. Quantum-coherence driven self-organized criticality and non-equilibrium light localization

    NASA Astrophysics Data System (ADS)

    Jha, Pankaj; Tsakmakidis, Kosmas; Wang, Yuan; Zhang, Xiang

    In its 28 years since its introduction in 1987, self-organized criticality (SOC) has had a major impact across a broad range of seemingly dissimilar fields of science. However, until now, it has primarily been applied to classical systems, and it remains a fundamental open question whether the theory also finds a place in complex systems driven by quantum coherence (QC). Here, on the basis of a many-body quantum-field theory and corroborating Maxwell-Bloch-Langevin computations, we report on the first example of fractal SOC driven, in the nano-world, by quantum coherence. We show that a quantum-coherently controlled active nano-plasmonic heterostructure allows, in the regime where the light speed is very close to zero, for the phase-synchronization in space of a continuous ensemble of nano-optical oscillators, giving rise to a fundamentally new kind of non-equilibrium light localization. We observe all hallmarks of SOC in this quantum many-body photonic nano-system of interacting heavy bosons, and we identify two critical points, one signifying the onset of spontaneous spatial self-organization, followed in time by another one that signifies the onset of activity. Our analysis reveals a quantum-coherence driven self-organized double-critical property in photonics and a new type of robust light localization, far out of thermodynamic and optical equilibria, with a broad range of potential applications in nano-optics and condensed-matter photonics.

  9. Astronomical image segmentation by self-organizing neural networks and wavelets.

    PubMed

    Núñez, Jorge; Llacer, Jorge

    2003-01-01

    Standard image segmentation methods may not be able to segment astronomical images because their special nature. We present an algorithm for astronomical image segmentation based on self-organizing neural networks and wavelets. We begin by performing wavelet decomposition of the image. The segmentation process has two steps. In the first we separate the stars and other prominent objects using the second plane (w(2)) of the wavelet decomposition, which has little noise but retains enough signal to represent those objects. This method was as least as effective as the traditional source extraction methods in isolating bright objects both from the background and from extended sources. In the second step the rest of the image (extended sources and background) is segmented using a self-organizing neural network. The result is a predetermined number of clusters, which we associate with extended regions plus a small region for each star or bright object. We have applied the algorithm to segment images of both galaxies and planets. The results show that the simultaneous use of all the scales in the self-organizing neural network helps the segmentation process, since it takes into account not only the intensity level, but also both the high and low frequencies present in the image. The connectivity of the regions obtained also shows that the algorithm is robust in the presence of noise. The method can also be applied to restored images. PMID:12672436

  10. Numerical studies on self-organized liquid crystal micro photonic systems

    NASA Astrophysics Data System (ADS)

    Matsui, Tatsunosuke; Kitaguchi, Masahiro; Okajima, Akiko

    2014-03-01

    The liquid crystals (LCs) form various types of nano- and micro- structures in a self-organized manner. In recent years, numerous studies have been carried out to develop novel types of optical functional materials and devices utilizing such self-organizing characteristics of the LCs. Based on the finite-difference time-domain (FDTD) method or its extended version, auxiliary differential equation FDTD (ADE-FDTD) method, we have been numerically studying on the optical characteristics and functionalities of the self-organized LCs such as: (1) lasing from the cholesteric LCs (CLCs) and (2) photonic nanojet (PNJ) from LC micro-systems. Based on the ADE-FDTD method incorporating the equation of motion of the macroscopic polarization and the rate equations at the four level energy structures, we have successfully reproduced circularly polarized lasing from CLC at the edge energy of the stop band. It has also been clarified that the introduction of the defect is effective to lower the lasing threshold. Our technique can be utilized to design the CLC laser devise architecture for much lowered lasing threshold. The PNJ from LC micro-systems are uniquely polarized reflecting birefringence of LCs, which cannot be obtained using optically isotropic microdroplets or microcylinders. A small degree of birefringence drastically changes the optical characteristics of the obtained PNJ. Our findings may open the way for the development of the novel optical functional materials and devices.

  11. Self-Organization of Microscale Condensate for Delayed Flooding of Nanostructured Superhydrophobic Surfaces.

    PubMed

    Ölçeroğlu, Emre; McCarthy, Matthew

    2016-03-01

    Superhydrophobic surfaces enhance condensation by inhibiting the formation of an insulating liquid layer. While this produces efficient heat transfer at low supersaturations, superhydrophobicity has been shown to break down at increased supersaturations. As heat transfer increases, the random distribution and high density of nucleation sites produces pinned droplets, which lead to uncontrollable flooding. In this work, engineered variations in wettability are used to promote the self-organization of microscale droplets, which is shown to effectively delay flooding. Virus-templated superhydrophobic surfaces are patterned with an array of superhydrophilic islands designed to minimize surface adhesion while promoting spatial order. By use of optical and electron microscopy, the surfaces are optimized and characterized during condensation. Mixed wettability imparts spatial order not only through preferential nucleation but more importantly through the self-organization of coalescing droplets at high supersaturations. The self-organization of microscale droplets (diameters of <25 μm) is shown to effectively delay flooding and govern the global wetting behavior of larger droplets (diameters of >1 mm) on the surface. As heat transfer increases, the surfaces transition from jumping-mode to shedding-mode removal with no flooding. This demonstrates the ability to engineer surfaces to resist flooding and can act as the basis for developing robust superhydrophobic surfaces for condensation applications. PMID:26855239

  12. Self-organization of stabilized microtubules by both spindle and midzone mechanisms in Xenopus egg cytosol.

    PubMed

    Mitchison, Timothy J; Nguyen, Phuong; Coughlin, Margaret; Groen, Aaron C

    2013-05-01

    Previous study of self-organization of Taxol-stabilized microtubules into asters in Xenopus meiotic extracts revealed motor-dependent organizational mechanisms in the spindle. We revisit this approach using clarified cytosol with glycogen added back to supply energy and reducing equivalents. We added probes for NUMA and Aurora B to reveal microtubule polarity. Taxol and dimethyl sulfoxide promote rapid polymerization of microtubules that slowly self-organize into assemblies with a characteristic morphology consisting of paired lines or open circles of parallel bundles. Minus ends align in NUMA-containing foci on the outside, and plus ends in Aurora B-containing foci on the inside. Assemblies have a well-defined width that depends on initial assembly conditions, but microtubules within them have a broad length distribution. Electron microscopy shows that plus-end foci are coated with electron-dense material and resemble similar foci in monopolar midzones in cells. Functional tests show that two key spindle assembly factors, dynein and kinesin-5, act during assembly as they do in spindles, whereas two key midzone assembly factors, Aurora B and Kif4, act as they do in midzones. These data reveal the richness of self-organizing mechanisms that operate on microtubules after they polymerize in meiotic cytoplasm and provide a biochemically tractable system for investigating plus-end organization in midzones. PMID:23515222

  13. Entropy production rate in a flux-driven self-organizing system

    NASA Astrophysics Data System (ADS)

    Kawazura, Y.; Yoshida, Z.

    2010-12-01

    Entropy production rate (EPR) is often effective to describe how a structure is self-organized in a nonequilibrium thermodynamic system. The “minimum EPR principle” is widely applicable to characterizing self-organized structures, but is sometimes disproved by observations of “maximum EPR states.” Here we delineate a dual relation between the minimum and maximum principles; the mathematical representation of the duality is given by a Legendre transformation. For explicit formulation, we consider heat transport in the boundary layer of fusion plasma [Z. Yoshida and S. M. Mahajan, Phys. Plasmas 15, 032307 (2008)10.1063/1.2890189]. The mechanism of bifurcation and hysteresis (which are the determining characteristics of the so-called H-mode, a self-organized state of reduced thermal conduction) is explained by multiple tangent lines to a pleated graph of an appropriate thermodynamic potential. In the nonlinear regime, we have to generalize Onsager’s dissipation function. The generalized function is no longer equivalent to EPR; then EPR ceases to be the determinant of the operating point, and may take either minimum or maximum values depending on how the system is driven.

