Genesis of self-organized zebra textures in burial dolomites: Displacive veins, induced stress, and dolomitization

The dolomite veins making up rhythmites common in burial dolomites are not cement infillings of supposed cavities, as in the prevailing view, but are instead displacive veins, veins that pushed aside the host dolostone as they grew. Evidence that the veins are displacive includes a) small transform-fault-like displacements that could not have taken place if the veins were passive cements, and b) stylolites in host rock that formed as the veins grew in order to compensate for the volume added by the veins. Each zebra vein consists of crystals that grow inward from both sides, and displaces its walls via the local induced stress generated by the crystal growth itself. The petrographic criterion used in recent literature to interpret zebra veins in dolomites as cements - namely, that euhedral crystals can grow only in a prior void - disregards evidence to the contrary. The idea that flat voids did form in dolostones is incompatible with the observed optical continuity between the saddle dolomite euhedra of a vein and the replacive dolomite crystals of the host. The induced stress is also the key to the self-organization of zebra veins: In a set of many incipient, randomly-spaced, parallel veins just starting to grow in a host dolostone, each vein¿s induced stress prevents too-close neighbor veins from nucleating, or redissolves them by pressure-solution. The veins that survive this triage are those just outside their neighbors¿s induced stress haloes, now forming a set of equidistant veins, as observed.

Giant step bunching from self-organized coalescence of SrRuO3 islands

Step bunching develops in the epitaxy of SrRuO3 on vicinal SrTiO3(001) substrates. We have investigated the formation mechanisms and we show here that step bunching forms by lateral coalescence of wedgelike three-dimensional islands that are nucleated at substrate steps. After coalescence, wedgelike islands become wider and straighter with growth, forming a self-organized network of parallel step bunches with altitudes exceeding 30 unit cells, separated by atomically flat terraces. The formation mechanism of step bunching in SrRuO3, from nucleated islands, radically differs from one-dimensional models used to describe bunching in semiconducting materials. These results illustrate that growth phenomena of complex oxides can be dramatically different to those in semiconducting or metallic systems.

What determines the wavelength of self-organized shoreline sand waves?

Shoreline undulations extending into the bathymetric contours with a length scale larger than that of the rhythmic surf zone bars are referred to as shoreline sand waves. Many observed undulations along sandy coasts display a wavelength in the order 1-7 km. Several models that are based on the hypothesis that sand waves emerge from a morphodynamic instability in case of very oblique wave incidence predict this range of wavelengths. Here we investigate the physical reasons for the wavelength selection and the main parametric trends of the wavelength in case of sand waves arising from such instability. It is shown that the existence of a minimum wavelength depends on an interplay between three factors affecting littoral drift: (A) the angle of wave fronts relative to local shoreline, which tends to cause maximum transport at the downdrift flank of the sand wave, (B) the refractive energy spreading which tends to cause maximum transport at the updrift flank and (C) wave focusing (de-focusing) by the capes (bays), which tends to cause maximum transport at the crest or slightly downdrift of it. Processes A and C cause decay of the sand waves while process B causes their growth. For low incidence angles, B is very weak so that a rectilinear shoreline is stable. For large angles and long sand waves, B is dominant and causes the growth of sand waves. For large angles and short sand waves C is dominant and the sand waves decay. Thus, wavelength selection depends on process C, which essentially depends on shoreline curvature. The growth rate of very long sand waves is weak because the alongshore gradients in sediment transport decrease with the wavelength. This is why there is an optimum or dominant wavelength. It is found that sand wave wavelength scales with λ0/β where λ0 is the water wave wavelength in deep water and β is the mean bed slope from shore to the wave base.

Self-accelerating dolomite-for-calcite replacement: Self-organized dynamics of burial dolomitization and associated mineralization

A new dynamic model of dolomitization predicts a multitude of textural, paragenetic, geochemical and other properties of burial dolomites. The model is based on two postulates, (1) that the dolomitizing brine is Mg-rich but under saturated with both calcite and dolomite, and (2) that the dolomite-for-calcite replacement happens not by dissolution-precipitation as usually assumed, but by dolomite-growth-driven pressure solution of the calcite host. Crucially, the dolomite-for-calcite replacement turns out to be self-accelerating via Ca2 : the Ca2 released by each replacement increment accelerates the rate of the next, and so on. As a result, both pore-fluid Ca2 and replacement rate grow exponentially.

Giant step bunching from self-organized coalescence of SrRuO3 islands

Step bunching develops in the epitaxy of SrRuO3 on vicinal SrTiO3(001) substrates. We have investigated the formation mechanisms and we show here that step bunching forms by lateral coalescence of wedgelike three-dimensional islands that are nucleated at substrate steps. After coalescence, wedgelike islands become wider and straighter with growth, forming a self-organized network of parallel step bunches with altitudes exceeding 30 unit cells, separated by atomically flat terraces. The formation mechanism of step bunching in SrRuO3, from nucleated islands, radically differs from one-dimensional models used to describe bunching in semiconducting materials. These results illustrate that growth phenomena of complex oxides can be dramatically different to those in semiconducting or metallic systems.

Self-organized distribution of periodicity and chaos in an electrochemical oscillator

We report a detailed numerical investigation of a prototype electrochemical oscillator, in terms of high-resolution phase diagrams for an experimentally relevant section of the control (parameter) space. The prototype model consists of a set of three autonomous ordinary differential equations which captures the general features of electrochemical oscillators characterized by a partially hidden negative differential resistance in an N-shaped current-voltage stationary curve. By computing Lyapunov exponents, we provide a detailed discrimination between chaotic and periodic phases of the electrochemical oscillator. Such phases reveal the existence of an intricate structure of domains of periodicity self-organized into a chaotic background. Shrimp-like periodic regions previously observed in other discrete and continuous systems were also observed here, which corroborate the universal nature of the occurrence of such structures. In addition, we have also found a structured period distribution within the order region. Finally we discuss the possible experimental realization of comparable phase diagrams.

