This thesis examines the media representations of Chien-Ming Wang, a Taiwanese baseball player who played for the New York Yankees, in American and Taiwanese print media from 2005 to 2009. Wang had been attracting media attention in both the United States and in Taiwan during the time because of his athletic performance and dual identities in the two places. The results show that the Taiwanese media usually placed heavy emphasis on his national identity, making him one of the most high-profile athletes in Taiwan. On the other hand, as a foreign player and an Asian athlete, his racial identity was sometimes the focus of the American media. While he had been generally portrayed in a positive way, his Asian identity is still well-scrutinized. I argue that his media representations in the United States fit the model minority discourse which remains the typical perception in the US, meaning that stereotypical characteristics of Asians or Asian Americans are emphasized or overrepresented.

The purpose of this study is to investigate the evolution of the Arctic Ocean’s carbon uptake capacity and impacts on ocean acidification with the changing sea-ice scape. In particular, I study the influence on air-ice-sea fluxes of carbon with two major updates to commonly-used carbon cycle models I have included. One, incorporation of sea ice algae to the ecosystem, and two, modification of the sea-ice carbon pump, to transport brineassociated Dissolved Inorganic Carbon (DIC) and Total Alkalinity (TA) to the depth of the bottom of the mixed layer (as opposed to releasing it in the surface model layer). I developed the ice algal ecosystem model by adding a sympagic (ice-associated) ecosystem into a 1D coupled sea ice-ocean model. The 1D model was applied to Resolute Passage in the Canadian Arctic Archipelago and evaluated with observations from a field campaign during the spring of 2010. I then implemented an inorganic carbon system into the model. The carbon system includes effects on both DIC and TA due to the coupled ice-ocean ecosystem, ikaite precipitation and dissolution, ice-air and air-sea carbon exchange, and ice-sea DIC and TA exchange through a formulation for brine rejection to depth and freshwater dilution associated with ice growth and melt. The 1D simulated ecosystem was found to compare reasonably well with observations in terms of bloom onset and seasonal progression for both the sympagic and pelagic algae. In addition, the inorganic carbon system showed reasonable agreement between observations of upper water column DIC and TA content. The simulated average ocean carbon uptake during the period of open water was 10.2 mmol C m−2 day−1 ( 11 g C m−2 over the entire open-water season). Using the developments from the 1D model, a 3D biogeochemical model of the Arctic Ocean incorporating both sea ice and the water column was developed and tested, with a focus on the pan-Arctic oceanic uptake of carbon in the recent era of Arctic sea ice decline (1980 – 2015). The model suggests the total uptake of carbon for the Arctic Ocean (north of 66.5 N) increases from 110 Tg C yr−1 in the early eighties (1980 – 1985) to 140 Tg C yr−1 for 2010 – 2015, an increase of 30%. The rise in SST accounts for 10% of the increase in simulated pan-Arctic sea surface pCO2. A regional analysis indicated large variability between regions, with the Laptev Sea exhibiting low sea surface pH relative to the pan- Arctic domain mean and seasonal undersaturation of arag by the end of the standard run. Two sensitivity studies were performed to assess the effects of sea-ice algae and the sea-ice carbon pump in the pan-Arctic, with a focus on sea surface inorganic carbon properties. Excluding the sea ice-carbon-pump showed a marked decrease in seasonal variability of sea-surface DIC and TA averaged over the Arctic Ocean compared to the standard run, but only a small change in the net total carbon uptake (of 1% by the end of the no icecarbon-pump run). Neglecting the sea ice algae, on the other hand, exhibits only a small change in sea-surface DIC and TA averaged over the pan-Arctic Ocean, but a cumulative effect on the net total carbon uptake of the Arctic Ocean (reaching 5% less than that of the standard run by the end of the no-ice-algae run). / Graduate

