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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. The concept of self-organization in cellular architecture

    PubMed Central

    Misteli, Tom

    2001-01-01

    In vivo microscopy has recently revealed the dynamic nature of many cellular organelles. The dynamic properties of several cellular structures are consistent with a role for self-organization in their formation, maintenance, and function; therefore, self-organization might be a general principle in cellular organization. PMID:11604416

  3. Bio-inspired self-organizing cellular systems.

    PubMed

    Stauffer, André; Mange, Daniel; Rossier, Joël; Vannel, Fabien

    2008-01-01

    Bio-inspiration borrows three properties characteristic of living organisms: multicellular architecture, cellular division, and cellular differentiation. Implemented in silicon according to these properties, our self-organizing systems are able to grow, to self-replicate, and to self-repair. The growth and branching processes, performed by the so-called Tom Thumb algorithm, lead thus to the configuration and cloning mechanisms of the systems. The repair processes allow its cicatrization and regeneration mechanisms. The cellular design and hardware implementation of these mechanisms constitute the core of this paper.

  4. Computational models of molecular self-organization in cellular environments.

    PubMed

    LeDuc, Philip; Schwartz, Russell

    2007-01-01

    The cellular environment creates numerous obstacles to efficient chemistry, as molecular components must navigate through a complex, densely crowded, heterogeneous, and constantly changing landscape in order to function at the appropriate times and places. Such obstacles are especially challenging to self-organizing or self-assembling molecular systems, which often need to build large structures in confined environments and typically have high-order kinetics that should make them exquisitely sensitive to concentration gradients, stochastic noise, and other non-ideal reaction conditions. Yet cells nonetheless manage to maintain a finely tuned network of countless molecular assemblies constantly forming and dissolving with a robustness and efficiency generally beyond what human engineers currently can achieve under even carefully controlled conditions. Significant advances in high-throughput biochemistry and genetics have made it possible to identify many of the components and interactions of this network, but its scale and complexity will likely make it impossible to understand at a global, systems level without predictive computational models. It is thus necessary to develop a clear understanding of how the reality of cellular biochemistry differs from the ideal models classically assumed by simulation approaches and how simulation methods can be adapted to accurately reflect biochemistry in the cell, particularly for the self-organizing systems that are most sensitive to these factors. In this review, we present approaches that have been undertaken from the modeling perspective to address various ways in which self-organization in the cell differs from idealized models.

  5. 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

  6. 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

  7. Cellular self-organization on micro-structured surfaces.

    PubMed

    Röttgermann, Peter J F; Alberola, Alicia Piera; Rädler, Joachim O

    2014-04-14

    Micro-patterned surfaces are frequently used in high-throughput single-cell studies, as they allow one to image isolated cells in defined geometries. Commonly, cells are seeded in excess onto the entire chip, and non-adherent cells are removed from the unpatterned sectors by rinsing. Here, we report on the phenomenon of cellular self-organization, which allows for autonomous positioning of cells on micro-patterned surfaces over time. We prepared substrates with a regular lattice of protein-coated adhesion sites surrounded by PLL-g-PEG passivated areas, and studied the time course of cell ordering. After seeding, cells randomly migrate over the passivated surface until they find and permanently attach to adhesion sites. Efficient cellular self-organization was observed for three commonly used cell lines (HuH7, A549, and MDA-MB-436), with occupancy levels typically reaching 40-60% after 3-5 h. The time required for sorting was found to increase with increasing distance between adhesion sites, and is well described by the time-to-capture in a random-search model. Our approach thus paves the way for automated filling of cell arrays, enabling high-throughput single-cell analysis of cell samples without losses.

  8. Quantitative analysis of cellular metabolic dissipative, self-organized structures.

    PubMed

    de la Fuente, Ildefonso Martínez

    2010-09-27

    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.

  9. 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

  10. 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.

  11. A strategy for tissue self-organization that is robust to cellular heterogeneity and plasticity.

    PubMed

    Cerchiari, Alec E; Garbe, James C; Jee, Noel Y; Todhunter, Michael E; Broaders, Kyle E; Peehl, Donna M; Desai, Tejal A; LaBarge, Mark A; Thomson, Matthew; Gartner, Zev J

    2015-02-17

    Developing tissues contain motile populations of cells that can self-organize into spatially ordered tissues based on differences in their interfacial surface energies. However, it is unclear how self-organization by this mechanism remains robust when interfacial energies become heterogeneous in either time or space. The ducts and acini of the human mammary gland are prototypical heterogeneous and dynamic tissues comprising two concentrically arranged cell types. To investigate the consequences of cellular heterogeneity and plasticity on cell positioning in the mammary gland, we reconstituted its self-organization from aggregates of primary cells in vitro. We find that self-organization is dominated by the interfacial energy of the tissue-ECM boundary, rather than by differential homo- and heterotypic energies of cell-cell interaction. Surprisingly, interactions with the tissue-ECM boundary are binary, in that only one cell type interacts appreciably with the boundary. Using mathematical modeling and cell-type-specific knockdown of key regulators of cell-cell cohesion, we show that this strategy of self-organization is robust to severe perturbations affecting cell-cell contact formation. We also find that this mechanism of self-organization is conserved in the human prostate. Therefore, a binary interfacial interaction with the tissue boundary provides a flexible and generalizable strategy for forming and maintaining the structure of two-component tissues that exhibit abundant heterogeneity and plasticity. Our model also predicts that mutations affecting binary cell-ECM interactions are catastrophic and could contribute to loss of tissue architecture in diseases such as breast cancer.

  12. A strategy for tissue self-organization that is robust to cellular heterogeneity and plasticity

    PubMed Central

    Cerchiari, Alec E.; Garbe, James C.; Jee, Noel Y.; Todhunter, Michael E.; Broaders, Kyle E.; Peehl, Donna M.; Desai, Tejal A.; LaBarge, Mark A.; Thomson, Matthew; Gartner, Zev J.

    2015-01-01

    Developing tissues contain motile populations of cells that can self-organize into spatially ordered tissues based on differences in their interfacial surface energies. However, it is unclear how self-organization by this mechanism remains robust when interfacial energies become heterogeneous in either time or space. The ducts and acini of the human mammary gland are prototypical heterogeneous and dynamic tissues comprising two concentrically arranged cell types. To investigate the consequences of cellular heterogeneity and plasticity on cell positioning in the mammary gland, we reconstituted its self-organization from aggregates of primary cells in vitro. We find that self-organization is dominated by the interfacial energy of the tissue–ECM boundary, rather than by differential homo- and heterotypic energies of cell–cell interaction. Surprisingly, interactions with the tissue–ECM boundary are binary, in that only one cell type interacts appreciably with the boundary. Using mathematical modeling and cell-type-specific knockdown of key regulators of cell–cell cohesion, we show that this strategy of self-organization is robust to severe perturbations affecting cell–cell contact formation. We also find that this mechanism of self-organization is conserved in the human prostate. Therefore, a binary interfacial interaction with the tissue boundary provides a flexible and generalizable strategy for forming and maintaining the structure of two-component tissues that exhibit abundant heterogeneity and plasticity. Our model also predicts that mutations affecting binary cell–ECM interactions are catastrophic and could contribute to loss of tissue architecture in diseases such as breast cancer. PMID:25633040

  13. Causal architecture, complexity and self-organization in time series and cellular automata

    NASA Astrophysics Data System (ADS)

    Shalizi, Cosma Rohilla

    2001-10-01

    All self-respecting nonlinear scientists know self- organization when they see it: except when we disagree. For this reason, if no other, it is important to put some mathematical spine into our floppy intuitive notion of self-organization. Only a few measures of self- organization have been proposed; none can be adopted in good intellectual conscience. To find a decent formalization of self-organization, we need to pin down what we mean by organization. The best answer is that the organization of a process is its causal architecture-its internal, possibly hidden, causal states and their interconnections. Computational mechanics is a method for inferring causal architecture-represented by a mathematical object called the ɛ-machine-from observed behavior. The ɛ-machine captures all patterns in the process which have any predictive power, so computational mechanics is also a method for pattern discovery. In this work, I develop computational mechanics for four increasingly sophisticated types of process-memoryless transducers, time series, transducers with memory, and cellular automata. In each case I prove the optimality and uniqueness of the ɛ-machine's representation of the causal architecture, and give reliable algorithms for pattern discovery. The ɛ-machine is the organization of the process, or at least of the part of it which is relevant to our measurements. It leads to a natural measure of the statistical complexity of processes, namely the amount of information needed to specify the state of the E-machine. Self-organization is a self- generated increase in statistical complexity. This fulfills various hunches which have been advanced in the literature, seems to accord with people's intuitions, and is both mathematically precise and operational.

  14. Emergent cellular self-organization and mechanosensation initiate follicle pattern in the avian skin.

    PubMed

    Shyer, Amy E; Rodrigues, Alan R; Schroeder, Grant G; Kassianidou, Elena; Kumar, Sanjay; Harland, Richard M

    2017-08-25

    The spacing of hair in mammals and feathers in birds is one of the most apparent morphological features of the skin. This pattern arises when uniform fields of progenitor cells diversify their molecular fate while adopting higher-order structure. Using the nascent skin of the developing chicken embryo as a model system, we find that morphological and molecular symmetries are simultaneously broken by an emergent process of cellular self-organization. The key initiators of heterogeneity are dermal progenitors, which spontaneously aggregate through contractility-driven cellular pulling. Concurrently, this dermal cell aggregation triggers the mechanosensitive activation of β-catenin in adjacent epidermal cells, initiating the follicle gene expression program. Taken together, this mechanism provides a means of integrating mechanical and molecular perspectives of organ formation. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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

    PubMed

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

    2015-04-01

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

  16. 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.

  17. Anisotropic cellular network formation in engineered muscle tissue through the self-organization of neurons and endothelial cells.

    PubMed

    Takahashi, Hironobu; Shimizu, Tatsuya; Nakayama, Masamichi; Yamato, Masayuki; Okano, Teruo

    2015-02-18

    Tissue anisotropy directed by cell sheets: Aligned myoblasts can be harvested as an anisotropic cell sheet using a micropatterned thermoresponsive substrate. Neurons and endothelial cells sandwiched between multiple anisotropic cell sheets self-organize oriented cellular networks in the tissue construct. This simple tissue engineering technique is useful for the creation of biomimetic microstructures in complex tissue, required for future advances in regenerative medicine.

  18. 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.

  19. Hyperplectonemes: A Higher Order Compact and Dynamic DNA Self-Organization.

    PubMed

    Japaridze, Aleksandre; Muskhelishvili, Georgi; Benedetti, Fabrizio; Gavriilidou, Agni F M; Zenobi, Renato; De Los Rios, Paolo; Longo, Giovanni; Dietler, Giovanni

    2017-03-08

    Bacterial chromosome has a compact structure that dynamically changes its shape in response to bacterial growth rate and growth phase. Determining how chromatin remains accessible to DNA binding proteins, and transcription machinery is crucial to understand the link between genetic regulation, DNA structure, and topology. Here, we study very large supercoiled dsDNA using high-resolution characterization, theoretical modeling, and molecular dynamics calculations. We unveil a new type of highly ordered DNA organization forming in the presence of attractive DNA-DNA interactions, which we call hyperplectonemes. We demonstrate that their formation depends on DNA size, supercoiling, and bacterial physiology. We compare structural, nanomechanic, and dynamic properties of hyperplectonemes bound by three highly abundant nucleoid-associated proteins (FIS, H-NS, and HU). In all these cases, the negative supercoiling of DNA determines molecular dynamics, modulating their 3D shape. Overall, our findings provide a mechanistic insight into the critical role of DNA topology in genetic regulation.

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

    PubMed

    Nakajima, Kohei; Haruna, Taichi

    2011-09-01

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

  1. Self-organized criticality in a spherically closed cellular automaton: Modeling soft gamma repeater bursts driven by magnetic reconnection

    NASA Astrophysics Data System (ADS)

    Nakazato, Ken'ichiro

    2014-08-01

    A new cellular automaton (CA) model is presented for the self-organized criticality (SOC) in recurrent bursts of soft gamma repeaters (SGRs), which are interpreted as avalanches of reconnection in the magnetosphere of neutron stars. The nodes of a regular dodecahedron and a truncated icosahedron are adopted as spherically closed grids enclosing a neutron star. It is found that the system enters the SOC state if there are sites where the expectation value of the added perturbation is nonzero. The energy distributions of SOC avalanches in CA simulations are described by a power law with a cutoff, which is consistent with the observations of SGR 1806-20 and SGR 1900+14. The power-law index is not universal and depends on the amplitude of the perturbation. This result shows that the SOC of SGRs can be illustrated not only by the crust quake model but also by the magnetic reconnection model.

  2. The emergence of extracellular matrix mechanics and cell traction forces as important regulators of cellular self-organization.

    PubMed

    Checa, Sara; Rausch, Manuel K; Petersen, Ansgar; Kuhl, Ellen; Duda, Georg N

    2015-01-01

    Physical cues play a fundamental role in a wide range of biological processes, such as embryogenesis, wound healing, tumour invasion and connective tissue morphogenesis. Although it is well known that during these processes, cells continuously interact with the local extracellular matrix (ECM) through cell traction forces, the role of these mechanical interactions on large scale cellular and matrix organization remains largely unknown. In this study, we use a simple theoretical model to investigate cellular and matrix organization as a result of mechanical feedback signals between cells and the surrounding ECM. The model includes bi-directional coupling through cellular traction forces to deform the ECM and through matrix deformation to trigger cellular migration. In addition, we incorporate the mechanical contribution of matrix fibres and their reorganization by the cells. We show that a group of contractile cells will self-polarize at a large scale, even in homogeneous environments. In addition, our simulations mimic the experimentally observed alignment of cells in the direction of maximum stiffness and the building up of tension as a consequence of cell and fibre reorganization. Moreover, we demonstrate that cellular organization is tightly linked to the mechanical feedback loop between cells and matrix. Cells with a preference for stiff environments have a tendency to form chains, while cells with a tendency for soft environments tend to form clusters. The model presented here illustrates the potential of simple physical cues and their impact on cellular self-organization. It can be used in applications where cell-matrix interactions play a key role, such as in the design of tissue engineering scaffolds and to gain a basic understanding of pattern formation in organogenesis or tissue regeneration.

  3. 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

  4. 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

    2015-09-03

    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.

  5. 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).

  6. Self-organized criticality

    NASA Astrophysics Data System (ADS)

    Turcotte, Donald L.

    1999-10-01

    The concept of self-organized criticality was introduced to explain the behaviour of the sandpile model. In this model, particles are randomly dropped onto a square grid of boxes. When a box accumulates four particles they are redistributed to the four adjacent boxes or lost off the edge of the grid. Redistributions can lead to further instabilities with the possibility of more particles being lost from the grid, contributing to the size of each avalanche. These model 'avalanches' satisfied a power-law frequency-area distribution with a slope near unity. Other cellular-automata models, including the slider-block and forest-fire models, are also said to exhibit self-organized critical behaviour. It has been argued that earthquakes, landslides, forest fires, and species extinctions are examples of self-organized criticality in nature. In addition, wars and stock market crashes have been associated with this behaviour. The forest-fire model is particularly interesting in terms of its relation to the critical-point behaviour of the site-percolation model. In the basic forest-fire model, trees are randomly planted on a grid of points. Periodically in time, sparks are randomly dropped on the grid. If a spark drops on a tree, that tree and adjacent trees burn in a model fire. The fires are the `avalanches' and they are found to satisfy power-law frequency-area distributions with slopes near unity. This forest-fire model is closely related to the site-percolation model, that exhibits critical behaviour. In the forest-fire model there is an inverse cascade of trees from small clusters to large clusters, trees are lost primarily from model fires that destroy the largest clusters. This quasi steady-state cascade gives a power-law frequency-area distribution for both clusters of trees and smaller fires. The site-percolation model is equivalent to the forest-fire model without fires. In this case there is a transient cascade of trees from small to large clusters and a power

  7. Self-organizing plasmas

    NASA Astrophysics Data System (ADS)

    Hayashi, T.; Sato, T.; Complexity Simulation Group

    1999-03-01

    The primary purpose of this paper is to extract a grand view of self-organization through an extensive computer simulation of plasmas. The assertion is made that self-organization is governed by three key processes, i.e. the existence of an open complex system, the existence of information (energy) sources and the existence of entropy generation and expulsion processes. We find that self-organization takes place in an intermittent fashion when energy is supplied continuously from outside. In contrast, when the system state is suddenly changed into a non-equilibrium state externally, the system evolves stepwise and reaches a minimum energy state. We also find that the entropy production rate is maximized whenever a new ordered structure is created and that if the entropy generated during the self-organizing process is expelled from the system, then the self-organized structure becomes more prominent and clear.

  8. Ultrastructural Analysis of the Human Lens Fiber Cell Remodeling Zone and the Initiation of Cellular Compaction

    PubMed Central

    Costello, M. Joseph; Mohamed, Ashik; Gilliland, Kurt O.; Fowler, W. Craig; Johnsen, Sönke

    2013-01-01

    The purpose is to determine the nature of the cellular rearrangements occurring through the remodeling zone (RZ) in human donor lenses, identified previously by confocal microscopy to be about 100 µm from the capsule. Human donor lenses were fixed with 10% formalin followed by 4% paraformaldehyde prior to processing for transmission electron microscopy. Of 27 fixed lenses, ages 22, 55 and 92 years were examined in detail. Overview electron micrographs confirmed the loss of cellular organization present in the outer cortex (80 µm thick) as the cells transitioned into the RZ. The transition occurred within a few cell layers and fiber cells in the RZ completely lost their classical hexagonal cross-sectional appearance. Cell interfaces became unusually interdigitated and irregular even though the radial cell columns were retained. Gap junctions appeared to be unaffected. After the RZ (40 µm thick), the cells were still irregular but more recognizable as fiber cells with typical interdigitations and the appearance of undulating membranes. Cell thickness was irregular after the RZ with some cells compacted, while others were not, up to the zone of full compaction in the adult nucleus. Similar dramatic cellular changes were observed within the RZ for each lens regardless of age. Because the cytoskeleton controls cell shape, dramatic cellular rearrangements that occur in the RZ most likely are due to alterations in the associations of crystallins to the lens-specific cytoskeletal beaded intermediate filaments. It is also likely that cytoskeletal attachments to membranes are altered to allow undulating membranes to develop. PMID:24183661

  9. Cytoskeletal self-organization in neuromorphogenesis.

    PubMed

    Dehmelt, Leif

    2014-01-01

    Self-organization of dynamic microtubules via interactions with associated motors plays a critical role in spindle formation. The microtubule-based mechanisms underlying other aspects of cellular morphogenesis, such as the formation and development of protrusions from neuronal cells is less well understood. In a recent study, we investigated the molecular mechanism that underlies the massive reorganization of microtubules induced in non-neuronal cells by expression of the neuronal microtubule stabilizer MAP2c. In that study we directly observed cortical dynein complexes and how they affect the dynamic behavior of motile microtubules in living cells. We found that stationary dynein complexes transiently associate with motile microtubules near the cell cortex and that their rapid turnover facilitates efficient microtubule transport. Here, we discuss our findings in the larger context of cellular morphogenesis with specific focus on self-organizing principles from which cellular shape patterns such as the thin protrusions of neurons can emerge.

  10. 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.

  11. 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'.

  12. Emergence or self-organization?

    PubMed Central

    2011-01-01

    Emergence is not well defined, but all emergent systems have the following characteristics: the whole is more than the sum of the parts, they show bottom-up rather top-down organization and, if biological, they involve chemical signaling. Self-organization can be understood in terms of the second and third stages of thermodynamics enabling these stages used as analogs of ecosystem functioning. The second stage system was suggested earlier to provide a useful analog of the behavior of natural and agricultural ecosystems subjected to perturbations, but for this it needs the capacity for self-organization. Considering the hierarchy of the ecosystem suggests that this self-organization is provided by the third stage, whose entropy maximization acts as an analog of that of the soil population when it releases small molecules from much larger molecules in dead plant matter. This it does as vigorously as conditions allow. Through this activity, the soil population confers self-organization at both the ecosystem and the global level. The soil population has been seen as both emergent and self-organizing, supporting the suggestion that the two concepts are are so closely linked as to be virtually interchangeable. If this idea is correct one of the characteristics of a biological emergent system seems to be the ability to confer self-organization on an ecosystem or other entity which may be larger than itself. The beehive and the termite colony are emergent systems which share this ability. PMID:21966574

  13. Self-Organized Criticality Systems

    NASA Astrophysics Data System (ADS)

    Aschwanden, M. J.

    2013-07-01

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

  14. The self-organizing consciousness.

    PubMed

    Perruchet, Pierre; Vinter, Annie

    2002-06-01

    We propose that the isomorphism generally observed between the representations composing our momentary phenomenal experience and the structure of the world is the end-product of a progressive organization that emerges thanks to elementary associative processes that take our conscious representations themselves as the stuff on which they operate, a thesis that we summarize in the concept of Self-Organizing Consciousness (SOC).

  15. Self-Organization and Information

    NASA Astrophysics Data System (ADS)

    Haken, H.

    1987-03-01

    This paper is concerned with processes of self-organization which can take place both in the inanimate and animate world. In particular we study the question what physics can contribute to the understanding of these processes. Its traditional disciplines, namely thermodynamics and statistical mechanics which are concerned with the behavior of multi-component systems, require new ideas and concepts in order to cope with self-organizing systems. These concepts were elaborated in the new field of synergetics from the microscopic point of view. The present paper is mainly concerned with a macroscopic approach. In Section 1 we briefly remind the reader of various concepts of entropy and information and we give brief definitions of structure and self-organization. At present there seems to be no satisfactory definition of complexity available. Section 2 provides two examples of self-organizing systems, namely the laser and slime mold. In Section 3 we briefly remind the reader of the microscopic approach used in synergetics. As a new result it is shown that the information of the total system close to instability points is essentially contained in the information in the order parameters for which the specific example of a single order parameter is then treated explicitly. Finally we show how adequate constraints can be found to formulate the maximum information entropy principle for self-organizing systems. Our approach allows one to deduce the order parameters and dominant spatial patterns of a system which undergoes a non-equilibrium phase transition by means of an algorithm rather than by guessing.

  16. 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

  17. Self-organized criticality in forest-landscape evolution

    Treesearch

    J.C. Sprott; Janine Bolliger; David J. Mladenoff

    2002-01-01

    A simple cellular automaton replicates the fractal pattern of a natural forest landscape and predicts its evolution. Spatial distributions and temporal fluctuations in global quantities show power-law spectra, implying scale-invariance, characteristic of self-organized criticality. The evolution toward the SOC state and the robustness of that state to perturbations...

  18. Understanding and Self-Organization

    PubMed Central

    Newton, Natika W.

    2017-01-01

    How do we manage to understand a completely novel state of affairs, such as the sudden effects of an unexpected earthquake, or the arrival of a total stranger instead of the sister we were waiting for? In each case, for a moment we might be stunned, but we are able quite quickly to fit these events into our overall framework for understanding the world. However, terrified and despairing we feel, we know what earthquakes are and this event fits that schema; in the case of the stranger we know that this kind of thing happens, and that we must ask the stranger “Who are you, and where is my sister?” This paper asks about the mechanisms by which we rapidly achieve an understanding of our world, both the unexpected changes we may experience, and the ongoing comfortable familiarity we normally have with our surroundings. We attempt a solution by means of examining fundamental questions: What is it to understand something?What sorts of things do we try to understand?Is there a conscious EXPERIENCE of understanding?Does understanding involve conscious mental images?What is self-organization? I will argue that these questions revolve around the need of a living organism to take action, and that understanding anything involves knowing how we might act relative to that thing in our environment. The experience of understanding is a feeling that the action affordances of a situation are clear and available. Action (as opposed to reaction) includes imagery, particularly motor imagery, which can be used in the guidance of action. Understanding requires a conscious process involving motor imagery of action affordances, and action can be understood only in self-organizational terms. I explain how self-organization can ground the kinds of action affordance experience needed for conscious understanding. The paper concludes that our day-to-day understanding of our environment is the result of a self-organizing process. PMID:28303093

  19. Understanding and Self-Organization.

    PubMed

    Newton, Natika W

    2017-01-01

    How do we manage to understand a completely novel state of affairs, such as the sudden effects of an unexpected earthquake, or the arrival of a total stranger instead of the sister we were waiting for? In each case, for a moment we might be stunned, but we are able quite quickly to fit these events into our overall framework for understanding the world. However, terrified and despairing we feel, we know what earthquakes are and this event fits that schema; in the case of the stranger we know that this kind of thing happens, and that we must ask the stranger "Who are you, and where is my sister?" This paper asks about the mechanisms by which we rapidly achieve an understanding of our world, both the unexpected changes we may experience, and the ongoing comfortable familiarity we normally have with our surroundings. We attempt a solution by means of examining fundamental questions: What is it to understand something?What sorts of things do we try to understand?Is there a conscious EXPERIENCE of understanding?Does understanding involve conscious mental images?What is self-organization? I will argue that these questions revolve around the need of a living organism to take action, and that understanding anything involves knowing how we might act relative to that thing in our environment. The experience of understanding is a feeling that the action affordances of a situation are clear and available. Action (as opposed to reaction) includes imagery, particularly motor imagery, which can be used in the guidance of action. Understanding requires a conscious process involving motor imagery of action affordances, and action can be understood only in self-organizational terms. I explain how self-organization can ground the kinds of action affordance experience needed for conscious understanding. The paper concludes that our day-to-day understanding of our environment is the result of a self-organizing process.

  20. 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.

  1. CXCL11 Expression by Keratinocytes Occurs Transiently Between Reaching Confluence and Cellular Compaction

    PubMed Central

    Huen, Arthur C.; Marathi, Archana; Nam, Peter K.; Wells, Alan

    2016-01-01

    Objective: To investigate whether differentiation or cellular confluence is responsible for CXCL11 expression patterns in re-epithelialization. Approach: In vitro model systems of re-epithelialization using the HaCaT keratinocyte cell line were utilized in monitoring expression of differentiation markers, including desmoplakin and various cytokeratins while evaluating for an association with chemokine CXCL11 expression. Results: CXCL11 expression was elevated in sparse culture with peak expression near the time of confluence. This somewhat followed the accumulation of desmoplakin in detergent-insoluble pool of proteins. However, in postconfluent, despite continued accumulation of desmoplakin within cells, CXCL11 expression decreased to baseline levels. This biphasic pattern was also seen in low calcium culture, an environment that inhibits keratinocyte differentiation and accumulation of desmosomal proteins. Highest CXCL11-expressing areas best correlated with newly confluent areas within culture expressing basal keratin 14, but also activated keratin 6. Innovation: Achievement of a threshold cellular density induces cell signaling cascade through CXCR3 that, in addition to other undiscovered pathways, can progress cutaneous wounds from the proliferative into the remodeling phases of cutaneous wound healing. Conclusion: These results suggest that the achievement of confluence with increased cellular density by migrating keratinocytes at the wound edge triggers expression of CXCL11. Since CXCR3 stimulation in endothelial cells results in apoptosis and causes neovascular pruning, whereas stimulation of CXCR3 in fibroblasts results decreased motility and cellular contraction, we speculate that CXCL11 expression by epidermal cells upon achieving cellular confluence could be the source of CXCR3 stimulation in the dermis ushering a transition from proliferative to remodeling phases of wound healing. PMID:28078185

  2. 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.

