Stability analysis of abnormal multiplication of plankton using parameter identification technique

This paper presents the mathematical approach for the abnormal multiplication of plankton. An abnormal multiplication can be expressed as an unstable problem and the stability of the system is investigated by introducing eigenvalues of a mathematical equation. The stability of the system can be judged by an eigenvalue based on the Lyapunov's stability theory. In this paper, the Arnoldi‐QR method is used to obtain eigenvalues and eigenvectors of the system. The mode superposition method is employed to create spatial distribution needed to analyse the stability. To obtain the objective eigenvalue, the parameter identification technique is employed. The finite element method is used for the discretization in space. Lake Kasumigaura, which is located in Ibaraki Prefecture in Japan, is selected and actual data in 1975, 1976, 1991 and 2000 are used in order to investigate the stability of the specified lake in Japan. Copyright © 2004 John Wiley & Sons, Ltd.     

Qualitative Theory and Identification of Dynamic System with One Degree of Freedom

Dynamic systems described by nonlinear differential equations of the second order are studied. It is assumed that certain preliminary information on the dissipative or elastic characteristics of systems is known. A new approach is demonstrated to obtaining full information on unknown or partially known characteristics of a system from measurements of not only displacements but also velocities and accelerations __________ Published in Prikladnaya Mekhanika, Vol. 41, No. 6, pp. 139–143, June 2005.     

Robust Adaptive Identification of Fuzzy Systems with Uncertain Data

This study presents a method of adaptive identification of parameters describing Sugeno fuzzy inference system in presence of bounded disturbances while maintaining the readability and interpretability of the fuzzy model during and after identification. This method do not require any a priori knowledge of a bound on the disturbance and noise and of a bound on the unknown parameters values. The method can be used for the robust and adaptive identification of slowly time varying nonlinear systems using fuzzy inference systems. The suggested method was used to build a fuzzy expert system that approximates the functional relationship between physical fitness and some of the measurable physiological parameters by their real measurements and opinion (human-experiences) of a medical expert.     

硅色敏器件对复色光色差辨识能力的数值分析

对复色光的光谱功率分布和色敏器件光谱响应的实验曲线进行了函数拟合，采用Mathematica 4．2计算了具有不同峰值波长和半高宽的高斯分布的复色光在色敏器件中产生的电流比．计算结果表明，待测复色光的峰值波长和半高宽变化对两种典型的色敏器件的输出信号影响的权重比分别为100：1和10：1。权重比说明色敏器件的输出电流比随峰值波长和半高宽的变化非常灵敏，但两者权重不同，其中峰值波长的变化影响更为显著，是影响复色光颜色变化的主要因素．数值分析的结果表明，硅双结色敏器件对复色光色差有良好的辨识能力．两种器件权重比的差异说明了器件制作工艺与其辨识能力的关系，为器件合理设计提供了理论依据．     

Applications of electronic speckle interferometry (ESI) techniques for spacecraft structural components

Laser-based electronic speckle interferometry (ESI) techniques, viz., electronic speckle pattern interferometry (ESPI) and electronic speckle shearographic interferometry (ESSI) are used for testing of spacecraft structural components. The combined ESPI and ESSI system developed in house was successfully used for the non-destructive evaluation (NDE) of honeycomb sandwich panels and propellant tanks of Indian Space Research Organization (ISRO). Debonds between face sheet and the honeycomb core were identified using (i) thermal and (ii) dual vacuum stressing methods. On-line NDE of the propellant tanks under internal pressure loading for identification of the minute cracks and thickness reduction areas were successfully implemented by ESI.     

Long-range predictive adaptive fuzzy relational control

A class of long-range predictive adaptive fuzzy relational controllers is presented. The plant behavior is described over an extended time horizon by a fuzzy relational model which is identified based on input-output closed-loop observations of the plant variables. In this class of adaptive controllers the control law attempts to minimize a quadratic cost over an extended control horizon. When used with linear models, this approach has revealed a significant potential for overcoming the limitations of one-step ahead schemes, such as the stabilization of non-minimum phase plants. Here, a uniform framework is adopted for implementing both the fuzzy model and the fuzzy controller, namely distributed fuzzy relational structures gaining from their massive parallel processing features and from the learning capabilities typical of the connectivist approaches. Issues such as maintenance during the adaptation process of the meaning of linguistic terms used at both fuzzy systems interfaces are addressed, namely by introducing a new design methodology for on-line fuzzy systems interface adaptation. The examples presented reinforce the claim of the usefulness of this new approach.     

