The extent to which economic evaluations of public health programs in Ontario are conducted and used by decision makers is currently very limited. This thesis supports public health decision-making through applied and methodological work. The applied work demonstrates different methods to evaluate the cost-effectiveness of public health interventions using the examples of seasonal and pandemic influenza immunization programs. The methodological component explores whether time horizon choice, one methodological consideration in economic evaluations, introduces bias. The economic evaluation of Ontario’s universal influenza immunization program (UIIP) uses primarily provincial health administrative databases to assess the impact of UIIP on health outcomes (quality-adjusted life years (QALYs), mortality), health care resource use (physician office visits, emergency department visits, and hospitalizations), and costs due to seasonal influenza. Ontario’s UIIP was found to be cost-effective compared to a targeted program. The economic evaluation of Ontario’s H1N1 (2009) mass immunization program uses a mathematical modeling approach to describe the pandemic as observed in Ontario. By removing immunization from the simulation, the impact of the program was evaluated. Outcome measures include health outcomes (attack rate, deaths, QALYs), resource use, and cost (physician office visits, emergency department visits, hospitalizations). The analysis found Ontario’s mass immunization program to be highly cost-effective despite high program cost. The methodological component investigates whether time horizon choice, a major methodological choice, introduces bias to economic evaluations. The existence, magnitude and direction of time horizon bias are demonstrated using a formal model. This work supports current guidelines in recommending a lifetime time horizon and provides a framework to discuss bias in economic evaluations. This thesis demonstrates different approaches to evaluate the cost-effectiveness of public health interventions, informs decision-making, and establishes the groundwork to guide future economic evaluations of public health interventions.

The extent to which economic evaluations of public health programs in Ontario are conducted and used by decision makers is currently very limited. This thesis supports public health decision-making through applied and methodological work. The applied work demonstrates different methods to evaluate the cost-effectiveness of public health interventions using the examples of seasonal and pandemic influenza immunization programs. The methodological component explores whether time horizon choice, one methodological consideration in economic evaluations, introduces bias. The economic evaluation of Ontario’s universal influenza immunization program (UIIP) uses primarily provincial health administrative databases to assess the impact of UIIP on health outcomes (quality-adjusted life years (QALYs), mortality), health care resource use (physician office visits, emergency department visits, and hospitalizations), and costs due to seasonal influenza. Ontario’s UIIP was found to be cost-effective compared to a targeted program. The economic evaluation of Ontario’s H1N1 (2009) mass immunization program uses a mathematical modeling approach to describe the pandemic as observed in Ontario. By removing immunization from the simulation, the impact of the program was evaluated. Outcome measures include health outcomes (attack rate, deaths, QALYs), resource use, and cost (physician office visits, emergency department visits, hospitalizations). The analysis found Ontario’s mass immunization program to be highly cost-effective despite high program cost. The methodological component investigates whether time horizon choice, a major methodological choice, introduces bias to economic evaluations. The existence, magnitude and direction of time horizon bias are demonstrated using a formal model. This work supports current guidelines in recommending a lifetime time horizon and provides a framework to discuss bias in economic evaluations. This thesis demonstrates different approaches to evaluate the cost-effectiveness of public health interventions, informs decision-making, and establishes the groundwork to guide future economic evaluations of public health interventions.

