334 research outputs found

    Modulated structures in electroconvection in nematic liquid crystals

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    Motivated by experiments in electroconvection in nematic liquid crystals with homeotropic alignment we study the coupled amplitude equations describing the formation of a stationary roll pattern in the presence of a weakly-damped mode that breaks isotropy. The equations can be generalized to describe the planarly aligned case if the orienting effect of the boundaries is small, which can be achieved by a destabilizing magnetic field. The slow mode represents the in-plane director at the center of the cell. The simplest uniform states are normal rolls which may undergo a pitchfork bifurcation to abnormal rolls with a misaligned in-plane director.We present a new class of defect-free solutions with spatial modulations perpendicular to the rolls. In a parameter range where the zig-zag instability is not relevant these solutions are stable attractors, as observed in experiments. We also present two-dimensionally modulated states with and without defects which result from the destabilization of the one-dimensionally modulated structures. Finally, for no (or very small) damping, and away from the rotationally symmetric case, we find static chevrons made up of a periodic arrangement of defect chains (or bands of defects) separating homogeneous regions of oblique rolls with very small amplitude. These states may provide a model for a class of poorly understood stationary structures observed in various highly-conducting materials ("prechevrons" or "broad domains").Comment: 13 pages, 13 figure

    Three-dimensional pattern formation, multiple homogeneous soft modes, and nonlinear dielectric electroconvection

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    Patterns forming spontaneously in extended, three-dimensional, dissipative systems are likely to excite several homogeneous soft modes (\approx hydrodynamic modes) of the underlying physical system, much more than quasi one- and two-dimensional patterns are. The reason is the lack of damping boundaries. This paper compares two analytic techniques to derive the patten dynamics from hydrodynamics, which are usually equivalent but lead to different results when applied to multiple homogeneous soft modes. Dielectric electroconvection in nematic liquid crystals is introduced as a model for three-dimensional pattern formation. The 3D pattern dynamics including soft modes are derived. For slabs of large but finite thickness the description is reduced further to a two-dimensional one. It is argued that the range of validity of 2D descriptions is limited to a very small region above threshold. The transition from 2D to 3D pattern dynamics is discussed. Experimentally testable predictions for the stable range of ideal patterns and the electric Nusselt numbers are made. For most results analytic approximations in terms of material parameters are given.Comment: 29 pages, 2 figure

    Understanding the local structure of Eu3+- and Y3+-stabilized zirconia: insights from luminescence and X-ray absorption spectroscopic investigations

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    This study combines bulk structural and spectroscopic investigations of Eu3+^{3+}- or Y3+^{3+}/Eu3+^{3+} co-doped tetragonal and cubic zirconia polymorphs to gain an indepth understanding of the solid solution formation process. Our bulk structural characterizations show that the dopant is homogenously distributed in the ZrO2_{2} host structure resulting in an increase of the bulk symmetry with increasing dopant substitution (from 8 to 26 mol%). The local site symmetry around the Eu3+^{3+} dopant, however, determined with luminescence spectroscopy (TRLFS), remains low in all samples. Results obtained with X-ray pair distribution function and X-ray absorption spectroscopy show that the average coordination environment in the stabilized zirconia structures remains practically unchanged. Despite this very constant average dopant environment, siteselective TRLFS data show the presence of three nonequivalent Eu3+^{3+} environments in the ZrO2_{2} solid structures. These Eu3+^{3+} environments are assumed to arise from Eu3+^{3+} incorporation at superficial sites, which increase in abundance as the size of the crystallites decrease, and incorporation on two bulk sites differing in the location of the oxygen vacancies with respect to the dopant cation

    1D-confinement of polyiodides inside single-wall carbon nanotubes

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    International audience1D-confinement of polyiodides inside single-wall carbon nanotubes (SWCNT) is investigated. Structural arrangement of iodine species as a function of the SWCNT diameters is studied. Evidence for long range one dimensional ordering of the iodine species is shown by X-ray and electron diffraction experiments independently of the tube diameter. The structure of the confined polyiodides is investigated by X-ray absorption spectroscopy. The confinement influences the local arrangement of the chains. Below a critical diameter Fc of 1 nm, long linear polyiodides are evidenced leading to a weaker charge transfer than for nanotube diameter above Fc. A shortening of the polyiodides is exhibited with the increase of the nanotube diameter leading to a more efficient charge transfer. This point reflects the 1D-confinement of the polyiodides inside the nanotubes

    Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

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    We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.Comment: 36 pages, 6 figures, 2 tables; to be published in "Physica A

    Data driven optimal filtering for phase and frequency of noisy oscillations: application to vortex flowmetering

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    A new method for extracting the phase of oscillations from noisy time series is proposed. To obtain the phase, the signal is filtered in such a way that the filter output has minimal relative variation in the amplitude (MIRVA) over all filters with complex-valued impulse response. The argument of the filter output yields the phase. Implementation of the algorithm and interpretation of the result are discussed. We argue that the phase obtained by the proposed method has a low susceptibility to measurement noise and a low rate of artificial phase slips. The method is applied for the detection and classification of mode locking in vortex flowmeters. A novel measure for the strength of mode locking is proposed.Comment: 12 pages, 10 figure

