Documenting the extent of cellular diversity is a critical step in defining the functional organization of the nervous system. In this context, we sought to develop statistical methods capable of revealing underlying cellular diversity given incomplete data sampling - a common problem in biological systems, where complete descriptions of cellular characteristics are rarely available. We devised a sparse Bayesian framework that infers cell type diversity from partial or incomplete transcription factor expression data. This framework appropriately handles estimation uncertainty, can incorporate multiple cellular characteristics, and can be used to optimize experimental design. We applied this framework to characterize a cardinal inhibitory population in the spinal cord. Animals generate movement by engaging spinal circuits that direct precise sequences of muscle contraction, but the identity and organizational logic of local interneurons that lie at the core of these circuits remain unresolved. By using our Sparse Bayesian approach, we showed that V1 interneurons, a major inhibitory population that controls motor output, fractionate into diverse subsets on the basis of the expression of nineteen transcription factors. Transcriptionally defined subsets exhibit highly structured spatial distributions with mediolateral and dorsoventral positional biases. These distinctions in settling position are largely predictive of patterns of input from sensory and motor neurons, arguing that settling position is a determinant of inhibitory microcircuit organization. Finally, we extensively validated inferred cell types by direct experimental measurement and then, extend our Bayesian framework to full transcriptome technologies. Together, these findings provide insight into the diversity and organizational logic through which inhibitory microcircuits shape motor output.

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with hundreds of human traits. Yet the common variant model tested by traditional GWAS only provides an incomplete explanation for the known genetic heritability of many traits. Many divergent methods have been proposed to address the shortcomings of GWAS, including most notably the extension of association methods into rarer variants through whole exome and whole genome sequencing. GWAS methods feature numerous simplifications designed for feasibility and ease of use, as opposed to statistical rigor. Furthermore, no systematic quantification of the performance of GWAS across all traits exists. Beyond improving the utility of data that already exist, a more thorough understanding of the performance of GWAS on common variants may elucidate flaws not in the method but rather in its implementation, which may pose a continued or growing threat to the utility of rare variant association studies now underway. This thesis focuses on systematic evaluation and incremental improvement of GWAS modeling. We collect a rich dataset containing standardized association results from all GWAS conducted on quantitative human traits, finding that while the majority of published significant results in the field do not disclose sufficient information to determine whether the results are actually valid, those that do replicate precisely in concordance with their statistical power when conducted in samples of similar ancestry and reporting accurate per-locus sample sizes. We then look to the inability of effectively all existing association methods to handle missingness in genetic data, and show that adapting missingness theory from statistics can both increase power and provide a flexible framework for extending most existing tools with minimal effort. We finally undertake novel variant association in a schizophrenia cohort from a bottleneck population. We find that the study itself is confounded by nonrandom population sampling and identity-by-descent, manifesting as batch effects correlated with outcome that remain in novel variants after all sample-wide quality control. On the whole, these results emphasize both the past and present utility and reliability of the GWAS model, as well as the extent to which lessons from the GWAS era must inform genetic studies moving forward.

Traditionally, cancer epidemiologists have investigated the causes of disease under the premise that patients with a certain site of disease can be treated as a single entity. Then risk factors associated with the disease are identified through case-control or cohort studies for the disease as a whole. However, with the rise of molecular and genomic profiling, in recent years biologic subtypes have increasingly been identified. Once subtypes are known, it is natural to ask the question of whether they share a common etiology, or in fact arise from distinct sets of risk factors, a concept known as etiologic heterogeneity. This dissertation seeks to evaluate methods for the study of etiologic heterogeneity in the context of cancer research and with a focus on methods for case-control studies. First, a number of existing regression-based methods for the study of etiologic heterogeneity in the context of pre-defined subtypes are compared using a data example and simulation studies. This work found that a standard polytomous logistic regression approach performs at least as well as more complex methods, and is easy to implement in standard software. Next, simulation studies investigate the statistical properties of an approach that combines the search for the most etiologically distinct subtype solution from high dimensional tumor marker data with estimation of risk factor effects. The method performs well when appropriate up-front selection of tumor markers is performed, even when there is confounding structure or high-dimensional noise. And finally, an application to a breast cancer case-control study demonstrates the usefulness of the novel clustering approach to identify a more risk heterogeneous class solution in breast cancer based on a panel of gene expression data and known risk factors.