With the rapid growth of energy demand and consequently growth in supply, increasing energy costs, and environmental concerns, there is a critical need to find new ways to make better use of existing energy systems and resources and decelerate the demand growth towards a sustainable energy system. All of these facts are leading to the proposal of novel approaches to optimize the utilization of energy in different sectors to reduce the customer's total energy costs, demand and greenhouse gas (GHG) emissions while taking into account the end-user preferences. Utilities have implemented Demand Side Management (DSM) and Demand Response (DR) programs to better manage their network, offer better services to their customers, handle the increase in electricity demand, and at the same time increase system reliability and reduce environmental impacts. Smart Grid developments such as information technology, communication infrastructure and smart meters improve the effectiveness and capability of Energy Management Systems (EMSs) and facilitate the development of automated operational decision-making structures for energy systems, thus assisting DSM and DR programs to reach their full potential. The literature review indicates that whereas significant work has been done in DSM and DR in utilities, these works have mostly focused on direct load control of particular loads, and there is a lack of a general framework to consider all types of energy hubs in an integrated Energy Hub Management System (EHMS). In this context, mathematical modeling of energy systems for EMSs, which is the main concern of the present work, plays a critical role. This research proposes mathematical optimization models of energy hubs which can be readily incorporated into EHMS in the context of Smart Grids. The energy hub could be a single or multi-carrier energy system in residential, commercial, agricultural and/or industrial sectors. Therefore, mathematical models for energy hubs in residential, commercial, and agricultural sectors have been developed and are presented and discussed in this thesis. In the residential sector, this research presents mathematical optimization models of residential energy hubs which can be readily incorporated into automated decision making technologies in Smart Grids, and can be solved efficiently in a real-time frame to optimally control all major residential energy loads, storage and production components while properly considering the customer preferences and comfort levels. Mathematical models for major household demand, i.e., fridge, freezer, dishwasher, washer and dryer, stove, water heater, hot tub, and pool pumps, are formulated. Also, mathematical models of other components of a residential energy system including lighting, heating, and air-conditioning are developed, and generic models for solar PV panels and energy storage/generation devices are proposed. The developed mathematical models result in a Mixed Integer Linear Programming (MILP) optimization problem, whose objective is to minimize demand, total costs of electricity and gas, emissions and peak load over the scheduling horizon while considering end-user preferences. The application of this model to a real household are shown to result in savings of up to 20% on energy costs and 50% on peak demand, while maintaining the household owner's desired comfort levels. In the commercial sector, mathematical optimization models of produce storage facilities to optimize the operation of their energy systems are proposed. In the storage facilities, climate control of the storage rooms consumes considerable energy; thus, a mathematical model of storage facilities appropriate for their optimal operation is developed, so that it can be implemented as a supervisory control in existing climate controllers. The proposed model incorporates weather forecasts, electricity price information, and the end-user preferences to optimally operate existing climate control systems in storage facilities. The objective is to minimize total energy costs and demand charges while considering important parameters of storage facilities; in particular, inside temperature and humidity should be kept within acceptable ranges. Effects of uncertainty in electricity price and weather forecast on optimal operation of the storage facilities are studied via Monte-Carlo simulations. The presented simulation results show the effectiveness of the proposed model to reduce total energy costs while maintaining required operational constraints. In the agricultural sector, this work presents mathematical optimization models of greenhouses to optimize the operation of their energy systems. In greenhouses, artificial lighting, CO2 production, and climate control consume considerable energy; thus, a mathematical model of greenhouses appropriate for their optimal operation is developed, so that it can be implemented as a supervisory control in existing greenhouse controllers. The proposed model incorporates weather forecasts, electricity price information, and the end-user preferences to optimally operate existing control systems in greenhouses. The objective is to minimize total energy costs and demand charges while considering important parameters of greenhouses; in particular, inside temperature and humidity, CO2 concentration, and lighting levels should be kept within acceptable ranges. Effects of uncertainty in electricity price and weather forecast on optimal operation of the storage facilities are studied via Monte-Carlo simulations and robust optimization approach. The presented simulation results show the effectiveness of the proposed model to reduce total energy costs while maintaining required operational constraints.

