Browsing by Subject "Bayesian analysis"
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Item Adaptive Reliability Analysis of Excavation Problems(2012-10-19) Park, Jun KyungExcavation activities like open cutting and tunneling work may cause ground movements. Many of these activities are performed in urban areas where many structures and facilities already exist. These activities are close enough to affect adjacent structures. It is therefore important to understand how the ground movements due to excavations influence nearby structures. The goal of the proposed research is to investigate and develop analytical methods for addressing uncertainty during observation-based, adaptive design of deep excavation and tunneling projects. Computational procedures based on a Bayesian probabilistic framework are developed for comparative analysis between observed and predicted soil and structure response during construction phases. This analysis couples the adaptive design capabilities of the observational method with updated reliability indices, to be used in risk-based design decisions. A probabilistic framework is developed to predict three-dimensional deformation profiles due to supported excavations using a semi-empirical approach. The key advantage of this approach for practicing engineers is that an already common semi-empirical chart can be used together with a few additional simple calculations to better evaluate three-dimensional displacement profiles. A reliability analysis framework is also developed to assess the fragility of excavation-induced infrastructure system damage for multiple serviceability limit states. Finally, a reliability analysis of a shallow circular tunnel driven by a pressurized shield in a frictional and cohesive soil is developed to consider the inherent uncertainty in the input parameters and the proposed model. The ultimate limit state for the face stability is considered in the analysis. The probability of failure that exceeding a specified applied pressure at the tunnel face is estimated. Sensitivity and importance measures are computed to identify the key parameters and random variables in the model.Item Currency and political choice : analytical political economy of exchange rate policy in East Asia(2010-05) Meng, Chih-Cheng; Roberts, Brian E.; Hinich, Melvin J.; Lin, Tse-min; Elkins, Zachary; Vaughn, BrandonHow do catch-up East Asian countries cultivate their exchange rate (ER) policies in a different trajectory than advanced economies often cited in current literature? What are the dynamics and results (pros and cons) of choosing a particular ER policy, and what influence does it have on the progress of developmental states? How do domestic and international politics explain the convergences and variances of ER policy decisions in East Asia? The decisions of ER policy are by all means political choices. ERs influence the prices of daily exchanged goods, and thereby determine resource allocation within and across national borders. Therefore, any internal political actor, including a government, interest group, foreign party or constituent exerts discretionary power to manipulate an ER to satisfy its own interests. Externally, the size of foreign trade and the status of international monetary accounts closely depend on the valuation and volatility of ER. Thus for the transitional polities and the trade-driving economies in East Asia, the analysis of ER politics not only helps to clarify the complex mechanisms of ER influences combined with various interests and institutional settings, but also to advance the political study of globalization. My dissertation proposes an integrated framework to contend that the domestic distributional politics and economic determinants, as well as the international monetary relations, and regional market force and adaptive policy diffusion are crucial factors that influence and interact with ER policy in East Asia. This theoretical framework explains how an ER policy decision is compromised between domestically generated preferences and apparently intense international interactions. Likewise, this dissertation provides a vigorous empirical specification toward the spatiotemporal differences of ER policy in East Asia. The application of the structural vector autoregression (SVAR) model properly specifies the theoretical dynamics across variables in the East Asian panel data compiled from 1980 to 2004. Furthermore, by using the alternative Bayesian estimation, SVAR successfully demonstrates the "spinning stories" that distinguish the variances with regard to country-specific development under the asymmetrically international and interdependently regional monetary system. The empirical findings verify that my theoretical variables interact significantly with ER policy decisions in East Asia. The statistics also demonstrate that most East Asian countries tend to strategically withstand influences from the various waves of capital liberalization and keep their currencies at low values. In a general testing, however, domestic pursuits for preferred interests gradually yield to the persistent influences of international and regional forces on ER policy making in East Asia.Item Ecosystem health at the texas coastal bend: a spatial analysis of exposure and response(2009-05-15) Bissett, Wesley