Basic principles of building of E-network model of a complex technical system

Methodological bases of building of dynamic models of hybrid systems using principles of a «block» modelling are exposed on the basis of the E-network formalism. The presented methods are based on use of mechanisms of hierarchical interaction of dynamic model elements. Principles of organization of E-network hierarchical circuits with use of rigid and flexible structures are shown. The mechanism of interaction of static and dynamic components is specified

Highly inheritable variable components in the clonal plantation of Scots pine

The variability of the data on elemental composition of needles from the clonal population of Scots pine Pinus sylvestris L., established on the long­term field experiment, was studied by principal components extraction from the normalized data matrix, and broad­sense heritability Н2, i.e. the contribution of clones to the total data variance was calculated both for the original variables and principal components. To find the linear combinations of variables with the highest heritability the discriminant analysis was performed. The results suggest the importance of multivariate statistics for forest genetics and selection in targeting search for genetic marker traits in the populations of woody plants, in assessing genetic differentiation among populations, identification of the best genotypes via their phenotypes, etc

Interaction of ultrarelativistic electron and proton bunches with dense plasmas

Here we discuss the possibility of employment of ultrarelativistic electron and proton bunches for generation of high plasma wakefields in dense plasmas due to the Cherenkov resonance plasma-bunch interaction. We estimate the maximum amplitude of such a wake and minimum system length at which the maximum amplitude can be generated at the given bunch parameters.Comment: 8 page

Estimation of social network user's influence in a given area of expertise

Nowadays social networks are frequently used to express personal opinion on a topic of interest. Some users' opinion has more informational influence than others do. These users are called influential users. There are services that allow evaluating how popular and influential users are; however, any information on evaluation methods is proprietary and represents know-how of such software services. Furthermore, most services could not provide extensive data on the influential users within the specified area of knowledge. This article proposes the method of evaluating a user influence index within a social network in a given area of expertise