Cheng, Yuk Lap. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 64-67). / Abstracts in English and Chinese; appendix and questionnaire also in Chinese. / ACKNOWLEDGEMENT --- p.I / ABSTRACT --- p.II / TABLE OF CONTENT --- p.V / LIST OF FIGURES --- p.VII / LIST OF TABLES --- p.VIII / Chapter I --- INTRODUCTION --- p.1 / Background --- p.1 / Statement of Problem --- p.3 / Hypothesis --- p.3 / Significance of Study --- p.4 / Theoretical Contribution --- p.4 / Practical Contribution --- p.4 / Operational Definition --- p.5 / Chapter II --- REVIEW OF LITERATURE --- p.7 / Problem of poor fitting --- p.7 / Common foot problem --- p.10 / Definition of fit --- p.11 / Recommendation of shoe fit --- p.13 / Sizing --- p.13 / Pressure distribution --- p.14 / Subjective fit --- p.15 / Footwear Comfort --- p.15 / Chapter III --- METHODOLOGY --- p.18 / Design --- p.18 / Subject --- p.18 / Instrumentation --- p.18 / Fit questionnaire --- p.18 / Foot scanner --- p.19 / Pressure sensors --- p.19 / Running shoes --- p.20 / Shoe lasts --- p.20 / Procedure --- p.21 / Foot scanning --- p.22 / Fit questionnaire --- p.24 / Set up --- p.24 / Reliability test --- p.25 / Pressure measurement --- p.25 / Data Reduction --- p.29 / Foot scanning --- p.29 / Fit questionnaire --- p.29 / Video --- p.29 / Pressure distribution --- p.30 / Data Analysis --- p.30 / Chapter IV --- RESULT --- p.32 / Subject Detail --- p.32 / Questionnaire --- p.32 / Fit Rating --- p.37 / Size Difference --- p.39 / Pressure Distribution --- p.43 / Regression --- p.46 / Chapter V --- DISCUSSION --- p.52 / Subjective fit rating --- p.52 / Reliability of the fit questionnaire --- p.52 / Fit rating --- p.53 / Size --- p.54 / Foot shape --- p.54 / Dimensional Difference --- p.54 / Correlation with subjective fit --- p.55 / Pressure --- p.58 / Dimensional Difference and Pressure --- p.59 / Subjective fit and objective measures --- p.60 / Limitation --- p.61 / Future Direction --- p.62 / Chapter VI --- CONCLUSION --- p.63 / Chapter VII --- REFERENCE --- p.64 / APPENDIX / Appendix A -Explanation of study --- p.68 / Appendix B - Informed consent --- p.69 / Appendix C - Footwear fit questionnaire --- p.70 / Appendix D -Explanations of fit questionnaire --- p.72 / Appendix E - Anthropometric information of the subjects --- p.73 / Appendix F - Fit rating --- p.74 / Appendix G - Foot dimensions of the subjects --- p.89 / Appendix H - Foot - last size difference of each subject --- p.90 / Appendix I - Guilford's suggested interpretation for value of r --- p.92

The present journal article formatted dissertation assessed the characteristics of effect sizes of commonly used statistical techniques. In the first study, the author examined the American Educational Research Journal (AERJ) and select American Psychological Association (APA) and American Counseling Association (ACA) journals to provide an historical account and synthesis of which statistical techniques were most prevalent in the fields of education and psychology. These reviews represented a total of 17,698 techniques recorded from 12,012 articles. Findings point to a general decrease in the use of the tvtest and ANOVA/ANCOVA and a general increase in the use of regression and factor/cluster analysis. In the second study, the author compared the efficacy of one Pearson r2 and seven multiple R2 correction formulas for the Pearson r2. The author computed adjustment bias and precision under 108 conditions (6 population p2 values, 3 shape conditions and 6 sample size conditions). The Pratt and the Olkin-Pratt Extended formulas more consistently provided unbiased estimates across sample sizes, p2 values and the shape conditions investigated. In the third study, the author evaluated the robustness of estimates of practical significance (n2, e2 and w2) in one-way between subjects univariate ANOVA. There were 360 simulation conditions (5 population Cohen's d values, 4 group proportion ratios, 3 shape conditions, 3 variance conditions, and 2 total sample size conditions) for each of three group configurations (2, 3 and 4 groups). Three indices of practical significance (n2, e2, w2) and two indices of statistical significance (Type I error and power) were computed for each of the 5,400, 000 (5,000 replications x 360 simulation conditions x 3 group configurations). Simulation findings for n2 under heterogeneous variance conditions indicated that for the k=2 and k=3 condition Cohen's d values up to 0.2 (up to 0.5 for k=4) tend to produce overestimated population n2 values. Under heterogeneous variance conditions for e2 and w2 at Cohen's d = 0.0 and 0.2, the negative variance pairing overestimated and the positive variance pairing underestimated the parameter n2 but at Cohen's d greater than or equal to 0.5, both the positive and negative variance conditions resulted in underestimated parameter n2 values.

