The study reveals how nurses operationalize their daily caring practices in a hospital oncology unit that is described by nursing students as having a “culture of caring”. Despite ample evidence that changes to nursing practices in hospitals are occurring, there exists a dearth of work, theoretical or otherwise, that clearly addresses what appears to be emerging as a major trend. This ethnographic study directs attention to issues and concerns related to the changes by exploring the question of how nurses sustain their daily caring practices in light of the contextual influences that support or impinge upon their daily nursing activities. The study spans over a three month period (2-3 days a week) and involves 19 registered nurses who volunteered to be participants. Participant observation and journaling are the methods used to generate data. This field study is strengthened by participants’ corroboration with the researcher. Data collection, analysis, and interpretation were conflated into a single simultaneous process. The findings are presented in the form of an artistic portrayal: termed a closet drama”. Analysis revealed nine themes of caring practices that framed a collective story of ‘caring comes first’: making connections, creating form, making do, tolerating ambiguity, committing to diversity and dealing with difference; facing the possibility of death and facing dying, thinking outside the box of strategic moves, caring for self and others, and staying the course. They are the titles for the nine acts. A discussion of the findings is included as part of the drama in a series of passages called ‘After Wards’. Practices of caring are identified as a third mode of thinking that is situational and immediate and located between the two worldviews of modernity and postmodern; certain and uncertainty. Nurses’ intentionality is aimed at building bridges of understanding between the predetermined strategies of imposed order, developed to direct patient care, and uncertainty stemming from patients’ personal understandings of health and unique responses to their current health event. The characteristics of caring practices are identified as thoughtful conversations and generative tensions as a consequence of the dialogical encounters that result in reflective understandings. Caring practices create a space for the centrality of the social in intellectual thinking where assumptions are questions, contextual influences are taken into account, and capacity building occurs at an individual and system level. Of note is that one of the themes, “making do”, resulted in nurses directing their attention in two different directions: towards their patient and towards system issues. Thus, “making-do” is seen to serve two different functions. One is that it resists the loss of different possibilities for care. The second is that it serves to maintain hegemonic norms. In the discussion related to the significance of the research, making do is identified as a fault line for the limiting of caring practices. The researcher concludes that there is a need for lens that would better enable nurses to examine the effects of contextual influences on nursing and nurses; to recognize the effects and opportunities related to changing worldviews.

Identifying and developing strengths may serve as an intervention to improve selfconcept. The power of positive psychology is the foundation for recent studies in strengths-development research. Positive psychology is based on the premise that, if people are taught to capitalize on their strengths and to be resilient and optimistic, they will lead happier, more productive lives. The purpose of this research was to measure the effects of a positive psychology intervention on students’ self-concept. Based on positive psychology principles, the intervention was designed to help students learn both about positive psychology and about their personal strengths. This intervention was designed to serve a population of children, ages 10 to 15 years old, in Victoria, Canada. A sample size of 26 students diagnosed with learning disabilities were randomly assigned to either the experimental or control group. The intervention group participated in a 3-week intervention course about positive psychology, and they completed the VIA (Values in Action Inventory of Strengths – Youth)( Park& Peterson, 2003) to identify their individual strengths. Before and after the intervention program, students were assessed using the Self Description Questionnaire (SDQ-1; Marsh, 1992). Using a pre and post test design, t-tests indicated there was no statistically significant difference between the groups gains. There was, however, a small effect for the intervention group in the selfconcept domains of Math (d=0.30), Reading (d=0.22), and Total Academic Self-Concept (d=0.20) following the positive psychology intervention.

Clearcut harvesting can create conditions unfavourable to forest regeneration. In response, variable retention harvest methods are being investigated in montane forests on Vancouver Island, Canada. The effect of this overstory removal is unknown for canopy microarthropods, especially oribatid mites. As mites contribute significantly to nutrient cycling and decomposition processes in the canopy, changes in community structure and abundance may have dramatic effects on forest productivity. I studied the effects of two variable retention treatments, patch-cut and shelterwood systems, on arthropod communities associated with Abies amabilis (amabilis fir) branches and lichens. Changes in community structure were evident among the treatments and an old-growth control site. I also investigated the use of lichen abundance as a surrogate for oribatid mite abundance because it is time consuming and laborious to collect, count and identify microarthropods. Lichen abundance was a good predictor of mites in the old-growth and shelterwood, but not in the patch-cuts. Lichen abundance estimates should not replace biotic inventories, but can he used as an indicator when rapid biodiversity assessments are required.

