The role of Mycobacterium avium subsp paratuberculosis (MAP) in the etiology and pathogenesis of inflammatory bowel disease (IBD) including Crohn's Disease (CD), has been investigated. The fastidious characteristics and cross reactivity of MAP with other members in Mycobacteria have produced significant challenges in their detection and identification. In this two year pilot study, an array of three PCR molecular assays based on the detection of sequences from the16S rRNA, IS1245, and IS900 genes, belonging to members of the MAC, have been developed and optimized into a common protocol to be used as a rapid and accurate diagnostic tool regarding M. avium complex (MAC) infection. The PCR protocol time was reduced by half, and the sensitivity and specificity of the molecular assays has been significantly improved barring the need for southern hybridization. This improved methodology was employed for the molecular typing of MAC in 100 resected, full-thickness tissue samples removed from IBD patients. The tissue samples were homogenized, decontaminated, and inoculated into two mycobacterial culture media systems. A total of 328 Bactec and Mycobacteria Growth Indicator Tube (MIGT) cultures were evaluated for positive MAC growth. Harvested cells were then subjected to genomic DNA extraction and subsequent PCR typing. The I6 S rRNA-based PCR resulted in detection of 26/28 (93%) MAC in Bactec cultures. Specifically, 25/28 (89%) of positive MAC indicated the presence of IS1245 specific to M. avium subsp avium (MAV), and 6/28 (21%) produced results consistent with the presence of IS900 following nested PCR. Moreover, 20/100 (20%) of MGIT cultures were positive for MAP. Sequence analysis was performed on amplified regions of the IS900 element from seven isolates. A nucleotide alignment revealed that 2/7 isolates demonstrated 100% homology to Bovine MAP and 5/7 isolates showed 96-99% homology to sequenced Bovine MAP published in GenBank. The detection of at least two Bovine derived MAP in IBD tissue will have great impact on the epidemiology and reclassification of IBD. The significant homology of the other five isolates to Bovine derived MAP suggests a diversity in the geographical distribution of MAP regarding Johne's disease and CD. Ultimately, the etiology, diagnosis, and the treatment of IBD as well as control and prevention measures may be enhanced with better tools for investigating emerging infectious diseases.

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<p>This work explores a new method of force generation for flying robots on the sub-cm wingspan scale: resonant curved piezoelectric cantilevers created using completely parallel MEMS fabrication. It theorizes that because a resonating curved beam has a different drag coefficient on the upstroke than the downstroke, it should act as a fluid diode: a partial one-way gate for fluids, and thereby generate an asymmetric force over a symmetric one-degree-of-freedom flapping cycle. It develops a simplified model for the large-amplitude resonant mode of thin circular arcs by analytically extending the resonant mode shape of straight cantilevers, shows that this shape is a better fit to experimental data than previous models, and shows that it accurately predicts the resonant frequency. It uses this resonant mode to compute the force on flapping curved arcs under a wide range of amplitudes, Reynolds numbers, and arc angles using computational fluid dynamics (CFD) simulations, and extends the concept of a drag coefficient from steady-flow fluid mechanics to steady-state oscillatory fluid mechanics both for net force generation and power dissipation. It develops a framework to analyze the CFD results in the broader context of a complete robot, and uses this framework to determine priorities for material selection, robot size, and flapping shape, depending on desired robot application. It tests these theoretical predictions by creating prototype 7.6 mm wings out of 7.5 micrometer thick x-cut quartz and SU-8, after developing and implementing a method to smoothly thin x-cut quartz leaving the surface free of dielectric-compromising pits using reactive ion etching (RIE). Finally, it constructs a test chamber to measure the force, amplitude, and electrical parameters of the flapping wings under a variety of air pressures and demonstrates that the results are consistent with the theoretical predictions, indicating that this approach can in fact lead to successful flying microrobots.</p> / Doctor of Philosophy (PhD)

This thesis investigates the possibility of using reinforcement learning (RL) techniques to create a flight controller for a quadrotor Micro Aerial Vehicle (MAV). A capable flight control system is a core requirement of any unmanned aerial vehicle. The challenging and diverse applications in which MAVs are destined to be used, mean that considerable time and effort need to be put into designing and commissioning suitable flight controllers. It is proposed that reinforcement learning, a subset of machine learning, could be used to address some of the practical difficulties. While much research has delved into RL in unmanned aerial vehicle applications, this work has tended to ignore low level motion control, or been concerned only in off-line learning regimes. This thesis addresses an area in which accessible information is scarce: the performance of RL when used for on-policy motion control. Trying out a candidate algorithm on a real MAV is a simple but expensive proposition. In place of such an approach, this research details the development of a suitable simulator environment, in which a prototype controller might be evaluated. Then inquiry then proposes a possible RL-based control system, utilising the Q-learning algorithm, with an adaptive RBF-network providing function approximation. The operation of this prototypical control system is then tested in detail, to determine both the absolute level of performance which can be expected, and the effect which tuning critical parameters of the algorithm has on the functioning of the controller. Performance is compared against a conventional PID controller to maximise the usability of the results by a wide audience. Testing considers behaviour in the presence of disturbances, and run-time changes in plant dynamics. Results show that given sufficient learning opportunity, a RL-based control system performs as well as a simple PID controller. However, unstable behaviour during learning is an issue for future analysis. Additionally, preliminary testing is performed to evaluate the feasibility of implementing RL algorithms in an embedded computing environment, as a general requirement for a MAV flight controller. Whilst the algorithm runs successfully in an embedded context, observation reveals further development would be necessary to reduce computation time to a level where a controller was able to update sufficiently quickly for a real-time motion control application. In summary, the study provides a critical assessment of the feasibility of using RL algorithms for motion control tasks, such as MAV flight control. Advantages which merit interest are exposed, though practical considerations suggest at this stage, that such a control system is not a realistic proposition. There is a discussion of avenues which may uncover possibilities to surmount these challenges. This investigation will prove useful for engineers interested in the opportunities which reinforcement learning techniques represent.