Innovative Projects Realized

Quantification de l’endommagement dû à la méthode de perçage

Les composites et le titane sont de plus en plus utilisés en aéronautique, mais sont difficiles à percer. Le perçage des deux matériaux dans une seule opération représente un défi supplémentaire puisque la méthode et les paramètres idéaux diffèrent. L’identification et la quantification d’un critère d’endommagement avant des essais en tension percée et en tension assemblée permet de relier le comportement en fatigue avec la méthode de perçage du trou. Un modèle mathématique pourra par la suite relié l’endommagement initial à la durée de vie de chaque échantillon et fournir un estimé de la propagation de l’endommagement pendant l’essais.

Machine learning applications to digital rock mechanics data

In rock engineering practice there is often insufficient time, schedule, and computational/expert resources to investigate complex rock mass phenomena in detail. The large amount of multivariate data that characterizes complex rock mass behaviour creates the ideal conditions to use machine learning. Machine learning allows for the use of all relevant data and can inform the design and maintenance of underground excavations such as mines, tunnels, hydropower assets, and utilities.
The purpose of this research is to advance the applications of machine learning in a way that is accessible to practicing rock engineers. To accomplish this, a framework will be developed comprising the acquisition of reliable digital rock mass data and subsequently using it to develop machine learning for forecasting excavation behaviour. The industry partner, RockMass Technologies, is a global leader in the field of digital geotechnical mapping. Currently, RockMass does not offer any machine learning capabilities as part of its product offerings. By participating in this project, RockMass will benefit in-kind from the research advancements made with respect to use of its data in downstream machine learning applications, placing itself at the forefront of machine learning innovation in rock engineering.

Embedding Social and Health Equity into Greenspace Programs and Policies

Experiencing and accessing nature has been shown to promote individual and communal physical and mental well-being. However, these benefits are not universally enjoyed due to social inequities. There are limited tools and strategies to ensure that greenspace programs and policies have positive social and health equity impacts.

During the COVID-19 pandemic, we saw the confluence of systemic issues around health equity, greenspaces in cities and social injustice. As part of the need for equitable cities where people and nature thrive synergistically, this project will: 1) develop an equity-informed impact measurement process for Park People’s Sparking Change Toronto program; 2) engage subject matter experts across disciplines to identify key strategies for embedding equity in greenspace initiatives; and 3) host a series of “solutions workshops” with key stakeholders to identify significant principles, challenges, and guidelines. This work will result in a framework and toolkit for embedding social and health equity into greenspace programs and policies, with the aim of supporting stakeholders (community groups, professionals, and non-governmental organizations) to create more equitable greenspaces.

Evaluating the effect of abrasive waterjet machining on 3D printed composites for repair applications

The research project aims to evaluate the potential of using abrasive waterjet machining and additive manufacturing in composite repair as a sustainable, circular economic strategy. The study will investigate the effectiveness of abrasive waterjet machining on additively manufactured composite specimens, assess the quality of machined surfaces, and simulate composite repair scenarios in a laboratory setting. The goal is to determine if this non-conventional technique can enable more sustainable and circular economic practices in composite repair when coupled with additive manufacturing.

Gestion innovante et durable des eaux souterraines à Saint-Hippolyte dans un contexte de développement résidentiel

La ressource en eau souterraine est la source d’alimentation en eau potable de la Municipalité de Saint-Hippolyte (QC). Le développement du territoire ajoute une pression additionnelle à la ressource en eau souterraine et Saint-Hyppolite vise une gestion durable de cette ressource. Le projet vise à créer un observatoire de la ressource en eau souterraine dans la Municipalité de Saint-Hippolyte afin d’améliorer la gestion de cette ressource. Un système de suivi sera implanté et des modèles seront développés pour mieux comprendre les effets du développement résidentiel sur les eaux souterraines. Les résultats du projet permettront d’identifier en temps réel des domaines dans lesquels des progrès doivent être réalisés et ceux qui exigent une attention urgente, et d’examiner les différents aspects pour une gestion participative des ressources en eau. Le projet servira de modèle de gestion durable des eaux souterraines au Québec.

Development of novel chemical probes and SARS-CoV-2 antiviral therapeutics through engineered HAI-2 protein inhibitors of TMPRSS proteases

Respiratory viruses exploit the biological activity of human proteins present at the surface of airway cells to allow viruses to penetrate that physical barrier and subsequently replicate in infected cells. It has been established that a family of human proteins, the type 2 transmembrane serine proteases, are directly responsible for this viral entry, but they have been challenging to develop drugs against because they have been unable to be studied in isolation. Our group developed the leading strategy to isolate and study one of these proteins, transmembrane protease, serine-2 (TMPRSS2), which is exploited by coronaviruses (including SARS-CoV-2) and Influenza A/B viruses, for entry of the airways. Our access to TMPRSS2 enabled us to determine its 3D molecular structure for the first time, an important advancement that paves the way for the development of highly specific TMPRSS2 drugs that could block viral entry. Importantly, drugs blocking TMPRSS2 may be insensitive to emerging virus mutations because TMPRSS2 is such an important human protein for infection. By modifying the protein known to regulate TMPRSS2 activity, HAI-2, we engineered highly effective TMPRSS2 inhibitors.

