Innovative Projects Realized

Impact Evaluation and Developmental Evaluation Planning with a Community- Based Not-for-Profit Organisation Focussed on Poverty Reduction

The purpose of this project is to assist a community non-profit organisation to build a comprehensive plan to evaluate its poverty reduction initiatives and activities. The agency partners with other non-profit agencies as well as with government partners, other stakeholders, and persons with lived/living experience. The purpose of the project is also to develop a set of common/shared measures of progress amongst several agencies as a demonstration project that will be evaluated to determine its utility across agencies and potentially within government to enhance collaboration and improve reporting.

High solid content wood foams for thermal insulation

The proposed research aims to develop a new wood foam to be used as thermal insulation in the construction industry. The wood foam has the potential to replace plastic foams and will be made out of unwanted forest residue (pine beetle kill, ash borer kills and forest trimmings) and environmentally-benign additives that impart strength and flame retardancy. Different water-based routes to prepare wet foams and then dry them will be tested. The mechanical, chemical, thermal, and flame-retardant performance of the foams will be characterized. Additionally, the foams will be ground up and reconstituted to demonstrate their recyclability. While the focus is on wood foams for thermal insulation, these foams may also find application in sound abatement, transportation, furniture, separation technologies, and packaging. This research will have social, economic and environmental benefits to Canada and is expected to generate new intellectual property for the partner organization while quickly moving them towards a low cost, scalable and “green” commercial foam product.

The role of regulatory T cells in blood during acute heart transplant rejection

Patients receive heart transplants as a life-saving measure after heart failure; thus, ensuring the success of the transplant is of utmost importance. Rejection is a primary cause for heart transplant failure, and consequently, patients must take drugs that suppress the immune system to prevent rejection. However, these drugs are highly unspecific and cause serious side effects that can be life-threatening. New immunosuppressive drugs that can prevent transplant rejection while allowing normal immune function can greatly improve care and patient outcomes. One type of immune cells called regulatory T cells (Tregs) can effectively suppress the immune system in a highly specific manner. We believe these cells can be effective in preventing and treating acute rejection. Working toward such a goal, our research plan is to first understand how Tregs behave during rejection. We will track their activities by measuring 46 genes in the blood of heart transplant patients throughout the first year post-operation. These genes provide valuable information on the risk of acute rejection at a given time and on changing Treg responses.

Portable Detection and Characterization of the Synovium and Effusion inMusculoskeletal Ultrasound

Rheumatoid arthritis (RA) is an autoimmune disease often characterized by the inflammation of the synovium and effusion of joints. RA is a chronic condition and may affect quality of life. Detection and characterization of the synovium and effusion in joints is most often assessed by a trained sonographer or radiologist. Recently ultrasound has been brought into the clinic and used by other trained healthcare professionals such as clinicians and physiotherapists. In order to assist in the acquisition of musculoskeletal ultrasound, the current proposal will examine the incorporation of artificial intelligence/ machine learning assisted guidance for scanning to allow for more accessible and standardized assessment.

Identifying Opportunities and Barriers for Local Food Infrastructure in Yellowknife, NWT

Communities throughout Canada’s North are turning to small-scale agriculture in hopes of solving food security issues, fostering economic growth and adapting to climate change. The City of Yellowknife has developed an Agriculture Strategy to build a resilient local food system. Through an emerging partnership between the City of Yellowknife and Wilfrid Laurier University, the Mitacs intern will engage community members and local food actors to identify how potential infrastructure, such as a food hub, can foster opportunities and address community-defined needs to enhance the local food economy. Through interviews and focus groups, community members will envision a sustainable food system in Yellowknife and provide input into how infrastructure can improve access to healthy, locally produced food and support the emerging local food economy. This research will result in recommendations to the City Council on infrastructure, programming and policy needs to further the dialog of local and sustainable food systems in the North.

Effect of harvest time on cattail (Typha) fibers for non-woven applications.

The objective of the proposed project is to develop the fibre properties of the common cattail, Typha latifolia, and to investigate the effect of harvest time on fibre quality as it relates to nonwoven applications, such as composites and packaging industries. Recent study has revealed that cattails contain fibres with properties that suggest applications in industrial applications, and Typha co., which is a Winnipeg based company, intends on finding market applications of these common wetland plants otherwise left unused. The aim of this study is to highlight the optimal conditions for harvesting cattails in a controlled environment, should commercial interest for cattail-based bio-products develop, in order to introduce and establish cattails as a novel resource in the Canadian bioeconomy.

