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Autonomous navigation requires multi-sensor fusion to achieve a high level of accuracy in different environments. Global navigation satellite system (GNSS) receivers are the main components in most navigation systems. However, GNSS signals are subject to blockage and multipath effects in challenging areas, e.g., tunnels, underground parking, and downtown or urban areas. Therefore, different sensors, such as inertial navigation systems (INSs) and radar, can be used to compensate for GNSS signal deterioration and to meet continuity requirements. In this paper, a novel algorithm was applied to improve land vehicle navigation in GNSS-challenging environments through radar/INS integration and map matching. Four radar units were utilized in this work. Two units were used to estimate the vehicle's forward velocity, and the four units were used together to estimate the vehicle's position. The integrated solution was estimated in two steps. First, the radar solution was fused with an INS through an extended Kalman filter (EKF). Second, map matching was used to correct the radar/INS integrated position using OpenStreetMap (OSM). The developed algorithm was evaluated using real data collected in Calgary's urban area and downtown Toronto. The results show the efficiency of the proposed method, which had a horizontal position RMS error percentage of less than 1% of the distance traveled for three minutes of a simulated GNSS outage. [ABSTRACT FROM AUTHOR]

Background: Direct‐acting antiviral agents (DAAs) have transformed chronic hepatitis C (CHC) treatment. Continued affordable access to DAAs requires updated cost‐effectiveness analyses (CEA). Utility is a preference‐based measure of health‐related quality of life (HRQoL) used in CEA. This study evaluated the impact of DAAs on utilities for patients with CHC in two clinical settings. Methods: This prospective longitudinal study included patients aged ≥18 years, diagnosed with CHC and scheduled to begin DAA treatment, from two tertiary care hospital clinics and four community clinics in Toronto, Calgary, and Montreal. Patients completed two utility instruments (EQ‐5D‐5L and Health Utilities Index 2/3 (HUI2/3)) before treatment, 6 weeks after treatment initiation, and 12 weeks and 1 year after treatment completion. We measured utilities for all patients, and for hospital‐based and community‐based groups. Results: Between 2017 and 2020, 209 patients (126 hospital‐based, 83 community‐based; average age 53 years; 65% male) were recruited, and 143 completed the 1‐year post‐treatment assessment. Pre‐treatment, utilities were (mean ± standard deviation) 0.77 ± 0.21 (EQ‐5D‐5L), 0.69 ± 0.24 (HUI2) and 0.58 ± 0.34 (HUI3). The mean changes at 1‐year post‐treatment were 0.035, 0.038 and 0.071, respectively. While utilities for hospital‐based patients steadily improved, utilities for the community‐based cohort improved between baseline and 12‐weeks post‐treatment, but decreased thereafter. Discussion: This study suggests that utilities improve after DAA treatment in patients with CHC in a variety of settings. However, community‐based patients may face challenges related to comorbid health and social conditions that are not meaningfully addressed by treatment. Our study is essential for valuing health outcomes in CHC‐related CEA. [ABSTRACT FROM AUTHOR]

Long‐term residential segregation can exacerbate social inequality and exclusion in urban populations. Existing models of segregation aim to represent and better understand drivers of segregation and assess possible segregation effects in response to incoming immigrant populations. However, these studies are not typically implemented on real geospatial data to represent the urban environment, and even less frequently compare patterns of segregation between cities. Therefore, the objective of this study is to implement an agent‐based model that simulates the decision‐making process of immigrants as they arrive and settle in three Canadian gateways for immigration, including the City of Toronto, the City of Calgary, and Metro Vancouver. The resulting simulated spatial patterns of segregation are visually compared to real data representing the location of hotspots of immigrants of various ethnic origins. The degree of segregation is measured and compared, with measures of segregation obtained from actual census data. The spatial patterns and degree of segregation are compared across the three study areas. The developed model has the potential to be used as a tool for knowledge discovery and decision‐making in the processes of city planning. [ABSTRACT FROM AUTHOR]

The objective of this research was to use intersectionality to explore Asian men's experiences of stigma and mental illness to tease out the ways in which stigma of mental illness among Asian men is mediated by age, immigration experiences, sexual and gender identities, racism and racialization processes, normative expectations about masculinity, and material inequality. The data for this research are based on a 4-year, multi-site (Calgary, Vancouver, and Toronto) mixed-methods intervention study that evaluated the effectiveness of interventions in reducing self and social mental health stigma among Asian men (Livingston et al. International Journal of Social Psychiatry 64, 679-689, 2018; Guruge et al. Contemporary Clinical Trials 71, 133–139, 2018). Participants were Asian men living with or affected by mental illness and community leaders interested in stigma reduction and advocacy. Quantitative survey data captured participants' self-reports of stigma, psychological flexibility, valued life domains, mindfulness, and empowerment readiness. Qualitative data included focus group transcripts, field notes, and participants' logs about anti-stigma activities in their communities. The data analyzed here are from ten pre-intervention and seven post-intervention focus groups conducted at the Vancouver site. The data collected pre- and post-interventions revealed that men understand and experience stigma as inextricably linked to social location, specifically age, race, masculinity, ethnicity, and time of migration. Our analysis also revealed that mental health stigma cannot be understood in isolation of other social and structural barriers. The application of intersectional frameworks must figure prominently in psychological research and in public health policies that seek to reduce mental health stigma in racialized communities. [ABSTRACT FROM AUTHOR]

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Copyright of Canadian Journal of Political Science / Revue Canadienne de Science Politique is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Day-to-day temperature variability has been examined within the context of three theoretical climates: orderly, random and oscillatory. Using highly idealized examples two measures of day-to-day variability were compared. It was found that standard deviation works well to characterize variability for random climates, as expected, but did not perform well for orderly and oscillatory climates. For these climates, a more direct calculation of day-to-day variability was found to be more representative. This method better captures the clustering of temperatures that may result from a number of meteorological and geographic factors which bring order to the local climate. These concepts were applied to two Canadian cities, Toronto, Ontario and Calgary, Alberta. Both cities were found to have a degree of orderliness in their climate. Toronto’s orderliness appears to be linked to the temperature mitigating effect of a moister climate and midlatitude cyclones. In addition, the proximity of Lake Ontario produces land/sea breezes which act to reduce thermal variability. Calgary experienced more variability, both on average and in the exceedances of 5 °C and 10 °C thresholds for day-to-day temperature swings. This is a result of a drier climate with less hydro-climatic inertia and the presence of chinook winds which produce, particularly in winter, swings of temperature frequently exceeding 10 °C. Although all the measures of day-to-day temperature variability examined appear to be decreasing in both cities, only the decrease of 5 °C exceedances of T min at Toronto was statistically significant. [ABSTRACT FROM AUTHOR]