  14. Optical soliton in dielectric fibers and self-organization of turbulence in plasmas in magnetic fields

    PubMed Central

    Hasegawa, Akira

    2009-01-01

    One important discovery in the twentieth century physics is the natural formation of a coherent or a well-ordered structure in continuous media, in contrary to degradation of the state as predicted earlier from the second law of thermodynamics. Here nonlinearity plays the essential role in its process. The discovery of soliton, a localized stable wave in a nonlinear and dispersive medium and the self-organization of fluid turbulence are of the major examples. A soliton is formed primarily in one-dimensional medium where the dispersion and nonlinearity play the essential role. Here the temporal evolution can be described by an infinite dimensional Hamiltonian system that is integrable. While a self-organization appears in an infinite dimensional non-Hamiltonian (or dissipative) system where more than two conservative quantities exist in the limit of no dissipation. In this manuscript, by showing examples of the optical soliton in dielectric fibers and self-organization of turbulence in a toroidal plasma in a magnetic field, we demonstrate these interesting discoveries. The manuscript is intended to describe these discoveries more on philosophical basis with some sacrifice on mathematical details so that the idea is conveyed to those in the wide area of sciences. PMID:19145067

  15. Sugar-Based Polyamides: Self-Organization in Strong Polar Organic Solvents.

    PubMed

    Rosu, Cornelia; Russo, Paul S; Daly, William H; Cueto, Rafael; Pople, John A; Laine, Roger A; Negulescu, Ioan I

    2015-09-14

    Periodic patterns resembling spirals were observed to form spontaneously upon unassisted cooling of d-glucaric acid- and d-galactaric acid-based polyamide solutions in N-methyl-N-morpholine oxide (NMMO) monohydrate. Similar observations were made in d-galactaric acid-based polyamide/ionic liquid (IL) solutions. The morphologies were investigated by optical, polarized light and confocal microscopy assays to reveal pattern details. Differential scanning calorimetry was used to monitor solution thermal behavior. Small- and wide-angle X-ray scattering data reflected the complex and heterogeneous nature of the self-organized patterns. Factors such as concentration and temperature were found to influence spiral dimensions and geometry. The distance between rings followed a first-order exponential decay as a function of polymer concentration. Fourier-Transform Infrared Microspectroscopy analysis of spirals pointed to H-bonding between the solvent and the pendant hydroxyl groups of the glucose units from the polymer backbone. Tests on self-organization into spirals of ketal-protected d-galactaric acid polyamides in NMMO monohydrate confirmed the importance of the monosaccharide's pendant free hydroxyl groups on the formation of these patterns. Rheology performed on d-galactaric-based polyamides at high concentration in NMMO monohydrate solution revealed the optimum conditions necessary to process these materials as fibers by spinning. The self-organization of these sugar-based polyamides mimics certain biological materials. PMID:26270020

  16. Compaction behavior of roller compacted ibuprofen.

    PubMed

    Patel, Sarsvatkumar; Kaushal, Aditya Mohan; Bansal, Arvind Kumar

    2008-06-01

    The effect of roller compaction pressure on the bulk compaction of roller compacted ibuprofen was investigated using instrumented rotary tablet press. Three different roller pressures were utilized to prepare granules and Heckel analysis, Walker analysis, compressibility, and tabletability were performed to derive densification, deformation, course of volume reduction and bonding phenomenon of different pressure roller compacted granules. Nominal single granule fracture strength was obtained by micro tensile testing. Heckel analysis indicated that granules prepared using lower pressure during roller compaction showed lower yield strength. The reduction in tabletability was observed for higher pressure roller compacted granules. The reduction in tabletability supports the results of granule size enlargement theory. Apart from the granule size enlargement theory, the available fines and relative fragmentation during compaction is responsible for higher bonding strength and provide larger areas for true particle contact at constant porosity for lower pressure roller compacted granules. Overall bulk compaction parameters indicated that granules prepared by lower roller compaction pressure were advantageous in terms of tabletability and densification. Overall results suggested that densification during roller compaction affects the particle level properties of specific surface area, nominal fracture strength, and compaction behavior. PMID:18280716

  17. Compact Reactor

    SciTech Connect

    Williams, Pharis E.

    2007-01-30

    Weyl's Gauge Principle of 1929 has been used to establish Weyl's Quantum Principle (WQP) that requires that the Weyl scale factor should be unity. It has been shown that the WQP requires the following: quantum mechanics must be used to determine system states; the electrostatic potential must be non-singular and quantified; interactions between particles with different electric charges (i.e. electron and proton) do not obey Newton's Third Law at sub-nuclear separations, and nuclear particles may be much different than expected using the standard model. The above WQP requirements lead to a potential fusion reactor wherein deuterium nuclei are preferentially fused into helium nuclei. Because the deuterium nuclei are preferentially fused into helium nuclei at temperatures and energies lower than specified by the standard model there is no harmful radiation as a byproduct of this fusion process. Therefore, a reactor using this reaction does not need any shielding to contain such radiation. The energy released from each reaction and the absence of shielding makes the deuterium-plus-deuterium-to-helium (DDH) reactor very compact when compared to other reactors, both fission and fusion types. Moreover, the potential energy output per reactor weight and the absence of harmful radiation makes the DDH reactor an ideal candidate for space power. The logic is summarized by which the WQP requires the above conditions that make the prediction of DDH possible. The details of the DDH reaction will be presented along with the specifics of why the DDH reactor may be made to cause two deuterium nuclei to preferentially fuse to a helium nucleus. The presentation will also indicate the calculations needed to predict the reactor temperature as a function of fuel loading, reactor size, and desired output and will include the progress achieved to date.

  18. Ceramic powder compaction

    SciTech Connect

    Glass, S.J.; Ewsuk, K.G.; Mahoney, F.M.

    1995-12-31

    With the objective of developing a predictive model for ceramic powder compaction we have investigated methods for characterizing density gradients in ceramic powder compacts, reviewed and compared existing compaction models, conducted compaction experiments on a spray dried alumina powder, and conducted mechanical tests and compaction experiments on model granular materials. Die filling and particle packing, and the behavior of individual granules play an important role in determining compaction behavior and should be incorporated into realistic compaction models. These results support the use of discrete element modeling techniques and statistical mechanics principals to develop a comprehensive model for compaction, something that should be achievable with computers with parallel processing capabilities.

  19. Synchrotron X-ray Scattering from Self-organized Soft Nanostructures in Clays

    NASA Astrophysics Data System (ADS)

    Fossum, J. O.

    2009-04-01

    In the general context of self-organization of nanoparticles (in our case clay particles), and transitions in such structures, we study interconnected universal complex physical phenomena such as: (i) spontaneous gravitationally induced phase separation and nematic self-organization in systems of anisotropic clay nanoparticles in aqueous suspension, including studies of isotropic to nematic transitions [1,2] (ii) transitions from biaxial to uniaxial nematics by application of external magnetic field to self-organized systems of the same anisotropic (diamagnetic) clay nanoparticle systems [3,4] (iii) guided self-organization into chainlike structures of the same anisotropic clay nanoparticles in oil suspension when subjected to external electrical fields (electrorheological structures of polarized nanoparticles), and the stability of, and transitions of, such structures, when subjected to external mechanical stress [5,6] The experimental techniques used by us include synchrotron X-ray scattering, neutron scattering, rheometry. microscopy and magnetic resonance. We have demonstrated that clays may be used as good model systems for studies of universal physical phenomena and transitions in self-organized nanostructured soft and complex matter. Self-organization and related transitions in clay systems in particular, may have practical relevance for nano-patterning, properties of nanocomposites, and macroscopically anisotropic gels, among many other applications [7]. The synchrotron experiments have been performed at LNLS-Brazil, PLS- Korea, BNL-USA and ESRF-France. Acknowledgments: Collaborators, postdocs and students at NTNU-Norway, UiO-Norway, IFE-Norway, BNL-USA, LNLS-Brazil, UFPE-Brazil, UnB-Brazil, Univ. Amsterdam-Netherlands, Univ.Paris 7-France and other places. This research has been supported by the Research Council of Norway (RCN), through the NANOMAT, SUP and FRINAT Programs. References 1. J.O. Fossum, E. Gudding, D.d.M. Fonseca, Y. Meheust, E. DiMasi, T

  20. Mechanical coupling limits the density and quality of self-organized carbon nanotube growth

    NASA Astrophysics Data System (ADS)

    Bedewy, Mostafa; Hart, A. John

    2013-03-01

    Aligned carbon nanotube (CNT) structures are promising for many applications; however, as-grown CNT "forests" synthesized by chemical vapor deposition (CVD) are typically low-density and mostly comprise tortuous defective CNTs. Here, we present evidence that the density and alignment of self-organized CNT growth is limited by mechanical coupling among CNTs in contact, in combination with their diameter-dependent growth rates. This study is enabled by comprehensive X-ray characterization of the spatially and temporally-varying internal morphology of CNT forests. Based on this data, we model the time evolution and diameter-dependent scaling of the ensuing mechanical forces on catalyst nanoparticles during CNT growth, which arise from the mismatch between the collective lengthening rate of the forest and the diameter-dependent growth rates of individual CNTs. In addition to enabling self-organization of CNTs into forests, time-varying forces between CNTs in contact dictate the hierarchical tortuous morphology of CNT forests, and may be sufficient to influence the structural quality of CNTs. These forces reach a maximum that is coincident with the maximum density observed in our growth process, and are proportional to CNT diameter. Therefore, we propose that improved manufacturing strategies for self-organized CNTs should consider both chemical and mechanical effects. This may be especially necessary to achieve high density CNT forests with low defect density, such as for improved thermal interfaces and high-permeability membranes.Aligned carbon nanotube (CNT) structures are promising for many applications; however, as-grown CNT "forests" synthesized by chemical vapor deposition (CVD) are typically low-density and mostly comprise tortuous defective CNTs. Here, we present evidence that the density and alignment of self-organized CNT growth is limited by mechanical coupling among CNTs in contact, in combination with their diameter-dependent growth rates. This study is

  1. Control of the NASA Langley 16-Foot Transonic Tunnel with the Self-Organizing Feature Map

    NASA Technical Reports Server (NTRS)

    Motter, Mark A.

