Projets novateurs réalisés

Dynamique spatia Ie de la tordeuse des bourgeons de I’epinette au cours dudernier siecle en foret boreale

Ce projet vise a effectuer une analyse spatia Ie de la diffusion des epidemies du principal

ravageur des coniferes en Amerique du Nord: la tordeuse des bourgeons de I’epinette,

pendant tout Ie 20e siecle. La defoliation par cet insect entraine une reduction caracteristique

de la croissance, visible dans Ie cerne de croissance des arbres hotes de I’insecte, qui sont

des archives de cet evenement au cours du temps. Nous utiliserons des chronologies de

largeur de cernes des arbres hotes de la tordeuse dans toute son aire de distribution, du sud

du Quebec jusqu’au circa 53e paraliele, dans la pessiere noire, pour identifier les moments

ou il y a eu attaque de I’insecte a differents endroits pendant Ie 20e siecie. Nous pourrons

ainsi produire des scenarios de diffusion des epidemies selon I’intensite de la defoliation qui

serant indispensables pour predire la diffusion des epidemies futures et pour adapter

I’amenagement forestier en fonction de la susceptibilite et de la vulnerabilite des

peuplements.

Assessing Harvest and Post Harvest Fruit Quality in Blueberry

Blueberry is a soft fruit species for which consumption has increased drastically in the last two decades. The rapid increase in consumption is mainly driven by the health benefits and pleasant flavour of the fruit. However, consumers assess fruit quality in terms of flavour, texture and aroma and use these features as the main criteria for purchasing product. Nonetheless, there is a lack of study for these quality traits for blueberry at harvest and post harvest stages. Therefore, this project aims to develop a method for assessing fruit quality using analytical platforms, comparing new potential varieties (i.e., breeding selections) with established commercial varieties and developing novel technologies to improve postharvest blueberry quality.

Development of a human immortalized FSHD cell line to study the epigenetic targeting of DUX4 to treat FSHD

Facioscapulohumeral muscular dystrophy (FSHD) is a debilitating disease resulting from the loss of skeletal muscles mainly in the face, shoulder blades and upper arms. FSHD results from expression of the protein DUX4
which causes skeletal muscle cell death and therefore loss of muscles. This project aims to immortalize isolated skeletal muscle cells from patients with FSHD and produce long-lived cells that can be used to screen
pharmaceutical compounds for their ability to inhibit the expression of DUX4 and therefore treat FSHD. The completion of this project will result in a new tool to advance Resverlogix’s efforts in FSHD drug development.

Interior Construction Progress Monitoring Using Computer Vision and BIM

Progress monitoring is an essential task in all construction projects. A proper progress monitoring can minimize the level of project overruns, which is very common among construction projects but incurring significant loss to public and private funds annually. Manual methods of progress tracking are too infrequent to represent continuous and live insights about the workplace. Recent advancements in the area of computer vision and machine learning inspired researchers to use these techniques for development of new automated progress monitoring systems. The main objective in these types of research is to use different types of cameras, and by capturing videos or photos, monitor and measure the progress during construction. Reaching to this objective becomes more complicated when the construction occurs indoor and many objects obstruct and confuse the vision of cameras. TO BE CONT’D

Application mobile pour collecter en temps réel les données de blessures post-traumatiques des pompiers

Le personnel de sécurité publique, y compris les pompiers et les premiers répondants, peut être exposé à des événements troublants ou menaçants, tels que des blessés graves, des enfants décédés et des personnes en détresse. En moyenne, les pompiers assistent à environ huit différents événements potentiellement traumatiques au travail chaque année. Des blessures de stress opérationnel (BSO) peuvent résulter de ces expositions et peuvent inclure anxiété, dépression, toxicomanie et trouble de stress post-traumatique. Les nouvelles technologies, telles que les applications mobiles, peuvent être un moyen utile d’effectuer des évaluations répétées en temps réel. La recherche proposée est une étude longitudinale qui a pour but d’évaluer les BSO en temps réel (par une application mobile) parmi les pompiers/premiers répondants et à étudier la trajectoire des BSO et des facteurs associés sur une période de trois mois. TO BE CONT’D

Integrated Configurable Power Input/Output Systems for Avionic Applications

Thales Canada develops control systems for avionics applications, which operate in harsh environments that may compromise the functionality of very high density chips. The company needs to develop a generic power interface for different avionics applications with a high level of criticality. However, such circuitry requires a lot of space on printed circuit boards when implemented as discrete components. The main goal of this research is to elaborate methods and techniques to design miniature configurable power systems for transportation vehicles under harsh conditions using integrated circuit techniques and technologies. This research will exploit the capabilities offered by System- in-Package (SiP) technology to minimize space by integrating a plurality of low and high power silicon integrated circuits, microelectromechanical systems (MEMS) and multi-layer substrates inside the same package, giving designers more flexibility to reduce the number of components and for system miniaturization.

