Innovative Projects Realized

Technological training for lawyers

Although law schools ensure that legal professionals are well prepared to offer their clients legal advice, little is done to evaluate their basic technological skills (word processing software, accounting tools, etc.). We therefore have no way of benchmarking how often and how well legal professionals use the technologies at their disposal to serve their clients. Although this might seem trivial, improper or insufficient use of technology could have significant impacts on a lawyer’s ethical obligations, efficiency, and fees – which could in turn affect access to justice for their clients. The overlying purpose of this project is therefore to develop a tool that can evaluate Canadian lawyers’ technological competencies and generate sufficient data to modify law school curriculums in order to produce more well-rounded legal professionals.

Objective Assessment of Suicide Ideation using Measures of Electrophysiology Data and Machine Learning

Digital Medical Experts Inc. (DME) is a Canadian start-up company in the business of developing cloud-based point-of-care monitoring systems for the management of psychiatric illnesses. DME has developed algorithms to diagnose and predict optimal treatment for major depression disorder and schizophrenia, and has been allowed patents describing its technology in Canada, the USA, and Australia.
As part of this proposal I will be working with DME to develop and assess the viability of an objective measure of suicide risk taken directly from electroencephalogram (EEG) and electrocardiogram (ECG) recordings. We have already shown that particular interactions of electrical signals in the brain, known as cross-frequency couplings, can be used to characterize brain activity in ways relevant to psychiatric clinical practise. By developing data-driven algorithms, we will examine the robustness of these features for identification of suicidal ideation. If found acceptable the algorithms will be optimized and incorporated into a point-of-care monitoring system (that has already been developed by DME) using portable and wireless dry electrode EEG headsets.

Epigenetic effects of smolt-to-adult rearing in Atlantic Salmon

Stocking remains an important component of managing and conserving Atlantic Salmon populations, but it also has the potential to cause negative effects to wild populations. To understand the cause of these effects and the potential consequences of using a smolt-to-adult supplementation approach we will use cutting edge technology to investigate epigenetic changes in captive reared salmon. Epigenetic changes do not alter the genetic makeup of the fish but cause changes in the way genes are expressed which can affect their ability to survive. We will compare epigenetic differences between salmon raised from smolt-adult in a hatchery with wild fish as well as changes if these changes are observed in their offspring. The results of this research will help assess the risks of smolt-adult supplementation to wild populations and help improve captive rearing protocols to reduce impacts to wild populations.

A Policy Analysis of Rebate and Incentive Programs for StormwaterManagement in Local Governments.

This research will explore how local governments in the Western United States and Canada have

initiated and implemented rebate and incentive programs that help manage stormwater in community

watersheds. The exploration of stormwater rebate and incentive programs will assist the City of

Victoria in developing a rebate/incentive program for Victoria property owners. This research will fill a

knowledge gap in current stormwater management programs as current efforts in British Columbia

have not considered how best to involve property owners and interested members of the public in

changing the way in which stormwater is managed on privately owned land. Examining how rebate

and incentive programs from across Canada and the Pacific Northwest have been applied in a fair,

equitable, fle xible and progressive manner will provide valuable insight for the application of a rebate

and incentive program that supports the creation of a stormwater utility in the City of Victoria.

A randomized control trial comparing weight loss effects between the Keyto virtual “ketogenic diet” program compared to a standard-care weight loss app

Over 60% of overweight or obese individuals attempt weight loss diets each year. Although many different dietary approaches can lead to weight loss, increasing evidence suggests that a very low-carbohydrate ketogenic diet may have superior metabolic and weight loss effects. However, any diet is only as effective as adherence to it and adherence requires effective self-monitoring. While many evidence-based dietary programs are time and resource-intensive, Keyto is a scalable self-monitoring and app-enhanced intervention to help individuals learn about and monitor their breath acetone (a measure of ketosis) levels to promote dietary change and weight loss. Keyto has reported anecdotal success but would like robust evidence supporting the use of this low-cost, highly scalable intervention to help self-monitor and adhere to a ketogenic diet. The purpose of this research is to test the Keyto self-monitoring + app intervention against a “standard of care” mHealth weight loss dietary intervention.

Drug Repurposing for Neuromuscular Diseases

SMA is a neurodegenerative disease characterised by the loss of lower motor neurons and is an incurable disease. SMA is the leading genetic cause of early childhood lethality, with an incidence of 1 in 6,000 to 10,000 live births and a carrier frequency of 1 in 35-40. Current therapeutic strategies under development are almost exclusively based on increasing functional SMN protein. Given the divergence in prognoses due to the complexity of the different SMA type designation, the application of a combination of non-SMN dependent and SMN restoring therapies, would likely be essential to treat SMA. Therefore, there is an urgent need to develop and assess new non-SMN therapeutics for this incurable disease, which could be particularly effective at early stages of SMA. Modelis’ mission is to accelerate drug discovery for human genetic diseases and they are investing a large portion of their activities to drug repurposing. The current project will allow fastening the identification of already approved drugs for SMA using simple fish models of the disease in order to translate them quickly to the clinic

L’intelligence artificielle au service de l’industrie de l’assurance

L’évolution technologique révolutionne les processus administratifs dans les banques et les assurances, mais entraîne également de nouveaux défis, en particulier au niveau de la reconnaissance de l’écriture manuscrite et imprimée dans les documents qui doivent être numérisés pour extraire automatiquement l’information pertinente. Les systèmes de dialogues automatisés connaissent également un succès grandissant, grâce à l’utilisation de techniques de traitement de langages naturelles, mais présentent néanmoins de sérieuses imperfections qu’il convient de corriger.

