Projets novateurs réalisés

Fractionation of cereal grain constituents to study interactions of bioactives with proteins

Cereal grains are essential to human diets, providing vital nutrients and serving as key sources of carbohydrates and protein. With climate change posing challenges, identifying adaptable crops is crucial for global food security. Barley and sorghum stand out due to their resilience and nutritional benefits. They contain various phytochemicals, notably phenolic compounds, which offer health-promoting effects. However, the interaction between sorghum protein and phenolics can form protein-polyphenol complexes that may reduce protein digestibility, compromising nutritional quality. Yet, these complexes could also serve as carriers for bioactive compounds. Understanding the distribution of proteins and phytochemicals, along with their interactions, is essential for enhancing protein digestibility and developing bioactive complexes. This research will fractionate sorghum and barley grains through milling and debranning, analyzing the distribution of proteins and phenolics. Extracted components will be reconstituted to study their interactions, using techniques like electrophoresis, size exclusion chromatography, and FTIR spectroscopy to evaluate changes. The impact of heat treatment on these interactions will also be assessed. Ultimately, this project aims to provide insights for plant breeders, food scientists, and producers, enhancing the nutritional quality and application of sorghum and barley in various products.

Integrating History and Philosophy of Science into Science Education: Considering Two International Contexts

This study compares Taiwanese and Canadian teachers’ perspectives on teaching the history and nature of science (NOS). We aim to understand how cultural, societal, and educational factors influence these decisions. Understanding NOS is crucial for developing scientifically literate citizens.

For this goal, we conducted a comparative analysis of science teachers’ beliefs and practices in Taiwan and Canada. Data will be collected through surveys, interviews, and classroom observations. The survey was designed to gather quantitative data on teachers’ knowledge of NOS, attitudes towards teaching NOS, and the frequency they integrate NOS into their instruction. Interviews provided qualitative data on teachers’ reasons for their decisions, as well as their perceptions of the challenges and benefits of teaching NOS. Classroom observations allowed us to examine how teachers actually implement NOS in their teaching.

This research seeks to contribute to global efforts to improve science education by identifying the factors influencing teachers’ decisions to integrate the nature of science into their curricula. Our goal is to develop more effective strategies for promoting science literacy.

Géométrie des paramètres de Langlands

Le programme Mitacs Globalink est pour moi une remarquable opportunité de travailler avec un chercheur spécialiste dans de nombreux domaines des mathématiques. En effet, dans le travail que je mène actuellement en thèse, j’ai été conduit à arpenter diverses spécialités des mathématiques. Pour obtenir des résultats plus généraux que ceux que je suis en train de rédiger, la compréhension des « faisceaux pervers » et de ses liens avec la théorie des représentations est nécessaire. Ceux-ci me permettraient d’améliorer considérablement les résultats de ma thèse. Si je suis accepté, le programme Mitacs Globalink serait le pont qui me permettra de franchir cette étape.

Autisme et vieillissement : indicateurs des indicateurs de santé et de bien-être des personnes

L’originalité de cette recherche participative intersectorielle est qu’elle vise à mieux comprendre les besoins et les réalités plurielles des personnes autistes québécoises vieillissantes (50 ans et plus). Elle permettra ainsi de combler un besoin crucial identifié par la Fédération Québécoise de l’autisme, soit celui de développer une meilleure connaissance des caractéristiques de ces personnes. À cette fin, une analyse d’informations extraites d’une banque de données sur le vieillissement, de questionnaires et d’entrevues menées auprès de 50 personnes autistes québécoises enrichira notre compréhension du phénomène en vue de diffuser des recommandations pour optimiser la qualité des soutiens et des services offerts aux personnes autistes vieillissantes. Ces connaissances mèneront à différentes activités de diffusion et de mobilisation des connaissances, mais aussi à d’autres demandes de subvention pour poursuivre la recherche auprès des proches et des professionnels qui côtoient ces personnes.

Solutions technologiques pour augmenter l’efficacité des engrais phosphatés dans les sols hautement fixateurs en phosphore: organo-minéraux et biostimulants.

L’objectif principal de cette recherche est de maximiser les rendements des cultures tout en minimisant les impacts environnementaux. Les sous-objectifs incluront l’analyse de différentes formulations d’engrais organo-minéraux, l’évaluation de l’impact des biostimulants sur le rendement de la culture et son niveau de prélèvement du phosphore, ainsi que l’exploration des interactions avec les autres éléments fertilisants essentiels tels que N, K, Ca, Mg et oligoéléments. Les questions de recherche porteront sur la manière dont ces formulations influencent la disponibilité du phosphore et son assimilation par les plantes, avec l’hypothèse que les engrais organo-minéraux seront plus efficaces que les engrais chimiques traditionnels, et que leur association avec des biostimulants produira un effet plus synergique. Ce stage s’inscrit dans un projet plus large visant à développer des solutions durables pour l’amélioration de la gestion du phosphore dans les sols agricoles au Canada, contribuant ainsi à la mise en place de pratiques agricoles plus durables et rentables.

Misty plasma as a pathway to nano-structured materials

Droplet-containing plasma discharges (so-called “misty plasmas”) provide an exciting new route to the deposition of technologically important nano-structured and nano-composite thin films. These films have many potential applications in important technology sectors. The aim of this project is to study the plasma response to the injection of nanoparticle-containing microdroplets, and to correlate the evolution of the plasma discharge parameters with the structure of the deposited nanocomposites, in order to ultimately be able to optimize nanocomposite film deposition. Plasma-droplet interactions can have a significant influence on the evolution of plasma parameters (e.g. the electron and ion density, electron temperature, plasma composition, and plasma transport parameters such as diffusion constants) and hence on the plasma-assisted film deposition process. In this project, we will concentrate on the evolution of a capacitively-coupled argon discharge in which droplets of different liquids are injected. Because of the growing importance of nanocomposite films for sensor, quantum, energy, and biomedical applications, developing a detailed understanding of misty plasmas as a route to nanocomposite thin film deposition is of high technological importance.

