Renata Kasperska

Polyoptimal design of sandwich cylindrical panels with the application of an expert system

Thin-walled sandwich structures have become extremely useful because of their high strength-to-mass and stiffness-to-mass ratios. The results of the bicriteria optimization of thin-walled sandwich cylindrical panels under combined loads are presented in this article. Panel mass and panel deformability are two objective functions, where panel deformability is defined with the help of bending rigidity. A set of constraints includes stability and stress conditions, a constraint connected with the importance of applied theoretical models, and technological and constructional requirements. The optimization problem was solved using the Pareto concept of optimality and application of the OPTIKON computer program, which implements elements of an expert system. The OPTIKON program was designed to solve multicriteria optimization problems for non-linear engineering models with discrete and continuous sets of design variables. The results of numerical calculations are presented as tables and diagrams.

Bioenergetics of life, disease and death phenomena

In this article, some new aspects of unified cell bioenergetics are presented. From the perspective of unified cell bioenergetics certain subsequent stages of cancer development, from initiation stage, through transformation to metastasis, are analyzed. Here we show that after transformation, cancer cells are permanently exposed to reactive oxygen species, that causes continual random DNA mutations and as a result genome and chromosomal destabilizations. The modern cancer attractor hypothesis has been extended in explaining cancer development. Discussion is conducted in light of current cancerogenesis research, including bioenergetic cancer initiation, the somatic mutation theory and the tissue organization field theory. In the article reasons complicating the discovery of patterns of cancer genome changes and cancer evolution are presented. In addition certain cancer therapeutic aspects are given attention to.

A new approach to the automatic identification of organism evolution using neural networks

Automatic identification of organism evolution still remains a challenging task, which is especially exiting, when the evolution of human is considered. The main aim of this work is to present a new idea to allow organism evolution analysis using neural networks. Here we show that it is possible to identify evolution of any organisms in a fully automatic way using the designed EvolutionXXI program, which contains implemented neural network. The neural network has been taught using cytochrome b sequences of selected organisms. Then, analyses have been carried out for the various exemplary organisms in order to demonstrate capabilities of the EvolutionXXI program. It is shown that the presented idea allows supporting existing hypotheses, concerning evolutionary relationships between selected organisms, among others, Sirenia and elephants, hippopotami and whales, scorpions and spiders, dolphins and whales. Moreover, primate (including human), tree shrew and yeast evolution has been reconstructed.