Innovative Projects Realized

Harm reduction-based programming and services for people living with HIV/AIDS (PLHIV) in a novel clinical care setting: the opportunities and challenges for clinicians, clients, donors and fundraisers

Substance use significantly impacts the health and health care of many people living with HIV/AIDS (PLHIV), especially those dealing with additional medical, psychosocial, and economic complications. The need for comprehensive care for this population is particularly important given the current opioid overdose crisis in Canada. In response, harm reduction (HR) services (e.g., supervised injection, naloxone training, etc.) have been implemented to reduce drug-related deaths and harms. However, such services are typically not provided within hospitals/outpatient programs. Little is known about how HR services in these contexts may affect clinical care providers, complex service users, or broader organizational operations. This project provides a unique opportunity to examine the impacts of introducing HR services in a clinical care setting. The Casey House Foundation, supports a small community-based hospital which provides in/outpatient care to PLHIV with complex needs. This research will investigate the opportunities and challenges of implementing HR services from various unique perspectives (i.e., physicians, clinical and foundation staff, clients, donors) and collaboratively create a framework for evaluating these services. The foundation supports HR interventions to optimize safety and retain clients in care, and wishes to introduce these services in ways that also increase collaboration, expand clinical expertise, and engage donor support.

Developing seismic reliability analysis methods for complex infrastructure systems

Evaluate the seismic performance of complex infrastructure systems considering various uncertainties of structural system based on understanding of structural failure mechanism by the earthquake. To do this, it is necessary to estimate the seismic capacity and seismic demand of the structure in a stochastic manner. Therefore, accurately estimation of the seismic capacity and the capacity correlation between related structures as well as develop of the quantification method of the correlation coefficient will be carried out in this research project. By quantifying the seismic capacity correlation that has been excluded in previous research efforts due to the lack of novel methodology and difficulty of nonlinear structural analysis, it is possible to reduce the analysis time of many researchers around the world and make it easier for researchers to incorporate significant effects of the seismic capacity correlation on reliability analysis of complex systems.

Multi-agent reinforcement learning for decentralized UAV/UGV cooperative exploration – Year two

Over the last decade, artificial intelligence has flourished. From a research niche, it has been developed into a versatile tool, seemingly on route to bring automation into every aspect of human life. At the same time, robotics technology has also advanced significantly, and inexpensive multi-robot systems promise to accomplish all those tasks that require both physical parallelism and inherent fault tolerance—such as surveillance and extreme-environment exploration. Decentralized control laws are key to achieve reliability of these systems (as they eliminate the risks posed by single-points-of-failure). Yet, the effective synthesis of (i) machine learning, (ii) multi-robot approaches, and (iii) field robotics is no small task. Previous machine learning and distributed control research rarely ventures beyond computer simulations. GDLS-C and the University of Toronto will investigate how to effectively use multi-agent reinforcement learning in field robotics. GDLS-C’s goal is to improve situational awareness of ground vehicles by using swarms of Unmanned Aerial Vehicles (UAV). Learning decentralized cooperation strategies will improve the resilience of these multi-robot systems—potentially faced with adversarial environments—and, ultimately, the safety of their human operators. Answering our research questions will also enable large collections of robots to learn how to interact with one another—beyond the point human designers can attain.

Multi-agent reinforcement learning for decentralized UAV/UGV cooperative exploration

Over the last decade, artificial intelligence has flourished. From a research niche, it has been developed into a versatile tool, seemingly on route to bring automation into every aspect of human life. At the same time, robotics technology has also advanced significantly, and inexpensive multi-robot systems promise to accomplish all those tasks that require both physical parallelism and inherent fault tolerance—such as surveillance and extreme-environment exploration. Decentralized control laws are key to achieve reliability of these systems (as they eliminate the risks posed by single-points-of-failure). Yet, the effective synthesis of (i) machine learning, (ii) multi-robot approaches, and (iii) field robotics is no small task. Previous machine learning and distributed control research rarely ventures beyond computer simulations. GDLS-C and the University of Toronto will investigate how to effectively use multi-agent reinforcement learning in field robotics. GDLS-C’s goal is to improve situational awareness of ground vehicles by using swarms of Unmanned Aerial Vehicles (UAV). Learning decentralized cooperation strategies will improve the resilience of these multi-robot systems—potentially faced with adversarial environments—and, ultimately, the safety of their human operators. Answering our research questions will also enable large collections of robots to learn how to interact with one another—beyond the point human designers can attain.

