Mean Motion in Stochastic Plasmas With a Space-Dependent Diffusion Coefficient

Radial transport in the tokamap, which has been proposed as a simple model for the motion in a stochastic plasma, is investigated. A theory for previous numerical findings is presented. The new results are stimulated by the fact that the radial diffusion coefficients is space-dependent. The space-dependence of the transport coefficient has several interesting effects which have not been elucidated so far. Among the new findings are the analytical predictions for the scaling of the mean radial displacement with time and the relation between the Fokker-Planck diffusion coefficient and the diffusion coefficient from the mean square displacement. The applicability to other systems is also discussed. (c) 2009 WILEY-VCH GmbH & Co. KGaA, Weinheim

STABILITY ANALYSIS WITH APPLICATIONS OF A TWO-DIMENSIONAL DYNAMICAL SYSTEM ARISING FROM A STOCHASTIC MODEL FOR AN ASSET MARKET

We analyze the stability properties of equilibrium solutions and periodicity of orbits in a two-dimensional dynamical system whose orbits mimic the evolution of the price of an asset and the excess demand for that asset. The construction of the system is grounded upon a heterogeneous interacting agent model for a single risky asset market. An advantage of this construction procedure is that the resulting dynamical system becomes a macroscopic market model which mirrors the market quantities and qualities that would typically be taken into account solely at the microscopic level of modeling. The system`s parameters correspond to: (a) the proportion of speculators in a market; (b) the traders` speculative trend; (c) the degree of heterogeneity of idiosyncratic evaluations of the market agents with respect to the asset`s fundamental value; and (d) the strength of the feedback of the population excess demand on the asset price update increment. This correspondence allows us to employ our results in order to infer plausible causes for the emergence of price and demand fluctuations in a real asset market. The employment of dynamical systems for studying evolution of stochastic models of socio-economic phenomena is quite usual in the area of heterogeneous interacting agent models. However, in the vast majority of the cases present in the literature, these dynamical systems are one-dimensional. Our work is among the few in the area that construct and study analytically a two-dimensional dynamical system and apply it for explanation of socio-economic phenomena.

Symmetry in biology: from genetic code to stochastic gene regulation

Mathematical models, as instruments for understanding the workings of nature, are a traditional tool of physics, but they also play an ever increasing role in biology - in the description of fundamental processes as well as that of complex systems. In this review, the authors discuss two examples of the application of group theoretical methods, which constitute the mathematical discipline for a quantitative description of the idea of symmetry, to genetics. The first one appears, in the form of a pseudo-orthogonal (Lorentz like) symmetry, in the stochastic modelling of what may be regarded as the simplest possible example of a genetic network and, hopefully, a building block for more complicated ones: a single self-interacting or externally regulated gene with only two possible states: ` on` and ` off`. The second is the algebraic approach to the evolution of the genetic code, according to which the current code results from a dynamical symmetry breaking process, starting out from an initial state of complete symmetry and ending in the presently observed final state of low symmetry. In both cases, symmetry plays a decisive role: in the first, it is a characteristic feature of the dynamics of the gene switch and its decay to equilibrium, whereas in the second, it provides the guidelines for the evolution of the coding rules.

Effect of adding CaO to ZrO(2) support on nickel catalyst activity in dry reforming of methane

Nickel catalysts with a load of 5 wt% Ni, supported on pure ZrO(2) and ZrO(2) stabilized with 4, 8 and 14 mol% CaO, were prepared by the polymerization method. The samples were characterized by X-ray diffraction (XRD), temperature-programmed reduction with hydrogen (TPR-H(2)), specific surface area (BET) and impedance spectroscopy (IS) and tested in the carbon dioxide reforming of methane. The XRD patterns showed the presence of the oxide precursor (NiO) and the tetragonal phase of CaO-ZrO(2) solid solutions. According to the TPR-H(2) analysis, the reduction of various NiO species was influenced by the support composition. The electrical properties of the support have a proportional effect on the catalytic activities. Catalytic tests were done at 800 degrees C for 6 h and the composition of the gaseous products and the catalytic conversion depended on the CaO-ZrO(2) solid solution composition and its influence on supported NiO species. A direct relation was found between the variation in the electrical conductivity of the support, the nickel species supported on it and the performance in the catalytic tests. (C) 2009 Elsevier B.V. All rights reserved.

Effects of adding La and Ce to hydrotalcite-type Ni/Mg/Al catalyst precursors on ethanol steam reforming reactions

Catalyst precursors composed of Ni/Mg/Al oxides with added La and Ce were tested in ethanol steam reforming (ESR) reactions. La and Ce were added by anion-exchange. The oxides were characterized by X-ray photoelectron spectroscopy (XPS) and X-ray absorption near-edge structure (XANES) analysis. The catalyst precursors consist of a mixture of oxides, with the nickel in the form of NiO strongly interacting with the support Mg/Al. The XPS analysis showed a lanthanum-support interaction, but no interaction of Ce species with the support. The reaction data obtained with the active catalysts showed that the addition of Ce and La resulted in better H(2) production at 550 degrees C. The CeNi catalyst provided the higher ethanol conversion, with lower acetaldehyde production, possibly clue to a favoring of water adsorption on the weakly interacting clusters of CeO(2) on the surface. (C) 2010 Elsevier B.V. All rights reserved.

Road and Traffic Signs Recognition using Vector Machines

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

Environmental Objectives, Cost Efficiency, and Multivariate Stochastic Control

This paper is concerned with the cost efficiency in achieving the Swedish national air quality objectives under uncertainty. To realize an ecologically sustainable society, the parliament has approved a set of interim and long-term pollution reduction targets. However, there are considerable quantification uncertainties on the effectiveness of the proposed pollution reduction measures. In this paper, we develop a multivariate stochastic control framework to deal with the cost efficiency problem with multiple pollutants. Based on the cost and technological data collected by several national authorities, we explore the implications of alternative probabilistic constraints. It is found that a composite probabilistic constraint induces considerably lower abatement cost than separable probabilistic restrictions. The trend is reinforced by the presence of positive correlations between reductions in the multiple pollutants.