Dental healthcare workers (DHCWs) are at high risk of occupational exposure to droplets and aerosol particles emitted from patients' mouths during treatment. We evaluated the effectiveness of an air cleaner in reducing droplet and aerosol contamination by positioning the device in four different locations in an actual dental clinic. We applied computational fluid dynamics (CFD) methods to solve the governing equations of airflow, energy and dispersion of differentsized airborne droplets/aerosol particles. In a dental clinic, we measured the supply air velocity and temperature of the ventilation system, the airflow rate and the particle removal efficiency of the air cleaner to determine the boundary conditions for the CFD simulations. Our results indicate that use of an air cleaner in a dental clinic may be an effective method for reducing DHCWs' exposure to airborne droplets and aerosol particles. Further, we found that the probability of droplet/aerosol particle removal and the direction of airflow from the cleaner are both important control measures for droplet and aerosol contamination in a dental clinic. Thus, the distance between the air cleaner and droplet/aerosol particle source as well as the relative location of the air cleaner to both the source and the DHCW are important considerations for reducing DHCWs' exposure to droplets/aerosol particles emitted from the patient's mouth during treatments.

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In this paper, an event-triggered near optimal control structure is developed for nonlinear continuous-time systems with control constraints. Due to the saturating actuators, a nonquadratic cost function is introduced and the Hamilton-Jacobi-Bellman (HJB) equation for constrained nonlinear continuous-time systems is formulated. In order to solve the HJB equation, an actor-critic framework is presented. The critic network is used to approximate the cost function and the action network is used to estimate the optimal control law. In addition, in the proposed method, the control signal is transmitted in an aperiodic manner to reduce the computational and the transmission cost. Both the networks are only updated at the trigger instants decided by the event-triggered condition. Detailed Lyapunov analysis is provided to guarantee that the closed-loop event-triggered system is ultimately bounded. Three case studies are used to demonstrate the effectiveness of the proposed method.