Thesis (Ph. D.)--West Virginia University, 2001. / Title from document title page. Document formatted into pages; contains vii, 123 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 59-66).

Includes bibliographical references (p. 64-65).

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: mass balance approach; bioavailability; drug delivery; dynamic modeling; partial differential equations; sensitivity analysis; dynamic simulations. Includes bibliographical references (p. 62-67).

Biological invasions have increased dramatically in the past centuries and are one of the greatest threats to biodiversity today. Invasions occur when organisms are introduced at a location to which they are non-native, and they reproduce and spread, causing damage to the environment. Chromolaena odorata, a herbaceous shrub from the Americas, is one of the most widespread and problematic invasive plant species in the tropics and sub-tropics. The plant is a serious problem in South Africa, where invasive species threaten the nation’s biodiversity and limited water supply. This study combined transect monitoring data of C. odorata with ecological and clearing management data to assess the efficacy of an invasive plant clearing program over its decade of operation in the Hluhluwe-iMfolozi reserve in KwaZulu-Natal, South Africa. Densities and local extent of the C. odorata invasion were significantly reduced during the period of operations of the clearing program. Seasonal effects impacted clearing efficacy, namely a reduction in efficacy during the seed dispersal period. Effort and fire frequency were positively associated with clearing success, and rainfall negatively associated with clearing success. Excluding the northern section of the reserve, where the invasion progressed over the whole landscape, observations of C. odorata were closer to watercourses than randomized points, indicating a water limitation for invasion in most of the park. Management implications drawn from the results include halting clearing during seed-drop months, giving extra attention to areas with more rainfall and other water availability, and incorporating fire with other clearing methods where possible.

The present study investigated phonological encoding skills in children who stutter (CWS). Participants were 4 CWS (M=10;9years) and 4 children who do no stutter (CNS) (M=12;1 years) The groups were compared in phoneme monitoring and rhyme monitoring, with a tone monitoring task providing a neutral baseline for comparison. Both the phoneme monitoring and rhyme monitoring tasks were performed during silent picture naming. Results revealed that both groups were faster and more accurate when monitoring the rhyme than when monitoring the phoneme. Results further indicated that the children who stutter were significantly slower in both conditions. These findings suggest that there may be a later transition to incremental processing in both typically developing children and those who stutter and that children who stutter may be even less efficient than children who do not stutter. However, these results may have been compromised by a few key variables. / text

Heart rate monitoring (HRM) is an essential tool for monitoring physical activity and as a diagnostic tool in the clinical setting. The ability to monitor heart rate gives users and clinicians vital information about the current condition of the cardiovascular system before, during, and after exercise. However, HRM requires a telemetric chest strap, and comfort, transmission and fit can become problems with the chest strap. New technology using photoplethysmography (PPG) has emerged recently to provide the possibility of HRM without a telemetric chest strap during exercise. The aim of this study was to determine if a new device could detect heart rate over a broad range of skin types (I-V), and whether what wavelength would be most suitable for detecting the signals. A light emitting diode (LED) based PPG system was used to determine heart rate by change in pulsatile blood flow on 22 apparently healthy individuals (11 male and 11 female, 20-59 years old) of varying skin type. Skin type was classified according to a questionnaire in combination with digital photographs with a skin type chart. Each subject was exposed to four different wavelengths (470 nm, 520 nm, 630 nm, and 880 nm) and multiple trials were conducted on each wavelength. Heart rate detection was represented by modulation of the incident light wave and normalized by saturation into a pulsatile waveform represented as modulation average. The 520nm wavelength classified as visible green light provided a significantly greater (p<0.001) ability to detect heart rate. Increasing levels of melanin, or darker skin type (Type V) showed decreased modulation however this trend was not significant (p<0.067). There was no significant interaction between the wavelength of light and the skin type. In conclusion, a PPG based device can detect heart rate across skin types and use of a green light wavelength provides an even greater resolution. / text

