Innovative Projects Realized

Materialism, Minimalism, and Motivation: The Impact on Athletes’ Financial Well-Being

The way people spend their money—their consumer behaviour—can be categorized in terms of materialism or minimalism. More specifically, materialist individuals tend to accumulate material goods, seek new acquisitions often overbuying, and cling to useless objects. In turn, minimalists purchase only essential items, reuse what is still functional, and discard the superfluous. Although materialism is often associated with extrinsic motivation and minimalism is associated with intrinsic, this relationship is more complex. For example, materialists can be linked to intrinsic goals when resource allocation is done in an altruistic manner aiming to help others, and minimalism can be driven to project an image of sustainability to achieve social status and prestige. It is important to better understand how motivation orientations impact consumer behaviours because these concepts impact financial well-being. A better understanding of how these concepts interact can help prevent the negative consequences that may accrue from low financial well-being (e.g., bankruptcy, stress and anxiety, depression). As such, the goal of this study is to explore the influence of motivation orientations on the impact of consumption behaviours on financial well-being.

Pharmaceutical testing capacity of novel intestinal organoid for motility studies

Intestinal ‘organoids’ refer to a miniature intestine that can be grown in a laboratory dish. This organoid can mimic the biology of the real human intestine. We developed a novel organoid which can replicate our intestine to an astounding degree. In this project, we aim to test the capacity of this novel intestinal organoid to assess the efficacy of existing intestinal therapeutic drugs and also test the safety of existing anti-cancer drugs. This will allow us to assess if this novel organoid will be useful in testing drugs in development in the future. Using small but biologically powerful organoid such as this could help us make more effective yet safer drugs, faster.

LR-FHSS-base network size estimation for dts-iot

The project’s goal is to find out if the network size estimator L-OCI, designed for direct-to satellite Internet of Things LoRa based scenarios, can be extended and/or adapted to work based on LR-FHSS. We want to see if they can handle many devices, and whether this combination is good or bad for a specific problem. If it works well, it can help connect more areas and resources. The benefit for the participating institutions is that they will learn how to use L-OCI and LR-FHSS together, which can be very helpful for future research in direct-to satellite Internet of Things.

A Computational Modeling Approach For Magnetic Resonance Navigation In Targeted Embolization

The proposed project is centered on developing an advanced technique known as Magnetic Resonance Navigation (MRN) for liver cancer treatment. This cutting-edge method employs the magnetic field of MRI machines to create micro-particle aggregates, which are then precisely directed to liver tumor-feeding arteries using magnetic field gradients. This approach promises to be less invasive and more accurate than existing treatments. A critical aspect of this project involves a thorough study of particle aggregation to ensure the safe delivery of treatment without harming healthy tissues. The aim is to refine and perfect the MRN process by modeling the various forces that influence these aggregates under blood flow conditions.

This initiative is a collaborative venture between CR-CHUM in Canada and Inria in France, bringing together their respective strengths in medical research and computational modeling. The expected benefit of this collaboration is twofold: firstly, to establish a new benchmark in liver cancer treatment that could significantly enhance patient outcomes; and secondly, to exemplify the power of international collaboration in fostering medical technological advancements. In addition to advancing liver cancer treatment, this project will significantly bolster the research capabilities of both institutions.

Body and Soul in Ancient Philosophy

This project focuses on the ways in which ancient thinkers conceptualized the notions of “body”, “soul” and their relationships, as well as the receptions these concepts had in classical, modern and contemporary posterity. This will allow studying the physical and mental dimension of the explanations produced by ancient thinkers for the phenomenon of life, mind, emotion, health and disease; for the interaction of the human being with his physical environment and with other sentient beings; for the interaction between between the life principle and the bodies of sentient beings. The incorporation of the body in traditional philosophical themes is, more than a current trend, a necessity, since it not only addresses the explanation of the human being in its entirety, but also sheds important light on the ethical and political dimension of human action. . Although the study of ancient philosophy is no stranger to this articulation, approaches that either focus solely on the role of reason or treat the two concepts in isolation have traditionally prevailed, favoring a dualist exegetical stance. . This project seeks to look at both perspectives and study, beyond Plato and Aristotle, other receptions that the problem had in ancient times.

Machine learning developer interns within cross-functional teams to develop and commercialize AI-powered solutions (12)

AltaML is an innovative company capitalizing on a major technological trend: artificial intelligence (AI) technologies, enabled by big data, are driving a fourth industrial revolution. AI will transform all industries, but traditional industries face challenges in implementing AI. AltaML has a unique business model to overcome barriers to adoption of AI solutions by industry, which is to bring the innovating startup together with the large organization, thereby bringing together rich datasets, AI talent with a playbook for industry application and the close collaboration of subject matter experts and AI experts–with a mindset for change. In addition to AI expertise, we bring agility that our large, corporate partners often lack, and which is so essential for innovation. With a strategic focus on AI adoption and product, AltaML works across industries as well as with the public sector using a co-development approach to create applied AI solutions as well as joint AI ventures. This rich, complex multisectoral environment provides the breadth that enables insights in one area to be applied in new areas, leading to ever increasing opportunities for innovation.