    1998-01-01

    A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a Self Organizing Feature Map (SOFM). Local linear modeling of nonlinear autonomous systems with the SOFM is extended to a control framework where the modeled system is nonautonomous, driven by an exogenous input. This extension to a control framework is based on the consideration of a finite number of subregions in the control space. Multiple self organizing feature maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experimental knowledge gained from decades of operation. Each SOFM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOFM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal. Each SOFM provides a codebook representation of the tunnel dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the minimization of a similarity metric which is the essence of the self organizing feature of the map. Thus, the SOFM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme than selects the best available model for the applied control. Experimental results of controlling the wind tunnel, with the proposed method, during operational runs where strict research requirements on the control of the Mach number were met, are

  2. Self-Organizing Circuit Assembly through Spatiotemporally Coordinated Neuronal Migration within Geometric Constraints

    PubMed Central

    Sun, Yi; Huang, Zhuo; Yang, Kaixuan; Liu, Wenwen; Xie, Yunyan; Yuan, Bo; Zhang, Wei; Jiang, Xingyu

    2011-01-01

    Background Neurons are dynamically coupled with each other through neurite-mediated adhesion during development. Understanding the collective behavior of neurons in circuits is important for understanding neural development. While a number of genetic and activity-dependent factors regulating neuronal migration have been discovered on single cell level, systematic study of collective neuronal migration has been lacking. Various biological systems are shown to be self-organized, and it is not known if neural circuit assembly is self-organized. Besides, many of the molecular factors take effect through spatial patterns, and coupled biological systems exhibit emergent property in response to geometric constraints. How geometric constraints of the patterns regulate neuronal migration and circuit assembly of neurons within the patterns remains unexplored. Methodology/Principal Findings We established a two-dimensional model for studying collective neuronal migration of a circuit, with hippocampal neurons from embryonic rats on Matrigel-coated self-assembled monolayers (SAMs). When the neural circuit is subject to geometric constraints of a critical scale, we found that the collective behavior of neuronal migration is spatiotemporally coordinated. Neuronal somata that are evenly distributed upon adhesion tend to aggregate at the geometric center of the circuit, forming mono-clusters. Clustering formation is geometry-dependent, within a critical scale from 200 µm to approximately 500 µm. Finally, somata clustering is neuron-type specific, and glutamatergic and GABAergic neurons tend to aggregate homo-philically. Conclusions/Significance We demonstrate self-organization of neural circuits in response to geometric constraints through spatiotemporally coordinated neuronal migration, possibly via mechanical coupling. We found that such collective neuronal migration leads to somata clustering, and mono-cluster appears when the geometric constraints fall within a critical

  3. Self-organized structures in a superorganism: do ants “behave” like molecules?

    NASA Astrophysics Data System (ADS)

    Detrain, Claire; Deneubourg, Jean-Louis

    2006-09-01

    While the striking structures (e.g. nest architecture, trail networks) of insect societies may seem familiar to many of us, the understanding of pattern formation still constitutes a challenging problem. Over the last two decades, self-organization has dramatically changed our view on how collective decision-making and structures may emerge out of a population of ant workers having each their own individuality as well as a limited access to information. A variety of collective behaviour spontaneously outcome from multiple interactions between nestmates, even when there is no directing influence imposed by an external template, a pacemaker or a leader. By focussing this review on foraging structures, we show that ant societies display some properties which are usually considered in physico-chemical systems, as typical signatures of self-organization. We detail the key role played by feed-back loops, fluctuations, number of interacting units and sensitivity to environmental factors in the emergence of a structured collective behaviour. Nonetheless, going beyond simple analogies with non-living self-organized patterns, we stress on the specificities of social structures made of complex living units of which the biological features have been selected throughout the evolution depending on their adaptive value. In particular, we consider the ability of each ant individual to process information about environmental and social parameters, to accordingly tune its interactions with nestmates and ultimately to determine the final pattern emerging at the collective level. We emphasize on the parsimony and simplicity of behavioural rules at the individual level which allow an efficient processing of information, energy and matter within the whole colony.

  4. Dynamics of self-organized rotating spiral-coils in bacterial swarms.

    PubMed

    Lin, Szu-Ning; Lo, Wei-Chang; Lo, Chien-Jung

    2014-02-01

    Self-propelled particles (SPP) exhibit complex collective motions, mimicking autonomous behaviors that are often seen in the natural world, but essentially are generated by simple mutual interactions. Previous research on SPP systems focuses on collective behaviors of a uniform population. However, very little is known about the evolution of individual particles under the same global influence. Here we show self-organized rotating spiral coils in a two-dimensional (2D) active system. By using swarming bacteria Vibrio alginolyticus as an ideal experimental realization of a well-controlled 2D self-propelled system, we study the interaction between ultra-long cells and short background active cells. The self-propulsion of long cells and their interactions with neighboring short cells leads to a self-organized, stable spiral rotational state in 2D. We find four types of spiral coils with two main features: the rotating direction (clockwise or counter-clockwise) and the central structure (single or double spiral). The body length of the spiral coils falls between 32 and 296 μm and their rotational speed is within a range from 2.22 to 22.96 rad s(-1). The dynamics of these spiral coils involves folding and unfolding processes, which require local velocity changes of the long bacterium. This phenomenon can be qualitatively replicated by a Brownian dynamics simulation using a simple rule of the propulsion thrust, imitating the reorientation of bacterial flagella. Apart from the physical and biological interests in swarming cells, the formation of self-organized spiral coils could be useful for the next generation of microfabrication. PMID:24837552

  5. Self-organized charge puddles in a three-dimensional topological material

    NASA Astrophysics Data System (ADS)

    Borgwardt, N.; Lux, J.; Vergara, I.; Wang, Zhiwei; Taskin, A. A.; Segawa, Kouji; van Loosdrecht, P. H. M.; Ando, Yoichi; Rosch, A.; Grüninger, M.

    2016-06-01

    In three-dimensional (3D) topological materials, tuning of the bulk chemical potential is of crucial importance for observing their topological properties; for example, Weyl semimetals require chemical-potential tuning to the bulk Weyl nodes, while 3D topological insulators require tuning into the bulk band gap. Such tuning is often realized by compensation, i.e., by balancing the density of acceptors and donors. Here we show that in such a compensated 3D topological material, the possibility of local chemical-potential tuning is limited by the formation of self-organized charge puddles. The puddles arise from large fluctuations of the Coulomb potential of donors and acceptors. Their emergence is akin to the case of graphene, where charge puddles are already established as a key paradigm. However, there is an important difference: Puddles in graphene are simply dictated by the static distribution of defects in the substrate, whereas we find that puddles in 3D systems self-organize in a nontrivial way and show a strong temperature dependence. Such a self-organization is revealed by measurements of the optical conductivity of the bulk-insulating 3D topological insulator BiSbTeSe2, which pinpoints the presence of puddles at low temperatures as well as their surprising "evaporation" on a temperature scale of 30-40 K. The experimental observation is described semiquantitatively by Monte Carlo simulations. These show that the temperature scale is set by the Coulomb interaction between neighboring dopants and that puddles are destroyed by thermally activated carriers in a highly nonlinear screening process. This result indicates that understanding charge puddles is crucial for the control of the chemical potential in compensated 3D topological materials.

  6. Chaos-driven decay of nuclear giant resonances: Quantum route to self-organization

    SciTech Connect

    Drozdz, S.; Nishizaki, S.; Wambach, J. Institute of Nuclear Physics, PL-31-342 Krakow Institut fuer Kernphysik, Forschungszentrum Juelich, D-5170 Juelich College of Humanities and Social Sciences, Iwate University, Ueda 3-18-34, Morioka 020 )

    1994-05-02

    The influence of background states with increasing level of complexity on the strength distribution of the isoscalar and isovector giant quadrupole resonance in [sup 40]Ca is studied. It is found that the background characteristics, typical for chaotic systems, strongly affect the fluctuation properties of the strength distribution. In particular, the small components of the wave function obey a scaling law analogous to self-organized systems at the critical state. This appears to be consistent with the Porter-Thomas distribution of the transition strength.

  7. Self-organized broadband light trapping in thin film amorphous silicon solar cells.

    PubMed

    Martella, C; Chiappe, D; Delli Veneri, P; Mercaldo, L V; Usatii, I; Buatier de Mongeot, F

    2013-06-01

    Nanostructured glass substrates endowed with high aspect ratio one-dimensional corrugations are prepared by defocused ion beam erosion through a self-organized gold (Au) stencil mask. The shielding action of the stencil mask is amplified by co-deposition of gold atoms during ion bombardment. The resulting glass nanostructures enable broadband anti-reflection functionality and at the same time ensure a high efficiency for diffuse light scattering (Haze). It is demonstrated that the patterned glass substrates exhibit a better photon harvesting than the flat glass substrate in p-i-n type thin film a-Si:H solar cells. PMID:23633473

  8. Coexistence of Self-Organized Criticality and Intermittent Turbulence in the Solar Corona

    SciTech Connect

    Uritsky, Vadim M.; Paczuski, Maya; Davila, Joseph M.; Jones, Shaela I.