Yip Kin Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 101-104). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- The Distribution of Fluctuations in Financial Data --- p.5 / Chapter 2.1 --- Empirical Statistics --- p.5 / Chapter 2.2 --- Data analyzed --- p.8 / Chapter 2.3 --- Levy Distribution --- p.10 / Chapter 2.4 --- Returns Distribution and Scaling Properties --- p.12 / Chapter 2.5 --- Volatility Clustering --- p.19 / Chapter 2.6 --- Conclusion --- p.21 / Chapter 3 --- Models of Herd behaviour in Financial Markets --- p.22 / Chapter 3.1 --- Cont and Bouchaud's model --- p.22 / Chapter 3.2 --- The Model of Egiuluz and Zimmerman --- p.24 / Chapter 3.3 --- EZ Model with Size-Dependent Dissociation Rates --- p.28 / Chapter 3.4 --- Democratic and Dictatorship Self-Organized Model --- p.31 / Chapter 3.5 --- Effect of Size-Dependent Fragmentation and Coagulation Prob- abilities --- p.33 / Chapter 3.6 --- Extensions of EZ model --- p.35 / Chapter 3.7 --- Conclusion --- p.39 / Chapter 4 --- Review on the Minority Game(MG) --- p.42 / Chapter 4.1 --- The Model and Results --- p.42 / Chapter 4.2 --- Crowd-anticrowd Theory and Phase Transition --- p.46 / Chapter 4.3 --- Market Efficiency --- p.48 / Chapter 5 --- MG with biased strategy pool --- p.52 / Chapter 5.1 --- The Model --- p.53 / Chapter 5.2 --- Numerical Results and Discussion --- p.53 / Chapter 5.3 --- Theory: MG with Biased Strategy Pool --- p.61 / Chapter 5.4 --- Conclusion --- p.69 / Chapter 6 --- MG with Randomly Participating Agents --- p.71 / Chapter 6.1 --- The Model with One RPA --- p.71 / Chapter 6.2 --- Results for q = 0.5 --- p.72 / Chapter 6.3 --- Inefficiency and Success Rate --- p.76 / Chapter 6.4 --- Results for q ≠ 0.5 --- p.82 / Chapter 6.5 --- Many RPAs --- p.85 / Chapter 6.6 --- Conclusion --- p.86 / Chapter 7 --- A Model on Coupled Minority Games --- p.88 / Chapter 7.1 --- The Model --- p.89 / Chapter 7.2 --- Results and Discussion。 --- p.90 / Chapter 7.3 --- Conclusion --- p.95 / Chapter 8 --- Conclusion --- p.97 / Bibliography --- p.101 / Chapter A --- Solving Cluster Size distribution in EZ model --- p.105

Wong Ka Shing = 兩個二級蛋白質結構組中的氨基酸序列的統計特性 / 黃嘉誠. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 88-91). / Text in English; abstracts in English and Chinese. / Wong Ka Shing = Liang ge er ji dan bai zhi jie gou zu zhong de an ji suan xu lie de tong ji te xing / Huang Jiacheng. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Predicting tertiary structures of proteins --- p.2 / Chapter 1.2 --- Introduction to secondary structures of protein --- p.5 / Chapter 1.3 --- Prediction of secondary structural classes --- p.9 / Chapter 1.3.1 --- Multi-dimensional space representation --- p.10 / Chapter 2 --- Method of analysis --- p.12 / Chapter 2.1 --- Data sets --- p.12 / Chapter 2.2 --- Basic statistics of the data sets --- p.13 / Chapter 2.3 --- Method of analysis --- p.17 / Chapter 2.4 --- An interesting sum rule --- p.20 / Chapter 3 --- Results of analysis of C-words --- p.22 / Chapter 3.1 --- A first insight --- p.22 / Chapter 3.2 --- Distributions of 〈C(j)〉 --- p.24 / Chapter 3.2.1 --- "Comparing distributions for different m, s and secondary structural classes" --- p.29 / Chapter 3.3 --- Features of each secondary structural class --- p.33 / Chapter 3.3.1 --- C-words with the largest or the smallest values of 〈C(j)〉 in the all-a class --- p.33 / Chapter 3.3.2 --- C-words with the largest or the smallest values of 〈C(j)〉 in the all-β class --- p.35 / Chapter 4 --- Results of analysis of H-words --- p.37 / Chapter 4.1 --- 〈C(j)〉 for each H-word --- p.38 / Chapter 4.1.1 --- "When m increases, 〈C(j)〉 deviates more from 1" --- p.39 / Chapter 4.1.2 --- "When spacing parameter s is small, 〈C(j)〉 deviates more from 1" --- p.40 / Chapter 4.2 --- The mean over all possible H-words --- p.41 / Chapter 4.3 --- Comparing 〈C(j)〉 of