Seabed hydrocarbon seeps are environments where petroleum fluids from deep warm sources migrate upwards through marine sediments and up into the water column. These are important biological environments that also have industrial applications. Seeps can be indicative of deep petroleum reserves and are used in oil exploration. They also host microbial communities that are capable of living amidst petroleum and are capable of its biodegradation, potentially offering benefits in terms of oil spill or methane emissions remediation.

Sustainable product development adheres to the needs of the present while developing a product without compromising the ability of future generations to meet their needs. This proposal aims to develop a suite of sustainability metrics that can be computed by analyzing data like company website, product material information, etc. The metrics will be integrated into the existing Arbor sustainability product suite via dedicated mobile app and browser extension.

This research aims to model a large-scale urban network, consisted of thousands of short links and traffic signals, using a limited set of data collected from a combination of fixed and mobile traffic sensors. The required data for this study will be provided by the AMA Eco-drive trajectory data and Edmonton citywide Dynameq model. A general framework for describing a large traffic network will be developed using machine learning/artificial intelligence tools. Based on the developed traffic model, a congestion pricing scheme to optimize tolling prices and zones will be developed.

This research will develop a novel freeway control approach for the era of co-existence of connected and autonomous vehicles (CAVs) and human-driven vehicles (HDVs). Fully connected and autonomous vehicles can navigate roads without a human driver and connect and interact with other vehicles, roadside infrastructure, and their environment. It is anticipated that the technology will be made available to consumers in the very near future. However, generic market adaption and phasing out of the current vehicle fleet is likely to take years or even decades.

A clinical pathway for primary care Obstructive sleep apnea (OSA) management has been developed in Calgary to address specific barriers to OSA management by primary care physicians (PCPs) that were identified in a series of stakeholder consultation activities. This study’s primary goal is to maximize use of the clinical pathway to support evidence-based primary care OSA management. The results of this study will support more effective implementation of the pathway in the Calgary Zone and facilitate its scale and spread across Alberta.

The progression of bacterial antimicrobials resistance (AMR) has led us to an era that urgently requires alternative antimicrobial therapies. Metal-based antimicrobials (MBA) are increasingly seen as part of the solution. Several metals are already extensively used to prevent and treatment of infections. Silver/copper ionizers are presently used to control pathogens in Canadian hospital water distributions systems.

Heart defects that affect newborns are often correlated to a disfunction in the placenta, although we currently do not fully understand why this occurs. Our objective is to develop a screening platform that uses a model of heart development to understand how cells of the placenta communicate with to cells in the developing heart. This improved understanding will aid in developing therapies for congenital heart defects.

The demand for electricity is growing rapidly and it is expected to double by 2050. Currently, around 12% of this energy is supplied by renewable sources of energy. While wind and solar are the fastest growing energy generation sources, they are dependent on time and weather. To solve the instability of these energy sources, energy storage systems such as redox flow batteries is required. Alkaline zinc-air redox flow batteries, have been reported as promising candidates for energy storage technologies due to high energy densities and cheap raw materials.

Quantum computers, that is, computers that exploit quantum mechanical phenomena to process information, have been shown to theoretically perform some computations faster than the best available methods on traditional computers. One widely applicable quantum computing technique is quantum search which offers an improvement to the problem of finding a needle in a digital haystack. Despite its wide applicability, the usefulness of quantum search to performing any single computational task must often be evaluated on a case-by-case basis.

This project aims to find dynamic systems models of pregnant females exhibiting Type 1 Diabetes for their insulin to glucose behavior. Once a model is identified, this will enable development of an automatic feedback control scheme as a standalone device. This will greatly improve the quality of life of the individual and provide a margin of safety for the fetus during gestation. The project will collect data of injected insulin over time from an automated injection system and also gather measured glucose levels at selected intervals.