AbstractThis papers refers to demographic processes in the period from the 19th century through to the present and tries to define what they will look like in the future. Demographic trends i.a. relating to fertility, mortality, migrations, the process of family-union-household formation and dissolution, and the process of population ageing, are described by the concepts of demographic transformations: first, second and third. The transformation of demographic trends has coexisted and will coexist with globalization processes, though the scope of the mutual influence changes over time. Despite the fact that it takes place in various geographical regions, the transformation of demographic trends is characterised by high cultural diversity and socio-economic development.
In this paper, the PLC-based (Programmable Logic Controller) industrial implementation in the form of the general-purpose function block for ADRC (Active Disturbance Rejection Controller) is presented. The details of practical aspects are discussed because their reliable implementation is not trivial for higher order ADRC. Additional important novelties discussed in the paper are the impact of the derivative backoff and the method that significantly simplifies tuning of higher order ADRC by avoiding the usual trial and error procedure. The results of the practical validation of the suggested concepts complete the paper and show the potential industrial applicability of ADRC.
Despite the considerable progress that has recently been made in medicine, the treatment of viral infections is still a problem remaining to be solved. This especially concerns infections caused by newly emerging patogenes such as: human immunodeficiency virus, hepatitis C virus or SARS-coronavirus. There are several lines of evidence that the unusual genetic polymorphism of these viruses is responsible for the observed therapeutic difficulties. In order to determine whether some parameters describing a very complex and variable viral population can be used as prognostic factors during antiviral treatment computational methods were applied. To this end, the structure of the viral population and virus evolution in the organisms of two patients suffering from chronic hepatitis C were analyzed. Here we demonstrated that phylogenetic trees and Hamming distances best reflect the differences between virus populations present in the organisms of patients who responded positively and negatively to the applied therapy. Interestingly, the obtained results suggest that based on the elaborated method of virus population analysis one can predict the final outcome of the treatment even before it has started.