  3. Self-organizing learning array.

    PubMed

    Starzyk, Janusz A; Zhu, Zhen; Liu, Tsun-Ho

    2005-03-01

    A new machine learning concept--self-organizing learning array (SOLAR)--is presented. It is a sparsely connected, information theory-based learning machine, with a multilayer structure. It has reconfigurable processing units (neurons) and an evolvable system structure, which makes it an adaptive classification system for a variety of machine learning problems. Its multilayer structure can handle complex problems. Based on the entropy estimation, information theory-based learning is performed locally at each neuron. Neural parameters and connections that correspond to minimum entropy are adaptively set for each neuron. By choosing connections for each neuron, the system sets up its wiring and completes its self-organization. SOLAR classifies input data based on the weighted statistical information from all the neurons. The system classification ability has been simulated and experiments were conducted using test-bench data. Results show a very good performance compared to other classification methods. An important advantage of this structure is its scalability to a large system and ease of hardware implementation on regular arrays of cells.

  4. Self-Organized Porphyrinic Materials

    PubMed Central

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

    2009-01-01

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

  5. Self-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

  6. 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.

  7. Self-organized cell motility

    NASA Astrophysics Data System (ADS)

    Du, Xinxin; Doubrovinski, Konstantin

    2011-03-01

    Cell migration plays a key role in a wide range of biological phenomena, such as morphogenesis, chemotaxis, and wound healing. Cell locomotion relies on the cytoskeleton, a meshwork of filamentous proteins, intrinsically out of thermodynamic equilibrium and cross-linked by molecular motors, proteins that turn chemical energy into mechanical work. In the course of locomotion, cells remain polarized, i.e. they retain a single direction of motion in the absence of external cues. Traditionally, polarization has been attributed to intracellular signaling. However, recent experiments show that polarization may be a consequence of self-organized cytoskeletal dynamics. Our aim is to elucidate the mechanisms by which persistent unidirectional locomotion may arise through simple mechanical interactions of the cytoskeletal proteins. To this end, we develop a simple physical description of cytoskeletal dynamics. We find that the proposed description accounts for a range of phenomena associated with cell motility, including spontaneous polarization, persistent unidirectional motion, and the co-existence of motile and non-motile states.

  8. Adaptation to optimal cell growth through self-organized criticality.

    PubMed

    Furusawa, Chikara; Kaneko, Kunihiko

    2012-05-18

    A simple cell model consisting of a catalytic reaction network is studied to show that cellular states are self-organized in a critical state for achieving optimal growth; we consider the catalytic network dynamics over a wide range of environmental conditions, through the spontaneous regulation of nutrient transport into the cell. Furthermore, we find that the adaptability of cellular growth to reach a critical state depends only on the extent of environmental changes, while all chemical species in the cell exhibit correlated partial adaptation. These results are in remarkable agreement with the recent experimental observations of the present cells.

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  10. Self-Organizing Tissue-Engineered Constructs in Collagen Hydrogels

    PubMed Central

    Gourdie, Robert G.; Myers, Tereance A.; McFadden, Alex; Li, Yin-xiong; Potts, Jay D.

    2016-01-01

    A novel self-organizing behavior of cellularized gels composed of collagen type 1 that may have utility for tissue engineering is described. Depending on the starting geometry of the tissue culture well, toroidal rings of cells or hollow spheroids were prompted to form autonomously when cells were seeded onto the top of gels and the gels released from attachment to the culture well 12 to 24 h after seeding. Cells within toroids assumed distinct patterns of alignment not seen in control gels in which cells had been mixed in. In control gels, cells formed complex three-dimensional arrangements and assumed relatively higher levels of heterogeneity in expression of the fibronectin splice variant ED-A—a marker of epithelial mesenchymal transformation. The tissue-like constructs resulting from this novel self-organizing behavior may have uses in wound healing and regenerative medicine, as well as building blocks for the iterative assembly of synthetic biological structures. PMID:22214557

  11. Quantifying self-organization in fusion plasmas

    NASA Astrophysics Data System (ADS)

    Rajković, M.; Milovanović, M.; Škorić, M. M.

    2017-05-01

    A multifaceted framework for understanding self-organization in fusion plasma dynamics is presented which concurrently manages several important issues related to the nonlinear and multiscale phenomena involved, namely,(1) it chooses the optimal template wavelet for the analysis of temporal or spatio-temporal plasma dynamics, (2) it detects parameter values at which bifurcations occur, (3) it quantifies complexity and self-organization, (4) it enables short-term prediction of nonlinear dynamics, and (5) it extracts coherent structures in turbulence by separating them from the incoherent component. The first two aspects including the detection of changes in the dynamics of a nonlinear system are illustrated by analyzing Stimulated Raman Scattering in a bounded, weakly dissipative plasma. Self-organization in the fusion plasma is quantitatively analyzed based on the numerical simulations of the Gyrokinetic-Vlasov (GKV) model of plasma dynamics. The parameters for the standard and inward shifted magnetic configurations, relevant for the Large Helical Device, were used in order to quantitatively compare self-organization and complexity in the two configurations. Finally, self-organization is analyzed for three different confinement regimes of the MAST device.

  12. Self-organization in social tagging systems

    NASA Astrophysics Data System (ADS)

    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.

  13. Regeneration, morphogenesis and self-organization.

    PubMed

    Goldman, Daniel

    2014-07-01

    The RIKEN Center for Developmental Biology in Kobe, Japan, hosted a meeting entitled 'Regeneration of Organs: Programming and Self-Organization' in March, 2014. Scientists from across the globe met to discuss current research on regeneration, organ morphogenesis and self-organization - and the links between these fields. A diverse range of experimental models and organ systems was presented, and the speakers aptly illustrated the unique power of each. This Meeting Review describes the major advances reported and themes emerging from this exciting meeting. © 2014. Published by The Company of Biologists Ltd.

  14. Protein Folding and Self-Organized Criticality

    NASA Astrophysics Data System (ADS)

    Bajracharya, Arun; Murray, Joelle

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

  15. Self-organizing sensing and actuation for automatic control

    DOEpatents

    Cheng, George Shu-Xing

    2017-07-04

    A Self-Organizing Process Control Architecture is introduced with a Sensing Layer, Control Layer, Actuation Layer, Process Layer, as well as Self-Organizing Sensors (SOS) and Self-Organizing Actuators (SOA). A Self-Organizing Sensor for a process variable with one or multiple input variables is disclosed. An artificial neural network (ANN) based dynamic modeling mechanism as part of the Self-Organizing Sensor is described. As a case example, a Self-Organizing Soft-Sensor for CFB Boiler Bed Height is presented. Also provided is a method to develop a Self-Organizing Sensor.

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

    PubMed

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

    2016-10-04

    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.

  17. 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

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

    NASA Astrophysics Data System (ADS)

    Dewers, T. A.

    2010-12-01

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

  19. 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.

  20. 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.

  1. 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.

  2. Evolutionary aspect of protein self-organization

    NASA Astrophysics Data System (ADS)

    Rapis, E.

    2008-06-01

    Numerous experimental data (published in 1988 2006) show that, when an open protein-water system far from thermodynamic equilibrium is dehydrated (dried), abiogenic self-organization of the protein invariably takes place, which complicates the structure and also results in the formation of a 3D supramolecular architecture with synchronous replication of spiral vortices and domains (cells) with nuclei having spiral clockwise and counterclockwise symmetry typical of protein in the living organism. When a solvent evaporates, say, from a multicomponent solution, such as blood serum, a protein structure arises the morphology of which copies the morphology of the protein one-component system. Thus, the competing activity of protein is observed when it experiences phase transition in the course of self-organization. In light of a new evolutionary chemical theory based on the Rudenko concept, these data allow one to put forward a hypothesis that protein exhibits evolutionary properties under conditions far from thermodynamic equilibrium. This hypothesis relies on the assumption that the energetically active structure of protein self-organizing in the course of its phase transition may generate energy necessary for catalysis and autocatalysis when a one-component protein-water system dries out. An important piece of evidence in favor of this hypothesis is the presence of the basic type of symmetry (spiral mirror clockwise or counterclockwise symmetry) under the given nonequilibrium conditions in vitro, which is characteristic of animate nature, protein in the living organism in vivo, and abiogenic self-organization of protein in vitro.

  3. How self-organization can guide evolution.

    PubMed

    Glancy, Jonathan; Stone, James V; Wilson, Stuart P

    2016-11-01

    Self-organization and natural selection are fundamental forces that shape the natural world. Substantial progress in understanding how these forces interact has been made through the study of abstract models. Further progress may be made by identifying a model system in which the interaction between self-organization and selection can be investigated empirically. To this end, we investigate how the self-organizing thermoregulatory huddling behaviours displayed by many species of mammals might influence natural selection of the genetic components of metabolism. By applying a simple evolutionary algorithm to a well-established model of the interactions between environmental, morphological, physiological and behavioural components of thermoregulation, we arrive at a clear, but counterintuitive, prediction: rodents that are able to huddle together in cold environments should evolve a lower thermal conductance at a faster rate than animals reared in isolation. The model therefore explains how evolution can be accelerated as a consequence of relaxed selection, and it predicts how the effect may be exaggerated by an increase in the litter size, i.e. by an increase in the capacity to use huddling behaviours for thermoregulation. Confirmation of these predictions in future experiments with rodents would constitute strong evidence of a mechanism by which self-organization can guide natural selection.

  4. Neurodynamics with spatial self-organizations.

    PubMed

    Zak, M

    1991-01-01

    A neural network architecture with self-organization in phase and actual space is proposed and discussed. Special type of differential local interconnections simulating diffusion, dispersion, and convection were investigated. It is shown that these interconnections are responsible for biological pattern formation in a homogeneous neural structure. The model suggests a phenomenological explanation of the mechanisms of edge detection in vision process.

  5. Self-Organizing Tree Using Cluster Validity

    NASA Astrophysics Data System (ADS)

    Sasaki, Yasue; Suzuki, Yukinori; Miyamoto, Takayuki; Maeda, Junji

    Self-organizing tree (S-TREE) models solve clustering problems by imposing tree-structured constraints on the solution. It has a self-organizing capacity and has better performance than previous tree-structured algorithms. S-TREE carries out pruning to reduce the effect of bad leaf nodes when the tree reaches a predetermined maximum size (U), However, it is difficult to determine U beforehand because it is problem-dependent. U gives the limit of tree growth and can also prevent self-organization of the tree. It may produce an unnatural clustering. In this paper, we propose an algorithm for pruning algorithm that does not require U. This algorithm prunes extra nodes based on a significant level of cluster validity and allows the S-TREE to grow by a self-organization. The performance of the new algorithm was examined by experiments on vector quantization. The results of experiments show that natural leaf nodes are formed by this algorithm without setting the limit for the growth of the S-TREE.

  6. How self-organization can guide evolution

    PubMed Central

    Glancy, Jonathan; Stone, James V.

    2016-01-01

    Self-organization and natural selection are fundamental forces that shape the natural world. Substantial progress in understanding how these forces interact has been made through the study of abstract models. Further progress may be made by identifying a model system in which the interaction between self-organization and selection can be investigated empirically. To this end, we investigate how the self-organizing thermoregulatory huddling behaviours displayed by many species of mammals might influence natural selection of the genetic components of metabolism. By applying a simple evolutionary algorithm to a well-established model of the interactions between environmental, morphological, physiological and behavioural components of thermoregulation, we arrive at a clear, but counterintuitive, prediction: rodents that are able to huddle together in cold environments should evolve a lower thermal conductance at a faster rate than animals reared in isolation. The model therefore explains how evolution can be accelerated as a consequence of relaxed selection, and it predicts how the effect may be exaggerated by an increase in the litter size, i.e. by an increase in the capacity to use huddling behaviours for thermoregulation. Confirmation of these predictions in future experiments with rodents would constitute strong evidence of a mechanism by which self-organization can guide natural selection. PMID:28018644

  7. Controlled Emergence and Self-Organization

    NASA Astrophysics Data System (ADS)

    Müller-Schloer, Christian; Sick, Bernhard

    Admiration of nature's ability to develop robust self-organizing and complex structures showing emergent behavior was the starting point for the Organic Computing (OC) endeavor. Although the concepts of self-organization and emergence have been subject to extensive investigations and discussions for more than 100 years, soon it became clear that we lack a quantitative assessment of these concepts as a basis for an implementation in technical systems. The main questions to be answered in this context are: Can we define emergence and self-organization (or sub-concepts thereof) compatible with a quantitative, experimental, and objectifiable method as required in natural science? Can we control self-organization and emergence without forcing their meaning? Are there generic architectures generally applicable to technical systems serving this purpose? In this chapter, we will try to give some answers to these questions. After an introduction and specificationv of the problem we will review some recent approaches to a definition of emergence and assess them with respect to their usability in our technical context. We will then introduce an architectural template, the Observer/Controller architecture, which seems to be a key feature in most OC systems. In addition to the general pattern -; essentially constituting a higher-level control loop -; this Observer/Controller architecture will be developed in some detail as a framework for own implementations. We present a quantitative approach for a technically relevant definition of emergence and self-organization, and propose a systematic approach to a ranking of various Observer/Controller architectures.

  8. Self-Organizing Systems Show Apparent Intentionality

    NASA Astrophysics Data System (ADS)

    Tschacher, Wolfganfg; Dauwalder, Jean-Pierre; Haken, Hermann

    Cognitive science is frequently confronted with mind-body issues—is there a way by which the mentalist and the physical approaches to cognition can be integrated? Can the intentional attributes of mind be understood in physical terms? We propose that synergetics, the theory of nonlinear complex systems, offers steps towards a possible solution to this notorious problem. In particular, we claim that an essential property of self-organized pattern formation lies in its functionality, i.e. the ability to respond and adapt 'meaningfully' to environmental constraints. Patterns become functional because they consume the gradients that caused their evolution, and, in addition, they consume them in the most efficient manner. This makes synergetic pattern formation appear 'intentional'. Therefore, we suggest that self-organization phenomena may be considered basic explanations of the adaptive, intentional, and purposive behavior of many complex systems, in particular cognitive systems.

  9. Self-organization of cognitive performance.

    PubMed

    Van Orden, Guy C; Holden, John G; Turvey, Michael T

    2003-09-01

    Background noise is the irregular variation across repeated measurements of human performance. Background noise remains after task and treatment effects are minimized. Background noise refers to intrinsic sources of variability, the intrinsic dynamics of mind and body, and the internal workings of a living being. Two experiments demonstrate 1/f scaling (pink noise) in simple reaction times and speeded word naming times, which round out a catalog of laboratory task demonstrations that background noise is pink noise. Ubiquitous pink noise suggests processes of mind and body that change each other's dynamics. Such interaction-dominant dynamics are found in systems that self-organize their behavior. Self-organization provides an unconventional perspective on cognition, but this perspective closely parallels a contemporary interdisciplinary view of living systems.

  10. 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.

  11. 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

  12. 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.

  13. Self-Organized Criticality and earthquakes

    SciTech Connect

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

    2007-12-06

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

  14. Perception and self-organized instability

    PubMed Central

    Friston, Karl; Breakspear, Michael; Deco, Gustavo

    2012-01-01

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

  15. 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.

  16. 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

  17. Self-organized criticality in a computer network model

    PubMed

    Yuan; Ren; Shan

    2000-02-01

    We study the collective behavior of computer network nodes by using a cellular automaton model. The results show that when the load of network is constant, the throughputs and buffer contents of nodes are power-law distributed in both space and time. Also the feature of 1/f noise appears in the power spectrum of the change of the number of nodes that bear a fixed part of the system load. It can be seen as yet another example of self-organized criticality. Power-law decay in the distribution of buffer contents implies that heavy network congestion occurs with small probability. The temporal power-law distribution for throughput might be a reasonable explanation for the observed self-similarity in computer network traffic.

  18. Self-Organization Activities of College Students: Challenges and Opportunities

    ERIC Educational Resources Information Center

    Shmurygina, Natalia; Bazhenova, Natalia; Bazhenov, Ruslan; Nikolaeva, Natalia; Tcytcarev, Andrey

    2016-01-01

    The article provides the analysis of self-organization activities of college students related to their participation in youth associations activities. The purpose of research is to disclose a degree of students' activities demonstration based on self-organization processes, assessment of existing self-organization practices of the youth,…

  19. Self-organized criticality in fragmenting

    NASA Astrophysics Data System (ADS)

    Oddershede, Lene; Dimon, Peter; Bohr, Jakob

    1993-11-01

    The measured mass distributions of fragments from 26 fractured objects of gypsum, soap, stearic paraffin, and potato show evidence of obeying scaling laws; this suggests the possibility of self-organized criticality in fragmenting. The probability of finding a fragment scales inversely to a power of the mass; the power, or scaling exponent, was found to depend on the shape of the object rather than on the material. For objects of different shapes (balls, cubes, half cubes, plates, and bars) scaling was found for fragment sizes smaller than the smallest dimension of the object undergoing fragmentation.

  20. Self-organized criticality on quasiperiodic graphs

    NASA Astrophysics Data System (ADS)

    Joseph, D.

    1999-09-01

    Self-organized critical models are used to describe the 1/f-spectra of rather different physical situations like snow avalanches, noise of electric currents, luminosities of stars or topologies of landscapes. The prototype of the SOC-models is the sandpile model of Bak, Tang and Wiesenfeld (Phys. Rev. Lett. 59, (1987) 351). We implement this model on non-periodic graphs where it can become either isotropic or anisotropic and compare its properties with the periodic counterpart on the square lattice.

  1. Self-organized model of cascade spreading

    NASA Astrophysics Data System (ADS)

    Gualdi, S.; Medo, M.; Zhang, Y.-C.

    2011-01-01

    We study simultaneous price drops of real stocks and show that for high drop thresholds they follow a power-law distribution. To reproduce these collective downturns, we propose a minimal self-organized model of cascade spreading based on a probabilistic response of the system elements to stress conditions. This model is solvable using the theory of branching processes and the mean-field approximation. For a wide range of parameters, the system is in a critical state and displays a power-law cascade-size distribution similar to the empirically observed one. We further generalize the model to reproduce volatility clustering and other observed properties of real stocks.

  2. Tunable self-organization of nanocomposite multilayers

    NASA Astrophysics Data System (ADS)

    Chen, C. Q.; Pei, Y. T.; Shaha, K. P.; De Hosson, J. Th. M.

    2010-02-01

    In this letter we report the controlled growth and microstructural evolution of self-assembled nanocomposite multilayers that are induced by surface ion-impingement. The nanoscale structures together with chemical composition, especially at the growing front, have been investigated with high-resolution transmission electron microscopy. Concurrent ion impingement of growing films produces an amorphous capping layer 3 nm in thickness where spatially modulated phase separation is initiated. It is shown that the modulation of multilayers as controlled by the self-organization of nanocrystallites below the capping layer, can be tuned through the entire film.

  3. 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.

  4. Do earthquakes exhibit self-organized criticality?

    PubMed

    Yang, Xiaosong; Du, Shuming; Ma, Jin

    2004-06-04

    If earthquakes are phenomena of self-organized criticality (SOC), statistical characteristics of the earthquake time series should be invariant after the sequence of events in an earthquake catalog are randomly rearranged. In this Letter we argue that earthquakes are unlikely phenomena of SOC because our analysis of the Southern California Earthquake Catalog shows that the first-return-time probability PM(T) is apparently changed after the time series is rearranged. This suggests that the SOC theory should not be used to oppose the efforts of earthquake prediction.

  5. Robin Hood as self-organized criticality

    NASA Astrophysics Data System (ADS)

    Zaitsev, S. I.

    1992-11-01

    It is shown that a wide class of physical processes named low-temperature creep (or Robin Hood systems) has to demonstrate self-organized criticality. At least “real” and “toy” models (1D and 2D) demonstrate long range (restricted by the model size only) spatial correlation in Monte Carlo simulation. The models can be used for investigation of such phenomena as dislocation glide, movement of flux in superconductors, movement of domain walls in magnetics, grain boundaries in polycrystals, plastic deformation and so on.

  6. Self-organized chaos through polyhomeostatic optimization.

    PubMed

    Markovic, D; Gros, Claudius

    2010-08-06

    The goal of polyhomeostatic control is to achieve a certain target distribution of behaviors, in contrast to homeostatic regulation, which aims at stabilizing a steady-state dynamical state. We consider polyhomeostasis for individual and networks of firing-rate neurons, adapting to achieve target distributions of firing rates maximizing information entropy. We show that any finite polyhomeostatic adaption rate destroys all attractors in Hopfield-like network setups, leading to intermittently bursting behavior and self-organized chaos. The importance of polyhomeostasis to adapting behavior in general is discussed.

  7. Phase diagrams of self-organizing maps

    NASA Astrophysics Data System (ADS)

    Bauer, H.-U.; Riesenhuber, M.; Geisel, T.

    1996-09-01

    We present a method which allows the analytic determination of phase diagrams in the self-organizing map, a model for the formation of topographic projection patterns in the brain and in signal processing applications. The method only requires an ansatz for the tesselation of the data space induced by the map, not for the explicit state of the map. We analytically obtain phase diagrams for various examples, including models for the development of orientation and ocular-dominance maps. The latter phase diagram exhibits transitions to broadening ocular-dominance patterns as observed in a recent experiment.

  8. Temporal Self-organization in Galaxy Formation

    NASA Astrophysics Data System (ADS)

    Cen, Renyue

    2014-04-01

    We report on the discovery of a relation between the number of star formation (SF) peaks per unit time, νpeak, and the size of the temporal smoothing window function, Δt, used to define the peaks: νpeakvpropΔt 1 - phi (phi ~ 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 phi - 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.

  9. Non-Equilibrium Nanoscale Self-Organization

    SciTech Connect

    Aziz, Michael J

    2006-03-09

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

  10. 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.

  11. 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.

  12. 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.

  13. The self-organization of speech sounds.

    PubMed

    Oudeyer, Pierre-Yves

    2005-04-07

    The speech code is a vehicle of language: it defines a set of forms used by a community to carry information. Such a code is necessary to support the linguistic interactions that allow humans to communicate. How then may a speech code be formed prior to the existence of linguistic interactions? Moreover, the human speech code is discrete and compositional, shared by all the individuals of a community but different across communities, and phoneme inventories are characterized by statistical regularities. How can a speech code with these properties form? We try to approach these questions in the paper, using the "methodology of the artificial". We build a society of artificial agents, and detail a mechanism that shows the formation of a discrete speech code without pre-supposing the existence of linguistic capacities or of coordinated interactions. The mechanism is based on a low-level model of sensory-motor interactions. We show that the integration of certain very simple and non-language-specific neural devices leads to the formation of a speech code that has properties similar to the human speech code. This result relies on the self-organizing properties of a generic coupling between perception and production within agents, and on the interactions between agents. The artificial system helps us to develop better intuitions on how speech might have appeared, by showing how self-organization might have helped natural selection to find speech.

  14. Dynamics of self-organized vegetation patterns

    NASA Astrophysics Data System (ADS)

    Foti, R.; Ramirez, J. A.

    2011-12-01

    Vegetation patterns are a common and well-defined characteristic of many arid and semi-arid landscapes. In this study we explore some of the physical mechanisms responsible for the establishment of self-organized, non-random vegetation patterns that arise at the hillslope scale in many areas of the world, especially in arid and semi-arid regions. In doing so we use a water and energy balance model and provide a fundamental mechanistic understanding of the dynamics of vegetation pattern formation and development. Within the modeling, reciprocal effects of vegetation on the hillslope energy balance, runoff production and run-on infiltration, root density, surface albedo and soil moisture content are analyzed. In particular, we: 1) present a physically based mechanistic description of the processes leading to vegetation pattern formation; 2) Compare simulated vegetation coverage at the hillslope scale with observations; 3) quantify the relative impact of pattern-inducing dynamics on pattern formation; and 4) describe the relationships between vegetation patterns and the climatic, hydraulic and topographic characteristic of the system. The model is validated by comparing hillslope-scale simulations with available observations for the areas of Niger near Niamey and Somalia near Garoowe, where respectively tiger bushes and banded vegetation patterns are present. The model validation includes comparison of simulated and observed vegetation coverage as well as simulated and measured water fluxes, showing both qualitative and quantitative agreement between simulations and observations. The analysis of the system suggests that the main driver of pattern establishment is climate, in terms of average annual precipitation and incoming solar radiation. In particular, decreasing precipitation or, conversely, increasing incoming radiation are responsible for the system departure from fully vegetated with indistinguishable vegetation structures to sparsely vegetated with (self-organized

  15. Pearls are self-organized natural ratchets.

    PubMed

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

    2013-07-02

    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.

  16. Supramolecular materials: Self-organized nanostructures

    SciTech Connect

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

    1997-04-18

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

  17. 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.

  18. Self-organizing distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Clare, Loren P.; Pottie, Gregory J.; Agre, Jonathan R.

    1999-07-01

    Advances in CMOS IC and micro electrical-mechanical systems (MEMS) technologies are enabling construction of low-cost building blocks each of which incorporates sensing, signal processing, and wireless communications. Collections of these integrated microsensor nodes may be formed into sensor networks in a wide variety of ways, with characteristics that depend on the specific application--the total number of nodes, the spatial density, the geometric configuration (e.g., linear vs. areal), topographic aspects (e.g., smooth vs. rough terrain), and proximity and proportion of user/sink points. The power of these distributed sensor networks will be unleashed by means of their ability to self-organize, i.e., to bootstrap and dynamically maintain organizational structure befitting the purpose and situation that is presented, without the need for human assistance. A prototype sensor system and networking protocols are being developed under the DARPA/TTO AWAIRS Program and are described.

  19. 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.

  20. Self-organized criticality in a nutshell

    NASA Astrophysics Data System (ADS)

    Nagler, J.; Hauert, C.; Schuster, H. G.

    1999-09-01

    In order to gain insight into the nature of self-organized criticality (SOC), we present a minimal model exhibiting this phenomenon. In this analytically solvable model, the state of the system is fully described by a single-integer variable. The system organizes in its critical state without external tuning. We derive analytically the probability distribution of durations of disturbances propagating through the system. As required by SOC, this distribution is scale invariant and follows a power law over several orders of magnitude. Our solution also reproduces the exponential tail of the distribution due to finite size effects. Moreover, we show that large avalanches are suppressed when stabilizing the system in its critical state. Interestingly, avalanches are affected in a similar way when driving the system away from the critical state. With this model, we have reduced SOC dynamics to a leveling process as described by Ehrenfest's famous flea model.

  1. Self-organized atomic switch networks

    NASA Astrophysics Data System (ADS)

    Stieg, Adam Z.; Avizienis, Audrius V.; Sillin, Henry O.; Martin-Olmos, Cristina; Lam, Miu-Ling; Aono, Masakazu; Gimzewski, James K.

    2014-01-01

    The spontaneous emergence of complex behavior in dynamical systems occurs through the collective interaction of nonlinear elements toward a highly correlated, non-equilibrium critical state. Criticality has been proposed as a model for understanding complexity in systems whose behavior can be approximated as a state lying somewhere between order and chaos. Here we present unique, purpose-built devices, known as atomic switch networks (ASN), specifically designed to generate the class of emergent properties which underlie critical dynamics in complex systems. The network is an open, dissipative system comprised of highly interconnected (˜109/cm2) atomic switch interfaces wired through the spontaneous electroless deposition of metallic silver fractal architectures. The functional topology of ASN architectures self-organizes to produce persistent critical dynamics without fine-tuning, indicating a capacity for memory and learning via persistent critical states toward potential utility in real-time, neuromorphic computation.

  2. Self-organization, transformity, and information.

    PubMed

    Odum, H T

    1988-11-25

    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.

  3. 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

  4. 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.

  5. A self-organized neural comparator.

    PubMed

    Ludueña, Guillermo A; Gros, Claudius

    2013-04-01

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

  6. 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.

