Innovative Projects Realized

Geosynthetic drainage for improved stability of fine-grained materials in slopes & embankments

Innovative geosynthetic drainage products have been developed that have the potential to significantly benefit the stability of constructed embankments or reconstructed slopes especially where these are constructed from soil (or soil-like materials such as tailings) that are finer and less permeable (and thus weaker) then free-draining coarse-grained granular fills. Applications include reconstruction and stabilisation of natural slopes, embankments or dams constructed of (or at least partly from) mine tailings or other finer-grained materials. The project will consist of testing the DrainTube® material to determine its ability to convey water in saturated and unsaturated conditions. A computer numerical model will be developed using the properties of the DrainTube®, and a small physical model will be constructed to verify the numerical model. Parameters including spacing of tubes, slope of the ground, soil permeability, infiltration, and anticipated rainfall will be analyzed. The numerical simulation will then be optimized based on these parameters, and design guidelines will be recommended. The project partners will benefit from results that allow the DrainTube® product to be used confidently in engineering design.

An Analysis of the Cambridge Self-Help Food Bank Network and its Potential for Development

The project looks at the Cambridge Self-Help Food Bank to consider how the redevelopment of the existing network can promote opportunities for more integrated community development and cohabitation, while also improving access to food for vulnerable populations. The proposed method is to study the operations of the food banks by analyzing existing and new data, using geographic and statistical mappings, conducting interviews and undertaking comparative analyses with relevant case studies. In light of the organization’s impending relocation, the intention is to consider the operations holistically – across procurement through donation or cultivation, storage, distribution, kitchens, cooking workshops and other affiliated programs – so as to critically address the opportunities and potential limitations inherent to the spatial deployment of the organization in a single new site or across a number of different sites.
Ultimately, the ambition of the research is to think through the specific case of the Cambridge Self-Help Food Bank to spatially address the critical question of food security in mid-size cities.

Bacterial ATP synthase inhibitors as novel antibiotics for Gram positive and Gram negative bacterial infections.

The goal of this research project is to exploit a recent discovery made at Université de Sherbrooke and develop novel antibacterial agents for difficult to treat bacterial infections. The project will target both Gram positive and Gram negative bacteria, using a combination of structural biology, molecular modeling medicinal chemistry and microbiology.

Towards species specific management of invasive hawkweeds in British Columbia:Quantifying distributions, modeling potential invasion extent, and investigating genetic-morphometriccongruence

The species of European hawkweeds present in British Columbia are aggressive and ecologically

detrimental invaders of meadows, parks, agricultural lands and rangelands. Left unmanaged, these

species could cost the province of British Columbia upwards of $60 million in economic losses by

2020. The Ministry of Forests, Lands and Natural Resource Operations (MoFLNRO) is responsible

for addressing invasive plant species on Crown land. This collaborative project between the

MoFLNRO and UBC Okanagan will clarify the distributions and invasion extent of each hawkweed

species present in east-central British Columbia in order to inform management of these species. We

will use these data to predict, using Ecological Niche Models, areas of the province vulnerable to

invasion by these species. We also will determine if the current morphology-based identification

system is effective for on-site differentiation of these species. This research project will directly

inform and improve the effectiveness of managing these invasive weed species

High Performance Computing (HPC) of Full Waveform Inversion and Reverse Time Migration (FWI/RTM)

We will develop advanced software toolkits for seismic inversion and imaging. These method are called Full Waveform Inversion and Reverse Time Migration (FWIIRTM). The FWIIRTM will be used to obtain accurate 30 images and elastic properties of subsurface complex structures.

Determination the effectiveness of drought resilient bioretention bed in stormwater management

The greatest river in Calgary, Bow River, is an important source of water for industrial, agricultural and living activities for city and people of Calgary. With the incredibly fast of urbanization in Calgary, the natural landscapes are gradually replaced by impervious areas, such as urban streetscapes, houses and buildings. While the amount of water that cannot penetrate through those impervious areas during rainfall, known as stormwater run-off, will discharge into the Bow River and consequently increase pressure to water treatment systems, there are other extended droughts period that need to take potable water for irrigation activities. Therefore, this project focuses on analyzing the amount of stormwater run-off retained and treated using a bioretention system, and evaluates the possibility of using retained stormwater for irrigation. This project contributes to protecting the water of Bow River, which is one of the mandates of my partner organization Bow River Basin Council.

Dynamics of Viscous Fingering in Porous Media in the Presence of Injected or In Situ Generated Particles

In general, when a more viscous fluid is displaced by a less viscous one, instabilities grow at the interface between them which are referred to as viscous fingering. Viscous fingering is of paramount importance in many applications including, but not limited to, contamination transport in underground waters, enhanced oil recovery, filtration, and chromatographic separation of chemical species. As a result, understanding the dynamics of mixing induced by viscous fingering has received much attention, and has been the focus of many works. In this regard, the effects of dispersion, chemical reaction, heterogeneity, melting, non-monotonic viscosity, non-Newtonian fluids, multiple diffusivity, and non-isothermal displacement have been addressed in the past. In my PhD, I am working on the effect of injected (nanoparticles and nanocatalysts), and in situ generated (asphaltene) particles on the dynamics of viscous fingering in porous media. So far, this research led to publication of two papers and submission of two manuscripts.
Despite a large number of studies on viscous fingering, currently, there is an obvious knowledge gap in this area. In addition, an up-to-date critical review elaborating on various aspects that identifies critical areas for further research is lacking.