People with developmental disabilities are particularly susceptible to health challenges. If they are not capable of making treatment decisions, they rely on substitute decision makers to make decisions for them. In this research, I examined the experiences of families who have made decisions for their relatives with developmental disabilities when the individual’s wishes were unknown. Using a naturalistic, qualitative research design and an interpretive description approach, eleven family members, representing eight families who had made decisions for their relatives with developmental disabilities, were recruited in order to obtain data about their experiences. The data were analyzed in order to reconstruct current knowledge and interpret findings through a nursing theoretical lens. In my findings, I demonstrate that families of people with developmental disabilities are marginalized by the experience. They actively engage in lifelong processes and seek out community resources to support their relatives. The findings suggest that professionals should consider the processes, experiences and consequences of marginalization when supporting families of people with developmental disabilities.

Distributed systems are becoming increasingly common. However, the testing of these systems is difficult due to their non-linear, stochastic and dynamic behaviours, and limited application-level testing support. In this thesis, a prototype cluster computing-based test harness has been developed that can be used for performance testing on a variety of distributed systems. Its usefulness is demonstrated through tests conducted on an example distributed system, including using the test harness to perform a parameter search on the system in an iterative fashion.

Microprocessor architecture has changed significantly since Intel Corporation developed the first commercial computer chip in the 1970s. The modern processors are much smaller and more powerful than their predecessors. Yet, in the mobile computing era the market demands for smaller, faster, cooler, and more power-efficient CPUs that could provide greater performance-per-watt results. In this dissertation, we address some of the shortcomings in conventional microprocessor designs and discuss possible means of alleviating them. First, we investigate the energy dissipation in Branch Target Buffer (BTB), a commonly present component in branch prediction unit. Our primary contribution is a speculative allocation technique to improve BTB energy consumption. In this technique, a new on-chip structure predicts the BTB activity and dynamically eliminates unnecessary accesses. Next, we formulate a quantitative metric to analyze the trade-off between processor energy efficiency and cache energy consumption. We investigate the upper bound energy and latency budget available for alternative data and instruction cache enhancements. This dissertation concludes with a novel approach to increase processors’ performance by reducing data cache miss rate. We employ a speculative technique to bridge the performance gap between the common Least Recently Used (LRU) replacement algorithm and the optimal replacement policy. We evaluate the non-optimal decisions made by the LRU algorithm and provide a taxonomy of mistakes, which will aid to identify and avoid similar decisions in future incidents.

Type Ia supernovae (SNe Ia) are excellent tools in cosmology. Their intrinsic luminosities are found to vary systematically with the light-curve widths, providing an empirical calibration. This property, called the width-luminosity relation (WLR), is the basis of modern SN Ia cosmology and led to the unexpected discovery of the current accelerated rate of cosmic expansion. By examining the spectroscopic diversity of SNe Ia, this thesis aims to improve both the use of SNe Ia in cosmology and the physical understanding of the observed properties. Spectra of SNe Ia contain a wealth of information, but are difficult to organize. In this thesis, new methods are developed to consistently quantify and analyze the spectral features of supernovae. The efficacy of the methods is tested on a large library of observed spectra encompassing a wide range of properties. The spectroscopic diversity of SNe Ia enters cosmology through K-correction calculations. Before this work, K-correction was a major contributor of the systematic errors in cosmology. It is shown here that the systematic errors can be largely diminished by carefully quantifying the mean spectroscopic properties of SNe Ia. The remaining statistical errors are also quantified and shown to be redshift dependent. With the aid of principal component analysis (PCA), the multidimensional spectral information is reduced to a few components describing the largest variations in the spectral library. Using this tool, it is shown here that SN Ia intrinsic luminosity is the main driver of the spectroscopic diversity at maximum light, for every spectral feature from the ultraviolet to the near-infrared. These spectroscopic sequences can potentially account for a large fraction of the K-correction statistical errors and even enable the use of SN Ia spectra as independent indicators of intrinsic luminosity and colors. The established relations will also disentangle the effects of demographic shift and true evolution in high-redshift SN Ia spectra. The temporal evolution of the spectral features is shown to exhibit the persistence of the spectroscopic sequences throughout other epochs. The effect is attributed to the more rapid spectroscopic temporal evolution of fainter SNe Ia. This conclusion supports the theory that WLR is primarily a spectroscopic effect, rather than a bolometric one.

