The aims of this thesis are: 1. To examine patterns of morphological variation in the crania of extant species {Pan, Gorilla, Pongo, and H. sapiens) to determine if any common pattern of primate sexual dimorphism exists which could be used in the assessment of fossil hominid sexual dimorphism; 2. To examine patterns of between species variability among the crania of the above extant species to determine if characters exist which could be useful as taxonomic indicators, especially of specific distinctiveness in fossil Hominidae; and 3. To assess the validity of using traits which are dimorphic and/ or variable within species as taxonomic indicators in systematic analyses. This thesis entails an analysis of inter- and intra-specific diversity among the early hominids based on models derived from samples of modern H. sapiens and pongids. Metrical cranial characters were surveyed in order to assess the implications of their variability within the available early hominid sample {A. afarensis, A. africanus, A. robustus, A. boisei, H. habilis, and H. erectus) using univariate, multi variate, and cladistic analytical techniques. The univariate analysis found no common pattern of primate sexual dimorphism but it did identify characters of low sexual dimorphism and low variability common to all the extant hominoids. These were used to test the homogeneity of the fossil groups and indicated the possible heterogeneity of H. erectus, H. habilis, A. afarensis, and A. boisei. The remaining characters revealed an apparent trend among the hominids (fossil and modern) of dimorphic regions of the skull including the areas of nuchal and temporal muscle attachment, kyphosis of the basicrania, width of the palate, mandible, and base, and facial prognathism. The multivariate analyses used the patterns of variability and dimorphism known from the modern comparators to assess sex, degrees of sexual dimorphism, and homo geneity of the fossil samples. These analyses revealed the possible heterogeneity of H. erectus and A. afarensis, the sex of some individual specimens, and some interesting contrasts in the patterns of sexual dimorphism between the fossil and modern species. They also isolated KNM-ER 1805 as having unique basicranial proportions. Two different types of characters were used in cladistic analyses to determine which type produced the most parsimonious trees and the implications of their use for future cladistic analyses. The results show that non-variable, non-dimorphic traits generally produce more parsimonious trees than variable, dimorphic ones, thus demonstrating the importance of assessing within- and between-group variability of characters prior to cladistic analyses. The method of coding the data prior to the cladistic analysis was tested for its objectivity. The analyses showed that the constant used to code the data into discrete character states had a substantial effect upon the resultant trees. This study has demonstrated that characters have different properties due to the amount they vary or are dimorphic within groups and that utilising these characters for different purposes has the potential to enhance future systematic/ phyletic studies.

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The main subject of the research in this thesis is the study of conjugate gradient methods for optimization and the development of improved algorithms. After an introductory first chapter, Chapter 2 contains a background of numerical methods for optimization in general and of conjugate gradient-type algorithms in particular. In Chapter 3 we study the convergence properties of conjugate gradient methods and discuss Powell's (1983) counter example that proves that there exist twice continuously differentiable functions with bounded level sets for which the Polak-Ribiere method fails to achieve global convergence whereas the Fletcher-Reeves method is shown to be globally convergent, despite the fact that in numerical computations the Polak-Ribiere method is far more efficient than that of Fletcher-Reeves. Chapters 4 and 5 deal with the development of a number of new hybrid algorithms, three of which are shown to satisfy the descent property at every iteration and achieve global convergence regardless of whether exact or inexact line searches are used. A new restarting procedure for conjugate gradient methods is also given that ensures a descent property to hold and global convergence for any conjugate gradient method using a non negative update. The application of these hybrid algorithms and that of the new restarting procedure to a wide class of well-known test problems is given and discussed in the final Chapter "Discussions and Conclusions". The results obtained, given in the appendices, show that a considerable improvement is achieved by these hybrids and by methods using the new restarting procedure over the existing conjugate gradient methods and also over quasi-Newton methods.

<p> Post-abortion support groups are a new sub-movement or strategy of the broader anti-abortion movement that provide support to women who understand their prior abortions as problematic. These groups construct abortion as a form of trauma that causes post-abortion syndrome (PAS), a broad array of negative mental health and behavioral problems similar to post-traumatic stress disorder. Although these claims are not substantiated by empirical evidence, claims that abortion causes PAS are increasingly featured in the public domain to bolster national anti-abortion claims that abortion represents a public health issue. </p><p> A majority of PAS support groups are offered by crisis pregnancy centers (CPCs) affiliated with one of two national pregnancy resource centers whose approach to healing from abortion reflects the increased presence and influence of evangelical women in the CPC movement. The increased presence of evangelical women in the CPC movement is reflected in the growing influence of conservative Christian beliefs in the support services offered by CPCs in general and PAS groups specifically. This research examined a PAS group in Mississippi sponsored by an evangelical CPC affiliated with Care Net, a national pregnancy resource center, to understand the motivations of women who participate in a PAS group, how PAS group participation shapes participants' understandings of abortion to conform to broader anti-abortion claims that abortion is a public health issue, and how PAS claims are diffused into the public domain. </p><p> To discern the relationship between PAS groups and broader anti-abortion claims, I analyze state and national media coverage of the 2011 Mississippi political campaign in which voters overwhelmingly defeated a constitutional amendment to pass a personhood amendment to confer legal status to the fetus. Together these analyses show how evangelical groups are working through legislative and individual-level processes to shape the abortion debate and climate in contemporary American society.</p>

Thesis (M.S.)--University of Hawaii at Manoa, 2007. / Includes bibliographical references (leaves 71-74). / xi, 74 leaves, bound ill. 29 cm

Genes, the fundamental building blocks of life, act together (often through their derived proteins) in modules such as protein complexes and molecular pathways to achieve a cellular function such as DNA repair and cellular transport. A current emphasis in genomics research is to identify gene modules from gene profiles, which are measurements (such as a mutant phenotype or an expression level), associated with the individual genes under conditions of interest; genes in modules often have similar gene profiles. Clustering groups of genes with similar profiles can hence deliver candidate gene modules. Pairwise similarity measures derived from these profiles are used as input to the popular hierarchical agglomerative clustering algorithms; however, these algorithms offer little guidance on how to choose candidate modules and how to improve a clustering as new data becomes available. As an alternative, there are methods based on thresholding the similarity values to obtain a graph; such a graph can be analyzed through (probabilistic) methods developed in the social sciences. However, thresholding the data discards valuable information and choosing the threshold is difficult. Extending binary relational analysis, we exploit ranked relational data as the basis for two distinct approaches for identifying modules from genomic data, both based on the theory of random graph processes. We propose probabilistic models for ranked relational data that allow candidate modules to be accompanied by objective confidence scores and that permit an elegant integration of external information on gene-gene relationships. We first followed theoretical work by Ling to objectively select exceptionally isolated groups as candidate gene modules. Secondly, inspired by stochastic block models used in the social sciences, we construct a novel model for ranked relational data, where all genes have hidden module parameters which govern the strength of all gene-gene relationships. Adapting a classical likelihood often used for the analysis of horse races, clustering is performed by estimating the module parameters using standard Bayesian methods. The method allows the incorporation of prior information on gene-gene relationships; the utility of using prior information in the form of protein-protein interaction data in clustering of yeast mutant phenotype profiles is demonstrated.

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