PulsarSpectrum: simulating gamma-ray pulsars for the GLAST mission

We present here an overview of PulsarSpectrum, a program that simulates the gamma ray emission from pulsars. This simulator reproduces not only the basic features of the observed gamma ray pulsars, but it can also simulate more detailed effects related to pulsar timing. It is a very useful tool to understand the GLAST capabilities in the pulsar science.Comment: 6 pages, 3 figures, contribution for "Third Workshop on Science with the New Generation of High Energy Gamma-ray Experiments", May 2005, Cividale del Friuli (UD), Ital

Model predictive control using MISO approach for drug co-administration in anesthesia

In this paper, a model predictive control system for the depth of hypnosis is proposed and analyzed. This approach considers simultaneous co-administration of the hypnotic and analgesic drugs and their effect on the Bispectral Index Scale (BIS). The control scheme uses the nonlinear multiple-input–single-output (MISO) model to predict the remifentanil influence over the propofol hypnotic effect. Then, it exploits a generalized model predictive control algorithm and a ratio between the two drugs in order to provide the optimal dosage for the desired BIS level, taking into account the typical constraints of the process. The proposed approach has been extensively tested in simulation, using a set of patients described by realistic nonlinear pharmacokinetic/pharmacodynamic models, which are representative of a wide population. Additionally, an exhaustive robustness evaluation considering inter- and intra-patient variability has been included, which demonstrates the effectiveness of the analyzed control structure

Event-Based control of depth of hypnosis in anesthesia

Background and Objective: In this paper, we propose the use of an event-based control strategy for the closed-loop control of the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. Methods: A new event generator with high noise-filtering properties is employed in addition to a PIDPlus controller. The tuning of the parameters is performed off-line by using genetic algorithms by considering a given data set of patients. Results: The effectiveness and robustness of the method is verified in simulation by implementing a Monte Carlo method to address the intra-patient and inter-patient variability. A comparison with a standard PID control structure shows that the event-based control system achieves a reduction of the total variation of the manipulated variable of 93% in the induction phase and of 95% in the maintenance phase. Conclusions: The use of event based automatic control in anesthesia yields a fast induction phase with bounded overshoot and an acceptable disturbance rejection. A comparison with a standard PID control structure shows that the technique effectively mimics the behavior of the anesthesiologist by providing a significant decrement of the total variation of the manipulated variable