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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. Self-organization through dissipation in a non-conservative cellular-automaton model of earthquakes

    NASA Astrophysics Data System (ADS)

    Al-Kindy, F. H.; Main, I. G.

    2003-04-01

    Self-organizing systems are of particular interest from a thermodynamic perspective since they show the spontaneous emergence of pattern or order, in apparent contradiction of the second law of thermodynamics. Here we investigate self-organization in a non-conservative version of the Bak and Tang (BT) cellular-automaton model, and its dependence on dissipation for populations of synthetic earthquakes. The probability distributions of strain energy and radiated energy are used to calculate Shannon entropy S as a measure of disorder. As the conservation parameter α is decreased, the external entropy Se decreases as the internal entropy Si increases with Δ Se>0. This suggests that in the model, self-organization occurs at the expense of lowering the internal energy of the system through dissipation while increasing its entropy production globally. The results also show some similarities with recent analysis of real earthquake populations.

  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. Universality in the Self Organized Critical behavior of a cellular model of superconducting vortex dynamics

    NASA Astrophysics Data System (ADS)

    Sun, Yudong; Vadakkan, Tegy; Bassler, Kevin

    2007-03-01

    We study the universality and robustness of variants of the simple model of superconducting vortex dynamics first introduced by Bassler and Paczuski in Phys. Rev. Lett. 81, 3761 (1998). The model is a coarse-grained model that captures the essential features of the plastic vortex motion. It accounts for the repulsive interaction between vortices, the pining of vortices at quenched disordered locations in the material, and the over-damped dynamics of the vortices that leads to tearing of the flux line lattice. We report the results of extensive simulations of the critical ``Bean state" dynamics of the model. We find a phase diagram containing four distinct phases of dynamical behavior, including two phases with distinct Self Organized Critical (SOC) behavior. Exponents describing the avalanche scaling behavior in the two SOC phases are determined using finite-size scaling. The exponents are found to be robust within each phase and for different variants of the model. The difference of the scaling behavior in the two phases is also observed in the morphology of the avalanches.

  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 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

  13. 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

  14. Self-organization in phase separation of a lyotropic liquid crystal into cellular, network and droplet morphologies.

    PubMed

    Iwashita, Yasutaka; Tanaka, Hajime

    2006-02-01

    Phase separation is one of the most fundamental physical phenomena that controls the morphology of heterogeneous structures. Phase separation of a binary mixture of simple liquids produces only two morphologies: a bicontinuous or a droplet structure in the case of a symmetric or an asymmetric composition, respectively. For complex fluids, there is a possibility to produce other interesting morphologies. We found that a network structure of the minority phase can also be induced transiently on phase separation if the dynamics of the minority phase are much slower than those of the majority phase. Here we induce a cellular structure of the minority phase intentionally with the help of its smectic ordering, using phase separation of a lyotropic liquid crystal into the isotropic and smectic phase. We can control the three morphologies, cellular, network and droplet structures, solely by changing the heating rate. We demonstrate that the kinetic interplay between phase separation and smectic ordering is a key to the morphological selection. This may provide a new route to the formation of network and cellular morphologies in soft materials.

  15. 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).

  16. Adaptive handoff algorithms based on self-organizing neural networks to enhance the quality of service of nonstationary traffic in heirarchical cellular networks

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    2000-03-01

    Third-generation (3G) wireless networks, based on a hierarchical cellular structure, support tiered levels of multimedia services. These services can be categorized as real-time and delay-sensitive, or non-real-time and delay- insensitive. Each call carries demand for one or more services in parallel; each with a guaranteed quality of service (QoS). Roaming is handled by handoff procedures between base stations (BSs) and the mobile subscribers (MSs) within the network. Metrics such as the probabilities of handoff failure, dropped calls and blocked calls; handoff transition time; and handoff rate are used to evaluate the handoff schemes, which also directly affects QoS. Previous researchers have proposed a fuzzy logic system (FLS) with neural encoding of the rule base and probabilistic neural network to solve the handoff decision as a pattern recognition problem in the set of MS signal measurements and mobility amid fading path uncertainties. Both neural approaches evalute only voice traffic in a closed, single- layer network of uniform cells. This paper proposed a new topology-preserving, self-organizing neural network (SONN) for both handoff and admission control as part of an overall resource allocation (RA) problem to support QoS in a three- layer, wideband CDMA HCS with dynamic loading of multimedia services. MS profiles include simultaneous service requirements, which are mapped to a new set of variables, defined in terms of the network radio resources (RRs). Simulations of the new SONN-based algorithms under various operating scenarios of MS mobility, dynamic loading, active set size, and RR bounds, using published traffic models of 3G services, compare their performance with earlier approaches.

  17. 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

  18. Skeletal Muscle Cellularity and Glycogen Distribution in the Hypermuscular Compact Mice

    PubMed Central

    Kocsis, T.; Baán, J.; Müller, G.; Mendler, L.; Dux, L.

    2014-01-01

    The TGF-beta member myostatin acts as a negative regulator of skeletal muscle mass. The Compact mice were selected for high protein content and hypermuscularity, and carry a naturally occurring 12-bp deletion in the propeptide region of the myostatin precursor. We aimed to investigate the cellular characteristics and the glycogen distribution of the Compact tibialis anterior (TA) muscle by quantitative histochemistry and spectrophotometry. We have found that the deficiency in myostatin resulted in significantly increased weight of the investigated hindlimb muscles compared to wild type. Although the average glycogen content of the individual fibers kept unchanged, the total amount of glycogen in the Compact TA muscle increased two-fold, which can be explained by the presence of more fibers in Compact compared to wild type muscle. Moreover, the ratio of the most glycolytic IIB fibers significantly increased in the Compact TA muscle, of which glycogen content was the highest among the fast fibers. In summary, myostatin deficiency caused elevated amount of glycogen in the TA muscle but did not increase the glycogen content of the individual fibers despite the marked glycolytic shift observed in Compact mice. PMID:25308840

  19. 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.

  20. 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.

  1. 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'.

  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. 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

  4. 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.

  5. Evolution of self-organized systems.

    PubMed

    Cole, Blaine J

    2002-06-01

    In this paper I ask questions about the evolution of self-organized activity cycles that are found in some ant colonies. I use a computer model that generates periodic activity patterns in interacting subunits and explore the parameters of this model using a genetic algorithm in which selecting on one aspect of the system produces the distinctive self-organized pattern. The general point that I explore, using the example of activity cycles, is that the observation of a self-organized pattern does not mean that the pattern is an adaptation. Self-organized patterns can represent nonadaptive correlated responses to selection, exaptations or even selectively disadvantageous traits. Evolution of self-organized patterns requires genetic feedback between the self-organized output and the subunits that produce the pattern. Without this necessary feedback, a self-organized system does not evolve.

  6. 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.

  7. 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

  8. Self-Organization in Turbulent Plasmas

    NASA Astrophysics Data System (ADS)

    Diamond, P. H.

    1997-11-01

    Self-Organization is a ubiquitous phenomenon in turbulent laboratory, space and astrophysical plasmas. In this review, we focus on the emergent behavior of large scale order in turbulent plasmas. Instances of such emergent behavior have the common elements of broken symmetry, criticality and auto-regulation, which collectively govern order parameter evolution. Here, we discuss three classic and illustrative paradigms of self-organization (s.-o.). Perhaps the simplest paradigm of s.-o. is that of criticality in one and two-dimensional cellular automata (CA). The goal is to understand the link between emergent macroscopic profile structure and microscopic automata rules, an end closely related to the calculation of tokamak confinement from gradient-driven micro-instabilities. Here, profile shape and stiffness may be calculated to good accuracy from Markov-chain algorithms, which agree well with direct implementation of the CA's with noise. For strongly-driven piles, hydrodynamic models reproduce ballistic propagation scaling and confirm the expectation that cross-gradient shear flows significantly alter avalanche statistics and scaling. A second paradigm of s.-o. is the magnetic dynamo, a classic realization of large scale s.-o. induced by small scale symmetry breaking. Here, it is the reflection symmetry of the small-scale turbulence which is broken, yielding a net helicity and alpha-effect. The structure of the self-organized state (i.e. scale of growth) is determined by alpha, which displays the footprint of small scale asymmetry. A novel element in the theory is the nonlinearity induced by rapid amplification of small scale magnetic fields. This, in turn, induces a nonlinear feedback which quenches the dynamo at finite amplitude. The quenching process is also manifested in passive scalar and magnetic flux transport. The third paradigm is the self-regulating shear flow. Here, small scale and large scale asymmetry are linked by a mechanism very similar to that

  9. 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

  10. 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.

  11. Self-Organizing Mesh Generation

    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

  12. Self-organized nanotube serpentines.

    PubMed

    Geblinger, Noam; Ismach, Ariel; Joselevich, Ernesto

    2008-04-01

    Carbon nanotubes have unique mechanical, electronic, optical and thermal properties, which make them attractive building blocks in the field of nanotechnology. However, their organization into well-defined straight or curved geometries and arrays on surfaces remains a critical challenge for their integration into functional nanosystems. Here we show that combined surface- and flow-directed growth enable the controlled formation of uniquely complex and coherent geometries of single-walled carbon nanotubes, including highly oriented and periodic serpentines and coils. We propose a mechanism of non-equilibrium self-organization, in which competing dissipative forces of adhesion and aerodynamic drag induce oscillations in the nanotubes as they adsorb on the surface. Our results demonstrate the use of 'order through fluctuations' to shape nanostructures into complex geometries. The nanotube serpentines and loops are shown to be electrically conducting and could therefore find a wide range of potential applications, such as receiving and transmitting antennas, heating and cooling elements, optoelectronic devices and single-molecule dynamos.

  13. Physical Foundations of Self-organizing Systems

    NASA Astrophysics Data System (ADS)

    Chatterjee, Atanu; Georgiev, Georgi

    2014-03-01

    The appearance of coherent global pattern due to local interactions is known as self-organization. Self-organization is a spontaneous process in highly non-equilibrium dissipative systems that form structures which tend to maximize energy dissipation by leveling off energy gradients. This follows as a direct consequence of the Second Law of Thermodynamics. Also, a local interaction embodies in the above definition a mechanistic dimension to self-organization. The link between mechanics and the Second Law of Thermodynamics lie in the Principle of Least Action, a strong law of nature that is obeyed in every spontaneous process. Thus, self-organization rests on two basic foundational principles of nature namely, the Second Law of Thermodynamics and the Principle of Least Action. We attempt to develop a formal definition of self-organization based on those principles.

  14. Self-organization in social tagging systems.

    PubMed

    Liu, Chuang; Yeung, Chi Ho; Zhang, Zi-Ke

    2011-06-01

    Individuals often imitate each other to fall into the typical group, leading to a self-organized state of typical behaviors in a community. In this paper, we model self-organization in social tagging systems and illustrate the underlying interaction and dynamics. Specifically, we introduce a model in which individuals adjust their own tagging tendency to imitate the average tagging tendency. We found that when users are of low confidence, they tend to imitate others and lead to a self-organized state with active tagging. On the other hand, when users are of high confidence and are stubborn to change, tagging becomes inactive. We observe a phase transition at a critical level of user confidence when the system changes from one regime to the other. The distributions of post length obtained from the model are compared to real data, which show good agreement. PMID:21797438

  15. Triggering signaling pathways using F-actin self-organization

    PubMed Central

    Colin, A.; Bonnemay, L.; Gayrard, C.; Gautier, J.; Gueroui, Z.

    2016-01-01

    The spatiotemporal organization of proteins within cells is essential for cell fate behavior. Although it is known that the cytoskeleton is vital for numerous cellular functions, it remains unclear how cytoskeletal activity can shape and control signaling pathways in space and time throughout the cell cytoplasm. Here we show that F-actin self-organization can trigger signaling pathways by engineering two novel properties of the microfilament self-organization: (1) the confinement of signaling proteins and (2) their scaffolding along actin polymers. Using in vitro reconstitutions of cellular functions, we found that both the confinement of nanoparticle-based signaling platforms powered by F-actin contractility and the scaffolding of engineered signaling proteins along actin microfilaments can drive a signaling switch. Using Ran-dependent microtubule nucleation, we found that F-actin dynamics promotes the robust assembly of microtubules. Our in vitro assay is a first step towards the development of novel bottom-up strategies to decipher the interplay between cytoskeleton spatial organization and signaling pathway activity. PMID:27698406

  16. 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.

  17. 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.

  18. 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.

  19. Self-organized criticality of air pollution

    NASA Astrophysics Data System (ADS)

    Shi, Kai; Liu, Chun-Qiong

    In this work, we investigate the frequency-size distribution of three pollution indexes (PM 10, NO 2 and SO 2) in Shanghai. They are well approximated by power-law distributions, which suggest that air pollution might be a manifestation of self-organized criticality. We introduce a new numerical sandpile model with decay coefficient to reveal inherent dynamic mechanism of air pollution. Only changing the number value of decay coefficient of pollutants, this model gives a good simulation of three pollutants' statistical characteristic. This work shows that it is the self-organized criticality of the air pollutants that results in the temporal variation of air pollutant indexes and the minor air pollution sources can trigger the occurrence of large pollutant events by SOC behavior.

  20. 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.

  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. 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.

  4. 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

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

    PubMed

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

    2016-01-01

    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

  6. 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

  7. 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.

  8. 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.

  9. Self-Organization of Bioinspired Fibrous Surfaces

    NASA Astrophysics Data System (ADS)

    Kang, Sung Hoon

    Nature uses fibrous surfaces for a wide range of functions such as sensing, adhesion, structural color, and self-cleaning. However, little is known about how fiber properties enable them to self-organize into diverse and complex functional forms. Using polymeric micro/nanofiber arrays with tunable properties as model systems, we demonstrate how the combination of mechanical and surface properties can be harnessed to transform an array of anchored nanofibers into a variety of complex, hierarchically organized dynamic functional surfaces. We show that the delicate balance between fiber elasticity and surface adhesion plays a critical role in determining the shape, chirality, and hierarchy of the assembled structures. We further report a strategy for controlling the long-range order of fiber assemblies by manipulating the shape and movement of the liquid-vapor interface. Our study provides fundamental understanding of the pattern formation by self-organization of bioinspired fibrous surfaces. Moreover, our new strategies offer a foundation for designing a vast assortment of functional surfaces with adhesive, optical, water-repellent, capture and release, and many more capabilities with the structural and dynamic sophistication of their biological counterparts.

  10. Non-Equilibrium Nanoscale Self-Organization

    SciTech Connect

    Aziz, Michael J

    2006-03-09

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

  11. Self-organized permeability in carbonate aquifers.

    PubMed

    Worthington, S R H; Ford, D C

    2009-01-01

    Advances over the past 40 years have resulted in a clear understanding of how dissolution processes in carbonate rocks enhance aquifer permeability. Laboratory experiments on dissolution rates of calcite and dolomite have established that there is a precipitous drop in dissolution rates as chemical equilibrium is approached. These results have been incorporated into numerical models, simulating the effects of dissolution over time and showing that it occurs along the entire length of pathways through carbonate aquifers. The pathways become enlarged and integrated over time, forming self-organized networks of channels that typically have apertures in the millimeter to centimeter range. The networks discharge at point-located springs. Recharge type is an important factor in determining channel size and distribution, resulting in a range of aquifer types, and this is well demonstrated by examples from England. Most carbonate aquifers have a large number of small channels, but in some cases large channels (i.e., enterable caves) can also develop. Rapid velocities found in ground water tracer tests, the high incidence of large-magnitude springs, and frequent microbial contamination of wells all support the model of self-organized channel development. A large majority of carbonate aquifers have such channel networks, where ground water velocities often exceed 100 m/d.

  12. 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.

  13. Actomyosin-based Self-organization of cell internalization during C. elegans gastrulation

    PubMed Central

    2012-01-01

    Background Gastrulation is a key transition in embryogenesis; it requires self-organized cellular coordination, which has to be both robust to allow efficient development and plastic to provide adaptability. Despite the conservation of gastrulation as a key event in Metazoan embryogenesis, the morphogenetic mechanisms of self-organization (how global order or coordination can arise from local interactions) are poorly understood. Results We report a modular structure of cell internalization in Caenorhabditis elegans gastrulation that reveals mechanisms of self-organization. Cells that internalize during gastrulation show apical contractile flows, which are correlated with centripetal extensions from surrounding cells. These extensions converge to seal over the internalizing cells in the form of rosettes. This process represents a distinct mode of monolayer remodeling, with gradual extrusion of the internalizing cells and simultaneous tissue closure without an actin purse-string. We further report that this self-organizing module can adapt to severe topological alterations, providing evidence of scalability and plasticity of actomyosin-based patterning. Finally, we show that globally, the surface cell layer undergoes coplanar division to thin out and spread over the internalizing mass, which resembles epiboly. Conclusions The combination of coplanar division-based spreading and recurrent local modules for piecemeal internalization constitutes a system-level solution of gradual volume rearrangement under spatial constraint. Our results suggest that the mode of C. elegans gastrulation can be unified with the general notions of monolayer remodeling and with distinct cellular mechanisms of actomyosin-based morphogenesis. PMID:23198792

  14. Self-organizing nets for optimization.

    PubMed

    Milano, Michele; Koumoutsakos, Petros; Schmidhuber, Jürgen

    2004-05-01

    Given some optimization problem and a series of typically expensive trials of solution candidates sampled from a search space, how can we efficiently select the next candidate? We address this fundamental problem by embedding simple optimization strategies in learning algorithms inspired by Kohonen's self-organizing maps and neural gas networks. Our adaptive nets or grids are used to identify and exploit search space regions that maximize the probability of generating points closer to the optima. Net nodes are attracted by candidates that lead to improved evaluations, thus, quickly biasing the active data selection process toward promising regions, without loss of ability to escape from local optima. On standard benchmark functions, our techniques perform more reliably than the widely used covariance matrix adaptation evolution strategy. The proposed algorithm is also applied to the problem of drag reduction in a flow past an actively controlled circular cylinder, leading to unprecedented drag reduction.

  15. 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.

  16. Pearls are self-organized natural ratchets.

    PubMed

    Cartwright, Julyan H E; Checa, Antonio G; Rousseau, Marthe

    2013-07-01

    Pearls, the most flawless and highly prized of them, are perhaps the most perfectly spherical macroscopic bodies in the biological world. How are they so round? Why are other pearls solids of revolution (off-round, drop, ringed pearl), and yet others have no symmetry (baroque pearls)? We observe that with a spherical pearl the growth fronts of nacre are spirals and target patterns distributed across its surface, and that this is true for a baroque pearl, too, but that in pearls with rotational symmetry spirals and target patterns are found only in the vicinity of the poles; elsewhere the growth fronts are arrayed in ratchet fashion around the equator. We argue that pearl rotation is a self-organized phenomenon caused and sustained by physical forces from the growth fronts, and that rotating pearls are an example--perhaps unique--of a natural ratchet. PMID:23724968

  17. 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.

  18. 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

  19. 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.

  20. Feedback, Lineages and Self-Organizing Morphogenesis.

    PubMed

    Kunche, Sameeran; Yan, Huaming; Calof, Anne L; Lowengrub, John S; Lander, Arthur D

    2016-03-01

    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

  1. Pearls are self-organized natural ratchets.

    PubMed

    Cartwright, Julyan H E; Checa, Antonio G; Rousseau, Marthe

    2013-07-01

    Pearls, the most flawless and highly prized of them, are perhaps the most perfectly spherical macroscopic bodies in the biological world. How are they so round? Why are other pearls solids of revolution (off-round, drop, ringed pearl), and yet others have no symmetry (baroque pearls)? We observe that with a spherical pearl the growth fronts of nacre are spirals and target patterns distributed across its surface, and that this is true for a baroque pearl, too, but that in pearls with rotational symmetry spirals and target patterns are found only in the vicinity of the poles; elsewhere the growth fronts are arrayed in ratchet fashion around the equator. We argue that pearl rotation is a self-organized phenomenon caused and sustained by physical forces from the growth fronts, and that rotating pearls are an example--perhaps unique--of a natural ratchet.

  2. Self-organizing ARTMAP rule discovery.

    PubMed

    Carpenter, Gail A; Olivera, Santiago

    2012-01-01

    The self-organizing ARTMAP rule discovery (SOARD) system derives relationships among recognition classes during online learning. SOARD training on input/output pairs produces the basic competence of direct recognition of individual class labels for new test inputs. As a typical supervised system, it learns many-to-one maps, which recognize different inputs (Spot, Rex) as belonging to one class (dog). As an ARTMAP system, it also learns one-to-many maps, allowing a given input (Spot) to learn a new class (animal) without forgetting its previously learned output (dog), even as it corrects erroneous predictions (cat). As it learns individual input/output class predictions, SOARD employs distributed code representations that support online rule discovery. When the input Spot activates the classes dogand animal, confidence in the rule dog→animal begins to grow. When other inputs simultaneously activate classes cat and animal, confidence in the converse rule, animal→dog, decreases. Confidence in a self-organized rule is encoded as the weight in a path from one class node to the other. An experience-based mechanism modulates the rate of rule learning, to keep inaccurate predictions from creating false rules during early learning. Rules may be excitatory or inhibitory so that rule-based activation can add missing classes and remove incorrect ones. SOARD rule activation also enables inputs to learn to make direct predictions of output classes that they have never experienced during supervised training. When input Rex activates its learned class dog, the rule dog→animal indirectly activates the output class animal. The newly activated class serves as a teaching signal which allows input Rex to learn direct activation of the output class animal. Simulations using small-scale and large-scale datasets demonstrate functional properties of the SOARD system in both spatial and time-series domains.

  3. 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.

  4. Self organized criticality in an one dimensional magnetized grid. Application to GRB X-ray afterglows

    NASA Astrophysics Data System (ADS)

    Harko, Tiberiu; Mocanu, Gabriela; Stroia, Nicoleta

    2015-05-01

    A simplified one dimensional grid is used to model the evolution of magnetized plasma flow. We implement diffusion laws similar to those so-far used to model magnetic reconnection with Cellular Automata. As a novelty, we also explicitly superimpose a background flow. The aim is to numerically investigate the possibility that Self-Organized Criticality appears in a one dimensional magnetized flow. The cellular automaton's cells store information about the parameter relevant to the evolution of the system being modelled. Under the assumption that this parameter stands for the magnetic field, the magnetic energy released by one grid cell during one individual relaxation event is also computed. Our results show that indeed in this system Self-Organized Criticality is established. The possible applications of this model to the study of the X-ray afterglows of GRBs is also briefly considered.

  5. 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.

  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-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.

