Innovative Projects Realized

Building a soil organic carbon field sampling protocol for the Wabanaki region

One of the greatest challenges in monetizing forest carbon for climate change mitigation (i.e. carbon offsets) is in understanding the different carbon “pools”, and being able to accurately quantify them. The soil carbon pool is perhaps the greatest pool of forest carbon, and poorly understood. The objective of this project is to design a forest soil organic carbon sampling procedure that will be accurate, easy to use in the field, and efficient. The intern will undertake a review of academic literature and other draft forest soil organic carbon (SOC) sampling procedures to build a procedure for the Wabanaki forest region (the Maritimes provinces) of Canada. The intern and partner will ensure that the procedure yields high-quality data while also being efficient and practical to implement in the field. The benefit to the partner organization will be a SOC sampling procedure that is immediately usable through its programs.

UranOS: a Cloud-based Resource Management Framework for High Dimensionality Search Optimization

Multidisciplinary automated design-optimization (MDO) is a rapidly growing field of interest in sectors as diverse as architecture, engineering, science, and more. Often the computational cost of doing such optimization can be staggeringly high, requiring hundreds of computers connected through high-performance networks with complex custom designed software to support it. To address these problems, we propose to design, implement and deploy a novel Cloud resource management framework, UranOS, intended for use as a scalable and high resource efficiency resource management platform for MDO applications. UranOS is a lightweight and portable virtualization solution including algorithms, high level languages and tools for performance modeling and efficient resource allocation. Our platform will automatically provide customers with performance optimizations towards improving end-to-end Quality of Service compliance for MDO applications. Also, our industry partner will further benefit from lower operational costs as a result of high resource usage efficiency.

Uncovering Information Warfare: Detecting Russian Propaganda on Social Media

This research project aims to investigate the role of social media in information warfare, focusing on Russian propaganda campaigns related to the war in Ukraine. By collecting and analyzing tweets, the project will identify narratives and strategies used in these campaigns. The data will be classified and employed to train a machine learning model capable of detecting Russian propaganda on social media. The expected outcomes include a better understanding of the role social media plays in modern warfare and the development of tools to counteract propaganda campaigns and prevent the spread of false information.

Surveying sexual and reproductive health outcomes in New Brunswick prisons

There is little existing information about sexual and reproductive health outcomes and experiences among incarcerated women and gender diverse people in Canada. Women are the fastest growing population in prisons in Canada; most incarcerated women are of “reproductive age”, but there is no systematic data collection of sexual and reproductive health outcomes among incarcerated people. Access to sexual and reproductive care for incarcerated people is under-researched and critical to address structural, gender-, and race-based reproductive health inequities in Canada. Building on evidence of unmet reproductive health needs, this study will examine the sexual and reproductive health outcomes of people who are experiencing incarceration in New Brunswick (NB). To measure sexual and reproductive health outcomes among incarcerated people in provincial prisons for women, we have adapted an existing survey instrument guided by our SGBA+ approach, reproductive justice, and abolition theories. The instrument will be piloted in collaboration with the research team and lived experience experts. Questions will explore demographic information, sexual and reproductive health service needs, access, and outcomes.

Probiotics in endurance exercise performance

The gut microbiota comprises all bacteria inhabiting the intestines and has been shown to play a significant role in both health and disease. Although previously overlooked, new research shows that both the gut microbiota
and their metabolites may influence exercise performance. Probiotic supplementation has been shown to have a small but significant positive effect on endurance exercise performance, however, this research area is still in its
infancy and much about this relationship—including the underlying mechanisms responsible for the performance enhancing effects of probiotics—remains unknown. Therefore, this project aims to better understand how
probiotics affect endurance performance by employing a 4-wek probiotic intervention in trained cyclists. This research will contribute to the growing area of gut microbiota and exercise science research and may help lay
the groundwork for the future development of probiotic supplements targeting exercise performance.

Méthode d’analyse cinématique dans le domaine des sports aériens

Dans les sports aériens (parachutisme, parapente, bodyflight, gymnastique, etc.) l’obtention de données télémétriques fiables est nécessaire à l’amélioration du processus d’entraînement à tous les niveaux, des sportifs débutants aux champions du monde. La télémétrie peut être utilisée pour l’évaluation de figures acrobatique, la performance, ainsi que pour améliorer la sécurité des sports aériens. À ce jour, l’évaluation des données relatives aux sports aériens reste très qualitative, en raison des difficultés qui découlent des conditions dans lesquelles ces sports sont pratiqués. Des systèmes de mesure inertielle ont été développés ces dernières années, et semblent être une solution peu coûteuse et facile à utiliser pour l’analyse de mouvement. Cependant, ces systèmes ont certaines limitations liées au bruit des signaux, au phénomène de dérive pour l’estimation d’une position/orientation, et au désalignement entre les axes des capteurs et ceux des segments de corps. Ce projet vise à éliminer ces barrières technologiques afin de proposer une méthode de mesure et d’analyse du mouvement pendant les sports aériens qui peut être utilisée dans différents contextes liés à l’optimisation de la performance.

