Innovative Projects Realized

Carbon sequestration through 3 novel biomass-based methods and opportunity for integration into carbon offset markets.

Biocoal is made from wood charcoal and a binder. Biocoal made by BC Biocarbon is made to replace coal in high temperature combustion uses. As biocoal is similar to coal, it is thought to be used to store carbon in the ground. This project hopes to demonstrate the carbon storage ability of biocoal, plastic-sealed wood, and bitumen-bound wood.

Experiment conditions for each product will include landfill, surface environment, indoor room temperature, and frozen for one year. The project business partner, BC Biocarbon, will also benefit from a research project on how to sell their carbon-based products in a carbon offset or carbon storage market.

Results after one year will better show the carbon storage ability of biocoal, plastic-sealed wood and bitumen-bound wood. Also, this research will help show how biocoal, plastic-sealed and bitumenbound wood waste may be used for large scale carbon reducing programs for limiting climate change.

Integrated Amino Analyzer

Develop and design a fully automated and simple to operate amino acid analyzer capable of detecting with high degree of sensitivity the broadest range of amino acid metabolites or molecular structures found in living cells and chemical compounds. Analyzing the makeup of these structures is often the core to understanding the cause of human health conditions.

The project objective is to design an affordable and easy to use analyzer thereby making it more accessible to a larger human health sciences community and research laboratories. Current solutions are costly and require specialized skills which limits the research and advancement to that of the few large well funded organizations or research institutions.

Increasing accessibility of amino acid analysis will increase the research into existing and emerging human health issues thereby enhancing our knowledge and accelerating potential cures.

Induction Heating Supply

Electrical heating of oil sands allows for production in situ in a mode similar to conventional liquid oil production. This avoids disturbing and redistributing the overburden and production sands. A further advantage of electrical heating is that the power consumption can be matched to the availability of sources such as wind power.

Diagnostics and Explainable Machine Learning Models

Despite the advances of Machine Learning, the models are still being considered black-boxes that are difficult to diagnose and explain. The model performance diagnostic measures are critical to the assessment of the model’s relevance, accuracy and robustness. Good models’ performance is the primary enabler of their successful deployment in real-life applications. However, even if the models perform well, it is not known why the models predict the way they do, that is, which input variables are responsible for the models’ predictions. The purpose of the research is two-prone: 1) to identify the relationship between the measures of model performance and recommend which measures should be used in the model production environment, and, 2) develop the methodology of explaining machine learning models in terms of the models’ inputs, as well as, other, potentially relevant, variables, not selected in the model.

Therapeutic efficacy of tryptamine analogues in a PC12 Cell as a model of depression via assessment of neurite outgrowth and enhanced cellular viability

There is a growing body of evidence that certain combinations of bioactives derived from natural source products may have potent effect on neuritogenesis and foster neuronal cell viability. The effect of neuron plasticity suggests there are potential treatments of major neurodegenerative and psychiatric conditions. In this project we are proposing to use a robust in vitro cell model to test an array of bioactive compounds and combinations in collaboration with Seneca’s School of Biological Sciences and Applied Chemistry to assess the impact of these combinations on neurogenesis, neuritogenesis, and cell viability, among other measures proposed by the research team. We will determine which combinations provide the greatest effects in cell culture, which will guide our company in further studies for developing new therapeutics for potential treatments of these conditions.

An automated manufacturability analysis system

Currently, the service provided by GRAD4 allows buyers to upload their designs for quotes from the suppliers. However, there is no initial manufacturability check for buyers to evaluate their parts before submitting their quotes. Buyers may get feedback from the suppliers, which indicates that their parts are not able to be manufacturable after a several-days waiting period. In order to reduce the time waste of the communication between the buyers and suppliers and speed up the order process, an initial manufacturability checker is in demand. Based on this, the objective of this project is proposed 1) to investigate various approaches for automated manufacturability analysis 2) to implement the approach either in a software prototype or as a plugin for an existing online geometric modeling tool. Finally, the manufacturability system will be tested and validated based on the feedback from the users for GRAD4

Observing Microdosing: Effects on Cognitive Performance and Mental Health

We are studying the potential relationship between microdosing, cognitive performance and mental health. ‘Microdosing’ is the practice of taking psychedelic substances (e.g. psilocybin or LSD) in small, sub-perceptual amounts on a regular basis. There are many microdosing reports online, on blogs, and in books, but there are few research studies. The effects of microdosing on cognitive performance and mental health remains largely unexplored. Through this study, we are gathering data from both microdosing and non-microdosing groups. The results of this study will help guide future research and improve understanding of the effects of microdosing.
This research project is being conducted on Quantified Citizen’s decentralized online research platform, which allows for anonymous self-enrolment of participants who may not otherwise participate in a research project. The success of this project in recruiting a large number of participants and collecting a large dataset, demonstrates the usefulness of and informs this methodology.

