Development of new RNA-guided dual-cleaving nucleases

Gene editing with RNA-guided nucleases based on the CRISPR bacterial defence system (clustered regularly interspaced palindromic repeats) has revolutionized both basic science and therapeutic applications. However, CRISPR associated (Cas) nucleases are not optimized for all types of gene-editing applications. In particular, the double-strand breaks made in DNA by the Cas proteins are imperfectly repaired by cellular DNA repair pathways that lead to a spectrum of gene-editing outcomes.

Developing MRI Biomarkers for the Differential Diagnosis of Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disorder associated with death of dopamine-producing neurons. This results in structural changes to the striatum, substantial nigra (SNc), and ventral tegmental area (VTA). Motor symptoms of PD are extremely heterogeneous causing a high rate of misdiagnosis of similar disorders (e.g. Essential tremor; ET) as PD. This study aims to identify objective indicators of PD with MRI, to help physicians differentiate PD patients from healthy people, and ET patients. 60 participants from each group will be recruited.

Fundamental Review of the Trading Book: Explainable Equity Volatility Models with Event Risk

The Fundamental Review of the Trading Book is a set of regulations set by the Basel committee, which is expected to be implemented by banks in Canada by late 2023. According to these regulations, in order to maintain stability in the banking system, banks need to post extra capital against the so-called non-modellable risk factors. As this extra capital could significantly increase the total market risk capital requirements for a bank, reducing the weight of these non-modellable risk factors can greatly increase the bank’s profitability.

Effect of far infrared reflecting clothing on sleep physiology and sleep-dependent memory consolidation in healthy adults

Sleep is crucial for the formation of novel memories, and it underpins much of our psychological well-being. Unfortunately, millions of Canadians suffer from sleep difficulties, which are especially prevalent among women and populations with low education and income. These difficulties result in poorer cognitive performance and reduced well-being. Finding solutions to these difficulties is often complicated, as pharmacological interventions often have unwanted side effects, and the most efficient intervention (cognitive behavioral therapy) is hard to access for most of the population.

Temporal Interference Stimulation in the Rhesus Macaque

Deep brain stimulation is a treatment method for Parkinson’s Disease, involving implanting an electrode deep into the brain. This procedure has a small but serious risk of complications such as hemorrhage and infection. However, a new stimulation technique, called temporal interference stimulation, may circumvent these risks, and allow for non-invasive deep brain stimulation. Temporal interference stimulation can selectively target deep brain structures in the mouse, however whether it will work in larger animals is currently unknown.

Intelligent and Autonomous Monitoring of Peak Demand Avoidance in Commercial Refrigeration Systems

The utility service providers calculate the peak demand charges based on the highest level of power consumption that a facility uses in any interval (usually 15 mins) during the billing cycle. The peak demand charges in facilities such as supermarkets could represent nearly up to 40% of the total utility bill. In supermarkets, besides the building, refrigeration systems could potentially play a major role in affecting the peak demands.

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.