Évaluation des processus dominant le comportement géochimique de résidus miniers en conditions restaurée et non-restaurée par la modélisation de transport réactif

Les résidus de la Mine Raglan contiennent des minéraux pouvant réagir avec l’eau et l’air et potentiellement produire un drainage acide et riche en métaux s’ils ne sont pas gérés d’une manière optimale. Des essais au laboratoire ont permis de déterminer la qualité d’eau qu’ils produisent et leur comportement géochimique. La présente étude vise à évaluer des modélisations numériques simulant les réactions chimiques et l’écoulement de l’eau pour évaluer les processus contrôlant la production de contaminants. Des simulations seront effectuées pour cibler les principales réactions qui influencent la production de contaminants et pour évaluer le comportement des résidus pour davantage de scénarios et à plus long terme que ceux effectués au laboratoire. Ce projet apportera de l’information pour améliorer la gestion environnementale des résidus et sera utilisée dans le plan de restauration du parc à résidus.

Investigation of the relationship between firefighting water additive formulation and environmental fate and toxicity

Firefighting water additives are a mixture of chemicals that are mixed with water to more effectively extinguish fires (i.e., residential, industrial, forest fires). The use of these additives is likely to increase in fighting forest fires due to the projected increase in forest fire occurrence and intensity due to climate change. Ingredients of firefighting water additives used in the past were found to be persistent and detrimental to the environment. The Canadian company FireRein is working to design new firefighting water additives that are effective at fire suppression but also pose a relatively low risk to the environment. This project will investigate the toxicity of individual ingredients used by FireRein and new formulations water additives designed by FireRein on aquatic and terrestrial organisms. The objective of this project is to provide data that will allow FireRein to optimize the formulation of their new water additives so that they are as effective at fire suppression as additives currently on the market while also pose a relatively low risk to the environment.

Isolation et caractérisation de mégacaryocytes humains du sang adulte et du sang de cordon

Initialement découvert dans les neurones, le Brain-Derived-Neurotrophic Factor (BDNF) est un facteur de croissance qui module la survie neuronale et la plasticité synaptique. Il joue un rôle important dans des pathologies cognitives comme la maladie de Parkinson et d’Alzheimer. Or, le BDNF se retrouve aussi dans la circulation où il est emmagasiné dans les plaquettes à des concentrations qui peuvent atteindre jusqu’à 1000 fois les concentrations neuronales, ce qui en fait le réservoir périphérique le plus important. L’origine de tels niveaux demeure débattue puisque les plaquettes sont dépourvues de noyau, ce qui limite leur capacité de synthèse peptidique. Étant donné le rôle important du BDNF dans le système cardiovasculaire, il est primordial d’élucider son origine dans les plaquettes et les mécanismes régulant son stockage. Nous émettons l’hypothèse que la majorité du BDNF et de son ARNm sont hérités des mégacaryocytes, cellules précurseures des plaquettes, mais que les plaquettes peuvent aussi l’internaliser de la circulation. Notre but est donc d’élucider l’origine du BDNF et de ses isoformes dans les plaquettes ainsi que les mécanismes de sa biosynthèse et de son stockage.

Photo-identification du dauphin de Peale dans le détroit de Magellan

Il existe actuellement très peu de données sur le dauphin de Peale qui permettent aux autorités gouvernementales de prendre des décisions éclairées en termes de conservation. Le projet de recherche tente de développer un répertoire photographique du dauphin de Peale que l’on retrouve au sud du Chili, en Patagonie. Le but est d’identifier les individus qui fréquentent les eaux côtières qui se situent entre la ville de Punta Arenas et Agua Fresca. La création d’un répertoire photographique permettra l’identification des individus et ainsi de connaître les différentes habitudes de vie de chaque dauphin. De plus, il sera possible d’évaluer avec une grande précision le nombre d’individus que l’on retrouve dans cette portion du détroit de Magellan. Par ailleurs, une première utilisation rigoureuse d’un drone afin d’effectuer le suivi du dauphin de Peale permettra d’évaluer les avantages et les inconvénients associés à l’utilisation d’un tel instrument. Toutes les données recueillies seront incorporées au système d’information géographique Web intitulé iCetacea afin de permettre le partage de données entre les groupes scientifiques et les citoyens voulant en apprendre d’avantage sur les mammifères marins.

Deep Fraud Detection

Financial fraud is a serious issue that is taking place globally and causing considerable damage at great expense. Statistical analysis and machine learning tools can help financial institutions detect different types of fraud. In some cases however, mislabeling and the cost of classification may actually increase the volume of ‘false positives’ for supervised methods. As the number of normal transactions in financial domains far outweigh the number of anomalous transactions, it is challenging to classify the anomaly labels. In this research project, a combination of semi-supervised and unsupervised Deep Learning methods will be applied to detect outliers from different perspectives.