Multisystem Inflammatory Syndrome in Children (MIS-C) associated with new coronavirus infection (COVID-19), with signs of Kawasaki disease (KD) and toxic shock syndrome, well-defined diagnostic criteria, is the most severe manifestation of COVID-19 in pediatric patients. MIS-C is analogous to the cytokine storm in children with COVID-19. The article presents a clinical observation of a child with MIS-C with a lethal outcome. Clinical and anamnestic data, the results of laboratory and instrumental research allowed to diagnose MIS-C in a 2-year-old girl with full KD form. Autopsy results, detailed microscopic examination, which revealed systemic vasculitis of small and mediumsized vessels, inflammatory infiltrates in different organs, are presented, clinical and morphological comparisons are made.

The work is aimed at solving the actual problem of analyzing the interaction of market participants. The degree of unpredictability of market participant’s behavior determines economic risks and manifests itself as a violation of information symmetry. Asymmetry is expressed in different degrees of awareness of groups of sellers and groups of buyers-users of the product about the state of the market, which determines the different behavioral moods and intentions of market participants. The possibility of using the Shannon entropy and fractal dimension indicators to assess the degree of ordering of relationships between groups of buyers and the results of their behavior is considered.This allows us to draw conclusions about the logic of relationships between the behavior of different clients. An iterative box-counting algorithm is used to determine the approximate value of the Minkowski fractal dimension.As a metric of distances between the signs of transactions of pairs of clients, the cosine distance can be used for the case of sparse data.It is shown how the fractal dimension will change in the case of observation of more stable relationships between groups of clients.

The work is devoted to the actual problem of constructing decision trees with a multidimensional response of the optimal structure, which are used to create predictive models for the evolution of complex systems. The aim of the work is to generalize the experience of constructing decision trees with a multidimensional response and to study the homogeneity and violation of symmetry of classes of models of socioeconomic systems based on decision trees, which most clearly show the process of changing the states of the system and filling the space of possibilities, as well as signs of self-organization, which is cause of evolutionary processes and a consequence of symmetry breaking. An example of building a tree with a multidimensional response for a credit scoring problem is shown. The approaches described in the work show the connection between the phenomenon of symmetry breaking and the phenomenon of heteroscedasticity of regression models. The possibility of overcoming the problem of instability of finite predictions of models based on decision trees by developing approaches to the study of the heteroscedasticity of predictive models of socioeconomic systems and the homogeneity of groups of objects is considered.

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