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The article reports the findings of an investigation into pollution migration processes at the municipal solid waste (MSW) landfill located in the water protection zone of Lake Seliger (Tver Region). The distribution of pollutants is investigated and migration parameters are determined in field and laboratory conditions at the landfill site. A mathematical model describing physical and chemical processes of substance migration in soil strata is constructed. Pollutant migration is found to be due to a variety of factors. The major ones, having a significant impact on the migration of MSW ingredients and taken into account mathematically, include convective transport, diffusion and sorption processes. A modified mathematical model differs from its conventional counterparts by considering a number of parameters reflecting the decrease in the concentration of ammonium and nitrate nitrogen ions in ground water (transpiration by plant roots, dilution with infiltration waters, etc.). An analytical solution to assess the pollutant spread from the landfill is presented. The mathematical model provides a set of simulation models helping to obtain a computational solution of specific problems, vertical and horizontal migration of substances in the underground flow. Numerical experiments, analytical solutions, as well as field and laboratory data was studied the dynamics of pollutant distribution in the object under study up to the lake. A long-term forecast for the spread of landfill pollution is made. Simulation experiments showed that some zones of clean groundwater interact with those of contaminated groundwater during the pollution migration from the landfill, each characterized by a different pollutant content. The data of a computational experiments and analytical calculations are consistent with the findings of field and laboratory investigations of the object and give grounds to recommend the proposed models for predicting pollution migration from a landfill. The analysis of the pollution migration simulation allows to substantiate the numerical estimates of the increase in $NH_4^+$ and $NO_3^-$ ion concentration with the landfill operation time. It is found that, after 100 years following the landfill opening, toxic filtrate components will fill the entire pore space from the landfill to the lake resulting in a significant deterioration of the ecosystem of Lake Seliger.

Corrosion damage to metals and alloys is one of the main problems of strength and durability of metal structures and products operated in contact with chemically aggressive environments. Recently, there has been a growing interest in computer modeling of the evolution of corrosion damage, especially pitting corrosion, for a deeper understanding of the corrosion process, its impact on the morphology, physical and chemical properties of the surface and mechanical strength of the material. This is mainly due to the complexity of analytical and high cost of experimental in situ studies of real corrosion processes. However, the computing power of modern computers allows you to calculate corrosion with high accuracy only on relatively small areas of the surface. Therefore, the development of new mathematical models that allow calculating large areas for predicting the evolution of corrosion damage to metals is currently an urgent problem.

In this paper, the evolution of the corrosion front in the interaction of a polycrystalline metal surface with a liquid aggressive medium was studied using a computer model based on a cellular automat. A distinctive feature of the model is the specification of the solid body structure in the form of Voronoi polygons used for modeling polycrystalline alloys. Corrosion destruction was performed by setting the probability function of the transition between cells of the cellular automaton. It was taken into account that the corrosion strength of the grains varies due to crystallographic anisotropy. It is shown that this leads to the formation of a rough phase boundary during the corrosion process. Reducing the concentration of active particles in a solution of an aggressive medium during a chemical reaction leads to corrosion attenuation in a finite number of calculation iterations. It is established that the final morphology of the phase boundary has a fractal structure with a dimension of 1.323 ± 0.002 close to the dimension of the gradient percolation front, which is in good agreement with the fractal dimension of the etching front of a polycrystalline aluminum-magnesium alloy AlMg6 with a concentrated solution of hydrochloric acid. It is shown that corrosion of a polycrystalline metal in a liquid aggressive medium is a new example of a topochemical process, the kinetics of which is described by the Kolmogorov–Johnson– Meil–Avrami theory.

Migration has a significant impact on the shaping of the demographic structure of the territories population, the state of regional and local labour markets. As a rule, rapid change in the working-age population of any territory due to migration processes results in an imbalance in supply and demand on labour markets and a change in the demographic structure of the population. Migration is also to a large extent a reflection of socio-economic processes taking place in the society. Hence, the issues related to the study of migration factors, the direction, intensity and structure of migration flows, and the prediction of their magnitude are becoming topical issues these days.

Mathematical tools are often used to analyze, predict migration processes and assess their consequences, allowing for essentially accurate modelling of migration processes for different territories on the basis of the available statistical data. In recent years, quite a number of scientific papers on modelling internal and external migration flows using mathematical methods have appeared both in Russia and in foreign countries in recent years. Consequently, there has been a need to systematize the currently most commonly used methods and tools applied in migration modelling to form a coherent picture of the main trends and research directions in this field.

The presented review considers the main approaches to migration modelling and the main components of migration modelling methodology, i. e. stages, methods, models and model classification. Their comparative analysis was also conducted and general recommendations on the choice of mathematical tools for modelling were developed. The review contains two sections: migration modelling methods and migration models. The first section describes the main methods used in the model development process — econometric, cellular automata, system-dynamic, probabilistic, balance, optimization and cluster analysis. Based on the analysis of modern domestic and foreign publications on migration, the most common classes of models — regression, agent-based, simulation, optimization, probabilistic, balance, dynamic and combined — were identified and described. The features, advantages and disadvantages of different types of migration process models were considered.

