Projets novateurs réalisés

Spatio-temporal characterisation of the cooling potential of wetlands in the Prairie Pothole Region of Canada

Wetlands offer various benefits to the environment. They help store carbon, regulate the climate, and improve water quality. Wetlands also have a cooling effect on their surroundings, which influences the local and regional climate. This cooling effect benefits the plants and animals in the area. Due to changes in how we use land and more extreme weather events, the services provided by wetlands, especially their cooling effect, have become more important. Wetlands can be used as natural strategies to adapt to and reduce the impact of climate change. This particular study focuses on understanding how wetlands in the Prairie Pothole Region in Canada contribute to local cooling. The main aims are to measure and analyze the cooling effect based on factors like wetland size, type, proximity to other land types, and various environmental conditions. The study uses satellite data and field-based measurements to compare the temperature and characteristics of wetlands compared to surrounding land-uses. The goal is to provide a detailed analysis of how wetlands cool their surroundings over time and space. This information can be valuable for land management, conservation efforts, and environmental policies. Ultimately, the study aims to contribute to our understanding of how preserving, restoring, and managing wetlands can be part of natural solutions to climate-related challenges.

AAV6.2FF production and purification from lab-scale to pre-GMP small-scale

This research project is focused on improving a potential treatment for life-threatening lung disorders through gene therapy, which involves using a genetically engineered virus (a viral vector) to deliver a healthy copy of the problematic gene to the patient’s lung cells.

Our project has three main goals. First, we want to increase the production capacity for the viral vector we use for gene therapy. To do this, we are testing different ways to grow the virus in the lab and make sure it works well in the patient’s lung cells.

Second, we want to make sure the virus we use is very pure and safe. We use advanced methods to clean the virus and make sure it’s free from any harmful substances. This is really important to make sure the treatment is safe and effective.

Finally, we want to make the whole process of making this virus follow strict rules and guidelines, like the ones used for making medicines. This will help us use the treatment in future clinical trials to test its safety and effectiveness.

Étude géotechnique de confinement & de restauration de sites miniers abandonnes avec des intrants synthétiques et naturels locaux : le cas de la mine Sedren à Haïti

Devant le problème grandissant de sites miniers abandonnés issues de l’industrie minière qui cause de l’instabilité structurale des sols et des résidus miniers; et face aux diverses possibilités d’améliorer l’impact environnemental, tant en termes de procédés nouveaux ou de technologies nouvelles qu’en termes de protection de l’environnement, un programme de confinement et de restauration de ces sites sera développé grace à la technique de stabilisation des sols et des résidus miniers. Des solutions réalistes et raisonnables de restauration des sites abandonnés (avec des intrants synthétiques locaux et naturels) seront fournies. Nous proposerons certes cette méthode utile, pertinente et contributrice permettant la restauration de ces sites dans le respect de l’environnement.

Developing a User-Friendly Portal for Building Energy Efficiency and Decarbonization Assessments

Meeting the climate change timetable of emission reductions entails significant investment in the current building stock. Knowing what should be done to improve the efficiency of and reduce emissions from these buildings needs easily accessible and user-friendly tools. We propose delivery of such a tool. We aim to produce a portal that allows a wide range of users to assess the suitability of commercial and residential buildings for energy efficiency & decarbonization interventions.

The influence of social adversity on cardiovascular aging

Cardiovascular disease (CV) is a leading global cause of death, primarily linked to aging, but influenced by various factors like inactivity, poor diet, and limited healthcare access. Social adversities, such as social isolation and challenging childhoods, also significantly impact CV health, weakening the immune system and altering genes. Understanding how social challenges affect CV health is complex, especially in humans due to overlapping risk factors. Rhesus macaques, with similar biological and social traits, offer a valuable translational model. This project at the Caribbean Primate Research Centre aims to explore the impact of social adversity on CV disease. Combining comprehensive CV health data with social metrics and physiological stress markers, the study seeks to uncover the biological mechanisms involved. By investigating the relationship between life challenges and CV disease, the research promises insights into safeguarding CV health amidst social adversity, potentially informing strategies for human health protection.

Functional analysis of subgroup IV CDPKs in soybean

Soybean stands as one of the major field crops globally. However, its production encounters annual yield losses, partially attributed to pathogenic threats. To enhance the immunity of crops such as soybean, it is crucial to comprehend the molecular mechanisms of immune signaling. Building on our prior research, we propose that specific CDPKs may represent promising targets to fortify anti-microbial immunity in soybean. To test this hypothesis, we have brought together two experts in plant immunity and crop biotechnology for a Mitacs Globalink project that involves a PhD student from Queen’s University interning at Iowa State University.

Using digital phenotyping measures to predict the symptoms and functional outcomes in first episode of psychosis

Psychotic disorders including schizophrenia are severe mental disorders affecting 2-3% of the population and
rank among the leading causes of disability worldwide. Although early intervention is effective in improving illness
outcome, a significant proportion of first-episode psychosis (FEP) patients experience persistent functional
impairment even after clinical remission. Accurate prediction of FEP patient trajectories will allow clinicians to
select better interventions at the beginning, leading to better patient outcomes and quality of life. However,
predicting FEP patient outcomes is challenging because assessments of the clinical and behavioral factors are
often based on patient self-report, which is vulnerable to recall and reporting biases. The biases can reduce the
accuracy of outcome prediction. Digital phenotyping, which refers to the use of mobile devices (e.g., smartphone,
wearable) to initiate data collection in everyday life, has great potential to address these issues. The goal of this
project is to develop and implement prediction models for symptom and functional outcomes in FEP, using both
self-reported and digital phenotyping data. If successful, the prediction models will greatly enhance clinicians’
capability of outcome prediction and decision making, leading to better patient outcome and quality of life.

