The issue of how to test and ultimately regulate tobacco products represents a critical challenge for the public health community. Although the current international testing regime for conventional cigarettes is widely acknowledged to be seriously flawed, there is a lack of data to guide potential alternatives, particularly in the area of human puffing behaviour. The current study sought to: 1) collect naturalistic measures of smoking behaviour, 2) examine the extent to which levels of tar, nicotine, and carbon monoxide from each of five testing protocols were associated with measures of nicotine uptake among smokers, and 3) examine the validity of self-report measures of smoking behaviour. These questions were examined through two different studies. First, a field study of smoking behaviour was conducted with 59 adult smokers, who used a portable device to measure smoking topography over the course of 3 one-week trials. Participants were asked to smoke their usual ?regular-yield? brand through the device for Trial 1 and again, 6 weeks later, at Trial 2. Half the subjects were then randomly assigned to smoke a ?low-yield? brand for Trial 3. The smoke intake and constituent yield of each brand was then tested under five testing protocols: ISO, Massachusetts, Canadian, a Compensatory protocol, and a Human Mimic regime. Participants also completed self-report measures of puffing behaviour at recruitment and immediately following each of the three one-week smoking trials. Several of these self-report measures were subsequently included in the Waves 2 and 3 of the International Tobacco Control Policy Evaluation (ITC) Survey?an international cohort survey of adult smokers from Canada, Australia, the US, and the UK. <br /><br /> The results of the field study indicate a high degree of stability in puffing behaviour within the same smoker over time, but considerable variability between smokers, including those smoking the same brand. Puffing behaviour was strongly associated with cotinine levels, particularly when included in an interaction term with cigarettes per day (<em>Part r</em> = . 50, <em>p</em><. 001). Smokers who were switched to a ?low-yield? cigarette increased their total smoke intake per cigarette by 40% (<em>p</em>=. 007), with no significant change in their in salivary cotinine levels. <br /><br /> The results indicate systematic differences between human puffing behaviour and the puffing regimes used by machine testing protocols. The puffing behaviour observed among participants during the one-week smoking trials was significantly more intense than the puffing parameters of the ISO and Compensatory testing regimes. When cigarette brands were machine tested using participants? actual puffing behaviour, the results suggest that participants ingested two to four times the level of tar, nicotine, and carbon monoxide indicated by the ISO regime, and twice the amounts generated by the Compensatory regime for ?regular-yield? brands. The Canadian and Massachusetts regimes produced yields much closer to the ?Human Mimic? yields, although nowhere near a maximum or intense standard, as they were designed to do. Only the nicotine yields from the Human Mimic regime were correlated with measures of nicotine uptake among smokers, and only moderately so (<em>Part r</em> = . 31, <em>p</em>=. 02). <br /><br /> Self-report measures of puffing behaviour collected during the field study were moderately correlated with physiological measures of puffing and exposure. Self-report measures of puff depth and puff number showed some promise as predictors of salivary cotinine, although the results are characterized by inconsistencies across models. The self-report measures included in the ITC survey were only weakly associated with age and cigarettes per day, with modest between-country differences. <br /><br /> Overall, this research highlights the importance of puffing behaviour as a determinant of smoke exposure, and provides strong evidence of compensatory smoking for ?low-yield? brands. The findings also highlight the variability in human smoking behaviour and the limitations associated with machine testing protocols. Perhaps most important, the findings underscore the immediate need to revise the ISO protocol, which systematically underestimates smoking behaviour among humans and exaggerates differences between cigarette brands.

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The objective of this work is to investigate the influence of hot rolling process on the mechanical properties of AA 5052 aluminum alloy. Hot-rolled band fabricated by tandem mill (hot-band A) will be compared with that fabricated by reverse mill hot-band C). Optical microscopic observations revealed that hot-band A has a uniform microstructure throughout the thickness, while hot-band C exhibits non-uniform microstructure, fine grains near the surface and coarser grains in the center. Both hot-bands were subjected to cold-rolling and annealing to O-temper. Two annealing processes were used: (a) annealing in 500oC salt bath, which may simulate the high heating rate of continuous annealing line (CAL), and (b) annealing in 320oC conventional air furnace with heating rate of 30oC/h, which may simulate the slow heating rate of batch-type annealing. In general, both materials annealed in 320oC air furnace exhibit higher yield strength than those annealed in 500oC salt bath do, however, both materials exhibit better tensile ductility after annealed in 500oC salt bath as compared with those annealed in 320oC air furnace.TEM examinations indicated that the cold-rolled sheet after annealing in 320oC air furnace contains larger number of precipitates comparing with its 500oC salt bath annealed counterpart. This observation may account for the higher yield strength of cold-rolled sheet annealed in 320oC air furnace. After cold-rolling and annealing in 320oC air furnace, the material C shows higher yield strength than the material A does. However, after annealing in 500oC salt bath, both materials have similar yield strength. XRD pole-figure analysis indicated that hot-band A exhibited stronger texture than hot-band C did. The texture intensity for both materials decreased considerably after cold-rolling and annealing. Orientation image mapping (OIM) obtained by EBSD (electron backscattered diffraction) analysis indicated that the grain boundaries in both materials after cold-rolling and annealing were mainly high angle boundaries, and the 500oC salt bath annealed specimens have more equiaxed grain shape as compared with the 320oC air furnace annealed specimens.

