The effect of semen analysis factors regarding IUI with male factor infertility

AbstractBackground and Purpose: There is evidence in literature that IUI is the first line treatment and the most cost-effective procedure for mild to moderate male factor sub-fertility, however, the relative influence of various semen characteristics with the likelihood of a successful outcome is controversial. This study is designed to show the correlation between semen parameters and the pregnancy rate in patients, with mild to moderate male factor sub-fertility and whose wives were normal and underwent hyper-stimulation, including IUI.Materials and Methods: From January 2005 to January of 2006, 95 couples with male factor infertility underwent 140 IUI cycles with husbands washed semen were included in this study .They were divided into two groups based on semen parameters, mild and moderate. Post- wash sperm parameters, type of infertility (primary and secondary), male/ female age and duration of infertility were evaluated and correlated with clinical pregnancy outcome.Results: The clinical pregnancy rate per cycle was 26 (18.5%); 15 (21.4%) in mild group, while 11(15.7%) in moderate group. The clinical pregnancy rate per couple was 27.3%.There were significant correlation between female age, duration of infertility, sperm concentration and progressive motility, and clinical pregnancy.Conclusion: Our findings suggest that post- wash sperm concentration and progressive motility, female age and duration of infertility are the most important factors for prediction of successful pregnancJ Mazand Univ Med Sci 2008; 18(65):10-18 (Persian

Modeling of Bicomponent Mixing System Used in the Manufacture of Wind Generator Blades

The clean energy use has increased during the last years, especially, electricity generation through wind energy. Wind generator blades are usually made by bicomponent mixing machines. With the aim to predict the behavior of this type of manufacturing systems, it has been developed a model that allows to know the performance of a real bicomponent mixing equipment. The novel approach has been obtained by using clustering combined with regression techniques with a dataset obtained during the system operation. Finally, the created model has been tested with very satisfactory results