  7. Self-organized growth of germanium nanocolumns

    NASA Astrophysics Data System (ADS)

    Mussabek, G. K.; Yermukhamed, D.; Dikhanbayev, K. K.; Schleusener, A.; Mathur, S.; Sivakov, V.

    2017-03-01

    The crystalline germanium nanostructures were obtained on a silicon surface by the chemical vapor deposition technique using a germanium (IV) iso-propoxide ([Ge(OiPr)4]) metalorganic precursor as a germanium source. As was observed, the one-dimensional (1D) germanium nanostructures on the silicon surface form without using a metal catalyst, meaning that the formation of 1D nanostructures is based not on a vapor-liquid-solid (VLS) growth mechanism, but on self-organization processes which take place on the silicon surfaces during the CVD process of germanium iso-propoxide pyrolysis. Our observation suggests that the non-catalytic growth of germanium nanocolumns is strongly dependent on the CVD process temperature. The germanium phase composition and morphology have been investigated by x-ray diffraction (XRD) and x-ray photoelectron spectroscopy (XPS), and high resolution scanning electron microscopy (HRSEM), respectively. Our results provide a new way to grow 1D germanium nanostructures without contamination by a catalyst, which the vapor-liquid-solid growth mechanism is known to cause, allowing for the application of such materials in micro- and optoelectronics.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. Web content management by self-organization.

    PubMed

    Freeman, Richard T; Yin, Hujun

    2005-09-01

    We present a new method for content management and knowledge discovery using a topology-preserving neural network. The method, termed topological organization of content (TOC), can generate a taxonomy of topics from a set of unannotated, unstructured documents. The TOC consists of a hierarchy of self-organizing growing chains (GCs), each of which can develop independently in terms of size and topics. The dynamic development process is validated continuously using a proposed entropy-based Bayesian information criterion (BIC). Each chain meeting the criterion spans child chains, with reduced vocabularies and increased specializations. This results in a topological tree hierarchy, which can be browsed like a table of contents directory or web portal. A brief review is given on existing methods for document clustering and organization, and clustering validation measures. The proposed approach has been tested and compared with several existing methods on real world web page datasets. The results have clearly demonstrated the advantages and efficiency in content organization of the proposed method in terms of computational cost and representation. The TOC can be easily adapted for large-scale applications. The topology provides a unique, additional feature for retrieving related topics and confining the search space.

  13. Self-organization and complexity in historical landscape patterns

    Treesearch

    Janine Bolliger; Julien C. Sprott; David J. Mladenoff

    2003-01-01

    Self-organization describes the evolution process of complex structures where systems emerge spontaneously, driven internally by variations of the system itself. Self-organization to the critical state is manifested by scale-free behavior across many orders of magnitude (Bak et al. 1987, Bak 1996, Sole et a1. 1999). Spatial scale-free behavior implies fractal...

  14. Formation And Maintenance of Self-Organizing Wireless Networks

    NASA Technical Reports Server (NTRS)

    Scott, Keith; Bambos, Nicholas

    1997-01-01

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

  15. 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.

  16. 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.

  17. 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.

  18. Fractal Self-Organization of Bacteria-Inspired Agents

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

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

  19. Self-organization in chronic pain: a concept analysis.

    PubMed

    Monsivais, Diane

    2005-01-01

    The purpose of this article is to examine the concept of self-organization in chronic pain using Rodgers' (2000) evolutionary approach. This article describes the antecedents, attributes, and consequences of self-organization in chronic pain. Self-organization in chronic pain may be achieved through the attributes of being believed, accessing credible resources, and taking action and responsibility. Self-organization occurs when the patient with pain develops a transformed identity, new insights, and is an active, in-control participant in care. Chronic pain is a common and costly problem, and recognition of the key attributes of self-organization in this condition is an important step in promoting positive health outcomes. Rehabilitation nurses play a key role in providing credible resources and working with the patient to take action and responsibility.

  20. Designed self-organization for molecular optoelectronics

    NASA Astrophysics Data System (ADS)

    Norton, Michael; Neff, David; Towler, Ian; Day, Scott; Grambos, Zachary; Shremshock, Mikala; Butts, Heather; Meadows, Christiaan; Samiso, Yuko; Cao, Huan; Rahman, Mashiur

    2006-05-01

    The convergence of terahertz spectroscopy and single molecule experimentation offer significant promise of enhancement in sensitivity and selectivity in molecular recognition, identification and quantitation germane to military and security applications. This presentation reports the results of experiments which address fundamental barriers to the integration of large, patterned bio-compatible molecular opto-electronic systems with silicon based microelectronic systems. The central thrust of this approach is sequential epitaxy on surface bound single stranded DNA one-dimensional substrates. The challenge of producing highly structured macromolecular substrates, which are necessary in order to implement molecular nanolithography, has been addressed by combining "designer" synthetic DNA with biosynthetically derived plasmid components. By design, these one dimensional templates are composed of domains which contain sites which are recognized, and therefore addressable by either complementary DNA sequences and/or selected enzymes. Such design is necessary in order to access the nominal 2 nm linewidth potential resolution of nanolithography on these one-dimensional substrates. The recognition and binding properties of DNA ensure that the lithographic process is intrinsically self-organizing, and therefore self-aligning, a necessity for assembly processes at the requisite resolution. Another requirement of this molecular epitaxy approach is that the substrate must be immobilized. The challenge of robust surface immobilization is being addressed via the production of the equivalent of molecular tube sockets. In this application, multi-valent core-shell fluorescent quantum dots provide a mechanism to prepare surface attachment sites with a pre-determined 1:1 attachment site : substrate (DNA) molecule ratio.

  1. 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.

  2. 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.

  3. Essentials of the self-organizing map.

    PubMed

    Kohonen, Teuvo

    2013-01-01

    The self-organizing map (SOM) is an automatic data-analysis method. It is widely applied to clustering problems and data exploration in industry, finance, natural sciences, and linguistics. The most extensive applications, exemplified in this paper, can be found in the management of massive textual databases and in bioinformatics. The SOM is related to the classical vector quantization (VQ), which is used extensively in digital signal processing and transmission. Like in VQ, the SOM represents a distribution of input data items using a finite set of models. In the SOM, however, these models are automatically associated with the nodes of a regular (usually two-dimensional) grid in an orderly fashion such that more similar models become automatically associated with nodes that are adjacent in the grid, whereas less similar models are situated farther away from each other in the grid. This organization, a kind of similarity diagram of the models, makes it possible to obtain an insight into the topographic relationships of data, especially of high-dimensional data items. If the data items belong to certain predetermined classes, the models (and the nodes) can be calibrated according to these classes. An unknown input item is then classified according to that node, the model of which is most similar with it in some metric used in the construction of the SOM. A new finding introduced in this paper is that an input item can even more accurately be represented by a linear mixture of a few best-matching models. This becomes possible by a least-squares fitting procedure where the coefficients in the linear mixture of models are constrained to nonnegative values.

  4. 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

  5. Self-organization in coordination-driven self-assembly.

    PubMed

    Northrop, Brian H; Zheng, Yao-Rong; Chi, Ki-Whan; Stang, Peter J

    2009-10-20

    Self-assembly allows for the preparation of highly complex molecular and supramolecular systems from relatively simple starting materials. Typically, self-assembled supramolecules are constructed by combining complementary pairs of two highly symmetric molecular components, thus limiting the chances of forming unwanted side products. Combining asymmetric molecular components or multiple complementary sets of molecules in one complex mixture can produce myriad different ordered and disordered supramolecular assemblies. Alternatively, spontaneous self-organization phenomena can promote the formation of specific product(s) out of a collection of multiple possibilities. Self-organization processes are common throughout much of nature and are especially common in biological systems. Recently, researchers have studied self-organized self-assembly in purely synthetic systems. This Account describes our investigations of self-organization in the coordination-driven self-assembly of platinum(II)-based metallosupramolecules. The modularity of the coordination-driven approach to self-assembly has allowed us to systematically study a wide variety of different factors that can control the extent of supramolecular self-organization. In particular, we have evaluated the effects of the symmetry and polarity of ambidentate donor subunits, differences in geometrical parameters (e.g., the size, angularity, and dimensionality) of Pt(II)-based acceptors and organic donors, the influence of temperature and solvent, and the effects of intermolecular steric interactions and hydrophobic interactions on self-organization. Our studies have shown that the extent of self-organization in the coordination-driven self-assembly of both 2D polygons and 3D polyhedra ranges from no organization (a statistical mixture of multiple products) to amplified organization (wherein a particular product or products are favored over others) and all the way to the absolute self-organization of discrete

  6. Self-Organization in Coordination-Driven Self-Assembly

    PubMed Central

    Northrop, Brian H.; Zheng, Yao-Rong; Chi, Ki-Whan; Stang, Peter J.

    2009-01-01

    Conspectus Self-assembly allows for the preparation of highly complex molecular and supramolecular systems from relatively simple starting materials. Typically, self-assembled supramolecules are constructed by combining complementary pairs of two highly symmetric molecular components, thus limiting the chances of forming unwanted side products. Combining asymmetric molecular components or multiple complementary sets of molecules in one complex mixture can produce myriad different ordered and disordered supramolecular assemblies. Alternatively, spontaneous self-organization phenomena can promote the formation of specific product(s) out of a collection of multiple possibilities. Self-organization processes are common throughout much of nature and are especially common in biological systems. Recently, researchers have studied self-organized self-assembly in purely synthetic systems. This Account describes our investigations of self-organization in the coordination-driven self-assembly of platinum(II)-based metallosupramolecules. The modularity of the coordination-driven approach to self-assembly has allowed us to systematically study a wide variety of different factors that can control the extent of supramolecular self-organization. In particular, we have evaluated the effects of the symmetry and polarity of ambidentate donor subunits, differences in geometrical parameters (e.g. the size, angularity, and dimensionality) of Pt(II)-based acceptors and organic donors, the influence of temperature and solvent, and the effects of intermolecular steric interactions and hydrophobic interactions on self-organization. Our studies have shown that the extent of self-organization in the coordination-driven self-assembly of both 2D polygons and 3D polyhedra ranges from no organization (a statistical mixture of multiple products), to amplified organization (wherein a particular product or products are favored over others), and all the way to the absolute self-organization of

  7. Atomic force microscopy study of self-organization of chiral azobenzene derived from amino acid

    NASA Astrophysics Data System (ADS)

    Zhang, Yanjie; Tan, Changhui; Liu, Qingsheng; Lu, Ran; Song, Yanlin; Jiang, Lei; Zhao, Yingying; Li, Tie Jin; Liu, Yichun

    2003-12-01

    A kind of chiral azobenzene amphiphile, N-[4-(4-dodecyloxyphenylazo)benzoyl]- L-glutamic acid (C 12-Azo- L-Glu; as shown in Fig. 1), was synthesized and the self-organization properties on solid substrates were investigated. C 12-Azo- L-Glu underwent a reversible trans- cis photoisomerization in dilute solution. While the photoisomerization was suppressed on solid substrate because of the H-aggregation, indicating the formation of compact film. When C 12-Azo- L-Glu was cast from ethanol solution onto the hydrophilic surface of mica, a stable flat-layered structure formed spontaneously in large scale. High-resolution images allowed the identification of the relative orientation of molecular rows in the ordered thin film and the crystal lattice of mica. A molecular packing model of the layered structure was proposed. There was a template effect of mica to the self-organization process. Hydrogen bonding, π-π interaction and the chiral center in the molecule played the important roles in the self-organization process. The cooperative competitive effect between them led to the highly ordered structure.

  8. 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

  9. Self-organized Notch dynamics generate stereotyped sensory organ patterns in Drosophila.

    PubMed

    Corson, Francis; Couturier, Lydie; Rouault, Hervé; Mazouni, Khalil; Schweisguth, François

    2017-05-05

    The emergence of spatial patterns in developing multicellular organisms relies on positional cues and cell-cell communication. Drosophila sensory organs have informed a paradigm in which these operate in two distinct steps: Prepattern factors drive localized proneural activity, then Notch-mediated lateral inhibition singles out neural precursors. Here we show that self-organization through Notch signaling also establishes the proneural stripes that resolve into rows of sensory bristles on the fly thorax. Patterning, initiated by a gradient of Delta ligand expression, progresses through inhibitory signaling between and within stripes. Thus, Notch signaling can support self-organized tissue patterning as a prepattern is transduced by cell-cell interactions into a refined arrangement of cellular fates. Copyright © 2017, American Association for the Advancement of Science.

  10. 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.

  11. 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

  12. Study to develop techniques for a self-organizing computer

    NASA Technical Reports Server (NTRS)

    Schaffner, M. R.

    1972-01-01

    The main emphasis has been on the programming language for a self organizing computer. An example of programming with the language of finite state machines is presented in a real time processing for weather radars.

  13. 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.

  14. Self-organization in cold atomic gases: a synchronization perspective.

    PubMed

    Tesio, E; Robb, G R M; Oppo, G-L; Gomes, P M; Ackemann, T; Labeyrie, G; Kaiser, R; Firth, W J

    2014-10-28

    We study non-equilibrium spatial self-organization in cold atomic gases, where long-range spatial order spontaneously emerges from fluctuations in the plane transverse to the propagation axis of a single optical beam. The self-organization process can be interpreted as a synchronization transition in a fully connected network of fictitious oscillators, and described in terms of the Kuramoto model. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  15. Magnetic Nanostructures Patterned by Self-Organized Materials

    DTIC Science & Technology

    2016-01-05

    nanoporous membranes Journal of Magnetism and Magnetic Materials 350,88-93 (2014) 10. R. A. Escobar, N. M. Vargas, S. Castillo-Sepúlveda, S...AFRL-AFOSR-CL-TR-2016-0004 Magnetic nanostructures Patterned by Self-Organized Materials Dora Altbir-Drullinky UNIV OF SANTIAGO Final Report 01/05...PATTERNED BY SELF-ORGANIZED MATERIALS AFOSR – AFOSR FA9550-11-1-0347 Prof. Dora Altbir Drullinsky, P.I. Universidad de Santiago de Chile

  16. Spatial self-organization in hybrid models of multicellular adhesion

    NASA Astrophysics Data System (ADS)

    Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

    2016-10-01

    Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

  17. Spatial self-organization in hybrid models of multicellular adhesion.

    PubMed

    Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

    2016-10-01

    Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

  18. 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

  19. 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.

  20. 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

  1. The Origins of Concentric Demyelination: Self-Organization in the Human Brain

    PubMed Central

    Khonsari, Roman H.; Calvez, Vincent

    2007-01-01

    Baló's concentric sclerosis is a rare atypical form of multiple sclerosis characterized by striking concentric demyelination patterns. We propose a robust mathematical model for Baló's sclerosis, sharing common molecular and cellular mechanisms with multiple sclerosis. A reconsideration of the analogies between Baló's sclerosis and the Liesegang periodic precipitation phenomenon led us to propose a chemotactic cellular model for this disease. Rings of demyelination appear as a result of self-organization processes, and closely mimic Baló lesions. According to our results, homogeneous and concentric demyelinations may be two different macroscopic outcomes of a single fundamental immune disorder. Furthermore, in chemotactic models, cellular aggressivity appears to play a central role in pattern formation. PMID:17225855

  2. Cell polarity-driven instability generates self-organized, fractal patterning of cell layers.

    PubMed

    Rudge, Timothy J; Federici, Fernán; Steiner, Paul J; Kan, Anton; Haseloff, Jim

    2013-12-20

    As a model system to study physical interactions in multicellular systems, we used layers of Escherichia coli cells, which exhibit little or no intrinsic coordination of growth. This system effectively isolates the effects of cell shape, growth, and division on spatial self-organization. Tracking the development of fluorescence-labeled cellular domains, we observed the emergence of striking fractal patterns with jagged, self-similar shapes. We then used a large-scale, cellular biophysical model to show that local instabilities due to polar cell-shape, repeatedly propagated by uniaxial growth and division, are responsible for generating this fractal geometry. Confirming this result, a mutant of E. coli with spherical shape forms smooth, nonfractal cellular domains. These results demonstrate that even populations of relatively simple bacterial cells can possess emergent properties due to purely physical interactions. Therefore, accurate physico-genetic models of cell growth will be essential for the design and understanding of genetically programmed multicellular systems.

  3. Adaptive self-organization during growth of bacterial colonies

    NASA Astrophysics Data System (ADS)

    Ben-Jacob, Eshel; Shmueli, Haim; Shochet, Ofer; Tenenbaum, Adam

    1992-09-01

    systems provide new tools for the study of adaptive self-organization and mutation in the presence of selective pressures. We include brief reviews of both the recent developments in the study of interfacial pattern formation in non-living systems and the current trends in the view of mutation dynamics.

  4. Self-organized criticality in a block lattice model of the brittle crust

    NASA Astrophysics Data System (ADS)

    Lu, Chunsheng; Takayasu, Hideki; Tretyakov, Alex Yu; Takayasu, Misako; Yumoto, Shinji

    1998-06-01

    An earthquake model is introduced, in which the brittle crust is treated as a two-dimensional system of many blocks divided by faults, and the mechanical behavior of the faults is described by the Burridge-Knopoff stick-slip model. The coherent system naturally evolves into a self-organized critical state. Some universal scaling laws of seismicity, such as the Gutenberg-Richter law with the b value in agreement with the observational result and the fractal feature of fault patterns, are reproduced. Some ambiguity in simple cellular automata models is also solved.

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

    NASA Astrophysics Data System (ADS)

    Eldredge, Zachary; Solano, Pablo; Chang, Darrick; Gorshkov, Alexey V.

    2016-11-01

    Tightly confined modes of light, as in optical nanofibers or photonic 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 that are asymmetric between modes propagating in different directions. Strong long-range interaction among atoms via these modes can drive them to a self-organized periodic distribution. In this paper, we examine the self-organizing behavior of atoms in one dimension coupled to a chiral reservoir. We determine the solution to the equations of motion in different parameter regimes, relative to both the detuning of the pump laser that initializes the atomic dipole-dipole interactions and the degree of reservoir chirality. In addition, we calculate possible experimental signatures such as reflectivity from self-organized atoms and motional sidebands.

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

    PubMed Central

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

    2013-01-01

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

  7. Clustering with an Improved Self-Organizing Tree

    NASA Astrophysics Data System (ADS)

    Suzuki, Yukinori; Sasaki, Yasue

    A self-organizing tree (S-TREE) has a self-organizing capability and better performance than previously reported tree-structured clustering. In the S-TREE algorithm, since a tree grows in greedy fashion, a pruning mechanism is necessary to reduce the effect of bad leaf nodes. Extra nodes are pruned when the tree reaches a predetermined maximum size (U). U is problem-dependent and is therefore difficult to specify beforehand. Furthermore, since U gives the limit of tree growth and also prevents self-organizing of the tree, it may produce unnatural clustering. We are presenting a new pruning algorithm without U. In this paper, we present results showing the performance of the new pruning algorithm using samples generated from normal distributions. The results of computational experiments showed that the new pruning algorithm works well for clustering of those samples.

  8. Self-organized Anonymous Authentication in Mobile Ad Hoc Networks

    NASA Astrophysics Data System (ADS)

    Freudiger, Julien; Raya, Maxim; Hubaux, Jean-Pierre

    Pervasive communications bring along new privacy challenges, fueled by the capability of mobile devices to communicate with, and thus “sniff on”, each other directly. We design a new mechanism that aims at achieving location privacy in these forthcoming mobile networks, whereby mobile nodes collect the pseudonyms of the nodes they encounter to generate their own privacy cloaks. Thus, privacy emerges from the mobile network and users gain control over the disclosure of their locations. We call this new paradigm self-organized location privacy. In this work, we focus on the problem of self-organized anonymous authentication that is a necessary prerequisite for location privacy. We investigate, using graph theory, the optimality of different cloak constructions and evaluate with simulations the achievable anonymity in various network topologies. We show that peer-to-peer wireless communications and mobility help in the establishment of self-organized anonymous authentication in mobile networks.

  9. 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

  10. 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.

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

    PubMed

    Martius, Georg; Herrmann, J Michael

    2012-09-01

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

  12. Resource Letter SOP-1: Self-Organizing Physics

    NASA Astrophysics Data System (ADS)

    Jacobs, Donald T.

    2015-08-01

    This Resource Letter introduces the reader to an area of physics where systems can self-organize to a particular shape or behavior that, while dynamically changing, is surprisingly robust. The self-organization is due to the complex interactions that typically preclude explanation from just the forces among adjacent molecules or objects. How one recognizes such systems and explains their behavior is the topic of this Resource Letter. Some systems exhibit universal behavior that is well documented and understood, but other systems are just now being investigated.

  13. Associative learning in hierarchical self-organizing learning arrays.

    PubMed

    Starzyk, Janusz A; Zhu, Zhen; Li, Yue

    2006-11-01

    In this paper, we introduce feedback-based associative learning in self-organized learning arrays (SOLAR). SOLAR structures are hierarchically organized networks of sparsely connected neurons that define their own functions and select their interconnections locally. This paper provides a description of neuron self-organization and signal processing. Feedforward processing is used to make necessary correlations and learn the input patterns. Discovered associations between neuron inputs are used to generate feedback signals. These feedback signals, when propagated to the primary inputs, can establish the expected input values. This can be used for heteroassociative (HA) and autoassociative (AA) learning and pattern recognition. Example applications in HA learning are given.

  14. Self-Organized Cell Motility from Motor-Filament Interactions

    PubMed Central

    Du, XinXin; Doubrovinski, Konstantin; Osterfield, Miriam

    2012-01-01

    Cell motility is driven primarily by the dynamics of the cell cytoskeleton, a system of filamentous proteins and molecular motors. It has been proposed that cell motility is a self-organized process, that is, local short-range interactions determine much of the dynamics that are required for the whole-cell organization that leads to polarization and directional motion. Here we present a mesoscopic mean-field description of filaments, motors, and cell boundaries. This description gives rise to a dynamical system that exhibits multiple self-organized states. We discuss several qualitative aspects of the asymptotic states and compare them with those of living cells. PMID:22768929

  15. Self-organized call admission control for optical communication networks

    NASA Astrophysics Data System (ADS)

    Zuo, Bing; Liu, Lei; Wu, Jian; Lin, Jintong

    2008-11-01

    Call Admission Control (CAC) is widely used in optical communication networks to reduce network congestion. However, the conventional CAC scheme recommended by International Telecommunication Union -Telecommunication Standardization Sector (ITU-T) has a serious deficiency under high traffic load. In this paper, the disadvantage of conventional CAC scheme is analyzed in detail, and a Self-organized Call Admission Control (SCAC) scheme is proposed to solve this disadvantage. This scheme is accord with the principle of self-organization system, so it can be easily implemented in practice. Numerical results show that the proposed scheme can improve the network performance to a great extent.

  16. A principle of fractal-stochastic dualism and Gompertzian dynamics of growth and self-organization.

    PubMed

    Waliszewski, Przemyslaw

    2005-10-01

    The emergence of Gompertzian dynamics at the macroscopic, tissue level during growth and self-organization is determined by the existence of fractal-stochastic dualism at the microscopic level of supramolecular, cellular system. On one hand, Gompertzian dynamics results from the complex coupling of at least two antagonistic, stochastic processes at the molecular cellular level. It is shown that the Gompertz function is a probability function, its derivative is a probability density function, and the Gompertzian distribution of probability is of non-Gaussian type. On the other hand, the Gompertz function is a contraction mapping and defines fractal dynamics in time-space; a prerequisite condition for the coupling of processes. Furthermore, the Gompertz function is a solution of the operator differential equation with the Morse-like anharmonic potential. This relationship indicates that distribution of intrasystemic forces is both non-linear and asymmetric. The anharmonic potential is a measure of the intrasystemic interactions. It attains a point of the minimum (U(0), t(0)) along with a change of both complexity and connectivity during growth and self-organization. It can also be modified by certain factors, such as retinoids.

  17. Cytoskeletal actin networks in motile cells are critically self-organized systems synchronized by mechanical interactions

    PubMed Central

    Cardamone, Luca; Laio, Alessandro; Torre, Vincent; Shahapure, Rajesh; DeSimone, Antonio

    2011-01-01

    Growing networks of actin fibers are able to organize into compact, stiff two-dimensional structures inside lamellipodia of crawling cells. We put forward the hypothesis that the growing actin network is a critically self-organized system, in which long-range mechanical stresses arising from the interaction with the plasma membrane provide the selective pressure leading to organization. We show that a simple model based only on this principle reproduces the stochastic nature of lamellipodia protrusion (growth periods alternating with fast retractions) and several of the features observed in experiments: a growth velocity initially insensitive to the external force; the capability of the network to organize its orientation; a load-history-dependent growth velocity. Our model predicts that the spectrum of the time series of the height of a growing lamellipodium decays with the inverse of the frequency. This behavior is a well-known signature of self-organized criticality and is confirmed by unique optical tweezer measurements performed in vivo on neuronal growth cones. PMID:21825142

  18. Cytoskeletal actin networks in motile cells are critically self-organized systems synchronized by mechanical interactions.

    PubMed

    Cardamone, Luca; Laio, Alessandro; Torre, Vincent; Shahapure, Rajesh; DeSimone, Antonio

    2011-08-23

    Growing networks of actin fibers are able to organize into compact, stiff two-dimensional structures inside lamellipodia of crawling cells. We put forward the hypothesis that the growing actin network is a critically self-organized system, in which long-range mechanical stresses arising from the interaction with the plasma membrane provide the selective pressure leading to organization. We show that a simple model based only on this principle reproduces the stochastic nature of lamellipodia protrusion (growth periods alternating with fast retractions) and several of the features observed in experiments: a growth velocity initially insensitive to the external force; the capability of the network to organize its orientation; a load-history-dependent growth velocity. Our model predicts that the spectrum of the time series of the height of a growing lamellipodium decays with the inverse of the frequency. This behavior is a well-known signature of self-organized criticality and is confirmed by unique optical tweezer measurements performed in vivo on neuronal growth cones.

  19. Simple model of self-organized biological evolution

    NASA Astrophysics Data System (ADS)

    de Boer, Jan; Derrida, Bernard; Flyvbjerg, Henrik; Jackson, Andrew D.; Wettig, Tilo

    1994-08-01

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

  20. Adaptive self-organization of Bali's ancient rice terraces.

    PubMed

    Lansing, J Stephen; Thurner, Stefan; Chung, Ning Ning; Coudurier-Curveur, Aurélie; Karakaş, Çağil; Fesenmyer, Kurt A; Chew, Lock Yue

    2017-06-20

    Spatial patterning often occurs in ecosystems as a result of a self-organizing process caused by feedback between organisms and the physical environment. Here, we show that the spatial patterns observable in centuries-old Balinese rice terraces are also created by feedback between farmers' decisions and the ecology of the paddies, which triggers a transition from local to global-scale control of water shortages and rice pests. We propose an evolutionary game, based on local farmers' decisions that predicts specific power laws in spatial patterning that are also seen in a multispectral image analysis of Balinese rice terraces. The model shows how feedbacks between human decisions and ecosystem processes can evolve toward an optimal state in which total harvests are maximized and the system approaches Pareto optimality. It helps explain how multiscale cooperation from the community to the watershed scale could persist for centuries, and why the disruption of this self-organizing system by the Green Revolution caused chaos in irrigation and devastating losses from pests. The model shows that adaptation in a coupled human-natural system can trigger self-organized criticality (SOC). In previous exogenously driven SOC models, adaptation plays no role, and no optimization occurs. In contrast, adaptive SOC is a self-organizing process where local adaptations drive the system toward local and global optima.

