Current socio-economic measures, and not those measured during infancy, affect bone mass in poor urban South african children.

Understanding the impact of socio-economic status (SES) on physical development in children is important, especially in developing countries where considerable inequalities persist. This is the first study to examine the association between SES on bone development at the whole body, femoral neck, and lumbar spine in black children living in Soweto and Johannesburg, South Africa. Linear regression models were used to study associations between SES during infancy and current SES, anthropometric, and DXA-derived bone mass in 9/10-yr-old children (n = 309). Findings suggest that current SES measures, rather than SES during infancy, are stronger predictors of current whole body bone area (BA) and whole body BMC after adjusting for body size, pubertal development, physical activity, habitual dietary calcium intake, and body composition. SES had no significant effect on either hip or spine bone mass. Caregiver's marital/cohabiting status (indicator of social support) and whether there was a television in the home (indicator of greater income) at age 9/10 yr were the most important socio-economic determinants of whole body BA and BMC. SES has a significant independent effect on whole body BMC through its impact on BA. This suggests that poverty alleviation policies in South Africa could have a positive effect on bone health

On the Mental Workload Assessment of Uplift Mapping Representations in Linked Data

Self-reporting procedures have been largely employed in literature to measure the mental workload experienced by users when executing a specific task. This research proposes the adoption of these mental workload assessment techniques to the task of creating uplift mappings in Linked Data. A user study has been performed to compare the mental workload of “manually” creating such mappings, using a formal mapping language and a text editor, to the use of a visual representation, based on the block metaphor, that generate these mappings. Two subjective mental workload instruments, namely the NASA Task Load Index and the Workload Profile, were applied in this study. Preliminary results show the reliability of these instruments in measuring the perceived mental workload for the task of creating uplift mappings. Results also indicate that participants using the visual representation achieved smaller and more consistent scores of mental workload

Cognitive orientation in business intelligence systems

With the increasing importance of cognitive aspects in decision making, this research addresses how human cognitive abilities, mainly situation awareness and mental models, can be used to drive the decision process in complex decision situations. Cognitive orientation has long been regarded as an important consideration in the development and application of decision support systems (DSS). Rather than cognitive orientation, a data-driven DSS emphasizes access to and manipulation of a series of company internal and external data, compared to a model-driven DSS underpinned by statistical, financial, optimization or simulation models. A business intelligence (BI) system is essentially a kind of data-driven DSS therefore shares the similar drawbacks with traditional DSS. A framework of cognitive BI system is firstly developed. A model of cognition-driven decision process is then proposed based on the system framework. In this framework and decision model, data retrieval, information filtering and knowledge presentation are based on the tacit knowledge elicited from the decision-maker. The final decision is no longer the direct output of a computer system, but the result of decision-making cycles of human-machine interaction. © 2008 Springer-Verlag Berlin Heidelberg