From the advent of association rule mining, it has become one of the most researched areas of data exploration schemes. In recent years, implementing association rule mining methods in extracting rules from a continuous flow of voluminous data, known as Data Stream has generated immense interest due to its emerging applications such as network-traffic analysis, sensor-network data analysis. For such typical kinds of application domains, the facility to process such enormous amount of stream data in a single pass is critical.

Bipolar affective disorder is a severe mood disorder, which is characterised by episodes of mania and depression. The aetiology of bipolar disorder remains elusive, with little known about the underlying biological, anatomical, or biochemical effects. However, family, twin and adoption studies provide evidence for a strong genetic component to the disorder. Due to the high heritability, familial clustering, and common population prevalence of the illness, molecular genetic studies can be implemented to identify bipolar disorder susceptibility genes. This thesis investigated the candidate gene serotonin 2A receptor (HTR2A), which lay within a region on chromosome 13q14 previously identified by bipolar disorder genome-wide linkage scans. Significant association was found with bipolar disorder and a SNP within intron 2 of HTR2A in an Australian case-control cohort. Haplotype association analysis identified a 5-SNP protective haplotype within HTR2A. Conducting a new genome-wide linkage scan on 35 Australian bipolar disorder pedigrees found significant evidence for linkage on chromosome 15q25-26. Subsequent fine-mapping of the region verified the linkage peak with a significant maximum multipoint LOD score of 4.58. Haplotype analysis, based on pedigree-specific, identical-by-descent allele sharing, supported the location of a bipolar susceptibility gene within a 6.2Mb confidence interval. The candidate gene sialyltransferase 8B (ST8SIA2), which had previously shown association with SNPs within the gene’s promoter region and schizophrenia in two independent Asian cohorts, lies within the chromosome 15q25-26 locus. Failing to replicate the association found with these specific SNPs, and without finding association with two additional SNPs in an upstream conserved putative regulatory region, a fine-mapping association study was conducted across the entire 6.2Mb interval. The strongest association signals were observed at SNPs 16kb upstream from and within the fourth intron of ST8SIA2. A specific bipolar disorder risk haplotype was identified for ST8SIA2, and this was also observed to be over-represented in a cohort of Australian schizophrenia cases. This finding suggests that the ST8SIA2 gene, for which strong developmental regulation was observed, may be a shared susceptibility gene for both bipolar disorder and schizophrenia. In summary, this thesis has provided evidence identifying both HTR2A and ST8SIA2 as bipolar disorder susceptibility genes.

The Implicit Association Test (IAT) is the most popular indirect measure of attitudes in social psychology. It has been suggested that salience asymmetries are a non-associative contaminant of the IAT that threatens the accurate assessment of attitudes. Salience asymmetries in the IAT are claimed to correspond with visual search asymmetries, and differences in target familiarity. In this thesis, I propose that processing fluency is the common mechanism underlying both visual search asymmetries and familiarity. Several experiments were conducted to determine whether visual search asymmetries, familiarity, or processing fluency most reliably corresponds with salience asymmetry effects in the IAT. The first series of experiments revealed that processing fluency is a better predictor of salience asymmetry effects in the IAT than is visual search asymmetry (Chapter 2). In Chapter 3, a novel method was developed to distinguish between the effects of valence and salience in the IAT. Using this method, I demonstrated that the effects of salience in the IAT are consistent with a fluency account of salience asymmetries. Familiarity was also shown to produce salience asymmetry effects in the IAT (Chapter 4), which is also consistent with the fluency account. When fluency and familiarity were set against each other in Chapter 5, it was processing fluency, rather than familiarity, that predicted salience asymmetry effects in the IAT. Although processing fluency is a good predictor of salience asymmetries, the results of Chapter 6 reveal that the fluency account cannot explain all examples of salience asymmetries in the IAT. The data presented here are consistent with the view that the more fluently processed target category is compatible with the pleasant attributes on the grounds of salience asymmetries. The current experiments suggest that when there are valence differences between the target categories, salience asymmetries can potentially distort IAT effects. When the positive target category is more salient, salience asymmetries appear to increase IAT effects. In contrast, when the negative target category is more salient, salience asymmetries appear to decrease IAT effects. However, further evidence is required to determine how the effects of salience and valence combine in the IAT.

