Kinematic measurements conducted during bike set-ups utilise either static or dynamic measures. There is currently limited data on reliability of static and dynamic measures nor consensus on which is the optimal method. The aim of the study was to assess the difference between static and dynamic measures of the ankle, knee, hip, shoulder and elbow. Nineteen subjects performed three separate trials of a 10min duration at a fixed workload (70% of peak power output). Static measures were taken with a standard goniometer (GM), an inclinometer (IM) and dynamic three dimensional motion capture (3DMC) using an eight camera motion capture system. Static and dynamic joint angles were compared over the three trials to assess repeatability of the measurements and differences between static and dynamic values. There was a positive correlation between GM and IM measures for all joints. Only the knee, shoulder and elbow were positively correlated between GM and 3DMC, and IM and 3DMC. Although all three instruments were reliable, 3D motion analysis utilised different landmarks for most joints and produced different means. Changes in knee flexion angle from static to dynamic are attributable to changes in the positioning of the foot. Controlling for this factor, the differences are negated. It was demonstrated that 3DMC is not interchangeable with GM and IM, and it is recommended that 3DMC develop independent reference values for bicycle configuration.

The purpose of this study was to investigate the hypothesis that a dispensing program utilizing rehabilitative follow-up in the form of a post-fitting check appointment would show: (1) less return for repairs for hearing aids; (2) higher patient satisfaction with the aid; and (3) higher patient satisfaction with the service received during the hearing aid dispense than would a clinic with no follow-up. Data for comparison between the two clinics were drawn from medical chart review, frequency of hearing aid repairs, and from a questionnaire which assessed satisfaction levels. Patients were also asked to estimate the amount of use with the aid and success with manipulation of the aid for purposes of comparison with other groups previously studied.

Two single-pass methods for fitting multiexponentials to experimental data are described. These methods rely on the construction of a matrix whose characteristic polynomial is used to determine the rates of decay. In the first method, which we call the multiple-delay method, the matrix is constructed using time delays of the experimental data. This method is fast and highly accurate even if the experimental signal contains exponential components with similar rates of decay. In the second method, which we call the successive-integral method, the matrix is constructed using integrals of the experimental data. This procedure yields good results for noisy signals and is a generalization of the method of Martin et al. ((1993) J. Neurosci. Methods, 51: 135-146). In addition, a particular instability of the multiexponential curve fitting problem is identified and a method for overcoming this instability is given.

Shape optimization has become an important tool in industry to minimize weight and generate new designs. At the same time, companies are turning to CAD-centric design strategies where robust parametric CAD models are used to generate new designs and part-families of current designs, as well as the tooling and manufacturing procedures. However, due to its complexity, the optimal topology results are often discarded or recreated by hand into a CAD model. From a design stand point, the results can be improved with the use of manufacturing constraints on the shape optimization process. These constraints improve the manufacturability based on common manufacturing practices. Even with these improvements, the process of converting topology results to CAD can cost substantial amounts of time and money. This thesis proposes a method of semi-automatically recognizing the voids, created during the shape optimization process, with parametric features based on CAD geometry construction. These parametric features are based on sets of cross-sectional shapes and spine rules to create solid objects. These features are then sent to the CAD part file via programming APIs that exist in the software packages. By recognizing features usable to the CAD systems, the voids can be characterized in the CAD model using robust dimensional constraints. This allows for the CAD model approximation to represent the topology optimization results with dimensional values from simpler shapes. Size optimization can then be applied to optimize the approximating model and regain any fidelity loss in the analytic model. Test cases created with and without manufacturing constraints show considerable promise in a proof-of-concept scenario. These tests utilize the topology optimization software HyperMesh from Altair and the CAD package NX 4.0 from Siemens (formerly UGS). The voids from shape optimization in these tests are recognized inside of HyperMesh, fit with a simple parametric feature, and created in the part model using the Open C API in NX.

Converging shocks have long been a topic of interest in theoretical fluid mechanics, and are of prime importance in inertial confinement fusion. However, tracking converging shocks in numerical schemes poses several challenges. Numerical schemes based on shock capturing inherently diffuse out shocks to multiple grid cells, making it hard to track the shock. Converging shocks are significantly harder to track, as this numerical smearing is much more significant when converging shocks approach the axis of convergence. To mitigate this problem, we transform the conservation laws to a non-inertial frame of reference in which the accelerating shock is stationary. A system of equations is derived based on the transformed conservation laws coupled to the shock speed obtained from jump conditions and a characteristic-based derivation of a relation governing shock acceleration. We solve these equations using a finite volume method. Our numerical results compare favorably with the analytical value of Guderley exponent for self-similarly converging cylindrical hydrodynamic shocks. Results for fast magnetosonic shock in MHD are also presented and compared with results from geometrical shock dynamics (GSD). Results from our shock fitting method, developed without any approximation to the original ideal magnetohydrodynamics equations, provide further credibility to GSD applied to converging fast magnetosonic shocks. This sort of shock fitting is a precursor to future multidimensional stability analysis of imploding shocks.

Numerous biological phenomena occur as a result of macromolecular interactions. Metal-ion-biomolecule binding account for a large portion of these reactions, and unsurprisingly, a vast amount of new research in this area is constantly emerging. Gaining insight into the characteristics that define these interactions; including equilibrium fluctuations, metal center formation, global stability perturbation, cooperativity, allostery, and site-specific binding are all significant. As with all chemical reactions, biological interactions are regulated by thermodynamics; and the development of novel tools and methods by which to study these interactions becomes highly relevant. In this dissertation, three systems involving macromolecular binding are studied using well established biophysical techniques in conjunction with a critical look at appropriate uses for mathematical modeling. The first system studied is that of the serpin plasminogen activator inhibitor-1 (PAI-1). PAI-1 is a protease inhibitor that specifically effects fibrinolysis, or the process that prevents the formation of blood clots, and misregulation of this enzyme leads to uncontrollable hemorrhaging. ITC was utilized to investigate the thermodynamics of copper binding to PAI-1. Human carbonic anhydrase II (CA) was the second system investigated. Studies were conducted on zinc(II) and copper(II) binding to CA, a metalloenzyme responsible for acid-base balances in the blood and the transport of carbon dioxide. Interestingly, CA binds two copper(II) ions, one at the active site, and one at a higher affinity N-terminal site. Temperature dependent ITC, CD and GdnHCl denaturation studies were performed to explore the impact of copper(II) binding, particularly at the higher affinity N-terminal site. Finally, protein binding to inorganic gold nanoparticles (AuNPs) was investigated. AuNPS are utilized in areas of diagnostics, biological sensing and drug delivery. We studied binding of nanoparticles to a set of six biologically relevant proteins; glutathione, wild-type GB3, K19C GB3 (a variant at position 19), bovine CA, bovine serum albumin, and fibrinogen. Nanoparticle-protein binding was monitored via UV-Visible extinction and polarized resonance synchronous spectroscopy (PRS2). The UV extinction maxima wavelength shifts were fit with two models, a Langmuir isotherm model and a mass action-derived model. The models fit the data equally well, however, they predict very different Kd values, specifically for smaller sized AuNPs.

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