Third-order nonlinear optical properties of silver nanoparticles mediated by chitosan

Silver nanoparticles in chitosan medium were prepared by the chemical reduction method. Silver nitrate and hydrazine were used as the precursor and reducing agent in the present of chitosan as a natural host polymer. The samples are characterized by UV–visible spectroscopy, X-ray diffraction (XRD) and transmission electron microscopy (TEM). The measurements of nonlinear optical properties were defined by Z-scan technique using green CW laser beam operated at 532 nm wavelengths. Thermal effect has a dominant role in the overall material nonlinearity with CW laser. It is shown that the synthesized samples have a negative nonlinear refractive index.     

Optical solitons in birefringent fibers with spatio-temporal dispersion

This paper studies the propagation of solitons through birefringent fibers in the presence of spatio-temporal dispersion. Both Kerr and parabolic laws of nonlinearity are addressed. The exact 1-soliton solutions are obtained. There are several constraint conditions that ensure soliton solutions are derived. Three types of solitons are obtained: bright, dark and singular solitons.     

Order and pole locator estimation in fractional order systems using bode diagram

This paper deals with estimation of fractional order and pole locator in fractional order systems. The estimation is based on Bode diagram of the system that is obtained using input and output measurements. Here the magnitude diagram is approximated with number of straight lines depending on the level of complexity and in consequence a very good estimation of fractional order and acceptable approximations of pole locators are determined. Relying on the proposed method, complexity of fractional order system identification which is mostly due to the estimation of fractional order is substantially resolved. Some example simulation results are provided to explain the work and show its effectiveness.     

A decision theoretic approach for channel ranking in crowded unlicensed bands

Interference is disruptive to the operation of wireless sensor networks (WSNs) in unlicensed bands as wireless systems proliferate on the spectrum. The design of a spectrum sharing scheme for WSNs to enable coexistence with geographically collocated heterogeneous wireless systems having multiple parallel interfering channels is a persistent challenge. In this context, interference identification and channel ranking in terms of spectrum access opportunities are addressed in this paper. The goal is to develop a low complexity channel ranking algorithm from channel energy measurements at sensors when a packet-reception-ratio to signal-to-interference-and-noise-ratio (PRR-SINR) interference model is unavailable at network initialization phase. The interference characterizing estimators, temporal occupancy and strength level of a channel, are proposed for interference identification. The effectiveness of the estimators is tested on a sensor platform at 2.4 GHz ISM band under interference from WLAN. Subsequently, the impact of the interference estimators on a channel quality from a receiver perspective is determined with a decision theoretic approach. The estimators are weighted according to their influence on the fitness of a channel and channel ranking is established. The proposed channel ranking achieves a significant gain over heuristic channel ranking (HCR) and gives an accurate interference profile of the channels.     

Combined higher order finite volume and finite element scheme for double porosity and non-linear adsorption of transport problem in porous media

In this work, a dual porosity model of reactive solute transport in porous media is presented. This model consists of a nonlinear-degenerate advection-diffusion equation including equilibrium adsorption to the reaction combined with a first-order equation for the non-equilibrium adsorption interaction processes. The numerical scheme for solving this model involves a combined high order finite volume and finite element scheme for approximation of the advection-diffusion part and relaxation-regularized algorithm for nonlinearity-degeneracy. The combined finite volume-finite element scheme is based on a new formulation developed by Eymard et al. (2010) [10]. This formulation treats the advection and diffusion separately. The advection is approximated by a second-order local maximum principle preserving cell-vertex finite volume scheme that has been recently proposed whereas the diffusion is approximated by a finite element method. The result is a conservative, accurate and very flexible algorithm which allows the use of different mesh types such as unstructured meshes and is able to solve difficult problems. Robustness and accuracy of the method have been evaluated, particularly error analysis and the rate of convergence, by comparing the analytical and numerical solutions for first and second order upwind approaches. We also illustrate the performance of the discretization scheme through a variety of practical numerical examples. The discrete maximum principle has been proved.     

Numerical solution of nth‐order integro‐differential equations using trigonometric wavelets

The main aim of this paper is to apply the trigonometric wavelets for the solution of the Fredholm integro‐differential equations of nth‐order. The operational matrices of derivative for trigonometric scaling functions and wavelets are presented and are utilized to reduce the solution of the Fredholm integro‐differential equations to the solution of algebraic equations. Furthermore, we get an estimation of error bound for this method. Copyright © 2011 John Wiley & Sons, Ltd.     

Simulation and evaluation of dual fully fuzzy linear systems by fuzzy neural network

In this paper, a novel hybrid method based on fuzzy neural network for approximate solution of fuzzy linear systems of the form Ax = Bx + d, where A and B are two square matrices of fuzzy coefficients, x and d are two fuzzy number vectors, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate solution, a simple and fast algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples.     

Antioxidant, total phenolic content and cytotoxicity evaluation of selected Malaysian plants

Aqueous and ethanol extracts of different traditional Malaysian plants (Polygonum minus, Andrographis paniculata, Curcuma xanthorrhiza, Momordica charantia and Strobilanthes crispus) were evaluated for their antioxidant properties, total phenolic content and cytotoxic activity. Antioxidant activity was evaluated by using 1,1-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays. The results showed that ethanol extracts contain high antioxidant activities compared to aqueous extracts. The findings exhibited a strong correlation between antioxidant activity and the total phenol contents. In addition, all the plant extracts showed non-toxic effects against a normal human lung fibroblast cell line (Hs888Lu). Although traditionally aqueous extracts are used, we determined that ethanol extracts usually achieved better activity in the assays.     

Characterization of deep acceptor level in as-grown ZnO thin film by molecular beam epitaxy

We report deep level transient spectroscopy results from ZnO layers grown on silicon by molecular beam epitaxy(MBE). The hot probe measurements reveal mixed conductivity in the as-grown ZnO layers, and the current–voltage(I–V)measurements demonstrate a good quality p-type Schottky device. A new deep acceptor level is observed in the ZnO layer having activation energy of 0.49±0.03 eV and capture cross-section of 8.57×10-18cm2. Based on the results from Raman spectroscopy, photoluminescence, and secondary ion mass spectroscopy(SIMS) of the ZnO layer, the observed acceptor trap level is tentatively attributed to a nitrogen–zinc vacancy complex in ZnO.