Innovative Projects Realized

Development of robust analytical methods for the quantification of trace elements in speciality polymers

The presence of metals impurities in conjugated polymers can have important consequences on their
performances and lifespan. Yet, measuring trace levels of metals in polymeric matrices is challenging both in
terms of sample preparation and detectability. In this project, we aim at assessing diverse approaches to
overcome the challenges associated with the measure of numerous metals in speciality polymers.

Group Field Theory and Black Holes

The project will consist on visiting the Gravitation and Cosmology research group of the university of Sheffield in order to start a collaboration in a specific area of mathematical aspects of gravitation. The research in this area will: provide insights on quantum theories of gravity, in particular Group Field Theory; help to develop general mathematical tools for solving physical problems; and broaden our understanding of the universe. This interchange of ideas will lead to: 1. Enhancing research productivity. 2. Building networks for success internationally 3. Providing opportunity for global talent to work with Canadian institutions. Moreover, the project’s outcome will contribute to providing experiential learning for students, foster a culture of support recognition and result in scientific publications. These points are an important part of the Mitacs and UNB Strategic Plan (as stated in the UNB Toward 2030 document) and by awarding funding to this project we will be supporting innovation and excellence.

Dynamic Proteomic Profiling During Skeletal Muscle Loading and Unloading in Humans

Skeletal muscle plays several different roles in the promotion and maintenance of health and well-being. The loss of muscle mass that occurs with aging, chronic muscle wasting diseases, and physical inactivity puts people at an increased risk of frailty and becoming insulin resistant. Some individuals fail to increase the size of their muscle following (low responders) whereas others show vary large increases in muscle size (high responders) in response to the same resistance training program. People also show differences in the amount of muscle tissue they lose when they have a limb immobilized (i.e., leg casted, or leg brace). However, the molecular mechanisms driving changes in muscle size remain poorly understood. Recent methodological advances might allow us to uncover molecular mechanisms that govern changes in muscle size. Using an innovative methodology, the purpose of my Gloablink research project is to implement a novel methodology designed to discover key regulators of muscle size in humans.

Recours au juge administratif et conséquence du CETA comparaison France — Québec

Dans le cadre de mon travail de séminaire de Staatsexamen (équivalent d’une maîtrise) au sein de l’Université de la Sarre (Allemagne), je souhaite réaliser une étude comparée de droit français, européen et canadien. M’intéressant particulièrement au droit européen ainsi que au droit administratif, je souhaite saisir l’opportunité de l’entrée en vigueur de l’accord économique et commercial global (AECG ou CETA – Comprehensive and Economic Trade Agreement) entre l’Union européenne et le Canada pour faire un exposé synthétique des apports de l’accord dans ce domaine.

Cette étude doit, rédigée en langue française, s’inscrit dans le cadre d’un cursus bilingue et binational proposé par l’Université de la Sarre en partenariat avec l’Université de Lorraine (France). L’étude doit comporter au moins 40 pages. Suite au séjour au Canada et l’évalution de mon étude, une soutenance orale aura lieu en langue allemande.

Elle pourrait être une aide précieuse alors que le marché de l’emploi, particulièrement au Luxembourg dont la Sarre est voisine, requiert des compétences en droit comparé français, allemand et une connaissance du droit d’un pays tiers.

TA-A001, a New CB2R Agonist for Ocular Inflammation and Pain. Proof of Concept and IND Enabling Studies

Blindness resulting from inflammatory ocular conditions such as age-related macular degeneration (AMD) and progressive keratoconus (PK) is increasing around the world as populations age. Together they affect over 8 million individuals in N. America alone with up to one in four of those over 80 being at risk. Despite this, treatments for such conditions are limited, ineffective, and often extremely costly. Dry-eye disease, another ocular inflammatory disorder leading to severe disability, especially in the elderly people, is similarly undertreated, today’s leading therapies, such as Restasis® (a reformulation of cyclosporin, a drug approved in 1983) being ineffective and painful for many patients.
TA-A001 is a new mechanism anti-inflammatory drug working via the body’s natural immune system to control inflammation and associated pain. In a first series of studies, we will use TA-A001, enabled by our ocular delivery technology SmartCelle, to control the excruciating pain occurring after sight-saving PK surgery. Today’s analgesics are ineffective in this setting leading to treatment delays and poor surgical outcomes. TA-A001 can reverse this trend promoting earlier surgical intervention, improved patient experience and clearer vision.

Analyse et modélisation de la performance au boccia

Les athlètes de boccia doivent maîtriser différents types de lancers (par exemple, placement, montée, ouverture, etc.) et les mettre en oeuvre avec succès au bon moment pendant un match afin de prendre le dessus sur leur adversaire et marquer des points. L’analyse notationnelle pour quantifier les actions réussies et non réussies ainsi que les schémas tactiques est donc bien adaptée à ce sport.
À partir des données récoltées par l’analyse notationelle de matchs de boccia sur une période de 4 ans, nous explorerons des techniques d’apprentissage non supervisé telles que le regroupement et l’analyse en composantes principales pour trouver de nouvelles façons d’interpréter les données et donner un avantage compétitif au programme national de boccia.

