The present work focuses on the study of two-phase flow behavior called “Intermittent Buoyancy Induced Flow” (IBIF) resulting from the loss of coolant circulation in a CANDU nuclear reactor core. The main objectives are to study steam bubble formation and migration through the pressure tube and into the feeder tubes and headers, and to study the effect of pressure tube sagging on the two-phase flow behavior during IBIF. Experiments are conducted using air and water flow at atmospheric pressure to qualitatively examine the IBIF phenomena. The test showed oscillating periodic behavior in the void fraction as the air vents. In addition to this, a mathematical model based on a simplified momentum balance for the liquid and gas phases was formulated. The model was further solved and compared to the experimental data. The model predictions showed a reasonable agreement within the investigated range of void fractions.

The present work focuses on the study of two-phase flow behavior called “Intermittent Buoyancy Induced Flow” (IBIF) resulting from the loss of coolant circulation in a CANDU nuclear reactor core. The main objectives are to study steam bubble formation and migration through the pressure tube and into the feeder tubes and headers, and to study the effect of pressure tube sagging on the two-phase flow behavior during IBIF. Experiments are conducted using air and water flow at atmospheric pressure to qualitatively examine the IBIF phenomena. The test showed oscillating periodic behavior in the void fraction as the air vents. In addition to this, a mathematical model based on a simplified momentum balance for the liquid and gas phases was formulated. The model was further solved and compared to the experimental data. The model predictions showed a reasonable agreement within the investigated range of void fractions.

Remittances significantly affect recipient households’ behavior. Using data from the Jamaican Survey of Living Conditions and the Jamaican Labor Force Survey ( 2001-2007), this dissertation explores the effects of remittances on labor market participation and household expenditures. Jamaica’s proximity to the United States and its diaspora of educated individuals shapes an economy largely dependent on remittances, thus providing an interesting case study. First, we investigate whether remittances alter labor market behavior of married women in remittance-receiving households located in Jamaica. Remittances, the wife’s education, and wages are all treated as endogenous when estimating labor market participation and hours worked. Unlike other studies, we find that after instrumenting for remittances, the outside income has no significant effect on the supply of labor. Second, we assess the extent that remittances alter the consumption pattern of recipient households in Jamaica. Classical theory predicts that total income affects household consumption decisions, but developments in behavioral economics suggest otherwise. The disaggregation of income streams and consumption expenditures provide us with unique insight into household behavior and in particular, spending on items such as food, schooling, and vices. Using Engel curve estimation and the two-part fractional response models, we find that the source of income significantly affects the shares of income spent in specific consumption categories. Recipients, for example, generally spend more of their income on schooling and home production and less at the grocery store. These findings suggest important implications should government look to tax or restrict the flow of remittances.

The goal of this research is to understand how three different parameters affect single chain variable fragment (scFv) binding capacity. The parameters that were varied include the number of variable complementarity determining regions (CDRs), the number amino acids used to diversify CDRs, and configuration of the structure. How the parameters affect the binding capacity will be tested using the yeast two hybrid assay against five different protein domains. Eight scFv libraries were generated; the genes expressing the scFvs were constructed and the CDRs were randomized using PCR amplification. Genes expressing scFvs were cloned, using the homologous gap repair mechanism in <i>Saccharomyces cerevisiae</I>. Representative members of scFv libraries were sequenced to confirm correct construction.<p> Library diversity was calculated from the library transformation efficiency. Transformation efficiency refers to the number of cells that grew at the time of transformation of the scFv gene into yeast cells. There were significant differences in the diversity of the scFv libraries, which created difficulty in comparing the library binding capacities. Sequencing the scFv libraries revealed that on average 50% of each library contained correct scFv sequences. The percent of correct sequences within each library was then used to calculate the functional diversity.<p> The yeast two-hybrid assay was used to screen the scFv libraries for interactions and to test binding capacity. The binding capacity of the scFv libraries was tested and compared in five different yeast two-hybrid assays using five protein domains as the targets for each screen. The screening results showed that in all cases cyclic scFv libraries had a statistically significant higher binding capacity than linear scFv libraries despite a diversity bias against the cyclic libraries. There was no clear trend in binding capacity with the other two parameters; however, the four amino acid three CDR libraries dominated over the other libraries in almost every screen.<p> Some of the scFvs isolated from the screens were expressed in <i>E. coli</i> and <i>S. cerevisiae</i>to analyze for proper expression and correct size. All the scFvs that were isolated and analyzed were the correct size and could be purified using a poly histidine tag.<p> Due to its bioaffinity and specificity, scFvs were constructed to profile disease patterns, and to identify potential drug targets. In addition to its original application to health-related studies, scFvs could also be extended to locate potential metabolic bottlenecks, to alter metabolic flux to enhance productivity, and regulate metabolic bionetworks. Industrial microorganisms are generally carrying more than two sets of chromosomes, making it difficult to be genetically engineered when conventional approaches are employed. With the availability of scFvs as reported in this thesis, we are able to design specific scFvs that selectively bind to target proteins, resulting in re-routing of metabolic flux within the microorganism, toward a high productivity of desired product. ScFvs can be applied to industrial microorganisms directly, leading to the development of new fermentation processes.

