Free inertial processes driven by Gaussian noise: Probability distributions, anomalous diffusion and fractal behavior

We study the motion of an unbound particle under the influence of a random force modeled as Gaussian colored noise with an arbitrary correlation function. We derive exact equations for the joint and marginal probability density functions and find the associated solutions. We analyze in detail anomalous diffusion behaviors along with the fractal structure of the trajectories of the particle and explore possible connections between dynamical exponents of the variance and the fractal dimension of the trajectories.

Long-range correlations in diffusive systems away from equilibrium

We study the dynamics of density fluctuations in purely diffusive systems away from equilibrium. Under some conditions the static density correlation function becomes long ranged. We then analyze this behavior in the framework of nonequilibrium fluctuating hydrodynamics.

Structural disorder in two-dimensional random magnets: Very thin films of rare earths and transition metals

The low-temperature isothermal magnetization curves, M(H), of SmCo4 and Fe3Tb thin films are studied according to the two-dimensional correlated spin-glass model of Chudnovsky. We have calculated the magnetization law in approach to saturation and shown that the M(H) data fit well the theory at high and low fields. In our fit procedure we have used three different correlation functions. The Gaussian decay correlation function fits well the experimental data for both samples.

Nonequilibrium patterns and shape fluctuations in reactive membranes

A simple kinetic model of a two-component deformable and reactive bilayer is presented. The two differently shaped components are interconverted by a nonequilibrium reaction, and a phenomenological coupling between local composition and curvature is proposed. When the two components are not miscible, linear stability analysis predicts, and numerical simulations show, the formation of stationary nonequilibrium composition/curvature patterns whose typical size is determined by the reactive process. For miscible components, a linearization of the dynamic equations is performed in order to evaluate the correlation function for shape fluctuations from which the behavior of these systems in micropipet aspiration experiments can be predicted.

Comparison of the power spectral changes of the voluntary surface electromyogram and M wave during intermittent maximal voluntary contractions.

INTRODUCTION: To compare the power spectral changes of the voluntary surface electromyogram (sEMG) and of the compound action potential (M wave) in the vastus medialis and vastus lateralis muscles during fatiguing contractions. METHODS: Interference sEMG and force were recorded during 48 intermittent 3-s isometric maximal voluntary contractions (MVC) from 13 young, healthy subjects. M waves and twitches were evoked using supramaximal femoral nerve stimulation between the successive MVCs. Mean frequency (F mean), and median frequency were calculated from the sEMG and M waves. Muscle fiber conduction velocity (MFCV) was computed by cross-correlation. RESULTS: The power spectral shift to lower frequencies was significantly greater for the voluntary sEMG than for the M waves (P < 0.05). Over the fatiguing protocol, the overall average decrease in MFCV (~25 %) was comparable to that of sEMG F mean (~22 %), but significantly greater than that of M-wave F mean (~9 %) (P < 0.001). The mean decline in MFCV was highly correlated with the mean decreases in both sEMG and M-wave F mean. CONCLUSIONS: The present findings indicated that, as fatigue progressed, central mechanisms could enhance the relative weight of the low-frequency components of the voluntary sEMG power spectrum, and/or the end-of-fiber (non-propagating) components could reduce the sensitivity of the M-wave spectrum to changes in conduction velocity.

Aggregation under a forced convective flow

Morphological transitions are analyzed for a radial multiparticle diffusion-limited aggregation process grown under a convective drift. The introduction of a tangential flow changes the morphology of the diffusion-limited structure, into multiarm structures, inclined opposite to the flow, whose limit consists of single arms, when decreasing density. The case of shear flow is also considered. The anisotropy of the patterns is characterized in terms of a tangential correlation function based analysis. Comparison between the simulation results and preliminary experimental results has been done.

EEG-based functional networks in schizophrenia.

