Développement d’un procédé de culture aérobique de cellules de la plante Catharanthus roseus pour la production de molécules à haute valeur ajoutée

Les végétaux produisent de nombreuses molécules bioactives pour lesquelles il n’est pas économiquement rentable de les synthétiser. La demande pour certaines de ces molécules dépasse l’approvisionnement à l’échelle mondiale, mais nombreuses de ces espèces sont d’origines tropicales et leur culture est difficile à rentabiliser en sol canadien. Des méthodes de production alternatives existent, comme la […]

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Engineering the moss Physcomitrium patens to produce the monoterpene indole alkaloid strictosidine

This project aims to genetically engineer moss to make the molecule strictosidine. Strictosidine is a building block molecule upon which many important medicines are made, including cancer drugs, sedatives, and heart medications; together, these compounds are classified as monoterpene indole alkaloids (MIA). Current methods of making MIAs rely on extraction from plants such as Madagascar […]

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Multi-Modal Wild Salmon Enumeration and Monitoring: A Video and Sonar-based Deployment in Indigenous Rivers of British Columbia

We develop a real-time salmon monitoring system and web application that includes automated counting using computer vision technologies, lowering our partner’s technician resources in performing manual counting. We will deploy the monitoring system in at least nine river locations with small computer hardware capable of deep learning acceleration to run the automated counting system in […]

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Assessment of resistant starch in extruded and canned pet food formulations

Extruded pet foods are produced using steam, water, and shear that gelatinize starches in the formula. The type of starch and extrusion parameters influence the texture, palatability, and expansion of the kibble. Different types of starch may be less accessible to digestive enzymes. Resistant starch, an indigestible starch that is fermented by bacteria in the […]

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Application of A.I. Techniques and Remote Sensing to Predict Water Quality

The project will develop an A.I. based model and framework to predict water quality conditions in lakes and/or larger streams using satellite imagery. The approach will be generalized and automated so that it can be easily applied to quantify water quality for water bodies in various regions within Canada. Models will be trained using government […]

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AI-driven Methods for Patrol Vehicle Dispatch and Route Optimization Under Uncertainty

A security company needs a method to dispatch patrol vehicles and plan vehicle routes to reduce costs, maximize revenue, and deliver to customers the best value. Vehicle dispatching and routing planning are two well-known combinatorial optimization problems (COPs) that find wide applications in transportation (e.g., truck routing and luggage handling), logistics (e.g., warehouse planning and […]

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Traffic Estimation and Stable Resource Allocation Using Distributed Machine Learning

The proposed research will develop novel distributed machine learning techniques for stable resource allocation and improving traffic estimation in networks. It is a well-known fact that networks are becoming complex and user demand is growing in many directions including the traditional demand for capacity and less delay, as well as improvements in Quality of Experience […]

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Identifying Molecular Targets for New Bipolar Disorder Drugs

Bipolar Disorder (BD) is the 4th leading cause of disability amongst 10-24-year-olds. This illness is characterized by recurrent episodes of mania and depression, with 7% of BD patients die by suicide, representing a significant public health concern. Since BD patients spend half of their life experiencing mood symptoms despite treatments, identifying novel therapies that are […]

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