Informal learning involves acquiring knowledge outside of a structured setting in which
learning is self-directed and developed from experience, exposure, and interactions with their
environments (Nelson et al., 2006).

Noise affects everyone, and our cities try to limit noise impacts through effective policy. We focus on the issue of night noise, where the needs of different people can vary widely between wanting quiet for sleeping and for the great nightlife that cities are known for. This collaboration between the City of Montreal and the Sounds in the City research team uses Montreal as a living laboratory to develop new tools and methods to take sound into account when developing and evaluating a new nightlife policy.

BACKGROUND: Viral respiratory tract infection (VRTI) is the most common illness in humans, resulting in a total economic impact of $40 billion annually in the United States. Taking into consideration the current novel coronavirus pandemic - impacting billions of people around the world, compromising the global economy, and putting extreme pressure on healthcare systems - it is imperative to identify novel ways to both detect and prevent VRTIs such as COVID-19.

The project addresses urgent and clinically-relevant questions related to COVID-19, which causes in some patients life-threatening respiratory distress, septic shock and organ failures. Patients in intensive care units were found to have significantly higher levels of high mobility group box 1 (HMGB1) than patients with milder symptoms. HMGB1 is a protein normally found in the cell nucleus that is released outside the cell under inflammatory conditions such as viral infections.

The post-doctoral fellow will first develop novel approaches for the unsteady flow design environment. The use of real-world automotive geometries will allow the post-doctoral fellow to gain valuable insights of the challenges in this field, a firmer grasp of the transient flow over automotive vehicles in real-world flow conditions and the use of commercial-industrial level numerical tools. In addition, the post-doctoral fellow will work closely with professional engineers from FCA and understand the intricacies and challenges associated with automotive vehicles.

Schizophrenia is a debilitating psychiatric disorder characterized by positive (hallucinations, delusions), negative (lack of motivation, flat affect), and cognitive (impaired memory and attention) symptoms. Aripiprazole, a dual-action antipsychotic, shows promise in enhancing brain structure and memory in schizophrenia, which may have downstream positive effects on negative symptoms and outcome. However, the mechanisms and timing underlying these potential effects have yet to be determined.

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Despite significant efforts in the area of prevention and treatment, tobacco and e-cigarette addictions remain a recognized public health problem in Canada. Artificial intelligence (AI) in health offers an innovative avenue in tobacco treatment: the combination of an intelligent pulmonary inhaler coupled with a mobile health app would offer a real-time nicotine cessation and self-care personalized protocol aimed at helping the user quit smoking or, at least, reduce the harms associated with tobacco consumption.

Biosensors are can detect a variety of molecules in a rapid and highly sensitive manner. A new biosensing technology was developed to allow scientists to customize the biomolecular target they wanted to detect, called an open-gated silicon junction field effect transistor (JFET). However, this technology lacks user friendly packaging needed accommodate its use in diverse research settings. This can discourage people from using and building new sensing platforms.

In recent years, automation has become more accessible to small- and medium-sized businesses, leading to an increase in popularity of ultra-compact and easy-to-integrate industrial robot arms like Mecademic’s Meca500. However, because of their size constraints, it is harder for these robots to accurately follow a programmed path. This research project aims to improve the path-tracking performance of Mecademic’s Meca500 robot by fusing state-of-the-art machine learning techniques with modern control design techniques.

The IPCC project aims to utilize the advancements in lasers, optics and semiconductor fabrication facilities to deliver a computing chip that uses laser instead on electrical signals to perform computations. The new paradigm of computation execution allows computations to be performed much faster at lower energy consumption which directly leads to lower costs for computations. The advantage is particularly huge for AI computations. The Interns will perform research work to design, fabricate and test the new chip and develop software that allow using this chip efficiently.