Evaluation of some procedures relevant to the determination of trace elemental components in biological materials by destructive neutron activation analysis

The development of a simplified procedure for the analysis of biological materials by destructive neutron activation analysis (DNAA) is described. The sample manipulations preceding gamma ray assay were investigated as five specific stages of processing: (1) pre-irradiation treatment; (2) sample irradiation; (3) removal of the organic matrix; (4) removal of interfering radioactivities; and (5) concentration and separation of analyte activities. Each stage was evaluated with respect to susceptibility to sample contamination, loss of trace elemental components, and compatibility with other operations in the overall DNAA procedures. A complete DNAA procedure was proposed and evaluated for the analysis of standard bovine liver and blood samples. The DNAA system was effective for the determination of As, Cu, Fe, Hg, Mo, Rb, Sb, Se, and Zn without yield determinations and with a minimum turn-around time of approximately 3 days

Toddler milk advertising in Australia: the infant formula ads we have when we don’t have infant formula ads

The Marketing in Australia of Infant Formula: Manufacturers’ and Importers’ Agreement (MAIF) prevents manufacturers and importers from advertising infant formula. However, toddler milks, which share brand identities with infant formula, are advertised freely; and recent research suggests consumers fail to distinguish between advertising for infant formula and for toddler milk. This study examined whether Australian parents recalled having seen advertisements for ‘formula’. Most respondents (66.8%) reported seeing an advertisement for infant formula, with those who had only seen non-retail advertising more than twice as likely to believe that they had seen such an advertisement as those who had only seen retail advertising. This suggests that toddler milk advertisements are functioning as defacto infant formula advertisements in Australia. Thus the MAIF is failing to achieve its stated purpose

A new Bayesian approach incorporating covariate information for heterogeneity and its comparison with HLOD

We consider a new Bayesian approach for heterogeneity that can take into account categorical covariates, if available. We use the Genetic Analysis Workshop 14 simulated data to first compare the Bayesian approach with the heterogeneity LOD, when no covariate information is used. We find that the former is more powerful, while the two approaches have comparable false-positive rates. We then include informative covariates in the Bayesian approach and find that it tends to give more precise interval estimates of the disease gene location than when covariates are not included. We had knowledge of the simulation models at the time we performed the analyses

Well-being in action

This thesis consists of a critique of two influential accounts of what is good for a human being: that which satisfies their desires, and that which gives them pleasure. Both accounts are therefore ‘subjectivist’ in that they are centred on the personal values of the agent in question. In contrast to the conventional philosophical approach, the study will evaluate these two theories in the context of their suitability for guiding our deliberations about what to do and how best to live. It offers an argument against both theories when they are thus put to work as a basis for making our choices. The argument proceeds by considering what is required in order for us to develop and maintain certain practical and intellectual powers that are essential to our forming an adequate conception of our own good and effectively pursuing this ideal in practice. I will claim that gaining and maintaining these powers requires a certain kind of supportive social context – and, in particular, engagement in certain kinds of formative relationships with others. However, participating in these relationships in the required way necessitates our having an openness to learning from and being influenced by these others that is not possible for an agent who fully commits to either of our two subjectivist views

Passive Multi-Target Tracking Using the Adaptive Birth Intensity PHD Filter

Passive multi-target tracking applications require the integration of multiple spatially distributed sensor measurements to distinguish true tracks from ghost tracks. A popular multi-target tracking approach for these applications is the particle filter implementation of Mahler's probability hypothesis density (PHD) filter, which jointly updates the union of all target state space estimates without requiring computationally complex measurement-to-track data association. Although this technique is attractive for implementation in computationally limited platforms, the performance benefits can be significantly overshadowed by inefficient sampling of the target birth particles over the region of interest. We propose a multi-sensor extension of the adaptive birth intensity PHD filter described in (Ristic, 2012) to achieve efficient birth particle sampling driven by online sensor measurements from multiple sensors. The proposed approach is demonstrated using distributed time-difference-of-arrival (TDOA) and frequency-difference-of-arrival (FDOA) measurements, in which we describe exact techniques for sampling from the target state space conditioned on the observations. Numerical results are presented that demonstrate the increased particle density efficiency of the proposed approach over a uniform birth particle sampler.Comment: 21st International Conference on Information Fusio