Between Principle and Practicality: A Dynamic Realist Examination of Independence in the Canadian Justice System

This work examines independence in the Canadian justice system using an approach adapted from new legal realist scholarship called ‘dynamic realism’. This approach proposes that issues in law must be considered in relation to their recursive and simultaneous development with historic, social and political events. Such events describe ‘law in action’ and more holistically demonstrate principles like independence, rule of law and access to justice. My dynamic realist analysis of independence in the justice system employs a range methodological tools and approaches from the social sciences, including: historical and historiographical study; public administrative; policy and institutional analysis; an empirical component; as well as constitutional, statutory interpretation and jurisprudential analysis. In my view, principles like independence represent aspirational ideals in law which can be better understood by examining how they manifest in legal culture and in the legal system. This examination focuses on the principle and practice of independence for both lawyers and judges in the justice system, but highlights the independence of the Bar. It considers the inter-relation between lawyer independence and the ongoing refinement of judicial independence in Canadian law. It also considers both independence of the Bar and the Judiciary in the context of the administration of justice, and practically illustrates the interaction between these principles through a case study of a specific aspect of the court system. This work also focuses on recent developments in the principle of Bar independence and its relation to an emerging school of professionalism scholarship in Canada. The work concludes by describing the principle of independence as both conditional and dynamic, but rooted in a unitary concept for both lawyers and judges. In short, independence can be defined as impartiality, neutrality and autonomy of legal decision-makers in the justice system to apply, protect and improve the law for what has become its primary normative purpose: facilitating access to justice. While both independence of the Bar and the Judiciary are required to support access to independent courts, some recent developments suggest the practical interactions between independence and access need to be the subject of further research, to better account for both the principles and the practicalities of the Canadian justice system.

The application of PCA as a movement pattern recognition technique: A proof of principle

Quantitative methods can help us understand how underlying attributes contribute to movement patterns. Applying principal components analysis (PCA) to whole-body motion data may provide an objective data-driven method to identify unique and statistically important movement patterns. Therefore, the primary purpose of this study was to determine if athletes’ movement patterns can be differentiated based on skill level or sport played using PCA. Motion capture data from 542 athletes performing three sport-screening movements (i.e. bird-dog, drop jump, T-balance) were analyzed. A PCA-based pattern recognition technique was used to analyze the data. Prior to analyzing the effects of skill level or sport on movement patterns, methodological considerations related to motion analysis reference coordinate system were assessed. All analyses were addressed as case-studies. For the first case study, referencing motion data to a global (lab-based) coordinate system compared to a local (segment-based) coordinate system affected the ability to interpret important movement features. Furthermore, for the second case study, where the interpretability of PCs was assessed when data were referenced to a stationary versus a moving segment-based coordinate system, PCs were more interpretable when data were referenced to a stationary coordinate system for both the bird-dog and T-balance task. As a result of the findings from case study 1 and 2, only stationary segment-based coordinate systems were used in cases 3 and 4. During the bird-dog task, elite athletes had significantly lower scores compared to recreational athletes for principal component (PC) 1. For the T-balance movement, elite athletes had significantly lower scores compared to recreational athletes for PC 2. In both analyses the lower scores in elite athletes represented a greater range of motion. Finally, case study 4 reported differences in athletes’ movement patterns who competed in different sports, and significant differences in technique were detected during the bird-dog task. Through these case studies, this thesis highlights the feasibility of applying PCA as a movement pattern recognition technique in athletes. Future research can build on this proof-of-principle work to develop robust quantitative methods to help us better understand how underlying attributes (e.g. height, sex, ability, injury history, training type) contribute to performance.

Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.

