ELECTROCATALYTIC OXIDATION AND FLOW DETECTION OF CYSTEINE AT AN AQUOCOBALAMIN ADSORBED GLASSY-CARBON ELECTRODE

A chemically modified electrode (CME) constructed by adsorption of aquocobalamin (VB12a) onto a glassy carbon electrode surface was demonstrated to catalyze the electro-oxidation of cysteine, a sulfhydryl-containing compound. The sulfhydryl oxidation occured at 0.54-0.88 V vs. Ag/AgCl depending on pH value (3.0-10.0). The electrocatalytic behavior of cysteine is elucidated with respect to solution pH, operating potential and other variables as well as the CME preparation conditions. When used as the sensing electrode in flow injection amperometric detection, the CME permitted detection of the compound at 0.8 V. The detection limit was 1.7 pmol. The linear response range went up to 1.16 nmol. The stability of the CME was shown by RSD (4.2%) over 10 repeated injections.

CATALYTIC-OXIDATION AND FLOW DETECTION OF ACETAMINOPHEN AT A DICYANOBIS(1,10-PHENANTHROLINE)IRON(II)-MODIFIED ELECTRODE

Dicyanobis(1,10-phenanthroline)iron(II)-modified glassy carbon electrodes were shown to exhibit an electrocatalytic response for the oxidation of acetaminophen with a decrease of 100 mV in the potential required. It can also inhibit the oxidation of ascor

WAVELENGTH POSITIONING ERRORS AND TRUE DETECTION LIMIT IN RELATION TO MULTICOMPONENT ANALYSIS TECHNIQUES FOR THE CORRECTION OF LINE INTERFERENCES IN INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION-SPECTROMETRY

The present paper deals with the evaluation of the relative error (DELTA(A)) in estimated analyte concentrations originating from the wavelength positioning error in a sample scan when multicomponent analysis (MCA) techniques are used for correcting line interferences in inductively coupled plasma atomic emission spectrometry. In the theoretical part, a quantitative relation of DELTA(A) with the extent of line overlap, bandwidth and the magnitude of the positioning error is developed under the assumption of Gaussian line profiles. The measurements of eleven samples covering various typical line interferences showed that the calculated DELTA(A) generally agrees well with the experimental one. An expression of the true detection limit associated with MCA techniques was thus formulated. With MCA techniques, the determination of the analyte and interferent concentrations depend on each other while with conventional correction techniques, such as the three-point method, the estimate of interfering signals is independent of the analyte signals. Therefore. a given positioning error results in a larger DELTA(A) and hence a higher true detection limit in the case of MCA techniques than that in the case of conventional correction methods. although the latter could be a reasonable approximation of the former when the peak distance expressed in the effective width of the interfering line is larger than 0.4. In the light of the effect of wavelength positioning errors, MCA techniques have no advantages over conventional correction methods unless the former can bring an essential reduction ot the positioning error.

ELECTROCATALYTIC OXIDATION AND FLOW DETECTION OF HYDRAZINE COMPOUNDS IN LIQUID-CHROMATOGRAPHY AT A VITAMIN-B-12 ADSORBED GLASSY-CARBON ELECTRODE

A vitamin B-12 chemically modified electrode (CME) was constructed by adsorption of vitamin B-12 onto a glassy carbon surface. The electrode catalyzes the electrooxidation of hydrazine compounds over a wide pH range. The electrocatalytic behavior of hydrazines is elucidated with respect to the CME preparation conditions, solution pH, operating potential, mobile phase flow rate, and other variables. When applied to liquid chromatographic detection of the analytes, the vitamin B-12 CME yielded a linear response range over 2 orders of magnitude, and detection limits at the picomole level. The vitamin B-12 CME offers acceptable catalytic stability in both batch and flow systems.

Sensitive and Rapid Detection of Genetic Modified Soybean (Roundup Ready) by Loop-Mediated Isothermal Amplification

Using the LAMP method, a highly specific and sensitive detection system for genetically modified soybean (Roundup Ready) was designed. In this detection system, a set of four primers was designed by targeting the exogenous 35S epsps gene. Target DNA was amplified and visualized on agarose gel within 45 min under isothermal conditions at 65 degrees C. Without gel electrophoresis, the LAMP amplicon was visualized directly in the reaction tube by the addition of SYBR Green I for naked-eye inspection. The detection sensitivity of LAMP was 10-fold higher than the nested PCR established in our laboratory. Moreover, the LAMP method was much quicker, taking only 70 min, as compared with 300 min for nested PCR to complete the analysis of the GM soybean. Compared with traditional PCR approaches, the LAMP procedure is faster and more sensitive, and there is no need for a special PCR machine or electrophoresis equipment. Hence, this method can be a very useful tool for GMO detection and is particularly convenient for fast screening.