Diabetes mellitus is a chronic disease in which the body does not produce sufficient insulin or in which the body has high insulin resistance thus making the regulation of blood glucose metabolism difficult. Currently, diabetes is still incurable. All patients need to well manage their blood glucose levels to reduce the risk of complications. This dissertation is comprised of two major studies. In diabetes type I, the blood glucose can only be managed by multiple daily injection of insulin. However, most patients tend to have difficulty in deciding the right amount of insulin dose. The first study is the development of a mathematical model of blood glucose levels, which leads to the development of a decision support system for diabetes type I using the Markov theory. In some type II and gestational diabetes, blood glucose can be managed by choosing diet properly and by exercising regularly. However, people tend to overestimate their activity levels. The second study describes the design and development of a wearable device based on the triaxial accelerometer that estimates the energy levels of normal daily physical activity with comparable accuracy to the gas analysis. This device development leads to two clinical studies. The first clinical study investigates whether the energy monitor could help people with diabetes in promoting and managing their daily activity and help to improve the glycosylated haemoglobin and body mass index. The second clinical study investigates whether the energy monitor could help pregnant women with gestational diabetes in managing their daily activity, blood glucose levels and body weight gain. This thesis also develops a telemedicine system to automate the data collection during the clinical trial period. The system would securely transmit all diabetes and energy data from the participants' home to a remote server. A key finding of this study was that a higher activity score results in smaller fluctuations in blood glucose levels between measurements in both diabetes and gestational diabetes subjects. This suggests that higher activity levels would make the management of diabetes more effective by reducing the fluctuation in blood glucose levels.

Environmental education is a relatively young area that can trace its roots back to the global environmental crises of the late 1960s and 1970s. Research in environmental education since this time has established the justification for its existence in the formal curriculum of schools. Less research has been conducted on the actual pedagogy of environmental education. This forms one part of the justification for this research study. The other justification for this research study is school students' objectification of the environment evidenced from the findings of a large survey of NSW school students. The objectification of the environment finding referred to students' responses that suggested that the environment was separate from them in contrast to a minority of students' responses that referred to a relational view (Loughland, Reid, Walker & Petocz, 2003). The two foci of pedagogy and students' understandings of the environment come together in the research question of this thesis, what is the relation between pedagogy and representations of the environment in environmental education? A Bernsteinian model of pedagogy, the pedagogical device, underpins the theoretical analysis of the pedagogy of environmental education in this study (Bernstein, 1990). A particular aspect of this device, the pedagogic recontextualising field, is used as a framework of analysis for the exposition of the major influences on the development of pedagogy of environmental education in NSW. Another theory of pedagogy, the NSW Quality Teaching Framework, is used to offer a performative angle on pedagogy to provide theoretical triangulation for the study. The pedagogy of environmental education was examined through a classroom ethnography with the researcher acting as a participant observer. The data were in the form of field notes, curriculum materials including children's literature, transcripts of classroom learning and products of students' learning. The analysis of the data was conducted using a variety of methods of analysis. The data were initially coded for themes that were the different representations of the environment in the pedagogy of this classroom. Further, the NSW Quality Teaching Framework (NSW DET 2003) was used as a theoretical framework of analysis in order to examine the data from the perspective of student performance in relation to current understandings of what constitutes good pedagogical practice. Next, Bernstein's model of the pedagogic device (1990) was used to analyse the data in the larger context of the social construction of knowledge in the school curriculum. This analysis incorporated Bernstein's original notions of pedagogical classification and framing (1971). This study has two main findings. First, the pedagogy of environmental education has strong classification and framing (after Bernstein 1971) that supports the objectification of the environment. Second, there is also some weak framing of the pedagogy of environmental education that generally does not support the objectification of the environment. The implications for these findings for practice are that environmental educators should be aware of deterministic curriculum that seeks to impose one view of the environment onto students. This curriculum positions the environment as an object that needs to be saved through human intervention. Further research into the pedagogy of environmental education that explores the relation of students' understandings of the environment and their relation to the epistemological and theoretical bases of pedagogy is warranted as a result of this study.

One challenge that faces hydrologists in water resources planning is to predict the catchment???s response to a given rainfall. Estimation of parameter uncertainty (and model uncertainty) allows assessment of the risk in likely applications of hydrological models. Bayesian statistical inference, with computations carried out via Markov Chain Monte Carlo (MCMC) methods, offers an attractive approach to model specification, allowing for the combination of any pre-existing knowledge about individual models and their respective parameters with the available catchment data to assess both parameter and model uncertainty. This thesis develops and applies Bayesian statistical tools for parameter estimation, comparison of model performance and hierarchical model aggregation. The work presented has three main sections. The first area of research compares four MCMC algorithms for simplicity, ease of use, efficiency and speed of implementation in the context of conceptual rainfall-runoff modelling. Included is an adaptive Metropolis algorithm that has characteristics that are well suited to hydrological applications. The utility of the proposed adaptive algorithm is further expanded by the second area of research in which a probabilistic regime for comparing selected models is developed and applied. The final area of research introduces a methodology for hydrologic model aggregation that is flexible and dynamic. Rigidity in the model structure limits representation of the variability in the flow generation mechanism, which becomes a limitation when the flow processes are not clearly understood. The proposed Hierarchical Mixtures of Experts (HME) model architecture is designed to do away with this limitation by selecting individual models probabilistically based on predefined catchment indicators. In addition, the approach allows a more flexible specification of the model error to better assess the risk of likely outcomes based on the model simulations. Application of the approach to lumped and distributed rainfall runoff models for a variety of catchments shows that by assessing different catchment predictors the method can be a useful tool for prediction of catchment response.