    2007-07-13

    An extended data set of extreme ultraviolet images of the solar corona provided by the SOHO spacecraft is analyzed using statistical methods common to studies of self-organized criticality (SOC) and intermittent turbulence (IT). The data exhibit simultaneous hallmarks of both regimes: namely, power-law avalanche statistics as well as multiscaling of structure functions for spatial activity. This implies that both SOC and IT may be manifestations of a single complex dynamical process entangling avalanches of magnetic energy dissipation with turbulent particle flows.

  9. Separation and electrical properties of self-organized graphene/graphite layers

    NASA Astrophysics Data System (ADS)

    Mailian, Manuel R.; Mailian, Aram R.

    2015-02-01

    Intrinsic layered structure of graphite is the source of ongoing and expanding search of ways of obtaining low-cost and promising graphite thin layers. We report on a novel method of obtaing and seperating rubbed graphite sheets by using water soluble NaCl substrate. The electrical behavior of sheets was characterized by current-voltage measurements. An in-plane electrical anisotropy depending on rubbing direction is discovered. Optical microscopy observations combined with discovered non-linear electrical behavior revealed that friction leads to the formation of sheet makeup which contain an optically transparent lamina of self-organized few-layer graphene.

  10. In-situ observation of atomic self-organization processes in Xe nanocrystals embedded in Al.

    SciTech Connect

    Mitsuishi, K.; Song, M.; Furuya, K.; Birtcher, R. C.; Allen, C. W.; Donnelly, S. E.

    1998-03-10

    Self-organization processes in Xe nanocrystals embedded in Al are observed with in-situ high-resolution electron microscopy. Under electron irradiation, stacking fault type defects are produced in Xe nanocrystals. The defects recover in a layer by layer manner. Detailed analysis of the video reveals that the displacement of Xe atoms in the stacking fault was rather small for the Xe atoms at boundary between Xe and Al, suggesting the possibility of the stacking fault in Xe precipitate originating inside of precipitate, not at the Al/Xe interface.

  11. Self-Organized Criticality in a Model of Collective Bank Bankruptcies

    NASA Astrophysics Data System (ADS)

    Aleksiejuk, Agata; HoŁyst, Janusz A.; Kossinets, Gueorgi

    The question we address here is of whether phenomena of collective bankruptcies are related to self-organized criticality. In order to answer it we propose a simple model of banking networks based on the random directed percolation. We study effects of one bank failure on the nucleation of contagion phase in a financial market. We recognize the power law distribution of contagion sizes in 3d- and 4d-networks as an indicator of SOC behavior. The SOC dynamics was not detected in 2d-lattices. The difference between 2d- and 3d- or 4d-systems is explained due to the percolation theory.

  12. Self-organized field structures in electron-depleted multi-ion dusty plasma

    NASA Astrophysics Data System (ADS)

    Iqbal, M.; Gondal, S. M.; Shuaib, A.; Qurat-Ul-Ain

    2015-06-01

    It is shown that there exists a strong interaction between the magnetic and kinetic aspects of a multi-ion plasma. The interaction appears as a system of simultaneous equations which show the alignment of vortices to flows and satisfy the Beltrami condition. Solving these equations lead to a non-force-free magnetic field which can be cast as a superposition of three multiscale force-free magnetic field configurations. It is the consequence of different Beltrami parameters of positive and negative ion fluids. It is also shown that self-organized paramagnetic and diamagnetic field structures could be created by varying the vorticities and flows of ion fluids.

  13. Analysis of 2D Phase Contrast MRI in Renal Arteries by Self Organizing Maps

    NASA Astrophysics Data System (ADS)

    Zöllner, Frank G.; Schad, Lothar R.

    We present an approach based on self organizing maps to segment renal arteries from 2D PC Cine MR, images to measure blood velocity and flow. Such information are important in grading renal artery stenosis and support the decision on surgical interventions like percu-tan transluminal angioplasty. Results show that the renal arteries could be extracted automatically. The corresponding velocity profiles show high correlation (r=0.99) compared those from manual delineated vessels. Furthermore, the method could detect possible blood flow patterns within the vessel.

  14. Scaling laws and simulation results for the self-organized critical forest-fire model

    NASA Astrophysics Data System (ADS)

    Clar, S.; Drossel, B.; Schwabl, F.

    1994-08-01

    We discuss the properties of a self-organized critical forest-fire model which has been introduced recently [B. Drossel and F. Schwabl, Phys. Rev. Lett. 69, 1629 (1992)]. We derive scaling laws and define critical exponents. The values of these critical exponents are determined by computer simulations in one to eight dimensions. The simulations suggest a critical dimension dc=6 above which the critical exponents assume their mean-field values. Changing the lattice symmetry and allowing trees to be immune against fire, we show that the critical exponents are universal.

  15. A genetic algorithm approach to probing the evolution of self-organized nanostructured systems.

    PubMed

    Siepmann, Peter; Martin, Christopher P; Vancea, Ioan; Moriarty, Philip J; Krasnogor, Natalio

    2007-07-01

    We present a new methodology, based on a combination of genetic algorithms and image morphometry, for matching the outcome of a Monte Carlo simulation to experimental observations of a far-from-equilibrium nanosystem. The Monte Carlo model used simulates a colloidal solution of nanoparticles drying on a solid substrate and has previously been shown to produce patterns very similar to those observed experimentally. Our approach enables the broad parameter space associated with simulated nanoparticle self-organization to be searched effectively for a given experimental target morphology. PMID:17552572

  16. Self-Organized Traveling Chemo-Hydrodynamic Fingers Triggered by a Chemical Oscillator.

    PubMed

    Escala, D M; Budroni, M A; Carballido-Landeira, J; De Wit, A; Muñuzuri, A P

    2014-02-01

    Pulsatile chemo-hydrodynamic patterns due to a coupling between an oscillating chemical reaction and buoyancy-driven hydrodynamic flows can develop when two solutions of separate reactants of the Belousov-Zhabotinsky reaction are put in contact in the gravity field and conditions for chemical oscillations are met in the contact zone. In regular oscillatory conditions, localized periodic changes in the concentration of intermediate species induce pulsatile density gradients, which, in turn, generate traveling convective fingers breaking the transverse symmetry. These patterns are the self-organized result of a genuine coupling between chemical and hydrodynamic modes. PMID:26276584

  17. Firm Size, a Self-Organized Critical Phenomenon: Evidence from the Dynamical Systems Theory

    NASA Astrophysics Data System (ADS)

    Chandra, Akhilesh

    This research draws upon a recent innovation in the dynamical systems literature called the theory of self -organized criticality (SOC) (Bak, Tang, and Wiesenfeld 1988) to develop a computational model of a firm's size by relating its internal and the external sub-systems. As a holistic paradigm, the theory of SOC implies that a firm as a composite system of many degrees of freedom naturally evolves to a critical state in which a minor event starts a chain reaction that can affect either a part or the system as a whole. Thus, the global features of a firm cannot be understood by analyzing its individual parts separately. The causal framework builds upon a constant capital resource to support a volume of production at the existing level of efficiency. The critical size is defined as the production level at which the average product of a firm's factors of production attains its maximum value. The non -linearity is inferred by a change in the nature of relations at the border of criticality, between size and the two performance variables, viz., the operating efficiency and the financial efficiency. The effect of breaching the critical size is examined on the stock price reactions. Consistent with the theory of SOC, it is hypothesized that the temporal response of a firm breaching the level of critical size should behave as a flicker noise (1/f) process. The flicker noise is characterized by correlations extended over a wide range of time scales, indicating some sort of cooperative effect among a firm's degrees of freedom. It is further hypothesized that a firm's size evolves to a spatial structure with scale-invariant, self-similar (fractal) properties. The system is said to be self-organized inasmuch as it naturally evolves to the state of criticality without any detailed specifications of the initial conditions. In this respect, the critical state is an attractor of the firm's dynamics. Another set of hypotheses examines the relations between the size and the

  18. Locally self-organized quasicritical percolation in a multiple-disease model.

    PubMed

    Juul, Jeppe; Sneppen, Kim

    2011-09-01

    Diseases emerge, persist, and vanish in an ongoing battle for available hosts. Hosts, on the other hand, defend themselves by developing immunity that limits the ability of pathogens to reinfect them. We here explore a multidisease system with emphasis on mutual exclusion. We demonstrate that such a system develops toward a steady state, where the spread of individual diseases self-organizes to a state close to that of critical percolation, without any global control mechanism or separation of time scale. For a broad range of introduction rates of new diseases, the likelihood of transmitting diseases remains approximately constant. PMID:22060468

  19. A new approach for designing self-organizing systems and application to adaptive control

    NASA Technical Reports Server (NTRS)

    Ramamoorthy, P. A.; Zhang, Shi; Lin, Yueqing; Huang, Song

    1993-01-01

    There is tremendous interest in the design of intelligent machines capable of autonomous learning and skillful performance under complex environments. A major task in designing such systems is to make the system plastic and adaptive when presented with new and useful information and stable in response to irrelevant events. A great body of knowledge, based on neuro-physiological concepts, has evolved as a possible solution to this problem. Adaptive resonance theory (ART) is a classical example under this category. The system dynamics of an ART network is described by a set of differential equations with nonlinear functions. An approach for designing self-organizing networks characterized by nonlinear differential equations is proposed.

