As current educational policies continue to emphasize the importance of college readiness and growth, it is essential to understand the degree to which test scores collected throughout middle school and high school can provide information to make valid inferences about students' college readiness. This thesis sought to summarize the college readiness of Iowa students, describe the nature of student growth, and clarify the relationship between student growth and college readiness. Together, the results support the validity argument that scores from a general achievement test can be used for measuring student growth and making on-track interpretations about college readiness. Results of analyses on the use of benchmarks as indicators of college readiness are presented first. The analyses showed that the state's general achievement test was just as accurate as the ACT when the criterion was defined by grades in domain-specific, credit-bearing courses. Next, latent growth models and growth mixture models were used to summarize and evaluate longitudinal changes in student achievement and their relationship with college outcomes. A calibration sample representing potential college-bound students was used to set the growth trajectories. Then a cohort of students representing the full student population was used to provide validity evidence in support of the growth trajectories. It was shown that students in the highest-performing group could be considered college ready. Several applications of the growth models are also presented. The typical performance on a variety of college outcomes for each developmental group was presented for the validation sample. A second application illustrated how individual patterns of growth in Grade 8 could be used to predict future class membership in Grade 11. This thesis was predicated on the notion that understanding and documenting the nature of student growth, the college readiness of Iowa students, and the relationship between the two is an important step in improving the college readiness of Iowa students and meeting the future needs of an aligned K-16 educational system. As this study is among the first to examine the relationship between college readiness and student growth using modern latent variable modeling techniques with actual college outcomes, guidelines for future research are presented.

Estimating parameters in a mixture of normal distributions dates back to the 19th century when Pearson originally considered data of crabs from the Bay of Naples. Since then, many real world applications of mixtures have led to various proposed methods for studying similar problems. Among them, maximum likelihood estimation (MLE) and the continuous empirical characteristic function (CECF) methods have drawn the most attention. However, the performance of these competing estimation methods has not been thoroughly studied in the literature and conclusions have not been consistent in published research. In this article, we review this classical problem with a focus on estimation bias. An extensive simulation study is conducted to compare the estimation bias between the MLE and CECF methods over a wide range of disparity values. We use the overlapping coefficient (OVL) to measure the amount of disparity, and provide a practical guideline for estimation quality in mixtures of normal distributions. Application to an ongoing multi-site Huntington disease study is illustrated for ascertaining cognitive biomarkers of disease progression. We also study joint modeling of longitudinal and time-to-event data and discuss pattern-mixture and selection models, but focus on shared parameter models, which utilize unobserved random effects in order to "join" a marginal longitudinal data model and marginal survival model in order to assess an internal time-dependent covariate's effect on time-to-event. The marginal models used in the analysis are the Cox Proportional Hazards model and the Linear Mixed model, and both of these models are covered in some detail before defining joints models and describing the estimation process. Joint modeling provides a modeling framework which accounts for correlation between the longitudinal data and the time-to-event data, while also accounting for measurement error in the longitudinal process, which previous methods failed to do. Since it has been shown that bias is incurred, and this bias is proportional to the amount of measurement error, utilizing a joint modeling approach is preferred. Our setting is also complicated by monotone degeneration of the internal covariate considered, and so a joint model which utilizes monotone B-Splines to recover the longitudinal trajectory and a Cox Proportional Hazards (CPH) model for the time-to-event data is proposed. The monotonicity constraints are satisfied via the Projected Newton Raphson Algorithm as described by Cheng et al., 2012, with the baseline hazard profiled out of the $Q$ function in each M-step of the Expectation Maximization (EM) algorithm used for optimizing the observed likelihood. This method is applied to assess Total Motor Score's (TMS) ability to predict Huntington Disease motor diagnosis in the Biological Predictors of Huntington's Disease study (PREDICT-HD) data.

This study analyzes the relationship between inter rebel group dynamics and rebel biased third party interventions. Concerning the considerable amount of multiparty civil conflicts and internationalized civil conflicts, prior studies largely overlook the cause and effect of inter rebel dynamics in terms of third party interventions. I delve into two related research questions; How do inter rebel dynamics influence a third party’s decision to intervene in a multiparty civil conflict? What kinds of rebel group interactions are facilitated by such third party interventions? Existing rebel group interaction patterns play a key role in determining conflict process and, influence third party’s decision to intervene. I predict that a cooperative interaction pattern between rebel groups generates an intervention enriched environment for the rebel groups, due to the increased likelihood of successful intervention and the decreased cost of war. The third party’s involvement in ongoing multiple party civil conflict generates a change in bargaining structure between rebels in terms of number of bargainers and distribution of capabilities. I predict a conditional effect of rebel biased interventions on inter rebel dynamics; while forceful intervention boosts cooperation between rebels, weak intervention fuels competition between them. To test my theoretical conjectures, the interlocking relationship between rebels’ interactions and rebel biased interventions has been empirically estimated on a large-N framework. The estimated results strongly confirm my theoretical predictions that rebel cooperation encourages rebel biased interventions and, that increased cooperation and competition is dependent upon third party’s commitment. Overall, my findings highlight a distinctive process of multiparty civil conflicts in terms of third party interventions and rebel group dynamics. My first findings regarding rebel biased interventions, expand the existing intervention literature by focusing on rebel group dynamics in multiparty civil conflicts. The empirical evidence showing boosted competition and cooperation caused by intervention, can be linked to studies that discuss the correlation between interventions and conflict terminations. For the policy community, this project suggests that the success of intervention lies in the third party’s measure of intervention.