At the middle of the 2000-th, scientists studying the functioning of insect communities identified four basic patterns of the organizational structure of such communities. (i) Cooperation is more developed in groups with strong kinship. (ii) Cooperation in species with large colony sizes is often more developed than in species with small colony sizes. And small-sized colonies often exhibit greater internal reproductive conflict and less morphological and behavioral specialization. (iii) Within a single species, brood size (i. e., in a sense, efficiency) per capita usually decreases as colony size increases. (iv) Advanced cooperation tends to occur when resources are limited and intergroup competition is fierce. Thinking of the functioning of a group of organisms as a two-level competitive market in which individuals face the problem of allocating their energy between investment in intergroup competition and investment in intragroup competition, i. e., an internal struggle for the share of resources obtained through intergroup competition, we can compare such a biological situation with the economic phenomenon of “coopetition” — the cooperation of competing agents with the goal of later competitively dividing the resources won in consequence In the framework of economic researches the effects similar to (ii) — in the framework of large and small group competition the optimal strategy of large group would be complete squeezing out of the second group and monopolization of the market (i. e. large groups tend to act cooperatively) and (iii) — there are conditions, in which the size of the group has a negative impact on productivity of each of its individuals (this effect is called the paradox of group size or Ringelman effect). The general idea of modeling such effects is the idea of proportionality — each individual (an individual/rational agent) decides what share of his forces to invest in intergroup competition and what share to invest in intragroup competition. The group’s gain must be proportional to its total investment in competition, while the individual’s gain is proportional to its contribution to intra-group competition. Despite the prevalence of empirical observations, no gametheoretic model has yet been introduced in which the empirically observed effects can be confirmed. This paper proposes a model that eliminates the problems of previously existing ones and the simulation of Nash equilibrium states within the proposed model allows the above effects to be observed in numerical experiments.

The coconut tree is often mentioned as the “tree of life” due to its immense benefits to the human community ranging from edible products to building materials. Rugose spiraling whitefly (RSW), a natural enemy seems to be a major threat to farmers in bringing up these coconut trees. A mathematical model to study the dynamics of pest population in the presence of predator and parasite is developed. The biologically feasible equilibrium points are derived. Local asymptotic stability as well as global asymptotic stability is analyzed at the points. Furthermore, in order to educate farmers on pest control, we have added the impact of awareness programs in the model. The conditions of existence and stability properties of all feasible steady states of this model are analyzed. The result reveals that predator and parasite play a major role in reducing the immature pest. It also shows that pest control activities through awareness programs further reduce the mature pest population which decreases the egg laying rate which in turn reduces the immature population.

The article deals with the nonlinear boundary-value problem of hydrogen permeability corresponding to the following experiment. A membrane made of the target structural material heated to a sufficiently high temperature serves as the partition in the vacuum chamber. Degassing is performed in advance. A constant pressure of gaseous (molecular) hydrogen is built up at the inlet side. The penetrating flux is determined by mass-spectrometry in the vacuum maintained at the outlet side.

A linear model of dependence on concentration is adopted for the coefficient of dissolved atomic hydrogen diffusion in the bulk. The temperature dependence conforms to the Arrhenius law. The surface processes of dissolution and sorptiondesorption are taken into account in the form of nonlinear dynamic boundary conditions (differential equations for the dynamics of surface concentrations of atomic hydrogen). The characteristic mathematical feature of the boundary-value problem is that concentration time derivatives are included both in the diffusion equation and in the boundary conditions with quadratic nonlinearity. In terms of the general theory of functional differential equations, this leads to the so-called neutral type equations and requires a more complex mathematical apparatus. An iterative computational algorithm of second-(higher- )order accuracy is suggested for solving the corresponding nonlinear boundary-value problem based on explicit-implicit difference schemes. To avoid solving the nonlinear system of equations at every time step, we apply the explicit component of difference scheme to slower sub-processes.

The results of numerical modeling are presented to confirm the fitness of the model to experimental data. The degrees of impact of variations in hydrogen permeability parameters (“derivatives”) on the penetrating flux and the concentration distribution of H atoms through the sample thickness are determined. This knowledge is important, in particular, when designing protective structures against hydrogen embrittlement or membrane technologies for producing high-purity hydrogen. The computational algorithm enables using the model in the analysis of extreme regimes for structural materials (pressure drops, high temperatures, unsteady heating), identifying the limiting factors under specific operating conditions, and saving on costly experiments (especially in deuterium-tritium investigations).