  8. 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

  9. Self-organization in nonlinear wave turbulence

    SciTech Connect

    Jordan, Richard; Josserand, Christophe

    2000-02-01

    We present a statistical equilibrium model of self-organization in a class of focusing, nonintegrable nonlinear Schroedinger (NLS) equations. The theory predicts that the asymptotic-time behavior of the NLS system is characterized by the formation and persistence of a large-scale coherent solitary wave, which minimizes the Hamiltonian given the conserved particle number (L{sup 2}-norm squared), coupled with small-scale random fluctuations, or radiation. The fluctuations account for the difference between the conserved value of the Hamiltonian and the Hamiltonian of the coherent state. The predictions of the statistical theory are tested against the results of direct numerical simulations of NLS, and excellent qualitative and quantitative agreement is demonstrated. In addition, a careful inspection of the numerical simulations reveals interesting features of the transitory dynamics leading up to the long-time statistical equilibrium state starting from a given initial condition. As time increases, the system investigates smaller and smaller scales, and it appears that at a given intermediate time after the coalescense of the soliton structures has ended, the system is nearly in statistical equilibrium over the modes that it has investigated up to that time. (c) 2000 The American Physical Society.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. Mapping Self-Organized Criticality onto Criticality

    NASA Astrophysics Data System (ADS)

    Sornette, Didier; Johansen, Anders; Dornic, Ivan

    1995-03-01

    We present a general conceptual framework for self-organized criticality (SOC), based on the recognition that it is nothing but the expression, “unfolded" in a suitable parameter space, of an underlying unstable dynamical critical point. More precisely, SOC is shown to result from the tunning of the order parameter to a vanishingly small, but positive value, thus ensuring that the corresponding control parameter lies exactly at its critical value for the underlying transition. This clarifies the role and nature of the very slow driving rate common to all systems exhibiting SOC. This mechanism is shown to apply to models of sandpiles, earthquakes, depinning, fractal growth and forest fires, which have been proposed as examples of SOC. Nous proposons une stratégie générale pour identifier le mécanisme responsable des phénomènes critiques auto-organisés, basée, sur l'idée qu'ils sont simplement la traduction, dans un espace de paramètres choisis, d'un point critique dynamique instable standard. La criticalité auto-organisée résulte du contrôle du paramètre d'ordre ajusté à une valeur positive tendant vers zéro, ce qui assure automatiquement que le paramètre de contrôle correspondant se cale exactement sur sa valeur critique de la transition de critique sous-jacente. Ce résultat explique le rôle particulier joué par le forçage infiniment lent qui est un caractère commun à tous les systèmes critiques auto-organisés. Nous appliquons ces idées aux modèles de tas de sable, aux modèles de tremblements de terre, de feux de forêts, aux transitions de décrochage et aux modèles de croissance fractale, qui ont été proposés comme autant d'exemples caractéristiques de la criticalité auto-organisée.

  19. Self-organization of protein with helical domains

    NASA Astrophysics Data System (ADS)

    Frenkel, Zakhar M.; Melker, Alexander I.

    2002-02-01

    In this contribution, we report on a study of the self- organization of isolated polypeptides. The process is computer simulated by the method of molecular dynamics. We observed that the helical structures have a very impotent role in the protein self-organization. We have found conditions under which such structures to be stable. The process and result of self-organization under these conditions were sharply different from others, unable to maintain the helical structures. The structures obtained have a strong resemblance to the native conformations of the corresponding real proteins in a case of proteins composed by helical domains.

  20. Self-organized critical system with no stationary attractor state

    NASA Astrophysics Data System (ADS)

    Nørrelykke, Simon F.; Bak, Per

    2002-03-01

    A simple model economy with interacting producers and consumers is introduced. When driven by extremal dynamics, the model self-organizes not to an attractor state, but to an asymptote, on which the economy has a constant rate of deflation, is critical, and exhibits avalanches of activity with power-law distributed sizes. This example demonstrates that self-organized critical behavior occurs in a larger class of systems than so far considered: systems not driven to an attractive fixed point, but, e.g., an asymptote, may also display self-organized criticality.

  1. 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.

  2. 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

  3. 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

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

    PubMed

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

    2011-02-22

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

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

    SciTech Connect

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

    2011-02-07

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

  6. Physics of Self-Organization Systems

    NASA Astrophysics Data System (ADS)

    Ishiwata, Shin'ichi; Matsunaga, Yasushi

    2008-04-01

    pt. A. Biophysics. Bio-physics Manifesto for the future of physics and biology / Y. Oono. Single molecule force measurement for protein dynthesis on the ribosome / S. Uemura. A rod probe reveals gait of Myosin V / K. Shiroguchi. Mechanism of spontaneous oscillation emerging from collective molecular motors / Y. Shimamoto and S. Ishiwata. Simulated rotational diffusion of F[symbol] molecular motor / H. Yamasaki and M. Takano -- pt. B. Nonequilibrium statistical physics and related topics. Thermodynamic time ssymmetry and nonequilibrium statistical mechanics / P. Gaspard. A measurement-based purification scheme and decoherence / H. Nakazato. Quantum fluctuation theorem in the existence of the tunneling and the thermal activation / T. Monnai. Statistical properties of the inter-occurrence times in the two-dimensional stick-slip model of earthquakes / T. Hasumi and Y. Aizawa. Second harmonic generation and polarization microscope observations of quantum relaxor lithium doped potasium tantalate / H. Yokota and Y. Uesu. Thermoelectric properties of Ni-doped LaRhO[symbol] / S. Shibasaki, Y. Takahashi and I. Terasaki. Collective precession of chiral liquid crystals under transmembrane mass flow / G. Watanabe, S. Ishizuka and Y. Tabe. Interplay of excitons with free carriers in carrier tunneling dynamics / S. Lu, A. Tackeuchi and S. Muto -- pt. C. Astrophysics as interdisciplimary science. New view on quantum gravity: micro-structure of spacetime and origin of the universe / B. L. Hu. Colliding branes and its application to string cosmology / Y. Takamizu. One-loop corrections to scalar and tensor perturbations during inflation / Y. Urakawa and K. Maeda. Variational calculation for the equation of state of nuclear matter toward supernova simulations / H. Kanzawa ... [et al.]. Two strong radio bursts at high and medium galactic latitude / S. Kida and T. Daishido. Effects of QCD phase transition on the ejected elements from the envelopes of compact stars / Y. Yasutake ... [et

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  8. 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

  9. Self-Organized Criticality in an Asexual Model?

    NASA Astrophysics Data System (ADS)

    Chisholm, Colin; Jan, Naeem; Gibbs, Peter; Erzan, Ayşe.

    Recent work has shown that the distribution of steady state mutations for an asexual ``bacteria'' model has features similar to that seen in Self-Organized Critical (SOC) sandpile model of Bak et al. We investigate this coincidence further and search for ``self-organized critical'' state for bacteria but instead find that the SOC sandpile critical behavior is very sensitive; critical behavior is destroyed with small perturbations effectively when the absorption of sand is introduced. It is only in the limit when the length of the genome of the bacteria tends to infinity that SOC properties are recovered for the asexual model.

  10. 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

  11. Self-Organizing Neural Network Models for State Anticipatory Systems

    NASA Astrophysics Data System (ADS)

    Pöllä, Matti; Honkela, Timo

    2006-06-01

    A vital mechanism of high-level natural cognitive systems is the anticipatory capability of making decisions based on predicted events in the future. While in some cases the performance of computational cognitive systems can be improved by modeling anticipatory behavior, it has been shown that for many cognitive tasks anticipation is mandatory. In this paper, we review the use of self-organizing artificial neural networks in constructing the state-space model of an anticipatory system. The biologically inspired self-organizing map (SOM) and its topologically dynamic variants such as the growing neural gas (GNG) are discussed using illustrative examples of their performance.

  12. Critical self-organized self-sustained oscillations in large regulatory networks: towards understanding the gene expression initiation.

    PubMed

    Rosenfeld, Simon

    2011-03-22

    In this paper, a new model of self-organized criticality is introduced. This model, called the gene expression paradigm, is motivated by the problem of gene expression initiation in the newly-born daughter cells after mitosis. The model is fundamentally different in dynamics and properties from the well known sand-pile paradigm. Simulation experiments demonstrate that a critical total number of proteins exists below which transcription is impossible. Above this critical threshold, the system enters the regime of self-sustained oscillations with standard deviations and periods proportional to the genes' complexities with probability one. The borderline between these two regimes is very sharp. Importantly, such a self-organization emerges without any deterministic feedback loops or external supervision, and is a result of completely random redistribution of proteins between inactive genes. Given the size of the genome, the domain of self-organized oscillatory motion is also limited by the genes' maximal complexities. Below the critical complexity, all the regimes of self-organized oscillations are self-similar and largely independent of the genes' complexities. Above the level of critical complexity, the whole-genome transcription is impossible. Again, the borderline between the domains of oscillations and quiescence is very sharp. The gene expression paradigm is an example of cellular automata with the domain of application potentially far beyond its biological context. The model seems to be simple enough for staging an experiment for verification of its remarkable properties.

  13. Architectures for optoelectronic analogs of self-organizing neural networks.

    PubMed

    Farhat, N H

    1987-06-01

    Architectures for partitioning optoelectronic analogs of neural nets into input-output and internal groups to form a multilayered net capable of self-organization, self-programming, and learning are described. The architectures and implementation ideas given describe a class of optoelectronic neural net modules that, when interfaced to a conventional computer controller, can impart to it artificial intelligence attributes.

  14. 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.

  15. 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…

  16. 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.

  17. Modeling of self organization in Xe micro hollow cathode discharges

    NASA Astrophysics Data System (ADS)

    Akashi, Haruaki

    2009-10-01

    Recently, self organization discharges in Xe micro hollow cathode discharges(MHCDs) have been obtained. The discharge is sustainable in DC, not like dielectric barrier discharge(DBD). Stollenwerk et al[1] reported the self organized pattern in DBD is related to the accumulated charge on the dielectric. In DBD, self organized patterns are significantly affected by dielectric, however, it is not known yet in MHCD. To clarify the mechanism, the simulation has been started. Cylindrical symmetric two dimensional fluid model is taken. The fluid model is adapted from the ref.[2]. The electrodes configuration is similar to ref.[3]. Negative voltage is applied to cathode. In this condition, the self organization pattern is not shown, but the discharge becomes glow like discharge as written in ref.[3]. The peak of electron density is obtained slightly above the hole, but the excimer and ions density peaks are obtained in the hole.[4pt] [1] L.Stollenwerk et al. Phys.Rev.Lett.,96,255001(2006)[0pt] [2] H.Akashi et al, IEEE Trans.Plasma Sci.,33,2,308(2005)[0pt] [3] W.Zhu et al, J.Phys.D: Appl.Phys.,40,3896(2007)

  18. 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.

  19. 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

  20. Self-organization vs. self-ordering events in life-origin models

    NASA Astrophysics Data System (ADS)

    Abel, David L.; Trevors, Jack T.

    2006-12-01

    Self-ordering phenomena should not be confused with self-organization. Self-ordering events occur spontaneously according to natural “law” propensities and are purely physicodynamic. Crystallization and the spontaneously forming dissipative structures of Prigogine are examples of self-ordering. Self-ordering phenomena involve no decision nodes, no dynamically-inert configurable switches, no logic gates, no steering toward algorithmic success or “computational halting”. Hypercycles, genetic and evolutionary algorithms, neural nets, and cellular automata have not been shown to self-organize spontaneously into nontrivial functions. Laws and fractals are both compression algorithms containing minimal complexity and information. Organization typically contains large quantities of prescriptive information. Prescriptive information either instructs or directly produces nontrivial optimized algorithmic function at its destination. Prescription requires choice contingency rather than chance contingency or necessity. Organization requires prescription, and is abstract, conceptual, formal, and algorithmic. Organization utilizes a sign/symbol/token system to represent many configurable switch settings. Physical switch settings allow instantiation of nonphysical selections for function into physicality. Switch settings represent choices at successive decision nodes that integrate circuits and instantiate cooperative management into conceptual physical systems. Switch positions must be freely selectable to function as logic gates. Switches must be set according to rules, not laws. Inanimacy cannot “organize” itself. Inanimacy can only self-order. “Self-organization” is without empirical and prediction-fulfilling support. No falsifiable theory of self-organization exists. “Self-organization” provides no mechanism and offers no detailed verifiable explanatory power. Care should be taken not to use the term “self-organization” erroneously to refer to low

  1. Self-organized phenomena of pedestrian counterflow through a wide bottleneck in a channel

    NASA Astrophysics Data System (ADS)

    Dong, Li-Yun; Lan, Dong-Kai; Li, Xiang

    2016-09-01

    The pedestrian counterflow through a bottleneck in a channel shows a variety of flow patterns due to self-organization. In order to reveal the underlying mechanism, a cellular automaton model was proposed by incorporating the floor field and the view field which reflects the global information of the studied area and local interactions with others. The presented model can well reproduce typical collective behaviors, such as lane formation. Numerical simulations were performed in the case of a wide bottleneck and typical flow patterns at different density ranges were identified as rarefied flow, laminar flow, interrupted bidirectional flow, oscillatory flow, intermittent flow, and choked flow. The effects of several parameters, such as the size of view field and the width of opening, on the bottleneck flow are also analyzed in detail. The view field plays a vital role in reproducing self-organized phenomena of pedestrian. Numerical results showed that the presented model can capture key characteristics of bottleneck flows. Project supported by the National Basic Research Program of China (Grant No. 2012CB725404) and the National Natural Science Foundation of China (Grant Nos. 11172164 and 11572184).

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

    PubMed

    Tsiairis, Charisios D; Aulehla, Alexander

    2016-02-11

    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.

  3. 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

  4. Functional liquid-crystalline assemblies: self-organized soft materials.

    PubMed

    Kato, Takashi; Mizoshita, Norihiro; Kishimoto, Kenji

    2005-12-16

    In the 21st century, soft materials will become more important as functional materials because of their dynamic nature. Although soft materials are not as highly durable as hard materials, such as metals, ceramics, and engineering plastics, they can respond well to stimuli and the environment. The introduction of order into soft materials induces new dynamic functions. Liquid crystals are ordered soft materials consisting of self-organized molecules and can potentially be used as new functional materials for electron, ion, or molecular transporting, sensory, catalytic, optical, and bio-active materials. For this functionalization, unconventional materials design is required. Herein, we describe new approaches to the functionalization of liquid crystals and show how the design of liquid crystals formed by supramolecular assembly and nano-segregation leads to the formation of a variety of new self-organized functional materials.

  5. 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.

  6. Energy sources, self-organization, and the origin of life.

    PubMed

    Boiteau, Laurent; Pascal, Robert

    2011-02-01

    The emergence and early developments of life are considered from the point of view that contingent events that inevitably marked evolution were accompanied by deterministic driving forces governing the selection between different alternatives. Accordingly, potential energy sources are considered for their propensity to induce self-organization within the scope of the chemical approach to the origin of life. Requirements in terms of quality of energy locate thermal or photochemical activation in the atmosphere as highly likely processes for the formation of activated low-molecular weight organic compounds prone to induce biomolecular self-organization through their ability to deliver quanta of energy matching the needs of early biochemical pathways or the reproduction of self-replicating entities. These lines of reasoning suggest the existence of a direct connection between the free energy content of intermediates of early pathways and the quanta of energy delivered by available sources of energy.

  7. Multivariate student-t self-organizing maps.

    PubMed

    López-Rubio, Ezequiel

    2009-12-01

    The original Kohonen's Self-Organizing Map model has been extended by several authors to incorporate an underlying probability distribution. These proposals assume mixtures of Gaussian probability densities. Here we present a new self-organizing model which is based on a mixture of multivariate Student-t components. This improves the robustness of the map against outliers, while it includes the Gaussians as a limit case. It is based on the stochastic approximation framework. The 'degrees of freedom' parameter for each mixture component is estimated within the learning procedure. Hence it does not need to be tuned manually. Experimental results are presented to show the behavior of our proposal in presence of outliers, and its performance in adaptive filtering and classification problems.

  8. Sex and Self-Organization on Rugged Landscapes

    NASA Astrophysics Data System (ADS)

    Finjord, Jan

    The two-parent reproduction model of Derrida and Peliti is simulated on a rugged fitness landscape. Fixed fitness values for each possible genotype are assigned randomly, with all fit individuals having the same probability of reproduction. The previously observed transition to a self-organized state of the population with less recombinational load, implies an abrupt change of genetic overlap distributions, showing up characteristics of a phase transition. A crossover variant of the model has a smoother transition to the adapted regime, with a residual collective adaptation for small values of the threshold in fitness. When a geographical constraint (shortest possible distance) on pairwise reproduction in a population arranged one-dimensionally is imposed, a poised state results, suggestive of self-organized criticality.

  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. 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.

  11. Self-organizing map models of language acquisition

    PubMed Central

    Li, Ping; Zhao, Xiaowei

    2013-01-01

    Connectionist models have had a profound impact on theories of language. While most early models were inspired by the classic parallel distributed processing architecture, recent models of language have explored various other types of models, including self-organizing models for language acquisition. In this paper, we aim at providing a review of the latter type of models, and highlight a number of simulation experiments that we have conducted based on these models. We show that self-organizing connectionist models can provide significant insights into long-standing debates in both monolingual and bilingual language development. We suggest future directions in which these models can be extended, to better connect with behavioral and neural data, and to make clear predictions in testing relevant psycholinguistic theories. PMID:24312061

  12. 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.

  13. 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

  14. Self-organizing map models of language acquisition.

    PubMed

    Li, Ping; Zhao, Xiaowei

    2013-01-01

    Connectionist models have had a profound impact on theories of language. While most early models were inspired by the classic parallel distributed processing architecture, recent models of language have explored various other types of models, including self-organizing models for language acquisition. In this paper, we aim at providing a review of the latter type of models, and highlight a number of simulation experiments that we have conducted based on these models. We show that self-organizing connectionist models can provide significant insights into long-standing debates in both monolingual and bilingual language development. We suggest future directions in which these models can be extended, to better connect with behavioral and neural data, and to make clear predictions in testing relevant psycholinguistic theories.

  15. 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

  16. 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.

  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. 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.

  19. 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.

  20. 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

  1. 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,…

  2. 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

  3. 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.

  4. 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.

  5. Simple lecture demonstrations of instability and self-organization

    NASA Astrophysics Data System (ADS)

    Mayer, V. V.; Varaksina, E. I.; Saranin, V. A.

    2014-11-01

    A dielectric liquid layer with an electric field created inside it is proposed as a means for demonstrating the phenomenon of self-organization. The field is produced by the distributed charge transferred by a corona discharge from the tip to the liquid surface. The theory of the phenomenon is presented. An analogy with the Rayleigh - Taylor instability is drawn and a comparison with the Benard instability is given. The practicality of the method for both natural sciences and the humanities is discussed.

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

    Mortazavi, Vahid

    results show how interfacial patterns form, how the transition between stick and slip zones occurs, and which parameters affect them. In chapter 6, we use Cellular Potts Model to study contact angle (CA) hysteresis as a measure of solid-liquid energy dissipation. We simulate CA hysteresis for a droplet over the tilted patterned surface, and a bubble placed under the surface immersed in liquid. We discuss the dependency of CA hysteresis on the surface structure and other parameters. This analysis allows decoupling of the 1D (pinning of the triple line) and 2D effects (adhesion hysteresis in the contact area) and obtain new insights on the nature of CA hysteresis. To summarize, we examine different cases in frictional interface and observe similar trends. We investigate and discus how these trends could be beneficial in design, synthesis and characterization of different materials and tribosystems. Furthermore, we describe how to utilize fundamental concepts for specific engineering applications. Finally, the main theme of this research is to find new applications of concept of self-organization to tribology and the role played by different physical and chemical interactions in modifying and controlling friction and wear. (Abstract shortened by UMI.)

  9. Self-Organized Criticality and Scaling in Lifetime of Traffic Jams

    NASA Astrophysics Data System (ADS)

    Nagatani, Takashi

    1995-01-01

    The deterministic cellular automaton 184 (the one-dimensional asymmetric simple-exclusion model with parallel dynamics) is extended to take into account injection or extraction of particles. The model presents the traffic flow on a highway with inflow or outflow of cars.Introducing injection or extraction of particles into the asymmetric simple-exclusion model drives the system asymptotically into a steady state exhibiting a self-organized criticality. The typical lifetime of traffic jams scales as \\cong Lν with ν=0.65±0.04. It is shown that the cumulative distribution Nm (L) of lifetimes satisfies the finite-size scaling form Nm (L) \\cong L-1 f(m/Lν).

  10. 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.

  11. 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).

  12. 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

  13. 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

  14. Self-organization of magnetic particles at fluid interfaces

    NASA Astrophysics Data System (ADS)

    Belkin, Maxim

    Understanding principles that govern emergent behavior in systems with complex interactions has puzzled scientists for many years. In my work I studied seemingly simple but highly non-trivial system of magnetic micro-particles suspended at fluid interface and energized by an external vertical AC magnetic field. It can be considered as a prototype for probing the interplay of individual interactions on the collective response of system to the external driving. The first part of this work is focused on experimental study of self-organization in this system. In a certain region of parameters formation of localized snake-like structures with accompanying large-scale symmetric surface flows is observed. Characteristics of the self-organized structure as well as flows strongly depend on parameters of the external driving. Increased driving leads to a spontaneous symmetry breaking of the surface flows which results in a self-propulsion of the "snake". This observation leads to an idea of controlled design of a self-propelled swimmer. Numerical calculations based on a phenomenological model proposed for the description of such system successfully reproduces self-organization of the snake-like structures, self-propulsion under spontaneous and artificial symmetry breaking. Increase in the number of the particles promotes a formation of multiple snakes which are in turn unstable with respect to self-induced flows and become mobile swimmers. Such ensemble effectively mixes the surface of liquid. Experimental study of such two-dimensional mixing is the focus of the second part of this work. Results of molecular-dynamics simulations based on proposed theoretical model are reported.

  15. 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

  16. Spam Detection Based on a Hierarchical Self-Organizing Map

    NASA Astrophysics Data System (ADS)

    Palomo, Esteban José; Domínguez, Enrique; Luque, Rafael Marcos; Muñoz, José

    The GHSOM is an artificial neural network that has been widely used for data clustering. The hierarchical architecture of the GHSOM is more flexible than a single SOM since it is adapted to input data, mirroring inherent hierarchical relations among them. The adaptation process of the GHSOM architecture is controlled by two parameters. However, these parameters have to be established in advance and this task is not always easy. In this paper, a new hierarchical self-organizing model that has just one parameter is proposed. The performance of this model has been evaluated by building a spam detector. Experimental results confirm the goodness of this approach.

  17. 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.

  18. 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.

  19. 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.

  20. Self-Organized Topological State with Majorana Fermions

    NASA Astrophysics Data System (ADS)

    Vazifeh, M. M.; Franz, M.

    2013-11-01

    Most physical systems known to date tend to resist entering the topological phase and must be fine-tuned to reach that phase. Here, we introduce a system in which a key dynamical parameter adjusts itself in response to the changing external conditions so that the ground state naturally favors the topological phase. The system consists of a quantum wire formed of individual magnetic atoms placed on the surface of an ordinary s-wave superconductor. It realizes the Kitaev paradigm of topological superconductivity when the wave vector characterizing the emergent spin helix dynamically self-tunes to support the topological phase. We call this phenomenon a self-organized topological state.

  1. Self organizing maps in urban heat stress projections

    NASA Astrophysics Data System (ADS)

    Lee, Kyoung

    2016-04-01

    A self organizing map (SOM) is an unsupervised machine learning algorithm well suited for identifying patterns in large datasets. It has been used successfully to classify atmospheric states in climate data and as part of statistical downscaling procedures. This study aims to use SOMs to produce downscaled CMIP5-based projections of wet-bulb temperature in urban areas, taking into account the regional atmospheric state and learned local dynamics. These downscaled projections will be compared to the CMIP5 models as well as to observations and then used to project local extreme heat stress events in the future.

  2. 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.

  3. School children dyslexia analysis using self organizing maps.

    PubMed

    Novák, D; Kordík, P; Macas, M; Vyhnálek, M; Brzezny, R; Lhotská, L

    2004-01-01

    The main goal of the study is an unsupervised classification of school children dyslexia. Eye movements of 49 subjects were measured using videooculographic technique (VOG) during two non-reading and one reading tasks. A feature selection was performed obtaining data set consisting of 26 features. Next an inductive modelling technique was applied to data set resulting in extraction of six features which were used as the input to self-organizing map (SOM). Three clusters were finally formed by the SOM proving that the proposed methodology is suitable for automatic dyslexia analysis.

