This dissertation comprises three parts and is presented in two chapters. Chapter 1 concerns Arthrobacter, a bacterium with an intriguing growth cycle. Whereas most bacteria exist as either a rod or coccus, this bacterium shares the rod/coccus lifestyle. It therefore seemed important to examine the growth regulatory pathways from the rod and coccus. The committed step, that catalyzed by aspartate transcarbamoylase (ATCase), in the pyrimidine biosynthetic pathway was chosen. The ATCase in Arthrobacter is like the well known Pseudomonas enzyme except that it has an active dihydroorotase (DHOase) associated. Included in Chapter 1 is the description of a microorganism, Burkholderia cepacia, whose ATCase has characteristics that are at once reminiscent of bacteria, mammals, and fungi. It differs in size or aggregation based on environmental conditions. In addition, it has an active DHOase associated with the ATCase, like Arthrobacter. B. cepacia is important both medically and for bioremediation. Since B. cepacia is resistant to most antibiotics, its unique ATCase is a prime target for inhibition. Whereas the first chapter deals with the de novo pathway to making pyrimidines, which is found mainly in the lag and log phase, Chapter 2 addresses the salvage pathway, which comes more into play during the …

On-road remote sensing has the ability to operate in real-time, and under real world conditions, making it an ideal candidate for detecting gross polluters on major freeways and thoroughfares. In this study, remote sensing was employed to detect carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxide (NO). On-road remote sensing data taken from measurements performed in six states, (Arizona, California, Colorado, Illinois, Texas, and Utah) were cleaned and analyzed. Data mining and exploration were first undertaken in order to search for relationships among variables such as make, year, engine type, vehicle weight, and location. Descriptive statistics were obtained for the three pollutants of interest. The data were found to have non-normal distributions. Applied transformations were ineffective, and nonparametric tests were applied. Due to the extremely large sample size of the dataset (508,617 records), nonparametric tests resulted in "p" values that demonstrated "significance." The general linear model was selected due to its ability to handle data with non-normal distributions. The general linear model was run on each pollutant with output producing descriptive statistics, profile plots, between-subjects effects, and estimated marginal means. Due to insufficient data within certain cells, results were not obtained for gross vehicle weight and engine type. The "year" …