The paper has a goal to identify a set of parameters of the environment and infrastructure with the most significant impact on institutional-matrices that dominate in different countries. Parameters of environmental conditions includes raw statistical indices, which were directly derived from the databases of open access, as well as complex integral indicators that were by method of principal components. Efficiency of discussed parameters in task of dominant institutional matrices type recognition (X or Y type) was evaluated by a number of methods based on machine learning. It was revealed that greatest informational content is associated with parameters characterizing risk of natural disasters, level of urbanization and the development of transport infrastructure, the monthly averages and seasonal variations of temperature and precipitation.

Base long-term modern scenarios of hydrochemical and temperature regimes of the Sea of Azov were considered. New schemes of modeling mechanisms of algal adaptation to changes in the hydrochemical regime and temperature were proposed. In comparison to the traditional ecological-evolutionary schemes, these models have a relatively small dimension, high speed and allow carrying out various calculations on long-term perspective (evolutionally significant times). Based on the ecology-evolutionary model of the lower trophic levels the impact of these environmental factors on the dynamics and microevolution of algae in the Sea of Azov was estimated. In each scenario, the calculations were made for 100 years, with the final values of the variables and parameters not depending on the choice of the initial values. In the process of such asymptotic computer analysis, it was found that as a result of climate warming and temperature adaptation of organisms, the average annual biomass of thermophilic algae (Pyrrophyta and Cyanophyta) naturally increases. However, for a number of diatom algae (Bacillariophyta), even with their temperature adaptation, the average annual biomass may unexpectedly decrease. Probably, this phenomenon is associated with a toughening of competition between species with close temperature parameters of existence. The influence of the variation in the chemical composition of the Don River’s flow on the dynamics of nutrients and algae of the Sea of Azov was also investigated. It turned out that the ratio of organic forms of nitrogen and phosphorus in sea waters varies little. This stabilization phenomenon will take place for all high-productive reservoirs with low flow, due to autochthonous origin of larger part of organic matter in water bodies of this type.

The functioning of DNA regulatory regions rely primarily on their physicochemical and structural properties but not on nucleotide sequences, i.e. ‘genetic text’. The formers are responsible for coding of DNA-protein interactions that govern various regulatory events. One of the characteristics is SIDD (Stress-Induced Duplex Destabilization) that quantify DNA duplex region propensity to melt under the imposed superhelical stress. The duplex property has been shown to participate in activity of various regulatory regions. Here we employ the SIDD model to calculate melting probability profiles for T7 bacteriophage promoter sequences. The genome is characterized by small size (approximately 40 thousand nucleotides) and temporal organization of expression: at the first stage of infection early T7 DNA region is transcribed by the host cell RNA polymerase, later on in life cycle phage-specific RNA polymerase performs transcription of class II and class III genes regions. Differential recognition of a particular group of promoters by the enzyme cannot be solely explained by their nucleotide sequences, because of, among other reasons, it is fairly similar among most the promoters. At the same time SIDD profiles obtained vary significantly and are clearly separated into groups corresponding to functional promoter classes of T7 DNA. For example, early promoters are affected by the same maximally destabilized DNA duplex region located at the varying region of a particular promoter. class II promoters lack substantially destabilized regions close to transcription start sites. Class III promoters, in contrast, demonstrate characteristic melting probability maxima located in the near-downstream region in all cases. Therefore, the apparent differences among the promoter groups with exceptional textual similarity (class II and class III differ by only few singular substitutions) were established. This confirms the major impact of DNA primary structure on the duplex parameter as well as a need for a broad genetic context consideration. The differences in melting probability profiles obtained using SIDD model alongside with other DNA physicochemical properties appears to be involved in differential promoter recognition by RNA polymerases.

In this paper, we address the mathematical modeling of robots based on tensegrity structures. The pivotal property of such structures is the forming elements working only for compression or tension, which allows the use of materials and structural solutions that minimize the weight of the structure while maintaining its strength.

Tensegrity structures hold several properties important for collaborative robotics, exploration and motion tasks in non-deterministic environments: natural compliance, compactness for transportation, low weight with significant impact resistance and rigidity. The control of such structures remains an open research problem, which is associated with the complexity of describing the dynamics of such structures.

We formulate an approach for describing the dynamics of such structures, based on second-order dynamics of the Cartesian coordinates of structure elements (rods), first-order dynamics for angular velocities of rods, and first-order dynamics for quaternions that are used to describe the orientation of rods. We propose a numerical method for solving these dynamic equations. The proposed methods are implemented in the form of a freely distributed mathematical package with open source code.

Further, we show how the provided software package can be used for modeling the dynamics and determining the operating modes of tensegrity structures. We present an example of a tensegrity structure moving in zero gravity with three rigid rods and nine elastic elements working in tension (cables), showing the features of the dynamics of the structure in reaching the equilibrium position. The range of initial conditions for which the structure operates in the normal mode is determined. The results can be directly used to analyze the nature of passive dynamic movements of the robots based on a three-link tensegrity structure, considered in the paper; the proposed modeling methods and the developed software are suitable for modeling a significant variety of tensegrity robots.