  4. Self-organizing map classifier for stressed speech recognition

    NASA Astrophysics Data System (ADS)

    Partila, Pavol; Tovarek, Jaromir; Voznak, Miroslav

    2016-05-01

    This paper presents a method for detecting speech under stress using Self-Organizing Maps. Most people who are exposed to stressful situations can not adequately respond to stimuli. Army, police, and fire department occupy the largest part of the environment that are typical of an increased number of stressful situations. The role of men in action is controlled by the control center. Control commands should be adapted to the psychological state of a man in action. It is known that the psychological changes of the human body are also reflected physiologically, which consequently means the stress effected speech. Therefore, it is clear that the speech stress recognizing system is required in the security forces. One of the possible classifiers, which are popular for its flexibility, is a self-organizing map. It is one type of the artificial neural networks. Flexibility means independence classifier on the character of the input data. This feature is suitable for speech processing. Human Stress can be seen as a kind of emotional state. Mel-frequency cepstral coefficients, LPC coefficients, and prosody features were selected for input data. These coefficients were selected for their sensitivity to emotional changes. The calculation of the parameters was performed on speech recordings, which can be divided into two classes, namely the stress state recordings and normal state recordings. The benefit of the experiment is a method using SOM classifier for stress speech detection. Results showed the advantage of this method, which is input data flexibility.

  5. Self-organizing wireless sensor networks for structural health monitoring

    NASA Astrophysics Data System (ADS)

    Basheer, Mohammed R.; Rao, Vittal S.; Derriso, Mark M.

    2003-07-01

    A smart sensor node has been developed which has (a) the ability to sense strain of the structure under observation, (b) process this raw sensor data in cooperation with its neighbors and (c) transmit the information to the end user. This network is designed to be self organizing in the sense of establishing and maintaining the inter node connectivity without the need for human intervention. For the envisioned application of structural health monitoring, wireless communication is the most practical solution for node interconnectivity not only because they eliminate interconnecting cables but also for their ability to establish communication links even in inaccessible regions. But wireless nework brings with it a number of issues such as interference, fault tolerant self organizing, multi-hop communication, energy effieiciency, routing and finally reliable operation in spite of massive complexity of the sysetm. This paper addresses the issue of fault tolerant self organiing in wireless sensor networks. We propose a new architecture called the Redundant Tree Network (RTN). RTN is a hierarchical network which exploits redundant links between nodes to provide reliability.

  6. 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

  7. 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

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

    DOE PAGES

    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

  9. Geometry sensing by self-organized protein patterns.

    PubMed

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

    2012-09-18

    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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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

  15. Self-organization in cathode boundary layer discharges in xenon

    NASA Astrophysics Data System (ADS)

    Takano, Nobuhiko; Schoenbach, Karl H.

    2006-05-01

    Self-organization of direct current xenon microdischarges in cathode boundary layer configuration has been studied for pressures in the range 30-140 Torr and for currents in the range 50 µA-1 mA. Side-on and end-on observations of the discharge have provided information on the structure and spatial arrangement of the plasma filaments. The regularly spaced filaments, which appear in the normal glow mode when the current is lowered, have a length which is determined by the cathode fall. It varies, dependent on pressure and current, between 50 and 70 µm. The minimum diameter is approximately 80 µm, as determined from the radiative emission in the visible. The filaments are sources of extensive excimer emission. Measurements of the cathode fall length have allowed us to determine the secondary emission coefficient for the discharge in the normal glow mode and to estimate the cathode fall voltage at the transition from normal glow mode to filamentary mode. It was found that the cathode fall voltage at this transition decreases, indicating the onset of additional electron gain processes at the cathode. The regular arrangement of the filaments, self-organization, is assumed to be due to Coulomb interactions between the positively charged cathode fall channels and positive space charges on the surface of the surrounding dielectric spacer. Calculations based on these assumptions showed good agreement with experimentally observed filament patterns.

  16. Modeling Multisensory Enhancement with Self-organizing Maps

    PubMed Central

    Martin, Jacob G.; Meredith, M. Alex; Ahmad, Khurshid

    2009-01-01

    Self-organization, a process by which the internal organization of a system changes without supervision, has been proposed as a possible basis for multisensory enhancement (MSE) in the superior colliculus (Anastasio and Patton, 2003). We simplify and extend these results by presenting a simulation using traditional self-organizing maps, intended to understand and simulate MSE as it may generally occur throughout the central nervous system. This simulation of MSE: (1) uses a standard unsupervised competitive learning algorithm, (2) learns from artificially generated activation levels corresponding to driven and spontaneous stimuli from separate and combined input channels, (3) uses a sigmoidal transfer function to generate quantifiable responses to separate inputs, (4) enhances the responses when those same inputs are combined, (5) obeys the inverse effectiveness principle of multisensory integration, and (6) can topographically congregate MSE in a manner similar to that seen in cortex. Thus, the model provides a useful method for evaluating and simulating the development of enhanced interactions between responses to different sensory modalities. PMID:19636382

  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. 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.

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

    PubMed Central

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

    2009-01-01

    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. PMID:19706461

  20. Self-organization in cathode boundary layer discharges

    NASA Astrophysics Data System (ADS)

    Takano, Nobuhiko

    Cathode boundary layer (CBL) discharge, which has been developed as a UV light source, operates in a direct current between a planar cathode and a ring-shape anode that are separated by a dielectric with an opening of the same diameter as the anode. The nonthermal CBL discharges operate in a medium pressure range down to 30 Torr, emitting excimer radiation when operated with noble gases. The radiant excimer emittance at 172 nm in xenon reaches 1.7 W/cm2, and a maximum excimer efficiency of 6% has been obtained. The high excimer radiant emittance, in addition to low cost and simple geometry compared to other UV sources, makes CBL discharges an excellent choice for deep UV lamps and a candidate for integrated flat UV panels (Moselhy et al. 2004). It has been found that CBL discharges spontaneously give rise to regularly arranged filaments, i.e., self-organization, at a low current, e.g., less than 0.2 mA at 75 Torr (Schoenbach et al. 2004). In this thesis, the self-organization of direct current xenon discharges in the CBL configuration and parallel-plate geometry have been studied for a pressure range from 30 to 140 Torr and currents from 20 muA to 1 mA. Comprehensive examinations have been performed to investigate the behavior of those filaments by the use of optical, electrical, and spectral measurements. Side-on and end-on observations of the discharges have provided information on axial structure and distance of the filaments from the cathode fall. The electrical measurement has recorded a discrete I-V characteristic associated with the change of the numbers of the filaments. The spectral measurement provides scaling information on the relative population of high-lying states (1s 4, 1s5, and 2p6) of excited xenon atoms. Moreover, temperature measurement has revealed that the thermal electron emission from the cathode surface is negligible for the formation of filaments. The reactor geometry with parallel-plate electrodes analogously gives self-organization. The

  1. Self-organized sorting limits behavioral variability in swarms

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

    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.

  2. 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

  3. Simulating Self-organization and Interference between Certain Hierarchical Structures.

    PubMed

    Raczynski, Stanislaw

    2014-10-01

    A model of the dynamics and interactions between organizations with self-organizing hierarchical structures is presented for discrete events. The active objects of the model are individuals (people, organization members). The parameters of an individual are ability, corruption level, resources, and lust for power, among others. Three organizations are generated and interact with each other, attempting to gain more members and power. The individuals appear and disappear, due to a simple 'birth-and-death' process. If an individual disappears from the model, a corresponding reconfiguration in the hierarchical structure occurs. The organization's growth and macro-patterns are the result of the activities of the individuals. The aim of the simulation is to visualize the evolution of the organizations and the stability of the whole system. A 'steady state' for the model is rare; instead, in most parameter configurations, the model enters into oscillations.

  4. 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.

  5. 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.

  6. 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.

  7. Self-organization and the physics of glassy networks

    NASA Astrophysics Data System (ADS)

    Boolchand, P.; Lucovsky, G.; Phillips, J. C.; Thorpe, M. F.

    Network glasses are the physical prototype for many self-organized systems, ranging from proteins to computer science. Conventional theories of gases, liquids and crystals do not account for the strongly material-selective character of the glass-forming tendency, the phase diagrams of glasses or their optimizable properties. A new topological theory, only 25 years old, has succeeded where conventional theories have failed. It shows that (probably all slowly quenched) glasses, including network glasses, are the result of the combined effects of a few simple mechanisms. These glass-forming mechanisms are topological in nature and have already been identified for several important glasses, including chalcogenide alloys, silicates (window glass and computer chips) and proteins.

  8. 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.

  9. Theory of self-organized critical transport in tokamak plasmas

    SciTech Connect

    Kishimoto, Y.; Tajima, T.; Horton, W.; LeBrun, M.J.; Kim, J.Y. |

    1995-07-01

    A theoretical and computational study of the ion temperature gradient and {eta}{sub i} instabilities in tokamak plasmas has been carried out. In toroidal geometry the modes have a radially extended structure and their eigenfrequencies are constant over many rational surfaces that are coupled through toroidicity. These nonlocal properties of the ITG modes impose strong constraint on the drift mode fluctuations and the amciated transport, showing a self-organized characteristic. As any significant deviation away from marginal stability causes rapid temperature relaxation and intermittent bursts, the modes hover near marginality and exhibit strong kinetic characteristics. As a result, the temperature relaxation is self-semilar and nonlocal, leading to a radially increasing heat diffusivity. The nonlocal transport leads to the Bohm-like diffusion scaling. The heat input regulates the deviation of the temperature gradient away from marginality. The obtained transport scalings and properties are globally consistent with experimental observations of L-mode charges.

  10. 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

  11. 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.

  12. Self-Organization in Hypersonic Shock Driven Plasmas

    NASA Astrophysics Data System (ADS)

    Williams, Kyron; Alexander, A. B.; Scott, M.; Buchanan, J.; Johnson, J. A., III

    2011-10-01

    Evidence has been found using the arc-driven shock tube of self-induced Stark effect lines due to the production of hypersonic shock waves. We take advantage of high time resolution measurements of optical spectral lines. In addition, previous work also indicated a possible means to determine the time evolution of the internal EM field geometry on short time scales (less than 250 microseconds). Further examination of hypersonic argon and krypton plasmas using a phase transition model indicates preliminary evidence of local plasma self-organization and collective behavior. The determination of the system complexity from turbulence analysis also sheds insight into the interaction of hypersonic turbulent plasmas with external magnetic fields. Research supported in part by DOE FES and NSF.

  13. 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.

  14. 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

  15. 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.

  16. Self-organization of cosmic radiation pressure instability

    NASA Technical Reports Server (NTRS)

    Hogan, Craig J.

    1991-01-01

    Under some circumstances the absorption of radiation momentum by an absorbing medium opens the possibility of a dynamical instability, sometimes called 'mock gravity'. Here, a simplified abstract model is studied in which the radiation source is assumed to remain spatially uniform, there is no reabsorption or reradiated light, and no forces other than radiative pressure act on the absorbing medium. It is shown that this model displays the unique feature of being not only unstable, but also self-organizing. The structure approaches a statistical dynamical steady state which is almost independent of initial conditions. In this saturated state the absorbers are concentrated in thin walls around empty bubbles; as the instability develops the big bubbles get bigger and the small ones get crushed and disappear. A linear analysis shows that to first order the thin walls are indeed stable structures. It is speculated that this instability may play a role in forming cosmic large-scale structure.

  17. 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

  18. Self-organization and leadership emergence in emergency response teams.

    PubMed

    Guastello, Stephen J

    2010-04-01

    Emergency response (ER) teams can be formal or ad hoc citizen groups that respond to natural disasters or sentient attackers. This article examines the emergence of leaders in ER teams as a nonlinear dynamical process by which a group that is in a high state of entropy self-organizes into a social structure containing primary and secondary leaders and non-leaders. The empirical study involved 228 undergraduates who were organized into groups of 4 to 12 participants; groups worked against an adversary in a board game simulation. The analysis illustrated the swallowtail catastrophe structure, defined three control parameters, and explored the curious relationship between leadership emergence and performance. Group size, group performance, and competitive behavior contributed to the control parameters in the swallowtail model for ER Teams.

  19. 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

    2016-03-16

    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.

  20. 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

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    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.

  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-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

  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. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Characterization of suicidal behaviour with self-organizing maps.

    PubMed

    Leiva-Murillo, José M; López-Castromán, Jorge; Baca-García, Enrique

    2013-01-01

    The study of the variables involved in suicidal behavior is important from a social, medical, and economical point of view. Given the high number of potential variables of interest, a large population of subjects must be analysed in order to get conclusive results. In this paper, we describe a method based on self-organizing maps (SOMs) for finding the most relevant variables even when their relation to suicidal behavior is strongly nonlinear. We have applied the method to a cohort with more than 8,000 subjects and 600 variables and discovered four groups of variables involved in suicidal behavior. According to the results, there are four main groups of risk factors that characterize the population of suicide attempters: mental disorders, alcoholism, impulsivity, and childhood abuse. The identification of specific subpopulations of suicide attempters is consistent with current medical knowledge and may provide a new avenue of research to improve the management of suicidal cases.

  14. Interrupted Self-Organization of SiGe Pyramids

    NASA Astrophysics Data System (ADS)

    Aqua, Jean-Noël; Gouyé, Adrien; Ronda, Antoine; Frisch, Thomas; Berbezier, Isabelle

    2013-03-01

    We investigate the morphological evolution of SiGe quantum dots deposited on Si(100) during long-time annealing. At low strain, the dots’ self-organization begins by an instability and interrupts when (105) pyramids form. This evolution and the resulting island density are quantified by molecular-beam epitaxy. A kinetic model accounting for elasticity, wetting, and anisotropy is shown to reproduce well the experimental findings with appropriate wetting parameters. In this nucleationless regime, a mean-field kinetic analysis explains the existence of nearly stationary states by the vanishing of the coarsening driving force. The island size distribution follows in both experiments and theory the scaling law associated with a single characteristic length scale.

  15. 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.

  16. Do lattice protein simulations exhibit self-organized criticality?

    NASA Astrophysics Data System (ADS)

    Wisthoff, Addison; Murray, Joelle

    2014-03-01

    Proteins are known to fold into tertiary structures that determine their functionality in living organisms. The goal of my research is to better understand the protein folding process through a lattice Monte-Carlo simulation. Specifically, amino acids in the chain at each time step are allowed to fold to certain locations according to two main criteria: folds must maintain bond length and should be thermally and energetically favorable. This simulation will then be used to examine whether the folding process can be viewed through the lens of self-organized criticality (SOC). In particular I am interested in whether there are features of the folding process that are independent of the size of the protein. Student

  17. 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)].

  18. 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).

  19. 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

  20. 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.

  1. QMESH,RENUM,QPLOT. Self-Organizing Mesh Generation

    SciTech Connect

    Jones, R.E.

    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, 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.

  2. 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

  3. Traffic instabilities in self-organized pedestrian crowds.

    PubMed

    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

  4. Theory of self-organized critical transport in tokamak plasmas

    SciTech Connect

    Kishimoto, Y.; Tajima, T.; Horton, W.; LeBrun, M.J.; Kim, J.Y.

    1996-04-01

    A theoretical and computational study of the ion temperature gradient (ITG) and {eta}{sub {ital i}} instabilities in tokamak plasmas has been carried out. In a toroidal geometry the modes have a radially extended structure and their eigenfrequencies are constant over many rational surfaces that are coupled through toroidicity. These nonlocal properties of the ITG modes impose a strong constraint on the drift mode fluctuations and the associated transport, showing self-organized criticality. As any significant deviation away from marginal stability causes rapid temperature relaxation and intermittent bursts, the modes hover near marginality and exhibit strong kinetic characteristics. As a result of this, the temperature relaxation is self-similar and nonlocal, leading to radially increasing heat diffusivity. The nonlocal transport leads to Bohm-like diffusion scaling. Heat input regulates the deviation of the temperature gradient away from marginality. We present a critical gradient transport model that describes such a self-organized relaxed state. Some of the important aspects in tokamak transport like Bohm diffusion, near marginal stability, radially increasing fluctuation energy and heat diffusivity, intermittency of the wave excitation, and resilient tendency of the plasma profile can be described by this model, and these prominent features are found to belong to one physical category that originates from the radially extended nonlocal drift modes. The obtained transport properties and scalings are globally consistent with experimental observations of low confinement mode (L-mode) discharges. The nonlocal modes can be disintegrated into smaller radial islands by a poloidal shear flow, suggesting that the transport changes from Bohm-like to near gyro-Bohm. {copyright} {ital 1996 American Institute of Physics.}

  5. Self-organizing dominance hierarchies in a wild primate population.

    PubMed

    Franz, Mathias; McLean, Emily; Tung, Jenny; Altmann, Jeanne; Alberts, Susan C

    2015-09-01

    Linear dominance hierarchies, which are common in social animals, can profoundly influence access to limited resources, reproductive opportunities and health. In spite of their importance, the mechanisms that govern the dynamics of such hierarchies remain unclear. Two hypotheses explain how linear hierarchies might emerge and change over time. The 'prior attributes hypothesis' posits that individual differences in fighting ability directly determine dominance ranks. By contrast, the 'social dynamics hypothesis' posits that dominance ranks emerge from social self-organization dynamics such as winner and loser effects. While the prior attributes hypothesis is well supported in the literature, current support for the social dynamics hypothesis is limited to experimental studies that artificially eliminate or minimize individual differences in fighting abilities. Here, we present the first evidence supporting the social dynamics hypothesis in a wild population. Specifically, we test for winner and loser effects on male hierarchy dynamics in wild baboons, using a novel statistical approach based on the Elo rating method for cardinal rank assignment, which enables the detection of winner and loser effects in uncontrolled group settings. Our results demonstrate (i) the presence of winner and loser effects, and (ii) that individual susceptibility to such effects may have a genetic basis. Taken together, our results show that both social self-organization dynamics and prior attributes can combine to influence hierarchy dynamics even when agonistic interactions are strongly influenced by differences in individual attributes. We hypothesize that, despite variation in individual attributes, winner and loser effects exist (i) because these effects could be particularly beneficial when fighting abilities in other group members change over time, and (ii) because the coevolution of prior attributes and winner and loser effects maintains a balance of both effects.

  6. Traffic instabilities in self-organized pedestrian crowds.

    PubMed

    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.

  7. Self-organizing dominance hierarchies in a wild primate population.

    PubMed

    Franz, Mathias; McLean, Emily; Tung, Jenny; Altmann, Jeanne; Alberts, Susan C

    2015-09-01

    Linear dominance hierarchies, which are common in social animals, can profoundly influence access to limited resources, reproductive opportunities and health. In spite of their importance, the mechanisms that govern the dynamics of such hierarchies remain unclear. Two hypotheses explain how linear hierarchies might emerge and change over time. The 'prior attributes hypothesis' posits that individual differences in fighting ability directly determine dominance ranks. By contrast, the 'social dynamics hypothesis' posits that dominance ranks emerge from social self-organization dynamics such as winner and loser effects. While the prior attributes hypothesis is well supported in the literature, current support for the social dynamics hypothesis is limited to experimental studies that artificially eliminate or minimize individual differences in fighting abilities. Here, we present the first evidence supporting the social dynamics hypothesis in a wild population. Specifically, we test for winner and loser effects on male hierarchy dynamics in wild baboons, using a novel statistical approach based on the Elo rating method for cardinal rank assignment, which enables the detection of winner and loser effects in uncontrolled group settings. Our results demonstrate (i) the presence of winner and loser effects, and (ii) that individual susceptibility to such effects may have a genetic basis. Taken together, our results show that both social self-organization dynamics and prior attributes can combine to influence hierarchy dynamics even when agonistic interactions are strongly influenced by differences in individual attributes. We hypothesize that, despite variation in individual attributes, winner and loser effects exist (i) because these effects could be particularly beneficial when fighting abilities in other group members change over time, and (ii) because the coevolution of prior attributes and winner and loser effects maintains a balance of both effects. PMID:26336168

  8. 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.

  9. 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

  10. Mechanism of self-organization in point vortex system

    NASA Astrophysics Data System (ADS)

    Yatsuyanagi, Yuichi; Hatori, Tadatsugu

    2015-12-01

    A mechanism of the self-organization in an unbounded two-dimensional (2D) point vortex system is discussed. A kinetic equation for the system with positive and negative vortices is derived using the Klimontovich formalism. Similar to the Fokker-Planck collision term, the obtained collision term consists of a diffusion term and a drift term. It is revealed that the mechanism for the self-organization in the 2D point vortex system at negative absolute temperature is mainly provided by the drift term. Positive and negative vortices are driven toward opposite directions respectively by the drift term. As a result, well-known, two isolated clumps with positive and negative vortices, respectively, are formed as an equilibrium distribution. Regardless of the number of species of the vortices, either single- or double-sign, it is found that the collision term has following physically good properties: (i) when the system reaches a quasi-stationary state near the thermal equilibrium state with negative absolute temperature, the sign of dω/dψ is expected to be positive, where ω is the vorticity and ψ is the stream function. In this case, the diffusion term decreases the mean field energy, while the drift term increases it. As a whole, the total mean field energy is conserved. (ii) Similarly, the diffusion term increases the Boltzmann entropy, while the drift term decreases it. As a whole, the total entropy production rate is positive or zero (H theorem), which ensures that the system relaxes to the global thermal equilibrium state characterized by the zero entropy production.

  11. 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

  12. 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.

  13. 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.

  14. Self-organization towards optimally interdependent networks by means of coevolution

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Szolnoki, Attila; Perc, Matjaž

    2014-03-01

    Coevolution between strategy and network structure is established as a means to arrive at the optimal conditions needed to resolve social dilemmas. Yet recent research has highlighted that the interdependence between networks may be just as important as the structure of an individual network. We therefore introduce the coevolution of strategy and network interdependence to see whether this can give rise to elevated levels of cooperation in the prisoner's dilemma game. We show that the interdependence between networks self-organizes so as to yield optimal conditions for the evolution of cooperation. Even under extremely adverse conditions, cooperators can prevail where on isolated networks they would perish. This is due to the spontaneous emergence of a two-class society, with only the upper class being allowed to control and take advantage of the interdependence. Spatial patterns reveal that cooperators, once arriving at the upper class, are much more competent than defectors in sustaining compact clusters of followers. Indeed, the asymmetric exploitation of interdependence confers to them a strong evolutionary advantage that may resolve even the toughest of social dilemmas.

  15. 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

  16. Hydropathic self-organized criticality: a magic wand for protein physics.

    PubMed

    Phillips, J C

    2012-10-01

    Self-organized criticality (SOC) is a popular concept that has been the subject of more than 3000 articles in the last 25 years. The characteristic signature of SOC is the appearance of self-similarity (power-law scaling) in observable properties. A characteristic observable protein property that describes protein-water interactions is the water-accessible (hydropathic) interfacial area of compacted globular protein networks. Here we show that hydropathic power-law (size- or length-scale-dependent) exponents derived from SOC enable theory to connect standard Web-based (BLAST) short-range amino acid (aa) sequence similarities to long-range aa sequence hydropathic roughening form factors that hierarchically describe evolutionary trends in water - membrane protein interactions. Our method utilizes hydropathic aa exponents that define a non-Euclidean metric realistically rooted in the atomic coordinates of 5526 protein segments. These hydropathic aa exponents thereby encapsulate universal (but previously only implicit) non-Euclidean long-range differential geometrical features of the Protein Data Bank. These hydropathic aa exponents easily organize small mutated aa sequence differences between human and proximate species proteins. For rhodopsin, the most studied transmembrane signaling protein associated with night vision, analysis shows that this approach separates Euclidean short- and non-Euclidean long-range aa sequence properties, and shows that they correlate with 96% success for humans, monkeys, cats, mice and rabbits. Proper application of SOC using hydropathic aa exponents promises unprecedented simplifications of exponentially complex protein sequence-structure-function problems, both conceptual and practical.

