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Adsorptive-catalytic stripping voltammetry is commonly used for monitoring trace metals. This study reverses the scheme by developing a sensitive procedure for measuring the catalyst. The catalytic action of bromate upon the cathodic response of the adsorbed molybdenum-3-methoxy-4-hydroxymandelic acid (VMA) complex has been exploited for measuring bromate down to the micromolar concentration level. Experimental variables affecting the response, including the metal and ligand concentrations or the accumulation time and potential, were characterized and optimized to yield a highly linear response (up to at least 1x10(-4) mol l(-1)) and good precision (RSD of 3.5%; n=10; 2x10(-6) mol l(-1) bromate). Analogous adsorptive-catalytic stripping protocols may be utilized for the voltammetric detection of other catalysts.

A bienzyme amperometric graphite-Teflon composite biosensor, in which lactate oxidase (LOD) and peroxidase, together with the mediator ferrocene, are incorporated into the electrode matrix, was developed for the determination of L-lactate in food samples such as wine and yogurt by using both batch- and flow-injection modes. This bienzyme electrode was fabricated by simple physical inclusion of the enzymes and the mediator in the bulk of the graphite-Teflon matrix. A Teflon content of 70%, an applied potential of 0.00 V, and a pH of 7.4 were employed as working conditions. The composite bioelectrode exhibited long-term operation because of the renewability of its surface by polishing. Reproducible amperometric responses were achieved with different electrodes fabricated from different composite matrices, and no significant loss of the enzyme activity occurred after 6 months of storage at 4 degrees C. Detection limits for L-lactate of 1.4 and 0.9 microM were obtained by batch amperometry in stirred solutions and flow-injection with amperometric detection, respectively. An interferences study with different substances which may be present in wine and yogurt together with L-lactic acid demonstrated very good selectivity for the determination of this analyte. The bienzyme composite electrode was applied to the determination of L-lactic acid in red wine and shaken yogurt, and the methods were validated by comparing these results with those obtained by applying a recommended reference method.

In this paper, we present a complete system for the recognition and localization of a three-dimensional (3-D) model from a sequence of monocular images with known motion. The originality of this system is twofold. First, it uses a purely 3-D approach, starting from the 3-D reconstruction of the scene and ending by the 3-D matching of the model. Second, unlike most monocular systems, we do not use token tracking to match successive images. Rather, subpixel contour matching is used to recover more precisely complete 3-D contours. In contrast with the token tracking approaches, which yield a representation of the 3-D scene based on disconnected segments or points, this approach provides us with a denser and higher level representation of the scene. The reconstructed contours are fused along successive images using a simple result derived from the Kalman filter theory. The fusion process increases the localization precision and the robustness of the 3-D reconstruction. Finally, corners are extracted from the 3-D contours. They are used to generate hypotheses of the model position, using a hypothesize-and-verify algorithm that is described in detail. This algorithm yields a robust recognition and precise localization of the model in the scene. Results are presented on infrared image sequences with different resolutions, demonstrating the precision of the localization as well as the robustness and the low computational complexity of the algorithms.