  1. Web Image Retrieval Using Self-Organizing Feature Map.

    ERIC Educational Resources Information Center

    Wu, Qishi; Iyengar, S. Sitharama; Zhu, Mengxia

    2001-01-01

    Provides an overview of current image retrieval systems. Describes the architecture of the SOFM (Self Organizing Feature Maps) based image retrieval system, discussing the system architecture and features. Introduces the Kohonen model, and describes the implementation details of SOFM computation and its learning algorithm. Presents a test example…

  2. 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…

  3. 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.

  4. 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…

  5. 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.

  6. An Adaptive-PSO-Based Self-Organizing RBF Neural Network.

    PubMed

    Han, Hong-Gui; Lu, Wei; Hou, Ying; Qiao, Jun-Fei

    2016-10-24

    In this paper, a self-organizing radial basis function (SORBF) neural network is designed to improve both accuracy and parsimony with the aid of adaptive particle swarm optimization (APSO). In the proposed APSO algorithm, to avoid being trapped into local optimal values, a nonlinear regressive function is developed to adjust the inertia weight. Furthermore, the APSO algorithm can optimize both the network size and the parameters of an RBF neural network simultaneously. As a result, the proposed APSO-SORBF neural network can effectively generate a network model with a compact structure and high accuracy. Moreover, the analysis of convergence is given to guarantee the successful application of the APSO-SORBF neural network. Finally, multiple numerical examples are presented to illustrate the effectiveness of the proposed APSO-SORBF neural network. The results demonstrate that the proposed method is more competitive in solving nonlinear problems than some other existing SORBF neural networks.

  7. Critical Self-Organized Self-Sustained Oscillations in Large Regulatory Networks: Towards Understanding the Gene Expression Initiation

    PubMed Central

    Rosenfeld, Simon

    2011-01-01

    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. PMID:21523248

  8. 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

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

    SciTech Connect

    Yang, Hui Liu, Gang

    2013-12-15

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

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

    NASA Astrophysics Data System (ADS)

    Yang, Hui; Liu, Gang

    2013-12-01

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

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

    PubMed

    Yang, Hui; Liu, Gang

    2013-12-01

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

  12. An abstract cell model that describes the self-organization of cell function in living systems.

    PubMed

    Wolkenhauer, Olaf; Hofmeyr, Jan-Hendrik S

    2007-06-07

    The principal aim of systems biology is to search for general principles that govern living systems. We develop an abstract dynamic model of a cell, rooted in Mesarović and Takahara's general systems theory. In this conceptual framework the function of the cell is delineated by the dynamic processes it can realize. We abstract basic cellular processes, i.e., metabolism, signalling, gene expression, into a mapping and consider cell functions, i.e., cell differentiation, proliferation, etc. as processes that determine the basic cellular processes that realize a particular cell function. We then postulate the existence of a 'coordination principle' that determines cell function. These ideas are condensed into a theorem: If basic cellular processes for the control and regulation of cell functions are present, then the coordination of cell functions is realized autonomously from within the system. Inspired by Robert Rosen's notion of closure to efficient causation, introduced as a necessary condition for a natural system to be an organism, we show that for a mathematical model of a self-organizing cell the associated category must be cartesian closed. Although the semantics of our cell model differ from Rosen's (M,R)-systems, the proof of our theorem supports (in parts) Rosen's argument that living cells have non-simulable properties. Whereas models that form cartesian closed categories can capture self-organization (which is a, if not the, fundamental property of living systems), conventional computer simulations of these models (such as virtual cells) cannot. Simulations can mimic living systems, but they are not like living systems.

  13. Directing three-dimensional multicellular morphogenesis by self-organization of vascular mesenchymal cells in hyaluronic acid hydrogels.

    PubMed

    Zhu, Xiaolu; Gojgini, Shiva; Chen, Ting-Hsuan; Fei, Peng; Dong, Siyan; Ho, Chih-Ming; Segura, Tatiana

    2017-01-01

    Physical scaffolds are useful for supporting cells to form three-dimensional (3D) tissue. However, it is non-trivial to develop a scheme that can robustly guide cells to self-organize into a tissue with the desired 3D spatial structures. To achieve this goal, the rational regulation of cellular self-organization in 3D extracellular matrix (ECM) such as hydrogel is needed. In this study, we integrated the Turing reaction-diffusion mechanism with the self-organization process of cells and produced multicellular 3D structures with the desired configurations in a rational manner. By optimizing the components of the hydrogel and applying exogenous morphogens, a variety of multicellular 3D architectures composed of multipotent vascular mesenchymal cells (VMCs) were formed inside hyaluronic acid (HA) hydrogels. These 3D architectures could mimic the features of trabecular bones and multicellular nodules. Based on the Turing reaction-diffusion instability of morphogens and cells, a theoretical model was proposed to predict the variations observed in 3D multicellular structures in response to exogenous factors. It enabled the feasibility to obtain diverse types of 3D multicellular structures by addition of Noggin and/or BMP2. The morphological consistency between the simulation prediction and experimental results probably revealed a Turing-type mechanism underlying the 3D self-organization of VMCs in HA hydrogels. Our study has provided new ways to create a variety of self-organized 3D multicellular architectures for regenerating biomaterial and tissues in a Turing mechanism-based approach.

  14. Self-Organizing OFDMA System for Broadband Communication

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  15. Evolution as a self-organized critical phenomenon.

    PubMed Central

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

    1995-01-01

    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. Images Fig. 3 Fig. 6 Fig. 7 PMID:7761475

  16. Self-organization of gold nanoparticles on silanated surfaces.

    PubMed

    Kyaw, Htet H; Al-Harthi, Salim H; Sellai, Azzouz; Dutta, Joydeep

    2015-01-01

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

  17. Exploiting Self-organization in Bioengineered Systems: A Computational Approach.

    PubMed

    Davis, Delin; Doloman, Anna; Podgorski, Gregory J; Vargis, Elizabeth; Flann, Nicholas S

    2017-01-01

    The productivity of bioengineered cell factories is limited by inefficiencies in nutrient delivery and waste and product removal. Current solution approaches explore changes in the physical configurations of the bioreactors. This work investigates the possibilities of exploiting self-organizing vascular networks to support producer cells within the factory. A computational model simulates de novo vascular development of endothelial-like cells and the resultant network functioning to deliver nutrients and extract product and waste from the cell culture. Microbial factories with vascular networks are evaluated for their scalability, robustness, and productivity compared to the cell factories without a vascular network. Initial studies demonstrate that at least an order of magnitude increase in production is possible, the system can be scaled up, and the self-organization of an efficient vascular network is robust. The work suggests that bioengineered multicellularity may offer efficiency improvements difficult to achieve with physical engineering approaches.

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

    PubMed

    Pavin, Nenad; Tolić, Iva M

    2016-07-05

    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.

  19. 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.

  20. Adding dynamic rules to self-organizing fuzzy systems

    NASA Technical Reports Server (NTRS)

    Buhusi, Catalin V.

    1992-01-01

    This paper develops a Dynamic Self-Organizing Fuzzy System (DSOFS) capable of adding, removing, and/or adapting the fuzzy rules and the fuzzy reference sets. The DSOFS background consists of a self-organizing neural structure with neuron relocation features which will develop a map of the input-output behavior. The relocation algorithm extends the topological ordering concept. Fuzzy rules (neurons) are dynamically added or released while the neural structure learns the pattern. The DSOFS advantages are the automatic synthesis and the possibility of parallel implementation. A high adaptation speed and a reduced number of neurons is needed in order to keep errors under some limits. The computer simulation results are presented in a nonlinear systems modelling application.

  1. 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

  2. Self-organizing map models of language acquisition.

    PubMed

    Li, Ping; Zhao, Xiaowei

    2013-11-19

    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.

  3. 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.

  4. [Homeopathy between vital force and self-organization].

    PubMed

    Teut, M

    2001-06-01

    The idea of the vital force served European 18th-century scientists as theoretical background and as an integration model for many popular theories. The vital force was used to explain why physiological processes occur in a practical, useful and functional way and to answer the questions about the nature of biotic organization. At the end of 18th century, Samuel Hahnemann, the founder of homeopathy, used the theory of the vital force as a theoretical basis to explain the effects of homeopathic treatment and to justify his medical system. Vitalists represented a holistic tradition, they were not willing to accept purely mechanical interpretations of biological phenomena. The discussion between holistic and mechanistic scientists resulted in the development of modern self-organization theories, such as system, network, and chaos theory.The article gives an overview about the historical development from vital force to modern self-organization theories and discusses the relevance of the modern theories for homeopathic research.

  5. Self-organization of gold nanoparticles on silanated surfaces

    PubMed Central

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

    2015-01-01

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

  6. Current Sheet Formation and Self-Organization in Turbulent Plasmas

    NASA Astrophysics Data System (ADS)

    Spangler, Steven

    2009-05-01

    Self-Organization can be defined as the process by which a physical system, in the course of its evolution, changes its spatial structure, the form of its equations of motion, or key coefficients in those equations. A turbulent magnetohydrodynamic (MHD) fluid can exhibit self-organization, so defined. A turbulent MHD fluid with collisional resistivity has a low rate of dissipation of turbulent energy. However, as the turbulence develops, it forms thin current sheets in which the current density increases exponentially. When the electron drift speed becomes comparable to or exceeds the ion acoustic speed, plasma instabilities can enhance the resistivity, and thus the dissipation rate. In turbulent evolution of this kind, an MHD fluid can transform itself from a low dissipation to a high dissipation state. Calculations show that it is plausible that turbulence in the solar corona could exhibit this behavior.

  7. 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

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

    PubMed

    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.

  9. Exploiting Self-organization in Bioengineered Systems: A Computational Approach

    PubMed Central

    Davis, Delin; Doloman, Anna; Podgorski, Gregory J.; Vargis, Elizabeth; Flann, Nicholas S.

    2017-01-01

    The productivity of bioengineered cell factories is limited by inefficiencies in nutrient delivery and waste and product removal. Current solution approaches explore changes in the physical configurations of the bioreactors. This work investigates the possibilities of exploiting self-organizing vascular networks to support producer cells within the factory. A computational model simulates de novo vascular development of endothelial-like cells and the resultant network functioning to deliver nutrients and extract product and waste from the cell culture. Microbial factories with vascular networks are evaluated for their scalability, robustness, and productivity compared to the cell factories without a vascular network. Initial studies demonstrate that at least an order of magnitude increase in production is possible, the system can be scaled up, and the self-organization of an efficient vascular network is robust. The work suggests that bioengineered multicellularity may offer efficiency improvements difficult to achieve with physical engineering approaches. PMID:28503548

  10. A massively parallel architecture for self-organizing feature maps.

    PubMed

    Porrmann, M; Witkowski, U; Ruckert, U

    2003-01-01

    A hardware accelerator for self-organizing feature maps is presented. We have developed a massively parallel architecture that, on the one hand, allows a resource-efficient implementation of small or medium-sized maps for embedded applications, requiring only small areas of silicon. On the other hand, large maps can be simulated with systems that consist of several integrated circuits that work in parallel. Apart from the learning and recall of self-organizing feature maps, the hardware accelerates data pre- and postprocessing. For the verification of our architectural concepts in a real-world environment, we have implemented an ASIC that is integrated into our heterogeneous multiprocessor system for neural applications. The performance of our system is analyzed for various simulation parameters. Additionally, the performance that can be achieved with future microelectronic technologies is estimated.

  11. Topics in the mechanics of self-organizing systems

    NASA Astrophysics Data System (ADS)

    Tambe, Dhananjay

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

  12. SOUNET: Self-Organized Underwater Wireless Sensor Network

    PubMed Central

    Kim, Hee-won; Cho, Ho-Shin

    2017-01-01

    In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the time-varying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment. PMID:28157164

  13. Self-Organization and Annealed Disorder in Fracturing Process

    SciTech Connect

    Caldarelli, G. |

    1996-09-01

    We show that a vectorial model for inhomogeneous elastic media self-organizes under external stress. An onset of crack avalanches of every duration and length scale compatible with the lattice size is observed. The behavior is driven by the introduction of {ital annealed} {ital disorder}, i.e., by lowering the breaking threshold in the neighborhood of a bond broken by the stress, with a process similar to self-organized criticality. A further comparison with experimental results of acoustic emission (AE), shows that the stability of the elastic potential energy of the system in the AE regime is a sufficient condition for reproducing the algebraic distribution of the energy released during cracks formation. {copyright} {ital 1996 The American Physical Society.}

  14. 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.

  15. Evolution as a self-organized critical phenomenon

    SciTech Connect

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

    1995-05-23

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

  16. SOUNET: Self-Organized Underwater Wireless Sensor Network.

    PubMed

    Kim, Hee-Won; Cho, Ho-Shin

    2017-02-02

    In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

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

    PubMed

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

    2013-01-06

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

  18. Developing neuronal networks: self-organized criticality predicts the future.

    PubMed

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

    2013-01-01

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

  19. Self-organized criticality in ant brood tending.

    PubMed

    O'Toole, D V; Robinson, P A; Myerscough, M R

    2003-03-07

    A new stochastic lattice gas model of ant brood tending is formulated to examine the role played by repulsive ant-ant interactions in the even distribution of care among brood members. The deterministic limit of the model is known to be self-organized critical. Numerical simulations of the model show that the ant-ant repulsion facilitates an even distribution of brood care in the middle of the brood. This provides a possible explanation for the fact that ants sort their brood so that the youngest brood (which are most in need of care) are placed in the middle. Simulations show that the uniformity of brood care distribution is optimal when ants operate in a regime intermediate between completely random and completely deterministic. A certain degree of randomness helps ants to avoid becoming trapped in suboptimal configurations but does not destroy the long-range correlations that are inherent to self-organized critical systems.

  20. Energy Sources, Self-organization, and the Origin of Life

    NASA Astrophysics Data System (ADS)

    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.

  1. Self-organizing model of motor cortical activities during drawing

    NASA Astrophysics Data System (ADS)

    Lin, Siming H.; Si, Jennie; Schwartz, Andrew B.

    1996-05-01

    The population vector algorithm has been developed to combine the simultaneous direction- related activities of a population of motor cortical neurons to predict the trajectory of the arm movement. In our study, we consider a self-organizing model of a neural representation of the arm trajectory based on neuronal discharge rates. Self-organizing feature mapping (SOFM) is used to select the optimal set of weights in the model to determine the contribution of individual neuron to the overall movement. The correspondence between the movement directions and the discharge patterns of the motor cortical neurons is established in the output map. The topology preserving property of the SOFM is used to analyze real recorded data of a behavior monkey. The data used in this analysis were taken while the monkey was drawing spirals and doing the center out movement. Using such a statistical model, the monkey's arm moving directions could be well predicted based on the motor cortex neuronal firing information.

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

    PubMed

    Guo, Chin-Lin

    2013-01-01

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

  3. 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,…

  4. Self-organizing Complex Networks: individual versus global rules

    PubMed Central

    Mahmoodi, Korosh; West, Bruce J.; Grigolini, Paolo

    2017-01-01

    We introduce a form of Self-Organized Criticality (SOC) inspired by the new generation of evolutionary game theory, which ranges from physiology to sociology. The single individuals are the nodes of a composite network, equivalent to two interacting subnetworks, one leading to strategy choices made by the individuals under the influence of the choices of their nearest neighbors and the other measuring the Prisoner's Dilemma Game payoffs of these choices. The interaction between the two networks is established by making the imitation strength K increase or decrease according to whether the last two payoffs increase or decrease upon increasing or decreasing K. Although each of these imitation strengths is selected selfishly, and independently of the others as well, the social system spontaneously evolves toward the state of cooperation. Criticality is signaled by temporal complexity, namely the occurrence of non-Poisson renewal events, the time intervals between two consecutive crucial events being given by an inverse power law index μ = 1.3 rather than by avalanches with an inverse power law distribution as in the original form of SOC. This new phenomenon is herein labeled self-organized temporal criticality (SOTC). We compare this bottom-up self-organization process to the adoption of a global choice rule based on assigning to all the units the same value K, with the time evolution of common K being determined by consciousness of the social benefit, a top-down process implying the action of a leader. In this case self-organization is impeded by large intensity fluctuations and the global social benefit turns out to be much weaker. We conclude that the SOTC model fits the requests of a manifesto recently proposed by a number of European social scientists. PMID:28736534

  5. Assessing Self Organization and Emergence in C2 Processes

    DTIC Science & Technology

    2006-06-01

    Self Organization, FAQ, ©1997 Chris Lucas, version 1 (draft) 24 May 1997 3. Holland, John, H., “Emergence”, Perseus Books, 1998 19 4. Morin , Edgar ...interdependence and reliability, thus providing the system with the possibility of lasting for a certain length of time, despite chance disruptions ( Morin ...1977. La Methode I: la Nature de la Nature. Paris: Seuil. See also, Kelly, Sean. 1988. "Hegel and Morin : The Science of Wisdom and the Wisdom of

  6. Self-organization via active exploration in robotic applications

    NASA Technical Reports Server (NTRS)

    Ogmen, H.; Prakash, R. V.

    1992-01-01

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

  7. Self-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.

  8. Autowave self-organization in heterogeneous natural-anthropogenic ecosystems

    NASA Astrophysics Data System (ADS)

    Sidorova, A. E.; Levashova, N. T.; Melnikova, A. A.; Deryugina, N. N.; Semina, A. E.

    2016-11-01

    This article considers the spatio-temporal model of natural-anthropegenic ecosystems as a conjugated active media that takes the heterogeneity of anthropogenic and natural factors into account. The approach aims to identify the threshold values of the control parameters. The theoretical basis of the system analysis of the sustainability of the ecosystems is synergistic data on autowave self-organization in active media. The mathematical model is based on the modified FitzHugh-Nagumo system of equations.

  9. Clustering Similarity Digest Bloom Filters in Self-Organizing Maps

    DTIC Science & Technology

    2012-12-01

    Science Foundation. xv THIS PAGE INTENTIONALLY LEFT BLANK xvi CHAPTER 1: Introduction In the late 1980s, IBM’s 3390 Model 1 direct access storage device...information autonomously. From there, we look at a specific type of artificial neural network, the self-organizing map, as a appropriate model to build...training was not thorough enough for significant similarity scor - ing with the untrained document collection. In Section 4.1 we saw that each SOM had a

  10. 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.

  11. 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

  12. Forest fires: An example of self-organized critical behavior

    PubMed

    Malamud; Morein; Turcotte

    1998-09-18

    Despite the many complexities concerning their initiation and propagation, forest fires exhibit power-law frequency-area statistics over many orders of magnitude. A simple forest fire model, which is an example of self-organized criticality, exhibits similar behavior. One practical implication of this result is that the frequency-area distribution of small and medium fires can be used to quantify the risk of large fires, as is routinely done for earthquakes.

  13. 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.

  14. Self-Organized Collective Displacements of Self-Driven Individuals

    NASA Astrophysics Data System (ADS)

    Albano, Ezequiel V.

    1996-09-01

    An archetype model for the collective displacements of self-driven individuals, aimed to describe the dynamic of flocking behavior among living things, is presented and studied. Processes such as growth, death, survival, self-propagation, and competition are considered. It is shown that systems ruled by the model self-organize into a critical state exhibiting power-law behavior in both the distribution of population avalanches and the spatial correlation between individuals.

  15. Self-organized criticality in single-neuron excitability.

    PubMed

    Gal, Asaf; Marom, Shimon

    2013-12-01

    We present experimental and theoretical arguments, at the single-neuron level, suggesting that neuronal response fluctuations reflect a process that positions the neuron near a transition point that separates excitable and unexcitable phases. This view is supported by the dynamical properties of the system as observed in experiments on isolated cultured cortical neurons, as well as by a theoretical mapping between the constructs of self-organized criticality and membrane excitability biophysics.

  16. Digitally Printed Dewetting Patterns for Self-Organized Microelectronics.

    PubMed

    Eckstein, Ralph; Alt, Milan; Rödlmeier, Tobias; Scharfer, Philip; Lemmer, Uli; Hernandez-Sosa, Gerardo

    2016-09-01

    Self-organization of functional materials induced by low surface-energetic direct printed structures is presented. This study investigates fundamental fluid and substrate interactions and fabricates all-printed small area organic photodetectors with On-Off ratios of ≈10(5) and dark current densities of ≈10(-4) mA cm(-2) , as well as ring oscillators based on n-type organic field-effect transistors showing working frequencies up to 400 Hz.

  17. Architectural Patterns for Self-Organizing Systems-of-Systems

    DTIC Science & Technology

    2011-05-01

    of needs ( Maslow 1943). At the base of the hierarchy are the physiological needs ; these are the most primitive needs for all organisms based on self...motivation hierarchy is self-actualization. Maslow describes this motivation as a person achieving potential ( Maslow 1943). Satisfaction of needs at any...show that they are necessary for self-organization to occur. Common Purpose Abraham Maslow proposed a theory on human motivation based on a hierarchy

  18. 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.

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

    PubMed Central

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

    2014-01-01

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

  20. 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).

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

    PubMed Central

    Tsiairis, Charisios D.; Aulehla, Alexander

    2016-01-01

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

  2. Plasmas as a Prototypical Complex System: Self-Organized Criticality as a Paradigm for Plasma Transport

    NASA Astrophysics Data System (ADS)

    Newman, David

    2001-04-01

    In nature there are many systems which exhibit some form of self-organization. Among these are forest fires, earthquakes, sandpiles, maybe sunspots and even life itself. Investigations into the similarity of the dynamics of such systems have been undertaken by using simple cellular automata models. These models have produced some important insight into the dynamics of such systems. Recently a Self-Organized Criticality (SOC) model for turbulent transport in magnetically confined plasmas has been proposed in order to explain some of the observed features of the transport dynamics in these plasmas. This model is based on the dynamics of a sandpile and has among others, the remarkable feature that a sheared wind across the sandpile (or a flow across the plasma) can fundamentally change the transport. The dynamics of the model show some remarkably similar characteristics to the observed data and suggest explanations for some puzzling aspects of the observations. Adding new, physically realistic, dynamical transport mechanisms such as classical diffusion to the SOC system have been found to lead to a new set of dynamical regimes with evidence of critical transitions between them. These regimes can then be explored in the plasma experiments. In addition to the intrinsic novelty of the basic physics involved, these observations can have interesting ramifications for the control of many real systems. Some of these features of the SOC systems, from forest fires to earthquakes, and the extension to the sandpile model for turbulent transport will be discussed.

  3. Self-organized partitioning of dynamically localized proteins in bacterial cell division.

    PubMed

    Di Ventura, Barbara; Sourjik, Victor

    2011-01-04

    How cells manage to get equal distribution of their structures and molecules at cell division is a crucial issue in biology. In principle, a feedback mechanism could always ensure equality by measuring and correcting the distribution in the progeny. However, an elegant alternative could be a mechanism relying on self-organization, with the interplay between system properties and cell geometry leading to the emergence of equal partitioning. The problem is exemplified by the bacterial Min system that defines the division site by oscillating from pole to pole. Unequal partitioning of Min proteins at division could negatively impact system performance and cell growth because of loss of Min oscillations and imprecise mid-cell determination. In this study, we combine live cell and computational analyses to show that known properties of the Min system together with the gradual reduction of protein exchange through the constricting septum are sufficient to explain the observed highly precise spontaneous protein partitioning. Our findings reveal a novel and effective mechanism of protein partitioning in dividing cells and emphasize the importance of self-organization in basic cellular processes.

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

    NASA Astrophysics Data System (ADS)

    Sasai, Yoshiki

    2013-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Lushi, Enkeleida; Wioland, Hugo; Goldstein, Raymond

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

  6. Correlations induced by depressing synapses in critically self-organized networks with quenched dynamics

    NASA Astrophysics Data System (ADS)

    Campos, João Guilherme Ferreira; Costa, Ariadne de Andrade; Copelli, Mauro; Kinouchi, Osame

    2017-04-01

    In a recent work, mean-field analysis and computer simulations were employed to analyze critical self-organization in networks of excitable cellular automata where randomly chosen synapses in the network were depressed after each spike (the so-called annealed dynamics). Calculations agree with simulations of the annealed version, showing that the nominal branching ratio σ converges to unity in the thermodynamic limit, as expected of a self-organized critical system. However, the question remains whether the same results apply to the biological case where only the synapses of firing neurons are depressed (the so-called quenched dynamics). We show that simulations of the quenched model yield significant deviations from σ =1 due to spatial correlations. However, the model is shown to be critical, as the largest eigenvalue of the synaptic matrix approaches unity in the thermodynamic limit, that is, λc=1 . We also study the finite size effects near the critical state as a function of the parameters of the synaptic dynamics.

  7. Light-mediated self-organization of sunflower stands increases oil yield in the field.

    PubMed

    López Pereira, Mónica; Sadras, Victor O; Batista, William; Casal, Jorge J; Hall, Antonio J

    2017-07-25

    Here, we show a unique crop response to intraspecific interference, whereby neighboring sunflower plants in a row avoid each other by growing toward a more favorable light environment and collectively increase production per unit land area. In high-density stands, a given plant inclined toward one side of the interrow space, and the immediate neighbors inclined in the opposite direction. This process started early as an incipient inclination of pioneer plants, and the arrangement propagated gradually as a "wave" of alternate inclination that persisted until maturity. Measurements and experimental manipulation of light spectral composition indicate that these responses are mediated by changes in the red/far-red ratio of the light, which is perceived by phytochrome. Cellular automata simulations reproduced the patterns of stem inclination in field experiments, supporting the proposition of self-organization of stand structure. Under high crop population densities (10 and 14 plants per m(2)), as yet unachievable in commercial farms with current hybrids due to lodging and diseases, self-organized crops yielded between 19 and 47% more oil than crops forced to remain erect.

  8. Self-organization of atom wires on vicinal surfaces

    NASA Astrophysics Data System (ADS)

    Snijders, Paul

    2008-03-01

    Self-organization is possibly the best way to produce nanostructures in large quantities. This also holds for the ultimate 1D system, atom wires; they can be self-assembled in large arrays on vicinal Si surfaces. Such atom wire systems often show intriguing electronic properties such as competing charge density waves and spin-orbit split one-dimensional bands. However, because of their low dimensionality, these wires also frequently show profound thermodynamic fluctuations that limit their structural uniformity and have a large influence on their electronic properties. Therefore, in this talk I will focus on structural fluctuations in Ga atom wires self-organized on the Si(112) surface. In these atom wires, strain-relieving adatom vacancies self-organize into meandering vacancy lines (VLs) similar to the well-known nx2 superstructures for Ge on Si(100). The average spacing between these line defects can be experimentally controlled continuously by adjusting the chemical potential μ of the Ga adatoms. Significant VL correlations are discovered in STM experiments that cannot be captured within a mean field analysis. These structural flucuations are well described by a new lattice model that combines Density Functional Theory (DFT) calculations for perfectly ordered structures with the fluctuating disorder seen in experiment, and the experimental control parameter μ. This hybrid approach of lattice modeling and DFT can be applied to other examples of line defects in hetero-epitaxy, especially in cases where correlation effects are significant and a mean field approach is not valid.

  9. 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.

  10. Self-organized structures in z-pinch devices

    NASA Astrophysics Data System (ADS)

    Ortíz-Tapia, Arturo

    2002-11-01

    In several z-pinch devices there has been observation of regular structures, which appear systematically when repeating the experiments. The fact that very identifiable, recurrent, geometrical structures appear in z-pinches, which are relatively long lived, has motivated the analysis of the experimental data in a way that would cast light over these structures. In order to study this problem, diagnostic methods such as Schlieren photography, Quadro camera diagnostics, X-ray diagnostics, interferometry measurements and streak camera were used. This work includes analysis of experimental results, and the determination of some of the parameters which probably give rise to self-organized structures and some regular structures. It was found that a major contributor, for self-organization to occur, was the dominance of electromagnetic energy over the kinetic energy in the wire corona. The induction of an azimuthal magnetic field contributed to the generation of azimuthal currents, which in turn induced an axial magnetic field. Both axial and azimuthal magnetic fields contributed to the formation of helical-like structures, at least until the pinch began to dissipate. An important stabilizing factor for the plasma channel could have been played by the solid remains of part of the fiber inside the channel. There is a positive strong correlation between the expulsion of entropy and the persistence in the existence of self-organized structures.

