Innovative Projects Realized

Part of the water, part of the land’: Developing Indigenous water legislation for Carcross/Tagish First Nation – Year two

The protection of water is a priority for Carcross/Tagish First Nation (C/TFN) and revitalizing Indigenous legal and governance systems is fundamental to advancing Indigenous approaches to water governance. While the citizens of C/TFN have governed the waters and lands within their traditional territory since time immemorial, their Tagish and Tlingit legal orders have been disrupted by colonial forms of governance. Nevertheless, knowledge of these systems endures in practice and oral history. The revitalization of Indigenous legal traditions and forms of governance is a core objective of for C/TFN. Under the supervision of Carcross/Tagish Management Corporation, this MITACS Postdoctoral research will contribute to the advancement of innovative Indigenous approaches to water governance. It aims to collaboratively develop Indigenous water legislation, which brings together Indigenous legal traditions with western legal frameworks to advance contemporary legislation. TO BE CONT’D

Advancement of bio-processing technology for ginseng polysaccharides: a model for value-added medicinal plant polysaccharides development – Year two

This proposed project focuses on American ginseng (AmG), a natural herb native to Canada that has been used as a traditional medicine for many generations. Southern Ontario has become the World’s largest producer of AmG with annual sales of over $400M at the farm gate. Polysaccharides (PS) are a major active component of AmG showing various biological activities including anti-carcinogenic, anti-aging, immunostimulatory and antioxidant effects. Despite of having such significant pharmacological activities, they have limited bioavailability due to their physicochemical properties including molecular size, heterogeneity, and solubility. Herein, advanced state-of-the-art technologies including nanosizing and encapsulation will be employed for enhancing penetration, absorption and controlled delivery. In addition, fluorescent dye labelling of PS will be developed to allow the tracking of PS. Pharmacology of these innovative health products will be studied to evaluate their safety and delivery efficacy. TO BE CONT’D

Molecular Characteristics of Cellulose and Cellulose Derivatives – Year two

Cellulose is a commercially important biopolymer. Due to its abundance, biocompatibility and renewability it has shown important commercial applications in food, pharmaceuticals, biomedical. Depending on the origin and the processing methods used, the resulting fiber dimensions, structure, crystallinity and molecular weight (MW) can vary over a broad range. MW is one of the most important parameters in polymer characterization as many of its properties depend on it. Gel permeation chromatography (GPC) has been the technique of choice for determining these properties. However, this method has limitations and requires optimization. Its accuracy is dependent on complete dissolution of the sample. Cellulose is insoluble in most solvents due to its structure and strong hydrogen bonding network. Either derivatization or special solvent systems have been used for solubilization. Derivatization changes the chemical nature and there is no consensus on a definitive solvent system for cellulose. TO BE CONT’D

Optimization of astaxanthin production in large-scale cultivation of microalgae by utilizing industrial CO2 emissions – Year two

Haematococcus pluvialis is a green microalga that concentrates the compound astaxanthin, a commercial product with nutraceutical, pharmaceutical, cosmetic, aquaculture, and food applications. Astaxanthin is a carotenoid pigment with high antioxidative activity, used as a feed additive to provide a characteristic pink color to salmonids and shrimp, as well as a human nutraceutical providing protection from oxidative stress.
Maximizing large-scale biomass production rates and enhancing astaxanthin concentration in algal cells grown by capturing industrial carbon dioxide (CO2) emissions are the main objectives of this research study. TO BE CONT’D

Adversarial Examples and Uncertainty

While neural networks can classify images with very high accuracy, it was shown in 2013 (original paper by Szegedy et al) that it is also possible to make very small perturbation to an image so that the network misclassifies it (e.g. so that a panda is classified as an airplane). Many variations of this effect have subsequently been discovered and studied, but the mechanisms underlying this are still not well-understood. In this project, we plan to look at the system’s underlying uncertainties and certainties that might contribute to this effect. For example, even though the system might predict that the panda is an airplane with probability of 98%, is there some other way in which the system is in fact uncertain about this? How might we be able to quantify this?

Leveraging micro-sensors for minimally invasive neuromodulation device

More than 1/3 of people will be affected by a neurological condition in their lifetime. Seeking effective treatments for various brain ailments is paramount to a healthy and prosperous society. Both the quality of life and the economic impact of brain disorders is staggering, costing our healthcare systems billions of dollars annually. Unfortunately, most patients impacted by brain-related ailments can only be managed either pharmacologically or surgically; both approaches however fail to resolve the underlying neurological problems, which is likely to exacerbate as our population ages. Recent progresses in neural recording and stimulation have rendered the field of brain-machine-interfaces as a viable solution to treat, at least part, of the neurological disorder sufferers.

This more recent and medically proven approach consists of treating brain problems by engineering devices that can be interfaced directly with neural tissue. Such devices can record and electrically stimulate the brain, thus forming a two-way link between the brain and the electronics, allowing clinicians to “listen” and “talk” back to their patients’ brain, similar to pacemaker for the heart.