The purpose of this project was to produce visual work that examined a possible nostalgia that unfolds around the breakfast meal. The method of examination involved creating a process breakfast that was followed thirty times. The result of following this process was the taking of three hundred Polaroids that were then edited for their potential to visually reconstruct the ideal process breakfast. This process of discovery has resulted in a number of significant insight into the narrative of breakfast: that an idealized narrative could exist in the visualization of the process breakfast; that elements of nostalgia that may exist within the work are contingent on the viewer; and the level of authenticity of the project affects the nature of the idealization in effect.

Astrocytes, the major type of non-neuronal cells in the brain, play an important functional role in the brains extracellular potassium (K+) and pH homeostasis. Pathological brain states have been shown to cause astrocyte swelling. However, these volume changes have never before been verified to occur in response to physiological activity. In the present thesis, two-photon laser scanning microscopy was used to visualize real-time astrocyte volume changes in the stratum radiatum of the CA1 region of the hippocampus. Astrocyte somas and primary processes were observed to swell by 19.0±0.9% in response to a physiological (3 mM) increase in the concentration of extracellular K+. Astrocyte swelling was partially mediated by K+ influx through inwardly rectifying K+ channels (Kir), as their inhibition resulted in a significant decrease of the increased K+ induced astrocyte swelling (13.9±0.9%). In addition, the bicarbonate ion (HCO3-) was found to play a significant role in the increased K+ induced astrocyte swelling. The astrocyte swelling was significantly decreased when the influx of HCO3- was decreased in 1) a HCO3- free extracellular solution (5.4±0.7%), 2) in the presence of an extracellular carbonic anhydrase inhibitor (11.4±0.6% ), and 3) when the activity of the sodium-bicarbonate cotransporter (NBC) was blocked (8.3±0.7%) . Conversely, astrocytes were found to shrink by 7.7±0.5% in response to ã-Amino-butyric Acid (GABA) receptor activation. GABAA receptor mediated astrocyte shrinkage was significantly decreased to 5.0±0.6% when HCO3- efflux was reduced. Furthermore, in this thesis it was shown for the first time that astrocytes swell in response to neuronal stimulation (4.0±0.4%). This activity induced astrocyte swelling was significantly decreased to 1.5±0.2% in a HCO3- free extracellular solution. These astrocyte volume changes may have important implications for the regulation of brain activity under both physiological and pathological brain states.

Bubble and cavitation effects phenomena can be encountered in two-phase gas-liquid systems in industry. In certain industries, particularly high-risk systems such as a nuclear reactor/plant, the detection of bubble dynamics, and the monitoring and measurement of their characteristics are necessary in controlling temperature. While in the petro-chemical engineering industry, such as oil transportation pipelines, the detection and monitoring of bubbles/cavitation phenomena are necessary to minimise surface erosion in fluid carrying components or downstream facilities. The high sensitivity of Acoustic Emission (AE) technology is feasible for the detection and monitoring of bubble phenomena in a two phase gas-liquid system and is practical for application within the industry. Underwater measurement of bubble oscillations has been widely studied using hydrophones and employing acoustic techniques in the audible range. However, the application of Acoustic Emission (AE) technology to monitor bubble size has hitherto not been attempted. This thesis presents an experimental investigation aimed at exploring AEs from gas bubble formation, motion and destruction. AE in this particular investigation covers the frequency range of between 100 kHz to 1000 kHz. The AE waveform analysis showed that the AE parameter from single bubble inception and burst events, i.e. AE amplitude, AE duration and AE energy, increased with the increase of bubble size and liquid viscosity. This finding significantly extends the potential use of AE technology for detecting the presence of bubbles in two-phase flow. It is concluded that bubble activity can be detected and monitored by AE technology both intrusively and non-intrusively. Furthermore, the bubble size can be determined by measurement of the AE and this forms the significant contribution of this thesis.

