Screening, optimization and extraction of polyhydroxyalkanoates and peptidoglycan from Bacillus megaterium

Bioplastics are polymers (such as polyesters) produced from bacterial fermentations that are biodegradable and nonhazardous. They are produced by a wide variety of bacteria and are made only when stress conditions allow, such as when nutrient levels are low, more specifically levels of nitrogen and oxygen. These stress conditions cause certain bacteria to build up excess carbon deposits as energy reserves in the form of polyhydroxyalkanoates (PHAs). PHAs can be extracted and formed into actual plastic with the same strength of conventional, synthetic-based plastics without the need to rely on foreign petroleum. The overall goal of this project was to select for a bacteria that could grow on sugars found in the lignocellulosic biomass, and get the bacteria to produce PHAs and peptidoglycan. Once this was accomplished the goal was to extract PHAs and peptidoglycan in order to make a stronger more rigid plastic, by combing them into a co-polymer. The individual goals of this project were to: (1) Select and screen bacteria that are capable of producing PHAs by utilizing the carbon/energy sources found in lignocellulosic biomass; (2) Maximize the utilization of those sugars present in woody biomass in order to produce optimal levels of PHAs. (3) Use room temperature ionic liquids (RTILs) in order to separate the cell membrane and peptidoglycan, allowing for better extraction of PHAs and more intact peptidoglycan. B. megaterium a Gram-positive PHA-producing bacterium was selected for study in this project. It was grown on a variety of different substrates in order to maximize both its growth and production of PHAs. The optimal conditions were found to be 30°C, pH 6.0 and sugar concentration of either 30g/L glucose or xylose. After optimal growth was obtained, both RTILs and enzymatic treatments were used to break the cell wall, in order to extract the PHAs, and peptidoglycan. PHAs and peptidoglycan were successfully extracted from the cell, and will be used in the future to create a new stronger co-polymer. Peptidoglycan recovery yield was 16% of the cells’ dry weight.

Graphite exfoliation by supercritical carbon dioxide extraction

Supercritical carbon dioxide is used to exfoliate graphite, producing a small, several-layer graphitic flake. The supercritical conditions of 2000, 2500, and 3000 psi and temperatures of 40°, 50°, and 60°C, have been used to study the effect of critical density on the sizes and zeta potentials of the treated flakes. Photon Correlation Spectroscopy (PCS), Brunauer-Emmett-Teller (BET) surface area measurement, field emission scanning electron microscopy (FE-SEM), and atomic force microscopy (AFM) are used to observe the features of the flakes. N-methyl-2-pyrrolidinone (NMP), dimethylformamide (DMF), and isopropanol are used as co-solvents to enhance the supercritical carbon dioxide treatment. As a result, the PCS results show that the flakes obtained from high critical density treatment (low temperature and high pressure) are more stable due to more negative charges of zeta potential, but have smaller sizes than those from low critical density (high temperature and low pressure). However, when an additional 1-hour sonication is applied, the size of the flakes from low critical density treatment becomes smaller than those from high critical density treatment. This is probably due to more CO2 molecules stacked between the layers of the graphitic flakes. The zeta potentials of the sonicated samples were slightly more negative than nonsonicated samples. NMP and DMF co-solvents maintain stability and prevented reaggregation of the flakes better than isopropanol. The flakes tend to be larger and more stable as the treatment time increases since larger flat area of graphite is exfoliated. In these experiments, the temperature has more impact on the flakes than pressure. The BET surface area resultsshow that CO2 penetrates the graphite layers more than N2. Moreover, the negative surface area of the treated graphite indicates that the CO2 molecules may be adsorbed between the graphite layers during supercritical treatment. The FE-SEM and AFM images show that the flakes have various shapes and sizes. The effects of surfactants can be observed on the FE-SEM images of the samples in one percent by weight solution of SDBS in water since the sodium dodecylbenzene sulfonate (SDBS) residue covers all of the remaining flakes. The AFM images show that the vertical thickness of the graphitic flakes can ranges from several nanometers (less than ten layers thick), to more than a hundred nanometers. In conclusion, supercritical carbon dioxide treatment is a promising step compared to mechanical and chemical exfoliation techniques in the large scale production of thin graphitic flake, breaking down the graphite flakes into flakes only a fewer graphene layers thick.