  20. Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps.

    PubMed

    Moya, José M; Araujo, Alvaro; Banković, Zorana; de Goyeneche, Juan-Mariano; Vallejo, Juan Carlos; Malagón, Pedro; Villanueva, Daniel; Fraga, David; Romero, Elena; Blesa, Javier

    2009-01-01

    The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals. PMID:22291569

  1. Self Organization of Wireless Sensor Networks Using Ultra-Wideband Radios

    SciTech Connect

    Nekoogar, F; Dowla, F; Spiridon, A

    2004-07-19

    Ultra-wideband (UWB) technology has proven to be useful in short range, high data rate, robust, and low power communications. These features can make UWB systems ideal candidates for reliable data communications between nodes of a wireless sensor network (WSN). However, the low powered UWB pulses can be significantly degraded by channel noise, inter-node interference, and intentional jamming. In this paper we present a novel interference suppression technique for UWB based WSNs that promises self-organization in terms of power conservation, scalability, and channel estimation for the entire distributed network.

  2. High hole mobility GeSn on insulator formed by self-organized seeding lateral growth

    NASA Astrophysics Data System (ADS)

    Liu, Zhi; Wen, Juanjuan; Zhang, Xu; Li, Chuanbo; Xue, Chunlai; Zuo, Yuhua; Cheng, Buwen; Wang, Qiming

    2014-11-01

    Tensile strained single-crystal GeSn on insulator (GSOI) was obtained using self-organized seeding lateral growth. Segregation of Sn atoms and Sn distribution occurred during the lateral growth of the GeSn stripe. At both edges of the GSOI, Sn concentration distribution was found in good agreement with calculation based on the Scheil equation. P-channel metal-oxide-semiconductor field effect transistors were fabricated using the GSOI materials. Good transistor performance with the low field peak hole mobility of 383 cm2 V-1 s-1 was obtained, which indicated the high quality of this GSOI structure.

  3. Hydrogen atom trapping in a self-organized one-dimensional dimer

    SciTech Connect

    Takami, Tsuyoshi; Kawamura, Kazushi

    2014-09-01

    Metal–organic frameworks (MOFs) have attracted widespread attention owing to their unusual structure and properties produced by their nanospaces. However, many MOFs possess the similar three-dimensional frameworks, limiting their structural variety and operating capacity for hydrogen storage under ambient conditions. Here we report the synthesis and structural characterization of a single-crystal one-dimensional dimer whose structure, operating capacity, and physical mechanism contrast with those of existing MOFs. The hydrogen storage capacity of 2.6 wt.% is comparable to the highest capacity achieved by existing MOFs at room temperature. This exceptional storage capacity is realized by self-organization during crystal growth using a weak base.

  4. Renormalization group and instantons in stochastic nonlinear dynamics. From self-organized criticality to thermonuclear reactors

    NASA Astrophysics Data System (ADS)

    Volchenkov, D.

    2009-03-01

    Stochastic counterparts of nonlinear dynamics are studied by means of nonperturbative functional methods developed in the framework of quantum field theory (QFT). In particular, we discuss fully developed turbulence, including leading corrections on possible compressibility of fluids, transport through porous media, theory of waterspouts and tsunami waves, stochastic magneto-hydrodynamics, turbulent transport in crossed fields, self-organized criticality, and dynamics of accelerated wrinkled flame fronts advancing in a wide canal. This report would be of interest to the broad auditorium of physicists and applied mathematicians, with a background in nonperturbative QFT methods or nonlinear dynamical systems, having an interest in both methodological developments and interdisciplinary applications.

  5. Effect of barrier capacitance on self-organized structure in dielectric-barrier discharge microplasma

    NASA Astrophysics Data System (ADS)

    Mukaigawa, Seiji; Fujiwara, Kazunobu; Sato, Tomohiko; Odagiri, Ryo; Kudoh, Tomohiro; Yokota, Atsuya; Oguni, Kyohei; Takaki, Koichi

    2016-07-01

    We experimentally observed variations in self-organized microgap barrier discharge with changes in barrier capacitance. We also performed a computer simulation using a reaction–diffusion equation. The simulation results showed the same tendency for the lattice spacing and size of filaments as hexagonal pattern structures in discharge experiments. We confirmed that the experimental result of the dependence of voltage on filament number density is consistent with the simulation result. From a theoretical viewpoint, it is possible that the size of filaments of a hexagonal structure caused by Turing instability corresponds to the characteristic wavelength obtained by simple analysis.

  6. Magnetism of CoPd self-organized alloy clusters on Au(111)

    NASA Astrophysics Data System (ADS)

    Ohresser, P.; Otero, E.; Wilhelm, F.; Rogalev, A.; Goyhenex, C.; Joly, L.; Bulou, H.; Romeo, M.; Speisser, V.; Arabski, J.; Schull, G.; Scheurer, F.

    2013-12-01

    Magnetic properties of gold-encapsulated CoxPd1-x self-organized nano-clusters on Au(111) are analyzed by x-ray magnetic circular dichroism for x = 0.5, 0.7, and 1.0. The clusters are superparamagnetic with a blocking temperature decreasing with increasing Pd concentration, due to a reduction of the out-of-plane anisotropy strength. No magnetic moment is detected on Pd in these clusters, within the detection limit, contrary to thick CoPd films. Both reduction of anisotropy and vanishing Pd moment are attributed to strain.

  7. Synthesis, properties and self-organization of meso-arylporphyrins with higher alkyl substituents

    NASA Astrophysics Data System (ADS)

    Bragina, N. A.; Zhdanova, K. A.; Mironov, A. F.

    2016-05-01

    The review summarizes published data on the methods for preparation of meso-arylporphyrins with higher alkyl substituents. The methods for creation of self-organized nanostructures based on these compounds and the data on their applications are presented. Approaches to the synthesis of functionalized lipophilic and amphiphilic meso-arylporphyrins are discussed. The ways and driving forces for the formation of supramolecular porphyrin arrays in solutions and on the substrate surface are considered. The prospects of using alkyl porphyrin derivatives for the design of nanomaterials are shown. The bibliography includes 204 references.

  8. Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    2006-05-01

    A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the

  9. Self-Organizing Two-Temperature Ising Model Describing Human Segregation

    NASA Astrophysics Data System (ADS)

    Ódor, Géza

    A two-temperature Ising-Schelling model is introduced and studied for describing human segregation. The self-organized Ising model with Glauber kinetics simulated by Müller et al. exhibits a phase transition between segregated and mixed phases mimicking the change of tolerance (local temperature) of individuals. The effect of external noise is considered here as a second temperature added to the decision of individuals who consider a change of accommodation. A numerical evidence is presented for a discontinuous phase transition of the magnetization.

  10. Self-organization of Pb islands on Si(111) caused by quantum size effects

    NASA Astrophysics Data System (ADS)

    Hong, Hawoong; Basile, L.; Czoschke, P.; Gray, A.; Chiang, T.-C.

    2007-01-01

    Growth of metallic Pb islands on Si(111) by vacuum deposition was studied in real time using synchrotron x-ray diffraction. The islands coarsen and order, maintaining a nearly uniform interisland distance but without angular correlation. The resulting interisland structure is akin to a two-dimensional liquid. Over a wide temperature range, the interisland ordering is well correlated with the development of "magic" island heights caused by energy minimization of the Pb electrons. The results demonstrate quantum confinement effects as a driving force for self-organization, as opposed to strain effects that generally govern the formation of semiconductor quantum dot arrays.

  11. Self Organization of Pb Islands on Si(111) Caused by Quantum Size Effects

    NASA Astrophysics Data System (ADS)

    Hong, Hawoong; Basile, Leo; Czoschke, Peter; Gray, Aaron; Chiang, Tai-Chang

    2007-03-01

    Growth of metallic Pb islands on Si(111) by vacuum deposition was studied in real time using synchrotron x-ray diffraction. The islands coarsen and order, maintaining a nearly uniform inter-island distance but without angular correlation. The resulting inter-island structure is akin to a two-dimensional liquid. Over a wide temperature range, the inter-island ordering is well correlated with the development of ``magic'' island heights caused by energy minimization of the Pb electrons. The results demonstrate quantum confinement effects as a driving force for self organization, as opposed to strain effects that generally govern the formation of semiconductor quantum dot arrays.