    A Grassmann integral equation

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    The present study introduces and investigates a new type of equation which is called Grassmann integral equation in analogy to integral equations studied in real analysis. A Grassmann integral equation is an equation which involves Grassmann integrations and which is to be obeyed by an unknown function over a (finite-dimensional) Grassmann algebra G_m. A particular type of Grassmann integral equations is explicitly studied for certain low-dimensional Grassmann algebras. The choice of the equation under investigation is motivated by the effective action formalism of (lattice) quantum field theory. In a very general setting, for the Grassmann algebras G_2n, n = 2,3,4, the finite-dimensional analogues of the generating functionals of the Green functions are worked out explicitly by solving a coupled system of nonlinear matrix equations. Finally, by imposing the condition G[{\bar\Psi},{\Psi}] = G_0[{\lambda\bar\Psi}, {\lambda\Psi}] + const., 0<\lambda\in R (\bar\Psi_k, \Psi_k, k=1,...,n, are the generators of the Grassmann algebra G_2n), between the finite-dimensional analogues G_0 and G of the (``classical'') action and effective action functionals, respectively, a special Grassmann integral equation is being established and solved which also is equivalent to a coupled system of nonlinear matrix equations. If \lambda \not= 1, solutions to this Grassmann integral equation exist for n=2 (and consequently, also for any even value of n, specifically, for n=4) but not for n=3. If \lambda=1, the considered Grassmann integral equation has always a solution which corresponds to a Gaussian integral, but remarkably in the case n=4 a further solution is found which corresponds to a non-Gaussian integral. The investigation sheds light on the structures to be met for Grassmann algebras G_2n with arbitrarily chosen n.Comment: 58 pages LaTeX (v2: mainly, minor updates and corrections to the reference section; v3: references [4], [17]-[21], [39], [46], [49]-[54], [61], [64], [139] added

    A general framework for combining ecosystem models

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    When making predictions about ecosystems, we often have available a number of different ecosystem models that attempt to represent their dynamics in a detailed mechanistic way. Each of these can be used as a simulator of large-scale experiments and make projections about the fate of ecosystems under different scenarios to support the development of appropriate management strategies. However, structural differences, systematic discrepancies and uncertainties lead to different models giving different predictions. This is further complicated by the fact that the models may not be run with the same functional groups, spatial structure or time scale. Rather than simply trying to select a “best” model, or taking some weighted average, it is important to exploit the strengths of each of the models, while learning from the differences between them. To achieve this, we construct a flexible statistical model of the relationships between a collection of mechanistic models and their biases, allowing for structural and parameter uncertainty and for different ways of representing reality. Using this statistical meta-model, we can combine prior beliefs, model estimates and direct observations using Bayesian methods and make coherent predictions of future outcomes under different scenarios with robust measures of uncertainty. In this study, we take a diverse ensemble of existing North Sea ecosystem models and demonstrate the utility of our framework by applying it to answer the question what would have happened to demersal fish if fishing was to stop

    Steeper size spectra with decreasing phytoplankton biomass indicate strong trophic amplification and future fish declines

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    Under climate change, model ensembles suggest that declines in phyto�plankton biomass amplify into greater reductions at higher trophic levels, with serious implications for fisheries and carbon storage. However, the extent and mechanisms of this trophic amplification vary greatly among models, and validation is problematic. In situ size spectra offer a novel alternative, com�paring biomass of small and larger organisms to quantify the net efficiency of energy transfer through natural food webs that are already challenged with multiple climate change stressors. Our global compilation of pelagic size spectrum slopes supports trophic amplification empirically, independently from model simulations. Thus, even a modest (16%) decline in phytoplankton this century would magnify into a 38% decline in supportable biomass of fish within the intensively-fished mid-latitude ocean. We also show that this amplification stems not from thermal controls on consumers, but mainly from temperature or nutrient controls that structure the phytoplankton baseline of the food web. The lack of evidence for direct thermal effects on size structure contrasts with most current thinking, based often on more acute stress experiments or shorter-timescale responses. Our synthesis of size spectra integrates these short-term dynamics, revealing the net efficiency of food webs acclimating and adapting to climatic stressor

    Microbial transformations of selenite by methane-oxidizing bacteria

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    Abstract Methane oxidizing bacteria are well known for their role in the global methane cycle and their potential for microbial transformation of wide range of hydrocarbon and chlorinated hydrocarbon pollution. Recently, it has also emerged that methane-oxidizing bacteria interact with inorganic pollutants in the environment. Here we report what we believe to be the first study of the interaction of pure strains of methane-oxidizing bacteria with selenite. Results indicate that the commonly used laboratory model strains of methane oxidizing bacteria, Methylococcus capsulatus (Bath) and Methylosinus trichosporium OB3b are both able to reduce the toxic selenite (SeO32-) but not selenate (SeO42-) to red spherical nanoparticulate elemental selenium (Se0), which was characterised via EDX and EXAFS. The cultures also produced volatile selenium-containing species, which suggests that both strains may have an additional activity that can either transform Se0 or selenite into volatile methylated forms of selenium. Transmission electron microscopy (TEM) measurements and experiments with the cell fractions: cytoplasm, cell wall and cell membrane show that the nanoparticles are formed mainly on the cell wall. Collectively these results are promising for the use of methane-oxidizing bacteria for bioremediation or suggest possible uses in the production of selenium nanoparticles for biotechnology
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