Dimensional Accuracy of Computer-Aided Design/Computer-Assisted Manufactured Orbital Prostheses

Purpose: The aim of this research was to assess the dimensional accuracy of orbital prostheses based on reversed images generated by computer-aided design/computer-assisted manufacturing (CAD/CAM) using computed tomography (CT) scans. Materials and Methods: CT scans of the faces of 15 adults, men and women older than 25 years of age not bearing any congenital or acquired craniofacial defects, were processed using CAD software to produce 30 reversed three-dimensional models of the orbital region. These models were then processed using the CAM system by means of selective laser sintering to generate surface prototypes of the volunteers` orbital regions. Two moulage impressions of the faces of each volunteer were taken to manufacture 15 pairs of casts. Orbital defects were created on the right or left side of each cast. The surface prototypes were adapted to the casts and then flasked to fabricate silicone prostheses. The establishment of anthropometric landmarks on the orbital region and facial midline allowed for the data collection of 31 linear measurements, used to assess the dimensional accuracy of the orbital prostheses and their location on the face. Results: The comparative analyses of the linear measurements taken from the orbital prostheses and the opposite sides that originated the surface prototypes demonstrated that the orbital prostheses presented similar vertical, transversal, and oblique dimensions, as well as similar depth. There was no transverse or oblique displacement of the prostheses. Conclusion: From a clinical perspective, the small differences observed after analyzing all 31 linear measurements did not indicate facial asymmetry. The dimensional accuracy of the orbital prostheses suggested that the CAD/CAM system assessed herein may be applicable for clinical purposes. Int J Prosthodont 2010;23:271-276.

The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.

Using Theory to Understand the Multiple Determinants of Low Participation in Worksite Health Promotion Programs

Low participation at the employee or worksite level limits the potential public health impact of worksite-based interventions. Ecological models suggest that multiple levels of influence operate to determine participation patterns in worksite health promotion programs. Most investigations into the determinants of low participation study the intrapersonal, interpersonal, and institutional influences on employee participation. Community- and policy-level influences have not received attention, nor has consideration been given to worksite-level participation issues. The purpose of this article is to discuss one macrosocial theoretical perspective—political economy of health—that may guide practitioners and researchers interested in addressing the community- and policy-level determinants of participation in worksite health promotion programs. The authors argue that using theory to investigate the full spectrum of determinants offers a more complete range of intervention and research options for maximizing employee and worksite levels of participation.

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.