A fundamental surface characterization study on the initial molecular level events occurring during fouling on quartz sleeves in ultraviolet water disinfection photoreactors

Ultraviolet (UV) photoreactors for water treatment comprise UV lamps encased in quartz sleeves, immersed in the water to be treated. Over time, these quartz sleeves become fouled with materials from the water, reducing the amount of UV available for treatment. This phenomenon requires that the systems be over-sized and often include costly automatic cleaning systems to restore system performance. This proposed project will study the molecular processes that result in fouling on the quartz surface, and investigate the effectiveness of anti-fouling coatings. Previously, we have utilized in-situ atomic force microscopy to investigate initial molecular level events of fouling. This project aims to build on previous work by studying the interfacial chemistry and speciation of the initial foulant material through the use of advanced surface characterization techniques.

Identification of beneficial probiotics for non-alcoholic fatty liver disease and elucidation of mechanism

Non-alcoholic fatty liver diseases (NAFLD) is cause by accumulation of lipid droplets in liver. NAFLD is the starting point of liver disease and later develop into nonalcoholic steatohepatitis, cirrhosis and finally hepatocellular carcinoma. Since there is no specific therapeutics for NAFLD-related liver diseases, development of new drug for NAFLD/NASH is actively on-going. Recently, application of lactic acid bacteria as probiotics has been popular because the correlation of intestinal composition of microbiome has been elucidated with chronic diseases including atopic dermatitis, obesity, insulin resistance and autism. In this collaborative project, we aim 1) to identify the beneficial intestinal bacteria or lactic acid bacteria from screening for decreased permeability of enterocytes, 2) to identify the metabolites with bioefficacy to activate fatty acid oxidation or inhibit lipogenesis in liver 3) to examine in vivo efficacy of selected probiotics for NAFLD/NASH in animal disease models. We expect that elucidation of efficacious probiotics and application will be a new therapeutic method to treat chronic liver diseases.

Verification of 3D numerical model and examination of applicability of new breakwater design

Recently damage of existing harbor structures is expected due to increase of external wave force by the climate change. For this reason, reinforcement of existing structures is proceeding in order to preemptively prevent disasters, and breakwater is mainly targeted. If the breakwater is not well designed, it will cause the severe damage of the structure. In this study, numerical simulation of breakwater simulation will be conducted by the numerical model which eliminated the problems of existing models. Furthermore, applicability of the new breakwater design will be examined through calculation by the model. The result of the research is expected to give direction of developing numerical models for simulating coastal structure.

Evaluation of Resiliency in Community Youth Empowerment Programs – Year two

Youths experience increased vulnerability to mental health challenges associated with their development and living contexts. Effective mental health promotion must consider the multidimensional determinants of resilience. To address these needs, Dr. Jenny Liu (Elevate applicant) has developed and validated an innovative model, Multi-System Model of Resilience (MSMR), which measures resilience capacities and needs at the individual, community, and structural levels. In collaboration with Hong Fook Mental Health Association (HFMHA) and with mentorship from Dr. Josephine Wong (academic supervisor), Dr. Liu will apply the MSMR model to evaluate and strengthen existing youth programs at HFMHA, as well as implementing new programs with the following objectives:

1. Conduct baseline assessment of existing programs as they are mapped onto resilience and mental health objectives;
2. Pilot the integration of resilience and evaluate program effectiveness in promoting resilience and mental wellbeing;
3. Support the integration of resilience concepts and evaluation framework into youth programming;
4. Apply novel knowledge towards model development of MSMR in relation to real-world community settings.

Dr. Liu will gain invaluable knowledge and skills in project management, research collaboration and application of the MSMR in real-world contexts. She will contribute to quality improvement, programming innovation, and research capacity building at HFMHA.

