Control synchronization and parameter identification of two different chaotic systems

In this paper, control synchronization between two chaotic systems governed by different formulas is studied. Based on the techniques of adaptive control and parameters modulation, the response system is controlled to coincide with the drive system without the prior knowledge of parameters. When synchronization is achieved, the unknown parameters of the drive system are well approximated simultaneously. The effect of control parameters on the degree of synchronization is also discussed.     

A new naphthimidazole derivative for saccharide labeling with enhanced sensitivity in mass spectrometry detection

A series of saccharides, including maltoheptose, blood type B antigen, pullulan and the glucan of Ganoderma lucidum, are easily converted into the naphthimidazole (NAIM) derivatives in high yields by the iodine‐promoted oxidative condensation. The NAIM‐labeled saccharides, without further purification, show enhanced signals in matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOFMS). The combined use of NAIM derivatization and MALDI‐TOFMS analysis thus provides a rapid method for identification of saccharides even in less than 1 pmol of saccharide in the sample. Characterization of the biologically active saccharides and complex polysaccharides is also achieved through the NAIM‐derivatization method. This study can be further applied to facilitate the isolation and analysis of novel saccharides. Copyright © 2009 John Wiley & Sons, Ltd.     

Viscous dissipation effects of power-law fluid flow within parallel plates with constant heat fluxes

Both hydro-dynamically and thermally fully developed laminar heat transfer of non-Newtonian fluids between fixed parallel plates has been analyzed taking into account the effect of viscous dissipation of the flowing fluid. Thermal boundary condition considered is that both the plates kept at different constant heat fluxes. The energy equation, and in turn the Nusselt number, were solved analytically in terms of Brinkman number and power-law index. The findings show that the heat transfer depends on the power-law index of the flowing fluid. Pseudo-plastic and dilatant fluids manifest themselves differently in the heat transfer characteristics under the influence of viscous dissipation. Under certain conditions, the viscous dissipation effects on heat transfer between parallel plates are significant and should not be neglected.     

Modeling volatility and dependency of agricultural price and production indices of Thailand: Static versus time-varying copulas

Volatility and dependence structure are two main sources of uncertainty in many economic issues, such as exchange rates, future prices and agricultural product prices etc. who fully embody uncertainty among relationship and variation. This paper aims at estimating the dependency between the percentage changes of the agricultural price and agricultural production indices of Thailand and also their conditional volatilities using copula-based GARCH models. The motivation of this paper is twofold. First, the strategic department of agriculture of Thailand would like to have reliable empirical models for the dependency and volatilities for use in policy strategy. Second, this paper provides less restrictive models for dependency and the conditional volatility GARCH. The copula-based multivariate analysis used in this paper nested the traditional multivariate as a special case (Tae-Hwy and Xiangdong, 2009) [13]. Appropriate marginal distributions for both, the percentage changes of the agricultural price and agricultural production indices were selected for their estimation. Static as well as time varying copulas were estimated. The empirical results were found that the suitable margins were skew t distribution and the time varying copula i.e., the time varying rotate Joe copula (270°) was the choice for the policy makers to follow. The one-period ahead forecasted-growth rate of agricultural price index conditional on growth rate of agricultural production index was also provided as an example of forecasting it using the resulted margins and time-varying copula based GARCH model.