Predictive Modelling and Functional Validation Of Long non-coding RNAs In The Heart

This research proposal aims to employ cutting-edge machine-learning tools to classify the a group of RNA molecules in heart cells and thereby unravel their function

La politique d’influence des entités supranationales : corrélation et délégation des capacités d’attraction des États membres au sein de l’Union européenne

Le projet de recherche se propose d’analyser les éléments qui constituent l’attractivité de l’Union européenne à l’international et surtout dans les États post-soviétiques que sont l’Ukraine, la Moldavie et la Géorgie. Il permettra de comprendre quels sont les acteurs qui influencent le plus l’Union européenne et la façonnent au quotidien. Il permettra d’évaluer les limites qu’ils ont sur le plan national et qu’ils peuvent compenser en travaillant en équipe avec les autres États membres. Cet échange permettra de lancer une réflexion sur les actions à entreprendre pour renforcer l’attractivité de l’Union et de savoir sur quels points celle-ci ne peut pas se substituer aux pays qui la composent.

LegiSimple – Enhancing Legal Research Efficiency Through AI-Powered Case Law Search

LegiSimple is an innovative project designed to simplify the legal process for lawyers, notaries, and paralegals in Quebec and Canada. The project leverages advanced AI to drastically reduce the time required to analyze, interpret, review, find jurisprudence, and refer to case law. This technology enables legal professionals to focus more on strategic aspects of their business rather than being bogged down by time-consuming tasks.

The primary goal of the LegiSimple project is to enhance the efficiency and productivity of legal professionals. By streamlining legal processes, LegiSimple aims to ensure that lawyers, notaries, and paralegals can perform their duties more effectively, ultimately leading to increased satisfaction and perceived value among users.

Interns working on the LegiSimple project will be responsible for helping to manage the code base, ensuring that all systems run smoothly. They will also contribute ideas to improve the product and the company, helping to drive innovation and efficiency within NeoGPT Technologies.

LegiSimple is primarily a process innovation project. It focuses on improving the efficiency and effectiveness of legal processes through the use of advanced AI technology. The project will employ a combination of agile development methodologies and user-centered design techniques. This includes regular iterations and feedback loops with end users to ensure that the product meets their needs and expectations. Data analysis and machine learning techniques will be extensively used to refine and enhance the AI models that power LegiSimple.

Advanced electrochemical analysis tools and methodologies

Pulsenics is a leading technology company specializing in advanced electrochemical analysis tools and methodologies. Their primary focus is on developing cutting-edge solutions for monitoring and optimizing electrochemical systems, including batteries, electrolyzers, and fuel cells. The company’s flagship technology, Electrochemical Impedance Spectroscopy (EIS), is utilized to assess the performance, health, and efficiency of various electrochemical devices without causing damage. Pulsenics aims to enhance the reliability and longevity of these systems by providing real-time data and insights into their internal processes.

Pulsenics is facing the challenge of improving the accuracy and reliability of battery stack performance evaluations. Traditional EIS methods, while effective, are time-consuming and can be limited by hardware constraints, such as power limitations and signal distortions. There is a need to optimize EIS protocols to provide faster, more detailed, and more reliable data, which will help in the early detection of issues and the enhancement of battery performance. The priority is to develop an advanced EIS protocol that leverages multisine signals and integrates machine learning techniques to enhance the resolution and reliability of battery performance data. This improved protocol should address hardware constraints and be validated through both simulation and real-world testing. This project will significantly advance Pulsenics’ capabilities

Enhancing Knowledge Self-Awareness in Large Language Models through Self-Explanation and Self-Reflection

Large language models (LLMs) are becoming ubiquitous given their ability to excel at many tasks. However, there has yet to emerge a comprehensive understanding of their internal mechanisms, in particular with regards to how LLMs use the knowledge it possesses. Previous works have suggested that despite LLMs possessing knowledge, they can often be incapable of using it directly. However, additional works have also proposed the use of self-explanations as a way to induce LLMs to rationalize and explain their behaviour, enabling for the analysis of LLMs even without explicit access or understanding of their internal dynamics. For this end, self-explanations also provide an avenue to better understand whether LLMs understand the scope of their knowledge and if they can use this information to achieve factually correct responses, even if such information is not directly known. Using LLMs within self-reflective loops, we can uncover how LLMs understand the information it has been trained on, how it accesses this information for downstream purposes as well as whether or not it can understand when necessary information is missing, providing an improved understanding of LLMs and better utilizing them in more reliable ways in the future.

Optimizing Anaerobic Digestion of Food Waste

In Canada every year, approximately 20% of the food produced becomes waste and food waste is Canada’s largest residual municipal solid waste category. Despite diversion strategies like composting, 28% of residential and 25% of industrial, commercial, and institutional solid waste is comprised of food waste and landfilled or incinerated. Food waste can be converted to valuable resources, for example anaerobic digestion relies on the activity of diverse groups of microbes to degrade food waste and convert it to biogas, which can be used in a similar manner to natural gas, and fertilizers useful for crop production. Although a useful technology, improvements to the anaerobic digestion process is possible by gaining a greater understanding of the relationship between various food waste feedstocks and the metabolic activity of different microbial groups. This project will analyze production of markers of microbial metabolism, lactic acid and volatile fatty acids, in response to different types of food waste. A greater understanding of the complex biological and chemical reactions occurring in anerobic digesters will lead to greater capacity to treat food waste and to increase the value of the biogas and fertilizer products via increased yields.