One psychosocial variable, human mate selection, has been studied extensively within the field of evolutionary psychology. A question of interest is how sexual/reproductive decision-making (i.e., dating, marrying, and childbearing) might be influenced by an individual’s perception of his/her genetic risk and other psychosocial variables. There is a paucity of empirical studies within the literature exploring this specific relationship. This partially mixed, sequential mixed methods study addresses how individual perception of genetic risk (PGR) influences or predicts sexual/reproductive intentions and decision-making. A systematic review of the literature was conducted by searching for English language, peer-reviewed, empirical studies in Cambridge Scientific Abstracts databases (N=26). Next, students from three Southwestern universities were recruited for focus groups and responded to 15 open-ended questions (N=86). Transcripts were audiotaped, transcribed verbatim and analyzed using holistic-content analysis. Based on the literature review and qualitative findings, a 138-item, web-based instrument was designed and tested at two Southwestern universities (N=2,576). Survey data were analyzed using non-parametric univariate analyses and multiple regression. Approximately 50 demographic, individual/familial psychosocial and genetic testing-related factors influenced the relationship between PGR and sexual/reproductive decision-making in reviewed studies. Individual psychosocial factors (e.g., intention, attitudes) represented 65.8% of all findings. Participants in the qualitative phase exhibited moderate health literacy when interpreting and discussing genetic risk information. A number of factors including age, gender, religion, individual/family values, and exposure to genetic concepts/technology appeared to influence sexual/reproductive decision-making. Demographic, Health Belief Model (HBM) and Theory of Planned Behavior (TPB) variables predicted the relationship between PGR and dating, marital, and childbearing intention in the quantitative phase. TPB variables were the strongest predictors of intention accounting for 33.1-38.7% of variance. Positive family norms were the single best predictor of dating and marital intention. Age was the best predictor of childbearing intention. Further research is needed to understand how young adults incorporate genetic risk perceptions into sexual/reproductive decision-making. Mixed methods and longitudinal study designs, and structural equation modeling are recommended for use in future studies. Study findings affirm a need for health educators to consider adopting genomic competencies; creating theory-based curricula/interventions; and forming partnerships with genetic specialists and local/regional health departments.

Population genetic variation of cultured oyster Crassostrea spp. in Taiwan and neighborhood Cheng-Pin Yu ¡]Advisor¡GDr. Jin-Hua Cheng¡^ Institute of Marine Biology, National Sun Yat-sen University, Kaohsuang 804 Taiwan R.O.C. Thesis Abstract The genetic variations among oyster populations of Taiwan, Ginmen and Fu-kein coast are analyzed using molecular method. Firstly, DNA sequences of mitochondrial 16S rRNA and COI genes are analyzed according to nucleotide differences and restriction enzyme recognition site. Then, population variations were analyzed by the lane pattern of restriction enzyme fragment¡]RFLP¡^. The sequences of 530 bp DNA fragment of 16S rRNA gene showed little difference¡]0-1 bp¡^between Portuguese oyster and oyster cultured in Taiwan, both have larger differences¡]3-4 bp¡^compared with C. gigas. The sequences of 700 bp DNA fragment of COI gene showed similar results. C. angulata is found in Ginmen and Fu-kein coast for the first time which is identified by the PCR-RFLP of COI gene fragment. PCR-RFLP analysis of COI gene fragment showed C. angulata from Portugal are genetically closest to the oysters collected from Ginmen and Fu-kein.

Researchers have applied genetic algorithms (GAs) and other heuristic optimization methods to perform truss optimization in recent years. Although a substantial amount of research has been performed on the optimization of truss member sizes, nodal coordinates, and member connections, research that seeks to simultaneously optimize the topology, geometry, and member sizes of trusses is still uncommon. In addition, most of the previous research is focused on the problem domains that are limited to a structured domain, which is defined by a fixed number of nodes, members, load locations, and load magnitudes. The objective of this research is to develop a computational method that can design efficient roof truss systems. This method provides an engineer with a set of near-optimal trusses for a specific unstructured problem domain. The unstructured domain only prescribes the magnitude of loading and the support locations. No other structural information concerning the number or locations of nodes and the connectivity of members is defined. An implicit redundant representation (IRR) GA (Raich 1999) is used in this research to evolve a diverse set of near-optimal truss designs within the specified domain that have varying topology, geometry, and sizes. IRR GA allows a Pareto-optimal set to be identified within a single trial. These truss designs reflect the tradeoffs that occur between the multiple objectives optimized. Finally, the obtained Pareto-optimal curve will be used to provide design engineers with a range of highly fit conceptual designs from which they can select their final design. The quality of the designs obtained by the proposed multi-objective IRR GA method will be evaluated by comparing the trusses evolved with trusses that were optimized using local perturbation methods and by trusses designed by engineers using a trial and error approach. The results presented show that the method developed is very effective in simultaneously optimizing the topology, geometry, and size of trusses for multiple objectives.

Thesis (M. Phil.)--University of Hong Kong, 2001. / Includes bibliographical references.

Thesis (Ph. D.)--University of Chicago, Dept. of Molecular Genetics and Cell Biology, 2002. / Includes bibliographical references. Also available on the Internet.

Thesis (Ph. D.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains x, 140 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 120-131).

Thesis (M. Phil.)--University of Hong Kong, 2009. / Includes bibliographical references (leaves 77-109). Also available in print.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from UMI/Dissertation Abstracts International.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from UMI/Dissertation Abstracts International.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2002. / Includes bibliographical references (leaves 175-187). Also available in electronic version. Access restricted to campus users.