  12. Self-organized critical phenomenon as a q-exponential decay - Avalanche epidemiology of dengue

    NASA Astrophysics Data System (ADS)

    Saba, H.; Miranda, J. G. V.; Moret, M. A.

    2014-11-01

    We studied the evolution of dengue disease in the state of Bahia. The number of epidemiological dengue cases for each city follows a Self-Organized Criticality behavior (SOC). However, the analysis of the number of cases in Bahia exhibits a q-exponential distribution. To understand this different behavior, we analyzed the distribution of the power law of SOC (γ) to all cities of Bahia. Our findings show that the distribution of γ exhibits a dependence between the exponents, which may be because of migration between cities, causing the emergence of outbreaks in different cities in a correlated and asynchronous time series.

  13. Hierarchical Self Organizing Map for Novelty Detection using Mobile Robot with Robust Sensor

    NASA Astrophysics Data System (ADS)

    Sha'abani, M. N. A. H.; Miskon, M. F.; Sakidin, H.

    2013-12-01

    This paper presents a novelty detection method based on Self Organizing Map neural network using a mobile robot. Based on hierarchical neural network, the network is divided into three networks; position, orientation and sensor measurement network. A simulation was done to demonstrate and validate the proposed method using MobileSim. Three cases of abnormal events; new, missing and shifted objects are employed for performance evaluation. The result of detection was then filtered for false positive detection. The result shows that the inspection produced less than 2% false positive detection at high sensitivity settings.

  14. Electroless plating of honeycomb and pincushion polymer films prepared by self-organization.

    PubMed

    Yabu, Hiroshi; Hirai, Yuji; Shimomura, Masatsugu

    2006-11-01

    This report describes the fabrication and electroless plating of regular porous and pincushion-like polymer structures prepared by self-organization. Honeycomb-patterned films were prepared by simple casting of polymer solution under applied humid air and pincushion structures by peeling off the top layer of the former films. Silver-deposited honeycomb-patterned films and pincushion films were obtained by simple electroless plating of the respective original structures. XPS revealed Ag deposition on the honeycomb-patterned film. After thermal decomposition or solvent elution of the template polymer, unique metal mesoscopic structures were obtained. PMID:17073508

  15. Comparison of brass alloys composition by laser-induced breakdown spectroscopy and self-organizing maps

    NASA Astrophysics Data System (ADS)

    Pagnotta, Stefano; Grifoni, Emanuela; Legnaioli, Stefano; Lezzerini, Marco; Lorenzetti, Giulia; Palleschi, Vincenzo

    2015-01-01

    In this paper we face the problem of assessing similarities in the composition of different metallic alloys, using the laser-induced breakdown spectroscopy technique. The possibility of determining the degree of similarity through the use of artificial neural networks and self-organizing maps is discussed. As an example, we present a case study involving the comparison of two historical brass samples, very similar in their composition. The results of the paper can be extended to many other situations, not necessarily associated with cultural heritage and archeological studies, where objects with similar composition have to be compared.

  16. Self-organization of dissipationless solitons in positive- and negative-refractive-index materials

    SciTech Connect

    Skarka, V.; Aleksic, N. B.; Berezhiani, V. I.

    2010-04-15

    A generalized Ginzburg-Landau equation describing dissipative solitons dynamics in negative-refractive-index materials is derived from Maxwell equations. This equation having only real terms with opposite sign differs from the usual Ginzburg-Landau equation for positive-refractive-index media. A cross-compensation between the saturating nonlinearity excess, losses, and gain makes obtained self-organized solitons dissipationless and exceptionally robust. In the presence of such solitons medium becomes effectively dissipationless. The compensation of losses is of particular interest for media with resonant character of interactions like negative-refractive-index materials.

  17. Self-organized MBE growth of II VI epilayers on patterned GaSb substrates

    NASA Astrophysics Data System (ADS)

    Wissmann, H.; Tran Anh, T.; Rogaschewski, S.; von Ortenberg, M.

    1999-05-01

    We report on the self-organized MBE growth of II-VI epilayers on patterned and unpatterned GaSb substrates resulting in quantum wires and quantum wells, respectively. The HgSe : Fe quantum wires were grown on (0 0 1)GaSb substrates with a buffer of lattice-matched ZnTe 1- xSe x. Due to the anisotropic growth of HgSe on the A-oriented stripes roof-like overgrowth with a definite ridge was obtained. Additional Fe doping in the direct vicinity of the ridge results in a highly conductive quantum wire.

  18. Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps

    PubMed Central

    Moya, José M.; Araujo, Álvaro; Banković, Zorana; de Goyeneche, Juan-Mariano; Vallejo, Juan Carlos; Malagón, Pedro; Villanueva, Daniel; Fraga, David; Romero, Elena; Blesa, Javier

    2009-01-01

    The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals. PMID:22291569

  19. Demonstration for novel self-organization theory by three-dimensional magnetohydrodynamic simulation

    NASA Astrophysics Data System (ADS)

    Kondoh, Yoshiomi; Hosaka, Yasuo; Liang, Jia-Ling

    1993-03-01

    It is demonstrated by three-dimensional simulations for resistive magnetohydrodynamic (MHD) plasmas with both 'spatially nonuniform resistivity eta' and 'uniform eta' that the attractor of the dissipative structure in the resistive MHD plasmas is given by del x (eta)j) = (alpha/2)B which is derived from a self-organization theory based on the minimum dissipation rate profile. It is shown by the simulations that the attractor is reduced to del x B = (lambda)B in the special case with the 'uniform eta' and no pressure gradient.

  20. Integrating self-organization theory into an advanced course on morphogenesis at Moscow State University.

    PubMed

    Beloussov, Lev V

    2003-01-01

    A lecture course on morphogenesis for fourth-year Moscow State University Specialist Diploma students specializing in embryology is described. The main goal of the course is to give the students an extensive theoretical background based on the tenets of the modern theory of Self-Organization and to show them how important this theory is for the proper understanding of developmental events. The corresponding mathematics are bound as tightly as possible to the actual morphogenetic processes. All of the lectures take the format of an active dialogue between the students and a tutor. PMID:12705667

  1. Portraits of self-organization in fish schools interacting with robots

    NASA Astrophysics Data System (ADS)

    Aureli, M.; Fiorilli, F.; Porfiri, M.

    2012-05-01

    In this paper, we propose an enabling computational and theoretical framework for the analysis of experimental instances of collective behavior in response to external stimuli. In particular, this work addresses the characterization of aggregation and interaction phenomena in robot-animal groups through the exemplary analysis of fish schooling in the vicinity of a biomimetic robot. We adapt global observables from statistical mechanics to capture the main features of the shoal collective motion and its response to the robot from experimental observations. We investigate the shoal behavior by using a diffusion mapping analysis performed on these global observables that also informs the definition of relevant portraits of self-organization.

  2. Exact results for spatiotemporal correlations in a self-organized critical model of punctuated equilibrium

    SciTech Connect

    Boettcher, S.; Paczuski, M.

    1996-01-01

    We introduce a self-organized critical model of punctuated equilibrium with many internal degrees of freedom ({ital M}) per site. We find exact solutions for {ital M}{r_arrow}{infinity} of cascade equations describing avalanche dynamics in the steady state. This proves the existence of simple power laws with critical exponents that verify general scaling relations for nonequilibrium phenomena. Punctuated equilibrium is described by a devil{close_quote}s staircase with a characteristic exponent {tau}{sub first}=2{minus}{ital d}/4 where {ital d} is the spatial dimension. {copyright} {ital 1996 The American Physical Society.}

  3. Self-Organization on Multiple Length Scales in ``Hairy-Rod''--Coil Block Copolymer Supramolecular Complexes

    NASA Astrophysics Data System (ADS)

    Mezzenga, Raffaele; Hammond, Matthew; Klok, Harm-Anton

    2008-03-01

    A peptide-synthetic hybrid block copolymer, poly(ethylene oxide)-block-poly(L-glutamic acid), is demonstrated to form supramolecular complexes with primary alkylamines of varying alkyl chain length (8 to 18 methylene units) in organic solvents via acid-base proton transfer and subsequent ionic bonding. The peptidic block being in the α-helical conformation, these materials behave as coil-``hairy rod'' block copolymers, and show hierarchically self-organized nanostructures in the solid state; X-ray scattering measurements show mesomorphic behavior at the length scales of both the overall block copolymer and the polypeptide-alkylammonium complex.

  4. Experimental evidence for self-organized criticality in tokamak plasma turbulence

    NASA Astrophysics Data System (ADS)

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

    1999-03-01

    Measurements of plasma turbulence spectra and particle flux from the DIII-D tokamak exhibit significant agreement with predictions of self-organized criticality (SOC) modeling. Power spectra of density ñ, potential g˜f, and particle flux Γ, are observed to have three regions of frequency dependence: f0, f-1 and f-4. In addition, the particle flux probability distribution displays a Γ-1 scaling over two decades in Γ. These results provide the first evidence that the plasma is in a state consistent with SOC models and place a constraint on plasma transport models.

