Analysis of Extended Partial Least Squares for Monitoring Large-Scale Processes

This paper theoretically analysis the recently proposed "Extended Partial Least Squares" (EPLS) algorithm. After pointing out some conceptual deficiencies, a revised algorithm is introduced that covers the middle ground between Partial Least Squares and Principal Component Analysis. It maximises a covariance criterion between a cause and an effect variable set (partial least squares) and allows a complete reconstruction of the recorded data (principal component analysis). The new and conceptually simpler EPLS algorithm has successfully been applied in detecting and diagnosing various fault conditions, where the original EPLS algorithm did only offer fault detection.

PURIFICATION AND PARTIAL CHARACTERIZATION OF AN ENDO-POLYGALACTURONASE FROM ASPERGILLUS NIGER

A pectinase was identified and isolated from a commercial Aspergillus niger pectinase preparation. The crude enzyme preparation, which was prepared by precipitation of the water extract of the culture of A. niger with ammonium sulfate, was further fractionated by three steps of chromatography, i. e., cation exchange, hydrophobic interaction and onion exchange, to obtain an electrophoretically homogeneous pectinase. The molecular weight of the purified enzyme was estimated by SDS-PAGE to be about 40.4 kDa under both nonreducing and reducing conditions, with the optimum pH at 5.0 and the optimum temperature at 36C. The enzyme was stable at temperatures below 35C. The partial N-terminal ammo acid sequence data analysis of the first 19 amina acids of the obtained pectinase revealed 94.7% and 89.5% homology with two reported pectinases from A. niger.