Depression is a common and often devastating illness that contributes to suffering for patients and families and is also the number one cause of disability globally. Many patients do not respond to their
first trial of treatment, and managing depression according to best practices can be difficult for clinicians. Using the power of machine learning, a new tool has been developed that is intended to help match
patients to treatments using a simple questionnaire and to assist clinicians in improving the quality of depression treatment.
In Canada, alfalfa is a widely cultivated legume forage and the principal source of protein in the diets of ruminant animals. High quality alfalfa (i.e. nutrient composition and fiber digestibility) is vital for profitable dairy production because it can reduce requirements of high-cost concentrated feeds. High fiber digestibility is associated with higher cow's intake and milk production. Low-lignin alfalfa has recently been developed through technological progress.
To aid in active management of Snowy Owls and other raptors at airports, it is essential to understand the spatial distribution and movement behaviour of birds both on and off the airfield. The impact of airfields on birds may be particularly pronounced because airfields provide open, undeveloped land similar to early successional habitats that are perceived as high quality by many species. Airport collisions are a significant threat to Snowy Owls and humans, and preventative measures cost over $500 million dollars each in North America alone.
Transportation systems are evolving towards intelligent transportation systems and ISR Transit is a leading provider of these systems providing solutions in fleet management. In these systems, one of the enabling technologies is wireless sensor networks in which sensors are used to obtain information about the fleets. For example, sensors are deployed on motor, brake modules, doors, emergency buttons and passenger stop request.
Two fundamental pillars of communications/communications networks are trust and truth; in particular, we must ensure that the message (or data) that a sender wishes to transmit does indeed reach the intended receiver without being altered or eavesdropped by an unwanted party. This project focuses on demonstrating one concept of the quantum internet. The quantum internet is not based on quantum communications per se, but rather considers exploiting quantum principles for encoding and decoding data transmitted over existing fiber networks as a means for obtaining secure transmission.
HIV prevention is a growing, and essential facet, of halting the HIV epidemic. Reducing the transmission of HIV and ensuring individuals are tested and put on antiretroviral therapy (ART) cannot effectively and efficiently be accomplished without decisions that are founded on high-quality evidence. Current projects focus on data availability and use among decision-makers and actors in the health sector, in an effort to understand barriers to data use and encourage decision-making that is founded on high quality evidence.
The research project will find optimal conditions for instrument-free, fast, and sensitive/specific detection of pathogen (COVID-19). The project is composed in two units(IU), each module within IU is offering independent technical solution for the current bottleneck in diagnostics industry. The first module is temperature-based denaturation of biological sample, coupled with nucleic acid-based detection (IU1). The second module is composed of specific amplification of biomarker for intended target/s, (instrument free) and the last module is colorimetric detection of amplified biomarker.
Perfluoroalkyl and Polyfluoroalkyl substances (PFAS) are anthropogenic compounds with unique properties and wide applications. The consequence of using such persistent chemicals is widespread contamination reported for groundwater, soil, sediment, and wastewater, especially in industrialized countries such as Canada. The endocrine-disrupting and likely carcinogenic nature of PFAS have resulted in strict regulations on PFAS in drinking water.
Bicycle and pedestrian counts are important data for the planning and design of safe roads. However, these data need to be inspected for quality, a time-consuming task. Part of this project is to make this project simpler, quicker and more accurate. Installing pedestrian and bicycle counters across an entire city road network is not financially viable. Therefore, a good option is to estimate counts at the network scale, using knowledge from a handful of pedestrian and bicycle counters (strategically placed) and trip data from users who willingly share their position from their smartphones.
The goal is to create a conversation loop between 3D designers and artificial intelligence programs. This will help the AI provide suggestions to the designer, while the designer provides the AI with feedback. This can help make it easier for designing complicated objects as well as complicated textures that belong to the surface of 3D objects. Through this interaction, the hope that AI can extend the utility of design software.