The United Nations have declared the effects of climate change as the “defining issue of our time” (United Nations, 2019). As a result of increased industrialization in the last century to keep up with the demands of a growing global population, the global output of greenhouse emissions has rocketed, which is linked to the shifting and abnormal weather patterns of the planet. Electricity and heat production alone are attributed to generating 25% of greenhouse gas emissions (Edenhofer, et al.). To alleviate the increasing levels of carbon emission there is an effort to transition in green energy power generation sources like wind energy that is abundantly available in the midwestern United States. This study aims to implement the Blade Element Method derived modeling methods for predicting the performance of a wind turbine. The experimental results obtained from the MEXICO project is employed as the validation source for the research.

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In the past two decades, molecular cell biology has transitioned from a traditional descriptive science into a quantitative science that systematically measures cellular dynamics on different levels of genome, transcriptome and proteome. Along with this transition emerges the interdisciplinary field of systems biology, which aims to unravel complex interactions in biological systems through integrating experimental data into qualitative or quantitative models and computer simulations. In this dissertation, we applied various systems biology tools to investigate two important problems with respect to cellular activation dynamics and reprograming. Specifically, in the first section of the dissertation, we focused on lipopolysaccharide (LPS)-mediated priming and tolerance: a reprogramming in cytokine production in macrophages pretreated with specific doses of LPS. Though both priming and tolerance are important in the immune system's response to pathogens, the molecular mechanisms still remain unclear. We computationally investigated all network topologies and dynamics that are able to generate priming or tolerance in a generic three-node model. Accordingly, we found three basic priming mechanisms and one tolerance mechanism. Existing experimental evidence support these in silico found mechanisms. In the second part of the dissertation, we applied stochastic modeling and simulations to investigate the phenotypic transition of bacteria E.coli between normally-growing cells and persister cells (growth-arrested phenotype), and how this process can contribute to drug resistance. We built up a complex computational model capturing the molecular mechanism on both single cell level and population level. The paper also proposed a novel way to accelerate the phenotypic transition from persister cells to normally growing cell under resonance activation. The general picture of phenotypic transitions should be applicable to a broader context of biological systems, such as T cell differentiation and stem cell reprogramming. / Ph. D.