  11. Self-organization of polymerizable bolaamphiphiles bearing diacetylene mesogenic group.

    PubMed

    Yin, Shouchun; Song, Bo; Liu, Guanqing; Wang, Zhiqiang; Zhang, Xi

    2007-05-22

    We report herein the synthesis of a series of polymerizable bolaamphiphiles containing a diacetylene group and mesogenic unit and their self-organization behaviors in bulk and at interface. The polymerizable bolaamphiphiles are noted as DPDA-n, where n refers to the spacer length of alkyl chain. DPDA-10 with suitable spacer length can self-organize into stable cylindrical micellar nanostructures, and these nanostructures have preferred orientation regionally when adsorbed at the mica/water interface. It is confirmed that the micellar nanostructure of DPDA-10 can be polymerized both in the bulk solution and in the film by UV irradiation. The emission property of DPDA-10 after UV irradiation has been significantly enhanced in comparison to that before polymerization, which may be due to the extension of the conjugated system arising from the transformation of the diacetylene group into polydiacetylene upon polymerization. In addition, the self-organization of DPDA-n is dependent on the spacer length. DPDA-7 with a short spacer length forms an irregular flat sheet structure with many defects; DPDA-15 with a long spacer length forms rodlike micellar structures. Thus, this work may provide a new approach for designing and fabricating organic functional nanostructured materials.

  12. Self-organization at the frictional interface for green tribology.

    PubMed

    Nosonovsky, Michael

    2010-10-28

    Despite the fact that self-organization during friction has received relatively little attention from tribologists so far, it has the potential for the creation of self-healing and self-lubricating materials, which are important for green or environment-friendly tribology. The principles of the thermodynamics of irreversible processes and of the nonlinear theory of dynamical systems are used to investigate the formation of spatial and temporal structures during friction. The transition to the self-organized state with low friction and wear occurs through destabilization of steady-state (stationary) sliding. The criterion for destabilization is formulated and several examples are discussed: the formation of a protective film, microtopography evolution and slip waves. The pattern formation may involve self-organized criticality and reaction-diffusion systems. A special self-healing mechanism may be embedded into the material by coupling the corresponding required forces. The analysis provides the structure-property relationship, which can be applied for the design optimization of composite self-lubricating and self-healing materials for various ecologically friendly applications and green tribology.

  13. 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.)

  14. Modeling of self-organization of two-dimensional ordered structures

    NASA Astrophysics Data System (ADS)

    Egorov, V. V.; Garmay, Y. P.; Shaldzhyan, A. A.; Lebedev, D. V.; Vasin, A. V.; Grudinina, N. A.; Kiselev, O. I.

    2011-04-01

    The problem of the search of biostructures capable to self-organization is quite urgent considering the prospects of application of nanostructured biomaterials as components of composite materials in transplantology and optics as well as "scaffolds" for the synthesis of nanostructured materials based on inorganic particles. The given study focuses on modeling of the growth of structures using the cellular automata with a set of states of the two values (0 and 1), with the value corresponding to the state is determined by the contribution of "the closest neighbor" (by the probability of induction of the state of the nextgeneration in the direction of the interaction) and the geometry of the field isdetermined by the vector of the direction of the particle and the direction of the interaction.

  15. 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).

  16. Bio-Inspired Networking — Self-Organizing Networked Embedded Systems

    NASA Astrophysics Data System (ADS)

    Dressler, Falko

    The turn to nature has brought us many unforeseen great concepts and solutions. This course seems to hold on for many research domains. In this article, we study the applicability of biological mechanisms and techniques in the domain of communications. In particular, we study the behavior and the challenges in networked embedded systems that are meant to self-organize in large groups of nodes. Application examples include wireless sensor networks and sensor/actuator networks. Based on a review of the needs and requirements in such networks, we study selected bio-inspired networking approaches that claim to outperform other methods in specific domains. We study mechanisms in swarm intelligence, the artificial immune system, and approaches based on investigations on the cellular signaling pathways. As a major conclusion, we derive that bio-inspired networking techniques do have advantages compared to engineering methods. Nevertheless, selection and employment must be done carefully to achieve the desired performance gains.

  17. Online Self-Organizing Social Systems: The Decentralized Future of Online Learning.

    ERIC Educational Resources Information Center

    Wiley, David A.; Edwards, Erin K.

    2002-01-01

    Describes an online self-organizing social system (OSOSS) which allows large numbers of individuals to self-organize in a highly decentralized manner to solve problems and accomplish other goals. Topics include scalability and bandwidth in online learning; self-organization; learning objects; instructional design underlying OSOSS, including…

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

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

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

  19. Epithelial self-organization in fruit fly embryogenesis

    NASA Astrophysics Data System (ADS)

    Hutson, M. Shane

    2010-03-01

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

  20. 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.

  1. Laser applications of self-organized organic photonic crystals

    NASA Astrophysics Data System (ADS)

    Furumi, Seiichi

    2008-08-01

    In this presentation, I report on the self-organized photonic crystals (PCs) of organic and polymer materials for laser applications. Here the self-organized PCs correspond to chiral liquid crystals (CLCs) and colloidal crystals (CCs). First, CLC molecules self-organize the supramolecular helical arrangement by the helical twisting power like as 1-D PC structure. When the fluorescent dye-doped CLC is optically excited with a linearly polarized beam, the laser emission appears at the photonic band gap (PBG) edge(s) of CLC hosts. The optically excited laser emission shows circularly polarized characteristic, even though the excitation beam is linearly polarized. Applying voltages to the optically excited CLC cells enables reversible switching of the laser action as a result of changes in the supramolecular helical structure of CLC host. Moreover, we succeed in the phototunable laser emission by using photoreactive CLCs. Second research topic is establishment of new potential utilities of CC structures of polymer micro-particles. Monodispersed micro-particles have an intrinsic capability to self-assemble the face-centered cubic lattice structures like as 3-D PCs on substrates from the suspension solutions. The highly ordered architectures of colloidal particles are called as the CCs. The laser cavity structure consists of an intermediate light-emitting layer of a fluorescent dye sandwiched between a pair of polymeric CC films. Optical excitation of the device gives rise to the laser oscillation within the photonic band-gap of the CC films. Interestingly, the laser action can be generated by optical excitation even though the CC laser device of all-polymer materials becomes bent shape by mechanical stress.

  2. Self-organization of charged particles in circular geometry

    NASA Astrophysics Data System (ADS)

    Nazmitdinov, R. G.; Puente, A.; Cerkaski, M.; Pons, M.

    2017-04-01

    The basic principles of self-organization of one-component charged particles, confined in disk and circular parabolic potentials, are proposed. A system of equations is derived, which allows us to determine equilibrium configurations for an arbitrary, but finite, number of charged particles that are distributed over several rings. Our approach reduces significantly the computational effort in minimizing the energy of equilibrium configurations and demonstrates a remarkable agreement with the values provided by molecular dynamics calculations. With the increase of particle number n >180 we find a steady formation of a centered hexagonal lattice that smoothly transforms to valence circular rings in the ground-state configurations for both potentials.

  3. Self-organization of charged particles in circular geometry.

    PubMed

    Nazmitdinov, R G; Puente, A; Cerkaski, M; Pons, M

    2017-04-01

    The basic principles of self-organization of one-component charged particles, confined in disk and circular parabolic potentials, are proposed. A system of equations is derived, which allows us to determine equilibrium configurations for an arbitrary, but finite, number of charged particles that are distributed over several rings. Our approach reduces significantly the computational effort in minimizing the energy of equilibrium configurations and demonstrates a remarkable agreement with the values provided by molecular dynamics calculations. With the increase of particle number n>180 we find a steady formation of a centered hexagonal lattice that smoothly transforms to valence circular rings in the ground-state configurations for both potentials.

  4. Self-organizing control for space-based sparse antennas

    NASA Technical Reports Server (NTRS)

    Hadaegh, Fred Y.; Jamnejad, Vaharaz; Scharf, Daniel P.; Ploen, Scott R.

    2003-01-01

    An integrated control and electromagnetic/antenna formulation is presented for evaluating the performance of a distributed antenna system as a function of formation geometry. A distributed and self-organizing control law for the control law for the control of multiple antennas in Low Earth Orbit (LEO) is presented. The control system provides collaborative commanding and performance optimization to configure and operate the distributed formation system. A large aperture antenna is thereby realized by a collection of miniature sparse antennas in formation. A case study consisting of a simulation of four antennas in Low Earth orbit (LEO)is presented to demonstrate the concept.

  5. Physical properties determining self-organization of motors and microtubules.

    PubMed

    Surrey, T; Nedelec, F; Leibler, S; Karsenti, E

    2001-05-11

    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.

  6. 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.

  7. Automated road extraction from aerial imagery by self-organization

    NASA Astrophysics Data System (ADS)

    Doucette, Peter J.

    To date, computer vision methods have largely focused on extraction from panchromatic imagery. Despite significant technological advances, road extraction algorithms have fallen short of satisfying rigorous production requirements. To that end, the objective of this thesis is to present a new approach for automating road detection from high-resolution multispectral imagery. This thesis considers three main research objectives: (1) development of a fully automated road extraction strategy in that interactive human supervision or input initializations are not required; (2) development of a globalized approach to road detection that is motivated by principles of self-organization; (3) meaningful exploitation of high-resolution multispectral imagery. Several new techniques are presented for fully automated road extraction from high-resolution imagery. The core algorithms implemented include (1) Anti-parallel edge Centerline Extractor (ACE), (2) Fuzzy Organization of Elongated Regions (FOrgER), and (3) Self-Organizing Road Finder (SORF). The ACE algorithm extends the idea of anti-parallel edge detection in a new approach that considers multi-layer images. The FOrgER algorithm is motivated by Gestalt grouping principles in perceptual organization. The FOrgER approach combines principles of self-organization with fuzzy inferencing to building road topology. Self-organization represents a learning paradigm that is neurobiologically motivated. Globalized analysis promotes lower sensitivity to fragmented information, and demonstrates robust capacity for handling scene clutter in high-resolution images. Finally, the SORF algorithm bridges concepts from ACE and FOrgER into a comprehensive and cooperative approach for fully automated road finding. By providing an exceptional breadth of input parameters, output metrics, modes of operation, and adaptability to various input, SORF is particularly well suited as an analytical research tool. Extraction results from the SORF

  8. GENERAL: Self-organized Criticality Model for Ocean Internal Waves

    NASA Astrophysics Data System (ADS)

    Wang, Gang; Lin, Min; Qiao, Fang-Li; Hou, Yi-Jun

    2009-03-01

    In this paper, we present a simple spring-block model for ocean internal waves based on the self-organized criticality (SOC). The oscillations of the water blocks in the model display power-law behavior with an exponent of -2 in the frequency domain, which is similar to the current and sea water temperature spectra in the actual ocean and the universal Garrett and Munk deep ocean internal wave model [Geophysical Fluid Dynamics 2 (1972) 225; J. Geophys. Res. 80 (1975) 291]. The influence of the ratio of the driving force to the spring coefficient to SOC behaviors in the model is also discussed.

  9. Self-organized metal nanowire arrays with tunable optical anisotropy

    SciTech Connect

    Toma, A.; Chiappe, D.; Massabo, D.; Boragno, C.; Buatier de Mongeot, F.

    2008-10-20

    Here we report on the development of an unconventional approach for the physical synthesis of laterally ordered self-organized arrays of metallic nanowires supported on nanostructured dielectric templates. The method, based on a combination of nanoscale patterning of the glass substrate by ion beam sputtering with shadow deposition of the metal nanoparticles, provides a viable alternative to time consuming serial nanopatterning approaches. Far-field optical characterization demonstrates that the nanowire arrays exhibit tunable anisotropic properties in the visible range due to the excitation of localized plasmon resonances.

  10. On the self-organizing maps and its applications

    NASA Astrophysics Data System (ADS)

    Jinno, Kenji; Yokota, Izumi; Iseri, Yoshihiko; Iryo, Ryuta

    The present short lecture introduces the fundamental concept of the self-organizing maps (SOM), which is widely used in the information technologies. The SOM is a method to analyze the data set composed of multi-component variables. Two applications of SOM are demonstrated: the application of SOM to the questionnaires of water done by the Water Supply Bureau of Fukuoka City, and the parameter sensitivity study for the Rossler equation which has a nonlinear term in the ordinary differential equation with three variables. The advantage of SOM is demonstrated by the two-dimensional SOM map where the multi-component variables are visualized representing the clusters with different properties.

  11. Biological and Physical Principles in Self-Organization of Brain

    NASA Astrophysics Data System (ADS)

    Kröger, H.

    2007-04-01

    Complexity is a widespread phenomenon in nature. The brain is a foremost example of complexity. We address the question: How does such complexity emerge in brain? Which are the biological, chemical or physical principles at work which organize the formation of complixity? In particular we address the topics (i) adaptive learning, (ii) neuron cell death and pruning of synaptic connection afterbirth, (iii) small world and scale free architecture of neural connectivity, (iv) feature maps and the Kohonen model, (v) self-organized criticality and 1/f frequency scaling.

  12. Self-organization in bacterial swarming: lessons from myxobacteria

    NASA Astrophysics Data System (ADS)

    Wu, Yilin; Jiang, Yi; Kaiser, A. Dale; Alber, Mark

    2011-10-01

    When colonizing surfaces, many bacteria are able to self-organize into an actively expanding biofilm, in which millions of cells move smoothly and orderly at high densities. This phenomenon is known as bacterial swarming. Despite the apparent resemblance to patterns seen in liquid crystals, the dynamics of bacterial swarming cannot be explained by theories derived from equilibrium statistical mechanics. To understand how bacteria swarm, a central question is how order emerges in dense and initially disorganized populations of bacterial cells. Here we briefly review recent efforts, with integrated computational and experimental approaches, in addressing this question.

  13. 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.

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

    PubMed

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

    2006-09-01

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

  15. A simple model for self-organization of bipartite networks

    NASA Astrophysics Data System (ADS)

    Sneppen, K.; Rosvall, M.; Trusina, A.; Minnhagen, P.

    2004-08-01

    We suggest a minimalistic model for directed networks and suggest an application to injection and merging of magnetic field lines. We obtain a network of connected donor and acceptor vertices with degree distribution 1/s2, and with dynamical reconnection events of size Δs occurring with frequency that scales as 1/Δs3. This suggests that the model is in the same universality class as the model with annihilation for self-organization in the solar atmosphere suggested by Hughes et al. (Phys. Rev. Lett. 90 (2003) 131101).

  16. 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.

  17. Dynamics of self-organization in complex adaptive networks

    NASA Astrophysics Data System (ADS)

    D'Humières, D.; Huberman, B. A.

    1984-02-01

    We study the dynamical behavior of complex adaptive automata during unsupervised learning of periodic training sets. A new technique for their analysis is presented and applied to an adaptive network with distributed memory. We show that with general imput pattern sequences, the system can display behavior that ranges from convergence into simple fixed points and oscillations to chaotic wanderings. We also test the ability of the self-organized automaton to recognize spatial patterns, discriminate between them, and to elicit meaningful information out of noisy inputs. In this configuration we determine that the higher the ratio of excitation to inhibition, the broader the equivalence class into which patterns are put together.

  18. Sperm whale identification using self-organizing maps

    NASA Astrophysics Data System (ADS)

    Ioup, Juliette W.; Ioup, George E.

    2004-05-01

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

  19. 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.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2007-02-01

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

  2. 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.

  3. Clogging and self-organized criticality in complex networks.

    PubMed

    Bianconi, Ginestra; Marsili, Matteo

    2004-09-01

    We propose a simple model that aims at describing, in a stylized manner, how local breakdowns due to imbalances or congestion propagate in real dynamical networks. The model converges to a self-organized critical stationary state in which the network shapes itself as a consequence of avalanches of rewiring processes. Depending on the model's specification, we obtain either single-scale or scale-free networks. We characterize in detail the relation between the statistical properties of the network and the nature of the critical state, by computing the critical exponents. The model also displays a nontrivial, sudden collapse to a complete network.

  4. Self-organized synchronization in decentralized power grids.

    PubMed

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

    2012-08-10

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

  5. Scaling and Regeneration of Self-Organized Patterns

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  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. A stochastic self-organizing map for proximity data.

    PubMed

    Graepel, T; Obermayer, K

    1999-01-01

    We derive an efficient algorithm for topographic mapping of proximity data (TMP), which can be seen as an extension of Kohonen's self-organizing map to arbitrary distance measures. The TMP cost function is derived in a Baysian framework of folded Markov chains for the description of autoencoders. It incorporates the data by a dissimilarity matrix D and the topographic neighborhood by a matrix H of transition probabilities. From the principle of maximum entropy, a nonfactorizing Gibbs distribution is obtained, which is approximated in a mean-field fashion. This allows for maximum likelihood estimation using an expectation-maximization algorithm. In analogy to the transition from topographic vector quantization to the self-organizing map, we suggest an approximation to TMP that is computationally more efficient. In order to prevent convergence to local minima, an annealing scheme in the temperature parameter is introduced, for which the critical temperature of the first phase transition is calculated in terms of D and H. Numerical results demonstrate the working of the algorithm and confirm the analytical results. Finally, the algorithm is used to generate a connection map of areas of the cat's cerebral cortex.

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

    PubMed

    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 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.

  9. Granular self-organization by autotuning of friction.

    PubMed

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

    2015-09-15

    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.

  10. 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.

  11. The Self-Organized Archive: SPASE, PDS and Archive Cooperatives

    NASA Astrophysics Data System (ADS)

    King, T. A.; Hughes, J. S.; Roberts, D. A.; Walker, R. J.; Joy, S. P.

    2005-05-01

    Information systems with high quality metadata enable uses and services which often go beyond the original purpose. There are two types of metadata: annotations which are items that comment on or describe the content of a resource and identification attributes which describe the external properties of the resource itself. For example, annotations may indicate which columns are present in a table of data, whereas an identification attribute would indicate source of the table, such as the observatory, instrument, organization, and data type. When the identification attributes are collected and used as the basis of a search engine, a user can constrain on an attribute, the archive can then self-organize around the constraint, presenting the user with a particular view of the archive. In an archive cooperative where each participating data system or archive may have its own metadata standards, providing a multi-system search engine requires that individual archive metadata be mapped to a broad based standard. To explore how cooperative archives can form a larger self-organized archive we will show how the Space Physics Archive Search and Extract (SPASE) data model will allow different systems to create a cooperative and will use Planetary Data System (PDS) plus existing space physics activities as a demonstration.

  12. Autonomous self-organizing resource manager for multiple networked platforms

    NASA Astrophysics Data System (ADS)

    Smith, James F., III

    2002-08-01

    A fuzzy logic based expert system for resource management has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar autonomous naval platforms defending their group against attackers. The platforms can be very general, e.g., ships, planes, robots, land based facilities, etc. Potential foes the platforms deal with can also be general. This paper provides an overview of the resource manager including the four fuzzy decision trees that make up the resource manager; the fuzzy EA model; genetic algorithm based optimization; co-evolutionary data mining through gaming; and mathematical, computational and hardware based validation. Methods of automatically designing new multi-platform EA techniques are considered. The expert system runs on each defending platform rendering it an autonomous system requiring no human intervention. There is no commanding platform. Instead the platforms work cooperatively as a function of battlespace geometry; sensor data such as range, bearing, ID, uncertainty measures for sensor output; intelligence reports; etc. Computational experiments will show the defending networked platform's ability to self- organize. The platforms' ability to self-organize is illustrated through the output of the scenario generator, a software package that automates the underlying data mining problem and creates a computer movie of the platforms' interaction for evaluation.

  13. 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.

  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. Attitudes and the Self as Self-Organizing Systems

    NASA Astrophysics Data System (ADS)

    Eiser, J. Richard

    This paper considers how conventional theories of attitudes and the self may be reconceptualized from the perspective of chaos theory and work on self-organization. Within attitude theory, there has been a long tradition of research that has treated attitudes as single points on a bipolar evaluative continuum. More recent approaches to attitudes treat attitudes as structures of evaluative associations stored in memory (Fazio, 1990). This work can be linked to chaos theory by regarding attitudes as attractors (Eiser, 1994) within a phase space whose dimensions correspond broadly to features of the attitude object and its context and which is contoured by previous and concurrent associative learning Specifically, it is proposed that attractors are laid down through processes of association. such as may be simulated through connectionist, or parallel distributed processing, systems. Associative learning and memory processes also are implicated in our concept of self, linking with the philosophy of Hume and contemporary research on interactive models of personality (Mischel & Shoda, 1995). Speculatively, it is suggested that consciousness involves representation of the self within a patterned (i.e. self-organized) environment.

  16. Rival-model penalized self-organizing map.

    PubMed

    Cheung, Yiu-ming; Law, Lap-tak

    2007-01-01

    As a typical data visualization technique, self-organizing map (SOM) has been extensively applied to data clustering, image analysis, dimension reduction, and so forth. In a conventional adaptive SOM, it needs to choose an appropriate learning rate whose value is monotonically reduced over time to ensure the convergence of the map, meanwhile being kept large enough so that the map is able to gradually learn the data topology. Otherwise, the SOM's performance may seriously deteriorate. In general, it is nontrivial to choose an appropriate monotonically decreasing function for such a learning rate. In this letter, we therefore propose a novel rival-model penalized self-organizing map (RPSOM) learning algorithm that, for each input, adaptively chooses several rivals of the best-matching unit (BMU) and penalizes their associated models, i.e., those parametric real vectors with the same dimension as the input vectors, a little far away from the input. Compared to the existing methods, this RPSOM utilizes a constant learning rate to circumvent the awkward selection of a monotonically decreased function for the learning rate, but still reaches a robust result. The numerical experiments have shown the efficacy of our algorithm.

  17. 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.

  18. Macromolecular target prediction by self-organizing feature maps.

    PubMed

    Schneider, Gisbert; Schneider, Petra

    2017-03-01

    Rational drug discovery would greatly benefit from a more nuanced appreciation of the activity of pharmacologically active compounds against a diverse panel of macromolecular targets. Already, computational target-prediction models assist medicinal chemists in library screening, de novo molecular design, optimization of active chemical agents, drug re-purposing, in the spotting of potential undesired off-target activities, and in the 'de-orphaning' of phenotypic screening hits. The self-organizing map (SOM) algorithm has been employed successfully for these and other purposes. Areas covered: The authors recapitulate contemporary artificial neural network methods for macromolecular target prediction, and present the basic SOM algorithm at a conceptual level. Specifically, they highlight consensus target-scoring by the employment of multiple SOMs, and discuss the opportunities and limitations of this technique. Expert opinion: Self-organizing feature maps represent a straightforward approach to ligand clustering and classification. Some of the appeal lies in their conceptual simplicity and broad applicability domain. Despite known algorithmic shortcomings, this computational target prediction concept has been proven to work in prospective settings with high success rates. It represents a prototypic technique for future advances in the in silico identification of the modes of action and macromolecular targets of bioactive molecules.

  19. Self Organization in the Solar Corona and Interstellar Medium

    NASA Astrophysics Data System (ADS)

    Spangler, Steven

    2009-11-01

    Self-organization can be defined as the process by which a physical system, in the course of its evolution, changes its spatial structure, the form of its equations of motions, or key coefficients in those equations. Paradigmatic examples are chemical reactions of the reaction-diffusion type, and biological systems. I discuss astrophysical processes where similar sorts of dynamics may be occurring. The first example is Joule heating of the solar corona. A major problem in astrophysics is the physical mechanism or mechanisms responsible for heating the solar corona to 1-2 million K. Coronal heating by turbulent current sheets is negligible if a standard expression for the resistivity of a plasma is used, but as the current sheets evolve, they develop progressively higher current densities. These high current densities can enhance the resistivity via plasma instabilities, and make Joule heating a more effective process. The second example is from the interstellar medium. The formation of massive stars leads to processes which compress the nearby interstellar medium, making star formation a more efficient process. Similarities and differences with better studied systems exhibiting self organization will be discussed.

  20. Metabolic self-organization of bioluminescent Escherichia coli.

    PubMed

    Simkus, Remigijus; Baronas, Romas

    2011-01-01

    A possible reason for the complexity of the signals produced by bioluminescent biosensors might be self-organization of the cells. In order to verify this possibility, bioluminescence images of cultures of lux gene reporter Escherichia coli were recorded for several hours after being placed into 8-10 mm diameter cylindrical containers. It was found that luminous cells distribute near the three-phase contact line, forming irregular azimuthal waves. As we show, space-time plots of quasi-one-dimensional bioluminescence measured along the contact line can be simulated by reaction-diffusion-chemotaxis equations, in which the reaction term for the cells is a logistic (autocatalytic) growth function. It was found that the growth rate of the luminous cells (~0.02 s(-1)) is >100 times higher than the growth rate of E. coli. We provide an explanation for this result by assuming that E. coli exhibits considerable respiratory flexibility (the ability of oxygen-induced switching from one metabolic pathway to another). According to the simple two-state model presented here, the number of oxic (luminous) cells grows at the expense of anoxic (dark) cells, whereas the total number of (oxic and anoxic) cells remains unchanged. It is conjectured that the corresponding reaction-diffusion-chemotaxis model for bioluminescence pattern formation can be considered as a model for the energy-taxis and metabolic self-organization in the population of the metabolically flexible bacteria under hypoxic conditions.

  1. 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

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

    SciTech Connect

    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 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. 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.

  3. The brain as a self-organizing system.

    PubMed

    Singer, W

    1986-01-01

    Clinical evidence and numerous results from animal experimentation indicate that cognitive functions have to be learned. Brain structures subserving these functions require sensory experience for their maturation. Genetic instructions are in principle not sufficient to specify neuronal connections with sufficient precision. Self-organization processes are implemented in addition which allow to optimize genetically determined blue prints of connectivity by making use of functional criteria. Thus, neuronal activity becomes an important shaping factor in the development of the structural and functional architecture of the forebrain. To the extent that this neuronal activity is modulated by sensory signals, environmental factors can influence the development of neuronal networks. Recent experiments indicate that these shaping processes are additionally controlled by modulatory systems. Both, the noradrenergic projection from the locus coeruleus and the cholinergic projection from the basal forebrain facilitate activity-dependent long-term changes of neuronal connections during development. The activity of these modulatory systems in turn depends on central states such as arousal, attention, and perhaps also motivation. It is inferred from this evidence that experience-dependent self-organization should not be considered as a passive imprinting process but rather as an active dialogue between the brain and its environment. The hypothesis is discussed that many developmental disturbances which are commonly attributed to deprivation are in fact due to defaults of the CNS which either lead to the formulation of wrong questions or to the reduction of exploratory drive.

  4. Geometry sensing by self-organized protein patterns

    PubMed Central

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

    2012-01-01

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

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

    PubMed

    Baldassarre, Gianluca; Parisi, Domenico; Nolfi, Stefano

    2006-01-01

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

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

    PubMed

    Zhao, Zhenjie; Zhang, Xuebo; Fang, Yongchun

    2015-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  8. 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

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

    PubMed

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

    2015-12-01

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

  10. 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.