  17. Heredity and self-organization: partners in the generation and evolution of phenotypes.

    PubMed

    Malagon, Nicolas; Larsen, Ellen

    2015-01-01

    In this review we examine the role of self-organization in the context of the evolution of morphogenesis. We provide examples to show that self-organized behavior is ubiquitous, and suggest it is a mechanism that can permit high levels of biodiversity without the invention of ever-increasing numbers of genes. We also examine the implications of self-organization for understanding the "internal descriptions" of organisms and the concept of a genotype-phenotype map.

  18. 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.

  19. [The significance of modular design in the investigation of processes of system self-organization].

    PubMed

    Bul'enkov, N A

    2005-01-01

    A model of the process of determined system self-organization based on system-forming modular water structures is proposed. The arrangement and symmetry of these structures, described by the symmetry groups entanglement, matches the basic principles of system self-organization: "system of systems", "recognition", "all-or-none". Crystallography modular generalization engulfs all stable forms of condensed state, including the bound water structures--matrices for the self-organization of biological systems. The bound water structures, besides being matrices, accomplish the metric selection of other structural components of biological systems capable of self-organization into a whole system by creating numerous directed weak bonds among them. PMID:16248172

  20. 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

  1. Self-Organizing Arrays of Size Scalable Nanoparticle Rings.

    PubMed

    Bao, Ying; Witten, Thomas A; Scherer, Norbert F

    2016-09-27

    A central challenge in nano- and mesoscale materials research is facile formation of specific structures for catalysis, sensing, and photonics. Self-assembled equilibrium structures, such as three-dimensional crystals or ordered monolayers, form as a result of the interactions of the constituents. Other structures can be achieved by imposing forces (fields) and/or boundary conditions, which Whitesides termed "self-organization". Here, we demonstrate contact line pinning on locally curved surfaces (i.e., a self-assembled monolayer of SiO2 colloidal particles) as a boundary condition to create extended arrays of uniform rings of Au nanoparticles (NPs) on the SiO2 colloids. The mechanism differs from the well-known "coffee-ring" effect; here the functionalized NPs deposit at the contact line and are not driven by evaporative transport. Thus, NP ring formation depends on the hydrophobicity and wetting of the SiO2 colloids by the chloroform solution, ligands on the NPs, and temperature. The NP rings exhibit size scaling behavior, maintaining a constant ratio of NP ring-to-colloid diameter (from 300 nm to 2 μm). The resultant high-quality NP ring structures are expected to have interesting photonic properties. PMID:27575751

  2. 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

  3. Image compression using a self-organized neural network

    NASA Astrophysics Data System (ADS)

    Ji, Qiang

    1997-04-01

    In the research described by this paper, we implemented and evaluated a linear self-organized feedforward neural network for image compression. Based on the generalized Hebbian learning algorithm (GHA), the neural network extracts the principle components from the auto-correlation matrix of the input images. To do so, an image is first divided into mutually exclusive square blocks of size m multiplied by m. Each block represents a feature vector of m2 dimension in the feature space. The input dimension of the neural net is therefore m2 and the output dimension is m. Training based on GHA for each block then yields a weight matrix with dimension of m multiplied by m2, rows of which are the eigenvectors of the auto-correlation matrix of the input image block. Projection of each image block onto the extracted eigenvectors yields m coefficients for each block. Image compression is then accomplished by quantizing and coding the coefficients for each block. To evaluate the performance of the neural network, two experiments were conducted using standard IEEE images. First, the neural net was implemented to compress images at different bit rates using different block sizes. Second, to test the neural networks's generalization capability, the sets of principle components extracted from one image was used for compressing different but statistically similar images. The evaluation, based on both visual inspection and statistical measures (NMSE and SNR) of the reconstructed images, demonstrates that the network can yield satisfactory image compression performance and possesses a good generalization capability.

  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-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

  6. 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.

  7. 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

  8. 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.

  9. Self-Organizing Arrays of Size Scalable Nanoparticle Rings.

    PubMed

    Bao, Ying; Witten, Thomas A; Scherer, Norbert F

    2016-09-27

    A central challenge in nano- and mesoscale materials research is facile formation of specific structures for catalysis, sensing, and photonics. Self-assembled equilibrium structures, such as three-dimensional crystals or ordered monolayers, form as a result of the interactions of the constituents. Other structures can be achieved by imposing forces (fields) and/or boundary conditions, which Whitesides termed "self-organization". Here, we demonstrate contact line pinning on locally curved surfaces (i.e., a self-assembled monolayer of SiO2 colloidal particles) as a boundary condition to create extended arrays of uniform rings of Au nanoparticles (NPs) on the SiO2 colloids. The mechanism differs from the well-known "coffee-ring" effect; here the functionalized NPs deposit at the contact line and are not driven by evaporative transport. Thus, NP ring formation depends on the hydrophobicity and wetting of the SiO2 colloids by the chloroform solution, ligands on the NPs, and temperature. The NP rings exhibit size scaling behavior, maintaining a constant ratio of NP ring-to-colloid diameter (from 300 nm to 2 μm). The resultant high-quality NP ring structures are expected to have interesting photonic properties.

  10. 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.

  11. 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.

  12. 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.

  13. Self-Organization of Aging in a Modified Penna Model

    NASA Astrophysics Data System (ADS)

    Kim, Gi Ok; Shim, Sugie

    The Penna model for biological aging is modified so that the fertility of each individual is determined by means of the number of activated mutations at that time. A new concept of "good" mutation, which makes an individual to mature enough to reproduce, is introduced. It is assumed that each individual can reproduce only during adulthood, which is determined by the number of activated mutations. The results of Monte Carlo calculations using the modified model show that the ranges of the reproductive age are broadened as time goes by, thus showing self-organization in the biological aging to the direction of the maximum self-conservation. In addition, the population, the survival rate, and the average life span were calculated and analyzed by changing the number of new mutations at birth. It is observed that the higher is the considered number of new mutations at birth, the shorter is the obtained average life span. The mortality functions are also calculated and they showed the exponential increase in adulthood, satisfying the Gompertz law.

  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. 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

    2016-05-04

    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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. Optimization via intermittency with a self-organizing neural network.

    PubMed

    Kwok, Terence; Smith, Kate A

    2005-11-01

    One of the major obstacles in using neural networks to solve combinatorial optimization problems is the convergence toward one of the many local minima instead of the global minima. In this letter, we propose a technique that enables a self-organizing neural network to escape from local minima by virtue of the intermittency phenomenon. It gives rise to novel search dynamics that allow the system to visit multiple global minima as meta-stable states. Numerical experiments performed suggest that the phenomenon is a combined effect of Kohonen-type competitive learning and the iterated softmax function operating near bifurcation. The resultant intermittent search exhibits fractal characteristics when the optimization performance is at its peak in the form of 1/f signals in the time evolution of the cost, as well as power law distributions in the meta-stable solution states. TheN-Queens problem is used as an example to illustrate the meta-stable convergence process that sequentially generates, in a single run, 92 solutions to the 8-Queens problem and 4024 solutions to the 17-Queens problem.

  1. 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.

  2. Modularity and Self-Organized Functional Architectures in the Brain

    NASA Astrophysics Data System (ADS)

    Iyer, Laxmi; Minai, Ali A.; Doboli, Simona; Brown, Vincent R.

    It is generally believed that cognition involves the self-organization of coherent dy- namic functional networks across several brain regions in response to incoming stimulus and internal modulation. These context-dependent networks arise continually from the spatiotemporally multi-scale structural substrate of the brain configured by evolution, development and previous experience, persisting for 100-200 ms and generating re- sponses such as imagery, recall and motor action. In the current paper, we show that a system of interacting modular attractor networks can use a selective mechanism for assembling functional networks from the modular substrate. We use the approach to develop a model of idea-generation in the brain. Ideas are modeled as combinations of concepts organized in a recurrent network that reflects previous associations between them. The dynamics of this network, resulting in the transient co-activation of concept groups, is seen as a search through the space of ideas, and attractor dynamics is used to "shape" this search. The process is required to encompass both rapid retrieval of old ideas in familiar contexts and efficient search for novel ones in unfamiliar situations (or during brainstorming). The inclusion of an adaptive modulatory mechanism allows the network to balance the competing requirements of exploiting previous learning and exploring new possibilities as needed in different contexts.

  3. 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.

  4. 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.

  5. 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

  6. Optimization via intermittency with a self-organizing neural network.

    PubMed

    Kwok, Terence; Smith, Kate A

    2005-11-01

    One of the major obstacles in using neural networks to solve combinatorial optimization problems is the convergence toward one of the many local minima instead of the global minima. In this letter, we propose a technique that enables a self-organizing neural network to escape from local minima by virtue of the intermittency phenomenon. It gives rise to novel search dynamics that allow the system to visit multiple global minima as meta-stable states. Numerical experiments performed suggest that the phenomenon is a combined effect of Kohonen-type competitive learning and the iterated softmax function operating near bifurcation. The resultant intermittent search exhibits fractal characteristics when the optimization performance is at its peak in the form of 1/f signals in the time evolution of the cost, as well as power law distributions in the meta-stable solution states. TheN-Queens problem is used as an example to illustrate the meta-stable convergence process that sequentially generates, in a single run, 92 solutions to the 8-Queens problem and 4024 solutions to the 17-Queens problem. PMID:16156935

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

    PubMed

    Ren, Minglun; Hu, Zhongfeng; Jain, Hemant

    2016-01-01

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

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Chapter 24: Computational modeling of self-organized spindle formation.

    PubMed

    Schaffner, Stuart C; José, Jorge V

    2008-01-01

    In this chapter, we provide a derivation and computational details of a biophysical model we introduced to describe the self-organized mitotic spindle formation properties in the chromosome dominated pathway studied in Xenopus meiotic extracts. The mitotic spindle is a biological structure composed of microtubules. This structure forms the scaffold on which mitosis and cytokinesis occurs. Despite the seeming mechanical simplicity of the spindle itself, its formation and the way in which it is used in mitosis and cytokinesis is complex and not fully understood. Biophysical modeling of a system as complex as mitosis requires contributions from biologists, biochemists, mathematicians, physicists, and software engineers. This chapter is written for biologists and biochemists who wish to understand how biophysical modeling can complement a program of biological experimentation. It is also written for a physicist, computer scientist, or mathematician unfamiliar with this class of biological physics model. We will describe how we built such a mathematical model and its numerical simulator to obtain results that agree with many of the results found experimentally. The components of this system are large enough to be described in terms of coarse-grained approximations. We will discuss how to properly model such systems and will suggest effective tradeoffs between reliability, simulation speed, and accuracy. At all times we have in mind the realistic biophysical properties of the system we are trying to model. PMID:19118693

  14. 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

  15. 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

  16. Self-organizing maps based on limit cycle attractors.

    PubMed

    Huang, Di-Wei; Gentili, Rodolphe J; Reggia, James A

    2015-03-01

    Recent efforts to develop large-scale brain and neurocognitive architectures have paid relatively little attention to the use of self-organizing maps (SOMs). Part of the reason for this is that most conventional SOMs use a static encoding representation: each input pattern or sequence is effectively represented as a fixed point activation pattern in the map layer, something that is inconsistent with the rhythmic oscillatory activity observed in the brain. Here we develop and study an alternative encoding scheme that instead uses sparsely-coded limit cycles to represent external input patterns/sequences. We establish conditions under which learned limit cycle representations arise reliably and dominate the dynamics in a SOM. These limit cycles tend to be relatively unique for different inputs, robust to perturbations, and fairly insensitive to timing. In spite of the continually changing activity in the map layer when a limit cycle representation is used, map formation continues to occur reliably. In a two-SOM architecture where each SOM represents a different sensory modality, we also show that after learning, limit cycles in one SOM can correctly evoke corresponding limit cycles in the other, and thus there is the potential for multi-SOM systems using limit cycles to work effectively as hetero-associative memories. While the results presented here are only first steps, they establish the viability of SOM models based on limit cycle activity patterns, and suggest that such models merit further study.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. Spatial self-organization favors heterotypic cooperation over cheating.

    PubMed

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

    2013-11-12

    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.

  2. Self-organization of muscle cell structure and function.

    PubMed

    Grosberg, Anna; Kuo, Po-Ling; Guo, Chin-Lin; Geisse, Nicholas A; Bray, Mark-Anthony; Adams, William J; Sheehy, Sean P; Parker, Kevin Kit

    2011-02-01

    The organization of muscle is the product of functional adaptation over several length scales spanning from the sarcomere to the muscle bundle. One possible strategy for solving this multiscale coupling problem is to physically constrain the muscle cells in microenvironments that potentiate the organization of their intracellular space. We hypothesized that boundary conditions in the extracellular space potentiate the organization of cytoskeletal scaffolds for directed sarcomeregenesis. We developed a quantitative model of how the cytoskeleton of neonatal rat ventricular myocytes organizes with respect to geometric cues in the extracellular matrix. Numerical results and in vitro assays to control myocyte shape indicated that distinct cytoskeletal architectures arise from two temporally-ordered, organizational processes: the interaction between actin fibers, premyofibrils and focal adhesions, as well as cooperative alignment and parallel bundling of nascent myofibrils. Our results suggest that a hierarchy of mechanisms regulate the self-organization of the contractile cytoskeleton and that a positive feedback loop is responsible for initiating the break in symmetry, potentiated by extracellular boundary conditions, is required to polarize the contractile cytoskeleton.

  3. 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.

  4. 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

  5. QMESH,RENUM,QPLOT. Self-Organizing Mesh Generation

    SciTech Connect

    Jones, R.E.; Schkade, A.F.

    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, RENUM or RENUM8. RENUM is applied when four-node elements are desired. Eight-node elements (with mid-size 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.

  6. 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)

  7. 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.

  8. 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.

  9. 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.

  10. Hypertrophic phenotype in cardiac cell assemblies solely by structural cues and ensuing self-organization

    PubMed Central

    Chung, Chiung-yin; Bien, Harold; Sobie, Eric A.; Dasari, Vikram; McKinnon, David; Rosati, Barbara; Entcheva, Emilia

    2011-01-01

    In vitro models of cardiac hypertrophy focus exclusively on applying “external” dynamic signals (electrical, mechanical, and chemical) to achieve a hypertrophic state. In contrast, here we set out to demonstrate the role of “self-organized” cellular architecture and activity in reprogramming cardiac cell/tissue function toward a hypertrophic phenotype. We report that in neonatal rat cardiomyocyte culture, subtle out-of-plane microtopographic cues alter cell attachment, increase biomechanical stresses, and induce not only structural remodeling, but also yield essential molecular and electrophysiological signatures of hypertrophy. Increased cell size and cell binucleation, molecular up-regulation of released atrial natriuretic peptide, altered expression of classic hypertrophy markers, ion channel remodeling, and corresponding changes in electrophysiological function indicate a state of hypertrophy on par with other in vitro and in vivo models. Clinically used antihypertrophic pharmacological treatments partially reversed hypertrophic behavior in this in vitro model. Partial least-squares regression analysis, combining gene expression and functional data, yielded clear separation of phenotypes (control: cells grown on flat surfaces; hypertrophic: cells grown on quasi-3-dimensional surfaces and treated). In summary, structural surface features can guide cardiac cell attachment, and the subsequent syncytial behavior can facilitate trophic signals, unexpectedly on par with externally applied mechanical, electrical, and chemical stimulation.—Chung, C., Bien, H., Sobie, E. A., Dasari, V., McKinnon, D., Rosati, B., Entcheva, E. Hypertrophic phenotype in cardiac cell assemblies solely by structural cues and ensuing self-organization. PMID:21084696

  11. The dynamics of marginality and self-organized criticality as a paradigm for turbulent transport

    SciTech Connect

    Newman, D.E.; Carreras, B.A.; Diamond, P.H.; Hahm, T.S.

    1995-12-31

    A general paradigm, based on the concept of self-organized criticality (SOC), for turbulent transport in magnetically confined plasmas has been recently suggested as an explanation for some of the apparent discrepancies between most theoretical models of turbulent transport and experimental observations of the transport in magnetically confined plasmas. This model describes the dynamics of the transport without relying on the underlying local fluctuation mechanisms. Computations based on a cellular automata realization of such a model have found that noise driven SOC systems can maintain average profiles that are linearly stable (submarginal) and yet are able to sustain active transport dynamics. It is also found that the dominant scales in the transport dynamics in the absence of sheared flow are system scales rather than the underlying local fluctuation scales. The addition of sheared flow into the dynamics leads to a large reduction of the system-scale transport events and a commensurate increase in the fluctuation-scale transport events needed to maintain the constant flux. The dynamics of these models and the potential ramifications for transport studies are discussed.

  12. 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

  13. 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.

  14. 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.

  15. Motivating Company Personnel by Applying the Semi-self-organized Teams Principle

    NASA Astrophysics Data System (ADS)

    Kumlander, Deniss

    The only way nowadays to improve stability of software development process in the global rapidly evolving world is to be innovative and involve professionals into projects motivating them using both material and non material factors. In this paper self-organized teams are discussed. Unfortunately not all kind of organizations can benefit directly from agile method including applying self-organized teams. The paper proposes semi-self-organized teams presenting it as a new and promising motivating factor allowing deriving many positive sides of been self-organized and partly agile and been compliant to less strict conditions for following this innovating process. The semi-self organized teams are reliable at least in the short-term perspective and are simple to organize and support.

  16. Self-Organization of Spatial Patterning in Human Embryonic Stem Cells.

    PubMed

    Deglincerti, Alessia; Etoc, Fred; Ozair, M Zeeshan; Brivanlou, Ali H

    2016-01-01

    The developing embryo is a remarkable example of self-organization, where functional units are created in a complex spatiotemporal choreography. Recently, human embryonic stem cells (ESCs) have been used to recapitulate in vitro the self-organization programs that are executed in the embryo in vivo. This represents an unique opportunity to address self-organization in humans that is otherwise not addressable with current technologies. In this chapter, we review the recent literature on self-organization of human ESCs, with a particular focus on two examples: formation of embryonic germ layers and neural rosettes. Intriguingly, both activation and elimination of TGFβ signaling can initiate self-organization, albeit with different molecular underpinnings. We discuss the mechanisms underlying the formation of these structures in vitro and explore future challenges in the field.

  17. 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

  18. Extending self-organizing particle systems to problem solving.

    PubMed

    Rodríguez, Alejandro; Reggia, James A

    2004-01-01

    Self-organizing particle systems consist of numerous autonomous, purely reflexive agents ("particles") whose collective movements through space are determined primarily by local influences they exert upon one another. Inspired by biological phenomena (bird flocking, fish schooling, etc.), particle systems have been used not only for biological modeling, but also increasingly for applications requiring the simulation of collective movements such as computer-generated animation. In this research, we take some first steps in extending particle systems so that they not only move collectively, but also solve simple problems. This is done by giving the individual particles (agents) a rudimentary intelligence in the form of a very limited memory and a top-down, goal-directed control mechanism that, triggered by appropriate conditions, switches them between different behavioral states and thus different movement dynamics. Such enhanced particle systems are shown to be able to function effectively in performing simulated search-and-collect tasks. Further, computational experiments show that collectively moving agent teams are more effective than similar but independently moving ones in carrying out such tasks, and that agent teams of either type that split off members of the collective to protect previously acquired resources are most effective. This work shows that the reflexive agents of contemporary particle systems can readily be extended to support goal-directed problem solving while retaining their collective movement behaviors. These results may prove useful not only for future modeling of animal behavior, but also in computer animation, coordinated movement control in robotic teams, particle swarm optimization, and computer games. PMID:15479544

  19. The impact of water management on watershed self-organization

    NASA Astrophysics Data System (ADS)

    Condon, Laura; Maxwell, Reed

    2014-05-01

    Temporal and spatial self-organization has been demonstrated for hydrologic variables including soil moisture, evapotranspiration and groundwater depth across many hydrologic catchments. Previous work has demonstrated that aquifers act as low pass filters, removing high frequency variability while allowing low frequency variability to pass through. While much research has focused on connections between water management and groundwater-surface water interactions, few studies have considered the impact of water management, specifically groundwater pumping and irrigation, on the scaling behavior of the natural system. We address this gap by simulating moisture dependent groundwater fed irrigation in the Little Washita Basin (Oklahoma, USA) using the fully integrated hydrologic model ParFlow-CLM. We present results from two simulations each spanning twenty years at hourly resolution, one with irrigated agriculture and one without. The model is forced with heterogeneous historical meteorological forcings and is populated with realistic land cover and subsurface units. Model results demonstrate scaling behavior for variables like latent heat flux and water table depth similar to other studies. Additionally, gridded model outputs allow for direct analysis of spatial patterns in temporal organization not possible with previous observational studies. Analysis shows clear spatial patterns in scaling. For example, water table depth and latent heat flux have the most similar scaling coefficients along the river, where groundwater and surface water are closely interacting. While scaling behavior is also observed in the irrigated agriculture scenario, there are notable differences in frequency behavior. Pumping and irrigation attenuate low frequency (inter-annual variability) while amplifying high frequency (intra-annual variability). Water management operations increase persistence in both groundwater and surface water systems and expand the spatial area where the two are

  20. 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.

  1. 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

  2. Extending self-organizing particle systems to problem solving.

    PubMed

    Rodríguez, Alejandro; Reggia, James A

    2004-01-01

    Self-organizing particle systems consist of numerous autonomous, purely reflexive agents ("particles") whose collective movements through space are determined primarily by local influences they exert upon one another. Inspired by biological phenomena (bird flocking, fish schooling, etc.), particle systems have been used not only for biological modeling, but also increasingly for applications requiring the simulation of collective movements such as computer-generated animation. In this research, we take some first steps in extending particle systems so that they not only move collectively, but also solve simple problems. This is done by giving the individual particles (agents) a rudimentary intelligence in the form of a very limited memory and a top-down, goal-directed control mechanism that, triggered by appropriate conditions, switches them between different behavioral states and thus different movement dynamics. Such enhanced particle systems are shown to be able to function effectively in performing simulated search-and-collect tasks. Further, computational experiments show that collectively moving agent teams are more effective than similar but independently moving ones in carrying out such tasks, and that agent teams of either type that split off members of the collective to protect previously acquired resources are most effective. This work shows that the reflexive agents of contemporary particle systems can readily be extended to support goal-directed problem solving while retaining their collective movement behaviors. These results may prove useful not only for future modeling of animal behavior, but also in computer animation, coordinated movement control in robotic teams, particle swarm optimization, and computer games.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Stretchable nanoparticle conductors with self-organized conductive pathways

    NASA Astrophysics Data System (ADS)

    Kim, Yoonseob; Zhu, Jian; Yeom, Bongjun; di Prima, Matthew; Su, Xianli; Kim, Jin-Gyu; Yoo, Seung Jo; Uher, Ctirad; Kotov, Nicholas A.

    2013-08-01

    electronic tunability of mechanical properties, which arise from the dynamic self-organization of the nanoparticles under stress. A modified percolation theory incorporating the self-assembly behaviour of nanoparticles gave an excellent match with the experimental data.

  8. 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.

  9. 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

  10. Criticality and Self-Organization in Atmospheric Processes

    NASA Astrophysics Data System (ADS)

    Corral, A.