In the context of China’s growing influence over the global economy, its newly developed labour market and the subsequent series of industrial relations issues have captured much attention. However, research on industrial relations and labour problems in China is relatively underdeveloped. The classic three-party industrial relations model, which was developed for western economies, has often been difficult to apply to China’s circumstances. The biggest difference between China and western countries in the matter of labour issues lies in the different institutional settings of the industrial relations systems. As a sub-system of the broader social system, the industrial relations system of a country is significantly affected by the fundamental socio-political system in that particular country. In view of this, Chapter One of this thesis will first review the relevant existing industrial relations theories and explore their applicability to China. The thesis then continues with the proposal of a new six-party taxonomy for the analysis of Chinese industrial relations. The new taxonomy takes into account distinctive industrial relations actors with “Chinese characteristics” as well as their inter-relationships which form at different social levels. This taxonomy provides a useful tool for drawing a broad picture of the evolving industrial relations in China, which constitute the main content of the later parts of this thesis: in Part One (Chapters Two to Four), we analyse the historical and current situation of the six Chinese industrial relations actors, namely the party-state, employers’ associations, the All China Federation of Trade Unions, grass roots unions, employers and employees; while in Part Two (Chapter Five and Six), we describe the interactions between each of these actors from a historical perspective. With the new taxonomy and the analyses that follow, this thesis aims to provide a new insight into Chinese industrial relations and labour studies. It attempts to present to the readers a broad picture of the Chinese industrial relations system. We believe that the discussion will be valuable for those interested in China’s social development (in particular, the development of modern industrial relations in the context of the Chinese political economy). Limitations of length, however, preclude the detailed discussion in this thesis of all Chinese industrial relations issues. Various future research topics have been identified in the concluding chapter, and we recognize that they are undoubtedly important questions in need of enormous research efforts. Therefore, we see this thesis as the beginning of a series of related works, which aim to contribute to a better understanding of industrial relations in the context of Chinese political economy.

From the advent of association rule mining, it has become one of the most researched areas of data exploration schemes. In recent years, implementing association rule mining methods in extracting rules from a continuous flow of voluminous data, known as Data Stream has generated immense interest due to its emerging applications such as network-traffic analysis, sensor-network data analysis. For such typical kinds of application domains, the facility to process such enormous amount of stream data in a single pass is critical.

The striking similarity between Gestational Diabetes Mellitus (GDM) and Type 2 Diabetes (T2D) in terms of the pathophysiologies and the risk factors has led to the hypothesis that GDM is an early manifestation of T2D, expressed under the stress of pregnancy, and therefore both diseases should share similar susceptibility genes. GDM patients may provide a more homogeneous sample for the genetic causes of the disease than T2D, and therefore make a useful group for the identification of the genes involved. Over 200 GDM affected sib-pairs from 178 families were investigated, with parents available in 40% of cases. Genomic regions from 4 different chromosomes, 6, 8, 14 and 18 were chosen from regions that showed clustering for positive linkage scores in previous linkage studies on T2D and one control region on 13, where no previous positive linkage was reported. A total of 19 microsatellite markers were analysed for linkage to GDM using sib-pair analysis. Subset analyses were performed by ranking sib-pairs on GDM-related variables, e.g. mean BMI of sibs, age at GDM episode, etc. GENEHUNTER was run multiple times, each time including the next highest ranked family in the analysis. This gave a continuous range of scores where increasing or decreasing NPL scores indicated heterogeneity associated with different environmental factors such as age and weight. To evaluate the significance of the subset analyses, the results were compared to 10,000 permutations generated by randomly ranking the sib-pairs. Using the entire dataset, the analysis showed no significant linkage to a disease locus. Positive evidence for linkage was found with the subset analysis on chromosomes 8 and 14, suggesting heterogeneity between sib-pairs in the dataset. Marker D8S1742 on 8p23 showed an NPL score of 3.01 (p=0.001) when age at GDM diagnosis was used as a covariate. Using waist-to-hip ratio (WHR), marker D14S275 on 14q12 showed an NPL score of 2.474 (p=0.006). When adjusted for multiple testing, the results were not statistically significant for linkage to a diabetes disease locus, but gave evidence that GDM and T2D share similar genetic determinants, and defined groups of siblings for follow-up analysis of both types of diabetes.

Thesis (Ed. D.)--George Washington University, [1985?]. / Abstracted in DAI-A 46/06, p. 1579, Dec 1985. Includes bibliographical references (leaves 245-260).

Thesis (D. Min.)--Temple Baptist Theological Seminary, 1989. / Includes bibliographical references (leaves 135-138).

Applied research project (D. Min.)--School of Theology and Missions, Oral Roberts University, 2006. / Includes abstract and vita. Translated from Korean. Includes bibliographical references (leaves 192-197).

Applied research project (D. Min.)--School of Theology and Missions, Oral Roberts University, 2006. / Includes abstract and vita. Includes bibliographical references (leaves 198-205).