Innovative Projects Realized

Inorganic Porous Nanomaterials

Developing intelligent self-propelled boom sprayer for variable rate plant protection product application

This project will aim to convert a commercially available variable rate sprayer into and intelligent sprayer able to precisely spray the pests and weeds in the potato seeds only when needed. The detection of the pests and seeds will take place by cameras equipped with algorithms able to detect each target. The team members will establish communication between the cameras and the electronic components in the sprayer and modify other components to enable a real-time application. The benefit to the organization who are the owners of the sprayer will be to optimize the applications of agrochemicals which will directly lead to reduction in the cost of production of potatoes.

Functional Characterization of bicarbonate transporter

Experimental analysis of an optimally controlled microscale polygeneration system

Interaction between consumer and resource control of stream biofilm

Development of a standardized assay for after cooking darkening by which to support cultivarselection for breeding program and timing from storage for optimum processing

The intern will work with McGill University researchers Dr. Danielle Donnelly and Dr. Stan Kubow to identify

potato cultivars with better processing quality and less inclination to form dark-colored compounds after

they have been cut (enzymatic browning) or cooked (after-cooking darkening or ACD). ACD is related to

content of certain minerals, the polyphenolic chlorogenic acid, and mediated by presence of organic acids

and possibly other antioxidants. Phytonutrients will be examined for 3 cultivars with varying ACD symptoms.

A better understanding of ACD is important to the potato processing industry.

High Power Wireless Charging System for Electric Vehicles

Effects of biodiversity loss on phytoplankton – Zooplankton dynamics

A Novel Approach to Total Shoulder Arthroplasty using Intraoperative Manufacturing for Patient Specific Guides

Total Shoulder Arthroplasty (TSA) is a surgical procedure to restore overall comfort and function of the affected shoulder. Traditional methods of TSA are highly invasive, and result in 68% of patients developing future complications post operation. Therefore, F. Rodriguez & J. Giles developed two paradigm shifting surgical methods to reduce the invasiveness of the surgery and allow clinicians to have a more calculated approach when performing the operation. My work at Imperial College will consist of combining the most beneficial aspects of each of the two systems into one standalone system. The goal is to further develop and refine the approach to improve functional patient outcomes and reduce complications post-surgery. It is expected that each of the two systems will be evaluated to form an initial plan to design the newly refined standalone system. This system will be developed with the assistance of F. Rodriguez & J. Giles then rigorously tested to validate the standalone systems ability to improve upon other methods for TSA guidance.

Spiroconjugated Donor–?–Acceptor Dyes for Optoelectronic Devices

Use of X-rays as an alternative for fungal and bacterial pathogen control in seeds and stored food

The shortage and quality of food to feed the existing and growing population is an issue of global concern. There is also serious problem with the fungal and bacterial pathogens which result in losses of billions of dollars of annual loss of agricultural products. This project is an attempt to mitigate this with the use of X-ray treatment of seeds and organic products in stead of gamma rays or electron beams of a few MeV energies. This project, when completed, has the prospects to develop field-deployable treatment facilities for use around the globe, including developing countries in the tropical zones to mitigate the food shortage of the hungry world.

Computational study of the effect of gene deletion (synthetic lethal) on cellular growth in pathogenic organisms

Infectious diseases kill millions of people each year. For example, according to World Health Organization’s estimate, 10 million people contracted tuberculosis in 2017 resulting in 1.6 million deaths, which is approximately one death every twenty seconds . Increasingly, the pathogenic organisms, responsible for these diseases, are evolving to be resistant to drugs already in use to tackle them. Due to cost and time involved in developing new drugs, researchers around the world are developing mathematical models to understand the cellular processes of these organisms and use them to rapidly develop new drugs. This research project will use Genome-scale mathematical models for cellular metabolism in a pathogen to identify proteins and genes essential for the survival of a pathogen responsible for a disease. Results from this research are essential to addressing the twin problems of evolution of drug resistance in pathogens and drug side effects, while developing drugs.