Estimation of Disease Severity in Rice with Deep Learning Neural Networks

NIRS is a popular secondary analytical method that is being used for non-destructive quantification of compounds and mixtures in the agriculture and agri-food sector. The study aims to estimate the starch content (amylose and amylopectin) in rice samples with NIRS. A dataset is being established by obtaining NIRS spectra (400 to 2500 nm, 0.5 nm resolution) on over 400 milled and ground rice samples. Iodine-binding and spectrophotometric techniques will be used for acquiring the ground-truth. Upon analysis, this study would report the methodologies and evaluation metrics comparing the conventional (PLS and PCA) algorithms with deep learning (ANN and CNN) algorithms. Moreover, If the deep learning models outperforms conventional models, a Python-based data analysis pipeline will be developed for the end-users

Formulations & Production Methods for Plant-based Salmon Fillet

This project seeks to trial the use of protein inputs from freshwater and marine algae and aquatic plants for use either individually or in various combinations in the formulation of an alternative protein fish product. The specific target species and cut for this product is an Atlantic salmon fillet. Therefore, algal biomass that contains the salmon-coloured pigment astaxanthin or astaxanthin extract on its own may be also trialed as ingredients. Overall, the physical, chemical and gelling properties of the different input materials will be characterized. The project will then explore ways of recreating the distinct structure of a conventional Atlantic salmon fillet by subjecting specific ingredients or formulations to either high-moisture extrusion or directional freezing. This project should help New School Foods understand what inputs and structuring processes should be considered for eventual commercial-scale production of an alternative protein Atlantic salmon fillet.

Investigating mycelial-plant biomass mat application to reduce early-colonizing weeds in row-crop agriculture

The intern will be investigating the use of plant crop biomass filled with fungal mycelium as means of stopping early-colonizing weeds in row crop agriculture. The crop biomass will be applied to the fields in liquid form and will solidify into a mat-like barrier. The intern will be coming up with the correct liquid formula in lab, and testing this initially in greenhouse trials. Once a suitable formula has been found, it will be produced at a larger scale and tested in fields owned by the industrial partner. In these larger trials, the intern will be measuring how effective the mat barrier is, as well as other soil values. The industrial partner will benefit by being able to manage weed control in a more environmentally friendly manner as well as potentially reduce the fuel required, and the amount of field tillage needed to control the weeds.

Multi-Gram Scale Synthesis, Purification and Formulation of Psilocybin

Mental illness and addiction refer to a wide range of disorders that affects mood, behavior and thinking and thus leads to depression, anxiety disorders, substance use disorder and stress. The psychedelic drug assisted therapy functions as a mental health therapy, which is evolving at a quicker pace nowadays. These drugs are useful in the treatment of anxiety, depression, post-traumatic stress, obsessive-compulsive disorder, substance addiction, cancer-related and end of life anxieties. So, many researchers believe that these drugs if administered properly, could revolutionize mental health care, without having adverse effects. We plan to synthesize a very promising psychoactive drug psilocybin in multi-gram scale with high purity and will prepare its various formulation to manage its accurate amount of administration and controlled slow release. It will be further evaluated for its biological activity in collaboration of Halucenex life sciences, Inc. Over the period of 8 months, psilocybin will be synthesized, purified, characterized and formulated at Acadia University and bio evaluated at Halucenex life sciences Inc.

Applying social psychological research to improve hearing rehabilitation outcomes for persons with hearing loss – Duplicated

Millions of Canadians experience hearing loss that impairs functioning and participation in everyday life, however, only a fraction of these individuals address this loss by adopting and using hearing aids. To address this gap, hearing aid research has traditionally focused on the biology of the ear to improve technical aspects of hearing aids as well as on individual factors related to hearing aid adoption (e.g., degree of hearing aid impairment). However, recently, research on hearing loss and rehabilitation has begun to recognize the relevance of considering social aspects, such as trust, social support, and stigma, in the adoption and of hearing aids. This project aims to investigate social psychological factors involved in hearing loss and hearing aid adoption and to provide clinicians with practical recommendations for improving healthcare quality services to patients with hearing loss. The partner organization will benefit from improved healthcare quality to support patients with hearing loss and to increase patients’ quality of life. In particular, better quality of healthcare services may lead more people with hearing impairment to adopt and consistently use hearing aids.

Economic forecasting with Agent based model under Bayesian framework

This project is about implementing a technique called Agent-Based modelling (ABM) so it can work better in real-world application. Particularly, it aims to help policy makers to do more adaptive decisions when the whole economics environment changes. For example, how to set the federal interest rate after COVID-19 panic? This model could simulate how all kinds of people, regulators, corporations, banks, or investors interact with others and how that interaction could cause specific things to happen to them and to the market more broadly. Even ABM can provide a realistic view of economics system, the validation and calibration are undeniably complex, which leads the result is hardly to interpret. Moreover, it is highly possible to see one model may performance well in one period and other competitor models may do better in another period, but there is no obviously criteria for choosing which model is the most realistic.
Second, the computational cost of ABM is essentially large. These issues have been a barrier to their more widespread adoption in economics application.

Our research will focus on solving those two problems. First, we would like to apply a Bayesian approach so we could compare models systemically.