Statistics of opinion domains of the majority-vote model on a square lattice

The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.

Regional scale analysis of landform configuration with base-level (isobase) maps

Base-level maps (or ""isobase maps"", as originally defined by Filosofov, 1960), express a relationship between valley order and topography. The base-level map can be seen as a ""simplified"" version of the original topographic surface, from which the ""noise"" of the low-order stream erosion was removed. This method is able to identify areas with possible tectonic influence even within lithologically uniform domains. Base-level maps have been recently applied in semi-detail scale (e.g., 1:50 000 or larger) morphotectonic analysis. In this paper, we present an evaluation of the method's applicability in regional-scale analysis (e.g., 1:250 000 or smaller). A test area was selected in northern Brazil, at the lower course of the Araguaia and Tocantins rivers. The drainage network extracted from SRTM30_PLUS DEMs with spatial resolution of approximately 900 m was visually compared with available topographic maps and considered to be compatible with a 1:1,000 000 scale. Regarding the interpretation of regional-scale morphostructures, the map constructed with 2nd and 3rd-order valleys was considered to present the best results. Some of the interpreted base-level anomalies correspond to important shear zones and geological contacts present in the 1:5 000 000 Geological Map of South America. Others have no correspondence with mapped Precambrian structures and are considered to represent younger, probably neotectonic, features. A strong E-W orientation of the base-level lines over the inflexion of the Araguaia and Tocantins rivers, suggest a major drainage capture. A N-S topographic swath profile over the Tocantins and Araguaia rivers reveals a topographic pattern which, allied with seismic data showing a roughly N-S direction of extension in the area, lead us to interpret this lineament as an E-W, southward-dipping normal fault. There is also a good visual correspondence between the base-level lineaments and geophysical anomalies. A NW-SE lineament in the southeast of the study area partially corresponds to the northern border of the Mosquito lava field, of Jurassic age, and a NW-SE lineament traced in the northeastern sector of the study area can be interpreted as the Picos-Santa Ines lineament, identifiable in geophysical maps but with little expression in hypsometric or topographic maps.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Random perturbations of stochastic processes with unbounded variable length memory

We consider binary infinite order stochastic chains perturbed by a random noise. This means that at each time step, the value assumed by the chain can be randomly and independently flipped with a small fixed probability. We show that the transition probabilities of the perturbed chain are uniformly close to the corresponding transition probabilities of the original chain. As a consequence, in the case of stochastic chains with unbounded but otherwise finite variable length memory, we show that it is possible to recover the context tree of the original chain, using a suitable version of the algorithm Context, provided that the noise is small enough.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

The impact of the subtropical South Atlantic SST on South American precipitation

The Community Climate Model (CCM3) from the National Center for Atmospheric Research (NCAR) is used to investigate the effect of the South Atlantic sea surface temperature (SST) anomalies on interannual to decadal variability of South American precipitation. Two ensembles composed of multidecadal simulations forced with monthly SST data from the Hadley Centre for the period 1949 to 2001 are analysed. A statistical treatment based on signal-to-noise ratio and Empirical Orthogonal Functions (EOF) is applied to the ensembles in order to reduce the internal variability among the integrations. The ensemble treatment shows a spatial and temporal dependence of reproducibility. High degree of reproducibility is found in the tropics while the extratropics is apparently less reproducible. Austral autumn (MAM) and spring (SON) precipitation appears to be more reproducible over the South America-South Atlantic region than the summer (DJF) and winter (JJA) rainfall. While the Inter-tropical Convergence Zone (ITCZ) region is dominated by external variance, the South Atlantic Convergence Zone (SACZ) over South America is predominantly determined by internal variance, which makes it a difficult phenomenon to predict. Alternatively, the SACZ over western South Atlantic appears to be more sensitive to the subtropical SST anomalies than over the continent. An attempt is made to separate the atmospheric response forced by the South Atlantic SST anomalies from that associated with the El Nino - Southern Oscillation (ENSO). Results show that both the South Atlantic and Pacific SSTs modulate the intensity and position of the SACZ during DJF. Particularly, the subtropical South Atlantic SSTs are more important than ENSO in determining the position of the SACZ over the southeast Brazilian coast during DJF. On the other hand, the ENSO signal seems to influence the intensity of the SACZ not only in DJF but especially its oceanic branch during MAM. Both local and remote influences, however, are confounded by the large internal variance in the region. During MAM and JJA, the South Atlantic SST anomalies affect the magnitude and the meridional displacement of the ITCZ. In JJA, the ENSO has relatively little influence on the interannual variability of the simulated rainfall. During SON, however, the ENSO seems to counteract the effect of the subtropical South Atlantic SST variations on convection over South America.

