This summer, Nathalia Soares Covre, a Mitacs intern from Brazil, is helping the modelEAU team develop a digital model of an innovative wastewater treatment process. This new process reduces the discharge of nitrogen into lakes and rivers so that plant operators can work to reduce the impact of urban wastewater on local ecosystems.
To work on the development of a tool enabling the measurement of blood oxygenation in the eye in vivo, using non-invasive methods. More specifically, the student involved will work on the development, implementation, and advancement of an algorithm for the measurements of oxygen saturation (through oxyhemoglobin content) in the retina.
Cyclin-dependent kinase-2 (CDK2) regulates cell cycle, whose structure and biological characteristics are well known. CRIF1 plays a regulatory role in the bone marrow microenvironment-induced leukemia cell cycle arrest through inhibiting CDK2. In this multi-disciplinary research, we will use a combined structure function study to reveal the interaction between CDK2 and CRIF1. This will facilitate the design of inhibitors for the interaction of the two important proteins, for eventual treatment of leukemia.
Online communities abound today, arising on social networking sites, on the websites of real-world communities like schools or clubs, on web discussion forums, on the discussion boards of videogames, and even on the comment pages of news sites and blogs. Some of these communities are “healthy” and foster polite discussion between respectful members, but others are “toxic” and devolve into virulent fights, trolling, cyber-bullying, fraud, or worse even, incitation to suicide, radicalization, or the sexual predation and grooming of minors.
Whether due to urbanization or climate changes, flood events have an impact on property value. Newly available geography data about flood risk zone have yet not been utilized to their full potential in Canada. This project aims to study the impact of the flood risk zone on the value of homes for Quebec City, and to identify other regions in Canada where similar conditions could affect housing value. The development of a strategy to expand the aim of research at the country-wide level will else be part of the project.
Several studies have shown that water levels of the Great Lakes would inevitably decline in a warmer climate. These studies were based on a modeling system that was not accounting for two-way exchanges of water and energy between the atmosphere and the earth surface, hence excluding key feedback mechanisms. The general objective of this project is to improve our understanding of the Great Lakes water resources and its sensitivity to climate change.
Infertility is a health issue that affects over half a million Canadian of childbearing age. Half of these cases are related to male reproductive dysfunctions. While semen analysis provides information about some causes of male infertility, about thirty percent of these cases remains unexplained. In this context, the main goal of our project is to assess the potential of target molecules, which are secreted from the internal organs of the male reproductive system into the seminal plasma, as biomarkers for the non-invasive diagnosis of infertility.
The planned research aims to validate food allergen and gluten testing tools, and their incorporation in novel quality-management systems used in food production. It will leverage existing methodologies developed by r-Biopharm Canada (r-BPC), over the past decade through its parent company.
Rio Tinto operates aluminium plants in Saguenay that are powered by their hydroelectric system. An efficient management of water available in the system is primordial to ensure energy supply to the aluminium smelters. This quantity is uncertain since the exact inflows in the reservoirs are unknown when decisions are taken. Stochastic optimization is used to make decisions under uncertainty. Mid-term optimization models determine reservoir volumes while short-term models dispatch the available water as efficiently as possible between the power plants and turbines in the system.
Machine learning is a subfield of artificial intelligence that aims at producing computing models from observations (data), with no explicit coding made by humans. Recent advances have illustrated a strong potential of machine learning, with the potential of being a disruptive technology in many domains. For the current project, we are investigating techniques for making practical machine learning.