Polybrominated diphenyl ethers and age: analysis of pooled human blood serum from birth to over 60 years

Polybrominated diphenyl ethers (PBDEs) are considered to be a cost effective and efficient way to reduce flammability therefore reducing harm caused by fires. PBDEs are incorporated into a variety of manufactured products and are found worldwide in biological and environmental samples (e.g. Hites et al. 2004). Unlike other persistent organic pollutants there is limited data on PBDE concentrations by age and/or other population specific factors. Some studies have shown no variation in adult serum PBDE concentrations with age (e.g. Mazdai et al., 2003, Meironyte Guvenius et al., 2003) while Petreas et al. (2003) and Schecter et al. (2005) found results to be suggestive of an age trend in adult data but no statistically significant correlation was found. In addition to the data on adult concentrations there is limited data which investigates the levels of PBDEs in infants and young children. Fangström et al. (2005) showed that in seven year olds there was no difference in PBDE concentration when compared to adult concentrations. While Thomsen et al. (2002, 2005) found the concentration of PBDEs in pooled samples of blood serum from a 0-4 years age group to be higher than other age groups (4 to > 60 years). In addition, a family of four was studied in the U.S. and the concentrations were found to be greatest in the 18-month-old infant followed by the 5 year old child, then the mother and father (Fischer et al., 2006). The objectives of this study were to assess age, gender and regional trends of PBDE concentrations in a representative sample of the Australian population.

Estimating the prevalence of unregistered driving in Queensland. Report to Queensland Department of Transport and Main Roads

A state-wide observational study was undertaken by the Centre for Accident Research and Road Safety – Queensland (CARRS-Q) in order to investigate the prevalence of unregistered vehicles on Queensland roads. This study was conducted on behalf of the Queensland department of Transport and Main Roads (TMR). This study builds upon research commissioned by Queensland Transport and conducted in 2000, 2003 and 2005. Vehicles were observed throughout Queensland from April 13th, 2010 to May 8th, 2010 in a mix of small rural towns, regional centres and metropolitan locations. The locations sampled for this study were restricted to destinations (e.g. shopping centres, hospitals, airports and park-and-ride facilities) rather than residential areas, and a variety of different destinations were sampled. Sampling vehicles in these types of locations provides a higher probability that the vehicles captured in the survey are being driven on a regular basis (Younglove, et al. 2004).

Investigating the effectiveness of an ecological approach to learning design in a first year mathematics for engineering unit

This paper reports on the results of a project aimed at creating a research-informed, pedagogically reliable, technology-enhanced learning and teaching environment that would foster engagement with learning. A first-year mathematics for engineering unit offered at a large, metropolitan Australian university provides the context for this research. As part of the project, the unit was redesigned using a framework that employed flexible, modular, connected e-learning and teaching experiences. The researchers, interested in an ecological perspective on educational processes, grounded the redesign principles in probabilistic learning design (Kirschner et al., 2004). The effectiveness of the redesigned environment was assessed through the lens of the notion of affordance (Gibson, 1977,1979, Greeno, 1994, Good, 2007). A qualitative analysis of the questionnaire distributed to students at the end of the teaching period provided insight into factors impacting on the successful creation of an environment that encourages complex, multidimensional and multilayered interactions conducive to learning.

Stochastic growth models for analyzing crustacean data

The contemporary methodology for growth models of organisms is based on continuous trajectories and thus it hinders us from modelling stepwise growth in crustacean populations. Growth models for fish are normally assumed to follow a continuous function, but a different type of model is needed for crustacean growth. Crustaceans must moult in order for them to grow. The growth of crustaceans is a discontinuous process due to the periodical shedding of the exoskeleton in moulting. The stepwise growth of crustaceans through the moulting process makes the growth estimation more complex. Stochastic approaches can be used to model discontinuous growth or what are commonly known as "jumps" (Figure 1). However, in stochastic growth model we need to ensure that the stochastic growth model results in only positive jumps. In view of this, we will introduce a subordinator that is a special case of a Levy process. A subordinator is a non-decreasing Levy process, that will assist in modelling crustacean growth for better understanding of the individual variability and stochasticity in moulting periods and increments. We develop the estimation methods for parameter estimation and illustrate them with the help of a dataset from laboratory experiments. The motivational dataset is from the ornate rock lobster, Panulirus ornatus, which can be found between Australia and Papua New Guinea. Due to the presence of sex effects on the growth (Munday et al., 2004), we estimate the growth parameters separately for each sex. Since all hard parts are shed too often, the exact age determination of a lobster can be challenging. However, the growth parameters for the aforementioned moult processes from tank data being able to estimate through: (i) inter-moult periods, and (ii) moult increment. We will attempt to derive a joint density, which is made up of two functions: one for moult increments and the other for time intervals between moults. We claim these functions are conditionally independent given pre-moult length and the inter-moult periods. The variables moult increments and inter-moult periods are said to be independent because of the Markov property or conditional probability. Hence, the parameters in each function can be estimated separately. Subsequently, we integrate both of the functions through a Monte Carlo method. We can therefore obtain a population mean for crustacean growth (e. g. red curve in Figure 1). [GRAPHICS]