Real-time monitoring of fracture critical steel bridges can potentially enhance inspection practices by tracking the behavior of the bridge. Significant advances have occurred in recent years on the development of robust hardware for field monitoring applications. These systems can monitor, process, and store data from a variety of sensors (e.g. strain gages, crack propagation gages etc.) to track the behavior of the bridge. The research outlined in this dissertation is part of a large study focused on the development of a wireless system for use in long-term monitoring of bridges. The wireless monitoring system had a target maintenance-free life of ten years, and independent from the power grid. Thus, the feasibility to harvest energy for the monitoring system is an important step in the development of the system. In addition, the reliability of the sensors in the bridge is very important upon the success of the system. The focus of this dissertation is on two primary aspects of the wireless monitoring system. First, the feasibility to harvest energy from vehicular-induced vibrations is evaluated through analytical models of highway bridges under truck loads. Acceleration results from simple line-element models and detailed finite element models of five steel bridges in Texas and Oregon are compared with actual field data from the same bridges. Second, the dissertation also highlights studies on the identification of strain gages and installation procedures that result in long lives. In addition, the effect of temperature fluctuations and other environmental factors on the sensor drift and noise is also considered. In long-term monitoring applications, slight sensor drift and noise can build up over time to produce misleading results. This dissertation presents the results of transient dynamic analyses of bridges under moving truck loading and laboratory tests on gage durability that were conducted as part of a research project sponsored by the National Institute of Standards and Technology (NIST). / text

Reservoir models are generally constructed from seismic, well logs and other related datasets using inversion methods and geostatistics. It has already been recognized by the geoscientists that such a process is prone to non-uniqueness. Practical methods for estimation of uncertainty still remain elusive. In my dissertation, I propose two new methods to estimate uncertainty in reservoir models from seismic, well logs and well production data. The first part of my research is aimed at estimating reservoir impedance models and their uncertainties from seismic data and well logs. This constitutes an inverse problem, and we recognize that multiple models can fit the measurements. A deterministic inversion based on minimization of the error between the observation and forward modeling only provides one of the best-fit models, which is usually band-limited. A complete solution should include both models and their uncertainties, which requires drawing samples from the posterior distribution. A global optimization method called very fast simulated annealing (VFSA) is commonly used to approximate posterior distribution with fast convergence. Here I address some of the limitations of VFSA by developing a new stochastic inference method, named Greedy Annealed Importance Sampling (GAIS). GAIS combines VFSA with greedy importance sampling (GIS), which uses a greedy search in the important regions located by VFSA to attain fast convergence and provide unbiased estimation. I demonstrate the performance of GAIS on post- and pre-stack data from real fields to estimate impedance models. The results indicate that GAIS can estimate both the expectation value and the uncertainties more accurately than using VFSA alone. Furthermore, principal component analysis (PCA) as an efficient parameterization method is employed together with GAIS to improve lateral continuity by simultaneous inversion of all traces. The second part of my research involves estimation of reservoir permeability models and their uncertainties using quantitative joint inversion of dynamic measurements, including synthetic production data and time-lapse seismic related data. Impacts from different objective functions or different data sets on the model uncertainty and model predictability are investigated as well. The results demonstrate that joint inversion of production data and time-lapse seismic related data (water saturation maps here) reduces model uncertainty, improves model predictability and shows superior performance than inversion using one type of data alone. / text

