In this thesis, we develop an adaptive mesh refinement (AMR) code including magnetic fields, and use it to perform high resolution simulations of magnetized molecular clouds. The purpose of these simulations is to study present day star formation in the presence of turbulence and magnetic fields. We first present MHDEnzo, the extension of the cosmology and astrophysics code Enzo to include the effects magnetic fields. We use a higher order Godunov Riemann solver for the computation of interface fluxes; constrained transport to compute the electric field from those interface fluxes, which advances the induction equation in a divergence free manner; divergence free reconstruction technique to interpolate the magnetic fields to fine grids; operator splitting to include gravity and cosmological expansion. We present a series of test problems to demonstrate the quality of solution achieved. Additionally, we present several other solvers that were developed along the way. Finally we present the results from several AMR simulations that study isothermal turbulence in the presence of magnetic fields and self gravity. Ten simulations with initial Mach number 8.9 were studied varying several parameters; virial parameter $\alpha$ from 0.52 to 3.1; whether they were continuously stirred or allowed to decay ; and the number of refinement levels (4 or 6). Measurements of the density probability density function (PDF) were made, showing both the expected log normal distribution and an additional power law. Measurements of the line of sight magnetic field vs. column density are done, giving excellent agreement with recent observations. The line width vs. size relationship is measured and compared with good agreement to observations, reproducing both turbulent and collapse signatures. The core mass distribution is measured and agrees well with observations of Serpens and Perseus core samples, but the power-law distribution in Ophiuchus is not reproduced by our simulations. Finally we attempt to make contact with recent theoretical predictions of the star formation rate. Our measured rate is significantly higher than predicted, indicating that our root grid resolution is likely too low. Nonetheless, the simulations presented here are the first of their kind, and the general agreement with observations indicates the promise of our approach. We conclude by outlining future work which will explore numerical systematics more fully, and make detailed contact with observations.

Generating aerosol droplets via the atomization of thin aqueous films with high frequency surface acoustic waves (SAWs) offers several advantages over existing nebulization methods, particularly for pulmonary drug delivery, offering droplet sizes in the 1-5-μm range ideal for effective pulmonary therapy. Nevertheless, the physics underlying SAW atomization is not well understood, especially in the context of thin liquid film formation and spreading and how this affects the aerosol production. Here, we demonstrate that the film geometry, governed primarily by the applied power and frequency of the SAW, indeed plays a crucial role in the atomization process and, in particular, the size of the atomized droplets. In contrast to the continuous spreading of low surface energy liquids atop similar platforms, high surface energy liquids such as water, in the present case, are found to undergo transient spreading due to the SAW to form a quasisteady film whose height is determined by self-selection of the energy minimum state associated with the acoustic resonance in the film and whose length arises from a competition between acoustic streaming and capillary effects. This is elucidated from a fundamental model for the thin film spreading behavior under SAW excitation, from which we show good agreement between the experimentally measured and theoretically predicted droplet dimension, both of which consistently indicate a linear relationship between the droplet diameter and the mechanical power coupled into the liquid by the SAW (the latter captured by an acoustic Weber number to the two thirds power, and the reciprocal of the SAW frequency).

Background

Although studies of health coaching for behavior change in chronic disease prevention and management are increasing, to date no studies have reported on what concepts and skills providers integrate into their clinical practice following participation in health coaching courses. The purpose of this qualitative study was to assess Veterans Health Administration (VHA) providers' perceptions of the individual-level and system-level changes they observed after participating with colleagues in a 6-day Whole Health Coaching course held in 8 VHA medical centers nationwide.

Methods

Data for this study were from the follow-up survey conducted with participants 2 to 3 months after completing the training. A total of 142 responses about individual-level changes and 99 responses about system-level changes were analyzed using content analysis.

Results

Eight primary themes emerged regarding individual changes, including increased emphasis on Veterans' values, increased use of listening and other specific health coaching skills in their clinical role, and adding health coaching to their clinical practice.Four primary themes emerged regarding system-level changes, including leadership support, increased staff awareness/support/learning and sharing, increased use of health coaching skills or tools within the facility, and organizational changes demonstrating a more engaged workforce, such as new work groups being formed or existing groups becoming more active.

Conclusions

Findings suggest that VHA providers who participate in health coaching trainings do perceive positive changes within themselves and their organizations. Health coaching courses that emphasize patient-centered care and promote patient-provider partnerships likely have positive effects beyond the individual participants that can be used to promote desired organizational change.

Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of 'partial' imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

Heterozygosity of Human leukocyte antigen (HLA) class I genes is linked to beneficial outcomes after HIV infection, presumably through greater breadth of HIV epitope presentation and cytotoxic T cell response. Distinct allotype pairs, however, differ in the extent to which they bind shared sets of peptides. We developed a functional divergence metric that measures pairwise complementarity of allotype-associated peptide binding profiles. Greater functional divergence for pairs of HLA-A and/or HLA-B allotypes was associated with slower AIDS progression and independently with enhanced viral load control. The metric predicts immune breadth at the peptide level rather than gene level and redefines HLA heterozygosity as a continuum differentially affecting disease outcome. Functional divergence may affect response to additional infections, vaccination, immunotherapy, and other diseases where HLA heterozygote advantage occurs.