Optimizing Exploration Success at the Troilus Gold Deposit, Quebec

Mining employs ~400,000 Canadians and generates billions of dollars for the Canadian economy. Western University and Troilus Gold Corp. recognize that innovation is central to responsible resource exploration and extraction. Canada is a world leader in mineral exploration and mining technology, but discovery of new mineral resources has declined, despite increasing exploration expenditures.

Open source Layer Batching For Waste Reduction In Multi-Material 3D Printing

The most popular type of 3D printing globally uses plastic filament. Historically, this has been done with only one plastic at a time. 3D printers can now use multiple materials and/or colors to be part of a single print. Unfortunately, today multi-material 3D printing results in a lost of waste plastic and the associated environmental problems. Each time a material change happens, waste is produced through nozzle priming and/or purging to get rid of the last material. 3D printing software typically changes the material on each layer meaning that every layer, a lot of plastic is wasted.

Polymer composites with graphene

With the increasing effects of Green House Gas (GHG) emissions on climate change, there is also increasing interest to alternatives to internal combustion engines for mobility. Battery electric vehicles are one route, and another is fuel cells. There is increasing interest in polymer composites that are not only mechanically strong and lightweight, but also have other properties, such as electrical and thermal conductivity.

Advanced Methods for Time Series Data Augmentation

Modern machine learning methods are data-intensive processes, requiring massive amounts of training data to achieve a high level of performance. As such, these techniques are challenging to deploy on tasks where datasets are especially difficult or expensive to obtain or where edge cases and other rare events are most relevant and worth learning. In such occasions, data augmentation techniques offer enormous benefits to alleviate the issue of limited training data.

Development of a novel automated device to detect lymph nodes in surgical pathology (cancer) specimens

Inaccurate staging of colorectal cancer contributes to poor patient outcomes and increased healthcare costs. The current staging process involves a manual and time-consuming search by pathology staff for lymph nodes (LNs) in surgically removed fatty tissues. These LNs are then investigated to determine if the cancer has spread, which informs treatment decisions. We developed a novel robotic system that leverages ultrasound imaging to automatically scan and mark locations of LNs for dissection by pathology staff.

Effective Algorithms in Polyhedral Geometry and Symbolic Analysis

The proposed research projects will expand the scope of computer algebra systems (CAS) into two areas where much remains to be done: symbolic analysis and polyhedral geometry. One of the proposed research projects will also strengthen CAS in one of their well-established territory, namely symbolic integration. These themes will support applications such as the analysis, transformation and scheduling of computer programs as well as the computation of limits of families of geometrical objects (e.g. tangent cones) algebraic geometry.

Synthesis of glycopolymers by in vacuo glycation

Sugars play many important roles in our bodies. For example, they provide a supporting environment around cells and are also involved numerous processes, including viral and bacterial infection. In addition to their natural existence, there is also interest in preparing sugar-based polymers, called “glycopolymers”, in the lab both to better understand biological processes and also to develop potential therapeutics. However, most methods to prepare these molecules are costly and time consuming.

Mobile Electroencephalography and Mobility in Parkinson’s Disease

Attention, an important aspect of human cognition, is needed for safe mobility and navigation through the environment. With age, the ability to move and navigate through the world requires greater cognitive resources. Previous brain imaging research has shown that mobility impairments are associated with reduced attention. However, previous work was limited to assessing attention while participants were stationary and/or in a laboratory environment, which does not necessarily translate to what would occur in the real-world.

Multi-scale Image integration for Surgical Guidance - Year two

During surgery, a neurosurgeon must refer to three levels of image information: macroscopic from the patient’s MRI or CT, providing anatomical context of the surgical target; mesoscopic information from a surgical microscope or exoscope providing a highly magnified view of the region surrounding the surgical target; and the most important microscopic information provided by histology samples of excised tissue that must be analyzed in a pathology laboratory.

Investigating the in vivo antiviral effects of “Pheophorbide a” in a mouse model of SARS-CoV-2 infection

The COVID-19 pandemic continues to represent a global health risk. Definite strides have been made to limit infection through the use of personal protective equipment and mass vaccinations, yet new variants of the virus that causes COVID-19 are still being detected in the population and spreading worldwide. As the pandemic enters its third year, medical professionals must focus on developing new ways to stop these variants. One way is to study compounds that are able to kill cells infected with virus and are known as antivirals.

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