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Open Genes database is created to enhance and simplify the search for potential aging therapy targets. We collected data on 2402 genes associated with aging and developed convenient tools for searching and comparing gene features. We provided a comprehensive description for genes, such as lifespan-extending interventions, aging-related changes, longevity associations, gene evolution, associations with diseases and hallmarks of aging, and functions of gene products. We provided detailed structured data for each experiment needed to evaluate the quality and interpret the study result. Our goal was to stay objective and precise while connecting a particular gene and human aging. We distinguished 6 types of studies and 12 criteria for adding genes to our database. Genes were classified according to the confidence level of the link between the gene and aging. All data collected in a database are provided both by API and user interface. The database is publicly available on a website https://open-genes.org/.

Introduction. This work is aimed at solving the problem of phytoplankton dynamics in the coastal environments using the example of the Azov Sea. This takes into account the transformation of forms of phosphorus, nitrogen and silicon, as well as the aquatic medium motion, the distribution of temperatures and salinities over the sea area. River flow, varying in volume and chemical composition, affects significantly the variability of hydrophysical and biogeochemical parameters of the processes occurring in the coastal environment. This explains the need for statistical processing of the data from long-term observations over the river flow characteristics. Materials and Methods. The mathematical model of biogeochemical cycles is based on a system of non-stationary equations of the convection-diffusion-reaction of parabolic type with nonlinear functions of sources and lower-order derivatives, to which the corresponding initial and boundary conditions are added. In the course of statistical analysis of the series of long-term observations over river flows, the values of the following indicators were found: skewness coefficient, degree of kurtosis, variance and standard deviation, coefficient of variation, autocorrelation coefficient, Neumann ratio, and Anderson criterion. Results. The statistical analysis of the series of long-term observations over the hydrochemical indicators of the Don river suggests heterogeneity of the field data. This is due to the stochasticity of nutrient inputs and the volume of freshwater flow to the sea as a result of natural and anthropogenic factors. Field data should be correlated with seasonal changes in the aquatic environment temperature. This paper presents the results of a computational experiment to model the dynamics of phytoplankton populations in summer season, when temperatures are favorable for their reproduction and growth. The proposed mathematical model considers the spatially inhomogeneous distribution and transformation of forms of phosphorus, nitrogen, and silicon, as well as changes in salinity, temperature, and motion of the aquatic environment. Discussion and Conclusions. The multispecies mathematical model of the dynamics of phytoplankton populations is considered with account for the transformation of forms of phosphorus, nitrogen, and silicon in the coastal environments. The analysis of data from field observations, for which its major statistical parameters are calculated, is carried out. As a result, it is concluded that data of the long-term observations are significantly variable. This is due to two reasons. Random nature of the input of nutrients and the volume of river flow as a result of anthropogenic factors is the first reason. The second reason includes the alternation of relatively high-water and low-water periods for fresh flow over the last 12-15 years. The hydrological regime is changing mainly due to the reduction of the average annual freshwater flow of the Don and partly of the Kuban. This trend is likely to increase due to climate changes, as well as with further regulation of the Don river flow after the Bagaevsky hydroelectric installation start-up. Numerical experiments based on the field data confirmed the predictive validity of the developed models and programs. They can be used to predict change in the composition and abundance (concentrations) in the Azov sea core planktonic populations, which define, on the one hand, food resources, and, on the other hand, the aquatic environment in terms of the ongoing sea salinization.

Increased influence of abiotic and anthropogenic factors on the ecological state of coastal systems leads to uncontrollable changes in the overall ecosystem. This paper considers the crucial problem of studying the effect of an increase in the water’s salinity in the Azov Sea and the Taganrog Bay on hydrobiological processes. The main aim of the research is the diagnostic and predictive modeling of the geographic dynamics of the general phytoplankton populations. A mathematical model that describes the dynamics of three types of phytoplankton is proposed, considering the influence of salinity and nutrients on algae development. Discretization is carried out based on a linear combination of Upwind Leapfrog difference schemes and a central difference scheme, which makes it possible to increase the accuracy of solving the biological kinetics problem at large values of the grid Péclet number (Peh > 2). A software package has been developed that implements interrelated models of hydrodynamics and biogeochemical cycles. A modified alternating-triangular method was used to solve large-dimensional systems of linear algebraic equations (SLAE). Based on the scenario approach, several numerical experiments were carried out to simulate the dynamics of the main species of phytoplankton populations at different levels of water salinity in coastal systems. It is shown that with an increase in the salinity of waters, the habitats of phytoplankton populations shift, and marine species invasively replace freshwater species of algae.

