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Inverse problems aim at estimating the unknown excitations or properties of a physical system based on available measurements of the system response. For example, wave tomography is used in geophysics for seismic waveform inversion; in biomedical engineering, optical tomography is used to detect breast cancer tissue; in structural engineering, inversion techniques are used for health monitoring and damage detection in structural safety evaluation. Inverse solvers depend on the type of measurement data the unknown parameters to be estimated. The work in this thesis focuses on structural parameter identification based on static and dynamic measurements. As an integral part of the formulated inverse solver, the associated forward problem is studded and deeply investigated. In reality, the data are associated with uncertainties caused by measurement devices or unfriendly environmental conditions during data acquisition. Traditional approaches use probability theory and model uncertainties as random variables. This approach has its own limitation due to a prior assumption on the probability structure of uncertainty. This is usually too optimistic or not realistic. However, in practice, it is usually difficult to reliably assess the statistical nature of uncertainties. Instead, only bounds on the uncertain variables and some partial information about their probabilities are known. The main source of uncertainty is due to the accuracy of measuring devices; these are designed to operate within specific allowable tolerances, as defined by National Institute of Standards and Technology (NIST). Tolerances are performance requirements that fix the limit of allowable error or departure from true performance or value. Thus closed intervals are the most realistic way to model uncertainty in measurements. In this work, uncertainties in measurement data are modeled as interval variables bounded by their endpoints. It is proven that interval analysis provides guaranteed enclosure of the exact solution set regardless of the underlying nature of the associated uncertainties. This work presents a solution of inverse problems under measurements uncertainty within the framework of Interval Finite Element Methods (IFEM) and adjoint-based optimization techniques. The solution consists of a two-step algorithm: first, an estimate of the parameters is obtained by means of a deterministic iterative solver. Then, the algorithm switches to a full interval solution, using the previous deterministic estimate as an initial guess. In general, the solution of an inverse problem requires iterative solutions of the forward problem. Efficient and accurate interval forward solutions in static and dynamic domains have been developed. In particular, overestimation due to interval dependency has been drastically reduced using a new decomposition of the load, stiffness, and mass matrices. Further improvements in the available interval iterative solvers have been achieved. Conjugate gradient and Newton-Raphson methods to gether with an inexact line search are used in the newly formulated optimization procedure. Moreover Tikhonov regularization is used to improve the conditioning of the ill-posed inverse problem. The developed interval solution for the inverse problem under uncertainty has been tested in a wide range of applications in static and dynamic domains. By comparing current solutions with other available methods in the literature, it is proven that the developed method provides guaranteed sharp bounds on the exact solution sets at a low computational cost. In addition, it contains those solutions provided by probabilistic approaches regardless of the used probability distributions. In conclusion, the developed method provides a powerful tool for the analysis of structural inverse problem under uncertainty.

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In this thesis we consider integrals of a certain class of interval functions. Specifically we consider a nondegenerate number interval [a,b], a real valued function m, defined and nondecreasing on [a,b], and the set Hm, of real valued functions f, defined on [a,b] such that: 1) f(a)=0; 2) for each subinterval [p,q] of [a,b], if m(q)-m(p)=0, then f(q)-f(p)=0; and 3) the set of all sums of the form Σ(Δf)2/Δm for subdivisions D of [a,b] is bounded above.

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Decomposition chemistry refers to the biochemical degradation processes which occur in soft tissue as decomposition proceeds. This study aims to investigate the relationship between the release of decomposition fluids into contrasting soil environments and their potential correlation with the presence of a decomposing carcass. Soil from two different carcass decomposition trials was utilized to determine if seasonal and soil variation altered the soils reaction to a carcass. The reaction was determined by investigating the soil available phosphorus, extractable lipid-phosphate, pH, moisture and fatty acid content. A significant increase in the relative concentration of extractable lipid-phosphate, soil available phosphorus, and fatty acid content was identified, confirming the flux in the microbial biomass in the soil. Contrary to these nutrients, there were no notable changes in the soil pH and moisture content. The findings of this study were able to highlight the future forensic potential of these techniques and demonstrate a need for further research.

Understanding the relationship between childbearing and socioeconomic status could help explain one mechanism by which the United States’ gender disparity in poverty comes to exist. However, measuring the relationship between childbearing and socioeconomic status is complicated by the very high prevalence of childbearing among women and multiple sources of endogeneity in the characteristics of childbearing that do vary. Focusing on the timing of childbearing, I use miscarriage to construct an instrument for delivery and build a counterfactual condition for having a short temporal space between births. Using this approach with data from the National Longitudinal Survey of Youth 1979, I estimate the effect on midlife poverty of having first and second births within 24 months of each other. My results indicate that these short interbirth intervals are causally related to increased midlife poverty. The results are robust to a variety of alternate specifications of counterfactual conditions and estimation methods. / text

A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine. / Objectives: Interpregnancy interval (IPI), the time period between the end of one pregnancy and the conception of the next, can have a significant impact on maternal and infant outcomes. This study examines the relationship between interpregnancy interval and neonatal outcomes of low birth weight, preterm birth, and specific neonatal morbidities. Study Design: Retrospective cohort study comparing neonatal outcomes across 6 categories of IPI using data on 202,600 cases identified from Arizona birth certificates and the Newborn Intensive Care Program data. Comparisons between groups were made using odds ratios and 95% confidence intervals, and multivariable logisitic regression analysis. Results: Interpregnancy intervals of < 12 months and ≥ 60 months were associated with low birth weight, preterm birth, and small for gestational age births. The shortest and longest IPI categories were also associated with specific neonatal morbidities, including periventricular leukomalacia, bronchopulmonary dysplasia, intraventricular hemorrhage, apnea bradycardia, respiratory distress syndrome, transient tachypnea of the newborn, and suspected sepsis. Relationships between interpregnancy interval and specific neonatal morbidities did not remain significant when adjusted for birth weight and gestational age. Conclusions: Significant differences in neonatal outcomes (preterm birth, low birth weight, and small for gestational age) were observed between IPI categories. Consistent with previous research, interpregnancy intervals < 12 months and ≥ 60 months appear to be associated with increased risk of poor neonatal outcomes. Any difference in specific neonatal morbidities between IPI groups appears to be mediated through increased risk of low birth weight and preterm birth by IPI.

Considering the increasing global prevalence of overweight and obesity and their propensity for disease, this study was undertaken in an attempt to optimize exercise prescription for this at-risk group by determining if the benefits associated with interval training occur in an intensity dependent manner. 19 sedentary, overweight males (Age: 22.7 ± 3.9 yrs, BMI: 31.4 ± 2.6 kg/m2, WC: 106.5 ± 6.6 cm) performed interval training for three weeks at either 70% or 100% of their peak work rate on a cycle ergometer. Aerobic capacity measurements, time to completion trials, muscle biopsies, and fasted blood samples were all performed pre and post training. Analyses of aerobic capacity and exercise performance demonstrate greater improvements made in the 100% compared to the 70% group, while measures of skeletal muscle oxidative capacity indicate equivalent changes between groups. Taking into account the similar increases in mitochondrial content in both groups and understanding the influence of both oxygen supply and demand in determining maximal oxygen consumption, the greater increases in aerobic capacity achieved by the 100% group may be the result of enhanced cardiovascular adaptations. These findings suggest that some of the health benefits associated with interval exercise may be intensity dependent. Therefore, there may be additional benefit to exercise at higher intensities. / Thesis (Master, Kinesiology & Health Studies) -- Queen's University, 2012-09-27 17:26:19.425