Innovative Projects Realized

HIV infection and fertility among adolescent girls in sub-Saharan Africa

Adolescent girls in sub-Saharan Africa are the population group with the highest level of unmet sexual and reproductive health needs worldwide. Early onset of sexual activity is associated with a double burden of HIV infection and pregnancy. However, so far both problems have been analyzed as independent events. My objective is to examine fertility patterns among HIV-positive and negative adolescent girls in sub-Saharan Africa and study the mechanisms underlying adolescent childbearing and/or adolescent HIV infection. For doing so, I will use household- and individual-level data from the Demographic and Health Surveys collected in 32 sub-Saharan African countries. This project seeks to demonstrate that early pregnancy and HIV infection are two concurrent risks faced by adolescents in sub-Saharan Africa when they initiate sexual activity. Failure to address the dual problems of high HIV prevalence and high adolescent fertility could have negative short-term and long-term consequences for adolescent girls and their future children.

Antireflective nano-patterned surface treatment and glass flow modeling for large-scale glass applications

Based at Montréal, Canada, Edgehog specializes in anti-reflection and other light management solutions for displays and solar panel covers. Their nanostructuring technology aims to enable full display readability from all angles in direct sunlight and reduced power consumption through lowered screen brightness as well as boosting solar panel efficiency by increased sunlight absorbance. As their current technology proofs the concept at lab scale, further research is needed to find scalable fabrication processes for successful technology transfer to industry level and large-scale applications such as solar panel covers. During the proposed project, two academic interns will build on prior build preliminar technology developed under a Mitacs Accelerate grant to contribute to development, and process prediction by numerical modeling, of a scalable fabrication processes that is compatible with state-of-the-art devices and large-scale solar panels. Results of the study will be transferred to Edgehog supporting this Canadian company in successfully entering this market internationally at large scale. This will help position a Canadian company at the forefront of this key market in the electronics and solar industries, leading to the creation of new knowledge on high-precision advanced manufacturing technologies and the creation of new jobs, and thereby provide a benefit to Canada overall.

Effective dynamic stiffness of piping systems under dynamic excitations

Dynamic loading has a significant effect of the structural response of piping systems. Pipelines transmission and distribution systems consist of various components such as pipes, the underlying supporting structures, pipe supports, and fluids conveyed through pipelines. Interactions effects of all these components are not well addressed in the literature. Inaccurate predictions of the response of piping system under dynamic excitation may cause structural, functional, and operational failures which have a significant influence on the society, environment, and economy. This research seeks to develop practical approaches to accurately predict the structural response of piping systems under dynamic loading. At the end of this research, the partner organization will be provided with practical techniques to properly analyze piping systems and choose suitable pipe supports under dynamic excitation.

Identification of Optimum Digestate Management Option for an Anaerobic Digester in the Fraser Valley

Anaerobic digestion ias a process that converts the organic waste into methane-enriched biogas and fertilizer by combined action of a mixed community of microorganisms in the absence of oxygen. Fraser Vallet Biogas Ltd. operates BC’s first anaerobic digester that utilizes on-farm and off-farm waste to generate biogas (Methane) and digestate. Crrently the digestate produced is field-applied locally without being dewatered. The volume of the digestate produced daily is very large compared to the amount handled which constrains the volume of waste input that the anaerobic digester is able to process due to the fixed storage capacity. Therefore, Fraser Valley Biogas Ltd. would like to explore various alternative digestate treatment ideas for a better digestate management. In this project, the intern will carry out an extensive literature review which will cover various farm-based digester operations and digestate management practices described in the scientific literature, reports or online sources. Using the data collected, a cost/benefit analysis will be performed. The project deliverable, a final report, is expected to present a fairly clear idea about the direction that Fraser Valley Biogas Ltd. is recommended to take to improve its digestate management.

The Effect of Droplet Size on Automotive Paint Colour

Spray painting in the automotive manufacturing industry is an extremely difficult technical challenge. Approximately 25% of cars coming off the assembly line must be reworked or scrapped due to a poor paint job. Previous research has shown that the droplet size distribution of the paint being applied to the car is important for the final coating finish and colour. In this project, experiments using an automotive paint spray robot will be done to collect droplet size information and paint coating quality and colour data. The correlation between the droplet size distribution and coating quality will be investigated and the results will be used to develop a model to predict when a spray will produce a poor coating based on the droplet size information. This project will further validate Mazlite’s technology in optimizing the automotive paint spray process and accelerate the commercialization of their product line.

