Innovative Projects Realized

Sparse array photodetector in multiplexed confocal FLIM

Confocal microscopy is a specialized imaging technique that is used by universities and pharmaceutical companies to perform drug discovery. The research team developed a multiplexing technique that can improve the imaging speed by 1000 times. In this project, the team will develop customized versions of the instrument with different cameras to cater to specific customer needs. Success of the proposed development will significantly strengthen the technology and pave the path towards a Startup company to bring it to the market.

Growing Healthy Bodies: The development of a healthy body score-card for Canadian children and youth

This project represents the initial step in a larger project, the development of a “Healthy Body Scorecard” which will allow for more comprehensive and holistic approach to measurement and classification of health in children. This particular project will involve an in depth review of current literature in order to identify the various forms of health measurement and the factors and behaviors associated with each. This project as a whole will be of significant benefit to the Sandbox Project and McDonalds Restaurants of Canada, the industry partner for this research. The Sandbox Project is a not for profit organization that is designed to improve the health of Canadian children. The Sandbox Project brings together industry partners, government, academics, policy makers and community members. The industrial partners involved include leading companies such as McDonalds Canada, Telus, Microsoft, General Mills among others. This project directly addresses the stated goals of the Growing Healthy…TOECONT’D

Multi-scale direct measurements and source determination of methane emissions in Montréal

Methane is a potent greenhouse gas and reducing methane emissions is a key strategy in many climate change action plans. Because cities and their methane emissions are growing, it is essential to characterize and mitigate methane emissions from urban sources. Because there are no published studies of methane emission measurements in Montréal, we propose to conduct direct measurements to quantify methane emission rates and attribute the emissions to sources in Montréal. The results from the proposed project can better estimate urban greenhouse gas emissions and provide new greenhouse gas emissions reduction options to governments and companies.

Penser l’intégration et l’inclusion sociale des enfants: le cas des familles immigrantes colombiennes à Trois-Rivières

L’objectif de cette étude est de décrire l’utilisation des services de garde par les familles colombiennes de la
Mauricie et leur impact sur leur vie professionnelle. Elle permettra de générer de nouvelles connaissances sur les
améliorations possibles au soutien offert aux familles étrangères.
Les caractéristiques du processus d’intégration actuellement utilisé par la ville de Trois-Rivières seront
documentées. La question des services aux enfants immigrés ainsi que l’intégration de leurs parents par le travail
contribueront à l’amélioration des politiques migratoires.
Nous décrirons l’utilisation des services de garde par les familles immigrantes colombiennes et les défis qui leur
sont associés, à travers un questionnaire en ligne et des entrevues semi-structurées. Le questionnaire
documentera l’utilisation des services de garde d’enfants et les pratiques éducatives utilisées dans ces centres.
Des entrevues semi-structurées permettront de recueillir de l’information sur l’impact de ce service sur l’accès des
parents à l’emploi.

Social Media and Canadian Women’s Physical Activity Participation: Developing a New Methodology for Understanding Digital Health

The proposed research will explore how Canadian women’s interactions with health and fitness content on Instagram impacts upon physical activity participation. This research is sorely needed because, while social media is increasingly pertinent to the formation of everyday health practices, this dimension is seldom explored. In addition, this project will pilot a novel method, developed by Hockin-Boyers, called ‘screenshot elicitation’, which seeks to capture the fast, dynamic, mobile and everyday nature of interactions with digital content. Whilst Hockin-Boyers has already begun to develop this technique as part of her PhD research, the Mitacs Globalink project will provide the space and resources to pilot and advance this methodology.

The findings resulting from this project have the potential to enhance Canadian women’s quality of life, health and wellbeing, by informing digital platform design, social media pedagogies, and public policy in Canada. Furthermore, by providing Hockin-Boyers access to the variety of expertise in Digital Health at UBC, new knowledge and methodological techniques will be brought back to the UK, thus enhancing capacity for further research and innovation

Exploring the Risk Factors for Sequential or Concurrent Dengue and Zika Outbreaks in a Naïve Population

Arboviruses pose an ever-growing concern as the habitat of vectors expand alongside climate change. The outcome of outbreaks is often heavily influenced by the immune status of the population. Different pathogens can either protect against others or increase susceptibility and morbidity depending on infection timings and how closely related the pathogens are. A good example of this is seen with flaviviruses, particularly dengue and Zika, where both cross-reactivity and antibody dependent enhancement is observed. Zika and the different strains of dengue are carried by the same vectors, Aedes aegypti and albopictus, therefore, concurrent and sequential outbreaks often occur in the same regions. Ontario, Canada has had persistent population of A. albopictus since 2016 putting it at risk of new arboviruses. This project aims to combine statistical models to map A. albopictus and mechanistic models comparing concurrent and sequential outbreaks of flaviviruses in terms of antibody dependent enhancement to explore the dynamics and risk factors associated with such outbreaks in an immunologically naïve population.

