Abstract Purpose: To determine the prevalence and factors associated with injury in professional ballet and modern dancers, to explore dancers’ attitudes and perceptions of injury, and to assess if dancers are reporting their injuries and reasons for not reporting injuries. Methods: A cross-sectional survey was undertaken in professional ballet and modern dance companies in Canada, Denmark, Israel, and Sweden. Results: The point prevalence of injury in dancers is high (55% ballet; 46% modern) and most have chronic pain. Years dancing professionally and rank were associated with injury in ballet dancers. Attitudes towards injury vary and some dancers are continuing to dance when injured. Greater than 15% of all injured dancers have not reported their injury. Conclusions: Injury is common in dancers and there is an urgent need to investigate interventions to help control injury and understand the long-term implications of these conditions in this population.

Nausea and vomiting of pregnancy (NVP) affects up to 90% of pregnancies. Diclectin (doxylamine/pyridoxine) is the only anti-emetic approved in Canada for NVP, at a maximum dose of 4 tablets/day. However, some women receive higher doses, up to 12 tablets/day. In this study we compared the neurocognitive development of children from four mother-child groups: (1) NVP and >4 tablets Diclectin, (2) NVP and ≤ 4 tablets Diclectin, (3) NVP and no treatment and (4) no NVP. Children received a full age-appropriate psychological assessment. All groups scored in the normal range for IQ and cognition tests. The Diclectin-exposed groups scored significantly higher on a small number of subtests, but none of the differences could be considered clinically significant. No dose-dependent effects were observed. Above manufacturer recommended doses of Diclectin do not appear to harm neurodevelopment and should be considered safe for the treatment of NVP.

This study sought to examine the performance of participants in training courses of the Agricultural and Environmental Services (AES) unit and determine variables affecting participants' scores on the General Standards Examination (GSE). The data sample for the study comprised 150 individuals who completed the 8-hour course between February 2011 and February 2012 and submitted instruments developed for this study (demographic and evaluation survey, pre-test, post-test, and GSE). The demographics of the pest control industry in Texas - or, more specifically, the demographics of those taking a Structural Pesticide Applicator Training (SPAT) course from AES - have not changed much since 1998. The major differences in demographics between the two groups of individuals investigated (commercial and non-commercial applicants) were in age and size of business where employed. Commercial participants tended to be younger than non-commercial participants. Those seeking commercial certification tended to be employed in smaller firms than did those seeking non-commercial certification. This study found moderate, positive correlations between the pre-test, post-test, and GSE. Finally, though the examination scores were correlated, there were statistically significant differences between participants' performances on the pre-test, post-test, and GSE. These differences were quadratic; all three pairs - pre-test and post-test, post-test and GSE, and pre-test and GSE - differed, with pretest scores in the middle, then post-test scores highest, and GSE scores lowest. The researcher recommended that further research be conducted on demographic variables that may affect the outcome of the examinations, and that the rigor and relevance of the pre-test and post-test be increased to predict more accurately the results of the GSE.

Our knowledge of a drug’s potential for harm is incomplete at the time of drug licensing leaving residual questions about the long-term safety and effectiveness of drugs in the ‘real world’. Pharmacoepidemiologic research can contribute to the study of the unintended effects of drugs. The central aims of this dissertation were to create new knowledge about drug-related harm in the postmarketing environment using pharmacoepidemiologic methods and larged linked databases, and understand how various types of design and analytic strategies can be applied to reduce bias and threats to internal validity when studying drug harm. The aims of the thesis were achieved by performing three studies. The first study examined elderly individuals hospitalized with bradycardia and identified an association with recent initiation of cholinesterase inhibitor therapy (adjusted odds-ratio 2.13, 95% confidence interval 1.29 to 3.51). The second study examined the measurement properties of administrative diagnostic codes for subtrochanteric and femoral shaft fractures and found the positive predictive value and sensitivity of the codes to be reasonably good (90% and 81%, respectively). This study was linked to the third study which explored the association between long-term bisphosphonate use and subtrochanteric or femoral shaft fractures in postmenopausal women and found an increased risk of these unusual fractures in women with greater than 5 years of bisphosphonate use. The research performed as part of this thesis provides an example of the types of new knowledge about drug-related harm that can be generated using pharmacoepidemiologic designs and analytic strategies. The pharmacoepidemiologic studies will play an important and dynamic role in the larger evolving focus on post-marketing drug safety and effectiveness as new data sources become increasingly available and and the methods within the pharmacoepidemiologic discipline become more sophisticated and refined.

