Projets novateurs réalisés

Un nouveau regard sur les protéines et le microbiote intestinal afin de mieux comprendre les bienfaits des produits laitiers sur la santé.

La composition en nutriments a été traditionnellement considérée comme un point clé pour justifier et recommander la consommation de certains aliments. En ce qui concerne les produits laitiers, les guides alimentaires de nombreux pays ont principalement insisté sur le lien calcium-lait selon lequel un nombre minimal de portions quotidiennes de lait et produits connexes devrait être consommé pour maintenir une santé osseuse adéquate. Au-delà de ce constat, la recherche sur les produits laitiers au cours des dernières décennies a également documenté une relation bénéfique entre la consommation de produits laitiers et le risque de développer des problèmes de santé tels que le diabète de type 2 et l’obésité. Dans un tel contexte, le calcium s’est de nouveau avéré être un acteur important bien qu’il ait également été établi que les protéines sont importantes. Cette demande propose donc une continuation de cette preuve de concept qui devrait montrer qu’au-delà de la quantité, les protéines laitières peuvent faire la différence dans le contexte de la prise en charge clinique de l’obésité.

Les effets de la pratique d’activités culturelles parascolaires à l’école secondaire sur le développement personnel et social des jeunes

En mars 2022, ACLAM, anciennement la corporation Secondaire en spectacle, a adopté une nouvelle raison d’être : le développement global et du plein potentiel des élèves des écoles secondaires par la pratique d’activités culturelles parascolaires. L’organisme doit toutefois être en mesure de faire valoir l’importance de ces activités pour l’élève. Le projet de recherche consiste à rassembler un maximum de connaissances à propos des effets de la participation des adolescents aux activités parascolaires du secteur des arts et de la culture. Les effets néfastes de la participation doivent être connus et compris si on veut mettre en place des mécanismes pour les réduire ou les éliminer. Les effets positifs, eux, doivent être valorisés, maximisés et mis de l’avant.

Influence of redox conditions on the fate of emerging contaminants in groundwater environments

Contaminants of emerging concern (CEC) have negative impacts on human and ecosystem health as well as the potential to develop antimicrobial resistance which is projected to result in 10 million deaths annually by 2050. Some examples of CECs include antibacterial agents, artificial sweeteners, and pharmaceuticals. Recently, the presence of these CECs has been found widespread throughout the environment including in our fresh waters. This research will focus on gathering preliminary field measurements on CEC fate and transport in groundwater environments known to have strong redox gradients. This will be completed at field sites near Sydney, Australia that are known to have CECs in the groundwater including recharge sites where treated wastewater is injected into the ground. Solid phase and groundwater samples will be collected and analyzed for CEC concentrations, redox conditions, as well as some other traditional geochemical parameters. Multiple sampling events will be conducted to better understand spatial and temporal relationships between CEC concentrations, redox gradients, and some other parameters. This research will help to better predict the transport of these CECs in groundwater allowing for future remediation.

Abnormal Detection for Language Assessment

A typical language test usually consists of four parts: speaking, listening, reading, and writing. Both audio and text data from the test takers will be collected and used by the automated scoring system. During the test, some test takers will intentionally/unintentionally provide abnormal answers, which may contain memorized content, repeated sentences, and meaningless or off-topic words, and may affect the accuracy of the scoring system. Pearson would like to develop a more robust system for automated scoring to identify and penalize abnormalities in the audio and text data, which could greatly improve Pearson’s competitiveness in the market and in the meantime contribute to the development of abnormal detection models.

Statistical Analysis and Machine Learning Approach to Retail Sales Forecasting Based on Localized Weather Features

In recent years, weather has been recognized as an important factor that can have a significant impact on
consumer behavior in certain industries. Predictive models that incorporate weather data can help industries to
adjust their inventory and marketing strategies to optimize sales.
This research project focuses on using machine learning and data analytics to determine any weather-related
signals on retail sales based on historical data and then to predict sales using weather information. The project
will involve literature review, developing complex SQL queries, engineering features, analyzing weather and
retail sales databases, and developing machine learning algorithms. The ultimate goal of this end-to-end project
is to create an accurate and scalable sales forecasting model that can be used by industries to optimize their
inventory and marketing strategies based on weather patterns.

Deep-learning cross-modality super-resolution imaging of the cellular network in bone

Many organisms, such as bone, depend on fluid-filled network structures for cellular transport, signaling and mechanosensing. Bone is made of a network called the lacunocanalicular network (LCN), which consists of lacunae that house osteocyte cells connected together by a network of 300-nm wide canals called canaliculi. An understanding of this vast network is incredibly important and could provide valuable insight into bone function and disease. While many techniques exist to visualize LCN, the large size of the network makes acquiring images at sufficient resolution while covering a large field of view difficult.

The proposed research aims to use and develop deep learning image-to-image translation to improve the resolution of microscopic images of bone and enable graph network extraction of the LCN directly from low-resolution (LR) images. It is hypothesized that deep learning can be used to perform same-modality super-resolution (SR) of LR confocal microscope images, as well as cross-modality SR of LR confocal microscope images to high-resolution Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM), and to directly extract large area graph networks more efficiently.