Complex Oscillatory Response of a PEM Fuel Cell Fed with H(2)/CO and Oxygen

Oscillatory kinetics is commonly observed in the electrocatalytic oxidation of most species that can be used in fuel cell devices. Examples include formic acid, methanol, ethanol, ethylene glycol, and hydrogen/carbon monoxide mixtures, and most papers refer to half-cell experiments. We report in this paper the experimental investigation of the oscillatory dynamics in a proton exchange membrane (PEM) fuel cell at 30 degrees C. The system consists of a Pt/C cathode fed with oxygen and a PtRu (1:1)/C anode fed with H(2) mixed with 100 ppm of CO, and was studied at different cell currents and anode flow rates. Many different states including periodic and nonperiodic series were observed as a function of the cell current and the H(2)/CO flow rate. In general, aperiodic/chaotic states were favored at high currents and low flow rates. The dynamics was further characterized in terms of the relationship between the oscillation amplitude and the subsequent time required for the anode to get poisoned by carbon monoxide. Results are discussed in terms of the mechanistic aspects of the carbon monoxide adsorption and oxidation. (C) 2010 The Electrochemical Society. [DOI: 10.1149/1.3463725] All rights reserved.

Low dimensional behavior in three-dimensional coupled map lattices

The analysis of one-, two-, and three-dimensional coupled map lattices is here developed under a statistical and dynamical perspective. We show that the three-dimensional CML exhibits low dimensional behavior with long range correlation and the power spectrum follows 1/f noise. This approach leads to an integrated understanding of the most important properties of these universal models of spatiotemporal chaos. We perform a complete time series analysis of the model and investigate the dependence of the signal properties by change of dimension. (c) 2008 Elsevier Ltd. All rights reserved.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

Complexity of human postural control in young and older adults during prolonged standing

Aging is known to have a degrading influence on many structures and functions of the human sensorimotor system. The present work assessed aging-related changes in postural sway using fractal and complexity measures of the center of pressure (COP) dynamics with the hypothesis that complexity and fractality decreases in the older individuals. Older subjects (68 +/- 4 years) and young adult subjects (28 +/- 7 years) performed a quiet stance task (60 s) and a prolonged standing task (30 min) where subjects were allowed to move freely. Long-range correlations (fractality) of the data were estimated by the detrended fluctuation analysis (DFA); changes in entropy were estimated by the multi-scale entropy (MSE) measure. The DFA results showed that the fractal dimension was lower for the older subjects in comparison to the young adults but the fractal dimensions of both groups were not different from a 1/f noise, for time intervals between 10 and 600 s. The MSE analysis performed with the typically applied adjustment to the criterion distance showed a higher degree of complexity in the older subjects, which is inconsistent with the hypothesis that complexity in the human physiological system decreases with aging. The same MSE analysis performed without adjustment showed no differences between the groups. Taken all results together, the decrease in total postural sway and long-range correlations in older individuals are signs of an adaptation process reflecting the diminishing ability to generate adequate responses on a longer time scale.

Electrodeposition of copper on titanium wires: Taguchi experimental design approach

Electrodeposition of thin copper layer was carried out on titanium wires in acidic sulphate bath. The influence of titanium surface preparation, cathodic current density, copper sulphate and sulphuric acid concentrations, electrical charge density and stirring of the solution on the adhesion of the electrodeposits was studied using the Taguchi statistical method. A L(16) orthogonal array with the six factors of control at two levels each and three interactions was employed. The analysis of variance of the mean adhesion response and signal-to-noise ratio showed the great influence of cathodic current density on adhesion. on the contrary, the other factors as well as the three investigated interactions revealed low or no significant effect. From this study optimized electrolysis conditions were defined. The copper electrocoating improved the electrical conductivity of the titanium wire. This shows that copper electrocoated titanium wires could be employed for both electrical purpose and mechanical reinforcement in superconducting magnets. (C) 2008 Elsevier B.V. All rights reserved.