The current guideline for culverts design account for hydrologic, hydraulic, and geomorphological conditions at the construction site. Less attention is given to the assessment of the potential for sedimentation within and in the culvert vicinity. Sedimentation becomes an increasing concern for regions where the soil erodibility is historically high (such as the US Midwest) as the recent changes in the land use and climate exacerbate the problem. Culvert design is based on a wide variety of data sources typically stored in various formats in multiple data provider repositories. Assembly of the data needed for design as currently conducted is time consuming and inefficient while the wealth of information garnered through post-construction monitoring is not used to inform the construction of new culverts in the same geographical area. This thesis presents a solution to the issues above using Hydroinformatics approaches. The end product of the thesis is a geo-platform designed to achieve automated culvert design, sediment mitigation design, and digital culvert inspection. The platform has two primary workflows: culvert design and culvert monitoring. All the functions and tools inside the platform are developed using information and GIS technologies. The platform is web assessable, light weighted, and user friendly.

Atypical hemolytic uremic syndrome (aHUS) is a rare renal disorder characterized by thrombotic microangiopathy, thrombocytopenia, and acute kidney injury. Its pathogenesis has been attributed to a ‘triggering' event that leads to dysregulation of the complement cascade at the level of the endothelial cell surface. Consistent with this understanding of the disease, mutations in complement genes have been definitively implicated in aHUS. However, the existence of other genetic contributors is supported by two observations. First, in ~50% of cases, disease-causing variants are not identified in complement genes, and second, disease penetrance is typically incomplete and highly variable. To test this hypothesis, we identified pathways established to have crosstalk with the complement cascade, focusing initially on the coagulation pathway. Using targeted genomic enrichment and massively parallel sequencing we screened 36 European-American patients with sporadic aHUS patients for genetic variants in 85 complement and coagulation genes, identifying deleterious rare variants in several coagulation genes. The most frequently mutated coagulation gene in our study cohort was PLG, which encodes a zymogen of plasmin and plays key role in fibrinolysis. These results implicate the coagulation pathway in the pathogenesis of aHUS. Based on this outcome, we developed a clinical genetic testing panel to screen disease-related genes in a group of ultra-rare complement-mediated diseases that includes, in addition to aHUS, thrombotic thrombocytopenic purpura (TTP), C3 glomerulonephritis (C3GN) and dense deposit disease (DDD) patients. Data from 193 patients validate the usage of this panel in clinical practice and also provide confirmatory insight into the pathogeneses of these diseases. Specifically, we found that in aHUS and TTP patients, variants were frequently identified in complement regulator genes, while in C3GN and DDD patients, variants were additionally found in C3 convertase genes. To understand variability in disease penetrance, we completed targeted genetic screening in two aHUS families grossly discordant for disease penetrance, identifying in one family a co-segregating Factor X-deficiency variant (F10 p.Glu142Lys) that abrogated the effect of the complement mutation. Functional studies of the F10 p.Glu142Lys variant show that it decreases Factor X activity predicting to a hypo-coagulable state and further illustrating the importance of complement-coagulation crosstalk in exacerbating, but also mitigating the aHUS phenotype. In our final studies, we have sought to complete a comprehensive analysis for other potentially related pathways by using bioinformatics to identify candidate pathways coupled with whole exome sequencing. Preliminary data from 43 aHUS patients and 300 controls suggest that pathways for dermatan and heparan sulfate synthesis, which are relevant to the formation of the extra-cellular matrix and cell surface adhesion, may be implicated in the aHUS.

