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We have evaluated the dynamics of skin microvascular blood flow (BF) and tissue oxygenation parameters (OXY) measured simultaneously at the same site using a combined non-invasive BF+OXY+temperature probe. Skin BF, oxygenated (oxyHb) and deoxygenated (deoxyHb) haemoglobin and mean oxygen saturation (SO 2 ) were measured in 50 healthy volunteers at rest and during perturbation of local blood flow by post-occlusive reactive hyperaemia, sympathetic nervous system-mediated vasoconstriction (deep inspiratory breath-hold) and local skin warming. The relationship between BF and SO 2 over the range of flows investigated was described by a non-linear equation with an asymptote for SO 2 of 84% at BF >50 PU. SO 2 was independently associated with BF, skin temperature, BMI and age, which together identified 59% of the variance in SO 2 (p<0.0001). Fourier analysis revealed periodic low frequency fluctuations in both BF and SO 2 , attributable to endothelial (~0.01 Hz), neurogenic (~0.04 Hz) and myogenic (~0.1Hz) flow motion activity. The frequency coherence between the BF and SO 2 signals was greatest in the endothelial and neurogenic frequency bands. The simultaneous evaluation of microvascular blood flow and oxygenation kinetics in healthy skin provides a platform from which to investigate microvascular impairment in the skin and more generally the pathogenesis of microvascular disease.

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Abstract-This paper investigates the use of a nonconventional approach to control a gas turbine aero-engine. The rationale behind this study is the need to develop advanced tools and techniques that can assist in improving the performance of the system and simultaneously enhance the flexibility of the control strategy. Modern techniques are required for many complex systems where increasingly strict performance and regulatory requirements must be achieved. This is particularly true of aerospace systems where consideration of safety, reliability, maintainability, and environmental impact are all necessary as part of the control requirements. This paper investigates a combination of two such potential techniques: fuzzy logic and evolutionary algorithms. Emerging from new requirements for gas turbine aero-engine control, a flexible gain scheduler is developed and analyzed. A hierarchical multiobjective genetic algorithm is employed to search and optimize the potential solutions for a wide envelope controller covering idle, cruise, and full-power conditions. The overall strategy is demonstrated to be a straightforward and feasible method of refining the control system performance and increasing its flexibility.