The assimilation and chronic effects of sub-lethal concentrations of Endosulfan on condition and spawning in the common mussel Mytilus edulis

The rate of uptake of Endosulfan by Mytilus edulis L. exposed to pesticide concentrations of 0.1, 0.5, and 1.0 mg/l, and its subsequent elution on removal to clean sea water, was investigated. Higher residue levels were recorded for mussels exposed to higher concentrations of the pesticide, but concentration factors were reduced. There was a rapid initial fall in tissue residue levels on transfer to clean sea water due, it is suggested, to elution of Endosulfan adsorbed on particulate matter assimilated in the gut. The spawning period was prolonged at higher concentrations and, at 1.0 mg/l, the onset of spawning was delayed, possibly due to interference with gamonic action. At 0.1 mg/l, the minor protraction of the spawning period may reflect the effect of experimental tank conditions. No seasonal trend was obvious, and there was an exaggeration of the expected fall in condition in mussels exposed to higher concentrations of Endosulfan. In controls, the expected seasonal trend was reduced.

Dynamic evolution of the genetic search region through fuzzy coding

A technique for automatic exploration of the genetic search region through fuzzy coding (Sharma and Irwin, 2003) has been proposed. Fuzzy coding (FC) provides the value of a variable on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree-of-membership. It is an indirect encoding method and has been shown to perform better than other conventional binary, Gray and floating-point encoding methods. However, the static range of the membership functions is a major problem in fuzzy coding, resulting in longer times to arrive at an optimum solution in large or complicated search spaces. This paper proposes a new algorithm, called fuzzy coding with a dynamic range (FCDR), which dynamically allocates the range of the variables to evolve an effective search region, thereby achieving faster convergence. Results are presented for two benchmark optimisation problems, and also for a case study involving neural identification of a highly non-linear pH neutralisation process from experimental data. It is shown that dynamic exploration of the genetic search region is effective for parameter optimisation in problems where the search space is complicated.