Innovative Projects Realized

Mechanical characterization of valve compression packings at high temperature

The leak tightness of valves, compressors and pumps is ensured by packed stuffing-box systems. The most critical element of this assembly is the compressed braided rings called packings. These packings are compressed axially to produce lateral contact pressures large enough to confine the fluid within process vesse1s and pipe segments. The mechanical properties of the compression packing material are the main factors affecting fluid-tightness at room and high temperature and yet there is little or no data available in manufacturer’s catalogues or in the literature. lt is proposed to measure the mechanical properties such as compression modulus, Poisson’s ratio, pressure transmission ratio, short-term creep deformation and thermal expansion coefficient of packing materials. This project initiative will hopefully serve as a basis to launch a North American testing program to develop ASTM-like lasting procedures for compression packing.

Unique Cultural Expressions in Cheerfulness

Recent research indicated the importance of trait cheerfulness in predicting adaptive coping mechanisms, life satisfaction, and flourishing. With worldwide interests in studying this construct, it becomes imperative to understand how the measurement of cheerful behaviours and attitudes may differ cross-culturally. The present study investigates unique cultural patterns in cheerfulness that are distinctive to one culture at the level of the concept, instrument, and item. Participants are recruited from Italy, Canada, Spain, Japan, China, and Germany and mathematical models are used to reveal unique expressions of hilarity (i.e., merry, outward mood state), and cheerful mood (tranquil, composed mood state) cross-culturally. We anticipate unique findingson cultural expressions, including implicit expression of cheerfulness in Eastern cultures, and an explicit way of expressing cheerfulness in Western Cultures. This project not only supports recent calls to investigate cross-cultural invariance across psychological traits, but furthers the investigation on the fundamental conceptualization of cheerfulness.

Deep Hashing and Clustering for Deduplication

Identifying and removing duplicated records by leveraging state-of-the-art AI and machine learning techniques (deep neural networks) from co-op banks’ customer databases, such as the one within the partner organization, Desjardins, will help the banks pay out the appropriate share of dividends to their customers.

How Interest Groups Polarize Elected Officials

Do interest groups use information to polarize elected officials? Conventional wisdom holds that legislative committees transcend partisan bickering and promote evidence-based policymaking. But there remain gaps in the literature and in our understanding of how and whether committees are able to meet this ideal In this project, I propose a research framework to uncover the “hidden hallways” of information exchange in Parliament. I scrape a large, unstructured, and dynamic corpus of committee transcripts and interest group submissions. Using Big Data tools (e.g. Machine Learning, Natural Language Processing, dynamic network analysis), I augment this corpus with federal lobbying records. My goal is to generate new knowledge about how legislators of different parties build lobbying networks, and how these networks change over time and across issue areas. Specifically, I test whether co-partisan legislators who share a connection to semantically similar interest groups are more likely to share additional affiliations, relative to non-co-partisans with connections to semantically dissimilar interest groups.

Preclinical validation of humanized chicken recombinant antibodies targeting GPCRs overexpressed in cancers

In recent years, significant scientific breakthroughs have opened the door to harnessing the immune system to fight cancer. For the first time in history, this brings a cure within reach. However, there are still some scientific and business hurdles to overcome, especially for a group of well-known proteins called G protein coupled receptors (GPCRs). GPCRs are difficult targets, and sometimes referred as intractable proteins, due to their membrane localization and the existence of several close analogues which often leads to non-specific mode of action of small molecules. Over the past 3 years, a multidisciplinary collaboration between researchers from Université de Sherbrooke (UdeS) and Immune Biosolutions (IBio) has tackled this problem and assembled a new therapeutic antibody discovery workflow. In this project, we propose to evaluate the therapeutic potential of two recombinant antibodies with antagonist properties targeting neurotensin receptor 1 and kinin B1 receptor for the treatment of several cancers.

Development of novel, systematic methods for expanding, screening, and selecting biodiversity in industrial yeast strains

Yeast is arguably the most important industrial microorganism in the world, playing a critical role in the fermentation of food and beverage products, as well as cellular factory for production of biofuels, chemicals, and pharmaceuticals. In order to produce such a range of products efficiently and economically, specialized yeast must be optimized for each task. Current tools for yeast optimization are lacking, especially in the sectors of food, beverage, and feed, where consumers demand non-GMO yeast products. In this proposal, we seek to expand the range of non-GMO yeast strain development tools to facilitate the high-throughput, robust optimization and specialization of yeast. In this way, we expect to be able to develop novel yeast that solve industrial process/product challenges, offer efficiency gains and process optimization opportunities, and/or introduce the potential for novel product flavors, aromas and functions while also meeting end-user demand for non-GMO ingredients.

