Mood disorders, including depression and bipolar disorder, represent a common and severe group of mental illnesses. Poor eating behaviors contribute to worsened symptoms and quality of life in these patient populations, but this aspect is not adequately addressed in clinical care. Previous work characterized six groups of eating behaviors in mood disorders, including low appetite, high appetite, emotional eating, food addiction, irregular eating rhythms, and poor diet quality.

The rejection of pyrrhotite from copper-nickel mineral concentrates has long been a pain point for the Canadian mining industry. The presence of pyrrhotite in the mineral concentrate takes up smelter capacity, adversely affects energy efficiency, and generates large quantities of SO2. It is well established that pulp chemistry influences pyrrhotite rejection and flotation performance; however, many pulp chemistry parameters (such as Eh and dissolved oxygen) go unmeasured in industrial processing plants.

Social determinants of health, including factors such as social isolation, food insecurity, and income, play a big part in our health. To account for these important social factors, some healthcare organizations have begun to adopt a strategy called social prescribing which involves regularly asking people if they need help with social determinant of health issues and connecting patients with community resources that can help.

The operation of multiple autonomous aerial vehicles, also known as drones, is a difficult task, usually demanding several skilled operators. However, drones, and other autonomous vehicles as autonomous cars, may operate in areas where operators cannot be present or there are not enough skilled people for the safe use of these vehicles. This project will investigate the use of modern machine learning and artificial intelligence techniques for the reduction of the need of skilled operators in missions requiring the use of multiple vehicles.

Imaging the brain’s vascular response can provide useful information in diagnosing and treating patients with different brain pathologies. Commonly, this imaging is performed using magnetic resonance imaging (MRI) and often involves the use gas inhalation devices that involve a great deal of complexity and setup time. The expensive costs of these devices, and the inability of some patients to tolerate the gas inhalation protocol, has been a major hindrance to the wide-scale implementation of vascular response imaging across MRI centers and hospitals.

Tiresias is a client private solution to malware protection and threat intelligence. Tiresias allows a user to put all their incoming files in a cryptographically secure Data Chest locally. After sending the Data Chest to our cloud environment, our AI scans and infers if it is malicious without seeing the actual file content from the Data Chest. This method protects the client data privacy and confidentiality. The Data Chest is a novel research outcome at the Queen’s School of Computing.

Metal nanoparticles are increasingly used in cosmetics, food packaging, textiles, toothpaste, and other ubiquitous products. Yet, their impact on our environment, food, and health is largely unknown because measuring nanoparticles in environmental and biological systems is very difficult. Similarly, measuring the uptake of metal-containing drugs by cells to develop smart therapeutics targeting tumors is also difficult because it requires analysis of numerous individual cells to assess the selectivity of the drug uptake by diseased cells versus healthy cells.

Youth living in social housing often face a number of challenges to success, including histories of intergenerational poverty, high rates of mental health and substance use issues, limited educational attainment, and weak or absent work histories. Secure employment is one approach to addressing key social determinants of health, including having a secure income, food security, access to needed supports, and social connections.

Motion capture technology that uses markers attached to the body and specialized cameras has been used for research on human motion, but has been limited to laboratories with expert users. New markerless motion capture technology removes these limitations by using standard video cameras and advanced artificial intelligence algorithms, allowing us to measure motion in real-life environments and of multiple people simultaneously.