different H-words --- p.43 / Chapter 4.3.1 --- A few plots --- p.43 / Chapter 4.3.2 --- Results --- p.44 / Chapter 4.4 --- Features of each secondary structural class --- p.47 / Chapter 4.4.1 --- A first insight --- p.47 / Chapter 4.4.2 --- The H-words with the largest values of 〈C(j)〉 in the all-α class with particular number of letter m --- p.54 / Chapter 4.4.3 --- The H-words with the smallest values of 〈C(j) in the all-α class with particular number of letter m --- p.57 / Chapter 4.4.4 --- The H-words with the largest values of 〈C(j) in the all-β class with particular number of letter m --- p.60 / Chapter 4.4.5 --- The H-words with the smallest values of 〈C(j) in the all-β class with particular number of letter m --- p.63 / Chapter 4.4.6 --- A summary --- p.66 / Chapter 4.5 --- Possible indicators to predict secondary structural class --- p.67 / Chapter 4.5.1 --- H-words with the largest values of --- p.68 / Chapter 4.5.2 --- H-words with the largest magnitude of --- p.71 / Chapter 4.5.3 --- Discussion --- p.71 / Chapter 5 --- Prediction using patterns found in H-words --- p.72 / Chapter 6 --- Conclusion --- p.86 / Bibliography --- p.88

Ma Ning. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 49-57). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.5 / Chapter 2 --- Literature Review --- p.11 / Chapter 2.1 --- Problems about Using Sibling Samples --- p.19 / Chapter 2.2 --- Difficulties with the Within-twin-pair Studies --- p.20 / Chapter 3 --- Method --- p.21 / Chapter 3.1 --- Omitted Variable Bias (Selection Effect) --- p.21 / Chapter 3.1.1 --- OLS Model --- p.21 / Chapter 3.1.2 --- Fixed-Effect Model --- p.23 / Chapter 3.1.3 --- GLS Model --- p.23 / Chapter 3.2 --- Measurement Error --- p.24 / Chapter 4 --- Data --- p.26 / Chapter 5 --- Results --- p.29 / Chapter 5.1 --- "OLS, Fixed-Effect, GLS and IV estimates" --- p.29 / Chapter 5.2 --- Important findings --- p.34 / Chapter 5.3 --- Further Results --- p.35 / Chapter 5.3.1 --- Consistency of Fixed-Effect Estimate --- p.35 / Chapter 5.3.2 --- Smoking as an Instrument for Education --- p.39 / Chapter 5.3.3 --- Symmetry Test --- p.41 / Chapter 5.3.4 --- Hausman Test --- p.44 / Chapter 5.3.5 --- Selection Bias --- p.45 / Chapter 6 --- Conclusions --- p.48 / Chapter 7 --- Bibliography --- p.49

行为学、社会学、心理学和医药学方面，结构方程模型(SEMs) 是研究有关潜在变量最常用的模型。这篇论文的目的是研究基本和高级结构方程模型的贝叶斯诊断，本文研究的结构方程模型包括非线性纺构方程模型、变换结构方程模型、二层结构方程模型和混合结构方程模型。基于对数贝叶斯因子的一阶与二阶局部影响测度是本文进行贝贝叶斯诊断的基础。局部影响测度的计算和模型参数估计是利用了蒙特卡洛(MCMC) 和扩展数据的方法。对比传统的基于极大似然的诊断，本文提出的贝叶斯诊断方法不仅能检测异常点或者影响点，而且可以诊断模型假设和先验设定的敏感性。 这些是通过对数据、模型假设和先验设定进行不同的扰动获得的 本文用大量的模拟实验来说明所提出的贝叶斯诊断方法的作用。 本文基于不同类型的结构方程模型，应用所提出的贝叶斯诊断方法于一些实际数据。 / In the behavioral, social, psychological, and medical sciences, the most widely used models in assessing latent variables are structural equation models (SEMs). This thesis aims to develop Bayesian diagnostic procedures for basic and advanced SEMs such as nonlinear SEMs, transformation SEMs, two-level SEMs, and mixture SEMs. The first- and second-order local inference measures with the objective functions defined based on the logarithm of Bayes factor are proposed to perform the Bayesian diagnostics. Markov chain Monte Carlo (MCMC) methods, along with data augmentation, are developed to compute the local influence measures and to estimate unknown model parameters. Compared with conventional maximum likelihood-based diagnostic procedures, the proposed Bayesian diagnostic approach can not only detect outliers or influential points in the observed data, but also conduct model comparison and sensitivity analysis by perturbing the data, sampling distributions, and the prior distributions of model parameters via a variety of perturbations. The empirical performances of the proposed Bayesian diagnostic procedures are revealed through extensive simulation studies. Several real-life data sets are used to illustrate the application of our proposed methodology in the context of different SEMs. / Detailed summary in vernacular field only. / Chen, Ji. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 130-135). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Structural equation models --- p.1 / Chapter 1.2 --- Bayesian diagnostics --- p.3 / Chapter 1.2.1 --- The first and second order local influence measures --- p.5 / Chapter 1.2.2 --- A simple example --- p.9 / Chapter 2 --- Bayesian diagnostics of nonlinear SEMs --- p.15 / Chapter 2.1 --- Model description --- p.16 / Chapter 2.2 --- Bayesian estimation and local inference of nonlinear SEMs --- p.17 / Chapter 2.3 --- Simulation study --- p.24 / Chapter 2.3.1 --- Simulation study 1 --- p.24 / Chapter 2.3.2 --- Simulation study 2 --- p.25 / Chapter 2.3.3 --- Simulation study 3 --- p.27 / Chapter 2.4 --- Application: A study of kidney disease for type 2 diabetic patients --- p.29 / Chapter 3 --- Bayesian diagnostics of transformation SEMs --- p.40 / Chapter 3.1 --- Model description --- p.41 / Chapter 3.2 --- Bayesian estimation and local inference of the transformation SEMs --- p.44 / Chapter 3.3 --- Simulation study --- p.54 / Chapter 3.3.1 --- Simulation study 1 --- p.54 / Chapter 3.3.2 --- Simulation study 2 --- p.56 / Chapter 3.4 --- Application: A study on the risk factors of osteoporotic fracture in older people --- p.58 / Chapter 4 --- Bayesian diagnostics of two-level SEMs --- p.73 / Chapter 4.1 --- Model description --- p.74 / Chapter 4.2 --- Bayesian estimation and local inference of two-level SEMs --- p.75 / Chapter 4.3 --- Simulation study --- p.88 / Chapter 4.4 --- Application: A study of AIDS data --- p.91 / Chapter 5 --- Bayesian diagnostics of mixture SEMs --- p.106 / Chapter 5.1 --- Model description --- p.107 / Chapter 5.2 --- Bayesian estimation and local inference ofmixture SEMs --- p.108 / Chapter 5.3 --- Simulation study --- p.116 / Chapter 5.3.1 --- Simulation study 1 --- p.116 / Chapter 5.3.2 --- Simulation study 2 --- p.118 / Chapter 6 --- Conclusion --- p.126 / Bibliography --- p.130 / Chapter A --- Proof of Theorem 1.1 and 1.2 --- p.136 / Chapter B --- Full conditional distributions of the nonlinear SEM --- p.138 / Chapter C --- Full conditional distributions of the transformation SEM --- p.141 / Chapter D --- Full conditional distributions of the two-level SEM --- p.144 / Chapter E --- AIDS preventative intervention data --- p.150 / Chapter F --- Permutation sampler in the mixture SEM --- p.152 / Chapter G --- Full conditional distributions of the mixture SEM --- p.153

Keywords: Non-inferiority Test, Bootstrap, Misclassification, Partially Validated Data. / Moreover, misclassification is frequently encountered in collecting ordinal categorical data. We also consider the non-inferiority test based on the data with misclassification. We have explored two different approaches. The first approach can be applied when misclassification probabilities are known or can be calibrated. The second approach deals with the case when we have partially validated data that provide the information on misclassification. The proposed approaches have wide applications that are not confined to tests in medical research. We design a substantive study to illustrate the practicality and applicability of the proposed approaches. / When a new treatment comes out, it is likely to find benefits of the new one, such as fewer side effects, greater convenience of employment, or lower cost in terms of money and time. Therefore, the more appropriate research question is whether the new one is non-inferior or equivalent to, but not necessarily superior to the reference treatment. Consequently, the non-inferiority test or equivalence test is widely used in medical research, which is oriented towards showing that the difference of effect between the two treatments probably lies