Xia Qing

Influence of overlying tissue and probe geometry on the sensitivity of a near-infrared tissue oximeter

In this paper, the influences of overlying tissue and detecting distance between the source and the detector on the measurement of a tissue oximeter were discussed. The signal-noise-ratio of the detector was also examined. A semi-infinite multi-layer Monte Carlo model was induced to simulate the migration of the photons in the skin, adipose and muscle. The thickness of the adipose layer and the separation between the source and the detector in the muscle were changed to simulate the clinical application. Partial pathlength was introduced as a characteristic parameter to evaluate the sensitivity of the oximeter. A two-wavelength (700 and 830 nm) tissue oximeter was developed to verify the results of the simulation. The Monte Carlo simulation results showed that the sensitivity of the near infrared spectroscopy (NIRS) oximeter declined greatly with increasing overlying tissue thickness. Increasing the distance between the light source and the detector improved the sensitivity. However, in order to achieve a sufficiently high signal-to-noise ratio, it was necessary to limit this distance. The results of a bicycle ergometer exercise verified the above results and showed that, for a special adipose thickness (AT), there may be a reasonable range of the emitter-detector separation.

Optimal daily scheduling of cascaded plants using a new algorithm of nonlinear minimum cost network flow

An optimality condition theorem and an algorithm for nonlinear minimum-cost network flow are proposed. A computational network model for optimal daily scheduling of cascaded plants (ODSCP) is established, and an algorithm for searching the minimum-cost flow-augmenting path and the maximum-cost flow-reducing path in the computational network model of ODSCP is described. Digital computations are carried out and the results show that the proposed method is very fast compared to existing methods. >