Using tacit knowledge in peer communications and research literature to identify emerging respiratory therapy practice topics and trends

Each day several email messages containing respiratory care topics, issues, and latest treatments are exchanged within the Respiratory Therapy community. Effective exploration and visualization of informal knowledge in these email threads and combining them with the scientific articles published in the Canadian Journal of Respiratory Therapy (CJRT) has the potential to inform future respiratory care practice. The intern combines domain expert knowledge with visual text analytics approaches to extract and visualize emerging issues, trends and decision-making patterns among Respiratory Therapists in Canada. A visual text analytics tool will be created and the knowledge generated will inform respiratory therapy practice in Canada.

Mapping Affordable Housing Need: Rental Housing Demand and Core Housing Need in BC to 2031

In collaboration with the BC Non-Profit Housing Association, the two interns involved in this

project will forecast core housing need and affordable housing demand in the province of BC.

These forecasts will be broken down by household type and sub-population as well as by

region. The results will be mapped for effective analysis and communication of the geography

and extent of housing need throughout the province. This project will inform strategic planning

by the BC Non-Profit Housing Association as well as other organizations across the province

that are seeking more information and analysis on current and future housing needs.

Integrated Microlens Technology for Light Steering Projectors

MTT Innovation Inc. is a Canadian company that is based out of Vancouver, British Columbia. MTT develops technologies for next-generation projectors in home entertainment systems and theatres. The developed projectors are engineered to provide especially high quality images, with enhanced brightness and dynamic range, and an emerging product of MTT that targets these goals is their light steering projector. Such a projector is being developed through the proposed project as a partnership between MTT and researchers at the University of British Columbia’s Okanagan campus. The team is developing polymer-based microlenses that can be used within the light steering projectors to provide the desired high quality images with enhanced brightness and dynamic range. A fully-functioning light source will be developed during the project for use in MTT’s light steering projector.

Eye Gazing Enabled Driving Behavior Monitoring and Prediction

Automobiles have become one of the necessities of modern life, but also introduced numerous traffic accidents that threaten drivers and other road users. Most state-of-the-art safety systems are passively triggered, reacting to dangerous road conditions or driving behaviors only after they happen and are observed, which greatly limits the last chances for collision avoidances. Timely tracking and predicting the driving behaviors calls for a more direct interface beyond the traditional steering wheel/brake/gas pedal. We argue that a driver’s eyes are the interface, as this is the first and the essential window that gathers external information. The objective of the proposed research is to develop an active driving behavior monitoring and prediction framework for driving assistance applications, which is closely related to PANOMOTION TECHNOLOGY INC., a local startup working on intelligence driving assistants. The proposed research can greatly benefit the company by applying the research outcomes to its main products.

Design and optimization of topography based customizable mini-scleral contact lenses

Cornea disorder diseases, like keratoconus, are characterized by progressive thinning and distortion of the apical cornea that leads to complex optical aberrations due to either irregular astigmatism or corneal scarring. For patients with irregular cornea, corneal contact lenses no longer fit and become intolerable with discomfort. In such cases, scleral and mini-scleral (MS) contact lenses are an attractive option. The objective of this project is to develop a mathematical model for predicting optimum profile of MS lenses that is customizable for individual irregular cornea. Analytical and numerical models will be developed to find optimum 3D topographies by solving profile matching and mitigating stress points. Three degrees of freedom will be provided on the posterior surface of MS lenses in terms of corneal, limbal and scleral clearance to conform to individual eye topographic maps. The design of optimum 3D topography for customizable contact lens development can highly beneficial for vision science.

SAR Interferometric Time Series Methods for Monitoring Natural Surfaces

This project involves developing novel methods for improving the estimation of surface displacement of natural earth surfaces using Synthetic Aperture Radar Interferometry (InSAR). The developed methods improve the precision that can be obtained when analyzing a series of sequentially acquired images over the same area. The methods also improve the robustness of the estimation in the presence of strong spatial signal gradients. Together these improvements aim to broaden the envelope of earth surface displacement processes that can be robustly monitored with InSAR. In particular the project will extend the investigation of these methods to the X-band radar frequency band by utilizing SAR imagery acquired by the TerraSAR-X and TandDEM-X satellites which are operated by the German Aerospace Centre (DLR). The project outcome will be a documented assessment of the benefits realized with these methods and how well their performance extends to X-band datasets.