Fault-Diagnosis and Fault-Recovery System of Hall Sensors in Brushless DC Motor Based on Neural Networks.

This paper proposes a neural-network-based framework using Convolutional Neural Network and Long-Short Term Memory (CNN-LSTM) for detecting faults and recovering signals from Hall sensors in brushless DC motors. Hall sensors are critical components in determining the position and speed of motors, and faults in these sensors can disrupt their normal operation. Traditional fault-diagnosis methods, such as state-sensitive and transition-sensitive approaches, and fault-recovery methods, such as vector tracking observer, have been widely used in the industry but can be inflexible when applied to different models.

The virtual Clinical Assessment of Skills and Competence: the impact and challenges of a digitised final examination.

The COVID-19 pandemic has affected how clinical examinations are conducted, resulting in the Royal College of Psychiatrists delivering the Clinical Assessment of Skills and Competence virtually. Although this pragmatic step has allowed for progression of training, it has come at the cost of a significantly altered examination experience. This article aims to explore the fairness of such an examination, the difference in trainee experience, and the use of telemedicine to consider what might be lost as well as gained at a time when medical education and delivery of healthcare are moving toward the digitised frontier.

Mobile application to optimize care for ST-segment elevation myocardial infarction patients in a large healthcare system, STEMIcathAID: rationale and design.

Aims: Technological advancements have transformed healthcare. System delays in transferring patients with ST-segment elevation myocardial infarction (STEMI) to a primary percutaneous coronary intervention (PCI) centre are associated with worse clinical outcomes. Our aim was to design and develop a secure mobile application, STEMIcathAID, streamlining communication, and coordination between the STEMI care teams to reduce ischaemia time and improve patient outcomes.