In this work, we have developed user interactive capabilities that allow us to perform segmentation and manipulation of patient-specific geometries required for Computational Fluid Dynamics (CFD) studies, entirely in image domain and within a single platform of ‘IAFEMesh'. Within this toolkit we have added commonly required manipulation capabilities for performing CFD on segmented objects by utilizing libraries like ITK, VTK and KWWidgets. With the advent of these capabilities we can now manipulate a single patient specific image into a set of possible cases we seek to study; which is difficult to do in commercially available software like VMTK, Slicer, MITK etc. due to their limited manipulation capabilities. Levelset representation of the manipulated geometries can be simulated in our flow solver (SCIMITAR-3D) without creating any surface or volumetric mesh. This image-levelset-flow framework offers few advantages. 1) We don't need to deal with the problems associated with mesh quality, edge connectivity related to mesh models, 2) and manipulations like boolean operation result in smooth, physically realizable entities which is challanging in mesh domain. We have validated our image-levelset-flow setup with the known results from previous studies. We have modified the algorithm by Krissian et al. and implemented it for the segmentation of Type-A aortic dissection. Finally, we implemented these capabilities to study the hemodynamics in Type-A aortic dissection. Our image based framework is a first of its kind and the hemodynamic study of Type-A dissection too is first study onto the best of our knowledge.

This dissertation examines media narratives of Chien-Ming Wang, Yani Tseng, and Jeremy Lin as the entry point for interrogating the construction of transnational Taiwanese identity through modern sports. On the one hand, the (re-)articulation of Taiwanese nationalism has been reproduced and driven through the sporting success of these sporting figures. On the other hand, their national identities, their physical movements across national borders, and their sporting performances—mainly on American soil—also trouble the orthodox notion of nation and nationalism. Through examining media texts published in the United State and Taiwan, I argue that a fluid and flexible transnational Taiwanese identity has emerged. Although global capitalism and transnational corporations have been the leading forces of such media discourses, nation and nationalism still largely regulate and define the ways in which meanings are produced and consumed in these localities. More importantly, I contend that the power imbalance—politically, economically, and culturally—between America and Asia should be critically foregrounded in this conjuncture. In sum, the United States' intervention in Asia during the Cold War era and Taiwan's special status in this historical period still have a lasting effect in contemporary Taiwanese societies. The “light of Taiwan” discourses revolving around Wang, Tseng, and Lin could be understood as a continuation of U.S. cultural imperialism and hegemony since the end of the World War II. Meanwhile, transnational capital and a relatively new Taiwanese nationalism also played prominent roles in these nationalistic celebrations in contemporary Taiwan.

Aerosols are important atmospheric constituents that impact the Earth's radiative balance and climate. The detailed knowledge of the aerosol optical properties is required for a comprehensive analysis of the impacts of aerosols on climate. Mie theory is often used in satellite and ground-based retrieval algorithms to account for atmospheric mineral dust. However, the approximations used in Mie theory are often not appropriate for mineral dust and can lead to errors in the optical properties modeling. Analytic models based on Rayleigh theory that account for particle shapes can offer significant advantages when used to model infrared (IR) extinction of mineral dust. Here, the IR optical properties of some components of mineral dust, authentic dust samples and minerals processed with organic acids were investigated. Detailed characterization of the particles through online and offline methods of analysis that include IR extinction spectroscopy, micro-Raman spectroscopy and scanning electron microscopy was performed. Analysis of the IR extinction spectra and spectral simulations showed that the positions of the peaks and the shapes of the bands of the IR characteristic features are not well simulated by Mie theory in any of the samples studied. The resonance peaks were consistently shifted relative to the experimental spectrum in the Mie simulation. Rayleigh model solutions derived for different particle shapes better predicted the peak positions and band shapes of experimental spectra. To fill the gaps in the refractive index data for atmospherically relevant organic compounds in the IR region optical properties of atmospherically relevant carboxylic acids and humic-like substances using the IR extinction spectra and size distributions measured in the laboratory were determined. In addition to properties of mineral dust this dissertation focuses on properties of sea spray aerosol. Chemical and elemental composition of individual sea spray aerosol particles were studies using micro-Raman spectroscopy, mass-spectrometry and X-ray spectroscopy to provide insights into the biochemical processes that give rise to classes of organic molecules that make up these aerosol particles. The results suggested that degradation of biota (bacteria and diatoms) present in sea water led to lipopolysaccharides and extracellular polymeric substances that further degraded down to carbohydrates and fatty acids. Solubility of the resulting organic species seemed to play a role in their transfer to the aerosol phase. Furthermore, water uptake and hygroscopic growth of multi-component particles were studied. Understanding the interactions of water with atmospheric aerosols is crucial for determining their size, physical state, reactivity, and therefore for aerosol interactions with electromagnetic radiation and clouds. It was determined that particles composed of ammonium sulfate with succinic acid and of mixture of chlorides typical for marine environment show size dependent hygroscopic behavior. Microscopic analysis of the distribution of components within the aerosol particles showed that the observed size dependence is due to the differences in the mixing state. The composition and water uptake properties of sea spray aerosol particles were also measured during a phytoplankton bloom. The results showed that water uptake properties were directly related to the chemical composition of the particles and hygroscopicity decreased with increase in the fraction of water insoluble organic matter emitted during phytoplankton bloom. Finally, multiple methods of particle size, phase and shape analysis were compared and the results showed that the techniques that operate under ambient conditions provide the most relevant and robust measurement of particle size. Additionally, several storage methods for substrate deposited aerosol particles were evaluated and it was determined that storing samples at low relative humidity led to irreversible changes due to sample dehydration while sample freezing and thawing leads to irreversible changes due to phase changes and water condensation. Therefore it is suggested that samples used for single-particles analysis should be stored at ambient laboratory conditions, or near conditions which they were collected, in order to preserve the sample phase and hydration state. The results presented in this dissertation provide insight into physicochemical properties of atmospheric aerosols and help us better understand the role of aerosol particles in the Earth's atmosphere.

