Projets novateurs réalisés

Development of operations, retail and online strategy for growing business needs

Developing an online and e-commerce strategy to meet increased business demands requires a structured approach by focusing on enhancing customer experience, optimizing digital presence, and streamlining operations. By implementing an e-commerce strategy, we can drive sales, enhance brand loyalty, and successfully move our business from a 7-month seasonal business to 12 months of the year, through e-commerce. We would also like to take an educational approach to the public on our industry and its function. Our intern has shifted her focus on studies to Environmental studies, and we would like to implement learnings to both our commercial and direct-to consumer parts of our business.

Race and Representation in Nova Scotia’s Criminal Justice System: Analyzing the Experiences of People of African Descent in the Province’s Courts and Correctional Facilities

This research project will contribute to the literature on Canada’s criminal justice system by using de-identified race-based data from Nova Scotia’s Department of Justice to understand Black people’s experiences in the province’s correctional facilities. It addresses two main problems: Gaps in knowledge about Black people’s experiences in provincial correctional facilities, and the need to improve correctional practices in Nova Scotia. Alongside filling important gaps in race-based data, this project will also contribute to improvements in correctional practices in Nova Scotia by engaging with formerly incarcerated individuals to understand their experiences and needs while incarcerated, and their reintegration needs once they have left prison.

The purpose of this research project is to understand Black people’s experiences in Nova Scotia’s provincial correctional facilities, to facilitate advocacy efforts and contribute to the literature on race-based data. In this research project, data from Nova Scotia’s Department of Justice (DOJ) on Black people’s experiences within provincial correctional facilities will be analyzed to identify any systemic or persistent differences in treatment or outcomes, in comparison to other racial groups. In addition, building on the quantitative findings, the project will undertake qualitative research that will involve interviewing Black people who have been incarcerated within provincial correctional facilities to determine whether the findings reflect their experiences, and to better understand the services and supports they need to better reintegrate into their communities.

Decoding coded language in video-games communications

Hate speech manifests in various forms, ranging from overt slurs to more subtle, coded messages known as dogwhistles. These dogwhistles allow speakers to convey apparently innocuous messages that include an additional controversial layer only recognizable to a specific subgroup. This duality enables plausible deniability for the speaker while reinforcing group identity among those who understand the hidden message. Computational methods have emerged as a promising approach to detect these subtle cues. By leveraging deep contextual representations and network-based analysis, researchers can uncover patterns and associations within language that hint at underlying negative connotations. For instance, certain words may not inherently carry hateful meanings but are associated with negativity due to their usage in specific contexts. The integration of transformer-based architectures with social network signals further enhances the detection of covert hate speech, enabling systems to distinguish it from merely offensive language. These multifaceted approaches are essential for developing robust moderation systems capable of addressing toxicity. Overall, detecting hate speech requires a comprehensive understanding of linguistic nuances and social contexts, combined with advanced computational techniques like deep learning and network analysis. As such, our integrated approach will effectively tackle the challenge of identifying both overt and subtle forms of hate speech.

Development and Assessment various Materials for the Adsorption of Ethylene for Prolonging Vegetables and Fruits Shelf-life

