The reverse mortgage market has been expanding rapidly in developed economies in recent years. Reverse mortgages provide an alternative source of funding for retirement income and health care costs. Increase in life expectancies and decrease in the real income at retirement continue to worry those who are retired or close to retirement. Therefore, financial products that help to alleviate the "risk of living longer" continue to be attractive among the retirees. Reverse mortgage contracts involve a range of risks from the insurer's perspective.

Purpose A recursive scheme for the ALIENOR method is proposed as a remedy for the difficulties induced by the method. A progressive focusing on the most promising region, in combination with a variation of the density of the alpha-dense curve, is proposed. Design/methodology/approach ALIENOR method is aimed at reducing the space dimensions of an optimization problem by spanning it by using a single alpha-dense curve: the curvilinear abscissa along the curve becomes the only design parameter for any design space.

The study of complex hereditary diseases is a very challenging area of research. The expanding set of in silico approaches offers a flourishing ground for the acceleration of meaningful findings in this area by exploitation of rich and diverse sources of omic data. These approaches are cheap, flexible, extensible, often complementary and can continuously integrate new information and tests to improve the selection of genes responsible for hereditary diseases.

In recent years, the development of high throughput devices for the massive parallel analyses of genomic data has lead to the generation of large amount of new biological evidences and has triggered the proliferation of data mining algorithms for the extraction of meaningful information. Microarrays for gene expression analyses are part of this revolution and provide important insight in molecular biology often in the form of coherent sets of genes representing previously uncharacterized processes.