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Great progress has been made in sleep medical research in recent years and sleep medicine has thus evolved into a specialized medical field. Sleep apnea syndrome is one of the mostly commonly seen sleep disorders. It is now clear that sleep apnea has adverse effects on the heart and is a risk factor for several cardiovascular diseases. Studies have found that decreased heart rate variability (HRV) is a prognostic factor for cardiovascular disease and it also associated with higher mortality rate. Considering the confounding effect of BMI and sleep apnea severity, this work investigates the correlation between heart rate variability and AHI (apnea-hypopnea index which is used to characterize the severity of sleep apnea) by dividing patients into different BMI subgroups. This work includes 1068 male subjects with complete overnight ECG recordings. The low-frequency (LF), the high-frequency (HF) component and the LF/HF ratio of HRV are computed for the 10 BMI subgroups. The Bootstrap method and the BCa technique for confidence interval estimation are employed to verify the linear association between the HRV measures and the severity of sleep apnea. The experimental results show that statically significant correlation exist between LF/HF ratio and AHI for BMI ¡Ù28 patient groups. Statically significant correlation between LF and AHI also exists for BMI ¡Ù27 patient groups. These results demonstrate that the associations between some of the HRV measures and AHI are clearly BMI dependent.

Throughout the United States accelerated bridge construction is becoming increasingly popular to meet growing transportation demands while keeping construction time and costs to a minimum. This research focuses on eliminating the need to form full-depth concrete bridge deck overhangs, accelerating the construction of concrete bridge decks, by using full-depth precast prestressed concrete deck panels. Full-depth precast overhang panels in combination with cast-in-place (CIP) reinforced concrete are experimentally and analytically investigated to assess the structural performance. Experimental loaddeformation behavior for factored AASHTO LRFD design load limits is examined followed by the collapse capacity of the panel-to-panel seam that exists in the system. Adequate strength and stiffness of the proposed full-depth panels deem the design safe for implementation for the Rock Creek Bridge in Fort Worth, Texas. New failure theories are derived for interior and exterior bridge deck spans as present code-based predictions provide poor estimates of the ultimate capacity. A compound shear-flexure failure occurs at interior bays between the CIP topping and stay-in-place (SIP) panel. Overhang failure loads are characterized as a mixed failure of flexure on the loaded panel and shear at the panel-to-panel seam. Based on these results design recommendations are presented to optimize the reinforcing steel layout used in concrete bridge decks.

Fuel cells are the tools which convert chemical energy into electricity directly by the effective utilization of hydrogen and oxygen (or air). One of the most important barriers for the fuel cell commercialization is the durability of the fuel cell components in the long term operations. In this study, the durability of the PEM fuel cell electrocatalysts were investigated via cyclic voltammetry (CV) and rotating disk electrode (RDE) experiments in order to determine the hydrogen oxidation reaction (HOR) and oxygen reduction reaction (ORR) which corresponds to the half cell reactions in the fuel cell. PEM fuel cell electrodes mainly composed of carbon supported Pt catalysts. In long term operations due to Pt dissolution and carbon corrosion some properties of the electrocatalysts can be changed. Performance losses in catalysts mainly depend on / i) decrease in the total metal surface area (SA) and the electrochemically active surface area (ESA) due to the increase in the particle size ii) decrease in the tafel slope potential in ORR and iii) increase in carbon corrosion. In this study, these properties were examined via accelerated degradation tests performed in CV and RDE. The catalysts having different Pt loadings, synthesized with different ink compositions, pH values and microwave durations were investigated. The commercial catalysts having Pt loadings of 20, 50 and 70 (wt %) were tried and best results were obtained for Pt/V (50 wt %) catalyst. Different carbon to Nafion&reg / ratios of 4, 8, 12 in the ink composition were tried. C/N ratio of 8 gave the best result in Pt dissolution and carbon corrosion degradation tests. The catalysts prepared at different pH values of 1.4, 6.25 and 10 were tried and the catalyst prepared at pH of 10 was less degraded in Pt dissolution test and the catalyst prepared at pH of 6.25 showed better resistance to carbon corrosion. Catalysts prepared under different microwave durations of 50, 60 and 120 s were tried and the catalyst prepared at 60 s gave the best performances.

