Operational problems related to the preparation of the seawater soluble fraction of crude oil

Owing to the importance of dissolution and weathering processes following oil spills, this work focused on the operational (quantitative) aspects related to the dissolution of petroleum-derived products, as well as the influence of solar light on both dissolution and the photoproduction of hydrogen peroxide. Four Brazilian crude oil samples were used to study the transfer process of organic compounds from the crude oil film to the aqueous phase (natural seawater) over a period of up to 45 days. Dissolved organic carbon (DOC), measured by non-dispersive infrared spectroscopy followed by high temperature catalytic combustion, was used to follow the partitioning between the two phases. Aqueous DOC values increased as a function of time (up to 15 days) until equilibrium was reached at concentrations ranging from 5 to 45 mg C L(-1). The final DOC concentration as well as the rate of dissolution depends on the nature of the crude oil. When exposed to sunlight, the dissolution was enhanced by up to 67.3%, and inorganic peroxides were generated in the concentration range from 4.5 up to 8.0 micromol L(-1) after 7.3 h irradiation. These results indicate that there is a need for a standard procedure for the production of the WSF in order to generate a more reliable tool to assess the impact of oil spills on the marine environment.     

Logistic regression and fuzzy logic as a classification method for feral fish sampling sites

This study presents a classification method combining logistic regression and fuzzy logic in the determination of sampling sites for feral fish, Nile Tilapia (Tilapia rendalli). This method statistically analyzes the variable domains involved in the problem, by using a logistic regression model. This in turn generates the knowledge necessary to construct the rule base and fuzzy clusters of the fuzzy inference system (FIS) variables. The proposed hybrid method was validated using three fish stress indices; the Fulton Condition Factor (FCF) and the gonadossomatic and hepatossomatic indices (GSI and HSI, respectively), from fish sampled at 3 different locations in the Rio de Janeiro State. A multinomial logistic regression allowed for the FIS construction of the proposed method and both statistical approaches, when combined, complemented each other satisfactorily, allowing for the construction of an efficient classification method regarding feral fish sampling sites that, in turn, has great value regarding fish captures and fishery resource management.