Preserving fruits and vegetables represents a significant global challenge due to their high susceptibility to spoilage driven by the phytohormone ethylene. Ethylene accelerates ripening, leading to a rapid decline in the quality and shelf life of produce, ultimately causing substantial postharvest losses. Currently, traditional approaches, such as potassium permanganate, are widely used for ethylene absorption and reaction. However, several limitations exist, including concerns about toxicity and environmental hazards associated with potassium permanganate. This project aims to evaluate the performance of existing ethylene adsorbents, such as the zeolite family, while introducing novel adsorbents based on the emerging and highly efficient class of Metal-Organic Frameworks (MOFs). Zeolites, renowned for their high adsorption capacity and favorable surface properties, have been applied in ethylene control. Nevertheless, further optimization is required to maximize their efficiency. MOFs, on the other hand, with their precisely engineered structures, exceptional chemical stability, and tunable properties, emerge as a groundbreaking alternative for ethylene adsorption. By focusing on the development of advanced adsorbents, this research seeks to enhance the performance of zeolites by properly functionalizing them and designing novel MOFs with superior efficacy. The ultimate objective is to significantly extend the shelf life of fruits and vegetables, reduce food waste, and promote sustainability within the food supply chain. Experimental studies will be conducted with a model produce such as tomatoes, to assess the efficacy of the existing zeolitic, modified zeolitic, and MOF adsorbents on the shelf-life of the selected produce. These efforts align closely with the mission of Quiper Canada Inc. committed to developing innovation in food preservation, offering substantial benefits to producers, retailers, and consumers across Canada.

Development of a novel bio-adsorbent filtration system derived from renewable bioresources to capture particulate matter emissions from wood-based furnaces

This project aims to reduce particulate emissions below 2.5 g/h from wood furnaces to comply with EPA and CSA standards. We will develop an innovative adsorbent column to capture particulate emissions. We will investigate the effects of different adsorbents and their blending ratios on capturing particulate emissions.

A Multidisciplinary Quantum-Based Clinical Decision Support System to Advance Medical Diagnostics and Treatment

Complex diseases like neurological disorders, rare pediatric conditions, chronic kidney diseases, sepsis, and complications from maxillofacial surgery are putting pressure on the global healthcare system. As the volume of medical data grows, ranging from imaging and physiological signals to electronic health records, there is an increasing need for more precise and personalized approaches to diagnosis and treatment. Traditional methods often fall short in handling this complexity, but quantum computing offers a promising solution. With its ability to perform large-scale, parallel computations using principles like superposition and entanglement, it opens new possibilities for tackling these medical challenges.

This project aims to revolutionize clinical decision support systems by leveraging advanced quantum techniques. We will integrate quantum machine learning (QML) methods, including quantum decision fusion, fuzzy clustering, reinforcement learning, and Siamese neural networks, to improve diagnostic accuracy, optimize treatments, and ultimately enhance patient outcomes. Our focus spans four critical medical areas: pediatrics, nephrology, neurology-sepsis, and maxillofacial surgery.

By addressing these pressing clinical challenges, our work not only pushes the limits of medical AI but also brings quantum technologies closer to real-world healthcare applications.

Welfare Governance: Regulating the Rise of Private Credit in Social Welfare Services

Around the world, private equity funds and other investors have acquired social welfare service providers such as hospitals, physician groups, colleges, and childcare centres. While private equity funds bring significant financing to these sectors, private equity ownership is associated with reduced service quality, higher costs, and deteriorating working conditions for service providers—especially where private equity has a substantial share of a local market. This project examines the legal and regulatory reforms in social policy and financial regulation that have permitted and incentivized the expansion of investor-backed childcare services. Drawing on the primary legal regimes regulating social services, it analyzes the interrelationships between welfare, labour, and competition laws and aims to propose a legal framework to regulate private financing in social services.

Focusing on childcare as a key welfare institution, the project compares the legal frameworks in Canada, France, and the United States. In the U.S., childcare financing and delivery is largely market-based, while France’s traditionally public-supported childcare sector has seen the recent extensive expansion of for-profit private service providers. The differing welfare market structures arise from the contrasting welfare financing and regulation. Both countries offer lessons for Canada, where the roll-out of increased government financing for childcare services is underway.