Impacts of warming on boreal peatland microbial community structure and function

Peatlands, a type of wetland containing a thick organic layer of partially decayed plant material, are the largest terrestrial carbon stocks. Climatic changes, including warming, could result in a lowering of the water table in peatlands, increasing oxygen availability to microbes and mesofauna allowing faster break down of the organic material and consequent release of this carbon back into the atmosphere. Northern regions, including peatlands found in Canada, are thought to be particularly vulnerable to climate warming. Using a unique climate manipulation experiment where two peatland sites, located near White River, Ontario, have undergone experimental warming for the past three years, we will investigate the impacts of warming on peatland ecosystems focussing on changes to soil microbial community structure and decomposition processes. We will link these changes in the soil microbiology to the changes in mesofauna communities and the wider soil food web dynamics. This project will enable us to determine the resilience of peatland ecosystems to environmental change. This empirical data can be used to inform policymakers and mitigation strategies.

Optimization of the machining processes of carbon/epoxy composites and multilayer materials (CRIAQ MANU413)

The first master student internship (5. Berube, Bombardier) concerns the optimization of trimming

parameters for two materials. The carbon-epoxy composites as well as the multi-layer material

including aluminum and titanium in stacks under the carbon-epoxy laminate. At Bombardier,

Sebastien will familiarizes with all the composite manufacturing process and the actual machining

done at one or the other site of the company through the key-role people involved in this

specialization area (machinists, technicians, engineers). He will also analyses the different existing

cutting tools from suppliers that the partners would be willing to test based on their production

requirements to come over the years. Sebastien would thus complete a literature survey concerning

the trimming of the two materials and explore the in-house setup utilized for their thin material

machining. Finally, in order to perform the machining tests at the university laboratory, a plan of

experiments will be proposed from the intern. He also will interact with Bombardier’s project leader (M…..TOBECONT’D

Predicting life history traits for data-poor ray species

Fisheries are the main global threat to elasmobranchs (sharks and rays). Elasmobranchs commonly display conservative life history traits (slow growth, long life, late sexual maturity and low fecundity), making them extremely vulnerable to non-natural mortalities. However, there is significant variation, with some species exhibiting life history traits more resilient to exploitation. In order to assess species status and fisheries sustainability, species-specific life history data are needed, yet these data are severely lacking. Novel approaches to utilise available data to determine life history for data-poor species is crucial in assessing their resilience to fisheries pressure and therefore the management and conservation actions required. This project aims to utilise Bayesian and machine learning statistical models to estimate the maximum intrinsic rate of population increase (rmax) for data-sparse ray species using widely available life history, phylogenetic, and environmental temperature data. This will allow wider assessment of status and relative resilience of different ray species that can be used to inform global fisheries management.

Using genetic variants as a treatment decision aid for the optimization of antipsychotic treatments: a critical appraisal of the literature.

The group in Canada has extensively studied the factors (known as biomarkers) that can influence how people respond to anti-psychotic drugs, including if patients will develop side-effects. Our group in Liverpool has experience with compiling and analysing the large amounts of evidence required to prove a link between the biomarkers, and the patient’s response. The current methods for doing this are time consuming and labour-intensive. During this study, we will trial a new machine learning method for analysing biomarker evidence to antipsychotic drug responses. This will be compared with a parallel analysis using the established methods. In addition to allowing a comparison of the two methods, an understanding of the evidence around biomarkers and anti-psychotic drugs will be generated, hopefully identifying biomarkers showing strong links with responses. Based on this, we hope to be able to make recommendations for the use of biomarkers in clinical practice.

Secondary forest permanence in the Brazilian Amazon

To avoid dangerous climate change, large quantities of carbon dioxide must be removed from the atmosphere. Forest growth is one of the most efficient strategies for achieving this, with tropical secondary forest key to recovering carbon stocks. The carbon benefit of secondary forest, which grows on cleared land following abandonment, is determined not only by its extent but also by its permanence. However, the patterns of its persistence are poorly understood. Secondary forest is a valuable resource and it is vital that we improve our understanding of it so we can ensure its potential carbon benefits are achieved. We will model the probability of secondary forest growth and clearance in the Brazilian Amazon using a number of forest characteristics (e.g. distance from roads, patch size) known to influence forest permanence and estimate the carbon potential of future secondary forest cover.

Photonic Computing and Brain-Computer Interfaces

My lab’s research projects involve developing integrated silicon photonic devices for both brain-computer interfaces and artificial intelligence computing hardware. My focus will be developing photonic computing hardware that is neuromorphic, meaning it emulates the way our brains work. My main objectives will involve developing and characterizing integrated photonic chip designs that involve functional and trainable light-based neural networks, such as networks comprised of silicon waveguides and phase change materials. Working with photonics provides the computing benefits of high bandwidth and fast signaling properties, so these photonic neural networks can theoretically complement traditional electronic circuits to lead to machine learning and artificial intelligence that is orders of magnitude faster and more energy efficient than today, enabling data processing in data-intensive and power-critical applications such as edge-computing.