Thurlow, Jr.This dissertation investigated locational risks to ecosystem health associated with proximity to industrial complexes. The study was performed at the behest of ranchers and citizens living and working down-prevailing wind from the Formosa Plastics, Inc. and ALCOA facilities located in Calhoun County, Texas. Concerns expressed were for potential genotoxicity resulting from exposure to complex chemical mixtures released by the facilities. Exposure assessment of the marine environment was performed with sediments and oysters from Lavaca Bay being analyzed. Numerous chemicals were found to be present at concentrations considered likely to result in adverse responses in exposed populations. Bayesian geostatistical analysis was performed to determine if the concentrations were affected by a spatial process. Mercury and polycyclic aromatic hydrocarbons were the most notable of the chemicals found to be present at elevated concentrations and affected by a spatial process. Evaluation of maps generated from spatial modeling revealed that proximity to ALCOA resulted in elevated risks for exposure to harmful concentrations of pollutants. Genotoxicity was measured in two sentinel species. Oysters (Crassostrea virginica) were utilized for evaluation of the marine environment and cattle (Bos taurus and Bos taurus crossbred cattle) were chosen for evaluation of the terrestrial environment. Chromosomal aberration analysis was performed on oyster hematocytes. Analysis of the results failed to demonstrate the presence of an important generalized spatial process but some specific locations close to the ALCOA plant had elevations in this measure of genotoxicity. Stress as measured by the lysosomal destabilization assay was also performed on oyster hematocytes. These results were found to be affected by a significant spatial process with the highest degree of destabilization occurring in close proximity to ALCOA. Genotoxicity in cattle was evaluated with the single cell gel electrophoresis assay and chromosomal aberration analysis. Bayesian geostatistical analyis revealed the presence of important spatial processes. DNA-protein cross-linkage was the most notable with a strong indication of increased damage down-prevailing wind from the industrial complexes. Results indicated that proximity to industrial facilities increased the risk for harmful exposures, genotoxicity, and lysosomal destabilization.Item Effects of altered precipitation regimes on North American desert plant physiology(Texas Tech University, 2008-05) Patrick, Lisa Dori; Tissue, David T.; Holaday, A. Scott; Loik, Michael; Payton, Paxton R.; Zak, JohnClimate change will significantly impact deserts since precipitation drives biological activity in these ecosystems. Further, ecosystem responses to precipitation may be non-linear due to differential species responses to variation in the timing and magnitude of precipitation. Since plants impact total ecosystem function, it is critical to evaluate physiological responses to precipitation across multiple spatial and temporal scales. As such, this dissertation focuses on the physiological responses of desert grasses and shrubs to altered precipitation, spanning from the leaf- to the ecosystem-level. First, I examined the effects of increased precipitation on ecosystem fluxes of CO2 and H2O in Big Bend National Park (BIBE), Texas in the Chihuahuan Desert. To partition ecosystem fluxes, I conducted field measurements of plant, soil, and ecosystem fluxes after precipitation pulses throughout the summer. Increased summer precipitation altered soil carbon and water, and plant water fluxes over shorter time scales and carbon fluxes of grasses over longer time scales, which may lead to increased ecosystem carbon storage. Second, I focused on the leaf-level by measuring short-term physiological responses to precipitation events. I collected photosynthesis data for dominant plants in BIBE to examine the effects of natural and supplemental seasonal precipitation on carbon fluxes. I also measured environmental and biological variables to determine regulators of photosynthesis. Leaf-level fluxes of shrubs were more sensitive to both the amount of deep soil water and nitrogen, while grasses were only affected by leaf nitrogen. Further, increased precipitation in the summer and winter could have significant impacts on plant carbon gain and utilization due to soil nitrogen dynamics. Lastly, I collected photosynthetic data for seven dominant desert plants across North America to determine if the responses seen in BIBE were common across all deserts. I developed a Bayesian model of photosynthesis to analyze these data. Photosynthetic responses were similar across deserts and species, but different from temperate forest trees, leading to a unified understanding of desert plant physiology. When photosynthesis parameters were examined in relation to altered precipitation, data indicated that increased summer precipitation altered maximum electron transport and the temperature sensitivity of enzymatic reactions in C3 shrubs. Altered seasonal precipitation regimes also decoupled relationships between limitations to photosynthesis and nitrogen across all deserts and species studied.Item Fossils, phylogeny, and anatomical regions : insights exemplified through