Incomplete data is a pervasive problem in health research, and as a result statistical methods enabling inference based on partial information play a critical role. This thesis explores estimation of regression coefficients and associated inferences when variables are incompletely observed. In the later chapters, we focus primarily on settings with incomplete covariate data which arise by design, as in studies with two-phase sampling schemes, as opposed to incomplete data which arise due to events beyond the control of the scientist. We consider the problem in which "inexpensive" auxiliary information can be used to inform the selection of individuals for collection of data on the "expensive" covariate. In particular, we explore how parameter estimation relates to the choice of sampling scheme. Efficient sampling designs are defined by choosing the optimal sampling criteria within a particular class of selection models under a two-phase framework. We compare the efficiency of these optimal designs to simple random sampling and balanced sampling designs under a variety of frameworks for inference. As a prelude to the work on two-phase designs, we first review and study issues related to incomplete data arising due to chance. In Chapter 2, we discuss several models by which missing data can arise, with an emphasis on issues in clinical trials. The likelihood function is used as a basis for discussing different missing data mechanisms for incomplete responses in short-term and longitudinal studies, as well as for missing covariates. We briefly discuss common ad hoc strategies for dealing with incomplete data, such as complete-case analyses and naive methods of imputation, and we review more broadly appropriate approaches for dealing with incomplete data in terms of asymptotic and empirical frequency properties. These methods include the EM algorithm, multiple imputation, and inverse probability weighted estimating equations. Simulation studies are reported which demonstrate how to implement these procedures and examine performance empirically. We further explore the asymptotic bias of these estimators when the nature of the missing data mechanism is misspecified. We consider specific types of model misspecification in methods designed to account for the missingness and compare the limiting values of the resulting estimators. In Chapter 3, we focus on methods for two-phase studies in which covariates are incomplete by design. In the second phase of the two-phase study, subject to correct specification of key models, optimal sub-sampling probabilities can be chosen to minimise the asymptotic variance of the resulting estimator. These optimal phase-II sampling designs are derived and the empirical and asymptotic relative efficiencies resulting from these designs are compared to those from simple random sampling and balanced sampling designs. We further examine the effect on efficiency of utilising external pilot data to estimate parameters needed for derivation of optimal designs, and we explore the sensitivity of these optimal sampling designs to misspecification of preliminary parameter estimates and to the misspecification of the covariate model at the design stage. Designs which are optimal for analyses based on inverse probability weighted estimating equations are shown to result in efficiency gains for several different methods of analysis and are shown to be relatively robust to misspecification of the parameters or models used to derive the optimal designs. Furthermore, these optimal designs for inverse probability weighted estimating equations are shown to be well behaved when necessary design parameters are estimated using relatively small external pilot studies. We also consider efficient two-phase designs explicitly in the context of studies involving clustered and longitudinal responses. Model-based methods are discussed for estimation and inference. Asymptotic results are used to derive optimal sampling designs and the relative efficiencies of these optimal designs are again compared with simple random sampling and balanced sampling designs. In this more complex setting, balanced sampling designs are demonstrated to be inefficient and it is not obvious when balanced sampling will offer greater efficiency than a simple random sampling design. We explore the relative efficiency of phase-II sampling designs based on increasing amounts of information in the longitudinal responses and show that the balanced design may become less efficient when more data is available at the design stage. In contrast, the optimal design is able to exploit additional information to increase efficiency whenever more data is available at phase-I. In Chapter 4, we consider an innovative adaptive two-phase design which breaks the phase-II sampling into a phase-IIa sample obtained by a balanced or proportional sampling strategy, and a phase-IIb sample collected according to an optimal sampling design based on the data in phases I and IIa. This approach exploits the previously established robustness of optimal inverse probability weighted designs to overcome the difficulties associated with the fact that derivations of optimal designs require a priori knowledge of parameters. The efficiency of this hybrid design is compared to those of the proportional and balanced sampling designs, and to the efficiency of the true optimal design, in a variety of settings. The efficiency gains of this adaptive two-phase design are particularly apparent in the setting involving clustered response data, and it is natural to consider this approach in settings with complex models for which it is difficult to even speculate on suitable parameter values at the design stage.