Sensor-based Collision-Free Motion Planning and Control for Autonomous Cart Pullers at Advanced Intelligent Systems (AIS)

The objective is to develop and implement safe navigation algorithms and frameworks for autonomous cart pullers that are supposed to move planted pots on carts within an unknown and dynamically-changing environment in plant nurseries. The cart puller operation needs to be done safely in an environment that is shared by other vehicles, nursery utilities such as planted pots, and human operators. In this regard, the developed software- and hardware-based framework should be capable to overcome following challenges: (1) perform perception using on board LiDAR and camera vision, (2) construct a safe global path between current state of the cart puller and its desired destination, (3) develop dynamic/local motion planning algorithms to avoid collision with obstacles, (4) generate control commands for trajectory tracking, and (5) integration of all modules. In this project, it is intended to use Robot Operating System (ROS) as the basic software framework for developed motion planning and control algorithms. Also for real-time purposes, Robot Operating System 2 (ROS2) is planned to be used alongside ROS1.

Assessing the immune response to stem cell-derived beta cells and associated bioprinted devices for diabetes cell therapy

Type 1 diabetes (T1D) is an autoimmune disease where pancreatic beta cells are destroyed and no longer produce insulin, a hormone that maintains healthy blood sugar levels. People with T1D must replace insulin with injections or a pump. Although insulin is lifesaving, maintaining normal blood sugar levels is often a struggle for people with diabetes. Extreme low or high blood sugar can have deadly consequences. Replacing beta cells through islet transplantation is a promising therapy that allows the restoration of normal blood glucose levels. However, there are many challenges with this including limited donor supply, and patients must take powerful immunosuppressant drugs to prevent the immune system from rejecting the islets. Although beta cells derived from stem cells provide a potentially unlimited source of insulin-producing cells, immune-mediated rejection is still an issue once transplanted. This project aims to protect these cells with an innovative 3D bioprinted device that is designed to help them survive. However, in order to do this, key immune responses must be identified to both cells and device material. If successful, this will provide a new treatment option for people with T1D.

Advanced AI for Demand Forecast in Fashion and Apparel Retailing

The ultimate objective of the project is to develop an AI-based framework addressing the forecasting needs of a typical fashion and apparel retailer. The project activities involve development of models predicting demand for particular fashion and apparel items in the context of different customer groups, as well as techniques for identifying fashion trends. The developed methods and algorithms will be able to handle uncertainty, as well as imperfection and missing information. Graph-based formats for representing relevant information will be explored. The project will demonstrate applicability of AI methods to solve real-world challenges.

Design and development of piezoresistive MEMS sensors for applications in life sciences

Microfluidic BioMEMS sensors are a promising technology to bring personalized diagnostic on a chip. Currently large scale instruments are required to take measurements with microfluidic MEMS. This introduces a technical challenge to launch affordable bio medical devices into the market. Therefore, through this project, bulky instruments required for microfluidic MEMS sensors will be replaced with miniaturized microchips, with on-chip piezoresistors. Such a transition will enable us to produce MEMS sensors, at a fraction of the cost incurred in the production of large scale optical instruments, required for our MEMS sensors.

StreamSight: General Purpose Algorithm for Estimating Waste Weight at the Waste Collection Stage

The problem at hand is an inability for municipalities across Canada to audit recycling and waste collection. Auditing comprises both the quantity and type of objects being disposed or recycled. The only existing option is manual, which cannot be applied beyond small intermittent inspections due to the significant cost, time commitment and inefficiency.
In this project, two research directives are targeted: (1) to classify items at the point of waste collection in real time, and (2) to estimate the weight of individual collection bins using information obtained in (1), the fuel consumption in vehicles, and motion data obtained while loading waste into the vehicle using machine learning techniques