Predicting Breast Cancer Outcome based on tumour morphology with Explainable AI

Breast cancer (BC) diagnosis and treatment generate a significant and increasing portion of healthcare cost in Canada. Detection of a potential BC by mammogram screening triggers a confirmatory biopsy. When a BC is confirmed, additional tests are performed on the biopsy material to guide therapy. Since 2015 a new expansive (~ 5000.00 CAD per patient) molecular predictive test is also performed to predict the likelihood of chemotherapy benefit and 10-year risk of distant recurrence to inform adjuvant treatment decisions in certain women with early-stage invasive breast cancer. This new test adds financial burden on Canadian health care system. Use of artificial intelligence to predict and guide therapy for breast cancer patients can potentially reduce these costs and turn around time significantly. In this research, Alberta health Services (AHS) is collaborating with Computing Science, University of Alberta (U of A) to design such AI algorithms. While many AI-based algorithms, especially, deep learning-based algorithms lack explanations of the decision made by the AI, this research will focus on explanation capability of deep learning. The proposed MITACS internship will foster this U of A developed expertise along with the pathological and diagnostic acumen of the AHS laboratory personnel.

Méthode de caractérisation de modules photovoltaiques en extérieur

Les énergies renouvelables sont amenées à remplacer les énergies fossiles dans le mix énergétique mondial. Parmi les différentes technologies disponibles, les technologies photovoltaïques prennent une part importante. L’objectif de ce stage est de développer des méthodes de test de modules photovoltaïques à concentration en environnement extérieur, et d’appliquer ces méthodes pour caractériser des modules fabriqués à l’Université de Sherbrooke.

Ai TooLs to chAracterize and identify uNstable aTherosclerotIc plaqueS (ATLANTIS)

Strokes and myocardial infarctions, caused by the rupture of unstable atherosclerotic plaques in the carotid and coronary arteries, are the leading causes of death world-wide. Current clinical guidelines recommend surgical removal of plaques based solely on the degree of artery stenosis. However, stenosis alone is an incomplete determinant of stroke/heart attack risk, leading to suboptimal medical decisions or inappropriate treatment allocation. Although plaque composition is a more accurate indicator of plaque instability and a better predictor of clinical outcomes, no method currently exists for its accurate, quantitative, and non-invasive characterization. We aim to develop artificial intelligence-based platforms to characterize atherosclerotic plaque features from 1) histological and 2) ultrasound plaque images. These platforms will provide a complete and accurate analysis of plaque features and instability, while eliminating bias and inter-individual variability. This method can be used to improve the prediction, treatment, and prevention of heart attacks and strokes.

Towards an understanding of women’s experiences on well-being in mining communities

Mining operations can have positive and negative impacts on local communities and there are no standardised ways to measure the overall impact of mining operations on community wellbeing. On the one hand, this is because corporate reporting on sustainability related issues is targeted towards investors and other financial stakeholders which are (overall) less concerned with local community concerns. On the other hand, the subjective nature of community wellbeing and the different needs of community members limit the insights a standardized approach could reveal. This study provides the space for marginalized groups to express their lived realities and proposes an in-depth analysis of the conversations with women from mining host communities. The aim of the project is to bring to the fore women’s unique experiences and unique challenges of women in mining communities which in turn will allow the partner organization to address these concerns in a more nuanced way to strengthen the community-company relationships and advance corporate reporting strategies.

Fabricating and Investigating Laser-induced Reduced Graphene Oxide RFID Tag

Transient electronics and their dissolution byproducts, are usually harmless and benign, and hence they are an attractive approach for the global e-waste problem especially for low-cost, one time use devices such as RFID tag antennas. For this research, a straightforward laser-induced method of environmentally friendly reduced Graphene Oxide films is proposed for fabricating transient RFID tags possessing sufficient electrical and mechanical properties for proper functioning. First, the effects of fabricating conditions, such as laser power, exposure time, and laser scanning speed, on the final architecture and electrical/mechanical properties will be investigated using scanning electron microscopy, Raman, and X-ray diffraction. Having optimized the conditions, several hypotheses regarding the reduction process will be tested. First, it is hypothesized that the wider the Graphene Oxide flakes are, the higher the conductivity of reduced part will be. Furthermore, it is proposed that adding nano-additives like Carbon Nanotubes to make hybrids with the precursor (GO) will improve interconnectivity and reduce inter-facial effects between GO’s flakes, resulting in lower resistivity. The final expected outcome of research is a facile method of co-reduction of GO-based hybrids for biodegradable transient RFID tags.

Digital Twin Platform Canada’s Resilience to Climate Induced Risk

Over the past decades, Canada has witnessed a continuous increase in the frequency and magnitude of climate change-induced natural disasters. Flood events are considered the most occurring climate-induced hazards in Canada. Cities rely on a series of Critical Infrastructure Networks (CIN) to perform adequately, flood events can be the reason for serious disruptions in these CINs. City resilience is the capacity of an urban system to recover and reach an acceptable level of functionality after being exposed to a hazard. Up until this stage, city resilience research has been focusing on modeling certain aspects of the built environment, without a mean to model future changes. This calls for a tool that would empower decision makers to predict, visualize, optimize, and run what-if scenarios before tampering with the built environment. The proposed research will contribute to the development of a framework that will assist managers and decision makers develop policies and optimize specified sets of city-flood resilience within specific resources and time constraints, and immediately visualize the consequences and act accordingly, potentially saving Canadians millions of taxpayers’ money.