Genetic evidence of two sibling species within the Contracoecum ogmorhini Johnson & Mawson 1941 complex (Nematoda; Anisakidae) from otariid seals in boreal and austral regions

Genetic variation of Contracaecum ogmorhini (sensu lato) populations from different otariid seals of the northern and southern hemisphere was studied on the basis of 18 enzyme loci as well as preliminary sequence analysis of the mitochondrial cyt b gene (260 bp). Samples were collected from Zalophus californianus in the boreal region and from Arctocephalus pusillus pusillus, A. pusillus doriferus and A. australis from the austral region. Marked genetic heterogeneity was found between C. ogmorhini (sensu lato) samples from the boreal and austral region, respectively. Two loci (Mdh-2 and NADHdh) showed fixed differences and a further three loci (Iddh, Mdh-1 and 6Pgdh) were highly differentiated between boreal and austral samples. Their average genetic distance was DNei = 0.36 at isozyme level. At mitochondrial DNA level, an average proportion of nucleotide substitution of 3.7% was observed. These findings support the existence of two distinct sibling species, for which the names C. ogmorhini (sensu stricto) and C. margolisi n. sp., respectively, for the austral and boreal taxon, are proposed. A description for C. margolisi n. sp. is provided. No diagnostic morphological characters have so far been detected; on the other hand, two enzyme loci, Mdh-2 and NADHdh, fully diagnostic between the two species, can be used for the routine identification of males, females and larval stages. Mirounga leonina was found to host C. ogmorhini (s.s.) inmixed infections with C. osculatum (s.l.) (of which C. ogmorhini (s.l.) was in the past considered to be a synonym) and C. miroungae; no hybrid genotypes were found,confirming the reproductive isolation of these three anisakid species. The hosts and geographical range so far recorded for C. margolisi n. sp. and C. ogmorhini (s.s.) are given.

Muitiobjective pressurized water reactor reload core design by nondominated genetic algorithm search

The design of pressurized water reactor reload cores is not only a formidable optimization problem but also, in many instances, a multiobjective problem. A genetic algorithm (GA) designed to perform true multiobjective optimization on such problems is described. Genetic algorithms simulate natural evolution. They differ from most optimization techniques by searching from one group of solutions to another, rather than from one solution to another. New solutions are generated by breeding from existing solutions. By selecting better (in a multiobjective sense) solutions as parents more often, the population can be evolved to reveal the trade-off surface between the competing objectives. An example illustrating the effectiveness of this novel method is presented and analyzed. It is found that in solving a reload design problem the algorithm evaluates a similar number of loading patterns to other state-of-the-art methods, but in the process reveals much more information about the nature of the problem being solved. The actual computational cost incurred depends: on the core simulator used; the GA itself is code independent.