Modelling interactions between genes and their regulators is fundamental to understanding how, for example a disease progresses, or the impact of inserting a synthetic circuit into a cell. We use an existing method to infer regulatory networks under multiple conditions: the Joint Graphical Lasso (JGL), a shrinkage based Gaussian graphical model. We apply this method to two data sets: one, a publicly available set of microarray experiments perturbing the gram-positive bacteria Bacillus subtilis under multiple experimental conditions; the second, a set of RNA-seq samples of Mouse (Mus musculus) embryonic fibroblasts (MEFs) infected with different strains of the parasite Toxoplasma gondii. In both cases we infer a subset of the regulatory networks using relatively small sample sizes. For the Bacillus subtilis analysis we focused on the use of these regulatory networks in synthetic biology and found examples of transcriptional units active only under a subset of conditions, this information can be useful when designing circuits to have condition dependent behaviour. We developed methods for large network decomposition that made use of the condition information and showed a greater specificity of identifying single transcriptional units from the larger network using our method. Through annotating these results with known information we were able to identify novel connections and found supporting evidence for a selection of these from publicly available experimental results. Biological data collection is typically expensive and due to the relatively small sample sizes of our MEF data set we developed a novel empirical Bayes method for reducing the false discovery rate when estimating block diagonal covariance matrices. Using these methods we were able to infer regulatory networks for the host infected with either the ME49 or RH strain of the parasite. This enabled the identification of known and novel regulatory mechanisms. The Toxoplasma gondii parasite has shown to subvert host function using similar mechanisms as cancers and through our analysis we were able to identify genes, networks and ontologies associated with cancer, including connections that have not previously been associated with T. gondii infection. Finally a Shiny application was developed as an online resource giving access to the Bacillus subtilis inferred networks with interactive methods for exploring the networks including expansion of sub networks and large network decomposition.

Master of Science / Department of Chemistry / Emily McLaurin / Quantum dots (QDs) are novel semiconductors of interest for applications because of their special tunable properties. Among the many types of QDs, InP QDs attract attention because they do not have toxic-heavy-metal elements such as Cd or Pb. Charge-transfer (CT) is important in applications of InP QDs. CT consists of two or more molecules and some of them donate electrons and others accept those electrons. An understanding of CT between QDs with tetracyanoquinodimethane (TCNQ) is important for applications of QDs in photovoltaic and photocatalytic materials. TCNQ is an organic electron acceptor and CT complexes of TCNQ exhibit metallic electric conductivity. Previous research about CT between QDs and TCNQ examined PbS and CdSe QDs, but toxic-heavy-metals limit future application of these materials. So, it is important to research CT between InP QDs and TCNQ. This thesis examines how the amount of InP QDs (QD:TCNQ ratio) and diameters of InP QDs affect the CT between InP QDs and TCNQ. In this thesis, InP QDs are synthesized by a microwave-assisted ionic liquid (MAIL) method and InP QDs of different sizes are isolated using size-selective precipitation. Then, TCNQ-InP QD solutions are prepared with different ratios, with and without light, and with InP QDs of different sizes. These InP QDs and InP QDs-TCNQ samples are characterized using UV-Vis-NIR absorption, photoluminescence (PL), time-correlated single photon counting (TCSPC), and FT-IR spectroscopies. In Chapter 2, the details of synthesizing InP QDs, size selection, and preparation of different TNCQ-InP QD solutions are presented. Then, factors that affect the interaction between InP QDs and TCNQ and possible reasons for these factors are discussed. Based on calculations and experimental results, the carbon atom with the biggest amount of positive charge in TCNQ and phosphorous in InP QDs are likely the acceptor and donor, respectively. CT is affected by the amount of InP QDs in solution, and more InP QDs will reduce more TCNQ. The CT is also affected by the size of the InP QDs and enhanced by light.

