Innovative Projects Realized

How is Comfort Related to the Distinct and Coupled Dynamic Movement of Breast Tissue?

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Enhancing Wastewater Treatment Efficiency Through the Pilot-Scale Study of Zeelung MABR Technology

A global leader in optimized resource management, Veolia focuses on water, waste, and energy management solutions that contribute to the sustainable development of communities and industries. The company’s current aim is to address the critical challenges of improving wastewater treatment efficiency, reducing energy consumption, and minimizing the environmental impact of traditional wastewater treatment methods. Through this pilot project, Veolia has deployed an innovative Zeelung Membrane Aerated Biofilm Reactor (MABR) technology at an Ontario Water Consortium (OWC) facility. The technology targets enhanced nutrient removal, operational cost reductions, and process intensification without expanding the physical footprint of existing wastewater treatment facilities. The successful implementation and scalability of MABR technology is expected to provide Veolia with a competitive advantage. This innovative approach positions Veolia at the forefront of wastewater management innovation, offering municipalities and industries globally a competitive, energy-efficient, and environmentally friendly solution. The project also aligns seamlessly with Veolia’s commitment to ecological transformation as it promises cleaner water bodies, reduces greenhouse gas emissions, and promotes circular economy principles. The anticipated success and outcomes of the project will reinforce Veolia’s market leadership and further contribute to community well-being and environmental stewardship. These efforts directly align with Veolia’s core mission and values.

BenSI24 : statut des communautés benthiques dans la Baie de Sept-Îles et lien avec les activités humaines

Afin de soutenir un développement anthropique durable des zones industrielles et portuaires, ce projet a pour objectif de poursuivre la caractérisation des écosystèmes de la Baie de Sept-Îles. En particulier, les espèces benthiques (en lien avec le sédiment) sont de bons indicateurs de l’influence des activités humaines sur les habitats, notamment grâce à un mode de vie sédentaire ou fixé qui leur permet de tenir un rôle de sentinelles face aux changements de l’environnement.
Plusieurs campagnes d’échantillonnages et analyses en laboratoire permettront de connaître les espèces présentes ainsi que les conditions physico-chimiques des sédiments dans la Baie. En combinant ces données avec celles de l’Observatoire Environnemental de la Baie de Sept-Îles, il sera possible d’évaluer la variabilité et la stabilité temporelle des écosystèmes ainsi que de cartographier l’environnement benthique. Ces résultats augmenteront les connaissances sur les écosystèmes portuaires subarctiques et de soutiendront le développement d’outils de gestion robuste, notamment des modèles prédictifs de l’état des communautés.

Validation of Muse EEG Headband for Assessment of MCI and Dementia

Mild cognitive impairment (MCI) presents a risk state for dementia and Alzheimer’s disease. Early detection of MCI is essential, allowing for improved outcomes through early lifestyle interventions. However, current methods used to detect and diagnose MCI require skilled administrators and significant time investment. As prevalence rates of MCI grow with an aging population there remains a clear need for an accessible, efficient, and objective method of detection. Electroencephalography (EEG, or “brain waves”) is sensitive to the presence of MCI, but the cost, time, and technical requirements of traditional EEG systems limit their feasibility as a diagnostic tool. Mobile EEG systems, which are quick to set up and do not require skilled technicians to operate, provide a potential solution to this problem. Previously, our lab has shown that it is possible to collect research-quality data with the low-cost Muse mobile EEG system; and more importantly that mobile EEG systems are sensitive to the same potential electrophysiological biomarkers of MCI as full-size EEG systems. We are seeking funding to validate the use of the Muse mobile EEG system as an early screening tool for MCI, making screening accessible and objective, leading to better management and outcomes for patients.

Effect of breast volume reduction surgery on pulmonary system, respiratory symptom and biomechanical responses to exercise in healthy females with breast hypertrophy

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Étude comparative de l’impact des vésicule extracellulaires relâchés par Babesia sur le système immunitaire sain ou immunosupprimé

La distribution géographique de la babésiose évolue avec le réchauffement climatique, se rapprochant tranquillement du Québec. Ce parasite transmis par les tiques est à risque d’être transféré lors de transfusions sanguines puisqu’il infecte les globules rouges. Comme les personnes recevant des transfusions sont généralement en moins bonne santé que la population générale, elles sont beaucoup plus à risque de développer des symptômes graves de la maladie, pouvant mener au décès dans près de 20% des cas. Dans ce contexte, il paraît essentiel de comprendre l’impact de babesia sur le système immunitaire des donneurs sains d’Héma Québec, mais aussi des personnes immunosupprimées qui reçoivent ces dons. Comme les globules rouges infectés par babesia produisent jusqu’à 10 fois plus de vésicules que les globules rouges sains, nous étudierons l’impact de ces particules au contenu varié sur des cellules immunitaires provenant de donneurs sain d’Héma-Québec, telles quelles ou soumises à un traitement immunosuppressant.

