Innovative Projects Realized

Preparation of an injection molding stainless-steel tool and optimization of the processing parameters to fabricate superhydrophobic silicone rubber insulators

This project is defined to mitigate the problems associated with the accumulation of ice and pollution on the high-voltage insulators and subsequent flashover and power outage. Superhydrophobic surfaces, having a controlled combination of low surface energy materials and surface roughness, are one of the best candidates for icephobic and self-cleaning applications. As the high-voltage silicone rubber insulators are manufactured using injection molding systems, this project aims to prepare an industrial injection molding system for fabrication of superhydrophobic insulators. To this end, proper surface features (in micro- and nanometer size) will be created on the injection molding tool. The molding parameters will also be modified to properly replicate the tool’s patterns on the silicone rubber surface. Consequently, the produced silicone rubber insulator, having surface micro-nanofeatures, will acquire superhydrophobic and subsequent icephobic and self-cleaning properties. This project can put the partner organization as the leading enterprises in the field of electrical transmission lines in Canada and worldwide.

STRUCTURAL HEALTH MONITORING AND LIFE PROGNOSIS OF COMPOSITE STRUCTURES

Structural Health Monitoring/Management (SHM) through adequate prediction of the remaining useful life of structures is a major area of interest for the aerospace community, especially considering aging aircraft where the growing maintenance costs can reduce their economic life. Also, composite structures due to their high strength-to-weight ratios, high stiffness, inherent corrosion resistance, and improved fatigue performance offer many advantages over the conventional metallic materials, and therefore are utilized in a variety of load bearing structures such as helicopter rotor blades, aircraft fuselage, rib chord, trailing edges, and cargo doors. This makes the understanding and then improving durability of composite structures very critical. Recent aircraft structural failures caused by undetected faults have resulted in a change in philosophy in design and maintenance of aircraft from fatigue safe-life to damage tolerance….

COVID19 and Disclosure of Risk in Energy Exposed Sectors

COVID19 has accelerated shifts in the global energy market such that energy companies and banks may be impacted in the medium to long term. At the same time, the decarbonization of the world’s highest carbon sectors present opportunities for alternative energy carriers. For investors and policy makers it is important to understand the scope and scale of these potential changes both from the point of view of individual companies as well as entire sectors. In turn, this presents an opportunity to identify capital investment flows aligned with decarbonization through these new energy carriers. This project aims to develop novel and scalable ways to understand financial trends by analyzing current economic factors – financial data, annual reports, forecast reports, as well as various developing events focused on carbon-based and alternative energy sources. To do so, we will first leverage and fine tune state-of-the-art tools in text mining and natural language processing to automate information extraction steps performed manually by human experts, contributing domain-specific corpora and resources for the research community.

Novel Portable Sensor to Reveal “Hidden” COVID-19 Infection

In Canada, as of April 21, only 569,878 people (~1.5% of the population) have been tested, with more than 38,413 positive COVID-19 cases identified; yet most people, including the asymptomatic COVID-19 cases, are not eligible for testing. Given that as many as 45% of all COVID-19 cases lack the known symptoms, or so-called asymptomatic cases, up to an estimated 17,000 cases could be asymptomatic and thus endangering public health. Moreover, these symptoms are not observed in the early stages of the disease, even in symptomatic cases.
Early detection and isolation of COVID-19 cases, especially asymptomatic cases, is therefore crucial for controlling this outbreak, and a novel method to identify asymptomatic cases is urgently needed. In response to this urgent situation, we propose a rapid solution to identify asymptomatic and presymptomatic cases through early detection of a “hidden” symptom. We will combine microfluidic, microelectronic, and open-JFET (junction gate field-effect transistor) sensing techniques to develop a safe, low-complexity, rapid, and easy-to-use technology to fight COVID-19. The proposed technology would allow rapid testing at home using a portable sensor to evaluate disease progress or treatment, eliminating the need to break quarantine (which could potentially infect others) as part of follow-up testing.

The Acquisition of Land for Community Benefit: Dynamics of Organizational Structure and Management

Union: Sustainable Development Co-operative (Union Co-operative) seeks to democratize city-building by empowering its members to collectively buy, upgrade, and manage commercial and residential properties to improve the environmental, social, and economic health of Waterloo Region. This project will support the evolution of the Co-operative’s model, the development of affordable housing for refugees, and create templates that can be implemented by other communities seeking to establish affordable rents and community control of property. COVID-19 highlights the critical importance of adequate and affordable housing for sheltering in place, and the need for additional capacity to welcome refugees as the United Nation predicts increased global instability.
The research will utilize document analysis, interviews, focus groups, and facilitated design sessions.

Semi and weakly supervised clinical data labelling for deep learning NLP

We are building a machine learning algorithm to be able to better understand the messy clinical notes that doctors write on patients and to automatically structure them. This will help hospitals and healthcare systems standardize and extract insights from these notes to make them more useful for determining how sick COVID patients are and how they are improving over time.

