Visual and metric analysis both provide accepted methods for sex determination in humans. Visual ascertainment uses differing morphological traits in males and females to establish sex. Researchers have continually sought accurate methods of sexing long bones when skulls or pelves are absent or fragmented. These long bone elements may not have sexually distinct characteristics, but tend to survive in the field quite well. Metric analysis depends on size dimorphism between males and females to correctly assign sex. Metric methods fail where the sexes overlap or when skeletal elements cannot be assigned to their correct biological population. Under these conditions, visual ascertainment is extremely useful. It relies on descriptive features, not size, to interpret the shape variations between male and female elements. For example, physiological soft tissue variations in the "carrying angle'" of the arm at the humero-radioulnar junction are known to be sexually dimorphic; therefore, the hard tissue features of the distal humerus also should be sexually dimorphic. I observed six distinct visual characteristics of the distal humerus to determine sex in a blind study conducted on 649 individuals sampled from diverse biological populations. In addition to visual assessment, I collected four humeral measurements to determine whether quantitative analysis would be a better indicator of sex than non-metric analysis. I used nonparametric statistical methods to examine· the significance of each morphological feature and its relationship to known sex. All characteristics showed a high association with sex, and the relationships between sex and each characteristic were statistically strong. The final predictive quality of this method was 84% regardless of population; I concluded that my visual method is a dependable sex predictor among diverse populations. Every biological group varied considerably in size dimensions, but exhibited common morphological features of the distal humerus. This confirms that visual techniques provide accurate results regardless of biological affiliation. In many cases, visual assessment was as accurate or more accurate than metric analysis. Therefore, the distal humerus and its unique physical features provide an alternative method to previously used quantitative techniques in the determination of sex.

We have constructed a new finite-difference time-domain (FDTD) method in this project. Our new algorithm focuses on the most important and more challenging transverse electric (TE) case. In this case, the electric field is discontinuous across the interface between different dielectric media. We use an electric permittivity that stays as a constant in each medium, and magnetic permittivity that is constant in the whole domain. To handle the interface between different media, we introduce new effective permittivities that incorporates electromagnetic fields boundary conditions. That is, across the interface between two different media, the tangential component, Er(x,y), of the electric field and the normal component, Dn(x,y), of the electric displacement are continuous. Meanwhile, the magnetic field, H(x,y), stays as continuous in the whole domain. Our new algorithm is built based upon the integral version of the Maxwell's equations as well as the above continuity conditions. The theoretical analysis shows that the new algorithm can reach second-order convergence O(∆x2)with mesh size ∆x. The subsequent numerical results demonstrate this algorithm is very stable and its convergence order can reach very close to second order, considering accumulation of some unexpected numerical approximation and truncation errors. In fact, our algorithm has clearly demonstrated significant improvement over all related FDTD methods using effective permittivities reported in the literature. Therefore, our new algorithm turns out to be the most effective and stable FDTD method to solve Maxwell's equations involving multiple media.

There were three underlying purposes to this study: 1) To test the main effect of gender on work -> family and family -> work conflict; 2) To re-examine the predictors of inter-role conflict used by Frone, Russell, and Cooper (1992) (i.e., job involvement, job stress, family involvement, and family stress); and 3) To investigate the importance of using personality characteristics as predictors of how individuals deal with inter-role conflict. A questionnaire was assembled, consisting of: a work -> family conflict spillover scale, a family -> work conflict spillover scale, a job involvement scale, a family involvement scale, a job stressors scale, a family stressors scale, and two sub-scales from the California Psychological Inventory (i.e., the Managerial Potential scale and the Work Orientation scale) . Questionnaires were completed by 134 employees of a civil service agency. Results indicated that gender was not a significant predictor of either work -> family or family ->work conflict. Job stress was found to be a significant predictor of both work -> family, and family ->work conflict. Where as family stress was found to be a significant predictor of family -> work conflict only. Job involvement was found to be a significant predictor of work -> family conflict for managers only. When all predictors were assessed simultaneously, Work Orientation was the only variable found to be a significant predictor of work -> family conflict. The results from this study clarify and add to Frone, Russell, and Cooper's (1992) study of the work-family interface.

In previous research men have been shown to obtain higher mean scores on tests of horizontality CH) and verticality CV) than do women. This study investigated the role of experiential factors in this gender difference. Undergraduate psychology students were randomly assigned to one of three treatment groups: training, enhanced training, and placebo. The pretest measure of verticality and horizontality CV/ H), training, and posttest were administered via videotape. Major findings were: men obtained higher mean V/H scores than women; V and H scores correlated significantly; and training increased performance relative to a placebo, but enhanced training was not superior to standard training. It was hypothesized that participation in athletics might eliminate the V/ H sex difference. This was supported by initial analyses of the data. However, further analyses revealed that this may have been artifactual. Errors on the V/H test were classified as undercorrections, overcorrections, and miscorrections. It was found that miscorrections corresponded to relatively low scores, inconsistent responding, and resistance to training. Scores on a generalization test substantiated al l findings from the original V/H measure.