  11. 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

  12. Self-Organized Behavior Generation for Musculoskeletal Robots.

    PubMed

    Der, Ralf; Martius, Georg

    2017-01-01

    With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot

  13. Self-Organized Behavior Generation for Musculoskeletal Robots

    PubMed Central

    Der, Ralf; Martius, Georg

    2017-01-01

    With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors “waiting” to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self

  14. Is there a self-organization principle of river deltas?

    NASA Astrophysics Data System (ADS)

    Tejedor, Alejandro; Longjas, Anthony; Foufoula-Georgiou, Efi

    2017-04-01

    River deltas are known to possess a complex topological and flux-partitioning structure which has recently been quantified using spectral graph theory [Tejedor et al., 2015a,b]. By analysis of real and simulated deltas it has also been shown that there is promise in formalizing relationships between this topo-dynamic delta structure and the underlying delta forming processes [e.g., Tejedor et al., 2016]. The question we pose here is whether there exists a first order organizational principle behind the self-organization of river deltas and whether this principle can be unraveled from the co-evolving topo-dynamic structure encoded in the delta planform. To answer this question, we introduce a new metric, the nonlocal Entropy Rate (nER) that captures the information content of a delta network in terms of the degree of uncertainty in delivering fluxes from any point of the network to the shoreline. We hypothesize that if the "guiding principle" of undisturbed deltas is to efficiently and robustly build land by increasing the diversity of their flux pathways over the delta plane, then they would exhibit maximum nonlocal Entropy Rate at states at which geometry and flux dynamics are at equilibrium. At the same time, their nER would be non-optimal at transient states, such as before and after major avulsions during which topology and dynamics adjust to each other to reach a new equilibrium state. We will present our results for field and simulated deltas, which confirm this hypothesis and open up new ways of thinking about self-organization, complexity and robustness in river deltas. One particular connection of interest might have important implications since entropy rate and resilience are related by the fluctuation theorem [Demetrius and Manke, 2005], and therefore our results suggest that deltas might in fact self-organize to maximize their resilience to structural and dynamic perturbations. References: Tejedor, A., A. Longjas, I. Zaliapin, and E. Foufoula

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

    PubMed

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

    2011-06-01

    Erwin Schrödinger pointed out in his 1944 book "What is Life" that one defining attribute of biological systems seems to be their tendency to generate order from disorder defying the second law of thermodynamics. Almost parallel to his findings, the science of complex systems was founded based on observations on physical and chemical systems showing that inanimate matter can exhibit complex structures although their interacting parts follow simple rules. This is explained by a process known as self-organization and it is now widely accepted that multi-cellular biological organisms are themselves self-organizing complex systems in which the relations among their parts are dynamic, contextual and interdependent. In order to fully understand such systems, we are required to computationally and mathematically model their interactions as promulgated in systems biology. The preponderance of network models in the practice of systems biology inspired by a reductionist, bottom-up view, seems to neglect, however, the importance of bidirectional interactions across spatial scales and domains. This approach introduces a shortcoming that may hinder research on emergent phenomena such as those of tissue morphogenesis and related diseases, such as cancer. Another hindrance of current modeling attempts is that those systems operate in a parameter space that seems far removed from biological reality. This misperception calls for more tightly coupled mathematical and computational models to biological experiments by creating and designing biological model systems that are accessible to a wide range of experimental manipulations. In this way, a comprehensive understanding of fundamental processes in normal development or of aberrations, like cancer, will be generated. Copyright © 2011 Elsevier Ltd. All rights reserved.

  16. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    PubMed Central

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

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

    PubMed Central

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

    2011-01-01

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

  18. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations.

    PubMed

    Wang, Sheng-Jun; Hilgetag, Claus C; Zhou, Changsong

    2011-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  19. 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.

  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. 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.

  2. 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.

  3. 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.

  4. Self-organization of mesoscopic silver wires by electrochemical deposition.

    PubMed

    Zhong, Sheng; Koch, Thomas; Walheim, Stefan; Rösner, Harald; Nold, Eberhard; Kobler, Aaron; Scherer, Torsten; Wang, Di; Kübel, Christian; Wang, Mu; Hahn, Horst; Schimmel, Thomas

    2014-01-01

    Long, straight mesoscale silver wires have been fabricated from AgNO3 electrolyte via electrodeposition without the help of templates, additives, and surfactants. Although the wire growth speed is very fast due to growth under non-equilibrium conditions, the wire morphology is regular and uniform in diameter. Structural studies reveal that the wires are single-crystalline, with the [112] direction as the growth direction. A possible growth mechanism is suggested. Auger depth profile measurements show that the wires are stable against oxidation under ambient conditions. This unique system provides a convenient way for the study of self-organization in electrochemical environments as well as for the fabrication of highly-ordered, single-crystalline metal nanowires.

  5. 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.

  6. Avalanche Prediction in a Self-Organized Pile of Beads

    NASA Astrophysics Data System (ADS)

    Ramos, O.; Altshuler, E.; Måløy, K. J.

    2009-02-01

    It is a common belief that power-law distributed avalanches are inherently unpredictable. This idea affects phenomena as diverse as evolution, earthquakes, superconducting vortices, stock markets, etc., from atomic to social scales. It mainly comes from the concept of “self-organized criticality” (SOC), where criticality is interpreted in the way that, at any moment, any small avalanche can eventually cascade into a large event. Nevertheless, this work demonstrates experimentally the possibility of avalanche prediction in the classical paradigm of SOC: a pile of grains. By knowing the position of every grain in a two-dimensional pile, avalanches of moving grains follow a distinct power-law distribution. Large avalanches, although uncorrelated, are on average preceded by continuous, detectable variations in the internal structure of the pile that are monitored in order to achieve prediction.

  7. Self-organized enhancement of conductivity in biological ion channels

    NASA Astrophysics Data System (ADS)

    Tindjong, R.; Kaufman, I.; Luchinsky, D. G.; McClintock, P. V. E.; Khovanov, I.; Eisenberg, R. S.

    2013-10-01

    We discuss an example of self-organization in a biological system. It arises from long-range ion-ion interactions, and it leads us to propose a new kind of enhanced conduction in ion channels. The underlying mechanism involves charge fluctuations near the channel mouth, amplified by the mismatch between the relative permittivities of water and the protein of the channel walls. We use Brownian dynamics simulations to show that, as in conventional ‘knock on’ permeation, these interactions can strongly enhance the channel current; but unlike the conventional mechanism, the enhancement occurs without the instigating bath ion entering the channel. The transition between these two mechanisms is clearly demonstrated, emphasizing their distinction. A simple model accurately reproduces the observed phenomena. We point out that electrolyte plus protein of low relative permittivity are universal in living systems, so that long-range ion-ion correlations of the kind considered must be common.

  8. Interrupted self-organization of SiGe pyramids.

    PubMed

    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.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  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. 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.

  13. 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

  14. 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.

  15. 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.

  16. Self-organization of disc-like molecules: chemical aspects.

    PubMed

    Kumar, Sandeep

    2006-01-01

    The hierarchical self-assembly of disc-shaped molecules leads to the formation of discotic liquid crystals. These materials are of fundamental importance not only as models for the study of energy and charge migration in self-organized systems but also as functional materials for device applications such as, one-dimensional conductors, photoconductors, light emitting diodes, photovoltaic solar cells, field-effect transistors and gas sensors. The negative birefringence films formed by polymerized nematic discotic liquid crystals have been commercialized as compensation foils to enlarge the viewing angle of commonly used twisted nematic liquid crystal displays. To date the number of discotic liquid crystals derived from more than 50 different cores comes to about 3000. This critical review describes, after an in-depth introduction, recent advances in basic design principles and synthetic approaches towards the preparation of most frequently encountered discotic liquid crystals.

  17. Microfluidic pump powered by self-organizing bacteria.

    PubMed

    Kim, Min Jun; Breuer, Kenneth S

    2008-01-01

    Results are presented that demonstrate the successful use of live bacteria as mechanical actuators in microfabricated fluid systems. The flow deposition of bacteria is used to create a motile bacterial carpet that can generate local fluid motion inside a microfabricated system. By tracking the motion of tracer particles, we demonstrate that the bacterial cells that comprise the carpet self-organize, generating a collective fluid motion that can pump fluid autonomously through a microfabricated channel at speeds as high as 25 microm s(-1). The pumping performance of the system can also be augmented by changing the chemical environment. The addition of glucose to the working buffer raises the metabolic activity of the bacterial carpet, resulting in increased pumping performance. The performance of the bacterial pump is also shown to be strongly influenced by the global geometry of the pump, with narrower channels achieving a higher pumping velocity with a faster rise time.

  18. 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

  19. Self-organization of the protocell was a forward process

    NASA Technical Reports Server (NTRS)

    Fox, S. W.; Matsuno, K.

    1983-01-01

    Yockey's (1981) interpretation of information theory relative to concepts of self-organization in the origin of life is criticized on the ground that it assumes that each amino acid residue type in a given sequence is an unaided information carrier throughout evolution. It is argued that more than one amino acid residue can act as a unit information carrier, and that this was the case in prebiotic protein evolution. Forward-extrapolation should be used to study prebiotic evolution, not backward-extrapolation. Transposing the near-random internal order of modern proteins to primitive proteins, as Yockey has done, is an unsupported assumption and disagrees with the results of experimental models of the primordial type. Studies indicate that early primary information carriers in evolution were mixtures of free alpha amino acids which necessarily had the capability of sequencing themselves.

  20. Self-Organized Criticality Model for Brain Plasticity

    NASA Astrophysics Data System (ADS)

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

    2006-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Ivanov, Plamen Ch.; Bartsch, Ronny P.

    2012-02-01

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

  2. Avalanche prediction in a self-organized pile of beads.

    PubMed

    Ramos, O; Altshuler, E; Måløy, K J

    2009-02-20

    It is a common belief that power-law distributed avalanches are inherently unpredictable. This idea affects phenomena as diverse as evolution, earthquakes, superconducting vortices, stock markets, etc., from atomic to social scales. It mainly comes from the concept of "self-organized criticality" (SOC), where criticality is interpreted in the way that, at any moment, any small avalanche can eventually cascade into a large event. Nevertheless, this work demonstrates experimentally the possibility of avalanche prediction in the classical paradigm of SOC: a pile of grains. By knowing the position of every grain in a two-dimensional pile, avalanches of moving grains follow a distinct power-law distribution. Large avalanches, although uncorrelated, are on average preceded by continuous, detectable variations in the internal structure of the pile that are monitored in order to achieve prediction.

  3. A self-organized critical model for evolution

    SciTech Connect

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

    1996-01-01

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

  4. Self-organization 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.

  5. 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.

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

    SciTech Connect

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

    2016-06-13

    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.

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

    SciTech Connect

    Paczuski, M.; Nagel, K.

    1995-12-31

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  9. Modeling financial markets by self-organized criticality.

    PubMed

    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.

  10. Autonomous Data Collection Using a Self-Organizing Map.

    PubMed

    Faigl, Jan; Hollinger, Geoffrey A

    2017-03-28

    The self-organizing map (SOM) is an unsupervised learning technique providing a transformation of a high-dimensional input space into a lower dimensional output space. In this paper, we utilize the SOM for the traveling salesman problem (TSP) to develop a solution to autonomous data collection. Autonomous data collection requires gathering data from predeployed sensors by moving within a limited communication radius. We propose a new growing SOM that adapts the number of neurons during learning, which also allows our approach to apply in cases where some sensors can be ignored due to a lower priority. Based on a comparison with available combinatorial heuristic algorithms for relevant variants of the TSP, the proposed approach demonstrates improved results, while also being less computationally demanding. Moreover, the proposed learning procedure can be extended to cases where particular sensors have varying communication radii, and it can also be extended to multivehicle planning.

  11. 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.

  12. 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.

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

    PubMed

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

    2009-04-21

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

  14. Self-organized Collaboration Network Model Based on Module Emerging

    NASA Astrophysics Data System (ADS)

    Yang, Hongyong; Lu, Lan; Liu, Qiming

    Recently, the studies of the complex network have gone deep into many scientific fields, such as computer science, physics, mathematics, sociology, etc. These researches enrich the realization for complex network, and increase understands for the new characteristic of complex network. Based on the evolvement characteristic of the author collaboration in the scientific thesis, a self-organized network model of the scientific cooperation network is presented by module emerging. By applying the theoretical analysis, it is shown that this network model is a scale-free network, and the strength degree distribution and the module degree distribution of the network nodes have the same power law. In order to make sure the validity of the theoretical analysis for the network model, we create the computer simulation and demonstration collaboration network. By analyzing the data of the network, the results of the demonstration network and the computer simulation are consistent with that of the theoretical analysis of the model.

  15. Self-organization of the protocell was a forward process

    NASA Technical Reports Server (NTRS)

    Fox, S. W.; Matsuno, K.

    1983-01-01

    Yockey's (1981) interpretation of information theory relative to concepts of self-organization in the origin of life is criticized on the ground that it assumes that each amino acid residue type in a given sequence is an unaided information carrier throughout evolution. It is argued that more than one amino acid residue can act as a unit information carrier, and that this was the case in prebiotic protein evolution. Forward-extrapolation should be used to study prebiotic evolution, not backward-extrapolation. Transposing the near-random internal order of modern proteins to primitive proteins, as Yockey has done, is an unsupported assumption and disagrees with the results of experimental models of the primordial type. Studies indicate that early primary information carriers in evolution were mixtures of free alpha amino acids which necessarily had the capability of sequencing themselves.

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

    NASA Astrophysics Data System (ADS)

    Huang, J. P.

    2015-03-01

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

  17. Self-organized critical model for protein folding

    NASA Astrophysics Data System (ADS)

    Moret, M. A.

    2011-09-01

    The major factor that drives a protein toward collapse and folding is the hydrophobic effect. At the folding process a hydrophobic core is shielded by the solvent-accessible surface area of the protein. We study the fractal behavior of 5526 protein structures present in the Brookhaven Protein Data Bank. Power laws of protein mass, volume and solvent-accessible surface area are measured independently. The present findings indicate that self-organized criticality is an alternative explanation for the protein folding. Also we note that the protein packing is an independent and constant value because the self-similar behavior of the volumes and protein masses have the same fractal dimension. This power law guarantees that a protein is a complex system. From the analyzed data, q-Gaussian distributions seem to fit well this class of systems.

  18. Coronal loops as self-organized critical systems

    NASA Astrophysics Data System (ADS)

    López Fuentes, M. C.; Klimchuk, J. A.

    We developed a numerical model that explains the evolution of coronal loops observed with GOES-SXI (see Lopez Fuentes, Klimchuk and Mandrini, ApJ, 2006, in press) in terms of Self-organized Critical Systems (SOC). We are inspired by the idea originally proposed by Parker (1988, ApJ, 330, 474), that coronal loops are made of elemental magnetic strands that wrap around each other due to photospheric convection. In our code the magnetic strength between neighbor strands increase until a threshold is reach and strands reconnect, releasing energy and heating the plasma. The number and intensity of these release events increase and a critical steady-state is reached. At some point, the photospheric dispersion makes the ``feeding'' mechanism inefficient and the loop decays. We model the plasma response and we obtain synthetic light curves that qualitatively reproduce the observed loop evolution.

  19. 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)].

  20. 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.

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

    PubMed

    Graziano, Brian R; Weiner, Orion D

    2014-10-01

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

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

    PubMed Central

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

    2013-01-01

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

  3. Self-organized correlations lead to explosive synchronization.

    PubMed

    Chen, Yang; Cao, Zhoujian; Wang, Shihong; Hu, Gang

    2015-02-01

    Very recently, a first-order phase transition, named explosive synchronization (ES), has attracted great attention due to its remarkable novelty in theory and significant impact in applications. However, so far, all observations of ES have been associated with various correlation constraints on system parameters, which restrict its generality and applications. Here we consider heterogeneous networks around Hopf bifurcation point described by chemical reaction-diffusion systems and also by their reduced order parameter versions, the complex Ginzburg-Landau equations, and demonstrate that explosive synchronization can appear as an emergent feature of oscillatory networks, and the restrictions on specific parameter correlations used so far for ES can be lifted entirely. Theoretical analyses and numerical simulations show with a perfect agreement that explosive synchronization can appear in networks with nodes having identical natural frequencies, and necessary correlation conditions for ES can be realized in a self-organized manner by network evolution.

  4. Self-organized criticality model for brain plasticity.

    PubMed

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

    2006-01-20

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

  5. 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.

  6. 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.

  7. Self-organized global control of carbon emissions

    NASA Astrophysics Data System (ADS)

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

    2010-09-01

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

  8. Nanostructure control in polymer solar cells by self-organization.

    PubMed

    Tajima, Keisuke; Hashimoto, Kazuhito

    2011-02-01

    Recently, polymer solar cells (PSCs) based on "bulk heterojunctions" using a simple mixture of electron donor and acceptor materials in thin films have been extensively studied. Although relatively high power conversion efficiencies have been achieved by using this approach, further improvement is necessary to precisely construct stable, reproducible nanostructures that are suitable for both efficient charge separation and transport inside such films. For this purpose, it is highly desirable to utilize a bottom-up approach, such as the self-organized formation of inorganic and organic nanostructures. In this review, an overview of our recent studies on the control of nanostructures in PSCs is presented. Copyright © 2011 The Japan Chemical Journal Forum and Wiley Periodicals, Inc.

  9. 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.

  10. Self-organizing feature maps for dynamic control of radio resources in CDMA microcellular networks

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    1998-03-01

    The application of artificial neural networks to the channel assignment problem for cellular code-division multiple access (CDMA) cellular networks has previously been investigated. CDMA takes advantage of voice activity and spatial isolation because its capacity is only interference limited, unlike time-division multiple access (TDMA) and frequency-division multiple access (FDMA) where capacities are bandwidth-limited. Any reduction in interference in CDMA translates linearly into increased capacity. To satisfy the high demands for new services and improved connectivity for mobile communications, microcellular and picocellular systems are being introduced. For these systems, there is a need to develop robust and efficient management procedures for the allocation of power and spectrum to maximize radio capacity. Topology-conserving mappings play an important role in the biological processing of sensory inputs. The same principles underlying Kohonen's self-organizing feature maps (SOFMs) are applied to the adaptive control of radio resources to minimize interference, hence, maximize capacity in direct-sequence (DS) CDMA networks. The approach based on SOFMs is applied to some published examples of both theoretical and empirical models of DS/CDMA microcellular networks in metropolitan areas. The results of the approach for these examples are informally compared to the performance of algorithms, based on Hopfield- Tank neural networks and on genetic algorithms, for the channel assignment problem.

  11. Temporal Fluctuations in Biorhythms: Expression of Self-Organized Criticality?

    NASA Astrophysics Data System (ADS)

    Kniffki, Klaus-D.; Mandel, Wolfgang; Tran-Gia, Phuoc

    Recently, a general organizing principle has been reported connecting 1/f-noise with the self-similar scale-invariant `fractal' properties in space, hence reflecting two sides of a coin, the so-called self-organized critical state. The basic idea is that dynamical systems with many degrees of freedom operate persistently far from equilibrium at or near a threshold of stability at the border of chaos. Temporal fluctuations which cannot be explained as consequences of statistically independent random events are found in a variety of physical and biological phenomena. The fluctuations of these systems can be characterized by a power spectrum density S(f) decaying as f-b at low frequencies with an exponent b < 1.5. We present a new approach to describe the individual biorhythm of humans using data from a colleague who has kept daily records for two years of his state of well-being applying a fifty-point magnitude category scale. This time series was described as a point process by introducing two discriminating rating levels R for the occurrence of R ≥ 40 and R ≤ 10. For b < 1 a new method to estimate the low frequency part of S(f) was applied using counting statistics without applying Fast Fourier Transform. The method applied reliably discriminates these types of fluctuations from a random point process, with b = 0.0. It is very tempting to speculate that the neural mechanisms at various levels of the nervous system underlying the perception of different values of the subjective state of well-being, are expressions of a self-organized critical state.

  12. Flexible flapping wings with self-organized microwrinkles.

    PubMed

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

    2015-06-29

    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.

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

    PubMed Central

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

    2015-01-01

    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

  14. 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

  15. 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.

  16. 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.

  17. The analysis of multispectral image data with self-organizing feature maps

    SciTech Connect

    Schaale, M.

    1996-11-01

    The analysis of multispectral sceneries is still a challenging task although many different algorithms for a mathematical analysis exist. Most classification algorithms work in a supervised mode only, i.e. they need to know the possible land usage classes prior to the calculation. In this step many simplifications and assumptions have to be done which directly influence the result. KOHONEN`s self-organizing feature maps, which are based on a biological model, provide a powerful tool to describe the multispectral scenery under consideration with a limited number of reference vectors, the so-called codebook. The resulting code-book, generated with an unsupervised learning scheme, is a compressed description of the multi-dimensional data in terms of non-linear principal components which thus overcomes the problems of a linear principal component analysis. Using this code-book as a basis for a lateral fully interconnected network and introducing a non-linear activity flow between radial-basis functions located at the-positions of the reference vectors results in an unsupervised clustering scheme. This method has been successfully adapted to multispectral sceneries recorded by casi (compact airborne spectrographic imager). 16 refs., 8 figs., 1 tab.

  18. 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.

  19. Nanospace-Mediated Self-Organization of Nanoparticles in Flexible Porous Polymer Templates.

    PubMed

    Kuroda, Yoshiyuki; Muto, Itaru; Shimojima, Atsushi; Wada, Hiroaki; Kuroda, Kazuyuki

    2017-08-31

    Self-organization is a fundamental process for the construction of complex hierarchically ordered nanostructures, which are widespread in biological systems. However, precise control of size, shape, and surface properties is required for self-organization of nanoparticles. Here, we demonstrate a novel self-organization phenomenon mediated by flexible nanospaces in templates. Inorganic nanoparticles (e.g., silica, zirconia, and titania) are deposited in porous polymer thin films with randomly distributed pores on the surface, leaving a partially filled nanospace in each pore. Heating at temperatures beyond the glass transition temperature of the template leads to self-organization of the inorganic nanoparticles into one-dimensional chainlike networks. The self-organization is mediated by the deformation and fusion of the residual nanospaces, and it can be rationally controlled by sequential heat treatments. These results show that a nanospace, defined by the nonexistence of matter, interacts indirectly with matter and can be used as a component of self-organization systems.

  20. 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.

  1. Quasiperiodic Strain Bursts and Self-Organization in Crystal Microplasticity (PREPRINT)

    DTIC Science & Technology

    2012-03-01

    AFRL-RX-WP-TP-2012-0249 QUASIPERIODIC STRAIN BURSTS AND SELF- ORGANIZATION IN CRYSTAL MICROPLASTICITY (PREPRINT) D.M. Dimiduk Metals...2012 4. TITLE AND SUBTITLE QUASIPERIODIC STRAIN BURSTS AND SELF-ORGANIZATION IN CRYSTAL MICROPLASTICITY (PREPRINT) 5a. CONTRACT NUMBER In-house...18 Quasiperiodic strain bursts and self-organization in crystal microplasticity S. Papanikolaou,1,2∗ D. M. Dimiduk,3 W. Choi4, J. P. Sethna4, M. D

  2. 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.

  3. The Ramifications of Meddling with Systems Governed by Self-organized Critical Dynamics

    NASA Astrophysics Data System (ADS)

    Carreras, B. A.; Newman, D. E.; Dobson, I.

    2002-12-01

    Complex natural, well as man-made, systems often exhibit characteristics similar to those seen in self-organized critical (SOC) systems. The concept of self-organized criticality brings together ideas of self-organization of nonlinear dynamical systems with the often-observed near critical behavior of many natural phenomena. These phenomena exhibit self-similarities over extended ranges of spatial and temporal scales. In those systems, scale lengths may be described by fractal geometry and time scales that lead to 1/f-like power spectra. Natural applications include modeling the motion of tectonics plates, forest fires, magnetospheric dynamics, spin glass systems, and turbulent transport. In man-made systems, applications have included traffic dynamics, power and communications networks, and financial markets among many others. Simple cellular automata models such as the running sandpile model have been very useful in reproducing the complexity and characteristics of these systems. One characteristic property of the SOC systems is that they relax through what we call events. These events can happen over all scales of the system. Examples of these events are: earthquakes in the case of plate tectonic; fires in forest evolution extinction in the co evolution of biological species; and blackouts in power transmission systems. In a time-averaged sense, these systems are subcritical (that is, they lie in an average state that should not trigger any events) and the relaxation events happen intermittently. The time spent in a subcritical state relative to the time of the events varies from one system to another. For instance, the chance of finding a forest on fire is very low with the frequency of fires being on the order of one fire every few years and with many of these fires small and inconsequential. Very large fires happen over time periods of decades or even centuries. However, because of their consequences, these large but infrequent events are the important ones

  4. Self organization in oleic acid-coated CoFe2O4 colloids: a SAXS study

    NASA Astrophysics Data System (ADS)

    Fernández van Raap, M. B.; Mendoza Zélis, P.; Coral, D. F.; Torres, T. E.; Marquina, C.; Goya, G. F.; Sánchez, F. H.

    2012-09-01

    We report a structural study of magnetic colloids composed of CoFe2O4 nanoparticles (mean radii in the range 2-7 nm) synthesized by thermal decomposition of different high boiling temperature organic solvents in the presence of oleic acid and oleylamine, and subsequently re-suspended in hexane. Although the surfactant layer prevents permanent aggregation and precipitation of the disperse phase, competition between attractive interactions (i.e., dipolar and van der Waals) and repulsive steric interaction leads to self organization of the magnetic nanoparticles. Our small angle X-ray scattering results evidence the presence of distinctive self organized structures in the liquid colloid depending on the type of solvent used in the synthesis. A completely homogeneous dispersion is obtained for those colloids synthesized with benzyl-ether and octadecene. Bi-disperse systems, in which nanoclusters coexist with free nanoparticles, appear when phenyl-ether and trioctylamine are used. Chain-like structures are observed in a colloid containing the particles synthesized using phenyl-ether, while more compact 3D structures form in colloids prepared with particles synthesized with trioctylamine. The presented results have important implications in the design and selection of magnetic nanoparticles for those applications where the size dispersion determines the final efficiency of the material, such as magnetic fluid hyperthermia clinical therapy.

  5. 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

  6. 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.

  7. Self-organized models of selectivity in calcium channels

    NASA Astrophysics Data System (ADS)

    Giri, Janhavi; Fonseca, James E.; Boda, Dezső; Henderson, Douglas; Eisenberg, Bob

    2011-04-01

    The role of flexibility in the selectivity of calcium channels is studied using a simple model with two parameters that accounts for the selectivity of calcium (and sodium) channels in many ionic solutions of different compositions and concentrations using two parameters with unchanging values. We compare the distribution of side chains (oxygens) and cations (Na+ and Ca2+) and integrated quantities. We compare the occupancies of cations Ca2+/Na+ and linearized conductance of Na+. The distributions show a strong dependence on the locations of fixed side chains and the flexibility of the side chains. Holding the side chains fixed at certain predetermined locations in the selectivity filter distorts the distribution of Ca2+ and Na+ in the selectivity filter. However, integrated quantities—occupancy and normalized conductance—are much less sensitive. Our results show that some flexibility of side chains is necessary to avoid obstruction of the ionic pathway by oxygen ions in 'unfortunate' fixed positions. When oxygen ions are mobile, they adjust 'automatically' and move 'out of the way', so they can accommodate the permeable cations in the selectivity filter. Structure is the computed consequence of the forces in this model. The structures are self-organized, at their free energy minimum. The relationship of ions and side chains varies with an ionic solution. Monte Carlo simulations are particularly well suited to compute induced-fit, self-organized structures because the simulations yield an ensemble of structures near their free energy minimum. The exact location and mobility of oxygen ions has little effect on the selectivity behavior of calcium channels. Seemingly, nature has chosen a robust mechanism to control selectivity in calcium channels: the first-order determinant of selectivity is the density of charge in the selectivity filter. The density is determined by filter volume along with the charge and excluded volume of structural ions confined within it

  8. 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.

