Projets novateurs réalisés

Biochemical and structural characterisation of KLCR-NET3C interactions

Improving Clinical Outcomes for Patients at the Canadian addiction treatment centres

Canadian Addiction Treatment Centres (CATC) is the largest multi-site organization devoted to treating Opioid Use Disorder (OUD) in Canada. CATC has implemented comprehensive protocols and a detail-rich model of care for patients with OUD. CATC has been generating practice summaries for each physician, comparing their outcomes to the peer group on factors that impact retention. However, they identified a need to improve the audit and feedback process to drive change and improve patient outcomes. This will use best practices audit and feedback processes to improve CATC patient outcomes using routinely collected data from the electronic medical system to satisfy the following objectives, a) Create a comprehensive database of all CATC patients to facilitate the audit/feedback process, b) Evaluate how patient, program and physician characteristics impact treatment outcomes to provide meaningful feedback to physicians and clinics using comparators and, c) Evaluate trends to make actionable recommendations for practice change.

Organosolv Lignins from Renewable Resources for Active Packaging Applications

Une démarche d’analytique RH au sein de l’UMQ afin de suivre l’état de la santé psychologique des employés municipaux en période pandémique

Les coûts annuels associés à des problèmes de santé mentale au travail sont astronomiques pour une organisation. Conséquemment, l’organisme partenaire a lancé deux sondages portant sur cette thématique Ne disposant pas d’expertise pour analyser pleinement les résultats, l’objectif du projet est donc d’analyser les sondages déployés. Qui plus est, le partenaire s’interroge sur l’efficacité d’activités mises en place pour prévenir ou soulager la santé psychologique chez les employés. Le deuxième grand objectif est de concevoir un sondage portant sur les initiatives mises en place et de les relier aux indicateurs de santé psychologique mesurés. Ce sondage reposera sur des assises provenant a) d’une recension des écrits sur le sujet et b) d’entrevues auprès de responsables RH municipaux.

Automatic Model Risk Management

Regulatory bodies, such as the Office of the Superintendent of Financial Institutions (OSFI) require that financial institutions properly assess and manage risk. Regulatory bodies aim to ensure the stability of financial markets, and the economy at large, and they do so by imposing guidelines on a firm’s risk management practices. Risk management models in general, however, rely on ex-ante assumptions, which can lead to estimation errors, even if the model is “correct”, hence subjecting them to model risk (also known as model uncertainty) and conclusions can vary widely depending on the underlying assumptions. Measuring model performance of rating systems is a major task for regulated firms. This project aims to develop methodology that helps institutions assess their exposure to model risk without the need of setting up specialized in-house teams.

Arts’ Civic and Social Impact Beyond Covid-19: Researchers in Residence

Four research interns will be supported by four arts funders, five universities and four arts and culture organizations, which will come together under the leadership of Mass Culture to see how the arts and culture sector impacts society today. Together, we will look at ways to strengthen community ties and foster shared social values through the arts so that we can more capably address complex issues such as mental health, climate change, systemic racism and strategic public policy. More than the sum of its parts, this coalition of professionals, researchers and funders will use the arts as a foundation to develop and test four unique approaches to measuring cultural, business, social and civic impact. Benefits will include well-researched practical tools for the arts, health and environmental sectors, as well as documenting evolving policy, community-building and knowledge-sharing approaches.

Production Line Packaging Sensor Optimization

Automated production lines use in food, beverage and pharmaceutical manufacture can subject the product being produced and especially the product packaging to high levels of mechanical stress. These stresses can take many forms, be it impact, side pressure, vertical pressure, etc. Plant quality assurance engineers are constantly making adjustments to their automated systems to reduce these stresses to acceptable levels while increasing throughput. MASITEK’s sensor packages help identify these stresses, especially those that are potentially damaging. As consumers demand more environmentally friendly packaging, sizes of products decrease and speeds of automated handling systems increases it is important that the sensor packages be smaller, more sensitive and more accurate. This project will focus on increasing the sensitivity and repeatability of the sensor packages, significantly decreasing their size, and improving the radio link employed.

Homelessness Prevention at Covenant House Toronto

The proposed research project to be undertaken by the intern is concerning the use of preventative measures to combat youth homelessness and trafficking in Toronto through Covenant House Toronto. Youth homelessness and trafficking are on the rise and researching how prevention for this vulnerable population can be utilized has the potential to significantly reduce rates of youth homelessness and trafficking in Toronto. The project will use both quantitative and qualitative methods of analyzing existing Covenant House Toronto data on the youth that are experiencing or have experienced homelessness and/ or trafficking. The intern will be working towards completing a high-level report that implements the findings and trends from the data to generate recommendations on the next steps to undertake for a youth homelessness prevention strategic plan.

Developments of the data evaluation procedure at the FRS Ion Catcher

Modeling and simulation of a magnetic MEMS Container

Using deep learning methods to solve optimization problems

Control of Behavior in Shared Spaces