Analyse en temps réel de signes vitaux grâce à l’application de techniques d’apprentissage automatique et à la synchronisation d’une pluralité de senseurs physiologiques

La photopléthysmographie (PPG) est une méthode non invasive mesurant les changements de volume sanguin
dans les tissus. Cette technique permet de dériver des métriques physiologiques importantes, telles que la
fréquence cardiaque, la saturation en oxygène et la pression artérielle. Cependant, pour des résultats fiables, il
est crucial de prendre en compte les différences physiologiques des individus, notamment relié à la couleur de
peau, au sexe ainsi qu’à l’âge et de surmonter les problèmes d’artefacts de mouvement.
Le projet vise à améliorer la fiabilité des métriques PPG en utilisant l’IA et un nouveau capteur portable de SiFi
Laboratoires pour améliorer la précision de la mesure de la pression artérielle en télémédecine. L’intégration de
ces technologies de pointe permettra d’obtenir des mesures de pression artérielle plus précises, ce qui peut avoir
des implications significatives pour la surveillance à distance de la santé des patients, en particulier pour les
personnes atteintes d’hypertension artérielle.

Totem-Pole PFC using Cascaded GaN Switches

The proposed project will be a collaboration between the Ottawa (ON) based integrated circuit (IC) company, Power Integrations Inc. (PI) and RIGA lab at University of Manitoba, Winnipeg (MB). The result of the research project will be transferred to the IC design team in PI to integrate power semiconductors, gate drivers, controllers
company to identify the challenges and opportunities of using GaN power semiconductors in their other new power IC products. And then their products can help other power electronics (PE) companies to reduce power losses and the society to achieve electrification. Thus, it will benefit both IC manufacturers and power electronics companies. Further, one PhD HQP will be trained in PE technologies and will be able to contribute to Canadian PE industry in the future.

Développement de modèles de prédiction et de contrôle de composition chimique et de largeur de bain dans un four de réduction

L’industrie minière est un secteur manufacturier clé pour le Québec et le Canada qui doit constamment améliorer sa compétitivité, notamment par des investissements permettant le contrôle des opérations. Un équipement important et très énergivore dans le procédé de production de dioxyde de Titane est le four à arc électrique de réduction du minerai d’ilménite. Ce dernier utilise une grande quantité d’électricité et un agent réducteur pour fonctionner. Cet équipement est contrôlé par un système de commande automatique et par des opérateurs en fonction d’une cible d’opération établie par des métallurgistes. Ces cibles permettent de garantir le maintien de l’intégrité de l’équipement qui est opéré à haute température et la teneur en dioxyde de Titane du produit. L’objectif de ce projet est une amélioration de la performance du contrôle du procédé de réduction d’ilménite par l’utilisation de méthodes d’apprentissage automatique. Cette amélioration permettra le maintien de l’intégrité du four, une meilleure sécurité de son opération et une stabilité de la qualité des produits obtenus

Geometry reconstruction of rapidly moving specular surfaces relevant to fusion energy devices

This project seeks to play a role in making fusion energy a reality, a big step in energy decarbonization. The project is in collaboration with General Fusion, based in British Columbia, where a fusion reactor is being designed, based on a spinning cylinder of liquid lithium which is mechanically collapsed around a plasma to produce fusion, releasing energy the same way as the sun.

One design challenge is for the lithium to be collapsed perfectly, since any asymmetry in the collapse leads to inadequate pressure and temperature for fusion. The proposed MITACS partnership between General Fusion and the University of Waterloo is to characterize, in detail, the precise shape of the liquid lithium both before and during the collapse. There are significant imaging challenges present, both from the high speed of collapse, and the extreme temperatures at which the reactor operates, making this an outstanding research project.

Water is our Friend

This project supports relationship development with First Nations communities in British Columbia to facilitate collaboration on a larger flood-risk reduction project, which focuses on integrating Western expertise in architecture, engineering and social science with Indigenous Traditional Knowledge to create a new, collaborative approach for flood risk reduction in Indigenous communities in Canada. Relationship building prior to beginning a collaborative project with First Nations communities is necessary for successful adaptation and will ensure the community’s wants and needs for the project are understood. The project will be conducted in collaboration with the First Nations Emergency Services Society of British Columbia (FNESS), who have existing working relationships with many First Nations in British Columbia. Involvement in this project will engage FNESS in flood mitigation efforts that will be beneficial to their flood preparedness and response activities.

Evaluating the impact of climate change on forest watershed ecosystem services surrounding Cape Breton drinking water source areas

The trees surrounding the source drinking water lakes in Cape Breton Regional Municipality influence the pH and electrical conductivity of throughfall water in preliminary studies, particularly conifers like black spruce. The Kelly Lake Watershed that provides drinking water to the community of Louisbourg suffers from an acidity pulse each spring, potentially influenced by overland flow during the spring melt carrying associated activity from interactions with conifer needles. As low pH values help liberate metal ions, we want to see if the soil in these conifer dominated watersheds is leaching acidity, and possible metal ions, in the spring freshet. Climate change may push the black spruce further north, beyond its current distribution surrounding Kelly Lake, potentially alleviating the vernal acid pulses over time. Accelerating this transition to more favourable FES through stand manipulation may be a short-term management technique available to the CBRM Water Utility Managers.