  9. 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.

  10. 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.

  11. Metabolic evolution and the self-organization of ecosystems.

    PubMed

    Braakman, Rogier; Follows, Michael J; Chisholm, Sallie W

    2017-04-11

    Metabolism mediates the flow of matter and energy through the biosphere. We examined how metabolic evolution shapes ecosystems by reconstructing it in the globally abundant oceanic phytoplankter Prochlorococcus To understand what drove observed evolutionary patterns, we interpreted them in the context of its population dynamics, growth rate, and light adaptation, and the size and macromolecular and elemental composition of cells. This multilevel view suggests that, over the course of evolution, there was a steady increase in Prochlorococcus' metabolic rate and excretion of organic carbon. We derived a mathematical framework that suggests these adaptations lower the minimal subsistence nutrient concentration of cells, which results in a drawdown of nutrients in oceanic surface waters. This, in turn, increases total ecosystem biomass and promotes the coevolution of all cells in the ecosystem. Additional reconstructions suggest that Prochlorococcus and the dominant cooccurring heterotrophic bacterium SAR11 form a coevolved mutualism that maximizes their collective metabolic rate by recycling organic carbon through complementary excretion and uptake pathways. Moreover, the metabolic codependencies of Prochlorococcus and SAR11 are highly similar to those of chloroplasts and mitochondria within plant cells. These observations lead us to propose a general theory relating metabolic evolution to the self-amplification and self-organization of the biosphere. We discuss the implications of this framework for the evolution of Earth's biogeochemical cycles and the rise of atmospheric oxygen.

  12. 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.

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

    PubMed Central

    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. DOI: http://dx.doi.org/10.7554/eLife.05913.001 PMID:25821989

  14. Spatial self-organization favors heterotypic cooperation over cheating

    PubMed Central

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

    2013-01-01

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

  15. Self-organization of intracellular gradients during mitosis.

    PubMed

    Fuller, Brian G

    2010-01-29

    Gradients are used in a number of biological systems to transmit spatial information over a range of distances. The best studied are morphogen gradients where information is transmitted over many cell lengths. Smaller mitotic gradients reflect the need to organize several distinct events along the length of the mitotic spindle. The intracellular gradients that characterize mitosis are emerging as important regulatory paradigms. Intracellular gradients utilize intrinsic auto-regulatory feedback loops and diffusion to establish stable regions of activity within the mitotic cytosol. We review three recently described intracellular mitotic gradients. The Ran GTP gradient with its elaborate cascade of nuclear transport receptors and cargoes is the best characterized, yet the dynamics underlying the robust gradient of Ran-GTP have received little attention. Gradients of phosphorylation have been observed on Aurora B kinase substrates both before and after anaphase onset. In both instances the phosphorylation gradient appears to result from a soluble gradient of Aurora B kinase activity. Regulatory properties that support gradient formation are highlighted. Intracellular activity gradients that regulate localized mitotic events bare several hallmarks of self-organizing biologic systems that designate spatial information during pattern formation. Intracellular pattern formation represents a new paradigm in mitotic regulation.

  16. 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.

  17. Topology and structural self-organization in folded proteins

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  18. Tween surfactants: Adsorption, self-organization, and protein resistance

    NASA Astrophysics Data System (ADS)

    Shen, Lei; Guo, Athena; Zhu, Xiaoyang

    2011-03-01

    Tween surfactants, each containing hydrophilic ethylene glycol head groups and a hydrophobic alkyl tail, are being actively explored as protein-resistant surface coatings, but little is known about how they adsorb on surfaces. We carry out a comparative study of the adsorption of two Tween molecules (same hydrophilic head group, but a shorter dodecyl tail for Tween 20 and a longer octadecyl tail for Tween 40) on Au and polystyrene surfaces. Despite the similarity between these two molecules, there is a drastic difference in their protein resistance: a monolayer of Tween 20 on a hydrophobic surface is repulsive against protein adsorption but that of Tween 40 is not. The difference in protein resistance can be attributed to two distinctly different adsorption mechanisms. While the adsorption of Tween 40 is described by a simple first-order mechanism, that of Tween 20 consists of a fast adsorption step and a slower reorganization process at a high surface coverage. The latter leads to the formation of a high-density and self-organized monolayer, which is responsible for the enhanced stability and resistance against non-specific protein adsorption.

  19. 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

  20. Self-Organized Platinum Nanoparticles Elevated on Freestanding Graphene

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  1. 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.

  2. Trading leads to scale-free self-organization

    NASA Astrophysics Data System (ADS)

    Ebert, M.; Paul, W.

    2012-12-01

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

  3. 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.

  4. Self-organized instability in graded-index multimode fibres

    NASA Astrophysics Data System (ADS)

    Wright, Logan G.; Liu, Zhanwei; Nolan, Daniel A.; Li, Ming-Jun; Christodoulides, Demetrios N.; Wise, Frank W.

    2016-12-01

    Multimode fibres (MMFs) are attracting interest in the study of spatiotemporal dynamics as well as in the context of ultrafast fibre sources, imaging and telecommunications. This interest stems from three differences compared with single-mode fibre structures: their spatiotemporal complexity (information capacity), the role of disorder, and their complex intermodal interactions. To date, MMFs have been studied in limiting cases in which one or more of these properties can be neglected. Here, we study a regime in which all these elements are integral. We observe a spatial beam-cleaning phenomenon that precedes spatiotemporal modulation instability. We provide evidence that the origin of these processes is a universal unstable attractor in graded-index MMFs. The self-organization and instability of the attractor are both caused by intermodal interactions characterized by cooperating disorder, nonlinearity and dissipation. Disorder-enhanced nonlinear processes in MMFs have important implications for future telecommunications, and the multifaceted nature of the considered dynamics showcases MMFs as potential laboratories for a variety of topics in complexity science.

  5. 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

  6. Metabolic evolution and the self-organization of ecosystems

    PubMed Central

    Braakman, Rogier; Follows, Michael J.; Chisholm, Sallie W.

    2017-01-01

    Metabolism mediates the flow of matter and energy through the biosphere. We examined how metabolic evolution shapes ecosystems by reconstructing it in the globally abundant oceanic phytoplankter Prochlorococcus. To understand what drove observed evolutionary patterns, we interpreted them in the context of its population dynamics, growth rate, and light adaptation, and the size and macromolecular and elemental composition of cells. This multilevel view suggests that, over the course of evolution, there was a steady increase in Prochlorococcus’ metabolic rate and excretion of organic carbon. We derived a mathematical framework that suggests these adaptations lower the minimal subsistence nutrient concentration of cells, which results in a drawdown of nutrients in oceanic surface waters. This, in turn, increases total ecosystem biomass and promotes the coevolution of all cells in the ecosystem. Additional reconstructions suggest that Prochlorococcus and the dominant cooccurring heterotrophic bacterium SAR11 form a coevolved mutualism that maximizes their collective metabolic rate by recycling organic carbon through complementary excretion and uptake pathways. Moreover, the metabolic codependencies of Prochlorococcus and SAR11 are highly similar to those of chloroplasts and mitochondria within plant cells. These observations lead us to propose a general theory relating metabolic evolution to the self-amplification and self-organization of the biosphere. We discuss the implications of this framework for the evolution of Earth’s biogeochemical cycles and the rise of atmospheric oxygen. PMID:28348231

  7. Dynamic self-organization of confined autophoretic particles

    NASA Astrophysics Data System (ADS)

    Medrano, Anthony; Michelin, Sébastien; Kanso, Eva

    2016-11-01

    We study the behavior of chemically-active Janus particles in microfluidic Hele-Shaw-type confinement. These micron-scale chemical motors, when immersed in a fuel-laden fluid, produce an ionic chemical field which leads to motility and consequently a local fluid flow. In unconfined settings, experimental and computational studies have shown these particles to spontaneously self-organize into crystal structures, and form into asters of two or more particles. Here, we show that geometric confinement alters both the chemical and hydrodynamic signature of the particles in such a way that their far-field effects can be modeled as source dipoles. Each particle moves according to its own self-propelled motion and in response to the chemical and hydrodynamic field created by other particles. Two interaction modes are observed: self-assembly into quasi-static crystals and into dynamically-evolving chains. We discuss the conditions that lead to these modes of interactions and the phase transitions between them for various Janus particle concentrations. The National GEM Consortium.

  8. Ordering and self-organization in nanocrystalline silicon

    NASA Astrophysics Data System (ADS)

    Grom, G. F.; Lockwood, D. J.; McCaffrey, J. P.; Labbé, H. J.; Fauchet, P. M.; White, B.; Diener, J.; Kovalev, D.; Koch, F.; Tsybeskov, L.

    2000-09-01

    The spontaneous formation of organized nanocrystals in semiconductors has been observed during heteroepitaxial growth and chemical synthesis. The ability to fabricate size-controlled silicon nanocrystals encapsulated by insulating SiO2 would be of significant interest to the microelectronics industry. But reproducible manufacture of such crystals is hampered by the amorphous nature of SiO2 and the differing thermal expansion coefficients of the two materials. Previous attempts to fabricate Si nanocrystals failed to achieve control over their shape and crystallographic orientation, the latter property being important in systems such as Si quantum dots. Here we report the self-organization of Si nanocrystals larger than 80Å into brick-shaped crystallites oriented along the <111> crystallographic direction. The nanocrystals are formed by the solid-phase crystallization of nanometre-thick layers of amorphous Si confined between SiO2 layers. The shape and orientation of the crystallites results in relatively narrow photoluminescence, whereas isotropic particles produce qualitatively different, broad light emission. Our results should aid the development of maskless, reproducible Si nanofabrication techniques.

  9. 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.

  10. 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.

  11. 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.

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

    DOE PAGES

    Liu, Wenyan; Halverson, Jonathan; Tian, Ye; ...

    2016-06-13

    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 ismore » 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.« less

  13. Self-organization in a driven dissipative plasma system

    NASA Astrophysics Data System (ADS)

    Shaikh, Dastgeer; Dasgupta, B.; Hu, Q.; Zank, G. P.

    2010-02-01

    We perform a fully self-consistent three-dimensional numerical simulation for a compressible, dissipative magnetoplasma driven by large-scale perturbations, that contain a fairly broad spectrum of characteristic modes, ranging from largest scales to intermediate scales and down to the smallest scales, where the energy of the system is dissipated by collisional (ohmic) and viscous dissipations. Additionally, our simulation includes nonlinear interactions amongst a wide range of fluctuations that are initialized with random spectral amplitudes, leading to the cascade of spectral energy in the inertial range spectrum, and takes into account large-scale as well as small-scale perturbations that may have been induced by the background plasma fluctuations, as well as the non-adiabatic exchange of energy leading to the migration of energy from the energy-containing modes or randomly injected energy driven by perturbations and further dissipated by the smaller scales. Besides demonstrating the comparative decays of the total energy and the dissipation rate of the energy, our results show the existence of a perpendicular component of the current, thus clearly confirming that the self-organized state is non-force free.

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

    PubMed

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

    2015-02-20

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

  15. Examining the NZESM Cloud representation with Self Organizing Maps

    NASA Astrophysics Data System (ADS)

    Schuddeboom, Alex; McDonald, Adrian; Parsons, Simon; Morgenstern, Olaf; Harvey, Mike

    2017-04-01

    Several different cloud regimes are identified from MODIS satellite data and the representation of these regimes within the New Zealand Earth System Model (NZESM) is examined. For the development of our cloud classification we utilize a neural network algorithm known as self organizing maps (SOMs) on MODIS cloud top pressure - cloud optical thickness joint histograms. To evaluate the representation of the cloud within NZESM, the frequency and geographical distribution of the regimes is compared between the NZESM and satellite data. This approach has the advantage of not only identifying differences, but also potentially giving additional information about the discrepancy such as in which regions or phases of cloud the differences are most prominent. To allow for a more direct comparison between datasets, the COSP satellite simulation software is applied to NZESM output. COSP works by simulating the observational processes linked to a satellite, within the GCM, so that data can be generated in a way that shares the particular observational bias of specific satellites. By taking the COSP joint histograms and comparing them to our existing classifications we can easily search for discrepancies between the observational data and the simulations without having to be cautious of biases introduced by the satellite. Preliminary results, based on data for 2008, show a significant decrease in overall cloud fraction in the NZESM compared to the MODIS satellite data. To better understand the nature of this discrepancy, the cloud fraction related to different cloud heights and phases were also analysed.

  16. 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.

  17. Self-organization of mega-scale glacial lineations

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  18. Self-organized optical device driven by motor proteins

    PubMed Central

    Aoyama, Susumu; Shimoike, Masahiko; Hiratsuka, Yuichi

    2013-01-01

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

  19. Harmonic competition: a self-organizing multiple criteria optimization.

    PubMed

    Matsuyama, Y

    1996-01-01

    Harmonic competition is a learning strategy based upon winner-take-all or winner-take-quota with respect to a composite of heterogeneous subcosts. This learning is unsupervised and organizes itself. The subcosts may conflict with each other. Thus, the total learning system realizes a self-organizing multiple criteria optimization. The subcosts are combined additively and multiplicatively using adjusting parameters. For such a total cost, a general successive learning algorithm is derived first. Then, specific problems in the Euclidian space are addressed. Vector quantization with various constraints and traveling salesperson problems are selected as test problems. The former is a typical class of problems where the number of neurons is less than that of the data. The latter is an opposite case. Duality exists in these two classes. In both cases, the combination parameters of the subcosts show wide dynamic ranges in the course of learning. It is possible, however, to decide the parameter control from the structure of the total cost. This method finds a preferred solution from the Pareto optimal set of the multiple object optimization. Controlled mutations motivated by genetic algorithms are proved to be effective in finding near-optimal solutions.

  20. 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.

  1. 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.

  2. 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

  3. Roles of Viscous Membrane in an MHD Self-Organization

    NASA Astrophysics Data System (ADS)

    Yabuki, Kentaro; Watanabe, Kunihiko; Sato, Tetsuya

    1997-07-01

    In order to examine the role of the energy input in the formation of an ordered structure in a semi-open system, we have developed a nonlinear simulation model in which the energy input time and the dynamic response time of the system are changeable. For this purpose, a viscous membrane (boundary layer) is placed between a steady convection source and a nonlinear feedback system in which a dissipation-free magnetohydrodynamic plasma and a resistive weakly-ionized plasma are coupled.It is found that the thin viscous membrane acts to be a high-pass filter that can play a role of a fixed boundary for the dc component but a free boundary for the ac component. Because of this character of the membrane, when the ratio of the ac energy input time to the dynamic response time of the system becomes relatively large, the membrane acts to release the fluctuation (ac) energy from the system. Consequently, the positive feedback effect for the fluctuation is weakened and the structure formation is prevented as the ratio exceeds a certain critical value.It is also found that the viscous membrane plays another important role in self-organization, namely, that as the structure formation is highly progressed, the dc energy input rate is autonomously adjusted so as to keep the developed structure in a steady form.

  4. Self-organized criticality in a network of interacting neurons

    NASA Astrophysics Data System (ADS)

    Cowan, J. D.; Neuman, J.; Kiewiet, B.; van Drongelen, W.

    2013-04-01

    This paper contains an analysis of a simple neural network that exhibits self-organized criticality. Such criticality follows from the combination of a simple neural network with an excitatory feedback loop that generates bistability, in combination with an anti-Hebbian synapse in its input pathway. Using the methods of statistical field theory, we show how one can formulate the stochastic dynamics of such a network as the action of a path integral, which we then investigate using renormalization group methods. The results indicate that the network exhibits hysteresis in switching back and forward between its two stable states, each of which loses its stability at a saddle-node bifurcation. The renormalization group analysis shows that the fluctuations in the neighborhood of such bifurcations have the signature of directed percolation. Thus, the network states undergo the neural analog of a phase transition in the universality class of directed percolation. The network replicates the behavior of the original sand-pile model of Bak, Tang and Wiesenfeld in that the fluctuations about the two states show power-law statistics.

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

    PubMed

    Stella, Federico; Treves, Alessandro

    2015-03-30

    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.

  6. Self-organization of intracellular gradients during mitosis

    PubMed Central

    2010-01-01

    Gradients are used in a number of biological systems to transmit spatial information over a range of distances. The best studied are morphogen gradients where information is transmitted over many cell lengths. Smaller mitotic gradients reflect the need to organize several distinct events along the length of the mitotic spindle. The intracellular gradients that characterize mitosis are emerging as important regulatory paradigms. Intracellular gradients utilize intrinsic auto-regulatory feedback loops and diffusion to establish stable regions of activity within the mitotic cytosol. We review three recently described intracellular mitotic gradients. The Ran GTP gradient with its elaborate cascade of nuclear transport receptors and cargoes is the best characterized, yet the dynamics underlying the robust gradient of Ran-GTP have received little attention. Gradients of phosphorylation have been observed on Aurora B kinase substrates both before and after anaphase onset. In both instances the phosphorylation gradient appears to result from a soluble gradient of Aurora B kinase activity. Regulatory properties that support gradient formation are highlighted. Intracellular activity gradients that regulate localized mitotic events bare several hallmarks of self-organizing biologic systems that designate spatial information during pattern formation. Intracellular pattern formation represents a new paradigm in mitotic regulation. PMID:20181052

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

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

    PubMed

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

    2016-04-15

    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.

  13. Self-organized criticality in developing neuronal networks.

    PubMed

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

    2010-12-02

    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.

  14. Russian Character Recognition using Self-Organizing Map

    NASA Astrophysics Data System (ADS)

    Gunawan, D.; Arisandi, D.; Ginting, F. M.; Rahmat, R. F.; Amalia, A.

    2017-01-01

    The World Tourism Organization (UNWTO) in 2014 released that there are 28 million visitors who visit Russia. Most of the visitors might have problem in typing Russian word when using digital dictionary. This is caused by the letters, called Cyrillic that used by the Russian and the countries around it, have different shape than Latin letters. The visitors might not familiar with Cyrillic. This research proposes an alternative way to input the Cyrillic words. Instead of typing the Cyrillic words directly, camera can be used to capture image of the words as input. The captured image is cropped, then several pre-processing steps are applied such as noise filtering, binary image processing, segmentation and thinning. Next, the feature extraction process is applied to the image. Cyrillic letters recognition in the image is done by utilizing Self-Organizing Map (SOM) algorithm. SOM successfully recognizes 89.09% Cyrillic letters from the computer-generated images. On the other hand, SOM successfully recognizes 88.89% Cyrillic letters from the image captured by the smartphone’s camera. For the word recognition, SOM successfully recognized 292 words and partially recognized 58 words from the image captured by the smartphone’s camera. Therefore, the accuracy of the word recognition using SOM is 83.42%

  15. Computer simulations of self-organized megaripples in the nearshore

    NASA Astrophysics Data System (ADS)

    Gallagher, E. L.

    2011-03-01

    Megaripples are bed forms with heights of 20-50 cm and lengths of 1-10 m that are common in the surf zone of natural beaches. They affect sediment transport, flow energy dissipation, and larger-scale hydro- and morphodynamics. They are thought to be dynamically similar to bed forms in deserts, rivers, and deeper marine environments. Here a self-organization model (similar to models for subaerial bed forms) is used to simulate the formation and development of megaripples in the surf zone. Sediment flux is determined from combined wave and current flows using stream power and bed shear stress formulations as well as a third formulation for transport based on simple rules, which represent sheet flow. Random bed irregularities, either imposed or resulting from small variations in transport representing turbulence, are necessary seeds for bed form development. Feedback between the bed and the flow, in the form of a shadow zone downstream of a bed form and increasing flow acceleration with elevation over the crests of bed forms, alter the transport such that organized bed forms emerge. Modeled bed form morphology (including cross-sectional shape and plan view) and dynamics (including growth and migration) are similar to natural megaripples. The model can be used to extend the field observations of Clarke and Werner (2004), which suggest that, if conditions remain the same, megaripples will continue to grow. Contrary to many bed form models, this model supports the idea that bed form spacing grows continually.

  16. Thermodynamics of surface degradation, self-organization and self-healing for biomimetic surfaces.

    PubMed

    Nosonovsky, Michael; Bhushan, Bharat

    2009-04-28

    Friction is a dissipative irreversible process; therefore, entropy is produced during frictional contact. The rate of entropy production can serve as a measure of degradation (e.g. wear). However, in many cases friction leads to self-organization at the surface. This is because the excess entropy is either driven away from the surface, or it is released at the nanoscale, while the mesoscale entropy decreases. As a result, the orderliness at the surface grows. Self-organization leads to surface secondary structures either due to the mutual adjustment of the contacting surfaces (e.g. by wear) or due to the formation of regular deformation patterns, such as friction-induced slip waves caused by dynamic instabilities. The effect has practical applications, since self-organization is usually beneficial because it leads to friction and wear reduction (minimum entropy production rate at the self-organized state). Self-organization is common in biological systems, including self-healing and self-cleaning surfaces. Therefore, designing a successful biomimetic surface requires an understanding of the thermodynamics of frictional self-organization. We suggest a multiscale decomposition of entropy and formulate a thermodynamic framework for irreversible degradation and for self-organization during friction. The criteria for self-organization due to dynamic instabilities are discussed, as well as the principles of biomimetic self-cleaning, self-lubricating and self-repairing surfaces by encapsulation and micro/nanopatterning.

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

    ERIC Educational Resources Information Center

    Soltzberg, Leonard J.; And Others

    1989-01-01

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

  18. Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development.

    PubMed

    Cotter, Christopher R; Schüttler, Heinz-Bernd; Igoshin, Oleg A; Shimkets, Lawrence J

    2017-06-06

    Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell-cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with data-driven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues.

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

    NASA Astrophysics Data System (ADS)

    Aschwanden, Markus J.

    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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Self-organized synchronous oscillations in a network of excitable cells coupled by gap junctions.

    PubMed

    Lewis, T J; Rinzel, J

    2000-11-01

    Recent evidence suggests that electrical coupling plays a role in generating oscillatory behaviour in networks of neurons; however, the underlying mechanisms have not been identified. Using a cellular automata model proposed by Traub et al (Traub R D, Schmitz D, Jefferys J G and Draguhn A 1999 High-frequency population oscillations are predicted to occur in hippocampal pyramidal neural networks interconnected by axo-axonal gap junctions Neuroscience 92 407-26), we describe a novel mechanism for self-organized oscillations in networks that have strong, sparse random electrical coupling via gap junctions. The network activity is generated by random spontaneous activity that is moulded into regular population oscillations by the propagation of activity through the network. We explain how this activity gives rise to particular dependences of mean oscillation frequency on network connectivity parameters and on the rate of spontaneous activity, and we derive analytical expressions to approximate the mean frequency and variance of the oscillations. In doing so, we provide insight into possible mechanisms for frequency control and modulation in networks of neurons.

  6. Self-organization of spatial patterning in human embryonic stem cells

    PubMed Central

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

    2017-01-01

    The developing embryo is a remarkable example of self-organization, where functional units are created in a complex spatio-temporal 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 a unique opportunity to address self-organization in humans that is otherwise not addressable with current technologies. In this essay, 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. PMID:26970615

  7. 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.

  8. 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.

  9. 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

  10. Behavioral self-organization underlies the resilience of a coastal ecosystem.

    PubMed

    de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R; Herman, Peter M J; van de Koppel, Johan

    2017-07-25

    Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds (Mytilus edulis) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance.

  11. 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.

  12. 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

  13. The physical principles underpinning self-organization in plants.

    PubMed

    Turner, Philip; Nottale, Laurent

    2017-01-01

    Based on laboratory based growth of plant-like structures from inorganic materials, we present new theory for the emergence of plant structure at a range of scales dictated by levels of ionization, which can be traced directly back to proteins transcribed from genetic code and their interaction with external sources of charge in real plants. Beyond a critical percolation threshold, individual charge induced quantum potentials merge to form a complex, interconnected geometric web, creating macroscopic quantum potentials, which lead to the emergence of macroscopic quantum processes. The assembly of molecules into larger, ordered structures operates within these charge-induced coherent bosonic fields, acting as a structuring force in competition with exterior potentials. Within these processes many of the phenomena associated with standard quantum theory are recovered, including quantization, non-dissipation, self-organization, confinement, structuration conditioned by the environment, environmental fluctuations leading to macroscopic quantum decoherence and evolutionary time described by a time dependent Schrödinger-like equation, which describes models of bifurcation and duplication. The work provides a strong case for the existence of quintessence-like behaviour, with macroscopic quantum potentials and associated forces having their equivalence in standard quantum mechanics. The theory offers new insight into evolutionary processes in structural biology, with selection at any point in time, being made from a wide range of spontaneously emerging potential structures (dependent on conditions), which offer advantage for a specific organism. This is valid for both the emergence of structures from a prebiotic medium and the wide range of different plant structures we see today.

  14. 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

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

    NASA Astrophysics Data System (ADS)

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

    1998-03-01

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

  16. Conformational analysis of lipid molecules by self-organizing maps

    NASA Astrophysics Data System (ADS)

    Murtola, Teemu; Kupiainen, Mikko; Falck, Emma; Vattulainen, Ilpo

    2007-02-01

    The authors have studied the use of the self-organizing map (SOM) in the analysis of lipid conformations produced by atomic-scale molecular dynamics simulations. First, focusing on the methodological aspects, they have systematically studied how the SOM can be employed in the analysis of lipid conformations in a controlled and reliable fashion. For this purpose, they have used a previously reported 50ns atomistic molecular dynamics simulation of a 1-palmitoyl-2-linoeayl-sn-glycero-3-phosphatidylcholine (PLPC) lipid bilayer and analyzed separately the conformations of the headgroup and the glycerol regions, as well as the diunsaturated fatty acid chain. They have elucidated the effect of training parameters on the quality of the results, as well as the effect of the size of the SOM. It turns out that the main conformational states of each region in the molecule are easily distinguished together with a variety of other typical structural features. As a second topic, the authors applied the SOM to the PLPC data to demonstrate how it can be used in the analysis that goes beyond the standard methods commonly used to study the structure and dynamics of lipid membranes. Overall, the results suggest that the SOM method provides a relatively simple and robust tool for quickly gaining a qualitative understanding of the most important features of the conformations of the system, without a priori knowledge. It seems plausible that the insight given by the SOM could be applied to a variety of biomolecular systems and the design of coarse-grained models for these systems.

  17. Hyperspectral Image Classification using a Self-Organizing Map

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Sleep, Norman H.

    2011-12-01

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

  19. 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.

  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. 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.

  2. Hierarchical Self-Organization of Non-Cooperating Individuals

    PubMed Central

    Nepusz, Tamás; Vicsek, Tamás

    2013-01-01

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

  3. 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.

  4. 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.

  5. Self-Organizing Reactive Fluid Escape from Dehydrating Rocks

    NASA Astrophysics Data System (ADS)

    John, T.; Pluemper, O.; Podladchikov, Y.; Vrijmoed, J. C.; Scambelluri, M.