Patient survival post liver transplant (LT) is important to both the patient and the center's accreditation, but over the years physicians have noticed that distant patients struggle with post LT care. I hypothesized that patient's distance from the transplant center had a detrimental effect on post LT survival. I suspected Hepatitis C (HCV) and Hepatocellular Carcinoma (HCC) patients would deteriorate due to their recurrent disease and there is a need for close monitoring post LT. From the current literature it was not clear if patients' distance from a transplant center affects outcomes post LT. Firozvi et al. (Firozvi AA, 2008) reported no difference in outcomes of LT recipients living 3 hours away or less. This study aimed to examine outcomes of LT recipients based on distance from a transplant center. I hypothesized that the effect of distance from a LT center was detrimental after adjusting for HCV and HCC status. Methods: This was a retrospective single center study of LT recipients transplanted between 1996 and 2012. 821 LT recipients were identified who qualified for inclusion in the study. Survival analysis was performed using standard methods as well as a newly developed Monte Carlo (MC) approach for change point detection. My new methodology, allowed for detection of both a change point in distance and a time by maximizing the two parameter score function (M2p) over a two dimensional grid of distance and time values. Extensive simulations using both standard distributions and data resembling the LT data structure were used to prove the functionality of the model. Results: Five year survival was 0.736 with a standard error of 0.018. Using Cox PH it was demonstrated that patients living beyond 180 miles had a hazard ratio (HR) of 2.68 (p-value<0.004) compared to those within 180 miles from the transplant center. I was able to confirm these results using KM and HCV/HCC adjusted AFT, while HCV and HCC adjusted LR confirmed the distance effect at 180 miles (p=0.0246), one year post LT. The new statistic that has been labeled M2p allows for simultaneous dichotomization of distance in conjunction with the identification of a change point in the hazard function. It performed much better than the previously available statistics in the standard simulations. The best model for the data was found to be extension 3 which dichotomizes the distance Z, replacing it by I(Z>c), and then estimates the change point c and tau. Conclusions: Distance had a detrimental effect and this effect was observed at 180 miles from the transplant center. Patients living beyond 180 miles from the transplant center had 2.68 times the death rate compared to those living within the 180 mile radius. Recipients with HCV fared the worst with the distance effect being more pronounced (HR of 3.72 vs. 2.68). Extensive simulations using different parameter values in both standard simulations and simulations resembling LT data, proved that these new approaches work for dichotomizing a continuous variable and finding a point beyond which there is an incremental effect from this variable. The recovered values were very close to the true values and p-values were small.

The science and technology of catalysis is more important today than at any other time in our history due to the grand energy and environment challenges we are facing. With the explosively growth of computation power nowadays, computer simulation can play an increasingly important role in the design of new catalysts, avoiding the costly trail-and-error attempts and facilitating the development cycle. The goal to inverse design of new materials with desired catalytic property was once far off, but now achievable. The major focus of this dissertation is to find the general rules that govern the catalytic performance of a nanoparticle as the function of its structure. Three types of multi-metallic nanoparticles have been investigated in this dissertation, core-shell, random alloy and alloy-core@shell. Significant structural rearrangement was found on Au@Pt and Pd@Pt nanoparticle, which is responsible for a dramatic improvement in catalytic performance. Nonlin- ear binding trends were found and modeled for random alloy nanoparticles, providing a prescription for tuning catalytic activity through alloying. Studies of ORR on Pd/Au random alloy NP and hydrogenation reaction on Rh/Ag random alloy NP revealed that binding on individual ensemble should be in- vestigated when large disparity of adsorbate affinity is presented between two alloying elements. In the alloy-core@shell system, I demostrated a general linear correlations between the adsorbate binding energy to the shell of an alloy-core@shell nanoparticle and the composition of the core. This relation- ship allows for interpolation of the properties of single-core@shell particles and an approach for tuning the catalytic activity of the particle. A series of promising catalysts were then predicted for ORR, HER and CO oxidation. As a first attempt to bridge the material gap, bimetallic nano clus- ter supported on CeO₂(111) was investigated for CO oxidation. A strong support-metal interaction induces a preferential segregation of the more reac- tive element to the NC-CeO₂ perimeter, generating an interface with the Au component. (Au-Cu)/CeO₂ was found to be optimal for catalyzing CO oxida- tion via a bifunctional mechanism. O₂ preferentially binds to the Cu-rich sites whereas CO binds to the Au-rich sites. A method called distributed replica dynamics (DRD) is proposed at last to utilize enormous distributed computing resources for molecular dynamics simulations of rare-event in chemical reac- tions. High efficiency can be achieved with an appropriate choice of N [subscript rep] and t [subscript rep] for long-time MD simulation. / text

Dual credit, which allows students to simultaneously earn high school and college credit for the same course, is widely-implemented across the country. Dual credit is thought to promote student success in higher education. However, there is limited research on whether dual credit courses taken in high school positively influence college-level outcomes. Using Ordinary Least Squares and Logistic analysis to control for student background characteristics, this study examines the relationship between dual credit and student success in college, specifically freshman grade point average and college graduation. The study examines an existing dataset from the Texas Higher Education Coordinating Board that includes approximately 35,870 students. Results suggest that dual credit positively influences college outcomes. / text

