First report of a novel plant lysozyme with both antifungal and antibacterial activities.

A novel lysozyme exhibiting antifungal activity and with a molecular mass of 14.4 kDa in SDS–polyacrylamide gel electrophoresis was isolated from mung bean (Phaseolus mungo) seeds using a procedure that involved aqueous extraction, ammonium sulfate precipitation, ion exchange chromatography on CM-Sephadex, and high-performance liquid chromatography on POROS HS-20. Its N-terminal sequence was very different from that of hen egg white lysozyme. Its pI was estimated to be above 9.7. The specific activity of the lysozyme was 355 U/mg at pH 5.5 and 30 °C. The lysozyme exhibited a pH optimum at pH 5.5 and a temperature optimum at 55 °C. It is reported herein, for the first time, that a novel plant lysozyme exerted an antifungal action toward Fusarium oxysporum, Fusarium solani, Pythium aphanidermatum, Sclerotium rolfsii, and Botrytis cinerea, in addition to an antibacterial action against Staphylococcus aureus.

A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.