Innovative Projects Realized

Iron Removal In vivo Study (IRIS)

Infections and inflammation of the eyes are becoming increasingly prevalent problems for patients

with chronic diseases or for people who use implanted eye lenses. Serious ocular infectious and

inflammatory disease can lead to significant visual disability and requires aggressive treatment

intervention to mitigate disease pathology and prevent vision loss. Preliminary work suggests that ironchelating

agents developed by Chelation Partners Incorporated can effectively control microbes and

inflammation. These excipients can enhance the power of antibiotics, especially in clinically resistant

infections, dampen inflammation and reduce the need for harsh preservatives. Studies will be designed

to: (i) evaluate the safety of the excipients, (ii) determine the ability of these agents to control

inflammatory response in the eye (iii) examine the ability of these agents to limit eye infections or their

ability to enhance the anti-microbial activity of antibiotics. Results of these studies will be valuable in

assessing the safety and efficacy of these iron-chelating agents in vivo (in animals) prior to their TOBECONTINUED

Covalent and non-covalent interactions self-supervised representation of molecules for chemotherapeutic drug design

Most of the drugs used to treat cancer have been originally identified from natural sources. While Nature did a great job selecting those compounds, some of them have shown limitations in the treatment of cancer and others have shown to be insufficient on some cancer types. Furthermore, it exists a gigantic number (nearly infinite) of small molecules human can synthetize. The goal of this project is to use existing machine learning technics and novel input representation approaches in order to efficiently search in this gigantic chemical space, newly potential molecules that could be used as new chemotherapeutic drugs.

Synthesizing the State of Practice of On-Demand Transit in Canada

This project proposes a survey directed at transit agencies in Canada that have operated, operating, or planning to operate flexible transit, with special emphasis placed on app-based on-demand transit services. Personal interviews will be conducted with key personnel at the transit agencies, likely using phone communication. The results of the survey along with a more comprehensive review of industry reports will be summarized to highlight the key practices of flexible transit in Canada. With the increased interest in technology and automated operations, this study will also approach technology and software companies that usually provide the software for scheduling and dynamic routing application to support flexible transportation services.

Dynamic Credit Scoring

Banks use a myriad of methodologies to inform their officers on credit extension decisions. One of the most employed approach is to summarize borrower creditworthiness by credit scores, which in turn depend on loan default probabilities. The probability of default depends both on borrower characteristic and on the overall state of the economy. The goal of this project is to create credit scores that are responsive to the expected state of the economy. The core idea is to establish the link between default probabilities and borrower characteristics separated in good and bad-market state scenarios. These good/bad-market-states scores are then combined using forecasts of the probability of the economy falling in either scenarios. The output is dynamic credit scoring for borrowers characteristics.

Forecasting Ability of Non-consumer Scorecards and their Ability to Predict Probability of Default

International Financial Reporting Standards (IFRS) for loss allowances are changing, and financial institutions are proactively adapting existing methodologies and developing new ones to remain compliant. The main ingredient in the myriad of evaluations that banks are required to perform for compliance is risk assessment. The first goal of this research project is to review best practice risk models, with a special focus on modeling the evolution of default probabilities. In particular, the project evaluates the forecasting ability of internally credit ratings of borrowers in predicting probability of default. The linkage between internal scores and probability of default will be explored using a classical statistical approach (re-logit) and a methodology stemming from recent advances in machine learning (random forest with undersampling).

“Transit Gender Sunshine List”: Assessment of Representation of Women as CEOs and Directors of Canadian Transit Systems

CUTRIC, in partnership with the University of Windsor are seeking greater understanding of the barriers to participation which have resulted in the low representation of women within the leadership ranks of Canadian transit systems. To better understand this lack of representation, a literature review will be conducted to ascertain what knowledge exists in this field and will be used to provide a foundation for the next steps of the research. Following this, interviews and focus groups with members of transit system leadership will be conducted to discover which barriers exist within this industry. Comparative analyses with U.S. and relevant mobility sector cohorts will be conducted. This research will help CUTRIC to better understand and address systemic barriers within transit systems and increase the representation of women within this industry.

