This work focuses on the MLP Neural Network in order to solve the problem of an apartment's monetary worth appraisement at the Porto Alegre city (south Brazil). Many factors are involved in this calculation, like the size of the apartment, the environment conditions of the site, the actual conservation state of the apartment, the neighborhood, it's geographical localization in the city, etc.. Two data bases where investigated: the first one is a list of apartments for sale and the second one is a list of apartments for rent. The analysis was performed with the use of both Linear Regression and Neural Network methods, with the purpose of comparison. The last one was used mainly to model the strong nonlinearities due to the geographical position of the apartments, since there is not a linear monotonic relation between position and value.

No abstract

Background: NEP1-like proteins (NLPs) are a novel family of microbial elicitors of plant necrosis. Some NLPs induce a hypersensitive-like response in dicot plants though the basis for this response remains unclear. In addition, the spatial structure and the role of these highly conserved proteins are not known.

Nep1-like proteins (NLPs) are a novel family of microbial elicitors of plant necrosis that induce a hypersensitive-like response in dicot plants. The spatial structure and role of these proteins are yet unknown. In a paper published in BMC Plant Biology (2008; 8:50) we have proposed that the core region of Nep1-like proteins (NLPs) belong to the Cupin superfamily. Based on what is known about the Cupin superfamily, in this addendum to the paper we discuss how NLPs could form oligomers.

No abstract