Schizophrenia is often considered as a dysconnection syndrome in which, abnormal interactions between large-scale functional brain networks result in cognitive and perceptual deficits. In this article we apply the graph theoretic measures to brain functional networks based on the resting EEGs of fourteen schizophrenic patients in comparison with those of fourteen matched control subjects. The networks were extracted from common-average-referenced EEG time-series through partial and unpartial cross-correlation methods. Unpartial correlation detects functional connectivity based on direct and/or indirect links, while partial correlation allows one to ignore indirect links. We quantified the network properties with the graph metrics, including mall-worldness, vulnerability, modularity, assortativity, and synchronizability. The schizophrenic patients showed method-specific and frequency-specific changes especially pronounced for modularity, assortativity, and synchronizability measures. However, the differences between schizophrenia patients and normal controls in terms of graph theory metrics were stronger for the unpartial correlation method.

Algebraic decay of velocity fluctuations near a wall

Computer simulations of the dynamics of a colloidal particle suspended in a fluid confined by an interface show that the asymptotic decay of the velocity correlation functions is algebraic. The exponents of the long-time tails depend on the direction of motion of the particle relative to the surface, as well as on the specific nature of the boundary conditions. In particular, we find that for the angular velocity correlation function, the decay in the presence of a slip surface is faster than the one corresponding to a stick one. An intuitive picture is introduced to explain the various long-time tails, and the simulations are compared with theoretical expressions where available.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Amplitude envelope synchronization in coupled chaotic oscillators.

A peculiar type of synchronization has been found when two Van der PolDuffing oscillators, evolving in different chaotic attractors, are coupled. As the coupling increases, the frequencies of the two oscillators remain different, while a synchronized modulation of the amplitudes of a signal of each system develops, and a null Lyapunov exponent of the uncoupled systems becomes negative and gradually larger in absolute value. This phenomenon is characterized by an appropriate correlation function between the returns of the signals, and interpreted in terms of the mutual excitation of new frequencies in the oscillators power spectra. This form of synchronization also occurs in other systems, but it shows up mixed with or screened by other forms of synchronization, as illustrated in this paper by means of the examples of the dynamic behavior observed for three other different models of chaotic oscillators.

A two-dimensional doppler-radiometer for earth observation

Compared to synthetic aperture radars (SARs), the angular resolution of microwave radiometers is quite poor. Traditionally, it has been limited by the physical size of the antenna. However, the angular resolution can be improved by means of aperture synthesis interferometric techniques. A narrow beam is synthesized during the image formation processing of the cross-correlations measured at zero-lag between pairs of signals collected by an array of antennas. The angular resolution is then determined by the maximum antenna spacing normalized to the wavelength (baseline). The next step in improving the angular resolution is the Doppler-Radiometer, somehow related to the super-synthesis radiometers and the Radiometer-SAR. This paper presents the concept of a three-antenna Doppler-Radiometer for 2D imaging. The performance of this instrument is evaluated in terms of angular/spatial resolution and radiometric sensitivity, and an L-band illustrative example is presented.

Capacity of MIMO Channels: asymptotic evaluation under correlated fading

This paper investigates the asymptotic uniform power allocation capacity of frequency nonselective multiple-inputmultiple-output channels with fading correlation at either thetransmitter or the receiver. We consider the asymptotic situation,where the number of inputs and outputs increase without boundat the same rate. A simple uniparametric model for the fadingcorrelation function is proposed and the asymptotic capacity perantenna is derived in closed form. Although the proposed correlationmodel is introduced only for mathematical convenience, itis shown that its shape is very close to an exponentially decayingcorrelation function. The asymptotic expression obtained providesa simple and yet useful way of relating the actual fadingcorrelation to the asymptotic capacity per antenna from a purelyanalytical point of view. For example, the asymptotic expressionsindicate that fading correlation is more harmful when arising atthe side with less antennas. Moreover, fading correlation does notinfluence the rate of growth of the asymptotic capacity per receiveantenna with high Eb /N0.

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.

Magnetoestratigrafía de las sucesiones del Mioceno medio y superior del Vallés occidental (Depresión del Vallés-Penedés, NE España): Implicaciones biocronológicas y cronoestratigráficas.