turtles(2013-08) Burroughs, Robert Wayne; Bell, Christopher J., 1966-There are more than 300 species of extant turtles, the majority of which belong to the Testudinoidea. Here I describe a new box turtle from the Eocene-Oligocene boundary of west Texas. This specimen impacts the phylogeny of Testudinoid turtles by pulling the divergence of extant Testudinoid turtles back in time approximately 25 million years. This results in a need to refocus on paleontological research of Testudinoid turtles into the late Paleogene and early Neogene to identify fossil localities and specimens that can help further elucidate the evolution of the group. New work on the fossil record of turtles also requires a re-evaluation of methods used for identifying and evaluating the evolutionary history of turtles as a group. An implicit assumption over the last 150 years of turtle paleontology was that both turtle shells and turtle heads reveal congruent and complimentary evolutionary relationships. This assumption was never adequately tested. I utilized a series of methods to evaluate the congruency of phylogenetic hypotheses using disparate anatomical regions. Using a dataset of extant Emydid turtles, I evaluated whether turtle shells and turtle heads provided congruent and complimentary phylogenetic hypotheses. My methods employed parsimony-based reconstruction, maximum-likelihood-based reconstruction, and Bayesian-based reconstruction, including Bayesian-partition analyses. My conclusions are that heads and shells do not provide fully congruent topologies, and that in many cases there is a loss of phylogenetic resolution when only turtle sklls are used to generate phylogenies. The implication is that a focus on a robust and complete dataset of anatomical features will provide the best basis for further investigation of fossils. My work also provides a framework for dataset exploration by providing a method to identify the most robust phylogenetic signal found within a dataset. This framework will allow non-turtle paleontologists and systematists the ability to further investigate their own datasets and develop robust hypotheses of evolutionary relationships across the diversity of the tree of Life.Item Improving the accuracy and realism of Bayesian phylogenetic analyses(2009-08) Brown, Jeremy Matthew; Hillis, David M., 1958-Central to the study of Life is knowledge both about the underlying relationships among living things and the processes that have molded them into their diverse forms. Phylogenetics provides a powerful toolkit for investigating both aspects. Bayesian phylogenetics has gained much popularity, due to its readily interpretable notion of probability. However, the posterior probability of a phylogeny, as well as any dependent biological inferences, is conditioned on the assumed model of evolution and its priors, necessitating care in model formulation. In Chapter 1, I outline the Bayesian perspective of phylogenetic inference and provide my view on its most outstanding questions. I then present results from three studies that aim to (i) improve the accuracy of Bayesian phylogenetic inference and (ii) assess when the model assumed in a Bayesian analysis is insufficient to produce an accurate phylogenetic estimate. As phylogenetic data sets increase in size, they must also accommodate a greater diversity of underlying evolutionary processes. Partitioned models represent one way of accounting for this heterogeneity. In Chapter 2, I describe a simulation study to investigate whether support for partitioning of empirical data sets represents a real signal of heterogeneity or whether it is merely a statistical artifact. The results suggest that empirical data are extremely heterogeneous. The incorporation of heterogeneity into inferential models is important for accurate phylogenetic inference. Bayesian phylogenetic estimates of branch lengths are often wildly unreasonable. However, branch lengths are important input for many other analyses. In Chapter 3, I study the occurrence of this phenomenon, identify the data sets most likely to be affected, demonstrate the causes of the bias, and suggest several solutions to avoid inaccurate inferences. Phylogeneticists rarely assess absolute fit between an assumed model of evolution and the data being analyzed. While an approach to assessing fit in a Bayesian framework has been proposed, it sometimes performs quite poorly in predicting a model’s phylogenetic utility. In Chapter 4, I propose and evaluate new test statistics for assessing phylogenetic model adequacy, which directly evaluate a model’s phylogenetic performance.Item Statistical analysis in downscaling climate models : wavelet and Bayesian methods in multimodel ensembles(2009-08) Cai, Yihua; Damien, Paul, 1960-; McCulloch, Robert E.Various climate models have been developed to analyze and predict climate change; however, model uncertainties cannot be easily overcome. A statistical approach has been presented in this paper to calculate the distributions of future climate change based on an ensemble of the Weather Research and Forecasting (WRF) models. Wavelet analysis has been adopted to de-noise the WRF model output. Using the de-noised model output, we carry out Bayesian analysis to decrease uncertainties in model CAM_KF, RRTM_KF and RRTM_GRELL for each downscaling region.