Development of an Amperometric Biosensor and Performance Studies with a Minimum Background Current

Abstract

An amperometric glucose biosensor with immobilized glucose oxidase enzyme is developed and its performance is investigated for the analysis of glucose concentration. A systematic method to find the background current in an amperometric biosensor is proposed, and the procedure for the minimization of the current has been reported. Tests were conducted for the analysis of glucose in different fruit juices. The current generated in an enzyme based amperometric biosensor depends on both the sensing current and the background current. The performance of amperometric biosensor is better when it is operated at optimized operating conditions and with minimum background current. The effect of current caused by the interference contained in the physiological fluids (uric acid and ascorbic acid) is found negligible. It has been found that the thickness of the membrane will affect the response time and the increase in background current will affect the sensitivity.     

KINETICS OF URANIUM EXTRACTION BY MACROPOROUS BIFUNCTIONAL PHOSPHINIC ACID RESIN

ABSTRACT

The rate of extraction of uranium by macroporous bifunctional phosphinic acid (MPBPA) resin from nitric acid medium has been studied under particle diffusion controlled conditions. The internal diffusion coefficient was found to increase with increase in temperature and decrease with increase in particle size. The activation energies and entropies suggest that the extraction of uranium essentially follows ion exchange mechanism at low concentration of nitric acid while it is through linkage of >P=0 group of the resin at high concentrations.     

Retinal vessel segmentation using enhanced fuzzy min-max neural network

Automated segmentation of retinal vessels plays a pivotal role in early diagnosis of ophthalmic disorders. In this paper, a blood vessel segmentation algorithm using an enhanced fuzzy min-max neural network supervised classifier is proposed. The input to the network is an optimal 11-D feature vector which consists of spatial as well as frequency domain features extracted from each pixel of a fundus image. The essence of the method is its hyperbox classifier which performs online learning and gives binary output without any need of post-processing. The method is tested on publicly available databases DRIVE and STARE. The results are compared with the existing methods in the literature. The proposed method exhibits efficient performance and can be implemented in computer aided screening and diagnosis of retinal diseases. The method attains an average accuracy, sensitivity and specificity of 95.73%, 74.75% and 97.81% on DRIVE database and 95.51%, 74.65% and 97.11% on STARE database, respectively.

     

Stability analysis of fuzzy parametric uncertain systems

In this paper, the determination of stability margin, gain and phase margin aspects of fuzzy parametric uncertain systems are dealt. The stability analysis of uncertain linear systems with coefficients described by fuzzy functions is studied. A complexity reduced technique for determining the stability margin for FPUS is proposed. The method suggested is dependent on the order of the characteristic polynomial. In order to find the stability margin of interval polynomials of order less than 5, it is not always necessary to determine and check all four Kharitonov’s polynomials. It has been shown that, for determining stability margin of FPUS of order five, four, and three we require only 3, 2, and 1 Kharitonov’s polynomials respectively. Only for sixth and higher order polynomials, a complete set of Kharitonov’s polynomials are needed to determine the stability margin. Thus for lower order systems, the calculations are reduced to a large extent. This idea has been extended to determine the stability margin of fuzzy interval polynomials. It is also shown that the gain and phase margin of FPUS can be determined analytically without using graphical techniques.     

Robust stability and performance for interval process plants

In this paper, a two-degrees-of-freedom control design methodology for interval plants to guarantee both the robust stability and performance has been considered. A simple necessary condition and sufficient condition for robust Hurwitz stability of interval polynomial has been obtained using the results of Nie [Nie YY. A new class of criterion for the stability of the polynomials. Acta Mechnica Sinica 1976;110-6] for fixed polynomials. The proposed design methodology based on the obtained necessary condition and sufficient condition is then applied to design a robust control system for a second-order unstable plant in the presence of unknown but bounded parameter uncertainties. Subsequently, a pre-filter is constructed to ensure the desired system performance. Simulation results are used to establish the efficacy of the proposed method for interval plants.     

