Innovative Projects Realized

STING modulation for the treatment of triple negative breast cancer using novel glyco-based delivery systems Part 1: design and synthesis of novel glyco-based delivery systems

Breast cancer affect one out of eight women worldwide. Triple-negative breast cancer is an invasive breast cancer that is estrogen receptor-negative, progesterone receptor-negative, and HER2-negative. Triple-negative breast cancer is a type of breast cancer that is usually more aggressive, harder to treat, and more likely to come back (recur) than cancers that are hormone receptor-positive or HER2-positive. About 10-15% of all breast cancers are triple-negative. There is no successful treatment for triple negative breast cancer. Exploring novel avenues to target these particular cancer cells would be of great benefit to cure this unmet medical need. In addition, these cancers are highly metastatic. This proposal aims at using novel nanomaterials for the highly selective targeting of anti-cancer agents, thus limiting their cytotoxicity and side-effects. The proposed nanomedicine is composed of liposomal formulations that have been very successful in the recent pandemic COVID-19 (Pfizer and Moderna vaccines

Performance comparison of additional versus basic view representation in MPEG Immersive Video

Augmented reality (AR) and virtual reality (VR) enable exciting experiences such as virtual tourism or participation in a live concert from home. These applications are expected to benefit the society as well as being a source of significant revenues. However, such applications are very bit rate- and computation-intensive. The recent MPEG Immersive Video (MIV) format, part of the MPEG-I standard, enables the efficient compression of visual content obtained from several camera feeds by removing redundant information from the various views. This research project aims at investigating the parameters influencing the performance of the MIV format for some uses cases of interest to the industrial partner. This knowledge will enable the partner to select the best MIV format parameters and improve the performance of its products.

Project Co-ordinator

The Battlefords Chamber of Commerce is working to ensure digitziation of specific processes, for example, board of director elections, and the addition of online “wow” factors for its events – online development of registraiton processes, innvative in-event social media and bolstering its sponsor recognition and appreciation.
We also know businesses are challenged to find talent and workers to fill specific roles in their operations, so we plan to assist them with innovative tools and resources to attract and retain employees while developing strategies and processes for their business.

Multisensor Integration for UAV Indoor Navigation and Mapping

UAVs are becoming essential solutions in a wide range of industries. In this market growth, the potential of UAVs to fly in indoor environments represents a massive opportunity for companies. In particular, for applications such as medical care, search and rescue operations, and industrial management and inspections. The main concern of UAVs flying indoors is damage to people and vital infrastructure on the ground. To address this concern, UAVs must be able to self-navigate at all times, which is the first objective of this project, and automatically detect people and objects. In addition, self-learning, situational understanding, and smart avoidance are among the priorities of this project. SOTI is initially investing $20 million (USD) to fund this project and started collaborations with several universities, such as Toronto Metropolitan University and the University of Zurich. This project will help the SOTI extend its expertise in multisensor integration for navigation and thus more quickly achieve the objectives of its overall investment more quickly.

Use of bacteriophage-derived lysins in combating multi-drug resistant pathogens that cause bovine respiratory disease

Bovine respiratory disease (BRD) is the most important disease of feedlot cattle, which remains the leading cause of disease-induced economic loss in the Canadian cattle industries. BRD is induced by bacterial pathogens including the Gram-negative (G-) bacteria Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni. Even with current prevention and control measures targeting associated pathogens, the clinical impact of BRD continues and the resulted morbidity and mortality are still high. The mass medication with antimicrobial is raising concerns about emergence of multi-drug resistence. Moreover, during the last decades, no new antibiotics classes have been approved for G- infections. Novel methods targeting BRD-related pathogens are urgently needed.
Bacteriophages (phages) are the most abundant entities on the planet, bacteriophage-derived lysins/endolysins (LYS) are peptidoglycan hydrolases produced by phages and degrade the peptidoglycan at the last step of lytic cycle, resulting in cell lysis and release of progeny phages. But LYS has been widely developed against G+ bacteria but not G- bacteria due to the reaction nature of the enzyme. The proposed project aims to engineer LYS to develop a new class of antimicrobial agent against BRD-related G- pathogens with rapid action, relatively high specificity, non-toxicity and low probability of resistance development.

Same-Day Delivery Strategy into Retail Industry

The research will focus on understanding how same-day delivery courier companies can collaborate with retailers in order to form a mutually beneficial option for the end consumer. It will focus on choosing retailers that can have such service incorporated into their current operations. The challenges, risks, and considerations of the transition will be analyzed to help all parties involved. Ultimately, the research will validate the market, which will show whether there is a demand for such service.
The research will ensure Novex continues to operate profitably in the future by helping the company understand which retailers they can partner with using Zipments’ online platform, mobile app, and an API in order to help revitalize its growth in the quickly changing courier industry.

Data Amalgamation and Analysis across Agricultural Data Silos

The agriculture industry uses multiple disparate data sources. Examples of these data sources includes different types of sensors like moisture sensors, weather information, intelligent farming equipment like tractors, and grain tracking applications. This project will integrate two data sources into a common hosted platform. Existing software such as Esri, for geospatial data and analytics, PI System for operational data (IoT) to provide situational awareness, and Maximo for asset management and tracking.

While Mera‘s partners in the agricultural industry have outlined numerous specific needs that are often siloed and are difficult to integrate, this project will look specifically at the initial creation of a central system to consolidate data and provide a user interface to view this data. We will be taking two data sources and integrating them into a central storage solution. These data sources are being identified as part of an in progress NSERC Engage grant and they will be selected prior to the interns starting.