The project comprises internships in a variety of technical and business roles, which are: associate machine learning developer, business development associate, communications associate, finance associate, associate business solutions consultant, and project delivery associate. Outcomes will include algorithm creation and deployment, data visualizations, market research reports, sales collateral, competitive landscape analysis, feasibility analysis; key messages and content writing such as case studies and feature articles, financial model development, data analysis, financial reports and variance analysis, customer workflow mapping, business case reports, resource allocation plans, project update reports, and project plans.

Effect of parabolic solar trough collectors (PSTCs) on performance of solar-geothermal power plant.

In an existing geothermal power plant found in Aydin, Turkey, three parabolic solar trough collectors have been installed to develop a hybrid solar-geothermal power plant. The main reason for such a hybridization is mainly to compensate the inefficiencies in the geothermal power plant due to changes in the ambient temperature. The parabolic solar trough collectors heat the oil circulating within the tubes of the collector and transfer this heat to the brine. In this project, a thermal model of the parabolic solar trough collectors will be developed to assess the effect of design and operating
parameters of the collectors on the performance of these collectors as well as the overall system.

L2M- Neuromod, non-invasive brain stimulation and augmented reality sensorimotor training to treat chronic musculoskeletal pain

Neuromod is a revolutionary pain treatment designed to help improve the quality of life of the ~4 million Canadians living with chronic musculoskeletal (MSK) pain. Chronic MSK pain represents a major healthcare challenge due to the severity of pain, its impact on the individual, family, and Canadian Healthcare system. Current therapies for chronic MSK pain are a ‘band-aid approach’, focused on symptoms rather than targeting the underlying mechanism of pain. As a result, these therapies provide minimal to no relief and are associated with severe side effects. Therefore, there is a need for effective chronic MSK pain treatment options that are non-invasive, target the mechanism of pain, and have minimal side effects. Neuromod uses a non-invasive form of brain simulation and virtual form of physiotherapy, called augmented reality sensorimotor training. These techniques combine to block pain signals and retrain how the brain controls movement in the affected area. In this way, Neuromod targets the mechanism of chronic musculoskeletal pain to alleviate pain. This program represents an excellent opportunity to engage with and learn from stakeholders and other individuals involved in healthcare commercialization. I will have the opportunity to meet with stakeholders including physicians, physiotherapists, and people with lived experience to further understand the market potential for our treatment and refine its delivery. In addition, the commercialization of healthcare innovations face unique challenges associated with regulations of medical devices and its use as a therapeutic. This program will allow me to understand the regulations required to offer Neuromod as a therapy.

Internet governance, meet collaborative governance: An Internet governance model to support 21st century privacy and security challenges

THIS IS A GENERIC TEXT PUT IN PLACE AS THERE WAS NO PROJECT OVERVIEW

Jumeaux numériques pour la formation et le soutien à la planification de chirurgie d’arthroplastie du genou

10% des patients d’arthroplastie du genou, sont sujets à des complications qui peuvent nécessiter une réopération.
Pour les cas les plus complexes, les chirurgiens ont encore peu d’informations pour appuyer leurs décisions quant à l’approche opératoire. L’entreprise Philomec a développé dans les dernières années un modèle musculo-squelettique donc les capacités prédictives peuvent répondre à ce besoin clinique. Ce projet vise à utiliser ce modèle rétrospectivement sur des cas patients dans le but d’évaluer son niveau de crédibilité et son potentiel d’application clinique. Cet outil de soutien à la décision peut permettre à un chirurg

Mathematical modeling the impact of dietary macronutrients on energy metabolism in cats

North American pet food industry utilizes predictive equations such as those including modified Atwater equations to estimate energy density. However research has shown these equations tend to overestimate energy which predisposes companion animals to be in positive energy balance and obese. One method for attaining better predictive energy density models would be to quantify net energy content of different dietary formulations. Net energy is used for diet formulation within agricultural species, however it has not been validated within obligate carnivores such as the domestic cat. Furthermore, the contribution of protein and fibre on true energy content has not been assessed in obligate carnivores. Two studies will be conducted where increasing concentrations of protein and total dietary fibre will be fed to domestic cats respectively for a 14-day feeding period. Activity will be measured for 72 hours and on the final day 24 hour indirect calorimetry will be conducted in conjunction will total collection of urine and feces. The results will be used to estimate digestible and metabolizable energy, heat increment of feeding and resulting net energy. The in vivo data will be used for mathematical modeling of predictive equations that determine net energy content in feline diets.

Caractérisation de la réponse immunitaire adaptative contre l’infection par les Streptocoques B type III

Les Streptocoques du groupe B (SGB) sont connus pour être l’une des principales causes de maladies infectieuses invasives chez les nouveau-nés en Amérique du Nord mais également à l’échelle mondiale. Le contrôle des infections à SGB repose sur une utilisation d’antimicrobiens dont l’efficacité n’est pas totalement satisfaisante tel que la pénicilline étant administré en première intention en absence d’allergie. De plus, au cours des 20 dernières années, les isolats de GBS résistants aux antimicrobiens ont augmenté, en particulier une résistance aux macrolides utilisé en seconde intention. La vaccination représente un élément clé des stratégies de prévention, or à ce jour, il n’existe aucun vaccin commercial efficace. Pour aider à faire progresser le développement de futurs traitements pour prévenir (vaccins) ou pour traiter les infections à SGB tout en limitant l’accroissement des résistances aux antibiotiques, ce projet vise à mieux comprendre les interactions entre le SGB et le développement d’une réponse immunitaire adaptative efficace.