The paper is devoted to modeling the dynamics of phyto- and zooplankton populations in coastal systems, taking into account the mechanism of external hormonal regulation and relying on NVIDIA Tesla K80 graphics accelerators. The mathematical model of the dynamics of plankton populations is based on a system of non-stationary equations of convection-diffusion-reaction with nonlinear terms. We carry out the linearization of the continuous problem and construct its discrete analog by splitting the original three-dimensional problem into a two-dimensional problem and a one-dimensional problem, in conformity with the linearized model. To construct the discrete two-dimensional model, we use a linear combination of the Upwind and the Standard Leapfrog difference schemes, which makes it possible to increase the modeling accuracy in the case of large values of the grid Peclet number. We introduce into the model of ectocrine regulation of interacting phytoplankton species a nonlinear dependence between the phytoplankton growth rate and the concentration of metabolites. By doing so, we manage to describe the ability of algal metabolites to control their growth, even under conditions of an excess of nutrients, which corresponds to modern concepts on the functioning of hydrobiocenosis. The solution to the problem is numerically implemented on a graphics accelerator for massively parallel computations, which significantly reduces the operating time of the software module. We study a parallel computing model on a GPU on a sequence of thickening grids with different numbers of threads.

Currently, one of the topical areas of application of artificial intelligence methods in ensuring environmental monitoring of water resources is the analysis of Earth remote sensing images in order to control and prevent potentially dangerous changes in the environment. In the future, algorithms with elements of artificial intelligence form the basis of forecasting and decision-making systems. Systems for ensuring high-quality environmental monitoring can be improved using artificial intelligence methods, in particular, the development and application of special algorithms to prevent emergencies. The aim of the study is to develop an algorithm using artificial intelligence to detect spots of substances of various origins on the water surface. It has been established that the YOLOv4 convolutional neural network is applicable for high-quality detection of oil spots and bloom spots of phytoplankton populations. The developed algorithm was tested on real satellite images and showed an accuracy of 84-94%.

The paper covers the development of an algorithm for modeling the pollutant distribution dynamics in shallow water and its implementation on a high-performance computer system in a limited time. A mathematical model of the pollutant transport, including oil and petroleum products, in the water environment has been developed taking into account a number of determining hydrodynamic and hydrophysical factors, including destruction and deposition, affecting the nature of their flow. Methods of its numerical implementation have been developed for prediction the pollution spread in shallow waters in limited time on a high-performance computer system. The main advantage of it in predictive modeling of environment processes and phenomena is taking into account the multidisciplinary nature of real processes, the complex geometry of simulated domain, ensuring high accuracy of calculations, performing a large number of calculations in a short time. Simulation of the pollutant transport of various etiologies was performed taking into account a number of determining factors, including their structure and deposition on the bottom surface, on the basis of the developed software and algorithmic tools. It used a scenario approach that meets the basic principles of effective predictive modeling in water systems. The simulation results are the foundation for planning and conducting measures to prevent and eliminate the consequences of technogenic hazards.

The work is devoted to the construction of a model of turbulent exchange in shallow water bodies using the results of expeditionary measurements. The Kalman filter algorithm was used to filter field data. An algorithm for calculating the coefficient of vertical turbulent exchange, which decisively affects the heat and gas exchange of the coastal system, has been developed, which has made it possible to significantly reduce the effect f noise in the experimental data used. As a result of the numerical implementation of the developed algorithm, the coefficient of microturbulent exchange in the vertical direction was obtained for a three-dimensional mathematical model of hydrodynamics of coastal systems.

The paper presents an approach to the implementation of the model of eutrophication of the Sea of Azov waters using variational methods for assimilation of data obtained during expeditionary studies. The current fields are calculated on the basis of a mathematical model of the hydrodynamics of shallow water bodies, which includes the equation of motion (the Navier-Stokes equation) and the continuity equation. The developed software package uses the materials of expeditionary work and allows you to refine the model of pollution of the aquatic environment and biota through the use of variational methods of data assimilation. Based on the developed software package, a forecast of water pollution with harmful substances is given, which in turn leads to the development of harmful diatoms and toxic blue-green algae.

The mathematical part of the algorithm for searching for objects in an image using additional classifying functions is presented. A software module has been developed in the Python programming language using the OpenCV library, designed to search for and highlight the boundaries of the coastal systems of southern Russia and build a condensing grid to the center from the boundaries. Experiments were carried out to test the performance of the software module under various weather conditions based on the Azov Sea.