Direct adaptive control using an adaptive reference model

Direct model reference adaptive control is considered when the plant-model matching conditions are violated due to large changes in the plant or incorrect knowledge of the plant's mathematical structure. Because of the mismatch, the plant can no longer track the original reference model, but may be able to track a modified reference model that still provides satisfactory performance. The proposed approach uses a time-varying ‘adaptive’ reference model that reflects the achievable performance of the changed plant. The approach consists of direct adaptation of state feedback gains for state tracking and simultaneous estimation of the plant-model mismatch. The reference model adapts to the changed plant, and is redesigned if the estimated plant-model mismatch exceeds a bound determined via robust stability and/or performance criteria. The resulting controller offers asymptotic state tracking in the presence of plant-model mismatch as well as matched parameter deviations.     

Robust Control for Two-Time-Scale Discrete Interval Systems

The problem of designing robust controller for discrete two-time-scale interval systems, conveniently represented using interval matrix notion, is considered. The original full order two-time-scale interval system is decomposed into slow and fast subsystems using interval arithmetic. The controllers designed independently to stabilize these two subsystems are combined to get a composite controller which also stabilizes the original full order two-time-scale interval system. It is shown that a state and output feedback control law designed to stabilize the slow interval subsystem stabilizes the original full order system provided the fast interval subsystem is asymptotically stable. The proposed design procedure is illustrated using numerical examples for establishing the efficacy of the proposed method.     

Effect of Solution Annealing on Susceptibility to Intercrystalline Corrosion of Stainless Steel with 20% Cr and 8% Ni

In general, as-received (AR) austenitic stainless steels (ASSs) contain complex carbide precipitates due to manufacturing operations, subsequent annealing treatment, or due to the fabrication processes such as welding. The presence of pre-existing carbides leads to cumulative sensitization and make the steel susceptible to intercrystalline corrosion (ICC)/intergranular corrosion (IGC) which causes premature failure during service. Solution annealing (SA) is one of the ways to deal with such situations. In this present investigation, the AR (hot rolled and mill annealed) chromium-nickel (Cr-Ni) ASS is compared with SA Cr-Ni ASS. The extent of ICC/IGC was evaluated qualitatively and quantitatively by various electrochemical tests including ASTM standard A-262 Practice A and Practice E, double loop electrochemical potentiokinetic reactivation and electrochemical impedance spectroscopy. The degree of sensitization for hot rolled mill annealed AR condition is found to be substantially higher (51.55%) than that of SA condition (26.9%) for thermally aged samples (at 700 °C). The chemical composition across the grain boundary was measured using electron probe micro-analyzer for both (AR and SA) conditions and confirms that the pre-sensitization effect was completely removed after SA treatment.     

Studies on Welding and Sensitization of Chrome–Manganese Austenitic Stainless Steel

The standard composition of austenitic stainless steel (ASS) includes Cr and Ni. However, due to rising cost of Ni, search for suitable alternative is always on. Manganese, on account of being an austenite stabilizer, can be considered as a replacement of Ni. Chrome–manganese steel (part of 200 series of ASS) contains chromium (≤15%) and low nickel. However, there is not enough confidence about their service life. Present work is an attempt to study the effect of welding and sensitization characteristics of this steel. The heat affected zone (HAZ) is identified microstructurally as per ASTM standard A262 Practice A test. Time temperature sensitization (TTS) diagram is established and critical cooling rate (CCR) is estimated. double loop electrochemical potentiokinetic reactivation (DLEPR) technique is used to quantify degree of sensitization (DOS) for heat treated and welded samples. The DOS for thermally aged sample at 750°C for 180 min is found to be 32.56% whereas for welded sample it is 31.30%. The results are discussed and mechanism of micro-structural changes due to welding of such steel is suggested.     

Optical Network Survivability: Protection Techniques in the WDM Layer

This paper is an introduction to survivability of WDM networks. All the main optical protection techniques proposed as far as now for the WDM layer are classified and reviewed. In particular, commonly adopted protection strategies for ring and mesh networks are explained. Moreover, off-line planning of WDM networks able to support path protection is briefly introduced. Finally, an example of heuristic network-capacity optimization is presented, discussing results obtained by considering a case-study network.