    2014-12-01

    Water escape from dehydrating rocks within the Earth's interior is a key process for long-term global water and element cycles, eg. at subduction zones a fluid escape mechanism must exist that prevents ocean water to be drained into the mantle. Existing fluid flow models require a priori physical assumptions (eg. preexisting porosity) and cannot resolve the evolution from initial fluid production to flow channelization. In order to develop a model of this evolution, we need to unravel natural laboratories that display the incipient dehydration stages and the micro- to macro-scale fluid escape route evolution. The Erro-Tobbio meta-serpentinites (Italy) provide a unique snapshot into these early dehydration stages, recording the breakdown of hydrous antigorite to anhydrous olivine plus fluid and the formation of an olivine-vein network. We find that dehydration, fluid pooling, and flow initiation are controlled by micro-scale compositional rock differences. Our model starts with a rock in which all water is stored in solid and any preexisting porosity is negligible (zero-porosity case). As the rock descents into the mantle increasing T will initiate dehydration reactions, dividing the rock continuously into a dry solid and a fluid-filled porosity. Spatially variable reaction progress results in dynamically evolving porosity/permeability and heterogeneous fluid-pore pressure distributions. Fluid-pressure gradient relaxation causes fluid flow and its thermodynamic feedback triggers reactions to progress, resulting in a self-amplifying process. Our new thermodynamic-mechanical model for reaction-porosity waves shows that fluid flow occurs solely in the reaction products and self-organizes into channelized fluid escape networks. This holds the key to formulating future quantitative models that address spatiotemporal processes such as the coupling between fluid release at depth and volcanic eruptions and the amounts of structurally bound water transferred into deep Earth.

  6. 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

  7. 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.

  8. Compact vortices

    NASA Astrophysics Data System (ADS)

    Bazeia, D.; Losano, L.; Marques, M. A.; Menezes, R.; Zafalan, I.

    2017-02-01

    We study a family of Maxwell-Higgs models, described by the inclusion of a function of the scalar field that represent generalized magnetic permeability. We search for vortex configurations which obey first-order differential equations that solve the equations of motion. We first deal with the asymptotic behavior of the field configurations, and then implement a numerical study of the solutions, the energy density and the magnetic field. We work with the generalized permeability having distinct profiles, giving rise to new models, and we investigate how the vortices behave, compared with the solutions of the corresponding standard models. In particular, we show how to build compact vortices, that is, vortex solutions with the energy density and magnetic field vanishing outside a compact region of the plane.

  9. Compact HPD

    SciTech Connect

    Suyama, M.; Kawai, Y.; Kimura, S.

    1996-12-31

    In order to be utilized in such application fields as high energy physics or medical imaging, where a huge number of photodetectors are assembled in designated small area, the world`s smallest HPD, the compact BFD, has been developed. The overall diameter and the length of the tube are 16mm and 15mm, respectively. The effective photocathode area is 8mm in diameter. At applied voltage of -8kV to the photocathode, the electron multiplication gain of a PD incorporated HPD (PD-BPD) is 1,600, and that of an APD (APD-BPD) is 65,000. In the pulse height distribution measurement, photoelectron peaks up to 6 photoelectrons are clearly distinguishable with the APD-BPD. Experiments established that there was no degradation of gain in magnetic fields up to 1.5T, an important performance characteristic of the compact BPD for application in high energy physics.

  10. 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).

  11. k-Nearest-Neighbor interaction induced self-organized pedestrian counter flow

    NASA Astrophysics Data System (ADS)

    Ma, Jian; Song, Wei-guo; Zhang, Jun; Lo, Siu-ming; Liao, Guang-xuan

    2010-05-01

    A recent field study confirmed that animal crowd behavior is dominated by the interaction from the k-Nearest-Neighbors rather than all the neighbors in a given metric distance. For the reason that systems with local interaction perform similar self-organized phenomena, we in this paper build two models, i.e., a metric distance based model and a k-Nearest-Neighbor ( kNN) counterflow model, based on a simple discrete cellular automaton model entitled the basic model, to investigate the fundamental interaction ruling pedestrian counter flow. Pedestrians move in a long channel and as a result are divided into left moving pedestrians and right moving pedestrians. These pedestrians interact with each other in different forms in different models. In the metric distance based model, ones direction of chosen behavior is influenced by all those who are in a small metric distance and come from the opposite direction; while in the kNN counterflow model, ones direction of chosen behavior is influenced by the distribution of a fixed number of the k-Nearest neighbors coming from the opposite direction. The self-organized lane formation is captured and factors affecting the number of lanes formed in the channel are investigated. Results imply that with varying density, the lane formation pattern is almost the same in the kNN counterflow model while it is not in the case of metric distance based model. This means that the kNN interaction plays a more fundamental role in the emergence of collective pedestrian phenomena. Then the kNN counterflow model is further validated by comparing the lane formation pattern and the fundamental diagram with real pedestrian counter flow. Reasons for the lane formation and improvement of flow rate are discussed. The relations among mean velocity, occupancy and total entrance density of the model are also studied. The results indicate that the kNN interaction provides a more efficient traffic condition, and is able to quantify features such as

  12. 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.

  13. Self-organizing map algorithm and distortion measure.

    PubMed

    Rynkiewicz, Joseph

    2006-01-01

    We study the statistical meaning of the minimization of distortion measure and the relation between the equilibrium points of the SOM algorithm and the minima of the distortion measure. If we assume that the observations and the map lie in a compact Euclidean space, we prove the strong consistency of the map which almost minimizes the empirical distortion. Moreover, after calculating the derivatives of the theoretical distortion measure, we show that the points minimizing this measure and the equilibria of the Kohonen map do not match in general. We illustrate, with a simple example, how this occurs.

  14. Compact VLSI neural computer integrated with active pixel sensor for real-time ATR applications

    NASA Astrophysics Data System (ADS)

    Fang, Wai-Chi; Udomkesmalee, Gabriel; Alkalai, Leon

    1997-04-01

    A compact VLSI neural computer integrated with an active pixel sensor has been under development to mimic what is inherent in biological vision systems. This electronic eye- brain computer is targeted for real-time machine vision applications which require both high-bandwidth communication and high-performance computing for data sensing, synergy of multiple types of sensory information, feature extraction, target detection, target recognition, and control functions. The neural computer is based on a composite structure which combines Annealing Cellular Neural Network (ACNN) and Hierarchical Self-Organization Neural Network (HSONN). The ACNN architecture is a programmable and scalable multi- dimensional array of annealing neurons which are locally connected with their local neurons. Meanwhile, the HSONN adopts a hierarchical structure with nonlinear basis functions. The ACNN+HSONN neural computer is effectively designed to perform programmable functions for machine vision processing in all levels with its embedded host processor. It provides a two order-of-magnitude increase in computation power over the state-of-the-art microcomputer and DSP microelectronics. A compact current-mode VLSI design feasibility of the ACNN+HSONN neural computer is demonstrated by a 3D 16X8X9-cube neural processor chip design in a 2-micrometers CMOS technology. Integration of this neural computer as one slice of a 4'X4' multichip module into the 3D MCM based avionics architecture for NASA's New Millennium Program is also described.

  15. 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.

  16. 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

  17. Expression cartography of human tissues using self organizing maps.

    PubMed

    Wirth, Henry; Löffler, Markus; von Bergen, Martin; Binder, Hans

    2011-07-27

    Parallel high-throughput microarray and sequencing experiments produce vast quantities of multidimensional data which must be arranged and analyzed in a concerted way. One approach to addressing this challenge is the machine learning technique known as self organizing maps (SOMs). SOMs enable a parallel sample- and gene-centered view of genomic data combined with strong visualization and second-level analysis capabilities. The paper aims at bridging the gap between the potency of SOM-machine learning to reduce dimension of high-dimensional data on one hand and practical applications with special emphasis on gene expression analysis on the other hand. The method was applied to generate a SOM characterizing the whole genome expression profiles of 67 healthy human tissues selected from ten tissue categories (adipose, endocrine, homeostasis, digestion, exocrine, epithelium, sexual reproduction, muscle, immune system and nervous tissues). SOM mapping reduces the dimension of expression data from ten of thousands of genes to a few thousand metagenes, each representing a minicluster of co-regulated single genes. Tissue-specific and common properties shared between groups of tissues emerge as a handful of localized spots in the tissue maps collecting groups of co-regulated and co-expressed metagenes. The functional context of the spots was discovered using overrepresentation analysis with respect to pre-defined gene sets of known functional impact. We found that tissue related spots typically contain enriched populations of genes related to specific molecular processes in the respective tissue. Analysis techniques normally used at the gene-level such as two-way hierarchical clustering are better represented and provide better signal-to-noise ratios if applied to the metagenes. Metagene-based clustering analyses aggregate the tissues broadly into three clusters containing nervous, immune system and the remaining tissues. The SOM technique provides a more intuitive and

  18. Templated dewetting: designing entirely self-organized platforms for photocatalysis

    PubMed Central

    Altomare, Marco; Nguyen, Nhat Truong

    2016-01-01

    Formation and dispersion of metal nanoparticles on oxide surfaces in site-specific or even arrayed configuration are key in various technological processes such as catalysis, photonics, electrochemistry and for fabricating electrodes, sensors, memory devices, and magnetic, optical, and plasmonic platforms. A crucial aspect towards an efficient performance of many of these metal/metal oxide arrangements is a reliable fabrication approach. Since the early works on graphoepitaxy in the 70s, solid state dewetting of metal films on patterned surfaces has been much explored and regarded as a most effective tool to form defined arrays of ordered metal particles on a desired substrate. While templated dewetting has been studied in detail, particularly from a mechanistic perspective on lithographically patterned Si surfaces, the resulting outstanding potential of its applications on metal oxide semiconductors, such as titania, has received only limited attention. In this perspective we illustrate how dewetting and particularly templated dewetting can be used to fabricate highly efficient metal/TiO2 photocatalyst assemblies e.g. for green hydrogen evolution. A remarkable advantage is that the synthesis of such photocatalysts is completely based on self-ordering principles: anodic self-organized TiO2 nanotube arrays that self-align to a highest degree of hexagonal ordering are an ideal topographical substrate for a second self-ordering process, that is, templated-dewetting of sputter-deposited metal thin films. The controllable metal/semiconductor coupling delivers intriguing features and functionalities. We review concepts inherent to dewetting and particularly templated dewetting, and outline a series of effective tools that can be synergistically interlaced to reach fine control with nanoscopic precision over the resulting metal/TiO2 structures (in terms of e.g. high ordering, size distribution, site specific placement, alloy formation) to maximize their photocatalytic

  19. Phase transitions in stochastic self-organizing maps

    NASA Astrophysics Data System (ADS)

    Graepel, Thore; Burger, Matthias; Obermayer, Klaus

    1997-10-01

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

  20. River delta self-organization via entropy rate analysis

    NASA Astrophysics Data System (ADS)

    Tejedor, A.; Longjas, A.; Foufoula-Georgiou, E.

    2016-12-01

    Previous work [Tejedor et al., 2015a,b; 2016] has shown that network topologic characteristics for a wide range of field and simulated delta channel networks vary significantly reflecting to some extend the different underlying physical processes. While more work remains to be done in this direction to advance quantitative delta classification, a problem of parallel interest is that of unraveling whether deltas evolve and attain topologies and flow partitions that are consistent with an underlying principle of optimization, as for example has been examined for tributary river networks. Here we study concepts of Entropy as applied to directed acyclic graphs such as river deltas, and specifically the concept of Entropy rate that measures the rate at which a stochastic process generates information. For deltas, Entropy rate can be interpreted as the amount of information we need to acquire at each time step to probabilistically track the position of the particles on the network. We propose a new Entropy metric, the non-local Entropy Rate (nER), which we argue is more pertinent to deltas as it captures the averaged information content of a delta network in terms of the degree of uncertainty in delivering fluxes from any point of the network to the shoreline. We interpret nER as measuring delta's capacity to optimally grow by spreading water and sediment over its delta top in a non-preferential way. We present results for field and simulated deltas, showing that conditional on a network topology, channel widths self-adjust such that the delivery of fluxes from the delta top to the shoreline has a maximal value of non-local Entropy Rate. Drawing on the connection between Entropy and resilience via the fluctuation theorem [Demetrius and Manke, 2005], we also suggest that deltas might in fact self-organize to maximize their resilience to perturbations. Tejedor, A., A. Longjas, I. Zaliapin, and E. Foufoula-Georgiou (2015), Water Resour. Res., 51, 3998-4018 Tejedor, A., A

  1. Expression cartography of human tissues using self organizing maps

    PubMed Central

    2011-01-01

    Background Parallel high-throughput microarray and sequencing experiments produce vast quantities of multidimensional data which must be arranged and analyzed in a concerted way. One approach to addressing this challenge is the machine learning technique known as self organizing maps (SOMs). SOMs enable a parallel sample- and gene-centered view of genomic data combined with strong visualization and second-level analysis capabilities. The paper aims at bridging the gap between the potency of SOM-machine learning to reduce dimension of high-dimensional data on one hand and practical applications with special emphasis on gene expression analysis on the other hand. Results The method was applied to generate a SOM characterizing the whole genome expression profiles of 67 healthy human tissues selected from ten tissue categories (adipose, endocrine, homeostasis, digestion, exocrine, epithelium, sexual reproduction, muscle, immune system and nervous tissues). SOM mapping reduces the dimension of expression data from ten of thousands of genes to a few thousand metagenes, each representing a minicluster of co-regulated single genes. Tissue-specific and common properties shared between groups of tissues emerge as a handful of localized spots in the tissue maps collecting groups of co-regulated and co-expressed metagenes. The functional context of the spots was discovered using overrepresentation analysis with respect to pre-defined gene sets of known functional impact. We found that tissue related spots typically contain enriched populations of genes related to specific molecular processes in the respective tissue. Analysis techniques normally used at the gene-level such as two-way hierarchical clustering are better represented and provide better signal-to-noise ratios if applied to the metagenes. Metagene-based clustering analyses aggregate the tissues broadly into three clusters containing nervous, immune system and the remaining tissues. Conclusions The SOM technique

  2. 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

  3. 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

  4. Dissecting Ubiquitin Folding Using the Self-Organized Polymer Model.

    PubMed

    Reddy, Govardhan; Thirumalai, D

    2015-08-27

    Folding of Ubiquitin (Ub), a functionally important protein found in eukaryotic organisms, is investigated at low and neutral pH at different temperatures using simulations of the coarse-grained self-organized-polymer model with side chains (SOP-SC). The melting temperatures (Tm's), identified with the peaks in the heat capacity curves, decrease as pH decreases, in qualitative agreement with experiments. The calculated radius of gyration, showing dramatic variations with pH, is in excellent agreement with scattering experiments. At Tm, Ub folds in a two-state manner at low and neutral pH. Clustering analysis of the conformations sampled in equilibrium folding trajectories at Tm, with multiple transitions between the folded and unfolded states, shows a network of metastable states connecting the native and unfolded states. At low and neutral pH, Ub folds with high probability through a preferred set of conformations resulting in a pH-dependent dominant folding pathway. Folding kinetics reveal that Ub assembly at low pH occurs by multiple pathways involving a combination of nucleation-collapse and diffusion collision mechanism. The mechanism by which Ub folds is dictated by the stability of the key secondary structural elements responsible for establishing long-range contacts and collapse of Ub. Nucleation collapse mechanism holds if the stability of these elements are marginal, as would be the case at elevated temperatures. If the lifetimes associated with these structured microdomains are on the order of hundreds of microseconds, then Ub folding follows the diffusion-collision mechanism with intermediates, many of which coincide with those found in equilibrium. Folding at neutral pH is a sequential process with a populated intermediate resembling that sampled at equilibrium. The transition state structures, obtained using a Pfold analysis, are homogeneous and globular with most of the secondary and tertiary structures being native-like. Many of our findings for

  5. Structure and dynamics in self-organized C60 fullerenes.

    PubMed

    Patnaik, Archita

    2007-01-01

    This manuscript on 'structure and dynamics in self-organized C60 fullerenes' has three sections dealing with: (A) pristine C60 aggregate structure and geometry in solvents of varying dielectric constant. Here, using positronium (Ps) as a fundamental probe which maps changes in the local electron density of the microenvironment, the onset concentration for stable C60 aggregate formation and its phase behavior is deduced from the specific interactions of the Ps atom with the surrounding. (B) A novel methanofullerene dyad, based on a hydrophobic (acceptor C60 moiety)-hydrophilic (bridge with benzene and ester functionalities)-hydrophobic (donor didodecyloxybenzene) network is chosen for investigation of characteristic self-assembly it undergoes leading to supramolecular aggregates. The pi-electronic amphiphile, necessitating a critical dielectric constant epsilon > or = 30 in binary THF-water mixtures, dictated the formation of bilayer vesicles as precursors for spherical fractal aggregates upon complete dyad extraction into a more polar water phase. (C) While the molecular orientation is dependent on the packing density, the ordering of the molecular arrangement, indispensable for self-assembly depends on the balance between the structures demanded by inter-molecular and molecule-substrate interactions. The molecular orientation in a monolayer affects the orientation in a multilayer, formed on the monolayer, suggesting the possibility of the latter to act as a template for controlling the structure of the three dimensionally grown self-assembled molecular aggregation. A systematic study on the electronic structure and orientation associated with C60 functionalized aminothiol self-assembled monolayers on Au(111) surface is presented using surface sensitive Ultra-Violet Photoelectron Spectroscopy (UPS) and C-K edge Near-Edge X-ray Absorption Fine Structure (NEXAFS) spectroscopy. The results revealed drastic modifications to d-band structure of Au(111) and the

  6. Initial Evidence for Self-Organized Criticality in Electric Power System Blackouts

    SciTech Connect

    Carreras, B.A.; Dobson, I.; Newman, D.E.; Poole, A.B.

    2000-01-04

    We examine correlations in a time series of electric power system blackout sizes using scaled window variance analysis and R/S statistics. The data shows some evidence of long time correlations and has Hurst exponent near 0.7. Large blackouts tend to correlate with further large blackouts after a long time interval. Similar effects are also observed in many other complex systems exhibiting self-organized criticality. We discuss this initial evidence and possible explanations for self-organized criticality in power systems blackouts. Self-organized criticality, if fully confirmed in power systems, would suggest new approaches to understanding and possibly controlling blackouts.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  8. Tissue as a self-organizing system with fractal dynamics.

    PubMed

    Waliszewski, P; Konarski, J

    2001-01-01

    Cell is a supramolecular dynamic network. Screening of tissue-specific cDNA library and results of Relative RT-PCR indicate that the relationship between genotype, (i.e., dynamic network of genes and their protein regulatory elements) and phenotype is non-bijective, and mendelian inheritance is a special case only. This implies non-linearity, complexity, and quasi-determinism, (i.e., co-existence of deterministic and non-deterministic events) of dynamic cellular network; prerequisite conditions for the existence of fractal structure. Indeed, the box counting method reveals that morphological patterns of the higher order, such as gland-like structures or populations of differentiating cancer cells possess fractal dimension and self-similarity. Since fractal space is not filled out randomly, a variety of morphological patterns of functional states arises. The expansion coefficient characterizes evolution of fractal dynamics. The coefficient indicates what kind of interactions occurs between cells, and how far from the limiting integer dimension of the Euclidean space the expanding population of cells is. We conclude that cellular phenomena occur in the fractal space; aggregation of cells is a supracollective phenomenon (expansion coefficient > 0), and differentiation is a collective one (expansion coefficient < 0). Fractal dimension or self-similarity are lost during tumor progression. The existence of fractal structure in a complex tissue system denotes that dynamic cellular phenomena generate an attractor with the appropriate organization of space-time. And vice versa, this attractor sets up physical limits for cellular phenomena during their interactions with various fields. This relationship can help to understand the emergence of extraterrestial forms of life. Although those forms can be composed of non-carbon molecules, fractal structure appears to be the common feature of all interactive biosystems.

  9. 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.

  10. Observation of a nonaxisymmetric magnetohydrodynamic self-organized state

    SciTech Connect

    Cothran, C. D.; Brown, M. R.; Gray, T.; Schaffer, M. J.; Marklin, G.; Lukin, V. S.

    2010-05-15

    A nonaxisymmetric stable magnetohydrodynamic (MHD) equilibrium within a prolate cylindrical conducting boundary has been produced experimentally at Swarthmore Spheromak Experiment (SSX) [M. R. Brown et al., Phys. Plasmas 6, 1717 (1999)]. It has m=1 toroidal symmetry, helical distortion, and flat lambda profile. Each of these observed characteristics are in agreement with the magnetically relaxed minimum magnetic energy Taylor state. The Taylor state is computed using the methods described by A. Bondeson et al. [Phys. Fluids 24, 1682 (1981)] and by J. M. Finn et al. [Phys. Fluids 24, 1336 (1981)] and is compared in detail to the measured internal magnetic structure. The lifetime of this nonaxisymmetric compact torus (CT) is comparable to or greater than that of the axisymmetric CTs produced at SSX; thus suggesting confinement is not degraded by its nonaxisymmetry. For both one- and two-spheromak initial state plasmas, this same equilibrium consistently emerges as the final state.

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

    SciTech Connect

    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.

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

    SciTech Connect

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

    2016-07-13

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

  13. Resource Provisioning in Large-Scale Self-Organizing Distributed Systems

    DTIC Science & Technology

    2012-06-01

    V. On-Line Service Profiling, Self-Organization, and Caching Configurations ............109 Introduction...Experiment .............................................................................126 Tenant Placement and Caching ...Configuration Quality with Caching Only .................................................152 25. Mean Response Time for Random

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. Self-Organization of FePt Nanoparticles on Photochemically Modified Diblock Copolymer Templates

    DTIC Science & Technology

    2005-01-01

    30, 6507. Self-Organization of FePt Nanoparticles on Photochemically Modified Diblock Copolymer Templates** By Seth B. Darling, Nataliya A. Yufa...60637 (USA) [**] The authors thank Ward Lopes for useful discussions and A. C. Sa- mia, J. Schleuter, and X. M. Lin for providing the FePt nanoparticles...REPORT DATE 2005 2. REPORT TYPE 3. DATES COVERED 00-00-2005 to 00-00-2005 4. TITLE AND SUBTITLE Self-Organization of FePt Nanoparticles on

  1. TransitSOM: Self-Organizing Map for Kepler and K2 transits

    NASA Astrophysics Data System (ADS)

    Armstrong, D. J.; Pollacco, D.; Santerne, A.

    2017-03-01

    A self-organizing map (SOM) can be used to identify planetary candidates from Kepler and K2 datasets with accuracies near 90% in distinguishing known Kepler planets from false positives. TransitSOM classifies a Kepler or K2 lightcurve using a self-organizing map (SOM) created and pre-trained using PyMVPA (ascl:1703.009). It includes functions for users to create their own SOMs.

  2. 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.

  3. 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.

  4. Compact torus

    SciTech Connect

    Furth, H.P.

    1980-10-01

    The objective of the compact torus approach is to provide toroidal magnetic-field configurations that are based primarily on plasma currents and can be freed from closely surrounding mechanical structures. Some familiar examples are the current-carrying plasma rings of reversed-field theta pinches and relativistic-electron smoke ring experiments. The spheromak concept adds an internal toroidal magnetic field component, in order to enhance MHD stability. In recent experiments, three different approaches have been used to generate spheromak plasmas: (1) the reversed-field theta pinch; (2) the coaxial plasma gun; (3) a new quasi-static method, based on the initial formation of a toroidal plasma sleeve around a mechanical ring that generates poloidal and toroidal fluxes, followed by field-line reconnection to form a detached spheromak plasma. The theoretical and experimental MHD stability results for the spheromak configuration are found to have common features.

  5. Self-organization of actin networks by a monomeric myosin

    PubMed Central

    Saczko-Brack, Dario; Warchol, Ewa; Rogez, Benoit; Kröss, Markus; Heissler, Sarah M.; Sellers, James R.; Batters, Christopher; Veigel, Claudia

    2016-01-01

    The organization of actomyosin networks lies at the center of many types of cellular motility, including cell polarization and collective cell migration during development and morphogenesis. Myosin-IXa is critically involved in these processes. Using total internal reflection fluorescence microscopy, we resolved actin bundles assembled by myosin-IXa. Electron microscopic data revealed that the bundles consisted of highly ordered lattices with parallel actin polarity. The myosin-IXa motor domains aligned across the network, forming cross-links at a repeat distance of precisely 36 nm, matching the helical repeat of actin. Single-particle image processing resolved three distinct conformations of myosin-IXa in the absence of nucleotide. Using cross-correlation of a modeled actomyosin crystal structure, we identified sites of additional mass, which can only be accounted for by the large insert in loop 2 exclusively found in the motor domain of class IX myosins. We show that the large insert in loop 2 binds calmodulin and creates two coordinated actin-binding sites that constrain the actomyosin interactions generating the actin lattices. The actin lattices introduce orientated tracks at specific sites in the cell, which might install platforms allowing Rho-GTPase–activating protein (RhoGAP) activity to be focused at a definite locus. In addition, the lattices might introduce a myosin-related, force-sensing mechanism into the cytoskeleton in cell polarization and collective cell migration. PMID:27956608

  6. 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.

  7. Compaction behavior of roller compacted ibuprofen.

    PubMed

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

    2008-06-01

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

  8. 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.

  9. Compact Reactor

    NASA Astrophysics Data System (ADS)

    Williams, Pharis E.

    2007-01-01

    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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. Identification of leader and self-organizing communities in complex networks.

    PubMed

    Fu, Jingcheng; Zhang, Weixiong; Wu, Jianliang

    2017-04-06

    Community or module structure is a natural property of complex networks. Leader communities and self-organizing communities have been introduced recently to characterize networks and understand how communities arise in complex networks. However, identification of leader and self-organizing communities is technically challenging since no adequate quantification has been developed to properly separate the two types of communities. We introduced a new measure, called ratio of node degree variances, to distinguish leader communities from self-organizing communities, and developed a statistical model to quantitatively characterize the two types of communities. We experimentally studied the power and robustness of the new method on several real-world networks in combination of some of the existing community identification methods. Our results revealed that social networks and citation networks contain more leader communities whereas technological networks such as power grid network have more self-organizing communities. Moreover, our results also indicated that self-organizing communities tend to be smaller than leader communities. The results shed new lights on community formation and module structures in complex systems.

  16. Transition from diffuse to self-organized discharge in a high frequency dielectric barrier discharge

    NASA Astrophysics Data System (ADS)

    Belinger, Antoine; Naudé, Nicolas; Gherardi, Nicolas

    2017-05-01

    Depending on the operating conditions, different regimes can be obtained in a dielectric barrier discharge (DBD): filamentary, diffuse (also called homogeneous) or self-organized. For a plane-to-plane DBD operated at high frequency (160 kHz) and at atmospheric pressure in helium gas, we show that the addition of a small amount of nitrogen induces a transition from the diffuse regime to a self-organized regime characterized by the appearance of filaments at the exit of the discharge. In this paper, we detail mechanisms that could be responsible of the transition from diffuse mode to this self-organized mode. We point out the critical role of the power supply and the importance of the gas memory effect from one discharge to the following one on the transition to the self-organised mode. The self-organized mode is usually attributed to a surface memory effect. In this work, we show an additional involvement of the gas memory effect on the self-organized mode. Contribution to the topical issue "The 15th International Symposium on High Pressure Low Temperature Plasma Chemistry (HAKONE XV)", edited by Nicolas Gherardi and Tomáš Hoder

  17. 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

  18. Global consensus theorem and self-organized criticality: unifying principles for understanding self-organization, swarm intelligence and mechanisms of carcinogenesis.

    PubMed

    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

  19. 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

  20. Domain-driven morphogenesis of cellular membranes

    PubMed Central

    Shnyrova, Anna V.; Frolov, Vadim A.; Zimmerberg, Joshua

    2012-01-01

    SUMMARY Cellular shape is defined by its boundary: the membrane. Extremely dynamic at small scales, biological membranes retain identifiable stationary shape as large structures, such as organelles. The lipid bilayer serves as a matrix for this shape-defining membrane, linking membrane dynamics and structural stability. Here, we analyze the central role of proteo-lipid membrane domains in the coordination of membrane dynamics and in the self-organization of membrane shape. PMID:19906579