School refusal occurs across a broad range of students from the first to the final years of school, and is of concern to students, parents and teachers alike. This study uses the perspective of practitioners working at the school level to identify linkages between the presenting problems, interventions and outcomes of school refusal. This pattern is then compared to the Functional Model of School Refusal to establish the relevance of the Model. A multiple single-case study approach was used with ten case histories with positive outcomes being matched against the Functional Model. As these provided some support for the model an additional six case histories with negative outcomes were then matched against the Model. Two interviews of practitioners who had worked with school refusal were also analysed. The Functional Model of School Refusal received some support through this analysis, but areas were identified which were not adequately addressed by the Model. The Model was subsequently revised into a broader functional approach which takes greater account of the role of the family and environmental factors affecting school refusal. It is recommended that a broader multi-modal approach to intervention be implemented by practitioners dealing with school refusal.

<p>In this work we examine a state constrained resource allocation model a with finite time horizon. Therefore, we use the necessary conditions of the Pontrjagin's Maximum Principle to find candidates for the solution and verify them later on using the sufficient conditions given by the duality concept of Klötzler. Moreover, we proof that the solution of the corresponding infinite horizon model does not fulfill the overtaking criterion of Weizsäcker.</p>

The quality of atomic force microscope (AFM) data strongly depends on scan and controller parameters. Data artifacts can result from poor dynamic response of the instrument. In order to achieve reliable data, dynamic interactions between AFM components need to be well understood and controlled. In this paper we present a summary of our work in this direction. It includes models for the probe-sample interaction, scanner lateral and longitudinal dynamics, scanner creep, and cantilever dynamics. The models were used to study the effect of scan parameters on the system dynamics. Simulation results for both frequency response and imaging were presented. Experimental results were given supporting the simulations and demonstrating the competence of the models. The results within will be used to develop algorithms that allow automated choice of key system parameters, guaranteeing reliable and artifact-free data for any given operating condition (sample, cantilever, environment). Consequently, expanding the AFM capabilities and permitting its use in a wider range of applications. / Singapore-MIT Alliance (SMA)

A model of long-haul hybrid-electric trucks was developed and analyzed to identify the economic benefits of hybrids during the 2009 to 2030 timeframe. Variables that were studied included the trucks operating miles, vehicle life years, fuel efficiency, hybrid fuel efficiency, cost of hybrid truck technology and diesel fuel costs. The model was studied using a case study of long-haul tractors to determine the life cycle savings of hybrid trucks during the twenty-year time period. It was predicted that hybrid long-haul trucks will be an option for trucks that have a majority of their operating cost spent on fuel and the truck is capable of achieving an improved efficiency of five-percent or greater. It was concluded that hybrid trucks will become more economical than a conventional diesel truck and generate a savings for fleet owners by as early as the year 2014. Recommendation for further study is enclosed.

Supersymmetric extensions to the Standard Model (SM) have many interesting experimental consequences which can provide important hints to the physics beyond the SM. In this thesis, we first study the anomalous magnetic moment of the muon and show that a significant constraint on the parameter space can be obtained from its current experimental value. In the next topic, we study the CP violations in B -> phi K decays and show that the SM and the minimal supergravity model (mSUGRA) cannot account for the current experimental observation. We then show that all the data can be accommodated for a wide range of parameters in models with non-universal soft breaking left-right A terms. In our last topic, which is based on a Horava-Witten inspired model proposed by R. Arnowitt and B. Dutta, we extend their analysis to the full fermion sector of the SM and propose a new mechanism different from the usual see saw mechanism to generate small neutrino masses which are in good agreement with the current neutrino oscillation data.