    2011-12-01

    The concept of self-organized criticality (SOC) was proposed 25 years ago by Bak et al. as a non-equilibrium paradigm for the ubiquity of 1/f noise and the emergence of fractal spatial structures. Although the original ideas came from condensed-matter physics, it became clear soon that geoscience was a fertile ground for SOC, which offered an elegant explanation for the power-law distributed avalanches that characterize the occurrence of landslides, forest fires, and earthquakes, among other catastrophic phenomena. Indeed, SOC postulates a dynamics in which the system energy slowly builds up, up to a point where a local instability appears, releasing energy and propagating rapidly in space. The balance between the slow energy input and the fast dissipation leads the system towards a critical point, which ensures the scale-invariant properties. The plausibility of this mechanism, together with the coincidence between the power-law distributions in the observations and in the models, is a strong support for the SOC paradigm, although the determination of the existence of a critical point is not possible without detailed knowledge of the internal state of the system. In contrast with the opacity of the Earth crust, the atmosphere is "transparent" to many kind of observations. We explain how diverse indicators of atmospheric convection, as the size of rainfall events and the dissipation of energy in tropical cyclones (including hurricanes), are in agreement with the recent finding by Peters and Neelin about the existence of a sharp increase of tropical rainfall rate as a function of atmospheric water-vapor content, i.e., a critical-point transition which, additionally, acts as an attractor for the state of the atmosphere. This view has important implications not only for the predictability of some atmospheric processes but for the very concept of a chaotic weather. As a by-product, the influence of ocean warming on the energy of tropical cyclones can be clearly

  11. 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.

  12. Precursor events and self-organization leading to landslide triggering

    NASA Astrophysics Data System (ADS)

    Lehmann, Peter; Or, Dani

    2010-05-01

    Hillslopes often consist of many interacting soil and land-cover elements differing in hydraulic properties and mechanical strength. Intense rainfall events may result in heterogeneous distribution of hydrologic loading and internal weakening leading to local failure and stress redistribution to neighboring intact units. For certain spatial distributions of hydro-mechanical properties and timing of local failure events, ‘local' failure may propagate across the entire system culminating in landslide release (a ‘global' failure). Such ‘global' event is often preceded by numerous small precursor events (local failures) that theoretically may contain statistical information regarding imminent ‘global' failure and thus could provide certain early warning. We model the system and precursor events by combining concepts of Self-Organized Criticality (SOC) and Fiber Bundle Models (FBM) in a physically-based hydro-mechanical framework. The model consists of hexagonal soil columns connected by fiber bundles at their base and between adjacent elements. Fiber bundles represent mechanical bonds made of numerous connections (fibers) representing friction, roots, cementing agents, water bridges and alike that impart soil strength. Hydrological pathways and load distribution are simulated enabling updating of stresses on fiber bundles. When a bundle fails at element base, stress is redistributed to adjacent connected elements which may initiate a cascade of failures similar to other SOC models (e.g. sand pile model). Increasing hydro-mechanical loads during a rainfall event results in gradual small local fiber failures whose statistics follow a power-law with exponent depending on proximity to global failure. Such state-dependent precursor event statistics could provide a physical basis for field monitoring networks for early warning and hazard prediction. Additionally, the SOC concepts provide a simple framework for landslide susceptibility mapping in space and time and

  13. Self-organization in cathode boundary layer microdischarges

    NASA Astrophysics Data System (ADS)

    Schoenbach, Karl H.; Moselhy, Mohamed; Shi, Wenhui

    2004-02-01

    Direct current glow discharges in xenon between a flat, 100 µm thin cathode and a ring shaped anode, separated by a distance of 250 µm, were found to be stable up to atmospheric pressure. The glow discharge structure in this electrode configuration reduces to only the cathode fall and negative glow, with the negative glow plasma serving to conduct the current radially to the circular anode. Photographs taken in the visible range of the spectrum and at the wavelength of excimer emission for xenon (172 nm) indicate the transition from a homogeneous plasma to a structured plasma when the current is reduced beyond a critical value that is dependent on pressure. The plasma pattern consists of filamentary structures arranged in concentric circles. The structures are most pronounced at pressures below 200 Torr and become less regular when the pressure is increased. The self-organization of such plasmas indicates the existence of two branches of the voltage-current density (V-J) characteristic with positive slope. For conventional glow discharges in the current range of interest (milliampere), the only discharge mode with a positive slope of the V-J characteristic is the abnormal glow mode. At a critical current density, the discharge transfers from the abnormal glow into an arc. However, by cooling the cathode, it seems to be possible to stabilize the discharge, even in the glow-to-arc transition range. This second stable region in the V-J characteristic of such 'cathode boundary layer discharges' would explain the existence of a plasma pattern with two distinct values of current density at the same discharge voltage.

  14. 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.

  15. 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.

  16. Hypothesis of self-organized criticality and non double couple seismic sources

    NASA Astrophysics Data System (ADS)

    Yunga, S.; Lutikov, A.

    2009-04-01

    events in much the same way that it is applied to ‘avalanches'. We suggest that observed NDC events should be studied in terms of SOC methodology. Indeed, in the terms of SOC these NDC events treated as non-steady deformation may be taken as examples of chaotic flows in nature. We can further extend outlined above model and suggest that faults play a role similar to role played by slider blocks in the SOC model of seismicity. A wide variety of slider-block models can exhibit classic chaotic behavior as these have been reviewed by Turcotte (1999; Phys. Ea. Pl. Int., 111, 275-293). In these models, the slip of one fault plane could lead to the instability of either or both of the adjacent blocks, which would then be allowed to slip in a subsequent step or steps, until all blocks were again stable. As the redistribution involves only nearest neighbor blocks, it is a cellular-automata model. Redistribution can lead to further instabilities with the possibility of an ‘avalanche' of slip events. Thus NDC event related with simultaneous complex faulting may be treated in terms of SOC as seismic ‘avalanche'. Self-organized criticality may be realized only if the heterogeneity is high enough. To some extent, notions of heterogeneity and chaotization seem to be closely linked. The case then probability of simultaneous slidings of all faults in cluster becomes very high is a classic example of critical point behavior typical for percolation model, forest-fire model, multiplicative cascade model and other models that exhibit self-organized critical behavior. Acknowledgments. The USGS and Harvard University kindly provided access to their centroid-moment tensor data. This work was partly supported by RFBR, № 07-05-00436.

  17. 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

  18. 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.

  19. Modeling substorm dynamics of the magnetosphere: from self-organization and self-organized criticality to nonequilibrium phase transitions.

    PubMed

    Sitnov, M I; Sharma, A S; Papadopoulos, K; Vassiliadis, D

    2002-01-01

    Earth's magnetosphere during substorms exhibits a number of characteristic features such as the signatures of low effective dimension, hysteresis, and power-law spectra of fluctuations on different scales. The largest substorm phenomena are in reasonable agreement with low-dimensional magnetospheric models and in particular those of inverse bifurcation. However, deviations from the low-dimensional picture are also quite considerable, making the nonequilibrium phase transition more appropriate as a dynamical analog of the substorm activity. On the other hand, the multiscale magnetospheric dynamics cannot be limited to the features of self-organized criticality (SOC), which is based on a class of mathematical analogs of sandpiles. Like real sandpiles, during substorms the magnetosphere demonstrates features, that are distinct from SOC and are closer to those of conventional phase transitions. While the multiscale substorm activity resembles second-order phase transitions, the largest substorm avalanches are shown to reveal the features of first-order nonequilibrium transitions including hysteresis phenomena and a global structure of the type of a temperature-pressure-density diagram. Moreover, this diagram allows one to find a critical exponent, that reflects the multiscale aspect of the substorm activity, different from the power-law frequency and scale spectra of autonomous systems, although quite consistent with second-order phase transitions. In contrast to SOC exponents, this exponent relates input and output parameters of the magnetosphere. Using an analogy to the dynamical Ising model in the mean-field approximation, we show the connection between the data-derived exponent of nonequilibrium transitions in the magnetosphere and the standard critical exponent beta of equilibrium second-order phase transitions.

  20. 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

  1. 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

  2. Self-organization with equilibration: A model for the intermediate phase in rigidity percolation

    NASA Astrophysics Data System (ADS)

    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 [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.

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

    PubMed

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

    2014-01-01

    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.

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

    DOE PAGES

    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.

  5. 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.

  6. 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

  7. The missing modes of self-organization in cathode boundary layer discharge in xenon

    NASA Astrophysics Data System (ADS)

    Zhu, WeiDong; Niraula, Prajwal

    2014-10-01

    Self-organized pattern formation has been previously observed in cathode boundary layer discharges (CBLDs) in high-purity xenon gas at pressures ranging from about 60 Torr to atmospheric pressure. However, certain modes predicted by the COMSOL multiphysics simulation were never observed. In this paper, using the same reactor design, we managed to fine tune the discharge current into regions that were not fully explored before. Two new self-organized patterns were observed, at the verge of the extinguishing of the self-organization. One pattern was a perfect ring that was detached from the dielectric walls. The other pattern was a series elongated spots arranged along a circle. Both patterns were preferably observed at pressures ranging from 60 to 120 Torr. The observation of these patterns may open up new discussions to the self-organized pattern formation in CBLD in xenon.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. Self-organization, the cascade model, and natural hazards

    PubMed Central

    Turcotte, Donald L.; Malamud, Bruce D.; Guzzetti, Fausto; Reichenbach, Paola

    2002-01-01

    We consider the frequency-size statistics of two natural hazards, forest fires and landslides. Both appear to satisfy power-law (fractal) distributions to a good approximation under a wide variety of conditions. Two simple cellular-automata models have been proposed as analogs for this observed behavior, the forest fire model for forest fires and the sand pile model for landslides. The behavior of these models can be understood in terms of a self-similar inverse cascade. For the forest fire model the cascade consists of the coalescence of clusters of trees; for the sand pile model the cascade consists of the coalescence of metastable regions. PMID:11875206

  13. Self-organization in Systems ofTreadmilling Filaments.

    NASA Astrophysics Data System (ADS)

    Doubrovinski, Konstantin; Kruse, Karsten

    2009-03-01

    The cytoskeleton is an active intracellular network of polar filaments responsible for maintenance of cell shape, cell division, and cell locomotion. A broad variety of cellular processes depend critically on the ability of cyoskeletal filaments to treadmill, i.e. to move by growing at one end while simultaneously shrinking at the other end. In particular, treadmilling is indispensable for cell crawling as well as for generation of various cellular appendages including stereocilia, microvilli, and filipodia. Quantitative modeling of systems involving treadmilling filaments is challenging since it requires describing long-range interactions of particles with many degrees of freedom. We introduce a novel framework for describing systems of treadilling filaments. Within our framework, we identify a class of systems that admit exact solution of the underlying dynamic equations. We compare the corresponding solutions to those obtained by coarse-graining, an approximation which is valid on large length-scales. We apply our new framework to treat two biological systems: cytoskeletal dynamics in fish melanophores and locomotion of human neutrophil cells. In both cases our theory faithfully accounts for the qualitative and semi-quantitative properties of the intracellular structures observed in the corresponding experiments.

  14. 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.

  15. 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).

  16. 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.

  17. 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.

  18. 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

  19. Mechanisms of self-organization and finite size effects in a minimal agent based model

    NASA Astrophysics Data System (ADS)

    Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

    2009-03-01

    We present a detailed analysis of the self-organization phenomenon in which the stylized facts originate from finite size effects with respect to the number of agents considered and disappear in the limit of an infinite population. By introducing the possibility that agents can enter or leave the market depending on the behavior of the price, it is possible to show that the system self-organizes in a regime with a finite number of agents which corresponds to the stylized facts. The mechanism for entering or leaving the market is based on the idea that a too stable market is unappealing for traders, while the presence of price movements attracts agents to enter and speculate on the market. We show that this mechanism is also compatible with the idea that agents are scared by a noisy and risky market at shorter timescales. We also show that the mechanism for self-organization is robust with respect to variations of the exit/entry rules and that the attempt to trigger the system to self-organize in a region without stylized facts leads to an unrealistic dynamics. We study the self-organization in a specific agent based model but we believe that the basic ideas should be of general validity.

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

    PubMed

    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.

  1. 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

  2. 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.

  3. 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

  4. Adolescent self-organization predicts midlife memory in a prospective birth cohort study.

    PubMed

    Xu, Man K; Jones, Peter B; Barnett, Jennifer H; Gaysina, Darya; Kuh, Diana; Croudace, Tim J; Richards, Marcus

    2013-12-01

    Childhood and adolescent mental health have a lasting impact on adult life chances, with strong implications for subsequent health, including cognitive aging. Using the British 1946 birth cohort, the authors tested associations between adolescent conduct problems, emotional problems and aspects of self-organization, and verbal memory at 43 years and rate of decline in verbal memory from 43 to 60-64 years. After controlling for childhood intelligence, adolescent self-organization was positively associated with verbal memory at 43 years, mainly through educational attainment, although not with rate of memory decline. Associations between adolescent conduct and emotional problems and future memory were of negligible magnitude. It has been suggested that interventions to improve self-organization may save a wide range of societal costs; this study also suggests that this might also benefit cognitive function in later life. PMID:24364401

  5. Model of multi-modal cortical processing: coherent learning in self-organizing modules.

    PubMed

    Ménard, Olivier; Frezza-Buet, Hervé

    2005-01-01

    In this paper (An abbreviated version of some portions of this article appeared in reference Menard and Frezza-Buet (Menard, O., & Frezza-Buet, H. (2004). Rewarded multi-modal neuronal self-organization: Example of the arm reaching movement. In: Proceedings of international conference on advances in intelligent systems theory and application.), as part of the IJCNN 2005 conference proceedings, published under the IEEE copyright.), an original self-organizing model is presented, with experiments highlighting its ability to be used in different frameworks, as phonetic coding dependent on semantics and arm-reaching. The model relies on the coupling of the learning processes that stand at different self-organizing modules, and exhibits dynamics that can be discussed in terms of the binding of different modalities, scattered over the different modules. Such a binding property is based on an emerging constraint of keeping consistency between the modules. This process is induced by partial connectivity and appropriate neural field competition mechanisms.

  6. Origin and evolution of the self-organizing cytoskeleton in the network of eukaryotic organelles.

    PubMed

    Jékely, Gáspár

    2014-09-02

    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.

  7. 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.

  8. Spatial fluctuations of pedestrian velocities in bidirectional streams: Exploring the effects of self-organization

    NASA Astrophysics Data System (ADS)

    Saberi, Meead; Aghabayk, Kayvan; Sobhani, Amir

    2015-09-01

    Individual pedestrian velocities vary over time and space depending on the crowd size, location of individuals' within the crowd, and formation of self-organized lanes. We use empirical data to explore the spatial fluctuations of pedestrian velocities in bidirectional streams. We find that, unlike ordinary fluids, the velocity profile in bidirectional pedestrian streams does not necessarily follow a hyperbolic form. Rather, the shape of the velocity profile is highly dependent on the formation of self-organized lanes. We also show that the spatial fluctuations of pedestrian velocities along and transverse to the flow direction are widely distributed and can be modeled by a sum of Gaussian distributions. Results suggest that the effect of self-organization phenomenon is strong enough that for the same crowd size, the velocity distribution does not significantly change when pedestrians are highly mixed compared to when separate lanes are formed.

  9. 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

  10. Tilt aftereffects in a self-organizing model of the primary visual cortex.

    PubMed

    Bednar, J A; Miikkulainen, R

    2000-07-01

    RF-LISSOM, a self-organizing model of laterally connected orientation maps in the primary visual cortex, was used to study the psychological phenomenon known as the tilt aftereffect. The same self-organizing processes that are responsible for the long-term development of the map are shown to result in tilt aftereffects over short timescales in the adult. The model permits simultaneous observation of large numbers of neurons and connections, making it possible to relate high-level phenomena to low-level events, which is difficult to do experimentally. The results give detailed computational support for the long-standing conjecture that the direct tilt aftereffect arises from adaptive lateral interactions between feature detectors. They also make a new prediction that the indirect effect results from the normalization of synaptic efficacies during this process. The model thus provides a unified computational explanation of self-organization and both the direct and indirect tilt aftereffect in the primary visual cortex.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. The Imbalance and Self-Organization in the Earth's Climate System (Invited)

    NASA Astrophysics Data System (ADS)

    Maslov, L.

    2013-12-01

    The increase in frequency and severity of storms, hurricanes and other atmospheric phenomena indicates a progressive imbalance in all planetary systems. Study of the temperature curve obtained from the Antarctic ice core showed that this data can be considered as a sum of two components: the 'cyclic' component and the 'stochastic' component, representing two different but tightly interconnected processes. The 'cyclic' and the 'stochastic' components represent two different types of self-organization of the Earth's climate system. The self-organization in the 'cyclic' process is a non-linear reaction of the Earth's climate system, as a whole, to the input of solar radiation. The self-organization in the 'stochastic' part is a self-organized nonlinear critical process, taking energy from, and fluctuating around the 'cyclic' part of the temperature variations. As a whole, the Earth's climate can be characterized as a nonlinear, self-organized, dynamic system with two levels of self-organization. This research can shed some light on the global climate imbalance and help us to understand the current trends in global weather and to predict global weather trends in the distant and not so distant future. First of all, global warming, as can be seen in repeated high temperature spikes in temperature cycles, has happened in every past climate cycle. The present interglacial period lasts a little bit longer than previous similar periods. This can be because of additional warming caused by human industrial activity. But, following the 'cyclic' pattern of glacial and interglacial temperature cycles, one can conclude that we are at the very beginning of a gradual cooling period to temperatures below freezing. This process is accompanied by sharp and intense fluctuations of temperature, represented by the 'stochastic' part of global temperature curve. Atmospheric temperature fluctuations are the direct result, and at the same time, a cause of atmospheric imbalance. It is

  17. 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

  18. 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

  19. Tuning self-organized O/Cu(110) nanostructures by co-adsorption of sulfur

    NASA Astrophysics Data System (ADS)

    Wiame, Frédéric; Poulain, Clément; Budinská, Zuzana; Maurice, Vincent; Marcus, Philippe

    2015-06-01

    A method for tuning the nanostructures formed by self-organized growth of oxygen on Cu(110) surface is proposed. It is shown that the range of possible nanostructures, consisting in alternating stripes of bare and oxidized copper, can largely be extended by the co-adsorption of sulfur. The classical Marchenko-Vanderbilt model describing the nanostructuration was generalized in order to take into account the change in the surface properties induced by the presence of sulfur. This modified model enabled us to infer the expressions of the periodicity and width of the self-organized stripes as a function of the sulfur and oxygen coverages.

  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.

  2. 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…

  3. 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.

  4. Phonons as probes in self-organized SiGe islands

    NASA Astrophysics Data System (ADS)

    Groenen, J.; Carles, R.; Christiansen, S.; Albrecht, M.; Dorsch, W.; Strunk, H. P.; Wawra, H.; Wagner, G.

    1997-12-01

    We show how optical phonons can be used as efficient probes in self-organized Si1-xGex islands grown on Si(001). Both the alloy composition and residual strain in the islands were originally determined from the phonon frequencies and Raman intensities. The experimental results are in good agreement with the strain relaxation simulated by means of the finite element method.

  5. 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

  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. 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.

  8. 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.

  9. 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...

  10. Self-organizing neural networks integrating domain knowledge and reinforcement learning.

    PubMed

    Teng, Teck-Hou; Tan, Ah-Hwee; Zurada, Jacek M

    2015-05-01

    The use of domain knowledge in learning systems is expected to improve learning efficiency and reduce model complexity. However, due to the incompatibility with knowledge structure of the learning systems and real-time exploratory nature of reinforcement learning (RL), domain knowledge cannot be inserted directly. In this paper, we show how self-organizing neural networks designed for online and incremental adaptation can integrate domain knowledge and RL. Specifically, symbol-based domain knowledge is translated into numeric patterns before inserting into the self-organizing neural networks. To ensure effective use of domain knowledge, we present an analysis of how the inserted knowledge is used by the self-organizing neural networks during RL. To this end, we propose a vigilance adaptation and greedy exploitation strategy to maximize exploitation of the inserted domain knowledge while retaining the plasticity of learning and using new knowledge. Our experimental results based on the pursuit-evasion and minefield navigation problem domains show that such self-organizing neural network can make effective use of domain knowledge to improve learning efficiency and reduce model complexity.

  11. 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…

  12. 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.

  13. Speculation about Behavior, Brain Damage, and Self-Organization: The Other Way to Herd a Cat

    ERIC Educational Resources Information Center

    Colangelo, Annette; Holden, John G.; Buchanan, Lori; Van Orden, Guy C.

    2004-01-01

    This article contrasts aphasic patients' performance of word naming and lexical decision with that of intact college-aged readers. We discuss this contrast within a framework of self-organization; word recognition by aphasic patients is destabilized relative to intact performance. Less stable performance shows itself as an increase in the…

  14. Self-organization of a hybrid nanostructure consisting of a nanoneedle and nanodot.

    PubMed

    Liu, Hai; Wu, Junsheng; Wang, Ying; Chow, Chee Lap; Liu, Qing; Gan, Chee Lip; Tang, Xiaohong; Rawat, Rajdeep Singh; Tan, Ooi Kiang; Ma, Jan; Huang, Yizhong

    2012-09-24

    A special materials system that allows the self-organization of a unique hybrid nanonipple structure is developed. The system consists of a nanoneedle with a small nanodot sitting on top. Such hybrid nanonipples provide building blocks to assemble functional devices with significantly improved performance. The application of the system to high-sensitivity gas sensors is also demonstrated.

  15. 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.

  16. 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:

  17. Simplified tandem polymer solar cells with an ideal self-organized recombination layer.

    PubMed

    Kang, Hongkyu; Kee, Seyoung; Yu, Kilho; Lee, Jinho; Kim, Geunjin; Kim, Junghwan; Kim, Jae-Ryoung; Kong, Jaemin; Lee, Kwanghee

    2015-02-25

    A new tandem architecture for printable photovoltaics using a versatile organic nanocomposite containing photoactive and interfacial materials is demonstrated. The nanocomposite forms an ideal self-organized recombination layer via a spontaneous vertical phase separation, which yields a simplified tandem structure fabricated with only four component layers and a high tandem efficiency of 10.8%. PMID:25449142

  18. Periodic Phenomena In Laser-Ablation Plasma Plumes: A Self-Organization Scenario

    SciTech Connect

    Gurlui, S.; Sanduloviciu, M.; Mihesan, C.; Ziskind, M.; Focsa, C.

    2006-01-15

    Experimental evidence of the appearance of a proper periodic dynamics in a plasma plume created by pulsed laser ablation is considered as a hint for the presence of a self-organization scenario that explains similar phenomena observed in plasma diodes.

  19. Self-Organization and the Self-Assembling Process in Tissue Engineering

    PubMed Central

    Eswaramoorthy, Rajalakshmanan; Hadidi, Pasha; Hu, Jerry C.

    2015-01-01

    In recent years, the tissue engineering paradigm has shifted to include a new and growing subfield of scaffoldless techniques which generate self-organizing and self-assembling tissues. This review aims to provide a cogent description of this relatively new research area, with special emphasis on applications toward clinical use and research models. Particular emphasis is placed on providing clear definitions of self-organization and the self-assembling process, as delineated from other scaffoldless techniques in tissue engineering and regenerative medicine. Significantly, during formation, self-organizing and self-assembling tissues display biological processes similar to those that occur in vivo. These help lead to the recapitulation of native tissue morphological structure and organization. Notably, functional properties of these tissues also approach native tissue values; some of these engineered tissues are already in clinical trials. This review aims to provide a cohesive summary of work in this field, and to highlight the potential of self-organization and the self-assembling process to provide cogent solutions to current intractable problems in tissue engineering. PMID:23701238

  20. 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.