Task interruption in distributed multiteams working in crisis management and emergency response

This research project is mainly concerned with maximizing distributed multiteam performance in the context of “extreme” work conditions. These conditions are those in which the human workforce is faced with safety-critical decisions, work overload, stress, complex peer interactions, uncertainty, and the prospect of serious consequences for error or delay. Fulfillment of project’s objectives will be done through the use of realistic human in-the-loop simulations reproducing public security operations, and allowing for simultaneous recoding of behaviour, decision making processes, as well as physiological responses of multiple interacting team members. This will allow the modeling of team behaviours and affects that are predictive of optimal performance in order to inform the development of intelligent technologies and adaptive training methods. This research endeavor has great potential for leading to the development of innovative solutions aiming to augment performance of the next generations of teams. Moreover, this partnership will build on its unique expertise in social, cognitive and organizational psychology. Thales’ major investment and key role in security will benefit greatly from this research project through cutting-edge knowledge of team dynamics and performance within the context of public security.

Evaluating alternatives to antibiotics in layers through coordinated in vivo experimental studies and barn-level surveillance with industry partners

The goal of this project is to bridge the gap between academic research into antibiotic alternatives and industry application. There has been extensive research into the use of alternative feed additives and water acidification to improve the ‘gut health’ of poultry; however, industry application of these findings has produced inconsistent results, resulting in a lack of confidence within the industry. Our research aims to identify fecal biomarkers that can identify whether a new product is having the
desired effect on the gut microbiome, without the need to sacrifice birds from the industry partner. Our proposal will evaluate two mechanisms of acidification (in-water and in-feed) with both a conventional and omega-3 enriched diet and examine microbial and short-chain fatty acid changes in response to treatment. Experiments will take place at the University of Guelph and build on an acidification trial already being performed with our industry partner at their facility.

Benchmarking ML based navigation systems in video games

This project develops and benchmarks novel offline training algorithms for AI navigation in gaming environments. As such, it is intended to be a self-contained project.
Traditional video game navigation heavily relies on navigation meshes (navmeshes) for pathfinding. Navmeshes offer a simplified representation of complex environments but face limitations in portraying nuanced navigation abilities, such as climbing or jumping. These abilities often necessitate additional constructs like navigation links (navlinks), which, while functional, can be unwieldy and less adaptable to dynamic game elements. Additionally, navmeshes can struggle to scale effectively in intricately detailed game environments, often requiring a compromise between accuracy and computational efficiency.
The evolution of game AI has seen a shift towards online learning methods like Reinforcement Learning (RL) and algorithms such as the Soft Actor-Critic (SAC). SAC, with its efficiency in handling continuous action spaces, has shown potential in navigating complex environments. However, the reliance on extensive simulations for training poses considerable challenges, including long iteration times and high resource demands.
In this context, offline training methods like Behavior Cloning and Goal-Conditioned Behavioral Cloning (GCBC) emerge as promising alternatives. Offline training, or batch RL, leverages pre-collected data for AI training, thereby circumventing the need for ongoing interaction with the environment. This approach significantly streamlines the development process by reducing iteration times.
Our aim is to improve AI navigation’s efficiency and effectiveness in dynamic game scenarios by leveraging offline training methods like BC and GCBC. We propose a dual-stage benchmarking process.
Initially, we’ll use a basic prototype environment in Godot for rapid algorithm iteration and refinement. Godot’s simplicity aids in early-stage algorithm tuning. Following this, we’ll escalate testing to a complex game currently under development at Ubisoft, offering a real-world application scenario. This step stress-tests the algorithms in a sophisticated, large-scale game setting, evaluating their robustness and scalability.
This two-pronged approach allows for rigorous testing from simple to complex environments, ensuring the algorithms’ applicability in diverse gaming contexts. Our research intends to significantly advance AI navigation in gaming, providing insights applicable to AI in interactive environments.

An ethnographic approach towards understanding the impact of canine-assisted support on hospital staff’s mental health

The goal of this study is to observe how a national service dog’s presence in a hospital setting impacts the mental health of various healthcare workers. The research trainee will observe the interactions between the dog and the staff and log detailed information regarding the interaction. When appropriate, the research trainee will conduct brief interviews with the staff receiving support from the dog to gain more understanding of these interactions. Additionally, the hospital has been logging the interactions between staff and the dog. The goal is to qualitatively analyze this data to complement the observational work.

Interpretation of Electrical Resistivity scans with the assistance of Machine Learning

The proposed research aims to use Machine Learning Methods to interpret data obtained during the Electrical Resistivity scans in the delineation of Fracking Sand deposits in Western Canada. Traditional exploration for sand deposits involves pricey and not always efficient auger and sonic drilling on the entire investigated Property. Currently, costs associated with those operations are the reason for importing the proppant sand from the USA rather than using our Canadian resources. The Electrical Resistivity Topography is a much more affordable field operation that can determine the near-surface lithology and location of valuable sand deposits by establishing the material’s resistivity distribution. Results obtained from ERT, combined with machine learning modelling and its predicting capabilities, would be an innovative approach for a quicker and more accessible exploration which will directly benefit the partner organization. The intern through his participation in this project will learn how to conduct mineral exploration using both the traditional exploration drilling techniques and geophysical methods. The work for the industrial partner will allow the intern to gain Canadian experience in the mineral exploration in Canada which will help him in finding employment un Canada.