Smart Particles to Prevent COVID-19 Infection & Complications

The COVID-19 pandemic has had an unprecedented global effect. While social distancing and proper PPE can minimize the spread of the virus, at risk populations have remained vulnerable. With additional waves of infection are likely to occur, there is an urgent need for an innovative protective solution. In the current project, we will repurpose a patented platform technology from the Sheardown lab as a nasal spray in order to minimize the risk of COVID-19 infection. We will examine the antiviral, hydroxychoroquine, overcoming its side effects by delivering low doses directly to the site of action. We will also deliver Mannin Research’s proprietary Tie-2 inhibitor, which has the potential to decrease ARDS, an often deadly complication of COVID-19 infection. This novel delivery system will provide options in the absence of a vaccine, mitigating the effect of the potentially deadly but expected second wave of the virus.

Develop a web based geospatial artificial intelligence framework to track, visualize, analyze, model, and predict infectious disease spread in real-time.

As location is an integral part of both population and individual health, there is an emerging role for geospatial artificial intelligence (GeoAI) technology in health and healthcare. Novel infectious diseases such as COVID-19 are associated with population density, environmental factors, and interactions between humans and wildlife. GeoAI technology can be used to collect and analyze large amounts of spatial data, such as individual-level epidemiological data, social media, human mobility, transportation, mobile phone data, and vulnerable populations. We will develop a Web based GeoAI framework to track, visualize, analyze, model, and predict infectious disease spread in real-time. The framework will analyze and simulate the transmission dynamics of the COVID-19 outbreak to predict trends in the demographic characteristics and the dynamics of the viral spread. Our Web based GeoAI framework will help Canadians understand how epidemics such as COVID-19 spread, what activities put people at risk, and where the next coronavirus hotspots are likely to be in Canada.

A decision support tool for promoting new business models of cultural organisations in the context of COVID-19 crisis

The COVID-19 crisis has stimulated the need for digital transformation among organizations in order to adapt their business models and practices to survive from the pandemic. Data-driven solutions would emerge as the key of success by supporting cultural organizations to launch new products / services, developing marketing strategies, and improving customer experience.

Our research project aims at proposing an approach for the design and implementation of a decision support tool for cultural organizations with the focus on dashboards supporting data-driven visualization and decisions. The proposed decision support tool is strongly believed to catch up with trends in customers’ preferences and behaviors. As the dashboards and interactive reports are integrated and analyzed from the diverse sources, cultural organizations can rely on the proposed decision support tool to develop new product or service offerings, improve marketing strategies, and gain competitive advantages.

Mechanism of CoVID-19 induced hyperinflammation

This Mitacs-NSERC COVID-19 joint initiative is to investigate the mechanism of COVID-19 inducing hyperinflammation and cytokine storm. COVID-19 infected cells cause injury that triggers immune cells to release inflammatory cytokines. The partnership with Encyt Technologies Inc. and PI will use established immune macrophage cell lines to identify the molecular mechanism of hyperinflammation induced by COVID-19 ACE2/Ang-(1-7)/Mas GPCR platform in triggering the processes associated with this cytokine storm. We have also identified that the prodrug, oseltamivir phosphate (OP), is active against mammalian neuraminidase-1 (Neu-1), which we think may have relevance as a potential anti-COVID-19 drug. Neu-1 has been reported by us to control the receptors on immune cells involved in this cytokine production. The potential outcomes will provide valuable knowledge and scientific evidence to treat patients infected with the COVID-19 virus in exhibiting signs and symptoms of impending respiratory failure.

Assessing the environmental impact of a novel solid-wall containment salmon aquaculture project

The intern will conduct a bio-physical audit of Agrimarines new salmon farming technology in China
and British Columbia. By collecting data about the farming operations, he will be able to account for
all the materials and energy used to build and run the farms. This includes things like building
materials, feed and amount of energy needed to run the farm day-to-day. This inventory will then be
used to build a model, called life cycle assessment, which can assess the average environmental
impacts associated with producing one tonne of salmon. The model will also be able to identify those
parts of the farming operation which contribute the most to environmental impact so that the
owner/operators can take steps to improve those parts of the system. By reducing these impacts, the
system can be made more sustainable. In addition parts of the system that are running inefficiently can…

Artificial Intelligence-based COVID-19 Radiology Image Analytics and Beyond

The excessive daily requirement for COVID-19 tests has put the healthcare providers in an overwhelming circumstance, especially in rural communities, with a limited number of resources. Moreover, the existing COVID-19 screening technique is time-consuming and expensive, which can be a luxury for many communities. Thus, in this research project, in collaboration with the TBRHRI, we press the necessity of an automated AI-aided solution for efficient and faster COVID-19 diagnostic. The main challenges during this pandemic time undertaken by this project are 1) facilitate the COVID-19 screening process by employing AI-based automated techniques, and 2) deploy the AI module in a web or mobile application by ensuring data privacy. This research project can benefit the TBRHRI to deal with uncertainties and excessive time-delay in terms of the COVID-19 screening process by utilizing artificial intelligence with automatic radiology image analysis to detect COVID-19.