Le projet sera principalement axé sur l’accélération et l’optimisation des logiciels développés au sein de Koïos, sur la base de la comparaison de plusieurs techniques reposant sur un échantillonnage intelligent des observations. Il permettra de valider et tester l’outil de reconnaissance d’objets (écriture manuscrite) et l’outil de reconnaissance de la voix qui sont implémentés à l’interne, ainsi que d’essayer différentes approches pour améliorer l’entraînement des algorithmes.

Intelligent Analytics for Dynamic Events in a Smart City

Artificial Intelligence (AI) research has grown rapidly in recent years as the result of faster computers and better algorithms. AI models can be trained to automate the decision process and provide results. However, if the model is not properly or sufficiently trained, the outcome will likely be unpredictable and inaccurate. Besides, training data is not easily available in a lot of applications. To address these issues, our strategy is to integrate classical Computer Vision (CV) algorithms and Deep Learning (DL) techniques. CV can provide solutions without training data. CV knowledge is also valuable to select significant features, which is necessary to train AI model. Our strategy takes into account of the trade-off between CV and DL, and can benefit a wide range of applications, including healthcare data analytics, event monitoring and pattern classification in general. The objective of this proposal is to support intelligent business operations in a smart city environment.

Quantum autoencoder as storage device

The Quantum Autoencoder was proposed as a device which can compress quantum states efficiently.
One possible application on near term quantum devices would be the compression of quantum data in order to protect it from decoherence effects. The compression however, also introduces noise to the quantum states so that it will not always be beneficial to apply it. This will depend on the individual circuit representing the autoencoder and also on the specific time for which the quantum state has to be stored.
In this project we aim to find the critical points in storage time after which the compression of the quantum states is beneficial in order to keep most of the quantum information for a variety building blocks which can be trained to be autoencoders.
Apart from specific examples from the literature we will try to categorize those building blocks with respect those storage times.

Sub Synchronous Oscillations in Power Systems

With increased levels of series compensation of transmission lines (Which is the most economical solution for bulk power transmission over long distances) and with more power electronic controllers such as HVDC, FACTS and converter based distributed generation in the power network, Sub Synchronous Interaction (SSI) problems arise. It is necessary to identify different types of SSI that could occur in the power network through proper means and to prevent such at the design stage or to take counter measures if required. This project intends to clarify different types of SSI by capturing any inconsistencies or limitations I definitions by developing various test cases in RSCAD. These test cases will be further expanded to evaluate reported screening techniques, analytical techniques and mitigation techniques in different aspects and thereafter to develop screening techniques to capture SSI phenomenon in multiple series compensated lines at multiple contingencies and to develop efficient and effective mitigation techniques. Furthermore, Average Value models of TCSC will be developed to speed up system level studies. The final major outcome of this project is a proper SSI risk evaluation methodology which one can follow in SSI case studies.

Local Growth Factor Presentation by Macrophages

Fibrosis comprises different connective tissue disorders that ultimately result in deposition of detrimental scar tissue in injured or inflamed organs. The culprit cells for organ scarring are called myofibroblasts because they secrete fibrous collagen matrix (“fibro”) that is contracted (“myo”) into scar tissue. Excessive myofibroblast activities are responsible for loss of function of vital organs after injury, such as the heart after an infarct – this life-threatening condition is called fibrosis.

Fibrosis ensues from normal repair partly because unresolved inflammation promotes continued activation of myofibroblasts to make and pull fibrous collagen matrix into stiff scar tissue. Our lab found that inflammatory macrophages carry an inactive fibrosis-inducing factor on their surface. We propose that myofibroblast can grab onto and activate this factor by pulling it our of a ‘straight-jacket’. The receptors involved in the grabbing process will need to be identified.

It is our aim to identify the molecular players mediating macrophage-induced fibroblast activation. We propose that preventing these cells to touch or blocking the interaction signaling molecules will ultimately reduce tissue scarring. We will study macrophages and fibroblasts derived from mouse tissue in unique co-culture environments. We will delete and inhibit already identified receptors on the macrophage and/or myofibroblast sur

L’anxiété de performance en milieu scolaire : état de la situation et évaluation d’un programme d’intervention pour y répondre

Le présent projet propose de renseigner sur la nature et l’ampleur de l’anxiété de performance en milieu scolaire, une problématique qui prend de l’ampleur chez les adolescents anxieux. Les médias discutent effectivement de plus en plus du fardeau de l’anxiété aux évaluations chez les élèves qui entrainent des coûts importants par ses conséquences sur la performance scolaire et le bien-être émotionnel des élèves. Il devient ainsi nécessaire d’avoir un portrait plus général de la situation et des solutions probantes pour y répondre. Ainsi, dans un deuxième temps, ce projet vise à évaluer le programme Étudier sans anxiété visant à diminuer l’anxiété de performance en milieu scolaire. Réalisé avec l’appui de l’organisme partenaire Boscoville, ce projet permettra de faire avancer les connaissances en plus d’évaluer dans un devis randomisé une intervention innovante. Boscoville aura alors la possibilité de venir diffuser un programme basé sur les données probantes dans l’ensemble du Québec.