Evaluation of Resiliency in Community Youth Empowerment Programs

Youths experience increased vulnerability to mental health challenges associated with their development and living contexts. Effective mental health promotion must consider the multidimensional determinants of resilience. To address these needs, Dr. Jenny Liu (Elevate applicant) has developed and validated an innovative model, Multi-System Model of Resilience (MSMR), which measures resilience capacities and needs at the individual, community, and structural levels. In collaboration with Hong Fook Mental Health Association (HFMHA) and with mentorship from Dr. Josephine Wong (academic supervisor), Dr. Liu will apply the MSMR model to evaluate and strengthen existing youth programs at HFMHA, as well as implementing new programs with the following objectives:

1. Conduct baseline assessment of existing programs as they are mapped onto resilience and mental health objectives;
2. Pilot the integration of resilience and evaluate program effectiveness in promoting resilience and mental wellbeing;
3. Support the integration of resilience concepts and evaluation framework into youth programming;
4. Apply novel knowledge towards model development of MSMR in relation to real-world community settings.

Dr. Liu will gain invaluable knowledge and skills in project management, research collaboration and application of the MSMR in real-world contexts. She will contribute to quality improvement, programming innovation, and research capacity building at HFMHA.

Understanding Health and Life Sciences Research and Innovation Impact in British Columbia

This project seeks to demonstrate the impact of health and life sciences research in the Province of British Columbia. Researchers from Simon Fraser University and University of British Columbia – Okanagan are working closed with the Genome BC and Michael Smith’s Foundation to develop new methodology to assess the value of health and life sciences research holistically. In this study, we refer health and life sciences research to a broad range of research activities (including basic, clinical, health services & policy, population health) that conducted within university, community or industry settings. Similar projects have been conducted in British Columbia and elsewhere, but many of them focus on direct and indirect economic benefits and are aimed only at demonstrating success. This project will also explore a broad range of indicators using a range of case studies to highlight weak linkages as well as strong ones. Ultimately, this project will provide evidence to strengthen health and life sciences research in the province.

Improving Automatic Calibration of Computationally Intensive Groundwater Models

This research aims to develop advanced but practical methodologies for automatic calibration of computationally intensive groundwater simulation models. Such models are largely used in many consulting engineering companies, but they may not be completely calibrated because of the time limits and their very large computational demands. The methodologies developed during this internship increase the computational efficiency of automatic calibration algorithms by using domain specific knowledge in groundwater modelling. The general frameworks for these methodologies have been already developed in the intern’s PhD thesis and tested across different automatic calibration practices on other models such as surface water models. This internship benefits the model development practice in the partner organization as the modellers are provided with advanced tools and techniques to efficiently make use of their available computational budgets when developing and calibrating their models. The computational efficiency gains enable the modellers to develop more accurate groundwater models of the real-world…..TOBECONTINUED

Development of nanoparticle in vivo labeling contrast probes for tissue clearing 3D microscopy compatible with multi-modal imaging in fluorescence, dark field, MRI, CT and electron microscopy modalities.

High resolution 3D microscopy in combination with tissue clearing techniques such as CLARITY, iDISCO, CUBIC is a rapidly growing area of biomedical research. It also has high potential to replace traditional 2D histology to become a method of choice for the analysis of tissue biopsy samples used in diagnosis of cancer and other diseases. However, currently there is a limited availability of contrast agents that can label organs, biological tissues, and cells in a live animal and are compatible with these techniques. To bridge this gap the Mitacs Fellow will work in collaboration with Luna Nanotech scientists to develop novel nanoparticle based probes that can label specific organs, tissues, structures, and cells in vivo. The outcome of this work will be a commercial line of labeling probes which are fully compatible with the tissue clearing techniques. Furthermore, unique properties of nanoparticles will make these probes highly versatile, allowing the high resolution fluorescence and dark field 3D microscopy to be combined with other whole body and tissue specific imaging modalities, such as magnetic particle imaging, microCT, and electron microscopy. This research will position Luna Nanotech as one of the leaders in the field of 3D tissue clearing microscopy and multi-modal imaging.