Three experiments were conducted to evaluate the impacts of removing antibiotic growth promoters (AGP) on broiler performance and yield and to evaluate alternative products as potential replacements. In experiment one, approximately 552,000 broilers were reared in four solid-wall, tunnel ventilated houses that were divided into two paired-house facilities, each assigned one of two dietary treatments. The treated group received basal diets containing salinomycin (SAL), roxarsone (ROX) and AGP, while the control group received the same diets without ROX and AGP. Removal of ROX and AGP had no affect on average body weight and feed efficiency, while livability was significantly affected negatively by the removal of ROX and AGP. Tender, wing, drum and percentage of total white meat showed significant improvements in yield during the study, while all other parts were not affected by removal of ROX and AGP. In experiment two, an investigation was conducted to evaluate the effects on performance from feeding Bacillus subtilis spores (Gallipro®, Chr Hansen A/S, Denmark), as a direct-fed microbial additive, to commercial broiler chickens. Birds were divided among two paired-house facilities. The treatment group received basal diets supplemented with B. subtilis spores, while the control group was fed the same basal diets containing an AGP. Feed conversion ratio was significantly lower for the treatment group, while average body weight, coccidiosis lesion scores, and footpad scores were not affected by the treatments. In experiment three, 6,000 broiler chickens were equally divided among four treatment groups and reared to 49 d to determine the effectiveness mannan oligosaccharides (MOS, Bio-Mos®, Alltech, Nicholasville, Kentucky, USA) as an alternative for an AGP program and MOS plus Natustat™ (NAT, Alltech, Nicholasville, Kentucky, USA) as an alternative to an enteric health program (AGP+anticoccidial drug). Average body weight for the control (CON) and antibiotic (ANT) groups was significantly different from the MOS+NAT group, but not the MOS group. Carcass front half, carcass hind half, frame and skin yields were improved for all treatments when compared to the MOS+NAT group. Conversely, percent total white meat yield was improved with the inclusion of MOS when compared to the ANT group. The findings of this research suggest that the removal of AGP from the diets of commercial broiler chickens does not affect the performance and yield of the birds over a one year production period. Furthermore, B. subtilis spores and mannan oligosaccharides provide acceptable alternatives to an AGP program.

Yield analysis is a critical step in memory designs considering a variety of performance constraints. Traditional circuit level Monte-Carlo simulations for yield estimation of Static Random Access Memory (SRAM) cell is quite time consuming due to their characteristic of low failure rate, while statistical method of yield sensitivity analysis is meaningful for its high efficiency. This thesis proposes a novel statistical model to conduct yield sensitivity prediction on SRAM cells at the simulation level, which excels regular circuit simulations in a significant runtime speedup. Based on the theory of Kriging method that is widely used in geostatistics, we develop a series of statistical model building and updating strategies to obtain satisfactory accuracy and efficiency in SRAM yield sensitivity analysis. Generally, this model applies to the yield and sensitivity evaluation with varying design parameters, under the constraints of most SRAM performance metric. Moreover, it is potentially suitable for any designated distribution of the process variation regardless of the sampling method.

As CMOS technologies move to sub-100nm regions, the design and verification for analog/mixed-signal circuits become more and more difficult due to the problems including the decrease of transconductance, severe gate leakage and profound mismatches. The increasing manufacturing-induced process variations and their impacts on circuit performances make the already complex circuit design even more sophisticated in the deeply scaled CMOS technologies. Given these barriers, efforts are needed to ensure the circuits are robust and optimized with consideration of parametric variations. This research presents innovative computer-aided design approaches to address three such problems: (1) large analog/mixed-signal performance modeling under process variations, (2) yield-aware optimization for complex analog/mixedsignal systems and (3) on-chip test scheme development to detect and compensate parametric failures. The first problem focus on the efficient circuit performance evaluation with consideration of process variations which serves as the baseline for robust analog circuit design. We propose statistical performance modeling methods for two popular types of complex analog/mixed-signal circuits including Sigma-Delta ADCs and charge-pump PLLs. A more general performance modeling is achieved by employing a geostatistics motivated performance model (Kriging model), which is accurate and efficient for capturing stand-alone analog circuit block performances. Based on the generated block-level performance models, we can solve the more challenging problem of yield-aware system optimization for large analog/mixed-signal systems. Multi-yield pareto fronts are utilized in the hierarchical optimization framework so that the statistical optimal solutions can be achieved efficiently for the systems. We further look into on-chip design-for-test (DFT) circuits in analog systems and solve the problems of linearity test in ADCs and DFT scheme optimization in charge-pump PLLs. Finally a design example of digital intensive PLL is presented to illustrate the practical applications of the modeling, optimization and testing approaches for large analog/mixed-signal systems.

