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The relative performance of three analgesic rating scales--visual pain analog, verbal pain intensity, and verbal pain relief--was assessed in clinical trials with 1,497 patients and a variety of pain models. The scales correlated strongly with one another, with inconsistent and generally minimal differences in sensitivity. Overall, the verbal relief scale tended to be slightly more sensitive than the pain analog rating, which in turn showed a small advantage over the verbal pain intensity assessment. When the scores derived from the categorized ratings 1 hour after drug dosing (generally the time of peak effect) were analyzed, there was little difference whether a parametric or nonparametric approach was taken. When the cumulative measures of overall effect over 6 hours were considered, however, the nonparametric approach was decidedly more powerful. There was a similar pattern when the analog scores were analyzed. This unanticipated finding appears to be due to the cumulative measures (from all three scales) being more skewed toward the lower end of their respective ranges than are the 1-hour scores. A composite efficacy variable was defined, incorporating data from the three primary scales; this measure was found to be generally comparable in sensitivity to the individual scales and may be useful as a global summary of response. While our investigation provides evidence that any of the ratings considered will accurately reflect analgesic response, the verbal relief scale was the most sensitive and might be the best choice if a single measure is desired.

A B S T R A C T The separate effects of volume expansion and of increased delivery of sodium on sodium reabsorption in the diluting segment of the distal nephron were studied in man. In six normal subjects during a sustained water diuresis, sodium delivery to the distal nephron was increased without volume expansion by the administration of acetazolamide. In these subjects, free water clearance rose linearly as a function of urine flow. In five patients with complete, central diabetes insipidus, distal sodium delivery was increased by the infusion of hypertonic saline during a sustained water diuresis. In four of these five patients, changes in free water clearance were also observed during hypertonic saline diuresis in the presence of distal blockade of sodium reabsorption with chlorothiazide. At high rates of distal delivery the following observations were made: (a) free water clearance was lower and fractional sodium excretion higher during saline diuresis compared to acetazolamide diuresis; (b) although free water clearance was moderately reduced by chlorothiazide at low rates of urine flow, there was no difference in free water clearance between saline loading alone and saline plus chlorothiazide at high rates of urine flow; and (c) during saline loading free water clearance rose without evidence of a limit when increased distal delivery was accompanied by spontaneous increases in glomerular filtration rate, but tended toward a limit when glomerular filtration rate remained constant.The data indicate that during acute volume expansion with saline, there is a decrease in the fraction of delivered sodium reabsorbed in the distal nephron when compared to the response of the distal nephron to comparable increases in distal sodium delivery in the absence of volume expansion.

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The main goal of this research effort is to determine the optimal trajectory for an unmanned aerial vehicle (UAV) in a dynamic environment. A Model Predictive Control (MPC) approach is utilized to provide collision avoidance in view of pop-up threats and a random set of moving and stationary obstacles (no fly zones). The UAV path planning needs to adapt in near real-time to the dynamic nature of the operational scenario, and to react rapidly to updates in the situational awareness, given the vehicle's maneuvering constraints. To achieve this objective, the UAV navigates from a given starting point to a desired target point via selected intermediate waypoints. The possible waypoints are geometrically obtained with additional waypoints placed near the vertices of each polygonshaped obstacle. The MPC optimizer minimizes a cost function at each control cycle using a nonlinear dynamic model of the situation with maneuvering constraints included. The MPC algorithm is selected because it can improve system performance while effectively handling constraints. However, the huge computational effort required for a complete nonlinear realization of the MPC algorithm renders infeasible a comprehensive real-time optimization for this application. To circumvent this problem, discrete-time Laguerre functions are used as basis functions to represent the control inputs instead of using their complete time histories. A representative scenario, consisting of five targets, five static obstacles, nine pop-up threats, and a large, moving no-fly zone, is used to demonstrate this algorithm. Results are presented based on MATLAB® simulation experiments using a UAV model that represents a RQ-7 Shadow 200 to demonstrate the effectiveness of this approach. I. Introduction LYING a piloted aircraft in a hazardous environment, such as a battle zone or severe weather, is a risky venture, because the life of the pilot is at stake. The merits of unmanned aerial vehicles (UAV's) are that they can accomplish many missions at relatively low cost, they are especially effective in long endurance surveillance missions [1], and they do not put human pilots in danger. UAVs are widely used today in military operations, and they have considerable potential for civilian applications as well [2]. UAVs need to avoid obstacles and pop-up threats as they maneuver through dynamic environments. To enhance its mission effectiveness, a fully autonomous UAV must follow an optimal, or nearly optimal, trajectory in terms of some cost function that reflects its effectiveness, such as total fuel use or total mission time. A primary challenge associated with UAV path planning is in dealing with the uncertainty associated with a dynamic environment and the implementation of autonomous decision-making within a given time frame. Many researchers have introduced various path planning algorithms for UAV's, such as Voronoi diagrams [3-6], A* algorithms [7-9], genetic algorithms (GA) [10-16], or virtual potential field (VPF) methods [17-19]. A Voronoi diagram is constructed base...