Agents with differential constraints, although common in the real world, pose a particular difficulty for motion planning algorithms. Methods for solving such problems are still relatively slow and inefficient. In particular, current motion planners generally can neither "see" the world around them, nor generalize from experience. That is, their reliance on collision tests as the only means of sensing the environment yields a tactile, myopic perception of the world. Such short-sightedness greatly limits any potential for detection, learning, or reasoning about frequently encountered situations. In result these methods solve each problem in exactly the same way, whether the first or the hundredth time they attempt it, each time none the wiser. The key component of this thesis proposes a general approach for motion planning in which local sensory information, in conjunction with prior accumulated experience, are exploited to improve planner performance. The approach relies on learning viability models for the agent's "perceptual space", and the use thereof to direct planning effort. In addition, a method is presented for improving runtimes of the RRT motion planning algorithm in heavily constrained search-spaces, a common feature for agents with differential constraints. Finally, the thesis explores the use of viability models for maintaing safe operation of user-controlled agents, a related application which could be harnessed to yield additional, more "natural" experience data for further improving motion planning.

Our knowledge of a drug’s potential for harm is incomplete at the time of drug licensing leaving residual questions about the long-term safety and effectiveness of drugs in the ‘real world’. Pharmacoepidemiologic research can contribute to the study of the unintended effects of drugs. The central aims of this dissertation were to create new knowledge about drug-related harm in the postmarketing environment using pharmacoepidemiologic methods and larged linked databases, and understand how various types of design and analytic strategies can be applied to reduce bias and threats to internal validity when studying drug harm. The aims of the thesis were achieved by performing three studies. The first study examined elderly individuals hospitalized with bradycardia and identified an association with recent initiation of cholinesterase inhibitor therapy (adjusted odds-ratio 2.13, 95% confidence interval 1.29 to 3.51). The second study examined the measurement properties of administrative diagnostic codes for subtrochanteric and femoral shaft fractures and found the positive predictive value and sensitivity of the codes to be reasonably good (90% and 81%, respectively). This study was linked to the third study which explored the association between long-term bisphosphonate use and subtrochanteric or femoral shaft fractures in postmenopausal women and found an increased risk of these unusual fractures in women with greater than 5 years of bisphosphonate use. The research performed as part of this thesis provides an example of the types of new knowledge about drug-related harm that can be generated using pharmacoepidemiologic designs and analytic strategies. The pharmacoepidemiologic studies will play an important and dynamic role in the larger evolving focus on post-marketing drug safety and effectiveness as new data sources become increasingly available and and the methods within the pharmacoepidemiologic discipline become more sophisticated and refined.

This study is an empirical analysis of adolescents' risk management on internet social network sites such as Facebook and MySpace. Using a survey of 935 U.S. adolescents gathered by the Pew Internet and American Life Project, I investigate the influence of offline social networks on online socialization, as well as the impact of parental and self mediation tactics on risky online information-sharing practices. Overall, the relationship between offline social network strength and online communications methods was inconclusive, with results suggesting that most teens use online communications in similar ways, regardless of offline connectedness. Some relationships were discovered between parental and individual mediation tactics and risky online information sharing, largely supporting the use of active mediation techniques by parents and informed control of shared information by individual users. User demographics had a strong effect on risky information sharing, with gender and age playing a significant role. This study also offers some suggestions for parents and policy-makers interested in the topic.