The magnetostratigraphic analysis of the middle to late Miocene continental deposits from the Valles-Penedes basin, combined with its well-documented fossil mammal record, provides a well-resoluted chronology for the upper basin infill. It is based on the biostratigraphic and magnetostratigraphic cross-correlation of 18 sections throughout the alluvial and transitional/shallow marine sequences in the Western Valles area. The biostratigraphic framework consists of 24 mammal localities of upper Aragonian and Vallesian age. Correlation of the studied sections to the geomagnetic polarity time scale (GPTS) is based on the distinctive pattern of local magnetozones, as well as the radiometric age of the late Vallesian fauna from the Bicorp Basin (9.6 + 0.3 Ma) and the known relationship of the late Vallesian assemblages with marine beds belonging to the planktonic forarninifera N16 zone. It has led to an absolute dating of the fauna1 events and a precise chronostratigraphy of the Vallesian marnrnal stage in its type area. The Hipparion First Appearance Datum (FAD) defines the lower Vallesian boundary and is dated at 11.1 Ma, at the base of chron C5r. ln. It is in good agreement with radiometric ages from the early Hipparion bearing sites in the Vienna Basin (1 1.1 * 0.5 Ma) and the classic Howenegg locality in Germany (10.8 * 0.3 Ma). It also agrees with the age of the turkish localities of Yailacilar (1 1.6 + 0.25 Ma) and Yenieskihisar-2 (1 1.1 * 0.2 Ma) with absence of Hipparion. Al1 these support the isochrony of the dispersa1 of Hipparion throughout the Mediterranean region. A possible isochrony at a larger geographical scale (Old World, Mesogea) must await more reliable ages of the Hipparion FAD in Asia and Africa. The Cricetulodon FAD that defines the MN9a/MN9b boundary occurs at the middle part of C5n. Assuming an on average constant sedimentation rate, this datum has an age of approximately 10.4 Ma. The earlyllate Vallesian boundary is marked by one of the most distinct fauna1 events of the late Neogene: the dispersa1 of the muridae Progonomys into Europe and North Africa, which coincides with an important macromarnmal turnover. The first extensive appearance of Progonomys in Europe (MN9íMN10 boundary) is dated at 9.7 Ma (C4Ar3r), showing a remarkable diachrony with the Himalayan region. F9i d lly, the FAD of Rotundomys bressnnus occurs in the upper part of C4Ar.ln (9.2-9.3 Ma). The Vallesian spans 2.4 Myr, from 11.1 Ma (CSr.ln) to 8.7 Ma (C4An), and correlates to the early Tortonian.

Spatial pattern of landslides in Swiss Rhone valley

The present study analyses the spatial pattern of quaternary gravitational slope deformations (GSD) and historical/present-day instabilities (HPI) inventoried in the Swiss Rhone Valley. The main objective is to test if these events are clustered (spatial attraction) or randomly distributed (spatial independency). Moreover, analogies with the cluster behaviour of earthquakes inventoried in the same area were examined. The Ripley's K-function was applied to measure and test for randomness. This indicator allows describing the spatial pattern of a point process at increasing distance values. To account for the non-constant intensity of the geological phenomena, a modification of the K-function for inhomogeneous point processes was adopted. The specific goal is to explore the spatial attraction (i.e. cluster behaviour) among landslide events and between gravitational slope deformations and earthquakes. To discover if the two classes of instabilities (GSD and HPI) are spatially independently distributed, the cross K-function was computed. The results show that all the geological events under study are spatially clustered at a well-defined distance range. GSD and HPI show a similar pattern distribution with clusters in the range 0.75?9 km. The cross K-function reveals an attraction between the two classes of instabilities in the range 0?4 km confirming that HPI are more prone to occur within large-scale slope deformations. The K-function computed for GSD and earthquakes indicates that both present a cluster tendency in the range 0?10 km, suggesting that earthquakes could represent a potential predisposing factor which could influence the GSD distribution.