Comparative analysis of the lettuce root microbiome under soil and hydroponic growing conditions

A comparative analysis of the root microbiomes of lettuce grown in soil to lettuce grown in hydroponic systems. The microbial community composition for each root sample will be identified using DNA sequencing and compared to determine differences between each sample. This information will help Ceragen improve their ability to identify plant growth promoting microbes that […]

Read More
Polysaccharide (PS) materials for managing cholesterol and diet–induced obesity (DIO)

High plasma cholesterol (hypercholesterolemia) is a potential consequence of obesity that is becoming a major public health challenge. Excess caloric intake without a corresponding increase in energy expenditure is believed to be the major contributing factor to weight gain among Canadians leading to hypercholesterolemia. This ‘silent killer’, hypercholesterolemia is characterized by increased low-density lipoprotein cholesterol […]

Read More
Non-invasive measurement of blood pressure with voice data

In North America, nearly half of adults experience chronically elevated blood pressure (BP), posing heightened risks of cardiovascular disease and kidney failure. Unfortunately, only half of those with elevated BP, or hypertension, are cognizant of their condition. The overarching goal of this project is to identify ways to monitor blood pressure with low cost, non-invasive […]

Read More
Innovative Patient Monitoring System: Integrating Affordable Load Sensors and Multi-Modal AI for Enhanced Care and Safety

Recent statistics in Canada highlight a growing aging population, with 18.8% aged 65 and older, projected to increase by 6.2% by 2036. Falls and pressure injuries (PI) are major concerns for seniors and hospitalized patients, contributing significantly to hospitalizations. About 20-30% of seniors experience falls annually, leading to 85% of senior injury-related hospitalizations. While various […]

Read More
Predicting Supercapacitor Performance Using Reinforcement Learning Methodology

In this proposal, intern will be tasked with reinforcement learning algorithm to refine the process of material selection. This method of machine learning is designed to iteratively enhance decision-making, ensuring the most effective materials are identified for various applications. The focus will be on aligning the materials’ performance characteristics with their intended use. As a […]

Read More
Design of an adaptable, customizable, and multi-user microfluidic process platform for fluidic applications

This NSERC Alliance MITACS grant brings together a world-renowned semiconductor micromanufacturing industrial leader Teledyne Micralyne, and a microfluidic device design and process development researcher to develop wafer-scale and versatile microfluidic fabrication processes adaptable to major microfluidic applications. It will provide a unique research and training opportunity for HQPs to enhance their professional and technical skills […]

Read More
Network Facility Location for Eco- and Cost-Efficient Chemical Supply Depots Supporting Municipal and Industrial Water Treatment

USP currently works with storage facilities in a manner akin to a broker network, relying on numerous third-party locations for freight-in and warehousing. USP is considering a strategic revision of its supply chain dynamics, with the intention of optimizing their current supply network in an effort to become more sustainable and cost effective. USP is […]

Read More
Reinforcement-Based Large Language Models to Enhance Energy Management Platform

Reinforcement Learning in Large Language Models (RL-LLM) is revolutionizing how AI understands and responds to human language, improving virtual assistants in various fields. It teaches models to follow instructions effectively, even with vague prompts, reducing inappropriate responses and false information. RL-LLM’s application extends to sectors like healthcare, finance, and online shopping, enhancing product suggestions and […]

Read More
Query Optimization using Machine and Deep Learning

In this project we will investigate and develop novel techniques that employ Machine Learning (ML) and Deep Learning (DL) for the optimal execution of queries in a relational DBMS. The research will be conducted with close collaboration with the team of IBM that develops Db2, the well-known relational DBMS of IBM. The goal is to […]

Read More
Evaluation of Equine Omega Complete in horses with IL-1 induced articular inflammation

Lameness (abnormal gait) associated with osteoarthritis (OA) represents a major cause of economic loss, as well as reduced performance and welfare in many veterinary species, including racehorses. Whilst administration of anti-inflammatory drugs can afford good pain management, they do not address the underlying degenerative condition and may accelerate cartilage breakdown over time. For this reason, […]

Read More