Polymer electrolyte membrane (PEM) fuel cells have increasingly become promising green energy sources for automobile and stationary cogeneration applications but its success in commercialization depends on performance optimization and manufacturing cost. The activation losses, expensive platinum catalyst, and water flooding phenomenon are the key factors currently hindering commercialization of PEM fuel cells. These factors are associated with the cathode catalyst layer (CCL), which is about ten micrometers thick. Given the small scale of this layer, it is extremely difficult to study transport phenomena inside the catalyst layer experimentally, either intrusively or non-intrusively. Therefore, mathematical and numerical models become the only means to provide insight on the physical phenomena occurring inside the CCL and to optimize the CCL designs before building a prototype for engineering application. In this thesis research, a comprehensive two-phase mathematical model for the CCL has been derived from the fundamental conservation equations using a volume-averaging method. The model also considers several water transport and physical processes that are involved in the CCL. The processes are: (a) electro-osmotic transport from the membrane to the CCL, (b) back-diffusion of water from the CCL to the membrane, (c) condensation and evaporation of water, and (d) removal of liquid water to the gas flow channel through the gas diffusion layer (GDL). A simple analytical model for the activation overpotential in the CCL has also been developed and an optimization study has been carried out using the analytical activation overpotential formulation. Further, the mathematical model has been simplified for the CCL and an analytical approach has been provided for the liquid water transport in the catalyst layer. The volume-averaged mathematical model of the CCL is finally implemented numerically along with an investigation how the physical structure of a catalyst layer affects fuel cell performance. Since the numerical model requires various effective transport properties, a set of mathematical expressions has been developed for estimating the effective transport properties in the CCL and GDL of a PEM fuel cell. The two-dimensional (2D) numerical model has been compared with the analytical model to validate the numerical results. Subsequently, using this validated model, 2D numerical studies have been carried out to investigate the effect of various physical and wetting properties of CCL and GDL on the performance of a PEM fuel cell. It has been observed that the wetting properties of a CCL control the flooding behavior, and hydrophilic characteristics of the CCL play a significant role on the cell performance. To investigate the effect of concentration variation in the flow channel, a three-dimensional numerical simulation is also presented.

<p>There were 2.5 million people newly infected with HIV in 2007, clearly motivating the need for additional novel prevention methods. In response, topical vaginal antimicrobials, or microbicides, are being developed. These products aim to stop HIV transmission through local, vaginal delivery of antiviral compounds. To succeed, microbicides require a potent active compound within a well-engineered delivery vehicle.</p><p>A well-engineered delivery vehicle provides an antiviral compound with the greatest opportunity to interact with HIV and/or infected cells, thereby increasing overall microbicide effectiveness. The theoretical and experimental investigations within this dissertation are concerned with the study of HIV and active compound transport within microbicide delivery vehicles and with the mechanisms by which these transport processes can be affected to maximize viral neutralization. To initially investigate the factors contributing to microbicide effectiveness, a combined pharmacokinetic and pharmacodynamic model of HIV transport and neutralization within a microbicide product was created. Model results suggested that thin (~100µm) layers of microbicide product may protect against HIV infection. Model results also indicated that a specific and engineerable property of delivery vehicles - the ability to restrict viral transport - may increase the overall effectiveness of a microbicide. Two new experimental assays were developed to test the hypothesis that delivery vehicles can slow viral transport. First, a novel methodology was created to measure particle diffusion over length scales relevant to microbicide delivery (50-500µm). Results showed that current vehicles significantly restrict the transport of small molecules and proteins. The second assay was designed to test HIV transport in a biologically relevant, layered (fluid-microbicide-tissue) configuration of a microbicide product in vivo; infectious HIV was placed above a thin layer of a microbicide delivery vehicle. Assay results showed that HIV transport is significantly slowed by two different placebo gels. This experimental confirmation of viral restriction in hydrogels, combined with the theoretical finding that viral restriction increased microbicide effectiveness, strongly motivates the future development of new delivery vehicles that intentionally slow viral transport. These new experimental methodologies can also be used to screen and compare future delivery vehicles to produce optimal microbicide products.</p><p>Finally, a two-dimensional, computational finite-element vaginal model was created to evaluate the transport of drugs from an intravaginal ring. This model determined that while IVRs may be effective in the delivery of antiviral compound, their performance is influenced by the flow of vaginal fluid. The analysis also warns about the potential for local toxicity. </p><p>Well-engineered delivery vehicles are an essential component to microbicide performance because they maximize the opportunities for active compounds to interact with and neutralize HIV. The studies in this dissertation demonstrate that delivery vehicles have a significant effect on active compound and HIV transport. To create an effective microbicide, vehicle effects on transport processes must be well understood, purposefully engineered, and carefully optimized to ensure maximal interactions between antiviral compounds and virus. Directed engineering of delivery vehicles contribute to the foundation for microbicide success.</p> / Dissertation