  5. A self organizing map approach to physiological data analysis for enhanced group performance.

    SciTech Connect

    Doser, Adele Beatrice; Merkle, Peter Benedict

    2004-10-01

    A Self Organizing Map (SOM) approach was used to analyze physiological data taken from a group of subjects participating in a cooperative video shooting game. The ultimate aim was to discover signatures of group cooperation, conflict, leadership, and performance. Such information could be fed back to participants in a meaningful way, and ultimately increase group performance in national security applications, where the consequences of a poor group decision can be devastating. Results demonstrated that a SOM can be a useful tool in revealing individual and group signatures from physiological data, and could ultimately be used to heighten group performance.

  6. Self-organized chains of nanodots induced by an off-normal incident beam

    PubMed Central

    2011-01-01

    We propose a model to show that under off-normal bombardment of an incident ion beam, a solid surface may spontaneously form nanoscale dots lining up into chains perpendicular to the incident beam direction. These dots demonstrate a highly ordered hexagonal pattern. We attribute the self-organization behavior to surface instability under concurrent surface kinetics and to a shadow effect that causes the self-alignment of dots. The fundamental mechanism may be applicable to diverse systems, suggesting an effective approach for nanofabrication. PMID:21711497

  7. The role of fluids in rock layering development: a pressure solution self-organized process revealed by laboratory experiments

    NASA Astrophysics Data System (ADS)

    Gratier, Jean-Pierre; Noiriel, Catherine; Renard, Francois

    2015-04-01

    Natural deformation of rocks is often associated with stress-driven differentiation processes leading to irreversible transformations of their microstructures. The development mechanisms of such processes during diagenesis, tectonic, metamorphism or fault differentiation are poorly known as they are difficult to reproduce experimentally due to the very slow kinetics of stress-driven chemical processes. Here, we show that experimental compaction with development of differentiated layering, similar to what happens in natural deformation, can be obtained by indenter techniques in laboratory conditions. Samples of plaster mixed with clay and of diatomite loosely interbedded with volcanic dust were loaded in presence of their saturated aqueous solutions during several months at 40°C and 150°C, respectively. High-resolution X-ray microtomography and scanning electron microscopy observations show that the layering development is a pressure solution self-organized process. Stress-driven dissolution of the soluble minerals (either gypsum or silica) is initiated in the areas initially richer in insoluble minerals (clays or volcanic dust) because the kinetics of diffusive mass transfer along the soluble/insoluble mineral interfaces is much faster than along the healed boundaries of the soluble minerals. The passive concentration of insoluble minerals amplifies the localization of dissolution along some layers oriented perpendicular to the maximum compressive stress. Conversely, in the areas with initial low content in insoluble minerals and clustered soluble minerals, dissolution is slower. Consequently, these areas are less deformed, they host the re-deposition of the soluble species and they act as rigid objects that concentrate the dissolution near their boundaries thus amplifying the differentiation. A crucial parameter required for self-organized process of pressure solution is the presence of a fluid that is a good solvent of at least some of the rock-forming minerals

  8. Self-organization of early vocal development in infants and machines: the role of intrinsic motivation

    PubMed Central

    Moulin-Frier, Clément; Nguyen, Sao M.; Oudeyer, Pierre-Yves

    2014-01-01

    We bridge the gap between two issues in infant development: vocal development and intrinsic motivation. We propose and experimentally test the hypothesis that general mechanisms of intrinsically motivated spontaneous exploration, also called curiosity-driven learning, can self-organize developmental stages during early vocal learning. We introduce a computational model of intrinsically motivated vocal exploration, which allows the learner to autonomously structure its own vocal experiments, and thus its own learning schedule, through a drive to maximize competence progress. This model relies on a physical model of the vocal tract, the auditory system and the agent's motor control as well as vocalizations of social peers. We present computational experiments that show how such a mechanism can explain the adaptive transition from vocal self-exploration with little influence from the speech environment, to a later stage where vocal exploration becomes influenced by vocalizations of peers. Within the initial self-exploration phase, we show that a sequence of vocal production stages self-organizes, and shares properties with data from infant developmental psychology: the vocal learner first discovers how to control phonation, then focuses on vocal variations of unarticulated sounds, and finally automatically discovers and focuses on babbling with articulated proto-syllables. As the vocal learner becomes more proficient at producing complex sounds, imitating vocalizations of peers starts to provide high learning progress explaining an automatic shift from self-exploration to vocal imitation. PMID:24474941

  9. Stable learning of functional maps in self-organizing spiking neural networks with continuous synaptic plasticity

    PubMed Central

    Srinivasa, Narayan; Jiang, Qin

    2013-01-01

    This study describes a spiking model that self-organizes for stable formation and maintenance of orientation and ocular dominance maps in the visual cortex (V1). This self-organization process simulates three development phases: an early experience-independent phase, a late experience-independent phase and a subsequent refinement phase during which experience acts to shape the map properties. The ocular dominance maps that emerge accommodate the two sets of monocular inputs that arise from the lateral geniculate nucleus (LGN) to layer 4 of V1. The orientation selectivity maps that emerge feature well-developed iso-orientation domains and fractures. During the last two phases of development the orientation preferences at some locations appear to rotate continuously through ±180° along circular paths and referred to as pinwheel-like patterns but without any corresponding point discontinuities in the orientation gradient maps. The formation of these functional maps is driven by balanced excitatory and inhibitory currents that are established via synaptic plasticity based on spike timing for both excitatory and inhibitory synapses. The stability and maintenance of the formed maps with continuous synaptic plasticity is enabled by homeostasis caused by inhibitory plasticity. However, a prolonged exposure to repeated stimuli does alter the formed maps over time due to plasticity. The results from this study suggest that continuous synaptic plasticity in both excitatory neurons and interneurons could play a critical role in the formation, stability, and maintenance of functional maps in the cortex. PMID:23450808

  10. Self-organized titanium oxide nano-channels for resistive memory application

    SciTech Connect

    Barman, A.; Saini, C. P.; Dhar, S.; Kanjilal, A.; Sarkar, P.; Satpati, B.; Bhattacharyya, S. R.

    2015-12-14

    Towards developing next generation scalable TiO{sub 2}-based resistive switching (RS) memory devices, the efficacy of 50 keV Ar{sup +}-ion irradiation to achieve self-organized nano-channel based structures at a threshold fluence of 5 × 10{sup 16} ions/cm{sup 2} at ambient temperature is presented. Although x-ray diffraction results suggest the amorphization of as-grown TiO{sub 2} layers, detailed transmission electron microscopy study reveals fluence-dependent evolution of voids and eventual formation of self-organized nano-channels between them. Moreover, gradual increase of TiO/Ti{sub 2}O{sub 3} in the near surface region, as monitored by x-ray photoelectron spectroscopy, establishes the upsurge in oxygen deficient centers. The impact of structural and chemical modification on local RS behavior has also been investigated by current-voltage measurements in conductive atomic force microscopy, while memory application is manifested by fabricating Pt/TiO{sub 2}/Pt/Ti/SiO{sub 2}/Si devices. Finally, the underlying mechanism of our experimental results has been analyzed and discussed in the light of oxygen vacancy migration through nano-channels.

  11. Emergence of Small-World Anatomical Networks in Self-Organizing Clustered Neuronal Cultures

    PubMed Central

    de Santos-Sierra, Daniel; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A.; Anava, Sarit; Ayali, Amir; Papo, David; Boccaletti, Stefano

    2014-01-01

    In vitro primary cultures of dissociated invertebrate neurons from locust ganglia are used to experimentally investigate the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. At all the different stages of the culture's development, identification of neurons' and neurites' location by means of a dedicated software allows to ultimately extract an adjacency matrix from each image of the culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main network's characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graph's micro- and meso-scale properties emerge. Finally, we identify the main physical processes ruling the culture's morphological transformations, and embed them into a simplified growth model qualitatively reproducing the overall set of experimental observations. PMID:24489675

  12. Laser-induced self-organization in silicon-germanium thin films

    SciTech Connect

    Weizman, M.; Nickel, N. H.; Sieber, I.; Yan, B.

    2008-05-01

    We report on the formation of self-organized structures in thin films of silicon-germanium (Si{sub 1-x}Ge{sub x}) with 0.3self-organization phenomenon can be turned off by increasing the solidification velocity.

  13. Self-organizing phenomena at membrane level and low-level laser therapy of rhinitis

    NASA Astrophysics Data System (ADS)

    Ailioaie, Laura; Ailioaie, C.; Topoliceanu, Fl.