  1. Simplified tandem polymer solar cells with an ideal self-organized recombination layer.

    PubMed

    Kang, Hongkyu; Kee, Seyoung; Yu, Kilho; Lee, Jinho; Kim, Geunjin; Kim, Junghwan; Kim, Jae-Ryoung; Kong, Jaemin; Lee, Kwanghee

    2015-02-25

    A new tandem architecture for printable photovoltaics using a versatile organic nanocomposite containing photoactive and interfacial materials is demonstrated. The nanocomposite forms an ideal self-organized recombination layer via a spontaneous vertical phase separation, which yields a simplified tandem structure fabricated with only four component layers and a high tandem efficiency of 10.8%.

  2. 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…

  3. 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

  4. 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.

  5. 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)

  6. 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.

  7. Self-organized nanoporous materials for chemical separations and chemical sensing

    NASA Astrophysics Data System (ADS)

    Pandey, Bipin

    Self-organized nanoporous materials have drawn a lot of attention because the uniform, highly dense, and ordered cylindrical nanopores in these materials provide a unique platform for chemical separations and chemical sensing applications. Here, we explore self-organized nanopores of PS-b-PMMA diblock copolymer thin films and anodic gallium oxide for chemical separations and sensing applications. In the first study, cyclic voltammograms of cytochrome c on recessed nanodisk-array electrodes (RNEs) based on nanoporous films (11, 14 or 24 nm in average pore diameter; 30 nm thick) derived from polystyrene-poly(methylmethacrylate) diblock copolymers were measured. The faradic current of cytochrome c was observed on RNEs, indicating the penetration of cytochrome c (hydrodynamic diameter ≈ 4 nm) through the nanopores to the underlying electrodes. Compared to the 24-nm pores, the diffusion of cytochrome c molecules through the 11- and 14-nm pores suffered significantly larger hindrance. The results reported in this study will provide guidance in designing RNEs for size-based chemical sensing and also for controlled immobilization of biomolecules within nanoporous media for biosensors and bioreactors. In another study, conditions for the formation of self-organized nanopores of a metal oxide film were investigated. Self-organized nanopores aligned perpendicular to the film surface were obtained upon anodization of gallium films in ice-cooled 4 and 6 M aqueous H2SO4 at 10 V and 15 V. The average pore diameter was in the range of 18 ~ 40 nm, and the anodic gallium oxide was ca. 2 microm thick. In addition, anodic formation of self-organized nanopores was demonstrated for a solid gallium monolith incorporated at the end of a glass capillary. Nanoporous anodic oxide monoliths formed from a fusible metal will lead to future development of unique devices for chemical sensing and catalysis. In the final study, surface chemical property of self-organized nanoporous anodic gallium

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. An evolutionary algorithm for global optimization based on self-organizing maps

    NASA Astrophysics Data System (ADS)

    Barmada, Sami; Raugi, Marco; Tucci, Mauro

    2016-10-01

    In this article, a new population-based algorithm for real-parameter global optimization is presented, which is denoted as self-organizing centroids optimization (SOC-opt). The proposed method uses a stochastic approach which is based on the sequential learning paradigm for self-organizing maps (SOMs). A modified version of the SOM is proposed where each cell contains an individual, which performs a search for a locally optimal solution and it is affected by the search for a global optimum. The movement of the individuals in the search space is based on a discrete-time dynamic filter, and various choices of this filter are possible to obtain different dynamics of the centroids. In this way, a general framework is defined where well-known algorithms represent a particular case. The proposed algorithm is validated through a set of problems, which include non-separable problems, and compared with state-of-the-art algorithms for global optimization.

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

    PubMed

    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.

  15. 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.

  16. Self-organization of the Earth's climate system versus Milankovitch-Berger astronomical cycles

    NASA Astrophysics Data System (ADS)

    Maslov, Lev A.

    2014-09-01

    The Late Pleistocene Antarctic temperature variation curve is decomposed into two components: "cyclic" and "high frequency, stochastic." For each of these components, a mathematical model is developed which shows that the cyclic and stochastic temperature variations are distinct, but interconnected, processes with their own self-organization. To model the cyclic component, a system of ordinary differential equations is written which represent an auto-oscillating, self-organized process with constant period. It is also shown that these equations can be used to model more realistic variations in temperature with changing cycle length. For the stochastic component, the multifractal spectrum is calculated and compared to the multifractal spectrum of a critical sine-circle map. A physical interpretation of relevant mathematical models and discussion of future climate development within the context of this work is given.

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

    PubMed

    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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

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

    SciTech Connect

    Randall A. Laviolette

    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.

  3. 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.

  4. Self-organization of triblock copolymer patterns obtained by drying and dewetting

    NASA Astrophysics Data System (ADS)

    Carvalho, A. J. F.; Pereira-da-Silva, M. A.; Faria, R. M.

    2006-07-01

    Self-organized block copolymer structures derived from dewetting of thin films are becoming important in nanotechnology because of the various spontaneous and regular sub-micrometric surface patterns that may be obtained. Here, we report on the self-organization of a poly(styrene)-b-poly(ethene-co-butene-1)-b-poly(styrene) triblock copolymer during drying of its solution over a mica substrate. Regular submicrometric arrangements with long-range order were formed at critical polymer concentrations, consisting of parallel ribbons and hexagonal arrays of dots (droplets). This variety of highly ordered structures is explained by the interplay between forming mechanisms, mainly due to “fingering instabilities” at the three-phase line of the copolymer solution during drying. The thickness of the structures was “quantized” due to the microphase separation of the block copolymer. The formation of hexagonal patterns may be attributed to Marangoni instability at the liquid film surface prior to dewetting.

  5. Self-organized ferromagnetic nanowires in MgO-based magnetic tunnel junctions

    NASA Astrophysics Data System (ADS)

    Seike, Masayoshi; Fukushima, Tetsuya; Sato, Kazunori; Katayama-Yoshida, Hiroshi

    2013-08-01

    The focus of this study is to examine the distribution of defects and defect-induced properties in MgO-based magnetic tunnel junctions (MTJs). To this end, first-principles calculations were performed to estimate the electronic structures and total energies of MgO with various defects by using the Heyd-Scuseria-Ernzerhof (HSE06) hybrid functional. From connections drawn between the calculated results and previously reported experimental data, we propose that self-organized ferromagnetic nanowires of magnesium vacancies can be formed in MgO-based MTJs. This self-organization may provide the foundation for a comprehensive understanding of the conductivity, tunnel barriers and quantum oscillations of MgO-based MTJs. Further experimental verification is needed before firm conclusions can be drawn.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    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.

  7. 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.

  8. Supramolecular [60]fullerene liquid crystals formed by self-organized two-dimensional crystals.

    PubMed

    Zhang, Xiaoyan; Hsu, Chih-Hao; Ren, Xiangkui; Gu, Yan; Song, Bo; Sun, Hao-Jan; Yang, Shuang; Chen, Erqiang; Tu, Yingfeng; Li, Xiaohong; Yang, Xiaoming; Li, Yaowen; Zhu, Xiulin

    2015-01-01

    Fullerene-based liquid crystalline materials have both the excellent optical and electrical properties of fullerene and the self-organization and external-field-responsive properties of liquid crystals (LCs). Herein, we demonstrate a new family of thermotropic [60]fullerene supramolecular LCs with hierarchical structures. The [60]fullerene dyads undergo self-organization driven by π-π interactions to form triple-layer two-dimensional (2D) fullerene crystals sandwiched between layers of alkyl chains. The lamellar packing of 2D crystals gives rise to the formation of supramolecular LCs. This design strategy should be applicable to other molecules and lead to an enlarged family of 2D crystals and supramolecular liquid crystals.

  9. 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.

  10. From self-organization to emergence: Aesthetic implications of shifting ideas of organization

    SciTech Connect

    Hayles, N.K.

    1996-06-01

    From 1945{endash}95, a shift took place within cybernetics from a paradigm emphasizing self-organization to one emphasizing emergence. Central in bringing about this shift was the spread of the microcomputer. With its greatly enhanced processing speed and memory capabilities, the microcomputer made simulations possible that could not have been done before. The microcomputer has also been instrumental in effecting a similar change within literary texts. To exemplify the aesthetic implications of the shift from self-organization to emergence, the chapter discusses Vladmir Nabokov{close_quote}s {ital Pale} {ital Fire} and Milorad Pavi{acute c}{close_quote}s {ital Dictionary} {ital of} {ital the} {ital Khazars}: {ital A} {ital Lexicon} {ital Novel} {ital in} 100,000 {ital Words}. {copyright} {ital 1996 American Institute of Physics.}

  11. 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.

  12. Self-organized criticality effect on stability: magneto-thermal oscillations in a granular YBCO superconductor

    NASA Astrophysics Data System (ADS)

    Legrand, L.; Rosenman, I.; Mints, R. G.; Collin, G.; Janod, E.

    1996-05-01

    We show that the self-organized criticality of Bean's state in each of the grains of a granular superconductor results in magneto-thermal oscillations. We find that the frequency of these oscillations is proportional to the external magnetic field sweep rate dot Be and is inversely proportional to the square root of the heat capacity. We demonstrate experimentally and theoretically that this dependence is influenced mainly by the granularity of the superconductor.

  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. [Participation and integration: the self-organization theories point of view].

    PubMed

    Aleksandrowicz, Ana Maria Coutinho

    2009-10-01

    This article presents theoretical bases to facilitate participation and integration within an interdisciplinary research team. In order to achieve this, we will sketch fundamental notions related to the new conceptual field of self-organization of living beings. Subsequently, we will expose some ideas by Henri Atlan, Jean-Pierre Dupuy and Cornelius Castoriadis that are important to reach our objectives. Finally, we will suggest how to turn these principles into practice. PMID:19750370

  15. An efficient approach to the travelling salesman problem using self-organizing maps.

    PubMed

    Vieira, Frederico Carvalho; Dória Neto, Adrião Duarte; Costa, José Alfredo Ferreira

    2003-04-01

    This paper presents an approach to the well-known Travelling Salesman Problem (TSP) using Self-Organizing Maps (SOM). The SOM algorithm has interesting topological information about its neurons configuration on cartesian space, which can be used to solve optimization problems. Aspects of initialization, parameters adaptation, and complexity analysis of the proposed SOM based algorithm are discussed. The results show an average deviation of 3.7% from the optimal tour length for a set of 12 TSP instances.

  16. Neurobiologically realistic determinants of self-organized criticality in networks of spiking neurons.

    PubMed

    Rubinov, Mikail; Sporns, Olaf; Thivierge, Jean-Philippe; Breakspear, Michael

    2011-06-01

    Self-organized criticality refers to the spontaneous emergence of self-similar dynamics in complex systems poised between order and randomness. The presence of self-organized critical dynamics in the brain is theoretically appealing and is supported by recent neurophysiological studies. Despite this, the neurobiological determinants of these dynamics have not been previously sought. Here, we systematically examined the influence of such determinants in hierarchically modular networks of leaky integrate-and-fire neurons with spike-timing-dependent synaptic plasticity and axonal conduction delays. We characterized emergent dynamics in our networks by distributions of active neuronal ensemble modules (neuronal avalanches) and rigorously assessed these distributions for power-law scaling. We found that spike-timing-dependent synaptic plasticity enabled a rapid phase transition from random subcritical dynamics to ordered supercritical dynamics. Importantly, modular connectivity and low wiring cost broadened this transition, and enabled a regime indicative of self-organized criticality. The regime only occurred when modular connectivity, low wiring cost and synaptic plasticity were simultaneously present, and the regime was most evident when between-module connection density scaled as a power-law. The regime was robust to variations in other neurobiologically relevant parameters and favored systems with low external drive and strong internal interactions. Increases in system size and connectivity facilitated internal interactions, permitting reductions in external drive and facilitating convergence of postsynaptic-response magnitude and synaptic-plasticity learning rate parameter values towards neurobiologically realistic levels. We hence infer a novel association between self-organized critical neuronal dynamics and several neurobiologically realistic features of structural connectivity. The central role of these features in our model may reflect their importance for

  17. 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.

  18. An Example of Unsupervised Networks Kohonen's Self-Organizing Feature Map

    NASA Technical Reports Server (NTRS)

    Niebur, Dagmar

    1995-01-01

    Kohonen's self-organizing feature map belongs to a class of unsupervised artificial neural network commonly referred to as topographic maps. It serves two purposes, the quantization and dimensionality reduction of date. A short description of its history and its biological context is given. We show that the inherent classification properties of the feature map make it a suitable candidate for solving the classification task in power system areas like load forecasting, fault diagnosis and security assessment.

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

    PubMed

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

    2014-07-01

    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

  20. Enhanced photoluminescence from self-organized rubrene single crystal surface structures

    NASA Astrophysics Data System (ADS)

    Stöhr, R. J.; Beirne, G. J.; Michler, P.; Scholz, R.; Wrachtrup, J.; Pflaum, J.

    2010-06-01

    We report on crystalline pyramidal structures grown via self-organization on the rubrene (001) surface. The analysis of their spectral response by means of photoluminescence with micrometer lateral resolution reveals an intensity enhancement on-top of the surface structures. As we demonstrate this intensity increase can be related to the excitation processes at the molecular level in combination with exciton confinement within the pyramids.

  1. Background and principles of self-organizing jet-emulsion metallurgical unit

    NASA Astrophysics Data System (ADS)

    Tsymbal, V. P.; Kozhemyachenko, V. I.; Rybenko, I. A.; Mochalov, S. P.; Padalko, A. G.; Kalashnikov, S. N.; Krasnoperov, S. Yu; Ermakova, L. A.; Olennikov, A. A.

    2016-09-01

    The basic principles laid in the creation of a new jet-emulsion process and metallurgical unit were considered. Development of self-organizing oscillator reactor, bottom feed of the prepared in it combustible mixture to the column reactor and a large deviation from the thermodynamic equilibrium allow dissipative structure to be created, and thus control the ratio of reducing and oxidizing processes, the carbon content in the metal.

  2. Effective palette indexing for image compression using self-organization of Kohonen feature map.

    PubMed

    Pei, Soo-Chang; Chuang, Yu-Ting; Chuang, Wei-Hong

    2006-09-01

    The process of limited-color image compression usually involves color quantization followed by palette re-indexing. Palette re-indexing could improve the compression of color-indexed images, but it is still complicated and consumes extra time. Making use of the topology-preserving property of self-organizing Kohonen feature map, we can generate a fairly good color index table to achieve both high image quality and high compression, without re-indexing. Promising experiment results will be presented.

  3. Self organized growth of doped vertical quantum wells for normal incidence intersubband transitions

    NASA Astrophysics Data System (ADS)

    Berger, V.; Vermeire, G.; Demeester, P.; Weisbuch, C.

    1996-06-01

    The self-organized growth of N-doped vertical AlGaAs quantum wells by metalorganic vapor phase epitaxy of a single doped AlGaAs layer on a submicron grating is described. Intersubband absorption at normal incidence is demonstrated in those vertical quantum wells. This opens new possibilities for infrared quantum well devices using intersubband transitions, including normal incidence infrared modulators.

  4. The psychobiology of mind-body communication: the complex, self-organizing field of information transduction.

    PubMed

    Rossi, E L

    1996-01-01

    The current information revolution in molecular biology has important implications for an new understanding of the phenomenology of mind, memory and behavior as a complex, self-organizing field of information transduction. This paper traces the pathways of information transduction in life processes from the molecular-genetic level to the dynamics of mind and behavior together with suggestions for future research exploring the psychobiology of mind-body communication and its implications for the psychotherapeutic arts of the future.

  5. 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.

  6. Inhomogeneous and Self-Organized Temperature in Schelling-Ising Model

    NASA Astrophysics Data System (ADS)

    Müller, Katharina; Schulze, Christian; Stauffer, Dietrich

    The Schelling model of 1971 is a complicated version of a square-lattice Ising model at zero temperature, to explain urban segregation, based on the neighbor preferences of the residents, without external reasons. Various versions between Ising and Schelling models give about the same results. Inhomogeneous "temperatures" T do not change the results much, while a feedback between segregation and T leads to a self-organization of an average T.

  7. 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

  8. 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

  9. 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.

  10. Self-Organized Vertical Superlattices in Epitaxial GaInAsSb

    SciTech Connect

    CA Wand; CJ Vineis; DR Calawa

    2004-02-09

    Self-organized superlattices are observed in GaInAsSb epilayers grown nominally lattice matched to vicinal GaSb substrates. The natural superlattice (NSL) is detected at the onset of growth; is continuous over the lateral extent of over several microns; and persists vertically throughout several microns of the epilayer. Furthermore, the NSL is inclined by an additional 4{sup o} with respect to the vicinal (001) GaSb substrate. The tilted NSL intersects the surface of the epilayer, and the NSL period is geometrically correlated with surface undulations. While the principle driving force for this type of phase separation arises from solution thermodyamics, 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 modulations and morphological perturbations.

  11. 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

  12. 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.

  13. Electrochemical properties of honeycomb-like structured HFBI self-organized membranes on HOPG electrodes.

    PubMed

    Yamasaki, Ryota; Takatsuji, Yoshiyuki; Lienemann, Michael; Asakawa, Hitoshi; Fukuma, Takeshi; Linder, Markus; Haruyama, Tetsuya

    2014-11-01

    HFBI (derived from Trichoderma sp.) is a unique structural protein, which forms a self-organized monolayer at both air/water interface and water/solid interfaces in accurate two-dimensional ordered structures. We have taken advantage of the unique functionality of HFBI as a molecular carrier for preparation of ordered molecular phase on solid substrate surfaces. The HFBI molecular carrier can easily form ordered structures; however, the dense molecular layers form an electrochemical barrier between the electrode and solution phase. In this study, the electrochemical properties of HFBI self-organized membrane-covered electrodes were investigated. Wild-type HFBI has balanced positive and negative charges on its surface. Highly oriented pyrolytic graphite (HOPG) electrodes coated with HFBI molecules were investigated electrochemically. To improve the electrochemical properties of this HFBI-coated electrode, the two types of HFBI variants, with oppositely charged surfaces, were prepared genetically. All three types of HFBI-coated HOPG electrode perform electron transfer between the electrode and solution phase through the dense HFBI molecular layer. This is because the HFBI self-organized membrane has a honeycomb-like structure, with penetrating holes. In the cases of HFBI variants, the oppositely charged HFBI membrane phases shown opposite electrochemical behaviors in electrochemical impedance spectroscopy. HFBI is a molecule with a unique structure, and can easily form honeycomb-like structures on solid material surfaces such as electrodes. The molecular membrane phase can be used for electrochemical molecular interfaces.

  14. Nanopatterning the electronic properties of gold surfaces with self-organized superlattices of metallic nanostructures.

    PubMed

    Didiot, Clement; Pons, Stephane; Kierren, Bertrand; Fagot-Revurat, Yannick; Malterre, Daniel

    2007-10-01

    The self-organized growth of nanostructures on surfaces could offer many advantages in the development of new catalysts, electronic devices and magnetic data-storage media. The local density of electronic states on the surface at the relevant energy scale strongly influences chemical reactivity, as does the shape of the nanoparticles. The electronic properties of surfaces also influence the growth and decay of nanostructures such as dimers, chains and superlattices of atoms or noble metal islands. Controlling these properties on length scales shorter than the diffusion lengths of the electrons and spins (some tens of nanometres for metals) is a major goal in electronics and spintronics. However, to date, there have been few studies of the electronic properties of self-organized nanostructures. Here we report the self-organized growth of macroscopic superlattices of Ag or Cu nanostructures on Au vicinal surfaces, and demonstrate that the electronic properties of these systems depend on the balance between the confinement and the perturbation of the surface states caused by the steps and the nanostructures' superlattice. We also show that the local density of states can be modified in a controlled way by adjusting simple parameters such as the type of metal deposited and the degree of coverage.

  15. Effects of self-organization on transport in granular matter: A network-based approach

    NASA Astrophysics Data System (ADS)

    Smart, A.; Umbanhowar, P.; Ottino, J.

    2007-07-01

    Granular matter may be one of the simplest prototypes of what have come to be regarded as complex systems —systems where simple interactions can lead to rich, often surprising, global behavior. For example, interparticle contacts in a granular system give rise to networks that are 1) heterogeneous, i.e., a few particles support high compressive force, while many others support relatively little, and 2) self-organized, i.e., spatially correlated strong forces tend to form a sub-network of interconnecting "force chains". Using numerical simulations, we investigate the influence of heterogeneity and self-organization on the transport properties of granular matter, with particular attention to heat conduction —a phenomenon of ubiquitous importance in engineering and nature. We find that self-organization in the granular network promotes efficient transport. Furthermore, a network-attack experiment suggests that contacts with high betweenness centrality, not necessarily those with highest local heat transfer coefficient, most significantly influence transport behavior. We find that concepts of network theory yield valuable insight —both qualitative and quantitative— into the observed behavior.

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

    PubMed Central

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

    2013-01-01

    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

  17. 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.