Due to their structural efficiency and architectural elegance, concrete arches have long been used in bridge applications. However, the construction of concrete arches requires significant temporary supporting structures, which prevent their widespread use in modern bridges. A relatively new form of arch bridges is the network arch, in which a dense arrangement of inclined hangers is used. Network arches are subjected to considerably smaller bending moments and deflections than traditional arches and are therefore suitable for modern, accelerated construction methods in which the arches are fabricated off-site and then transported to the bridge location. However, service-level stresses, which play a critical role in the performance of the structure, are relatively unknown for concrete network arches and have not been sufficiently investigated in the previous research on concrete arches. The primary objective of this dissertation is to improve the understanding of short-term and time-dependent stresses in concrete arches, and more specifically, concrete network arches. The research presented herein includes extensive field monitoring of the West 7th Street Bridge in Fort Worth, Texas, which is the first precast network arch bridge and probably the first concrete network arch bridge in the world. The bridge consists of twelve identically designed concrete network arches that were precast and post-tensioned before they were transported to the bridge site and erected. A series of vibrating wire gages were embedded in the arches and were monitored throughout the construction and for a few months after the bridge was opened to traffic. The obtained data were processed, and structural response parameters were evaluated to support the safe construction of the innovative arches, identify their short-term and time-dependent structural behavior, and verify the modeling assumptions. The variability of stresses among the arches was also used to assess the reliability of stress calculations. The results of this study provide valuable insight into the elastic, thermal, and time-dependent behavior of concrete arches in general and concrete network arches in particular. The knowledge gained in this investigation also has broader applications towards understanding the behavior of indeterminate prestressed concrete structures that are subjected to variable boundary conditions and thermal and time-dependent effects.

Because of the needs for producing highly reliable products and reducing product development time, Accelerated Life Testing (ALT) has been widely used in new product development as an alternative to traditional testing methods. The basic idea of ALT is to expose a limited number of test units of a product to harsher-than-normal operating conditions to expedite failures. Based on the failure time data collected in a short time period, an ALT model incorporating the underlying failure time distribution and life-stress relationship can be developed to predict the product reliability under the normal operating condition. However, ALT experiments often consume significant amount of energy due to the harsher-than-normal operating conditions created and controlled by the test equipment used in the experiments. This challenge may obstruct successful implementations of ALT in practice. In this dissertation, a new ALT design methodology is developed to improve the reliability estimation precision and the efficiency of energy utilization in ALT. This methodology involves two types of ALT design procedures - the sequential optimization approach and the simultaneous optimization alternative with a fully integrated double-loop design architecture. Using the sequential optimum ALT design procedure, the statistical estimation precision of the ALT experiment will be improved first followed by energy minimization through the optimum design of controller for the test equipment. On the other hand, we can optimize the statistical estimation precision and energy consumption of an ALT plan simultaneously by solving a multi-objective optimization problem using a controlled elitist genetic algorithm. When implementing either of the methods, the resulting statistically and energy efficient ALT plan depends not only on the reliability of the product to be evaluated but also on the physical characteristics of the test equipment and its controller. Particularly, the statistical efficiency of each candidate ALT plan needs to be evaluated and the corresponding controller capable of providing the required stress loadings must be designed and simulated in order to evaluate the total energy consumption of the ALT plan. Moreover, the realistic physical constraints and tracking performance of the test equipment are also addressed in the proposed methods for improving the accuracy of test environment. In this dissertation, mathematical formulations, computational algorithms and simulation tools are provided to handle such complex experimental design problems. To the best of our knowledge, this is the first methodological investigation on experimental design of statistically precise and energy efficient ALT. The new experimental design methodology is different from most of the previous work on planning ALT in that (1) the energy consumption of an ALT experiment, depending on both the designed stress loadings and controllers, cannot be expressed as a simple function of the related decision variables; (2) the associated optimum experimental design procedure involves tuning the parameters of the controller and evaluating the objective function via computer experiment (simulation). Our numerical examples demonstrate the effectiveness of the proposed methodology in improving the reliability estimation precision while minimizing the total energy consumption in ALT. The robustness of the sequential optimization method is also verified through sensitivity analysis.

Accelerated life testing (ALT) has been widely used in collecting failure time data of highly reliable products. Most parametric ALT models assume that the ALT data follows a specific probability distribution. However, the assumed distribution may not be adequate in describing the underlying failure time distribution. In this dissertation, a more generic method based on a phase-type distribution is presented to model ALT data. To estimate the parameters of such Erlang Coxian-based ALT models, both a mathematical programming approach and a maximum likelihood method are developed. To the best of our knowledge, this dissertation demonstrates, for the first time, the potential of using PH distributions for ALT data analysis. To shorten the test time of ALT, degradation tests have been studied as a useful alternative. Among many degradation tests, destructive degradation tests (DDT) have attracted much attention in reliability engineering. Moreover, some materials/products start degrading only after a random degradation initiation time that is often not even observable. In this dissertation, two-stage delayed-degradation models are developed to evaluate the reliability of a product with random initiation time. For homogeneous and heterogeneous populations, fixed-effects and random-effects Gamma processes are considered, respectively. An expectation-maximization algorithm and a bootstrap method are developed to facilitate the maximum likelihood estimation of model parameters and to construct the confidence intervals of the interested reliability index, respectively. With an Accelerated DDT model, an optimal test plan is presented to improve the statistical efficiency. In designing the ADDT experiment, decision variables related to the experiment must be determined under the constraints on limited resources, such as the number of test units and the total testing time. In this dissertation, the number of test units and stress level are pre-determined in planning an ADDT experiment. The goal is to improve the statistical efficiency by selecting appropriately allocate the test units to different stress levels to minimize the asymptotic variance of the estimator of the p-quantile of failure time. In particular, considering the random degradation initiation time, a three-level constant-stress destructive degradation test is studied. A mathematical programming problem is formulated to minimize the asymptotic variance of reliability estimate.