Water availability has been of great concern in the State of Texas and many other places worldwide. During 1997-2003, pursuant to the 1997 Senate Bill 1, the Texas Commission on Environmental Quality (TCEQ), its partner agencies, and contractors developed a Water Availability Modeling (WAM) System based on the Water Rights Analysis Package (WRAP) model, developed at Texas A&M University. WAM has been widely applied in the State of Texas and because of its convenience, applications, and capabilities, it is planned to be implemented in other States and Countries. This thesis addresses different aspects of WAM, including conditional reliability modeling, firm yield analysis following classic and recently developed methodologies, evaluating the impact of different considerations on reliability analyses, simplification of complex WAM datasets and the display of WRAP results into ArcMap. Conditional reliability modeling evaluates short term diversion/storage reliabilities based on an initial storage level. WRAP-CON has been evaluated and improved, in addition a new modeling methodology has been developed, in which probabilities of occurrence for each hydrologic sequence is based on the relationship between storage and future flows. Recently developed WRAP capabilities have been evaluated, providing users new tools and increased flexibility. Some of these improvements are firm yield analysis, cycling and dual simulation. In addition to improved software, guidelines have also been developed, including a set to simplify extremely large WAM datasets, while maintaining the effect of all the other water rights in a basin.

This research develops yield and reliability models for fault-tolerant semiconductor integrated circuits and develops optimization algorithms that can be directly applied to these models. Since defects cause failures in microelectronics systems, accurate yield and reliability models considering these defects as well as optimization techniques determining efficient defect-tolerant schemes are essential in semiconductor manufacturing and nanomanufacturing to ensure manufacturability and productivity. The defect-based yield model considers various types of failures, fault-tolerant schemes such as hierarchical redundancy and error correcting code, and burn-in effects, simultaneously. The reliability model counts on carry-over single-cell failures accompanied by the failure rate of the semiconductor integrated circuits under the assumption of an error correcting code policy. The redundancy allocation problem, which seeks to &#64257;nd an optimal allocation of redundancy that maximizes system reliability, is one of the representative problems in reliability optimization. The problem is typically formulated as a nonconvex integer nonlinear programming problem that is nonseparable and coherent. Two iterative heuristics, tree and scanning heuristics, and variants are studied to obtain local optima and a branch-and-bound algorithm is proposed to &#64257;nd the global optimum for redundancy allocation problems. The proposed algorithms engage a multiple-search paths strategy to accelerate efficiency. Experimental results of these algorithms indicate that they are superior to the existing algorithms in terms of computation time and solution quality. An example of memory semiconductor integrated circuits is presented to show the applicability of both the yield and reliability models and the optimization algorithms to fault-tolerant semiconductor integrated circuits.

Genetic gain studies in the past have been used to evaluate the historical improvement of different traits and give insight into what magnitudes of gain might be possible in the future. Additionally, they have been carried out to defend the role of genetics during periods of stagnant or decreasing yield trends. This study was conducted over a 2-year period (2003 and 2004) and included nine current or obsolete cotton (Gossypium hirsutum L.) cultivars grown in 5 plant densities designed to evaluate varying levels of interplant competition. Plant densities were single plant culture with plants spaced 3m x 3m, 2m x 2m, 1m x 1m, 1m x 0.3m, and two commercial populations with plants spaced 1m x 0.1m. Results were analyzed for each trait to determine whether genetic gains are interrelated with tolerance to interplant competition or strictly under genetic control. The rates of genetic gain for lint yield were highest in the 1m x 0.1m, 1m x 0.3m, and 1m x 1m treatment with slopes of 8.7, 8.2, and 7.1 kg ha-1 yr-1 respectively. The slopes were each significantly smaller in the 2m x 2m and 3m x 3m spaced populations with gains of 3.6 and 1.5 kg ha-1 yr-1 respectively, implying that for lint yield, genetic gains have been made for tolerance to interplant competition. Similarly, modern maize hybrids only out perform obsolete hybrids at higher plant densities. Genetic gain for lint yield, fiber length, fiber strength, and fiber micronaire made in the context of tolerance to interplant competition is due in large part to the excellent performance of Deltapine 491 (2002) at higher plant populations.

The application of popular image processing and classification algorithms, including agglomerative clustering and neural networks, is explored for the purpose of grouping semiconductor wafer defect map patterns. Challenges such as overlapping pattern separation, wafer rotation, and false data removal are examined and solutions proposed. After grouping, wafer processing history is used to automatically determine the most likely source of the issue. Results are provided that indicate these methods hold promise for wafer analysis applications. / text