Structural topology optimization is a mathematical approach developed to perform design optimization with the purpose of reducing the material usage, while maximizing structural performance, in accordance to specific design constraints. The principles behind this technique have been around for many decades, but recent advancements in the processing power of computers have allowed for the solving of complex problems, such as the optimization of tall wind turbine towers, bridges, and the bracing systems in skyscrapers. There are two approaches commonly used in structural topology optimization: discrete and continuum. This thesis uses continuum topology optimization, which involves adjusting the distribution of a porous elastic solid material to extremize the design objective(s) and to satisfy constraints. The material porosity is the design variable that is adjusted during the optimization process. The design domain is broken down into a system of continuum degenerated finite elements, which are used for both structural analysis and to create a mesh representation of the structural system, just as pixels make up a picture. Solid elements are modeled as having no porosity, while void spaces have total porosity. As the optimization process occurs, the shape of the boundaries, and the number and size of internal holes are altered in order to best meet the design objective(s) and constraint(s). The purpose of performing continuum structural topology optimization of structural elements is to obtain promising concepts which provide a basis upon which to begin the design process. The steps taken in this thesis to optimize the wind turbine tower are: 1. Create a solid model of the tower domain 2. Define the material properties 3. Determine the equivalent static design wind forces using the extreme loading conditions outlined in IEC 61400 4. Formulate the optimization problem by specifying the objective and constraint functions. 5. Solve the optimization problem and interpret the results. This study on continuum topology optimization on the tower shell, indicates even with a significant reduction in material from the original design space, the structure is capable of meeting the design criteria. The results indicate that opening void spaces in the shell of the tower and creating an open lattice shape may be an effective method to reduce the volume of wind turbine towers, as it has in other applications. This concurs with the stated goal of my research, which is to show that topology optimization has the potential to be used in a multitude of practical applications in order to increase efficiency, and reduce cost of the production of wind power.

This thesis presents two important contributions to the modeling of entrainment of air bubbles in water, with focus on ship hydrodynamics applications. The first contribution consists of a general framework for modeling turbulent air entrainment. The framework attempts to describe the evolution of bubbles from their formation at the free surface, size distribution changes due to breakup and coalescence, and rise due to buoyancy. This proposed framework describes the complex entrainment process as a series of simpler mechanisms which can be modeled independently. For each mechanism a simple but mechanistic model is developed to provide closure while leaving the door open for future improvements. These unique characteristics enable the entrainment model to be used in general problems while still producing results at least as good as the few other available models. The massive entrainment of air that takes place around a ship leads to very high void fractions and accumulation of bubbles against the hull, particularly underneath the flat regions of the hull and in low pressure regions near appendages. These processes also pose challenges for two phase solvers. As a second contribution in this thesis, numerical algorithms for two phase flows are developed to eliminate the numerical instabilities normally occurring at high void fractions or large void fraction gradients. A hybrid method to improve pressure-velocity coupling for collocated grids is introduced, which keeps advantages typical of staggered grids in mass conservation and face flux computations. A new two phase coupling strategy is developed to guarantee stability at high void fraction. The balanced force method is extended to general curvilinear grids to suppress spurious velocities. The overall methodology provides strong coupling among pressure, velocity and void fraction, while avoiding numerical instability, and works for free-surface flows on dynamic overset grids. The proposed numerical schemes are tested for 1D and 2D cases. It is shown that the two phase solver is stable and efficient, even under extreme cases. Good mass conservation properties for multigroup simulations are also demonstrated. The air entrainment model is tested for a 2D wave breaking case and compared with extensive experimental data. The results show good predictions for entrainment location and two-phase properties. Full scale simulations for Athena R/V are performed using the same modeling constants obtained for the 2D wave breaking case. A grid study is also carried out to evaluate grid convergence properties of the model. While the model can predict well experimental data at full scale for the ship, it also shows dramatic improvements respect to previous entrainment models by converging in grid and not needing to re-evaluate the model constants for each new application. The high-speed Kann boat is also simulated at full scale, showing encouraging results for a preliminary entrainment model for aeration due to impact. The proposed numerical schemes are proved stable and robust in high Reynolds number flows with complex relevant geometries. In addition, these full scale simulations also identify modeling and numerical issues for future improvements.