Management of thoracic trauma.

Managing major thoracic trauma begins with identifying and anticipating injuries associated with the mechanism of injury. The key aims are to reduce early mortality and the impact of associated complications to expedite recovery and restore the patient to their pre-injury state. While imaging is imperative to identify the extent of thoracic trauma, some pathology may require immediate treatment. The majority can be managed with adequate pleural drainage, but respiratory failure and poor gas exchange may require either non-invasive or invasive ventilation. Ventilation strategies to protect from complications such as barotrauma, volutrauma and ventilator-induced lung injury are important to consider. The management of pain is vital in reducing respiratory complications. A multimodal strategy using local, regional and systemic analgesia may mitigate respiratory side effects of opioid use. With optimal pain management, physiotherapy can be fully utilised to reduce respiratory complications and enhance early recovery. Thoracic surgeons should be consulted early for consideration of surgical management of specific injuries. With a greater understanding of the mechanisms of injury and the appropriate use of available resources, favourable outcomes can be reached in this cohort of patients. Overall, a multidisciplinary and holistic approach results in the best patient outcomes.

Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX.

The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations.