The implementation of data structures usually requires checking for certain mathematical properties such as equality. Those properties are usually implemented in methods that reason about the objects stored in these data structures. However, the implementation of such methods is fairly complex, and may exhibit software bugs that may not necessarily lead to program crashes. Therefore, it is often hard to reproduce such bugs.

Canada is among the world’s largest producers of energy derived from resource extraction. Canada’s Oil Sands Region produces 70% of Canada’s crude oil, and ranks third, after Saudi Arabia and Venezuela, in terms of proven global crude oil reserves. In order for Canadian industry to continue to meet this high demand for energy they must adhere to the social and environmental pressures to reclaim and restore the extraction sites to their original condition, and to offset potential environmental destruction.

Apelin, an innate peptide, is a critical component of the apelin pathway, which is responsible for regulatory mechanisms of the cardiovascular system. Apelin is downregulated in patients with cardiovascular disease, therefore limiting the cardioprotective potential of the pathway. This project focuses on the optimization of a biological analog, able to withstand enzyme degradation with improved function that acts as a substitute for apelin.

There is a growing movement within the agricultural community to use a nature-based approach to soil management, emphasizing its natural ability to sequester atmospheric carbon. Soil carbon sequestration not only improves soil health and fertility, but benefits the climate (reduced GHG emissions) and watersheds (facilitates water infiltration, mitigating floods, and purification).

Nutraceuticals are being used ubiquitously, but seldom undergo rigorous testing. This study is focused on two primary aspects of studying natural health products, specific cannabis and its oils. The first objective is to determine the shelf life (product stability) by performing a series of tests to accelerate the ageing process in order to provide an estimation of shelf life. Currently, cannabis oils have arbitrary assignments of expiry dates, if at all. The other key focus involves studying the antioxidant benefits (or pro-oxidant detriment) imparted by cannabis products.

Metabolomics is an emerging field of research that provides insight into health and disease by studying the levels of various small molecules (metabolites) in the body. In this project, we are developing new tools that will improve and standardize methods for collecting and stabilizing fecal samples for metabolomics studies based on the analysis of fecal samples. Ultimate goals of the project are improved workflows for analyzing fecal samples for metabolomics studies, and kits which will permit easy home-collection of samples. The kits will also stabilize the samples at room temperature.

Artificial Intelligence (AI) research has grown rapidly in recent years as the result of faster computers and better algorithms. AI models can be trained to automate the decision process and provide results. However, if the model is not properly or sufficiently trained, the outcome will likely be unpredictable and inaccurate. Besides, training data is not easily available in a lot of applications. To address these issues, our strategy is to integrate classical Computer Vision (CV) algorithms and Deep Learning (DL) techniques. CV can provide solutions without training data.

Flow cytometry is a technique used to detect and measure physical and chemical characteristics of a population of cells or particles. A sample containing cells or particles is suspended in a fluid and injected into the flow cytometer instrument. The sample is focused to ideally flow one cell at a time through a laser beam and the light scattered is characteristic to the cells and their components. Cells are often labeled with fluorescent markers so that light is first absorbed and then emitted in a band of wavelengths.

This project will develop data-driven models for production performance analysis and optimization for solvent-assisted bitumen recovery operations and related processes. Effective operations of solvent processes are crucial for improving oil production and maintaining a low solvent-to-oil ratio (SOR).

Oil recovery processes use flow control devices (FCDs) to ensure uniforms flow of fluids with minimized potential for well failure. These devices operate by restricting the flow through nozzles causing its velocity and pressure to significantly change. For the flow to keep its momentum, its pressure has to drop which unfortunately increases the likelihood of local well failure to occur. In this research, the performance of various nozzle types will be tested to investigate the effect of geometry on the pressure drop.