Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 100-105).

Characterization of jet fuels obtained from sources other than crude oil is a modern area of research that is developing continuously to replace available petroleum-based fuels with ‘drop-in’ alternative fuels. Therefore, reliable composition-property relations are developed to correlate the hydrocarbon compositions of formulated synthetic fuels with their properties to be certified for aviation commercial use. Intensive studies have been initiated at Texas A&M University Qatar in collaboration with industry and academia to study synthetic jet fuels derived from natural gas. These studies are being implemented at its Fuel Characterization Lab where the most advanced testing equipment is used and strict Quality Management and safety systems are followed. This study is divided into two tracks. The first track is focused on conducting experimental investigations using in-house formulated synthetic jet fuels derived from natural gas via Gas-to-Liquid technology and Fischer-Tropsch chemistry. Throughout this research work, these fuels will be referred to as Synthetic Paraffinic Kerosene (SPK). These experimental investigations activities are composed of three phases: the first phase focuses on the influence of SPK building blocks (paraffinic hydrocarbons) on fuels’ properties, the second phase concerns evaluating the role of aromatics and cyclo-paraffins on properties, and the third phase studies the influence of mixing SPK with conventional Jet A-1 derived from crude oil. All of the aforementioned experimental investigations are aimed at building an experimental data bank to assist the efforts of the formulation of new generations of SPKs that meet aviation industry standards. On the other hand, the second track is directed towards the development of mathematical correlations for four properties of high importance to SPK certification. These correlations aim at optimizing fuel composition whereby major physical/chemical properties of ASTM D1655 are met at the lowest cost of composed fuel. The primary findings of this study showed that GTL derived SPK paraffinic constituents can improve certain properties while affecting others negatively, and emphasizing the necessity of aromatics in improving specific properties. Further studies compensating the absence of aromatics and sulfur through blended Jet A-1 revealed a practical solution through jet fuels optimization based on cost and technical effective manners.

The objective of this research is a fast circular synthetic aperture radar (F-CSAR) algorithm. Slow-time imaging distinguishes synthetic aperture radar (SAR) from its predecessor imaging radars. SAR slow-time imaging is strongly rooted in Huygens-Fresnel principle and Kirchhoff's approximation based scalar diffraction theory. Slant-plane SAR Green's function and resultant Fourier integral, unlike some Fourier integrals, cannot be analyzed using residue theory from complex analysis and Cauchy-Riemann equations yield analyticity. The asymptotic expansion of 1D and 2D Fourier integrals renders a decomposition of the Green's function leading to SAR data focusing. The research unveils Fraunhofer diffraction patterns in 2D aperture synthesis formulation corresponding to various aperture shapes including circular aperture that appears to be an optimum aperture shape from the mathematical condition in the asymptotic expansion. It is shown that these diffraction patterns may be used for refocusing of defocused images. F-CSAR algorithm is demonstrated using Householder transform recently shown to have improved error bounds and stability. Research is also carried out into various interpolation schemes. Backprojection implementation of CSAR is compared to F-CSAR and elevation coverage renders 3D reconstruction. F-CSAR is also demonstrated using GTRI T-72 tank turntable data.

Diss. (sammanfattning) Stockholm : Karol. inst., 2003. / Härtill 5 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst., 2005. / Härtill 4 uppsatser.

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Mastitis is the most common disease affecting Swedish milk cows. Automatic image classification can be useful for quickly classifying the bacteria causing this inflammation, in turn making it possible to start treatment more quickly. However, training an automatic classifier relies on the availability of data. Data collection can be a slow process, and GANs are a promising way to generate synthetic data to add plausible samples to an existing data set. The purpose of this thesis is to explore the usefulness of GANs for generating images of bacteria. This was done through researching existing literature on the subject, implementing a GAN, and evaluating the generated images. A cGAN capable of generating class-specific bacteria was implemented and improvements upon it made. The images generated by the cGAN were evaluated using visual examination, rapid scene categorization, and an expert interview regarding the generated images. While the cGAN was able to replicate certain features in the real images, it fails in crucial aspects such as symmetry and detail. It is possible that other GAN variants may be better suited to the task. Lastly, the results highlight the challenges of evaluating GANs with current evaluation methods.

Synthetic biology, a field that sits between Biology and Engineering disciplines, has come into its own in the last decade. The decreasing cost of DNA synthesis has lead to the creation of larger and more complex synthetic gene networks, engineered with functional goals rather than simple demonstration. While many methods have been developed to reduce the time required to produce complex networks, none focus upon the considerable tuning needed to turn structurally correct networks into functional gene networks. To this end, we created a Plug-and-Play synthetic gene network assembly that emphasizes character-driven iteration for producing functional synthetic gene networks. This platform enables post-construction modification and easy tuning of networks through its ability to swap individual parts. To demonstrate this system, we constructed a functional bistable genetic toggle and transformed it into two functionally distinct synthetic networks. Once these networks have been created and tuned at the bench, they next must be delivered to bacteria in their target environment. While this is easy for industrial applications, delivering synthetic networks as medical therapeutics has a host of problems, such as competing microbes, the host immune system, and harsh microenvironments. Therefore, we employed bacteriophage technologies to deliver functional synthetic gene networks to specific bacterial strains in various microenvironments. We first sought to deliver functional genetic networks to bacteria present in the gut microbiome. This allows for functionalization of these bacteria to eventually sense disease states and secrete therapeutics. As a proof of concept a simple circuit was created using the Plug-and-Play platform and tested before being moved into the replicative form plasmid of the M13 bacteriophage. Bacteriophage particles carrying this network were used to infect gut bacteria of mice. Infection and functionality of the synthetic network was monitored from screening fecal samples. Next, we employed phagemid technologies to deliver high copy plasmids expressing antibacterial networks to target bacteria. This allows for sustained expression of antibacterial genes that cause non-lytic bacterial death without reliance upon traditional small molecule antibiotics. Phagemid particles carrying our antibacterial networks were then tested against wild type and antibiotic-resistant bacteria in an in vitro and in vivo environment.

The demand for economical, efficient protein production, reuse, and recovery has never been greater due to their versatility in a large variety of applications ranging from industrial chemical manufacturing to pharmaceutical drug production. The applications for naturally and artificially produced proteins include protein drugs and other pharmaceutical products, as biocatalysts in environmentally friendly chemical manufacturing, as enzymes for food processing purposes, and as an essential component in many biomedical devices. However, protein production suffers from many challenges, which include the cost of production, protein stability especially under harsh conditions, and recoverability and reusability of the proteins. The combination of two developing technologies, cell-free protein synthesis systems (CFPS) and unnatural amino acid incorporation, provides solutions to these protein production challenges.This dissertation reports on the use of cell-free protein synthesis systems and unnatural amino acid incorporation to develop new proteins and enzyme immobilization techniques that significantly increase activity and stability while simplifying recoverability and reuse.

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