Predicting sexual problems in women: The relevance of sexual excitation and sexual inhibition

This is the post-print version of the article. The official published version can be obtained from the link below.Data from a non-clinical sample of 540 heterosexual women were used to examine the relationships between scores on the Sexual Excitation/Sexual Inhibition Inventory for Women (SESII-W) and ratings of current sexual problems, lifetime arousal difficulty, lifetime orgasm difficulty, and lifetime problems with low sexual interest. Multiple regression analyses also included several demographic/background variables as predictors: age, full-time employment, completed college, children in household, married, health ratings, importance of sex, and whether the woman was in a sexual relationship. The strongest statistical predictors of both current and lifetime sexual problems were the SESII-W inhibition factors Arousal Contingency and Concerns about Sexual Function. Demographic factors did not feature largely in any of the models predicting sexual problems even when statistically significant relationships were found. If future research supports the predictive utility of the SESII-W in identifying women who are more likely to experience sexual difficulties, these scales may be used as prognostic factors in treatment studies.This study was funded, in part, by a grant from the Lilly Centre for Women's Health

FAST: A multi-processed environment for visualization of computational fluid dynamics

Three-dimensional, unsteady, multi-zoned fluid dynamics simulations over full scale aircraft are typical of the problems being investigated at NASA Ames' Numerical Aerodynamic Simulation (NAS) facility on CRAY2 and CRAY-YMP supercomputers. With multiple processor workstations available in the 10-30 Mflop range, we feel that these new developments in scientific computing warrant a new approach to the design and implementation of analysis tools. These larger, more complex problems create a need for new visualization techniques not possible with the existing software or systems available as of this writing. The visualization techniques will change as the supercomputing environment, and hence the scientific methods employed, evolves even further. The Flow Analysis Software Toolkit (FAST), an implementation of a software system for fluid mechanics analysis, is discussed

Dynamics of the magnetic and structural a -> e phase transition in Iron

We have studied the high-pressure iron bcc to hcp phase transition by simultaneous X-ray Magnetic Circular Dichroism (XMCD) and X-ray Absorption Spectroscopy (XAS) with an X-ray dispersive spectrometer. The combination of the two techniques allows us to obtain simultaneously information on both the structure and the magnetic state of Iron under pressure. The magnetic and structural transitions simultaneously observed are sharp. Both are of first order in agreement with theoretical prediction. The pressure domain of the transition observed (2.4 $\pm$ 0.2 GPa) is narrower than that usually cited in the literature (8 GPa). Our data indicate that the magnetic transition slightly precedes the structural one, suggesting that the origin of the instability of the bcc phase in iron with increasing pressure is to be attributed to the effect of pressure on magnetism as predicted by spin-polarized full potential total energy calculations

FAST: A multi-processed environment for visualization of computational fluid

Three dimensional, unsteady, multizoned fluid dynamics simulations over full scale aircraft is typical of problems being computed at NASA-Ames on CRAY2 and CRAY-YMP supercomputers. With multiple processor workstations available in the 10 to 30 Mflop range, it is felt that these new developments in scientific computing warrant a new approach to the design and implementation of analysis tools. These large, more complex problems create a need for new visualization techniques not possible with the existing software or systems available as of this time. These visualization techniques will change as the supercomputing environment, and hence the scientific methods used, evolve ever further. Visualization of computational aerodynamics require flexible, extensible, and adaptable software tools for performing analysis tasks. FAST (Flow Analysis Software Toolkit), an implementation of a software system for fluid mechanics analysis that is based on this approach is discussed

Scientific Visualization Using the Flow Analysis Software Toolkit (FAST)

Over the past few years the Flow Analysis Software Toolkit (FAST) has matured into a useful tool for visualizing and analyzing scientific data on high-performance graphics workstations. Originally designed for visualizing the results of fluid dynamics research, FAST has demonstrated its flexibility by being used in several other areas of scientific research. These research areas include earth and space sciences, acid rain and ozone modelling, and automotive design, just to name a few. This paper describes the current status of FAST, including the basic concepts, architecture, existing functionality and features, and some of the known applications for which FAST is being used. A few of the applications, by both NASA and non-NASA agencies, are outlined in more detail. Described in the Outlines are the goals of each visualization project, the techniques or 'tricks' used lo produce the desired results, and custom modifications to FAST, if any, done to further enhance the analysis. Some of the future directions for FAST are also described

A classification of tasks for the systematic study of immune response using functional genomics data

A full understanding of the immune system and its responses to infection by different pathogens is important for the development of anti-parasitic vaccines. A growing number of large-scale experimental techniques, such as microarrays, are being used to gain a better understanding of the immune system. To analyse the data generated by these experiments, methods such as clustering are widely used. However, individual applications of these methods tend to analyse the experimental data without taking publicly available biological and immunological knowledge into account systematically and in an unbiased manner. To make best use of the experimental investment, to benefit from existing evidence, and to support the findings in the experimental data, available biological information should be included in the analysis in a systematic manner. In this review we present a classification of tasks that shows how experimental data produced by studies of the immune system can be placed in a broader biological context. Taking into account available evidence, the classification can be used to identify different ways of analysing the experimental data systematically. We have used the classification to identify alternative ways of analysing microarray data, and illustrate its application using studies of immune responses in mice to infection with the intestinal nematode parasites Trichuris muris and Heligmosomoides polygyrus