This project will develop practical workflows, algorithms and programming codes for inferring unknown reservoir properties from distributed temperature and acoustic sensing data. In-situ pressure and flow conditions can be interpreted from downhole fiber signals gathered in real time, which are used to estimate unknown heterogeneous reservoir parameters continuously. Machine learning methods will be incorporated to facilitate the handling of large amount of measured data and computations more efficiently.
The focus of this study is on the understanding of the cellular interactions with polymeric drug carrier for intraarticular injection of therapeutic. The degradability of the Eupraxia’s polymeric drug carrier will be studied in contact with macrophages and/or enzymes. At each time point in the cell study the polymer surface will be characterized by SEM, and the enzymes and ROS production will be measured to compare to the control groups.
In the pursuit of materials that combine the inherent stability of a plastic with additional novel features, this project aims to develop a new platform of nitrogen containing polymers. Using novel synthetic pathways, we have developed and characterized such materials with features such as enhanced strength, adhesion, and self-healing capabilities. This project seeks to bring these materials from the academic bench-top to commercial production scale.
In the transportation industry customer satisfaction, driver retention and profitability are some of the most critical factors in company success. As regulatory environments change, and competition grows Contrans Corp., a flatbed freight company, is seeking to develop a user-friendly application that allows team members to rapidly and accurately determine an optimal dispatch schedule for the fleet.
Genecis Bioindustries makes bacteria that enables production of premium materials cost-competitively. Their first product line is a biodegradable plastic resin (PHAs) used for high-end applications, like 3D printing filaments and personal care products. Genecis can reduce production costs by 40% by using organic waste as the feedstock, lowering the barrier for plastic manufacturers to create healthy and affordable products.
The development of environment-friendly freezing technologies to contaminated water is a potential solution for water treatment in regions with cold weather conditions and vulnerable to anthropogenic impact. The results of laboratory tests fulfilled by Core Geoscience Services Inc. on the removal of mine-impacted water species through ice formation along with other publicly available data will form a basis for the next stage of research comprising quantitative analysis and mathematical modelling.
This project will test a variety of operating conditions used in anaerobic digestion (AD) in wastewater treatment (WWT) plants. The purpose is to identify optimal conditions for AD treatment process. Optimization of AD process would increase production of biogas for production of renewable energy, increase yield of bio-products for agriculture use, reduce WWT plant operating costs, and would decrease carbon footprint of municipal WWT plants. This study will use SENTRY-AD™ technology to monitor microbial activity under various treatment conditions.
RNA interference mediated gene silencing provides one of the most effective treatments for many genetic diseases such as cancer and viral infection. However, due to the many difficulties siRNAs would face during systemic pathway, a delivery system is needed to protect it from degradation and endosomal entrapment, and also to facilitate the unloading of the cargo. In such case, the main objective of this project is to produce a phosphorylation-mediated peptide-based siRNA delivery system.
Avana Canada Inc. is undertaking the development of a supercritical fluid extraction (SFE) unit within its GMP facility for cannabis processing. Cannabis has been used for medicinal purpose for a long time. SFE is currently the best technology for bioactive components extraction. By carefully changing the operational parameters, the solvent strength can provide selectivity to the extraction process, thus adjusting potency of the extract product.
Autonomous operation of oil and gas pipelines is being introduced to the marketplace by utilizing advanced process control and Artificial Intelligence. This Project will explore the use of advanced optimization algorithms in combination with autonomous operation to further increase efficiency of pipelines by continually driving pumps, compressors and valves to achieve the lowest cost operation.
Expected benefits of these efficiencies will be to increase the effective pipeline capacity without building new pipelines, while reducing the amount of energy required in a pipeline’s operation.