Projets novateurs réalisés

Development of Optical Fiber Sensing Devices for Strain Measurementin Rotational Components

Rotational components (e.g., shafts) are key parts of machinery equipment in automotive, aerospace,
energy production, etc industries. These components are continuously monitored for structural
sensing and failure diagnostics by attaching sensing devices on them. This project aims to implement
optical fiber sensors for strain sensing in rotational components. The available technologies for strain
measurement in are prone to electromagnetic noise and disturbance and the methods available to
overcome it have caused high-cost products. Considering the unique features of optical fiber sensors
(e.g., small size, robustness to electromagnetic noise, long-range linearity, etc), they can effectively
replace the electromagnetic devices. This requires addressing the challenges associated with their
implementation which is a goal this internship project. The development of this technology at ATA, will
allow the company to enter into high-tech manufacturing and earn revenue. This will result in the
involvement of Managers, Sales staff, Engineers and production associates for both innovation and
production at ATA.

An Integrated Multi-Case Study Approach to Advancing Business-to-Business (B2B) Online Marketing Strategies In an Expanded Multi-sector Study with 15 Companies

Business-to-business (B2B) marketing is considerably different from the business-to-consumer (B2C) marketing. Marketing strategies do not necessarily translate from one segment to another. This is evident in the social media/online marketing arena where many of the strategies and tools have been developed primarily for B2C marketing which results in many B2B companies dismissing social media/online marketing tools as irrelevant for their business. While social and online marketing may differ for a B2B context, it should not be dismissed. A strategic approach for the B2B context can drive brand recognition, acquire new customers, and create significant financial returns for a company.
This proposal seeks to better understand how online and social media marketing are best applied within a B2B context. We propose that utilizing a multi-case study approach will provide project participants with the opportunity to better understand social media/online marketing tools and develop more relevant and applicable best practices for a B2B business environment. The project’s research will focus on earned and paid social media coverage/content and which will be analyzed using the tools determined by the project partners (SEM, Hubspot, CRM, and/or Salesforce) in order to identify broad themes and patterns applicable to the partner’s B2B marketing needs.

Generation of correlation hypotheses between Adverse Events (AEs) and NamedEntity Recognition (NER) of drugs in social media and scientific journals usinga machine learning approach

Pharmacovigilance (PV) has evolved and grown more complex over the past 5 to 10 years due to increasing data volumes, evolving regulations, influence of emerging markets and the emerging social media and innovative technological advances.
Fast detection of Adverse Drug Reactions (ADRs) could allow the pharmaceutical industry to anticipate and then to control more efficiently eventual risks associated to taking some medications. There is a clear that the social medias data base is important for continuous and automated ADRs surveillance and it may reduce the number of ADR related potential deaths [1].
The scientific literature review is requires for tracking and identification of risk/benefit ratio of drugs and safety issues.
Adverse Drug Reactions (ADRs)

Development of a commercial protocol to differentiate human pluripotent stem cells into skeletal muscle progenitor cells (hPSC-SMPCs) with transplantation potential

Recent scientific breakthroughs have led to the development of methods to differentiate human PSCs (hPSCs) into skeletal muscle cells. This has allowed, for the first time, the development of cellular models to study muscle diseases such as Duchenne Muscular Dystrophy and the possibility to utilize these cells for cell therapy applications. However, the reliability, efficiency and prober characterization of cells produced from these differentiation protocols remains a roadblock for their routine utilization by the research community. In this proposal we aim to develop a commercial kit to differentiate hPSCs into skeletal muscle progenitor cells (hPSC-SMPCs) with reproducibility between cell lines with various genetic backgrounds. Building on an existing partnership between STEMCELL Technologies and the Rossi Lab (UBC) this project will perform extensive phenotypic and functional characterisation of hPSC-SMPCs required to validate if these cells represent a therapeutically relevant cell type. We anticipate advancement of this technology will enable researchers to overcome previous roadblocks and facilitate the robust and consistent generation of large numbers of skeletal muscle cells. This new tool will allow researchers to study human skeletal muscle development, model muscle diseases, screen cells for drug discover and investigate the regenerative potential of hPSC-SMPCs in preclinical cell therapy applications.

Healing the body, healing the brain: Nutrition and exercise treatments for childhood neurodevelopmental disorders

In the absence of a clear set of recommendations from doctors for the treatment of

neurodevelopmental disorders (NDD) such as fetal alcohol, cerebral palsy, and autism

spectrum disorders, many parents and children affected by NDDs turn to unproven diet- and

exercise-based treatments. While some research suggests that such interventions can boost

brain functioning, very few studies of these programs look at their effectiveness for NDDs.