    2000-06-01

    Allergic rhinitis is the most common allergic disease affecting many people worldwide. Low level laser therapy (LLLT) was applied as monotherapy to 32 children, under placebo controlled conditions. There have been used two GaAlAs diode lasers. The density of energy and the frequency 2 sessions daily - were applied under a special experimental protocol of treatment, including endonasal regions treated with an optical fiber and the extrameridian acupuncture points for rhinitis, 10 days monthly, three months consecutively. The initial investigations with fiberoptic rhinoscope revealed a swollen, pale and edematous mucosa, with increased nasal sections, which may be watery to mucoid. At the end of LLLT, the symptoms of rhinitis like sneezing, nasal congestion, stuffy nose, mouth breathing, snoring - have disappeared and the aspect of nasal mucosa was normal. The results could be explained in the new scenario of self-organizing phenomena at membrane level. The physiological beneficial effects may be correlated and possibly explained by self-organizing paradigms. Our result warrant that LLL is a very good therapy modality for children suffering from allergic rhinitis.

  14. Self-organization of highly ordered honeycomb buckling patterns in crystalline thin films

    NASA Astrophysics Data System (ADS)

    Choi, Yun Jeong; Naoi, Yoshiki; Tomita, Takuro

    2015-10-01

    Highly ordered honeycomb buckling patterns were self-organized by a simple annealing process. The patterns were formed by thin, layered crystalline films of Al4C3 and carbon synthesized on a sapphire c-plane substrate by chemical vapor deposition. While annealing at 1000 °C, the thin bilayer film wrinkled and began to develop a two-dimensionally periodic pattern. Two patterns, with periodicities of 34 and 20 µm, were observed by two-dimensional fast Fourier transform (2D-FFT) analysis. Both patterns showed clear and sharp peaks at six orientations, corresponding to the vertices of a regular hexagon, similarly to the crystallinity of sapphire. Additionally, a shift of the Raman peak to a lower frequency was observed after annealing. These results reveal that the self-organization of a periodic buckling pattern is possible without complicated conventional lithography through the use of crystalline materials. Thus, the highly periodic hexagonal patterns obtained with thin crystal materials have a high symmetry, as characterized from 2D-FFT, and can be applied as an optical grating.

  15. Self-organized flexible leadership promotes collective intelligence in human groups

    PubMed Central

    Kurvers, Ralf H. J. M.; Wolf, Max; Naguib, Marc; Krause, Jens

    2015-01-01

    Collective intelligence refers to the ability of groups to outperform individual decision-makers. At present, relatively little is known about the mechanisms promoting collective intelligence in natural systems. We here test a novel mechanism generating collective intelligence: self-organization according to information quality. We tested this mechanism by performing simulated predator detection experiments using human groups. By continuously tracking the personal information of all members prior to collective decisions, we found that individuals adjusted their response time during collective decisions to the accuracy of their personal information. When individuals possessed accurate personal information, they decided quickly during collective decisions providing accurate information to the other group members. By contrast, when individuals had inaccurate personal information, they waited longer, allowing them to use social information before making a decision. Individuals deciding late during collective decisions had an increased probability of changing their decision leading to increased collective accuracy. Our results thus show that groups can self-organize according to the information accuracy of their members, thereby promoting collective intelligence. Interestingly, we find that individuals flexibly acted both as leader and as follower depending on the quality of their personal information at any particular point in time. PMID:27019718

  16. Self-organization of rat cardiac cells into contractile 3-D cardiac tissue.

    PubMed

    Baar, Keith; Birla, Ravi; Boluyt, Marvin O; Borschel, Gregory H; Arruda, Ellen M; Dennis, Robert G

    2005-02-01

    The mammalian heart is not known to regenerate following injury. Therefore, there is great interest in developing viable tissue-based models for cardiac assist. Recent years have brought numerous advances in the development of scaffold-based models of cardiac tissue, but a self-organizing model has yet to be described. Here, we report the development of an in vitro cardiac tissue without scaffolding materials in the contractile region. Using an optimal concentration of the adhesion molecule laminin, a confluent layer of neonatal rat cardiomyogenic cells can be induced to self-organize into a cylindrical construct, resembling a papillary muscle, which we have termed a cardioid. Like endogenous heart tissue, cardioids contract spontaneously and can be electrically paced between 1 and 5 Hz indefinitely without fatigue. These engineered cardiac tissues also show an increased rate of spontaneous contraction (chronotropy), increased rate of relaxation (lusitropy), and increased force production (inotropy) in response to epinephrine. Cardioids have a developmental protein phenotype that expresses both alpha- and beta-tropomyosin, very low levels of SERCA2a, and very little of the mature isoform of cardiac troponin T. PMID:15574489

  17. Self-organization of poly(ethylene oxide) on the surface of aqueous salt solutions.

    PubMed

    Fuchs, Christian; Hussain, Hazrat; Amado, Elkin; Busse, Karsten; Kressler, Joerg

    2015-01-01

    It is demonstrated that stable Langmuir films of poly(ethylene oxide) (PEO) can be formed up to surface pressures of 30 mN m(-1) when potassium carbonate K2CO3 is added to the aqueous subphase. Generally, PEO homopolymer cannot stay on the water surface at a surface pressure ≥10 mN m(-1) due to its high water solubility. To prepare stable monolayer films, PEO can be modified with hydrophobic moieties. However, by exploiting the salting out effect by adding certain salts (K2CO3 or MgSO4) into the aqueous subphase, not only very stable films but also unusual self-organization can be achieved by the PEO homopolymer on the surface of the aqueous solution. Thus, a series of OH-terminated PEOs is found to form a stable monolayer at K2CO3 concentrations of 2 M and above in the aqueous subphase, and the stability of the film increases with an increase in K2CO3 concentration. Hysteresis experiments are also carried out. During the phase transition induced by progressive compression, self-organization into well-defined domains with sizes in the micrometer range are observed, and with further compression and holding of the film for 30 min and above the microdomains transform into a crystalline morphology as visualized by Brewster angle microscopy. PMID:25269665

  18. A novel self-organizing E-Learner community model with award and exchange mechanisms.

    PubMed

    Yang, Fan; Shen, Rui-min; Han, Peng

    2004-11-01

    How to share experience and resources among learners is becoming one of the hottest topics in the field of E-Learning collaborative techniques. An intuitive way to achieve this objective is to group learners which can help each other into the same community and help them learn collaboratively. In this paper, we proposed a novel community self-organization model based on multi-agent mechanism, which can automatically group learners with similar preferences and capabilities. In particular, we proposed award and exchange schemas with evaluation and preference track records to raise the performance of this algorithm. The description of learner capability, the matchmaking process, the definition of evaluation and preference track records, the rules of award and exchange schemas and the self-organization algorithm are all discussed in this paper. Meanwhile, a prototype has been built to verify the validity and efficiency of the algorithm. Experiments based on real learner data showed that this mechanism can organize learner communities properly and efficiently; and that it has sustainable improved efficiency and scalability. PMID:15495326

  19. Self-organization of developing embryo using scale-invariant approach

    PubMed Central

    2011-01-01

    Background Self-organization is a fundamental feature of living organisms at all hierarchical levels from molecule to organ. It has also been documented in developing embryos. Methods In this study, a scale-invariant power law (SIPL) method has been used to study self-organization in developing embryos. The SIPL coefficient was calculated using a centro-axial skew symmetrical matrix (CSSM) generated by entering the components of the Cartesian coordinates; for each component, one CSSM was generated. A basic square matrix (BSM) was constructed and the determinant was calculated in order to estimate the SIPL coefficient. This was applied to developing C. elegans during early stages of embryogenesis. The power law property of the method was evaluated using the straight line and Koch curve and the results were consistent with fractal dimensions (fd). Diffusion-limited aggregation (DLA) was used to validate the SIPL method. Results and conclusion The fractal dimensions of both the straight line and Koch curve showed consistency with the SIPL coefficients, which indicated the power law behavior of the SIPL method. The results showed that the ABp sublineage had a higher SIPL coefficient than EMS, indicating that ABp is more organized than EMS. The fd determined using DLA was higher in ABp than in EMS and its value was consistent with type 1 cluster formation, while that in EMS was consistent with type 2. PMID:21635789

  20. Ecosystem properties self-organize in response to a directional fog-vegetation interaction.

    PubMed

    Stanton, Daniel E; Armesto, Juan J; Hedin, Lars O

    2014-05-01

    Feedbacks between vegetation and resource inputs can lead to the local, self-organization of ecosystem properties. In particular, feedbacks in response to directional resources (e.g., coastal fog, slope runoff) can create complex spatial patterns, such as vegetation banding. Although similar feedbacks are thought to be involved in the development of ecosystems, clear empirical examples are rare. We created a simple model of a fog-influenced, temperate rainforest in central Chile, which allows the comparison of natural banding patterns to simulations of various putative mechanisms. We show that only feedbacks between plants and fog were able to replicate the characteristic distributions of vegetation, soil water, and soil nutrients observed in field transects. Other processes, such as rainfall, were unable to match these diagnostic distributions. Furthermore, fog interception by windward trees leads to increased downwind mortality, leading to progressive extinction of the leeward edge. This pattern of ecosystem development and decay through self-organized processes illustrates, on a relatively small spatial and temporal scale, the patterns predicted for ecosystem evolution. PMID:25000752