The proposed community rooted project affords an opportunity for interns to immerse themselves in community engaged research activities and work closely with our partner organizations (Île-à-la-Crosse & James Smith Cree Nation and Diabetes Canada). Guided by relational approaches and the interns will each spend time on site in their respective communities where they will gain experience in sharing and transferring health-promoting messaging specific to diabetes prevention that is grounded in Métis and Cree (respectively) ways of knowing and doing.
AIR Institutes is launching a new resilience online training through a digital portal called AIR Space. The goal of the proposed project will be to evaluate if the training delivered in an online format is effective in developing and improving resilience. As users go through different activities delivered through the digital portal, their level of resilience will be measured over time through short surveys and daily check-ins. This will allow to identify any improvement in resilience and whether the digital portal is effective in improving resilience.
Timely diagnosis of dementia is a public health challenge within Canada. It is hoped that machine-learning empowered cognitive examinations might improve Canada’s response to the dementia population. This study proposed the validation of an automated cognitive examination, the Autonomous Cognitive Examination, which uses machine learning to evaluate users to evaluate previously difficult to assess inputs such as complex images or speech.
Our main aim is to design and fabricate lightweight mechanical structures to show high energy absorption capacity with as low as initial reaction forces, electricity generation via embedding smart materials (piezo patches), and isolate external dynamic excitations. The designed mechanical structures could be applied in the automobile and motorcycle industries. In a car crash, the designed mechanical structures could absorb a significant amount of kinetic energy with low initial reaction forces simultaneously, that could provide safety for the passengers.
Translation of scientific bench-top discoveries into a commercial enterprise can be one of the hardest transitions for academic groups. Additionally, there are very few therapeutic options for neurodegenerative diseases, and a great need exists for the development of new drug candidates to treat diseases, such as amyotrophic lateral sclerosis. Our proposal seeks to continue with the development of new neurodegenerative therapeutics, while simultaneously analyzing and developing commercialization strategies for the translation of drug discoveries into start-up enterprises.
Manufacture companies use foam materials made of polystyrene to protect the goods during storage and shipping. However, polystyrene is plastic-based and made using crude oil, which is terrible for the environment. Used polystyrene foams are challenging to eliminate and occupy space in landfills for a very long period.
Pharmaceutical contamination of water systems poses direct threats to human health and the environment. Unfortunately, wastewater treatment plants are not always capable of sufficiently removing pharmaceutical contamination, particularly where drugs are disposed of in high concentrations – such as pharmaceutical manufacturing facilities. When some residual drugs are released into the environment they can persist and disrupt important functions in humans and wildlife.
Augmented Reality (AR) provides real-time interactive instructions to improve efficiency and accuracy of product maintenance processes. Although different methods have been proposed for the AR-based product maintenance, there is a lack of methods of automatic product disassembly and assembly planning under the AR environment. This project develops an AR-based tool for product maintenance instructions. The maintenance targets are modeled, tracked and simulated in an AR user interface developed to facilitate the guide and visualization of maintenance operations.
To maintain grain quality, grain drying is essential to turn the newly harvested grain from a high moisture content, high temperature and easily spoiled state to a safe condition for transportation or storage. Convection grain dryers are the most widely-used grain dryers around the world, however, the design of dryers nowadays is still mainly based on experience. This study presented a numerical model to simulate the drying processes in a mixed-flow grain dryer based on coupled DEM-CFD method.
Products have to meet high customer satisfaction standards, low production costs in order to compete in the global market. Comparing with conventional production techniques, the additive manufacturing (AM) technology can construct complicated forms with more efficiency. In order to produce high quality 3D printed parts, the appropriate selection of printing parameters is crucial. Advanced parameter settings can improve the printing quality and reduce the printing defect.