  18. Self-organization of polarized cerebellar tissue in 3D culture of human pluripotent stem cells.

    PubMed

    Muguruma, Keiko; Nishiyama, Ayaka; Kawakami, Hideshi; Hashimoto, Kouichi; Sasai, Yoshiki

    2015-02-01

    During cerebellar development, the main portion of the cerebellar plate neuroepithelium gives birth to Purkinje cells and interneurons, whereas the rhombic lip, the germinal zone at its dorsal edge, generates granule cells and cerebellar nuclei neurons. However, it remains elusive how these components cooperate to form the intricate cerebellar structure. Here, we found that a polarized cerebellar structure self-organizes in 3D human embryonic stem cell (ESC) culture. The self-organized neuroepithelium differentiates into electrophysiologically functional Purkinje cells. The addition of fibroblast growth factor 19 (FGF19) promotes spontaneous generation of dorsoventrally polarized neural-tube-like structures at the level of the cerebellum. Furthermore, addition of SDF1 and FGF19 promotes the generation of a continuous cerebellar plate neuroepithelium with rhombic-lip-like structure at one end and a three-layer cytoarchitecture similar to the embryonic cerebellum. Thus, human-ESC-derived cerebellar progenitors exhibit substantial self-organizing potential for generating a polarized structure reminiscent of the early human cerebellum at the first trimester. PMID:25640179

  19. Self-organization of neural tissue architectures from pluripotent stem cells.

    PubMed

    Karus, Michael; Blaess, Sandra; Brüstle, Oliver

    2014-08-15

    Despite being a subject of intensive research, the mechanisms underlying the formation of neural tissue architectures during development of the central nervous system remain largely enigmatic. So far, studies into neural pattern formation have been restricted mainly to animal experiments. With the advent of pluripotent stem cells it has become possible to explore early steps of nervous system development in vitro. These studies have unraveled a remarkable propensity of primitive neural cells to self-organize into primitive patterns such as neural tube-like rosettes in vitro. Data from more advanced 3D culture systems indicate that this intrinsic propensity for self-organization can even extend to the formation of complex architectures such as a multilayered cortical neuroepithelium or an entire optic cup. These novel experimental paradigms not only demonstrate the enormous self-organization capacity of neural stem cells, they also provide exciting prospects for studying the earliest steps of human neural tissue development and the pathogenesis of brain malformations in reductionist in vitro paradigms. PMID:24737617

  20. Phase separation explains a new class of self-organized spatial patterns in ecological systems

    PubMed Central

    Liu, Quan-Xing; Doelman, Arjen; Rottschäfer, Vivi; de Jager, Monique; Herman, Peter M. J.; Rietkerk, Max; van de Koppel, Johan

    2013-01-01

    The origin of regular spatial patterns in ecological systems has long fascinated researchers. Turing’s activator–inhibitor principle is considered the central paradigm to explain such patterns. According to this principle, local activation combined with long-range inhibition of growth and survival is an essential prerequisite for pattern formation. Here, we show that the physical principle of phase separation, solely based on density-dependent movement by organisms, represents an alternative class of self-organized pattern formation in ecology. Using experiments with self-organizing mussel beds, we derive an empirical relation between the speed of animal movement and local animal density. By incorporating this relation in a partial differential equation, we demonstrate that this model corresponds mathematically to the well-known Cahn–Hilliard equation for phase separation in physics. Finally, we show that the predicted patterns match those found both in field observations and in our experiments. Our results reveal a principle for ecological self-organization, where phase separation rather than activation and inhibition processes drives spatial pattern formation. PMID:23818579

  1. Phase separation explains a new class of self-organized spatial patterns in ecological systems.

    PubMed

    Liu, Quan-Xing; Doelman, Arjen; Rottschäfer, Vivi; de Jager, Monique; Herman, Peter M J; Rietkerk, Max; van de Koppel, Johan

    2013-07-16

    The origin of regular spatial patterns in ecological systems has long fascinated researchers. Turing's activator-inhibitor principle is considered the central paradigm to explain such patterns. According to this principle, local activation combined with long-range inhibition of growth and survival is an essential prerequisite for pattern formation. Here, we show that the physical principle of phase separation, solely based on density-dependent movement by organisms, represents an alternative class of self-organized pattern formation in ecology. Using experiments with self-organizing mussel beds, we derive an empirical relation between the speed of animal movement and local animal density. By incorporating this relation in a partial differential equation, we demonstrate that this model corresponds mathematically to the well-known Cahn-Hilliard equation for phase separation in physics. Finally, we show that the predicted patterns match those found both in field observations and in our experiments. Our results reveal a principle for ecological self-organization, where phase separation rather than activation and inhibition processes drives spatial pattern formation. PMID:23818579

  2. Formation of self-organized nanoporous anodic oxide from metallic gallium.

    PubMed

    Pandey, Bipin; Thapa, Prem S; Higgins, Daniel A; Ito, Takashi

    2012-09-25

    This paper reports the formation of self-organized nanoporous gallium oxide by anodization of solid gallium metal. Because of its low melting point (ca. 30 °C), metallic gallium can be shaped into flexible structures, permitting the fabrication of nanoporous anodic oxide monoliths within confined spaces like the inside of a microchannel. Here, solid gallium films prepared on planar substrates were employed to investigate the effects of anodization voltage (1, 5, 10, 15 V) and H(2)SO(4) concentration (1, 2, 4, 6 M) on anodic oxide morphology. Self-organized nanopores aligned perpendicular to the film surface were obtained upon anodization of gallium films in ice-cooled 4 and 6 M aqueous H(2)SO(4) at 10 and 15 V. Nanopore formation could be recognized by an increase in anodic current after a current decrease reflecting barrier oxide formation. The average pore diameter was in the range of 18-40 nm with a narrow diameter distribution (relative standard deviation ca. 10-20%), and was larger at lower H(2)SO(4) concentration and higher applied voltage. The maximum thickness of nanoporous anodic oxide was ca. 2 μm. In addition, anodic formation of self-organized nanopores was demonstrated for a solid gallium monolith incorporated at the end of a glass capillary. Nanoporous anodic oxide monoliths formed from a fusible metal will lead to future development of unique devices for chemical sensing and catalysis.

  3. 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

  4. 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.

  5. 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.

  6. Bacterial self-organization: co-enhancement of complexification and adaptability in a dynamic environment

    NASA Astrophysics Data System (ADS)

    Ben-Jacob, Eshel

    2003-06-01

    During colonial development, bacteria generate a wealth of patterns, some of which are reminiscent of those occurring in abiotic systems. They can exhibit rich behaviour, reflecting informative communication capabilities that include exchange of genetic materials and the fact that the colony's building blocks are biotic. Each has internal degrees of freedom, informatic capabilities and freedom to respond by altering itself and others via emission of signals in a self-regulated manner. To unravel the special secrets of bacterial self-organization, we conducted an integrative (experimental and theoretical) study of abiotic and biotic systems. Guided by the notion of general biotic motives and principles, I propose that the informative communication between individuals makes possible the enhancement of the individuals' regulated freedom, while increasing their cooperation. This process is accomplished via cooperative complexification of the colony through self-organization of hierarchical spatio-temporal patterning. The colonial higher complexity provides the degree of plasticity and flexibility required for better colonial adaptability and endurability in a dynamic environment. The biotic system can modify the environment and obtain environmental information for further self-improvement. I reflect on the potential applications of the new understanding on 'engineered self-organization of systems too complex to design' and other issues.

  7. 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.

  8. Coupling BCM and neural fields for the emergence of self-organization consensus.

    PubMed

    Lefort, Mathieu; Boniface, Yann; Girau, Bernard

    2011-01-01

    Human beings interact with the environment through different modalities, i.e. perceptions and actions, processed in the cortex by dedicated brain areas. These areas are self-organized, so that spatially close neurons are sensitive to close stimuli, providing generalization from previously learned examples. Although perceptive flows are picked up by different spatially separated sensors, their processings are not isolated. On the contrary, they are constantly interacting, as illustrated by the McGurk effect. When the auditory stimulus /ba/ and the /ga/ lip movement are presented simultaneously, people perceive a /da/, which does not correspond to any of the stimuli. Merging several stimuli into one multimodal perception reduces ambiguities and noises and is essential to interact with the environment. This article proposes a model for modality association, inspired by the biological properties of the cortex. The model consists of modality maps interacting through an associative map to raise a consistent multimodal perception of the environment. We propose the coupling of BCM learning rule and neural maps to obtain the decentralized and unsupervised self-organization of each modal map influenced by the multisensory context. We obtain local self-organization of modal maps with various inputs and discretizations. PMID:21744209

  9. Self Organization as a Tool for Complex System Understanding in a Changing World

    NASA Astrophysics Data System (ADS)

    Shachak, m.

    2012-04-01

    Recent developments in the field of complex systems provide new frontiers for the study of ecological organization and reorganization in a changing world. One of the hallmarks of complexity is that global phenomena emerge out of local interactions that affect global properties and behavior of systems. Non-linear interactions provide important sources for multi-level order that emerges from self-organization. Organization is defined as the process of forming non-random patterns that characterize individuals, species, ecosystems and landscapes. Reorganization refers to pattern modulation driven by internal and/or external processes. In ecological systems four global phenomena of self-organization result from local interactions among individual (population level), species (community level), organisms - environment (ecosystem level) and ecosystems (landscape level). These types of ecological interaction, which operate in all ecological systems, will form networks of interactions resulting in a self-organized complex adaptive system The challenge is to discover the principles that govern intra- and inter-level organization and reorganization as adaptive mechanisms. On the population and community levels, local interactions determine the organization of individuals and species assemblages, i.e. the distribution of individuals and species and their abundance in time and space. On the ecosystem and landscape levels, the global phenomenona are the organization of energy, materials and information fluxes. On these levels order appears in the form of functional properties such as nutrient cycling or biotically-induced mosaics of patches such as vegetation patterns in arid and semi-arid lands. All forms of organization are linked and important for understanding the functioning of ecological systems. In my presentation I will demonstrate the principles that govern intra- and inter-level organization and reorganization of ecological systems in water limited systems. Water

  10. Supramolecular chemistry: from molecular information towards self-organization and complex matter

    NASA Astrophysics Data System (ADS)

    Lehn, Jean-Marie

    2004-03-01

    Molecular chemistry has developed a wide range of very powerful procedures for constructing ever more sophisticated molecules from atoms linked by covalent bonds. Beyond molecular chemistry lies supramolecular chemistry, which aims at developing highly complex chemical systems from components interacting via non-covalent intermolecular forces. By the appropriate manipulation of these interactions, supramolecular chemistry became progressively the chemistry of molecular information, involving the storage of information at the molecular level, in the structural features, and its retrieval, transfer, and processing at the supramolecular level, through molecular recognition processes operating via specific interactional algorithms. This has paved the way towards apprehending chemistry also as an information science. Numerous receptors capable of recognizing, i.e. selectively binding, specific substrates have been developed, based on the molecular information stored in the interacting species. Suitably functionalized receptors may perform supramolecular catalysis and selective transport processes. In combination with polymolecular organization, recognition opens ways towards the design of molecular and supramolecular devices based on functional (photoactive, electroactive, ionoactive, etc) components. A step beyond preorganization consists in the design of systems undergoing self-organization, i.e. systems capable of spontaneously generating well-defined supramolecular architectures by self-assembly from their components. Self-organization processes, directed by the molecular information stored in the components and read out at the supramolecular level through specific interactions, represent the operation of programmed chemical systems. They have been implemented for the generation of a variety of discrete functional architectures of either organic or inorganic nature. Self-organization processes also give access to advanced supramolecular materials, such as

  11. 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

  12. Substrate dependent self-organization of mesoporous cobalt oxide nanowires with remarkable pseudocapacitance.

    PubMed

    Rakhi, R B; Chen, Wei; Cha, Dongkyu; Alshareef, H N

    2012-05-01

    A scheme of current collector dependent self-organization of mesoporous cobalt oxide nanowires has been used to create unique supercapacitor electrodes, with each nanowire making direct contact with the current collector. The fabricated electrodes offer the desired properties of macroporosity to allow facile electrolyte flow, thereby reducing device resistance and nanoporosity with large surface area to allow faster reaction kinetics. Co(3)O(4) nanowires grown on carbon fiber paper collectors self-organize into a brush-like morphology with the nanowires completely surrounding the carbon microfiber cores. In comparison, Co(3)O(4) nanowires grown on planar graphitized carbon paper collectors self-organize into a flower-like morphology. In three electrode configuration, brush-like and flower-like morphologies exhibited specific capacitance values of 1525 and 1199 F/g, respectively, at a constant current density of 1 A/g. In two electrode configuration, the brush-like nanowire morphology resulted in a superior supercapacitor performance with high specific capacitances of 911 F/g at 0.25 A/g and 784 F/g at 40 A/g. In comparison, the flower-like morphology exhibited lower specific capacitance values of 620 F/g at 0.25 A/g and 423 F/g at 40 A/g. The Co(3)O(4) nanowires with brush-like morphology exhibited high values of specific power (71 kW/kg) and specific energy (81 Wh/kg). Maximum energy and power densities calculated for Co(3)O(4) nanowires with flower-like morphology were 55 Wh/kg and 37 kW/kg respectively. Both electrode designs exhibited excellent cycling stability by retaining ∼91-94% of their maximum capacitance after 5000 cycles of continuous charge-discharge. PMID:22494065

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. Spatial self organization of surface structure during an oscillating catalytic reaction

    NASA Astrophysics Data System (ADS)

    Cox, M. P.; Ertl, G.; Imbihl, R.

    1985-04-01

    Under appropriate conditions, the rate of catalytic CO oxidation on a Pt(100) surface exhibits sustained temporal oscillations which are associated with a periodic surface-structural transformation from, the reconstructed (hex) to the nonreconstructed (1×1) phase and back again. By use of a newly developed scanning low-energy electron diffraction technique it is demonstrated that spatial self-organization in the oscillations involves a wavelike propagation of alternating bands of the two surface-structural modifications across the entire scanned area. These features can be modeled by numerical solution of a set of coupled differential equations.

  19. 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.

  20. Self-organized criticality, long-time correlations, and the standard transport paradigm

    SciTech Connect

    Krommes, J.A.

    2000-02-11

    Some aspects of low-frequency, long-wavelength fluctuations are considered. A stochastic model is used to show that power-law time correlations need not arise from self-organized criticality. A formula for the frequency spectrum of uncorrelated, overlapping avalanches is shown to be a special case of the spectral balance equation of renormalized statistical turbulence theory. It is argued that there need be no contradiction between the presence of long-time correlations and the existence of local transport coefficients.

  1. Learning by operant conditioning as a nonlinear self-organized process.

    PubMed

    Pascual, M A; Rodríguez, M A

    2006-07-01

    Responses of individuals have been rewarded in fixed ratio operant conditioning experiments throughout the last 5 years. The long numerical series of performance rates so obtained have been analyzed by using Fourier spectra, obtaining 1/f noise, and wavelet techniques for the analysis of local variability. These techniques reveal that the evolution of data in each individual is nonlinear but it fluctuates showing self-organized patterns in successive time scales, which leads to a long term logarithmic growth. Based on these observations a model has been developed. It can simulate with a great accuracy the rate of response exhibited by our subjects in all time scales.

  2. 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

  3. 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

  4. 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.

  5. Pattern formation and self-organization in plasmas interacting with surfaces

    NASA Astrophysics Data System (ADS)

    Trelles, Juan Pablo

    2016-10-01

    Pattern formation and self-organization are fascinating phenomena commonly observed in diverse types of biological, chemical and physical systems, including plasmas. These phenomena are often responsible for the occurrence of coherent structures found in nature, such as recirculation cells and spot arrangements; and their understanding and control can have important implications in technology, e.g. from determining the uniformity of plasma surface treatments to electrode erosion rates. This review comprises theoretical, computational and experimental investigations of the formation of spatiotemporal patterns that result from self-organization events due to the interaction of low-temperature plasmas in contact with confining or intervening surfaces, particularly electrodes. The basic definitions associated to pattern formation and self-organization are provided, as well as some of the characteristics of these phenomena within natural and technological contexts, especially those specific to plasmas. Phenomenological aspects of pattern formation include the competition between production/forcing and dissipation/transport processes, as well as nonequilibrium, stability, bifurcation and nonlinear interactions. The mathematical modeling of pattern formation in plasmas has encompassed from theoretical approaches and canonical models, such as reaction-diffusion systems, to drift-diffusion and nonequilibrium fluid flow models. The computational simulation of pattern formation phenomena imposes distinct challenges to numerical methods, such as high sensitivity to numerical approximations and the occurrence of multiple solutions. Representative experimental and numerical investigations of pattern formation and self-organization in diverse types of low-temperature electrical discharges (low and high pressure glow, dielectric barrier and arc discharges, etc) in contact with solid and liquid electrodes are reviewed. Notably, plasmas in contact with liquids, found in diverse

  6. Self-organization versus self-management: two sides of the same coin?

    PubMed

    Clancy, Thomas R

    2009-03-01

    As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the eighth in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the author explores self-organization as it relates to self-management in complex social organizations.

  7. Emergent self-organized complex network topology out of stability constraints.

    PubMed

    Perotti, Juan I; Billoni, Orlando V; Tamarit, Francisco A; Chialvo, Dante R; Cannas, Sergio A

    2009-09-01

    Although most networks in nature exhibit complex topologies, the origins of such complexity remain unclear. We propose a general evolutionary mechanism based on global stability. This mechanism is incorporated into a model of a growing network of interacting agents in which each new agent's membership in the network is determined by the agent's effect on the network's global stability. It is shown that out of this stability constraint complex topological properties emerge in a self-organized manner, offering an explanation for their observed ubiquity in biological networks. PMID:19792348

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. Controlled self-organization of atom vacancies in monatomic gallium layers.

    PubMed

    Snijders, P C; Moon, E J; González, C; Rogge, S; Ortega, J; Flores, F; Weitering, H H

    2007-09-14

    Ga adsorption on the Si(112) surface results in the formation of pseudomorphic Ga atom chains. Compressive strain in these atom chains is relieved via creation of adatom vacancies and their self-organization into meandering vacancy lines. The average spacing between these line defects can be controlled, within limits, by adjusting the chemical potential mu of the Ga adatoms. We derive a lattice model that quantitatively connects density functional theory (DFT) calculations for perfectly ordered structures with the fluctuating disorder seen in experiment and the experimental control parameter mu. This hybrid approach of lattice modeling and DFT can be applied to other examples of line defects in heteroepitaxy.

  17. 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.

  18. 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.

  19. A convolutional recursive modified Self Organizing Map for handwritten digits recognition.

    PubMed

    Mohebi, Ehsan; Bagirov, Adil

    2014-12-01

    It is well known that the handwritten digits recognition is a challenging problem. Different classification algorithms have been applied to solve it. Among them, the Self Organizing Maps (SOM) produced promising results. In this paper, first we introduce a Modified SOM for the vector quantization problem with improved initialization process and topology preservation. Then we develop a Convolutional Recursive Modified SOM and apply it to the problem of handwritten digits recognition. The computational results obtained using the well known MNIST dataset demonstrate the superiority of the proposed algorithm over the existing SOM-based algorithms.

  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.

  1. 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.

  2. Self-Organization of Quantum Rods Induced by Lipid Membrane Corrugations.

    PubMed

    Bizien, Thomas; Ameline, Jean-Claude; Yager, Kevin G; Marchi, Valérie; Artzner, Franck

    2015-11-10

    Self-organization of fluorescent nanoparticles, using biological molecules such as phospholipids to control assembly distances, is a promising method for creating hybrid nanostructures. We report here the formation of hybrid condensed phases made of anisotropic nanoparticles and phospholipids. Such structure formation is driven by electrostatic interaction between the nanoparticles and the phospholipids, and results in the formation of a 2D rectangular liquid crystal, as confirmed by high-resolution Small-Angle X-ray Scattering (SAXS). Moreover, we show that the fluorescent properties of the NPs are not modified by the self-assembly process.

  3. Self-organizing microstructures orientation control in femtosecond laser patterning on silicon surface.

    PubMed

    Liu, Pengjun; Jiang, Lan; Hu, Jie; Zhang, Shuai; Lu, Yongfeng

    2014-07-14

    Self-organizing rippled microstructures are induced on silicon surface by linearly polarized femtosecond laser pulses. At a near threshold fluence, it is observed that ripple orientation is co-determined by the laser polarization direction and laser scanning parameters (scanning direction and scanning speed) in surface patterning process. Under fixed laser polarization, the ripple orientation can be controlled to rotate by about 40° through changing laser scanning parameters. In addition, it is also observed that the ripple morphology is sensitive to the laser scanning direction, and it is an optimal choice to obtain ordered ripple structures when the angle between laser scanning and laser polarization is less than 45°.

  4. Tokamak plasma self-organization and the possibility to have the peaked density profile in ITER

    NASA Astrophysics Data System (ADS)

    Razumova, K. A.; Andreev, V. F.; Kislov, A. Ya.; Kirneva, N. A.; Lysenko, S. E.; Pavlov, Yu. D.; Shafranov, T. V.; T-10 Team; Donné, A. J. H.; Hogeweij, G. M. D.; Spakman, G. W.; Jaspers, R.; TEXTOR Team; Kantor, M.; Walsh, M.

    2009-06-01

    The self-organization of a tokamak plasma is a fundamental turbulent plasma phenomenon, which leads to the formation of a self-consistent pressure profile. This phenomenon has been investigated in several tokamaks with different methods of heating. It is shown that the normalized pressure profile has a universal shape for a wide class of tokamaks and regimes, if the normalized radius ρ = r/(IpR/κB)1/2 is used. The consequences of this phenomenon for low aspect ratio tokamaks, the optimal deposition of additional heating, fast velocity of heat/cold pulse propagation and the possibility of obtaining a peaked density profile in ITER are discussed.

  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. Self-organizing behaviour of glycosteroidal bolaphiles: insights into lipidic microsegregation.

    PubMed

    Xu, R; Ali-Rachedi, F; Xavier, N M; Chambert, S; Ferkous, F; Queneau, Y; Cowling, S J; Davis, E J; Goodby, J W

    2015-01-21

    In this article we describe work on the synthesis of bolaphile biomimics composed of glucose head groups and steroidal units linked together by a methylene chain of varying length. The condensed phases formed by self-organization of the products as a function of temperature were characterized by differential scanning calorimetry and thermal polarized light microscopy. The results of these studies show that the thermal stabilities of the lamellar mesophases formed vary linearly as a function of increasing aliphatic composition, which reflects a linear hydrophobic-hydrophilic balance with respect to transition temperatures.

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. Fairness Is an Emergent Self-Organized Property of the Free Market for Labor

    NASA Astrophysics Data System (ADS)

    Venkatasubramanian, Venkat

    2010-06-01

    The excessive compensation packages of CEOs of U.S. corporations in recent years have brought to the foreground the issue of fairness in economics. The conventional wisdom is that the free market for labor, which determines the pay packages, cares only about efficiency and not fairness. We present an alternative theory that shows that an ideal free market environment also promotes fairness, as an emergent property resulting from the self-organizing market dynamics. Even though an individual employee may care only about his or her salary and no one else's, the collective actions of all the employees, combined with the profit maximizing actions of all the companies, in a free market environment under budgetary constraints, lead towards a more fair allocation of wages, guided by Adam Smith's invisible hand of self-organization. By exploring deep connections with statistical thermodynamics, we show that entropy is the appropriate measure of fairness in a free market environment which is maximized at equilibrium to yield the lognormal distribution of salaries as the fairest inequality of pay in an organization under ideal conditions.

  12. Coherent scattering of electromagnetic waves by self-organized dust structures: Degree of coherence

    SciTech Connect

    Tsytovich, Vadim; Gusein-zade, Namik; Ignatov, Alexander

    2015-02-15

    It is demonstrated explicitly that the scattering of electromagnetic waves by dust structures can be strongly enhanced as compared to incoherent scattering by random electrons. If the size of the dust structure is much less than the wavelength of the incident radiation, the scattering is coherent. In this case, the scattering is proportional to the square of the total number of electrons in the structure. In the opposite limit, the scattering is incoherent being proportional to the total number of electrons in the structure. The factor describing the degree of coherency is calculated numerically for several models of self-organized structures. It is demonstrated in general way that for sudden heating of electrons, the factor of coherency in scattering by structures can decrease by several orders of magnitude with subsequent increase after the heating is switched off. In laboratory dusty plasmas, the coherent scattering is proposed for diagnostics of universal structuring instability and as a probe for determining the properties typical for self-organized nature of structures that are observed in recent experiments.

  13. 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

  14. Neural interactions between flicker-induced self-organized visual hallucinations and physical stimuli

    PubMed Central

    Billock, Vincent A.; Tsou, Brian H.

    2007-01-01

    Spontaneous pattern formation in cortical activity may have consequences for perception, but little is known about interactions between sensory-driven and self-organized cortical activity. To address this deficit, we explored the relationship between ordinary stimulus-controlled pattern perception and the autonomous hallucinatory geometrical pattern formation that occurs for unstructured visual stimulation (e.g., empty-field flicker). We found that flicker-induced hallucinations are biased by the presentation of adjacent geometrical stimuli; geometrical forms that map to cortical area V1 as orthogonal gratings are perceptually opponent in biasing hallucinations. Rotating fan blades and pulsating circular patterns are the most salient biased hallucinations. Apparent motion and fractal (1/f) noise are also effective in driving hallucinatory pattern formation (the latter is consistent with predictions of spatiotemporal pattern formation driven by stochastic resonance). The behavior of these percepts suggests that self-organized hallucinatory pattern formation in human vision is governed by the same cortical properties of localized processing, lateral inhibition, simultaneous contrast, and nonlinear retinotopic mapping that govern ordinary vision. PMID:17470794

  15. Self-organized criticality in asymmetric exclusion model with noise for freeway traffic

    NASA Astrophysics Data System (ADS)

    Nagatani, Takashi

    1995-02-01

    The one-dimensional asymmetric simple-exclusion model with open boundaries for parallel update is extended to take into account temporary stopping of particles. The model presents the traffic flow on a highway with temporary deceleration of cars. Introducing temporary stopping into the asymmetric simple-exclusion model drives the system asymptotically into a steady state exhibiting a self-organized criticality. In the self-organized critical state, start-stop waves (or traffic jams) appear with various sizes (or lifetimes). The typical interval < s>between consecutive jams scales as < s> ≃ Lv with v = 0.51 ± 0.05 where L is the system size. It is shown that the cumulative jam-interval distribution Ns( L) satisfies the finite-size scaling form ( Ns( L) ≃ L- vf( s/ Lv). Also, the typical lifetime ≃ Lv‧ with v‧ = 0.52 ± 0.05. The cumulative distribution Nm( L) of lifetimes satisfies the finite-size scaling form Nm( L)≃ L-1g( m/ Lv‧).

