Humanity faces the triple challenge of stabilizing climate, ensuring food security, and safeguarding nature. Innovative approaches for climate- and biodiversity-friendly agriculture capable of sustaining resilient production landscapes are urgently needed. Carbon markets offer a platform for market-driven solutions that incentivize soil carbon sequestration through nature-based solutions. Canada employs a cap-and-trade scheme for domestic carbon credit trading on route to net-zero carbon emissions by 2050.
Graphene is the thinnest, lightest, strongest, and a highly conductive material discovered to date, which makes it attractive for diverse applications, ranging from energy storage devices, electronics and automotive to construction. Despite the unique properties of graphene and its potential application in various industries, the widespread application of graphene is still limited due to the high cost of starting materials, high production cost, or low production volume.
Family Service Canada (FSC) is a Canadian nonprofit organization dedicated to building healthy families. One program delivered by FSC, called Family & Schools Together, has been shown to help families become more involved in their children’s education and support student’s learning but it has not yet been researched in Canada. To find out if this program is helpful for Canadian families, we will be interviewing FSC staff, families, children, and teachers across five FSC sites to determine whether or not they feel the F&ST program is effective.
Greenfield Global is developing a process to produce jet fuel from renewable materials, such as waste biomass and organic municipal waste. Fischer–Tropsch synthesis converts a mixture of carbon monoxide and hydrogen (synthesis gas) that was produced from the waste biomass and organic municipal waste into a synthetic crude oil that can be refined to produce jet fuel. This project deals only with Fischer–Tropsch synthesis.
Unmanned Arial Surveillance is rapidly gaining acceptance for various applications, such as monitoring of long power transmission lines, pipelines and mass transit systems that extend for hundreds of kilometers. Unmanned Aerial Vehicles (UAVs) such as drones provide the flexibility to reduce costs. In the case of natural disaster occurrence such as earthquake, flood or hurricane, drones can quickly fly over to high risk areas where human access would be impossible or dangerous and provide information for rescue operations, etc.
Next-generation integrated circuits require the innovation of new interconnect materials in order to maintain the performance improvements of Moore’s Law scaling. Cobalt (Co) and ruthenium (Ru) are two specific metals that are garnering strong interest for use in the filling of interconnects because of their better electrical performance and reliability at the extremely scaled dimensions required by sub-10 nm technology nodes.
We have seen the acceleration of global warming in recent years. Green-energy powered electronic devices are more desirable. In this proposal, we propose to develop an energy harvesting circuit and implement it on a system-on-chip. The design goals are low-cost, user-friendly, and portable. By partnering with Hidaca Ltd., our ultimate goal is to have this made-in-Canada technology available on the market as soon as possible to benefit Canadians and the global population.
Two primary objectives of this undertaking are (1) to determine whether ore recovery along pit walls can be increased by replacing and/or augmenting current pit wall stability assessments involving two-dimensional static methods with three-dimensional deformation analyses and (2) to differentiate pit wall deformations associated with stress relaxation from those associated with failure. Three-dimensional deformation analyses using traditional and/or semi-custom constitutive models calibrated against (a) laboratory testing data and (b) in-situ monitoring data will be used in this evaluation.
When utilizing and implementing ML for prediction using administrative health data, two key issues are ML algorithm evaluation and generalizability21. Current approaches evaluate model performance by quantifying how closely the prediction made by the model matches known health outcomes. Evaluation metrics include sensitivity, specificity, and positive predictive value, as well as measures such as the area under the receiver operating characteristic (ROC) curve, the area under the precision-recall curve, and calibration.
The SARS-CoV-2 outbreak, which started in Dec. 2019, has so far not been contained due to unpreparedness and unsuccessful development of antiviral drugs against SARS-CoV-2. In response to this pandemic, we propose development of a diagnostic assay based on saliva samples. We will also standardize virus collection procedure and inactivation steps to reduce the turnaround time of the results. We have the required expertise of working with virology techniques, molecular biology and diagnostic assay development.