<p>This dissertation explores strategies for reducing HIV-virion transport to mucosal surfaces to prevent HIV infection. Infection requires contact between HIV and an infectable cell, so any means of inhibiting this step could contribute to HIV prevention. Our goals were to quantify the effects of strategies that reduce transport of HIV virions and to evaluate them in the context of HIV prevention. We used fundamental transport theory to design two basic strategies: (1) modifying the effective radius of virions; and (2) modifying the native medium through which virions diffuse. We proposed to implement these strategies using (1) anti-HIV antibodies that would bind and aggregate virions and (2) topically-applied semi-solid gels that coat vaginal epithelial surfaces. </p> <p>We measured diffusion coefficients of HIV virions and HIV-like particles in the presence of antibodies and within semi-solid gels. In experiments with antibodies, we did not observe reductions in the diffusion coefficients. In experiments using particle tracking to measure the diffusion coefficients of virions in vaginal gels, we found that the diffusion coefficients in gels were approximately 10,000 times lower than those in water. </p> <p>We proceeded to evaluate the potential for semi-solid gels to prevent HIV transmission at mucosal surfaces. From previous experiments in our lab that characterized the topical deployment of vaginal gels <italic>in vivo</italic>, we know that vaginal gels form an uneven coating on the epithelium with gel layer thicknesses of the order of hundreds of microns. Thus, we determined whether semi-solid gels could function as physical barriers to HIV when deployed as thin, incomplete layers on the epithelium. </p> <p>We developed an experimental system to test the barrier functioning of thin gel layers. We applied thin gel layers to the porous membrane of a Transwell system, and added a solution of HIV to the top compartment. After incubation, samples were assayed for levels of HIV. We found that thin gel layers reduced levels of HIV in the bottom compartment compared to controls where no gel had been applied: There was a log reduction in levels of HIV in conditions where gel layers of approximately 150 &mu;m thickness had been applied to the membrane after 0-, 4-, and 8-hour incubation. Thus, it appears possible for gel layers of thicknesses found <italic>in vivo</italic> to function as physical barriers to HIV over biologically-relevant time scales. </p> <p>We studied how nonuniform deployment of semi-solid gels affects accumulation of virions in tissue using a mathematical model. We used transport theory to develop a model of HIV diffusing from semen, through gel layers where present, to tissue. Our findings suggest that comprehensive coating of over 80% of the tissue surface area and gel layer thicknesses over 100 &mu;m are crucial to the barrier functioning of topical gels. Under these conditions, the level of viral restriction makes a significant contribution to increasing the time required for virions to reach tissue. </p> <p>Overall, the work presented here applies transport theory in the context of HIV transmission and prevention. Results contribute to theoretical and experimental frameworks that can help understand events in HIV transmission and to design and evaluate new technologies for HIV prevention.</p> / Dissertation

The distribution, enrichment, and accumulation of heavy metals in the sediments, especially those at the vicinity of tributary estuaries of Kaohsiung Harbor, Taiwan were investigated. Sediment samples from six locations in the Kaohsiung Harbor were collected quarterly in the period from 2002 to 2005 and characterized for metal content (e.g., Hg, Pb, Cd, Cr, Cu, Zn and Al), water content, organic matter, total nitrogen, total phosphorous, total grease, and grain size. Results showed that metal concentrations varied from 0.58 mg kg-1 for Cd to 596 mg kg-1 for Zn. Metal concentrations at the vicinity of river mouths were higher than those at other locations. All heavy metals studied, except Cr, had relatively high enrichment factors and geo-accumulation indices in the estuaries. Moreover, metal concentrations correlated closely to the physical-chemical properties of the sediments, which strongly suggested the influence of industrial and municipal wastewaters discharged from the neighboring industrial parks and river basins. Results would help develop strategies for pollution control and sediment remediation of Kaohsiung Harbor. Ocean disposal of wastes such as dredged sediments causes the concentrations of contaminants and some other water quality parameters in the water column to change. In this study, the STFATE (Short-term Fate) system, a model developed by the US Corps of Engineers for managing automatic dredging and disposal of the dredged materials, was used to model and simulate the deposition, dispersion and accumulation of the dredged material disposed at an ocean site. Additionally, aerial photographs taken from a helicopter on dispersion of the disposed sediments were used to calibrate and verify the modeling results for evaluating its applicability in predicting the influence of disposing dredged sediments on the surrounding seawater quality. Simulation results indicate that after 4 h of ocean disposal, the dredged sediment showed negligible adverse influence on the seawater quality (SS = 3 ¡V 4 mg/L). Results of simulating the dispersion of dredged sediments revealed that 20 seconds disposal duration resulted in smaller influence distance and range but a longer time for the seawater to recover to its original state. A longer disposal time of 1,200 seconds would cause a larger distance and range of influence but a shorter recovery time. The verification results demonstrate that simulated values on the dispersion length, width, area and shape generally comfort to the trends of monitored data; the average error is around 27.8%.

