Rotator cuff tears: a covert source of shoulder disability (Prognostic value of patient’s demographic, clinical and genetic factors)

This study aims to develop a scoring system to screen the sub-clinical forms of rotator cuff tears and predict the tear progression. All the medical, genetic, work, and lifestyle backgrounds of individuals with rotator cuff defects (with and without symptoms) will be evaluated and a battery of manual tests and measurements will be performed to understand the predisposing risk factors for both sub-clinical and clinical manifestations.

Peptide-Based Environment Sensitive siRNA Delivery System for Cancer Treatment

In this project, the main objective is developing a peptide-based environment sensitive siRNA delivery system for cancer treatment. If this deliver system can be proved efficient both in vitro and in vivo, it could have potential feasibility to be further characterized and become a pharmaceutical drug eventually.

Applications of deep learning to large-scale data analysis in mass spectrometry-based proteomics - Year Two

As a result of recent advances in high-throughput technologies, rapidly increasing amounts of mass spectrometry (MS) data pose new opportunities as well as challenges to existing analysis methods. Novel computational approaches are needed to take advantage of latest breakthroughs in high-performance computing for the large-scale analysis of big data from MS-based proteomics. In this project, we aim to develop new applications of deep learning and neural networks for the analysis of MS data.

New DNA technology expected to cure genetic diseases

Stargardt’s disease is a rare inherited ocular illness that affects the Canadian population. According to Fighting Blindness Canada, 1 in 8,000 Canadians suffer from Stargardt’s, a degenerative ocular illness that ultimately leads to vision loss. Typically, patients are diagnosed with the disease by the age of 13, and most experience progressive vision loss as they get older. It is not uncommon for patients to develop complete blindness by the age of 35. Still today, despite the many clinical trials taking place, there is no cure for Stargardt’s disease.

Electrical Material Characterization Studies on Power Cable Dielectric Materials subjected to Thermal Aging

Electric power is almost entirely transmitted through polymer insulated cables or wires in every home, factory, plant or apparatus. If the temperature of a cable increases, it would be an indication that some accidents or malfunctions such as inflow of excess electric current occur in the cable. The generated heat, indeed, degrades the polymer insulations in cable, thus, making it unsuitable and unsafe for extra service. Therefore, it would be markedly valuable if the thermally-degraded portion in a cable can be located precisely without destroying the cable.

Assessment of DNA Ministring technology in cell transfection and the treatment of Colorectal Cancer (CRC)

Despite the power of gene therapy, its successful application to medicine has been diminished due to: (i) high toxicities and potentially fatal adverse effects; (ii) poor transgene expression in target cells; and (iii) extensive vector degradation. While viral vectors greatly improve efficiency, they sometimes lead to cancers due to chromosomal integration and may suffer from a lack of desired tissue selectivity. In contrast, nonviral systems have proven safer, but less efficient.

Iron battery: a safety, economic and environmentally friendly aqueous secondary battery

The past few decades have witnessed the unprecedented development of aqueous rechargeable batteries and there are many scientific groups focusing their interest on this energy technology research field. Ideal active electrode materials and plain economic considerations are the critical factors in the design of batteries. Among them, Fe//MnO2 aqueous battery is one of the best candidates because of lower cost, high safety and eco-friendliness. In addition, improved conductivity and better cycle performance can be obtained by carbon coating.

Tagging and Auto-Captioning of Histopathology Scans for Diagnosis Assistance

Digital pathology uses modern scanners to capture high-resolution images from biopsy samples. Computer algorithms, especially artificial intelligence, can help in automatic searching for similar cases in the archive of hospitals and laboratories. Displaying similar images form the past patients, that have already been diagnosed and treated, can provide useful information to the pathologist to solidify the final diagnosis. These images, however, are very large such that their processing requires smart algorithm to distinguish between relevant and irrelevant information.

Knowledge Intensive Processes Representation and Analysis: Process-Aware Work-Graphs and Predictive Approaches

Processes are important concepts in modern society since they control and standardize the interactions between businesses, consumers, governments and other organizations. However, the rise of knowledge-based industries such as financial services, healthcare, advanced manufacturing and software development have produced unstructured and knowledge-dependent processes. These Knowledge Intensive Processes (KIPs) KIPs range from partially structured to unstructured processes and require some control and standardization while guiding but not completely constraining knowledge workers’ actions.

Instituting Composite Knowledge About Living Architectural Systems

This project seeks to accumulate information on several focused research initiatives, either recently completed or currently being conducted by partners of the Living Architectural Systems (LAS) group, and provide analysis of these with respects to their potential contribution to a paradigm of “living systems” in architecture. This project is embedded in the need to transcend the communication/methodological barriers seen in traditional interdisciplinary collaborations.

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