The work is devoted to mathematical modeling of the scenario for managing the sustainable development of coastal systems using the example of the Azov Sea. The dynamic problem of minimizing the costs of maintaining the ecosystem of the reservoir in a given state, which is interpreted as a requirement for sustainable development, is being solved. The mathematical model of the interaction of two phytoplankton types takes into account the influence of abiotic factors, such as salinity and temperature, on the algae growth, their absorption and excretion of nutrients, as well as the transition of these nutrients from one form to another. For the numerical implementation of the proposed interconnected mathematical models of biological kinetics, parallel algorithms have been developed that are adapted to multiprocessor and hybrid computing systems using the NVIDIA CUDA architecture. An analysis of the characteristics of the CUDA architecture showed the applicability of the algorithms for the numerical implementation of the developed mathematical models of hydrobiology to create high-performance information systems. The constructed software complex allows to simulate the problem of reducing eutrophication and toxicity of the coastal system under consideration by displacing harmful blue-green algae with a cultivated strain of green alga using high performance computing systems.

The paper covers the mathematical modelling of the main biogenic matter transformations in the production-destruction processes of phytoplankton populations in the Azov Sea, taking into account the influence of external factors, including the salinity and temperature. A multi-species mathematical model of the phytoplankton population dynamics taking into account the transport and transformation of nutrients was developed and researched. A numerical algorithm of salinity and temperature field restoration in shallow water for the case of the Azov Sea was offered to simulate biogeochemical cycles of the main pollutants, including nitrogen, phosphorus and silicon. A discrete analogue of the proposed water ecology model problem was developed based on the schemes of the increased accuracy taking into account the partial filling of the computational cells. A parallel algorithm adapted for hybrid computing systems using the NVIDIA CUDA architecture was developed for the numerical implementation of the proposed interrelated mathematical models of biological kinetics.

The purpose of this work is a mathematical modeling of the distribution of nutrients taking into account the dynamics of phytoplankton populations and the influence of salinity and temperature. The goals of this work: the development of the mathematical model of phytoplankton populations dynamics, taking into account the transport and transformation of biogenic substances; obtaining stationary modes for the case of a spatially uniform distribution of substances; restoration of salinity and temperature fields; modeling of nutrient distribution taking into account the obtained results. Stationary regimes were obtained under the assumption that the development of phytoplankton is limited by a single nutrient - phosphorus, nitrogen or silicon. The modified Laplace equation was used to improve the order of accuracy of recovery of salinity and temperature fields. The distribution of pollutant (nitrogen), affecting the development of harmful blue-green algae, has been obtained.The purpose of this work is a mathematical modeling of the distribution of nutrients taking into account the dynamics of phytoplankton populations and the influence of salinity and temperature. The goals of this work: the development of the mathematical model of phytoplankton populations dynamics, taking into account the transport and transformation of biogenic substances; obtaining stationary modes for the case of a spatially uniform distribution of substances; restoration of salinity and temperature fields; modeling of nutrient distribution taking into account the obtained results. Stationary regimes were obtained under the assumption that the development of phytoplankton is limited by a single nutrient - phosphorus, nitrogen or silicon. The modified Laplace equation was used to improve the order of accuracy of recovery of salinity and temperature fields. The distribution of pollutant (nitrogen), affecting the development of harmful blue-green algae, has been obtained.

The paper covers the development and research epy computational structure for mathematical modelling of hydrobiological processes in shallow waters – Azov Sea and Gelendzhik Bay, based on the modern information technologies and computational methods to improve the accuracy of predictive modelling the ecological situations in waters during the summer. The models take into account following: the water flow movement; microturbulent diffusion; gravitational settling of pollutants; plankton populations nonlinear interaction; the salinity impact, temperature. The scheme with weights was proposed for discretization of the developed model, that allowed significantly reduce the error and the computational time. Practical significance of the work is that the proposed model was software implemented; the limits and prospects of its use were defined. The experimental software was designed on the basis of a graphics accelerator for mathematical modelling of possible development scenarios of the shallow waters ecosystems, taking into account the environment influence. Parallel implementation was performed using the decomposition methods for computationally labours diffusion-convection problems taking into account the CUDA architecture characteristics.The paper covers the development and research epy computational structure for mathematical modelling of hydrobiological processes in shallow waters – Azov Sea and Gelendzhik Bay, based on the modern information technologies and computational methods to improve the accuracy of predictive modelling the ecological situations in waters during the summer. The models take into account following: the water flow movement; microturbulent diffusion; gravitational settling of pollutants; plankton populations nonlinear interaction; the salinity impact, temperature. The scheme with weights was proposed for discretization of the developed model, that allowed significantly reduce the error and the computational time. Practical significance of the work is that the proposed model was software implemented; the limits and prospects of its use were defined. The experimental software was designed on the basis of a graphics accelerator for mathematical modelling of possible development scenarios of the shallow waters ecosystem...

