Synchronous reproduction may facilitate introgression in a hybrid mussel (Mytilus) population

Mussel populations on the Irish Atlantic coast comprise an interbreeding mixture of the blue mussel, Mytilus edulis (L.) and the Mediterranean mussel, Mytilus galloprovincialis (Lmk.). The occurrence of hybrid genotypes varies between sites but can be as high 80%. This study compares the reproductive cycle of M. edulis, M. galloprovincialis and their hybrids to determine if the extensive hybridisation observed at Irish Atlantic coast sites is linked to spawning synchrony between the two taxa. Mussels (40-45 mm size class) were collected monthly from a sheltered shore in Galway Bay from January to December 2005. Two major spawning events (March- June and September-October) were observed and gametogenesis took place throughout the year. The spawning cycles of the three taxa were largely overlapping. Small differences were observed in the timing of peak spawning which occurred in March and October in M. galloprovincialis and in May-June and September in M.edulis. Spawning of hybrid individuals was intermediate between the parental genotypes. Fecundity was slightly higher in M. galloprovincialis females compared to the other taxa (up to 30% difference, p<0.05). This apparent advantage is not shared by the sexes and is likely being offset by high numbers of hybrid genotypes releasing gametes during peak spawning of M. galloprovincialis. There was no evidence for increased mortality in hybrid males; sex ratios did not deviate from the 1:1 ratio. The results show that in this region of the hybrid zone the timing of reproduction does not present a barrier to gene flow between M. edulis and M. galloprovincialis. Nonetheless, small differences in the timing of peak spawning may increase the likelihood of conspecific fertilisation at certain times of the year. Hybrids outnumber the parental genotypes, undergo complete gametogenesis and show no evidence of depressed fitness (i.e. hybrids are reproductively competent suggesting a high degree of introgression.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.