Self-organized criticality and the predictability of human behavior

The behavior of normal individuals and psychiatric patients vary in a similar way following power laws. The presence of identical patterns of behavioral variation occurring in individuals with different levels of activity is suggestive of self-similarity phenomena. Based on these findings, we propose that the human behavior in social context can constitute a system exhibiting self-organized criticality (SOC). The introduction of SOC concept in psychological theories can help to approach the question of behavior predictability by taking into consideration their intrinsic stochastic character. Also, the ceteris paribus generalizations characteristic of psychological laws can be seen as a consequence of individual level description of a more complex collective phenomena. Although limited, this study suggests that, if an adequate level of description is adopted, the complexity of human behavior can be more easily approached and their individual and social components can be more realistically modeled. (C) 2009 Elsevier Ltd. All rights reserved.

Negotiation mechanism for self-organized scheduling system

This paper presents a negotiation mechanism for Dynamic Scheduling based on Swarm Intelligence (SI). Under the new negotiation mechanism, agents must compete to obtain a global schedule. SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviors of insects and other animals. This work is concerned with negotiation, the process through which multiple selfinterested agents can reach agreement over the exchange of operations on competitive resources.

Negotiation mechanism for self-organized scheduling system with collective intelligence

Current Manufacturing Systems challenges due to international economic crisis, market globalization and e-business trends, incites the development of intelligent systems to support decision making, which allows managers to concentrate on high-level tasks management while improving decision response and effectiveness towards manufacturing agility. This paper presents a novel negotiation mechanism for dynamic scheduling based on social and collective intelligence. Under the proposed negotiation mechanism, agents must interact and collaborate in order to improve the global schedule. Swarm Intelligence (SI) is considered a general aggregation term for several computational techniques, which use ideas and inspiration from the social behaviors of insects and other biological systems. This work is primarily concerned with negotiation, where multiple self-interested agents can reach agreement over the exchange of operations on competitive resources. Experimental analysis was performed in order to validate the influence of negotiation mechanism in the system performance and the SI technique. Empirical results and statistical evidence illustrate that the negotiation mechanism influence significantly the overall system performance and the effectiveness of Artificial Bee Colony for makespan minimization and on the machine occupation maximization.

Self-organized criticality induced by diversity

We have studied the collective behavior of a population of integrate-and-fire oscillators. We show that diversity, introduced in terms of a random distribution of natural periods, is the mechanism that permits one to observe self-organized criticality (SOC) in the long time regime. As diversity increases the system undergoes several transitions from a supercritical regime to a subcritical one, crossing the SOC region. Although there are resemblances with percolation, we give proofs that criticality takes place for a wide range of values of the control parameter instead of a single value.

Long-tailed trapping times and Lévy flights in a self-organized critical granular system

We present a continuous time random walk model for the scale-invariant transport found in a self-organized critical rice pile [K. Christensen et al., Phys. Rev. Lett. 77, 107 (1996)]. From our analytical results it is shown that the dynamics of the experiment can be explained in terms of Lvy flights for the grains and a long-tailed distribution of trapping times. Scaling relations for the exponents of these distributions are obtained. The predicted microscopic behavior is confirmed by means of a cellular automaton model.

Self-organized criticality and synchronization in a coupled map lattice model of integrate-and-fire oscillators

We introduce two coupled map lattice models with nonconservative interactions and a continuous nonlinear driving. Depending on both the degree of conservation and the convexity of the driving we find different behaviors, ranging from self-organized criticality, in the sense that the distribution of events (avalanches) obeys a power law, to a macroscopic synchronization of the population of oscillators, with avalanches of the size of the system.

Symmetries and fixed point stability of stochastic differential equations modeling self-organized criticality

A stochastic nonlinear partial differential equation is constructed for two different models exhibiting self-organized criticality: the Bak-Tang-Wiesenfeld (BTW) sandpile model [Phys. Rev. Lett. 59, 381 (1987); Phys. Rev. A 38, 364 (1988)] and the Zhang model [Phys. Rev. Lett. 63, 470 (1989)]. The dynamic renormalization group (DRG) enables one to compute the critical exponents. However, the nontrivial stable fixed point of the DRG transformation is unreachable for the original parameters of the models. We introduce an alternative regularization of the step function involved in the threshold condition, which breaks the symmetry of the BTW model. Although the symmetry properties of the two models are different, it is shown that they both belong to the same universality class. In this case the DRG procedure leads to a symmetric behavior for both models, restoring the broken symmetry, and makes accessible the nontrivial fixed point. This technique could also be applied to other problems with threshold dynamics.

Noise and dynamics of self-organized critical phenomena

Different microscopic models exhibiting self-organized criticality are studied numerically and analytically. Numerical simulations are performed to compute critical exponents, mainly the dynamical exponent, and to check universality classes. We find that various models lead to the same exponent, but this universality class is sensitive to disorder. From the dynamic microscopic rules we obtain continuum equations with different sources of noise, which we call internal and external. Different correlations of the noise give rise to different critical behavior. A model for external noise is proposed that makes the upper critical dimensionality equal to 4 and leads to the possible existence of a phase transition above d=4. Limitations of the approach of these models by a simple nonlinear equation are discussed.