The paper deals with a method of the Nye figures construction for micropolar elastic solids. The method of tensors of the 4th and 3rd ranks representations by means of blocks of two-dimensional matrices and relationships between their elements is widely known in crystallography. Such approach makes it possible to simply determine the number of independent constitutive constants for micropolar elastic solids and guarantee the absence of relationships between them. In frameworks of the present study, the two-dimensional Nye figures for an ultraisotropic micropolar elastic solid were figured out based on the corresponding figures for hemitropic and isotropic micropolar elastic solids. It is shown that the constitutive tensors of ultraisotropic material characterized by only 4 independent constitutive constants: shear modulus of elasticity, Poisson’s ratio, characteristic nano/microlength and another dimensionless constant.

This paper describes the influence of intensity of external additive white noise on the nonlinear dynamics of rectangular plates as mechanical systems with an infinite number of degrees of freedom. A new scenario is discovered, which is a combination of the classic Feigenbaum and Pomeau–Manneville scenarios. The classical methods of nonlinear dynamics and wavelet transforms were used to reveal the peculiarities of a modified scenario. The noise-induced transitions are investigated, and it is shown that the noise exposure is accompanied with the transition to chaotic fluctuations with a lower amplitude of the driving load. It is determined that the presence of external fluctuations does not affect the scenario of transition from harmonic to chaotic fluctuations.

This paper describes the visualization of the study of signal entropy in two groups of subjects. Brain activity signals were obtained using electroencephalogram (EEG). Two groups of adolescents-a schizophrenic group and a control group-were the subjects of the study. For each of the participants in both groups, 16 channels were recorded. Multi-scale entropy, model entropy, and approximated entropy were analyzed for signal complexity. The results of the entropic assessments were compared in the form of topographic images. Topographic images of the head surface were obtained based on a spherical spline. The activity of brain hemispheres for both groups was compared using the mean values of the cross-correlation function. The study showed that the visualization of EEG signals could be a useful tool for classification of patients with schizophrenia and control groups. The analysis may be considered useful for the psychiatric examination of patients with schizophrenia. On the other hand, the proposed approach is useful to extend the functionality of the educative robotics. Identification of schizophrenic subjects in the group of students provided by the robotic complex on the fly helps to avoid possible antisocial behavior while applying adequate training methods.