Gated and RGB Fusion for Robust Perception

Robust perception in all weather conditions is a critical requirement for autonomous vehicles. This project proposes fusing gated and conventional RGB camera images for robust scenes encoding, depth estimation and trajectory prediction. Conventional approaches using lidar and RGB camera fail to perform robustly in rain, fog and snow. By extending existing computer vision algorithms to Gated-RGB camera pair the fusion algorithms developed will utilize features that are robust in one sensor modality but not the other. The proposed projects will allow Algolux to evaluate different fusion algorithms and augment the existing captured dataset with simulated data that are useful for algorithm development and evaluation.

3D Visualization Pipeline and Methodology for Large-Scale Artifact Collections Management

This project will develop the protocols, standards and procedures to establish a digitized, virtual artifact repository, accessible online for research and public education, by establishing the processes for large scale digitization of the analyzable objects representing the full range of the compiled archaeological heritage from Ontario.

Constrained Batch Estimation for Train Positioning with Inertial Sensors

Similar to current efforts in the automotive industry, there is a substantial interest in developing fully autonomous trains. One of the key steps towards enabling autonomous operation is being able to accurately estimate train position and speed. In addition to this, better estimates will also increase safety and reduce distance between trains, allowing more frequent trains in peak hours. The current project deals with a method of estimating the velocity and position without using GPS measurements, which is the standard method. This is because GPS signal can be unreliable in urban environments and are unavailable underground in subway networks. Instead of using measurements one by one, the position and velocity are estimated by using batches of measurements and fitting them to the track, which the train always travels on. For Thales, this presents an alternative method of estimating velocity and position that does not require multiple sensors, adding reliability and thus safety to existing solutions.

Les enjeux contemporains de l’inclusion financière au Mexique. Étude des liens entre politique publique, organisations de microfinance et secteur des micro entreprises

L’objectif de cette recherche est d’identifier et de problématiser les facteurs qui influencent l’efficacité de la politique nationale d’inclusion financière. Cette politique publique a été récemment mise en œuvre par le gouvernement mexicain pour lutter contre les inégalités d’accès aux services financiers qui affectent les individus et les entreprises.
La recherche vise à établir le fonctionnement de cette politique publique en analysant le contexte politique et socio-économique de sa mise en œuvre et en identifiant le rôle des différents acteurs qui interagissent.
Afin d’accéder aux services financiers, les demandes des individus et plus spécifiquement des entreprises doivent d’abord être sélectionnées par les institutions financières. La recherche examinera les facteurs qui influencent ce processus de sélection, qui est la première étape vers l’inclusion financière. Ce travail vise à combler une lacune dans la littérature et fournira un cadre analytique innovant pour la recherche sur les politiques d’inclusion financière. Les résultats aboutiront à des suggestions pour renforcer l’inclusion financière et minimiser la marginalisation de certains acteurs de la société.

Systematic Conservation Planning in Tsay Keh Dene Territory: Incorporating Climate Change and Bridging Traditional Ecological Knowledge

Systematic Conservation Planning (SCP) is the idea that the practice of protecting lands should be examined on a broad scale and be holistic in nature. Available areas of land with conservation potential should be examined critically for whether they fit into a larger ecological network – either as a link between existing protected areas, or as an area that is ecologically significant on its own. This project is an application of SCP principles and tools for a specific geography – the Tsay Keh Dene Nation Territory in northcentral British Columbia, Canada. The research is being carried out in cooperation with the Nation and their wholly-owned environmental consulting company, Chu Cho Environmental. Study results should help immediately in the processing of project proposals within the territory since the Nation is often overwhelmed by the number received, as well as in the long-term with natural resource management and activities related to large-scale conservation goals.

Cutaneous T cells and disease severity in adult atopic dermatitis

Strong evidence for T cell activation in atopic dermatitis disease pathogenesis exists, as demonstrated by the clinical efficacy of therapeutic T cell cytokine blockade. The subsets of human T cells capable of contributing to pathology of this disease remain poorly defined, lending importance to the characterization of T cells and their cytokines within active skin lesions of patients with atopic dermatitis. We hypothesize that novel effector T cell subtypes resident in human skin contribute to disease activity, particularly in adults. Using our newly validated methods for immunophenotyping T cells from human skin biopsies, we have identified heterogeneous sub-types of skin T cells secreting the pathogenic cytokine IL-13 from the lesional skin of atopic patients. We propose to combine the world-class human clinical studies expertise at Innovaderm Research, Montreal with state-of-the-art immunophenotyping techniques at the Research Institute of the McGill University Health Center in order to identify the contribution of these different sub-types of T cells in the severity and chronicity of disease in adult atopic patients.