LEADS in a Caring Environment Framework Refresh

The intent of this action research project is to refresh the LEADS in a Caring Environment capabilities framework with the best and most current knowledge of leadership’s leading practices worldwide and in the literature, which are consonant with Canadian values, beliefs, and structure. The project will also review the current content of the Canadian LEADS in a Caring Environment capabilities framework and ensure its language reflects the research-based leadership capabilities so identified to begin ensuring that evidence becomes linked to practice and policy, and sustain and grow the existing support for and use of the newly refreshed LEADS framework by health organizations and individuals within the Canadian Health System and, where applicable, internationally. We envision three major values to the healthcare industry in Canada and, through its efforts, the broader health of the Canadian population. They are (1) a common vocabulary for describing leadership in healthcare; (2) stimulating inter-professional and inter-organizational leadership development efforts that reduce redundancies of effort and maximize financial efficiency; (3) describing a set of standards and expectations for the practice of leadership that inform accreditation processes, human resource practices (i.e., learning plans, performance accountability).

Integrating conversational AI for accurate psychiatric diagnosis in primary care

This research project will explore how advanced artificial intelligence technology, specifically large language models (LLMs), can improve the Mental Health Assessment Tool (MHAT) developed by Harrison Healthcare. MHAT is a secure online tool designed to help primary care doctors identify and diagnose mental health conditions based on structured questionnaires and clinical guidelines. The project will test whether adding LLMs to MHAT can make the tool more effective by providing more personalized, empathetic, and flexible assessments. This improvement could lead to better patient experiences and more accurate mental health diagnoses.

A doctoral intern will work with Harrison Healthcare over a 12-month period to integrate and test the enhanced MHAT. The expected benefits include reducing the time doctors spend on assessments, improving the accuracy of mental health diagnoses, and helping patients feel more heard and supported during their care. This work will also position Harrison Healthcare as a leader in digital mental health innovation while contributing to the broader field of trustworthy AI in healthcare.

Application of Artificial Intelligence (AI) for improved and sustainable swine production

Artificial Intelligence (AI) and data-driven decision-making are finding widespread applications in various sectors, and pig production is no exception. In this fast-evolving landscape, there is a need to assess which areas would benefit the most from AI and to evaluate their impact on productivity and sustainability of the Canadian swine industry. There is also a need to objectively evaluate these new tools under controlled environments, and assess whether they are practical, accurate, affordable and sustainable in commercial settings, with a focus on the use of real-time data in a production context. In this project to be conducted at Prairie Swine Centre, the intern will develop an advanced AI technology with machine learning techniques to accurately detect farrowing onset and identify farrowing distress situations, test and validate the newly developed AI algorithms in in-barn tests, and perform cost analysis and develop recommendations for commercial application of the developed technologies.

GPU-based, multiscale, high-resolution numerical simulations of Ocean Alkalinity Enhancement interventions

Ocean Alkalinity Enhancement (OAE) consists of reducing the acidity of ocean water, allowing it to absorb more CO2 from the atmosphere without making it more acidic. By taking CO2 from the atmosphere and storing it in the ocean, OAE could reduce the effect of human greenhouse gas emissions on climate change. However, measuring how much CO2 is removed by OAE interventions in the ocean remains a challenge, as the transfer of CO2 from the atmosphere to the ocean takes weeks to months, and takes place in the open ocean, where currents, waves, and eddies mix and dilute the signal. This means that placing sensors in the ocean is not enough to measure the CO2 removal, and numerical models are needed. Such models have been used in academic research for decades and can fill the gaps when sensors cannot. However, these numerical models are too slow and have too poor a resolution to measure CO2 removal from OAE interventions, and they are too expensive to use in commercial operations.

In this project, we use a new generation of high-efficiency and high-performance ocean simulation codes developed at MIT and University of Cambridge, to create a model of an OAE intervention in the Bedford Basin, Canada, that achieves unprecedented spatial resolution yet remains computationally affordable. By integrating this model with data from ocean sensors deployed in Bedford Basin, we hope to establish a new standard for the assessment of OAE intervention, and demonstrate the operational capabilities of modern ocean model codes.

The Implementation of Hot Top Variations in Industrial Scale to Reduce Macrosegregation in Large Size Ingots

This project aims to help Finkl Steel-Sorel produce larger steel ingots with more consistent chemical composition and improved mechanical properties while reducing macrosegregation. By enhancing understanding of how chemical composition and solidification interact with casting systems, like hot top configurations, the project seeks to improve the quality and uniformity of steel. It involves developing a model to predict macrosegregation patterns, evaluating how different hot top materials and designs impact solidification, and applying these new designs in industrial settings. The project will also publish findings and share results through research articles and conferences. Overall, these efforts will provide Finkl Steel-Sorel with valuable tools and data to optimize their processes and enhance product quality.

Development of a Micro-Gas to Liquid technology: Control and Optimization to Reduce Carbon Emissions and Increase Green Fuel Yield

The Micro Refinery Unit (MRU) represents a promising solution for converting shale gas, natural gas, or biogas into green synthetic fuels. Each MRU has the potential to reduce CO2 emissions by over one million kilograms and produce over 1,100 barrels of fuel annually. The project’s objective is to develop a pilot process that operates safely, maximizes liquid fuel production, and minimizes carbon emissions. This technology not only lowers transportation and pipeline costs from waste methane sources to commercial refineries due to its mobility and ease of installation in remote areas, but it also creates local job opportunities. Moreover, the unit can be replicated and deployed across Canada and globally, with scalability achieved by modulating a series of mobile units. This approach significantly contributes to Canada’s Net-Zero emissions policy.