Innovative Projects Realized

Cryoprotecant toxicity accumulation models in mollusc oocytes

Cryopreservation of aquatic species’ gametes and embryos would enable stable and sustainable resources for genetic management in species preservation and breedstock for aquaculture. Cryopreservation of oocytes and embryos is of considerable financial interest to both Spanish and Canadian aquaculture, yet there have been no industry-scale successes in their cryopreservation. The Paredes lab at the University of Vigo is developing cryopreservation techniques for mussel oocytes, and the Benson Lab in the University of Saskatchewan uses mathematical modeling to predict optimal cryopreservation protocols in mammalian gametes. While the phyla are different, the underlying principles for protocol optimization are similar and have not been applied to aquatic species. Therefore, the student, Dominic Olver, who has been a part of the Benson Lab, will use data previously collected from the Paredes lab to develop a mathematical model of cryopreservation. TO BE CONT’D

Study Hot Cracking Susceptibility of Critical AA6111 Aluminum Alloys during Direct Chill Casting

AA6111 aluminum alloys possess a combination of excellent strength, good formability and good corrosion resistance that are widely use in the car panel manufacture. Direct chill (DC) casting process is typically employed for producing such alloy ingots. Despite its advantages, AA6111 alloys are considered as “hard-to-cast” alloy among 6xxx alloys because of high susceptibility to hot cracks. The present project will investigate the effect of chemical composition and grain refinement on hot crack susceptibility. Preventing one of the major cast defects, hot cracks, in aluminum ingot production not only increases the productivity of DC casting but also significantly reduce the production cost. This project will provide the best guideline to the industrial partner for improving the industrial production of aluminum alloys. The knowledge gained through this study would be highly beneficial for all aluminum industry in Quebec and Canada.

Sélection in vivo de symbiotes racinaires en vue d’améliorer la réhabilitation des habitats de la toundra arctique et alpine du Québec affectés par l’exploitation miniè

Avec le plan Nord 2035 lancé en 2011 (Gouvernement du Québec 2015), le Gouvernement du Québec prévoit investir dans la mise en place de 17 projets miniers dans le nord du Québec (au-delà du 49ième parallèle). Les écosystèmes fragiles comme la toundra subarctique ne peuvent pas retrouver leur état d’origine après une perturbation d’envergure comme l’exploitation minière. Il faut développer des techniques en harmonie avec le site à restaurer afin de rétablir les biens et services écosystémiques dès la fermeture du site. Plusieurs études on démontré que l’utilisation de champignons symbiotiques associés aux racines des plantes comme engrais vert permet le rétablissement des espèces végétales indigènes sur les sites dégradés. Notre projet vise à identifier les champignons qui offrent les meilleurs avantages de croissance et de survie aux plantes à réintroduire sur la mine de fer de Schefferville, dans le Nord du Québec.

Effect of Leading-Edge Manufacturing Defects on Propeller Performance

The objective of the proposed research is to investigate the performance degradation of a full-scale modified NACA 66 section, which is typically used for marine propellers, due to leading-edge (LE) manufacturing tolerances. Two-dimensional computational fluid dynamics (CFD) simulations will be carried out for the base section without defect (as designed) and sections with LE defects (as built) which are to be determined based on the ISO 484-1 Standard for propeller manufacture. The minimum pressures at various angles of attack (-4 degrees to +4 degrees) for these sections will be compared with those by Brockett (1966). The effect of LE defect on the cavitation bucket will be examined. Three-dimensional CFD simulations will also be conducted for the foil with 1m span, which will be tested in a cavitation tunnel. The experimental results will be used in future validation studies.

INSTITUTIONAL SUSTAINABILITY BENCHMARKING AND SUSTAINABILITYDEVELOPMENT STRATEGIES

sustainable institution using the STARS Sustainability Tracking Assessment and Rating

System as a benchmark. Analyze the baseline sustainability level of the college by the

application of set-target questions to staff members and students. USing this information, the

intern will indicate areas of strength and areas for development within the institution.

Resources may be created as a result of this research to support the sustainable path of

Lambton College. A literature research of successful sustainable measures taken by other

institutions will be performed to create a “Best Practice” report, and identify gaps and areas of

improvement. Practical recommendations will be provided and implemented. This work will

strongly support Lambton College towards its vision of becoming a leader in innovation and

sustainability.

