Urinary arsenic, porphyrins and malondialdehyde in a population 16 years after arsenic mitigation program in Xinjian, China

Arsenic contamination of groundwater (0.05 to 0.84 mg/L) in Kuitun, Xinjiang was first found in 1970’s. Alternative clean surface water was introduced in 1985. We aimed to assess the exposure and heath outcome since the mitigation. In 2000, we collected a total of 360 urine samples from villagers from the endemic area and a nearby control area for arsenic (As), porphyrins and malondialdehyde (MDA) measurements. The averaged urinary As level of villagers from the endemic site (117±8.3 μg/g creatinine; 4.2 to 943.8 μg/g creat) was higher than that of the control site (73.6±3.2 μg/g creat). No significant differences were found in urinary porphyrins or MDA between the endemic and control sites. However, when the urinary arsenic was higher than 150 μg/g creat, these two biomarkers were higher in the exposed group than the control. Within the exposed group, villagers with arsenic-related skin symptoms had higher arsenic, uroporphyrin and MDA compared to those who had not shown symptoms. Sine the water mitigation, villagers whose urinary arsenic levels were 270 μg/g creat dropped from 20% to 10% of the population. Population with arsenic-related skin symptoms remained unchanged at 31%. We noted that 7.8% of those who had skin lesions were born after the implementation of intervention and that some villagers still prefer to drink the groundwater. Further, in the dry season, lack of surface water and electrical power breakdowns are to blame for failure to ensure continuous supply of clean water. It is concluded that despite the prompt action and successful water mitigation program to curb arsenic poisonings, it is essential to continue to monitor the health outcome of this population.

Predictive vaccinology: Optimisation of predictions using support vector machine classifiers

Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial neural networks as prediction algorithms. We report a system based on support vector machines that outperforms previously published methods. Preliminary testing showed that it can predict peptides binding to HLA-A2 and -A3 super-type molecules with excellent accuracy, even for molecules where no binding data are currently available.

Using machine vision classification to control access of animals to water

Invasive vertebrate pests together with overabundant native species cause significant economic and environmental damage in the Australian rangelands. Access to artificial watering points, created for the pastoral industry, has been a major factor in the spread and survival of these pests. Existing methods of controlling watering points are mechanical and cannot discriminate between target species. This paper describes an intelligent system of controlling watering points based on machine vision technology. Initial test results clearly demonstrate proof of concept for machine vision in this application. These initial experiments were carried out as part of a 3-year project using machine vision software to manage all large vertebrates in the Australian rangelands. Concurrent work is testing the use of automated gates and innovative laneway and enclosure design. The system will have application in any habitat throughout the world where a resource is limited and can be enclosed for the management of livestock or wildlife.

The effect of residence time and aeration on coal recovery within the high density zone of a flotation machine

The high intensity zone within the Jameson Cell is the downcomer. It is largely external and separated from the flotation tank. This, together with operation of the downcomer under vacuum, rather than at elevated pressure and the absence of moving parts, allows ready access to the high intensity zone for measurement and analysis. Experimentation was conducted allowing measurements of recovery for residence times of between 20 milliseconds and ten seconds within the downcomer of a Jameson Cell. The affect of aeration rate on the recovery of different particle sizes was also studied.

Critical feature analysis of a radiotherapy machine

The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An `assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code.