Unmanned Underwater Vehicles (UUV) in open-seas are highly nonlinear with system motions. Because of the complex interaction of the body with environment it is difficult to control them efficiently. Linearization is applied to system in order to design controllers developed for linear systems. To overcome the effects of disturbances, a mathematical model which will compensate all disturbances and effects of linearization is required. In this study first a mathematical model is formed wherein the linear and nonlinear hydrodynamic coeffi- cients are calculated with strip theory. After the basic mathematical model is developed, it is simplified and decoupled into speed, steering and diving subsystems. Consequently PID (Proportional Derivative Integral), SMC (SlidingMode Control) and LQR (Linear Quadratic Regulator)/LQG (Linear Quadratic Gaussian) control methods can be applied on each subsystem to design controllers. Some of the system parameters can be estimated from state vector data based on measurements using the methods of linear sequential estimation and genetic algorithms. As for the final part of the study, an online obstacle avoidance algorithm which avoids local optimums using Boolean operators is presented. In addition a simple guidance algorithm is suggested for waypoint navigation. Due to the fact that ULISAR UUV is still on construction phase, we were unable to test our algorithms. But in the near future, we plan to study all these algorithms on the UUV ULISAR.

A comprehensive model, previously developed for a rectangular parallelepiped shaped 0.3 MWt circulating fluidized bed combustor (CFBC) fired with high calorific value coal burning in sand and validated against experimental data is adapted to cylindrical configuration and is extended to incorporate NOx formation and reduction reactions and pressure drops around cyclone, downcomer and loop seal. Its predictive accuracy is tested by applying it to the simulation of Middle East Technical University (METU) 150 kWt CFBC burning low calorific value indigenous lignite with high Volatile Matter/Fixed Carbon (VM/FC) ratio in its own ash and comparing its predictions with measurements. Favorable comparisons are obtained between the predicted and measured temperatures, pressure profiles and emissions of gaseous species. Results reveal that predictive accuracy in pressure profile strongly depends on the correlation utilized for entrainment in dilute zone and that accuracy in NO emission requires data on partitioning of coal nitrogen into char-N and volatile-N and is affected significantly by dilute zone oxygen content.

The flow of a liquid film over a rapidly rotating horizontal disk has many applications inmedical, industrial, and engineering fields. A specific example is the heat and mass transfer processes between expanded liquid and surrounded dense gas. Diferent wave regimes of a liquid film depend on a flow conditions such as the properties of a liquid, its initial speed,parameters of environment, etc. Therefore, experimental investigation of the film flow over a spinning disk is needed to both validate theoretical predictions and establish methods for fluid flow monitoring.This thesis presents novel video-based algorithms for detection and tracking wave structural data of the liquid film flowing over a spinning disk reactor. The algorithms are based on the spiral model of wave and the quasi-optimal method for estimation of a wave velocity as ill-posed problem. Their performance is compared with results predicted by the fluid dynamics based on the Navier-Stokes equations in the case of thin film.Using experimental video data, the developed models and algorithms allow investigators to estimate the characteristics of wave regimes such as wavelengths, inclination angles, and the radial and azimuthal velocity components of the fluid. The accuracy of estimated characteristics was analyzed. It was shown that average distance between consecutive two waves,their spiral shapes, and the radial velocities of waves confirm the theoretical results and predictions. In particular, computed wavelength is within 1% and a change of the inclination angles is within 2% of the predicted values.