The search for lepton flavour violation is significant to our understanding of the standard model of particle physics. This measurement uses the muon decay data collected by the TWIST experiment at TRIUMF to search for lepton flavour violation between charged lepton species. Specifically, I searched for the decay µ+→e+X0, where X° is an unknown, undetected, neutral boson, against a background of stan¬dard muon decays, µ+→e+vevµ I set branching ratios for these decays such that B(µ+→e+X0)< 2 x 10-5 - 5 x 10-5, for X0 of various masses accessable by the momenta of the muon decay spectrum, to a confidence level of 95%. This improves upon the previous best limits by a. factor of three. A correction to the spectrum was required to set a limit on a massless X0 of B(µ+→e+X0)< 6.3 x 10-5.

The use of beamlets as a dose calculation tool in Intensity Modulated Radiation Therapy (IMRT) treatment planning is widespread and well documented. A beamlet can simply be defined as the contribution of radiation passing through a particular geometrically defined subdivision of a given linear accelerator's emerging radiation field. The most common classes of algorithms used today to calculate the dose distributions deposited by beamlets are the pencil beam convolution and col-lapsed cone classes of algorithms. Using BEAMnrc [1], a Monte Carlo (MC) based radiation transport simulation software package, this thesis presents a novel method of calculating MC beamlet dose distributions with a level of accuracy not achievable using the above analytic dose calculation methods. In a first application, the MC beamlet dose distributions generated in this thesis are used to fine-tune the output of the MC or "virtual" linear accelerator from which they are produced. This is achieved through the adjustment of individual beamlet weights to align the output of the virtual accelerator to the experimentally measured output of the modeled accelerator in water. In a second application, MC beamlets are used to derive corrections to particular Multileaf Collimator (MLC) leaf sequences of IMRT treatment plans that have been miscalculated by a convolution-based dose calculation algorithm. These calculation inaccuracies (up to as much as 15%) arise due to the well known fact that convolution-based algorithms do not accurately model dose deposition in inhomoge¬neous media, such as lung [2] [3] [4]. In a final application, the MC beamlet generation method described in this thesis is implemented into a direct aperture optimization (DAO) algorithm. The implementation of MC beamlet generation in DAO forms the basis for a purely MC based inverse treatment planning system.

Canada is committed to report on the current state and condition of its forests in support of national commitments such as Montreal Process, Convention on Biodiversity, Kyoto Climate Accord and others. National reporting requires data to be extracted, collated and analyzed from multi-resolution, multi-scale data sets held by the Federal, 10 Provincial, and 3 Territorial jurisdictions. New methods and techniques for the integration, storage and analysis of data held by independent custodians over a distributed infrastructure are reviewed and applied for this project. Problems occur when required data are located in a distributed infrastructure. Accessing, analyzing, and reporting on this data has been time consuming, complicated and expensive. The object of this study was to investigate how spatial operations can be efficiently undertaken in a distributed environment without copying the data to a centralized location for analysis. A study of tessellations, re-sampling approaches, geospatial Web services. and spatial data handling was conducted to create and develop an approach that will allow for the analysis of distributed data sets. The resultant system, Expanding Primary Attributes for National Decision making (ExPAND) allows for the distributed analysis and synthesis of independently collected and stored data held on a distributed network of data warehouses. ExPAND was developed and designed to perform over a formalized international standards based infrastructure. These standards and specifications are created and maintained by the Open Geospatial Consortium (OGC). Any infrastructure that adheres to OGC's Web Mapping Service specifications can benefit from ExPAND. This thesis draws on a subset of Canada's National Forest Inventory (NFI) over an OGC based architecture as a test and demonstration of ExPAND.