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Two cores of bottom sediments were collected in 2018 to a depth of ∼200 cm in the deepest part of the Scheckino reservoir on the Upa River (9500 km 2), Tula region, Russia. This area was severely contaminated by radiocesium (r-Cs) after the Chernobyl accident in 1986. The fact that 137Cs activity concentrations in a specific horizon of the bottom sediments correspond to 137Cs concentrations associated with suspended matter delivered to the reservoir, provides a basis for constructing the dynamics of particulate 137Cs activity concentrations in the Upa River catchment from 1986 to 2017. Over the time since the Chernobyl accident, the particulate 137Cs concentrations have decreased by more than an order of magnitude, with only minor changes occurring during the last 15 years. Using a typical value for the distribution coefficient Kd for the rivers of the Chernobyl contamination zone, dissolved 137Cs activity concentrations in the Upa River have been estimated and their changes over the past 30 years since the accident have been studied. The resulting estimates of dissolved 137Cs concentrations in the Upa River have been found to be in good agreement with measured data over the period 1987–1991. The proposed and tested method provides a basis for reconstructing the long-term dependence of radionuclide concentrations in rivers and reservoirs based on their vertical distribution in bottom sediments. Reconstructed time dependencies of particulate and dissolved 137Cs activity concentrations in the Upa River were found to be described well by the proposed semi-empirical "diffusion" model based on an assumption that the time dependency of particulate r-Cs in the river corresponds to the time dependency of its concentration in top soil layers across the catchment which can be approximated by a dispersion-convection equation with physically meaningful parameters. [ABSTRACT FROM AUTHOR]

In recent years consulting for organizations has become very popular. Let us consider marketing consulting which includes several types. They can be divided in the following three directions: single solutions to selected aspects; solution of a set of problems; outsourcing of certain activities. Each of these directions is heterogeneous. Successful marketing consulting development requires deep investigation of processes taking place in it and its environment. One of initial important stages in studying organization’s activity in marketing consulting is creating a cognitive model of this activity. The model considers important variables of external and internal environment as well as qualitative cause-and-effect relations between them. Later, a quantitative model of consulting activity is constructed on the basis of this model, with the help of which the methods of successful consulting organization management are developed. Initial statements and assumptions concerning the structure of the consulting activity model are proposed based on the analysis of the processes taking place in the model. The initial model received serves as the basis for creating more detailed models. The consulting organization activity model takes into account both external and internal factors. An enlarged scheme of interrelations of the major groups of factors is created taking into account the features of marketing consulting: economic parameters; external demand for consulting services; competitors; marketing tactics; order flow; personnel; order execution. The obtained model can be used also for quantitative analysis of activity of a small consulting organization. It considers variables that are important for this activity and their relations. The model allows identifying a change in the structure of demand as a result of a change of phases of a business cycle. It is possible to select the appropriate marketing tactics on the basis of the parameters considered. Apart from that, the paper shows that the activity of an organization using this model is sustainable. Thus, a cognitive model of organization activity in the consulting market is an important step in understanding the processes being analyzed, which is necessary for a transfer to upper level models for raising the financial sustainability of the organizations considered. [ABSTRACT FROM AUTHOR]

Within the framework of this work the solution of the problem of synthesis of adaptive electronic document management system (EDMS) is considered. An important problem of modern information systems is their personalization to the individual characteristics of users. This improves their efficiency, flexibility, convenience and productivity. To solve the problem of synthesis of adaptive EDMS proposed algorithmic and mathematical support, the original concept of information system architecture and the use of machine learning methods. Within the framework of the presented algorithmic and mathematical support, the approaches to the formalization of document management processes using the original architecture of the EDMS, ways to adapt the interface to the user parameters using artificial neural networks, the formulation of the problem of optimization of EDMS using as a target function of a comprehensive assessment of the system adaptability. The presented algorithm of synthesis of adaptive EDMS is characterized by the use of machine learning technologies to solve a number of problems in the selection of system components, the original architecture as the basis for the formalization of document management processes. The obtained scientific results can be used to solve the problem of design, optimization and adaptation of EDMS in various subject areas. [ABSTRACT FROM AUTHOR]