A capacity building initiative for rural community health research in Northern Newfoundland and coastal Labrador

Rural physicians are well positioned to conduct impactful community-based research but their research progress is often impeded by scarce funding and a lack of research assistance to bring projects to fruition. These issues are profound in Northern Newfoundland and coastal Labrador (NNCL), some of the most geographically remote areas of the province. We are seeking to enhance the subthemes of rural health economics, aboriginal health, community engagement, knowledge translation, healthcare innovation & outcomes, medical education united by the overall goal of social accountability: research for and about NNCL communities and citizens.

Quantifying fish-turbine interactions using VEMCO’s new high residency acoustic electronic tagging technology-Phase 2

It remains unclear if fishes that occupy Canada’s leading tidal energy test site in Minas Passage, Bay of Fundy, Nova Scotia, will be negatively affected by turbine installations. The objective of this project is to determine fishes’ interactions with operating turbines. Of approximately 70 species of fishes that interact with Minas Passage only three have abundance estimates (Gaspereau River Alewife; Shubenacadie River Striped Bass; Saint John River Atlantic Sturgeon) that are necessary to predict effects at the population level. Atlantic salmon are listed endangered by SARA so the loss of even one individual is significant. We will use new, innovative High Residency fish tracking technology from industry partner VEMCO to determine spatial and temporal overlap, and interactions of Alewife, Atlantic Salmon, Striped Bass and Atlantic Sturgeon, with operating turbines. This will provide information central to predicting negative effects of operating turbines, on fishes, at the population level.

Examination of beneficial effects of copper fabric on cardiometabolic status, and mechanistic role of gut microbiome

Copper has long been proposed to have important biological properties. Designed to deliver the health benefits of copper, CuTEC yarn is a USPTO|EPO patent pending, bio-engineered copper-based yarn that can be produced as products such as clothing and mattress ticking. Although many believe in the positive properties of copper for well-being, many remain retiscent to believe strong anecdotal evidence with regards to benefits of exposing skin to a pure metal or metal alloy. The current project aims to elucidate via robust experimental approaches whether the copper fabric can act to delay or attenuate inflammation, and associated complications, in mice. The new customers that will be generated by positive research are hard to predict, but for the small extra cost per item, Fine Cotton Factory predicts that copper products will dominate the textiles market, and under protection of its filed patents, copyrighted materials, advertising campaigns, internet sales, and first to market benefit, the ensuing revenue generation and exports would be enormous. Data from this project will guide Fine Cotton Factory in their future strategy and potential future collaborative research endeavours. The economic benefit would be robust to the Canadian economy.

AI-powered operating system for buildings: new performance metrics

In the real estate sector, a large volume of data is produced by businesses, commercial users and building visitors in a great variety of forms. For instance, three extensive sources of data come from unstructured text (e.g. documents, contracts), numerical data containing resources consumption and sensor/image-type data describing user behavior. A challenging problem for the sector is how to process the generated data into a useful asset that can provide insights to help business decisions, optimize user navigation and automate building-related processes. In this context, modern machine learning offers a plethora of solutions, ranging from well-established predictive statistical models to natural language processing techniques for automatically analyzing texts. Given the variety of out-of-the box machine learning methods, it becomes essential to be able to compare solutions efficiently in terms of quality measure, model training and generalization capacity for annotated data, as well as intrinsic metrics for non-annotated data. TO BE CONT’D

Oil price prediction using dynamic multiresolution modeling

In this project, we will explore novel modeling methods to predict oil prices, based on a combination of machine learning methods with dynamic multiresolution analysis. The objective is to develop a software to better forecast oil prices. Oil is the world’s leading fuel, and its prices have a big impact on the global environment, the economy as well as oil exploration and exploitation activities. Oil price forecasts are very useful to relevant industries, governments, and many individuals. Many methods have been developed for predicting oil prices. However, it remains one of the most challenging forecasting problems due to the high volatility of prices. In this project, we will explore novel modeling methods to predict oil prices, based on a combination of machine learning methods with dynamic multiresolution analysis. To evaluate and validate this model, we will compare the resulting forecasts with some popular oil price prediction models.

“Virtually” connected: Can virtual reality technology foster closeness and intimacy in romantic relationships?

Social connections, especially satisfying romantic relationships, are vital for health and well-being. Yet, couples are spending increasingly more time apart, limiting opportunities for connection and intimacy. However, engaging in shared novel activities (i.e. self-expanding activities) can help couples connect and maintain their relationship over time. Indeed, couples who experience more self-expanding opportunities in relationships feel closer to their partner and are more satisfied and connected in their relationship. As such, we will assess the extent to which virtual reality (VR) can be used to simulate face-to-face interactions and provide couples with the opportunity to connect and self-expand when apart. We anticipate that VR will increase perceptions of novelty, as well as perceived intimacy and satisfaction. Hence, we propose two studies testing whether using VR technology simulates face-to-face interactions fostering more closeness and intimacy compared to other forms of mediated communication (e.g., video interactions, instant messaging). Additionally, we seek to assess if orienting couples toward the opportunities for connection and novel experiences using VR compared can bolster feelings of closeness and connection during virtual interactions. Our results will also provide useful information about couple’s experiences using VR and provide Facebook with information about couple’s experiences using Oculus Rift.