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This work reports the influence of lead (Pb) on fluorescence characteristics and protein structure of phycocyanin molecules experimentally in vitro. The fluorescence intensity decreases with the increasing concentration of Pb from 0 to 5 × 10 mol L, showing the fluorescence quenching of phycocyanin by Pb. The quenching process is suggested to be static regarding the calculation results and the experimental results of time-resolved fluorescence decay profiles. The synchronous fluorescence spectra show that the effect of Pb on the Tyr residues of phycocyanin is more significant than the Trp residues. The forming of aggregation by the interaction of Pb with phycocyanin molecules is suggested from the results of resonance light scattering spectra. The UV-Vis spectra of the protein skeleton of phycocyanin have a red-shift of about 10 nm with increasing the Pb concentration from 0 to 5 × 10 mol L, indicating a change in the protein skeleton and its secondary structure. With the increasing Pb concentration, the two negative peaks (209 nm and 218 nm) on circular dichroism spectra become smaller, showing a decrease of the α-helix structure. These results may give people a deeper understanding of that how the heavy metal (Pb) can affect the chemo-physical properties of phycocyanin.

Intelligent Magnetic Detection Microsystems (IMDM) are complex microsystems, which are used to obtain the information of motor flux and speed in singledriveway traffic system; the microsystems have to fulfill the task in a harsh environment of field, which would infect the reliability of system. An effective method to ensure maintenance cost and reliability is to integrate efficient built-in-test and monitoring function into IMDM, so testability analysis is introduced in the design of Microsystems. The Microsystems testing-points and diagnostic strategy are reasonably identified, which are beneficial to implement the rapid detection and fault isolation. This paper presents an approach to construct a fault message matrix based on the functional block diagram and signal flow chart of the microsystems. By analyzing the contribution of the testing-points to fault detection and fault isolation, the matrix is resolved step by step, the most necessary testing-points are identified and optimal diagnostic strategy is determined. Thus, the purpose of fault detection and fault isolation is achieved by the use of the fewest testing-points and short time.

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