947 resultados para Chaotic synchronization


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We derive the chaotic expansion of the product of nth- and first-order multiple stochastic integrals with respect to certain normal martingales. This is done by application of the classical and quantum product formulae for multiple stochastic integrals. Our approach extends existing results on chaotic calculus for normal martingales and exhibits properties, relative to multiple stochastic integrals, polynomials and Wick products, that characterize the Wiener and Poisson processes.

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Considering teams as complex adaptive systems (CAS) this study deals with changes in team effectiveness over time in a specific context: professional basketball. The sample comprised 23 basketball teams whose outcomes were analysed over a 12-year period according to two objective measures. The results reveal that all the teams showed chaotic dynamics, one of the key characteristics of CAS. A relationship was also found between teams showing low-dimensional chaotic dynamics and better outcomes, supporting the idea of healthy variability in organizational behaviour. The stability of the squad was likewise found to influence team outcomes, although it was not associated with the chaotic dynamics in team effectiveness. It is concluded that studying teams as CAS enables fluctuations in team effectiveness to be explained, and that the techniques derived from nonlinear dynamical systems, developed specifically for the study of CAS, are useful for this purpose.

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Background: Glutathione (GSH) dysregulation at the gene, protein and functional levels observed in schizophrenia patients, and schizophrenia-like anomalies in GSH deficit experimental models, suggest that genetic glutathione synthesis impairments represent one major risk factor for the disease (Do et al., 2009). In a randomized, double blind, placebo controlled, add-on clinical trial of 140 patients, the GSH precursor N-Acetyl-Cysteine (NAC, 2 g/day, 6 months) significantly improved the negative symptoms and reduced side-effects due to antipsychotics (Berk et al., 2008). In a subset of patients (n=7), NAC (2 g/day, 2 months, cross-over design) also improved auditory evoked potentials, the NMDAdependent mismatch negativity (Lavoie et al, 2008). Methods: To determine whether increased GSH levels would modulate the topography of functional brain connectivity, we applied a multivariate phase synchronization (MPS) estimator (Knyazeva et al, 2008) to dense-array EEGs recorded during rest with eyes closed at the protocol onset, the point of crossover, and at its end. Phase synchronization phenomena are appealing because they can be associated to synchronized phases while the amplitudes stay uncorrelated. MPS measures the degree of interactions among the recorded neuronal oscillators by quantifiying to what extent they behave like a macro-oscillator (i.e. the oscillators are phase synchronous). To assess the whole-head synchronization topography, we computed the MPS sensor-wise over the cluster of locations defined by the sensor itself and he surrounding ones belonging to its second-order neighborhood (Carmeli et al, 2005). Such a cluster spans about 12 cm on average. Abstracts 245 Results: The whole-head imaging revealed a specific synchronization landscape in NAC compared to placebo condition. In particular, NAC increased MPS over frontal and left temporal regions in a frequency-specific manner. Importantly, the topography and direction of MPS changes were similar and robust in all 7 patients. Moreover, these changes correlated with the changes in the Liddle's score of disorganization (Liddle, 1987) thus linking EEG synchronization to the improvement of clinical picture. Discussion: The data suggest an important pathway towards new therapeutic strategies that target GSH dysregulation in schizophrenia. They also show the utility of MPS mapping as a marker of treatment efficacy.

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Aim: 125I-iododeoxyuridine is a potential Auger radiation therapy agent. Its incorporation in DNA of proliferating cells is enhanced by fluorodeoxyuridine. Here, we evaluated therapeutic activities of 125I-iododeoxyuridine in an optimized fluorodeoxyuridine pre-treatment inducing S-phase synchronization. Methods: After S-phase synchronization by fluorodeoxyuridine, cells were treated with 125I-iododeoxyuridine. Apoptosis analysis and S-phase synchronization were studied by flow cytometry. Cell survival was determined by colony-forming assay. Based on measured growth parameters, the number of decays per cell that induced killing was extrapolated. Results: Treatment experiments showed that 72 to 91% of synchronized cells were killed after 0.8 and 8 kBq/ml 125I-iododeoxyuridine incubation, respectively. In controls, only 8 to 38% of cells were killed by corresponding 125I-iododeoxyuridine activities alone and even increasing the activity to 80 kBq/ml gave only 42 % killing. Duplicated treatment cycles or repeated fluorodeoxyuridine pre-treatment allowed enhancing cell killing to >95 % at 8 kBq/ml 125I-iododeoxyuridine. About 50 and 160 decays per S-phase cells in controls and S-phase synchronization, respectively, were responsible for the observed cell killing at 0.8 kBq/ml radio-iododeoxyuridine. Conclusion: These data show the successful application of fluorodeoxyuridine that provided increased 125I-iododeoxyuridine Auger radiation cell killing efficacy through S-phase synchronization and high DNA incorporation of radio-iododeoxyuridine.