The Method of Virtual Experts in Mathematical Diagnostics

Mathematical Diagnostics (MD) deals with identification problems arising in different practical areas. Some of these problems can be described by mathematical models where it is required to identify points belonging to two or more sets of points. Most of the existing tools provide some identification rule (a classifier) by means of which a given point is assigned (attributed) to one of the given sets. Each classifier can be viewed as a virtual expert. If there exist several classifiers (experts), the problem of evaluation of experts’ conclusions arises. In the paper for the case of supervised classification the method of virtual experts (the VE-method) is described. Based on this method, a generalized VE method is proposed where each of the classifiers can be chosen from a given family of classifiers. As a result, a new optimization problem with a discontinuous functional is stated. Examples illustrating the proposed approach are provided. The work of the second author was supported by the Russian Foundation for Fundamental Studies (RFFI) under Grant No 03-01-00668.     

The Purification and Rapid Identification of Heavy Metal-binding Peptides of Water Hyacinth

This paper studies the rapid identification of heavy metal-binding peptides (phytochelatin) by taking Water Hyacinth as a model plant. Plants were cultured in water containing 2 μg/ml Cd2+ for 13 days. The Sephadex G-50 chromatography of root extract under low salt concentration (0. 01 mol/L PBS) gave a Cd-binding peak with MW of 10 ,000 determined by SEC HPLC. After oxidation with performic acid, its SEC HPLC molecular weight decreased to below 1300 and the reverse phase HPLC showed one peptide peak, whose amino acid composition is the same as that of the sample never undertaking oxidation, and (Glu/Gln):Cys:Gly=2:2:1. According to the general structure of phytochelatin (γ-Glu-Cys)n-Gly, n is 2 in this case. The protocol including the sequential steps of Sephadex G-50 chromatography→performic acid oxidation→reverse phase HPLC→amino acid analysis is a rapid and effective method to identify the existence of phytochelatin and determine its values of n.     

Near-crater discoloration of white lead in wall paintings during laser induced breakdown spectroscopy analysis

During Laser-Induced Breakdown Spectroscopy (LIBS) analysis of white lead pigment (basic lead carbonate, 2PbCO₃·Pb(OH)₂), used in wall paintings of historical interest, a yellow–brown discoloration has been observed around the crater. This phenomenon faded after a few days exposure under ambient atmosphere. It was established that the mechanism of this discoloration consists in lead oxides (PbO) formation. It was verified by further experiments under argon atmosphere that recombination of lead with oxygen in the plasma plume produces the oxides, which settle around the crater and induce this discoloration. The impact of discoloration on the artwork's aesthetic aspect and the role of atmosphere on discoloration attenuation are discussed. The mechanism is studied on three other pigments (malachite, Prussian blue and ultramarine blue) and threshold for discoloration occurrence is estimated.     

Affinity enrichment of plasma membrane for proteomics analysis

Proteomics analysis of plasma membranes from cells exposed to different extracellular environments is potentially a powerful approach for the identification of membrane-associated proteins responding to these environments. Preparation of high concentration plasma membrane fractions with low contamination from cellular organelles is essential for such studies. Here, we describe an affinity enrichment method, which combines cell surface biotinylation with affinity enrichment by immobilized streptavidin beads, for the isolation of plasma membranes. This method results in a 400-fold enrichment of plasma membrane relative to endoplasmic reticulum, a major contaminant in standard plasma membrane preparations, and dramatically reduces contamination from other cellular organelles. The biotinylation reaction did not interfere with ligand-dependent activation of receptor tyrosine kinases or G-protein coupled receptors, suggesting cell-surface signal transduction machinery remains functional. Membrane fractions prepared by this method should provide excellent starting materials for membrane proteomics analysis such as studies of dynamic trafficking and regulation of signaling molecules or identification of disease-specific membrane markers.