TERPENE AND TERPENOID EMISSIONS AND SECONDARY ORGANIC AEROSOL PRODUCTION

Approximately 90% of fine aerosol in the Midwestern United States has a regional component with a sizable fraction attributed to secondary production of organic aerosol (SOA). The Ozark Forest is an important source of biogenic SOA precursors like isoprene (> 150 mg m-2 d-1), monoterpenes (10-40 mg m-2 d-1), and sesquiterpenes (10-40 mg m-2d-1). Anthropogenic sources include secondary sulfate and nitrate and biomass burning (51-60%), vehicle emissions (17-26%), and industrial emissions (16-18%). Vehicle emissions are an important source of volatile and vapor-phase, semivolatile aliphatic and aromatic hydrocarbons that are important anthropogenic sources of SOA precursors. The short lifetime of SOA precursors and the complex mixture of functionalized oxidation products make rapid sampling, quantitative processing methods, and comprehensive organic molecular analysis essential elements of a comprehensive strategy to advance understanding of SOA formation pathways. Uncertainties in forecasting SOA production on regional scales are large and related to uncertainties in biogenic emission inventories and measurement of SOA yields under ambient conditions. This work presents a bottom-up approach to develop a conifer emission inventory based on foliar and cortical oleoresin composition, development of a model to estimate terpene and terpenoid signatures of foliar and bole emissions from conifers, development of processing and analytic techniques for comprehensive organic molecular characterization of SOA precursors and oxidation products, implementation of the high-volume sampling technique to measure OA and vapor-phase organic matter, and results from a 5 day field experiment conducted to evaluate temporal and diurnal trends in SOA precursors and oxidation products. A total of 98, 115, and 87 terpene and terpenoid species were identified and quantified in commercially available essential oils of Pinus sylvestris, Picea mariana, and Thuja occidentalis, respectively, by comprehensive, two-dimensional gas chromatography with time-of-flight mass spectrometric detection (GC × GC-ToF-MS). Analysis of the literature showed that cortical oleoresin composition was similar to foliar composition of the oldest branches. Our proposed conceptual model for estimation of signatures of terpene and terpenoid emissions from foliar and cortical oleoresin showed that emission potentials of the foliar and bole release pathways are dissimilar and should be considered for conifer species that develop resin blisters or are infested with herbivores or pathogens. Average derivatization efficiencies for Methods 1 and 2 were 87.9 and 114%, respectively. Despite the lower average derivatization efficiency of Method 1, distinct advantages included a greater certainty of derivatization yield for the entire suite of multi- and poly-functional species and fewer processing steps for sequential derivatization. Detection limits for Method 1 using GC × GC- ToF-MS were 0.09-1.89 ng μL-1. A theoretical retention index diagram was developed for a hypothetical GC × 2GC analysis of the complex mixture of SOA precursors and derivatized oxidation products. In general, species eluted (relative to the alkyl diester reference compounds) from the primary column (DB-210) in bands according to n and from the secondary columns (BPX90, SolGel-WAX) according to functionality, essentially making the GC × 2GC retention diagram a Carbon number-functionality grid. The species clustered into 35 groups by functionality and species within each group exhibited good separation by n. Average recoveries of n-alkanes and polyaromatic hydrocarbons (PAHs) by Soxhlet extraction of XAD-2 resin with dichloromethane were 80.1 ± 16.1 and 76.1 ± 17.5%, respectively. Vehicle emissions were the common source for HSVOCs [i.e., resolved alkanes, the unresolved complex mixture (UCM), alkylbenzenes, and 2- and 3-ring PAHs]. An absence of monoterpenes at 0600-1000 and high concentrations of monoterpenoids during the same period was indicative of substantial losses of monoterpenes overnight and the early morning hours. Post-collection, comprehensive organic molecular characterization of SOA precursors and products by GC × GC-ToFMS in ambient air collected with ~2 hr resolution is a promising method for determining biogenic and anthropogenic SOA yields that can be used to evaluate SOA formation models.

Skin Lesion Extraction And Its Application

In this thesis, I study skin lesion detection and its applications to skin cancer diagnosis. A skin lesion detection algorithm is proposed. The proposed algorithm is based color information and threshold. For the proposed algorithm, several color spaces are studied and the detection results are compared. Experimental results show that YUV color space can achieve the best performance. Besides, I develop a distance histogram based threshold selection method and the method is proven to be better than other adaptive threshold selection methods for color detection. Besides the detection algorithms, I also investigate GPU speed-up techniques for skin lesion extraction and the results show that GPU has potential applications in speeding-up skin lesion extraction. Based on the skin lesion detection algorithms proposed, I developed a mobile-based skin cancer diagnosis application. In this application, the user with an iPhone installed with the proposed application can use the iPhone as a diagnosis tool to find the potential skin lesions in a persons' skin and compare the skin lesions detected by the iPhone with the skin lesions stored in a database in a remote server.

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.