Calibrated and automated recognition of barcodes in complex, highly variable scenes

The main objective of this project is to investigate, develop and evaluate state-of-the-art artificial-intelligence (AI) algorithms for the automatic recognition of extremely diversified barcode instances, in complex, highly variable and non-controlled scenes. The application area is of high interest to the industrial partner, and the ultimate goal is to build a state-of-the-art, automated and well-calibrated barcode analysis system, which meets challenging industrial expectations of high accuracy and computational efficiency, while providing measures of confidence of the predictions (to mitigate the risks associated with potential errors). The recent years have witnessed substantial technical advances in deep learning (e.g., convolutional neural networks), which promises to address such complex image analysis problems. The project will involve one intern (a PhD student), whose objective is to adapt, extend and develop state-of-the-art convolutional neural networks for training automatic recognition models, while accounting for specific industrial challenges: high-accuracy requirements, the need for effective uncertainty estimation to mitigate the high cost of errors, and the need for active learning and exploring the diversity of large-scale unlabeled data. These model-calibration, semi-supervision and active-learning problems are of great interest to the industrial partner and to the computer vision community in general.

Examination of Foundations and Disbursement Quota in Canada

The purpose of this project is to provide a study of charitable spending by members of Philanthropic Foundations Canada, document the historical impacts brought about by changes to Canada’s disbursement quota (DQ) policy, and recommend changes to the T3010 form. The intern will lead knowledge generation in the form of member engagement, issue briefs, and attending conferences. Throughout this process, the intern will encourage Canadian charitable foundations to embrace DQ-related policy positions that promote sustainability and the success of the charitable sector as well as supporting the application of best-practices. This research will provide a foundation for further study.

Understanding minke whale migration, feeding, and population structure in the North Atlantic

Minke whales are common in the North Atlantic, but there are huge gaps in scientific knowledge about the species. Through collaboration with Mériscope, we will attach satellite tags to minke whales that feed in the St Lawrence Estuary (SLE) in the summer to track where they migrate throughout the rest of the year. At the same time, we will collect tissue samples from the SLE minkes, which we will analyze in comparison with minke whales across other parts of the Atlantic. By looking at their genetics, we can identify differences and connectivity between groups, and using other chemical signals in their tissues, we can shed light on the whales’ diet, which in turn can provide information about the larger ecosystem. Overall, having a better understanding of minke whale biology will be essential both to their conservation and to understanding how climate change is affecting the North Atlantic marine landscape.

Improving power production by better recognizing power quality issue events with machine learning

Solar energy offers a green energy future both for Canada and the world. To best collect this energy, solar farms, collections of solar panels, are often distributed to ensure efficient local collection. Weather is often a challenge for production; however, the failure of components can also adversely affect this as well. These failures can be difficult to track and predict; in this project, we propose to develop tools to help operators expect events that could lead to power losses and improve solar energy harvesting using both standard analytical tools and machine learning. This will lead to improved economic benefits for Canada and production efficiency improvements.

The effects of stress during white sturgeon early life history on larval physiology, development and olfactory sensitivity

Elevated levels of stress hormones (i.e. cortisol) provide a potential mechanism by which substrate condition affects larval development and survival in the endangered white sturgeon. The possibility that stress hormones mediate larval response to substrate conditions will be investigated by artificially elevating cortisol levels and identifying effects on larval physiology. Cortisol levels of wild caught adult fish will also be investigated to determine the effects of capture and handling on spawning success and larval quality. Two final projects will investigate whether substrate condition (habitat stress) affects larval olfactory development and/or thyroid hormone levels. Both of these factors may be linked to the mechanism of imprinting by which fish return to their birthplace to spawn (e.g. salmon). A better understanding of factors affecting larval survival and quality will help both project partners implement both hatchery and habitat based components of the species recovery plan.

Functional and structural characterization of clinically relevant amyloid fibrils

Irreversible, progressive, and incurable neurodegenerative diseases, such as Alzheimer’s disease (AD) or Parkinson’s disease (PD), constitute severe challenges for the modern and, in particular, for the healthcare system. Recent reports suggest that worldwide >50 Mio. people and >10 Mio. people are living with AD or PD, respectively. Both diseases are related to protein misfolding and aggregation towards elongated and helical amyloid fibrils. However, although amyloid fibrils are considered pathological hallmarks for AD and PD, the mechanisms of how such fibrils hamper normal cellular function are largely unknown.

The long-term objective is to shed light on the molecular basis of neurodegenerative diseases, in particular AD and PD. Therefore, we integratively combine high-resolution structure determination of clinically relevant amyloid fibrils with modern biochemical in vitro and in vivo characterization. Our approach may elevate the understanding of the pathologic mechanisms of neurodegenerative diseases, which is essential to promote the rational search for novel, innovative drugs.

Cross-frequency coupling in organoids

By growing stem cells in the right conditions, we are able to create miniature brain tissue structures called organoids. These organoids have many properties that make them similar to adult brains, which makes them a valuable tool to study how brain tissues might be affected by drugs, or how brain diseases like epilepsy can occur. One method that doctors currently use to choose which drugs to give to an epileptic patient is to examine the electrical activity of an epileptic brain for the kinds of rhythms that are present and to test different anticonvulsants over time to find one that works. Our project aims to measure the electrical activity of organoids for the same kinds of rhythms that might be present in an epileptic brain, to see if these same rhythms can exist in organoids. In order to make sure we mimic what happens in epilepsy, we can add a chemical convulsant to stimulate epilepsy-like behavior from the organoids.