Design Optimization of Nozzle Shapes for Maximum Uniformity of Exit Flow

The objective of this study is to identify the optimal designs of converging-diverging supersonic and hypersonic nozzles that perform at maximum uniformity of thermodynamic and flow-field properties with respect to their average values at the nozzle exit. Since this is a multi-objective design optimization problem, the design variables used are parameters defining the shape of the nozzle. This work presents how variation of such parameters can influence the nozzle exit flow non-uniformities. A Computational Fluid Dynamics (CFD) software package, ANSYS FLUENT, was used to simulate the compressible, viscous gas flow-field in forty nozzle shapes, including the heat transfer analysis. The results of two turbulence models, k-e and k-ω, were computed and compared. With the analysis results obtained, the Response Surface Methodology (RSM) was applied for the purpose of performing a multi-objective optimization. The optimization was performed with ModeFrontier software package using Kriging and Radial Basis Functions (RBF) response surfaces. Final Pareto optimal nozzle shapes were then analyzed with ANSYS FLUENT to confirm the accuracy of the optimization process.

Towards the prediction of mutations in genomic sequences

Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^

The endocrine basis for reproductive life-history trade-offs during the previtellogenic resting stage in the yellow fever mosquito, Aedes Aegypti

Juvenile hormone (JH) is the central hormonal regulator of life-history trade-offs in many insects. In Aedes aegypti, JH regulates reproductive development after emergence. Little is known about JH's physiological functions after reproductive development is complete or JH's role in mediating life-history trade-offs. By examining the effect of hormones, nutrition, and mating on ovarian physiology during the previtellogenic resting stage, critical roles were determined for these factors in mediating life-history trade-offs and reproductive output. The extent of follicular resorption during the previtellogenic resting stage is dependent on nutritional quality. Feeding females a low quality diet during the resting stage causes the rate of follicular resorption to increase and reproductive output to decrease. Conversely, feeding females a high quality diet causes resorption to remain low. The extent of resorption can be increased by separating the ovaries from a source of JH or decreased by exogenous application of methoprene. Active caspases were localized to resorbing follicles indicating that an apoptosis-like mechanism participates in follicular resorption. Accumulations of neutral lipids and the accumulation of mRNA's integral to endocytosis and oocyte development such as the vitellogenin receptor (AaVgR), lipophorin receptor (AaLpRov), heavy-chain clathrin (AaCHC), and ribosomal protein L32 (rpL32) were also examined under various nutritional and hormonal conditions. The abundance of mRNA's and neutral lipid content increased within the previtellogenic ovary as mosquitoes were offered increasing sucrose concentrations or were treated with methoprene. These same nutritional and hormonal manipulations altered the extent of resorption after a blood meal indicating that the fate of follicles and overall fecundity depends, in part, on nutritional and hormonal status during the previtellogenic resting stage. Mating female mosquitoes also altered follicle quality and resorption similarly to nutrition or hormonal application and demonstrates that male accessory gland substances such as JH III passed to the female during copulation have a strong effect on ovarian physiology during the previtellogenic resting stage and can influence reproductive output. Taken together these results demonstrate that the previtellogenic resting stage is not an inactive period but is instead a period marked by extensive life-history and fitness trade-offs in response to nutrition, hormones and mating stimuli.