in a tolerance interval with the pre-defined lower or upper bounds. In this thesis, we consider non-inferiority tests when the data are ordinal categorical. In particular, we are interested in correlated data. We will develop non-inferiority testing procedures for data that are obtained by the paired design and three-armed design. We take advantage of a latent normal distribution approach to model ordinal categorical data. / Han, Yuanyuan. / Adviser: Poon Wai-Yin. / Source: Dissertation Abstracts International, Volume: 73-06, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 114-117). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Basic technologies for fingerprint feature extraction and matching have been improved to such a stage that they can be embedded into commercial Automatic Fingerprint Verification Systems (AFVSs). However, the reliability of AFVSs has kept attracting concerns from the society since AFVSs do fail occasionally due to difficulties like problematic fingers, changing environments, and malicious attacks. Furthermore, the absence of a solid theoretical foundation for evaluating AFVSs prevents these failures from been predicted and evaluated. Under the traditional empirical AFVS evaluation framework, repeated verification experiments, which can be very time consuming, have to be performed to test whether an update to an AFVS can really lead to an upgrade in its performance. Also, empirical verification results are often unable to provide deeper understanding of AFVSs. To solve these problems, we propose a novel statistical evaluation model for minutiae-based AFVSs based on the understanding of fingerprint minutiae patterns. This model can predict the verification performance metrics as well as their confidence intervals. The analytical power of our evaluation model, which makes it superior to empirical evaluation methods, can assist system developers to upgrade their AFVSs purposefully. Also, our model can facilitate the theoretical analysis of the advantages and disadvantages of various fingerprint verification techniques. We verify our claims through different and extensive experiments. / Chen, Jiansheng. / "November 2006." / Adviser: Yiu-Sang Moon. / Source: Dissertation Abstracts International, Volume: 68-08, Section: B, page: 5343. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 110-122). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

A clinical trial may have no subject (0%) or every subject (100%) developing the outcome of concern in either of the two comparison groups. This will cause a zero-cell in the four-cell (2x2) table of a trial using a binary outcome and make it impossible to estimate the odds ratio, a commonly used effect measure. A usual way to deal with this problem is to add 0.5 to each of the four cells in the 2x2 table. This is known as Haldane's approximation. In meta-analysis, Haldane's approximation can also be applied. Two approaches are possible: add 0.5 to only the trials with a zero cell or to all the trials in the meta-analysis. Little is known which approach is better when used in combination with different definitions of the odds ratio: the ordinary odds ratio, Peto's odds ratio and Mantel-Haenszel odds ratio. / A new formula is derived for converting Peto's odds ratio to the risk difference. The derived risk difference through the new method was then compared with the true risk difference and the risk difference derived by taking the Peto's odds ratio as the ordinary odds ratio. All simulations and analyses were conducted on the Statistical Analysis Software (SAS). / Conclusions. The estimated confidence interval of a meta-analysis would mostly exclude the truth if an inappropriate correction method is used to deal with zero cells. Counter-intuitively, the combined result of a meta-analysis will be worse as the number of studies included