Urban design and development is an iterative process that involves community engagement and multiple feedback cycles. Advances in internet technologies and web mapping technologies has made it possible to display design plans on websites and to collect feedback on specific locations or aspects of the provided design. Using web mapping applications to feedback from the community is formally known as facilitated volunteer geographic information (FVGI).
There is growing pressure from intergovernmental organizations, governments and consumers to reduce the quantity of greenhouse gases being released into the atmosphere. Investments in green technology such as renewable energy sources, battery technology and carbon capture and sequestration can often yield significant reductions in carbon emissions. However, the corresponding economic costs of these projects can regularly result in a balancing act between environmental benefit and affordable energy consumption. Smart Energy Network, SEN, systems could provide a solution to this dilemma.
While we know how many mobile phones get recycled through the Recycle My Cell program in Canada, we know much less about the ones that dont make it into these type of take-back programs. Over the past few years academic research on the topic of mobile phone waste has increased dramatically, although a recent study shows that only about 6% of this research has focused on the North American market.
High-volume online stream processing, also known as fast data processing, is becoming increasingly important in a number of different commercial sectors. Unlike big data processing in which data is processed asynchronously in batches, fast data processing performs synchronous data analysis that generates actionable results within a specified deadline. One of the key challenges in building a fast data processing system is in scaling with increasing volumes of data. In our proposed research, we plan to build a system to efficiently manage the available memory across the entire deployment.
Brain natriuretic peptide (BNP) is an established prognostic marker for the early detection of heart failure. Elevated blood BNP levels are directly correlated to the severity of HF and decompensation. Current FDA approved immunoassays for BNP detection can only be carried out in medical laboratories or emergency rooms. Outpatient-use BNP monitors are yet to be developed. The objective of this project is to develop a prototype of the portable diagnostic device that can give a rapid electrical readout of BNP levels in a drop of blood.
Using surface characterization techniques, the relationship between the surface hydrophilicity level of the positive electrode and the electrochemical performance of a rechargeable aqueous battery system will be investigated. Oxygen is generated during the battery operation due to the decomposing of water, the solvent for the electrolyte, and may cover the surface of the positive electrode, thus hinder the battery operation.
The project involves the identification of a Canadian community to be compared with Barcelona (Spain), Bristol (UK) and other two international communities, all experienced cities on sustainability with more than 100 partners including businesses, NGOs, academia and the public sector. The Canadian community must comply with certain criteria to make findings comparable with the international communities.
Acute myeloid leukemia (AML) is a blood cancer with very poor prognosis, especially for patients older than 60 years of age. This is in part because of the severe toxicity of medicines available. Less harmful medicines are needed to better treat older patients. Therapure Biopharma Inc. has chemically linked the standard toxic chemotherapy medicine called cytarabine to the blood protein hemoglobin to make a potentially safer and more effective medicine to treat AML. In collaboration with the University Of Waterloo School Of Pharmacy, Therapure Biopharma Inc.
Over the last few years, the data revolution occurred with the emergence of Big data. In medical field, the term big data refers to large databases in terms of patients and/or information from varied sources. Nevertheless, heterogeneity is encountered in this kind of data. Indeed, data arise from different medical centers. Furthermore, we cant perform traditional statistical methods on these large databases: major problem are multicollinearity and overfitting. Lots of regularization methods have been proposed in order to adapt classical methods. Mittal et al.