This project will produce a long-form piece of investigative journalism seeking to explore the

promises and dangers of relying on diet and exercise to remedy NDD. Sidebar articles with

multimedia components will further examine and provide alternative angles to the use of such

non-drug treatments. Additionally, monthly articles about NDD science and related social and

legal issues will be produced. Work will appear in The Vancouver Sun, in print and online

versions. Ultimately, this work aims to benefit The Sun’s audience by explaining complex

science and ethical concerns in plain language that accurately reflects the facts…..TOBECONTINUED

Curiosity driven reinforcement learning for molecular design

Organic molecules are used in many areas, for example in drugs or solar cells. However, the development of new organic molecules with desired properties is difficult, time-intensive, and requires a lot of trial and error. A new line of research uses artificial intelligence to partially automate this process and make it more reliable. This project aims to further advance the approach. Specifically, the use of curiosity-driven reinforcement learning will be explored. Reinforcement learning is a kind of algorithm, that teaches an artificially intelligent agent to achieve a defined goal, like predicting molecules with desired properties. Curiosity in reinforcement learning generally helps the agent to explore its environment. Here, it has the potential to help agents better explore the chemical space, which can lead to faster development of better molecules that were previously overlooked by human chemists.

New therapeutics against T-cell acute lymphoblastic leukemia

A protein named c-Myc is causally implicated in over 50% of all human cancers. Preliminary work supports two proteins (POZ domain protein and c-Myc cofactor Miz-1) as a new drug target to disable c-Myc function. We have identified small molecules which act on this target and will now serve develop a series of optimized and effective molecules as cancer therapeutics.
To optimize these molecules, a combination of computational design and medicinal chemistry (synthesis and biological evaluation) will be carried out. Molecules that demonstrate high potency will be tested for chemical properties such as solubility in water (ie plasma) and for biological effects such as the effect of cell lines. The best compounds will then be scaled up, formulated, tested for required properties (e.g., toxicity, metabolism) and then in vivo. The results of the biological assays will guide the design and synthesis of molecules with improved potency, efficacy and pharmaceutical profile.

IoT Big-data-based network performance analytics

The main objective of the project is to upgrade the existing system at Cheetah Networks to make use of Canadian cellular CAT M1 monitored network data to develop innovative QoE analytics that can be used to provide actionable insights. The system will explore applying new techniques to capture in real-time QoE visibility into experiences locally, regionally and nationally. The primary methodologies that we will be employing are based on machine learning and deep learning techniques for data classification, clustering and analysis.

Statistical machine learning methods applied to ATB data for debt collection optimization, small business lending decision modelling, and open banking initiatives

The intern will research new modelling technology to determine if the new models can make a significant improvement in servicing customers for loan approvals, debt collections, and open banking. The intern will work closely with the partner to understand the banking process and opportunity. The partner organization will receive several benefits from working with the innovative and knowledgeable intern including cross-training of techniques through collaboration, enhanced model accuracy, and enabling the partner to test new techniques. The partner regularly hires former interns to open roles based on their experience on several projects and their proven performance in completing projects efficiently and innovatively.

Stories Incarnate: Using Body-tracking/Body-Sensing Technology to Create Interactive Narrative Experiences for Audiences

Ryerson’s Synaesthetic Media Lab is working with Cirque du Soleil Entertainment Group’s creative design studio, 4U2C, to develop several ways for audiences to meaningfully interact with live performance. This project is looking at how tracking sensors, computer vision, and digital displays can be used to track audience movements and/or emotions for audiences to be able to participate in the storytelling of a live show. Through this research, 4U2C — and Cirque du Soleil Entertainment Group and its numerous ventures — will be equipped with new, immersive design concepts and technologies that will bring audiences more closely into the co-creation role, as they partake in determining how a live story will unfold.

A Toolset to facilitate transparent exchange and querying of digitizeddocumen

Digitizing paper records facilitates efficient storage and lookup of information. It is

o,lten necessary to support advanced keyword-based querying features that allow

extraction of specific information and filtering of digitized documents. However, this

often requires manual intervention since records might have vastly different formats

even though they essentially contain the same information. This makes digitization

time consuming and increases costs for organizations that want to digitize their

records. This project will develop tools to scan a group of paper records serving a

similar function, e.g., representing invoices, and automatically indexing them through a

common set of metadata. This metadata would allow access and querying of digitized

records in a manner that is transparent to the formatting differences of the underlying

paper records. Automating this task can result in significant cost savings for those

undertaking digitization efforts.

Developing ‘all-natural’ approaches to food-grade Malic acid production

Malic acid is a naturally-occurring chemical found in fruits such as blueberries, apples, cherries and grapes. Malic acid gives food a sour or tart taste. Because of this, it is an important food additive used to balance sweetness or salt. Examples of industrial malic acid use in snack foods are sour gummy candies and flavoured potato chips. Bartek Ingredients Inc. is a Canadian company and the largest manufacturer of malic acid in the world. Malic acid is made commercially from petroleum products, a non-renewable resource. Bartek Ingredients Inc. would like to develop methods to use natural, renewable resources and generate malic acid for the food industry. Our project’s goal is to test and develop strategies that might be scaled up for Bartek’s commercial use. First, we examine methods to extract malic acid from food (a renewable resource); particularly, by-products of farming that would otherwise not be used. Second, we develop methods to make malic acid in yeast cultures that are similar to wine making, but where the end product is malic acid. Third, we test methods to purify food-grade malic acid that use less water and energy and contribute to greater industrial sustainability and lower costs.