Twelve tips for strengthening global equity in health professions education publication.

Despite recent calls to engage in scholarship with attention to anti-racism, equity, and social justice at a global level in Health Professions Education (HPE), the field has made few significant advances in incorporating the views of the so-called "Other" in understanding the nature, origin, and scope of knowledge as well as the epistemic justification of knowledge production. Editors, authors, and reviewers must take responsibility for questioning existing systems and structures, specifically about how they diffuse the knowledge of a few and silence the knowledge of many. This article presents 12 recommendations proposed by (GSCAC), a group of HPE professionals, representing countries in the Global South, to help the Global North enact practical changes to become more inclusive and engage in authentic and representative work in HPE publishing.

Advancing Fault Detection in HVAC Systems: Unifying Gramian Angular Field and 2D Deep Convolutional Neural Networks for Enhanced Performance.

Efficiency and comfort in buildings rely on on well-functioning HVAC systems. However, system faults can compromise performance. Modern data-driven fault detection methods, considering diverse techniques, encounter challenges in understanding intricate interactions and adapting to dynamic conditions present in HVAC systems during occupancy periods.

Hybrid Random Forest and Support Vector Machine Modeling for HVAC Fault Detection and Diagnosis.

The malfunctioning of the heating, ventilating, and air conditioning (HVAC) system is considered to be one of the main challenges in modern buildings. Due to the complexity of the building management system (BMS) with operational data input from a large number of sensors used in HVAC system, the faults can be very difficult to detect in the early stage. While numerous fault detection and diagnosis (FDD) methods with the use of statistical modeling and machine learning have revealed prominent results in recent years, early detection remains a challenging task since many current approaches are unfeasible for diagnosing some HVAC faults and have accuracy performance issues.