  16. 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.

  17. Self-organized neural network for the quality control of 12-lead ECG signals.

    PubMed

    Chen, Yun; Yang, Hui

    2012-09-01

    Telemedicine is very important for the timely delivery of health care to cardiovascular patients, especially those who live in the rural areas of developing countries. However, there are a number of uncertainty factors inherent to the mobile-phone-based recording of electrocardiogram (ECG) signals such as personnel with minimal training and other extraneous noises. PhysioNet organized a challenge in 2011 to develop efficient algorithms that can assess the ECG signal quality in telemedicine settings. This paper presents our efforts in this challenge to integrate multiscale recurrence analysis with a self-organizing map for controlling the ECG signal quality. As opposed to directly evaluating the 12-lead ECG, we utilize an information-preserving transform, i.e. Dower transform, to derive the 3-lead vectorcardiogram (VCG) from the 12-lead ECG in the first place. Secondly, we delineate the nonlinear and nonstationary characteristics underlying the 3-lead VCG signals into multiple time-frequency scales. Furthermore, a self-organizing map is trained, in both supervised and unsupervised ways, to identify the correlations between signal quality and multiscale recurrence features. The efficacy and robustness of this approach are validated using real-world ECG recordings available from PhysioNet. The average performance was demonstrated to be 95.25% for the training dataset and 90.0% for the independent test dataset with unknown labels.

  18. Self-organizing maps as a model of brain mechanisms potentially linked to autism.

    PubMed

    Noriega, Gerardo

    2007-06-01

    The application of artificial neural networks in the study of psychopathological syndromes has great potential. Several computational models of acquired and developmental disorders, including autism, have been proposed recently. In this paper, we use the framework of self-organizing maps to study several aspects of autism, by modeling abnormalities in the learning process in biologically plausible manners. We then interpret the resulting feature maps with reference to autistic characteristics. The effects of manipulating the physical structure and size of self-organizing maps were measured and compared with the general characteristics of neural growth abnormalities in autistic children. We find no effect on stimuli coverage, but a negative impact on map unfolding, dependant on the intensity of the abnormality, but not the time of onset. We analyze sensory issues by introducing the concept of attention functions, used to model hypersensitivities and hyposensitivities. The issue of focus on details rather than the whole is analyzed through a model in which distant neighbors are explicitly rejected; we show the model may lead to improved coverage of finely-shaped areas or isolated stimuli, but poorer map unfolding. Finally, we consider effects of noisy communication channels on the development of maps, and show a strong sensitivity of both coverage and unfolding of maps.

  19. Self-Organized Collective Crystal-Like Formations of the Attractive/repulsive Swarming System

    NASA Astrophysics Data System (ADS)

    Tian, Wen-Qiang; Gao, Dan; Wang, Ying-Guan

    2014-01-01

    In this paper, an adaptive attractive/repulsive (A/R) swarming model is proposed to explore the role of self-organized formation in swarming systems. By defining the adjustable A/R range γi, which is affected by the localized steady state of agents, the standard collective crystal-like swarming formations are straightforwardly unfolded in different scale. Meanwhile, with numerical simulations and analyses, the results show that the adaptive A/R swarming model provides an effective solution to the current existing dilemma of the collective liquid-like formation with unexpected neighbor distances and the split crystal-like formation. The actual neighbor distance of the adaptive A/R model could converge to the expected neighbor distance as planned, based on the different settings of the expected neighbor distance and the A/R range. Moreover, such adjustable A/R swarming formations may find their potential applications such as the formation of self-organized multi-robots and unmanned aerial vehicles, the automatic networking of sensors, etc.

  20. 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.

  1. Self-organization in cytoskeletal mixtures: from synthetic cilia to flowing networks

    NASA Astrophysics Data System (ADS)

    Sanchez, Tim

    2013-03-01

    Inspired by biological functions such as ciliary beating and cytoplasmic streaming, we have developed a highly tunable and robust model system from biological components that self-organizes to produce a broad range of far-from-equilibrium materials with remarkable emergent properties. Using only simple components - microtubules, kinesin motor clusters, and a depletion agent that bundles MTs - we reproduced several essential biological functions, including cilia-like beating, the emergence of metachronal waves in bundle arrays, and internally generated flows in active cytoskeletal gels. The occurrence of these biomimetic functions as self-organized processes provides unique insight into the mechanisms that drive these processes in biology. Beyond these biomimetic behaviors, we have also used the same components to engineer novel active materials which have no biological analogues: active streaming 2D nematics, and finally self-propelled emulsion droplets. These observations exemplify how assemblages of animate microscopic objects exhibit highly sought-after collective and biomimetic properties, challenging us to develop a theoretical framework that would allow for a systematic engineering of their far-from-equilibrium material properties.

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

    PubMed

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

    2015-12-01

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Towards developing next generation scalable TiO2-based resistive switching (RS) memory devices, the efficacy of 50 keV Ar+-ion irradiation to achieve self-organized nano-channel based structures at a threshold fluence of 5 × 1016 ions/cm2 at ambient temperature is presented. Although x-ray diffraction results suggest the amorphization of as-grown TiO2 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/Ti2O3 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/TiO2/Pt/Ti/SiO2/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.

  4. Light-Directed Dynamic Chirality Inversion in Functional Self-Organized Helical Superstructures.

    PubMed

    Bisoyi, Hari Krishna; Li, Quan

    2016-02-24

    Helical superstructures are widely observed in nature, in synthetic polymers, and in supramolecular assemblies. Controlling the chirality (the handedness) of dynamic helical superstructures of molecular and macromolecular systems by external stimuli is a challenging task, but is of great fundamental significance with appealing morphology-dependent applications. Light-driven chirality inversion in self-organized helical superstructures (i.e. cholesteric, chiral nematic liquid crystals) is currently in the limelight because inversion of the handedness alters the chirality of the circularly polarized light that they selectively reflect, which has wide potential for application. Here we discuss the recent developments toward inversion of the handedness of cholesteric liquid crystals enabled by photoisomerizable chiral molecular switches or motors. Different classes of chiral photoresponsive dopants (guests) capable of conferring light-driven reversible chirality inversion of helical superstructures fabricated from different nematic hosts are discussed. Rational molecular designs of chiral molecular switches toward endowing handedness inversion to the induced helical superstructures of cholesteric liquid crystals are highlighted. This Review is concluded by throwing light on the challenges and opportunities in this emerging frontier, and it is expected to provide useful guidelines toward the development of self-organized soft materials with stimuli-directed chirality inversion capability and multifunctional host-guest systems.

  5. Network Catastrophe: Self-Organized Patterns Reveal both the Instability and the Structure of Complex Networks

    PubMed Central

    Moon, Hankyu; Lu, Tsai-Ching

    2015-01-01

    Critical events in society or biological systems can be understood as large-scale self-emergent phenomena due to deteriorating stability. We often observe peculiar patterns preceding these events, posing a question of—how to interpret the self-organized patterns to know more about the imminent crisis. We start with a very general description — of interacting population giving rise to large-scale emergent behaviors that constitute critical events. Then we pose a key question: is there a quantifiable relation between the network of interactions and the emergent patterns? Our investigation leads to a fundamental understanding to: 1. Detect the system's transition based on the principal mode of the pattern dynamics; 2. Identify its evolving structure based on the observed patterns. The main finding of this study is that while the pattern is distorted by the network of interactions, its principal mode is invariant to the distortion even when the network constantly evolves. Our analysis on real-world markets show common self-organized behavior near the critical transitions, such as housing market collapse and stock market crashes, thus detection of critical events before they are in full effect is possible. PMID:25822423

  6. Network Catastrophe: Self-Organized Patterns Reveal both the Instability and the Structure of Complex Networks

    NASA Astrophysics Data System (ADS)

    Moon, Hankyu; Lu, Tsai-Ching

    2015-03-01

    Critical events in society or biological systems can be understood as large-scale self-emergent phenomena due to deteriorating stability. We often observe peculiar patterns preceding these events, posing a question of--how to interpret the self-organized patterns to know more about the imminent crisis. We start with a very general description -- of interacting population giving rise to large-scale emergent behaviors that constitute critical events. Then we pose a key question: is there a quantifiable relation between the network of interactions and the emergent patterns? Our investigation leads to a fundamental understanding to: 1. Detect the system's transition based on the principal mode of the pattern dynamics; 2. Identify its evolving structure based on the observed patterns. The main finding of this study is that while the pattern is distorted by the network of interactions, its principal mode is invariant to the distortion even when the network constantly evolves. Our analysis on real-world markets show common self-organized behavior near the critical transitions, such as housing market collapse and stock market crashes, thus detection of critical events before they are in full effect is possible.

  7. Surface target-tracking guidance by self-organizing formation flight of fixed-wing UAV

    NASA Astrophysics Data System (ADS)

    Regina, N.; Zanzi, M.

    This paper presents a new concept of ground target surveillance based on a formation flight of two Unmanned Aerial Vehicles (UAVs) of fixed-wing type. Each UAV considered in this work has its own guidance law specifically designed for two different aims. A self organizing non-symmetric collaborative surveying scheme has been developed based on pursuers with different roles: the close-up-pursuer and the distance-pursuer. The close-up-pursuer behaves according to a guidance law which takes it to continually over-fly the target, also optimizing flight endurance. On the other hand, the distancepursuer behaves so as to circle around the target by flying at a certain distance and altitude from it; moreover, its motion ensures the maximum “ seeability” of the ground based target. In addition, the guidance law designed for the distance-pursuer also implements a collision avoidance feature in order to prevent possible risks of collision with the close-up-pursuer during the tracking maneuvers. The surveying scheme is non-symmetric in the sense that the collision avoidance feature is accomplished by a guidance law implemented only on one of the two pursuers; moreover, it is collaborative because the surveying is performed by different tasks of two UAVs and is self-organizing because, due to the collision avoidance feature, target tracking does not require pre-planned collision-risk-free trajectories but trajectories are generated in real time.

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

    PubMed

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

    2015-12-01

    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

  9. Modeling the self-organized phosphatidylinositol lipid signaling system in chemotactic cells using quantitative image analysis.

    PubMed

    Shibata, Tatsuo; Nishikawa, Masatoshi; Matsuoka, Satomi; Ueda, Masahiro

    2012-11-01

    A key signaling event that is responsible for gradient sensing in eukaryotic cell chemotaxis is a phosphatidylinositol (PtdIns) lipid reaction system. The self-organization activity of this PtdIns lipid system induces an inherent polarity, even in the absence of an external chemoattractant gradient, by producing a localized PtdIns (3,4,5)-trisphosphate [PtdIns(3,4,5)P(3)]-enriched domain on the membrane. Experimentally, we found that such a domain could exhibit two types of behavior: (1) it could be persistent and travel on the membrane, or (2) be stochastic and transient. Taking advantage of the simultaneous visualization of PtdIns(3,4,5)P(3) and the enzyme phosphatase and tensin homolog (PTEN), for which PtdIns(3,4,5)P(3) is a substrate, we statistically demonstrated the inter-dependence of their spatiotemporal dynamics. On the basis of this statistical analysis, we developed a theoretical model for the self-organization of PtdIns lipid signaling that can accurately reproduce both persistent and transient domain formation; these types of formations can be explained by the oscillatory and excitability properties of the system, respectively. PMID:22899720

  10. The influence of topography and vegetation self-organization over resource fluxes in wetland ecosystems

    NASA Astrophysics Data System (ADS)

    Stieglitz, Marc; Cheng, Yiwei; Truk, Greg; Engel, Victor; Ross, Joshua

    2014-05-01

    While it is recognized that topography and vegetation self-organization (SO) are both first order controls over ecosystem dynamics, the discrete contributions that these two controls have over ecosystem functioning have not been studied in any rigorous way. This work is focused on systematically isolating the separate and combined impacts of topography and SO over vegetation dynamics. We simulate the steady state and transient dynamics of nitrogen-limited patterned peat vegetation observed in the bogs of northern Siberia. We do so across a realistic range of land slopes, nutrient limitation values, and rainfall amounts. Simulation results show that on relatively shallow slopes, vegetation SO is a primary control over the spatial arrangement of vegetation, and that such self-organized arrangements yield the most efficient capture of ecosystem resources. However, as slope increases, and or resource limitation is low, topography begins to exert its control over the temporal and spatial dynamics. As will be discussed, these results suggest a simple continuum framework, valid across biomes, for understanding the interplay between these two first order controls. Specifically, as resources (e.g., water, nutrients) increase, ecosystem dynamics shift towards topographic control, while when resources are reduced, ecosystem dynamics shift towards vegetation SO control.

  11. 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

  12. Self-organized critical branching in systems that violate conservation laws

    NASA Astrophysics Data System (ADS)

    Juanico, D. E.; Monterola, C.; Saloma, C.

    2007-04-01

    A non-conservative critical branching model is proposed to demonstrate that self-organized criticality (SOC) can occur in mean-field sandpiles that violate a conservation law. The critical state is characterized by avalanche sizes and lifetimes that obey an inverse power-law distribution with exponents τS = 3/2 and τT = 2, respectively. Criticality is achieved when the branching process is coupled to a background activity characterized by the spontaneous switching between refractoriness and quiescence among system components. The stationary state of the system is analysed mathematically and numerically, and is shown to exhibit a transition from a subcritical phase to a critical phase. SOC in sandpile models has been widely believed to occur only when grains are conserved during avalanches. However, such a conservation law is likely to be violated by open, non-equilibrium systems such as biological networks and socially interacting systems like animal groups. The model explores the role of dynamic synapses and synaptic plasticity in maintaining criticality of cortical networks. These brain networks have been found to display neuronal avalanches that obey a power-law distribution. The non-conservative model also emulates the main features of the size distributions of free-swimming tuna schools and red deer herds. Demonstrating criticality in self-organizing systems that violate conservation laws enhances the predictive ability of the theory of SOC in the arena of biocomplexity.

  13. Self-organized transient facilitated atomic transport in Pt /Al(111)

    NASA Astrophysics Data System (ADS)

    Süle, P.

    2008-04-01

    During the course of atomic transport in a host material, impurity atoms need to surmount an energy barrier driven by thermodynamic bias or at ultralow temperatures by quantum tunneling. In the present article, we demonstrate using atomistic simulations that at ultralow temperature, transient interlayer atomic transport is also possible without tunneling when the Pt /Al(111) impurity/host system self-organizes itself spontaneously into an intermixed configuration. No such extremely fast athermal concerted process has been reported before at ultralow temperatures. The outlined novel transient atomic exchange mechanism could be of general validity. We find that the source of ultralow temperature heavy particle barrier crossing is intrinsic and no external bias is necessary for atomic intermixing and surface alloying in Pt /Al, although the dynamic barrier height is a few eV. The mechanism is driven by the local thermalization of the Al(111) surface in a self-organized manner arranged spontaneously by the system without any external stimulus. The core of the short lived thermalized region reaches the local temperature of ˜1000K (including a few tens of Al atoms), while the average temperature of the simulation cell is ˜3K. The transient facilitated intermixing process also takes place with repulsive impurity-host interaction potential leading to negative atomic mobility; hence, the atomic injection is largely independent of the strength of the impurity-surface interaction. We predict that similar exotic behavior is possible in other materials as well.

  14. On the logical relationship between natural selection and self-organization.

    PubMed

    Hoelzer, G A; Smith, E; Pepper, J W

    2006-11-01

    Most evolutionary biologists cherish Darwin's theory of natural selection (NS) as the process of adaptive evolution more than 140 years after publication of his first book on the subject. However, in the past few decades the study of self-organization (SO) in complex dynamical systems has suggested that adaptation may occur through intrinsic reorganization without NS. In this study, we attempt to describe the logical framework that relates the general process of SO to the specific process of NS. We describe NS as a mechanism that coordinates the coevolution of species in an ecosystem to effectively capture, process and dissipate solar energy into the earth's shadow. Finally, we conclude that NS is an emergent process founded on the same thermodynamic imperatives that are thought to underlie all SO. This perspective suggests that the theory of self-organizing systems offers a broader physical context in which to understand the process of NS, rather than contesting it. It even suggests the possibility that there may be a physical basis for understanding the origin of the process of NS. Rather than being merely a fluke of nature, the origin of NS that may be driven by energy flows across gradients.

  15. Self-Organizing Distributed Architecture Supporting Dynamic Space Expanding and Reducing in Indoor LBS Environment

    PubMed Central

    Jeong, Seol Young; Jo, Hyeong Gon; Kang, Soon Ju

    2015-01-01

    Indoor location-based services (iLBS) are extremely dynamic and changeable, and include numerous resources and mobile devices. In particular, the network infrastructure requires support for high scalability in the indoor environment, and various resource lookups are requested concurrently and frequently from several locations based on the dynamic network environment. A traditional map-based centralized approach for iLBSs has several disadvantages: it requires global knowledge to maintain a complete geographic indoor map; the central server is a single point of failure; it can also cause low scalability and traffic congestion; and it is hard to adapt to a change of service area in real time. This paper proposes a self-organizing and fully distributed platform for iLBSs. The proposed self-organizing distributed platform provides a dynamic reconfiguration of locality accuracy and service coverage by expanding and contracting dynamically. In order to verify the suggested platform, scalability performance according to the number of inserted or deleted nodes composing the dynamic infrastructure was evaluated through a simulation similar to the real environment. PMID:26016908

  16. From self-organization to self-assembly: a new materialism?

    PubMed

    Vincent, Bernadette Bensaude

    2016-09-01

    While self-organization has been an integral part of academic discussions about the distinctive features of living organisms, at least since Immanuel Kant's Critique of Judgement, the term 'self-assembly' has only been used for a few decades as it became a hot research topic with the emergence of nanotechnology. Could it be considered as an attempt at reducing vital organization to a sort of assembly line of molecules? Considering the context of research on self-assembly I argue that the shift of attention from self-organization to self-assembly does not really challenge the boundary between chemistry and biology. Self-assembly was first and foremost investigated in an engineering context as a strategy for manufacturing without human intervention and did not raise new perspectives on the emergence of vital organization itself. However self-assembly implies metaphysical assumptions that this paper tries to disentangle. It first describes the emergence of self-assembly as a research field in the context of materials science and nanotechnology. The second section outlines the metaphysical implications and will emphasize a sharp contrast between the ontology underlying two practices of self-assembly developed under the umbrella of synthetic biology. And unexpectedly, we shall see that chemists are less on the reductionist side than most synthetic biologists. Finally, the third section ventures some reflections on the kind of design involved in self-assembly practices.

  17. Neuronal avalanches of a self-organized neural network with active-neuron-dominant structure.

    PubMed

    Li, Xiumin; Small, Michael

    2012-06-01

    Neuronal avalanche is a spontaneous neuronal activity which obeys a power-law distribution of population event sizes with an exponent of -3/2. It has been observed in the superficial layers of cortex both in vivo and in vitro. In this paper, we analyze the information transmission of a novel self-organized neural network with active-neuron-dominant structure. Neuronal avalanches can be observed in this network with appropriate input intensity. We find that the process of network learning via spike-timing dependent plasticity dramatically increases the complexity of network structure, which is finally self-organized to be active-neuron-dominant connectivity. Both the entropy of activity patterns and the complexity of their resulting post-synaptic inputs are maximized when the network dynamics are propagated as neuronal avalanches. This emergent topology is beneficial for information transmission with high efficiency and also could be responsible for the large information capacity of this network compared with alternative archetypal networks with different neural connectivity.

  18. Self-organization and fractality in a metabolic processes of the Krebs cycle.

    PubMed

    Grytsay, V I; Musatenko, I V

    2013-01-01

    The metabolic processes of the Krebs cycle is studied with the help of a mathematical model. The autocatalytic processes resulting in both the formation of the self-organization in the Krebs cycle and the appearance of a cyclicity of its dynamics are determined. Some structural-functional connections creating the synchronism of an autoperiodic functioning at the transport in the respiratory chain and the oxidative phosphorylation are investigated. The conditions for breaking the synchronization of processes, increasing the multiplicity of cyclicity, and for the appearance of chaotic modes are analyzed. The phase-parametric diagram of a cascade of bifurcations showing the transition to a chaotic mode by the Feigenbaum scenario is obtained. The fractal nature of the revealed cascade of bifurcations is demonstrated. The strange attractors formed as a result of the folding are obtained. The results obtained give the idea of structural-functional connections, due to which the self-organization appears in the metabolism running in a cell. The constructed mathematical model can be applied to the study of the toxic and allergic effects of drugs and various substances on cell metabolism.

  19. A self-organizing radial basis network for estimating riverine fish diversity

    NASA Astrophysics Data System (ADS)

    Chang, Fi-John; Tsai, Wen-Ping; Chen, Hung-kwai; Yam, Rita Sau-Wai; Herricks, Edwin E.

    2013-01-01

    SummaryIn aquatic ecosystems, particularly rivers, hydrology plays a key role in structuring and maintaining habitats and flow regimes that influence ecological sustainability. Flow regime assessment in Taiwan has been facilitated recently by the Taiwan Eco-hydrologic Indicator System (TEIS). In this study, the self-organizing feature map (SOM) and radial basis function (RBF) neural network are combined to produce a self-organizing radial basis network (SORBN) that takes the advantages of both methods for strengthening the power of presentation and reliability of estimation. The SORBN is proposed to estimate the diversity of fish communities based on the TEIS and historic fish community composition at 36 locations in Taiwan. The discharge data are available for a minimum of 20 years. Data analysis applying a moving average method to the TEIS statistics is used to reflect the effects of antecedent flow conditions on fish diversity. Results indicate the hybrid SORBN not only effectively categorizes stream flow data but also reasonably identifies relationships between flow regime and fish community diversity. Results are encouraging so that it is possible to better relate flow and ecosystem conditions, and the proposed method can be used to quantify how flow influences river ecosystems.

  20. Self-organization in P_xGe_xSe_1-2x glasses^*

    NASA Astrophysics Data System (ADS)

    Chakravarty, Swapnajit; Georgiev, Daniel; Boolchand, Punit; Micoulaut, Matthieu

    2003-03-01

    Bulk glasses in the titled ternary, in the 0 < x < 0.26 composition range, are examined in MDSC and Raman scattering measurements. Both fresh and aged samples were studied. Bimodal endotherms are observed but only the high^T endotherm displays a reversing heat flow signal that represents a glass transition. The pre^_Tg endotherm is observed in quenched samples only, and represents an activation energy [1] associated with P4 units (Se^_P(Se_1/2)_3) converting to P3 (P(Se_1/2)_3) ones. T_g(x) accessed from the reversing heat flow are found to increase with x as a power^_law, displaying a cusp near x = 0.04. The non^_reversing enthalpy is found to display a global minimum in the 0.08 < x < 0.145 range identified with the self^_organized phase. Raman scattering reveals the isostatically rigid units ( P3 , P_4, CS and ES Ge(Se_1/2)_4) comprising building blocks of the self^_organized phase. These results are parallel to those encountered in the As^_Ge^_Se ternary [2,3]. ^*Supported by NSF grant DMR ^_01^_01808 1. D.G. Georgiev et al Phys. Rev. B 64,134204(2001) 2.Y. Wang et al Europhys. Lett. 52, 633 (2000) 3. T.Qu et al. companion abstract