The Cache County Study on Memory in Aging (CCSMA) is a longitudinal population-based study which took place in Cache County, Utah. The study followed 5092 older-adult residents (aged 65+) for approximately 12 years to examine risk and protective factors for dementia. Participants completed dementia screening and follow-up assessments across four triennial visits. Additionally, researchers gathered information regarding demographics, reproductive history (e.g. age of menopause; hormone replacement therapy [HRT]) and other health-related factors, such as physical activity. Genotyping of DNA was completed for a genetic variation of genes for brain-derived neurotrophic factor (BDNF), a protein found in the brain associated with neuronal health and survival. Estrogen has been associated with cognitive health and has been shown to interact with BDNF in the brain to promote neuronal survival. The current research investigated the associations between estrogen, BDNF, and cognitive decline in older adult women from the CCSMA. An examination of how reproductive history, including the reproductive window (age of menarche to menopause) and use of HRT, affects the cognitive health of women in older adulthood can provide a clearer understanding of how estrogen exposure across the lifespan contributes to cognition in late life. This research can be helpful in determining the implications of events such as pregnancy, breastfeeding, surgical menopause and use of HRT on cognitive decline. Additionally, an investigation of how these reproductive factors interact with BDNF genetics is important to understand gene-by-environment interactions. The results of the current project demonstrated that increased lifelong estrogen exposure, both in the form of the reproductive window and HRT use, had small cognitive benefits for women in late life. Additionally, it was shown that women who initiated HRT use closer to menopause had increased cognitive status compared to those who initiated later. The specific BDNF gene under investigation was not associated with cognitive status in late life, neither was the interaction between BDNF and lifetime estrogen exposure. This research contributes to the discussion of sex-dependent factors of cognitive health and can help provide a better understanding late life cognitive decline.

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This thesis describes a research study that investigated the relationships between school level environment and student outcomes. The study involved 620 teachers and 4645 students from 57 Australian secondary schools in all states and territories. Student outcome measures included mathematics achievement, attitudes and beliefs toward mathematics and were collected as part of the Third International Mathematics and Science Study. Teachers perceptions of their school environment were measured using the School Level Environment Questionnaire and included variables such as student support, affiliation, professional interest, mission consensus, empowerment, innovation, resource adequacy and work pressure. Previous research has shown that factors at the school level, like environment, influence education at the classroom level and to further investigate this, data regarding the instructional practices of teachers was included in the analysis. The unique methodology used to investigate influences on student mathematics achievement is also described in this thesis. A two-step approach to modelling consisted of the analysis of two conceptually distinct models. The first was an analysis of the measurement model, which specifies the relationships between the observed variables and the latent variables. The second involved a structural equation model, which specifies the relationships among the latent variables as posited by theory and previous research. In addition, a multilevel analysis was included to further partition the variance in student outcomes between the student level, the classroom level and the school level. The results of these analysis linked particular variables of interest to improved student outcomes. / For example, teachers who felt supported and empowered were more likely to employ student-centred instructional practices and that work pressure and resource adequacy influenced the instructional approaches in the classrooms. The success attribution of students determined which method of instruction promoted positive outcomes. Furthermore, these results indicate relationships between student outcomes, attitudes and achievement, and the relationships between attitude and achievement were recursive with influences from student background variables. The multilevel analysis demonstrated the importance of the influence of factors at the classroom level in influencing student outcomes and highlighted factors at the school level that explained differences in achievement. The significance of this study is in the provision of evidence that demonstrates the effects on student outcomes and not only supports, but significantly adds to previous research. This thesis provides practical implications for teaching and for school policy that can be implemented to promote positive student outcomes. The thesis also provides a rationale for further research that would involve an investigation of the effects of change as suggested from the results of these analysis reported from this study.

Abstract not available

Includes bibliographical references (leaves 158-163). Concerns the development of high-order finite-difference methods on a uniform rectangular grid for advection and diffuse problems with smooth variable coefficients. This technique has been successfully applied to variable-coefficient advection and diffusion problems. Demonstrates that the new schemes may readily be incorporated into multi-dimensional problems by using locally one-dimensional techniques, or that they may be used in process splitting algorithms to solve complicatef time-dependent partial differential equations.