A Satisficing Approach to Generative AI-Driven Design of Nanoparticle-Infused Structural Materials: Integrating Mixture-of-Experts for Efficient Optimization

This project aims to revolutionize the design of nanoparticle-infused structural materials by combining Generative AI with a ‘satisficing’ approach—prioritizing practical, manufacturable solutions over purely mathematical optimization. Instead of searching for a single perfect design, our method will generate a variety of high-performing, user-acceptable, and manufacturable structures using AI-driven models. By integrating a Mixture-of-Experts (MoE) framework, which leverages specialized sub-models for different performance criteria, the project will enhance design efficiency while reducing computational costs. The collaboration between Canadian and international researchers will strengthen expertise in AI-driven materials engineering, benefiting both institutions through knowledge exchange, student training, and advancements in next-generation manufacturing technologies.

Caractérisation des bactéries impliquées dans les parodontites des femmes gestantes et son influence sur la survenue de la prématurité

La prématurité constitue un réel problème de santé publique mondiale car approximativement 13,4 millions de nouveau-nés par an naissent dans cet état dans le monde, déterminant ainsi un taux de prématurité estimé à 11%. Cependant, la grande part de ces naissances revient aux pays en voie de développement, avec plus de 43% des cas. Bien que les suivis et les traitements de complications chez les femmes soient grandement améliorés, plus de 25% de cas de prématurité demeure inconnu.
L’état de la santé buccale maternelle peur être un facteur de risque de prématurité. Dans cette étude, nous tentons d’établir si un lien d’association existe entre la santé buccale maternelle et le risque d’accoucher prématurément en explorant la flore bactérienne chez les femmes en gestation.

Development of Multi-Frequency Ultrasound Localization Microscopy (ULM) Techniques on the Vevo F2 System and VADA Platform

In this project the interns will work with a leading ultrasound imaging company, FUJIFILM VisualSonics Inc, developing advanced ultrasound beamforming techniques (the process by which images are formed) using specialized ultrasound instrumentation (the F2 system using the VADA platform) that will produce high resolution images of blood vessels in tissues. These advanced beamforming techniques (based on a new method called ultrasound localization microscopy) will potentially be incorporated in subsequent versions of their device, further establishing the company as world leaders at the cutting edge of technology development.

Characterizing the relationship between infrared thermography of bony prominences occluded by lower limb orthopedic casts and local skin integrity in hospitalized children with disabilities

This project aims to improve the early detection of pressure injuries (PIs) in children with disabilities who wear casts for long periods. PIs occur when continuous pressure over bony areas damages the skin, leading to pain, infections, and longer hospital stays. Currently, it is difficult to monitor the skin under a cast because it cannot be seen or touched. This study will use thermal imaging to measure temperature changes through the cast material, which may indicate early signs of skin damage. By analyzing these thermal patterns and developing machine learning models, the project seeks to improve how hospital staff monitor and protect the skin health of casted children. This approach could enhance patient care and reduce complications, benefiting both children and the healthcare system.

A Novel Application of Plastination Technique for Transforming PMMA waste and Cotton Textile Waste into Functionality-enhanced Fabric Composites

Lululemon is a global leader in athletic apparel industry, focusing on high-quality, functional, and sustainable textiles. With a commitment to environmental responsibility, the partner is targeting 75% sustainable materials by 2025 and aims to source e.g. all cotton from sustainable sources. This joint project aligns with their sustainability mission by addressing two critical challenges: the excessive use of virgin fibers and the environmental impact of textile waste. Specifically, in this MITACS research, we aim to re-purpose a post-production PMMA waste along with recycled cotton waste into a novel high-performance composite, using a custom plastination technique. Once optimized, this innovative approach is expected to create durable, eco-friendly textiles with enhanced mechanical properties potentially suitable for multiple re-purposed applications such as apparel (e.g. outerwear) and accessories (e.g. bags). The anticipated social and economic benefits include reduced dependence on virgin fibres, minimized textile waste, and a scalable solution for using recycled materials in both textile (cotton) and plastic (PMMA) industries. By extending products life cycles and creating a circular economy model, this project offers a new pathway for Lululemon to integrate sustainable material innovation that meets high-performance standards, aligning with globally increasing consumer demands for environmentally responsible products.