The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils.

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil-water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil-water reaction in this case study). The probabilities of cells belonging to classes of oil-water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.

Neurological disability in leprosy: incidence and gender association in Sergipe, Brazil.

The environmental impact assessment process is over 40 years old and has dramatically expanded. Topics, such as social, health and human rights impact are now included. The main body of an impact analysis is generally hundreds of pages long and supported by countless technical appendices. For large, oil/gas, mining and water resources projects both the volume and technical sophistication of the reports has far exceeded the processing ability of host communities. Instead of informing and empowering, the reports are abstruse and overwhelming. Reinvention is required. The development of a visual integrated impact assessment strategy that utilizes remote sensing and spatial analyses is described.

Biomphalaria species distribution and its effect on human Schistosoma mansoni infection in an irrigated area used for rice cultivation in northeast Brazil.

The role of irrigated areas for the spread of schistosomiasis is of worldwide concern. The aim of the present study was to investigate the spatial distribution of the intermediate snail host Biomphalaria in an area highly endemic for schistosomiasis due to Schistosoma mansoni, evaluating the relationship between irrigation and types of natural water sources on one hand, and the influence of place and time of water exposure on the intensity of human infection on the other. A geographical information system (GIS) was used to map the distribution of the intermediate snail hosts in Ilha das Flores, Sergipe, Brazil, combined with a clinical/epidemiological survey. We observed a direct correlation between the intensity of human infection with S. mansoni and irrigation projects. Malacological studies to identify snail species and infection rates showed that B. glabrata is the main species responsible for human schistosomiasis in the municipality, but that B. straminea also plays a role. Our results provide evidence for a competitive selection between the two snail species in rice fields with a predominance of B. glabrata in irrigation systems and B. straminea in natural water sources.