The purpose of this work is development of program complex designed to simulate the spread of pollutants, including oil and petroleum products, in coastal systems, as well as transport, transformation and deposition of aerosols in air on a super-computer. The objective of this study is to develop the modules of aero- and hydrodynamics, which are part of the software package, an effective parallel method and conduct a computational experiment. For the effective implementation of the task, a parallel version of the adaptive modified alternating triangular method of the fastest descent was developed, its acceleration and efficiency were investigated. With the help of the software in question, an emergency oil spill was simulated that occurred in the Kerch Strait in November 2007. A computational experiment was also carried out to simulate the spread of impurities from motor vehicles in the coastal (recreational) area of Taganrog with and without forest plantations.The purpose of this work is development of program complex designed to simulate the spread of pollutants, including oil and petroleum products, in coastal systems, as well as transport, transformation and deposition of aerosols in air on a super-computer. The objective of this study is to develop the modules of aero- and hydrodynamics, which are part of the software package, an effective parallel method and conduct a computational experiment. For the effective implementation of the task, a parallel version of the adaptive modified alternating triangular method of the fastest descent was developed, its acceleration and efficiency were investigated. With the help of the software in question, an emergency oil spill was simulated that occurred in the Kerch Strait in November 2007. A computational experiment was also carried out to simulate the spread of impurities from motor vehicles in the coastal (recreational) area of Taganrog with and without forest plantations.

The paper covers the development and research of a mathematical model for description hydrobiological processes using the modern information technologies and computational methods to improve the accuracy of predictive modeling the ecological situation in shallow waters. The model takes into account the following factors: movement of water flows; microturbulent diffusion; gravitational settling of pollutants; nonlinear interaction of phyto- and zooplankton populations; nutrient, temperature and oxygen regimes; and influence of salinity. A space splitting scheme taking into account the partial filling of cells was proposed for model discretization. This scheme significantly reduces both error and calculation time. The practical significance of the paper is determined by software implementation of the model and the determination of limits and prospects of its practical use. Experimental software is designed on the basis of a supercomputer for mathematical modeling of possible development scenarios of shallow water ecosystems taking into account the influence of environment. For this, we consider as an example the Azov Sea in summer. The parallel implementation involves decomposition methods for computationally laborious diffusion-convection problems taking into account the architecture and parameters of a multiprocessor computer system.

The paper deals with the development and research of a mathematical model for hydrophysical processes which involves the use of modern information technologies and computational methods with the aim to improve the accuracy of predictive modeling of ecological condition of shallow waters during the summer. The model takes into account the following factors: movement of water flows; microturbulent diffusion; gravitational settling of pollutants; nonlinear interaction of plankton populations; nutrient, temperature and oxygen regimes; and impact of salinity. A scheme with weights is proposed for the discretization of the proposed model. This scheme significantly reduces both error and computation time. The practical significance of the paper is determined by the software implementation of the model and the determination of the limits and prospects of its practical use. Experimental software is designed on the basis of a supercomputer for mathematical modeling of possible development scenarios of shallow water ecosystems taking into account the influence of the environment. For this, we consider as an example the Sea of Azov in the summer period. The software parallel implementation involves decomposition methods for computationally intensive diffusion-convection problems taking account of the architecture and parameters of a multiprocessor computer system. The software complex contains a model for fluid dynamics which includes equations of motion in three coordinate directions.

The paper presents the results of hydrochemical observations obtained during the expedition on the scientific-research vessel “Deneb” in the Eastern part of the Azov Sea and the Taganrog Bay in July 2017. In the ecological and hydrophysical researches we have found abnormally low levels of dissolved oxygen in the bottom layer of the Azov Sea. Among the various approximations of the vertical turbulent exchange coefficient, the algebraic subgrid models are the most applicable. These models are based on the determination of turbulent flows as averaged multiplication of deviations over space or time (correlation) of the velocity components of the currents and a transferring physical quantity. The numerical experiment for determination of vertical turbulent exchange coefficient for some points of the Azov Sea was performed. Direct dependence between values of the vertical turbulent exchange coefficient and the concentration of dissolved oxygen in the bottom layer was obtained.

The purpose of this work is the development of a difference scheme for the solution of convection-diffusion problem at high Peclet numbers (Pe>2). In accordance with this purpose the following problems were solved: difference scheme for convection is built, comparison with the existing schemes is carried out; conditions for stability of the proposed difference scheme are obtained. Solutions of the convection-diffusion equation on the basis of the proposed difference scheme at various Peclet numbers are obtained.