Selective and specific detection of sulfate-reducing bacteria using potentiometric stripping analysis

A fast, sensitive and reliable potentiometric stripping analysis (PSA) is described for the selective detection of the marine pathogenic sulfate-reducing bacterium (SRB). Desulforibrio caledoiensis. The chemical and electrochemical parameters that exert influence on the deposition and stripping of lead ion, such as deposition potential, deposition time and pH value were carefully studied. The concentration of SRB was determined in acetate buffer solution (pH 5.2) under the optimized condition (deposition potential of -1.3 V. deposition time of 250 s, ionic strength of 0.2 mol L-1 and oxidant mercury (II) concentration of 40 mg L-1). A linear relationship between the stripping response and the logarithm of the bacterial concentration was observed in the range of 2.3 x 10 to 2.3 x 10(7) cfu mL(-1). In addition, the potentiometric stripping technique gave a distinct response to the SRB, but had no obvious response to Escherichia coli. The measurement system has a potential for further applications and provides a facile and sample method for detection of pathogenic bacteria. (C) 2010 Elsevier B.V. All rights reserved.

Learning and Example Selection for Object and Pattern Detection

This thesis presents a learning based approach for detecting classes of objects and patterns with variable image appearance but highly predictable image boundaries. It consists of two parts. In part one, we introduce our object and pattern detection approach using a concrete human face detection example. The approach first builds a distribution-based model of the target pattern class in an appropriate feature space to describe the target's variable image appearance. It then learns from examples a similarity measure for matching new patterns against the distribution-based target model. The approach makes few assumptions about the target pattern class and should therefore be fairly general, as long as the target class has predictable image boundaries. Because our object and pattern detection approach is very much learning-based, how well a system eventually performs depends heavily on the quality of training examples it receives. The second part of this thesis looks at how one can select high quality examples for function approximation learning tasks. We propose an {em active learning} formulation for function approximation, and show for three specific approximation function classes, that the active example selection strategy learns its target with fewer data samples than random sampling. We then simplify the original active learning formulation, and show how it leads to a tractable example selection paradigm, suitable for use in many object and pattern detection problems.

Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning

Ellis, D. I., Broadhurst, D., Kell, D. B., Rowland, J. J., Goodacre, R. (2002). Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning. ? Applied and Environmental Microbiology, 68, (6), 2822-2828 Sponsorship: BBSRC

Semi-Supervised OWA Aggregation for Link-Based Similarity Evaluation and Alias Detection

T.Boongoen and Q. Shen. Semi-Supervised OWA Aggregation for Link-Based Similarity Evaluation and Alias Detection. Proceedings of the 18th International Conference on Fuzzy Systems (FUZZ-IEEE'09), pp. 288-293, 2009. Sponsorship: EPSRC

Real Time Eye Tracking and Blink Detection with USB Cameras

A human-computer interface (HCI) system designed for use by people with severe disabilities is presented. People that are severely paralyzed or afflicted with diseases such as ALS (Lou Gehrig's disease) or multiple sclerosis are unable to move or control any parts of their bodies except for their eyes. The system presented here detects the user's eye blinks and analyzes the pattern and duration of the blinks, using them to provide input to the computer in the form of a mouse click. After the automatic initialization of the system occurs from the processing of the user's involuntary eye blinks in the first few seconds of use, the eye is tracked in real time using correlation with an online template. If the user's depth changes significantly or rapid head movement occurs, the system is automatically reinitialized. There are no lighting requirements nor offline templates needed for the proper functioning of the system. The system works with inexpensive USB cameras and runs at a frame rate of 30 frames per second. Extensive experiments were conducted to determine both the system's accuracy in classifying voluntary and involuntary blinks, as well as the system's fitness in varying environment conditions, such as alternative camera placements and different lighting conditions. These experiments on eight test subjects yielded an overall detection accuracy of 95.3%.