The ability to effectively analyze particulate matter (PM2.5) in air is becoming increasingly pertinent. Allen Goldstein of the University of California in Berkeley is studying the semi-volatile fraction of organic compounds in PM2.5 through the use of the thermal desorption aerosol gas chromatograph (TAG) system. However, as conventional GC does not provide adequate separation power, the development of comprehensive two-dimensional gas chromatography (GC × GC) was required. GC × GC works more effectively by utilizing a modulator that periodically traps and focuses analytes from a primary column onto a secondary column. This allows for the primary and secondary columns to separate the analytes based on two different properties. This report focuses on the continuing study and enhancement of a modulator designed by Ognjen Panić during his Masters project. Improving and testing the robustness of this dual stage modulator was originally the focus of this project. However, this study led to the development of a single stage modulator. In addition to that, the effect of modulator characteristics such as length of the restriction, total length of the modulator and wall thickness on the modulator performance were studied. A robustness test of the single stage modulator was also completed. Experiments conducted tested the characteristics of the new modulator to ensure it performed effectively and would satisfy the requirements of the TAG system. A study comparing the sensitivity of conventional gas chromatography and GC × GC was also preformed. The sensitivity of GC × GC was on average an order of magnitude better than that of 1D GC.

Abnormal pressures have been measured in the deep boreholes at the Bruce site, southern Ontario, where a deep geologic repository for low and intermediate level radioactive waste disposal has been proposed. The pressure regime in the stratigraphic units exhibits either higher than hydrostatic pressure (over-pressured) or lower than hydrostatic pressure (under-pressured) are considered to be abnormal. At the Bruce site, the Ordovician sediments are under-pressured while the underlying Cambrian sandstone and the overlying Guelph carbonate are over-pressured. Hypotheses have been documented in literature to explain the phenomenon of abnormal pressures. These hypotheses include osmosis, glacial loading and deglaciation unloading, exhumation of overlying sediments, crustal flexure and the presence of an immiscible gas phase. Previous work on the Bruce site has shown that the under-pressures in the Ordovician limestone and shales could not be explained by glaciation and deglaciation or by saturated analyses. The presence of a gas phase in the Ordovician formations has been determined to be a reasonable cause of the under-pressure developed in the Ordovician shales and limestones at the Bruce site. Support for the presence of a gas phase includes solution concentrations of methane, concentrations of environmental isotopes related to methane and estimates of water and gas saturations from laboratory core analyses. The primary contribution of this thesis is the sensitivity analyses performed on the hydrogeologic parameters with respect to a one dimensional two-phase flow model. First, a one dimensional two-phase air and water flow model was adopted and reconstructed to simulate the long-term evolution of the groundwater regimes at the DGR site. Then the hydrogeologic parameters which impact the presence of under-pressure in the groundwater are investigated. Data required to quantify the properties of geologic media and groundwater are adopted directly from borehole testing and laboratory testing results. The permeable boundaries of the domain are assumed to be water saturated and pressure specified (using hydrostatic conditions in the Guelph Formation and hydrostatic with 120 m over-pressure condition in the Cambrian and Precambrian). Isothermal conditions were assumed, thus constant water density and viscosity values are estimated for the average total dissolved solids (TDS) concentration of the modelled stratigraphic column. A constant diffusion coefficient (a diffusivity of $0.25\times10^{-8}$ m$^2$/s) of air in water is assumed with a saturation-dependent tortuosity. The air generation rate is assumed to simulate the gas phase generated in the Ordovician formations. The numerical simulation of up to 4 million years provides a means to explore the behaviour of gas phase dissipation due to partitioning into the water phase and diffusive transport in the solute phase. Results confirmed that the presence of a gas phase would result in the under-pressure in water.