An integrated and adaptive study examining central and peripheral mechanisms of chronic pain in knee osteoarthritis patients

It has been estimated that 300 million people worldwide have osteoarthritis (OA) and this has increased by 97% over the past 25 years. The pain and loss of mobility experienced by people with knee OA can seriously reduce quality of life, while pain management causes significant healthcare spending. Unfortunately, the pain associated with OA is complex and difficult to treat. One promising theory to explain the reason why many people with OA and chronic pain, called nociplastic pain, focuses on changes in the brain and spinal cord that lead to painful hypersensitivity to normally painful and non-painful sensations. Our research study plans to use advanced magnetic resonance imaging techniques and novel analysis methods to determine if specific parts of the brain are responsible for nociplastic pain. We will include 99 knee OA patients, some without pain and others with chronic pain, to explore the group differences at baseline and after a cold sensation. It is expected that knee OA patients who experience chronic pain will exhibit dysfunction in parts of their brain that is not present in patients who do not experience chronic pain.

COSMIC – Software Functional Sizing – AI-NFR-DevOps

Theoretically sound and industry-robust software measures are necessary in industry and research. Functional sizing measures of software, such as COSMIC Function Points – ISO 19761 – are useful for the quantitative planning, monitoring, control, and objective assessment of software projects and organizations. Through this project, the COSMIC Group will adapt this international measurement method to Artificial Intelligence applications, the sizing of non-functional requirements (NFR), and integrates its usage into the measurement of DevOps products and porfolios. This project also includes the design of related measurement case studies to serve as reference material for training and for facilitating the accuracy and consistency of measurements in industry and research projects.

Address key problems in therapeutic interventions using nanomedicine

Ever-increasing complexity of high morbidity rate diseases including infections, cancer, atherosclerosis, has posed significant challenges in delivering active pharmaceutical agents at their intended targets. Polymeric soft nanoparticles based therapeutics have provided an advantageous platform, and have provoked the design of tailor-made nanoarchitectures that can load, target and deliver with high efficiency. Using synthetically articulated stimuli responsive macromolecules, we are designing smart nanocarriers that can both help overcome physicochemical obstacles; and deliver sufficient dosage of drug molecules in response to endogenous and exogenous triggers. The goal in this project will be to design and develop an optimized drug delivery platform that could sense multifold aberrations in the physiological environment of disease sites and respond synchronously, for sustained drug delivery, nanoparticle disassembly, and its safe clearance. The purpose will be to simplify the formulation design strategy and remove complexities of synthetic build-up of macromolecular precursors; impart sensitivities to nanoparticles through novel functional group(s); and help expedite clinical therapeutic interventions of lipophilic drugs.

Examining the Efficacy of Equine Assisted Learning for Public Safety Personnel with PTSD

Public safety personnel (PSP) (e.g., police, paramedics) ensure the safety of our communities and are at risk of experiencing traumatic events. In a recent study, 44% of surveyed PSPs screened positive for a mental health condition, such as post-traumatic stress disorder (PTSD). We must understand the impact of PTSD on PSP and how to treat it so we can promote PSP health to keep Canadian communities safe. Equine Assisted Learning (EAL) is an intervention that involves unmounted interactions with a horse with the guidance of an equine specialist. Recent research conducted with military Veterans with PTSD shows that EAL might be effective in reducing PTSD symptoms but no one has tested EAL with PSP who have PTSD. We will investigate the effectiveness of EAL in reducing PTSD symptoms among PSP with PTSD by conducting a randomized clinical trial where PSP participants are assigned to one of two groups: one that receives EAL treatment and one that does not. We will compare these two groups to see whether they differ in PTSD symptom severity.

Workforce retention strategies for RPNs within the home and community health care sector

The current nursing shortage in the home and community care (HCC) sector is cause for concern. The demand for home care services is greater than what organizations can provide, especially during the COVID-19 pandemic, leading to high turnover rates. This study will explore the personal and professional resilience of RPNs working in the HCC sector and the role of stakeholders in creating an environment that supports their resilience.
Findings from this study will be used to provide evidence for stakeholders in developing and implementing strategies to increase recruitment-retention and resilience of RPNs in the HCC sector.

Distributed Extremum Seeking Control Using Observer-based Methods

In this project, we propose a new technique for controlling the formation of high-altitude balloons. Instead of using traditional high-pass filters, we suggest using high-gain observers to improve the accuracy and effectiveness of extremum-seeking control. Our research on this multi-agent approach aligns with the main objectives of Stratotegic Inc, which focus on the research and development of controlling aerospace systems.