Comparative analysis of triple band S-C-L erbium-doped fibre and semiconductor optical amplifier for CWDM applications

The authors present a comparative analysis between a triple-band S-C-L erbium-doped fibre amplifier and a commercial semiconductor optical amplifier in a CWDM application scenario. Both technologies were characterised for gain and noise figures from 1480 to 1610 nm (S, C and L bands) and their systemic performances were evaluated in terms of bit error rate measurements for a wide range of optical power levels.

NEX-LMS: A novel adaptive control scheme for harmonic sound quality control

This paper presents a novel adaptive control scheme. with improved convergence rate, for the equalization of harmonic disturbances such as engine noise. First, modifications for improving convergence speed of the standard filtered-X LMS control are described. Equalization capabilities are then implemented, allowing the independent tuning of harmonics. Eventually, by providing the desired order vs. engine speed profiles, the pursued sound quality attributes can be achieved. The proposed control scheme is first demonstrated with a simple secondary path model and, then, experimentally validated with the aid of a vehicle mockup which is excited with engine noise. The engine excitation is provided by a real-time sound quality equivalent engine simulator. Stationary and transient engine excitations are used to assess the control performance. The results reveal that the proposed controller is capable of large order-level reductions (up to 30 dB) for stationary excitation, which allows a comfortable margin for equalization. The same holds for slow run-ups ( > 15s) thanks to the improved convergence rate. This margin, however, gets narrower with shorter run-ups (<= 10s). (c) 2010 Elsevier Ltd. All rights reserved.

Positioning of Deadeners for Vibration Reduction in Vehicle Roof Using Embedded Sensitivity

The noise, vibration and harshness (NVH) performance of passenger vehicles strongly depends on the fluid-structure interaction between the air in the vehicle cavity and the sheet metal structure of the vehicle. Most of the noise and vibration problems related to this interaction come from resonance peaks of the sheet metal, which are excited by external forces (road, engine, and wind). A reduction in these resonance peaks can be achieved by applying bitumen damping layers, also called deadeners, in the sheet metal. The problem is where these deadeners shall be fixed, which is usually done in a trial-and-error basis. In this work, one proposes the use of embedded sensitivity to locate the deadeners in the sheet metal of the vehicle, more specifically in the vehicle roof. Experimental frequency response functions (FRFs) of the roof are obtained and the data are processed by adopting the embedded sensitivity method, thus obtaining the sensitivity of the resonance peaks on the local increase in damping due to the deadeners. As a result, by examining the sensitivity functions, one can find the optimum location of the deadeners that maximize their effect in reducing the resonance peaks of interest. After locating the deadeners in the optimum positions, it was possible to verify a strong reduction in resonance peaks of the vehicle roof, thus showing the efficiency of the procedure. The main advantage of this procedure is that it only requires FRF measurements of the vehicle in its original state not needing any previous modification of the vehicle structure to find the sensitivity functions. [DOI: 10.1115/1.4000769]

A state-space modeling approach for active structural acoustic control

The demands for improvement in sound quality and reduction of noise generated by vehicles are constantly increasing, as well as the penalties for space and weight of the control solutions. A promising approach to cope with this challenge is the use of active structural-acoustic control. Usually, the low frequency noise is transmitted into the vehicle`s cabin through structural paths, which raises the necessity of dealing with vibro-acoustic models. This kind of models should allow the inclusion of sensors and actuators models, if accurate performance indexes are to be accessed. The challenge thus resides in deriving reasonable sized models that integrate structural, acoustic, electrical components and the controller algorithm. The advantages of adequate active control simulation strategies relies on the cost and time reduction in the development phase. Therefore, the aim of this paper is to present a methodology for simulating vibro-acoustic systems including this coupled model in a closed loop control simulation framework that also takes into account the interaction between the system and the control sensors/actuators. It is shown that neglecting the sensor/actuator dynamics can lead to inaccurate performance predictions.