The automotive industry is actively supporting research and innovation to meet manufacturers' requirements related to safety issues, performance and environment. The Green ITS project is among the efforts in that regard. Safety is a major customer and manufacturer concern. Therefore, much effort have been directed to developing cutting-edge technologies able to assess driver status in term of alertness and suitability. In that regard, we aim to create with this thesis a framework for a context-aware driver status assessment system. Context-aware means that the machine uses background information about the driver and environmental conditions to better ascertain and understand driver status. The system also relies on multiple sensors, mainly video and audio. Using context and multi-sensor data, we need to perform multi-modal analysis and data fusion in order to infer as much knowledge as possible about the driver. Last, the project is to be continued by other students, so the system should be modular and well-documented. With this in mind, a driving simulator integrating multiple sensors was built. This simulator is a starting point for experimentation related to driver status assessment, and a prototype of software for real-time driver status assessment is integrated to the platform. To make the system context-aware, we designed a driver identification module based on audio-visual data fusion. Thus, at the beginning of driving sessions, the users are identified and background knowledge about them is loaded to better understand and analyze their behavior. A driver status assessment system was then constructed based on two different modules. The first one is for driver fatigue detection, based on an infrared camera. Fatigue is inferred via percentage of eye closure, which is the best indicator of fatigue for vision systems. The second one is a driver distraction recognition system, based on a Kinect sensor. Using body, head, and facial expressions, a fusion strategy is employed to deduce the type of distraction a driver is subject to. Of course, fatigue and distraction are only a fraction of all possible drivers' states, but these two aspects have been studied here primarily because of their dramatic impact on traffic safety. Through experimental results, we show that our system is efficient for driver identification and driver inattention detection tasks. Nevertheless, it is also very modular and could be further complemented by driver status analysis, context or additional sensor acquisition.

This report accounts for investigations of ways to reduce the calculation times forsimulations of falling control rods in boiling water reactors done prior to everyreactor startup, known as RIA-calculations. Two methodologies to lower thecalculation times have been proposed, developed and implemented in a set ofmatlab-scripts, which are fully compatible with the previously used methodology.The new methodologies have been applied on 17 authentic power cycles at the threeForsmark reactors, whereby a reduction in calculation times by 70 to 90 % could bedemonstrated while still confidently maintaining the analysis performance. Thesimulations made and the basis of the new methodologies are described in detail inthis report, and possible steps to further lower the calculation times are alsoproposed.

Adverse weather conditions can increase travel risk. Understanding how drivers react to adverse weather, such as rainfall, can aid in the understanding of road safety patterns and traffic operations. This information can in turn be used to improve driver education as well as highway operation through improved signing or the introduction of intelligent highway systems. Hourly rainfall data collected from the Pearson International Airport weather station and City of Toronto traffic data collected at the study site on the Gardiner expressway were used to create event and control pairs. In total, 115 hours with rainfall were matched to control data one week before or after the rainfall event. The traffic sensor at the study site collected speed, volume, and occupancy data at 20-second intervals, which was aggregated to five minutes. In addition, speed deviation and headway data at the 5-minute interval were used for analysis purposes. Two methods were used to test the effects of rainfall on traffic variables and the relationships between them. Matched pair t-tests were used to determine the magnitude of change between event and control conditions for the volume, speed, speed deviation, and headway variables for congested and uncongested traffic conditions. In addition, stepwise multiple linear regression was used to test the effects of rainfall on speed-volume and volume-occupancy relationships. Results of the matched pair t-tests indicated that volumes, speeds, and speed deviations dropped in event conditions, while headways increased slightly. Changes tended to be greater for congested than uncongested conditions. Linear regression results indicated that changes in speed were sensitive to volume conditions, and changes in volume were sensitive to occupancy, although only to a limited extent. Overall, drivers respond to rainfall conditions by reducing both speed and speed deviations, and increasing headway. Reductions in speed are larger in congested conditions, while increases in headway are smaller. Taken in combination, drivers are taking positive steps in order to either maintain or improve safety levels.