The increasing prevalence causes great burden to global health. Although there is not yet an agreement on the effect of SMBG for non-insulin-treating type 2 DM patients in comprehensive management, some guidelines recommended all diabetes patients should conduct SMBG. This literature review of 5 meta-analyses and 13 randomized controlled clinical trials assessed the effectiveness of SMBG in glucose control (HbA1c), detection of hypoglycemia, non-glycemic outcomes and potential influence factors(duration of diabetes, baseline HaB1c level, SMBG frequency, SMBG duration, co-interventions) of SMBG efficacy on type 2 diabetes patients not using insulin. The method of this literature review is through a comprehensive electronic literature search of Ovid MEDLINE, EMBASE, the Cochrane Library and China Journals Full-text Database. Both English and Chinese language literatures were reviewed. All meta-analysis and randomized controlled trials of type 2 diabetes non-insulin-using patients taking SMBG to improve the glycemic control and other outcomes were included. In these studies, absolute HbA1c reduction, recognized episodes of hypoglycemia, wellbeing, QALY, DALY, complication morbidity, mortality were used as outcome measures if available. A score list based on the PRISMA Statement was used to evaluate the quality of meta-analyses. 5 meta-analysis all reported a statistical significant but clinical modest-moderate difference in HbA1c reduction between SMBG and non-SMBG group, a new published randomized controlled trial with small cohort enrolled in none of the meta- analyses did not support this conclusion. Evidence showed frequency of SMBG did not influence the efficacy of SMBG, co-interventions as education/consultation, regimen change played a positive roll on SMBG efficacy. Whether baseline HbA1c, duration of diabetes or SMBG itself have an effect on SMBG efficacy was still unknown. There is inadequate evidence of SMBG efficacy of detection of hypoglycemia of patient-oriented outcomes. No eligible Chinese article was defined to enroll in this review. This review did not support to suggest all type 2 diabetes patients not using insulin to conduct SMBG at the frequency the guidelines recommended. Carefully designed and longer-term trials are needed to obtain evidence that is more robust. Further investigation would provide more evidence of the characteristics of potential influence factors, which may help to define the specific population or optimal mode that guarantee the greatest efficacy of SMBG. / published_or_final_version / Public Health / Master / Master of Public Health

Consumer health information technologies (CHITs) are emerging as promising tools for delivering healthcare services and facilitating patient self-management of chronic diseases; however, the use of the CHITs is largely constrained by usability problems and unclear evidence on the effectiveness of the technologies. The ergonomics research team of The University of Hong Kong developed a patient-centered computerized self-monitoring system that appeared to be useful and easy to use; with the system, this thesis focuses on the examination of the short-term impacts of the technology on patient outcomes for diabetic and hypertensive patients. The self-monitoring technology was designed using user-centered approaches and relevant human factors principles. Iterative usability evaluations were conducted to assess and improve the usability of the technology with 97 chronically ill patients. Also, using data from a larger randomized controlled trial (RCT) of technology-based disease self-management to improve patients’ outcomes, this thesis compared the short-term effects of the use of a computerized self-monitoring system to usual care using 63 patients with type 2 diabetes and hypertension for four weeks. Thirty-three patients were randomized into intervention group, whose disease care was supported by the self-monitoring system, while 30 patients into control group, who continued with their usual care. A pretest-posttest repeated measures design was employed to determine the effects of the technology on clinical, psychosocial, behavioral, usage, and technology perception outcomes over time. Measurements were obtained at baseline, and after 2 and 4 weeks. The iterative usability studies improved and verified the usability of the self-monitoring system for chronically ill patients. Results from the RCT showed that after four weeks, there were significant decreases in systolic blood pressure (p < 0.001) and diastolic blood pressure (p < 0.001), self-efficacy for managing chronic disease (p = 0.001), and adherence to treatment (p = 0.001) in the intervention group compared with the control group. Significant differences in favor of intervention group after four weeks were also documented for changes of several quality of life subscales (i.e., general health (p = 0.010), role physical (p = 0.001), role emotional (p = 0.002), bodily pain (p = 0.050), and physical component summary score (p = 0.005)), and perceived ease of use (p = 0.007). No significant difference was found between groups for fasting blood glucose (p = 0.687), perceived usefulness (p = 0.661), frequency of self-monitoring of blood pressure (p = 0.230) and self-monitoring of blood glucose (p = 0.993), and several other quality of life subscales over time. The usability evaluation presented in this thesis report demonstrated that the method was effective and efficient in identifying potential usability problems at the early stage of system development for CHITs. The findings from the RCT indicated that the use of the human factored-engineered self-monitoring technology had short-term effectiveness in improving blood pressure control, self-efficacy for managing chronic disease, adherence to treatment, and quality of life for patients with type 2 diabetes and hypertension. A human factored-engineered self-management technology appears to be an effective tool in patient self-management of chronic diseases. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy