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Various control methods used in the meat and poultry processing environment to mitigate listeriosis were evaluated using a dynamic in-plant Monte Carlo model. These control methods included food contact surface testing, sanitation, post-processing lethality treatment, and product formulation with microbial growth inhibitors. The dynamic in-plant model served as an input into the risk assessment model developed by the FDA and FSIS in 2003 which predicts the number of deaths and illnesses resulting from the use of each control method. The use of growth inhibitors combined with a post-processing lethality step was estimated to save over 200 more lives than the FSIS proposed minimum sampling standard. An analysis of data collected by the National Alliance for Food Safety and Security (NAFSS) found that retail-sliced deli meats have a greater prevalence and concentration of L. monocytogenes than prepackaged deli meats. Cross contamination at the retail level is suspected due to clustering of sample positives by store and the influence of sampling time of day on the prevalence of L. monocytogenes. The comparative risk of Listeria monocytogenes in retail sliced versus prepackaged deli meats was evaluated using a modified version of the 2003 FDA-FSIS risk assessment model which considered slicing location and the use of growth inhibitors. The comparative risk ratio for the number of deaths from retail-sliced versus prepackaged deli meats was found to be 9.1 and retail-sliced product with a growth inhibitor was found to be at greater risk for listeriosis than prepackaged product without growth inhibitor. / Master of Science

The purpose of this thesis was to investigate certain aspects of risk programming. In the computational example, experimental data based on varietal tests were used to obtain estimates of the variances of net revenue of the various crops considered. As was expected, the consideration of risk increased the importance of corn, the crop with the lowest unit level variance, and decreased the importance of tomatoes, a comparatively high risk crop. In the risk program, the total revenue was, of course, decreased, but the expected utility was increased and the standard deviation of the net revenue was substantially decreased. The risk program also requires less capital and labor than the no-risk program. An opportunity curve was formed by joining several points of tangency between the opportunity line and indifference curve corresponding to utility functions with different values of the risk aversion constant “a”. This opportunity curve represents combinations of net revenue and the variance of net revenue which are available to the entrepreneur. An entrepreneur could choose a point on the curve which to him represents the best combination of net revenue and variance. In doing so, he will effectively be choosing his own risk aversion constant and corresponding optimal program. By this procedure, the difficulty of hypothesising an incorrect risk aversion constant can be avoided. Computational shortcuts for arriving at optimum programs for various risk aversion constants were developed as were methods for varying the price of a process and the availability of a scarce resource. / Master of Science

The 2007 Energy Independence and Security Act mandates the production of 135 billion liters of transportation fuel achieved through the use of alternative energy sources. The most economically and sustainably competitive bioenergy crops will need to be high yielding, perennial species which require minimal inputs coupled with the ability to grow on marginal land. Grower adoption will be imperative to the success of this industry. Our results indicate that after three years of growth, several species including Arundo donax and Miscanthus × giganteus are able to produce up to 48.2 and 61.4 Mg ha⁻¹ dry weight of feedstock respectively. We also found that weed management may not be necessary under ideal growing conditions, but a group of herbicides appear promising for preemergence and postemergence application timings, tested under greenhouse conditions. The herbicides pyroxasulfone, sethoxydim and nicosulfuron may prove to be useful tools for the control of bioenergy crops if they escape cultivation. The potential for many of these exotic and highly competitive species to become invasive has hindered advancement of this industry. We develop a beginning framework to evaluate the potential for seeded Miscanthus × giganteus to become invasive, as no proven formula currently exists. We developed a novel methodology to assess the invasive potential of bioenergy crops across a continuum of invasiveness, which proved to be critical to the interpretation of our results. This methodology allows us to make relative comparisons of risk, evaluating our otherwise isolated results in broader context. We chose to evaluate M. × giganteus in a direct comparison with known exotic invasives, as well as with species that are known not to be invasive. We use a tiered approach, combining qualitative risk assessment models with quantitative field trials. Results from two weed risk assessment models indicate that many bioenergy feedstocks are of high risk, but agronomic crops such as Oryza sativa were also found to be high risk. Subsequent field trials indicate that seedling establishment for M. × giganteus in perennial systems may be low as only 0.1% of emerged seedlings survived after six months, while up to 10% of the invasive Microstegium vimineum survived. Spread of fertile M. × giganteus seedlings into annual systems with low competition had greater success; we observed 316 culms m⁻², at a distance of 1.5 m from the planted plot, after three years of growth. The observed spread of fertile M. × giganteus, in the low competition environment, did not differ from that of our positive control species; however, spread of fertile M. × giganteus seedlings into areas of high competition was significantly lower than our positive controls, up to 3 m from the cultivated plot. Importantly, A. donax and sterile M. × giganteus never spread from the cultivated plot. Results from our study and application of this novel methodology will help to prepare for the expansion of this burgeoning industry while providing useful information for the implementation of best management practices and improved stewardship. / Ph. D.

This study examines the extent to which the equivalency provision presented in the SPS agreement is able to foster trade negotiations between countries adopting different food safety measures. The study examines the role of scientific evidence as well as the political, economic, and cultural factors in impacting the national regulatory process and the international trade negotiations. It focuses on the limitations of science in allowing countries to reach consensus in contentious trade-related debates laden with risk uncertainty and missing data. The study consists of comparing the key components of the U.S. and French regulatory systems to identify the cultural basis for the differences in the perception of listeria risk and in preferences to control it. The stringent standards adopted in the U.S. and the preference for pasteurization are attributed to the complete separation of the regulatory functions form those of food production, the open style of decision-making which allows private citizens to review and comment on administrative actions, the unwillingness of U.S. regulators to expose vulnerable individuals to deadly pathogens, and the reliance on quantitative data to validate the effectiveness of pasteurization. The more flexible standards impacting listeria regulation in France are attributed to the the integration of regulatory functions with those of food production, the consumer preference for natural products, the public's trust in the government's regulatory decisions, and the belief that the determination of appropriate safety measures should be left up to the producers. / Master of Science

The Fukushima Daiichi accident prompted the nuclear community to find a new solution to reduce the risky situations in nuclear power plants (NPPs) due to beyond-design-basis external events (BDBEEs). An implementation guide for diverse and flexible coping strategies (FLEX) has been presented by Nuclear Energy Institute (NEI) to manage the challenge of BDBEEs and to enhance reactor safety against extended station blackout (SBO). To assess the effectiveness of FLEX strategies, probabilistic risk assessment (PRA) methods can be used to calculate the reliability of such systems. Due to the uniqueness of FLEX systems, these systems can potentially carry dependencies among components not commonly modeled in NPPs. Therefore, a suitable method is needed to analyze the reliability of FLEX systems in nuclear reactors. This thesis investigates the effectiveness and applicability of Bayesian networks (BNs) and Discrete-Time Bayesian Networks (DTBNs) in the reliability analysis of FLEX equipment that is utilized to reduce the risk in nuclear power plants. To this end, the thesis compares BNs with two other reliability assessment methods: Fault Tree (FT) and Markov chain (MC). Also, it is shown that these two methods can be transformed into BN to perform the reliability analysis of FLEX systems. The comparison of the three reliability methods is shown and discussed in three different applications. The results show that BNs are not only a powerful method in modeling FLEX strategies, but it is also an effective technique to perform reliability analysis of FLEX equipment in nuclear power plants. / Master of Science / Some external events like earthquakes, flooding, and severe wind, may cause damage to the nuclear reactors. To reduce the consequences of these damages, the Nuclear Energy Institute (NEI) has proposed mitigating strategies known as FLEX (Diverse and Flexible Coping Strategies). After the implementation of FLEX in nuclear power plants, we need to analyze the failure or success probability of these engineering systems through one of the existing methods. However, the existing methods are limited in analyzing the dependencies among components in complex systems. Bayesian networks (BNs) are a graphical and quantitative technique that is utilized to model dependency among events. This thesis shows the effectiveness and applicability of BNs in the reliability analysis of FLEX strategies by comparing it with two other reliability analysis tools, known as Fault Tree Analysis and Markov Chain. According to the reliability analysis results, BN is a powerful and promising method in modeling and analyzing FLEX strategies.

The increasing amounts of initial capital investments in the chemical and petroleum industry are making accurate and realistic economic analyses a necessity. The purpose of this investigation was to develop a general economic evaluation model which was an improvement over previous analysis techniques. The new aspect of this model is its capability of analysing multiple investments with a comprehensive risk analysis and with a short computer running time. Significant features of the analysis technique include: (1) A general and flexible computer model which can easily be applied to a wide range of capital investment decisions, (2) The use of present value for a consistent and realistic economic evaluation criterion, (3) Consideration of the future economic environment through the capability of predicting the time-dependent changes of the main variables, (4) Monte Carlo risk analysis to determine the effect of uncertainty in the 14 main variables, (5) Two-plant analysis with the advantage of a delayed decision on the second plant, and (6) Execution in a relatively short computer running time (six minutes on IBM 360, 65). / Master of Science

Inhibited immune responses have been observed following occupational, inadvertent, or therapeutic exposure to chemically diverse xenobiotics. In the present studies, preliminary data were generated showing limited but significant systemic immunotoxicity following low-level topical exposure to the pyrethroid insecticide, permethrin (formerly not considered an immunotoxicant). Permethrin was applied to the shaved dorsal interscapular region of C57Bl/6N mice at doses of 0.5, 1.5, or 5.0 μl/day. The highest of these doses was approximately equal to 215 μg/kg/day, which is about seven times the estimated daily human exposure in individuals wearing permethrin treated clothing for insect protection. Mice were thus exposed to permethrin daily for 10 or 30 consecutive days, or every other day for 7 or 14 exposures. Body weight was not affected by the treatment. However thymic weight was decreased and splenic weight increased 2 days after termination of the topical exposure. Histopathology of immune organs showed no significant changes. Splenic macrophages showed significantly depressed chemiluminescent responses up to 10 days following termination of exposure, but macrophage phagocytic activity was not affected. Cell surface markers of thymocytes, splenocytes and bone marrow cells were not affected. Antibody production as shown by plaque forming cell (PFC) assay decreased significantly at 10 days after dosing termination. Taken together, these data indicate that low-level topical permethrin exposure may produce systemic immunotoxicity. / Master of Science

The usage of unmanned aerial systems (UAS), also called drones, has grown at an increasing rate, with expectations of the number of unmanned aircraft (UA) to triple between 2019 and 2023 as commercial and government usage of UAS increases as per the Federal Aviation Administration. As the usage of UA increases, the probability of a UA crash resulting in injuries of 3rd parties on the ground also increases. The goal of this research was to create a method and software tool that gives the user an accurate representation of the risk to 3rd parties on the ground associated with a given flight plan. The main area of focus was on large rotorcraft and fixed-wing aircraft that are used by the military and that have the potential to do large amounts of damage if a crash were to occur. How unique types of failures affect the ground area at risk and the UA crash characteristics and how these characteristics affect population on the ground were all considered. With this information, a probability of fatality value is calculated, which helps the user determine if the mission risk is acceptable. The ability to optimize this flight path to find the lowest risk flight path is also possible, based upon user specifications. / Master of Science / Understanding the likelihood of an undesired event occurring is vital for the use of any system in the real world. This is especially true in the case of aircraft, were an undesired event can likely cause loss of life. A new area of aircraft that require additional insight into the failure characteristics are unmanned aerial systems, often referred to as drones. Drones do not have a pilot inside the aircraft, who could correct for any failures that might occur. Due to this potential inability to correct for a failure, a method must be developed to gain a better understanding of the potential failures and risks involved in drone operations. The method developed during this work was turned into a software tool, which allows a mission for a drone to be mapped out and the risk to be determined. Due to the drones being unmanned the risk is taken as the expected number of fatalities to the 3rd party individuals on the ground. This expected number of fatalities is determined by the population density of the area the flight is occurring over, and the crash characteristics for the aircraft. These methods and accompanying assumptions are outlined in the body of this work.