Landfill Leachate Toxicity to Oncorhynchus mykiss (Rainbow Trout) at the Merrick Landfill

At the Merrick Landfill, located outside of North Bay (Ontario, CA), an investigation into the potential for an environmental impact to the Little Sturgeon River as a result of landfill leachate discharge was undertaken using toxicity testing using 96 hour acute lethality on Oncorhynchus mykiss (Rainbow Trout). Landfill leachate may present a risk to receiving environments as it is comprised of an array of chemicals including organics, ammonia, and metals. Testing was conducted in three phases, firstly testing was completed on site throughout an existing natural attenuation zone where the presence of several groundwater seeps down gradient of the site had been identified to determine the effectiveness of the existing leachate control features at reducing the environmental risks. These tests indicated that the existing capture strategies were largely effective at reducing toxicity risks to the receiving environment. Testing was also completed on two pilot-scale hybrid-passive treatment systems to determine their effectiveness for leachate treatment. Summer performance of a constructed gravel wetland system was also shown to be effective at reducing the toxicity of the landfill leachate at the site. Lastly in order to support evaluation of leachate treatment requirements, a toxicity identification evaluation (TIE) was performed to determine the principle cause of toxicity within the leachate. Based on water chemistry analyses of samples collected at various locations at the site, the TIE identified ammonia toxicity as the primary source of toxicity in the leachate, with a secondary focus on metal toxicity.

Supporting Run-time Monitoring of UML-RT through Customizable Monitoring Configurations in PapyrusRT

Model Driven Engineering uses the principle that code can automatically be generated from software models which would potentially save time and cost of development. By this methodology, a systems structure and behaviour can be expressed in more abstract, high level terms without some of the accidental complexity that the use of a general purpose language can bring. Models are the actual implementation of the system unlike in traditional software development where models are often used for documentation purposes only. However once the code is generated from the model, testing and debugging activities tend to happen on the code level and the model is not updated. We believe that monitoring on the model level could potentially facilitate quality assurance activities as the errors are detected in the early phase of development. In this thesis, we create a Monitoring Configuration for an open source model driven engineering tool called PapyrusRT in Eclipse. We support the run-time monitoring of UML-RT elements with a tracing tool called LTTng. We annotate the model with monitoring information to be used by the code generator for adding tracepoint statements for the corresponding elements. We provide the option of a timing specification to discover latency errors on the model. We validate the results by creating and tracing real time models in PapyrusRT.

Targeting the actin cytoskeleton in HER2+ metastatic cancer cells using a macrolide toxin

Breast and ovarian cancers are among the leading causes of cancer related deaths in women worldwide. In a subset of these cancers, dysregulation of the human epidermal growth factor receptor 2 (HER2) leads to overexpression of the receptor on the cell surface. Previous studies have found that these HER2+ cancers show high rates of progression to metastatic disease. Metastasis is driven by cytoskeletal rearrangements that produce filamentous actin (F-actin) based structures that penetrate and degrade extracellular matrix to facilitate tumour invasion. Advancements in targeted therapy have made F-actin an attractive target for the development of new cancer therapies. In this thesis, we tested the actin-depolymerizing macrolide toxin, Mycalolide B (MycB), as a potential warhead for a novel antibody drug conjugate (ADC) to target highly metastatic HER2+ breast and ovarian cancers. We found that MycB treatment of HER2+ breast (SKBR3, MDA-MB-453) and ovarian (SKOV3) cancer cells led to loss of viability (IC50 values ≤ 64 nM). Sub-lethal doses of MycB treatment caused potent suppression of leading edge protrusions, migration and invasion potential of HER2+ cancer cells (IC50 ≤ 32 nM). In contrast, other F-actin based processes such as receptor endocytosis were less sensitive to MycB treatment. MycB treatment skewed the size of endocytic vesicles, which may reflect defects in F-actin based vesicle motility or maturation. Given that HER2+ cancers have been effectively targeted by Trastuzumab and Trastuzumab-based ADCs, we tested the effects of a combination of Trastuzumab and MycB on cell migration and invasion. We found that MycB/ Trastuzumab combination treatments inhibited motility of SKOV3 cells to a greater degree than either treatment alone. Altogether, our results provide proof-of-principle that actin toxins such as MycB can be used as a novel class of warheads for ADCs to target and combat highly metastatic cancers.