becomes larger. Mantel-Haenszel odds ratio without applying Haldane's approximation is recommended in general for dealing with sparse data in meta-analysis. The ordinary odds ratio with adding 0.5 to only the trials with a zero cell can be used when the trials are heterogeneous and the odds ratio is close to 1. Applying Haldane's approximation to all trials in a meta-analysis should always be avoided. Peto's odds ratio without Haldane's approximation can always be considered but the new formula should be used for converting Peto's odds ratio to the risk difference. / In addition, the odds ratio needs to be converted to a risk difference to aid decision making. Peto's odds ratio is preferable in some situations and the risk difference is derived by taking Peto's odds ratio as an ordinary odds ratio. It is unclear whether this is appropriate. / Methods. For studying the validity of Haldane's approximation, we defined 361 types of meta-analysis. Each type of meta-analysis is determined by a unique combination of the risk in the two compared groups and thus provides a unique true odds ratio. The number of trials in a meta-analysis is set at 5, 10 and 50 and the sample size of each trial in a meta-analysis varies at random but is made sufficiently small so that at least one trial in a meta-analysis will have a zero-cell. The number of outcome events in a comparison group of a trial is generated at random according to the pre-determined risk for that group. One thousand homogeneous meta-analyses and one thousand heterogeneous meta-analyses are simulated for each type of meta-analysis. Two Haldane's approximation approaches in addition to no approximation are evaluated for three definitions of the odds ratio. Thus, nine combined odds ratios are estimated for each type of meta-analysis and are all compared with the true odds ratio. The percentage of meta-analyses with the 95% confidence interval including the true odds ratio is estimated as the main index for validity of the correction methods. / Objectives. (1) We conducted a simulation study to examine the validity of Haldane's approximation as applied to meta-analysis, and (2) we derived and evaluated a new method to covert Peto's odds ratio to the risk difference, and compared it with the conventional conversion method. / Results. By using the true ordinary odds ratio, the percentage of meta-analyses with the confidence interval containing the truth was lowest (from 23.2% to 53.6%) when Haldane's approximation was applied to all the trials regardless the definition of the odds ratios used. The percentage was highest with Mantel-Haenszel odds ratio (95.0%) with no approximation applied. The validity of the corrections methods increases as the true odds ratio gets close to one, as the number of trials in a meta-analysis decreases, as the heterogeneity decreases and the trial size increases. / The proposed new formula performed better than the conventional method. The mean relative difference between the true risk difference and the risk difference obtained from the new formula is -0.006% while the mean relative difference between the true risk difference and the risk difference obtained from the conventional method is -10.9%. / The validity is relatively close (varying from 86.8% to 95.8%) when the true odds ratio is between 1/3 and 3 for all combinations of the correction methods and definitions of the odds ratio. However, Peto's odds ratio performed consistently best if the true Peto's odds ratio is used as the truth for comparison among the three definitions of the odds ratio regardless the correction method (varying from 88% to 98.7%). / Tam Wai-san Wilson. / "Jan 2006." / Adviser: J. L. Tang. / Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6488. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 151-157). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.