The purpose of this paper is to calculate a method of estimating minimum dairy farm sizes for specific income levels. A survey of a sample of Utah dairy farmers was conducted to obtain data to calculate a long run average cost schedule. Dairy farmers who had just recently built new facilities and with varying sized herds were interviewed. Individual costs were studied to establish their effect on the long run average cost curve. Different average revenue curves for varying prices and production levels were used to establish minimum cow numbers needed to give s pecified incomes and growth potentials. Marginal analysis was used to establish the most efficient methods of growth, i.e., cow numbers, herd production and blend price.

<p> Drop sizes were measured photographically for water in kerosene and for water in methyl isobutyl ketone, at varying flow rates and levels of agitation. At high levels of agitation the data could be represented very approximately by the well known relationship of Hinze and others: d32= CONS(σ0.6)/ρ0.6E0.44) (where d32=mean drop diameter, σ= interfacial tension, p̂= mean density and E= power input per unit mass). However this equation was not satisfactory at low levels of agitation, and an alternative equation based on dimensional analysis and including effects of density difference and gravity has been proposed. Qualitative observations regarding drop formation, holdup and various operating phenomena are made. </p> / Thesis / Master of Engineering (MEngr)

No description available.

A large percentage of the total annual lumber production in the U.S.A is consumed by the pallet industry. However, standardized design procedures for these products have only recently been developed. A four-year cooperative pallet research, development and application program was undertaken by the National Wooden Pallet and Container Association, Virginia Polytechnic Institute and State University, and the U.S Forest Service. This research is directed towards developing standardized design procedures for both stringer and block-type pallets. Phase I dealt exclusively with stringer-type pallets while Phase II expands the scope to include block-type pallets. The objective of this work was to develop methods to analyze the effects of loads, supports and geometry on the response of block-style pallets. The developed analysis procedures are based on matrix structural analysis methods. A quarter symmetric 3-dimensional model is used to simulate pallets racked across the stringerboards (RAS) and a half symmetric 2-dimensional model is used for the racked across deckboards (RAD) and sling support modes. Both models are used in the stack condition. Deckboard/stringerboard joints are modeled as a single spring in the RAS model and the deck-block joint in both the RAS and RAD models are modeled as a framework of rigidly connected members and five springs (2 rotational and three axial). The procedure has the capability to handle both uniformly distributed and line loads in rack, stack, or sling support modes, and a wide variety of commonly used geometries. The developed analysis methodology is presented in computerized form and will provide the user a means of communication with pallet manufacturers for defining expected performance. / M.S.

