An autonomous eco-robotic Surface Vessel (ASV) is designed to operate in extreme weather conditions with an autonomy of several days. This research work aims to present a process for on-board power management between the vessel's power sources, while maximizing the use of Renewable Energy Sources (RES) and taking into consideration onboard sensor, navigation and control and data transfer power requirements. A detailed architecture for a DC network integrating Photovoltaic (PV) panels, Fuel Cells (FCs), hydro generator and energy storage systems is developed. An efficient and flexible Energy Management System (EMS) is developed for managing power sources and maximising endurance using only clean energy. To assess the performance of EMS in meeting the energy demands of the Ocean drone's equipment and propulsion systems, a simulation-based analysis is carried out for realistic missions and scenarios. The developed EMS strategy intends to harvest the energy from PV and hydrogenerator while maintaining the Battery Energy Storage Systems (BESS) as charged as possible. The developed power supply system architecture and EMS can jointly accommodate the need for efficient and long-lasting operation of the vessel with CO2-emission free energy sources.

Limb pain as a presenting feature of an ischemic or hemorrhagic stroke is extremely rare. Here we present a case of a 65-year-old male with complaints of left arm pain and allodynia (specifically light touch to any part of the left arm produced significant discomfort) who was found to have a right parietal lobe intraparenchymal bleed after smoking crack cocaine. Acute central pain is mainly associated with parietal, thalamic, and brainstem lesions. It has been proposed that acute limb pain from a parietal lobe stroke is due to the disconnection of the parietal cortex from the thalamus secondary to the interruption of the pathways between the hemisphere and thalamus/basal ganglia.

Whenever the total power that can be provided by the distributed energy resources (DERs) is less than the total power demand of the loads, the DC bus voltages start to fall which could lead to power collapse. This paper investigates and compares the performances of the existing non-communication based (decentralized) load shedding schemes in a direct current (DC) microgrid to protect the integrity of the microgrid under a large disturbance. The simulation is carried out in a Matlab environment with various forms of load and distributed energy resources on an IEEE 37 AC Node converted to DC. The findings show that the conventional load shedding scheme could expose critical loads to substantial and lengthy voltage sags. Voltage sags and over-shedding of load could be resolved using combined load shedding scheme. The adaptive schemes minimise the duration and magnitude of voltage drop by utilizing the rate of change of voltage (ROCOV) to achieve a more reliable assessment of the microgrid operating conditions and determine the appropriate load shedding voltage thresholds and time delays. All the schemes could not achieve an optimal load shedding, this work therefore leads to the need for more advanced load shedding schemes that can shed load optimally for future DC microgrids.