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There is much policy interest in the possible linkages that might exist between land use and downstream fluvial flood risk. On the one hand, this position is sustained by observations from plot- and field-scale studies that suggest land management does affect runoff. On the other, upscaling these effects to show that land-management activities impact upon flood risk at larger catchment scales has proved to be elusive. This review considers the reasons for why this upscaling is problematic. We argue that, rather than it reflecting methodological challenges associated with the difficulties of modelling hydrological processes over very large areas and during extreme runoff events, it reflects the fact that any linkage between land management and flood risk cannot be generalized and taken out of its specific spatial (catchment) and temporal (flood event) context. We use Sayer's (1992) notion of a `chaotic conception' to describe the belief that there is a simple and general association between land management and downstream flood risk rather than the impacts of land management being spatially and temporally contingent in relation to the particular geographical location, time period and scale being considered. Our argument has important practical consequences because it implies that land-management activities to reduce downstream flood risk will be different to traditional flood-reduction interventions such as levees. The purpose of demonstration projects then needs careful consideration such that conclusions made for one project are not transferred uncritically to other scales of analysis or geographical locations.

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It is known that post-movement beta synchronization (PMBS) is involved both in active inhibition and in sensory reafferences processes. The aim of this study was examine the temporal and spatial dynamics of the PMBS involved during multi-limb coordination task. We investigated post-switching beta synchronization (assigned PMBS) using time-frequency and source estimations analyzes. Participants (n = 17) initiated an auditory-paced bimanual tapping. After a 1500 ms preparatory period, an imperative stimulus required to either selectively stop the left while maintaining the right unimanual tapping (Switch condition: SWIT) or to continue the bimanual tapping (Continue condition: CONT). PMBS significantly increased in SWIT compared to CONT with maximal difference within right central region in broad-band 14âeuro"30 Hz and within left central region in restricted-band 22âeuro"26 Hz. Source estimations localized these effects within right pre-frontal cortex and left parietal cortex, respectively. A negative correlation showed that participants with a low percentage of errors in SWIT had a large PMBS amplitude within right parietal and frontal cortices. This study shows for the first time simultaneous PMBS with distinct functions in different brain regions and frequency ranges. The left parietal PMBS restricted to 22âeuro"26 Hz could reflect the sensory reafferences of the right hand tapping disrupted by the switching. In contrast, the right pre-frontal PMBS in a broad-band 14âeuro"30 Hz is likely reflecting the active inhibition of the left hand stopped. Finally, correlations between behavioral performance and the magnitude of the PMBS suggest that beta oscillations can be viewed as a marker of successful active inhibition.

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Considering teams as complex adaptive systems (CAS) this study deals with changes in team effectiveness over time in a specific context: professional basketball. The sample comprised 23 basketball teams whose outcomes were analysed over a 12-year period according to two objective measures. The results reveal that all the teams showed chaotic dynamics, one of the key characteristics of CAS. A relationship was also found between teams showing low-dimensional chaotic dynamics and better outcomes, supporting the idea of healthy variability in organizational behaviour. The stability of the squad was likewise found to influence team outcomes, although it was not associated with the chaotic dynamics in team effectiveness. It is concluded that studying teams as CAS enables fluctuations in team effectiveness to be explained, and that the techniques derived from nonlinear dynamical systems, developed specifically for the study of CAS, are useful for this purpose.

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Chaotic systems, when used to drive copies of themselves (or parts of themselves) may induce interesting behaviors in the driven system. In case the later exhibits invariance under amplification or translation, they may show amplification (reduction), or displacement of the attractor. It is shown how the behavior to be obtained is implied by the symmetries involved. Two explicit examples are studied to show how these phenomena manifest themselves under perfect and imperfect coupling.

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Control of a chaotic system by homogeneous nonlinear driving, when a conditional Lyapunov exponent is zero, may give rise to special and interesting synchronizationlike behaviors in which the response evolves in perfect correlation with the drive. Among them, there are the amplification of the drive attractor and the shift of it to a different region of phase space. In this paper, these synchronizationlike behaviors are discussed, and demonstrated by computer simulation of the Lorentz model [E. N. Lorenz, J. Atmos. Sci. 20 130 (1963)] and the double scroll [T. Matsumoto, L. O. Chua, and M. Komuro, IEEE Trans. CAS CAS-32, 798 (1985)].

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Monet henkilökohtaiset mobiililaitteet tarjoavat mahdollisuuden tallentaa henkilötietoja ja mahdollisuuden lyhyen kantaman radiotekniikoiden hyödyntämiseen. Vastaavasti henkilötietoja käyttävien tai vaativien verkkopalveluiden määrä on kasvussa. Mobiililaitteisiin tallennetut henkilötiedot tarjoavat potentiaalisen keinon välttää samojen henkilötietojen toistuva käsinsyöttö erilaisiin verkkopalveluihin ja keskitettyyn ajantasallapitoon. Tässä työssä käydään läpi ratkaisumalli henkilökohtaisen mobiililaitteen ja verkkopalveluiden välillä tapahtuvaan henkilötietojen siirtoon ja synkronointiin. Malli pohjautuu selainlaajennukseen, joka voi pyytää sekä selaimessa auki olevalta verkkopalvelun sivulta että mobiililta päätelaitteelta senhetkiset henkilötiedot ja synkronoida ne. Jo olemassaolevia henkilötietojen hallintaa helpottavia ratkaisuja käydään läpi arvioiden käyttökelpoisuutta tämänkaltaisiin tarpeisiin. Ratkaisumallin kannalta olennaiset tekniikat ja standardit, erityisesti Bluetooth ja SyncML, esitellään. Ratkaisumallin arkkitehtuuri käydään korkealla tasolla läpi ja esitellään toteutuksen yksityiskohtia. Tuloksena on periaatteeltaan kelvollinen henkilökohtaisten tietojen synkronointijärjestelmä, jonka toteutusta nykyisten mobiilien päätelaitteiden toiminnallisuus jossain määrin hankaloittaa.

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Self-sustained time-dependent current oscillations under dc voltage bias have been observed in recent experiments on n-doped semiconductor superlattices with sequential resonant tunneling. The current oscillations are caused by the motion and recycling of the domain wall separating low- and high-electric-field regions of the superlattice, as the analysis of a discrete drift model shows and experimental evidence supports. Numerical simulation shows that different nonlinear dynamical regimes of the domain wall appear when an external microwave signal is superimposed on the dc bias and its driving frequency and driving amplitude vary. On the frequency-amplitude parameter plane, there are regions of entrainment and quasiperiodicity forming Arnold tongues. Chaos is demonstrated to appear at the boundaries of the tongues and in the regions where they overlap. Coexistence of up to four electric-field domains randomly nucleated in space is detected under ac+dc driving.

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The multifractal dimension of chaotic attractors has been studied in a weakly coupled superlattice driven by an incommensurate sinusoidal voltage as a function of the driving voltage amplitude. The derived multifractal dimension for the observed bifurcation sequence shows different characteristics for chaotic, quasiperiodic, and frequency-locked attractors. In the chaotic regime, strange attractors are observed. Even in the quasiperiodic regime, attractors with a certain degree of strangeness may exist. From the observed multifractal dimensions, the deterministic nature of the chaotic oscillations is clearly identified.

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Parameter estimation still remains a challenge in many important applications. There is a need to develop methods that utilize achievements in modern computational systems with growing capabilities. Owing to this fact different kinds of Evolutionary Algorithms are becoming an especially perspective field of research. The main aim of this thesis is to explore theoretical aspects of a specific type of Evolutionary Algorithms class, the Differential Evolution (DE) method, and implement this algorithm as codes capable to solve a large range of problems. Matlab, a numerical computing environment provided by MathWorks inc., has been utilized for this purpose. Our implementation empirically demonstrates the benefits of a stochastic optimizers with respect to deterministic optimizers in case of stochastic and chaotic problems. Furthermore, the advanced features of Differential Evolution are discussed as well as taken into account in the Matlab realization. Test "toycase" examples are presented in order to show advantages and disadvantages caused by additional aspects involved in extensions of the basic algorithm. Another aim of this paper is to apply the DE approach to the parameter estimation problem of the system exhibiting chaotic behavior, where the well-known Lorenz system with specific set of parameter values is taken as an example. Finally, the DE approach for estimation of chaotic dynamics is compared to the Ensemble prediction and parameter estimation system (EPPES) approach which was recently proposed as a possible solution for similar problems.

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Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

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State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.