Les marais de Baie-Saint Paul sont de haute valeur environnementale, s’insèrent dans l’économie locale et régionale et dans l’orientation de mise en valeur du patrimoine de la ville. Ces écosystèmes sont le sujet de ce travail qui vise leur étude au niveau physique, historique, géographique et biologique. Quatre grandes questions sont abordées sur ces marais: […]

This project aims to develop and validate markers for adaptive neurological performance therapies for persons with moderate-to severe traumatic brain injury (m/sTBI), with the purpose to further develop clinical paradigms for at-risk populations. In order to accomplish this, we have formed a collaboration between two Universities (Université Laval and McGill University) and two industrial partners […]

The use of ionic liquids (ILs) in enhanced oil recovery is considered a new and promising technology as it has never been tested in any pilot plant or reservoir field. ILs are very similar to surfactants as they help reduce the interfacial tension, change the wettability of the reservoir, and some have strong viscous effect, […]

The most successful computer vision approaches are based on deep learning architectures, which typically require a large amount of labeled data. This can be impractical or expensive to acquire. Therefore, few-shot learning techniques were proposed to learn new concepts with just one or few annotated examples. However, unsupervised methods such as generative adversarial networks (GANs) […]

Depuis des milliers d’années, les déplacements des humains ont introduit des espèces exotiques dans des milieux où elles ne se retrouvaient pas naturellement. Une de ces espèces, le nerprun, a été introduite en Amérique du nord vers la fin des années 1800. Elle prend aujourd’hui de plus en plus de place dans nos environnements forestiers, […]

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is […]

Peroxisome Biogenesis Disorders of the Zellweger Spectrum (PBD-ZSD) are a group of inherited genetic disorders caused by mutations in any one of 13 PEX genes. Individuals with the common PEX1-G843D mutation consistently develop a retinopathy that progresses to blindness. To test whether we could slow visual loss in these patients, we performed a proof-of-concept trial […]

Peroxisome Biogenesis Disorders of the Zellweger Spectrum (PBD-ZSD) are a group of inherited genetic disorders caused by mutations in any one of 13 PEX genes. Individuals with the common PEX1-G843D mutation consistently develop a retinopathy that progresses to blindness. To test whether we could slow visual loss in these patients, we performed a proof-of-concept trial […]

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is […]

Vaccination is a widely accepted public health intervention, yet public confidence in vaccines is affected by misinformation about vaccine safety shared mainly on Facebook. This project aims to increase availability of credible information about HPV vaccines and influenza vaccines on Facebook. It includessix phases: 1) identify the most relevant approaches for marketing campaigns; 2) conduct […]

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is […]

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is […]