Pallets are abundant throughout the supply chain with 2.6 billion pallets in circulation in the United States (Freedonia, 2015). More than 93% of goods are transported in the form of a palletized unit load (White and Hamner, 2005). Plastics are the second most commonly used material to manufacture these shipping platforms (Bond, 2018), yet there is a lack of information to be found about the plastic pallet industry's characteristics. Therefore, the main objective of this research was to investigate the status of the plastic pallet industry in the United States in 2018. To gather information, an online survey was conducted. It was sent out electronically to twenty-six plastic pallet manufacturers with response rate of 54%. The results have shown that almost 16 million plastic pallets were manufactured in the United States by the survey respondents in 2018. Of these, over 80% were multiple use pallets and about 80% were standard size. Most plastic pallets that were manufactured by the respondents were made with high pressure injection molding (63%) using high density polyethylene (HDPE) resin (68%). Close to 50% of the pallets had reinforcement beams and 12% had fiberglass reinforcement. Although most plastic pallets were manufactured using virgin resin, 34% were manufactured from recycled resin which reduces the cost and increases the sustainability of the plastic pallet. In addition, this study has shown that most of the plastic pallets manufactured in 2018 had no flame-retardant additives since only 20% from the respondents indicated that their pallets were Underwriter Laboratories (UL) or Factory Mutual (FM) certified. Based on these results, a new survey format and framework is designed with a recommendation to conduct it in every five years in order to further explore the state and market trends of the plastic pallet industry. / Master of Science / Pallets are abundant throughout the supply chain with 2.6 billion pallets in circulation in the United States (Freedonia, 2015). In 2005 it is estimated that more than 93% of goods are transported in the form of a palletized unit load (White and Hamner, 2005). Plastics are the second most commonly used material to manufacture these shipping platforms (Bond, 2018), yet there is a lack of information to be found about the plastic pallet industry's characteristics. Therefore, the main objective of this research was to investigate the status of the plastic pallet industry in the United States in 2018. To gather information, an online survey was conducted. It was sent out electronically to twenty-six plastic pallet manufacturers with response rate of 54%. The results have shown that almost 16 million plastic pallets were manufactured in the United States by respondents in 2018. Of these, over 80% were multiple use pallets and about 80% were standard size (48 in. x 40 in., 45 in. x48 in.). Most plastic pallets manufactured by the respondents were made with high pressure injection molding (63%) using high density polyethylene (HDPE) resin (68%). Close to 50% of the pallets had reinforcement beams and 12% had fiberglass reinforcement. Although most plastic pallets were manufactured using virgin resin, 34% were manufactured from recycled resin which reduces the cost and increases the sustainability of the plastic pallet. In addition, this study has shown that most of the plastic pallets manufactured in 2018 had no flame-retardant additives since only 20% from the respondents indicated that their pallets were Underwriter Laboratories (UL) or Factory Mutual (FM) certified. Based on these results, a new survey format and framework is designed with a recommendation to conduct it in every five years in order to further explore the state and market trends of the plastic pallet industry.

Current practice for sample size computations in clinical trials is largely based on frequentist or classical methods. These methods have the drawback of requiring a point estimate of the variance of treatment effect and are based on arbitrary settings of type I and II errors. They also do not directly address the question of achieving the best balance between the costs of the trial and the possible benefits by using a new medical treatment, and fail to consider the important fact that the number of users depends on evidence for improvement compared with the current treatment. A novel Bayesian approach, Behavioral Bayes (or BeBay for short) (Gittins and Pezeshk, 2000a,b, 2002a,b; Pezeshk, 2003), assumes that the number of patients switching to the new treatment depends on the strength of the evidence which is provided by clinical trials, and takes a value between zero and the number of potential patients in the country. The better a new treatment, the more patients switch to it and the more the resulting benefit. The model defines the optimal sample size to be the sample size that maximises the expected net benefit resulting from a clinical trial. Gittins and Pezeshk use a simple form of benefit function for paired comparisons between two medical treatments and assume that the variance of the efficacy is known. The research in this thesis generalises these original conditions by introducing a logistic benefit function to take account of differences in efficacy and safety between two drugs. The model is also extended to the more general cases of unpaired comparisons and unknown variance. The expected net benefit defined by Gittins and Pezeshk is based on the efficacy of the new drug only. It does not consider the incidence of adverse reactions and their effect on patients’ preferences. Here we include the costs of treating adverse reactions and calculate the total benefit in terms of how much the new drug can reduce societal expenditure. We describe how our model may be used for the design of phase III clinical trials, cluster randomised clinical trials and bridging studies. This is done in some detail and using illustrative examples based on published studies. For phase III trials we allow the possibility of unequal treatment group sizes, which often occur in practice. Bridging studies are those carried out to extend the range of applicability of an established drug, for example to new ethnic groups. Throughout the objective of our procedures is to optimise the costbenefit in terms of national health-care. BeBay is the leading methodology for determining sample sizes on this basis. It explicitly takes account of the roles of three decision makers, namely patients and doctors, pharmaceutical companies and the health authority.