The mid-latitude ionosphere is more complicated than previously thought, as it includes many different scales of wave-like structures. Recent studies reveal that the mid-latitude ionospheric irregularities are less understood due to lack of models and observations that can explain the characteristics of the observed wave structures. Since temperature and density gradients are a persistent feature in the mid-latitude ionosphere near the plasmapause, the drift mode growth rate at short wavelengths may explain the mid-latitude decameter-scale ionospheric irregularities observed by the Super Dual Auroral Radar Network (SuperDARN). In the context of this dissertation, we focus on investigating the plasma waves responsible for the mid-latitude ionospheric irregularities and studying their influence on Global Positioning System (GPS) scintillations. First, the physical mechanism of the Temperature Gradient Instability (TGI), which is a strong candidate for producing mid-latitude irregularities, is proposed. The electro- static dispersion relation for TGI is extended into the kinetic regime appropriate for High- Frequency (HF) radars by including Landau damping, finite gyro-radius effects, and tem- perature anisotropy. The kinetic dispersion relation of the Gradient Drift Instability (GDI) including finite ion gyro-radius effects is also solved to consider decameter-scale waves gen- eration. The TGI and GDI calculations are obtained over a broad set of parameter regimes to underscore limitations in fluid theory for short wavelengths and to provide perspective on the experimental observations. Joint measurements by the Millstone Hill Incoherent Scatter Radar (ISR) and the Su- perDARN HF radar located at Wallops Island, Virginia have identified the presence of decameter-scale electron density irregularities that have been proposed to be responsible for low-velocity Sub-Auroral Ionospheric Scatter (SAIS) observed by SuperDARN radars. In order to investigate the mechanism responsible for the growth of these irregularities, a time series for the growth rate of both TGI and GDI is developed. The time series is computed for both perpendicular and meridional density and temperature gradients. The growth rate comparison shows that the TGI is the most likely generation mechanism for the observed quiet-time irregularities and the GDI is expected to play a relatively minor role in irregular- ity generation. This is the first experimental confirmation that mid-latitude decameter-scale ionospheric irregularities are produced by the TGI or by turbulent cascade from primary irregularity structures produced from this instability. The quiet- and disturbed-times plasma wave irregularities are compared by investigating co-located experimental observations by the Blackstone SuperDARN radar and the Millstone Hill ISR under various sets of geomagnetic conditions. The radar observations in conjunction with growth rate calculations suggest that the TGI in association with the GDI or a cascade product from them may cause the observations of disturbed-time sub-auroral ionospheric irregularities. Following this, the nonlinear evolution of the TGI is investigated utilizing gyro-kinetic Particle-In-Cell (PIC) simulation techniques with Monte Carlo collisions for the first time. The purpose of this investigation is to identify the mechanism responsible for the nonlinear saturation as well as the associated anomalous transport. The simulation results indicate that the nonlinear E x B convection (trapping) of the electrons is the dominant TGI sat- uration mechanism. The spatial power spectra of the electrostatic potential and density fluctuations associated with the TGI are also computed and the results show wave cascad- ing of TGI from kilometer scales into the decameter-scale regime of the radar observations. This suggests that the observed mid-latitude decameter-scale ionospheric irregularities may be produced directly by the TGI or by turbulent cascade from primary longer-wavelength irregularity structures produced from this instability. Finally, the potential impact of the mid-latitude ionospheric irregularities on GPS signals is investigated utilizing modeling and observations. The recorded GPS data at mid-latitude stations are analyzed to study the amplitude and phase fluctuations of the GPS signals and to investigate the spectral index variations due to ionospheric irregularities. The GPS measurements show weak to moderate scintillations of GPS L1 signals in the presence of ionospheric irregularities during disturbed geomagnetic conditions. The GPS spectral indices are calculated and found to be in the same range of the numerical simulations of TGI and GDI. Both simulation results and GPS spectral analysis are consistent with previous in-situ satellite measurements during disturbed periods, showing that the spectral index of mid- latitude density irregularities are of the order 2. The scintillation results along with radar observations suggest that the observed decameter-scale irregularities that cause SuperDARN backscatter, co-exist with kilometer-scale irregularities that cause L-band scintillations. The alignment between the experimental, theoretical, and computational results of this study suggests that turbulent cascade processes of TGI and GDI may cause the observations of GPS scintillations that occur under disturbed conditions of the mid-latitude F-region ionosphere. The TGI and GDI wave cascading lends further support to the belief that the E-region may be responsible for shorting out the F-region TGI and GDI electric fields before and around sunset and ultimately leading to irregularity suppression. / Ph. D.

The mucosal immune system encompasses a wide array of interactions that work in concert to protect an individual from harmful agents while retaining tolerance to molecules, microbes, and self-antigens that present no danger. The upheaval in the regulation-response balance is a critical aspect in both infectious and immune-mediated disease. To understand this balance and methods of its restoration, iterative and integrative modeling cycles on the pathogenesis of disease are necessary. In this thesis, I present three studies highlighting phases of a systems immunology cycle. Firstly, the thesis provides a description of the construction of a computational ordinary differential equation based model on the host-pathogen-microbiota interactions during Clostridium difficile infection and the use of this model for the development of the hypothesis that host-antimicrobial peptide production may correlate with increased disease severity and promote increased recurrence. Secondly, it provides insight into the necessity of trans-disciplinary analysis for the understanding of novel molecular targets in disease through the immunometabolic regulation of CD4+ T cell by NLRX1 in inflammatory bowel disease. Third, it provides the assessment of novel therapeutics in disease through the evaluation of LANCL2 activation in influenza virus infection. In total, the computational and experimental strategies used in this dissertation are critical foundational pieces in the framework of precision medicine initiatives that can assist in the diagnosis, understanding, and treatment of disease. / Ph. D. / Many diseases are a result of altered patterns of interaction between the body, bacteria, viruses or nutrients. When these patterns are altered, inflammation occurs. If not controlled, the inflammation can cause pain, damage to the affected area, and other specific symptoms depending on the type of disease. This dissertation details the use of alternative methods of treating disease and analyzing disease in the context of Clostridium difficile infection, inflammatory bowel disease and influenza infection. It provides insight into the development of computational models with equations to capture the response patterns. It assesses the connections between immunology and metabolism that can lead to inflammation. And, it identifies a new therapeutic target for influenza infection. Together, these three phases are important pieces toward a future with improved understanding of disease and treatments that can be specific and customized for every individual.