Regeneration of ABS material by compounding from recycled SAN produced via a solvent-base green recycling process

This project is associated to the creation of a circular economy around styrene-based plastics such as polystyrene, acrylonitrile-styrene copolymer (SAN) and ABS (acrylonitrile-butadiene-styrene) terpolymer. Polystyvert has
developed a technology that transform ABS post-consumer materials that come from electronics, car parts, toys ect. in a recycled SAN (rSAN) of high purity. This solvent-based technology is green and non-destructive using
dissolution and subsequent precipitation technique. ABS has a complex architecture made of SAN as stiff matrix and dispersed polybutadiene rubber particles that provide impact properties. Herein, the present investigation will
tackle the challenge of making ABS from rSAN by means of hot blends with virgin and recycled rubber. In a last stage, the produced rABS formulations would be evaluated in term of cost and sustainability for further
commercialization.

A Novel Solvent-free Approach for Production of Bean Protein Fractions

The fast-growing market demand for food products with high nutritional qualities requires innovative and sustainable technologies. The proposed process employs an electrostatic technique to selectively charge proteins, carbohydrates, fibers, and other components in the bean flour and separate them based on the magnitude and type of their charge. The proposed methodology produces protein-rich flour from beans without using solvents or chemicals which significantly reduces the capital and operating costs. It preserves the bio-functionality of the protein, and averts the likelihood of toxic microbial contamination common in currently used wet processes. This proposal aims to build on the knowledge garnered in the previous proof-of-concept project, funded by Mitacs Accelerate. Motivated by the promising preliminary results, the industrial partner, Advanced CERT Canada, is willing to conduct process optimization, fine-tunning, and scale-up studies to move towards designing and evaluating a pilotscale (dry) protein extraction plant.

Nouveaux domaines thérapeutiques pour la commercialisation des médicaments : Une analyse comparative de l’ETS au Canada, au Royaume-Uni et en Amérique latine

Cette recherche vise à identifier les nouveaux domaines thérapeutiques d’intérêt pour le marché canadien, ainsi qu’à évaluer les principales différences entre les processus d’évaluation des technologies de la santé au Canada, au Royaume-Uni et en Amérique latine.

Les études et recommandations de remboursement publiées au cours des cinq dernières années par les organismes d’évaluation des technologies de la santé du Canada, du Royaume-Uni et de l’Amérique latine seront évaluées sous la forme d’une revue de la littérature. Les examens des remboursements seront évalués à l’aide d’un modèle d’extraction de données. Les domaines d’extraction de données incluront les besoins actuels et émergents non satisfaits, ainsi que les facteurs cliniques et économiques contribuant à une recommandation de remboursement. Après l’extraction des données, les informations seront analysées pour déterminer les nouveaux domaines thérapeutiques d’intérêt sur les marchés canadien, britannique et latino-américain, les principales justifications cliniques et économiques des recommandations de remboursement positives et négatives, ainsi que les similitudes et les différences entre les organismes d’évaluation des technologies de la santé.

Stratigraphic Architecture of a Carbon Sequestration Target: Aquistore Site, Saskatchewan

This project will train a Master’s geology student to use a variety of geological and geophysical datasets and concepts to define the stratigraphic architecture of deeply buried sandstones used for CO2 sequestration at the Aquistore site in Saskatchewan. The extent to which these sandstones form a single continuous body, or are compartmentalized, will affect their ability to transmit and store the injected gas. These characteristics were defined nearly 500 million years ago when these strata were deposited. Results will inform ongoing monitoring and modeling efforts at Aquistore whereas the methods will be transferable to other proposed CO2 sequestration sites in Canada and abroad.

Generating Synthetic Bank Transaction Sequences with GAN-based Models

Financial institutions gather vast amounts of data from our transactions. However, using this data directly can risk our privacy. A potential solution is generating “synthetic data”, which contains real data information without copying the original data. Generating this data, especially for bank transaction sequences, is challenging. During our research internship, we will use recent developments in deep generative models to design a generative model that can create high-quality bank transaction sequences. This research project opens doors for Verafin to team up with outside experts and lets them show potential clients how their product works using realistic, risk-free examples.

A proposed hybrid machine learning model for fault-type classification and detection in a 10 MW wind farm based on synchrophasor and weather data

Incorporating renewable energy sources, such as wind and solar farms, have posed a challenge to electrical engineers due to their intermittent nature as the time and amount of energy generated depends on the weather. For this reason, grid stability and predicting the behaviour of renewables has been increasingly more important. In this study, we propose to train a machine learning algorithm on weather data, synchrophasor readings (voltage, current, and phase), and turbine monitoring data from a 10 MW wind farm located in PEI to detect and classify faults in their wind turbines. We will use the algorithm to develop a protection plan for their wind turbines based on these results.