Development of activated carbon from thermal coal for electrical double-layer supercapacitors – Part 2

Supercapacitors are electrochemical energy storage devices that promise fast charge-discharge rate, high power density, and long cycle life. However, low energy density and high cost of supercapacitors are yet to be addressed to catch up with the established market of batteries. This research project will design low-cost and high-energy electrodes for high-performance supercapacitors. To this end, we will develop activated carbons from thermal coal as the main component of electrode materials. This project will also determine simplified manufacturing process of supercapacitor cells with special attention to the cost. This project will help the partner organization, Atlas Power Generation Inc., commercialize supercapacitor technology for grid scale applications. This project will ultimately contribute to the transition of the coal industry into the clean energy technolog

Cellulose Nanocrystals Reinforced Nitrile Butadiene Rubber (NBR) nanocomposite dipped products: Processing and Structural Properties

The research project will develop processes for the fabrication of latex rubber films containing cellulose nanocrystals (CNCs) as reinforcement to enhance the physical properties of the films. Similarly, improving the compatibility between the latex rubber and the CNCs will be investigated which is expected to significantly improve the physical properties of the films, resulting in the possibility of using thinner films. Benefits to the partner organization will be the added value of CNCs especially to the rubber industry which will generate more market and revenue.

Automated detection of vegetation in proximity to distribution electric network

Tree contact with distribution lines is a leading cause of electric power outages for utilities in North America. Nova Scotia Power Inc. (NSPI) operates over 26,000 km of distribution lines. NSPI subscribes to a condition based asset management approach to mitigating vegetation that has the potential to threaten reliability of the distribution network. Currently, understanding the condition of the system in the context of vegetation proximity to conductor is an ocular exercise that is subjective in nature and lacks conformity. The key question intended to be addressed is how technology can optimize the collection of information regarding the location of utility structures and vegetation condition through remote sensing technology. To address this need, we will look at advancements in remote sensing technology to see if sensors available using photogrammetry and/or LiDAR can be rapidly deployed on utility fleet vehicles to aid in deriving asset condition.

Middle ear optical coherence tomography imaging system

This project will develop a microscope to allow ear surgeons to non-invasively see through the ear drum and into the middle ear. 250,000 ear surgeries are conducted annually in the US, but currently ear surgeons do not have a good diagnostic tool for imaging the middle ear non-invasively. For many forms of conductive hearing loss, conclusive diagnosis is only achieved in the operating room once the eardrum is cut open. Our imaging system uses optical coherence tomography, a safe, non-invasive imaging method that produces depth-resolved images of the ear and measure the response of ear structures to sound. This last feature allows clinicians to pinpoint the site of fixations or discontinuities that cause conductive hearing loss. The aim of this work is to answer the question: Can middle ear optical coherence tomography improve middle ear diagnostics and generate better treatment outcomes for patients suffering from conductive hearing loss

Using chemokines to enhance DC-based cell therapy

Immune therapies for cancer are in their early stages and require further investigation to improve their function. Chemokines and their receptors are responsible for directing white blood cells to various parts of the body. Because they are so important in controlling the immune response, they make ideal targets for therapy. To exploit this, we aim to use these receptors to identify cells that are ready to migrate and investigate the effect these cells have on tumour growth We expect that the cells which are more suited to moving to lymph nodes will be better at inducing an immune response capable of controlling tumour growth. Therefore, we suggest that using these cells as a therapy will result in smaller tumours. These tumours will also contain an increased number of white blood cells which are better equipped for killing the cancer cells.

Deep Portfolio Model

Portfolio management is a well-known multi-factor optimization problem, which involves historical price data, macroeconomic data and market indicators. Many researches have been conducted to find optimal portfolio allocation using machine learning. However, some limitations still exist, such as incorporating multiple factors into a single model, the robustness for encountering economic events, and potential bias by using historical data. The objective of the project is to develop an adaptive portfolio selection method to achieve the desired objectives (e.g. risk minimization, return maximization, index tracking) based on deep learning. The procedures include: Investigate the current limitations and identify their causes; Propose solutions to the limitations through literature review and empirical experiments; Implement the solutions into the portfolio selection model; Achieve more desirable results than the current ones. The improved method would be able to assist in automating portfolio management and be adaptive to a diversity of objectives and different types of data.

Deep learning-based Vision Inspection

Quality inspection is very important for manufacturing industry, current solution struggles with accuracy and requires machine vision knowledge to use. We are proposing to use deep learning technology to improve the performance of inspection as well as to ease the use of such system, so that user can simply use labeled data to build a new inspection system. Through the internship, the student will gain much hands-on experience with deep learning, the company will be able to commercialize the research result.