Computational and Experimental Evaluation of Leading-Edge Droops for Performance Enhancement of Wind Turbine Rotors

Wind power is becoming an important source of clean electricity. However, wind turbines operating at low wind conditions suffer from reduced efficiency and reduced electricity generation. Leading-edge droops are small extensions added to the front of the blade that can potentially improve the turbine efficiency under low wind speeds. The Mitacs project will investigate how aviation-inspired leading edge droops affect the aerodynamic characteristics of wind turbine blades. The research will use computer simulations to evaluate the effect of droops on the performance of various wind turbine families and to optimize the droop geometry for a selected family. The findings from the computer simulations will be compared to field measurements of droops added to a small-scale wind turbine.

New Catalysts and Chemical Processes for the Pharmaceutical Industry

Synthetic chemistry is used to assemble the small organic molecules that comprise many of the important consumer products used by society every day. Such fine chemicals are used to assemble drugs, agrochemicals, electronics, materials, dyes, etc.. Metal catalysts are part of the arsenal that the synthetic chemist uses to make such prized small molecules and Total Synthesis Ltd. (TSL), the sponsor of this research, is a globally recognized leader in catalyst invention and sales. The interns on this project will work in the company lab to develop methods to prepare palladium-based catalysts at various scales and to evaluate these catalysts in new chemical transformations being invented in the academic lab. TO BE CONT’D

Revitalizing Indigenous traditional management of salmon – evaluating risk, opportunities and needs for re-emergence of traditional terminal fisheries

First Nations have fished for salmon in British Columbia for more than 10,000 years. Traditionally, many First Nations fisheries were conducted using weirs – fences constructed in the river – or stone fish traps, and these traditional technologies were used for thousands of years to manage and harvest salmon. However, with the arrival of commercial fishing in British Columbia, these traditional technologies were banned under the Fisheries Act, and salmon fishing is now primarily conducted in marine waters, targeting hundreds of co-migrating populations. With declines in abundance of many wild salmon stocks, conservation concerns for at-risk populations has led to reductions in fishing opportunity in First Nations subsistence, commercial, and sport fisheries. Our project will provide scientific analysis and data collection to support the Heiltsuk Nation as they work to rebuild a traditional terminal fishery for salmon in the Kunsoot River. TO BE CONT’D

Development of biological models for Near Infrared measurements

Spinal cord injuries and other pathologies of the spinal column represent a large cause of disabilities or deaths and significantly affect the quality of life of the individuals affected. To reduce the risk of further injury during spinal surgery and to support diagnostic and treatment, there is a need for a non-invasive real time monitoring system which can assess the health of the spinal cord.
The objective of the research project is to monitor the functional state of the spinal cord by spectroscopy in the visible and near infrared, by utilizing a telecommunicating implant. Performing multiphysical modeling and analysis of the luminous flux passing through the spinal cord in altering configurations is desired. There is an interest in using near infrared (NIR) spectroscopy methods to detect fibrosis. TO BE CONT’D

Improving Receipt Classification Through Text Processing

10sheet is a third party software company aimed at providing easy bookkeeping to client companies. One of the steps in bookkeeping is classifying receipts based on their content. Without relying on a human bookkeeper, 10sheet uses a classification algorithm to build an automatic classifier for this purpose. However, such a classifier needs to have a high performance to be trusted with real world tasks. In this project, an investigation will be conducted of various methods of preprocessing the input text used in building the classifier and the classification algorithms to identify solutions and enhancements that have the potential to boost the current performance of the automatic classifier for receipts. Then the chosen methods out of the proposed ones for will be prototyped and evaluated for inclusion in, and advancement of, the company’s system.

Low Data Drug Discovery

The project aims to facilitate the research and development of new drugs by exploring Machine Learning methodology useful for both the generation of new molecules and the prediction of molecule properties. Doing so will involve training deep learning models on a large number of small, heterogeneous datasets, with the objective of transferring learned representations quickly when faced with a new drug-discovery or drug optimization objectives. The trained models will be used for the purposes of predicting molecular properties of new drugs and generating novel molecules with high likelihood of satisfying certain properties. The multi-objective nature of designing new molecules satisfying competing objectives will be approached using techniques from Reinforcement Learning.