Développement du dialogue entre les perspectives scientifiques et autochtones sur la forêt boréale

Les Premières Nations sont de plus en plus impliquées dans les projets de recherche qui touchent leur territoire. Or, le développement de compétences en recherche en sciences naturelles au sein des communautés est nécessaire pour assurer une collaboration équitable et harmonieuse avec les institutions de recherche. La recherche proposée sera menée par la Première Nation Abitibiwinni, en partenariat avec l’Institut national de la recherche scientifique et Ressources naturelles Canada. Elle se décline en trois parties. Un premier volet vise à documenter la biodiversité dans le bassin versant de la Rivière Harricana depuis les perspectives autochtones et scientifiques, à partir de l’ADN environnemental contenu dans des échantillons d’eau. Le second volet porte sur la conciliation des valeurs pour la conservation du caribou forestier en contexte autochtone. Il vise à documenter les critères et valeurs des différentes parties-prenantes de l’aménagement du territoire et à développer des outils pour faciliter la prise en compte des enjeux autochtones. Le troisième volet s’attarde à la mobilisation des savoirs développés par la communauté dans ses différents partenariats de recherche. L’objectif est de développer du matériel pédagogique en sciences naturelles destiné aux élèves des écoles des communautés autochtones du Québec et du Canada.

Atmospheric water harvesting with carbon nanoporous sponges

Water scarcity threatens more and more people in the world. Cape Town (South Africa) imposed strict water restrictions in 2018 in response to shortages. Closer to home, water restrictions were put into place in Quebec in the summer of 2020, and First Nation communities have been confronted with fresh water issues for years. Water scarcity is a worldwide issue amplified by climate change, even in Canada. Alternate water sources, including atmospheric water harvesting, are required to secure a fresh water supply. Nanoporous sponges (NPS) are new carbon-based water harvesting material synthesized via the pyrolysis of low-cost materials, achieving comparable performance to metal organic framework (MOF) based systems, but at significantly lower cost. This material was developed at Polytechnique Montreal, in partnership with McGill University and Awn Nanotech, via a collaboration started in 2017. This research project aims to bridge the gap between lab scale prototyping and commercial uptake. We aim to: (1) Create a roadmap for NPS production at large scale; (2) Identify the key parameters impacting water capture and subsequent release through modelling and experimental validation; and (3) Fabricate and test water capture prototypes based on NPS technology and benchmark them against other adsorbents.

Using Phase Field Modelling and Machine Learning to Develop a Microstructure Design Platform for Hydraulic Turbine Steels

Materials fatigue has a detrimental impact upon the lifetime and cost-effectiveness of turbine equipment in Hydro-Québec’s energy production division. Metal fatigue, in turn, is linked to it internal microstructure, that developed in a metal during its fabrication or repair through welding, as is often done to damaged hydroelectric turbine blades that break during operation. The ability to efficiently and accurately predict the evolution of said microstructure is thus key to optimizing turbine blade performance. This project will develop and ultimately combine two state-of-the art computational approaches to develop a tool that can id Hydro-Québec to predictively design repair strategies of optimal turbine performance. The first will be a multi-physics model, called a phase field (PF) model, that can predict realistic solidification microstructures in steel. The second is a machine learning (ML) algorithm that will be trained from PF data to rapidly predict the evolution of microstructure from partial knowledge of initial conditions and processing environment. The first model will be used to investigate strategies for optimal microstructure design in turbine blade welding of austenitic and ferritic steels. The machine learning algorithm will be used to improve the PF model’s predictive potential over longer intervals of welding time.

Line of Business Explainability

Current planning/business analytics platforms automate time-consuming manual budgeting, forecasting, and reporting processes to help business users (e.g., financial officer, human resources, merchandising, marketing, or sales) make business decisions. Moreover, end users often use the interactive “what-if” analyses to understand the data from different perspectives and gain insights. However, the current way of presenting the analysis results has limitations, which only reactively responds to end users’ requests and requires sufficient knowledge on the part of the business users. In this research project, we would like to design and develop an involuntary analytics system that proactively provides suggestions for end users to look into different perspectives of the data, highlight a subset of the data that might be anomalous and worth further investigation, and generate transparent, accountable, and trustworthy explanations for the results of the analysis using terminology that makes sense to business users. In this research project, we will study how to improve the explainability of business analysis results and make it possible for almost anyone (regardless of skill level) to pinpoint business problems and make informed business decisions. The main outcomes will include the design and development of an involuntary analysis infrastructure that enhances business analytics.

Design of Prefabricated Exterior Wall Panels for Robotic Building Retrofit

Retrofitting aging commercial buildings from the exterior using wall panels can increase their sustainability and energy efficiency. The partner, RoBIM Technologies Inc., is developing an end-to-end automated solution by using robotic technologies and introducing more energy efficiency materials into the panel design. The combination of robotic prefabrication and sustainability of engineered wood products (EWPs) are well matched with the goals of greening Alberta’s construction industry and reducing carbon emissions from buildings. The purpose of this research is to develop a new EWP-based exterior wall panel system for commercial building retrofits from perspectives of structural integrity, thermal efficiency, robotic constructability. The outcome of this research will provide Alberta’s building industry with an example of robot-constructable panel system will facilitate future adoptions of the integration of EWPs and robotic technologies in building retrofits.