Projets novateurs réalisés

Understanding mixed-severity fire regimes, their dynamics and their resilience to climate change in the southern Alberta Foothills – Year two

Mounting evidence shows that boreal and mountain forests are not solely driven by high severity fires that kill most of the above-ground vegetation (i.e. stand-replacing fires). Indeed, wildfire severity can be highly heterogeneous, leading to spatially complex forest landscapes, with multiple species and uneven ages. Many existing fire dynamics models do not explicitly consider the complex interactions and feedbacks between fire, vegetation and climate, which drive mixed-severity fire regimes. Yet such a model is crucial both for immediate landscape management and to manage for climate change. This project aims at building a spatially explicit, landscape dynamical model of mixed severity fire regimes using the SpaDES (SPAtial Discrete Event Simulator) framework. We will build upon an on-going Mitacs Accelerate project, during which model development and data compilation have been initiated, and take it further to consider climate change impacts on wildfire patterns and vegetation dynamics, but also changes in ecosystem stability and resilience. Our mixed-severity fire (MSF) model will be calibrated and validated on a study area in the southern Alberta Foothills, where evidence of MSF regimes exists and is being investigated further by another Mitacs Elevate project that will supply data for model calibration and validation.

Understanding mixed-severity fire regimes, their dynamics and their resilience to climate change in the southern Alberta Foothills

Mounting evidence shows that boreal and mountain forests are not solely driven by high severity fires that kill most of the above-ground vegetation (i.e. stand-replacing fires). Indeed, wildfire severity can be highly heterogeneous, leading to spatially complex forest landscapes, with multiple species and uneven ages. Many existing fire dynamics models do not explicitly consider the complex interactions and feedbacks between fire, vegetation and climate, which drive mixed-severity fire regimes. Yet such a model is crucial both for immediate landscape management and to manage for climate change. This project aims at building a spatially explicit, landscape dynamical model of mixed severity fire regimes using the SpaDES (SPAtial Discrete Event Simulator) framework. We will build upon an on-going Mitacs Accelerate project, during which model development and data compilation have been initiated, and take it further to consider climate change impacts on wildfire patterns and vegetation dynamics, but also changes in ecosystem stability and resilience. Our mixed-severity fire (MSF) model will be calibrated and validated on a study area in the southern Alberta Foothills, where evidence of MSF regimes exists and is being investigated further by another Mitacs Elevate project that will supply data for model calibration and validation.

Towards the development of a bone substitute-based targeted drug delivery tool to treat bone metastasis

We aim to develop human bone extracts mixed with commercially available bone putty and prepare customized 3D print materials, both of which are infused with anti-cancer drugs. These bone substitutes could be used to fill and stabilize the large empty spaces and to locally deliver anti-cancer drugs that kills any remaining tumor cells and promote bone healing following tumor resection in patients with bone metastasis. We also aim to establish a 3D bone metastasis-like model that will be used to test the drug delivery from bone substitutes. J & J could adopt and manufacture these new treatment modalities and commercialize them for hospitals to treat patients with bone metastasis.

Multilingual Semantic Similarity Engine

To communicate with their end users, businesses regularly produce written documents such as letters, notices, statements, etc.., in various languages. A set of rules are usually used to ensure that information in these documents is ‘correct’ and consistent across languages and communication channels. However, with the increasing volume and variety of information being sent out to clients, it becomes difficult to preserve the semantics of client messages across vocabulary and language variations. This project aims at creating algorithms capable of measuring semantic similarity of two text documents regardless of the natural language being used for each document. The set of similarity algorithms must scale with the size of the corpus being used.

Next-generation antibody drug for immuno-oncology treatment: anti-TIM3 antibody development

Unprecedented advances have been made in the treatment of cancer through the use of antibody against immune checkpoints, priming immune system instead of targeting cancer, with approval of several antibodies for multiple cancer types. However, so far we are merely seeing the tip of the iceberg because responses to this form of therapy are not universal.
Next-generation antibody drug is needed. TIM-3 negatively regulates immune system and is one of the next generation targets. We have generated 13 clones of TIM-3 antibodies, potentially can be anti-tumor drug. Here, a serial of experiments in biochemical, cellular, and animal models experiments are proposed. Evolution of this understanding will ultimately help guide treatment strategies to enhance therapeutic responses.

