| Date: Friday, September 12, 2003 Time: 1:45 PM Location: EGRC building - Room # 136 Speaker: Dr. Mette Sofie Olufsen North Carolina State University
Title: Modeling baroreflex and autoregulation of cerebral blood flow velocity and finger pressure during posture change from sitting to standing Abstract: Hypertension that causes increased systolic blood pressure, decreased cerebral flow velocity, and decreased cardiovascular control are among the first signs indicating the presence of cerebral vascular disease. One such diseases is arteriosclerosis that can lead to stroke, the most common and devastating vascular disease that affects the central nervous system. In this work we demonstrate how mathematical modeling can be used to predict systemic blood pressure and cerebral flow velocity control (baroreflex and autoregulation) during posture change from sitting to standing. The cardiovascular circulation was modeled using a system of ordinary differential equations that describes blood pressure and flow velocity in compartments representing the heart, the arteries and veins in the upper body, in the legs, and in the brain. When standing up, blood is pooled in the legs due to effect of gravity resulting in a drop in systemic arterial pressure and widening of the blood flow velocity. This was modeled by increasing the blood pressure in the compartments representing the lower body. To restore blood pressure and flow velocity we modeled the baroreflex control by increasing the activity of the sympathetic nervous system while the activity of the parasympathetic nervous system was decreased. The changes in nervous activity results in increased heart rate and cardiac contractility, vasoconstriction of the systemic arterioles, and changes in unstressed volume and venous compliance. Simultaneously, we modeled autoregulation by dilating arterioles in the cerebral vascular bed. It is not clear how baroreflex and autoregulation interacts; one theory suggests that vasoconstriction, resulting from increased baroreflex activity, has an effect throughout the body, but that cerebral vasoconstriction gets overridden by autoregulation resulting in a net vasodilation of the cerebral vascular bed. We demonstrate how mathematical modeling can be used to elucidate this and other hypothesis. Discrete delays have been included to incorporate accurate timing of the onset of the controls. To justify our mathematical model and control mechanisms development, an integral component of our research has been to validate our model against experimental data for both normotensive and diseased people, the latter has been done using optimal control techniques. Date: Friday, September 26, 2003 Time: 11:00 AM Location: EGRC building - Room # 136 Speaker: Dr. Sarah John University of Maryland, College Park
Title: Multiframe selective information fusion from robust error estimation theory Abstract: Multiframe selective information fusion aims at simultaneous extraction and integration of distinct focused regions from multiple frames, each frame consisting of varying blurred and focused regions, into a synthetic output frame. This is accomplished by means of a nonlinear pde, which is a time evolution equation with anisotropic gain, derived from robust error estimation theory. Several applications will be considered, such as the removal of blurred obstructions in front of a distant focused scene, imaging through turbulence to achieve a stationary focused view, multispectral imaging, and high resolution microscopy of 3-D objects
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