Research on the Social and Ecological Impacts of “The Thingery” Community Sharing Platform

The Thingery Sharing Inc. is the logistics provider and parent organization of five co-operatively owned community-level goods lending libraries known as Thingeries located throughout the Lower Mainland of BC. As a data-intensive enterprise, Thingery Sharing Inc. has the potential to track the social and ecological impacts of community level goods sharing. However, the existing literature provides insufficient guidance on how to structure indicators of social impact in the newly emerging sharing economy. This project will use social impact research to identify and understand the impact that a Thingery has on the social connectivity and ecological footprint of its members. It will analyze these findings to develop a set of metrics that can be incorporated into Thingery Sharing Inc.’s information systems for ongoing analysis and planning.

Development of plant-based beverage with high content and quality proteins

Plant-based beverages are inappropriate alternatives to bovine milk, due to lower protein content and not sufficient amount of essential amino acids. To produce nutritionally complete plant-based beverage with high overall acceptability, the technological interventions and fortification techniques need to be developed. Oat is one of the promising raw material for preparation of functional plant-based milk due to the presence of dietary fibres and good nutritional quality of oat proteins. Appropriate complementation of oat proteins with other high nutritious plant protein isolate will enable to produce plant-based beverage with all essential amino acids required for a complete source of protein in a single serving. The applied interventions may lead to process improvements for better quality and performance of plant based beverages and further growth and global competitiveness of Canadian products in a global market

Data Driven Assessment for Self-Determined Employment

MatchWork enables non-profit employment support organizations to support marginalized people to find meaningful employment opportunities. This includes people with physical and mental challenges, veterans, new immigrants and refugees.

Improving Situation Awareness for a Collaborative Service Robot in Care Environment – Year two

Development of Collaborative Service Robot (CSR) technologies usually targets a certain population group like seniors or people with developmental disabilities (DD) and requires tailored and dedicated research and development. This project is ultimately seeking to provide a proof of concept of a CSR platform that can assist people with DD. The overall project involves research and development focused on two broad robotics themes: autonomous navigation and situation awareness. Through previous Mitacs Accelerate and NSERC Engage programs, Developmental Disabilities Association (DDA) and JDQ Systems Inc. as the industry partners have established the basics of a CSR through collaborations with academic experts. Therefore, the expected outcomes of this project are to advance the existing features and add new features to the existing CSR prototype. TO BE CONT’D

Improving Situation Awareness for a Collaborative Service Robot in Care Environment

Development of Collaborative Service Robot (CSR) technologies usually targets a certain population group like seniors or people with developmental disabilities (DD) and requires tailored and dedicated research and development. This project is ultimately seeking to provide a proof of concept of a CSR platform that can assist people with DD. The overall project involves research and development focused on two broad robotics themes: autonomous navigation and situation awareness. Through previous Mitacs Accelerate and NSERC Engage programs, Developmental Disabilities Association (DDA) and JDQ Systems Inc. as the industry partners have established the basics of a CSR through collaborations with academic experts. Therefore, the expected outcomes of this project are to advance the existing features and add new features to the existing CSR prototype. TO BE CONT’D

A Framework for Robust, Fast, Efficient and Configurable Navigation of Video Game Characters

We will create new software technology for generating intelligent-looking movement behavior

of virtual characters in video games. When characters move around in game worlds, they

typically plan their path around fixed obstacles and use some simple rules to avoid dynamic

obstacles, such as other characters. Recently a family of methods based on the concept of

Velocity Obstacles (VO) has been developed at the University of North Carolina. These

algorithms have been shown to produce collision-free navigation in theory and in practice.

We aim to extend these methods in two ways: (1) find approximate methods with very fast

and efficient implementations for real time games; and (ii) make the character behavior

“tweakable”, i.e. provide good behavior over a range of parameter settings so that different

virtual characters have perceptively different behavior while still navigating sensibly.

Optimization of novel antibacterials targeting the ATP synthase of difficult pathogens

The proposed research project aims to optimize novel antibiotics for difficult-to-treat bacterial infections, particularly those involving Staphylococcus aureus or Escherichia coli. Toward that end, three post-doctoral fellows will be recruited, two working on the synthesis of analogues of two classes of molecules in the lab of Pr E Marsault (Université de Sherbrooke), the third on the biological evaluation of such analogues in the lab of Pr F malouin (Université de Sherbrooke). The first class of molecules involve derivatives of a natural product, tomatidine, which has been identified as a promising lead molecule against persistent strains of S. aureus. The second class is a synthetic product identified via a recent screen. The ability to kill bacteria, the inhibition of the molecules’ target, the protein ATP synthase, and the toxicity of the molecules will be assessed, to ultimately deliver a lead candidate for subsequent preclinical evaluation.